masa-umich/mcnugget
Oct 2024 – May 2025
8 Months active
Languages Used
CSVPNGPowerShellPythonShellJupyter NotebookPDFXLSX
Technical Skills
Code OrganizationData ProcessingData SimulationData VisualizationFile ManagementPython
evanhekman
PROFILE
Evanhekman
Ethan Hekman developed and maintained core data acquisition and simulation tooling for the masa-umich/mcnugget repository over eight months, focusing on rocket engine test automation and reliability. He engineered configurable autosequence frameworks, robust sensor data pipelines, and simulation environments using Python and C++, integrating hardware interfaces and real-time data processing. His work included refactoring for maintainability, implementing structured logging, and enhancing configuration management to support reproducible experiments. By standardizing data workflows and improving test sequencing, Ethan enabled safer, more repeatable hot-fire and cold-flow tests. The depth of his contributions advanced system integration, data integrity, and the overall readiness of the testing platform.
Overall Statistics
Feature vs Bugs
85%Features
Repository Contributions
80Total
Bugs
5
Commits
80
Features
29
Lines of code
523,715
Activity Months8
Your Network
192 people
Work History
May 2025
3 Commits • 1 Features
May 1, 2025May 2025 (2025-05) performance summary for masa-umich/mcnugget: Key features delivered - Rocket Engine Testing: Simulation and Data Acquisition Enhancements - Implemented cold-flow simulation script and refactored connection and channel handling to improve test reliability. - Refined data processing for load cells and thermocouple channels, ensuring cleaner, more actionable telemetry. - Updated hot-fire sequencing parameters, data processing scripts, burn duration, and pressure targets; added median tank pressure calculations and reconfigured DAQ channels to enhance data integrity. Major bugs fixed - Stabilized test sequencing and DAQ configurations to reduce intermittent data loss during hot-fire events; improved error handling in data collection scripts; increased reliability of channel mappings and burn termination criteria. Overall impact and accomplishments - Substantially improved test reliability and data quality for engine testing, enabling more repeatable experiments and faster iteration cycles. - Demonstrated end-to-end capability from simulation through data acquisition to post-test processing, contributing to safer, more controllable test campaigns. - Achieved a meaningful test milestone: 3700 lbs startup, 3000 lbs steady-state, full 22-second burn, advancing project readiness for flight-like tests. Technologies/skills demonstrated - Python scripting for simulation, data processing, and test orchestration - Data acquisition (DAQ) configuration and channel management - Test sequencing design and parameterization for hot-fire tests - Refactoring for reliability and maintainability - Strong emphasis on data integrity, filtering, and reporting for engineering decisions Commit highlights - bb17f114b46ae668b12d0a813c716c4768d64d90 – prep for rrs coldflow - a4f0b16d8a14eeda4f10cc158c44e6466e8721ae – refinement of reliability and test readiness - cb5c320942e9aaa24aedda91ac41d045dbe4c01d – 3700lbs startup, 3000lbs steady state, full 22 second burn achieved
3 Commits • 1 Features
May 1, 2025May 2025 (2025-05) performance summary for masa-umich/mcnugget: Key features delivered - Rocket Engine Testing: Simulation and Data Acquisition Enhancements - Implemented cold-flow simulation script and refactored connection and channel handling to improve test reliability. - Refined data processing for load cells and thermocouple channels, ensuring cleaner, more actionable telemetry. - Updated hot-fire sequencing parameters, data processing scripts, burn duration, and pressure targets; added median tank pressure calculations and reconfigured DAQ channels to enhance data integrity. Major bugs fixed - Stabilized test sequencing and DAQ configurations to reduce intermittent data loss during hot-fire events; improved error handling in data collection scripts; increased reliability of channel mappings and burn termination criteria. Overall impact and accomplishments - Substantially improved test reliability and data quality for engine testing, enabling more repeatable experiments and faster iteration cycles. - Demonstrated end-to-end capability from simulation through data acquisition to post-test processing, contributing to safer, more controllable test campaigns. - Achieved a meaningful test milestone: 3700 lbs startup, 3000 lbs steady-state, full 22-second burn, advancing project readiness for flight-like tests. Technologies/skills demonstrated - Python scripting for simulation, data processing, and test orchestration - Data acquisition (DAQ) configuration and channel management - Test sequencing design and parameterization for hot-fire tests - Refactoring for reliability and maintainability - Strong emphasis on data integrity, filtering, and reporting for engineering decisions Commit highlights - bb17f114b46ae668b12d0a813c716c4768d64d90 – prep for rrs coldflow - a4f0b16d8a14eeda4f10cc158c44e6466e8721ae – refinement of reliability and test readiness - cb5c320942e9aaa24aedda91ac41d045dbe4c01d – 3700lbs startup, 3000lbs steady state, full 22 second burn achieved
May 2025
April 2025
5 Commits • 3 Features
Apr 1, 2025April 2025: Delivered a robust, configurable hotfire autosequence framework in masa-umich/mcnugget, including a modified_hotfire.py with refactored config loading, parameter handling, and structured logging for clearer, more reliable test sequences; tuned ignition/prepress timing and data handling with a new fuel prepress dome isolation thread and enhanced averaging/data streaming to improve reliability and precision of hotfire tests; overhauled autosequences configuration with Config and Parameter classes, plus validation, loading/saving/locking and testing tooling to bolster configuration verification and test coverage. These changes improved reliability, repeatability, and observability, enabling safer experiments, faster parameter iteration, and easier future research.
