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DOE OSTI2025

Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment

The United States is accelerating its shift toward a renewable energy system. However, renewable resources, which harness energy from the Earth system, are susceptible to both present-day climate variability and future climate change. For example, variations in regional climate can alter renewable energy production patterns and site viability. The use of high-resolution climate model projections can therefore facilitate and may be critical to long-term planning of renewable energy investments. However, climate models must first be validated for renewable resource assessment. This research employs multiple high-spatiotemporal-resolution datasets to assess the capability of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 North American Regionally Refined Model (E3SMv2-NARRM) for predicting multi-year climatological values of solar and wind energy capacity factors in the continental U.S., with a focus on regional and seasonal variability. Present-day E3SMv2-NARRM simulations are compared with reported utility-scale production data obtained from the Energy Information Administration (EIA). In addition, E3SMv2-NARRM data are evaluated against non-climate benchmark models from the National Renewable Energy Laboratory, including the Wind Integration National Dataset Toolkit and the National Solar Radiation Database (NSRDB), as well as three wind energy datasets from PLUSWIND. Our analysis indicates that solar capacity factors from E3SM closely match those from the NSRDB dataset. However, both datasets tend to overestimate values by 10% in comparison to EIA data. Furthermore, biases in wind capacity factors within E3SM are notably pronounced in the West Coast regions, where the seasonal cycle diverges from EIA data.

Energy forecasting, Capacity factor, Renewable ene↗

DOE OSTI2025

Relativistic core–valence-separated equation-of-motion coupled-cluster singles and doubles method: Efficient implementation and benchmark calculations

An efficient implementation for the relativistic exact two-component core–valence-separated equation-of-motion coupled-cluster singles and doubles (X2C-CVS-EOM-CCSD) method is reported. The explicit exclusion of pure valence excitations in the EOM-CCSD excited-state eigenvalue equations significantly improves the efficiency for calculations of core-excited states. Benchmark relativistic CVS-EOM-CC calculations with systematic inclusion of relativistic, correlation, and basis-set effects are shown to provide highly accurate results for core ionized and excited states involving heavy atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

First-principles calculation of excited states of diatomic molecules: a benchmark for the Gutzwiller conjugate gradient minimisation method

We recently proposed the Gutzwiller conjugate gradient minimisation (GCGM) method for efficient and accurate calculation of the ground state total energy of molecular and bulk systems. The GCGM method is developed under the framework of Gutzwiller wave function but goes beyond the commonly adopted Gutzwiller approximation to improve the accuracy and flexibility in treating the correlation effects. In this conference proceeding, we benchmark the GCGM method with the calculation of excited state potential energy curves of three diatomic molecules, namely H 2 , N 2 , and O 2 . Our calculations demonstrate the flexibility and reasonable accuracy of the method.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Benchmark Simulation of the Natural Convection Shutdown Heat Removal Test Facility Using SAM

Natural convection systems are a promising method to passively remove heat from reactor cavities during loss of forced flow accident scenarios. In this work at Argonne National Laboratory (ANL), a highly instrumented Natural Convection Shutdown Heat Removal Test Facility (NSTF) was used to demonstrate the effectiveness of air-cooled natural convection systems. In previous work, RELAP5-3D simulations were performed on this facility with favorable comparisons to experiment for mass flow rate, pressure drop, air temperature increase, and air velocity. Both experimental and simulation efforts with this facility present a useful opportunity to perform a benchmark study with the System Analysis Module (SAM). SAM is an advanced thermal-hydraulic system code currently in development at ANL for advanced non-light water reactor safety analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Depletion Benchmark Analysis on a Lead Fast Reactor Using PyARC/OpenMC

PyARC is a user-friendly fast reactor analysis tool that automates multiphysics workflows using the “extended suite” of Argonne Reactor Computation (ARC) codes by providing a single common input for model definition, code execution, and output post-processing. A lead fast reactor (LFR) benchmark model is used to perform depletion calculations using the newly integrated OpenMC depletion capability in PyARC, building on previous analysis using the ARC codes through PyARC and Serpent. Results for core lifetime k-effective, shutdown decay heat, and end-of-life heavy-metal inventory are compared to verify the PyARC/OpenMC integration against the PyARC/ARC workflow and Serpent for depletion analysis of LFR designs. The results show satisfactory agreement among all three methods, with remaining discrepancies largely attributable to differences in nuclear data libraries and decay-chain modeling detail rather than to fundamental modeling limitations.

