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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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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Quantifying Mapping Orbit Performance in the Vicinity of Primitive Bodies

Predicting and quantifying the capability of mapping orbits in the vicinity of primitive bodies is challenging given the complex orbit geometries that exist and the irregular shape of the bodies themselves. This paper employs various quantitative metrics to characterize the performance and relative effectiveness of various types of mapping orbits including terminator, quasi-terminator, hovering, ping pong, and conic-like trajectories. Metrics of interest include surface area coverage, lighting conditions, and the variety of viewing angles achieved. The metrics discussed in this investigation are intended to enable mission designers and project stakeholders to better characterize candidate mapping orbits during preliminary mission formulation activities. The goal of this investigation is to understand the trade space associated with carrying out remote sensing campaigns at small primitive bodies in the context of a robotic space mission. Specifically, this study seeks to understand the surface viewing geometries, ranges, etc. that are available from several commonly proposed mapping orbits architectures

Pavlak, Thomas A.↗
NASA NTRS1990

Pragmatic quality metrics for evolutionary software development models

Due to the large number of product, project, and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability, or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently. The usefulness of these metrics is evaluated by applying them to a large, real world, Ada project.

Royce, Walker↗
NASA NTRSDate not supplied

Verification of Viscous Goal-Based Anisotropic Mesh Adaptation

Adaptive unstructured mesh techniques have a limited, but growing impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, anisotropic metric construction methods, and anisotropic mesh adaptation mechanics. A key ingredient for the broader acceptance of unstructured mesh adaptation is the verification of these implementations. Anisotropic metric construction methods are evaluated with analytically defined primal fields and the corresponding entropy variables as adjoint fields. This allows the comparison of different metric formulations and different implementations of the same formulation without the complications of a flow and adjoint solution method. The convergence of the output associated with the entropy variable adjoint is studied for mesh adaptation to these fields and a manufactured solution. Mesh adapted drag output is studied for two simple wings in compressible laminar flow to show fine-mesh convergence of multiple metric construction methods to less than a single drag count. The documentation of these verification exercises helps to prepare these goal-based methods for routine use in more complex simulations for production workflows.

mesh adaptation↗
DOE OSTI2026

A flexible and differentiable coil proxy for stellarator equilibrium optimization

Balancing plasma performance and coil cost is a significant challenge when designing a stellarator power plant. Most current stellarator designs are produced through two-stage optimization: stage-1 for the equilibrium and stage-2 for a coil design that reproduces its magnetic configuration. Because few proxies connect both stages, two-stage optimization can produce plasmas that have high-quality physical properties but overly complex coils. In recent years, single-stage optimization has increasingly been used to optimize the plasma and coils simultaneously in order to improve the plasma–coil balance. However, all existing single-stage tools are specialized for filament coils, cannot model coil systems containing permanent magnets or dipole arrays, and continue to be challenged by numerical problems. The quasi-single-stage optimization finds a middle ground by integrating a coil optimization subproblem into stage-1 optimization. We present a flexible, differentiable coil complexity proxy based on the newly developed QUADCOIL coil optimization code. QUADCOIL is fast and can target realistic coil metrics and constraints that are unavailable to codes with comparable speed. We demonstrate the effectiveness and flexibility of the QUADCOIL proxy by presenting two QSS optimization studies. The first study produces a permanent magnet solution for the MUSE stellarator with 34% fewer magnets than previous solutions. The second study produces a coil solution for the ARIES-CS stellarator with 30% reductions in both peak and root-mean-square force.

Fu, Lanke [Princeton Plasma Physics Laboratory (PP↗
DOE OSTI2022

Wabash CarbonSAFE Static and Dynamic Modeling: Task 9.0 (Technical Report)

The objective of the Wabash CarbonSAFE project’s static and dynamic modeling task is to assess the feasibility of storing 50 million tonnes (1.67 million metric tonnes annually; MMTA) of industrially-sourced carbon dioxide (CO 2 ) in a commercial-scale geological storage complex at Wabash Valley Resources LLC (WVR) gasification facility near Terre Haute, Indiana over a period of 30 years. The targeted formations for storing CO 2 are: 1) Mt. Simon Sandstone (MSS) and the 2) Potosi Dolomite (Knox Group). All of the available data from the recently drilled Wabash #1 stratigraphic test well (now plugged and abandoned) were used in the construction of both the static and dynamic models. Geologic models were constructed to characterize both the Mt. Simon Sandstone and Potosi Dolomite storage complexes. Dynamic simulation models were constructed and used to assess the feasibility of injecting CO 2 into the Mt. Simon and Potosi formations. The geocellular models for the Potosi Dolomite and Mt. Simon Sandstone were built using Petrel™, Schlumberger’s reservoir modeling software. The dynamic simulations were run using Landmark’s Nexus ® reservoir simulation software.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Freeform thermoelectrics in single-step manufacturing: additive manufacturing of bismuth-telluride thermoelectrics

