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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Further Developments in Modeling Creep Effects Within Structural SiC/SiC Components

Anticipating the implementation of advanced SiC/SiC composites into turbine section components of future aero-propulsion engines, the primary objective of this on-going study is to develop physics-based analytical and finite-element modeling tools to predict the effects of constituent creep on SiC/SiC component service life. A second objective is to understand how to possibly manipulate constituent materials and processes in order to minimize these effects. Focusing on SiC/SiC components experiencing through-thickness stress gradients (e.g., airfoil leading edge), prior NASA creep modeling studies showed that detrimental residual stress effects can develop globally within the component walls which can increase the risk of matrix cracking. These studies assumed that the SiC/SiC composites behaved as isotropic viscoelastic continuum materials with creep behavior that was linear and symmetric with stress and that the creep parameters could be obtained from creep data as experimentally measured in-plane in the fiber direction of advanced thin-walled 2D SiC/SiC panels. The present study expands on those prior efforts by including constituent behavior with non-linear stress dependencies in order to predict such key creep-related SiC/SiC properties as time-dependent matrix stress, constituent creep and content effects on composite creep rates and rupture times, and stresses on fiber and matrix during and after creep.

Lang, Jerry↗
DOE OSTI2019

Microstructure-based model of nonlinear ultrasonic response in materials with distributed defects

Nonlinear ultrasonic technique is one of promising NDE methods for monitoring defect evolution in irradiated nuclear materials. In this work, we have studied the effect of distributed defects on nonlinear ultrasonic response, in particular, the nonlinear parameter ß from the 2nd harmonic wave. A three-dimensional microstructure-based model has been developed for investigating the dynamic interaction between distributed defects and a propagating longitudinal sound wave. Both linear and nonlinear materials are considered. It is known that the 2nd harmonic wave is generated when a monochromatic wave propagates in a nonlinear elastic material. The results show that second phase particles with elastic heterogeneity and lattice mismatch have strong impact on the nonlinear parameter ß. Lattice mismatches have more effect on the nonlinear parameter no matter they are expansion or contraction. The developed model enables one to explore the contributions of different types of defects to the nonlinear ultrasonic signals and shed light on the development of nonlinear ultrasound nondestructive detection of material defects in nuclear reactors.

Second harmonic generation, Scattered distributed ↗
NASA NTRS1979

Development of a model and computer code to describe solar grade silicon production processes

Mathematical models, and computer codes based on these models were developed which allow prediction of the product distribution in chemical reactors in which gaseous silicon compounds are converted to condensed phase silicon. The reactors to be modeled are flow reactors in which silane or one of the halogenated silanes is thermally decomposed or reacted with an alkali metal, H2 or H atoms. Because the product of interest is particulate silicon, processes which must be modeled, in addition to mixing and reaction of gas-phase reactants, include the nucleation and growth of condensed Si via coagulation, condensation, and heterogeneous reaction.

Srivastava, R.↗
NASA NTRS1972

Shock-wave structure using nonlinear model Boltzmann equations.

The structure of strong plane shock waves in a perfect monatomic gas was studied using four nonlinear models of the Boltzmann equation. The models involved the use of a simplified collision operator with velocity-independent collision frequency, in place of the complicated Boltzmann collision operator. The models employed were the BGK and ellipsoidal models developed by earlier authors, and the polynomial and trimodal gain function models developed during the work. An exact set of moment equations was derived for the density, velocity, temperature, viscous stress, and heat flux within the shock. This set was reduced to a pair of coupled nonlinear integral equations and solved using specially adapted numerical techniques. A new and simple Gauss-Seidel iteration was developed during the work and found to be as efficient as the best earlier iteration methods.

Segal, B. M.↗
NASA NTRS1992

The Middeck Active Control Experiment (MACE)

Viewgraphs on the Middeck Active Control Experiment (MACE) are presented. Topics covered include: program objectives; program features; flight experiment features; current activities; MACE development model lab testing; MACE test article deployed on STS middeck; and development model testing.

