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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 181 records · Page 10

Telescience Resource Kit Software Lifecycle

The challenge of a global operations capability led to the Telescience Resource Kit (TReK) project, an in-house software development project of the Mission Operations Laboratory (MOL) at NASA's Marshall Space Flight Center (MSFC). The TReK system is being developed as an inexpensive comprehensive personal computer- (PC-) based ground support system that can be used by payload users from their home sites to interact with their payloads on board the International Space Station (ISS). The TReK project is currently using a combination of the spiral lifecycle model and the incremental lifecycle model. As with any software development project, there are four activities that can be very time consuming: Software design and development, project documentation, testing, and umbrella activities, such as quality assurance and configuration management. In order to produce a quality product, it is critical that each of these activities receive the appropriate amount of attention. For TReK, the challenge was to lay out a lifecycle and project plan that provides full support for these activities, is flexible, provides a way to deal with changing risks, can accommodate unknowns, and can respond to changes in the environment quickly. This paper will provide an overview of the TReK lifecycle, a description of the project's environment, and a general overview of project activities.

Griner, Carolyn S.↗

Aerosol Constraints from Multi-Angle Imaging That Modelers Can Use

As we continue to develop, refine, and apply the MISR aerosol products to a range of scientific questions, the strengths and limitations of the data content regarding aerosol optical depth (AOD), aerosol type, and plume height mapping have become pretty clear. Optimizing the operational algorithms to take advantage of the multi-angle, multi-spectral radiance information content is challenging in some situations, so we have also developed a number of specialized tools that run only on individual cases. These include the MISR Research Aerosol Retrieval algorithm, the highest-quality aerosol plume heights derived from the MINX software, and MISR-MODIS aerosol transport mapping code. This presentation will focus on some of the research products we are creating, with emphasis on those that might be most useful for constraining aerosol transport models, As we have acquired more than 11 years of once-weekly global coverage from MISR, discussion with the group will consider where and when having these products would maximize our contribution to AeroCom modeling efforts, in the context of practical limitations on specialized product generation.

Kahn, Ralph↗

Uncertainty Quantification in GADRAS Inverse Modeling

The Gamma Detector Response and Analysis Software (GADRAS) package includes an inverse modeling tool that is helpful in identifying characteristics of unknown radioactive materials. Traditionally, uncertainties in this analysis were derived solely from measurement data quality and the fit of synthetic spectra. This paper aims to rigorously quantify additional sources of uncertainty, focusing on uncertainties arising from measurements being analyzed, Detector Response Function (DRF) characterization, and DRF extrapolation. Applying these findings to the BeRPBall benchmark data set, we demonstrated the impact of these uncertainties on plutonium and polyethylene estimates. The results underscore the importance of incorporating diverse uncertainty sources to enhance the accuracy and reliability of GADRAS’s inverse modeling capabilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Design and Fabrication of DebriSat - A Representative LEO Satellite for Improvements to Standard Satellite Breakup Models

This paper discusses the design and fabrication of DebriSat, a 50 kg satellite developed to be representative of a modern low Earth orbit satellite in terms of its components, materials used, and fabrication procedures. DebriSat will be the target of a future hypervelocity impact experiment to determine the physical characteristics of debris generated after an on-orbit collision of a modern LEO satellite. The major ground-based satellite impact experiment used by DoD and NASA in their development of satellite breakup models was SOCIT, conducted in 1992. The target used for that experiment was a Navy transit satellite (~40 cm, 35 kg) fabricated in the 1960's. Modern satellites are very different in materials and construction techniques than those built 40 years ago. Therefore, there is a need to conduct a similar experiment using a modern target satellite to improve the fidelity of the satellite breakup models. To ensure that DebriSat is truly representative of typical LEO missions, a comprehensive study of historical LEO satellite designs and missions within the past 15 years for satellites ranging from 1 kg to 5000 kg was conducted. This study identified modern trends in hardware, material, and construction practices utilized in recent LEO missions. Although DebriSat is an engineering model, specific attention is placed on the quality, type, and quantity of the materials used in its fabrication to ensure the integrity of the outcome. With the exception of software, all other aspects of the satellite s design, fabrication, and assembly integration and testing will be as rigorous as that of an actual flight vehicle. For example, to simulate survivability of launch loads, DebriSat will be subjected to a vibration test. As well, the satellite will undergo thermal vacuum tests to verify that the components and overall systems meet typical environmental standards. Proper assembly and integration techniques will involve comprehensive joint analysis, including the precise torqueing of fasteners and thread locking. Finally, the implementation of process documentation and verification procedures is discussed to provide a comprehensive overview of the design and fabrication of this representative LEO satellite.

