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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Studies of the structure of the plasmasphere as seen by radiosounder measurements aboard the Alovetti-satellite

The structure of the plasmasphere was studied as seen by radiosounder measurements aboard the Alovetti-2 satellite. Magnetic tape data files were obtained from the NASA Ames Research Center to give a reasonably complete set of high latitude electron density profiles. Considerable effort was expended to develop models of ion flow in the topside ionosphere. These models took both H(+) and O(+) into account and permitted various parameter studies to be made of the various factors which affect H(+) escape in polar wind flows. The results of these studies are included. Extensive computer programs were written to display the measured electron density profiles in ways useful to geophysical analysis. The expected mid-latitude trough was easily discernable in the nightime ionosphere at locations expected from similar observations of the plasmapause. In the dayside ionosphere, however, it proved extremely difficult to find any trough-like phenomena. Using the previously developed computer models, it was possible to study the region where the plasmapause appeared to be absent. It was found that over much of the dayside, large fluxes were computed well inside the plasmapause extending down to L-shells as low as 2.5.

Banks, P. M.↗
NASA NTRS2013

No Vent Tank Fill and Transfer Line Chilldown Analysis by Generalized Fluid System Simulation Program (GFSSP)

The purpose of the paper is to present the analytical capability developed to model no vent chill and fill of cryogenic tank to support CPST (Cryogenic Propellant Storage and Transfer) program. Generalized Fluid System Simulation Program (GFSSP) was adapted to simulate charge‐holdvent method of Tank Chilldown. GFSSP models were developed to simulate chilldown of LH2 tank in K‐site Test Facility and numerical predictions were compared with test data. The report also describes the modeling technique of simulating the chilldown of a cryogenic transfer line and GFSSP models were developed to simulate the chilldown of a long transfer line and compared with test data.

Majumdar, Alok↗
NASA NTRS1977

New model framework and structure and the commonality evaluation model

The development of a framework and structure for shuttle era unmanned spacecraft projects and the development of a commonality evaluation model is documented. The methodology developed for model utilization in performing cost trades and comparative evaluations for commonality studies is discussed. The model framework consists of categories of activities associated with the spacecraft system's development process. The model structure describes the physical elements to be treated as separate identifiable entities. Cost estimating relationships for subsystem and program-level components were calculated.

Source record↗
DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

SAGE Intrusion Detection System: Sensitivity Analysis Guided Explainability for Machine Learning.

This report details the results of a three-fold investigation of sensitivity analysis (SA) for machine learning (ML) explainability (MLE): (1) the mathematical assessment of the fidelity of an explanation with respect to a learned ML model, (2) quantifying the trustworthiness of a prediction, and (3) the impact of MLE on the efficiency of end-users through multiple users studies. We focused on the cybersecurity domain as the data is inherently non-intuitive. As ML is being using in an increasing number of domains, including domains where being wrong can elicit high consequences, MLE has been proposed as a means of generating trust in a learned ML models by end users. However, little analysis has been performed to determine if the explanations accurately represent the target model and they themselves should be trusted beyond subjective inspection. Current state-of-the-art MLE techniques only provide a list of important features based on heuristic measures and/or make certain assumptions about the data and the model which are not representative of the real-world data and models. Further, most are designed without considering the usefulness by an end-user in a broader context. To address these issues, we present a notion of explanation fidelity based on Shapley values from cooperative game theory. We find that all of the investigated MLE explainability methods produce explanations that are incongruent with the ML model that is being explained. This is because they make critical assumptions about feature independence and linear feature interactions for computational reasons. We also find that in deployed, explanations are rarely used due to a variety of reason including that there are several other tools which are trusted more than the explanations and there is little incentive to use the explanations. In the cases when the explanations are used, we found that there is the danger that explanations persuade the end users to wrongly accept false positives and false negatives. However, ML model developers and maintainers find the explanations more useful to help ensure that the ML model does not have obvious biases. In light of these findings, we suggest a number of future directions including developing MLE methods that directly model non-linear model interactions and including design principles that take into account the usefulness of explanations to the end user. We also augment explanations with a set of trustworthiness measures that measure geometric aspects of the data to determine if the model output should be trusted.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Development of global model for atmospheric backscatter at CO2 wavelengths

The improvement of an understanding of the variation of the aerosol backscattering at 10.6 micron within the free troposphere and the development model to describe this was undertaken. The analysis combines theoretical modeling with the results contained within three independent data sets. The data sets are obtained by the SAGE I/SAM II satellite experiments, the GAMETAG flight series and by direct backscatter measurements. The theoretical work includes use of a bimodal, two component aerosol model, and the study of the microphysical and associated optical changes occurring within an aerosol plume. A consistent picture is obtained, which describes the variation of the aerosol backscattering function in the free troposphere with altitude, latitude, and season. Most data are available and greatest consistency is found inside the Northern Hemisphere.

