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19951
|
Untitled project by @Wallenti | Stardance
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Wallenti
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0
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0.0
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0
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[]
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[]
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Title: Untitled project by @Wallenti | Stardance
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1794077322.5819938
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1794682122.5819938
|
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19952
|
My awesome macropad! by @parthk | Stardance
|
parthk
|
0
|
0.0
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0
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[]
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[]
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Title: My awesome macropad! by @parthk | Stardance
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1793901044.4582675
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1794505844.4582675
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19953
|
LinAlg Visualizer by @caasion | Stardance
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caasion
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1
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1.0
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0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-06-16T14:24:12Z", "hours": 1.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "I made a visualizer to see linear algebra concepts in action. I’ve been itching to build something, but I also had to study for my test, so I decided to build something to help studying. It was really fun applying class concepts to build this project", "repo": "https://github.com/caasion/linear-algebra-visualizer", "demo": "https://linear-algebra-visualizer-blue.vercel.app/"}]...
|
[{"post_id": 9942, "ts": "2026 [{"post_id": 9942, "ts": "2026-06-16T13:54:38Z", "hours": 1.1806, "text": "My linear algebra test is coming up soon, and I need to study for it, but I also really wanted to build something, so I built a tool to help my peers and I study lin alg. The visualizer helps you see what it means for a matrix to be a linear transformation and also shows you concepts like eigenvectors and eigenvalues."}]...
|
Title: LinAlg Visualizer by @caasion | Stardance
Title: LinAlg Visualizer by @caasion | Stardance
Devlogs:
My linear algebra test is coming up soon, and I need to study for it, but I also really wanted to build something, so I built a tool to help my peers and I study lin alg. The visualizer helps you see what it means for a matrix to be a linear transformation and also shows you concepts like eigenvectors and eigenvalues.
Ships:
I made a visualizer to see linear algebra concepts in action. I’ve been itching to build something, but I also had to study for my test, so I decided to build something to help studying. It was really fun applying class concepts to build this project...
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1794041594.0908487
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1794127994.0908487
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19954
|
Frictionless by @hasinireddy | Stardance
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hasinireddy
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0
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0.0
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0
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[]
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[]
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Title: Frictionless by @hasinireddy | Stardance
|
1793461882.800497
|
1794066682.800497
|
|
19955
|
Frictionless by @Nishant_Honnavar | Stardance
|
Nishant_Honnavar
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0
|
0.0
|
0
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[]
|
[]
|
Title: Frictionless by @Nishant_Honnavar | Stardan Title: Frictionless by @Nishant_Honnavar | Stardance...
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1793436807.327418
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1794041607.327418
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19956
|
My first slack bot! by @offcial_pratyay | Stardanc My first slack bot! by @offcial_pratyay | Stardance...
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offcial_pratyay
|
0
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0.0
|
0
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[]
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[]
|
Title: My first slack bot! by @offcial_pratyay | S Title: My first slack bot! by @offcial_pratyay | Stardance...
|
1793552094.2184916
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1794156894.2184916
|
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19957
|
My awesome macropad! by @Y-man | Stardance
|
Y-man
|
0
|
0.0
|
0
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[]
|
[]
|
Title: My awesome macropad! by @Y-man | Stardance
|
1793991162.4870532
|
1794595962.4870532
|
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19958
|
Frictionless by @akulaaarav | Stardance
|
akulaaarav
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0
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0.0
|
0
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[]
|
[]
|
Title: Frictionless by @akulaaarav | Stardance
|
1793774942.3622599
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1794379742.3622599
|
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19959
|
Frictionless by @jshakerspeare | Stardance
|
jshakerspeare
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0
|
0.0
|
0
|
[]
|
[]
|
Title: Frictionless by @jshakerspeare | Stardance
|
1793782290.8363945
|
1794387090.8363945
|
|
19960
|
My awesome macropad! by @hasinireddy | Stardance
|
hasinireddy
|
0
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0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @hasinireddy | Star Title: My awesome macropad! by @hasinireddy | Stardance...
|
1794019945.0412557
|
1794624745.0412557
|
|
19961
|
AI stuff by @tigerlion0502 | Stardance
|
tigerlion0502
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: AI stuff by @tigerlion0502 | Stardance
|
1793537760.2940285
|
1794142560.2940285
|
|
19962
|
My awesome macropad! by @golden_e1ka | Stardance
|
golden_e1ka
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @golden_e1ka | Star Title: My awesome macropad! by @golden_e1ka | Stardance...
|
1793411626.8579168
|
1794016426.8579168
|
|
19963
|
Jarvis by @Churu | Stardance
|
Churu
|
1
|
0.0
|
0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-06-16T15:26:44Z", "hours": 0.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "I built a Python voice assistant called Jarvis. It listens for a wake word (“Jarvis”), processes spoken input, and then responds using text-to-speech or executes basic system actions like opening apps, running commands, or answering queries through an AI/API layer. How it works (in simple terms) The flow is basically: Microphone input The program constantly listens through the mic until it detects the wake word. Wake word detection Once “Jarvis” is detected, it switches into active listening mode. Speech-to-text Your speech is converted into text using a speech recognition engine. Processing layer The text is either: matched to predefined commands (like opening apps, searching, etc.), or sent to an AI model/API for a response Response output The response is converted back to speech and played through speakers. State control It manages states like “listening”, “thinking”, and “speaking” so it doesn’t overlap audio input and output. devlog / what actually went wrong At the start it looked simple, but most of the time was spent fixing edge cases and weird failures. Mic input was the first issue. It either didn’t pick up sound or used the wrong device entirely. On my system it worked, but on another setup it silently failed because the default audio index was different. I had to explicitly handle device selection instead of relying on defaults. Speech recognition was inconsistent too. It would misinterpret short commands or fail when there was background noise. I had to tweak sensitivity and improve how it handled pauses in speech so it wouldn’t cut off early. One major mistake was not separating speaking and listening states. The assistant would sometimes hear its own response and trigger itself again, creating loops. I fixed this by adding a simple lock so it cannot listen while speaking. The biggest structural issue came later with packaging. It worked perfectly when running python main.py, but broke when converted into an executable. The dist version failed due to missing modules, broken file paths, and hardcoded system-specific directories. I initially assumed the environment would behave the same after packaging, but PyInstaller changed everything. I had to fix relative paths, remove hardcoded references to my machine, and manually ensure hidden dependencies were included. API and environment variables also caused issues. The program would run fine in terminal but fail in packaged form because the .env file or API key wasn’t being loaded correctly in the new runtime context. what I learned from it Most of the problems were not in “AI logic” but in system-level behavior: audio devices, file paths, packaging, and runtime differences. The main takeaways were: voice input systems are fragile and device-dependent Python packaging is not equivalent to running a script state management matters more than expected in real-time systems debugging usually comes from environment mismatch, not code logic itself", "repo": "https://github.com/jasersans1-create/Jarvis", "demo": "https://github.com/jasersans1-create/Jarvis/releases/tag/v1.0.0"}]...
|
[{"post_id": 9982, "ts": "2026 [{"post_id": 9982, "ts": "2026-06-16T14:53:45Z", "hours": 0.0, "text": "so i made this voice assistant “jarvis” in python basically it listens for a wake word, then you talk to it, and it replies or runs stuff like opening apps / answering questions / whatever i wired into it I built a Python voice assistant called Jarvis. It listens for a wake word “Jarvis”, processes spoken input, and then responds using tts or executes basic system actions like opening apps, running commands, or answering queries through an AI/API layer. How it works (in simple terms) The flow is basically: Microphone input The program constantly listens through the mic until it detects the wake word. Wake word detection Once “Jarvis” is detected, it switches into active listening mode. Speech-to-text Your speech is converted into text using a speech recognition engine. Processing layer The text is either: matched to predefined commands (like opening apps, searching, etc.), or sent to an AI model/API for a response Response output The response is converted back to speech and played through speakers. State control It manages states like “listening”, “thinking”, and “speaking” so it doesn’t overlap audio input and output. at first it was kinda simple but then everything started breaking mic input was the first pain it either didn’t hear me or picked up the wrong device spent way too long just figuring out why it was “silent” but actually listening to the wrong mic then speech recognition started being annoying like it would randomly misunderstand words or just freeze if i spoke too fast also made the classic mistake of letting it listen while it was speaking so it would hear its own voice and start looping responses , so i had to add a lock so it doesnt talk while talking biggest headache was the API / env stuff worked fine when i ran python main.py then i packaged it and suddenly everything was “missing key / file not found / module not found” turned out i had hardcoded paths and assumed my machine layout is universal fixed that by making paths dynamic + cleaning up env loading also packaging with pyinstaller was pain some imports just randomly didn’t show up in dist build and i had to manually force include them now it mostly works but i still feel like it’s fragile, one change and it might break again. but yeah overall it taught me: audio stuff is way harder than it looks packaging python apps is cursed and debugging voice stuff is basically just “try everything until it works”"}]...
