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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

LandScan HD: a high-resolution gridded ambient population methodology for the world

Unwarned population distributions accounting for routine human activities are needed to address many global human security challenges, including disasters, conflict, and infrastructure demand. LandScan High Definition (LSHD) supports this need through gridded ambient population estimates that measure average human presence between daytime and nighttime at a high spatial resolution of 3 arcseconds (approximately 90 m). Although LSHD has traditionally been produced on a country-specific basis, advances in global foundational data and computational resources now enable scaling its methodology to the world. Combining aspects of top-down and bottom-up gridded population methods, LSHD allocates subnational population totals from authoritative statistics to built-up areas based on occupancy estimates for multiple facility types (e.g., residential, commercial) and then reaggregates these estimates to a global population grid. We scale this approach by organizing the LSHD data stack into a 1° resolution tileset of vector analytic features, enabling an efficient and repeatable workflow for all countries worldwide. Examining the Philippines as an output of the global LSHD baseline dataset, we contrast unwarned and residential (WorldPop) population distributions by (1) exploring a practical application of flood risk assessment and (2) evaluating their congruence with outcomes of collective human activities (subnational CO 2 emissions). Finally, we discuss plans to address current LSHD limitations through data/modeling and uncertainty quantification improvements and provide outlook for workflow automation and extending the model to social, demographic and economic population characteristics.

Building morphology↗
DOE OSTI2013

Supercomputing meets seismology in earthquake exhibit

When the California Academy of Sciences created the "Earthquake: Evidence of a Restless Planet" exhibit, they called on Lawrence Livermore to help combine seismic research with the latest data-driven visualization techniques. The outcome is a series of striking visualizations of earthquakes, tsunamis and tectonic plate evolution. Seismic-wave research is a core competency at Livermore. While most often associated with earthquakes, the research has many other applications of national interest, such as nuclear explosion monitoring, explosion forensics, energy exploration, and seismic acoustics. For the Academy effort, Livermore researchers simulated the San Andreas and Hayward fault events at high resolutions. Such calculations require significant computational resources. To simulate the 1906 earthquake, for instance, visualizing 125 seconds of ground motion required over 1 billion grid points, 10,000 time steps, and 7.5 hours of processor time on 2,048 cores of Livermore's Sierra machine.

58 GEOSCIENCES↗
DOE OSTI2024

ARPA-E Grid Optimization (GO) Competition Challenge 2

The ARPA-E Grid Optimization (GO) Competition Challenge 2, from 2020 to 2021, expanded upon the problem posed in Challenge 1 by adding adjustable transformer tap ratios, phase shifting transformers, switchable shunts, price-responsive demand, ramp rate constrained generators and loads, and fast-start unit commitment. Furthermore, Challenge 2 was a maximization problem while Challenge 1 was a minimization problem. Specifically, the economic surplus, defined as the benefit of serving load minus the cost of generation, is being maximized. It was expected that the objective value of a given solution should be positive, representing economic gain, but negative objectives from poor solutions were possible. The two code submission feature of Challenge 1 was maintained. Additionally, Divisions 3 and 4 within the competition permitted on/off switching of transmission lines (Divisions 1 and 2 did not). After the initial release of the Problem Formulation on 7/20/2020, ARPA-E Director Lane Genatowski announced Challenge 2 on 9/12/2020. The final May 31, 2021, version of the Problem Formulation was 97 pages long with 299 equations. The Challenge proceeded with 2 non-prize Events and 2 prize Events. Teams receiving Challenge 1 FOA awards and prize money were required to use the prize money to fund their Challenge 2 efforts (Georgia Institute of Technology, Global Optimal Technology, Inc., Lawrence Livermore National Laboratory, Lehigh University, Northwestern University, Artelys, Columbia, Pearl Street Technologies, Pennsylvania State University, and University of Colorado Boulder). For more information on the competition and challenge 2 see the "GO Competition Challenge 2 Information" resource below. Challenge 1 and Challenge 3 information can be found in the resources linked below.

ACOPF↗
DOE OSTI2015

Computational Fluid Dynamics Simulation of Gasoline Compression Ignition

Gasoline compression ignition (GCI) is a low temperature combustion (LTC) concept that has been gaining increasing interest over the recent years owing to its potential to achieve diesel-like thermal efficiencies with significantly reduced engine-out nitrogen oxides (NOx) and soot emissions compared to diesel engines. In this work, closed-cycle computational fluid dynamics (CFD) simulations are performed of this combustion mode using a sector mesh in an effort to understand effects of model settings on simulation results. One goal of this work is to provide recommendations for grid resolution, combustion model, chemical kinetic mechanism, and turbulence model to accurately capture experimental combustion characteristics. Grid resolutions ranging from 0.7 mm to 0.1 mm minimum cell sizes were evaluated in conjunction with both Reynolds averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) based turbulence models. Solution of chemical kinetics using the multi-zone approach is evaluated against the detailed approach of solving chemistry in every cell. The relatively small primary reference fuel (PRF) mechanism (48 species) used in this study is also evaluated against a larger 312-species gasoline mechanism. Based on these studies the following model settings are chosen keeping in mind both accuracy and computation costs – 0.175 mm minimum cell size grid, RANS turbulence model, 48-species PRF mechanism, and multi-zone chemistry solution with bin limits of 5 K in temperature and 0.05 in equivalence ratio. With these settings, the performance of the CFD model is evaluated against experimental results corresponding to a low load start of injection (SOI) timing sweep. The model is then exercised to investigate the effect of SOI on combustion phasing with constant intake valve closing (IVC) conditions and fueling over a range of SOI timings to isolate the impact of SOI on charge preparation and ignition. Simulation results indicate that there is an optimum SOI timing, in this case -30?aTDC (after top dead center), which results in the most stable combustion. Advancing injection with respect to this point leads to significant fuel mass burning in the colder squish region, leading to retarded phasing and ultimately misfire for SOI timings earlier than -42?aTDC. On the other hand, retarding injection beyond this optimum timing results in reduced residence time available for gasoline ignition kinetics, and also leads to retarded phasing, with misfire at SOI timings later than -15?aTDC.