Kent, G. S.↗
NASA NTRSDate not supplied

Developing a Multilingual Auto-coding Interface Control for the MAVERIC-II Dynamics Simulator

Simulation model development in certain high-level languages such as Python, MATLAB, or Simulink are unparalleled by their convenience and rapid turnover time. However, legacy simulation engines often depend on more traditional languages such as FORTRAN or C/C++. The NASA Marshall Aerospace Vehicle Representation in C version II (MAVERIC-II) is a modular, legacy-derived computer program used for high-fidelity, 6 degree-of-freedom (6DOF) simulation for aerospace vehicle flights and analyses of guidance and control performance with built-in mathematical modeling of environmental effects such as wind, atmosphere, and gravity as well as dispersion capability for Monte Carlo analysis. MAVERIC-II is modular in the sense that each component software element of the simulation engine may be supplanted for a higher or lower fidelity version. The design flow of the development of these models is often performed in high-level languages as mentioned previously, which must then be translated into C or C++ code to be integrated into MAVERIC-II. Using principles of model-based design, we propose a unified method of auto-coding and interfacing between several languages and MAVERIC-II, which may be generalized further to any type of 6DOF simulation engine.

Mason Nixon↗
DOE OSTI2016

Packed Bed thermal storage for compact Light water-cooled Small Modular Reactors

Nuclear power plants (NPPs) have less flexibility to follow grid load demand than their natural-gas fueled counterparts. Most of the natural-gas power plants can supply peak-loads by adding more fuel, and thus, can generate far more revenue during those peak hours. On the other hand, use of NPPs for peak load following is quite complex due to technical constraints associated with reactor behavior. These technical challenges include the adequate handling of reactivity swings caused by time-varying fuel and moderator temperatures, a higher fuel-failure probability due to thermal-structural cycling, and spatial variations in xenon concentration. Although there are presently some reactors around the world that are operating with flexible load-following capabilities, such operation is restricted to slowly-varying powers, 2-3 times a day, and only up to 80% of the fuel cycle. Thus, a more convenient and effective method to facilitate load following by NPPs would be to integrate energy storage Authors have previously developed models and performed exergy analysis for integrating liquid type TES with LWRs and SMRs. These exergy based models show that technical feasibility index of integrating thermal energy storage is very high. But most of these previous studies include integration based on existing layout of NPPs with heat exchange between storage Heat Transfer Fluid (HTF) and Reactor Coolant (RC). However, most of the Light Water-cooled Small modular reactor (LW-SMR) based NPP designs can not accommodate additional heat exchange equipment. Although power production is only reduced to 1/20 scale, the containment volume in thus NuScale LW-SMR is reduced to {approx} 1/170 scale. As steam is the secondary or working fluid which exits out of the reactor containment in LW-SMRs, the simplest and most practical way to integrate thermal storage with LW-SMRs is to directly store the energy from steam. Indirect heat exchange between steam and another heat transfer fluid during the storage process, and then heat recovery again via indirect heat exchange is inefficient process due to heat transfer resistance. This inefficiency is due to what is called as 'Pinch point' which occurs whenever there is indirect heat transfer between two media where one undergoes phase change and other undergoes change in sensible heat. Another existing popular option is to use a steam accumulator which stores dry or wet steam directly inside the pressure vessels, however, due to large volumetric requirements it is not a viable option. This work proposes a new method of integrating packed bed TES systems with LW-SMRs, where steam produced in the secondary side of LW-SMRs can be injected into the packed bed of inert particles with sufficient thermal conductivity and capacity to efficiently store energy with high energy density. The changes in the load demand will not effect the LWSMR operation and the excess steam will be diverted to TES. When the demand increases this stored energy in hot packed beds can be recovered by injecting cold pressurized water. Although there are some existing packed bed TES designs and models which consider steam as HTFs, these models have not been extended for wide range of process parameters important for this integration. Authors have previously developed a packed bed thermal model for steam injection and validated it using experimental data. This thermal model is extended to assess behavior of packed bed thermal energy storage (TES) system under storage and recovery cycles. Steam is the only heat transfer fluid (HTF) which exits the reactor vessel, so any application such as process heat or TES integration should be evaluated with steam as process fluid. This project will develop a process system integration model of LW-SMR with packed bed type TES using steam as HTF. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2014

The NASA High Speed ASE Project: Computational Analyses of a Low-Boom Supersonic Configuration

A summary of NASA's High Speed Aeroservoelasticity (ASE) project is provided with a focus on a low-boom supersonic configuration developed by Lockheed-Martin and referred to as the N+2 configuration. The summary includes details of the computational models developed to date including a linear finite element model (FEM), linear unsteady aerodynamic models, structured and unstructured CFD grids, and discussion of the FEM development including sizing and structural constraints applied to the N+2 configuration. Linear results obtained to date include linear mode shapes and linear flutter boundaries. In addition to the tasks associated with the N+2 configuration, a summary of the work involving the development of AeroPropulsoServoElasticity (APSE) models is also discussed.

