Search NASA⌕ Search

SEARCH · Search NASA

Results for “physical simulation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Bayesian Framework for Milling Stability Prediction and Reverse Parameter Identification

This paper describes a physics-guided Bayesian framework for identifying the milling stability boundary and system parameters through iterative testing. Prior uncertainties for the parameters are identified through physical simulation and literature reviews, without physical testing of the actual milling system. Those uncertainties are then propagated to the stability map using a physics-based stability model, which is used to suggest a test point. The uncertainties are updated based on the new information acquired from the cutting test to form a new probability distribution, called the posterior. Finally, the posterior are compared to measured values for the stability boundary and system parameters to evaluate the approach. Based on experimental observations, the advantages and disadvantages of using a physics-guided model are discussed.

Cornelius, Aaron↗
DOE OSTI2022

Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs

Abstract Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hands-on with OWL: the Oak–Ridge Wang–Landau Monte Carlo software suite

The Oak–Ridge Wang–Landau (OWL) package is an open-source scientific software specialized for large-scale, Monte Carlo simulations for the study of materials properties at finite temperature. In this paper, we discuss the main features and capabilities of OWL, followed by detailed descriptions of building and running the code. The readers will be guided through the usage and functionality of the code with a few hands-on examples. This paper is based on a tutorial on OWL given at the 32nd Center for Simulational Physics Workshop on Recent Developments in Computer Simulation Studies in Condensed Matter Physics.

Li, Ying Wai↗
NASA NTRS2021

SoMo: Fast and Accurate Simulations of Continuum Robots in Complex Environments

Engineers and scientists often rely on their intuition and experience when designing soft robotic systems. The development of performant controllers and motion plans for these systems commonly requires time-consuming iterations on hardware. We present the SoMo (Soft Motion) toolkit, a software framework that makes it easy to instantiate and control typical continuum manipulators in an accurate physics simulator. SoMo introduces a standardized and human-readable description format for continuum manipulators. It leverages this description format and the Bullet physics engine to enable fast and accurate simulations of soft and soft-rigid hybrid robots in environments with complex contact interactions. This allows users to vary design and control parameters across simulations with minimal effort. We compare the capabilities of SoMo to other physics simulators and highlight the benefits and accuracy of SoMo by demonstrating the agreement between simulation and real-world experiments on several examples; these include an in-hand manipulation task with continuum fingers, an automated exploration of how to design soft fingers for precision grasping, and a brief snake locomotion study. Overall, SoMo provides an accessible way for designers of soft robotic hardware and control systems to gain access to a simulation-accelerated workflow.

Moritz A. Graule↗
DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗
DOE OSTI2021

PUMIPic: A mesh-based approach to unstructured mesh Particle-In-Cell on GPUs

Unstructured mesh particle-in-cell, PIC, simulations executing on the current and next generation of massively parallel systems require new methods for both the mesh and particles to achieve performance and scalability on GPUs. The traditional approach to implementing PIC simulations defines data structures and algorithms in terms of particles with a full copy of the unstructured mesh on every process. To effectively scale the unstructured mesh and particles, mesh-based PIC uses the unstructured mesh as the predominant data structure with the particles stored in terms of the mesh entities. Here, this paper details the PUMIPic library, a framework for developing efficient and performance-portable mesh-based PIC simulations on GPU systems. A pseudo physics simulation based on a five-dimensional gyro-kinetic code for modeling plasma physics is used to examine the performance of PUMIPic. Scaling studies of the unstructured mesh partition and number of particles are performed up to 4096 nodes of the Summit system at Oak Ridge National Laboratory. The studies show that mesh-based PIC can utilize a partitioned mesh and maintain scaling up to system limitations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Accelerating Flash-X Simulations with Asynchronous I/O

Most high-fidelity physics simulation codes, such as Flash-X, need to save intermediate results (checkpoint files) to restart or gain insights into the evolution of the simulation. These simulation codes save such intermediate files synchronously, where computation is stalled while the data is written to storage. Depending on the problem size and computational requirements, this file write time can be a substantial portion of the total simulation time. In order to hide the I/O latency of checkpointing, asynchronous I/O methods have been introduced. These methods use background threads for performing I/O while the main threads continue with the simulation. The usage of background threads can compete for resources on the node as well as with communication. In this paper, we evaluate the overheads and the overall benefit of asynchronous I/O in HDF5 to simulations. Results from real-world high-fidelity simulations on the Summit supercomputer show that I/O operation is overlapped with application communication or computation or both, effectively hiding some or all of the I/O latency. Our evaluation shows that while using asynchronous I/O adds overhead to the application, the I/O time reduction is more significant, resulting in overall up to 1.5X performance speedup.

