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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Status of the CERBERUS Evaluation for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

Modeling & Simulation (M&S) tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers continue to improve, we are able to enhance resolution in our calculations. Therefore, the limitations of simulation capability are in the quality of data that is being used, including our ability to quantify the uncertainty and sensitivity of that data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. These experiments, along with differential measurements, can help improve the quality of nuclear data. Concerns regarding the accuracy of Cu nuclear data have been published. The large values and trend of C-E for the Zeus intermediate energy benchmark, being one of the primary examples. Furthermore, very few experiments have been designed to be sensitive to Cu (as shown in Figure 1), so an integral, critical experiment is needed to help resolve these differences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

NEA HTTR LOFC Project Test#3 Benchmark Results

In the second half of FY23, the High Temperature Engineering Test Reactor (HTTR) Loss Of Forced Cooling (LOFC)#3 data for the 9 MW test case with Vessel Cooling System (VCS) off were made available through the Nuclear Energy Agency (NEA) LOFC project framework; the neutronic model developed for the initial test (LOFC#1) achieved a satisfactory level of maturity, demonstrating its accuracy in predicting power evolution and core re-criticality, but LOFC#3 should be used primarily to investigate thermal hydraulic phenomena, as the reactor was shut down prematurely due to overheating in the upper reactor components, which prevented re-criticality; this report focuses on advancing the HTTR thermal hydraulic model to accurately simulate the LOFC#3 scenario, including simulating the LOFC#3 benchmark and generating the corresponding benchmark specifications, aiming to ensure consistency across participant models and provide essential data for future participants, including private industry stakeholders seeking to validate their computational tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) benchmark environment, for reinforcement learning (RL) control strategies in energy-efficient liquid cooling of high-performance computing (HPC) systems. Built on the baseline of a high-fidelity digital twin of Oak Ridge National Lab's Frontier Supercomputer cooling system, LC-Opt provides detailed Modelica-based end-to-end models spanning site-level cooling towers to data center cabinets and server blade groups. RL agents optimize critical thermal controls like liquid supply temperature, flow rate, and granular valve actuation at the IT cabinet level, as well as cooling tower (CT) setpoints through a Gymnasium interface, with dynamic changes in workloads. This environment creates a multi-objective real-time optimization challenge balancing local thermal regulation and global energy efficiency, and also supports additional components like a heat recovery unit (HRU). We benchmark centralized and decentralized multi-agent RL approaches, demonstrate policy distillation into decision and regression trees for interpretable control, and explore LLM-based methods that explain control actions in natural language through an agentic mesh architecture designed to foster user trust and simplify system management. LC-Opt democratizes access to detailed, customizable liquid cooling models, enabling the ML community, operators, and vendors to develop sustainable data center liquid cooling control solutions.

Naug, Avisek [Hewlett Packard Enterprise]↗
DOE OSTI2026

Benchmarking quantum trial wavefunctions for phaseless auxiliary-field quantum Monte Carlo

The phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) method is a stochastic imaginary-time projection technique for computing ground-state properties of strongly correlated quantum systems, with accuracy that depends critically on the choice of trial wavefunction. Here, we investigate ph-AFQMC with trial states prepared using parameterized quantum circuits. In this work, we present a comprehensive benchmarking study of quantum trial wavefunctions spanning unitary coupled-cluster, Hamiltonian-informed, Jastrow-inspired, and adaptively constructed ansatze. The benchmarking evaluates accuracy, expressibility, and scalability of these ansatze within the QC-AFQMC framework. We test these ansatze on linear hydrogen chains under bond stretching and find that several ansatz families produce chemically accurate ph-AFQMC energies across the dissociation curve. We have performed simulations using the CUDA-Q quantum development platform on the GPU partition of the Perlmutter supercomputer. When comparing ansatze at similar numbers of variational parameters, we find that different ansatz families yield comparable ph-AFQMC results despite exhibiting substantially different variational energies, optimization costs, and circuit depths. Our results indicate that the variational energy of an ansatz is not always a reliable indicator of its quality for ph-AFQMC and reveal instances of over-parameterization. In the strongly correlated regime, trial wavefunctions obtained from adaptive ansatze, exemplified here by ADAPT-VQE with the UCCSD operator pool, can outperform their fixed-ansatz counterparts (UCCSD) in terms of projected energies while using substantially more compact circuits, providing a flexible route to optimize quantum resources within the ph-AFQMC framework.

