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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Towards Risk Based Design for NASA's Missions

This paper describes the concept of Risk Based Design in the context of NASA s low volume, high cost missions. The concept of accounting for risk in the design lifecycle has been discussed and proposed under several research topics, including reliability, risk analysis, optimization, uncertainty, decision-based design, and robust design. This work aims to identify and develop methods to enable and automate a means to characterize and optimize risk, and use risk as a tradeable resource to make robust and reliable decisions, in the context of the uncertain and ambiguous stage of early conceptual design. This paper first presents a survey of the related topics explored in the design research community as they relate to risk based design. Then, a summary of the topics from the NASA-led Risk Colloquium is presented, followed by current efforts within NASA to account for risk in early design. Finally, a list of "risk elements", identified for early-phase conceptual design at NASA, is presented. The purpose is to lay the foundation and develop a roadmap for future work and collaborations for research to eliminate and mitigate these risk elements in early phase design.

Tumer, Irem Y.↗
NASA NTRS2004

Inverse FEM for Full-Field Reconstruction of Elastic Deformations in Shear Deformable Plates and Shells

The inverse problem of real-time reconstruction of full-field structural displacements is addressed through the application of a new variational formulation leading to versatile, robust and computationally efficient inverse shell finite element analysis. Utilizing surface strain measurements from strain sensors mounted on the load-carrying structural components, the methodology enables accurate computations of the three-dimensional displacement field. This high fidelity computational technology is essential for providing feedback to the actuation and control systems of the next generation of aerospace vehicles.

Tessler, Alexander↗
NASA NTRS2008

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗
NASA NTRS2008

Mars Phoenix Entry, Descent, and Landing Simulation Design and Modelling Analysis

The 2007 Mars Phoenix Lander was launched in August of 2007 on a ten month cruise to reach the northern plains of Mars in May 2008. Its mission continues NASA s pursuit to find evidence of water on Mars. Phoenix carries upon it a slew of science instruments to study soil and ice samples from the northern region of the planet, an area previously undiscovered by robotic landers. In order for these science instruments to be useful, it was necessary for Phoenix to perform a safe entry, descent, and landing (EDL) onto the surface of Mars. The EDL design was defined through simulation and analysis of the various phases of the descent. An overview of the simulation and various models developed to characterize the EDL performance is provided. Monte Carlo statistical analysis was performed to assess the performance and robustness of the Phoenix EDL system and are presented in this paper. Using these simulation and modelling tools throughout the design and into the operations phase, the Mars Phoenix EDL was a success on May 25, 2008.

Prince, Jill L.↗
NASA NTRS2020

Assessment of Transition Modeling Capability in OVERFLOW with Emphasis on Swept-Wing Configurations

In preparation for comparisons with data obtained from the recently concluded experiments in the National Transonic Facility at the NASA Langley Research Center on the new common research model with natural laminar flow (CRM-NLF), an assessment of the current transition modeling capability in the NASA OVERFLOW 2.2o code has been carried out. A combination of the available experimental data and linear stability analysis is used to evaluate the accuracy and robustness of these models for selected swept-wing type configurations, with significant crossflow. An additional goal for this work involves providing a comparative assessment of the relevant transition models in the context of a single flow solver and identifying model limitations as well as the potential for future improvements that would help strengthen the physical basis of such transition models. Included in this investigation is an assessment of the sensitivities of the underlying transition models to grid resolution (wall-normal, as well as streamwise and spanwise) and the values of extra input parameters such as the level of surface roughness and freestream turbulence variables. The flow configurations targeted in this assessment include the NASA NLF(2)-0415 swept-wing configuration, the sickle-shaped wing introduced by the Technical University of Braunschweig, and the wing-body configuration of the CRM model from the fourth and fifth AIAA CFD Drag Prediction Workshops.

