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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.15 User's Manual

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis (V.6.16 User's Manual)

The Dakota toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Glovebox CFD Analysis: Low-Flow, Laminar CFD Analysis of Glovebox Ventilation and Humidity Transport in Ansys Fluent 2025 R1

There are gloveboxes that frequently exceed the 30% relative humidity level required for operations. These exceedances result in alternative operations needing to be utilized. This report documents a computational fluid dynamics (CFD) analysis performed to characterize airflow and humidity transport within a representative glovebox under nominal, low-flow conditions. The analysis focuses on establishing the flow regime, identifying transport-limited regions, and evaluating the implications of laminar flow on humidity removal. A single-phase, laminar flow model with a species transport model was used to represent air and water vapor mixing. Results demonstrate that, at the nominal flow rates, airflow is laminar with weak mixing, which will result in long residence times, tens of minutes long or more, in low-velocity regions. These conclusions suggests that humidity reduction is transport-limited. This analysis provides qualitative insight into airflow structure and humidity transport trends. In addition to characterization of glovebox airflow and humidity transport, results are intended to inform experimental validation and future transient modeling efforts.

42 ENGINEERING↗
NASA NTRS1975

Mariner 10 mission analysis - Application of a black art

A major accomplishment of the mission analysis performed for Mariner 10 was the selection of a trajectory which optimized science return from the mission. The analysis utilized simple, unweighted 'science value functions' which allowed the relative values of each candidate trajectory, for each of the seven science experiments, to be calculated. A total relative value for each trajectory was determined by a simple averaging process and sensitivities were revealed by multiplying individual values. This showed a clear scientific preference for launching in early November and was used to support deferral of the launch from early October to November 3, 1973.

Shirley, D. L.↗
NASA NTRS1984

Configuration study for a 30 GHz monolithic receive array, volume 1

Gregorian, Cassegrain, and single reflector systems were analyzed in configuration studies for communications satellite receive antennas. Parametric design and performance curves were generated. A preliminary design of each reflector/feed system was derived including radiating elements, beam-former network, beamsteering system, and MMIC module architecture. Performance estimates and component requirements were developed for each design. A recommended design was selected for both the scanning beam and the fixed beam case. Detailed design and performance analysis results are presented for the selected Cassegrain configurations. The final design point is characterized in detail and performance measures evaluated in terms of gain, sidelobe level, noise figure, carrier-to-interference ratio, prime power, and beamsteering. The effects of mutual coupling and excitation errors (including phase and amplitude quantization errors) are evaluated. Mechanical assembly drawings are given for the final design point. Thermal design requirements are addressed in the mechanical design.

Nester, W. H.↗
NASA NTRS1986

Study of new systems concepts for a Titan atmospheric probe

Results of a systems concepts study for a Titan Probe were examined. The key tradeoffs performed are described in detail. Mass breakdown of each Probe subsystem or major element were given. The mission analysis performed to determine compliance with the high altitude sampling and descent time requirements are described. The baseline Descent Module design was derived. The element of the Probe System left on the Carrier after separation were described.

Bernard, Doug↗
NASA NTRS1987

A normal incidence X-ray telescope

The postflight performance evaluation of the X-ray telescope was summarized. All payload systems and subsystems performed well within acceptable limits, with the sole exception of the light-blocking prefilters. Launch, flight and recovery were performed in a fully satisfactory manner. The payload was recovered in a timely manner and in excellent condition. The prefilter performance analysis showed that no X-ray images were detected on the processed flight film. Recommendations for improved performance are listed.

Golub, Leon↗
NASA NTRS1996

Parallel Climate Data Assimilation PSAS Package

We have designed and implemented a set of highly efficient and highly scalable algorithms for an unstructured computational package, the PSAS data assimilation package, as demonstrated by detailed performance analysis of systematic runs on up to 512node Intel Paragon. The equation solver achieves a sustained 18 Gflops performance. As the results, we achieved an unprecedented 100-fold solution time reduction on the Intel Paragon parallel platform over the Cray C90. This not only meets and exceeds the DAO time requirements, but also significantly enlarges the window of exploration in climate data assimilations.

