Gabriel Putnam

OpenGL

• groups G. C. Putnam
• language Hello Triangle, LearnOpenGL
• quick_reference Program demonstrating one of the hardest parts of modern OpenGL, drawing your first triangles with keyboard input.

download DownloadDownload Hello Triangle Example

• groups G. C. Putnam
• language Shaders, LearnOpenGL
• quick_reference Program demonstrating implementing and compiling a simple three color shader in OpenGL.

download DownloadDownload Shaders Example

• groups G. C. Putnam
• language Textures, LearnOpenGL
• quick_reference Program demonstrating drawing geometry with colorized and textured surfaces. Keyboard input to swap render modes.

download DownloadDownload Textures Example

• groups G. C. Putnam
• language Transforms, LearnOpenGL
• quick_reference Program demonstrating drawing geometry displaced, scaled, and rotated with matrix transforms.

download DownloadDownload Transforms Example

• groups G. C. Putnam
• language Coordinate Systems, LearnOpenGL
• quick_reference Program demonstrating drawing multiple shapes with 3D perspective projection, color, textures, transforms, and keyboard input.

download DownloadDownload Coordinate Systems Example

• groups G. C. Putnam
• language Camera, LearnOpenGL
• quick_reference Program demonstrating adding a user moveable camera to the scene of objects from previous examples.

download DownloadDownload Camera Example

• groups G. C. Putnam
• language Colors, LearnOpenGL
• quick_reference Program demonstrating adding simplistic lighting with constant object and light color.

download DownloadDownload Colors Example

• groups G. C. Putnam
• language Basic Lighting, LearnOpenGL
• quick_reference Program demonstrating adding ambient, diffuse, and specular phong lighting.

download DownloadDownload Basic Lighting Example

• groups G. C. Putnam
• language Materials, LearnOpenGL
• quick_reference Program demonstrating (amb, diff, spec) colored materials with varying lighting, and normal maps.

download DownloadDownload Materials Example

• groups G. C. Putnam
• language Lighting Maps, LearnOpenGL
• quick_reference Program demonstrating (diff, spec) material lighting maps along with multi-image textures. The varying light was also made constant color.

download DownloadDownload Lighting Maps Example

• groups G. C. Putnam
• language Light Casters, LearnOpenGL
• quick_reference Program demonstrating different lighting types (ambient, directional, point, spot, point attenuating, spot attenuating.

download DownloadDownload Light Casters Example

• groups G. C. Putnam
• language Multiple Lights, LearnOpenGL
• quick_reference Program demonstrating scenes with colored backgrounds and multiple lights with different colors and intensities.

download DownloadDownload Multiple Lights Example

• groups G. C. Putnam
• language Models, LearnOpenGL
• library_books OBJ Loader, Robert Smith (Bly7), Github
• deployed_code Survival Guitar Backpack, Berk Gedik, Sketchfab
• article "Improved alpha-tested magnification for vector textures and special effects." Green, Chris. ACM SIGGRAPH 2007 courses, pp. 9-18. 2007. Steam CDN. (also provided below in a minified copy)
• quick_reference Program demonstrating OBJ model loading (OBJ Loader was used rather than ASIMP in the LearnOpenGL example) along with Signed Distance Field Fonts based on the 2007 SIGGRAPH paper from Chris Green of Valve used for Frames Per Second (FPS) display as well as writing.
• attachment

download DownloadDownload Model and SDF Text Example

• groups G. C. Putnam
• language Framebuffers, LearnOpenGL
• quick_reference Program demonstrating use of offscreen framebuffers to perform multiple post-processing effects (color inversion, grayscale, unsharp mask [3x3 and 5x5], sharpen [3x3], emboss [3x3], gaussian blur [3x3, 5x5, and two-step 9x9], box blur [3x3], edge detect, lapacian blur [two-step 9x9], poisson blur [two-step 9x9], rayleigh blur [two-step 9x9], spherical blur [two-step 9x9].

download DownloadDownload Framebuffers Example

• groups G. C. Putnam
• language Cubemaps, LearnOpenGL
• quick_reference Program demonstrating use of cubemaps to draw a background skybox, along with visible object depth, reflection surfaces, refraction surfaces, and multi-view single shader rendering.

download DownloadDownload Cubemaps Example

• groups G. C. Putnam
• language Advanced GLSL, LearnOpenGL
• quick_reference Program demonstrating a particle system using point sprites.

download DownloadDownload Advanced GLSL Example

• groups G. C. Putnam
• language Geometry Shader, LearnOpenGL
• quick_reference Program demonstrating drawing normals, shifting vertex locations, and creating instances using a geometry shader.

download DownloadDownload Geometry Shader Example

• groups G. C. Putnam
• language Instancing, LearnOpenGL
• language Advanced-Lighting, LearnOpenGL
• quick_reference Program demonstrating instancing using two different methods (pre-created matrices, and matrices in the vertex shader) vs independent draw calls per object, along with blinn-phong lighting relative to regular phong lighting.

download DownloadDownload Instancing Example

• groups G. C. Putnam
• language Shadow Mapping, LearnOpenGL
• quick_reference Program demonstrating creating objects shadows by rendering to a object depth based shadow map (results displayed on a status panel).

download DownloadDownload Shadow Mapping Example

• groups G. C. Putnam
• language Point Shadows, LearnOpenGL
• quick_reference Program demonstrating creating objects shadows by rendering to a object depth based shadow map (results displayed on a status panel).

download DownloadDownload Point Shadows Example

• groups G. C. Putnam
• language Parallax Mapping, LearnOpenGL
• language HDR, LearnOpenGL
• quick_reference Program demonstrating parallax mapping (per pixel surface height offsets) with image exposure and gamma lighting adjustments for High Definition Rendering (HDR).

download DownloadDownload Parallax Mapping with Exposure and Gamma Example

• groups G. C. Putnam
• language Deferred Shading, LearnOpenGL
• quick_reference Program demonstrating deferred shading (two step shading with lighting calculated on a depth image of the geometry). Point lights have also been changed to render to four layers of a single texture rather than four textures. Further icosahedrons have been added as an additional shape.

download DownloadDownload Deferred Shading Example

• groups G. C. Putnam
• language Physics Based Rendering, Theory, LearnOpenGL
• language Physics Based Rendering, Lighting, LearnOpenGL
• quick_reference Program demonstrating Physics Based Rendering (PBR). Using moving and multiple point lights simulataneously.

download DownloadDownload Physics Based Rendering Example

• groups G. C. Putnam
• language PBR, Irradiance Based Lighting, Diffuse, LearnOpenGL
• language PBR, Irradiance Based Lighting, Specular, LearnOpenGL
• quick_reference Program demonstrating Irradiance Based Lighting with PBR. (HDR lighting cubemaps with diffuse and specular contibution). Spheres with a range of PBR textures along with tetrahedron objects were added. The ability to adjust sphere hue is included. Further, point lights can now move dynamically for changing shadows and lighting, light frustrums can be drawn on screen to show lighting extents, and the multiple point lights can be switch between for individual lighting.

download DownloadDownload Irradiance Based Lighting Example

• groups G. C. Putnam
• quick_reference Program refactoring the work from all the previous examples. Shaders have all been changed to have consistent naming. Font colors can now be changed. Grass models and textures have been added to test transparent objects. In addition, particles using texture storage have been added, along with paraboloid mapping shadows. Downloads had to be split for this example because the compressed files were too large.

download Download Main FilesDownload ReFactor Example download Download Additional ResourcesDownload ReFactor Additional Resources Example

Shadertoy

Statistics of Magic the Gathering

• This is a 40+ image album of the state of the card game Magic the Gathering up until 2018.
• I start off by looking at the distribution trends for cards, card types, and keywords over the history of Magic. In addition to basic divisions, this also cover divisions like rarities, creature types, creature classes, Power (P)/Toughness (T) trends, and the use of more general "action" words like "Create" or "Sacrifice".
• Next, I perform regression analysis (Ax = b, where A are the traits / card, x are the trait values, and b are the card Converted Mana Cost (CMC)) to explore the value of various card traits in CMC.
• Said another way, I try to answer the question "how much is a given trait worth in CMC?" ex: Power is currently valued more highly than Toughness with a point of Power ~worth 0.5 CMC while a point of Toughness is worth 0.4 CMC. Both have also been increasing with time. This is done on a per / block basis so that I would have enough cards to do the regression with.
• Finally, I look at how the art of Magic the Gathering has changed over time. To do so, I collected samples of the art for every card released and performed what is known as Perceptual Hash Analysis on those cards (www.phash.org)
• The basic idea of a perceptual hash is that it compares art / images and gives you a number which represents the distance of those images from one another. For each set in Magic, I then constructed a matrix of all of these distances and then backsolved to find the positions of the images as if they were points in space using a technique called Multi-Dimensional Scaling. Finally, for every art piece, I also averaged the entire art down to a single pixel so see how much correlation the average color had on the "closeness" predicted by the pHash algorithm.
• Original post on Reddit
• Original post on Imgur

 

• groups G. C. Putnam
• quick_reference A tally of the # of cards released per block / year over the history of magic. Summation performed from Aug(yr N) - Aug(yr N+1). This puts the yearly set (ex: Magic Origins (ORI, 15, web_stories) or Magic 2015 (M15, 14, web_stories)) as the capstone of the year with a new rotation generally starting Sept-Oct. The choice of which year to put them in is somewhat arbitrary, but this made the cutoff's smoother as the Beta (LEB, 93, web_stories) and 2nd / Unlimited Edition (2ED, 93, web_stories) were the only major sets not released on the pre-Aug side of the year.

