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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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DOE OSTI2016

GridPACK™ : A Framework for Developing Power Grid Simulations on High-Performance Computing Platforms

This paper describes the GridPACK™ framework, which is designed to help power grid engineers develop modeling software capable of running on high performance computers. The framework makes extensive use of software templates to provide high level functionality while at the same time allowing developers the freedom to express whatever models and algorithms they are using. GridPACK™ contains modules for setting up distributed power grid networks, assigning buses and branches with arbitrary behaviors to the network, creating distributed matrices and vectors and using parallel linear and non-linear solvers to solve algebraic equations. It also provides mappers to create matrices and vectors based on properties of the network and functionality to support IO and to mana

Palmer, Bruce J.↗
DOE OSTI2015

Complex-energy approach to sum rules within nuclear density functional theory

The linear response of the nucleus to an external field contains unique information about the effective interaction, correlations governing the behavior of the many-body system, and properties of its excited states. To characterize the response, it is useful to use its energy-weighted moments, or sum rules. By comparing computed sum rules with experimental values, the information content of the response can be utilized in the optimization process of the nuclear Hamiltonian or nuclear energy density functional (EDF). But the additional information comes at a price: compared to the ground state, computation of excited states is more demanding. To establish an efficient framework to compute energy-weighted sum rules of the response that is adaptable to the optimization of the nuclear EDF and large-scale surveys of collective strength, we have developed a new technique within the complex-energy finite-amplitude method (FAM) based on the quasiparticle random- phase approximation. The proposed sum-rule technique based on the complex-energy FAM is a tool of choice when optimizing effective interactions or energy functionals. The method is very efficient and well-adaptable to parallel computing. As a result, the FAM formulation is especially useful when standard theorems based on commutation relations involving the nuclear Hamiltonian and external field cannot be used.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗
DOE OSTI2025

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim’s capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6 × better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware.

Vatsavai, Sairam Sri [Brookhaven National Laborato↗
DOE OSTI2019

ATOMISTIC CHARACTERIZATION OF METAL-ORGANIC FRAMEWORKS FOR SUB-AMBIENT PRESSURE SWING ADSORPTION OF POST-COMBUSTION CO2 CAPTURE AND SEPARATION

Developing cost-effective and less energy-intensive carbon capture processes for dilute CO2 sources is of high interest. Adsorption-based CO2 capture such as pressure swing adsorption (PSA) is one promising approach to this challenge. PSA and other cyclic adsorption processes are materials-enabled separations that use porous adsorbents, including metal-organic frameworks (MOFs). This thesis examines post-combustion carbon capture in sub-ambient PSA, a potential route to an effective adsorption process, using MOF materials via molecular modeling. We first estimated the reproducibility of CO2 adsorption isotherm measurements in MOFs via literature meta-analysis. This chapter provides a comprehensive summary of the state of knowledge regarding CO2 adsorption in MOFs and its implications for molecular modeling of adsorption in MOFs. We then examined the upper bounds on CO2 swing capacity in sub-ambient PSA by Grand Canonical Monte Carlo (GCMC) simulation of an extensive collection of MOFs. A wide variety of MOFs was found to have swing capacity exceeding 10 mol/kg at sub-ambient temperatures provided that MOFs are appropriately selected based on their physical properties. We also assessed the capability of simple proxies for adsorbent performance and approximate models of cyclic adsorption to predict the outcomes of detailed process models of adsorption-based CO2 capture processes. To this end, we discuss the correlations between predictions from the simpler models and detailed process models. As a separate contribution, molecular modeling of chemical warfare agents (CWAs) adsorption in MOFs was analyzed. Molecular models of adsorption of CO2, CWAs or other molecules typically employ a rigid framework approximation for computational convenience. All real frameworks including MOFs, however, have intrinsic flexibility due to thermal vibrations. We examine the implications of this simple observation for quantitative predictions of the properties of adsorbed CWAs.

Park, Jongwoo↗
DOE OSTI2018

Bayesian characterization of explosive sources using infrasonic signals

In this paper, a Bayesian approach is applied to the estimation of source characteristics for above ground explosive events using infrasonic observations at propagation distances of hundreds of kilometers. Propagation-based, stochastic path geometry models have previously been investigated for infrasonic source localization with promising results; here, statistical transmission loss models are investigated using archived atmospheric specifications and propagation simulation tools to demonstrate that such an approach is applicable to source characterization. The resulting transmission loss models models are utilized in estimating near-source spectral characteristics for explosive events from infrasonic observations at regional distances of several hundred kilometers or more using a Bayesian framework to compute a combined estimate. The near-source spectral characterization can be used along with a simplistic explosive source model to compute an estimate of explosive yield with quantifiable uncertainty. Finally, the yield estimation framework is evaluated using above-ground explosive events from the western US during the fall of 2012 with promising results.