PSAS data scalable algorithms Intel Paragon 512nod↗
NASA NTRS2006

Numerical Propulsion System Simulation

The NASA Glenn Research Center, in partnership with the aerospace industry, other government agencies, and academia, is leading the effort to develop an advanced multidisciplinary analysis environment for aerospace propulsion systems called the Numerical Propulsion System Simulation (NPSS). NPSS is a framework for performing analysis of complex systems. The initial development of NPSS focused on the analysis and design of airbreathing aircraft engines, but the resulting NPSS framework may be applied to any system, for example: aerospace, rockets, hypersonics, power and propulsion, fuel cells, ground based power, and even human system modeling. NPSS provides increased flexibility for the user, which reduces the total development time and cost. It is currently being extended to support the NASA Aeronautics Research Mission Directorate Fundamental Aeronautics Program and the Advanced Virtual Engine Test Cell (AVETeC). NPSS focuses on the integration of multiple disciplines such as aerodynamics, structure, and heat transfer with numerical zooming on component codes. Zooming is the coupling of analyses at various levels of detail. NPSS development includes capabilities to facilitate collaborative engineering. The NPSS will provide improved tools to develop custom components and to use capability for zooming to higher fidelity codes, coupling to multidiscipline codes, transmitting secure data, and distributing simulations across different platforms. These powerful capabilities extend NPSS from a zero-dimensional simulation tool to a multi-fidelity, multidiscipline system-level simulation tool for the full development life cycle.

Naiman, Cynthia↗
NASA NTRSDate not supplied

Optimization of the 4-Bed CO2 Scrubber Performance Based on Ground Tests

Testing of ground hardware closely matching the flight design for the 4-Bed CO2Scrubber (4BCO2) has provided a wealth of information about the complex and highly coupled batch process. The 4BCO2 process is a Thermal and Vacuum Swing Adsorption (TVSA) cycle with recirculating flows. The ability to measure CO2concentration at intermediate points in this architecture is new to this ground test system and has revealed a better understanding of system performance and its dependence on system design, operational parameters, and boundary conditions. This paper will discuss a statistical analysis performed to identify significant correlations between performance factors and operational parameters. Using these new insights on the highly coupled system physics, means for improvements to system performance are proposed.

CO2 Removal↗
DOE OSTI2022

Use of Machine Learning on PMU Data for Transmission System Fault Analysis

Synchrophasor technology has been used for monitoring, control, and protection of bulk power system for over 10 years. Deployment of phasor measurement units (PMUs) in the USA power system has surpassed 3000 units installed in the transmission substations as stand-alone intelligent electronic devices (IEDs) or as a software add-on to other devices such as digital protective relays (DPRs) or digital fault recorders (DFRs). By now, thousands of terabytes of PMU data may have been captured and stored by various transmission system operators (TSOs) and independent system operators (ISOs). This creates an opportunity to deploy advanced machine learning (ML) techniques to detect and classify faults recorded by PMUs automatically to be used by the system operators for rapid, critical decision-making when manual analysis of the past or unfolding events is not feasible. In this paper we offer a brief background on how the automated fault analysis may be done using DPR and/or DFR data, and compare some of the legacy approaches to the new ML approaches in the context of the system-wide PMU recordings. We then offer insights from developing practical ML solutions that have been applied on field recordings captured by close to 450 PMUs from all three US interconnections (Western, Eastern and ERCOT) over two years (2016-2017). We identify and illustrate ML challenges we addressed: inaccurate data, data with scarce and temporally imprecise fault labels, data recorded by PMUs sparsely located at substations resulting in the fault records taken afar from the ends of the faulted lines, data containing only positive sequence values, and data taken at different voltage levels. We then illustrate the ML model results for fault analysis under different application scenarios. The novelty of this study is not only in the design, implementation, and performance analysis of the ML algorithms, but also in the use of advanced fault modelling and simulation approaches to improve the training results when developing supervised ML models for fault detection and classification. Extensive simulations of faults were conducted on a 14-bus power system to create a training dataset with over 1400 accurately labelled faults. This dataset was applied to enhance the accuracy of fault detection and classification of machine learning-based models trained with small number of labelled faults in large datasets recorded in the grid interconnections ranging from 5,000 to 70,000 buses.

Synchrophasors, Machine Learning, Fault Analysis, ↗
DOE OSTI2023

Experimental Characterization of Hydrocarbons and Nitrogen Oxides Production in a Heavy-Duty Diesel–Natural Gas Reactivity-Controlled Compression Ignition Engine