|
Title: Jarvis by @Churu | Stardance
Devlogs:
so i Title: Jarvis by @Churu | Stardance
Devlogs:
so i made this voice assistant “jarvis” in python basically it listens for a wake word, then you talk to it, and it replies or runs stuff like opening apps / answering questions / whatever i wired into it I built a Python voice assistant called Jarvis. It listens for a wake word “Jarvis”, processes spoken input, and then responds using tts or executes basic system actions like opening apps, running commands, or answering queries through an AI/API layer. How it works (in simple terms) The flow is basically: Microphone input The program constantly listens through the mic until it detects the wake word. Wake word detection Once “Jarvis” is detected, it switches into active listening mode. Speech-to-text Your speech is converted into text using a speech recognition engine. Processing layer The text is either: matched to predefined commands (like opening apps, searching, etc.), or sent to an AI model/API for a response Response output The response is converted back to speech and played through speakers. State control It manages states like “listening”, “thinking”, and “speaking” so it doesn’t overlap audio input and output. at first it was kinda simple but then everything started breaking mic input was the first pain it either didn’t hear me or picked up the wrong device spent way too long just figuring out why it was “silent” but actually listening to the wrong mic then speech recognition started being annoying like it would randomly misunderstand words or just freeze if i spoke too fast also made the classic mistake of letting it listen while it was speaking so it would hear its own voice and start looping responses , so i had to add a lock so it doesnt talk while talking biggest headache was the API / env stuff worked fine when i ran python main.py then i packaged it and suddenly everything was “missing key / file not found / module not found” turned out i had hardcoded paths and assumed my machine layout is universal fixed that by making paths dynamic + cleaning up env loading also packaging with pyinstaller was pain some imports just randomly didn’t show up in dist build and i had to manually force include them now it mostly works but i still feel like it’s fragile, one change and it might break again. but yeah overall it taught me: audio stuff is way harder than it looks packaging python apps is cursed and debugging voice stuff is basically just “try everything until it works”
Ships:
I built a Python voice assistant called Jarvis. It listens for a wake word (“Jarvis”), processes spoken input, and then responds using text-to-speech or executes basic system actions like opening apps, running commands, or answering queries through an AI/API layer. How it works (in simple terms) The flow is basically: Microphone input The program constantly listens through the mic until it detects the wake word. Wake word detection Once “Jarvis” is detected, it switches into active listening mode. Speech-to-text Your speech is converted into text using a speech recognition engine. Processing layer The text is either: matched to predefined commands (like opening apps, searching, etc.), or sent to an AI model/API for a response Response output The response is converted back to speech and played through speakers. State control It manages states like “listening”, “thinking”, and “speaking” so it doesn’t overlap audio input and output. devlog / what actually went wrong At the start it looked simple, but most of the time was spent fixing edge cases and weird failures. Mic input was the first issue. It either didn’t pick up sound or used the wrong device entirely. On my system it worked, but on another setup it silently failed because the default audio index was different. I had to explicitly handle device selection instead of relying on defaults. Speech recognition was inconsistent too. It would misinterpret short commands or fail when there was background noise. I had to tweak sensitivity and improve how it handled pauses in speech so it wouldn’t cut off early. One major mistake was not separating speaking and listening states. The assistant would sometimes hear its own response and trigger itself again, creating loops. I fixed this by adding a simple lock so it cannot listen while speaking. The biggest structural issue came later with packaging. It worked perfectly when running python main.py, but broke when converted into an executable. The dist version failed due to missing modules, broken file paths, and hardcoded system-specific directories. I initially assumed the environment would behave the same after packaging, but PyInstaller changed everything. I had to fix relative paths, remove hardcoded references to my machine, and manually ensure hidden dependencies were included. API and environment variables also caused issues. The program would run fine in terminal but fail in packaged form because the .env file or API key wasn’t being loaded correctly in the new runtime context. what I learned from it Most of the problems were not in “AI logic” but in system-level behavior: audio devices, file paths, packaging, and runtime differences. The main takeaways were: voice input systems are fragile and device-dependent Python packaging is not equivalent to running a script state management matters more than expected in real-time systems debugging usually comes from environment mismatch, not code logic itself...
|
1793771480.1032784
|
1794635480.1032784
|
|
19964
|
My first slack bot! by @soniya | Stardance
|
soniya
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My first slack bot! by @soniya | Stardance
|
1793955064.210413
|
1794559864.210413
|
|
19965
|
Frictionless by @Vijaya_Sairam | Stardance
|
Vijaya_Sairam
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Frictionless by @Vijaya_Sairam | Stardance
|
1793393706.5248995
|
1793998506.5248995
|
|
19966
|
Frictionless by @ahuan20100 | Stardance
|
ahuan20100
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Frictionless by @ahuan20100 | Stardance
|
1793562927.996948
|
1794167727.996948
|
|
19967
|
My awesome macropad! by @ego | Stardance
|
ego
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @ego | Stardance
|
1793400994.5319438
|
1794005794.5319438
|
|
19968
|
Cignal by @adityaverma19200 | Stardance
|
adityaverma19200
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Cignal by @adityaverma19200 | Stardance
|
1793836251.9147987
|
1794441051.9147987
|
|
19969
|
Frictionless by @aklima | Stardance
|
aklima
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Frictionless by @aklima | Stardance
|
1793371674.45776
|
1793976474.45776
|
|
19970
|
Untitled by @ego | Stardance
|
ego
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Untitled by @ego | Stardance
|
1793861399.0144315
|
1794725399.0144315
|
|
19971
|
Frictionless by @Ujjwaldaksh1 | Stardance
|
Ujjwaldaksh1
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Frictionless by @Ujjwaldaksh1 | Stardance
|
1793436919.4863877
|
1794041719.4863877
|
|
19972
|
Cosmopolitan by @iowanpalmcodes | Stardance
|
iowanpalmcodes
|
1
|
2.0
|
0
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-06-18T22:54:28Z", "hours": 2.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "Cosmopolitan is a small, streamlit-based cooking game that has you traverse multiple planets for rarer and rarer ingredients to ultimately cook.. well.. that’s for you to find out. I’m not too used to UIs and JSON/Data Management in General… the filters were pretty easy to make, though. Tips and Tricks: If you’re stuck on how to cook something, look at the recipe book. The items the special events give out currently have nothing to cook them with, but that’s sure to change SOON! (er or later)", "repo": "https://github.com/iowanpalmcode/sol", "demo": "https://cosmopolitan.streamlit.app/"}]...
|
[{"post_id": 11104, "ts": "202 [{"post_id": 11104, "ts": "2026-06-18T05:01:01Z", "hours": 0.2836, "text": "Dev log 4. Ok, sorry I lied. Had Ollama make me a log-in page that routes based on if it’s an account or not yet. This is it. this is the FINAL update. It’s really fun. Play it. Oh yeah I also added rebirths lol"}, {"post_id": 10962, "ts": "2026-06-17T23:40:40Z", "hours": 1.0761, "text": "Cosmopolitan Dev Log 3 (The final one) All good series end in a trilogy, obviously. Not much else added, minus a new restaurant tab and a save/load system (granted, I had Ollama do that for me). I’d say this game is pretty fun."}, {"post_id": 10935, "ts": "2026-06-17T22:28:36Z", "hours": 0.7064, "text": "Cosmopolitan Dev Log #2. I added 15+ new planets and a lot of new recipes/ingredients in the process (granted, they’re fairly repetitive). I implemented filters to make looking through ingredients/recipes a little bit easier. I think my next course of action is to actually make this into a cooking game-ish where you actually have to manage people in real time."}, {"post_id": 10341, "ts": "2026-06-17T00:46:52Z", "hours": 0.3667, "text": "Cosmopolitan Dev Log 1😀 The idea is pretty simple; what if you could cook.. in space? I’ve set up the basic framework, and I think I’ll work on adding real time events next. maybe."}]...
|
Title: Cosmopolitan by @iowanpalmcodes | Stardance Title: Cosmopolitan by @iowanpalmcodes | Stardance
Devlogs:
Cosmopolitan Dev Log 1😀 The idea is pretty simple; what if you could cook.. in space? I’ve set up the basic framework, and I think I’ll work on adding real time events next. maybe.
Cosmopolitan Dev Log #2. I added 15+ new planets and a lot of new recipes/ingredients in the process (granted, they’re fairly repetitive). I implemented filters to make looking through ingredients/recipes a little bit easier. I think my next course of action is to actually make this into a cooking game-ish where you actually have to manage people in real time.
Cosmopolitan Dev Log 3 (The final one) All good series end in a trilogy, obviously. Not much else added, minus a new restaurant tab and a save/load system (granted, I had Ollama do that for me). I’d say this game is pretty fun.
Dev log 4. Ok, sorry I lied. Had Ollama make me a log-in page that routes based on if it’s an account or not yet. This is it. this is the FINAL update. It’s really fun. Play it. Oh yeah I also added rebirths lol
Ships:
Cosmopolitan is a small, streamlit-based cooking game that has you traverse multiple planets for rarer and rarer ingredients to ultimately cook.. well.. that’s for you to find out. I’m not too used to UIs and JSON/Data Management in General… the filters were pretty easy to make, though. Tips and Tricks: If you’re stuck on how to cook something, look at the recipe book. The items the special events give out currently have nothing to cook them with, but that’s sure to change SOON! (er or later)...
|
1793872381.6476316
|
1793958781.6476316
|
|
19973
|
My first slack bot! by @longfei | Stardance
|
longfei
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My first slack bot! by @longfei | Stardance
|
1793447576.0458505
|
1794052376.0458505
|
|
19974
|
My first slack bot! by @prathameshpvp | Stardance
|
prathameshpvp
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My first slack bot! by @prathameshpvp | Sta Title: My first slack bot! by @prathameshpvp | Stardance...
|
1793811267.24563
|
1794675267.24563
|
|
19975
|
PadelYa by @mateopirela | Stardance
|
mateopirela
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: PadelYa by @mateopirela | Stardance
|
1793937175.322456
|
1794541975.322456
|
|
19976
|
My awesome macropad! by @itsnourawithau | Stardanc My awesome macropad! by @itsnourawithau | Stardance...
|
itsnourawithau
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @itsnourawithau | S Title: My awesome macropad! by @itsnourawithau | Stardance...
|
1793901126.3524525
|
1794505926.3524525
|
|
19977
|
Cosmic-Birthday-Scanner by @spec98 | Stardance
|
spec98
|
1
|
2.18
|
1
|
[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-07-04T09:05:40Z", "hours": 1.0, "multiplier": 1.58, "payout": 1, "blessing": "neutral", "text": "so this was the first project i did in hackclub,it is not perfect but with it i learned the basics.so you write your birth date and it gives you the exact pic that nasa took that day", "repo": "https://github.com/spec905/NASA-Project", "demo": "https://spec905.github.io/NASA-Project/gy.html"}]...
|
[{"post_id": 31357, "ts": "202 [{"post_id": 31357, "ts": "2026-07-19T18:00:05Z", "hours": 1.0056, "text": "i just fixed some style editing"}, {"post_id": 28169, "ts": "2026-07-14T09:22:59Z", "hours": 0.1697, "text": "i added a download button, NASA’s explanation text for each photo and the photographer credit"}, {"post_id": 22018, "ts": "2026-07-04T08:05:36Z", "hours": 0.5344, "text": "a website that lets users enter their birthday to see the official NASA Astronomy Picture of the Day from that exact date"}]...
|
Title: Cosmic-Birthday-Scanner by @spec98 | Starda Title: Cosmic-Birthday-Scanner by @spec98 | Stardance
Devlogs:
a website that lets users enter their birthday to see the official NASA Astronomy Picture of the Day from that exact date
i added a download button, NASA’s explanation text for each photo and the photographer credit
i just fixed some style editing
Ships:
so this was the first project i did in hackclub,it is not perfect but with it i learned the basics.so you write your birth date and it gives you the exact pic that nasa took that day...
|
1793879443.890824
|
1793965843.890824
|
|
19978
|
My first slack bot! by @Littletrooper68 | Stardanc My first slack bot! by @Littletrooper68 | Stardance...
|
Littletrooper68
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My first slack bot! by @Littletrooper68 | S Title: My first slack bot! by @Littletrooper68 | Stardance...
|
1793386175.0058815
|
1793990975.0058815
|
|
19979
|
MMOP by @cronozx | Stardance
|
cronozx
|
0
|
7.39
|
0
|
[]
|
[{"post_id": 10407, "ts": "202 [{"post_id": 10407, "ts": "2026-06-17T03:08:11Z", "hours": 7.3881, "text": "Hello Everyone, I have been working on a program called MMOP (Mod Management Operations) for quite some time now. It is a mod manager that allows you to work on modpacks with your friends instead of everyone yelling at that one friend trying to make it. Similar to how GitHub works with commits the owner of the modpack accepts or deny’s changes shown in a contribution log. The mod manager currently has a windows version only that has Minecraft, Stardew Valley, Lethal Company, and REPO. I would like to get a Mac version published, but the license is pretty expensive lol. I would love if you check it out and tell me what you think or submit a support request for games to be added. Thank you for your time, cronozx <3"}]...
|
Title: MMOP by @cronozx | Stardance
Devlogs:
Hell Title: MMOP by @cronozx | Stardance
Devlogs:
Hello Everyone, I have been working on a program called MMOP (Mod Management Operations) for quite some time now. It is a mod manager that allows you to work on modpacks with your friends instead of everyone yelling at that one friend trying to make it. Similar to how GitHub works with commits the owner of the modpack accepts or deny’s changes shown in a contribution log. The mod manager currently has a windows version only that has Minecraft, Stardew Valley, Lethal Company, and REPO. I would like to get a Mac version published, but the license is pretty expensive lol. I would love if you check it out and tell me what you think or submit a support request for games to be added. Thank you for your time, cronozx <3...
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1793415003.2241175
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1794019803.2241175
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19980
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Test by @Pannawit | Stardance
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Pannawit
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0
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0.0
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0
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[]
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[]
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Title: Test by @Pannawit | Stardance
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1794077566.3551264
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1794682366.3551264
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19981
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Space News by @Jaron | Stardance
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Jaron
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0
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0.0
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0
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[]
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[]
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Title: Space News by @Jaron | Stardance
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1793440601.1903727
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1794045401.1903727
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19982
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My very own WebOS by @ayaansid27 | Stardance
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ayaansid27
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0
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0.0
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0
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[]
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Title: My very own WebOS by @ayaansid27 | Stardanc Title: My very own WebOS by @ayaansid27 | Stardance...
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1793375383.9720592
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1793980183.9720592
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19983
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My very own WebOS by @syed_ahmed | Stardance
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syed_ahmed
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0
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0.0
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[]
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[]
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Title: My very own WebOS by @syed_ahmed | Stardanc Title: My very own WebOS by @syed_ahmed | Stardance...
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1793868958.6336894
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1794473758.6336894
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19984
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FRC Rebuilt inspired robot by @Carson | Stardance
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Carson
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1
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73.0
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0
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-09-22T00:36:13Z", "hours": 73.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "This is the cad for an FRC bot I designed for this years game Rebuilt one in which you shoot as many balls as you can into a big basket. I’m really proud of the whole thing honestly, its the first large and cohesive thing I’ve ever designed and I think it turned out pretty well. I’m especially proud of the shooter, scoring manipulators are always fun to make! I will say the process did not go without its hiccups, to be honest I only discovered the derrived tool like halfway through, that was rough but I finished it none the less and if you want to try it out just click the button below.", "repo": "https://github.com/CKFlare/FRC-Rebuilt-robot-CAD", "demo": "https://cad.onshape.com/documents/ef90526955e2c1079c0c9faf/w/03993b2fa40710a1deb74a90/e/58e238fa26bdce46de7e348d?renderMode=0&uiState=6aa8a33892df8e4b39a6d890"}]...
