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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Modeling cumulus convection with a one-dimensional updraft core model

A model developed for use in satellite rainfall retrievals and possibly useful in other areas of research such as in the development of cloud microphysical schemes or in the study of acid rain, is described. This model is unique in that it models explicitly only a small region about the central axis of the updraft, thus avoiding large errors that may occur by averaging variables across the entire updraft. Comparison of the model output with two 3D cloud model simulations proved to be ideal for utilization in the development of this model due to the small wind shear in these cases and to the significant difference in atmospheric stability in the soundings that were used.

Ridout, James A.↗
NASA NTRS1971

Improved scaling laws for stage inert mass space Propulsion systems. Volume 3: Propulsion synthesis program users and programmers manual

The analytical models developed for the Space Propulsion Automated Synthesis Modeling (SPASM) program are presented. Weight scaling laws developed during this study are incorporated into the program's scaling data bank. A detail listing, logic diagram and input/output formats are supplied for the SPASM program. Two test examples for one to four-stage vehicles performing different types of missions are shown to demonstrate the program's capability and versatility.

Source record↗
NASA NTRS2005

Second NASA Technical Interchange Meeting (TIM): Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

The Advanced Technology Lifecycle Analysis System (ATLAS), a spreadsheet analysis tool suite, applies parametric equations for sizing and lifecycle cost estimation. Performance, operation, and programmatic data used by the equations come from a Technology Tool Box (TTB) database. In this second TTB Technical Interchange Meeting (TIM), technologists, system model developers, and architecture analysts discussed methods for modeling technology decisions in spreadsheet models, identified specific technology parameters, and defined detailed development requirements. This Conference Publication captures the consensus of the discussions and provides narrative explanations of the tool suite, the database, and applications of ATLAS within NASA s changing environment.

ONeil, D. A.↗
DOE OSTI2016

Modeling and control of fuel distribution in a dual-fuel internal combustion engine leveraging late intake valve closings

In internal combustion engines, cycle-to-cycle and cylinder-to-cylinder variations of the combustion process have been shown to negatively impact the fuel efficiency of the engine and lead to higher exhaust emissions. The combustion variations are generally tied to differences in the composition and condition of the trapped mass throughout each cycle and across individual cylinders. Thus, advanced engines featuring exhaust gas recirculation, flexible valve actuation systems, advanced fueling strategies, and turbocharging systems are prone to exhibit higher variations in the combustion process. In this study, the cylinder-to-cylinder variations of the combustion process in a dual-fuel internal combustion engine leveraging late intake valve closing are investigated and a model to predict and address one of the root causes for these variations across cylinders is developed. The study is conducted on an inline six-cylinder heavy-duty dual-fuel engine equipped with exhaust gas recirculation, a variable geometry turbocharger, and a fully flexible variable intake valve actuation system. The engine is operated with late intake valve closure timings in a dual-fuel combustion mode in which a high reactivity fuel is directly injected into the cylinders and a low reactivity fuel is port injected into the cylinders. The cylinder-to-cylinder variations observed in the study have been associated with the maldistribution of the port-injected fuel, which is exacerbated at late intake valve timings. The resulting difference in indicated mean effective pressure between the cylinders ranges from 9% at an intake valve closing of 570° after top dead center to 38% at an intake valve closing of 620° after top dead center and indicates an increasingly uneven fuel distribution. The study leverages both experimental and simulation studies to investigate the distribution of the port-injected fuel and its impact on cylinder-to-cylinder variation. The effects of intake valve closing as well as the impact of intake runner length on fuel distribution were quantitatively analyzed, and a model was developed that can be used to accurately predict the fuel distribution of the port-injected fuel at different operating conditions with an average estimation error of 1.5% in cylinder-specific fuel flow. A model-based control strategy is implemented to adjust the fueling at each port and shown to significantly reduce the cylinder-to-cylinder variations in fuel distribution.

Kassa, Mateos↗
NASA NTRS1984

Discrete Random Media Techniques for Microwave Modeling of Vegetated Terrain

Microwave modeling of vegetated terrain was investigated. The purpose was to: (1) use discrete scatter theory to model vegetation (crops and forested regions) in microwave region; (2) develop models for scatterers and ground; (3) multiple scattering analysis relate model parameters to average scattered power; and (4) develop inversion techniques to remotely determine model parameters.