Clark, S.↗

Microwave Cavity Simulation Using Ansys HFSS

The design of microwave cavity detectors for axion dark matter research is often accomplished using advanced full-wave electromagnetic simulation software tools. These tools provide a cost-effective approach to evaluate a wide variety of cavity configurations, frequency tuning mechanisms, and conductive or dielectric materials and coatings. One simulation software package used for this application is Ansys High Frequency Structure Simulator (HFSS), which is based upon the well-established finite element method. HFSS includes numerous features useful for microwave cavity design such as parametric geometry modeling, adaptive meshing algorithm, curvilinear mesh elements, driven modal and eigenmode matrix solvers, and optimization algorithms. This paper describes the use of the HFSS software to simulate microwave cavities for axion haloscope detectors, with an example tutorial for a cylindrical cavity. Excellent agreement between the simulated and analytical results is shown for the resonant frequency, quality factor, and form factor.

Ansys HFSS, Cavity simulation, finite element mode↗

Modeling and Grid Generation of Iced Airfoils

SmaggIce Version 2.0 is a software toolkit for geometric modeling and grid generation for two-dimensional, singleand multi-element, clean and iced airfoils. A previous version of SmaggIce was described in Preparing and Analyzing Iced Airfoils, NASA Tech Briefs, Vol. 28, No. 8 (August 2004), page 32. To recapitulate: Ice shapes make it difficult to generate quality grids around airfoils, yet these grids are essential for predicting ice-induced complex flow. This software efficiently creates high-quality structured grids with tools that are uniquely tailored for various ice shapes. SmaggIce Version 2.0 significantly enhances the previous version primarily by adding the capability to generate grids for multi-element airfoils. This version of the software is an important step in streamlining the aeronautical analysis of ice airfoils using computational fluid dynamics (CFD) tools. The user may prepare the ice shape, define the flow domain, decompose it into blocks, generate grids, modify/divide/merge blocks, and control grid density and smoothness. All these steps may be performed efficiently even for the difficult glaze and rime ice shapes. Providing the means to generate highly controlled grids near rough ice, the software includes the creation of a wrap-around block (called the "viscous sublayer block"), which is a thin, C-type block around the wake line and iced airfoil. For multi-element airfoils, the software makes use of grids that wrap around and fill in the areas between the viscous sub-layer blocks for all elements that make up the airfoil. A scripting feature records the history of interactive steps, which can be edited and replayed later to produce other grids. Using this version of SmaggIce, ice shape handling and grid generation can become a practical engineering process, rather than a laborious research effort.

Vickerman, Mary B.↗

PIPES (Pipeline for Integrated Projects in Energy Systems) [SWR-24-89]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. https://github.com/nrel-pipes/pipes-api https://github.com/nrel-pipes/pipes-web https://github.com/nrel-pipes/nrel-pipes

Gu, Jianli↗

Pipeline for Integrated Projects in Energy Systems (PIPES): A Tool for Integrated System Planning [Slides]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. This presentation introduces PIPES a multi-model tool for integrated system planning; it describes the underlying architecture, deep dives into common user workflows, and outlines the upcoming development roadmap beyond its current alpha state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Lunar Mapping and Modeling Project Update