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[{"post_id": 72006, "ts": "202 [{"post_id": 72006, "ts": "2026-09-22T00:09:47Z", "hours": 5.7989, "text": "Devlog 10 I have done a lot since the last devlog and this is my final log before shipping, I’m very exited. completed pocketed everything assigned materials to a few things I missed finished organizing every part studio used in the final assembly prepared my repository and wrote a readme a bunch of other random stuff created an assembly to display balls in the path they would take from the intake to the shooter Sadly the robot is still way overweight, its like 200 pounds but I’m just going to leave it for now. its just a pet project. Stardance has been AWESOME and I’m really glad I was able to participate, thank you everyone!! Until next time Hack Clubbers!"}, {"post_id": 66957, "ts": "2026-09-12T22:59:45Z", "hours": 8.2739, "text": "Devlog 9 Completed re-added power chain to design added hopper element to cover power chain added camera mounts that work on the robot added belt between feeding path and conveyor belt because apparently it previousley had no way to spin went through half of the part studios and asemblys to organize them them added material and appearence to all parts without them. added radio and RSL (robot safety light) issues its very boring sifting through everything you’ve done, naming and grouping it all the cover for the power chain clips through the power chain’s pulley I’ve worked on it most of today and honestly Its come very far, I think I’m finally almost done."}, {"post_id": 63954, "ts": "2026-09-08T01:29:06Z", "hours": 7.5053, "text": "Devlog 8 completed I added mounts for all floating parts added a wall to funnel balls into the main feeding path added all timing belts to roller floor created baseplate and added main electronics added fasteners fixed miscelaneous issues issues my load times are taking longer and longer honestly the sticky streak has really motivated me, for the past 8 days i’ve managed to squeeze in at least 15 minutes each night."}, {"post_id": 46915, "ts": "2026-08-14T13:37:44Z", "hours": 6.6797, "text": "Devlog 7 completed made a cover for the PIcam I would use for PhotonVision, changed a few things on shooter to reduce height many odd jobs that I honestly cant remember Issues I keep getting this “Operation failed because it would create cyclical references : Part Studio 2 Copy 1 <- Part Studio 1.” error while trying to derive my reference sketch from another document and I honestly don’t know how to fix it I’ve had to go for multiple weeks without working on this project because I didn’t have access to a computer and now I’m struggling to get any real progress done, I’m almost done though I mainly just have to do a bunch more annoying jobs like pocketing all of the sheets, adding the electronics and designing a hopper, which shouldn’t be too bad, its just a few sheets of polycarbonate"}, {"post_id": 30307, "ts": "2026-07-17T19:19:03Z", "hours": 12.6442, "text": "devlog 6 completed redid turret mounting plate reworked feeding path make base of roller floor indexer miscelaneous changes It really doesn’t look like much but, I’ve done a lot, I’ve been focusing on making something very simple that would work, I’m creating most of the parts that will be used and just not pocketing them or fully doing the assemblies or even adding mounting holes tbh, but I am making sure nothing clips and that all of the subsystems fit together and work in tandem."}, {"post_id": 26152, "ts": "2026-07-10T19:36:49Z", "hours": 9.0636, "text": "Devlog 5 completed added energy chain for turret created basic intake started mount for intake Issues I’m kind of scatter brained and did not complete last logs to due list before starting the intake I’m extending about .05 further from my robot perimeter than is allowed, its finneeeee I think the intake wont actually be able to come back into the robot because the kicker bar descends too low while being stowed it weighs WAY too much the intake is very simple a rack and pinion sends it out then the kicker bars drop down because there will be a piece of surgical tubing tensioning them, pulling it down. then whenever the driver presses the assigned button two neo vortex’s will spin a set of rollers that will grab the balls press them against the kicker bars and shoot them into the hopper. it is just shy of a 5 ball wide intake which should allow for pretty high throughput. the energy chain assembly for the turret is also very simple. there is a freely spinning constant force spring attached to a bracket which pulls the bracket away from the shooter, the energy chain just loops through the bracket. total current weight with bumpers: 129 lbs"}, {"post_id": 24938, "ts": "2026-07-08T20:24:44Z", "hours": 4.61, "text": "Devlog 4 completed added structural support removed problem of turret scraping feeding path plates added indexing roller to top of belt sandwich entrance, will connect via belt to main indexing system added all fasteners to the superstructure, bolts, nuts, rivets etc fixed random errors changed which side the belts are located on the feeding path to allow for better packaging assigned materials and appearances to parts organized and named features in assemblies and part studios issues my pocketing feature script is tweaking out, I still heven’t a clue what the problem is clipping, per usual I didnt account for the size of another part and they ended up occupying the same space, to be honest I just chamfered the edge of a plate to remove one of these issues. but hey it worked. I have no time :( its been ages since I’ve been able to seroiusley spend time on this project, my summer has been really busy, there was one week where I cadded not even for 1 minute D: today was honestly really boring I was mostly just polishing up previous work, I’m almost done with the superstructure. the only things left to do is to implement a system to keep my power chain out of the way from tangling, that will be very simple, I also would like to add a set of compliant wheels to that vertical shaft on the right to funnel the balls from that side into the turret, then I think I just need to tighten it up before I will move onto either the intake or main indexer. until next time!"}, {"post_id": 14055, "ts": "2026-06-23T01:10:26Z", "hours": 8.9728, "text": "Devlog 3 -changed the backplate on shooter - fixed clipping - created a very rudimentary feeding path, needs a LOT more work i wasted a lot of time on the feeding path, changing belt positions ironing out belt lengths and pitch, I originally was using 5 mm but I couldn’t get the right lengths so I switched to 3mm. I also didn’t now how I was going to mount it so I spent a while figuring that out. I’m using a belt on the top and bottom of the balls to funnel them into an array of compliant wheels that sends it up into the shooter"}, {"post_id": 11503, "ts": "2026-06-18T19:59:30Z", "hours": 4.0336, "text": "Yesterday I quickly knocked out the chassis and timelapsed me planning out the superstructure on paper. Today I designed the turret and I modified the shooter such that it can be mounted to the turret, this took longer than anticipated but oh well. my Laptop is so slow that Onshape crashed the whole computer like 3 times while making the turret, I suppose I have to keep my documents small. I’ve decided on a 30’’ by 25” chassis for this robot. This is to allow an intake about as wide as 5 balls, as well I did a rough estimate of my ball capacity based on rough numbers and it should be able to hold a maximum of about 80 balls. The drivetrain consists of SDS MK5Is powered by 8 Neo Vortexes."}, {"post_id": 10224, "ts": "2026-06-16T21:04:49Z", "hours": 5.6606, "text": "over the past few days I worked on my launcher for this years game piece, fuel (little yellow balls). I spent about an hour designing a carriage style hood so “it would be packaged better” but then realized it would add about 2 inches to the back and be heavier, so I reworked how the hood moves up and down by moving the rack onto the dynamic portion and the pinion onto the static part. the hood has an adjustable angle of about 25 degrees up to 60 degrees so weather we’re passing from the other alliance zone or butted against the hub we should be able to shoot. combined the 2 neo vortexes powering the flywheel achieve about 13,000 RPM so it can really lob balls."}]...
|
Title: FRC Rebuilt inspired robot by @Carson | Sta Title: FRC Rebuilt inspired robot by @Carson | Stardance
Devlogs:
over the past few days I worked on my launcher for this years game piece, fuel (little yellow balls). I spent about an hour designing a carriage style hood so “it would be packaged better” but then realized it would add about 2 inches to the back and be heavier, so I reworked how the hood moves up and down by moving the rack onto the dynamic portion and the pinion onto the static part. the hood has an adjustable angle of about 25 degrees up to 60 degrees so weather we’re passing from the other alliance zone or butted against the hub we should be able to shoot. combined the 2 neo vortexes powering the flywheel achieve about 13,000 RPM so it can really lob balls.
Yesterday I quickly knocked out the chassis and timelapsed me planning out the superstructure on paper. Today I designed the turret and I modified the shooter such that it can be mounted to the turret, this took longer than anticipated but oh well. my Laptop is so slow that Onshape crashed the whole computer like 3 times while making the turret, I suppose I have to keep my documents small. I’ve decided on a 30’’ by 25” chassis for this robot. This is to allow an intake about as wide as 5 balls, as well I did a rough estimate of my ball capacity based on rough numbers and it should be able to hold a maximum of about 80 balls. The drivetrain consists of SDS MK5Is powered by 8 Neo Vortexes.