Reactivity-Controlled Compression Ignition (RCCI) combustion is considered one of the most promising Low-Temperature Combustion (LTC) concepts aimed at reducing greenhouse gases for the transportation and power generation sectors. Due to the spontaneous combustion of a lean, nearly homogeneous mixture of air and low-reactivity fuel (LRF), ignited through the direct injection of a small quantity of high-reactivity fuel (HRF), RCCI (dual-fuel) shows higher efficiency and lower pollutants compared to conventional diesel combustion (CDC) if run at very advanced injection timing. Even though a HRF is used, the use of advanced injection timing leads to high ignition delays, compared to CDC, and generates high cycle-to-cycle variability, limited operating range, and high pressure rise rates at high loads. This work presents an experimental analysis performed on a heavy-duty single-cylinder compression ignited engine in dual-fuel diesel–natural gas mode. The objective of the present work is to investigate and highlight the correlations between combustion behavior and pollutant emissions, especially unburned hydrocarbons (HC) and oxides of nitrogen (NOx). Based on the analysis of crank-resolved pollutants measurements performed through fast FID and fast NOx systems under different engine operating conditions, two correlations were found demonstrating a good accordance between pollutant production and combustion behavior: Net Cyclic Hydrocarbon emission—cyclic IMEP variations (R 2 = 0.86), and Cyclic NOx—maximum value of the Rate of Heat Released (R 2 = 0.82).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

KEPLER MISSION STELLAR AND INSTRUMENT NOISE PROPERTIES REVISITED

An earlier study of the Kepler Mission noise properties on timescales of primary relevance to detection of exoplanet transits found that higher than expected noise followed, to a large extent, from the stars rather than instrument or data analysis performance. The earlier study over the first six quarters of Kepler data is extended to the full four years ultimately comprising the mission. Efforts to improve the pipeline data analysis have been successful in reducing noise levels modestly as evidenced by smaller values derived from the current data products. The new analyses of noise properties on transit timescales show significant changes in the component attributed to instrument and data analysis, with essentially no change in the inferred stellar noise. We also extend the analyses to timescales of several days, instead of several hours to better sample stellar noise that follows from magnetic activity. On the longer timescale there is a shift in stellar noise for solar-type stars to smaller values in comparison to solar values.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2024

Use of Forecast Atmosphere for Earth Entry, Descent, and Landing Modeling

Flight mechanics simulations are used to characterize the performance of Earth entry, descent, and landing vehicles. Atmospheric prediction models are often a key component of these simulations. Global atmospheric models are used for both engineering design due to their ability to define atmospheric properties over a large swath of locations and times as well as used for the availability of atmospheric uncertainties in the models that can be used in statistical performance analysis. However for day-of-flight operations, the use of forecast atmospheres based on more current measurements are beneficial to the accuracy of the performance prediction, including landing locations. Reanalysis of these forecasts can also be used for post-flight analysis, including trajectory reconstruction. This paper describes how forecast atmospheres can be beneficial for Earth entry, descent, and landing analysis and ways these models can be implemented in simulations.

Soumyo Dutta↗
NASA NTRS2004

Evolutionary computing for the design search and optimization of space vehicle power subsystems

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.

power↗
NASA NTRS1989

An advanced probabilistic structural analysis method for implicit performance functions

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Wu, Y.-T.↗
NASA NTRSDate not supplied

SERFE Water Quality Results

NASA has been developing a new spacesuit, called the Exploration Extravehicular Mobility Unit (xEMU) for over a decade. This spacesuit is underdevelopment to support missions to the International Space Station (ISS) and also to the Moon. Improvements in the life and robustness of the Portable Life Support System (PLSS) has been a major objective of these efforts. Water quality, and how that impacts the performance of the life support system hardware, are areas where improvements could greatly help to achieve these goals. The Suit Water Membrane Evaporator (SWME) was chosen as the technology to provide cooling to the xEMU and has undergone several iterations of development over this period. An ISS flight experiment centered around the SWME and other thermal loop technologies was developed and has been under test in an ISS EXpedite PRocessing of Experiments to the Space Station (EXPRESS) rack since November of 2020. In addition to the SWME, The SWME EXPRESS Rack Flight Experiment (SERFE) contains several technology demonstrations from the xEMU project and has been demonstrating their performance in micro-gravity and over an extended duration. This paper will summarize the results of the water quality analysis performed to date throughout the SERFE testing program. Special care was taken to select materials, process hardware, and control the quality of the feedwater used in SERFE testing so that it would be representative of a thermal control system that could be used on a spacesuit for a lunar mission. In addition, the testing schedule, including periods of quiescence in between tests, was also selected to simulate a real mission profile in ways that would be critical to water quality. Results include data and analysis on microbial activity, biocidal iodine, metals, organic carbon, and several other customary indicators of water quality in an operational system. Testing spans over a year and a half of wetted life of the SERFE Flight Unit and the SERFE Ground Unit.

Colin Campbell↗