Kiesling, Kalin R.↗

DOE OSTI2025

A transient near to far field transformation method and verification benchmarking procedure

The numerical calculation of electromagnetic far fields in the time-domain requires a near to far field transformation (NTFF) method. While time-domain NTFF methods for popular finite-difference time-domain (FDTD) approaches are well established, there is little discourse on NTFF methods for finite-element time-domain (FETD) codes. Here, this work is concerned with the development of an NTFF method for the Empire FETD code, which utilizes curl and divergence conforming elements. This discretization presents a difficulty in obtaining the equivalent electric current for the NTFF. Straightforward finite element interpolation of the fields is shown to give poor accuracy. Alternative interpolation methods are recommended. An expanding magnetic quadrupole pulse benchmark problem, which is fully developed in the appendices, provides the basis for quantitative comparison.

FETD↗

DOE OSTI2020

Benchmark calculations of electron impact electronic excitation of the hydrogen molecule

We present benchmark integrated and differential cross-sections for electron collisions with H 2 using two different theoretical approaches, namely, the R-matrix and molecular convergent close-coupling. This is similar to comparative studies conducted on electron–atom collisions for H, He and Mg. Electron impact excitation to the ${\mathrm{b}}^{3}{{\Sigma}}_{\mathrm{u}}^{+}$, ${\mathrm{a}}^{3}{{\Sigma}}_{\mathrm{g}}^{+}$, ${\mathrm{B}}^{1}{{\Sigma}}_{\mathrm{u}}^{+}$, c3Πu, ${\mathrm{E}\mathrm{F}}^{1}{{\Sigma}}_{\mathrm{g}}^{+}$, C1Πu, ${\mathrm{e}}^{3}{{\Sigma}}_{\mathrm{u}}^{+}$, ${\mathrm{h}}^{3}{{\Sigma}}_{\mathrm{g}}^{+}$, ${\mathrm{B}}^{\prime 1}{{\Sigma}}_{\mathrm{u}}^{+}$ and d3Πu excited electronic states are considered. Calculations are presented in both the fixed nuclei and adiabatic nuclei approximations, where the latter is shown only for the ${\mathrm{b}}^{3}{{\Sigma}}_{\mathrm{u}}^{+}$ state. Good agreement is found for all transitions presented. Where available, we compare with existing experimental and recommended data.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

Benchmark of few-level quantum theory vs ab initio numerical solutions for the strong-field Autler–Townes effect in photoionization of hydrogen

Abstract The temporal and spectral consequences of an intermediate resonance en route to photoionization are investigated theoretically in two ways: by solving few-level model equations and by ab initio numerical solution of the time-dependent Schrödinger equation, in both cases for hydrogen in three dimensions. The model consists of atomic states resonantly field-dressed in a three-level reduction of the hydrogen atom that consists of the 2 p –3 d (Balmer) transition and one energetically-distant continuum state. The model’s level occupation probabilities are derived from three Schrödinger amplitude equations and are benchmarked against an ab initio numerical solution for the hydrogen electron’s wavefunction under the same field. We examine contrasts between the results of the two approaches with a particular focus on Autler–Townes doublets that appear in the photoelectron spectrum.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Benchmark of gyrokinetic, kinetic MHD and gyrofluid codes for the linear calculation of fast particle driven TAE dynamics

