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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 685 records · Page 38

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NASA NTRS1987

On the simulation of ballistic shock loads

Blast or penetrator-impact induced shocks are characterized by high acceleration levels, particularily in the higher frequency range and for a short time duration. These shocks are dangerous for the equipment of ships, combat vehicles, airplanes or spacecraft structures. As ballistic shock loads are insufficiently simulated by laboratory test machines, researchers designed a ballistic shock simulator. The impact induced shocks are simulated by an explosive and the vehicle to be bombarded is replaced by a simplified structure. This structure is suitable to accommodate any equipment which can be tested up to their load limits.

Hollburg, Uwe↗

NASA NTRS1992

Simplified Modeling Of A Helicopter

Report discusses development of minimum-complexity mathematical model of helicopter for use in flight simulator. Development motivated by computational delays, costs, long development times, and inflexibility of sophisticated models now in use. New model overcomes these disadvantages and provides better engineering understanding of those features pertaining to handling qualities apparent to pilot who uses simulator.

Heffley, Robert K.↗

NASA NTRS1992

Vision-based recursive estimation of rotorcraft obstacle locations

The authors address vision-based passive ranging during nap-of-the-earth (NOE) rotorcraft flight. They consider the problem of estimating the relative location of identifiable features on nearby obstacles, assuming a sequence of noisy camera images and imperfect measurements of the camera's translation and rotation. An iterated extended Kalman filter is used to provide recursive range estimation. The correspondence problem is simplified by predicting and tracking each feature's image within the Kalman filter framework. Simulation results are presented which show convergent estimates and generally successful feature point tracking. Estimation performance degrades for features near the optical axis and for accelerating motions. Image tracking is also sensitive to angular rate.

Leblanc, D. J.↗

NASA NTRS1993

Comment on 'Comparison of observed and calculated implanted ion distributions outside Comet Halley's bow shock' by T. I. Gombosi, M. Neugebauer, A. D. Johnstone, A. J. Coates, and D. E. Huddleston

It is argued that the formulation used by Gombosi (1991) does not distinguish between two fundamental types of resonant interactions (those between cometary pickup ions and LF electromagnetic waves). Two problems arise from using their overly simplified expressions. The wave polarization of the solar wind Alfven wave is not purely right-handed, and values from alpha sub com and alpha sub sw are not well known, nor are the 'polarizations' of the 'backward'-going waves in either case. Gombosi et al. discuss the antisunward vs the sunward propagating solar wind Alfven wave, and assume a reasonable value of 0.2 for alpha sub sw. However, alpha sub com is totally unknown. It is concluded that a more correct analysis of wave polarization can lead to significant changes in the formulation and results from Gombosi et al. In his reply Gombosi argues that his simplified wave-particle interaction model is consistent with Giotto observations and plasma kinetic simulations and it leads to a reasonable approximation of the implanted ion transport coefficients. The more complicated approach suggested by Tsurutani & Thorne (1993) requires the introduction of several ad hoc parameters and it does not lead to any change of the energy diffusion coefficient.

Tsurutani, Bruce T.↗

NASA NTRS2017

Looking at A 0535+26 at Low Luminosities with NuSTAR

We report on two NuSTAR observations of the high-mass X-ray binary A 0535+26 taken toward the end of its normal 2015 outburst at very low 3-50 keV luminosities of approximately 1.4 times x 10 (sup 36) ergs per second and approximately 5 times x 10 (sup 35) ergs per second, which are complemented by nine Swift observations. The data clearly confirm indications seen in earlier data that the source's spectral shape softens as it becomes fainter. The smooth exponential rollover at high energies seen in the first observation evolves to a much more abrupt steepening of the spectrum at 20-30 keV. The continuum evolution can be nicely described with emission from a magnetized accretion column, modeled using the compmag model modified by an additional Gaussian emission component for the fainter observation. Between the two observations, the optical depth changes from 0.75 plus or minus 0.04 to 0.56 plus 0.01 (sup) minus 0.04 (sub), the electron temperature remains constant, and there is an indication that the column decreases in radius. Since the energy-resolved pulse profiles remain virtually unchanged in shape between the two observations, the emission properties of the accretion column reflect the same accretion regime. This conclusion is also confirmed by our result that the energy of the cyclotron resonant scattering feature (CRSF) at approximately 45 keV is independent of the luminosity, implying that the magnetic field in the region in which the observed radiation is produced is the same in both observations. Finally, we also constrain the evolution of the continuum parameters with the rotational phase of the neutron star. The width of the CRSF could only be constrained for the brighter observation. Based on Monte Carlo simulations of CRSF formation in single accretion columns, its pulse phase dependence supports a simplified fan beam emission pattern. The evolution of the CRSF width is very similar to that of the CRSF depth, which is, however, in disagreement with expectations.