The project succeeded in producing crack-free Bismuth Telluride thermoelectric parts with density exceeding 98% through laser powder bed fusion (LPBF) additive manufacturing (AM). This greatly exceeded the highest previously reported density of 88% and is the highest among all semiconducting materials processed by LPBF. The additively manufactured material shows comparable Seebeck coefficient as conventional form and can be made into complex geometries with reduced material loss. On the other hand, measured properties are dramatically sensitive to the AM process parameters used, such that with identical composition, the Seebeck coefficient can be controllably tuned from +120 µV/K to -207 µV/K, which means the material switches between an n-type to a p-type semiconductor depending on processing. These changes are accompanied by significant differences in the as-processed microstructure due to rapid solidification. A machine learning protocol was developed and greatly reduced the experimental burden of the project, reducing the typical process optimization period of 2 years to 6 months. The project was fully successful in the objective of producing defect-free, complex geometry of bismuth-telluride parts through LPBF, but only partially successful in achieving performance goals. First, cost reduction of manufacturing, as measured by material waste, was successfully reduced by up to 70% compared to conventional manufacturing methods. This exceeded the proposed 30% reduction in materials waste needed to reach the 20% cost reduction goal of the project. On the other hand, the device performance, as measured by Seebeck coefficient, failed to reach the 40% improvement in efficiency. Rather, we observe comparable Seebeck coefficient between AM samples and conventionally processed counterparts. The device-level efficiency improvement does exceed 40% for complex geometry samples due to shape-induced increase in temperature gradients, but this was not the originally proposed metric. The machine learning approach developed in this project greatly accelerated the process optimization and can be adopted for fast development of AM processing parameters for other brittle and otherwise difficult-to-print materials. For the public, we deliver an efficient and widely adoptable process for incorporating waste-heat harvesting thermoelectric devices in both industrial and commercial heat exchangers. The geometric flexibility allows the capturing device to conform to the shape of the heat source to improve the system-level conversion efficiency. The technique can be deployed on any commercial LBPF systems with zero modifications, thus poses minimal adoption barrier for any manufacturer that already employed AM technology. Beyond bismuth-telluride, the machine-learning guided optimization protocol can be used in the future to reduce both the time and cost of process development for AM of other energy conversion and harvesting materials.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Space Station Facility government estimating

This new, unique Cost Engineering Report introduces the 800-page, C-100 government estimate for the Space Station Processing Facility (SSPF) and Volume IV Aerospace Construction Price Book. At the January 23, 1991, bid opening for the SSPF, the government cost estimate was right on target. Metric, Inc., Prime Contractor, low bid was 1.2 percent below the government estimate. This project contains many different and complex systems. Volume IV is a summary of the cost associated with construction, activation and Ground Support Equipment (GSE) design, estimating, fabrication, installation, testing, termination, and verification of this project. Included are 13 reasons the government estimate was so accurate; abstract of bids, for 8 bidders and government estimate with additive alternates, special labor and materials, budget comparison and system summaries; and comments on the energy credit from local electrical utility. This report adds another project to our continuing study of 'How Does the Low Bidder Get Low and Make Money?' which was started in 1967, and first published in the 1973 AACE Transaction with 18 ways the low bidders get low. The accuracy of this estimate proves the benefits of our Kennedy Space Center (KSC) teamwork efforts and KSC Cost Engineer Tools which are contributing toward our goals of the Space Station.

Brown, Joseph A.↗
NASA NTRS1993

Estimating and bidding for the Space Station Processing Facility

This new, unique Cost Engineering Report introduces the 800-page, C-100 government estimate for the Space Station Processing Facility (SSPF) and Volume IV Aerospace Construction Price Book. At the January 23, 1991, bid opening for the SSPF, the government cost estimate was right on target. Metric, Inc., Prime Contractor, low bid was 1.2 percent below the government estimate. This project contains many different and complex systems. Volume IV is a summary of the cost associated with construction, activation and Ground Support Equipment (GSE) design, estimating, fabrication, installation, testing, termination, and verification of this project. Included are 13 reasons the government estimate was so accurate; abstract of bids, for 8 bidders and government estimate with additive alternates, special labor and materials, budget comparison and system summaries; and comments on the energy credit from local electrical utility. This report adds another project to our continuing study of 'How Does the Low Bidder Get Low and Make Money?' which was started in 1967, and first published in the 1973 AACE Transaction with 10 more ways the low bidder got low. The accuracy of this estimate proves the benefits of our Kennedy Space Center (KSC) teamwork efforts and KSC Cost Engineer Tools which are contributing toward our goals of the Space Station.