58 GEOSCIENCES↗
DOE OSTI2019

A unified approach to evaluating precipitation frequency estimates with uncertainty quantification: Application to Florida and California watersheds

Although a variety of climate datasets are now available, including observational and model products, there remains a pressing need for the development of a unified, automated and application-focused approach for evaluating and comparing climate extremes within and across these datasets. Precipitation frequency (PF) es- timates for extreme precipitation events are useful decision-relevant quantities among water managers. Our objective and quantitative framework for computing PF estimates of any duration uses known techniques in a novel combination. Our framework consists of three steps: (1) use of a regionalization-based statistical method for precipitation frequency estimation at observed sites; this involves hierarchical clustering (here we used Ward’s method) for delineating homogeneous regions, and regional frequency analysis using L-moments; (2) use of kriging for spatial mapping because of its advantages over other conventional interpolation methods; (3) use of z-scores accounts for estimation uncertainties when comparing PF estimates between datasets. The 24-h PF estimates in the Kissimmee-Southern Florida watershed (flat topography) and the Sacramento-San Joaquin watershed (complex topography) demonstrate the applicability of this approach in regions of any geographical complexity. Our results are shown to be reasonably calibrated using the probability integral transform (PIT) histogram of the best fitted distribution. Our results are compared with that of the NOAA Atlas 14 reports and show that for most of the stations the two estimates are statistically indistinguishable; and, the confidence intervals of our estimates are narrower than those of the NOAA estimates. Our approach is applicable to a variety of datasets and provides a baseline for assessing performance of climate models in historical simulations – a necessary first step towards analyzing future projections.

58 GEOSCIENCES↗
DOE OSTI2023

Computationally Efficient Control Co-Design Optimization Framework with Mixed-Fidelity Fluid and Structure Analysis: OpenTurbineCoDe (OTCD) - ARPA-E ATLANTIS Phase I Project (Final Technical Report)

The goal of the Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control (ATLANTIS) Program is to develop new technologies for floating offshore wind turbines, or wind farms, using the discipline of control co-design (CCD.) In this context, our goal is to develop a computationally efficient optimization framework for design of floating offshore wind turbines. Our specific aim is to utilize high-fidelity structural, aerodynamic, aero-structural tools, and to derive control-oriented reduced- or low-order models directly from the high-fidelity tools. We proposed a mixed-fidelity modeling approach which means that we are also using low- and mid-fidelity tools when necessary. This research is conducted by a multidisciplinary team consisting of Rutgers University, University of Michigan, Brigham Young University, and the National Renewable Energy Laboratory (NREL). The computational framework, called OpenTurbineCoDe, is designed to integrate, where possible, traditional structural, aerodynamic, aeroelastic models (e.g., OpenFAST) and advanced control algorithms with higher fidelity simulation tools including Reynolds-averaged Navier–Stokes (RANS) solvers, and three-dimensional structural finite element solvers. All the high-fidelity tools used in this research provide numerically exact gradients to facilitate both efficient optimization and local linearization for control implementation.

17 WIND ENERGY↗
DOE OSTI2016

Techno-Economic Simulation Approach in Preparation of Employing Renewable Energies for Process Industry

The energy system of process industry are faced with a new unprecedented challenge. Renewable energies should be incorporated but single of them cannot meet its energy demand of high degree and a large quantity. This paper investigates a simulation framework to compute the capacity of multiple energy sources including solar, wind power, diesel and batteries. The framework involves actual renewable energy supply and demand profile generation and supply demand matching. Eight configurations of different supply options are evaluated to illustrate the applicability of the proposed framework with some remarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

ARES v1.x - Performance Portable Tool to Simulate Supernovae based on Parthenon Framework

Historically, codes for simulating supernovae (such as Arepo, FLASH or LEAFS) have been at the forefront of scientific high-performance computing to the immense computational resources required for full 3D simulations. However, given the shift towards heterogenous HPC architectures, many current-generation codes are at the risk of losing their competitiveness as they are only designed to run on homogeneous CPU-only systems. There exist several efforts to enable these codes for GPU’s, however, these efforts only consider specific architectures or vendors (e.g., implement only CUDA or HIP), limiting themselves to a small range of exascale computing systems. Frameworks such as Kokkos aim to provide a framework which is agnostic of the targeted architecture, enabling the development of performant and portable code. In the Ares code, we develop a performance portable tool to simulate supernovae based on the Parthenon Framework, which in turn uses Kokkos in the background. Here, the Parthenon Framework provides an interface to the underlying mesh-refinement routines, which form the backbone of our code. In addition, we incorporate the already existing Singularity-EOS toolkit to provide us with various equations of state, primarily the Helmholtz equation of state. We also include the JINA Reaclib as a basis for our nuclear network solver. Finally, we implement a gravity solver to complete the required physics. This setup will provide us with a minimal code base to simulate supernova in a similar style to the tried-and-tested Arepo code, but in a futureproof performance portable framework.