Fast particles in fusion plasmas may drive Alfvén modes unstable leading to fluctuations of the internal electromagnetic fields and potential loss of particles. Such instabilities can have an impact on the performance and the wall-load of machines with burning plasmas such as ITER. A linear benchmark for a toroidal Alfvén eigenmode (TAE) is done with 11 participating codes with a broad variation in the physical as well as the numerical models. A reasonable agreement of around 20% has been found for the growth rates. Furthermore, the agreement of the eigenfunctions and mode frequencies is satisfying. However, they are found to depend strongly on the complexity of the used model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Geant4 Computing Performance Benchmarking and Monitoring

Performance evaluation and analysis of large scale computing applications is essential for optimal use of resources. As detector simulation is one of the most compute intensive tasks and Geant4 is the simulation toolkit most widely used in contemporary high energy physics (HEP) experiments, it is important to monitor Geant4 through its development cycle for changes in computing performance and to identify problems and opportunities for code improvements. All Geant4 development and public releases are being profiled with a set of applications that utilize different input event samples, physics parameters, and detector configurations. Results from multiple benchmarking runs are compared to previous public and development reference releases to monitor CPU and memory usage. Observed changes are evaluated and correlated with code modifications. Besides the full summary of call stack and memory footprint, a detailed call graph analysis is available to Geant4 developers for further analysis. The set of software tools used in the performance evaluation procedure, both in sequential and multi-threaded modes, include FAST, IgProf and Open|Speedshop. In conclusion, the scalability of the CPU time and memory performance in multi-threaded application is evaluated by measuring event throughput and memory gain as a function of the number of threads for selected event samples.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

A wind energy benchmark for ABL modelling of a diurnal cycle with a nocturnal low-level jet: GABLS3 revisited

The third GEWEX Atmospheric Boundary Layer Studies (GABLS3) model intercomparison study, around the Cabauw met tower in the Netherlands, is revisited as a benchmark for wind energy atmospheric boundary layer (ABL) models. The case was originally developed by the boundary layer meteorology community, interested in analysing the performance of single-column and large-eddy simulation atmospheric models dealing with a diurnal cycle leading to the development of a nocturnal low-level jet. The case addresses fundamental questions related to the definition of the large-scale forcing, the interaction of the ABL with the surface and the evaluation of model results with observations. The characterization of mesoscale forcing for asynchronous microscale modelling of the ABL is discussed based on momentum budget analysis of WRF simulations. Then a single-column model is used to demonstrate the added value of incorporating different forcing mechanisms in microscale models. The simulations are evaluated in terms of wind energy quantities of interest.

17 WIND ENERGY↗

DOE OSTI2024

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Abstract Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a cost similar to that of conventional interatomic potential approaches. While MLIPs have been extensively tested across various classes of materials and molecules, a clear characterization of the anharmonic terms encoded in the MLIPs is lacking. Here, we benchmark popular MLIPs using the anharmonic vibrational Hamiltonian of ThO 2 in the fluorite crystal structure, which was constructed from density functional theory (DFT) using our highly accurate and efficient irreducible derivative methods. The anharmonic Hamiltonian was used to generate molecular dynamics (MD) trajectories, which were used to train three classes of MLIPs: Gaussian approximation potentials, artificial neural networks (ANN), and graph neural networks (GNN). The results were assessed by directly comparing phonons and their interactions, as well as phonon linewidths, phonon lineshifts, and thermal conductivity. The models were also trained on a DFT MD dataset, demonstrating good agreement up to fifth-order for the ANN and GNN. Our analysis demonstrates that MLIPs have great potential for accurately characterizing anharmonicity in materials systems at a fraction of the cost of conventional first principles-based approaches.