Brown, Joseph A.↗
NASA NTRS2004

Autonomous Multi-Sensor Coordination: The Science Goal Monitor

Many dramatic earth phenomena are dynamic and coupled. In order to fully understand them, we need to obtain timely coordinated multi-sensor observations from widely dispersed instruments. Such a dynamic observing system must include the ability to Schedule flexibly and react autonomously to sciencehser driven events; Understand higher-level goals of a sciencehser defined campaign; Coordinate various space-based and ground-based resources/sensors effectively and efficiently to achieve goals. In order to capture transient events, such a 'sensor web' system must have an automated reactive capability built into its scientific operations. To do this, we must overcome a number of challenges inherent in infusing autonomy. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe dynamic phenomena. The SGM system enables users to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of data to identify occurrences of the key events previously specified by the scientisther. When an event occurs, the system autonomously coordinates the execution of the users' desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems' Aqua/Terra spacecrafts' MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM was used to investigate forest fires, floods and volcanic eruptions. We are now identifying new Earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗
NASA NTRS2004

Autonomous Multi-sensor Coordination: The Science Goal Monitor

Next-generation science and exploration systems will employ new observation strategies that will use multiple sensors in a dynamic environment to provide high quality monitoring, self-consistent analyses and informed decision making. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing of earth phenomenon. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe the dynamic phenomena. The SGM system enables users to specify events of interest and how to react when an event is detected. The system monitors streams of data to identify occurrences of the key events previously specified by the scientist/user. When an event occurs, the system autonomously coordinates the execution of the users desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems Aqua/Terra spacecrafts MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM is being used to investigate forest fires, floods and volcanic eruptions. We are now identifying new earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗
NASA NTRS2005

Reliability-Based Control Design for Uncertain Systems

This paper presents a robust control design methodology for systems with probabilistic parametric uncertainty. Control design is carried out by solving a reliability-based multi-objective optimization problem where the probability of violating design requirements is minimized. Simultaneously, failure domains are optimally enlarged to enable global improvements in the closed-loop performance. To enable an efficient numerical implementation, a hybrid approach for estimating reliability metrics is developed. This approach, which integrates deterministic sampling and asymptotic approximations, greatly reduces the numerical burden associated with complex probabilistic computations without compromising the accuracy of the results. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.

Crespo, Luis G.↗
NASA NTRS2017

Information Theoretic Evaluation of Satellite Soil Moisture Retrievals

Microwave radiometry has a long legacy of providing estimates of remotely sensed near surfacesoil moisture measurements over continental and global scales. A consistent assessment of theerrors and uncertainties associated with these retrievals is important for their effective utilization in modeling, data assimilation and end-use application environments. This article presents an evaluationof soil moisture retrieval products from AMSR-E, ASCAT, SMOS, AMSR2 and SMAPinstruments using information theory-based metrics. These metrics rely on time series analysis ofsoil moisture retrievals for estimating the measurement error, level of randomness (entropy) andregularity (complexity) of the data. The results of the study indicate that the measurement errors inthe remote sensing retrievals are significantly larger than that of the ground soil moisture measurements.The SMAP retrievals, on the other hand, were found to have reduced errors (comparable to Preprint submitted to Remote Sensing of Environment October 1, 2017those of in-situ datasets), particularly over areas with moderate vegetation. The SMAP retrievals also demonstrate high information content relative to other retrieval products, with higher levelsof complexity and reduced entropy. Finally, a joint evaluation of the entropy and complexity ofremotely sensed soil moisture products indicates that the information content of the AMSR-E, ASCAT,SMOS and AMSR2 retrievals is low, whereas SMAP retrievals show better performance. The use of information theoretic assessments is effective in quantifying the required levels of improvements needed in the remote sensing soil moisture retrievals to enhance their utility and information content.

Information theory↗
NASA NTRSDate not supplied

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗
DOE OSTI2026

A Guide to Nonaqueous Electrochemistry of f-Element Complexes

Electrochemistry is a powerful tool for assessing and understanding the redox chemistry of molecular complexes. Cyclic voltammetry enables the f-element community to study molecules in unusually high or low oxidation states, which potentially pose important broad-scope questions of electronic structure. In the pursuit of boundary-pushing compounds, reactive air- and moisture-sensitive species are often encountered, which can be challenging to characterize, especially when they are chemically incompatible with certain solvents, electrolytes, or electrodes or when their potentials lie outside of common electrochemical windows. Nonaqueous solvents and pseudo reference electrodes complicate many of the standard practices in acquiring high-quality and reproducible electrochemical data. This guide presents a detailed discussion of selecting appropriate cell conditions and referencing and addresses metrics for evaluating electrochemical and chemical reversibility. These methodological approaches have been extended to best practices for the electrochemical analysis of radioactive transuranic complexes.