Miller, David W.↗
NASA NTRS2022

Coupling Carbon Oxidation and Surface Recession in Direct-Simulation Monte Carlo Code, SPARTA

Ablative thermal protection system (TPS) materials for spacecraft are composites that are often made out of carbon-based reinforcement and a polymeric matrix. They endure high-temperature oxidation and surface recession when re-entering Earth’s atmosphere. Ablation is the result of many coupled and competing thermal, mechanical, and chemical phenomena, and it is difficult to isolate the role of each on the overall degradation of the TPS. Here we develop an ablation model for material recession coupled explicitly to finite rate carbon oxidation in complex microstructures. In this work, Stochastic PArallel Rarified-gas Time-accurate Analyzer (SPARTA), a direct-simulation Monte Carlo (DSMC) code, is modified to allow oxidation-driven ablation of implicitly defined carbon surfaces. In SPARTA, implicit surfaces are generated from the grid corner point values via a marching cubes algorithm, therefore creating a new set of surface elements every time ablation is performed. The finite-rate oxidation model developed by Gopalan et. al, was adapted to tally surface reactions and other surface data on a per-grid cell basis. The ablation functionality was also adjusted so once the reactions have occurred, the number of reactions leading to CO formation can be converted to corner point reduction values; therefore, carbon removal is directly proportional to surface recession. We also develop robust algorithms which handle the evolution of the flow cells and solid material regions, including split cells (flow cell divided in two by a solid surface). Finally, we demonstrate our implicit chemistry model for 2D and 3D geometries by producing reaction statistics and detailed visualization of oxidation-induced material recession at the microscale.

V Arias↗
NASA NTRSDate not supplied

Development of Modeling & Simulation Capability to Analyze Supply Chain

Supply chain has brought up many challenges to the current aerospace industry (e.g. limited sources, lack of inventory, and cyber security). The purpose of this research is to develop a web-based modeling and simulation platform for supply chains relating to Advanced Air Mobility and vertical take-off and landing vehicles (VTOLs).

Cybersecurity↗
DOE OSTI2018

Characterizing the Relative Importance Assigned to Physical Variables by Climate Scientists when Assessing Atmospheric Climate Model Fidelity

Evaluating a climate model’s fidelity (ability to simulate observed climate) is a critical step in establishing confidence in the model’s suitability for future climate projections, and in tuning climate model parameters. Model developers use their judgement in determining which trade-offs between different aspects of model fidelity are acceptable. However, little is known about the degree of consensus in these evaluations, and whether experts use the same criteria when different scientific objectives are defined. Here, we report on results from a broad community survey studying expert assessments of the relative importance of different output variables when evaluating a global atmospheric model’s mean climate. We find that experts adjust their ratings of variable importance in response to the scientific objective, for instance, scientists rate surface wind stress as significantly more important for Southern Ocean climate than for the water cycle in the Asian watershed. There is greater consensus on the importance of certain variables (e.g., shortwave cloud forcing) than others (e.g., aerosol optical depth). We find few differences in expert consensus between respondents with greater or less climate modeling experience, and no statistically significant differences between the responses of climate model developers and users. In conclusion, the concise variable lists and community ratings reported here provide baseline descriptive data on current expert understanding of certain aspects of model evaluation, and can serve as a starting point for further investigation, as well as developing more sophisticated evaluation and scoring criteria with respect to specific scientific objectives.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Aerospace Applications of Weibull and Monte Carlo Simulation with Importance Sampling

Recent developments in reliability modeling and computer technology have made it practical to use the Weibull time to failure distribution to model the system reliability of complex fault-tolerant computer-based systems. These system models are becoming increasingly popular in space systems applications as a result of mounting data that support the decreasing Weibull failure distribution and the expectation of increased system reliability. This presentation introduces the new reliability modeling developments and demonstrates their application to a novel space system application. The application is a proposed guidance, navigation, and control (GN&C) system for use in a long duration manned spacecraft for a possible Mars mission. Comparisons to the constant failure rate model are presented and the ramifications of doing so are discussed.