Silva, Walter A.↗
NASA NTRS1973

Analytic methods of orbit determination

This paper discusses several analytic models for predicting orbit determination performance during an interplanetary mission. Previously developed models for cruise radio tracking are reviewed and extended. Models for use with first radio and then optical tracking during approach are also developed. Comparison of the results with those obtained with full simulation models is emphasized. Several example problems using the analytic models are introduced to demonstrate the physical understanding possible with their employment.

Curkendall, D. W.↗
NASA NTRS2011

Summary of the Manufacture, Testing and Model Validation of a Full-Scale Radiator for Fission Surface Power Applications

A full-scale radiator for a lunar fission surface power application was manufactured by Material innovations, Inc., for the NASA Glenn Research Center. The radiator was designed to reject 6 kWt with an inlet water temperature of 400 K and a water mass flow rate of 0.5 kg/s. While not flight hardware, the radiator incorporated many potential design features and manufacturing techniques for future flight hardware. The radiator was tested at NASA Glenn Research Center for heat rejection performance. The results showed that the radiator design was capable of rejecting over 6 kWt when operating at the design conditions. The actual performance of the radiator as a function of operational manifolds, inlet water temperature and facility sink temperature was compared to the predictive model developed by NASA Glenn Research Center. The results showed excellent agreement with the model with the actual average face sheet temperature being within 1% of the predicted value. The results will be used in the design and production of NASA s next generation fission power heat rejection systems. The NASA Glenn Research Center s Technology Demonstration Unit will be the first project to take advantage of the newly developed manufacturing techniques and analytical models.

Ellis, David L.↗
NASA NTRS2003

Radiation Transport Properties of Potential In Situ-Developed Regolith-Epoxy Materials for Martian Habitats

Mission crews in space outside the Earth s magnetic field will be exposed to high energy heavy charged particles in the galactic cosmic radiation (GCR). These highly ionizing particles will be a source of radiation risk to crews on extended missions to the Moon and Mars, and the biological effects of and countermeasures to the GCR have to be investigated as part of the planning of exploration-class missions. While it is impractical to shield spacecraft and planetary habitats against the entire GCR spectrum, biological and physical studies indicate that relatively modest amounts of shielding are effective at reducing the radiation dose. However, nuclear fragmentation in the shielding materials produces highly penetrating secondary particles, which complicates the problem: in some cases, some shielding is worse than none at all. Therefore the radiation transport properties of potential shielding materials need to be carefully investigated. One intriguing option for a Mars mission is the use of material from the Martian surface, in combination with chemicals carried from Earth and/or fabricated from elements found in the Martian atmosphere, to construct crew habitats. We have measured the transmission properties of epoxy-Martian regolith composites with respect to heavy charged particles characteristic of the GCR ions which bombard the Martian surface. The composites were prepared at NASA Langley Research Center using simulated Martian regolith, in the process also evaluating fabrication methods which could lead to technologies for in situ fabrication on Mars. Initial evaluation of the radiation shielding properties is made using radiation transport models developed at NASA-LaRC, and the results of these calculations are used to select the composites with the most favorable radiation transmission properties. These candidates are then evaluated at particle accelerators which produce beams of heavy charged particles representative in energy and charge of the radiation at the surface of Mars. The ultimate objective is to develop the models into a design tool for use by mission planners, flight surgeons and radiation health specialists.

Miller, Jack↗
DOE OSTI2019

Comparison of a 2D nonlocal transport model to ECRH experiments in LHD

In this work, a recently developed model of nonlocal transport in two dimensions (2D), the “iterative method”, is applied to the published results of ECRH experiments performed in the Large Helical Device. It is found from the temperature profiles obtained from the 2D model that the sharply peaked electron temperature profiles observed in such experiments, and previously associated with local transport and “internal transport barriers” or Core Electron-Root Confinement, are also consistent with nonlocal transport. It is shown that the iterative method is suited to handling both scenarios

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A Clustering Graph Generator

In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps to understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Direct numerical simulation of reactor two-phase flows enabled by high-performance computing