Lim, Hyun↗
DOE OSTI2019

A graph theoretic framework for representation, exploration and analysis on computed states of physical systems

A graph theoretic perspective is taken for a range of phenomena in continuum physics in order to develop representations for analysis of large scale, high-fidelity solutions to these problems. Of interest are phenomena described by partial differential equations, with solutions being obtained by computation. The motivation is to gain insight that may otherwise be difficult to attain because of the high dimensionality of computed solutions. We consider graph theoretic representations that are made possible by low-dimensional states defined on the systems. These states are typically functionals of the high-dimensional solutions, and therefore retain important aspects of the high-fidelity information present in the original, computed solutions. Our method is rooted in regarding each state as a vertex on a graph and identifying edges via processes that are induced either by numerical solution strategies, or by the physics. Correspondences are drawn between the sampling of stationary states, or the time evolution of dynamic phenomena, and the analytic machinery of graph theory. A collection of computations is examined in this framework and new insights to them are presented through analysis of the corresponding graphs.

42 ENGINEERING↗
DOE OSTI2019

Computational screening of metal–organic frameworks for biogas purification

Biogas, which involves methane as the combustible compound, is an abundant and renewable energy resource that produces less harmful gases than conventional fossil-based liquid and solid energy sources. Although biogas is of primary interest due to its methane content, it may also include other gases, such as CO 2 , N 2 , H 2 S, and NH 3 . Studies investigating biogas purification often assume that biogas is a binary 50%/50% mixture of methane and carbon dioxide. However, together with N 2 , the toxic contaminants, H 2 S and NH 3 should be accounted for in the biogas mixture for a more realistic separation application. In this study, the computation-ready experimental metal–organic framework (CoRE-MOF) database is screened to identify a shortlist of potentially high-performing MOFs for multi-component biogas purification. Our hierarchical screening process involves (i) removal of MOFs with sub-3 Å pore limiting diameter and uncommon metal nodes, (ii) removal of MOFs that do not selectively capture the four undesired compounds, as determined from grand canonical Monte Carlo (GCMC) simulations for the binary mixtures of CH 4 /(CO 2 or N 2 or H 2 S or NH 3 ), and (iii) ranking of the remaining structures based on various performance metrics determined from GCMC for a five-component mixture. Finally, the relations between some of these metrics and structural properties are discussed to reveal favorable structural characteristics for biogas upgrading.

42 ENGINEERING↗
DOE OSTI2015

Bethe–Salpeter calculation of optical-absorption spectra of In 2 O 3 and Ga 2 O 3

Transparent conducting oxides keep attracting strong scientific interest not only due to their promising potential for “transparent electronics” applications but also due to their interesting optical absorption characteristics. Materials such as In 2 O 3 and Ga 2 O 3 have complicated unit cells and, consequently, are interesting systems for studying the physics of excitons and the anisotropy of optical absorption. Since currently no experimental data is available, for instance, for their dielectric functions across a large photon-energy range, we employ modern first-principles computational approaches based on many-body perturbation theory to provide theoreticalspectroscopy results. Using the Bethe-Salpeter framework, we compute dielectric functions and we compare these results to spectra computed without excitonic effects. We find that the electron-hole interaction strongly modifies the spectra and we discuss the anisotropy of the optical absorption that we find for Ga 2 O 3 in relation to existing theoretical and experimental data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Anomaly Attribution with Likelihood Compensation

This paper addresses the task of explaining anomalous predictions of a black-box regression model. When using a black-box model, such as one to predict building energy consumption from many sensor measurements, we often have a situation where some observed samples may significantly deviate from their prediction. It may be due to a sub-optimal black-box model, or simply because those samples are outliers. In either case, one would ideally want to compute a responsibility score indicative of the extent to which an input variable is responsible for the anomalous output. In this work, we formalize this task as a statistical inverse problem: Given model deviation from the expected value, infer the responsibility score of each of the input variables. We propose a new method called likelihood compensation (LC), which is founded on the likelihood principle and computes a correction to each input variable. To the best of our knowledge, this is the first principled framework that computes a responsibility score for real valued anomalous model deviations. We apply our approach to a real-world building energy prediction task and confirm its utility based on expert feedback.