The Lunar Mapping and Modeling Project (LMMP) is managing the development of a suite of lunar mapping and modeling tools and data products that support lunar exploration activities, including the planning, design, development, test, and operations associated with crewed and/or robotic operations on the lunar surface. In addition, LMMP should prove to be a convenient and useful tool for scientific analysis and for education and public outreach (E/PO) activities. LMMP will utilize data predominately from the Lunar Reconnaissance Orbiter, but also historical and international lunar mission data (e.g. Lunar Prospector, Clementine, Apollo, Lunar Orbiter, Kaguya, and Chandrayaan-1) as available and appropriate. LMMP will provide such products as image mosaics, DEMs, hazard assessment maps, temperature maps, lighting maps and models, gravity models, and resource maps. We are working closely with the LRO team to prevent duplication of efforts and ensure the highest quality data products. A beta version of the LMMP software was released for limited distribution in December 2009, with the public release of version 1 expected in the Fall of 2010.

Noble, S.↗

Automated Credibility Assessments of User Features in Scientific Software

Scientific software (SciSoft) is complex, often containing a mixture of production capabilities co-mingled with features under active research and development. Furthermore, SciSoft is often developed over decades by non-computer scientists who may not have a strong background in or prioritize software architecture design, testing, and quality (e.g., test coverage). These conditions lead to difficulty in understanding which software components or functions implement what user-facing features and therefore those features’ software quality pedigree. This lack of understanding poses challenges in assessing readiness and credibility of user features, and often relies on a SciSoft subject matter expert’s (SME) laborious investigation and assertion. This final report of a one-year Computing and Information Sciences Lab Directed Research and Development project presents a general framework for modeling SciSoft architecture as a direct relationship between user features and the software components/functions that implement them. Our approach leverages automated labeling of the SciSoft’s regression test suite and employs machine learning algorithms to construct the architecture model. We demonstrate this framework on the Solid Mechanics component of the SIERRA multi-physics engineering analysis suite developed at Sandia National Laboratories.

97 MATHEMATICS AND COMPUTING↗

Software Quality Assurance for the MOOSE-Based Open-Source Multiphysics Code Cardinal - An Expanded CI Testing Suite

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing and, maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program has been initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as a safety analysis tool. These gaps have been captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents a snapshot of the verification test cases currently available for Cardinal and NekRS in their assimilation into a Continuous Integration (CI) platform. Following the CI practice permits the integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. It should be noted that the SQA program itself, including the program plans, procedures, configuration management, and testing strategies, need to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Model Quality and Measurement Density Impact on Volt/Volt Ampere Reactive Optimization Performance

The operation of the utility grid is being reshaped by the continuous addition of distributed energy resources and advanced metering infrastructure, which challenge existing grid control strategies. Some utilities deploy advanced distribution management systems (ADMS) to assist with the consolidation of various applications and to augment situational awareness in response to the new power delivery dynamics. An ADMS is an integrated software platform that provides utilities with a way to enhance their reliability, control, and optimization with advanced applications, such as volt/VAR optimization (VVO). A VVO application could serve as a vehicle to deliver cost savings by providing the utility with a method to reduce rates by controlling the voltage and decreasing the energy usage in their service territory. Some utilities are reluctant to integrate an ADMS, because it is a significant investment that requires approval from the public regulatory commission and/or their customers. This paper evaluates the impact on VVO performance when using a lower-quality network model supplemented with additional measurements, which could provide an implementation for cost savings. The results show that a better model quality would provide the highest energy savings; however, some level of telemetry is necessary in all scenarios to prevent voltage exceedances.

24 POWER TRANSMISSION AND DISTRIBUTION↗

FENIX: An Open-Source Multiphysics Integrated Framework Enabling Collaborative Development of Plasma Facing Component Modeling Capabilities

Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Distributed synthetic aperture radar simulation

Synthetic aperture radar (SAR) depends primarily on attainable frequency resolution rather than on large physical size of the antenna array. The distributed architecture concept (DSAR) incorporates active elements (amplifiers) at or near the elemental radiators of the array. Since SAR's are expensive to build and expensive to test, a computer modeling approach is a feasible method of predicting the quality or nature of the SAR image from the proposed system parameters. The goal of this project is to produce a DSAR simulation software package. This report describes the progress made thus far and the work which remains to be done. Extensive work on this project had been done previously by two NASA contractors. The principal task remaining involved the creation of a suitable interface between these programs and the hardware and software available at the Johnson Space Center.