Freestream velocity↗
NASA NTRSDate not supplied

Porous Microstructure Analysis (PuMA) software

The Porous Microstructure Analysis (PuMA) software was developed to provide a robust and efficient framework for computing material properties based on their microstructures. The development was motivated by advancements in X-ray microtomography, an imaging technology that can resolve the structure of a material at a sub-micron scale, in 3D and even in 4D (over time). PuMA provides the capability of computing a comprehensive spectrum of properties, from the most fundamental geometric features of a microstructure, to advanced anisotropic thermo-elastic properties. In addition, the software can generate artificial microstructures, ranging from simple analytical shapes to complex fibrous woven and non- woven geometries, which can be used in performance optimization studies. This presentation will highlight many of the capabilities of the recent open-source release.

microtomography↗
NASA NTRSDate not supplied

Onboard Autonomous Trajectory Planning for Mars Power Descent

In recent years, there has been an increasing interest in space-qualified processors such as multi-core central processing units and graphics processing units that can withstand the adverse effects of space radiation. These processors can allow parallel programming to perform tasks that typically demand high computational power. One can study guidance schemes that can take advantage of these currently developing processors and provide more robust guidance. Software for Multi-model Autonomous Real-time Trajectories (SMART) guidance can identify robust trajectories by running an onboard Monte Carlo analysis. SMART guidance can take advantage of knowledge updates obtained from the onboard sensors, allowing it to consider the off-nominal cases that it would not typically encounter during the offline trajectory analysis. This work uses the SMART guidance for the powered divert at Mars simulation in Program to Optimize and Simulated Trajectories- II.

Pardha Sai Chadalavada↗
NASA NTRSDate not supplied

Onboard Autonomous Trajectory Planning for Mars Power Descent

In recent years, there has been an increasing interest in space-qualified processors such as multi-core central processing units and graphics processing units that can withstand the adverse effects of space radiation. These processors can allow parallel programming to perform tasks that typically demand high computational power. One can study guidance schemes that can take advantage of these currently developing processors and provide more robust guidance. Software for Multi-model Autonomous Real-time Trajectories (SMART) guidance can identify robust trajectories by running an onboard Monte Carlo analysis. SMART guidance can take advantage of knowledge updates obtained from the onboard sensors, allowing it to consider the off-nominal cases that it would not typically encounter during the offline trajectory analysis. This work uses the SMART guidance for the powered divert at Mars simulation in Program to Optimize and Simulated Trajectories- II.

Autonomous Planning↗
DOE OSTI2024

LA100 Equity Strategies

In the Los Angeles 100% Renewable Energy Study (LA100), the National Renewable Energy Laboratory (NREL) found that the City of Los Angeles can achieve its ambitious goal of reliable, 100% carbon-free energy as early as 2035. While all communities will benefit from air quality and health improvements of clean energy, improving equity in participation and outcomes requires intentionally designed equity strategies. To plan for a clean energy future that benefits all Angelenos, the Los Angeles Department of Water and Power (LADWP), NREL, and the University of California Los Angeles (UCLA) partnered on the LA100 Equity Strategies project. In an innovative, community-informed approach, the LA100 Equity Strategies project integrated robust social science research techniques with rigorous data analysis - and incorporated what community members themselves know is needed to achieve a more equitable energy future. The team developed effective strategies for engaging communities, funding equitable technology and infrastructure investments, expanding existing clean energy and energy assistance programs, and designing new programs and policies to enhance equity.

community↗
NASA NTRS2002

Independent Confirmation of the Pioneer 10 Anomalous Acceleration

I perform an independent analysis of radio Doppler tracking data from the Pioneer 10 spacecraft for the time period 1987-1994. All of the tracking data were taken from public archive sources, and the analysis tools were developed independently by myself. I confirm that an apparent anomalous acceleration is acting on the Pioneer 10 spacecraft, which is not accounted for by present physical models of spacecraft navigation. My best fit value for the acceleration, including corrections for systematic biases and uncertainties, is (8.60 plus or minus 1.34) x 10(exp -8) centimeters per second, directed towards the Sun. This value compares favorably to previous results. I examine the robustness of my result to various perturbations of the analysis method, and find agreement to within plus or minus 5%. The anomalous acceleration is reasonably constant with time, with a characteristic variation time scale of greater than 70 yr. Such a variation timescale is still too short to rule out on-board thermal radiation effects, based on this particular Pioneer 10 data set.