Idé, Tsuyoshi↗
DOE OSTI2024

Effective field theory for dark matter absorption on single phonons

Single phonon excitations, with energies in the 1–100 meV range, are a powerful probe of light dark matter (DM). Utilizing effective field theory, we derive a framework to compute DM absorption rates into single phonons starting from general DM-electron, proton, and neutron interactions. We apply the framework to a variety of DM models: Yukawa coupled scalars, axionlike particles with derivative interactions, and vector DM coupling via gauge interactions or Standard Model electric and magnetic dipole moments. We find that GaAs or Al 2 O 3 targets can set powerful constraints on a U ( 1 ) B − L model, and targets with electronic spin ordering are similarly sensitive to DM coupling to the electron magnetic dipole moment. Lastly, we make the code, (an extension of the existing code which computes general DM–single phonon scattering rates), publicly available. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Enhancing risk and crisis communication with computational methods: A systematic literature review

Abstract Recent developments in risk and crisis communication (RCC) research combine social science theory and data science tools to construct effective risk messages efficiently. However, current systematic literature reviews (SLRs) on RCC primarily focus on computationally assessing message efficacy as opposed to message efficiency. We conduct an SLR to highlight any current computational methods that improve message construction efficacy and efficiency. We found that most RCC research focuses on using theoretical frameworks and computational methods to analyze or classify message elements that improve efficacy. For improving message efficiency, computational and manual methods are only used in message classification. Specifying the computational methods used in message construction is sparse. We recommend that future RCC research apply computational methods toward improving efficacy and efficiency in message construction. By improving message construction efficacy and efficiency, RCC messaging would quickly warn and better inform affected communities impacted by current hazards. Such messaging has the potential to save as many lives as possible.

Mathematical Methods In Social Sciences↗
DOE OSTI2026

Sensitivity of the CUPID experiment to $0\nu \beta \beta$ decay of 100 Mo

CUPID is a next-generation bolometric experiment to search for neutrinoless double-beta decay ($0\nu \beta \beta$ ) of 100 Mo using Li 2 MoO 4 scintillating crystals. It will operate 1596 crystals at ~10 mK in the CUORE cryostat at the Laboratori Nazionali del Gran Sasso in Italy. Each crystal will be facing two Ge-based bolometric light detectors for α rejection. We compute the discovery and the exclusion sensitivity of CUPID to $0\nu \beta \beta$ in a Frequentist and a Bayesian framework. This computation is done numerically based on pseudo-experiments. For the CUPID baseline scenario, with a background and an energy resolution of 1.0 x 10 –4 counts/keV/kg/yr and 5 keV FWHM at the Q-value, respectively, this results in a Bayesian exclusion sensitivity (90% c.i.) of $\hat{T}_{1/2} > 1.6 \times 10^{27} \ \textrm{yr}$, corresponding to the effective Majorana neutrino mass of $\hat{m}_{\beta \beta } < \ 9.6$ – 28 meV. The Frequentist discovery sensitivity (3σ ) is $\hat{T}_{1/2}= 1.0 \times 10^{27} \ \textrm{yr}$, corresponding to $\hat{m}_{\beta \beta }= \ 12$ – 36 meV.

Alfonso, K. [Virginia Polytechnic Institute and St↗
DOE OSTI2018

Charge transport in organic molecular semiconductors from first principles: The bandlike hole mobility in a naphthalene crystal

Predicting charge transport in organic molecular crystals is notoriously challenging. Carrier mobility calculations in organic semiconductors are dominated by quantum chemistry methods based on charge hopping, which are laborious and only moderately accurate. We compute from first principles the electron-phonon scattering and the phonon-limited hole mobility of naphthalene crystal in the framework of ab initio band theory. Our calculations combine GW electronic bandstructures, ab initio electron-phonon scattering, and the Boltzmann transport equation. The calculated hole mobility is in very good agreement with experiment between 100–300K, and we can predict its temperature dependence with high accuracy. Here we show that scattering between intermolecular phonons and holes regulates the mobility, though intramolecular phonons possess the strongest coupling with holes. We revisit the common belief that only rigid molecular motions affect carrier dynamics in organic molecular crystals. Our paper provides a quantitative and rigorous framework to compute charge transport in organic crystals and is a first step toward reconciling band theory and carrier hopping computational methods.

36 MATERIALS SCIENCE↗