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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

TH-A-19A-07: The Effect of Particle Tracking Step Size Limit On Monte Carlo- Computed LET Spectrum of Therapeutic Proton Beams

Purpose: To investigate the effect of charged particle tracking step size limit in the determination of the LET spectrum of therapeutic proton beams using Monte Carlo simulations. Methods: The LET spectra at different depths in a water phantom from a 79.7 MeV spot-scanning proton beam were calculated using Geant4. Five different tracking step limits 0.5 mm, 0.1 mm, 0.05 mm, 0.01 mm and 1 μm were adopted. The field size was set to 10×10 cm{sup 2} on the isocenter plane. A 40×40×6 cm{sup 3} water phantom was modelled as the irradiation target. The voxel size was set to 1×1×0.5 mm{sup 3} to obtain high resolution results. The LET spectra were scored ranging from 0.01 keV/μm to 10{sup 4}keV/μm in the logarithm scale. In addition, the proton energy spectra at different depths were also scored. Results: The LET spectra calculated using different step size limits were compared at four depths along the Bragg curve. At any depths, the spread of the LET spectra increases with the decrease of step size limit. In the dose buildup region (z = 1.9 cm) and in the region proximal to the Bragg peak (z = 3.95 cm), the frequency mean LET does not vary with decreasing step size limit. At Bragg peak (z = 4.75 cm) and in the distal edge (z = 4.85 cm), frequency mean LET decreases with decreasing step size limit. The energy spectrum at any specified depths does not vary with the step size limit. Conclusion: The calculated LET has a spectral distribution rather than a single value at any depths along the Bragg curve and the spread of the computed spectrum depends on the tracking step limit. Incorporating the LET spectrum distribution into the robust IMPT optimization plan may provide more accurate biological dose distribution than using the dose- or fluence-averaged LET. NIH Program Project Grant P01CA021239.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2013

Unraveling the Geometry Dependence of In-Nozzle Cavitation in High-Pressure Injectors

Cavitation is an intricate multiphase phenomenon that interplays with turbulence in fluid flows. It exhibits clear duality in characteristics, being both destructive and beneficial in our daily lives and industrial processes. Despite the multitude of occurrences of this phenomenon, highly dynamic and multiphase cavitating flows have not been fundamentally well understood in guiding the effort to harness the transient and localized power generated by this process. In a microscale, multiphase flow liquid injection system, we synergistically combined experiments using time-resolved x-radiography and a novel simulation method to reveal the relationship between the injector geometry and the in-nozzle cavitation quantitatively. We demonstrate that a slight alteration of the geometry on the micrometer scale can induce distinct laminar-like or cavitating flows, validating the multiphase computational fluid dynamics simulation. Furthermore, the simulation identifies a critical geometric parameter with which the high-speed flow undergoes an intriguing transition from non-cavitating to cavitating.

FLUID DYNAMICS↗
DOE OSTI2023

DSS-SimPy-RL (Open-DSS and SimPy based Cyber-Physical RL environment) [SWR-23-29]

Recently, numerous data-driven approaches to control an electric grid using machine learning techniques have been investigated. With the advancement of reinforcement learning (RL) based techniques, gradually the conventional optimization based solvers are being replaced with RL approach where there is uncertainty in the environment such as renewable generation or cyber system emulation. However, to train an agent efficiently, it requires numerous interactions with an environment to learn the best policies. There are numerous RL environments for the power systems based on some well-known simulators, similarly there are environment for communication domains. While majority of the cyber emulators are based in an UNIX environment, the power simulators are based in the Windows-based operating system, the generation of cyber-physical mixed domain RL environment has been challenging. Existing co-simulation methods are efficient but resource and time intensive to generate large scale data set for training RL agents. Hence, this software focuses on development and validation of a mixed domain RL environment using Open DSS for the physical side and leverages a discrete event simulator python package, SimPy, for cyber-side emulation which is Operating Systems agnostic. Further utilizing this software co-simulation and training RL agents for re-routing based resilient control for network reconfiguration and volt-var control in power distribution feeder are performed.