Nuclear reactor two-phase flows remain a great engineering challenge, where the high-resolution two-phase flow database which can inform practical model development is still sparse due to the extreme reactor operation conditions and measurement difficulties. Owing to the rapid growth of computing power, the direct numerical simulation (DNS) is enjoying a renewed interest in investigating the related flow problems. A combination between DNS and an interface tracking method can provide a unique opportunity to study two-phase flows based on first principles calculations. More importantly, state-of-the-art high-performance computing (HPC) facilities are helping unlock this great potential. This paper reviews the recent research progress of two-phase flow DNS related to reactor applications. The progress in large-scale bubbly flow DNS has been focused not only on the sheer size of those simulations in terms of resolved Reynolds number, but also on the associated advanced modeling and analysis techniques. Specifically, the current areas of active research include modeling of sub-cooled boiling, bubble coalescence, as well as the advanced post-processing toolkit for bubbly flow simulations in reactor geometries. A novel bubble tracking method has been developed to track the evolution of bubbles in two-phase bubbly flow. Also, spectral analysis of DNS database in different geometries has been performed to investigate the modulation of the energy spectrum slope due to bubble-induced turbulence. In addition, the single-and two-phase analysis results are presented for turbulent flows within the pressurized water reactor (PWR) core geometries. The related simulations are possible to carry out only with the world leading HPC platforms. Furthermore, these simulations are allowing more complex turbulence model development and validation for use in 3D multiphase computational fluid dynamics (M-CFD) codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Development of an integrated model for energy systems planning and carbon dioxide mitigation under uncertainty – Tradeoffs between two-level decision makers

Highlights: • A bi-level model is developed for energy systems planning and carbon dioxide mitigation. • Tradeoffs between two-level decision-makers’ demands are quantified under uncertainty. • The energy and environmental impact of CO{sub 2} mitigation policy is analyzed for Beijing. • Results provide a range of decision alternatives between system optimality and reliability. A bi-level fuzzy programming (BFLP) method was developed for energy systems planning (ESP) and carbon dioxide (CO{sub 2}) mitigation under uncertainty. BFLP could handle fuzzy information and leader-follower problem in decision-making processes. It could also address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal. Then, a BFLP-ESP model was formulated for planning energy system of Beijing, in which the upper-level objective is to minimize CO{sub 2} emission and the lower-level objective is to minimize the system cost. Results provided a range of decision alternatives that corresponded to a tradeoff between system optimality and reliability under uncertainty. Compared to the single-level model with a target to minimize system cost, the amounts of pollutant/CO{sub 2} emissions from BFLP-ESP were reduced since the study system would prefer more clean energies (i.e. natural gas, LPG and electricity) to replace coal fuel. Decision alternatives from BFLP were more beneficial for supporting Beijing to adjust its energy mix and enact its emission-abatement policy. Results also revealed that the low-carbon policy for power plants (e.g., shutting down all coal-fired power plants) could lead to a potentially increment of imported energy for Beijing, which would increase the risk of energy shortage. The findings could help decision makers analyze the interactions between different stakeholders in ESP and provide useful information for policy design under uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

The birth of a field through a marriage of scales: urban meteorological modeling meets regional climate modeling

Urban meteorological modeling and regional climate modeling developed largely independently, with each discipline addressing different aspects of atmospheric processes across space and time. In this review, I show that urban climate modeling did not arise as a simple scaling extension of urban meteorological modeling or an add-on to regional climate modeling, but instead emerged through the selective inheritance of complementary strengths from its parents after both disciplines reached sufficient methodological maturity. By tracing the parallel evolution of these disciplines, I demonstrate that urban climate modeling inherited the physically explicit treatment of the built environment developed within urban meteorological modeling, and the hierarchical scale translation and climatological framing that matured within regional climate modeling, allowing urban effects to influence climate-relevant outcomes. Building on this synthesis, I propose an objective, and methodologically-grounded definition of urban climate modeling that distinguishes it from urban meteorological modeling. This distinction is increasingly important as urban climate data informs decisions with long-lived societal consequences, and as ambiguity in terminology risks conflating fundamentally different modeling frameworks with distinct physical meaning and decision relevance. In addition to a clarifying definition, this review outlines a research framework for advancing urban climate modeling through scale-aware coupling strategies that preserve physically consistent urban-atmosphere interactions.

regional climate↗
NASA NTRS1994

Deep Space Network Radiometric Remote Sensing Program

Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid, and precipitation, emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band because communication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of water vapor-induced propagation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity wave experiments, and radio science missions. During 1993, WVRs provided data for propagation model development, supported planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily, monthly, and seasonal variations. Only long-term monitoring will prevent biases from being introduced by an exceptionally wet or dry year. Support for planetary missions included tropospheric calibration for the recent Mars Observer gravity wave experiments and Ka-band link experiment (KaBLE). Additionally, several proposed radio science experiments such as profiling planetary atmospheres using satellite occultations and Ka-band gravitational wave searches require advanced radiometer technology development. Finally, there has been a consistent advanced technology program to advance satellite navigational and tracking capabilities. This year that included an experiment with radiometer based tropospheric calibration for a series of VLBI catalog measurements.

tropospheric calibration atmospheric water radio s↗