Electrodes↗
NASA NTRS2019

Evaluation of Classifier Complexity for Delay Tolerant Network Routing

The growing popularity of small cost effective satellites (SmallSats, CubeSats, etc.) creates the potential for a variety of new science applications involving multiple nodes functioning together or independently to achieve a task, such as swarms and constellations. As this technology develops and is deployed for missions in Low Earth Orbit and beyond, the use of delay tolerant networking (DTN) techniques may improve communication capabilities within the network. In this paper, a network hierarchy is developed from heterogeneous networks of SmallSats, surface vehicles, relay satellites and ground stations which form an integrated network. There is a tradeoff between complexity, flexibility, and scalability of user defined schedules versus autonomous routing as the number of nodes in the network increases. To address these issues, this work proposes a machine learning classifier based on DTN routing metrics. A framework is developed which will allow for the use of several categories of machine learning algorithms (decision tree, random forest and deep learning) to be applied to a dataset of historical network statistics, which allows for the evaluation of algorithm complexity versus performance to be explored. We develop the emulation of a hierarchical network, consisting of tens of nodes which form a cognitive network architecture. CORE (Common Open Research Emulator) is used to emulate the network using bundle protocol and DTN IP neighbor discovery.

Dudukovich, Rachel↗
NASA NTRS1992

The role of metrics and measurements in a software intensive total quality management environment

Paramax Space Systems began its mission as a member of the Rockwell Space Operations Company (RSOC) team which was the successful bidder on a massive operations consolidation contract for the Mission Operations Directorate (MOD) at JSC. The contract awarded to the team was the Space Transportation System Operations Contract (STSOC). Our initial challenge was to accept responsibility for a very large, highly complex and fragmented collection of software from eleven different contractors and transform it into a coherent, operational baseline. Concurrently, we had to integrate a diverse group of people from eleven different companies into a single, cohesive team. Paramax executives recognized the absolute necessity to develop a business culture based on the concept of employee involvement to execute and improve the complex process of our new environment. Our executives clearly understood that management needed to set the example and lead the way to quality improvement. The total quality management policy and the metrics used in this endeavor are presented.

Daniels, Charles B.↗
NASA NTRS2012

Prediction of Traffic Complexity and Controller Workload in Mixed Equipage NextGen Environments

Controller workload is a key factor in limiting en route air traffic capacity. Past efforts to quantify and predict workload have resulted in identifying objective metrics that correlate well with subjective workload ratings during current air traffic control operations. Although these metrics provide a reasonable statistical fit to existing data, they do not provide a good mechanism for estimating controller workload for future air traffic concepts and environments that make different assumptions about automation, enabling technologies, and controller tasks. One such future environment is characterized by en route airspace with a mixture of aircraft equipped with and without Data Communications (Data Comm). In this environment, aircraft with Data Comm will impact controller workload less than aircraft requiring voice communication, altering the close correlation between aircraft count and controller workload that exists in current air traffic operations. This paper outlines a new trajectory-based complexity (TBX) calculation that was presented to controllers during a human-in-the-loop simulation. The results showed that TBX accurately estimated the workload in a mixed Data Comm equipage environment and the resulting complexity values were understood and readily interpreted by the controllers. The complexity was represented as a "modified aircraft account" that weighted different complexity factors and summed them in such a way that the controllers could effectively treat them as aircraft count. The factors were also relatively easy to tune without an extensive data set. The results showed that the TBX approach is well suited for presenting traffic complexity in future air traffic environments.

Lee, Paul U.↗
DOE OSTI2024

Accessing bands with extended quantum metric in kagome Cs 2 Ni 3 S 4 through soft chemical processing

Flat bands that do not merely arise from weak interactions can produce exotic physical properties, such as superconductivity or correlated many-body effects. The quantum metric can differentiate whether flat bands will result in correlated physics or are merely dangling bonds. A potential avenue for achieving correlated flat bands involves leveraging geometrical constraints within specific lattice structures, such as the kagome lattice; however, materials are often more complex. In these cases, quantum geometry becomes a powerful indicator of the nature of bands with small dispersions. We present a simple, soft-chemical processing route to access a flat band with an extended quantum metric below the Fermi level. By oxidizing Ni-kagome material Cs 2 Ni 3 S 4 to CsNi 3 S 4 , we see a two orders of magnitude drop in the room temperature resistance. However, CsNi 3 S 4 is still insulating, with no evidence of a phase transition. Using experimental data, density functional theory calculations, and symmetry analysis, our results suggest the emergence of a correlated insulating state of unknown origin.

Science & Technology - Other Topics↗