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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Visualization of supercomputer simulations in physics

A description is given of the hardware and software tools and techniques in use at NASA's Numerical Aerodynamic Simulation Facility for visualization of computational fluid dynamics. The hardware consists of high-performance graphics workstations connected to the supercomputer with high-bandwidth lines, a frame buffer connected to the supercomputer with UltraNet, a digital video recording system, and film recorders. The software permits the scientist to view the three-dimensional scenes dynamically, to zoom into a region of interest, and to rotate his viewing position to study any region of interest in more detail. The software also provides automated animation and video recording of the scenes. The digital effects unit on the video system facilitates comparison of computer simulations with flight or wind tunnel experiments.

Watson, Val↗
DOE OSTI2024

Multi-physics Modeling of Radiative Heat Transfer and Fluid Flow for the Reactor Cavity Cooling System

High-temperature gas-cooled reactors (HTGRs) are notable for their high thermal efficiency and potential for combined heat and power applications. These reactors are particularly appealing due to their advanced passive safety features. HTGRs utilize passive safety systems that function without requiring active components like pumps or compressors during emergencies. These reactor designs depend on a Reactor Cavity Cooling System (RCCS) to manage decay heat removal from the reactor pressure vessel (RPV) during accident conditions. The RCCS consists of vertical rectangular channels known as "risers" or riser ducts positioned around the RPV. These risers receive heat from the RPV through both convective and radiative heat transfer mechanisms. Understanding the interplay of multiple physical phenomena, such as fluid dynamics, heat transfer, and neutron interactions, is essential for the effective design and operation of nuclear reactors, particularly for systems like the RCCS. Multi-physics simulations provide a comprehensive approach to studying these interactions, offering detailed insights and enhancing accuracy. They are especially important in RCCS designs, where the interaction between radiative and convective heat transfer can significantly impact system performance. By leveraging multi-physics simulations, complex reactor behaviors can be modeled without compromising the fidelity of the underlying physical processes. This work aims to establish a robust methodology for coupling multiple physical processes in an air-cooled RCCS. By focusing on validating this multi-physics approach, the study involves designing test cases that simulate various conditions to verify the numerical models employed. The outcomes of this research will provide critical insights for accurately modeling and optimizing complex nuclear systems like the RCCS.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Optimization-Based Parametric Design via High-Fidelity Simulation: Overview + Examples

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This talk presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation and includes example applications related to rigid wheel design for autonomous rovers and computational fluid dynamics.

optimization↗
NASA NTRS1998

An Ecosystem Model for the Simulation of Physical and Biological Oceanic Processes-IDAPAK User's Guide and Applications

This TM describes the development, testing, and application of a 4-component (phytoplankton, zooplankton, nitrate, and ammonium) ecosystem model capable of simulating oceanic biological processes. It also reports and documents an in-house software package (Interactive Data Analysis Package - IDAPAK) for interactive data analysis of geophysical fields, including those related to the forcing, verification, and analysis of the ecosystem model. Two regions were studied in the Pacific: the Warm Pool (WP) in the Equatorial Pacific (165 deg. E at the equator) and at Ocean Weather Station P (OWS P) in the Northeast Pacific (50 deg. N, 145 deg. W). The WP results clearly indicate that the upwelling at 100 meters correlates well with surface blooms. The upwelling events in late 1987 and 1990 produced dramatic increases in the surface layer values of all 4 ecosystem components, whereas the spring-summer deep mixing events, do not seem to incur a significant response in any of the ecosystem quantities. The OWS P results show that the monthly profiles of temperature, the annual cycles of solar irradiance, and 0- to 50-m integrated nitrate accurately reproduce observed values. Annual primary production is 190 gC/m(exp 2)/yr, which is consistent with recent observations but is much greater than earlier estimates.

McClain, Charles R.↗
NASA NTRS2017

Mapping the Limitations of Breakthrough Analysis in Fixed-Bed Adsorption

The separation of gases through adsorption plays an important role in the chemical processing industry, where the separation step is often the costliest part of a chemical process and thus worthy of careful study and optimization. This work developed a number of new, archival aspects on the computer simulations used for the refinement and design of these gas adsorption processes: 1. Presented a new approach to fit the undetermined heat and mass transfer coefficients in the axially dispersed plug flow equation and associated balance equations 2. Examined and described the conditions where non-physical simulation results can arise 3. Presented an approach to determine the limits of the axial dispersion and LDF mass transfer terms above which non-physical simulation results occur.

Knox, James Clinton↗
NASA NTRSDate not supplied

An Optimization-Based Toolchain for Parametric Mechanism Design

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This work presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation. The toolchain enables multi-objective optimization, generates parametric CAD files that can be further post-processed by an end user, and can be expanded to optimize full systems and non-mechanical parameters such as feedback control variables. We demonstrate the toolchain through an independently verifiable design problem that optimizes wheel radius to achieve a desired linear velocity in a rigid-body physics environment when the wheel rotates at a constant angular speed, and then post-process the parametric CAD file of the optimal design generated by the tool before ultimately manufacturing it via 3D printing. We end with a discussion of how the toolchain can incorporate other analysis tools, including finite element analysis, computational fluid dynamics, and granular media simulations.