Sahu, Abhijeet↗
NASA NTRS1978

Monte Carlo solution of Boltzmann equation for a simple model of highly nonequilibrium diatomic gases - Translational rotational energy relaxation

Theoretical results pertaining to internally excited translational-rotational energy relaxation in a spatially uniform diatomic gas far removed from solid boundaries are obtained by solving the Boltzmann equation by means of the Monte Carlo direct simulation method. The analysis is based on calculations involving three different types of initial conditions: equilibrium, nonequilibrium-equipartition (i.e., equipartition is satisfied, but the distributions are perturbed), and nonequilibrium-nonequipartition (i.e., both equipartition and the distributions are perturbed). Results of monatomic-gas simulations are also included to facilitate comparisons with the coupled translational-rotational relaxation simulations, and some simulations for a normal shock-wave structure are briefly examined. The results show that: (1) single-step transitions are the significant mechanisms of intermodal energy transfer; (2) translational-rotational transitions are coupled most efficiently for low-lying states of rotationally excited molecules and least efficiently for highly rotationally excited molecules; and (3) relaxation occurs via a successive set of distributions that are not Maxwell-Boltzmann (nonlocal Maxwellian).

Yoshikawa, K. K.↗
DOE OSTI2013

Detector density and small field dosimetry: Integral versus point dose measurement schemes

Purpose: TheAlfonso et al. [Med. Phys.35, 5179–5186 (2008)] formalism for small field dosimetry proposes a set of correction factors (k{sub Q{sub c{sub l{sub i{sub n,Q{sub m{sub s{sub r}{sup f{sub c}{sub l}{sub i}{sub n},f{sub m}{sub s}{sub r}}}}}}}}}) which account for differences between the detector response in nonstandard (clinical) and machine-specific-reference fields. In this study, the Monte Carlo method was used to investigate the viability of such small field correction factors for four different detectors irradiated under a variety of conditions. Because k{sub Q{sub c{sub l{sub i{sub n,Q{sub m{sub s{sub r}{sup f{sub c}{sub l}{sub i}{sub n},f{sub m}{sub s}{sub r}}}}}}}}} values for single detector position measurements are influenced by several factors, a new theoretical formalism for integrated-detector-position [dose area product (DAP)] measurements is also presented and was tested using Monte Carlo simulations. Methods: A BEAMnrc linac model was built and validated for a Varian Clinac iX accelerator. Using the egs++ geometry package, detailed virtual models were built for four different detectors: a PTW 60012 unshielded diode, a PTW 60003 Diamond detector, a PTW 31006 PinPoint (ionization chamber), and a PTW 31018 MicroLion (liquid-filled ionization chamber). The egs-chamber code was used to investigate the variation ofk{sub Q{sub c{sub l{sub i{sub n,Q{sub m{sub s{sub r}{sup f{sub c}{sub l}{sub i}{sub n},f{sub m}{sub s}{sub r}}}}}}}}} with detector type, detector construction, field size, off-axis position, and the azimuthal angle between the detector and beam axis. Simulations were also used to consider the DAP obtained by each detector: virtual detectors and water voxels were scanned through high resolution grids of positions extending far beyond the boundaries of the fields under consideration. Results: For each detector, the correction factor (k{sub Q{sub c{sub l{sub i{sub n,Q{sub m{sub s{sub r}{sup f{sub c}{sub l}{sub i}{sub n},f{sub m}{sub s}{sub r}}}}}}}}}) was shown to depend strongly on detector off-axis position and detector azimuthal angle in addition to field size. In line with previous studies, substantial interdetector variation was also observed. However, it was demonstrated that by considering DAPs rather than single-detector-position dose measurements the high level of interdetector variation could be eliminated. Under small field conditions, mass density was found to be the principal determinant of water equivalence. Additionally, the mass densities of components outside the sensitive volumes were found to influence the detector response. Conclusions: k{sub Q{sub c{sub l{sub i{sub n,Q{sub m{sub s{sub r}{sup f{sub c}{sub l}{sub i}{sub n},f{sub m}{sub s}{sub r}}}}}}}}} values for existing detector designs depend on a host of variables and their calculation typically relies on the use of time-intensive Monte Carlo methods. Future moves toward density-compensated detector designs or DAP based protocols may simplify the methodology of small field dosimetry.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

How the choice of exchange–correlation functional affects DFT-based simulations of the hydrated electron

Hydrated electrons are anionic species that are formed when an excess electron is introduced into liquid water. Building an understanding of how hydrated electrons behave in solution has been a long-standing effort of simulation methods, of which density functional theory (DFT) has come to the fore in recent years. The ability of DFT to model the reactive chemistry of hydrated electrons is an attractive advantage over semi-classical methodologies; however, relatively few density functional approximations (DFAs) have been used for the hydrated electron simulations presented in the literature. Here, we simulate hydrated electron systems using a series of exchange–correlation (XC) functionals spanning Jacob’s ladder. We calculate a variety of experimental and other observables of the hydrated electron and compare the XC functional dependence for each quantity. We find that the formation of a stable localized hydrated electron is not necessarily limited to hybrid XC functionals and that some hybrid functionals produce delocalized hydrated electrons or electrons that react with the surrounding water at an unphysically fast rate. Here, we further characterize how different DFAs impact the solvent structure and predicted spectroscopy of the hydrated electron, considering several methods for calculating the hydrated electron’s absorption spectrum for the best comparison between structures generated using different density functionals. None of the dozen or so DFAs that we investigated are able to correctly predict the hydrated electron’s spectroscopy, vertical detachment energy, or molar solvation volume.

Ab-initio molecular dynamics↗
DOE OSTI2014

SU-E-T-565: RAdiation Resistance of Cancer CElls Using GEANT4 DNA: RACE

Purpose: The objective of the RACE project is to develop a comparison between Monte Carlo simulation using the Geant4-DNA toolkit and measurements of radiation damage on 3D melanoma and chondrosarcoma culture cells coupled with gadolinium nanoparticles. We currently expose the status of the developments regarding simulations. Methods: Monte Carlo studies are driven using the Geant4 toolkit and the Geant4-DNA extension. In order to model the geometry of a cell population, the opensource CPOP++ program is being developed for the geometrical representation of 3D cell populations including a specific cell mesh coupled with a multi-agent system. Each cell includes cytoplasm and nucleus. The correct modeling of the cell population has been validated with confocal microscopy images of spheroids. The Geant4 Livermore physics models are used to simulate the interactions of a 250 keV X-ray beam and the production of secondaries from gadolinium nanoparticles supposed to be fixed on the cell membranes. Geant4-DNA processes are used to simulate the interactions of charged particles with the cells. An atomistic description of the DNA molecule, from PDB (Protein Data Bank) files, is provided by the so-called PDB4DNA Geant4 user application we developed to score energy depositions in DNA base pairs and sugar-phosphate groups. Results: At the microscopic level, our simulations enable assessing microscopic energy distribution in each cell compartment of a realistic 3D cell population. Dose enhancement factors due to the presence of gadolinium nanoparticles can be estimated. At the nanometer scale, direct damages on nuclear DNA are also estimated. Conclusion: We successfully simulated the impact of direct radiations on a realistic 3D cell population model compatible with microdosimetry calculations using the Geant4-DNA toolkit. Upcoming validation and the future integration of the radiochemistry module of Geant4-DNA will propose to correlate clusters of ionizations with in vitro experiments. All those developments will be released publicly. This work was supported by grants from Plan Cancer 2009-2013 French national initiative managed by INSERM (Institut National de la Sante et de la Recherche Medicale)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Toward a microscopic picture of hadronization and multi-parton processes

This project advanced the understanding of how quarks and gluons produced in high-energy collisions transform into the hadrons observed in particle detectors, a fundamental process known as quantum chromodynamics (QCD) hadronization. By combining theoretical calculations, quantum simulation methods, and modern AI techniques, the research developed new tools to study multi-parton dynamics and nonperturbative effects that are essential for interpreting data from current and future nuclear physics experiments. Key outcomes include new theoretical frameworks for jet and hadron measurements, pioneering quantum simulation algorithms for real-time dynamics in field theories, and the development of advanced machine-learning models, such as diffusion models and explainable classifiers, to simulate and analyze collider events. These results are directly relevant to experiments at Jefferson Lab, Brookhaven National Laboratory, and the future Electron-Ion Collider, and they also have a broader impact in areas such as quantum information science and data-driven modeling of complex systems. The project supported the training of graduate students and postdoctoral fellows and contributed to the broader scientific community through publications, workshops, and collaborative activities. Overall, this work provides new insights into the microscopic mechanisms of hadron formation and establishes a foundation for future studies at the intersection of nuclear physics, artificial intelligence, and quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

SU-E-T-121: Analyzing the Broadening Effect On the Bragg Peak Due to Heterogeneous Geometries and Implementing User-Routines in the Monte-Carlo Code FLUKA in Order to Reduce Computation Time

Purpose: Aim of this study was to analyze the modulating, broadening effect on the Bragg Peak due to heterogeneous geometries like multi-wire chambers in the beam path of a particle therapy beam line. The effect was described by a mathematical model which was implemented in the Monte-Carlo code FLUKA via user-routines, in order to reduce the computation time for the simulations. Methods: The depth dose curve of 80 MeV/u C12-ions in a water phantom was calculated using the Monte-Carlo code FLUKA (reference curve). The modulating effect on this dose distribution behind eleven mesh-like foils (periodicity ∼80 microns) occurring in a typical set of multi-wire and dose chambers was mathematically described by optimizing a normal distribution so that the reverence curve convoluted with this distribution equals the modulated dose curve. This distribution describes a displacement in water and was transferred in a probability distribution of the thickness of the eleven foils using the water equivalent thickness of the foil’s material. From this distribution the distribution of the thickness of one foil was determined inversely. In FLUKA the heterogeneous foils were replaced by homogeneous foils and a user-routine was programmed that varies the thickness of the homogeneous foils for each simulated particle using this distribution. Results: Using the mathematical model and user-routine in FLUKA the broadening effect could be reproduced exactly when replacing the heterogeneous foils by homogeneous ones. The computation time was reduced by 90 percent. Conclusion: In this study the broadening effect on the Bragg Peak due to heterogeneous structures was analyzed, described by a mathematical model and implemented in FLUKA via user-routines. Applying these routines the computing time was reduced by 90 percent. The developed tool can be used for any heterogeneous structure in the dimensions of microns to millimeters, in principle even for organic materials like lung tissue.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

Wall-Resolved Large-Eddy Simulation of Flow Separation Over NASA Wall-Mounted Hump

This paper reports the findings from a study that applies wall-resolved large-eddy simulation to investigate flow separation over the NASA wall-mounted hump geometry. Despite its conceptually simple flow configuration, this benchmark problem has proven to be a challenging test case for various turbulence simulation methods that have attempted to predict flow separation arising from the adverse pressure gradient on the aft region of the hump. The momentum-thickness Reynolds number of the incoming boundary layer has a value that is near the upper limit achieved by recent direct numerical simulation and large-eddy simulation of incompressible turbulent boundary layers. The high Reynolds number of the problem necessitates a significant number of grid points for wall-resolved calculations. The present simulations show a significant improvement in the separation-bubble length prediction compared to Reynolds-Averaged Navier-Stokes calculations. The current simulations also provide good overall prediction of the skin-friction distribution, including the relaminarization observed over the front portion of the hump due to the strong favorable pressure gradient. We discuss a number of problems that were encountered during the course of this work and present possible solutions. A systematic study regarding the effect of domain span, subgrid-scale model, tunnel back pressure, upstream boundary layer conditions and grid refinement is performed. The predicted separation-bubble length is found to be sensitive to the span of the domain. Despite the large number of grid points used in the simulations, some differences between the predictions and experimental observations still exist (particularly for Reynolds stresses) in the case of the wide-span simulation, suggesting that additional grid resolution may be required.

Uzun, Ali↗
DOE OSTI2023

Ceramide-1-phosphate transfer protein enhances lipid transport by disrupting hydrophobic lipid–membrane contacts

Cellular distributions of the sphingolipid ceramide-1-phosphate (C1P) impact essential biological processes. C1P levels are spatiotemporally regulated by ceramide-1-phosphate transfer protein (CPTP), which efficiently shuttles C1P between organelle membranes. Yet, how CPTP rapidly extracts and inserts C1P into a membrane remains unknown. Here, we devise a multiscale simulation approach to elucidate biophysical details of CPTP-mediated C1P transport. We find that CPTP binds a membrane poised to extract and insert C1P and that membrane binding promotes conformational changes in CPTP that facilitate C1P uptake and release. By significantly disrupting a lipid’s local hydrophobic environment in the membrane, CPTP lowers the activation free energy barrier for passive C1P desorption and enhances C1P extraction from the membrane. Upon uptake of C1P, further conformational changes may aid membrane unbinding in a manner reminiscent of the electrostatic switching mechanism used by other lipid transfer proteins. Insertion of C1P into an acceptor membrane, eased by a decrease in membrane order by CPTP, restarts the transfer cycle. Most notably, we provide molecular evidence for CPTP’s ability to catalyze C1P extraction by breaking hydrophobic C1P–membrane contacts with compensatory hydrophobic lipid–protein contacts. Our work, thus, provides biophysical insights into how CPTP efficiently traffics C1P between membranes to maintain sphingolipid homeostasis and, additionally, presents a simulation method aptly suited for uncovering the catalytic mechanisms of other lipid transfer proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Utilizing a Novel Acoustic Backscatter Array to Characterize Waste Consolidation and Settling in a Horizontal Flow Clarifier - 16051

As part of a collaboration between the University of Leeds, Sellafield Ltd and MMI Engineering Ltd, bespoke acoustic instrumentation and numerical simulation methods have been established to optimize nuclear legacy waste transfers. Specifically, a new ultrasonic measurement system has been developed, allowing suspended particle concentration and consolidation to be measured remotely. This technology has been combined with computational fluid dynamics (CFD) modelling of settling particulate systems, permitting full characterization, simulation and prediction of sludge separation processes. Presented here are experimental and numerical results on the transport and settling behavior of non-active nuclear-analogue suspensions in two flow geometries: gravitational settling of glass dispersions in a 250-liter column; and transport and sedimentation of flocculated calcite in a close-to-full-scale clarifier (9 m{sup 3} total volume and 4.8 m{sup 2} length). In addition, details of the design, construction and calibration of a custom-built Ultrasonic Array Research Platform (UARP) are described. Settling column results suggested that particle concentration changes could be simulated with good accuracy by a CFD model (developed using the open source OpenFOAM framework) when compared to measured samples. Large-scale clarifier trials were used to assess the effectiveness of the UARP controller with an attached in situ acoustic backscatter array (ABA). The ABA consisted of 8 transducers angled down at 20 deg. to the vertical, pulsing at 2-2.5 MHz in cycles (covering 1.8 m total depth). In comparison to a range of sampled concentrations across the length of the clarifier, results confirmed that the UARP-ABA system was highly successful at characterizing these complex flows over several hours of operation, allowing visualization of depth-wise bulk density changes and bed build-up over time. Collectively, this work highlights the capability of these tools to monitor and optimize a number of current waste transfer operations at Sellafield, with further potential applications for solid-liquid separations across waste, water treatment and minerals engineering industries. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS1994

A method for the probabilistic design assessment of composite structures

A formal procedure for the probabilistic design assessment of a composite structure is described. The uncertainties in all aspects of a composite structure (constituent material properties, fabrication variables, structural geometry, service environments, etc.), which result in the uncertain behavior in the composite structural responses, are included in the assessment. The probabilistic assessment consists of design criteria, modeling of composite structures and uncertainties, simulation methods, and the decision making process. A sample case is presented to illustrate the formal procedure and to demonstrate that composite structural designs can be probabilistically assessed with accuracy and efficiency.

Shiao, Michael C.↗
DOE OSTI2019

Learning to predict the cosmological structure formation

Matter evolved under the influence of gravity from minuscule density fluctuations. Nonperturbative structure formed hierarchically over all scales and developed non-Gaussian features in the Universe, known as the cosmic web. To fully understand the structure formation of the Universe is one of the holy grails of modern astrophysics. Astrophysicists survey large volumes of the Universe and use a large ensemble of computer simulations to compare with the observed data to extract the full information of our own Universe. However, to evolve billions of particles over billions of years, even with the simplest physics, is a daunting task. We build a deep neural network, the Deep Density Displacement Model ( D 3 M ), which learns from a set of prerun numerical simulations, to predict the nonlinear large-scale structure of the Universe with the Zel’dovich Approximation (ZA), an analytical approximation based on perturbation theory, as the input. Our extensive analysis demonstrates that D 3 M outperforms the second-order perturbation theory (2LPT), the commonly used fast-approximate simulation method, in predicting cosmic structure in the nonlinear regime. We also show that D 3 M is able to accurately extrapolate far beyond its training data and predict structure formation for significantly different cosmological parameters. Our study proves that deep learning is a practical and accurate alternative to approximate 3D simulations of the gravitational structure formation of the Universe.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

A system for automatic evaluation of simulation software

Within the field of computer software, simulation and verification are complementary processes. Simulation methods can be used to verify software by performing variable range analysis. More general verification procedures, such as those described in this paper, can be implicitly, viewed as attempts at modeling the end-product software. From software requirement methodology, each component of the verification system has some element of simulation to it. Conversely, general verification procedures can be used to analyze simulation software. A dynamic analyzer is described which can be used to obtain properly scaled variables for an analog simulation, which is first digitally simulated. In a similar way, it is thought that the other system components and indeed the whole system itself have the potential of being effectively used in a simulation environment.

Ryan, J. P.↗