Lang, R. H.↗
DOE OSTI2023

A mechanistic model for creep and thermal aging in Alloy 709

This report describes a physics-based model for creep and thermal aging in Alloy 709. Alloy 709 is an advanced austenitic alloy, targeted for use in future Sodium Fast Reactors (SFRs) and other advanced reactors. The material has superior high temperature properties compared to currently qualified 316 and 304 stainless steels. However, the available creep and thermal aging test database for Alloy 709 is significantly more limited compared to the historical materials. The physics-based model developed here is one way to accelerate the qualification of the material by providing more accurate long-term predictions for creep properties and thermal aging, compared to current empirical time-extrapolate techniques. The crystal plasticity finite element model is used to predict the deformation and failure of alloy 709. The same setup for the CPFE model is used in both the baseline model calibration process and the simulation campaigns for parameter inference. Specific constitutive choices are made for Alloy 709 to capture the primary deformation mechanisms. The dislocation creep formulation developed by Hu and Cocks is extended to account for coupled precipitation formation and the grain boundary cavitation model developed by Sham, Needleman, et al. is used to model grain boundary cavitation-induced failure. A novel update algorithm is proposed to render the semi-discrete constitutive update for the Sham-Needleman model unconditionally stable. A progressive calibration approach is adopted based on the observations that several types of material responses can be effectively decoupled. A surrogate model is trained based on full-fledged CPFE simulations to accelerate the forward model evaluations, and stochastic variational inference (SVI) is used to calibrate the unknown microstructural model parameters. The calibrated mechanistic model is used to predict the long-term creep life of Alloy 709, and the predictions are compared against classical empirical approaches.

36 MATERIALS SCIENCE↗
NASA NTRS1991

GIS modeling of archaeological site locations: A low-tech approach

A Geographic Information System (GIS)-type analysis of archaeological site locations using a dBase III plus program and a desk top computer is presented. A previously developed model of site locations in the Sequatchie Valley of northeastern Alabama is tested against known site locations in another large survey area there. The model fails to account for site locations in the test area. A model is developed for the test area and indicates the site locations are indeed different. Whether this is due to differences in site locations on a sub-regional level, or to sample error in the original model is unknown.

Futato, Eugene M.↗
DOE OSTI2021

Survey of Advanced Generation IV Reactor Parameters for Integrated Energy System Modeling Capabilities

This paper is to categorize and characterize advanced Generation IV nuclear reactors that are not water based according to the key parameters for the Integrated Energy Systems (IES) project[1]. A key goal of the IES project is to assess the economic viability of including an advanced nuclear reactor into an IES. The landscape of advanced reactors is heterogeneous: several unique designs with different heat profiles are currently being studied and designed. This report provides a high-level perspective of advanced reactor concepts, including primary loop nuclear output temperatures and operation schemes that could affect secondary side power production or storage. For example, this report addresses the type of thermodynamic system (Brayton, supercritical CO 2 [S-CO 2 ], etc.) and the various pressures and temperatures on the secondary side that are expected to be provided by the various primary side reactor types. Based on these characteristics, it may be possible to determine which type of nuclear power plant could be the most economical for analysis in the IES framework for power production coupled with energy storage and waste heat utilization. The results of this effort will serve as input for model development of various secondary side components, concentrating on off-the-shelf capabilities for current and near future secondary side power generation and heat rejection as simulated in TRANSFORM. Generic models can be created which are agnostic of the nuclear energy supply without violating intellectual property rights of the developer. These models can be used to make informed decisions on the economics of integrating various energy system components with nuclear plant designs. Once complete, conclusions may be drawn regarding (1) the economics, efficiency, and reliability of certain nuclear reactors, (2) certain industry processes and energy storage systems, and (3) prioritization of certain reactor types with the studied industry types.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Experimental characterization and constitutive modeling of the mechanical behavior of molybdenum under electromagnetically applied compression-shear ramp loading

