Engineering topics

Hoelscher, Brian

Publications and source records attributed to Hoelscher, Brian.

3 records

NASA NTRS2015

Post-Flight Analysis of the Guidance, Navigation, and Control Performance During Orion Exploration Flight Test 1

The first test flight of the Orion Multi-Purpose Crew Vehicle presented additional challenges for guidance, navigation and control as compared to a typical re-entry from the International Space Station or other Low Earth Orbit. An elevated re-entry velocity and steeper flight path angle were chosen to achieve aero-thermal flight test objectives. New IMU's, a GPS receiver, and baro altimeters were flight qualified to provide the redundant navigation needed for human space flight. The guidance and control systems must manage the vehicle lift vector in order to deliver the vehicle to a precision, coastal, water landing, while operating within aerodynamic load, reaction control system, and propellant constraints. Extensive pre-flight six degree-of-freedom analysis was performed that showed mission success for the nominal mission as well as in the presence of sensor and effector failures. Post-flight reconstruction analysis of the test flight is presented in this paper to show whether that all performance metrics were met and establish how well the pre-flight analysis predicted the in-flight performance.

Barth, Andrew↗

NASA NTRS2013

Simple Sensitivity Analysis for Orion Guidance Navigation and Control

The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch. We describe in this paper a sensitivity analysis tool ("Critical Factors Tool" or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.

Pressburger, Tom↗

NASA NTRS2013

Simple Sensitivity Analysis for Orion GNC

The performance of Orion flight software, especially its GNC software, is being analyzed by running Monte Carlo simulations of Orion spacecraft flights. The simulated performance is analyzed for conformance with flight requirements, expressed as performance constraints. Flight requirements include guidance (e.g. touchdown distance from target) and control (e.g., control saturation) as well as performance (e.g., heat load constraints). The Monte Carlo simulations disperse hundreds of simulation input variables, for everything from mass properties to date of launch.We describe in this paper a sensitivity analysis tool (Critical Factors Tool or CFT) developed to find the input variables or pairs of variables which by themselves significantly influence satisfaction of requirements or significantly affect key performance metrics (e.g., touchdown distance from target). Knowing these factors can inform robustness analysis, can inform where engineering resources are most needed, and could even affect operations. The contributions of this paper include the introduction of novel sensitivity measures, such as estimating success probability, and a technique for determining whether pairs of factors are interacting dependently or independently. The tool found that input variables such as moments, mass, thrust dispersions, and date of launch were found to be significant factors for success of various requirements. Examples are shown in this paper as well as a summary and physics discussion of EFT-1 driving factors that the tool found.

Monte Carlo Simulation↗