Devlog 3 -changed the backplate on shooter - fixed clipping - created a very rudimentary feeding path, needs a LOT more work i wasted a lot of time on the feeding path, changing belt positions ironing out belt lengths and pitch, I originally was using 5 mm but I couldn’t get the right lengths so I switched to 3mm. I also didn’t now how I was going to mount it so I spent a while figuring that out. I’m using a belt on the top and bottom of the balls to funnel them into an array of compliant wheels that sends it up into the shooter
Devlog 4 completed added structural support removed problem of turret scraping feeding path plates added indexing roller to top of belt sandwich entrance, will connect via belt to main indexing system added all fasteners to the superstructure, bolts, nuts, rivets etc fixed random errors changed which side the belts are located on the feeding path to allow for better packaging assigned materials and appearances to parts organized and named features in assemblies and part studios issues my pocketing feature script is tweaking out, I still heven’t a clue what the problem is clipping, per usual I didnt account for the size of another part and they ended up occupying the same space, to be honest I just chamfered the edge of a plate to remove one of these issues. but hey it worked. I have no time :( its been ages since I’ve been able to seroiusley spend time on this project, my summer has been really busy, there was one week where I cadded not even for 1 minute D: today was honestly really boring I was mostly just polishing up previous work, I’m almost done with the superstructure. the only things left to do is to implement a system to keep my power chain out of the way from tangling, that will be very simple, I also would like to add a set of compliant wheels to that vertical shaft on the right to funnel the balls from that side into the turret, then I think I just need to tighten it up before I will move onto either the intake or main indexer. until next time!
Devlog 5 completed added energy chain for turret created basic intake started mount for intake Issues I’m kind of scatter brained and did not complete last logs to due list before starting the intake I’m extending about .05 further from my robot perimeter than is allowed, its finneeeee I think the intake wont actually be able to come back into the robot because the kicker bar descends too low while being stowed it weighs WAY too much the intake is very simple a rack and pinion sends it out then the kicker bars drop down because there will be a piece of surgical tubing tensioning them, pulling it down. then whenever the driver presses the assigned button two neo vortex’s will spin a set of rollers that will grab the balls press them against the kicker bars and shoot them into the hopper. it is just shy of a 5 ball wide intake which should allow for pretty high throughput. the energy chain assembly for the turret is also very simple. there is a freely spinning constant force spring attached to a bracket which pulls the bracket away from the shooter, the energy chain just loops through the bracket. total current weight with bumpers: 129 lbs
devlog 6 completed redid turret mounting plate reworked feeding path make base of roller floor indexer miscelaneous changes It really doesn’t look like much but, I’ve done a lot, I’ve been focusing on making something very simple that would work, I’m creating most of the parts that will be used and just not pocketing them or fully doing the assemblies or even adding mounting holes tbh, but I am making sure nothing clips and that all of the subsystems fit together and work in tandem.
Devlog 7 completed made a cover for the PIcam I would use for PhotonVision, changed a few things on shooter to reduce height many odd jobs that I honestly cant remember Issues I keep getting this “Operation failed because it would create cyclical references : Part Studio 2 Copy 1 <- Part Studio 1.” error while trying to derive my reference sketch from another document and I honestly don’t know how to fix it I’ve had to go for multiple weeks without working on this project because I didn’t have access to a computer and now I’m struggling to get any real progress done, I’m almost done though I mainly just have to do a bunch more annoying jobs like pocketing all of the sheets, adding the electronics and designing a hopper, which shouldn’t be too bad, its just a few sheets of polycarbonate
Devlog 8 completed I added mounts for all floating parts added a wall to funnel balls into the main feeding path added all timing belts to roller floor created baseplate and added main electronics added fasteners fixed miscelaneous issues issues my load times are taking longer and longer honestly the sticky streak has really motivated me, for the past 8 days i’ve managed to squeeze in at least 15 minutes each night.
Devlog 9 Completed re-added power chain to design added hopper element to cover power chain added camera mounts that work on the robot added belt between feeding path and conveyor belt because apparently it previousley had no way to spin went through half of the part studios and asemblys to organize them them added material and appearence to all parts without them. added radio and RSL (robot safety light) issues its very boring sifting through everything you’ve done, naming and grouping it all the cover for the power chain clips through the power chain’s pulley I’ve worked on it most of today and honestly Its come very far, I think I’m finally almost done.
Devlog 10 I have done a lot since the last devlog and this is my final log before shipping, I’m very exited. completed pocketed everything assigned materials to a few things I missed finished organizing every part studio used in the final assembly prepared my repository and wrote a readme a bunch of other random stuff created an assembly to display balls in the path they would take from the intake to the shooter Sadly the robot is still way overweight, its like 200 pounds but I’m just going to leave it for now. its just a pet project. Stardance has been AWESOME and I’m really glad I was able to participate, thank you everyone!! Until next time Hack Clubbers!
Ships:
This is the cad for an FRC bot I designed for this years game Rebuilt one in which you shoot as many balls as you can into a big basket. I’m really proud of the whole thing honestly, its the first large and cohesive thing I’ve ever designed and I think it turned out pretty well. I’m especially proud of the shooter, scoring manipulators are always fun to make! I will say the process did not go without its hiccups, to be honest I only discovered the derrived tool like halfway through, that was rough but I finished it none the less and if you want to try it out just click the button below....
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1794026970.0054934
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1794113370.0054934
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19985
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My first slack bot! by @Alok09 | Stardance
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Alok09
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0
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0.0
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[]
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Title: My first slack bot! by @Alok09 | Stardance
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1793785898.1196976
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1794390698.1196976
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19986
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My very own WebOS by @basanth | Stardance
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basanth
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0.0
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[]
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Title: My very own WebOS by @basanth | Stardance
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1793490467.0854003
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1794095267.0854003
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19987
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My very own WebOS by @srinithasmailbox | Stardance
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srinithasmailbox
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0
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0.0
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0
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Title: My very own WebOS by @srinithasmailbox | St Title: My very own WebOS by @srinithasmailbox | Stardance...
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1793501447.7069888
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1794106247.7069888
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19988
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My awesome macropad! by @zhichenlim | Stardance
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zhichenlim
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0
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0.0
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0
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Title: My awesome macropad! by @zhichenlim | Stard Title: My awesome macropad! by @zhichenlim | Stardance...
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1794070248.4629436
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1794675048.4629436
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19989
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My first slack bot! by @Coolguy | Stardance
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Coolguy
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0
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0.0
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0
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[]
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Title: My first slack bot! by @Coolguy | Stardance
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1794012785.8185203
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1794617585.8185203
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19990
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My awesome macropad! by @Yusf | Stardance
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Yusf
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0
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0.0
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0
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[]
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Title: My awesome macropad! by @Yusf | Stardance
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1793404433.9673104
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1794009233.9673104
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19991
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Aeris Helmet by @trainerneel | Stardance
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trainerneel
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0.0
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Title: Aeris Helmet by @trainerneel | Stardance
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1794034269.435807
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1794639069.435807
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19992
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My very own WebOS by @Maximilian | Stardance
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Maximilian
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0
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0.0
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0
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Title: My very own WebOS by @Maximilian | Stardanc Title: My very own WebOS by @Maximilian | Stardance...
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1793386366.5024107
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1793991166.5024107
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19993
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DOSEFIELD by @Zhanik | Stardance
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Zhanik
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1
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18.36
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0
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-07-20T06:48:20Z", "hours": 12.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "Today was all about making the site tell the truth about itself instead of just describing itself. I added a Methods and Limitations page that pulls directly from METHODS.md and the README instead of being rewritten into friendly marketing copy. If the documentation and the code ever disagree, the documentation loses immediately because they are now the exact same file. Every page also got an automated footer showing the commit hash, the test count, and the exact verification date. It would have taken five minutes to hardcode a string like “111 tests passing” and move on. Instead, the build script runs the actual test suite first, and if anything fails, the entire build stops cold. This ensures the footer can never claim a passing state that is not true at that exact moment. Wiring a build to gate on its own test results took most of the afternoon because it required thinking through what happens during a failure, not just when everything goes smoothly, but the absolute transparency is worth it. What I like most is that the limitations table on the public site is word-for-word what is in the repository. There is no filtered summary for visitors. The 0.67x gap between my modeled absorbed dose and NASA’s measured RAD numbers reads just as blunt on the public page as it does in the source code. Transparency matters more than hype. Additionally, charts now export at 3200px, and the configuration that produced them gets baked directly into the image itself, meaning a PNG cannot wander off from the settings that generated it. If you want to test it yourself, you can check the live app at DOSEFIELD. Look at the footer for a real commit hash and test count, open the Methods and Limitations page to count the 12 rows in the limitations table, or export a chart to verify the resolution against what is rendered on your screen. The complete source code is also available on GitHub.", "repo": "https://github.com/izbanovj3-prog/DOSEFIELD", "demo": "https://izbanovj3-prog.github.io/DOSEFIELD/"}]...