 

 

 

• groups G. C. Putnam
• quick_reference Types of cards that have been released per set as a % of the set. Notable outlier, Mirrodin (MRD, 03, web_stories), which had a Huge number of artifacts. Alara (ALA, 08, web_stories) and Scars of Mirrodin (SOM, 10, web_stories) repeated this to a lesser degree, while the Theros block (THS, 13, web_stories) (BNG, 14, web_stories) (JOU, 14, web_stories), released dramatically larger #'s of enchantments. Creatures have since the very beginning held steady at ~50 % of every block.
• quick_reference The third images shows types of cards that are common, but less dominant for block percentages, as well as often having crossover with the other types. Lands have interestingly been growing as a percentage of sets, to a point that they now rival most of the lesser main types (Instant, Sorcery, Enchantment, Artifact). Legends had a huge surge in Kamigawa (CHK, 04, web_stories), and have otherwise been on a parabolic rise, while tribals had their single day during Lorwyn (LRW, 07, web_stories) / Shadowmoor (SHM, 08, web_stories), and then were largely absent. Planeswalkers, while dramatically influential in pricing and value, remain a tiny part of most sets.

 

• groups G. C. Putnam
• quick_reference For a long time, each of the three rarities got about 1/3 of a set until ~2006-2007. Around that time, with the addition of Mythics, Commons actually rise as a percent, while Rares effectively just split their total with Mythics.

 

 

 

 

 

 

• groups G. C. Putnam
• quick_reference Six (6) charts looking at the distribution of creature types among cards released, with the first being iconic creatures. The two winners here are obviously Dragons and Angels, yet while Dragons appear to be far more prominent, they actually only edge out Angels by 12 total cards. In truth, the Iconic types as a whole really see very little use for being "iconic" and both Sphinxs and Hydras are in drastic need of some attention. Surprising too, considering many Hydras have actually been very influential on their blocks (ex: Prime Hydra, Progenitus)
• quick_reference Next with characteristic creatures, it is little if not a human-centric world. They are far and away the most used type in magic only playing second fiddle in a couple of sets like Kamigawa (CHK, 04, web_stories) (spirits) and Lorwyn (LRW, 07, web_stories) / Shadowmoor (SHM, 08, web_stories) (tribal). In Lorwyn / Shadowmoor they are effectively replaced by their fractured counterparts from the Tribal groups.
• quick_reference The leftover types which are still popular and include at least 200 cards over magic history, which puts them above the "iconic" types in count. Other than the aforementioned Spirits / Elementals, Beasts are the other major group which got a lot of attention early in Magic (Masques (MMQ, 99, web_stories) / Onslaught (ONS, 02, web_stories)), and then largely faded from view. The second "popular" chart showing creature types with equal or less representation than the "iconics". Once again, Lorwyn / Shadowmoor is the source of a big spike (Giants) as well as its predecessor Time Spiral (TSP, 06, web_stories), when the Slivers came a calling. Walls used to be all over the place, but I guess we've been breaking down barriers, as they've almost completely vanished.
• quick_reference The final two charts show the second half of the major division for creatures, which is their "class" or occupation. Amusingly, the time when there was the most diversity of jobs was when there were the least Humans. Warriors have also been seeing a big surge lately with Khans of Tarkir (KTK, 14, web_stories) and Kaladesh (KLD, 16, web_stories) / Amonkhet (AKH, 17, web_stories) to the point where they now outnumber Soldiers (a long time leader). The final chart being the lesser used classes (notably, Cleric should actually be swapped with Shaman, having a lot of early use and steady later inclusion at ~2% / set) Oddly, Druids and Shamans are not particularly correlated, with the only really big set for Druids being Odyssey (ODY, 01, web_stories). The flower of Knighthood almost completely disappeared from the world, but has returned with a vengeance in the last year.

 

 

 

 

 

• groups G. C. Putnam
• quick_reference Five (5) charts that look at cards which include the use of a keyword in the main text, organized alphabetically. First three are Evergreen keywords, where notably spikey is Flash, which tends to have about a 6 year period between bursts, and Defender which has close to a 3 year period. (Reddit commenter "Qualdrion" noted that Flash may also included parts of "Flashback" for some inaccuracy.) In this group, First Strike is easily the most consistent, rarely dropping below 2%.
• quick_reference Among the second chart, easily the most used Evergreen keyword in all of magic, Flying almost never drops below 10% in a set, and has been above 12% much of its life. Likely, as it is a steady form of evasion with numerous counter moves available. As we'll see in later graphs, this also gives it one of the most consistent valuations of a keyword. However, Haste is also quite consistent, and has apparently met with approval, as it has been on a consistent rise over time. In addition to being a hallmark for Artifacts, Mirrodin block (MRD, 03, web_stories) (DST, 04, web_stories) (5DN, 04, web_stories) is also notable for being the genesis of numerous long lived keywords like Lifelink, Indestructible, and Hexproof.
• quick_reference The last of the Evergreen keyword charts, this illustrates particularly well the longevity of two green keywords, Trample and Reach. Trample has been with us since the beginning and has generally received upward inclusion in each block with notable outliers in Homelands (HML, 95, web_stories) (high) and Kamigawa (CHK, 04, web_stories) (low). Reach is an interesting case, as like Defender, it tends to be a keyword that offsets card value, and been decidedly more spikey in its use, featuring strongly in Kamigawa and Time Spiral (TSP, 06, web_stories), then taking a major break until Theros (THS, 13, web_stories) and Khans (KTK, 14, web_stories). At the time of 2018, the story for Prowess did not appear to be very good, as it was heavily used for about two sets, but was effectively in freefall ever since.
• quick_reference Usage stats for all of the Deciduous keywords (keywords that R&D has not ruled out, but says are unlikely in the future. Reddit commenter "JimHarbor" noted many are mostly deprecated.). The graph tends to support this, as it is evident that nearly every one of these keywords started out strong and has been slowly phased out over time. Regenerate in particular is a surprising example of this trend, as at one point it was the second most popular keyword after Flying. Protection at one point was also heavily used (Odyssey (ODY, 01, web_stories)) but got culled like the rest. Theros block was when the big change to remove most happened, with the phase out happening over the next two years until Battle for Zendikar (BFZ, 15, web_stories). However, most (excluding the highly confusing "banding") had been on the decline for a long time.
• quick_reference Finally, a quick look at the split for all the types of landwalk in the game, as it actually had a huge amount of diversity for such a rarely used ability. 8 major types with Swamp and Island being the big players, and Plains being the least used. This surprised me a bit, as I mentally always tallied Forestwalk as more influential due to its presence in many Elfball style decks.

 

 

• groups G. C. Putnam
• quick_reference Two (2) charts looking at Actions which can be taken by cards. Notably, Counter is a difficult case to filter, as this stat includes both cards that add "counters" to objects as well as cards which "counter" a spell. A difficult crossover of terminology. Removal effects (Destroy / Exile) are considerably more prominent than Create, but this make sense, as most spells when cast tend to "create" something. Although I focused on Discard, a notably absent action is Draw, which would likely have similar numbers. I didn't play the block, yet Odyssey (ODY, 01, web_stories) was obviously something of an outlier, as it once again features a huge spike in otherwise less commonly used terms and words (Exile / Discard) which have only recently returned to prominence.
• quick_reference Sacrifice used to be the darling of Magic the Gathering, featuring on more cards than even Flying, but has been in steady decline since the start. Part of this probably stems from the sheer number of infinite combos spawned through Sacrifice outlets. In the stats for Tap and Untap, the numbers for Tap should be significantly lower, as they overlapped with the values for Untap (regex patterns which see both)

 

 

• groups G. C. Putnam
• quick_reference Two (2) charts looking at creature Power and Toughness trends. Looking at the average power and toughness its interesting to see that a) the average for both has steady risen over time, b) they nearly perfectly parallel each other's movements, and c) show no sign of plateauing (ie: the curvature has yet to start turning downward.) Apparently its just an escalating arms race where new stuff has to be a little bit stronger / tougher than old stuff. (Reddit commenter "Ulthran" noted: "AVG P/T was growing since the beginning, especially since 2003, and since 2003 average mana cost is the same or lower than it was. Plus we know that many abilities are being sticked to creatures now.") This is approximately 8th Edition (8ED, 03, web_stories) onward.
• quick_reference Looking at the max values for power and toughness, the trend is similar, although the maxima are actually surprisingly aligned, with all but three blocks having the maximum P/T be identical over 25 years. This arms race does appear to have slowed down though, as after 2012, the escalation in max values has been curving downward, which may mean the averages will start to do the same.