Jain, Rajeev↗
DOE OSTI2014

SU-E-T-241: Monte Carlo Simulation Study About the Prediction of Proton-Induced DNA Strand Breakage On the Double Helix Structure

Purpose: In particle therapy and radiobiology, the investigation of mechanisms leading to the death of target cancer cells induced by ionising radiation is an active field of research. Recently, several studies based on Monte Carlo simulation codes have been initiated in order to simulate physical interactions of ionising particles at cellular scale and in DNA. Geant4-DNA is the one of them; it is an extension of the general purpose Geant4 Monte Carlo simulation toolkit for the simulation of physical interactions at sub-micrometre scale. In this study, we present Geant4-DNA Monte Carlo simulations for the prediction of DNA strand breakage using a geometrical modelling of DNA structure. Methods: For the simulation of DNA strand breakage, we developed a specific DNA geometrical structure. This structure consists of DNA components, such as the deoxynucleotide pairs, the DNA double helix, the nucleosomes and the chromatin fibre. Each component is made of water because the cross sections models currently available in Geant4-DNA for protons apply to liquid water only. Also, at the macroscopic-scale, protons were generated with various energies available for proton therapy at the National Cancer Center, obtained using validated proton beam simulations developed in previous studies. These multi-scale simulations were combined for the validation of Geant4-DNA in radiobiology. Results: In the double helix structure, the deposited energy in a strand allowed to determine direct DNA damage from physical interaction. In other words, the amount of dose and frequency of damage in microscopic geometries was related to direct radiobiological effect. Conclusion: In this report, we calculated the frequency of DNA strand breakage using Geant4- DNA physics processes for liquid water. This study is now on-going in order to develop geometries which use realistic DNA material, instead of liquid water. This will be tested as soon as cross sections for DNA material become available in Geant4-DNA.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1987

On direct numerical simulations of turbulent reacting flows

A description of the emerging field of direct numerical simulations of turbulent, chemically reacting flows is presented. The types of direct numerical simulations, physical issues related to implementing the simulations, as well as the various numerical methods used are described. Examples are presented of recent applications of direct numerical simulations to a variety of problems, displaying both the potential of the method and also some of its limitations. Finally, our view of the potential role of direct numerical simulations in future research on turbulent, chemically reacting flows is presented.

Jou, W.-H.↗
NASA NTRS2026

NASA JSC’s Simulant Development Lab Capabilities and Artemis Testing

The Simulant Development Lab (SDL) is a multifunctional collaborative workspace that supports the development, curation, analysis, testing, and distribution of planetary regolith simulants – including lunar, Martian, asteroidal, and other granular materials. The lab provides a multidisciplinary setting for scientific characterization of simulant physical properties and for engineering evaluations conducted with simulant test beds. To enable this work, the SDL curates and maintains a stock of more than 35 metric tons of simulant material. To evaluate these materials and support testing goals, the lab is equipped with a comprehensive suite of processing tools and analytical instruments. These capabilities enable the SDL’s mission at NASA’s Johnson Space Center to distribute, develop, process, characterize, and test regolith simulants for mission relevant applications. Through controlled and repeatable testing environments that replicate the physical and compositional properties of lunar regolith, the SDL supports Artemis hardware maturation, providing safe, Earth‑based analogs for evaluating systems that must withstand regolith dust interactions, physical wear and abrasion, and operational loads. The facility’s extensive simulant inventory and integrated geological and engineering test infrastructure accelerate technology readiness for Artemis and future exploration campaigns (e.g., future crewed or robotic missions to Mars).