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[{"post_id": 81574, "ts": "202 [{"post_id": 81574, "ts": "2026-10-21T18:39:31Z", "hours": 6.3597, "text": "Hey Stardance crew! Three months since my last devlog, so grab a snack and let me catch you up. DOSEFIELD estimates how much radiation an astronaut gets behind shielding on a trip to Mars, then checks itself against real data from NASA’s Curiosity cruise (MSL/RAD). The big news: I found a mistake in my own results. In my first public version, the solar modulation value (W = 30) could not be reproduced from the derivation I had written down. So I went back to the Oulu neutron-monitor data, matched the exact time window RAD used, skipped the solar-storm days, and got W = 47.50. The new numbers look worse, and I kept them: absorbed dose: 0.264 vs 0.458 mGy/day measured (0.58x) dose equivalent: 1.318 vs 1.75 mSv/day (0.75x) mean quality factor: 4.995 vs 3.82 (1.31x) My model skips secondary particles and neutrons, so it under-predicts the dose. I report the gap and leave it alone. Also shipped: a check against the full NIST PSTAR table (max deviation 1.55% from 10 to 1000 MeV), 190 passing tests, a code archive on Zenodo (DOI 10.5281/zenodo.23433384), a revised paper on SSRN, and a website that links to all of it."}, {"post_id": 30550, "ts": "2026-07-18T06:51:49Z", "hours": 2.6992, "text": "DEVLOG #6 Hey everyone!This is probably the last devlog for DOSEFIELD, at least for a while. It’s been an incredible journey—from the first rough prototype to something I’m genuinely proud to share. Thank you to everyone who followed along, tested the project, gave feedback, or simply read these updates. It really meant a lot.v2.3 is the “show your work” release. Nothing changed in the physics—and that’s exactly the point.The biggest addition is a new Methods page that renders the repository’s own METHODS.md and limitations table directly. That means anyone reading the website sees the exact same equations, assumptions, and all 12 limitations that exist in the source code. If the website and the repository ever disagree, the repository is the source of truth.Every page now also includes a provenance footer that’s generated automatically during the build. Instead of typing in a version number by hand, the site runs git rev-parse and the full test suite, then stamps something like:commit e22ef18 · 111/111 tests · verified 2026-07-18The build will actually fail if the tests don’t pass, so it’s impossible to accidentally display a “green” verification badge on a broken build.I also improved chart exports. Figures now render at 3200 px, and each exported chart includes its full configuration in the caption. That makes it much easier to trace a plot back to the exact settings that produced it, whether it’s used in a poster, report, or presentation.One thing I want to be completely clear about: this verification is about the software, not the physics. Passing 111 tests means the implementation behaves as expected according to those tests—it doesn’t prove the scientific model is perfect. The current validation remains the same: about 2× agreement with MSL/RAD, and the 0.67× absorbed-dose gap is still there, clearly documented.That’s exactly what this release is about: transparency over hype, reproducibility over screenshots, and being honest about what the model can—and can’t—do.Thanks for following this project. ❤️"}, {"post_id": 24869, "ts": "2026-07-08T18:38:22Z", "hours": 2.4278, "text": "DEVLOG #5 (might be the last devlog) Hey! It’s been 11 days since the last devlog. DOSEFIELD wasn’t abandoned—I was just busy building instead of writing.This update was really about two things: making the code cleaner and making the site feel like it belongs in a space mission.The first issue was hidden in the background. The NASA validation numbers on the website were calculated separately from the ones used in my research. The math was identical, but it existed in multiple places. That meant one future change could easily make the numbers disagree.So I refactored everything to use a single source of truth. Now every result comes from the same function, making the site much easier to maintain and much harder to break.Then I focused on the design. The old version worked, but it didn’t feel like DOSEFIELD. I redesigned the interface with a mission-control style, added a cleaner layout, and simplified the visuals. I also removed a lot of unnecessary effects—less glow, fewer gradients, and a more purposeful look.After all those changes, I reran every test. All 107 tests still pass, and the stopping-power calculations remain within 1.55% of NIST reference data, exactly as before.There’s still one limitation: my model predicts about 67% of the radiation dose measured by NASA during the trip to Mars. That’s because it doesn’t yet simulate secondary particle production inside spacecraft shielding. It’s an important limitation, and it’s clearly explained on the website rather than hidden.The biggest lesson from this update wasn’t about physics—it was about revisiting old work. Good code doesn’t duplicate logic, and good design doesn’t rely on effects to look impressive. Sometimes the best improvement is simply cleaning up what you already built."}, {"post_id": 16881, "ts": "2026-06-27T12:17:57Z", "hours": 1.2136, "text": "Devlog #4 — Heavy Elements Cut, Liquid Hydrogen Locked In Lead and titanium were off by 50%. I didn’t hide it. My model tracks how particles slow down inside matter. For heavy elements like lead and titanium, you need a correction for the atom’s electron shells — skip it, and your numbers drift by half the actual value. I haven’t built that correction yet. Faking the results to look clean would gut the whole point of the model. So heavy elements are out for now. Liquid hydrogen sits at the opposite extreme. One electron, no shell complexity — the model handles it without shortcuts. I checked against NIST’s official proton data: 0.14% deviation across the full energy range. In physics terms, that’s a bullseye. Five Materials, One Hierarchy I ran five materials together — liquid hydrogen, methane, polyethylene, water, and aluminum — and tested them as a chain. Two things had to hold: thicker shielding means lower dose, and going from hydrogen to aluminum, dose has to climb, because light elements stop protons better. Both held, with no exceptions. Polyethylene and water differ by just 3% in electrons per gram — the model caught even that gap correctly. The sharpest result: at 40 g/cm², liquid hydrogen cuts dose by 44% compared to aluminum. That’s why some spacecraft designs wrap the crew compartment in hydrogen tanks — fuel and radiation shield in one. All five materials are now locked into regression tests. Total: 103 green tests in CI. One Function, One Truth The dashboard and the generated reports used to calculate their numbers separately. Two parallel code paths mean two places for drift to appear. Now both pull from a single shared function. The number on screen and the number in the report are physically incapable of disagreeing."}, {"post_id": 14174, "ts": "2026-06-23T05:11:04Z", "hours": 2.5839, "text": "Devlog #3 — DOSEFIELD Is Live 🚀Hi! Long time no see.DOSEFIELD is now live: https://izbanovj3-prog.github.io/DOSEFIELD/ The entire dosimeter now runs directly in your browser — no installation required. That includes the controls, dose-vs-thickness chart, particle fragmentation toggle, and validation panel.Under the hood, the project is built with Vite and automatically deployed to GitHub Pages through a GitHub Actions workflow. Every push to the main branch triggers a fresh build and deployment. The setup is intentionally simple: deployment uses GitHub’s built-in Actions token, with no external services and no additional secrets.The only challenge in this release wasn’t physics — it was infrastructure. The first deployment failed because GitHub Actions cannot automatically enable GitHub Pages for a repository. The workflow reached that permission boundary and stopped. After enabling Pages in the repository settings and rerunning the workflow, everything deployed successfully.Once the site was live, I verified that all critical assets were being served correctly. The page, stylesheets, and, most importantly, the Web Worker bundle all return HTTP 200 responses with the correct content types.That Web Worker is particularly important because it handles the species-by-species dose integration calculations off the main UI thread. In practice, this means the interface remains responsive while the physics calculations run in the background.No physics models changed in this release, and the known limitations remain the same. This phase was focused entirely on one goal: shipping a fully accessible browser version of DOSEFIELD.The live demo link is now featured at the top of the README."