Bavuso, Salvatore J.↗
NASA NTRS1993

TeleOperator/telePresence System (TOPS) Concept Verification Model (CVM) development

The development of an anthropomorphic, undersea manipulator system, the TeleOperator/telePresence System (TOPS) Concept Verification Model (CVM) is described. The TOPS system's design philosophy, which results from NRaD's experience in undersea vehicles and manipulator systems development and operations, is presented. The TOPS design approach, task teams, manipulator, and vision system development and results, conclusions, and recommendations are presented.

Shimamoto, Mike S.↗
DOE OSTI2021

Application of machine learning to estimate fireball characteristics and their uncertainty from infrared spectral data

Experiments or events involving high explosives (HE) can be monitored remotely by infrared (IR) sensors to gather information about the configuration or materials involved in the device. Researchers at the Air Force Institute of Technology (AFIT) developed a phenomenological model for HE fireball spectra in the IR range that allows for parameters to be extracted from Fourier transform infrared (FTIR) data. This model includes parameters tied to physical characteristics of the fireball: temperature, size, soot, and gas concentrations. Previous works have sought to recover these parameters by the fitting of either whole spectra or select wavenumber bands to this phenomenological model. Difficulties arise due to the complex relationships between the parameters to be fit. Uncertainty quantification of the estimated fireball parameters is also problematic since HE experiments do not have any ground truth information on the parameters. It is suggested that artificial neural network (ANN) based approaches may be well suited to this problem, because of their ability to capture complex and highly nonlinear relationships. As such, this work seeks to explore the efficacy of deep artificial neural networks (DNNs) for this problem of parameter recovery from spectra and to also investigate the uncertainty of recovering the fireball parameters from FTIR data. Networks are designed using the hyperparameter optimization tool Hyperopt and trained/tested on artificial data generated using the phenomenological model developed by AFIT. The results of applying the network to the artificial data set are compared to a physics-based band approach that uses a selected number of bands based on their physical properties. Information on the uncertainty of estimating parameters from remotely sensed experimental data is obtained by treating the accuracy of the DNN model on artificial data as an upper bound and by examining the impact of emissivity due to soot on parameter estimation error; the results for artificial data are likely to be optimistic as compared to recovering parameters from experimental data.

42 ENGINEERING↗
NASA NTRS1989

Properties of grains derived from IRAS observations of dust

The authors used the results of Infrared Astronomy Satellite (IRAS) observations of diffuse medium dust to develop a theoretical model of the infrared properties of grains. Recent models based entirely on traditional observations of extinction and polarization include only particles whose equilibrium temperatures do not exceed 20 K in the diffuse interstellar medium. These classical grains, for which the authors have adopted the multipopulation model developed by Hong and Greenberg (1980), can explain only the emission in the IRAS 100 micron band. The measurements at shorter wavelengths (12, 25 and 60 microns) require two new particle populations. Vibrational fluorescence from aromatic molecules provides the most likely explanation for the emission observed at 12 microns, with polycyclic aeromatic hydrocarbons (PAHs) containing about 10 percent of cosmic carbon. A simplified model of the emission process shows that PAH molecules can also explain most of the emission measured by IRAS at 25 microns. The authors identified the warm particles responsible for the excess 60 microns emission with small (a approx. equals 0.01 microns) iron grains. A compilation of the available data on the optical properties of iron indicates that the diffuse medium temperature of small iron particles should be close to 50 K and implies that a large, possibly dominant, fraction of cosmic iron must be locked up in metallic particles in order to match the observed 60 microns intensities. The model matches the infrared fluxes typically observed by IRAS in the diffuse medium and can also reproduce the infrared surface brightness distribution in individual clouds. In particular, the combination of iron and classical cool grains can explain the surprising observations of the 60/100 microns flux ratio in clouds, which is either constant or increases slightly towards higher opacities. The presence of metallic grains has significant implications for the physics of the interstellar medium, including catalytic H2 formation, for which iron grains could be the main site; differences in depletion patterns between iron and other refractory elements (Mg, Si); and superparamagnetic behavior of large grains with embedded iron clusters giving rise to the observed high degree of alignment by the galactic magnetic field.