Magnetically applied pressure-shear (MAPS) is a new experimental technique that provides a platform for direct measurement of material strength at extreme pressures. The technique employs an imposed quasi-static magnetic field and a pulsed power generator that produces an intense current on a planar driver panel, which in turn generates high amplitude magnetically induced longitudinal compression and transverse shear waves into a planar sample mounted on the drive panel. In order to apply sufficiently high shear traction to the test sample, a high strength material must be used for the drive panel. Molybdenum is a potential driver material for the MAPS experiment because of its high yield strength and sufficient electrical conductivity. To properly interpret the results and gain useful information from the experiments, it is critical to have a good understanding and a predictive capability of the mechanical response of the driver. In this work, the inelastic behavior of molybdenum under uniaxial compression and biaxial compression-shear ramp loading conditions is experimentally characterized. It is observed that an imposed uniaxial magnetic field ramped to approximately 10 T through a period of approximately 2500 μs and held near the peak for about 250 μs before being tested appears to anneal the molybdenum panel. In order to provide a physical basis for model development, a general theoretical framework that incorporates electromagnetic loading and the coupling between the imposed field and the inelasticity of molybdenum was developed. Based on this framework, a multi-axial continuum model for molybdenum under electromagnetic loading is presented. The model reasonably captures all of the material characteristics displayed by the experimental data obtained from various experimental configurations. Additionally, data generated from shear loading provide invaluable information not only for validating but also for guiding the development of the material model for multiaxial loadings.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Learning plasma dynamics and robust rampdown trajectories with predict-first experiments at TCV

The rampdown phase of a tokamak pulse is difficult to simulate and often exacerbates multiple plasma instabilities. To reduce the risk of disrupting operations, we leverage advances in Scientific Machine Learning (SciML) to combine physics with data-driven models, developing a neural state-space model (NSSM) that predicts plasma dynamics during Tokamak à Configuration Variable (TCV) rampdowns. The NSSM efficiently learns dynamics from a modest dataset of 311 pulses with only five pulses in a reactor-relevant high-performance regime. The NSSM is parallelized across uncertainties, and reinforcement learning (RL) is applied to design trajectories that avoid instability limits. High-performance experiments at TCV show statistically significant improvements in relevant metrics. A predict-first experiment, increasing plasma current by 20% from baseline, demonstrates the NSSM’s ability to make small extrapolations. The developed approach paves the way for designing tokamak controls with robustness to considerable uncertainty and demonstrates the relevance of SciML for fusion experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks

Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel, data-driven model reduction methods, coupled with detection of abnormal modes with plasma physics, opens a unique opportunity to identify plasma instabilities through automated construction of parsimonious models that can be tuned to balance accuracy and cost. Our fusion transfer learning (FTL) model demonstrates success in rapidly reconstructing nonlinear kink mode structures by learning from a limited amount of nonlinear simulation data. The knowledge transfer process leverages a pre-trained neural encoder–decoder network, initially trained on linear simulations, to effectively capture nonlinear dynamics. The low-dimensional embeddings extract the coherent structures of interest, while preserving the inherent dynamics of the complex system. Experimental results highlight FTL’s capacity to capture transitional behaviors and dynamical features in plasma dynamics—a task often challenging for conventional methods. The model developed in this study is generalizable and can be extended broadly through transfer learning to address various magnetohydrodynamics modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗
NASA NTRS2016

Development of Detonation Modeling Capabilities for Rocket Test Facilities: Hydrogen-Oxygen-Nitrogen Mixtures

The objective of the presented work was to develop validated computational fluid dynamics (CFD) based methodologies for predicting propellant detonations and their associated blast environments. Applications of interest were scenarios relevant to rocket propulsion test and launch facilities. All model development was conducted within the framework of the Loci/CHEM CFD tool due to its reliability and robustness in predicting high-speed combusting flow-fields associated with rocket engines and plumes. During the course of the project, verification and validation studies were completed for hydrogen-fueled detonation phenomena such as shock-induced combustion, confined detonation waves, vapor cloud explosions, and deflagration-to-detonation transition (DDT) processes. The DDT validation cases included predicting flame acceleration mechanisms associated with turbulent flame-jets and flow-obstacles. Excellent comparison between test data and model predictions were observed. The proposed CFD methodology was then successfully applied to model a detonation event that occurred during liquid oxygen/gaseous hydrogen rocket diffuser testing at NASA Stennis Space Center.

Allgood, Daniel C.↗
DOE OSTI2025

Optimization based process modeling of an anaerobic membrane bioreactor system: Application to swine wastewater

To maintain current levels of consumption in the economy with the dwindling supply of non-renewable material and energy, alternative resource streams more traditionally viewed as waste streams must be considered. Fermentation of high-strength wastewaters is one such pathway that allows for the recovery of energy, nitrogen, phosphorus, and carbon compounds. Anaerobic membrane bioreactors (AnMBRs) are an emerging technology that allow for the digestion of wastewater in a much smaller footprint than traditional anaerobic digesters. Adoption of this technology into industry has been limited by membrane capital and cleaning costs, but these costs may be offset through the recovery of valuable products. To evaluate the viability of AnMBR technology in the context of swine wastewater treatment, an optimization-based process model built upon Anaerobic Digestion Model No. 1 (ADM1) has been developed. Modeling results show that a swine wastewater stream provides potential for net positive energy generation from the AnMBR system in most cases. Sensitivity analyses around important variables were conducted to determine focus areas for future research into AnMBR technology and evaluate the robustness of the model to microbial variables that may change with different microbial communities.