}, {"post_id": 11802, "ts": "2026-06-19T06:41:00Z", "hours": 1.3047, "text": "DOSEFIELD DAY #2:Fragmentation is now in the live app. Until today the web dosimeter only ran the primary-only transport — the most interesting result, that breaking up heavy ions is why hydrogen-rich shielding wins, was buried in a console script. Now there’s a “Primaries only ⇄ + Fragmentation” toggle, and flipping it visibly bends the curves: polyethylene pulls away from aluminium and the mean quality factor drops. Concretely, at solar minimum behind 20 g/cm², polyethylene’s edge over aluminium jumps from 12% to 34% the moment fragmentation turns on — the same figure the validation script prints, read from the same function, not hardcoded. Mean ⟨Q⟩ behind 16 g/cm² of aluminium falls 4.47 → 4.14. Nothing was tuned; the toggle just calls the existing Bradt–Peters model. And the honest ceiling stays put: still no secondary neutrons, so the absorbed-dose gap vs the real MSL/RAD measurement (~0.31 vs 0.46 mGy/day) remains — and the UI footnote says so out loud. 76/76 tests green, build clean. Next: surface the NIST + RAD validation inside the app itself."}, {"post_id": 10579, "ts": "2026-06-17T11:53:38Z", "hours": 1.5142, "text": "Day #1: the hard part is in, now I find out if it’s right I’m building DOSEFIELD, a 1D model that estimates how much radiation an astronaut absorbs on a deep-space mission — and how much shielding actually helps. Cosmic rays in, dose-equivalent out. What’s already solid: the stopping-power core matches NIST PSTAR reference data to within 1.6%, and behind 10 g/cm² of aluminium at solar minimum the model gives 1.96 mSv/day — about 0.70 Sv over a 360-day Mars cruise. That’s 17% past NASA’s 600 mSv career limit. A round trip to Mars quietly blows through the radiation an astronaut is allowed for their entire career. That’s the reason this project exists. But the first version only tracked primary particles, and it showed: my aluminium, polyethylene and water curves were sitting almost on top of each other. That’s physically wrong — polyethylene should shield noticeably better, because hydrogen is good at breaking up heavy ions. The missing piece is nuclear fragmentation. So this week I implemented it — real fragmentation cross sections (Bradt–Peters), not a fudge factor tuned to match NASA’s measured value. The material difference has to come out of the physics: hydrogen has the shortest nuclear interaction length per g/cm², so it should win on its own. No parameter is fit to the answer. Now I’m validating it, and I’m writing the test down BEFORE the result so I can’t quietly move the goalposts. If the physics is right, I should see four things: the curves separate (polyethylene below aluminium), aluminium flatten out at depth, the mean quality factor drop from 4.82 toward ~3.5–4, and the dose move closer to the real MSL/RAD cruise measurement. If they don’t, the model is wrong and I’ll say so. Numbers in the next entry. Either it works or it doesn’t — that’s the whole point of logging the test first. What it still isn’t: 1D, simplified fragmentation, not a replacement for NASA’s HZETRN. Every value traces to a cited source, and the validation suite re-runs on every change."}]...
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Title: DOSEFIELD by @Zhanik | Stardance
Devlogs:
Title: DOSEFIELD by @Zhanik | Stardance
Devlogs:
Day #1: the hard part is in, now I find out if it’s right I’m building DOSEFIELD, a 1D model that estimates how much radiation an astronaut absorbs on a deep-space mission — and how much shielding actually helps. Cosmic rays in, dose-equivalent out. What’s already solid: the stopping-power core matches NIST PSTAR reference data to within 1.6%, and behind 10 g/cm² of aluminium at solar minimum the model gives 1.96 mSv/day — about 0.70 Sv over a 360-day Mars cruise. That’s 17% past NASA’s 600 mSv career limit. A round trip to Mars quietly blows through the radiation an astronaut is allowed for their entire career. That’s the reason this project exists. But the first version only tracked primary particles, and it showed: my aluminium, polyethylene and water curves were sitting almost on top of each other. That’s physically wrong — polyethylene should shield noticeably better, because hydrogen is good at breaking up heavy ions. The missing piece is nuclear fragmentation. So this week I implemented it — real fragmentation cross sections (Bradt–Peters), not a fudge factor tuned to match NASA’s measured value. The material difference has to come out of the physics: hydrogen has the shortest nuclear interaction length per g/cm², so it should win on its own. No parameter is fit to the answer. Now I’m validating it, and I’m writing the test down BEFORE the result so I can’t quietly move the goalposts. If the physics is right, I should see four things: the curves separate (polyethylene below aluminium), aluminium flatten out at depth, the mean quality factor drop from 4.82 toward ~3.5–4, and the dose move closer to the real MSL/RAD cruise measurement. If they don’t, the model is wrong and I’ll say so. Numbers in the next entry. Either it works or it doesn’t — that’s the whole point of logging the test first. What it still isn’t: 1D, simplified fragmentation, not a replacement for NASA’s HZETRN. Every value traces to a cited source, and the validation suite re-runs on every change.
DOSEFIELD DAY #2:Fragmentation is now in the live app. Until today the web dosimeter only ran the primary-only transport — the most interesting result, that breaking up heavy ions is why hydrogen-rich shielding wins, was buried in a console script. Now there’s a “Primaries only ⇄ + Fragmentation” toggle, and flipping it visibly bends the curves: polyethylene pulls away from aluminium and the mean quality factor drops. Concretely, at solar minimum behind 20 g/cm², polyethylene’s edge over aluminium jumps from 12% to 34% the moment fragmentation turns on — the same figure the validation script prints, read from the same function, not hardcoded. Mean ⟨Q⟩ behind 16 g/cm² of aluminium falls 4.47 → 4.14. Nothing was tuned; the toggle just calls the existing Bradt–Peters model. And the honest ceiling stays put: still no secondary neutrons, so the absorbed-dose gap vs the real MSL/RAD measurement (~0.31 vs 0.46 mGy/day) remains — and the UI footnote says so out loud. 76/76 tests green, build clean. Next: surface the NIST + RAD validation inside the app itself.
Devlog #3 — DOSEFIELD Is Live 🚀Hi! Long time no see.DOSEFIELD is now live: https://izbanovj3-prog.github.io/DOSEFIELD/ The entire dosimeter now runs directly in your browser — no installation required. That includes the controls, dose-vs-thickness chart, particle fragmentation toggle, and validation panel.Under the hood, the project is built with Vite and automatically deployed to GitHub Pages through a GitHub Actions workflow. Every push to the main branch triggers a fresh build and deployment. The setup is intentionally simple: deployment uses GitHub’s built-in Actions token, with no external services and no additional secrets.The only challenge in this release wasn’t physics — it was infrastructure. The first deployment failed because GitHub Actions cannot automatically enable GitHub Pages for a repository. The workflow reached that permission boundary and stopped. After enabling Pages in the repository settings and rerunning the workflow, everything deployed successfully.Once the site was live, I verified that all critical assets were being served correctly. The page, stylesheets, and, most importantly, the Web Worker bundle all return HTTP 200 responses with the correct content types.That Web Worker is particularly important because it handles the species-by-species dose integration calculations off the main UI thread. In practice, this means the interface remains responsive while the physics calculations run in the background.No physics models changed in this release, and the known limitations remain the same. This phase was focused entirely on one goal: shipping a fully accessible browser version of DOSEFIELD.The live demo link is now featured at the top of the README.
Devlog #4 — Heavy Elements Cut, Liquid Hydrogen Locked In Lead and titanium were off by 50%. I didn’t hide it. My model tracks how particles slow down inside matter. For heavy elements like lead and titanium, you need a correction for the atom’s electron shells — skip it, and your numbers drift by half the actual value. I haven’t built that correction yet. Faking the results to look clean would gut the whole point of the model. So heavy elements are out for now. Liquid hydrogen sits at the opposite extreme. One electron, no shell complexity — the model handles it without shortcuts. I checked against NIST’s official proton data: 0.14% deviation across the full energy range. In physics terms, that’s a bullseye. Five Materials, One Hierarchy I ran five materials together — liquid hydrogen, methane, polyethylene, water, and aluminum — and tested them as a chain. Two things had to hold: thicker shielding means lower dose, and going from hydrogen to aluminum, dose has to climb, because light elements stop protons better. Both held, with no exceptions. Polyethylene and water differ by just 3% in electrons per gram — the model caught even that gap correctly. The sharpest result: at 40 g/cm², liquid hydrogen cuts dose by 44% compared to aluminum. That’s why some spacecraft designs wrap the crew compartment in hydrogen tanks — fuel and radiation shield in one. All five materials are now locked into regression tests. Total: 103 green tests in CI. One Function, One Truth The dashboard and the generated reports used to calculate their numbers separately. Two parallel code paths mean two places for drift to appear. Now both pull from a single shared function. The number on screen and the number in the report are physically incapable of disagreeing.