Optimization↗
NASA NTRSDate not supplied

Inlet Radiated Noise Predictions for the NASA Source Diagnostic Test Fan Using Physics-Based Simulations

Commercial supersonic aircraft are expected to produce considerably more noise during landing and take-off operations than existing subsonic aircraft. Establishing noise regulation is challenging because no examples of this aircraft type are currently flying. Existing aircraft noise prediction tools can be used, but the noise source models for these empirical tools are typically based on data from subsonic aircraft components. The present work documents a procedure for using physics-based computational tools to generate the propagating sound field radiating out the nacelle inlet. Although no analytical source modeling is demonstrated, these tools utilize measured data to compare the complex pressure for various propagating modes. The discrepancies found in applying the propagation tools to the subsonic inlet will be ascribed to calculations of supersonic inlets being used to update current empirical noise prediction tools.

Noise Predictions↗
DOE OSTI2026

Surrogate model for third-integer resonance extraction at the Fermilab Delivery Ring

We present an ongoing work in which a surrogate model is being developed to reproduce the response dynamics of the third-integer resonant extraction process in the Delivery Ring (DR) at Fermilab. This is in pursuit of smoothly extracting circulating beam to the Mu2e Experiment’s production target, whereby the goal is to extract a uniform slice of the circulating 1e12 protons in the DR over 25,000 turns (43 ms). The DR contains 3 harmonic sextupoles that excite a third-integer resonance and three fast, tune-ramping quadrupole magnets that drive the horizontal tune towards the 29/3 resonance. In our initial work, the surrogate model trains on a semi-analytical simulation provided in the same format as live data. Using Reinforcement Learning (and other potential ML methods), the trained surrogate acts as the “environment” in which a simple ML control agent could learn to dynamically adjust the quadrupole ramp at 430 break points within the 43 microsecond spill window. The controller will be hosted on a dedicated Arria 10 FPGA. In this work, we report the accuracy and fidelity of the surrogate model in comparison to the response dynamics of the physics simulator.

Narayanan, Aakaash [Fermilab]↗
DOE OSTI2025

Integrating HPC simulations and physical experiments to characterize the effects of gamma radiation on seismic protective devices

Seismic protective systems, composed of seismic isolators and dampers, can substantially reduce the effects of earthquake shaking on nuclear power plants and components therein. To enable the use of these devices to protect equipment inside a plant and close to a source of radiation, the U.S. Department of Energy (DOE) funded a project at the Idaho National Laboratory (INL) and the University at Buffalo to characterize the effects of absorbed gamma dose on their mechanical properties. An early task in the project was to determine the exposure time required in the INL Foss Therapy Services (FTS) 60 Co gamma irradiator to achieve a target absorbed dose in the materials used to construct isolators and dampers, including fluids, polymers, composites, and metals. This task required the novel integration of high-performance computing (HPC), Monte Carlo N-Particle (MCNP) simulations, and irradiation experiments using Fricke dosimetry. An MCNP model of the FTS irradiator at INL was developed and validated using Fricke dosimetry. Simulations of three experiments in the irradiator, two with Fricke vials only and one with Fricke vials and a large-size isolator, predicted the Fricke-measured absorbed dose rate to within 15% in all three cases, providing high confidence in the calculation of the gamma dose absorbed in the materials comprising the seismic protective devices. The simulations demonstrated that the effects of photon scattering on absorbed dose rate in the FTS irradiator are negligible for test articles installed close to the cobalt sources and near the rear of the irradiator. The validated MCNP model of the FTS irradiator is being used to support ongoing DOE-funded experiments on seismic protective devices and could be applied to future, non-seismic-related experiments. In conclusion, the novel validation process successfully deployed for the FTS irradiator at INL could be applied to other irradiators, requiring new MCNP models and simulations, and irradiation experiments using dosimeters.

42 - ENGINEERING↗
NASA NTRS2005

Physics-based Simulation of Human Posture Using 3D Whole Body Scanning Technology for Astronaut Space Suit Evaluation

Over the past few years high precision three-dimensional (3D) full body laser scanners have been developed to be used as a powerful anthropometry tool for quantification of the morphology of the human body. The full body scanner can quickly extract body characteristics in non-contact fashion. It is required for the Anthropometry and Biomechanics Facility (ABF) to have capabilities for kinematics simulation of a digital human at various postures whereas the laser scanner only allows capturing a single static posture at each time. During this summer fellowship period a theoretical study has been conducted to estimate an arbitrary posture with a series of example postures through finite element (FE) approximation and found that four-point isoparametric FE approximation would result in reasonable maximum position errors less than 5%. Subsequent pilot scan experiments demonstrated that a bead marker with a nominal size of 6 mm could be used as a marker for digitizing 3-D coordinates of anatomical landmarks for further kinematic analysis. Two sessions of human subject testing were conducted for reconstruction of an arbitrary postures from a set of example postures for each joint motion for the forearm/hand complex and the whole upper extremity.

Kim, Kyu-Jung↗
NASA NTRS2016

Decision Manifold Approximation for Physics-Based Simulations

With the recent surge of success in big-data driven deep learning problems, many of these frameworks focus on the notion of architecture design and utilizing massive databases. However, in some scenarios massive sets of data may be difficult, and in some cases infeasible, to acquire. In this paper we discuss a trajectory-based framework that quickly learns the underlying decision manifold of binary simulation classifications while judiciously selecting exploratory target states to minimize the number of required simulations. Furthermore, we draw particular attention to the simulation prediction application idealized to the case where failures in simulations can be predicted and avoided, providing machine intelligence to novice analysts. We demonstrate this framework in various forms of simulations and discuss its efficacy.

Wong, Jay Ming↗