Ballhausen, Ralf↗

NASA NTRS2022

Use of Machine Learning to Reduce Uncertainties in Particle Number Concentration and Aerosol Indirect Radiative Forcing Predicted by Climate Models

The radiative forcing of anthropogenic aerosols associated with aerosol–cloud interactions (RF(sub aci)) remains the largest source of uncertainty in climate prediction. The calculation of particle number concentration (PNC), one of the critical parameters affecting RF(sub aci), is generally simplified in climate models. Here we employ outputs from long-term (30-years) simulations of a global size-resolved (sectional) aerosol microphysics model and a machine-learning tool to develop a Random Forest Regression Model (RFRM) for PNC. We have implemented the PNC RFRM in GISS-ModelE2.1 with a mass-based One-Moment Aerosol module, which is one of CMIP6 models. Compared to the default setting, the GISS-ModelE2.1 simulation based on RFRM reduces the changes of cloud droplet number concentration associated with anthropogenic emissions, and decreases the RF(sub aci) from −1.46 W⋅m(exp −2) to −1.11 W⋅m(exp −2). This work highlights a promising approach based on machine learning to reduce uncertainties of climate models in predicting PNC and RF(sub aci) without compromising their computing efficiency.

Radiative forcing↗

DOE OSTI2024

Energy-dependent implementation of secondary electron emission models in continuum kinetic sheath simulations

The plasma-material interactions present in multiple fusion and propulsion concepts between the flow of plasma through a channel and a material wall drive the emission of secondary electrons. This emission is capable of altering the fundamental structure of the sheath region, significantly changing the expected particle fluxes to the wall. The emission spectrum is separated into two major energy regimes, a peak of elastically backscattered primary electrons at the incoming energy, and cold secondary electrons inelastically emitted directly from the material. The ability of continuum kinetic simulations to accurately represent the secondary electron emission is limited by relevant models being formulated in terms of monoenergetic particle interactions which cannot be applied directly to the discrete distribution function. As a result, rigorous implementation of energy-dependent physics is often neglected in favor of simplified, constant models. We present here a novel implementation of semi-empirical models in the boundary of continuum kinetic simulations which allows the full range of this emission to be accurately captured in physically-relevant regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

A Code-Agnostic Driver Application for Coupled Neutronics and Thermal-Hydraulic Simulations

While the literature has numerous examples of Monte Carlo and computational fluid dynamics (CFD) coupling, most are hard-wired codes intended primarily for research rather than as standalone, general-purpose applications. In this work, we describe an open source application, ENRICO, that enables coupled neutronic and thermal-hydraulic simulations between multiple codes that can be chosen at runtime (as opposed to a coupling between two specific codes). The application has been designed such that the control flow logic, domain mapping, nonlinear fixed-point iteration, solution transfers, and convergence checks are all agnostic to the underlying physics solvers used. Special emphasis has also been placed on enabling efficient execution on distributed-memory computing environments. The transfer of solution fields between solvers is performed in memory rather than through filesystem I/O. Additionally, solvers can be configured to run on overlapping or disjoint sets of processes. To date, coupling with the OpenMC and Shift Monte Carlo codes, the Nek5000 CFD code, and a simplified heat diffusion and subchannel solver has been implemented in ENRICO. We present results for coupled simulations of a single light-water reactor fuel assembly based on the NuScale reactor using various combinations of the physics solvers. For this problem, the coupled simulations are shown to converge in about four Picard iterations. A comparison of the heat source and temperature distributions computed by ENRICO using OpenMC coupled with Nek5000 and Shift coupled with Nek5000 illustrates remarkable agreement between the codes.