DEVLOG #5 (might be the last devlog) Hey! It’s been 11 days since the last devlog. DOSEFIELD wasn’t abandoned—I was just busy building instead of writing.This update was really about two things: making the code cleaner and making the site feel like it belongs in a space mission.The first issue was hidden in the background. The NASA validation numbers on the website were calculated separately from the ones used in my research. The math was identical, but it existed in multiple places. That meant one future change could easily make the numbers disagree.So I refactored everything to use a single source of truth. Now every result comes from the same function, making the site much easier to maintain and much harder to break.Then I focused on the design. The old version worked, but it didn’t feel like DOSEFIELD. I redesigned the interface with a mission-control style, added a cleaner layout, and simplified the visuals. I also removed a lot of unnecessary effects—less glow, fewer gradients, and a more purposeful look.After all those changes, I reran every test. All 107 tests still pass, and the stopping-power calculations remain within 1.55% of NIST reference data, exactly as before.There’s still one limitation: my model predicts about 67% of the radiation dose measured by NASA during the trip to Mars. That’s because it doesn’t yet simulate secondary particle production inside spacecraft shielding. It’s an important limitation, and it’s clearly explained on the website rather than hidden.The biggest lesson from this update wasn’t about physics—it was about revisiting old work. Good code doesn’t duplicate logic, and good design doesn’t rely on effects to look impressive. Sometimes the best improvement is simply cleaning up what you already built.
DEVLOG #6 Hey everyone!This is probably the last devlog for DOSEFIELD, at least for a while. It’s been an incredible journey—from the first rough prototype to something I’m genuinely proud to share. Thank you to everyone who followed along, tested the project, gave feedback, or simply read these updates. It really meant a lot.v2.3 is the “show your work” release. Nothing changed in the physics—and that’s exactly the point.The biggest addition is a new Methods page that renders the repository’s own METHODS.md and limitations table directly. That means anyone reading the website sees the exact same equations, assumptions, and all 12 limitations that exist in the source code. If the website and the repository ever disagree, the repository is the source of truth.Every page now also includes a provenance footer that’s generated automatically during the build. Instead of typing in a version number by hand, the site runs git rev-parse and the full test suite, then stamps something like:commit e22ef18 · 111/111 tests · verified 2026-07-18The build will actually fail if the tests don’t pass, so it’s impossible to accidentally display a “green” verification badge on a broken build.I also improved chart exports. Figures now render at 3200 px, and each exported chart includes its full configuration in the caption. That makes it much easier to trace a plot back to the exact settings that produced it, whether it’s used in a poster, report, or presentation.One thing I want to be completely clear about: this verification is about the software, not the physics. Passing 111 tests means the implementation behaves as expected according to those tests—it doesn’t prove the scientific model is perfect. The current validation remains the same: about 2× agreement with MSL/RAD, and the 0.67× absorbed-dose gap is still there, clearly documented.That’s exactly what this release is about: transparency over hype, reproducibility over screenshots, and being honest about what the model can—and can’t—do.Thanks for following this project. ❤️
Hey Stardance crew! Three months since my last devlog, so grab a snack and let me catch you up. DOSEFIELD estimates how much radiation an astronaut gets behind shielding on a trip to Mars, then checks itself against real data from NASA’s Curiosity cruise (MSL/RAD). The big news: I found a mistake in my own results. In my first public version, the solar modulation value (W = 30) could not be reproduced from the derivation I had written down. So I went back to the Oulu neutron-monitor data, matched the exact time window RAD used, skipped the solar-storm days, and got W = 47.50. The new numbers look worse, and I kept them: absorbed dose: 0.264 vs 0.458 mGy/day measured (0.58x) dose equivalent: 1.318 vs 1.75 mSv/day (0.75x) mean quality factor: 4.995 vs 3.82 (1.31x) My model skips secondary particles and neutrons, so it under-predicts the dose. I report the gap and leave it alone. Also shipped: a check against the full NIST PSTAR table (max deviation 1.55% from 10 to 1000 MeV), 190 passing tests, a code archive on Zenodo (DOI 10.5281/zenodo.23433384), a revised paper on SSRN, and a website that links to all of it.
Ships:
Today was all about making the site tell the truth about itself instead of just describing itself. I added a Methods and Limitations page that pulls directly from METHODS.md and the README instead of being rewritten into friendly marketing copy. If the documentation and the code ever disagree, the documentation loses immediately because they are now the exact same file. Every page also got an automated footer showing the commit hash, the test count, and the exact verification date. It would have taken five minutes to hardcode a string like “111 tests passing” and move on. Instead, the build script runs the actual test suite first, and if anything fails, the entire build stops cold. This ensures the footer can never claim a passing state that is not true at that exact moment. Wiring a build to gate on its own test results took most of the afternoon because it required thinking through what happens during a failure, not just when everything goes smoothly, but the absolute transparency is worth it. What I like most is that the limitations table on the public site is word-for-word what is in the repository. There is no filtered summary for visitors. The 0.67x gap between my modeled absorbed dose and NASA’s measured RAD numbers reads just as blunt on the public page as it does in the source code. Transparency matters more than hype. Additionally, charts now export at 3200px, and the configuration that produced them gets baked directly into the image itself, meaning a PNG cannot wander off from the settings that generated it. If you want to test it yourself, you can check the live app at DOSEFIELD. Look at the footer for a real commit hash and test count, open the Methods and Limitations page to count the 12 rows in the limitations table, or export a chart to verify the resolution against what is rendered on your screen. The complete source code is also available on GitHub....
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My very own WebOS by @Gautam | Stardance
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Title: My very own WebOS by @Gautam | Stardance
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Productivity Tracker by @Nexius1819 | Stardance
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[{"post_id": 14575, "ts": "202 [{"post_id": 14575, "ts": "2026-06-23T18:59:18Z", "hours": 6.5847, "text": "This is my first real coding project. I used python tkinter to create a productivity checker. The user can input and publish various categories. In each category, the user can input various tasks. Each task has a check button assigned to them, once clicked their task disappears. This isn’t the final product since, the UI is ugly and some buttons don’t work. In the near future, I’m will allow for the categories to be deleted and for a completed task section to appear."}]...
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Title: Productivity Tracker by @Nexius1819 | Stard Title: Productivity Tracker by @Nexius1819 | Stardance
Devlogs:
This is my first real coding project. I used python tkinter to create a productivity checker. The user can input and publish various categories. In each category, the user can input various tasks. Each task has a check button assigned to them, once clicked their task disappears. This isn’t the final product since, the UI is ugly and some buttons don’t work. In the near future, I’m will allow for the categories to be deleted and for a completed task section to appear....
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My very own WebOS by @simal26 | Stardance
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Title: My very own WebOS by @simal26 | Stardance
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My first slack bot! by @suryasid_mullangi | Starda My first slack bot! by @suryasid_mullangi | Stardance...
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Title: My first slack bot! by @suryasid_mullangi | Title: My first slack bot! by @suryasid_mullangi | Stardance...
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FireStack (stopped) by @Tlusty | Stardance
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[{"post_id": 10163, "ts": "202 [{"post_id": 10163, "ts": "2026-06-16T19:34:38Z", "hours": 1.0542, "text": "an investment calculator that makes the journey to financial independence real and achievable for everyone. Using Next.js"}]...
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Title: FireStack (stopped) by @Tlusty | Stardance
Title: FireStack (stopped) by @Tlusty | Stardance
Devlogs:
an investment calculator that makes the journey to financial independence real and achievable for everyone. Using Next.js...
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My very own WebOS by @RithvikC | Stardance
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Title: My very own WebOS by @RithvikC | Stardance
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My very own WebOS by @ShanmukhaR | Stardance
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Title: My very own WebOS by @ShanmukhaR | Stardanc Title: My very own WebOS by @ShanmukhaR | Stardance...
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1794001784.1776638
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