09 BIOMASS FUELS↗
DOE OSTI2018

Experimental and modeling study of the pyrolysis and oxidation of an iso-paraffinic alcohol-to-jet fuel

Single pulse shock tube experiments were performed to determine the pyrolytic and oxidative decomposition products of an alcohol-to-jet fuel (ATJ) composed primarily of about 90% iso-dodecane. Experiments were conducted at 4 bar nominal pressure, 2 ms nominal reaction time, and temperatures ranging from 900 K to 1550 K. For oxidation, the equivalence ratio was 0.27. Gas chromatography (GC) was used to analyze the products of the chemical reactions and to determine their mole fractions. The experimental results were compared against mole fractions computed using a detailed iso-alkane kinetic model, developed for the present study. The model was able to accurately reproduce the experimental results of both ATJ pyrolysis and oxidation. The experimental data and the kinetic modelintroduced in the current study shall aid in progress in understanding the oxidation of the alternative jet fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multi-cyclone analysis and machine learning model implications of cyclone effects on forests

Past studies of cyclones (hurricanes, typhoons, tropical cyclones) disturbance showed that meteorological, topographical, and biological factors affect the patterns of forest disturbance intensity but left open the extent to which these findings were representative across different global cyclone regions. Using remote sensing data and machine learning models, we examined how these factors change over spatial scales and assessed their consistency across four major cyclones: Katrina (August 2005), Rita (September 2005), Yasi (February 2011), and María (September 2017). Our results revealed that the factors which best explained forest disturbance intensity pattern varied across these regions. Wind speed and precipitation were the dominant factors contributing to the variation in impacts of Katrina; terrain features, especially elevation, explained most of the variation in disturbance intensity of Rita; pre-disturbance vegetation condition was significant predictors of effects of Yasi; these factors played equal roles in explaining the disturbance intensity variation of María. A 40 m/s (144 km/h) wind speed threshold was proposed to split low- and high-level forest disturbance intensity. Other than wind speed, few generalizations can be made on features across multiple regions. We built several generalized hurricane impact models, which worked well with the test data from cyclones used for model development (R 2 = 0.89). However, these models did not have good predictions on other cyclones, such as Michael (October 2018) and Laura (August 2020). This study showed that each cyclone interacted with the landscape in a unique way and the challenges remained in building a generalized cyclone impact model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Bubble explosion induced melt pool instabilities in electron beam melting of aluminum alloy

Electron beam melting (EBM) is an additive manufacturing technology that can process materials and manufacture components otherwise impossible or uneconomical. However, defects, including porosity and surface irregularities, are widely reported in EBM-built components, and their formation mechanisms are not fully understood. Here, using in-situ high-speed synchrotron X-ray imaging, we reveal that bubble explosions in Al6061 during EBM induce melt pool instabilities contributing to defect formation. The melt pool and keyhole evolve through three stages: (1) initial formation of a melt pool, (2) subsurface bubble formation and explosion, and (3) periodic keyhole oscillation. During scanning, periodic bubble explosions can eject molten liquid as spatters and disturb the vapor depression and melt pool, contributing to surface humping, that may trigger lack-of-fusion defects in subsequent layers. The physical insights we report could provide guidance for EBM machine development, process innovation, alloy design and model development.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Modelling the effect of acoustic waves on nucleation

A phase transformation in a metastable phase can be affected when it is subjected to a high intensity ultrasound wave. In this study we determined the effect of oscillation in pressure and temperature on a phase transformation using the Gibbs droplet model in a generic format. The developed model is valid for both equilibrium and non-equilibrium clusters formed through a stationary or non-stationary process. We validated the underlying model by comparing the predicted kinetics of water droplet formation from the gas phase against experimental data in the absence of ultrasound. Our results demonstrated better agreement with experimental data in comparison with classical nucleation theory. Then, we determined the thermodynamics and kinetics of nucleation and the early stage of growth of clusters in an isothermal sonocrystallisation process. This new contribution shows that the effect of pressure on the kinetics of nucleation is cluster size-dependent in contrast to classical nucleation theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