Rofougaran, Rod [LBNL, Berkeley; Columbia U.; PNL,↗
DOE OSTI2025

Hydrogen Bond Benchmark: Focal‐Point Analysis and Assessment of DFT Functionals

We performed a hierarchical, convergent ab initio benchmark study and systematically analyzed the performance of density functional approximations for describing hydrogen bonds in small neutral, cationic, and anionic complexes, as well as in larger systems involving amide, urea, deltamide, and squaramide moieties. Focal point analyses (FPA), extrapolating to the ab initio limit, were carried out using correlated wave function methods up to CCSDT(Q) for the small complexes and CCSD(T) for the larger systems, together with correlation-consistent Gaussian basis sets up to the complete basis set limit. Optimized geometries and vibrational frequencies were obtained at the CCSD(T) level. The resulting FPA hydrogen-bond energies converge within a few tenths of a kcal mol −1 . These reference data were used to evaluate 60 density functionals (including 12 dispersion-corrected), spanning the local-density approximation (LDA), generalized gradient approximations (GGAs), meta-GGAs, hybrids, meta-hybrids, double-hybrids, and range-separated hybrids. Overall, the meta-hybrid M06-2X provides the best performance for both hydrogen bond energies and geometries, while the dispersion-corrected GGAs BLYP-D3(BJ) and BLYP-D4 also yield accurate hydrogen-bond data and can serve as cost-effective options for studying large and complex systems.

coupled cluster theory↗
DOE OSTI2020

Clean Energy Manufacturing: Renewable Energy Technology Benchmarks

The manufacturing of clean energy technologies has become a global enterprise. An analysis of four clean energy technology manufacturing processes—wind turbine components, crystalline silicon solar photovoltaic modules, light-duty vehicle lithium-ion battery cells, and light-emitting diodes—was conducted to provide a reference point for comparison over time as this sector evolves. The manufacturing supply chain analysis included processing of raw materials, making required subcomponents, and assembling final products, using benchmarks that crossed 12 economies: Brazil, Canada, China, Germany, India, Japan, Malaysia, Mexico, South Korea, Republic of China (Taiwan), the United Kingdom, and the United States. Larger economies, with extensive manufacturing supply chains and high prevailing wages, tend to retain more value added from clean energy manufacturing than small economies. Manufacturing of clean energy technologies drives extensive trade among economies to support the widely distributed supply chain links. Production of wind turbine components and photovoltaic modules is more centralized than production of light-emitting diodes and lithium-ion battery cells. Across the four clean energy technologies evaluated, there was generally an excess of manufacturing capacity relative to global supply.

benchmarks↗
DOE OSTI2025

Benchmark study of the DTU OWC chamber with both two-way and one-way absorption

This paper reports on a benchmark study based on small-scale (1:50) measurements of a single, oscillating water column chamber mounted sideways in a long flume. The geometry of the OWC chamber is extracted from a barge-like, attenuator-type floating concept “KNSwing” with 40 chambers targeted for deployment in the Danish part of the North Sea. In addition to traditional two-way energy extraction we also consider one-way energy extraction with passive venting and compare chamber response, pressures and total absorbed energy between the two methods. A blind study was established for the numerical modeling, with participants applying several implementations of weakly nonlinear potential flow theory and commercial Navier–Stokes solvers (CFD). Both compressible and incompressible models were used for the air phase. Potential flow calculations predict more energy absorption near the chamber resonance for one-way absorption than for two-way absorption, but the opposite is found from the experimental measurements. This outcome is mainly attributed to energy losses in the experimental passive valve system, but this conclusion must be confirmed by better experimental measurements. Modeling the one-way valve in CFD proved to be very challenging and only one team was able to provide results which were generally closer to the experiments. The study illustrates the challenges associated with both numerical and experimental analysis of OWC chambers. Air compressibility effects were not found to be important at this scale, even with the large volume of additional air used for the one-way case.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Simulation of the BEAVRS benchmark using VERA

The Virtual Environment for Reactor Applications (VERA) is being developed by the Consortium for the Advanced Simulation of Light Water Reactors (CASL). Here, VERA is used to perform the Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS), which provides two cycles’ worth of operating power history, along with a full, detailed description of the geometry, and measured data. Cycle 1 and 2 are simulated with VERA and the results are compared to the measured zero power physics tests, critical boron concentration, and flux maps.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Linear and nonlinear benchmarks between the CLT code and the M3D-C1 code for the 2/1 resistive tearing mode and the 1/1 resistive kink mode