Simulant Development Lab↗
DOE OSTI2017

Transient Simulation of the Multi-SERTTA Experiment with MAMMOTH

This work details the MAMMOTH reactor physics simulations of the Static Environment Rodlet Transient Test Apparatus (SERTTA) conducted at Idaho National Laboratory in FY-2017. TREAT static-environment experiment vehicles are being developed to enable transient testing of Pressurized Water Reactor (PWR) type fuel specimens, including fuel concepts with enhanced accident tolerance (Accident Tolerant Fuels, ATF). The MAMMOTH simulations include point reactor kinetics as well as spatial dynamics for a temperature-limited transient. The strongly coupled multi-physics solutions of the neutron flux and temperature fields are second order accurate both in the spatial and temporal domains. MAMMOTH produces pellet stack powers that are within 1.5% of the Monte Carlo reference solutions. Some discrepancies between the MCNP model used in the design of the flux collars and the Serpent/MAMMOTH models lead to higher power and energy deposition values in Multi-SERTTA unit 1. The TREAT core results compare well with the safety case computed with point reactor kinetics in RELAP5-3D. The reactor period is 44 msec, which corresponds to a reactivity insertion of 2.685% delta k/k$. The peak core power in the spatial dynamics simulation is 431 MW, which the point kinetics model over-predicts by 12%. The pulse width at half the maximum power is 0.177 sec. Subtle transient effects are apparent at the beginning insertion in the experimental samples due to the control rod removal. Additional difference due to transient effects are observed in the sample powers and enthalpy. The time dependence of the power coupling factor (PCF) is calculated for the various fuel stacks of the Multi-SERTTA vehicle. Sample temperatures in excess of 3100 K, the melting point UO$_2$, are computed with the adiabatic heat transfer model. The planned shaped-transient might introduce additional effects that cannot be predicted with PRK models. Future modeling will be focused on the shaped-transient by improving the control rod models in MAMMOTH and adding the BISON thermo-elastic models and thermal-fluids heat transfer.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

FY25 MOOSE Usability Improvements: 3D Meshing Capabilities, Initiation of Geometry Support for Monte Carlo Tools, and Enhancement of MOOSE/Workbench User Input Interactions

Usability improvements have been made to MOOSE and Workbench in FY25 to enhance usability and user workflows. Assorted enhancement have been made to MOOSE’s intrinsic meshing capabilities in order to enable more flexible and complex meshing of nuclear reactor systems, in particular for 3D applications. Mesh generators have been added to perform operations such as batch mesh generation, surface mesh generation, and creation of 3D transition layers. These mesh generation capabilities make it much easier to generate high quality non-extruded 3D meshes. Additionally, work to integrate Monte Carlo reactor physics simulations into MOOSE-based multi-physics workflows has reached another milestone with the implementation of the Constructive Solid Geometry (CSG) base framework. This framework lays the foundation for mesh generators to offer the user a generic CSG output option (as opposed to a finite element mesh). To support users, workshop on the MOOSE Reactor Module was delivered which featured hands-on examples using the NEAMS Workbench on INL’s High Performance Computing system. Recent updates to the NEAMS Workbench, WASP, and the MOOSE language server have introduced several improvements aimed at making MOOSE-based simulation setup and input management faster, more accurate, and easier to use. Key capabilities that have been added include multi-tab-stop autocompletion, visual input diagnostics, developer-directed data visualizations, upgraded ParaView integration, and Workspace-level file tracking. Together, these changes make it easier for users to build, validate, and manage complex MOOSE-based simulation models — especially those involving reusable components, included files, and datasets. The improvements are designed to save time, reduce input errors, and help users get to a successful simulation run faster, with more confidence in the results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1992

Physical and digital simulations for IVA robotics

Space based materials processing experiments can be enhanced through the use of IVA robotic systems. A program to determine requirements for the implementation of robotic systems in a microgravity environment and to develop some preliminary concepts for acceleration control of small, lightweight arms has been initiated with the development of physical and digital simulation capabilities. The physical simulation facilities incorporate a robotic workcell containing a Zymark Zymate II robot instrumented for acceleration measurements, which is able to perform materials transfer functions while flying on NASA's KC-135 aircraft during parabolic manuevers to simulate reduced gravity. Measurements of accelerations occurring during the reduced gravity periods will be used to characterize impacts of robotic accelerations in a microgravity environment in space. Digital simulations are being performed with TREETOPS, a NASA developed software package which is used for the dynamic analysis of systems with a tree topology. Extensive use of both simulation tools will enable the design of robotic systems with enhanced acceleration control for use in the space manufacturing environment.

