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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
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DOE OSTI2024

Subhourly Clipping Correction Model Comparison

This work will compare the Allen method and Walker method of accounting for subhourly inverter clipping power losses in hourly PV performance models. The Allen method uses a matrix lookup based on DNI clearness and clipping potential to assign a clipping correction loss at each simulation timestep. The Walker method models the PV DC power input to the inverter as a distribution over the hourly timestep and uses integration over the timestep to determine the amount of clipping that occurs within the timestep. Both these models have been recently implemented in the System Advisor Model's (SAM) open-source code, and will be applied to hourly SURFRAD datasets to analyze the subhourly clipping loss predicted by each model for different system designs and inverter loading conditions. Both models will be compared to "true" 1-minute SURFRAD data simulations to see their accuracy against more accurate 1-minute clipping correction loss predictions. This model comparisons will be investigated in more detail at the PVSC conference in Seattle, Washington June 2024.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗
DOE OSTI2026

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ambient energy for buildings: Beyond energy efficiency

The following Key Messages comprise the salient findings of this study: 1. Ambient energy (from sun, air, ground, and sky) can heat and cool buildings; provide hot water, ventilation and daylighting; dry clothes; and cook food. These services account for about three-quarters of building energy consumption and a third of total US demand. Biophilic design (direct and indirect connections with nature) is an intrinsic adjunct to ambient energy systems, and improves wellness and human performance. 2. The current strategy of electrification and energy efficiency for buildings will not meet our climate goals, because the transition to an all-renewable electric grid is too slow. Widespread adoption of ambient energy is needed. Solar-heated buildings also flatten the seasonal demand for electricity compared to all-electric buildings, reducing required production capacity and long-term energy storage. In addition, ambient-conditioned buildings improve resilience by remaining livable during power outages. 3. National policies, incentives, and marketing should be enacted to promote ambient energy use. Federal administrative priorities should reflect the importance of ambient energy for buildings. Use of ambient energy should be encouraged through existing and new building codes and standards. 4. Ambient energy system design tools are needed for architects, engineers, builders, building scientists, realtors, appraisers, and consumers. PVWatts is used over 100 million times per year for photovoltaic system design. A similar, simple, and accessible tool for ambient design is crucial. 5. Training on ambient energy is needed throughout secondary, post-secondary, and continuing education for workforce development. Currently, only about 10% of colleges teach courses on passive heating and cooling systems. 6. Ambient-conditioned buildings should be demonstrated in all US climate zones. Performance should be monitored and reported, with quantitative case studies made widely available. 7. While current technology is sufficient to build high-performance ambient buildings now, research is needed to develop new technologies to harness ambient energy more effectively and more economically. Such advancements will facilitate adoption of ambient energy technologies in a wider range of buildings, including retrofits. Examples include windows with much lower thermal losses, use of the building shell as thermal storage, alternative light-weight thermal storage systems, sky radiation cooling systems, automated controls for solar gains and passive cooling, and ground coupling.

14 SOLAR ENERGY↗
DOE OSTI2025

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Completion of initial reduced-order model for flammable refrigerant dispersal in residential spaces