 

 

 

 

• groups G. C. Putnam
• quick_reference Four (4) charts looking at Converted Mana Cost (CMC) trends with time. While P/T have consistently risen over time, avg CMC found its ideal value of ~3.4 around 2002 Onslaught (ONS, 02, web_stories) and has stayed that way ever since.
• quick_reference Max CMC follows a similar trend as the average, with the high mark hitting during 2001 Planeshift (PLS, 01, web_stories), Draco, and most sets oscillating around ~12 max CMC after that point. Very spikey though by comparison, swinging from 10 to 15 depending on the Set, while Avg only oscillates 0.2 between Sets.
• quick_reference Moving onto how CMC's fall into cost bands, the biggest groups are by far 2-3 and 4-5. On either side of this CMC plateau, most other cards make up only ~20% of any given set. Effectively, this is close to a Gaussian distribution with a center near 3, and a lopsided long tail for larger CMCs.
• quick_reference This ~Gaussian distribution can be seen more clearly when we look at individual CMCs per set, with nearly 60% of all cards falling into either CMC 2 (~20%), CMC3 (~20%), or CMC4 (~< 20%). Surprisingly to me, CMC1 and CMC5 are roughly equal, with contributions dramatically falling above CMC5. Personally, I thought there would be more CMC1 cards to allow for ramping into a strategy. Yet, CMC1 cards were common in Alpha (LEA, 93, web_stories) / Beta (LEB, 93, web_stories) and then plunged in number all the way until 1999. CMC2 had a big year in 1997 (~30%), and then fell to <~20% afterward, while CMC3 had a big year in 1999, and then oscillate around 20% of most releases.

 

 

 

 

 

 

 

 

• groups G. C. Putnam
• quick_reference In the next set of eight (8) graphs, I have used regression analysis to solve Ax=b to find the values in mana for properties of cards. A is a matrix made up of the value of attributes (such as a creature's P/T #'s) and binary 0/1 values for whether it possesses Keywords or Actions, x is the value we are trying to solve for, and b is the known card CMC. Using Singular Value Decomposition, I find the least squares inversion of A and solve for x. One way to think of this is "how much does one point of P/T cost in mana from set to set?" In general, you could say the value for P has been getting slightly worse over time, with the current cost sitting at ~0.5, while one point of T only costs about 0.4.
• quick_reference A similar question for the value of a Variable P/T on a creature (x or * in its stat block) with the average value of such a stat sitting at ~2 mana points. Notably, variable T seems to be the more costly option (particularly in recent years) rising to a premium of 3-4 points.
• quick_reference For the third graph, the idea was to see how a Mana Symbol (or multiple) in the cost of a card affected its value (vs just being 1 mana). In these graphs, if the number is 0, the symbol is worth 1 mana, if positive (+), the symbol is worth extra mana, and if negative (-) it actually applies a cost increase (ex: from 2005-2007, each mana symbol, no matter the type, netted you ~0.4 reduction in the overall CMC of a card) Blue and Black tend to be the winners in this dept, as they more consistently give CMC reductions, while White shows decidedly worse performance during a few key years. The Invasion Block (INV, 00, web_stories) (PLS, 01, web_stories) (APC, 01, web_stories) and Mirrodin block (MRD, 03, web_stories) (DST, 04, web_stories) (5DN, 04, web_stories) (and a lesser extent Zendikar Block (ZEN, 09, web_stories) (WWK, 10, web_stories) (ROE, 10, web_stories) / Scars of Mirrodin Block (SOM, 10, web_stories) (MBS, 11, web_stories) (NPH, 11, web_stories)) were noticeably bad, with the usual discount actually turning into a cost increase. Apparently artifact planes are really bad for rainbow mana.
• quick_reference A lot of that cost reduction for Mirrodin was instead taken up by Rarity. However, since all three rose in tandem, it just means that the influence of Mana relative to Rarity changed dramatically. Historically, the discount was fairly obvious, with Rares, then Uncommon, then Common costing the most CMC. Rarity was supposed to cost a bunch. However, after Mythics were introduced in 2008, the script flipped. Now Rares and Mythics actually gave a CMC discount, making them often "better" than normal cards. This wasn't usually severe, with a notable exception being Mythics during 2015-2016 (Battle for Zendikar (BFZ, 15, web_stories) / Shadows over Innistrad (SOI, 16, web_stories)), where Mythics were ~0.5 CMC cheaper than comparable Commons / Uncommons.
• quick_reference The next three look at Keywords. Notable trends include the consistent cost discount applied by having Defender on a card (~1 CMC) and the surprising cost-discount of Deathtouch, whose CMC value actually tends to be negative.
• quick_reference The most heavily used of the Keywords, Flying, also tends to be one of the most consistently high valued, worth about 0.5 CMC on any card for its evasion. For being such a desirable property, Hexproof actually tends to be available at a CMC discount in many early years, with some initial cards severely under-costed. Indestructible is perhaps the most swingy of all the keywords, being heavily over-costed when it first came out (Kamigawa (CHK, 04, web_stories) 8CMC Myojin's and divinity counters anyone?), and then actually transitioning to a discount in later years.
• quick_reference Almost all the rest of the Keywords in the third Keyword graph have ~0 actual CMC cost or discount when included (oscillating between +/- 0.5) with the exception of Menace, which for a short time was a dramatically over-costed form of evasion.
• quick_reference The final chart looks at Action words. Despite their heavy use, few of the Action words actually apply very much CMC cost to creatures when they are added, with the exception of Create, which has generally been at least as valuable as Flying, if not dramatically moreso during the early years of Magic.

 

 

• groups G. C. Putnam
• quick_reference Two final graphs summarizing CMC contributions and errors in predictions. The first looks at the contribution of various components using the prediction methods above to give a sense of scale. By far, the biggest contributors are P/T (either static or variable) followed by the Rarity of the card. Since all the Rarities actually follow closely in lockstep with one another, and have been declining over time, this means that P/T is really the largest contributor that varies significantly. In one sense, most Keywords, and Mana Symbols actually have very little impact on card costs OR those costs effectively have already been taken into account as a "baseline" for cards. (ie, it is expected most cards will have 1-2 mana symbols and 1-2 keywords, with the outliers being exceptional)
• quick_reference This graph looks at how much the predictions of creature value miss the actual value of creatures when I calculate A * x = CMC(predicted) vs CMC(actual). Error avg just takes all the errors and averages them, Error abs takes their absolute values, while RMS is the Root-Mean Square error, which squares and then square roots each error and then averages. RMS is probably the most representative and most commonly used in statistics papers with usual error being about 0.75 CMC.

 

 

 

 

 

 

 

 

• groups G. C. Putnam
• quick_reference For these last sets of graphs, I wanted to look at how the art of Magic the Gathering has changed over time. To do so, I collected samples of the art for every card ever released and performed what is known as Perceptual Hash analysis on those cards (www.phash.org and WP: Perceptual Hashing)
• quick_reference The basic idea of a perceptual hash is that it compares art / images and gives you a number which represents the distance of those images from one another. For each set in Magic, I then constructed a matrix of all of these distances and then backsolved to find the positions of the images, as if they were points in space using a technique called Multi-Dimensional Scaling. The points were given three degrees of positioning freedom with X being the primary degree, Y being secondary, and Z being tertiary. While this was performed for every set, I have only included six examples for sake of brevity and to highlight interesting trends. Finally, for every art piece, I also averaged the entire art down to a single pixel so see how much correlation the average color had on the "closeness" predicted by the pHash algorithm. Short answer, not much.
• quick_reference A notable trend in color with Magic is that sets have been getting perceptibly darker over time. Legends (LEG, 1994, web_stories), was perhaps the most "pastel" set ever released, and Magic has rarely ever returned to that level of colorfulness. With later sets like Innistrad (ISD, 2011, web_stories) and Shadows over Innistrad (SOI, 2016, web_stories), the sets are damn near black. Amusingly, what was apparently one of the worst sets for the Gatewatch "heroes", as big-bad Nicol Bolas succeeded was actually one of the brightest / happiest sets in the art, while every set the Gatewatch feature prominently in has been dark, dark, dark. Makes you wonder who the "good" guys actually are? Or perhaps, it's all actually rather evil in Magic the Gathering land, and heroic folks are not much liked.
• quick_reference Most main releases, like 5th Edition (5ED, 1997, web_stories) tend to have a primary blob of similar art with an extended halo of art with more variety. Expansions, "usually" seem to have much less concentration and more variety all throughout. From the Perceptual Hash algorithm's perspective, Urza's Destiny (UDS, 1999, web_stories) is perhaps one of the most uniform art style expansions. Most sets have a +/- 10 range, Urza's Destiny has few outliers beyond +/- 5. Looking back over the art to check, a lot of the art is very similar, with head and shoulder's portraits featuring heavily.
• quick_reference Apocalypse, (APC, 2001, web_stories), is included being one of the most scattered / varied art sets ever made, with even the center of mass of the cloud having few-to-no contributing images, and very little clumping of art otherwise.
• quick_reference As noted earlier, Innistrad, and Shadows Over Innistrad, are dark to the point of nearly black. Its surprising looking back on it, as most cards barely even have another color besides black.
• quick_reference In contrast, Hour of Devastation (HOU, 2017, web_stories), where the planeswalkers fail, is actually one of the brightest, most pastel sets since the time of Legends. It also features a similar amount of art scatter as Apocalypse.
• quick_reference Finally, a view of the most recent set (at 2018), Dominaria (DOM, 2018, web_stories), which continues the pastel trend and diverse art assets. Compared to most of the core sets like the initial 2nd / Unlimited Edition (2ED, 93, web_stories) example I showed (representative of most core sets), it is spread out quite evenly with lots of diversity in the form and coloring of the art.