42 ENGINEERING↗

DOE OSTI2025

Integrating Analytical Solutions and U-Net Model for Predicting Groundwater Contaminant Plumes in Pump-and-Treat Systems

Pump-and-treat (P&T) is a common technique for groundwater remediation involving the extraction and treatment of contaminated water above ground. Optimizing the design and operation of the P&T well network is essential for maximizing the system’s effectiveness and efficiency. However, this optimization often necessitates many model evaluations, leading to computationally demanding tasks. This study introduces a novel approach that integrates analytical solutions for groundwater dynamics with the U-Net (Ronneberger et al., 2015) deep learning framework to predict groundwater contaminant plume migration under dynamic pumping conditions. By incorporating the Thiem equation (Thiem, 1906) into the input preprocessing, the U-Net model transforms sparse well data into a continuous spatial field that captures the hydraulic impacts of pumping activities. This integration enables the model to leverage both deep learning capabilities and classical physics-based groundwater theories, enhancing prediction accuracy and computational efficiency. These advancements can facilitate rapid, large-scale evaluations of P&T optimization simulations, allowing for timely and effective decision-making in well placement and system management. We demonstrate the model's robust performance across both simplified transient 2D models and a more complex 3D heterogeneous site model at the 200 West P&T facility at the Hanford Site. The U-Net-based model offers substantial computational advantages, reducing simulation times significantly compared to full physics-based models and providing a powerful tool for rapid site evaluation and P&T system optimization, such as evaluating alternative P&T well network designs. Our findings highlight the potential of advanced machine learning models to significantly enhance the efficiency and sustainability of groundwater remediation efforts, offering a novel application of U-Net architecture in environmental science.

Pump-and-treat↗

DOE OSTI2020

Simplified Performance Rating Method - Review of Existing Tools, Rulesets, and Programs. Literature and technical review

The Performance Rating Method (PRM) in ASHRAE Standard 90.1 (ASHRAE 2016) is a simulation ruleset for establishing minimum code compliance and for rating a building’s beyond-code applications. Building energy modeling (BEM) to comply with the PRM is often expensive and time consuming due to the complexity of code requirements. The goal of this project is to develop and codify a simplified PRM (S-PRM) approach for commercial buildings that will expand the use of BEM for small or simple buildings by defining a low-cost, simplified approach for creating robust and detailed models. This report summarizes a review of (i) the more commonly used existing codes, (ii) incentive programs, and (iii) the existing simplified energy modeling tools to identify which requirements are good candidates for simplification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1991

Experiments with simplified computed-torque controllers for free-flying robots

The effect of neglecting base accelerations in an inertial space endpoint computed-torque (CT) controller is examined. Numerical simulations predict a rather wide set of conditions under which CT controllers can neglect base accelerations in their dynamic model with insignificant performance degradation. Two predictions are experimentally verified with a laboratory robot. These two experiments show that negligible additional endpoint controller error results with a simplified CT controller for the given robot mass parameters and manipulator articulation.

Koningstein, R.↗

NASA NTRS1983

Modeling of turbulent separated flows for aerodynamic applications

Steady, high speed, compressible separated flows modeled through numerical simulations resulting from solutions of the mass-averaged Navier-Stokes equations are reviewed. Emphasis is placed on benchmark flows that represent simplified (but realistic) aerodynamic phenomena. These include impinging shock waves, compression corners, glancing shock waves, trailing edge regions, and supersonic high angle of attack flows. A critical assessment of modeling capabilities is provided by comparing the numerical simulations with experiment. The importance of combining experiment, numerical algorithm, grid, and turbulence model to effectively develop this potentially powerful simulation technique is stressed.