Markwardt, Craig B.↗
DOE OSTI2020

Towards Robustness Guarantees for Feedback-Based Optimization

Feedback-based online optimization algorithms have gained traction in recent years because of their simple implementation, their ability to reject disturbances in real time, and their increased robustness to model mismatch. While the robustness properties have been observed both in simulation and experimental results, the theoretical analysis in the literature is mostly limited to nominal conditions. In this work, we propose a framework to systematically assess the robust stability of feedback-based online optimization algorithms. We leverage tools from monotone operator theory, variational inequalities and classical robust control to obtain tractable numerical tests that guarantee robust convergence properties of online algorithms in feedback with a physical system, even in the presence of disturbances and model uncertainty. The results are illustrated via an academic example and a case study of a power distribution system.

approximation algorithms↗
NASA NTRS2012

Dispersed Fringe Sensing Analysis - DFSA

Dispersed Fringe Sensing (DFS) is a technique for measuring and phasing segmented telescope mirrors using a dispersed broadband light image. DFS is capable of breaking the monochromatic light ambiguity, measuring absolute piston errors between segments of large segmented primary mirrors to tens of nanometers accuracy over a range of 100 micrometers or more. The DFSA software tool analyzes DFS images to extract DFS encoded segment piston errors, which can be used to measure piston distances between primary mirror segments of ground and space telescopes. This information is necessary to control mirror segments to establish a smooth, continuous primary figure needed to achieve high optical quality. The DFSA tool is versatile, allowing precise piston measurements from a variety of different optical configurations. DFSA technology may be used for measuring wavefront pistons from sub-apertures defined by adjacent segments (such as Keck Telescope), or from separated sub-apertures used for testing large optical systems (such as sub-aperture wavefront testing for large primary mirrors using auto-collimating flats). An experimental demonstration of the coarse-phasing technology with verification of DFSA was performed at the Keck Telescope. DFSA includes image processing, wavelength and source spectral calibration, fringe extraction line determination, dispersed fringe analysis, and wavefront piston sign determination. The code is robust against internal optical system aberrations and against spectral variations of the source. In addition to the DFSA tool, the software package contains a simple but sophisticated MATLAB model to generate dispersed fringe images of optical system configurations in order to quickly estimate the coarse phasing performance given the optical and operational design requirements. Combining MATLAB (a high-level language and interactive environment developed by MathWorks), MACOS (JPL s software package for Modeling and Analysis for Controlled Optical Systems), and DFSA provides a unique optical development, modeling and analysis package to study current and future approaches to coarse phasing controlled segmented optical systems.

Sigrist, Norbert↗
NASA NTRS2008

Nonlinear Reduced-Order Analysis with Time-Varying Spatial Loading Distributions

Oscillating shocks acting in combination with high-intensity acoustic loadings present a challenge to the design of resilient hypersonic flight vehicle structures. This paper addresses some features of this loading condition and certain aspects of a nonlinear reduced-order analysis with emphasis on system identification leading to formation of a robust modal basis. The nonlinear dynamic response of a composite structure subject to the simultaneous action of locally strong oscillating pressure gradients and high-intensity acoustic loadings is considered. The reduced-order analysis used in this work has been previously demonstrated to be both computationally efficient and accurate for time-invariant spatial loading distributions, provided that an appropriate modal basis is used. The challenge of the present study is to identify a suitable basis for loadings with time-varying spatial distributions. Using a proper orthogonal decomposition and modal expansion, it is shown that such a basis can be developed. The basis is made more robust by incrementally expanding it to account for changes in the location, frequency and span of the oscillating pressure gradient.