April 2025
5 Commits • 3 Features
Apr 1, 2025April 2025: Delivered a robust, configurable hotfire autosequence framework in masa-umich/mcnugget, including a modified_hotfire.py with refactored config loading, parameter handling, and structured logging for clearer, more reliable test sequences; tuned ignition/prepress timing and data handling with a new fuel prepress dome isolation thread and enhanced averaging/data streaming to improve reliability and precision of hotfire tests; overhauled autosequences configuration with Config and Parameter classes, plus validation, loading/saving/locking and testing tooling to bolster configuration verification and test coverage. These changes improved reliability, repeatability, and observability, enabling safer experiments, faster parameter iteration, and easier future research.
March 2025
9 Commits • 3 Features
Mar 1, 2025March 2025 monthly summary for masa-umich/mcnugget focused on delivering core capabilities, stabilizing data workflows, and advancing automation for DAQ and hotfire experiments. Key outcomes include robust tooling for Synnax range data creation/retrieval with an accompanying Python script and sample data, expanded hardware integration with load cells, and a comprehensive autosequence overhaul that improves timing accuracy, sensor configuration, and shutdown sequencing. These efforts enhance data reliability, reduce setup time, and enable more reproducible experiment runs across the DAQ stack.
9 Commits • 3 Features
Mar 1, 2025March 2025 monthly summary for masa-umich/mcnugget focused on delivering core capabilities, stabilizing data workflows, and advancing automation for DAQ and hotfire experiments. Key outcomes include robust tooling for Synnax range data creation/retrieval with an accompanying Python script and sample data, expanded hardware integration with load cells, and a comprehensive autosequence overhaul that improves timing accuracy, sensor configuration, and shutdown sequencing. These efforts enhance data reliability, reduce setup time, and enable more reproducible experiment runs across the DAQ stack.
March 2025
February 2025
12 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for masa-umich/mcnugget focused on stabilizing sensor data workflows, hardening autosequences, and delivering a refreshed ignition/hydro processing pipeline. The work emphasizes business value through data standardization, reliability, and safer simulations, with clear improvements to data handling, sequence correctness, and user interaction prompts.
February 2025
12 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for masa-umich/mcnugget focused on stabilizing sensor data workflows, hardening autosequences, and delivering a refreshed ignition/hydro processing pipeline. The work emphasizes business value through data standardization, reliability, and safer simulations, with clear improvements to data handling, sequence correctness, and user interaction prompts.
January 2025
23 Commits • 12 Features
Jan 1, 20252025-01 monthly summary for masa-umich/mcnugget. Key features delivered include Synnax Versioning (version tag updates, schema-change handling), Diagnostics System (health checks and runtime diagnostics), Channel Interaction PoC and Simulation (three interaction types with simulation readiness), Cold Flow Simulation (running and working cold-flow capabilities), and Instrumentation Improvements (monitoring coverage across the system). Additional progress was achieved in Thermo Module (thermo_magic v1) and RSE Core, as well as code quality and repository organization (tests, formatting, and reorganized structure). Channel Management Enhancements, Torch-Related Behavior Updates, Miscellaneous/Experimental changes, and ongoing code cleanup/refactor contributed to maintainability and better project hygiene. Bug fixes included removal of a nonfunctional pause and ambientization validation. Overall, these efforts improve reliability, observability, upgrade readiness, and time-to-value for platform users.