Marvin, J. G.↗

NASA NTRS1986

Modeling of turbulent separated flows for aerodynamic applications

Marvin, J. G.↗

DOE OSTI2024

Virtual Tokamak for Test and Development of Plasma Control Applied to NSTX-U

Safe and efficient operation of tokamak experiments depends on shot preparation prior to the experiment to maximize performance and avoid issues that are predictable consequences of known physics. The General Atomics TokSys toolbox is used to test and develop the plasma control system (PCS) on numerous tokamaks around the world. Tokamaks that use a version of the DIII-D PCS can connect it to a TokSys simulation and control a virtual version of the tokamak with the real PCS. Recent upgrades to the simulation include more detailed profile and transport modeling to support design and implementation of optimized scenarios. The simulation combines a module called “Profiles” that simulates the 1D profiles of density, pressure, and current and a module called “GSevolve'' that evolves the 2D Grad-Shafranov equilibrium. The “Profiles'' module primarily uses simplified models for fueling, heating, and current. The TRANSP code provides precomputed diffusion coefficients and heating/current drive profiles from radio-frequency and neutral beam sources for the scenarios being simulated. The fidelity of a simulation can be enhanced by analyzing it with TRANSP and making corrections to the precomputed values and iterating until convergence. Simulations of the National Spherical Torus Upgrade (NSTX-U) are presented. It is shown that the simulation reproduces the experimental profile evolution. Here, the simulation has also been upgraded to reproduce the experimental outcome at points of bifurcation. This is demonstrated with a simulation of vertical displacement in NSTX-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Simulating Marine Ecosystem Dynamics and Biogeochemical Cycling With Multiple Plankton Functional Types

Current representations of marine ecosystems in Earth System Models are greatly simplified, neglecting key interactions between dynamic food webs, biogeochemistry, and climate change. We use the Marine Biogeochemistry Library code base within the Community Earth System Model 2.2.2 to create an expanded ecosystem model with eight phytoplankton groups and four zooplankton size classes (MARBL-8P4Z). Incorporating more specific plankton types and size classes has the potential to capture a wider range of possible behaviors of the ecosystem, its complex interactions with biogeochemistry, and its feedback to climate change. It also permits stronger observational constraints, including in situ group-specific biomass and various observational estimates of plankton community composition. MARBL-8P4Z broadly captures observed global-scale patterns in biomass and community composition for both phytoplankton and zooplankton, with a good performance in simulating broad biogeochemistry fields. The model shows comparable spatial patterns and magnitudes to the observed picophytoplankton biomass (Prochlorococcus, Synechococcus, picoeukaryotes), and captures the seasonal cycle of mesozooplankton biomass. Picophytoplankton groups and microzooplankton dominate biomass and production in oligotrophic, subtropical regions, while nano-phytoplankton, diatoms and the larger zooplankton groups prevail at higher latitudes and within upwelling zones. The model simulates reasonable energy transfer efficiency through the food web, with tight linkages between the phytoplankton community composition, zooplankton grazing, and carbon export, with the potential to link to fisheries models. Thus, MARBL-8P4Z has the potential to account for key climate-driven ecological shifts in the plankton that will modify ocean biogeochemistry in the future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Development of a conduction-based model for analyzing frozen startup of alkali-metal heat pipes

One key area of interest in heat pipe modeling/simulation is to analyze the startup behavior of the liquid-metal heat pipes (LMHPs) from a frozen state. This so-called ‘frozen startup’ process involves a complex set of nonlinear mass and heat transport phenomena, including phase transitions from solid to liquid and vapor, multiphase interactions, microporous wick flow, and compressible vapor dynamics. The complexity of these processes makes it challenging to simulate LMHP’s frozen startup using conventional numerical methods or commercial computational fluid dynamics (CFD) software. This paper presents a simplified conduction-based modeling approach that can provide practical insights into the entire LMHP frozen startup process, while alleviating the challenges of modeling its complex physics. The theoretical foundation and physical assumptions of the proposed model are based solely on heat-conduction equation, allowing for a more tractable simulation without sacrificing essential physical accuracy. The proposed model was implemented in a commercial CFD software, and its prediction was compared with the experimental data obtained from sodium heat-pipe startup experiments. The comparison highlights the proposed model's ability to capture the transient thermal behavior of LMHP during frozen startup. This study not only validates the conduction-based frozen startup modeling method but also shows its potential as a practical and efficient tool for understanding the startup performance of the LMHP systems.

Microreactor↗

DOE OSTI2021

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗

NASA NTRS1991

The biasing scheme in N-body simulations

A popular prescription for the galaxy formation, i.e., identifying peaks in the linear density field as sites of galaxy formation, is numerically justified under the Cold Dark Matter cosmogony. In particular, the peak-background scheme, originally developed to simplify analytic calculations of peak properties in a Gaussian random density field, is proven to be an excellent prescription for assigning peak tracers in low-resolution N-body simulations through many statistical comparisons. It is found that statistical properties of peak tracers allocated by the peak-background scheme closely resemble those of true peaks when the background smoothing length is about three times the galaxy scale and the correspondence improves as they evolve gravitationally. It is also shown that these peak particles are indeed strongly associated with nonlinear objects that are presently collapsed.

Park, Changbom↗