Energy conversion↗
DOE OSTI2026

MFC 5.0: An exascale many-physics flow solver

Many problems of interest in engineering, medicine, and the fundamental sciences rely on high-fidelity flow simulation, making performant computational fluid dynamics solvers a mainstay of the open-source software community. Previous work MFC 3.0 was made a published, documented, and open-source solver via Bryngelson et al. Comp. Phys. Comm. (2021) with numerous physical features, numerical methods, and scalable infrastructure. MFC 5.0 is a significant update to MFC 3.0, featuring a broad set of well-established and novel physical models and numerical methods, as well as the introduction of GPU and APU (or superchip) acceleration. Here, we exhibit state-of-the-art performance and ideal scaling on the first two exascale supercomputers, OLCF Frontier and LLNL El Capitan. Combined with MFC’s single-accelerator performance, MFC achieves exascale computation in practice, and achieved the largest-to-date public CFD simulation at 200 trillion grid points as a 2025 ACM Gordon Bell Prize finalist. New physical features include the immersed boundary method, N-fluid phase change, Euler–Euler and Euler–Lagrange sub-grid bubble models, fluid-structure interaction, hypo- and hyper-elastic materials, chemically reacting flow, two-material surface tension, magnetohydrodynamics (MHD), and more. Numerical techniques now represent the current state-of-the-art, including general relaxation characteristic boundary conditions, WENO variants, Strang splitting for stiff sub-grid flow features, and low Mach number treatments. Weak scaling to tens of thousands of GPUs on OLCF Summit and Frontier and LLNL El Capitan achieves efficiencies within 5% of ideal to over 90% of their respective system sizes. Strong scaling results for a 16-times increase in device count show parallel efficiencies over 90% on OLCF Frontier. MFC’s software stack has undergone further improvements, including continuous integration, which ensures code resilience and correctness through over 300 regression tests; metaprogramming, which reduces code length while maintaining performance portability; and code generation for computing chemical reactions

Computational fluid dynamics↗
DOE OSTI2016

CFD-Informed Spacer Grid Models in CTF: Heat Transfer Enhancement and Form Pressure Losses

This report presents the current status of the pressure loss coefficient and heat transfer enhancement models derived for CTF from computational fluid dynamics (CFD) data. This is an effort to improve the modeling capabilities of CTF using results from a higher-fidelity code such as STAR-CCM+. The following four phenomena are the current scope of CFD-informed spacer grid models for CTF: (1) grid directed lateral cross-flow effects; (2) grid-induced turbulent-mixing effects; (3) grid-induced heat transfer enhancement downstream of the grid; and (4) the detailed pressure-loss effects caused by the spacer grid. This document covers phenomena (3) and (4) and how they are captured using CFD data. Please refer to CASL-U-2015-0020-000 for a discussion on phenomena (1) and (2).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Software predicts disaster-driven grid failures

A new, free, open-source software reliably predicts how damage from hurricanes, ice storms, earthquakes, and other extreme events will restrict power delivery from utility grids. The Severe Contingency Solver for Electric Power Transmission is the only software available—commercially or open-source—that reliably supports analysis of extreme events that cause widespread damage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Analysis on the Influence of an Energy Storage System and its Impact to the Grid for a Wave Energy Converter

Reducing power fluctuations is essential for controlling the integration impacts of wave energy converter (WEC) plants in both distribution and transmission grids, and in stand-alone isolated power systems. This paper presents an analysis on the cost of and how a battery storage system can be used to further reduce the variation of power generated from the WEC due to the fluctuating nature of waves and its impact to the grid. The electrical power output from WEC-Sim simulations for the six sea states used in the Wave Energy Prize was analyzed to compute the peak power and power time history. The results were used to evaluate the battery storage capacity that is needed for a WEC system to provide reasonable power flow to the grid and estimate its cost based on the latest cost information for battery technologies published by the U.S. Energy Information Administration. Finally, a preliminary grid integration analysis was performed to demonstrate how WEC-generated power would contribute to a small island electricity system. As shown in the study, the instantaneous peak power is the primary cost driver for the battery storage and the power take-off system, and reducing the power fluctuations is essential for reducing the overall levelized cost of energy (LCOE). The power flow variation from WECs can be significantly reduced using battery storage without adding significant overall system costs, and the implementation of battery storage is essential for grid integration applications. There may also be additional opportunities to further investigate energy storage technologies that are specific to WEC applications to reduce these costs even further.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Co-Simulation Meets AI: MCP-Driven Power System Analysis