Wesselius, P. R.↗
DOE OSTI2025

Development of Predictive Model for Accurate Rupture Time from Multi-Axial Creep in Alloy 709 with Physics-Based Simulations

A physics-based model is developed to predict multiaxial creep behavior in Alloy 709 (A709), an advanced austenitic stainless steel intended for high-temperature applications such as Sodium Fast Reactors (SFRs). Compared to conventional stainless steels like 316H, A709 offers superior high-temperature performance; however, comprehensive data on its multiaxial creep response remain limited. To address this gap, a crystal plasticity finite element (CPFE) framework is used to simulate the deformation and failure mechanisms of A709 under multiaxial loading conditions. The model incorporates an extended Hu-Cocks dislocation creep formulation that accounts for precipitation effects, along with the Sham–Needleman model to capture grain boundary cavitation-driven failure. These advanced constitutive models enable a detailed understanding of the interplay between microstructural evolution and macroscopic creep response. Furthermore, the study evaluates the predictive accuracy of various effective stress measures in estimating creep rupture life, leveraging simulated multiaxial creep data. The findings provide critical insights into the applicability of different stress measures for engineering design and life prediction of A709 components operating under complex loading conditions. This work contributes to improving the reliability of high-temperature structural components by advancing predictive modeling capabilities for advanced austenitic steels.

Alloy 709↗
DOE OSTI2019

Biomass Grinding Process Optimization Using Response Surface Methodology and a Hybrid Genetic Algorithm

Biomass could be a key source of renewable energy. Agricultural waste products, such as corn stover, provide a convenient means to replace fossil fuels, such as coal, and a large amount of feedstock is currently available for energy consumption in the U.S. This study has two main objectives: (1) to understand the impact of corn stover moisture content and grinder speed on grind physical properties; and (2) develop response surface models and optimize these models using a hybrid genetic algorithm. The response surface models developed were used to draw surface plots to understand the interaction effects of the corn stover grind moisture content and grinder speed on the grind physical properties and specific energy consumption. The surface plots indicated that a higher corn stover grind moisture content and grinder speed had a positive effect on the bulk and tapped density. The final grind moisture content was highly influenced by the initial moisture content of the corn stover grind. Optimization of the response surface models using the hybrid genetic algorithm indicated that moisture content in the range of 17 to 19% (w.b.) and a grinder speed of 47 to 49 Hz maximized the bulk and tapped density and minimized the geomantic mean particle length. The specific energy consumption was minimized when the grinder speed was about 20 Hz and the corn stover grind moisture content was about 10% (w.b.).

09 BIOMASS FUELS↗
NASA NTRSDate not supplied

A Parallelized Oxidation-Driven Surface Recession Framework in DSMC Code, SPARTA

Spacecrafts rely on ablative thermal protection systems (TPS) made of composites consisting of a carbon-based reinforcement and a polymeric matrix. These materials are designed to withstand high-temperature oxidation and surface recession during re-entry into the Earth's atmosphere. However, ablation occurs due to a complex interplay of thermal, mechanical, and chemical factors, making it challenging to determine the individual impact of each on the TPS's overall degradation. In this study, we have developed an ablation model that can leverage a finite rate carbon oxidation model to predict material recession and surface states more accurately. Stochastic PArallel Rarified-gas Time-accurate Analyzer (SPARTA), a direct-simulation Monte Carlo (DSMC) code, is modified to allow oxidation-driven ablation of implicitly defined carbon surfaces. In SPARTA, implicit surfaces are generated from the grid corner point values via a marching cubes algorithm, therefore creating a new set of surface elements every time ablation is performed. The finite-rate oxidation model developed by Gopalan et. al can perform both gas-surface and pure-surface reactions and is now adapted to tally surface data on a per grid cell basis. The ablation functionality was also adjusted so once the reactions have occurred, the number of reactions leading to CO formation can be converted to corner point reduction values; therefore, carbon removal is directly proportional to surface recession. We also briefly discuss some unique challenges associated with parallelizing this dynamic surface state and geometry. Finally, we analyze the performance of this parallelized implicit chemistry model with simple 2D and 3D benchmark cases by producing surface state statistics, area changes over time, and visualization across a range of surface temperatures and processors with and without load-balancing.