interatomic potentials↗

DOE OSTI2025

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. Emerging universal machine learning interatomic potentials (uMLIPs) offer a transformative alternative by employing pre-trained neural network surrogates to predict interatomic forces directly from atomic coordinates. This approach dramatically reduces computation time and minimizes the need for technical knowledge. In this paper, we produce a phonon database comprising nearly 5000 inorganic crystals to benchmark the performance of several leading uMLIPs. We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. Through detailed comparisons, we identify the strengths and limitations of these uMLIPs, providing insights into their accuracy and suitability for fast calculations of phonons and related properties, as well as the potential for real-time interpretation of neutron scattering spectra. Our findings highlight how the rapid advancement of AI in science is revolutionizing experimental research and data analysis.

inelastic neutron scattering↗

DOE OSTI2026

EC-Bench: A Benchmark for Enzyme Commission Number Prediction

Enzymes are proteins that catalyze specific biochemical reactions in cells. Enzyme Commission (EC) numbers are used to annotate enzymes in a four-level hierarchy that classifies enzymes based on the specific chemical reactions they catalyze. Accurate EC number prediction is essential for understanding enzyme functions. Despite the availability of numerous methods for predicting EC numbers from protein sequences, there is no unified framework for evaluating and studying such methods systematically. This gap limits the ability of the community to identify the most effective approaches for enzyme annotation. We introduce EC-Bench, a benchmark for EC number prediction, consisting of 1) an initial representative set of existing methods (including homology-based, deep learning, contrastive learning, and language model methods), 2) existing and novel accuracy and efficiency performance metrics, and 3) selected datasets to allow for comprehensive comparative study. EC-Bench is open-source and provides a framework for researchers to not only compare among existing methods objectively under uniform conditions, but also to introduce and effectively evaluate performance of new methods in a comparative framework. To demonstrate the utility of EC-Bench, we perform extensive experimentation to compare the existing EC number prediction methods and establish their advantages and disadvantages in a variety of prediction tasks, namely “exact EC number prediction”, “EC number completion” and (partial or additional) “EC number recommendation”. We find wide variation in the performance of different methods, but also subtle but potentially useful differences in the performance of different methods across tasks and for different parts of the EC hierarchy.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

First discovery of an ultra-cool white dwarf benchmark in common proper motion with an M dwarf

Ultra-cool white dwarfs are among the oldest stellar remnants in the Universe. Their efficient gravitational settling and low effective temperatures are responsible for the smooth spectra they exhibit. For that reason, it is not possible to derive their radial velocities or to find the chemistry of the progenitors. The best that can be done is to infer such properties from associated sources, which are coeval. The simplest form of such a system is a common proper motion pair where one star is an evolved degenerate and the other a main-sequence star. Herein, we present the discovery of the first of such a system, the M dwarf LHS 6328 and the ultra-cool white dwarf PSO J1801+625, from the Pan-STARRS 1 3π survey and the Gaia Data Release 2. Follow-up spectra were collected covering a usable wavelength range of 3750–24 500 Å. Their spectra show that the white dwarf has an effective temperature of 3550 K and surface gravity of log $g$ = 7.45 ± 0.13 or log $g$ = 7.49 ± 0.13 for a CO or He core, respectively, when compared against synthetic spectra of ultra-cool white dwarf atmosphere models. The system has slightly subsolar metallicity with -0.25 < [Fe/H] < 0.0, and a spatial velocity of (U, V, W) = (-114.26 ± 0.24, 222.94 ± 0.60, 10.25 ± 0.34) km s -1 , the first radial velocity and metallicity measurements of an ultra-cool white dwarf. This makes it the first and only benchmark of its kind to date.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Primeval very low-mass stars and brown dwarfs – VIII. The first age benchmark L subdwarf, a wide companion to a halo white dwarf

