Assessment of the Mars helicopter thermal design sensitivities using the Veritrek software
ABSTRACT: The Mars Helicopter will be a technology demonstration conducted during the Mars 2020 mission. The primary mission objective is to achieve several 90-second flights and capture visible light images via forward and nadir mounted cameras. These flights could possibly provide reconnaissance data for sampling site selection for other Mars surface missions. The helicopter is powered by a solar array, which stores energy in secondary batteries for flight operations, imaging, communications, and survival heating. The helicopter thermal design is driven by minimizing survival heater energy while maintaining compliance with allowable flight temperatures in a variable thermal environment. Due to the small size of the helicopter and its complex geometries, along with the fact that it operates with very low power and small margins, additional care had to be paid while planning thermal tests and designing the thermal system. A Thermal Desktop® model has been developed to predict the thermal system’s performance. A reduced-order model (ROM) created with the Veritrek software has been utilized to explore the sensitivities of the thermal system’s drivers, such as electronics dissipations, gas gaps, heat transfer coefficients, etc., as well as to assess and verify the final thermal design. This paper presents the performance of the Veritrek software products and the details of the ROM creation process. The results produced by Veritrek were utilized to study the effect of the major thermal design drivers and Mars environment on the Mars Helicopter in as little as 10 days, an effort that would have taken over 4 months using traditional thermal analysis techniques.
Automatic creation of Reduced-order models using Thermal Desktop
ABSTRACT: Computer simulations are often complex and computationally expensive. When properly developed, reduced-order models (ROMs) can overcome these challenges by providing a computationally efficient surrogate that accurately captures the effects of an underlying high-fidelity thermal model (e.g. Thermal Desktop®). ROMs can then provide thousands of simulation results in seconds which enables evaluation of large design spaces. A reduced-order modeling approach to predict spacecraft output responses for a set of input factors was developed. It is based on Latin Hypercube sampling and Gaussian Process regression modeling. This approach was successfully applied to a broad range of applications including the Orion Crew Exploration Vehicle and a nominal Hex Spacecraft Bus. Results compared favorably to the underlying Thermal Desktop® model. This approach was developed into software tools that provide analysis features such as screening studies, optimization, and response surface plotting.
Enhanced data exploration through Reduced-order Models
ABSTRACT: A reduced-order modeling approach to predict spacecraft output responses for a set of
input factors was developed. It is based on Latin Hypercube sampling and Gaussian Process
regression modeling. A test case, based on a simplified Orion Crew Exploration Vehicle
Thermal Desktop® model, was developed and included nine input factors and seven output
responses. Output response residuals, found for predicted temperatures, hydraulic power,
and pressure, had means of 1.6 K, 0.2 W, 1.6 kPa and standard deviations of 5.0 K, 1.93 W,
18.2 kPa, respectively. Additionally, a software tool was developed to more easily utilize the
reduced-order model and enhance the ability to explore the data.