Statistics of Star Trek

• This is a 30+ image album breakdown of the 80's to 90's Star Trek shows, created by me in 2015, based on the user ratings of episodes (TV.com / IMDB), the Nielson ratings of the shows, and the largely user generated episode synopses on TV.com and Wikipedia (looking for word frequency and association with ratings).
• After having gone through a rewatch of Trek's high points, and guiding a lot of that watch on the recommendations of social media, I started to be curious how user ratings and commercial ratings like Nielson's interacted with the shows.
• Other data looks at: the Nielson's for shows in isolation, Nielson for TNG seasons, ratings by characters (main, support, guest), by settings and plot threads, by directors, and by writers, as well as some other visualizations to show relative ratings of groups.
• Original post on Reddit
• Original post on Imgur
• A second post was made called "Imgur: Statistics of Star Trek - Addendum: DS9" (also rocket_launcharchived on this site).

 

• groups G. C. Putnam
• quick_reference This first picture is just a bulk plot of the user ratings for all episodes of all Trek shows from the 80's to 00's era of Star Trek (TNG, DS9, VOY, ENT) with simple curve fits to the rating trends.

 

• groups G. C. Putnam
• quick_reference For this particular picture, I'm looking at the lifetime Nielson ratings for the 80' - 00's era of Star Trek (TNG, DS9, VOY, ENT), fitting simple curve fits to the data to look at how its trending, and then trying to highlight some of the data that may have led to shows getting pitched or canned.
• quick_reference Notes from Reddit folks:
  • - Many shows were not cancelled, but rather the production crew decided to quit making the show.
  • - TNG and DS9 were syndicated while VOY and ENT were network
  • - TNG and DS9 were [possibly stopped] because of the business model in place at the time, wherein a show became more costly to produce in syndication with each new season, thereby making it too expensive to keep on the air after seven seasons.
• quick_reference Responses and Other Observations:
  • - There is a visible trend where each show switches from 2nd order positive curvature (up) to second order negative curvature (down) near the end of their life (maybe why they quit/were canned)
  • - While TNG and DS9 were both created for syndication, TNG remained flat / up for most of its life while DS9 started with TNG's audience and then dropped off a cliff. It basically went into free-fall and never recovered. If it had kept going, it would have been at VOY / UPN levels.
  • - Further, VOY then started with audience part way down the slope, and followed nearly the exact-same-path as DS9 in the ratings. By mid-way through their lives they're entwined and look like a helix.
  • - You could also, without much challenge, make an easy curve fit hitting nearly every show's Nielsens with a single line. That says to me that there's more than just syndication issues going on. That's more like your whole audience base is shifting (possibly TV's greater shift, maybe you just lost the "hot, talked about show" trait.)
  • - The general shift for network vs not doesn't seem as pronounced as you would think. The shift honestly looks like about a flat 1-2 Nielsen point bias between syndication vs network if I just compare DS9 to VOY and look at their curves. That's not nearly the story of the woeful performance of the crummy network. That's 4 network vs 5-6 in syndication.

 

• groups G. C. Putnam
• quick_reference User ratings for Star Trek: The Original Series on TV.com and IMDB. No Nielson ratings could be found.

 

• groups G. C. Putnam
• quick_reference User ratings for Star Trek: The Next Generation on TV.com and IMDB along with Nielson ratings.

 

• groups G. C. Putnam
• quick_reference User ratings for Star Trek: Deep Space Nine on TV.com and IMDB along with Nielson ratings.

 

• groups G. C. Putnam
• quick_reference User ratings for Star Trek: Voyager on TV.com and IMDB along with Nielson ratings.

 

• groups G. C. Putnam
• quick_reference User ratings for Star Trek: Enterprise on TV.com and IMDB along with Nielson ratings.

 

 

 

 

 

 

 

• groups G. C. Putnam
• quick_reference Zoomed in view of user ratings for Star Trek: The Next Generation Season 1-7 on TV.com and IMDB along with Nielson ratings.

 

• groups G. C. Putnam
• quick_reference Plot of the various characters common to TNG and how they rate on average with viewers for their episodes.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the main cast appearances and average rating per cast member. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the main cast. The first chart is the number of episodes which directly reference a main cast character in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the supporting cast appearances and average rating per cast member. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the supporting cast. The first chart is the number of episodes which directly reference a supporting cast character in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the guest cast appearances and average rating per cast member. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the guest cast. The first chart is the number of episodes which directly reference a guest cast character in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the settings or antagonist appearances and average rating per cast member. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the settings or antagonist. The first chart is the number of episodes which directly reference a settings or antagonist in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the director participation (2+ episodes minimum) and average rating per show they worked on. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the director. The first chart is the number of episodes which directly reference a director in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the writers for teleplay participation (2+ episodes minimum) and average rating per show they worked on. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the writer. The first chart is the number of episodes which directly reference a writer in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the writers for story participation (2+ episodes minimum) and average rating per show they worked on. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the writer. The first chart is the number of episodes which directly reference a writer in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

Statistics of Star Trek - DS9 Addendum

• This is the second post in a series on the statistics of the Star Trek shows of the 90's and early 2000's. Originally created back in 2015, this was a follow on to a post covering general Star Trek summaries and specifics about The Next Generation, while this covers data on the show DS9. In this update, I have covered most of the ways I analyzed TNG, and then have updated my methods with some new ways of exploring the DS9 history.
• Original post on Reddit
• Original post on Imgur
• Follow on to the post "Imgur: The Statistics of Star Trek - Ratings and Reactions" (also rocket_launcharchived on this site).

 

• groups G. C. Putnam
• quick_reference This first visualization is the mean Nielsen ratings for show by season with Stdev bands, as I wanted to look at how ratings performed over time and whether there was much variation (like a ringdown). Oddly, what I found was that the show's ratings bleed was almost perfectly linear (which was kind of odd) except for a sharp drop between episodes 1 (TNG scale 19) and episode 2 (typical 13 heading downward). Makes me suspect that a large portion of the potential audience simply saw the setting, made a first impression judgement, and left, and then the show bled slowly for the rest of its life.

 

• groups G. C. Putnam
• quick_reference Almost perfectly counter to the Nielsen ratings for the show, the viewer quality ratings of the show almost linearly improved with time (S3 and S6 were big scatter seasons). Season 4 would probably be considered a highlight of the show, as it was significantly above the linear trend in quality. As you can note later, its curve in quality was smooth, and also curved upward which gives the impression of a heroic cycle during the season. One theory for the overall trend might be that the show concentrated its viewer base to only the diehard viewers, and then focused closer in on what those viewers wanted.

 

• groups G. C. Putnam
• quick_reference For this chart, I have graphed the Nielsen Rating (NR) vs the Viewer Rating Avg. (VR) for all seasons in red and plotted how it trends. Up to the right mean large VR correlates well with large NR. In the second column, I have instead plotted the change in NR (the Delta) from episode to episode ([Ep i NR] - Ep i-1 NR] vs the VR. In some cases this made a difference as a rating appeared to produce a large change in NR even though the shift was hidden when viewed as whole numbers. Noisy seasons (like season 3) were helped a lot by this effect. Finally, in the third column, I also looked at the Delta with a delay of 1 episode, to see if there was a time delay effect on ratings with any correlation. Fairly bad.

 

 

 

 

 

 

 

• groups G. C. Putnam
• quick_reference Zoomed in view of user ratings for Star Trek: Deep Space Nine, Season 1 on TV.com and IMDB along with Nielson ratings. Note the previously mentioned sharp drop between episodes 1 (TNG scale 19) and episode 2 (typical 13 heading downward), with ratings simply decaying linearly afterward.

 

• groups G. C. Putnam
• quick_reference A slightly more complex version of the reference vs rates chart that I used for TNG. Again, I am showing how the various characters and settings appear with respect to both time and quality and then identifying geometric groups among the set.

 

 

 

• groups G. C. Putnam
• quick_reference These plots graph the main cast appearances, average rating per cast member, and individual episode ratings with scatter and trends. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the main cast. The first chart is the number of episodes which directly reference a main cast character in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.
• quick_reference The third plot is a new type of charts I'm trying based on some papers on statistical processing that I read in the interim. In this version, I am plotting the individual episode ratings for each character so that the visual blob of their progress over time can be seen and then explicitly finding a trajectory for their time on the show. I started exploring the this type of chart specifically because of issues with this type of visualization. Although it looks like all the characters are very similar and have only minor differences, when we show the cloud of their actual ratings and the trajectories they took.

 

 

• groups G. C. Putnam
• quick_reference Another option I'm trying this round is showing how the evolution of characters with large numbers of appearances changed over time. For example, Julian shows an amazing amount of growth over the show, moving from the least to the most favorite character, in terms of average character specific episode ratings.

 

 

 

• groups G. C. Putnam
• quick_reference These plots graph the supporting cast appearances, average rating per cast member, and individual episode ratings with scatter and trends. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the supporting cast. The first chart is the number of episodes which directly reference a supporting cast character in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.
• quick_reference For the third plot, the individual episode ratings for each supporting character, so that the visual blob of their progress over time can be seen and then explicitly finding a trajectory for their time on the show.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the guest cast appearances and average rating per cast member. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the guest cast. The first chart is the number of episodes which directly reference a guest cast character in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.

 

 

 

• groups G. C. Putnam
• quick_reference These plots graph the setting or antagonist appearances, average rating per cast member, and individual episode ratings with scatter and trends. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the setting or antagonist. The first chart is the number of episodes which directly reference a setting or antagonist character in the synopsis on wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down.
• quick_reference For the third plot, the individual episode ratings for each setting or antagonist, so that the visual blob of their progress over time can be seen and then explicitly finding a trajectory for their time on the show.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the director participation (2+ episodes minimum) and average rating per show they worked on. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the director. The first chart is the number of episodes which directly reference a director in the synopsis on Wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down. I had no idea that Levar Burton was such a prominent director on this show. Unfortunately, of the heavy hitters, he's not one of the best. That distinction probably goes to Allan Kroecker and James Conway (much improved, as he was an OK director on TNG). Also, Michael Dorn proved to be another character actor with a good eye for behind the camera (after 300+ eps you'd think he might)

 

 

• groups G. C. Putnam
• quick_reference These plots graph the teleplay writer participation (2+ episodes minimum) and average rating per show they worked on. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the director. The first chart is the number of episodes which directly reference a director in the synopsis on Wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down. Within the teleplay writers, this show was heavily dominated by about five people, the kings of TNG writing, and particularly by Ira Steven Behr. The well rated Hans Beimler moved up in # cnt as well, and Peter Allan Fields performed much better on DS9 than on TNG.

 

 

• groups G. C. Putnam
• quick_reference These plots graph the teleplay writer participation (2+ episodes minimum) and average rating per show they worked on. Episode summaries on Wikipedia, IMDB, and TV.com were searched for a given keyword, in this case, the names of the director. The first chart is the number of episodes which directly reference a director in the synopsis on Wikipedia or TV.com and then showed how they trend over the seasons of the show. For the second chart, all episodes associated with those words had their ratings averaged, and then that rating is plotted here with the standard deviation up / down. Compared to TNG, this show was MUCH more dominated by a few guiding voices, with less of what we might call RAND() or MEOW (MonstEr/challenge Of the Week) episodes. Apparently Rick Berman and Jeri Taylor are REALLY consistent at making good stories, but they were not nearly so hot at turning those into functional teleplays.

Ares Scale Model Acoustic Test (ASMAT)

• The Ares I Scale Model Acoustic Test (ASMAT) program was implemented to verify the Ares I Liftoff Acoustics (LOA) and Ignition Over-Pressure (IOP) environments.
• These tests provided a well documented set of high fidelity acoustic measurements useful for validation, including data taken over a range of test conditions.
• A digital representation of the test setup was constructed and test firings of the motor were simulated using Loci/CHEM
• Results with the rocket in held down and elevated configurations, as well as with and without water suppression were compared to acoustic data.
• The results showed good correlation with the amplitude and temporal shape of pressure features.
• The work was accomplished primarily at NASA Marshall Space Flight Center in Alabama from 2010-2012.

• groups G. C. Putnam
• quick_reference Four (4) images showing the ASMAT test configuration and test samples, including: The full scale Ares 1-X rocket vs 5% scale model, the ground support equipment, a held down firing, and an elevated firing.

quick_reference The full scale Ares 1-X rocket on the launch pad next to the 5% scale model ASMAT.

quick_reference ASMAT ground support equipment. The test had a telescoping cage that could lift the vehicle to different heights to simulate liftoff.

quick_reference Held down firing of ASMAT at Marshall Space Flight Center Test Stand 116. The full test matrix had heights at 0 ft, 2.5 ft, 5 ft, 7.5 ft, and 10 ft + drift + water variations.

quick_reference Elevated firing of ASMAT at Marshall Space Flight Center Test Stand 116. The full test matrix had heights at 0 ft, 2.5 ft, 5 ft, 7.5 ft, and 10 ft + drift + water variations.

quick_reference Infrared imagery of the ASMAT plume taken during ASMAT test 7 with SC655 Camera.

quick_reference Animation of the infrared imagery of the ASMAT plume taken during ASMAT test 7 with SC655 Camera.

• linkhistory_edu Full Scale Acoustic Liftoff Environments versus Scale Model Results., Counter, Douglas D., and Nesman, Thomas., AIAA SciTech Forum, 2024.
• linkhistory_edu Verification of Ares I liftoff acoustic environments via the Ares I scale model acoustic test, D. D. Counter, J. D. Houston, Aerospace Testing Seminar, no. M12-1989, October 6th 2012.
• linkhistory_edu Overview of the Ares I scale model acoustic test program., D. D.Counter, J. D.Houston, 162nd ASA Meeting and Noise Conference 2011. No. M11-1210. 2011.
• linkhistory_edu Infrared Imagery of Solid Rocket Exhaust Plumes, R. P. Moran, J. D. Houston, JANNAF 8th Modeling and Simulation Subcommittee Meeting, no. M11-1356, December 5th 2011

• groups G. C. Putnam
• quick_reference Four (4) images showing the features of ASMAT and test hardware used for CFD data and validation, including: the main ASMAT features, the microphones used, the overhead cameras available, and the ground cameras.

quick_reference ASMAT 5% scale model test configuration features.

quick_reference Microphones and corresponding probes used for the simulation. IOP corresponds to Ignition Over-Pressure, the initial blast wave at rocket ignition.

quick_reference Cameras at overhead level. Cameras had many purposes including: Recording the hotfire, timing the hotfire with strobes, resolving test failures, and supporting CFD modeling.

quick_reference Cameras at ground level. Cameras had many purposes including: Recording the hotfire, timing the hotfire with strobes, resolving test failures, and supporting CFD modeling.

quick_reference Infrared Cameras at ground level. Infrared cameras were meant to provide support data for the validation, improve analysis data, and and corollate plume size with noise suppression achieved by water sound suppression.

• history_edu Development of modeling capabilities for launch pad acoustics and ignition transient environment prediction, J. S. West, L. L. Strutzenberg, G. C. Putnam, P. Liever, and B. Williams, 18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference), p. 2094, 2012
• history_edu Simulation of Ares Scale Model Acoustic Test Overpressure Transients Using Computational Fluid Dynamics, G. C. Putnam, 162nd Acoustical Society of America (ASA) Meeting, San Diego, CA, Paper M11, Volume 1226, 2011
• history_edu Validation and Simulation of ARES I Scale Model Acoustic Test - 1 - Pathfinder Development, G. C. Putnam, JANNAF 8th Modeling and Simulation Subcommittee Meeting, NASA George C. Marshall Space Flight Center, Huntsville, AL, no. M11-0635, 2011
• linkhistory_edu Overview of the Ares I scale model acoustic test program., D. D.Counter, J. D.Houston, 162nd ASA Meeting and Noise Conference 2011. No. M11-1210. 2011.
• linkhistory_edu Infrared Imagery of Solid Rocket Exhaust Plumes, R. P. Moran, J. D. Houston, JANNAF 8th Modeling and Simulation Subcommittee Meeting, no. M11-1356, December 5th 2011

• groups G. C. Putnam
• quick_reference Eight (8) images illustrating the CAD model source for the ASMAT simulation, the resulting CFD mesh, and quality of the mesh relative to the flow involved, including: the full CAD model, the simplified model, the simulation bounds, the nozzle and launch mount features, the full bounds mesh, the initial trench mesh, the refined trench mesh, and the CFL fluid velocity vs cell size and time step conditions.

quick_reference Full CAD model for ASMAT test setup

quick_reference Simplified CAD model for ASMAT test setup after visiting test pad and taking pictures to understand important features

quick_reference ASMAT simulation bounds. ANSA was used to divide the model into components, create a mesh, and place structure within a computational domain.

quick_reference Detail view of CAD model features within the rocket nozzle and launch mount.

quick_reference Section of volume mesh through vehicle and flame trench. At large distances the mesh quickly drops to a very low resolution, due to lack of applicability for acoustic environments, and changes made to the plume path and tower cells for the refined mesh were only slightly visible.

quick_reference Section of volume mesh in the vicinity of active trench region – Initial Mesh. The focus is on the critical areas within the plume core, below the deck, and just above the deck surface, with an order of magnitude difference in cell size between the upper and lower trench, and a lack of resolution near the exit of the plume hole.

quick_reference Section of volume mesh in the vicinity of active trench region – Refined Mesh. Issues with cell size near the plume hole were repaired, with a high density path column present up to the point of impact with the deflector, and a smooth cell size throughout the trench.

quick_reference Courant-Friedrichs-Lewy (CFL) numbers for the simulation at completion. Near vehicle regions exhibit CFL numbers of 1-10, near plume regions 10-100, and internal plume features 100-1000. Calculations used an implicit method with adjustable time steps that meant near plume and internal plume features required extremely small time steps calculated many times relative to the larger mesh.

• history_edu Simulation of Ares Scale Model Acoustic Test Overpressure Transients Using Computational Fluid Dynamics, G. C. Putnam, 162nd Acoustical Society of America (ASA) Meeting, San Diego, CA, Paper M11, Volume 1226, 2011
• history_edu Validation and Simulation of ARES I Scale Model Acoustic Test - 1 - Pathfinder Development, G. C. Putnam, JANNAF 8th Modeling and Simulation Subcommittee Meeting, NASA George C. Marshall Space Flight Center, Huntsville, AL, no. M11-0635, 2011

• groups G. C. Putnam
• quick_reference Three (3) images describing the mass flow rate inputs, difficulties with timing, and changes made to model the sharp starting transient, including: the basic profile, the various methods used to deal with the transient, and comparison to experimental data.

quick_reference Input curve for the mass flow rate in the nozzle chamber. Samples were taken every 2.5 ms prior to 0.06 seconds and every 12.5 ms after.

quick_reference Methods of Modeling Ignition Transient. The first method was a sharp start of mass flow (green line) at the point of maximum pressure during ignition. This reproduced the transient effects at motor start, but resulted in flow, and signals, too early. The second method used a time delay (blue line) of ~5 ms, resulting in the main mass flow peak shifting ~20 ms after simulation start.

quick_reference Pressure rise rate timing of the motor compared to transducer oscillations in the nozzle for the actual test. This provided experimental evidence of the pressure buildup and propagation delay prior to throat plug loss in the test hardware.

