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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

The Use of Microgravity Simulators for Space Research

The spaceflight environment is known to influence biological processes ranging from stimulation of cellular metabolism to possible impacts on cellular damage repair, suppression of immune functions, and bone loss in astronauts. Microgravity is one of the most significant stress factors experienced by living organisms during spaceflight, and therefore, understanding cellular responses to altered gravity at the physiological and molecular level is critical for expanding our knowledge of life in space. Since opportunities to conduct experiments in space are scarce, various microgravity simulators and analogues have been widely used in space biology ground studies. Even though simulated microgravity conditions have produced some, but not all of the biological effects observed in the true microgravity environment, they provide test beds that are effective, affordable, and readily available to facilitate microgravity research. A Micro-g Simulator Center is being developed at Kennedy Space Center (KSC) to offer a variety of microgravity simulators and platforms for Space Biology investigators. Assistance will be provided by both KSC and external experts in molecular biology, microgravity simulation, and engineering. Comparisons between the physical differences in microgravity simulators, examples of experiments using the simulators, and scientific questions regarding the use of microgravity simulators will be discussed.

Simulation↗
NASA NTRS2016

The Use of Microgravity Simulators for Space Research

The spaceflight environment is known to influence biological processes ranging from stimulation of cellular metabolism to possible impacts on cellular damage repair, suppression of immune functions, and bone loss in astronauts. Microgravity is one of the most significant stress factors experienced by living organisms during spaceflight, and therefore, understanding cellular responses to altered gravity at the physiological and molecular level is critical for expanding our knowledge of life in space. Since opportunities to conduct experiments in space are scarce, various microgravity simulators and analogues have been widely used in space biology ground studies. Even though simulated microgravity conditions have produced some, but not all of the biological effects observed in the true microgravity environment, they provide test beds that are effective, affordable, and readily available to facilitate microgravity research. Kennedy Space Center (KSC) provides ground microgravity simulator support to offer a variety of microgravity simulators and platforms for Space Biology investigators. Assistance will be provided by both KSC and external experts in molecular biology, microgravity simulation, and engineering. Comparisons between the physical differences in microgravity simulators, examples of experiments using the simulators, and scientific questions regarding the use of microgravity simulators will be discussed.

Simulation↗
NASA NTRS1993

Energy content of stormtime ring current from phase space mapping simulations

We perform a phase space mapping study to estimate the enhancement in energy content that results from stormtime particle transport in the equatorial magnetosphere. Our pre-storm phase space distribution is based on a steady-state transport model. Using results from guiding-center simulations of ion transport during model storms having main phases of 3 hr, 6 hr, and 12 hr, we map phase space distributions of ring current protons from the pre-storm distribution in accordance with Liouville's theorem. We find that transport can account for the entire ten to twenty-fold increase in magnetospheric particle energy content typical of a major storm if a realistic stormtime enhancement of the phase space density f is imposed at the nightside tail plasma sheet (represented by an enhancement of f at the neutral line in our model).

Chen, Margaret W.↗
NASA NTRS2009

A Process for Comparing Dynamics of Distributed Space Systems Simulations

The paper describes a process that was developed for comparing the primary orbital dynamics behavior between space systems distributed simulations. This process is used to characterize and understand the fundamental fidelities and compatibilities of the modeling of orbital dynamics between spacecraft simulations. This is required for high-latency distributed simulations such as NASA s Integrated Mission Simulation and must be understood when reporting results from simulation executions. This paper presents 10 principal comparison tests along with their rationale and examples of the results. The Integrated Mission Simulation (IMSim) (formerly know as the Distributed Space Exploration Simulation (DSES)) is a NASA research and development project focusing on the technologies and processes that are related to the collaborative simulation of complex space systems involved in the exploration of our solar system. Currently, the NASA centers that are actively participating in the IMSim project are the Ames Research Center, the Jet Propulsion Laboratory (JPL), the Johnson Space Center (JSC), the Kennedy Space Center, the Langley Research Center and the Marshall Space Flight Center. In concept, each center participating in IMSim has its own set of simulation models and environment(s). These simulation tools are used to build the various simulation products that are used for scientific investigation, engineering analysis, system design, training, planning, operations and more. Working individually, these production simulations provide important data to various NASA projects.

Cures, Edwin Z.↗
DOE OSTI2026

The Memory Scaling of Reverse-Mode Differentiation in Particle Accelerator Simulations with Space Charge

The recent development of differentiable simulation codes for particle accelerators has enabled gradient-based workflows that promise finer control and more realistic modeling of accelerator facilities. However, when using reverse-mode automatic differentiation, the memory usage continuously increases during the simulation, and can potentially exceed the available hardware memory - especially when costly space charge computation is included. To study the memory requirements for differentiable simulations, we have implemented space charge in Cheetah, a PyTorch-based beam tracking code that supports reverse-mode differentiation. We find that the memory usage for reverse-mode differentiation grows linearly with the number of macroparticles and cells, and that it is proportional to the number of space charge kicks involved in the simulation. This general scaling can be used to evaluate whether a given differentiable simulation is feasible given hardware memory constraints.

Dhamrait, Arjun↗
NASA NTRS2003

High Performance Parallel Methods for Space Weather Simulations

This is the final report of our NASA AISRP grant entitled 'High Performance Parallel Methods for Space Weather Simulations'. The main thrust of the proposal was to achieve significant progress towards new high-performance methods which would greatly accelerate global MHD simulations and eventually make it possible to develop first-principles based space weather simulations which run much faster than real time. We are pleased to report that with the help of this award we made major progress in this direction and developed the first parallel implicit global MHD code with adaptive mesh refinement. The main limitation of all earlier global space physics MHD codes was the explicit time stepping algorithm. Explicit time steps are limited by the Courant-Friedrichs-Lewy (CFL) condition, which essentially ensures that no information travels more than a cell size during a time step. This condition represents a non-linear penalty for highly resolved calculations, since finer grid resolution (and consequently smaller computational cells) not only results in more computational cells, but also in smaller time steps.

Hunter, Paul↗