Environmental regulations aimed at reducing global warming impacts of HVAC&R refrigerants have resulted in the phase-out of chlorofluorocarbons (CFCs) in 2010 and hydrochlorofluorocarbons (HCFCs) by 2030 in developed countries with additional restrictions on the use of hydrofluorocarbons (HFCs) set to take effect in 2036. Many of the remaining alternative refrigerants that have lower global warming potential (GWP) and that are suitable for use in HVAC&R systems (e.g., propane, difluoromethane) are flammable to some degree. Flammable refrigerants introduce new challenges and hazards to property and personal safety related to potential deflagration during system maintenance or due to leakage of the refrigerant accumulating in the conditioned space. Standards have been developed to set maximum charge limits for flammable refrigerants in HVAC&R systems; however, existing safety standards and codes still restrict their use. The bodies that maintain and update these codes need publicly available, science-based information to enable credible guidelines for setting safe charge limits for different flammable refrigerants in different HVAC&R applications. In 2016, the Alliance for Responsible Atmospheric Policy, the Air-Conditioning Heating and Refrigeration Institute (AHRI), ASHRAE, the U.S. Department of Energy (DOE), and the State of California began efforts to develop such information. As part of this effort, Oak Ridge National Laboratory (ORNL) began the current, ongoing project to examine imposed charge limits for flammable refrigerants and identify reasonable adjustments to these limits when found appropriate. Past tasks under this project have included development of experimentally vetted, computational fluid dynamics (CFD) simulation approaches to study the results of leakage of flammable refrigerants from various HVAC&R systems into different types of commercial and residential spaces. In this report, we discuss recent efforts to develop a predictive model of the flammable volume fraction and accumulated refrigerant mass in a single-room residential space resulting from the leak of a flammable refrigerant from a small room air conditioning (RAC) unit. The eventual goal is development of a model suitable for public release which could simulate a range of scenarios. In discussions with the AHRTI Flammable Refrigerant Subcommittee (FRS) at the beginning of this effort, a total of 9 input parameters were chosen for consideration including room area, room/door opening area, ventilation fan flow rate, unit/leak height, leak area, leak rate, total refrigerant charge, refrigerant molecular weight, and state of the unit fan.

42 ENGINEERING↗
DOE OSTI2022

Transient Data Library of Solar Grid Integrated Distributed System

This submission contains an open-source library of transient events in distributed system with high solar PV. The library includes the collected data, related documents and scripts for loading the data. The data library is built for transient event detection and machine learning based analysis algorithm development. The data was collected via both field test and software simulation. The units for the data are included in the data file headers for each data series. A text editor or spreadsheet software, such as Excel, and Matlab is required to view the data.

algorithms↗
DOE OSTI2022

Identifying candidate structured RNAs in CRISPR operons

Noncoding RNAs with secondary structures play important roles in CRISPR-Cas systems. Many of these structures likely remain undiscovered. We used a large-scale comparative genomics approach to predict 156 novel candidate structured RNAs from 36,111 CRISPR-Cas systems. A number of these were found to overlap with coding genes, including palindromic candidates that overlapped with a variety of Cas genes in type I and III systems. Among these 156 candidates, we identified 46 new models of CRISPR direct repeats and 1 tracrRNA. This tracrRNA model occasionally overlapped with predicted cas9 coding regions, emphasizing the importance of expanding our search windows for novel structure RNAs in coding regions. We also demonstrated that the antirepeat sequence in this tracrRNA model can be used to accurately assign thousands of predicted CRISPR arrays to type II-C systems. This study highlights the importance of unbiased identification of candidate structured RNAs across CRISPR-Cas systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Implementing a Laser Stabilization System for Trapping Ca+ Ions: an Internship Reflection

At Lawrence Livermore National Laboratory, I contributed to a project developing 3D printed micro ion traps for quantum computing. I designed, implemented, and assessed a laser stabilization system that locked lasers to the frequencies required for calibrating our High Finesse WS8-10 wavelength meter and for laser cooling and trapping of Ca+ ions. I also programmed a Python interface for hardware communication, data collection, and statistical analysis. Additionally, I optimized and aligned laser beam paths, and I implemented a closed digital feedback loop using Proportional, Integral, and Derivative (PID) control parameters. I analyzed both the long-term and short-term behavior of our locked lasers and adjusted PID parameters to enhance performance. Furthermore, I used COMSOL to simulate the capacitance of a linear Paul trap design and predict our trap’s performance. The procedures I developed for the interface, analysis, and simulations will continue to support the ion trapping experiment after my appointment. I strengthened my skills in data analysis, Python coding, and optical alignment for laser systems. My confidence as a researcher grew, particularly in communicating my research. This experience taught me the importance of careful planning and consideration in research and solidified my desire to continue exploring novel quantum technology as an undergraduate

42 ENGINEERING↗
DOE OSTI2019

Towards Native Execution of Deep Learning on a Leadership-Class HPC System

Large parallel machines generally offer the best parallel performance with "native execution" that is achieved using codes developed with the optimized compilers, communication libraries, and runtimes offered on the machines. In this paper, we report and analyze performance results from native execution of deep learning on a leadership-class high-performance computing (HPC) system. Using our new code called DeepEx, we present a study of the parallel speed up and convergence rates of learning achieved with native parallel execution. In the trade-off between computational parallelism and synchronized convergence, we first focus on maximizing parallelism while still obtaining convergence. Scaling results are reported from execution on up to 15,000 GPUs using two scientific data sets from atom microscopy and protein folding applications, and also using the popular ImageNet data set. In terms of the traditional measure of parallel speed up, excellent scaling is observed up to 12,000 GPUs. Additionally, accounting for convergence rates of deep learning accuracy or error, a deep learning-specific metric called "learning speed up" is also tracked. The performance results indicate the need to evaluate parallel deep learning execution in terms of learning speed up, and point to additional directions for improved exploitation of high-end HPC systems.

Yoginath, Srikanth↗
DOE OSTI2025

The HTR-Proteus Benchmark: Analysis and Use as a Verification and Validation Case

This presentation outlines the evaluation and application of the HTR-Proteus benchmark as a verification and validation (V&V) case for advanced reactor modeling tools. The work supports the U.S. Department of Energy’s HALEU Availability Program (HAP) and the joint DOE/NRC DNCSH project, which aims to reduce criticality safety uncertainties in commercial-scale HALEU fuel cycle and transportation systems. The HTR-Proteus experiments, conducted at the Paul Scherrer Institute, provide high-fidelity data for TRISO-fueled, graphite-moderated pebble bed reactors with high neutron leakage—conditions relevant to HALEU transport scenarios. This study focuses on Cores 4.2 and 4.3 of the HTR-Proteus benchmark, analyzing key sources of uncertainty including pebble packing, TRISO particle positioning, and core height. Using Project Chrono for realistic pebble geometries and Serpent, SHIFT, and MCNP for neutronics simulations, the study quantifies the impact of these uncertainties on the effective multiplication factor (keff). Results show that a sample size of 110 pebble configurations is sufficient to converge keff, with ±30 pcm uncertainty due to packing randomness. TRISO positioning and core height variations also significantly influence keff, highlighting the importance of detailed modeling in V&V efforts. The benchmark serves as a valuable test case for validating the Griffin reactor physics code and improving confidence in HALEU system simulations.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Soluble limit and criticality of fermions in $\mathbb Z_2$ gauge theories

Quantum information theory and strongly correlated electron systems share a common theme of macroscopic quantum entanglement. In both topological error correction codes and theories of quantum materials (spin liquid, heavy fermion and high-$T_c$ systems), entanglement is implemented by means of an emergent gauge symmetry. Inspired by these connections, in this paper we introduce a simple model for fermions moving in the deconfined phase of a $\mathbb Z_2$ gauge theory by coupling Kitaev's toric code to mobile fermions. This permits us to exactly solve the ground state of this system and map out its phase diagram. Reversing the sign of the plaquette term in the toric code permits us to tune the ground state between an orthogonal metal and an orthogonal semimetal in which gapless quasiparticles survive despite a gap in the spectrum of original fermions. The small-to-large Fermi surface transition between these two states occurs in a stepwise fashion with multiple intermediate phases. By using a diagrammatic technique, we are able to explore physics beyond the integrable point to examine various instabilities of the deconfined phase and to derive the critical theory at the transition between deconfined and confined phases. We outline how the fermionic toric code can be implemented as a quantum circuit, thus providing an important link between quantum materials and quantum information theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

High-Performance Molecular Dynamics Simulation for Biological and Materials Sciences: Challenges of Performance Portability, Dallas, TX, November 2018.

Highly-optimized parallel molecular dynamics programs have allowed researchers to achieve ground-breaking results in biological and materials sciences. This type of performance has come at the expense of portability: a significant effort is required for performance optimization on each new architecture. Using a metric that emphasizes speedup, we assess key accelerating programming components of four different best-performing molecular dynamics programs - GROMACS, NAMD, LAMMPS and CP2K-- each having a particular scope of application, for contribution to performance and for portability. We use builds with and without these components, tested on HPC systems. We also analyze the code-bases to determine compliance with portability recommendations. We find that for all four programs, the contributions of the non-portable components to speed are essential to the programs' performances; without them we see a reduction in time-to-solution of a magnitude that is insufferable to domain scientists. This characterizes the performance efficiency that must be approached for good performance portability on a programmatic level, suggesting solutions to this difficult problem, which should come from developers, industry and funding institutions, and possibly new research in programming languages.

Computer Science↗
DOE OSTI2022

FLASSH 1.0: Thermal Scattering Law Evaluation and Cross Section Generation

The Full Law Analysis Scattering System Hub ( FLASSH ) is an advanced code which evaluates the thermal scattering law (i.e. TSL, S(α,β)) for thermal scattering cross sections and resonance Doppler broadening. The ability to accurately capture these two key cross section features is dependent on accurate, high fidelity TSL evaluations. FLASSH 1.0 provides advanced physics capabilities resulting in an improved, generalized TSL to most accurately represent the lattice dynamics within any material. This improved TSL will allow for consistent analysis in both the thermal and epithermal energy ranges. The features for TSL analysis are packaged within the FLASSH GUI for easy user interface along with data output in many file formats including ENDF File 7 and ACE files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Tight-Binding-Based Method for Simulations of Complex Materials with Accompanying Database

The NRL-Tight-Binding (NRL-TB) method has been applied successfully to many monatomic, binary, and a few ternary systems. The method consists of a fit to Density Functional Theory (DFT) results and has transferability beyond the fitted DFT database including performing tight-binding molecular dynamics simulations. We are working on a new website with a detailed guide of how to use the method in performing the fit to DFT results (Fitting Code) and obtaining non-orthogonal TB parameters expressed in a polynomial form as environment-dependent Slater-Koster parameters (on-site terms), and neighbor distance-dependent Hamiltonian and Overlap terms. These parameters are then used in a Static Code to verify or make predictions for large systems often beyond the computational capabilities of standard DFT codes. Our starting point was a website developed at NRL some years ago which NRL no longer supports. We have now been augmenting that website with new examples of expanding the original capabilities of the method such as incorporating in the codes f-electron states. Our website (esd.cos.gmu.edu/tb) contains two separate branches: One named NRL-TB with the full documentation of the method including source codes and examples. The other branch, named ESD-dB, is a library of electronic structure calculations for all the monatomic elements (a subset of the elements also found in a recent book by the author of this proposal. See reference 22) and an approximately 700 hundred compounds in specific crystal structures. We discuss below the progress made so far in improving and expanding the capabilities of our TB method and the plans for further extensions of our approach.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Integrated Simulation Capabilities for Analysis of Experiments in the Versatile Test Reactor

The DOE-initiated Versatile Test Reactor (VTR) program aims to establish a domestic fast-neutron irradiation testing capability that meets a variety of domestic and international nuclear energy needs. Currently, integrated tools capable of mechanistic modeling of VTR and a test vehicle do not exist. To address this modeling and analysis deficiency, Argonne's SAS4A/SYSSYS-1 safety analysis code has been coupled with SAM (System Analysis Module) to provide a novel modeling capability that supports VTR and other fast test facilities. This report documents the design, implementation, and testing of this integrated capability. A coupling boundary has been identified at the test vehicle and primary coolant interface, where SAS4A/SASSYS-1 treats primary coolant thermal hydraulics outside the test vehicle, while SAM treats all thermal hydraulic behavior within the test vehicle, including the vehicle walls. Essential to this integrated tool is its newly developed capability to properly model the conjugate heat transfer process which ensures equality of temperatures and heat fluxes at the vehicle wall interface while ensuring energy conservation. A range of testing has been completed to support demonstration of this interface. The testing scope includes steady-state verification using a series of increasingly complex analytical solutions and transient demonstration for a range of design basis accident scenarios using prototypic VTR and test vehicle (i.e. cartridge loop) configurations. Results of this testing confirm verification of the steady-state solutions and provide reasonable and expected transient behavior. The coupling interface has been developed to be robust yet flexible. The implementation within SAS4A/SASSYS-1 supports coupling to any external software or module. The use of decomposed domains and the existing in-core thermal-hydraulic calculational framework within SAS4A/SASSYS-1 enable treatment of arbitrary test vehicle geometries with nonuniform meshing between SAS4A/SASSYS-1 and the coupled code. Modeling of multiple test locations is also supported. Furthermore, computational efficiency is enhanced by utilizing named pipes (or FIFOs), an interface for interprocess communication (IPC).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Unstructured mesh-based multi-physics reactor transient simulation with iMC code

In this study, we present a time-dependent Monte Carlo simulation result about a complex fuel-loaded light water reactor system with thermal-hydraulic feedback using the KAIST iMC code. The intra-pin temperature distribution is calculated based on Monte Carlo-tallied detailed power distribution and the finite element heat transfer method. The temperature effect of fuel, absorber, and coolant are adequately reflected into the dynamic response by the on-the-fly Doppler broadened cross-section correction. For the time-dependent Monte Carlo transport simulation, the predictor-corrector quasi-static Monte Carlo method is used for this study. We tested the coupled analysis framework with a 17-by-17 fuel assembly loaded with the centrally-shielded burnable absorber (CSBA) fuel element. The temperature feedback effect on the material cross-section and the moderator density incurred negative reactivity in response to the external positive reactivity insertion, showing the inherent stability of the reactor system. The pin-wise power and temperature change during the system transient are presented and discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

PV High Wind User Test Facility

The creation of a PV high wind test facility at the NREL Flatirons Campus that will enable private and public research efforts aimed at storm hardening PV systems. The facility will be instrumented to monitor effects of high wind conditions on modules and other array components. These in-field tests will coordinate with flow models, wind tunnel testing, validation of PV aeroelastic design codes, and post-testing module and system component analysis.

14 SOLAR ENERGY↗
DOE OSTI2025

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE neams program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework. This report summarizes recent advances in developing an integrated system- and engineering-scale modeling capability for the msr concept, which has gained significant interest in recent years. A consistent framework was established by coupling Pronghorn and SAM through the Saline interface, with thermophysical properties provided by the Molten Salt Thermal Property Database (MSTDB-TP). Further improvements were made to the coupling schemes and domain-overlapping strategies, enhancing the stability and robustness of multi-code simulations. Verification and validation efforts demonstrate the accuracy of this integration across a range of benchmark problems, including one-dimensional heated pipe flows, three-dimensional natural convection loops with evolving isotopic compositions, and \gls{msre} demonstration cases. Within Pronghorn, new capabilities were introduced to model corrosion and noble-metal plating phenomena, supported by an extended thermal-hydraulics framework and refined turbulence treatments. To capture two-phase flow behavior, a multiphase Euler–Euler model was implemented in Pronghorn, including advanced closure relations, high-resolution advection techniques, and capillary force reconstruction. Preliminary verification cases confirm the fidelity of the approach, while planned validation efforts target canonical multiphase benchmarks and application to msr components such as the msre pump bowl. Finally, updates to SAM’s msr mass transfer modeling were extended to consider noble gas migration into porous structures like graphite. The point kinetics model was updated to include reactivity feedback contributions from any defined species, such as xenon. The gas transport model was expanded for applicability to gas mixtures, bubble efflux phenomena, and species transport between liquid and gas phases. A selection of multi-scale Sherwood number correlations from MOSCATO/NekRS and multi-phase correlations from literature have been added for improved accuracy in calculating mass transfer coefficients. A companion effort on developing system-level redox corrosion has also been incorporated into SAM. Collectively, these enhancements strengthen the predictive capability of SAM and Pronghorn for simulating MSR thermal-hydraulics, corrosion, multiphase behavior, and fission-product transport, providing a more complete toolset for design, safety analysis, and licensing support of next-generation \gls{msr}s.

42 - ENGINEERING↗