• history_edu Simulation of Ares Scale Model Acoustic Test Overpressure Transients Using Computational Fluid Dynamics, G. C. Putnam, 162nd Acoustical Society of America (ASA) Meeting, San Diego, CA, Paper M11, Volume 1226, 2011
• history_edu Validation and Simulation of ARES I Scale Model Acoustic Test - 1 - Pathfinder Development, G. C. Putnam, JANNAF 8th Modeling and Simulation Subcommittee Meeting, NASA George C. Marshall Space Flight Center, Huntsville, AL, no. M11-0635, 2011

• groups G. C. Putnam
• quick_reference Four (4) images and three (3) videos showing the time progression of the simulation and comparing the initial and refined results, including: the initial results progression, the refined results progression, a comparison of the shock trains, a comparison of plume behavior, animations of the initial and refined results, and a full bounds animation of the refined results (shown as a NASA Booth demo at Supercomputing 11.

quick_reference Time Progression of Pressure Waves in Initial Pathfinder Simulation

quick_reference Time Progression of Pressure Waves in Refined Pathfinder Simulation

quick_reference Comparison of Initial Pressure Shock Train Behavior between Simulations

quick_reference Comparison of Plume Behavior and Trench Wall Attachment Between Simulations

quick_reference Animation of Pressure Waves in Initial Pathfinder Simulation

quick_reference Animation of Pressure Waves in Initial Pathfinder Simulation

quick_reference Animation of pressure contours through the centerline of the simulation as the rocket ignites, the ignition overpressure propagates, and the plume stabilizes, Supercomputing 11 Demo

• history_edu Simulation of Ares Scale Model Acoustic Test Overpressure Transients Using Computational Fluid Dynamics, G. C. Putnam, 162nd Acoustical Society of America (ASA) Meeting, San Diego, CA, Paper M11, Volume 1226, 2011
• history_edu Validation and Simulation of ARES I Scale Model Acoustic Test - 1 - Pathfinder Development, G. C. Putnam, JANNAF 8th Modeling and Simulation Subcommittee Meeting, NASA George C. Marshall Space Flight Center, Huntsville, AL, no. M11-0635, 2011
• history_edu Simulating the Ares I Scale Model Acoustic Test Using CFD, G. C. Putnam, Supercomputing 11, NASA@SC11 Booth, Seattle, Washington, 2011

Water Deluge

• A significant issue and risk for space vehicles is the acoustic and vibration environment. Ignition Over-Pressure (IOP) and plume reflections off the deck are concerns that need to be mitigated because of risk to the vehicle and payload.
• The Space Shuttle historically, and the Space Launch System, have both used deluges of water from rainbirds on the deck, pipes in the plume hole, and cascades down the flame trench.
• Modeling these systems is challenging for Computatational Fluid Dynamics (CFD) with 10,000 gallon's per minute (gpm) from individual sources, emitted as multi-foot sheets of liquid water, and nearly 900,000 gpm peak flow rates from all systems during launch.
• The final products at the time of 2012 involved 1000's of millions of particles, interacting with plumes at ~mach 10 and temperatures of 3,300°C (5,972°F) for the Space Shuttle Main Engine (SSME) and 2,500°C (4,500°F) for the Solid Rocket Boosters.
• The software demonstrated stability, bouncing, cascading, water sheets on complex hardware, evaporation, plume energy absorbing, and visible reductions in acoustics that matched well with test data available.
• At Marshall Space Flight Center (MSFC) this was a known issue for Liftoff Debris, and work was contracted to Mississippi State Univerity (MSU) to develop a large-scale lagrangian particle system appropriate for parallelized CFD with the Loci/CHEM software.
• My work at MSFC involved collaborating with MSU, testing and validating features, providing feedback on deficiencies or improvements, creating and evaluating unit problems, stress testing on large scale (rocket launch pad) problems, and implementing cases needed to address Liftoff Debris risks.
• Much credit to Ed Luke of Mississippi State University for the work of developing the lagrangian particle add-on for Loci/CHEM and ER42 of MSFC for employing me to work on the project.

• groups G. C. Putnam
• quick_reference Five (5) images providing reference for the water deluge and sound suppression systems used with the Space Launch System. The first two show rainbird testing on the launch pad and the large volumes of water emitted, the third shows the cascading water effect below deck in the trench, the fourth shows the SRB plume holes in integrated water systems, and the fifth shows imagery from the Space Shuttle Main Engines (SSMEs, or RS-25 model) entraining sound suppression water after startup.

• history_edu SLS Ignition Overpressure/Sound Suppression System Performance Evaluated Against Historical Configurations, A. J. Herron, M. J. Hays, M. J. Casiano, A. M. Smith, AIAA SCITECH 2024 Forum, p. 0255, 2024.
• history_edu Acoustic Prediction Method Modification for Sound Suppression Water Systems of Launch Vechicle Liftoff, K. Prichard, California State Polytechnic University, Pomona, Master's Thesis, 2023.

• groups G. C. Putnam
• quick_reference Space Shuttle rainbirds, ejecting water at tens of thousands of gallons per minute (gpm), mid-ejection (1 sec and 3.5 secs) prior to deck impact, in addition to water cascading across the launch pad after deck impact. These tested the Loci/CHEM Lagrangian two-phase model for its ability to achieve full size flow rates from single sources, and for the particle tracking to properly deal with impact, rebound, and surface flow across the launch pad. Injecting massive amounts of water in the form of Lagrangian particles requires a CFD tracking of millions of water droplets.

• history_edu The Direction of Fluid Dynamics for Liquid Propulsion at NASA Marshall Space Flight Center, L. W. Griffin, Advances in Rocket Engine Modeling and Simulation, and its Future, Tokyo, Japan, no. M12-2132, September 26th 2012.
• history_edu Development of modeling capabilities for launch pad acoustics and ignition transient environment prediction, J. S. West, L. L. Strutzenberg, G. C. Putnam, P. Liever, and B. Williams, 18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference), p. 2094, 2012.
• history_edu Hybrid computational fluid dynamics and computational aero-acoustic modeling for liftoff acoustic predictions, L. L. Strutzenberg, P. Liever, 162 ASA Meeting and Noise-Con, no. M11-1228, October 2011.

• groups G. C. Putnam
• quick_reference Testing expanded to simulations of the Solid Rocket Booster (SRB) water deluge system for the Space Shuttle. The first image shows water from a single plume hole, while the second shows both SRBs in a 3D see-thru configuration. Thousands of gallons per minute (gpm) of water are ejected from multiple opposing orifices in each SRB hole. These full-scale subsystem cases helped select suitable particle sizes, parameters for particle breakup and phase transition modeling, and interaction with solid walls. While the model handles exchange of mass, momentum and energy between the phases, particles were not aware of neighboring particles and had no particle-particle interaction. This lead to amassing of water droplets in computational cells resulting it excessive local densities. Collisions, agglomeration and deflection of particles were modeling difficulties.

• history_edu The Direction of Fluid Dynamics for Liquid Propulsion at NASA Marshall Space Flight Center, L. W. Griffin, Advances in Rocket Engine Modeling and Simulation, and its Future, Tokyo, Japan, no. M12-2132, September 26th 2012.
• history_edu Development of modeling capabilities for launch pad acoustics and ignition transient environment prediction, J. S. West, L. L. Strutzenberg, G. C. Putnam, P. Liever, and B. Williams, 18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference), p. 2094, 2012.
• history_edu Hybrid computational fluid dynamics and computational aero-acoustic modeling for liftoff acoustic predictions, L. L. Strutzenberg, P. Liever, 162 ASA Meeting and Noise-Con, no. M11-1228, October 2011.

• groups G. C. Putnam
• quick_reference A zoomed out, side by side comparison of the plume environment for the full Ares V launch pad in both dry configuration and water deluge configuration. From far away, a visible reduction in the on-deck plume regions above 500 K in temperature can be seen with water addition. The vehicle was held at a fixed height in space, and the water deluge environment had four on-deck rainbird systems activated and injected in excess of a 100,000 gallons per minute of water in total.

• history_edu The Direction of Fluid Dynamics for Liquid Propulsion at NASA Marshall Space Flight Center, L. W. Griffin, Advances in Rocket Engine Modeling and Simulation, and its Future, Tokyo, Japan, no. M12-2132, September 26th 2012.
• history_edu Development of modeling capabilities for launch pad acoustics and ignition transient environment prediction, J. S. West, L. L. Strutzenberg, G. C. Putnam, P. Liever, and B. Williams, 18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference), p. 2094, 2012.
• history_edu Hybrid computational fluid dynamics and computational aero-acoustic modeling for liftoff acoustic predictions, L. L. Strutzenberg, P. Liever, 162 ASA Meeting and Noise-Con, no. M11-1228, October 2011.

• groups G. C. Putnam
• quick_reference A zoomed in, side by side comparison of the plume environment for the full Ares V launch pad in water deluge configuration, showing the rainbirds just after activation on the left, and 4.5 seconds after activation on the right, once plume impingement and reduction are well under way. Plume impact regions above 500 K in temperature have been almost completely eliminated above the deck surface, and proper transition of a 100,000 gallons per minute of particulate water to gas phase steam can be observed.

