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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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

IEEE 1547-2018 Based Interoperable PV Inverter with Advanced Grid-Support Functions

Grid integration of photovoltaic (PV) inverters has been increasing in the past decade. As a result of the uncertainties introduced with high penetrations of PV, better monitoring and control of the PV inverters becomes crucial for improving overall system stability. This paper focuses on the communications capability of the inverter controller and on enabling interoperability. Multiple standards are available to enable interoperability in PV inverters. In this paper, an interoperable controller, enabled by Distributed Network Protocol 3 (DNP3) communications protocols, is developed for a grid-connected, three-phase PV inverter. The DNP3 server for the PV inverter is programmed on the real-time layer of the field-programmable gate array (FPGA)-based inverter controller. Set points for advanced inverter control functions, such as volt/VAr curves, ride-through curves, are sent from a DNP3 client, a simulated distribution management system application, to the PV inverter through DNP3. This communications capability of the inverter controller is validated using a controller-hardware-in-the-loop experimental setup. The code developed to achieve the interoperability is available in the public domain through open-source software licensing. This interoperability will enable smoother grid integration of smart PV inverters with advanced grid-support functions as well as allow better monitoring and control of PV inverters for grid stability.

14 SOLAR ENERGY↗
DOE OSTI2021

Isopod (inverse Optimization And Design): Moose-based Application For Performing Inverse Optimization On Multiphysics Modeling And Simulation

ISOPOD (InverSe OPtimizatiOn and Design) will be a MOOSE (Multiphysics Object Oriented Simulation Environment)-based framework which will iteratively estimate the parameters by minimizing the difference between simulated and experimental observables. While inverse optimization has long been used for parameter estimation, the unique feature of ISOPOD is rapid solution of new inverse problems, leading to accelerated Research, Development and Demonstration (RD&D) for complex parameter estimation problems. This will be achieved by extending the software structure of MOOSE to inverse optimization, as well as building on the unique automatic differentiation feature of MOOSE.

Munday, LynnB↗
DOE OSTI2023

Bifacial_Radiance v0.4.2 [SWR-18-03]

The bifacial_radiance software contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. For more information, check out our documentation, Tutorials in the form of Jupyter Notebooks, or refer to our Wiki and Issues page. Installation https://youtu.be/4A9GocfHKyM This video shows how to install the bifacial_radiance software and all associated software needed. More info on the Wiki. Instructions are also shown below. For detailed instructions of how to install bifacial_radiance, you can also refer to the installation guide. A GUI has been added in version 3.0. The GUI reads/writes all input parameters necessary to run a simulation, and runs the specified simulation by calling the correct functions with the specified parameters. So no need to use a journal or a script! But you still need to install following the procedure below.

Deline, Chris↗
DOE OSTI2023

Earth System Model Simulations of Ameriflux sites using dynamic roots and dynamic leaf to root allocation

This data package contains point-scale Earth System Model simulations run with DOE's E3SM Model. The package includes four sets of simulations, one set of simulations run in the default configuration, a second set of simulations run with the dynamic root module enabled, the third set with dynamic leaf to fine root allocation, and the fourth with the combination of dynamic roots and dynamic allocation. These simulations were run in point mode a Ameriflux sites, US-MMS, US-Moz, US-Syv, and US-NR1. These datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and R.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Files and scripts to support manuscript Needham et al. Canopy Gradients of Respiration

This dataset includes the parameter files, relevant output files, and scripts to perform analysis with Jupyter notebooks that support the manuscript Needham et al 2025 “Canopy Gradients of Respiration Drive Plant Carbon Budgets and Leaf Area Index.” We add functionality to the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) to allow flexible vertical gradients of leaf maintenance respiration (Rdark) and maximum carboxylation rate (Vcmax) through the canopy. We test the sensitivity of FATES to canopy gradients in Rdark, both in global simulations to assess broad scale impacts on leaf area index (LAI) and vegetation carbon, and in single site simulations where we assess impacts on plant functional type (PFT) competitive dynamics. Parameter files are netcdf files that can be converted to human readable .cdl files using NCO tools. Analysis scripts are Jupyter notebook files. These can be opened and run using the open source Jupyter notebook software. Model outputs are netcdf files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2022

MFIX-Exa: Performance prediction of multiphase energy conversion devices

MFIX-Exa targets the high-fidelity CFD-DEM model in which particles are unresolved by the fluid grid (typically using a fluid mesh approximately twice the particle diameter) but discrete particle dynamics including collisions are resolved with a simple linear-spring dashpot model. The fluid field is solved with a modern low Mach number formation of a cell-centered, nodal-pressure approximate projection method using a Godunov scheme . Physics capabilities include: complex geometries via embedded boundaries (EBs), open and closed system ideal gas equations of state, species transport and heterogeneous chemi- cal reactions. MFIX-Exa is built on the AMReX software framework, the ECP Block-Structured Adaptive Mesh Refinement (AMR) Co-Design Center, which allows the code to be portable and performant.Further integration into the ECP ecosystem includes HYPRE linear solvers and Ascent for in situ visualization. Current project efforts focus on scaling up realistic simulations to the KPP of the challenge problem: NETs 50kW chemical looping reactor, shakedown and scaling on JSLE and OLCF TDS systems and reaching for any remaining performance improvements.

Musser, Jordan↗
DOE OSTI2023

Developing Ultrahigh-Resolution E3SM Land Model for GPU Systems

Designing and refactoring complex scientific code, such as the E3SM land model (ELM), for new computing architectures is challenging. This paper presents design strategies and technical approaches to develop a data-oriented, GPU-ready ELM model using compiler directives (OpenACC/OpenMP). We first analyze the datatypes and processes in the original ELM code. Then we present design considerations for ultrahigh-resolution ELM (uELM) development for massive GPU systems. These techniques include the global data-oriented simulation workflow, domain partition, code porting and data copy, memory reduction, parallel loop restructure and flattening, and race condition detection. We implemented the first version of uELM using OpenACC targeting the NVidia GPUs in the Summit supercomputer at Oak Ridge National Laboratory. During the implementation, we developed a software tool (named SPEL) to facilitate code generation, verification, and performance tuning using these techniques. The first uELM implementation for Nvidia GPUs on Summit delivered promising results: 1) over 98% of the ELM code was automatically generated and tuned by scripts. Most ELM modules had better computational performances than the original ELM code for CPUs. The GPU-ready uELM is more scalable than the CPU code on fully-loaded Summit nodes. Example profiling results from several modules are also presented to illustrate the performance improvements and race condition detection. The lessons learned and toolkit developed in the study are also suitable for further uELM deployment using OpenMP on the first US exascale computer, Frontier, equipped with AMD CPUs and GPUs.

Schwartz, Peter↗
DOE OSTI2020

Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing

Additive manufacturing (AM) enables the fabrication of complex designs that are difficult to create by other means. Metal parts manufactured by laser powder bed fusion (LPBF) can incorporate intricate design features and demonstrate desirable mechanical properties. However, printing a part that is qualified for its intended application often involves reprinting and discarding many parts to eliminate defects, improve dimensional accuracy, and increase repeatability. The process of iteratively converging on the appropriate build parameters increases the time and cost of creating functional LPBF manufactured parts. This work describes a fast, scalable method for part-scale process optimization of arbitrary geometries. Additionally, the computational approach uses feature extraction to identify scan vectors in need of parameter adaptation and applies results from simulation-based feed forward control models. This method provides a framework to quickly optimize complex parts through the targeted application of models with a range of fidelity and by automating the transfer of optimization strategies to new part designs. The computational approach and algorithmic framework are described, a software package is implemented, the method is applied to parts with complex features, and parts are printed on a customized open architecture LPBF machine.

3D printing↗
DOE OSTI2022

Experiences with Porting the FLASH Code to Ookami, an HPE Apollo 80 A64FX Platform

We present initial experiences with running the community simulation code FLASH, developed at the University of Chicago for multi-scale multi-physics applications, on Ookami, a technology testbed featuring the A64FX processor developed by Fujitsu. Our effort focused largely on running FLASH “right out of the box” to see which combinations of compilers and software implementations (e.g. MPI) allowed the code to run with minimal modification. FLASH was one application in a larger effort to deploy Ookami; it served as a test for different versions of newly installed software, and as a cornerstone for the FAQ page of the Ookami website. Here, we report on our results with different compilers and other software, along with our initial scaling results and attempts to utilize the A64FX’s SVE instructions and NUMA architecture. We found that FLASH readily ran with different compilers and MPI implementations, and showed the expected good scaling with no turning. However, more work must be done to fully take advantage of the A64FX’s architectural features and produce a significant speedup for FLASH on Ookami.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

ACTIVE

The Automated Control Testbed for Integration, Verification, and Emulation (ACTIVE) framework is a software platform designed to support the optimized operation and management of a wide range of building types. It enables the development, testing, and validation of diverse control strategies, including AI-based, rule-based, and model-based approaches. The platform facilitates a seamless transition from simulation-based evaluation of control strategies to real-world field validation and deployment. ACTIVE supports the full building management lifecycle, encompassing data acquisition and management, system monitoring, optimized control, adaptive learning services, device dispatch and coordination, as well as advanced analytics and visualization. Together, these capabilities provide an integrated environment for improving building performance, operational efficiency, reducing energy cost, and reliability.

Smith, Robert [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2021

Numerical Codes for the DESC-LSST Analysis Pipeline: Core Cosmology Library Standard Modules and Beyond wCDM Modules (Final Technical Report)

The overall objective of the project is to investigate and develop specific software modules and analysis components for the software pipeline of LSST Dark Energy Science Collaboration (DESC). Following the key projects of DESC Science Roadmap (SRM), we will write and test computer codes for the Core Cosmology Library (CCL) in order to complete its modules, functionalities, and interface to work with the analysis pipelines from the five science probes of DESC (parts of SRM deliverables CX4.2TJP, CX6.2CS). We will also code modules for CCL to test models beyond w-Cold-Dark-Matter (wCDM) and modification to gravity (MG). Interfaces for MG models will also be developed for the TJPCOSMO software which is the main pipeline of the Theory and Joint Probe (TJP) working group (deliverable TJP2.3). In order to use the full power of LSST data to constrain MG models, we will also work on constraints from nonlinear regime by running and analyzing MG N-Body simulations using a Parameterized-Post-Friedmann framework into the Gadget-2 simulation package (deliverable TJP2.2). Preliminary results for the simulations were obtained in the past. In collaboration with other DESC groups, we plan to make these simulations feedable to cosmic emulators that are practical for likelihood analyzes (deliverable TJP2.2, parts of CX6.2CS). We will also modify and integrate our current codes for consistency tests between data sets and probes into the pipeline (parts of deliverables CX8.2TJP, TJP2.3). We understand that other groups will contribute to some of these objectives but our team will focus and collaborate with others on the particular part of testing MG and models beyond wCDM and refine the DESC pipeline for this purpose. PI has been coordinating his work with the TJP and CS working groups and the DESC management team. PI is a full member of DESC since June 2013. He and his students have been contributing to LSST-DESC activities and work including TJP telecons, collaboration meetings, hack-weeks, and workshops. PI chaired or co-chaired sessions at collaboration meetings and hack-weeks about testing gravity and models beyond wCDM using LSST. He is coordinating the TJP2 projects for testing models beyond wCDM including the writing of DESC-research-note, development of code for pipeline, and N-Body simulations for MG and beyond wCDM models testable with LSST analyses. As stressed in the DESC white paper, SRM, and P5 report, one of the important questions in understanding cosmic acceleration and dark energy is to be able to distinguish whether the acceleration is due to a dark energy component in the universe or a modification to gravity. Answering these questions will have a significant impact on the question of cosmic acceleration and dark energy. The methods that we will use include analytical work, numerical code, and N-Body simulations. A first approach that that we will use consists of using growth rate parameters that enter the perturbed dynamics equations. These parameters take distinctive values for distinct gravity theories and have potential to distinguish between Dark Energy and Modified Gravity. The second method is to look for inconsistencies in Dark Energy parameter spaces using specific combinations of cosmological data sets. Our investigation addresses the Dark Energy problem that is relevant to the mission of the HEP program to understand how our universe works at its most fundamental level. It will allow us to make progress on the HEP mission to explore the nature of Dark Energy and the basic nature of space and time using future surveys such as LSST. The investigation supports the DOE HEP program Cosmic Frontier as it will contribute to the study and understanding of dark energy and fundamental properties of the universe. The investigation contributes directly to LSST-DESC key projects and their deliverables as described in the Science Road-map document to build analysis pipeline and to test dark energy and beyond wCDM models using LSST.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Monte Carlo Analyses of the FOEHN Experiment

The FOEHN critical experiment, which has been carried out at Cadarache (France) in the reactor EOLE in the early 70s, was designed to verify RHF design analyses. This study focuses on the impact of the FOEHN experiment uncertainties on the calculation of the energy deposition. The latter has been obtained by the Monte Carlo codes Serpent and MCNP. In the calculation of the energy deposition, the first code relies on KERMA factors whereas the latter code relies on Q-values. The two Monte Carlo codes share the same geometry and material specifications. In addition to the design and experiment parameters uncertainties, nuclear data also impacts the calculation of the energy deposition. In this study, the MCNP simulations use three different nuclear data library sets: ENDF/B versions VII.0, VII.1, and VIII.0. Finally, the ksens card of MCNP, using perturbation theory, has been used to identify the cross sections and isotopes with largest impact on the effective multiplication factor. By showing that the use of different software and computational methodologies and design parameters uncertainties do not significantly impact the core power distribution, this work demonstrate the appropriateness of the tools and methods employed for the conversion of involute-plate reactors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