DSMC↗
DOE OSTI2018

Overview of IAEA MODARIA II Program Working Group 1 on Assessment and Decision Making of Existing Exposure Situations for NORM and Nuclear Legacy Sites - 18308

The International Atomic Energy Agency (IAEA) launched the Modelling and Data for Radiological Impact Assessments (MODARIA) II Programme in October. As part of the IAEA effort to enhance the capabilities of its Member States in assessing radiological impacts of radionuclides released to the environment from sites that were not operated in accordance with current standards, and to ensure protection of the public and the environment, the MODARIA II Programme aims to: (1) test the performance of models developed for predicting the transfer of radionuclides in the environment and assessing radiological impacts to the public and the environment; (2) develop and improve models for particular environments and, where appropriate, to agree on data sets that are generally applicable for use in testing environmental transfer models; and (3) provide an international forum for the exchange of experiences, ideas and research information. The Programme will run for 3 years from 2016 to 2019. The Programme comprises seven working groups covering a wide range of topics (https://wwwns.iaea.org/projects/modaria/modaria2.asp?s=8 and l=129). MODARIA II Working Group 1 (WG1) is focused on dose assessment and decision making regarding existing exposure situations due to naturally occurring radioactive material (NORM) and nuclear legacy sites. WG1 was formed as a combination of two MODARIA I WGs: WG1 focused on application of decision-aiding tools in remediation; and WG3 focused on risk assessment for NORM and radioactively contaminated legacy sites (https://wwwns.iaea.org/projects/modaria/default.asp?s=8 and l=129). It was recognized that the decision-making needs will inform the scope of risk assessments, and the risk insights and structured decision analyses will aid in informed decision-making. Therefore, MODARIA II WG1 is focused on developing methods and toolsets for risk-informed decision-making for NORM and nuclear legacy sites, including demonstration of decision-making processes and tools through case studies. MODARIA II WG1 has 91 registered participants from 33 Member States and IAEA (as of November 2017), some 30 of whom are actively engaged in various collaborative research and development activities within WG1. Members of WG1 participated in the First Technical Meeting of MODARIA II, which was held in Vienna, Austria from 31 October to 4 November 2016. The group then held its First Interim Meeting in Brussels, Belgium from 26 to 30 June 2017, which included a field trip to the legacy Tessenderlo Chemie (TCH) Phosphate Processing Site. At this meeting, the TCH Site and the Pridneprovsky Chemical Plant (PChP) in Ukraine were selected for case studies. The Los Alamos National Laboratory (LANL) Material Disposal Area B in the USA and the Beaverlodge Uranium Mill and Mill Site in northern Canada were selected as examples for sharing of good practices and lessons learned in risk-informed decision-making for environmental remediation and land conveyance. At the Second Technical Meeting held in Vienna on 30 October to 3 November 2017, an additional NORM site for tin processing in Brazil was added to the case studies, with another NORM site in Yunnan, China included for consideration at the Second Interim Meeting of WG1. The Second Interim Meeting will be held in in early to mid-May, 2018. The group has also decided to prepare an Interim Report by October 2018 to document the WG1 discussions and analyses for the period of 2016-2018, which will be finalized at the conclusion of MODARIA II in October 2019. Initial assignments have been discussed for IM1 participants to collect data, conduct modelling and analyses, and prepare draft sections for the Interim Report. This paper will provide an overview of the work plans for WG1. It will also highlight some near-term activities that the group is currently working on. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Mass Spectrometry Sample Submission Portal

Each step in the scientific process generates contextual information about the data that is important to consider when performing data integration, developing models of biological process, or training AI models. We will develop a flexible, template-driven tool that will log biological samples, capture metadata about those samples, and track the type(s) of analysis being performed by researchers providing samples for analysis by mass spectrometry.

97 MATHEMATICS AND COMPUTING↗