ABSTRACT We report the discovery of five white dwarf + ultracool dwarf systems identified as common proper motion wide binaries in the Gaia Catalogue of Nearby Stars. The discoveries include a white dwarf + L subdwarf binary, VVV 1256−62AB, a gravitationally bound system located 75.6$^{+1.9}_{-1.8}$ pc away with a projected separation of 1375$^{+35}_{-33}$ au. The primary is a cool DC white dwarf with a hydrogen dominated atmosphere, and has a total age of $10.5^{+3.3}_{-2.1}$ Gyr, based on white dwarf model fitting. The secondary is an L subdwarf with a metallicity of [M/H] = $-0.72^{+0.08}_{-0.10}$ (i.e. [Fe/H] = $-0.81\pm 0.10$) and $T_{\rm eff}$ = 2298$^{+45}_{-43}$ K based on atmospheric model fitting of its optical to near infrared spectrum, and likely has a mass just above the stellar/substellar boundary. The subsolar metallicity of the L subdwarf and the system’s total space velocity of 406 km s−1 indicates membership in the Galactic halo, and it has a flat eccentric Galactic orbit passing within 1 kpc of the centre of the Milky Way every $\sim$0.4 Gyr and extending to 15–31 kpc at apogal. VVV 1256−62B is the first L subdwarf to have a well-constrained age, making it an ideal benchmark of metal-poor ultracool dwarf atmospheres and evolution.

Zhang, Z. H. (ORCID:000000033047607X)↗

DOE OSTI2025

Benchmark of the Fe xvv 𝓡 ratio in photoionized plasma during eclipse of Centaurus X-3 with XRISM/Resolve

The $\mathcal {R}$ ratio is a useful diagnostic of the X-ray emitting astrophysical plasmas and is defined as the intensity ratio of the forbidden over the inter-combination lines in the K$\alpha$ line complex of He-like ions. The value is altered by excitation processes (electron impact or UV photoexcitation) from the metastable upper level of the forbidden line, thereby constraining the electron density or UV field intensity. The diagnostic has been applied mostly in electron density constraints in collisionally ionized plasmas using low-Z elements, as was originally proposed for the Sun (Gabriel & Jordan, 1969a, MNRAS, 145, 241), but it can also be used in photoionized plasmas. To make use of this diagnostic, we need to know its value in the limit of no excitation of metastables ($\mathcal {R}_{0}$), which depends on the element, how the plasmas are formed, how the lines are propagated, and the spectral resolution affecting line blending principally with satellite lines from Li-like ions. We benchmark $\mathcal {R}_0$ for photoionized plasmas by comparing calculations using radiative transfer codes and observation data taken with the Resolve X-ray microcalorimeter onboard XRISM. We use the Fe xxv He$\alpha$ line complex of the photo-ionized plasma in Centaurus X-3 observed during eclipse, in which the plasma is expected to be in the limit of no metastable excitation. The measured $\mathcal {R} = 0.65 \pm 0.08$ is consistent with the value calculated using xstar for the plasma parameters derived from other line ratios of the spectrum. We conclude that the $\mathcal {R}$ ratio diagnostic can be used for high-Z elements such as Fe in photoionized plasmas, which has wide applications in plasmas around compact objects at various scales.

X-rays: binaries↗

DOE OSTI2021

Benchmarking near-term quantum devices with the variational quantum eigensolver and the Lipkin-Meshkov-Glick model

The variational quantum eigensolver is a promising algorithm for noisy intermediate scale quantum (NISQ) computation. Verification and validation of NISQ algorithms' performance on NISQ devices is an important task. Here, we consider the exactly diagonalizable Lipkin-Meshkov-Glick (LMG) model as a candidate for benchmarking NISQ computers. We use the Bethe Ansatz to construct eigenstates of the trigonometric LMG model using quantum circuits inspired by the LMG's underlying algebraic structure. We construct circuits with depth $\mathcal{O}$(N) and $\mathcal{O}$(log 2 N) that can prepare any trigonometric LMG eigenstate of N particles. The number of gates required for both circuits is $\mathcal{O}$(N). The energies of the eigenstates can then be measured and compared to the exactly known answers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