MFiX Development Updates

This presentation discusses recent developments of the Multiphase Flow with Interphase eXchanges (MFiX) software. A brief review of all modeling approaches along with their cost versus accuracy is provided to guide users when selecting a model for a given application. The main new features of the past five official releases of MFiX are described. Improvement in chemistry management allow for easier simulation setup, and faster simulation speed. Progress in the implementation of a thin-wall boundary condition is presented. The major new model development over the past year is the release of the Glued Sphere Particle model (GSP), where component spheres are combined together to represent non-spherical particles. The integration of Machine Learning (ML) workflow in the CFD process is discussed with two applications: a surrogate model for stiff chemistry and the development of a PIC stress model using ML.

Dietiker, Jeff↗
DOE OSTI2025

A Python Tool for Reconstructing MCNP6 Particle Histories from an HDF5 PTRAC File [Slides]

A Python tool for converting the MCNP6 HDF5 PTRAC file to a list of Python trees is presented. The particle trees store MCNP6 simulated events for each history using parent-child relationships, which ensures that branching processes are accurately reproduced. A variety of post-processing scripts are presented and used in conjunction with the Python particle trees to make special tallies that are currently not available in the MCNP6 software and visualize the particle tracks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

GR-Athena++: Puncture Evolutions on Vertex-centered Oct-tree Adaptive Mesh Refinement

Numerical relativity is central to the investigation of astrophysical sources in the dynamical and strong-field gravity regime, such as binary black hole and neutron star coalescences. Current challenges set by gravitational-wave and multimessenger astronomy call for highly performant and scalable codes on modern massively parallel architectures. We present GR-Athena++, a general-relativistic, high-order, vertex-centered solver that extends the oct-tree, adaptive mesh refinement capabilities of the astrophysical (radiation) magnetohydrodynamics code Athena++. To simulate dynamical spacetimes, GR-Athena++ uses the Z4c evolution scheme of numerical relativity coupled to the moving puncture gauge. We demonstrate stable and accurate binary black hole merger evolutions via extensive convergence testing, cross-code validation, and verification against state-of-the-art effective-one-body waveforms. GR-Athena++ leverages the task-based parallelism paradigm of Athena++ to achieve excellent scalability. We measure strong-scaling efficiencies above 95% for up to ~1.2 × 10 4 CPUs and excellent weak scaling is shown up to ~10 5 CPUs in a production binary black hole setup with adaptive mesh refinement. GR-Athena++ thus allows for the robust simulation of compact binary coalescences and offers a viable path toward numerical relativity at exascale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Need for advanced research reactors for the next-generation reactor physics, analysis tools, and technology

Full text of publication follows. There is an urgent need for design and deployment of advanced research and test reactors in support of design, licensing and operation of advanced power reactors and education of next generation nuclear workforce. Existing research reactors mostly were designed and constructed decades ago with the main objectives of training operators, performing reactor physics experiments, and educating nuclear engineers and scientists. There are already gaps and significant concern about future capabilities for the existing research reactor facilities to address modern instrumentation and/or flexible environments for: performing reactor physics studies for advanced designs which have significantly different core materials forms and compositions, reactor shapes and size; validation of advanced high-fidelity software; development of machine learning algorithms for enhancement of human-machine collaboration in support of reactor monitoring, operation and safeguards; and, effective education of the next-generation workforce. The authors will focus on the need for advanced research reactors to improve and validate fast and accurate simulation tools for high-fidelity modeling and analysis of nuclear reactors in support of their design, optimization, licensing, operation, and monitoring. In the past, simulation tools were limited to relatively coarse models using approximate methodologies that benefited from two main factors: i) allowance for large margins and tolerances; ii) ability to construct prototype (e.g., zero power) reactors for adjustment of approximate methodologies. The next generation reactors have to be designed mainly by using novel high-fidelity computational tools that are accurate and fast, and therefore can be used for parametric studies and uncertainty quantification. To sufficiently demonstrate the accuracy of these tools, advanced research reactors are needed. The authors argue the need for new computational paradigms such as the MRT (Multistage, Response- function Transport) methodology which has resulted in the development of the novel high-fidelity RAPID (Real-time Analysis for Particle-transport and In-situ Detection) code system. Such code systems have to be robust in modeling any complex system, and should be fast and accurate, henceforth their uncertainties can be quantified at reasonable costs. Again, advanced research reactors are needed for the validation of the fidelity and accuracy of new computational tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