• history_edu The Direction of Fluid Dynamics for Liquid Propulsion at NASA Marshall Space Flight Center, L. W. Griffin, Advances in Rocket Engine Modeling and Simulation, and its Future, Tokyo, Japan, no. M12-2132, September 26th 2012.
• history_edu Development of modeling capabilities for launch pad acoustics and ignition transient environment prediction, J. S. West, L. L. Strutzenberg, G. C. Putnam, P. Liever, and B. Williams, 18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference), p. 2094, 2012.
• history_edu Hybrid computational fluid dynamics and computational aero-acoustic modeling for liftoff acoustic predictions, L. L. Strutzenberg, P. Liever, 162 ASA Meeting and Noise-Con, no. M11-1228, October 2011.

• groups G. C. Putnam
• quick_reference A side by side comparison of the turbulent kinetic energy on the mobile launch platform deck, a surrogate measure for acoustic emissions. A dry configuration is shown on the left and water deluge configuration is shown on the right. Almost all of the radiating 1,000+ emissions sources on the deck have been suppressed. This work was then uses to target regions of high turbulence to reduce vehicle damaging noise emissions.

• history_edu The Direction of Fluid Dynamics for Liquid Propulsion at NASA Marshall Space Flight Center, L. W. Griffin, Advances in Rocket Engine Modeling and Simulation, and its Future, Tokyo, Japan, no. M12-2132, September 26th 2012.
• history_edu Development of modeling capabilities for launch pad acoustics and ignition transient environment prediction, J. S. West, L. L. Strutzenberg, G. C. Putnam, P. Liever, and B. Williams, 18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference), p. 2094, 2012.
• history_edu Hybrid computational fluid dynamics and computational aero-acoustic modeling for liftoff acoustic predictions, L. L. Strutzenberg, P. Liever, 162 ASA Meeting and Noise-Con, no. M11-1228, October 2011.

• groups G. C. Putnam
• quick_reference Shown is the various water deluge systems for the Ares Scale Model Acoustic Test (ASMAT). The test was a 5% scale test of the full vehicle with water from rainbirds, water bags that broke on rocket ignition, trench deflectors to oppose plume flow below the deck, and sound suppression system in the mobile launcher and launch mount. Each system could activated independently, and individual combinations were tested to evaluate their need for the full scale vehicle.

• linkhistory_edu Overview of the Ares I scale model acoustic test program., D. D.Counter, J. D.Houston, 162nd ASA Meeting and Noise Conference 2011. No. M11-1210. 2011.

• groups G. C. Putnam
• quick_reference This video shows the Ares Scale Model Acoustic Test (ASMAT), which was a 5% scale model tests of the Ares I vehicle to address vibration and acoustic risks from the Constellation Program. Pressure contours through the centerline of the rocket and water suppression as the rocket ignites, the ignition over-pressure propagates, and the plume stabilizes. The left image is the rocket on a dry launch pad without water suppression, while the right image models water suppression effects. Liquid water droplets can be seen as sprays of blue dots, while evaporated steam is visible as a translucent cloud.

• history_edu Validating Water Spray Simulation Models for the SLS Launch Environment, G. C. Putnam, Supercomputing 12, NASA@SC12 Booth, Salt Lake City, Utah, November 10th-16th, 2012
• history_edu Simulation of Ares Scale Model Acoustic Test Overpressure Transients Using Computational Fluid Dynamics, G. C. Putnam, 162nd Acoustical Society of America (ASA) Meeting, San Diego, CA, Paper M11, Volume 1226, 2011
• history_edu Validation and Simulation of ARES I Scale Model Acoustic Test - 1 - Pathfinder Development, G. C. Putnam, JANNAF 8th Modeling and Simulation Subcommittee Meeting, NASA George C. Marshall Space Flight Center, Huntsville, AL, no. M11-0635, 2011
• history_edu Simulating the Ares I Scale Model Acoustic Test Using CFD, G. C. Putnam, Supercomputing 11, NASA@SC11 Booth, Seattle, Washington, 2011

• groups G. C. Putnam
• quick_reference A still-frame image of the ASMAT simulation shown in the video above. Snapshot of pressure contours through the centerline of the rocket with water suppression simulation as the overpressure propagates through the launch tower and a the translucent evaporation cloud of water forms in the flame trench.

• history_edu Validating Water Spray Simulation Models for the SLS Launch Environment, G. C. Putnam, Supercomputing 12, NASA@SC12 Booth, Salt Lake City, Utah, November 10th-16th, 2012
• history_edu Simulation of Ares Scale Model Acoustic Test Overpressure Transients Using Computational Fluid Dynamics, G. C. Putnam, 162nd Acoustical Society of America (ASA) Meeting, San Diego, CA, Paper M11, Volume 1226, 2011
• history_edu Validation and Simulation of ARES I Scale Model Acoustic Test - 1 - Pathfinder Development, G. C. Putnam, JANNAF 8th Modeling and Simulation Subcommittee Meeting, NASA George C. Marshall Space Flight Center, Huntsville, AL, no. M11-0635, 2011

• groups G. C. Putnam
• quick_reference Rocket plume gas and evaporating suppression water interact as the ignition overpressure (IOP) wave propagates through the launch tower. In this held-down ASMAT configuration, water sprays are emitted primarily in the plume path hole (shown as blue particulates), and then mix with the plume gas over the length of the trench, transitioning to gaseous H2O (steam) miway down the trench and at the exit.

• history_edu Simulating Rocket Ignition and Launch Environments for NASA's Space Launch System, P. Davis, G. C. Putnam, B. Williams, Supercomputing 12, NASA@SC12 Booth, Salt Lake City, Utah, November 10th-16th, 2012
• history_edu Validating Water Spray Simulation Models for the SLS Launch Environment, G. C. Putnam, Supercomputing 12, NASA@SC12 Booth, Salt Lake City, Utah, 2012
• history_edu The Direction of Fluid Dynamics for Liquid Propulsion at NASA Marshall Space Flight Center, L. W. Griffin, Advances in Rocket Engine Modeling and Simulation, and its Future, Tokyo, Japan, no. M12-2132, September 26th 2012.

Liftoff Debris

• Liftoff Debris description

• groups G. C. Putnam
• quick_reference Four (4) images of Space Shuttle launches taken from the STS-98, STS-105, STS-108, and STS-109 Debris/Ice/TPS Assessment and Integrated Photographic Analysis Reports produced after each launch. Provided for orientation about the launch environment (and they're just generally pretty imagery).

 

 

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-98, R. F. Speece, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2004-211524, February 7th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-105, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-211537, August 10th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-108, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212556, December 5th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-109, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212557, March 1st, 2002

• groups G. C. Putnam
• quick_reference Two (2) images of ice formation taken from the STS-98 and STS-108 debris and photo reports. Examples of somewhat common ice formation issues that needed to be watched prior-to and during launch for possible vehicle impact.

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-98, R. F. Speece, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2004-211524, February 7th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-108, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212556, December 5th, 2001

• groups G. C. Putnam
• quick_reference Three (3) images of farfield pad debris taken from the STS-98 and STS-109 debris and photo reports. Examples of somewhat common debris being ejected from the launch pad vicinity, usually moving away from the vehicle in the farfield. Some appeared near enough that multiple camera view checks were necessary to verify a lack of impact and risk to the vehicle.

 

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-98, R. F. Speece, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2004-211524, February 7th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-109, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212557, March 1st, 2002

• groups G. C. Putnam
• quick_reference Seven (7) images of nearfield pad debris taken from the STS-108, STS-109, and STS-110 debris and photo reports. Examples of the variety of debris that might appear near the vehicle. The first shows a failure in the GH2 vent line, that then caused debris releases after the vehicle had cleared the area. The next three show debris near the Solid Rocket Boosters (SRBs), sometimes emerging from the hardware itself, and other times being propelled by the plume flow. The final three show objects that were left on the pad, or liberated during launch, and then became debris risks (rope in both cases).

 

 

 

 

 

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-108, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212556, December 5th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-109, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212557, March 1st, 2002
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-110, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212558, April 8th, 2002

• groups G. C. Putnam
• quick_reference An image of a debris impact taken from the STS-108 debris and photo report. A somewhat rare example of a direct debris impact observation, with ice or frost observed impacting the umbilical well door of the vehicle.

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-108, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212556, December 5th, 2001

• groups G. C. Putnam
• quick_reference Sixe (6) images of free burning hydrogen taken from STS-104 and STS-108 debris and photo reports. Hydrogen collecting and burning in open air was observed on several launches and was viewed as a possible risk for explosion or detonation depending on the concentration. In a nominal launch there should have been very little excess hydrogen released.

 

 

 

 

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-104, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-211536, July 12, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-108, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212556, December 5th, 2001

• groups G. C. Putnam
• quick_reference Three (3) images of the post-launch walkdown and debris found after launch from STS-104 and STS-105 debris and photo reports. After launch, the post-launch team would go out to the pad and document the launch pad state and any debris issues found. Two examples of items found include a pipe end cap that came loose and a wall fastener that broke off (from among hundreds).