23 Commits • 12 Features
Jan 1, 20252025-01 monthly summary for masa-umich/mcnugget. Key features delivered include Synnax Versioning (version tag updates, schema-change handling), Diagnostics System (health checks and runtime diagnostics), Channel Interaction PoC and Simulation (three interaction types with simulation readiness), Cold Flow Simulation (running and working cold-flow capabilities), and Instrumentation Improvements (monitoring coverage across the system). Additional progress was achieved in Thermo Module (thermo_magic v1) and RSE Core, as well as code quality and repository organization (tests, formatting, and reorganized structure). Channel Management Enhancements, Torch-Related Behavior Updates, Miscellaneous/Experimental changes, and ongoing code cleanup/refactor contributed to maintainability and better project hygiene. Bug fixes included removal of a nonfunctional pause and ambientization validation. Overall, these efforts improve reliability, observability, upgrade readiness, and time-to-value for platform users.
January 2025
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for masa-umich/mcnugget: Delivered codebase hygiene improvements and a new sensor simulation framework to accelerate testing and development of the Synnax DAQ system. Upgraded core dependencies and cleaned unused imports to improve stability and compatibility. Introduced configuration generation and channel renaming utilities to support reproducible test environments and faster iteration.
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 monthly summary for masa-umich/mcnugget: Delivered codebase hygiene improvements and a new sensor simulation framework to accelerate testing and development of the Synnax DAQ system. Upgraded core dependencies and cleaned unused imports to improve stability and compatibility. Introduced configuration generation and channel renaming utilities to support reproducible test environments and faster iteration.
November 2024
20 Commits • 4 Features
Nov 1, 2024Nov 2024 performance summary for masa-umich/mcnugget: Focused on reliability, hardware configurability, and data integrity across the simulation, IO, and sensor-data pipelines. Key features delivered include Synnax integration with dynamic task configuration, NI hardware task configuration and Excel-based sensor data processing, and major improvements to simulation orchestration and IO reliability. A dedicated cleanup effort stabilized the codebase and dependencies, enabling smoother future iterations. A critical reader-writer reliability fix in coldflow_sim and averaging scripts further improved data integrity. The work collectively reduces manual setup time, increases hardware flexibility, and strengthens the end-to-end data acquisition and simulation workflow.
20 Commits • 4 Features
Nov 1, 2024Nov 2024 performance summary for masa-umich/mcnugget: Focused on reliability, hardware configurability, and data integrity across the simulation, IO, and sensor-data pipelines. Key features delivered include Synnax integration with dynamic task configuration, NI hardware task configuration and Excel-based sensor data processing, and major improvements to simulation orchestration and IO reliability. A dedicated cleanup effort stabilized the codebase and dependencies, enabling smoother future iterations. A critical reader-writer reliability fix in coldflow_sim and averaging scripts further improved data integrity. The work collectively reduces manual setup time, increases hardware flexibility, and strengthens the end-to-end data acquisition and simulation workflow.
November 2024
October 2024
5 Commits • 2 Features
Oct 1, 2024Month: 2024-10 — Masa-umich/mcnugget monthly summary highlighting key accomplishments, major fixes, and business/technical impact. This period prioritized delivering core data tooling, improving module maintainability, and removing obsolete components to sharpen the feature set and reduce maintenance overhead.
October 2024
5 Commits • 2 Features
Oct 1, 2024Month: 2024-10 — Masa-umich/mcnugget monthly summary highlighting key accomplishments, major fixes, and business/technical impact. This period prioritized delivering core data tooling, improving module maintainability, and removing obsolete components to sharpen the feature set and reduce maintenance overhead.
Activity
Loading activity data...
Quality Metrics
Correctness82.4%
Maintainability83.0%
Architecture79.8%
Performance73.4%
AI Usage20.4%
Skills & Technologies
Programming Languages
C++CSVJupyter NotebookPDFPNGPowerShellPythonShellXLSX
Technical Skills
API IntegrationArchivingAutomationAutomation ScriptingCode CleanupCode OrganizationCode RefactoringConcurrencyConfiguration ManagementControl SystemsData AcquisitionData EngineeringData GenerationData HandlingData Processing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline