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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

PyBioNetFit

Systems biology models written in the BioNetGen language often contain parameters that must be fit based on experimental data. PyBioNetFit is a software tool designed to fit parameters of BioNetGen models. The user is expected to provide a BioNetGen model that contains unknown parameters, along with one or more text files containing experimental data. PyBioNetFit will perform a series of calls to the BioNetGen simulator using different parameter sets, to identify the parameter set that best fits the data. The parameter search is dictated by the user's choice of one of several metaheuristic optimization algorithms, including differential evolution, particle swarm optimization, scatter search, and simulated annealing. The software supports parallelized computing on multi-core computers and on computing clusters. We expect this software to be a useful tool for researchers designing BioNetGen models in collaboration with experimentalists.

Mitra, Eshan↗
DOE OSTI2026

Roadrunner

SAND2026-17073O Roadrunner software provides a comprehensive platform for simulating the mechanical behavior of crystalline materials under various loading conditions, allowing users to investigate the effects of dislocation slip hardening and damage evolution. Developed as a fork of the Multiphysics Object Oriented Simulation Environment (MOOSE) software from Idaho National Laboratory, Roadrunner is optimized for high-performance computing and can simulate large-scale problems, enabling researchers to explore complex scenarios. Its applications include material design and optimization in aerospace and automotive industries, investigation of failure mechanisms in structural materials, and development of predictive models for crystalline materials under various loading conditions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Lim, Hojun [Sandia National Lab. (SNL-CA), Livermo↗
DOE OSTI2018

The dynamics of stellar discs in live dark-matter haloes

Recent developments in computer hardware and software enable researchers to simulate the self-gravitating evolution of galaxies at a resolution comparable to the actual number of stars. Here we present the results of a series of such simulations. In this study, we performed N-body simulations of disc galaxies with between 100 and 500 million particles over a wide range of initial conditions. Our calculations include a live bulge, disc, and dark-matter halo, each of which is represented by self-gravitating particles in the N-body code. The simulations are performed using the gravitational N-body tree-code BONSAI running on the Piz Daint supercomputer. We find that the time-scale over which the bar forms increases exponentially with decreasing disc-mass fraction and that the bar formation epoch exceeds a Hubble time when the disc-mass fraction is ~0.35. These results can be explained with the swing-amplification theory. The condition for the formation of m = 2 spirals is consistent with that for the formation of the bar, which is also an m = 2 phenomenon. We further argue that the non-barred grand-design spiral galaxies are transitional, and that they evolve to barred galaxies on a dynamical time-scale. We also confirm that the disc-mass fraction and shear rate are important parameters for the morphology of disc galaxies. The former affects the number of spiral arms and the bar formation epoch, and the latter determines the pitch angle of the spiral arms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Dimming the Lights: 2D Simulations of Deflagrations of Hybrid C/O/Ne White Dwarfs Using FLASH

The dimmest and most numerous outlier of the Type Ia supernova population, the Type Iax event, is increasingly being found in the results of observational campaigns. There is currently no single accepted model to describe these events. This 2D study explores the viability of modeling Type Iax events as a hybrid C/O/Ne white dwarf progenitor undergoing a deflagration using the multiphysics software FLASH. This hybrid was created using the stellar evolution code MESA, and its C-depleted core and mixed structure have demonstrated lower yields than traditional C/O progenitors in previous deflagration-to-detonation studies. To generate a sample, 30 “realizations” of this simulation were performed, the only difference being the shape of the initial match head used to start the deflagration. Consistent with earlier work, these realizations produce the familiar hot dense bound remnant surrounded by sparse ejecta. Our results indicate that the majority of the star remains unburned (∼70%) and bound (>90%). Our realizations produce total ejecta yields on the order of 10 −2 –10 −1 M ☉ , ejected 56 Ni yields on the order of 10 −4 –10 −2 M ☉ , and ejecta kinetic energies on the order of 10 48 –10 49 erg. Compared to yields inferred from recent observations of the dimmest Type Iax events—SN 2007qd, SN 2008ha, SN 2010ae, SN 2019gsc, SN 2019muj, SN 2020kyg, and SN 2021fcg—our simulation produces comparable 56 Ni yields but too-small total yields and kinetic energies. Reignition of the remnant is also seen in some realizations.

Hydrodynamical simulations↗
DOE OSTI2017

Modelling and measurements of bunch profiles at the LHC

The bunch profiles in the LHC are often observed to be non-Gaussian, both at Flat Bottom (FB) and Flat Top (FT) energies. Especially at FT, an evolution of the tail population in time is observed. In this respect, the Monte-Carlo Software for IBS and Radiation effects (SIRE) is used to track different types of beam distributions. The impact of the distribution shape on the evolution of bunch characteristics is studied. The results are compared with observations from the LHC Run 2 data.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

CHEMNODE: CHEMICAL KINETICS SOLVER APPROACH BASED ON NEURAL ORDINARY DIFFERENTIAL EQUATIONS

This software contains an algorithm to model and predict the time evolution of chemical kinetics in reacting flow simulations using neural ordinary differential equations (NODEs). The approach works by using artificial neural networks to predict the chemical source terms. It achieves this by using forward-mode automatic differentiation and the Levenberg-Marquardt algorithm to adjust the neural network parameters, such that the discrepancies between the actual and predicted species profiles are minimized.

OWOYELE, OPEOLUWA↗
DOE OSTI2017

Bellerophon

The Bellerophon software system supports CHIMERA, a production-level HPC application that simulates the evolution of core-collapse supernovae. Bellerophon enables CHIMERA's geographically dispersed team of collaborators to perform job monitoring and real-time data analysis from multiple supercomputing resources, including platforms at OLCF, NERSC, and NICS. Its multi-tier architecture provides an encapsulated, end-to-end software solution that enables the CHIMERA team to quickly and easily access highly customizable animated and static views of results from anywhere in the world via a cross-platform desktop application.

Lingerfelt, Eric J↗
DOE OSTI2020

Teaching Software Sustainability for High Performance Computing at ATPESC

The Argonne Training Program in Extreme Scale Computing (ATPESC) was started by Argonne National Laboratory with the objective of expanding the ranks of better-prepared users of high-performance computing (HPC) machines. One of the unique aspects of the program was inclusion of a track on software engineering and community codes. The inclusion was motivated by the observation that the projects with good software processes were better able to meet their scientific goals. Over the years, with greater awareness of software sustainability issues in the community, the track has evolved into a software productivity and sustainability track. In this paper we present our experience in choosing and disseminating the content related to the topic of software engineering in high performance computing science from the beginning of the program until now. We discuss the motivations and the reception of the tracks. We also document the evolution of the track over the years based on student feedback and also the growth of awareness about software productivity in high performance computing.

Dubey, Anshu↗
DOE OSTI2020

Quandary

Quandary numerically simulates and optimizes the time-evolution of open quantum systems. The underlying dynamics are modelled by Lindblad's master equation, a linear ordinary differential equation (ODE) describing quantum systems interacting with the environment. Quandary solves this ODE numerically by applying a time-stepping integration scheme, and utilizes a gradient-based optimization approach to determine optimal control pulses that drive the quantum system to a desired target state. Two optimization objectives are considered: (a) Unitary gate optimization that finds controls to realize a unitary gate transformation, and (b) optimal reset that aims to drive the quantum system to the ground states. Gradient-based optimization schemes utilizing Petsc's Tao optimization package are applied to generate control pulses that minimize the respective measure. To evaluate the gradient of the objective function, the discrete adjoint method is used while leveraging techniques from Algorithmic Differentiation to produce exact and consistent gradients. To mitigate excessive execution run times, the software can be build together with the XBraid software library which provides a parallelization strategy to distribute the time-evolution of the underlying dynamics onto multiple processor.

Petersson, NilsA.↗
DOE OSTI2015

Simultaneous X-ray diffraction and phase-contrast imaging for investigating material deformation mechanisms during high-rate loading

Using a high-speed camera and an intensified charge-coupled device (ICCD), a simultaneous X-ray imaging and diffraction technique has been developed for studying dynamic material behaviors during high-rate tensile loading. A Kolsky tension bar has been used to pull samples at 1000 s -1 and 5000 s -1 strain-rates for super-elastic equiatomic NiTi and 1100-O series aluminium, respectively. By altering the ICCD gating time, temporal resolutions of 100 ps and 3.37 µs have been achieved in capturing the diffraction patterns of interest, thus equating to single-pulse and 22-pulse X-ray exposure. Furthermore, the sample through-thickness deformation process has been simultaneously imaged via phase-contrast imaging. It is also shown that adequate signal-to-noise ratios are achieved for the detected white-beam diffraction patterns, thereby allowing sufficient information to perform quantitative data analysis diffraction via in-house software ( WBXRD_GUI ). Of current interest is the ability to evaluate crystal d -spacing, texture evolution and material phase transitions, all of which will be established from experiments performed at the aforementioned elevated strain-rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Closed-loop simulation with Grad-Shafranov equilibrium evolution for plasma control system development

Plasma control design increasingly depends on fast simulations able to connect to operational plasma control system (PCS) software for iterative development. GSevolve is a nonlinear free-boundary simulation that evolves the Grad-Shafranov equilibrium including current and pressure profiles, and can connect to all versions of the DIII-D PCS operational on devices around the world. Its ability to simulate the evolution of current continuously from open to closed field lines enables GSevolve to simulate full-discharge control from breakdown through plasma termination. GSevolve is compliant with the Plasma Control System Simulation Platform (PCSSP), a Matlab/Simulink®-based environment that serves as the primary framework for development of the ITER Plasma Control System (PCS). The code employs a novel response function-updating scheme to achieve fast simulations. The plasma evolves linearly until a significant shape change triggers a nonlinear update of the response while enforcing a prescribed accuracy. Old responses are recalled if the plasma changes back to an old shape. The equilibrium is a function of a state vector containing axisymmetric conductor currents and parameters related to parallel and perpendicular currents, which evolves according to an efficient state space circuit formulation. Control design and validation results are presented for simulations of DIII-D and EAST, connected to their corresponding versions of the DIII-D PCS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Reconstruction of high temporal resolution Thomson scattering data during a modulated electron cyclotron resonance heating using conditional averaging

This paper provides a software application of the sampling scope concept for fusion research. The time evolution of Thomson scattering data is reconstructed with a high temporal resolution during a modulated electron cyclotron resonance heating (MECH) phase. The amplitude profile and the delay time profile of the heat pulse propagation are obtained from the reconstructed signal for discharges having on-axis and off-axis MECH depositions. The results are found to be consistent with the MECH deposition.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Practical galaxy morphology tools from deep supervised representation learning

Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Cross-Layer Self-Adaptive/Self-Aware System Software for Exascale Systems

The extreme level of parallelism coupled with the limited available power budget expected in the exascale era brings unprecedented challenges that demand optimization of performance, power and resiliency in unison. Scalability on such systems is of paramount importance, while power and reliability issues may change the execution environment in which a parallel application runs. To solve these challenges exascale systems will require an introspective system software that combines system and application observations across all system stack layers with online feedback and adaptation mechanisms. In this paper we propose the design of a novel self-aware, self-adaptive system software in which a kernel-level Monitor, which continuously inspects the evolution of the target system through observation of Sensors, is combined with a user-level Controller, which reacts to changes in the execution environment, explores opportunities to increase performance, save power and adapts applications to new execution scenarios. We show that the monitoring system accurately monitors the evolution of parallel applications with a runtime overhead below 1-2%. As a test case, we design and implement a user-runtime system that aims at optimizing application’s performance and system power consumption on complex hierarchical architectures. Our results show that our adaptive system reaches 98% of performance efficiency of manually-tuned applications.

High Performance computing, Self-aware/self-adapti↗
DOE OSTI2017

Zircon age-temperature-compositional spectra in plutonic rocks

We present that geochronology can resolve dispersed zircon dates in plutonic rocks when magma cooling time scales exceed the temporal precision of individual U-Pb analyses; such age heterogeneity may indicate protracted crystallization between the temperatures of zircon saturation (T sat ) and rock solidification (T solid ). Diffusive growth models predict asymmetric distributions of zircon dates and crystallization temperatures in a cooling magma, with volumetrically abundant old, hot crystallization at T sat decreasing continuously to volumetrically minor young, cold crystallization at T solid . We present integrated geochronological and geochemical data from Bergell Intrusion tonalites (Central Alps, Europe) that document zircon compositional change over hundreds of thousands of years at the hand-sample scale, indicating melt compositional evolution during solidification. Ti-in-zircon thermometry, crystallization simulation using MELTS software, and U-Pb dates produce zircon mass-temperature-time distributions that are in excellent agreement with zircon growth models. In conclusion, these findings provide the first quantitative validation of longstanding expectations from zircon saturation theory by direct geochronological investigation, underscoring zircon’s capacity to quantify supersolidus cooling rates in magmas and resolve dynamic differentiation histories in the plutonic rock record.

58 GEOSCIENCES↗
DOE OSTI2024

An integrated modeling framework with open architecture for phase field simulation of multi-component alloys

An integrated modeling framework (PanPhaseField) has been developed, which enables a direct and fast coupling between CALPHAD calculations and large-scale phase field simulations for multi-component alloys. Further, it adopts an open architecture allowing for integration of user-defined phase field models in a plug-and-play manner by taking full advantage of the user-friendly graphical interface of Pandat software. The developed modeling platform becomes an enabling tool that can be used to simulate the evolution of spatially varying microstructures of industrial complex alloys for various engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Thermodynamic Model Toward the Comprehension of Ferrous Burden Softening and Melting Using FactSage Macro-Processing

The softening and melting properties of iron-bearing materials play a decisive role in the formation of the cohesive zone, which greatly affects blast furnace gas flow distribution and heat-transfer efficiency. To improve the understanding regarding the evolution of condensed phases during reduction, softening, and melting, a thermodynamic model has been developed using FactSage™ thermodynamic software and macro-processing. The model was constructed using a series of equilibrium stages and splitters to determine flow directions of streams and to consider kinetic inhibitions. For all iron-bearing materials studied, the methodology proposed for modeling was capable of obtaining reduction degrees in very good agreement to its experimental data. The evolution of solid phases was qualitatively comparable to the available literature, with Fayalite, Kirschsteinite, Melilite, and FeO as the main solid phases in equilibrium before slag formation. The comparison between the profiles of the calculated slag mass fraction and the experimental pressure drop showed a close relation between these properties. Moreover, the level of heterogeneity of each raw material may play a significant role in the interpretation of its results.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