Here, the linear and nonlinear benchmarks between the CLT code and the M3D-C1 code for the 2/1 resistive tearing mode and the 1/1 resistive kink mode are presented. CLT is an explicit finite difference code, while M3D-C1 is an implicit finite element code. Although the implementations of CLT and M3D-C1 are totally different, we find that the simulation results of the resistive-kink mode and the m/n=2/1 tearing mode from M3D-C1 and CLT are almost the same, including the linear and nonlinear growth rates, the mode structures, the nonlinear saturation levels, the Poincare plots, and the scaling laws. This confirms that the nonlinear results for the 1/1 resistive-kink mode and 2/1 tearing mode are accurate and reliable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Benchmarking of Solar Irradiance Nowcast Performance Derived from All-Sky Imagers

Fluctuations of the incoming solar irradiance impact the power generation from photovoltaic and concentrating solar thermal power plants. Accurate solar nowcasting becomes necessary to detect these sudden changes of generated power and to provide the desired information for optimal exploitation of solar systems. In the framework of the International Energy Agency's Photovoltaic Power Systems Program Task 16, a benchmarking exercise has been conducted relying on a bouquet of solar nowcasting methodologies by all-sky imagers (ASI). In this paper, four ASI systems nowcast the Global Horizontal Irradiance (GHI) with a time forecast ranging from 1 to 20 min during 28 days with variable cloud conditions spanning from September to November 2019 in southern Spain. All ASIs demonstrated their ability to accurately nowcast GHI, with RMSE ranging from 6.9% to 18.1%. Under cloudy conditions, all ASIs' nowcasts outperform the persistence models. Under clear skies, three ASIs are better than persistence. Discrepancies in the observed nowcasting performance become larger at increasing forecast horizons. The findings of this study highlight the feasibility of ASIs to reliably nowcast GHI at different sky conditions, time intervals and horizons. Such nowcasts can be used either to estimate solar power at distant times or detect sudden GHI fluctuations.

all-sky imagers↗
DOE OSTI2025

Using Electrochemistry to Benchmark, Understand, and Develop Noble Metal Nanoparticle Syntheses

The complex chemical nature of metal nanoparticle synthesis presents obstacles for the mechanistic understanding of nanoparticle growth and predictive synthesis design, despite significant progress in this area. Real-time characterization of the chemical processes that take place throughout nanoparticle growth will enable progress toward addressing outstanding challenges in metal nanoparticle synthesis, such as mitigating synthetic reproducibility issues, defining chemical mechanisms that direct nanoparticle growth, and designing synthetic conditions for previously unachievable combinations of nanoparticle shape and composition. In this Perspective, we present open-circuit potential (OCP) measurements as an in situ, real-time method for characterizing chemical changes during nanoparticle growth and discuss the method’s strengths in comparison to and in combination with other characterization techniques. We propose the use of OCP measurements as benchmarks for troubleshooting irreproducibility and streamlining synthetic optimization. Finally, we explore possibilities for using the increased parameter space accessible by electrodeposition to accelerate the development of shape-selective nanoparticle syntheses.

benchmarking↗
DOE OSTI2026

Integral Nuclear Data and Benchmarking Needs for Fusion Energy Systems

Fusion energy systems are currently being designed and optimized using radiation transport codes. To deal with the unique environment inside a fusion-based system, many of these designs incorporate novel materials able to withstand the high radiation fields, ensure adequate cooling and thermal protection, and produce tritium. Validation plays a vital role in building trust in the predictive power of these models and computational methods. Validation of a code consists of modeling documented real-world experiments and comparing the code-predicted response to the measured response. Adequate validation requires measured responses from real-world experiments, also known as integral data, that mimic the system being designed, including materials, impinging radiation, and temperature, among other variables. The most trusted integral data are experimental responses that have been through a rigorous benchmarking process that develops a recommended computational model and evaluates all experimental uncertainties. Finally, there are a few research groups around the world that have been producing integral data for fusion applications, but a substantial investment is needed to address the unique validation needs of the fusion community.