 

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-104, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-211536, July 12, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-105, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-211537, August 10th, 2001

• groups G. C. Putnam
• quick_reference Seven (7) images of damage locations found on the vehicle and damage maps from STS-98, STS-100, and STS-110 debris and photo reports. On orbit, the vehicle would be imaged over the surface to document damage sites, and record imagery of any serious issues. Maps of the damage locations were then prepared along with statistics of the total number of hits, impact trends, and long form discussions for any anomalous events.

 

 

 

 

 

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-98, R. F. Speece, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2004-211524, February 7th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-100, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2004-211525, August 1, 2004
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-110, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212558, April 8th, 2002

• groups G. C. Putnam
• quick_reference Three (3) images of post-retrieval condition of the SRBs from STS-98 and STS-110 debris and photo reports. After launch, and seperation from the vehicle, the Solid Rocket Boosters (SRBs) would parachute into the ocean, and then be retrieved by boats and brought back to the military base near Kennedy Space Center, where they would be evaluated for their condition and any anomalous issues.

 

 

 

• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-98, R. F. Speece, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2004-211524, February 7th, 2001
• history_edu Debris/Ice/TPS Assessment and Integrated Photographic Analysis of Shuttle Mission STS-110, A. Oliu, Process Engineering/Mechanical System Division/ET-SRB Branch, Kennedy Space Center, Florida, no. NASA/TM-2005-212558, April 8th, 2002

• groups G. C. Putnam
• quick_reference Seven (7) images providing an orientation to the launch pad environment, the critical debris zones, floors of specific interest because of debris issues and hardware, examples of debris items recorded over the flights, and the repair resolution of a specific bolt example identified as a trend in STS-119.

 

 

 

 

 

 

 

• history_edu Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation, M. Mitchell, C. Riley, PM Challenge 2011, 8th Annual NASA Project Management Challenge, Long Beach Convention Center, Long Beach, CA, no. M11-0123, February 9th, 2011
• history_edu The Role of CFD Simulation in Rocket Propulsion Support Activities, J. West, 3rd Annual SimBRS Conference, Starkville, MS, no. M11-0827, July 26th, 2011.
• history_edu CFD Modeling of Plume Induced Environments for Space Shuttle Liftoff Debris Transport Analysis, P. Liever, J. Radke, L. L. Strutzenberg, J. West, 2nd Workshop on Lunar and Martian Plume Effects and Mitigation, Kennedy Space Center, Florida, NASA no. M11-1234, January 20th, 2012.

• groups G. C. Putnam
• quick_reference Five (5) images showing the process used for computationally examining debris risk, the typical locations of the Shuttle in flight (and calculation cases used) for analysing risk, the CAD models available of the launch pad, the resulting CFD meshes produced, and a comparison of those models to the actual vehicle on the launch pad.

 

 

 

 

 

• history_edu Space Shuttle Propulsion Systems Plume Modeling and Simulation for the Lift-Off Computational Fluid Dynamics Model, L. L. Strutzenberg, N. S. Dougherty, P. A. Liever, J. S. West, S. D. Smith, 54th JANNAF Propulsion Meeting, Denver, CO, May 14, 2007
• history_edu Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation, M. Mitchell, C. Riley, PM Challenge 2011, 8th Annual NASA Project Management Challenge, Long Beach Convention Center, Long Beach, CA, no. M11-0123, February 9th, 2011
• history_edu The Role of CFD Simulation in Rocket Propulsion Support Activities, J. West, 3rd Annual SimBRS Conference, Starkville, MS, no. M11-0827, July 26th, 2011.
• history_edu CFD Modeling of Plume Induced Environments for Space Shuttle Liftoff Debris Transport Analysis, P. Liever, J. Radke, L. L. Strutzenberg, J. West, 2nd Workshop on Lunar and Martian Plume Effects and Mitigation, Kennedy Space Center, Florida, NASA no. M11-1234, January 20th, 2012.

• groups G. C. Putnam
• quick_reference Nine (9) images illustrating the CFD results and calculations used for liftoff debris, with an orientation to the launch pad winds, several results used for wind blown debris calculations, results showing the plumes calculated mid launch impacting the pad, and two cross sectional views of the Mach 3 plumes and the shock effect interactions for the SRBs that had to be handled.

 

 

 

 

 

 

 

 

 

• history_edu Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation, M. Mitchell, C. Riley, PM Challenge 2011, 8th Annual NASA Project Management Challenge, Long Beach Convention Center, Long Beach, CA, no. M11-0123, February 9th, 2011
• history_edu The Role of CFD Simulation in Rocket Propulsion Support Activities, J. West, 3rd Annual SimBRS Conference, Starkville, MS, no. M11-0827, July 26th, 2011.
• history_edu CFD Modeling of Plume Induced Environments for Space Shuttle Liftoff Debris Transport Analysis, P. Liever, J. Radke, L. L. Strutzenberg, J. West, 2nd Workshop on Lunar and Martian Plume Effects and Mitigation, Kennedy Space Center, Florida, NASA no. M11-1234, January 20th, 2012.

• groups G. C. Putnam
• quick_reference Four (4) images showing debris transport and the path traces used for evaluating impact risk when released, along with an example of a specific risk identified due to deck recirculation in CFD, and the debris transport calculated.

 

 

 

 

 

• history_edu Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation, M. Mitchell, C. Riley, PM Challenge 2011, 8th Annual NASA Project Management Challenge, Long Beach Convention Center, Long Beach, CA, no. M11-0123, February 9th, 2011
• history_edu CFD Modeling of Plume Induced Environments for Space Shuttle Liftoff Debris Transport Analysis, P. Liever, J. Radke, L. L. Strutzenberg, J. West, 2nd Workshop on Lunar and Martian Plume Effects and Mitigation, Kennedy Space Center, Florida, NASA no. M11-1234, January 20th, 2012.

• groups G. C. Putnam
• quick_reference Ten (10) images showing the various tile groups of the Space Shuttle and the regions used for calculating impacts, and risk to the vehicle, along with the external tank and solid rocket boosters (relatively durable by comparison). First is lower surface High-Temperature Reusable Surface Insulation (HRSI), then upper surface HRSI, Felt Reusable Surface Insulation (FRSI), Advanced Flexible Reusable Surface Insulation (AFRSI), Low-temperature Reusable Surface Insulation (LRSI), Reinforced Carbon-Carbon (RCC), and finally the Windows. Afterward, the more durable Space Shuttle Main Engines (SSMEs), the External Tank (ET), and the Solid Rocket Boosters (SRBs).

 

 

 

 

 

 

 

 

 

 

• history_edu Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation, M. Mitchell, C. Riley, PM Challenge 2011, 8th Annual NASA Project Management Challenge, Long Beach Convention Center, Long Beach, CA, no. M11-0123, February 9th, 2011

• groups G. C. Putnam
• quick_reference Nine (9) images showing background, and calculations for a major debris event during STS-124 where the flame trench wall liberated sending hundreds of bricks flying out the boundary fence region. Several were visible moving upward near the vehicle in infrared imagery (video). The event set off a several month effort to develop several new CFD models for the specific conditions involved, evaluate the risk to the vehicle, repair the trench, and certify the vehicle for the next flight. The results won our team an Agency level Exceptional Analysis award in 2008.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

• link collect Space, Topic: Pad 39A: Shuttle launch ejects Apollo-era debris
• link Launch Photography, STS-124 Discovery launches Kibo module to ISS, by Ben Cooper
• link NBC News, NASA to fix damaged launch pad, by Jeremy Hsu
• link NASA Space Flight, Investigation confirms vertical debris events during STS-124 launch, by Chris Bergen
• history_edu Adhesion Testing of Firebricks from Launch Pad 39A Flame Trench after STS-124, P. E. Hintze, J. P. Curran, Kennedy Space Center, Florida, no. NASA/TM-2009-214759, 2009
• history_edu Vibro-Acoustic Analysis of NASA's Space Shuttle Launch Pad 39A Flame Trench Wall, R. N. Margasahayam, International Congress on Sound and Vibration (ICSVI6), Krakow, Poland, no. KSC-2008-293, July 5-9, 2009
• history_edu Development and Implementation of Nationally Recognized Laboratory for Material Characterization in the Microwave and Millimeter Wave Bands, F. L. Hepburn, S. S. Russell, January, 2010
• history_edu Computation of Unsteady Flow in Flame Trench For Prediction of Ignition Overpressure Waves, D. Kwak, C. Kris, Seoul National University and Hanyang University, Seoul, Korea, NASA Ames Research Center, no. ARC-E-DAA-TN2199, October 25, 2010
• history_edu KSC Launch Pad Flame Trench Environment Assessment, L. M. Calle, P. E. Hintze, C. R. Parlier, J. P. Curran, M. R. Kolody, J. W. Sampson, Kennedy Space Center, Florida, no. NASA/TM-2010-216294, December, 2010
• history_edu The Role of CFD Simulation in Rocket Propulsion Support Activities, J. West, 3rd Annual SimBRS Conference, Starkville, MS, no. M11-0827, July 26th, 2011.
• history_edu Coherent Flow Structures in the Flame Trench Pressure Environment, C. Brehm, J.A. Housman, M. Barad, E. Sozer, S. Moini-Yekta, C. Kiris, B. Vu, and C. R. Parlier, 21st Thermal & Fluids Analysis Workshop (TFAWS), Kennedy Space Center, Florida, no. ARC-E-DAA-TN10931, July, 2013

Project Hope - Palestine

• Volunteer work teaching six classes in Palestine to age ranges from elementary school through college.
• Subjects included, drawing, photography, computer software, engineering, economics, and business.