Hinman, Elaine↗
DOE OSTI2021

Physics Studies for the LBNF Graphite Target Design

We present the simulated physics performance of the Long-Baseline Neutrino Facility (LBNF) graphite target that is being designed by the RAL High Power Targets Group for the Deep Underground Neutrino Experiment (DUNE). We first compare three conceptual cylindrical target design options as a function of target length (up to 2.2 m): downstream supported, two individual targets and an upstream-supported cantilever. Choosing the cantilever design as the baseline, we show the effect of widening the upstream inner conductor of the first focusing horn to provide extra space for supporting the target. We also give estimates of the expected performance of the 1.5 m prototype and 1.8 m production cantilevered targets. Furthermore, we show the effects of the main engineering updates made to the other two focusing horns since the DUNE TDR.

43 PARTICLE ACCELERATORS↗
NASA NTRS1989

Direct simulation of rarefied hypersonic flows

As the capability of the space transportation vehicles (STV's) expand to meet the requirements for future space exploration and utilization, the effects of rarefied hypersonic flows will play a more significant role in defining the aerodynamic and aerothermodynamic performance of STV's. This is particularly true of the low lift/drag aeroassisted STV's where aerobraking occurs at relatively high altitudes and high velocity. Because of the limitations of the continuum description as expressed by the Navier-Stokes equations and the difficulties of solving the Boltzmann equation, the particle of molecular approach has been developed over the last three decades for modeling rarefied gas effects. The direct simulation Monte Carlo (DSMC) method of Bird is the most used method today for simulating rarefied flows. The DSMC method provides a direct physical simulation as opposed to a numerical solution of a set of model equations. This is accomplished by developing phenomenological models of the relevant physical events. The DSMC method accounts for translational, thermal, chemical, and radiative nonequilibrium effects. The general features of the DSMC method, the numerical requirements for obtaining meaningful results, the modeling used to simulate high temperature gas effects, and applications of the method to calculate the flow about an aeroassist flight experiment vehicle (AFE) are reviewed. The AFE simulates a geosynchronous return while entering the Earth's upper atmosphere at approximately 10 km/s. Results obtained using a general 3-D code are presented for the more rarefied portion of the atmospheric encounter (altitudes of 200 to 100 km) emphasizing surface, flowfield, and aerodynamic characteristics of the AFE. Finally, results obtained using axisymmetric and 1-D versions of the code are presented for lower altitude conditions.

Moss, James N.↗
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Failure investigation of nuclear grade POCO graphite target in high energy neutrino physics through numerical simulation

In many high energy physics neutrino beamlines, targets are made up of isotropic POCO graphite grade for production of neutrinos for high energy particle physics research and are bombarded with highly energetic pulsed proton beam. The pulsed proton beam with a small beam size creates thermal stress waves as well as radiation damage such as displacement damage, void formation, swelling, and gas formation amongst others. As a result, after a few years of operation one of the longest operated targets appears to have undergone bulk swelling and fractured along the beam centerline. A complex interaction of dynamic loading due to beam, material degradation due to irradiation are thought to have caused such a failure. Here, we present a numerical simulation to capture the combined effects of swelling and the dynamic effect of thermal stress waves due to beam heating, to explain the failure of target. An empirical formula has been developed to take into account swelling as a function of temperature and proton fluence and has been implemented in a commercial finite element code. Extensive X-ray diffraction (XRD) were performed on graphite samples from the failed target to understand the lattice parameter changes due to irradiation and build a valid empirical model. Simulation results show that swelling plays a major role in elevating the stress state in the material exceeding the failure strength while the pulsed beam heating also introduces fatigue loading that would explain brittle fracture emanating from inside of the material and propagating outward. Such empirical formulations will help in identifying the threshold values of critical parameters to extend the service life of future multi-megawatt neutrino targets and targets in other accelerator environments.

43 PARTICLE ACCELERATORS↗