Search NASA⌕ Search

Engineering topics

Williams, Austin

Publications and source records attributed to Williams, Austin.

Stochastic gradient descent for optimization for nuclear systems

The use of gradient descent methods for optimizing k-eigenvalue nuclear systems has been shown to be useful in the past, but the use of k-eigenvalue gradients have proved computationally challenging due to their stochastic nature. ADAM is a gradient descent method that accounts for gradients with a stochastic nature. This analysis uses challenge problems constructed to verify if ADAM is a suitable tool to optimize k-eigenvalue nuclear systems. ADAM is able to successfully optimize nuclear systems using the gradients of k-eigenvalue problems despite their stochastic nature and uncertainty. Furthermore, it is clearly demonstrated that low-compute time, high-variance estimates of the gradient lead to better performance in the optimization challenge problems tested here.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Gradient-Informed Design Optimization of Select Nuclear Systems

In this work, we present a gradient-informed design optimization of nuclear reactor core components based on neutronics objectives with both continuous and discrete materials. The main argument in favor of using gradient-informed design optimization is that it scales well with increasing dimensionality of the design space. First, a challenge problem with 121 free parameters is solved with a gradient-informed method and then with a genetic algorithm. Then, a challenge problem to optimize the flux profile of a simplified assembly with eight axial zones is solved. Both challenge problems are solved using directly calculated derivatives from Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) in the SCALE package. Furthermore, we demonstrate how a discrete optimization problem—selection of materials for 121 voxels—can be lifted into a continuous problem with mixed materials. In the continuous space, adjoint-based gradients are well-defined, and gradient descent is applicable. Then, a forcing function is introduced that with the selection of an appropriately sized hyperparameter can be used to guide the optimized continuous solution back into a discrete solution. This paper presents an account of the challenges that were faced when applying a gradient-informed optimization algorithm using a Monte Carlo calculation to estimate the gradient information and compares a gradient descent optimization method to a genetic algorithm optimization of the same geometry. Overall, this work demonstrates the potential use of adjoint-based gradient calculations in design optimization of nuclear systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Structural response of 3D-printed rubber lattice structures under compressive fatigue

In this work, a new direct UV curing, polyurethane-like, highly stretchable rubber, Elastic ToughRubber 90™ (ETR 90), is demonstrated for 3D printing via photocuring with Texas Instruments DLP® optical systems. An array of test specimens, comprising a sandwich structure with a body-centered cubic lattice core, are 3D printed from ETR 90. The compressive behavior of these specimens is characterized up to 10 k and up to 100 k fatigue-loading cycles. The internal, visually obstructed, structures under loads are visualized using in situ X-ray tomography. All lattice structures remain intact and full recovery is observed, indicating the cyclic durability of the 3D-printed rubber.

36 MATERIALS SCIENCE↗

RainCube, a Ka-band Precipitation Radar in a 6U CubeSat

RainCube (Radar in a CubeSat) is a 6U CubeSat mission between the Jet Propulsion Laboratory (JPL) and Tyvak Nano-Satellite Systems (Tyvak). The objective of the mission is to develop, launch, and operate a 35.75 GHz nadirpointing precipitation profiling radar payload to validate a new architecture for Ka-band radars and an ultra-compact deployable Ka-band antenna design in the space environment. RainCube will also demonstrate the feasibility of a radar payload on a CubeSat platform. The radar payload is the evolution of two previous JPL research and development technologies – the miniaturized Ka-band atmospheric radar (miniKaAR) and the 0.5m diameter Ka-band parabolic deployable antenna (KaPDA). JPL has contracted Tyvak to develop the spacecraft bus, integrate the payload, and operate the spacecraft. RainCube is currently in integration and test with an expected ready-for-delivery in September 2017.

Williams, Austin↗

Interplanetary CubeSats: Opening the Solar System to a Broad Community at Lower Cost

Interplanetary CubeSats could enable small, low-cost missions beyond low Earth orbit. This class is defined by mass < ~ 10 kg, cost < $30 M, and durations up to 5 years. Over the coming decade, a stretch of each of six distinct technology areas, creating one overarching architecture, could enable comparatively low-cost Solar System exploration missions with capabilities far beyond those demonstrated in small satellites to date. The six technology areas are: (1) CubeSat electronics and subsystems extended to operate in the interplanetary environment, especially radiation and duration of operation; (2) Optical telecommunications to enable very small, low-power uplink/downlink over interplanetary distances; (3) Solar sail propulsion to enable high !V maneuvering using no propellant; (4) Navigation of the Interplanetary Superhighway to enable multiple destinations over reasonable mission durations using achievable !V; (5) Small, highly capable instrumentation enabling acquisition of high-quality scientific and exploration information; and (6) Onboard storage and processing of raw instrument data and navigation information to enable maximum utility of uplink and downlink telecom capacity, and minimal operations staffing. The NASA Innovative Advanced Concepts (NIAC) program in 2011 selected Interplanetary CubeSats for further investigation, some results of which are reported here for Phase 1.

Staehle, Robert L.↗

Onboard Autonomy and Ground Operations Automation for the Intelligent Payload Experiment (IPEX) CubeSat Mission

The Intelligent Payload Experiment (IPEX) is a cubesat manifested for launch in October 2013 that will flight validate autonomous operations for onboard instrument processing and product generation for the Intelligent Payload Module (IPM) of the Hyperspectral Infra-red Imager (HyspIRI) mission concept. We first describe the ground and flight operations concept for HyspIRI IPM operations. We then describe the ground and flight operations concept for the IPEX mission and how that will validate HyspIRI IPM operations. We then detail the current status of the mission and outline the schedule for future development.

project data planning↗

Onboard Processing and Autonomous Operations on the IPEX Cubesat

IPEX is a 1u Cubesat sponsored by NASA Earth Science Technology Office (ESTO), the goals or which are: (1) Flight validate high performance flight computing, (2) Flight validate onboard instrument data processing product generation software, (3) flight validate autonomous operations for instrument processing, (4) enhance NASA outreach and university ties.

Hyperspectral Infrared Imager (HyspIRI)↗