Fusion↗
DOE OSTI2021

2D radial-azimuthal particle-in-cell benchmark for E × B discharges

In this paper we propose a representative simulation test-case of E × B discharges accounting for plasma wall interactions with the presence of both the electron cyclotron drift instability and the modified-two-stream-instability. Seven independently developed particle-in-cell (PIC) codes have simulated this benchmark case, with the same specified conditions. The characteristics of the different codes and computing times are given. Here, results show that both instabilities were captured in a similar fashion and good agreement between the different PIC codes is reported as main plasma parameters were closely related within a 5% interval. The number of macroparticles per cell was also varied and statistical convergence was reached. Detailed outputs are given in the supplementary data, to be used by other similar groups in the perspective of code verification.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A code-to-code benchmark for magneto-convection in a horizontal duct

Liquid metals and magnetic fields are used in many technical applications such as metallurgy, crystal growth and nuclear fusion reactors. When an electrically conducting fluid moves in a magnetic environment, electric currents and electromagnetic forces are generated that affect velocity and pressure losses in the flow. These magnetohydrodynamic (MHD) interactions have to be investigated to optimize the engineering processes. The characteristics of MHD flows depend on the geometrical configuration, the strength of the applied magnetic field, the electrical properties of fluid and structural materials and the thermal conditions. In the so-called blankets for fusion reactors, where liquid metals are used to breed the plasma fuel component tritium and to extract the generated heat, magneto-convective flows play a crucial role in determining heat and mass transfer. Therefore, the availability of numerical codes to simulate this type of flow is mandatory and their validation is a necessary step to guarantee the reliability of the results. For that reason, a benchmark problem has been defined to simulate liquid metal flows in a horizontal rectangular duct heated from below and exposed to a non-uniform magnetic field. Results obtained by five research groups using different codes are compared.

benchmark↗
DOE OSTI2022

Benchmarking embedded chain breaking in quantum annealing*

Quantum annealing solves combinatorial optimization problems by finding the energetic ground states of an embedded Hamiltonian. However, quantum annealing dynamics under the embedded Hamiltonian may violate the principles of adiabatic evolution and generate excitations that correspond to errors in the computed solution. Here we empirically benchmark the probability of chain breaks and identify sweet spots for solving a suite of embedded Hamiltonians. We further correlate the physical location of chain breaks in the quantum annealing hardware with the underlying embedding technique and use these localized rates in a tailored post-processing strategies. Our results demonstrate how to use characterization of the quantum annealing hardware to tune the embedded Hamiltonian and remove computational errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Benchmarking noise extrapolation with the OpenPulse control framework

Distilling precise estimates from noisy intermediate scale quantum (NISQ) data has recently attracted considerable attention Kandala et al., Nature (London) 567, 491 (2019). In order to augment digital qubit metrics, such as gate fidelity, we discuss analog error mitigability, i.e., the ability to accurately distill precise observable estimates, as a hybrid quantum classical computing benchmarking task. Specifically, using Rabi oscillations as a test program, we characterize single qubit error rates on IBM's Poughkeepsie superconducting quantum hardware, incorporate control-mediated noise dependence into a generalized rescaling protocol, and analyze how noise characteristics influence Richardson extrapolation-based error mitigation. Finally, our results identify regions in the space of Hamiltonian control fields and circuit depth which are most amenable to reliable noise extrapolation, as well as shed light on how low-level hardware characterization can be used as a predictive tool for uncertainty quantification in error-mitigated NISQ computations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Benchmarking Information Scrambling

Information scrambling refers to the rapid spreading of initially localized information over an entire system, via the generation of global entanglement. This effect is usually detected by measuring a temporal decay of the out-of-time order correlators. However, in experiments, decays of these correlators suffer from fake positive signals from various sources, e.g., decoherence due to inevitable couplings to the environment, or errors that cause mismatches between the purported forward and backward evolutions. Here, in this Letter, we provide a simple and robust approach to single out the effect of genuine scrambling. This allows us to benchmark the scrambling process by quantifying the degree of the scrambling from the noisy backgrounds. We also demonstrate our protocol with simulations on IBM cloud-based quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Invited Paper: Benchmarking and Optimizing Data Movement on Emerging Heterogeneous Architectures

As supercomputers evolve, nodes are continually increasing in complexity. As a result, each generation of parallel systems brings new performance challenges. For instance, on recent systems inter-node communication has outperformed inter-socket, resulting in poor performance of many node-aware communication optimizations. Communication optimizations are critical for the performance and scalability of parallel applications, but are dependent on the parallel architecture, which varies significantly among recent generations of supercomputers. Furthermore, this paper investigates the performance of various paths of data movement on recent generations of systems, and analyzes the increased complexity of communication, particularly on recent heterogeneous systems. The paper also introduces MPI Advance, a communication library that enables optimizations to be created based on benchmark analysis of each emerging system.

benchmarking↗