Prezekop, Adam↗
DOE OSTI2017

High Performance-Multidisciplinary Simulation for Regional Scale Earthquake Hazard and Risk Assessments

Moderate-to-large magnitude earthquakes represent a significant risk around the world and a major issue across the Department of Energy (DOE) mission interests, ranging from DOE's one-of-a-kind mission critical facilities to national energy systems (nuclear power plants, electric/gas distribution systems, and renewable energy production facilities). As a result, for the DOE there is a strong motivation in promoting and developing a risk-informed and performance-based approach for both the assessment of existing facilities and the design of new structures. DOE National Labs have historically made multidisciplinary contributions to the solution of challenging seismic hazard and risk problems and have been at the forefront for the development of design standards for major facilities. The current approach for estimating the ground motion hazard for critical facilities is based upon a Probabilistic Seismic Hazard Analysis (PSHA), whereby measured ground motion data are collected and homogenized into a probabilistic framework to estimate the hazard for future events. However, recent studies have highlighted the site-specific nature of earthquakes and shown the limitations of a purely empirical approach. Moreover, the design of infrastructure systems has been moving toward a performance-based approach, in which specific performance goals are specified at different levels of excitation and for different limit states. Such an approach requires the availability of robust and reliable computational tools for the nonlinear dynamic analysis of complex structural systems. Ongoing research at Lawrence Berkeley National Laboratory (LBNL) and Lawrence Livermore National Laboratory (LLNL) aims at developing an advanced simulation environment at the exascale for a coupled assessment of earthquake hazard (ground motions) and earthquake risk (structural demands)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
NASA NTRSDate not supplied

Dragonfly Mission Entry and Descent Modeling and Simulation Overview

Dragonfly is a New Frontiers Program mission, led by The Johns Hopkins Applied Physics Laboratory, that will deliver a rotorcraft lander to Saturn’s moon, Titan. The focus of this work is to analyze the trajectory of the entry vehicle from cruise stage separation until lander separation. This analysis is done by the NASA Langley Research Center Entry, Descent, and Landing team using the Program to Optimize Trajectories II. This paper provides an overview of the current design and the robustness of the overall entry sequence using a Monte Carlo uncertainty analysis. The work presented in this study includes the updated design, models, and analysis completed since the Dragonfly Entry, Descent, and Landing Mission Preliminary Design Review.

Simulation↗
NASA NTRSDate not supplied

Dragonfly Mission Entry and Descent Modeling and Simulation Overview

Dragonfly is a New Frontiers Program mission, led by The Johns Hopkins Applied Physics Laboratory, that will deliver a rotorcraft lander to Saturn’s moon, Titan. The focus of this work is to analyze the trajectory of the entry vehicle from cruise stage separation until lander separation. This analysis is done by the NASA Langley Research Center Entry, Descent, and Landing team using the Program to Optimize Trajectories II. This paper provides an overview of the current design and the robustness of the overall entry sequence using a Monte Carlo uncertainty analysis. The work presented in this study includes the updated design, models, and analysis completed since the Dragonfly Entry, Descent, and Landing Mission Preliminary Design Review.

Simulation↗
DOE OSTI2019

Automating the Analysis of GHGRP Data Using Python, to Perform Temporal Analysis on Natural Gas Supply Chain Parameters - LCAXIX

This work was presented at the American Center for Life Cycle Assessment 2019 Conference (LCAXIX) in Tucson, AZ on September 24, 2019. Subpart W of the Environmental Protection Agency’s (EPA) Greenhouse Gas Reporting Program (GHGRP) consists of facility level greenhouse gas data for petroleum and natural gas systems that emit 25,000 metric tons or more of GHGs per year. Envirofacts is a tool that provides all publicly available data reported to GHGRP and it can be used to customize and download the data. This is one of the most granular datasets available that can be used to perform a detailed cradle-to-gate Life Cycle Analysis (LCA) of the United States natural gas supply chain. However, as robust as this data is, it is not available in a format that can be analyzed easily, and it is especially difficult to perform a temporal analysis on it. NETL's python script downloads all the .csv files for the desired reporting years from the subpart W of GHGRP.

Rai, Srijana↗