Bourgeois, B. A.↗

Co-registration of Laser Altimeter Tracks with Digital Terrain Models and Applications in Planetary Science

We have derived algorithms and techniques to precisely co-register laser altimeter profiles with gridded Digital Terrain Models (DTMs), typically derived from stereo images. The algorithm consists of an initial grid search followed by a least-squares matching and yields the translation parameters at sub-pixel level needed to align the DTM and the laser profiles in 3D space. This software tool was primarily developed and tested for co-registration of laser profiles from the Lunar Orbiter Laser Altimeter (LOLA) with DTMs derived from the Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) stereo images. Data sets can be co-registered with positional accuracy between 0.13 m and several meters depending on the pixel resolution and amount of laser shots, where rough surfaces typically result in more accurate co-registrations. Residual heights of the data sets are as small as 0.18 m. The software can be used to identify instrument misalignment, orbit errors, pointing jitter, or problems associated with reference frames being used. Also, assessments of DTM effective resolutions can be obtained. From the correct position between the two data sets, comparisons of surface morphology and roughness can be made at laser footprint- or DTM pixel-level. The precise co-registration allows us to carry out joint analysis of the data sets and ultimately to derive merged high-quality data products. Examples of matching other planetary data sets, like LOLA with LRO Wide Angle Camera (WAC) DTMs or Mars Orbiter Laser Altimeter (MOLA) with stereo models from the High Resolution Stereo Camera (HRSC) as well as Mercury Laser Altimeter (MLA) with Mercury Dual Imaging System (MDIS) are shown to demonstrate the broad science applications of the software tool.

Laser↗

DECIDER

This software offers methods and functions for building failure detectors for deep image classification models with the aid of vision-language models and LLMs. It includes functionalities for training baseline image classifiers, debiasing classifiers using vision-language models and LLMs, evaluating failure between models along with baselines. Developed using PyTorch, this software is compatible with standard neural network architectures used for imaging data. Additionally, it provides capabilities to compute evaluation metrics for assessing the performance and quality of the detectors.

Narayanaswamy, Vivek Sivaraman↗

Application of Domain Knowledge to Software Quality Assurance

This work focused on capturing, using, and evolving a qualitative decision support structure across the life cycle of a project. The particular application of this study was towards business process reengineering and the representation of the business process in a set of Business Rules (BR). In this work, we defined a decision model which captured the qualitative decision deliberation process. It represented arguments both for and against proposed alternatives to a problem. It was felt that the subjective nature of many critical business policy decisions required a qualitative modeling approach similar to that of Lee and Mylopoulos. While previous work was limited almost exclusively to the decision capture phase, which occurs early in the project life cycle, we investigated the use of such a model during the later stages as well. One of our significant developments was the use of the decision model during the operational phase of a project. By operational phase, we mean the phase in which the system or set of policies which were earlier decided are deployed and put into practice. By making the decision model available to operational decision makers, they would have access to the arguments pro and con for a variety of actions and can thus make a more informed decision which balances the often conflicting criteria by which the value of action is measured. We also developed the concept of a 'monitored decision' in which metrics of performance were identified during the decision making process and used to evaluate the quality of that decision. It is important to monitor those decision which seem at highest risk of not meeting their stated objectives. Operational decisions are also potentially high risk decisions. Finally, we investigated the use of performance metrics for monitored decisions and audit logs of operational decisions in order to feed an evolutionary phase of the the life cycle. During evolution, decisions are revisisted, assumptions verified or refuted, and possible reassessments resulting in new policy are made. In this regard we implemented a machine learning algorithm which automatically defined business rules based on expert assessment of the quality of operational decisions as recorded during deployment.

Wild, Christian W.↗

Data assimilation and model evaluation experiment datasets

The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

Lai, Chung-Cheng A.↗