GridGPT, a fine-tuned Generative AI model is designed for on-premise use in grid control rooms. This presentation will demonstrate how eGridGPT can seamlessly integrate with control room solutions to offer operators, engineers, and corporate users enhanced guidance and decision support. It is to show how this innovative AI solution can improve state estimation, boost variable energy forecasting, and optimize grid operations. By leveraging eGridGPT's unique features, audience will learn to unlock new levels of automation, predictive analytics, and reliability within their power systems, ultimately leading to reduced downtime and improved operational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Analysis on the Influence of an Energy Storage System and Its Impact to the Grid for a Wave Energy Converter: Preprint

This paper presents an analysis on the cost of and how a battery storage system can be used to further reduce the variation of power generated from the wave energy converter (WEC) due to the fluctuating nature of waves and its impact to the grid. The electrical power output from WEC-Sim simulations for the six sea states used in the Wave Energy Prize was analyzed to compute the peak power and power time history. The results were used to evaluate the battery storage capacity that is needed for a WEC system to provide reasonable power flow to the grid and estimate its cost based on the latest cost information for battery technologies published by the U.S. Energy Information Administration. Finally, a preliminary grid integration analysis was performed to demonstrate how WEC-generated power would contribute to a small island electricity system. As shown in the study, the instantaneous peak power is the primary cost driver for the battery storage and the power take-off system, and reducing the power fluctuations is essential for reducing the overall levelized cost of energy (LCOE). The power flow variation from WECs can be significantly reduced using battery storage without adding significant overall system costs, and the implementation of battery storage is essential for grid integration applications. There may also be additional opportunities to further investigate energy storage technologies that are specific to WEC applications to reduce these costs even further.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Model-Free Building Temperature Control and Power Allocation Under Measurement Time Delays

Taking a step towards a greener planet has created an increased need for a higher integration of renewable energy resources into the electric grid. Nonetheless, the intermittency and uncertainty associated with renewable generation have slowed down this integration. Demand response (DR) has been recently adopted to address this challenge by utilizing demand side flexibility and enabling the participation of many grid-interactive efficient buildings (GEBs). However, existing DR methods require significant modeling and/or training efforts and are computationally expensive. To address the aforementioned issues, we propose a model-free control (MFC)-based strategy that is robust to the time delays in the temperature measurements of the thermostatically controlled loads (TCLs). It assigns to each GEB a local controller to maintain the TCLs’ temperatures within desired comfort levels, while the load aggregator (LA) allocates the assigned reference power provided by the distribution system operator (DSO) to support a specific grid service, such as demand peak reduction, load shifting, balancing supply and demand, and consuming the solar photovoltaic power locally. We investigate the effects of such loss of information on the local control action as well as on meeting the power allocation constraint. We conclude that, for an appropriate choice of design parameters, the proposed MFC controller is satisfactorily robust to measurement time delays.

Telsang, Bhagyashri↗
DOE OSTI2019

Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators

We present an adaptive grid matrix-free operator approximation scheme based on a "product-convolution" interpolation of convolution operators. This scheme is appropriate for operators that are locally translation-invariant, even if these operators are high rank or full rank. Such operators arise in Schur complement methods for solving partial differential equations (PDEs), as Hessians in PDE-constrained optimization and inverse problems, as integral operators, as covariance operators, and as Dirichlet-to-Neumann maps. Constructing the approximation requires computing the impulse responses of the operator to point sources centered on nodes in an adaptively refined grid of sample points. A randomized a posteriori error estimator drives the adaptivity. Once constructed, the approximation can be efficiently applied to vectors using the fast Fourier transform. The approximation can be efficiently converted to hierarchical matrix (H-matrix) format, then inverted or factorized using scalable H-matrix arithmetic. The quality of the approximation degrades gracefully as fewer sample points are used, allowing cheap lower quality approximations to be used as preconditioners. Furthermore, this yields an automated method to construct preconditioners for locally translation-invariant Schur complements. We directly address issues related to boundaries and prove that our scheme eliminates boundary artifacts. We test the scheme on a spatially varying blurring kernel, on the nonlocal component of an interface Schur complement for the Poisson operator, and on the data misfit Hessian for an advection dominated advection-diffusion inverse problem. Numerical results show that the scheme outperforms existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A Full Multigrid Method for the Self-Adjoint Angular Flux Equation Based on Cellwise Block Jacobi Iteration

Previous work by Densmore et al. has demonstrated that multigrid methods for the self-adjoint angular flux (SAAF) equation with cellwise block Jacobi smoothing can be extremely effective at solving for the angular flux in one dimension. The extension of that work to two dimensions demonstrated that while the smoother works well, the use of a direct coarse-grid approximation can severely limit the rate of convergence for optically thin cells. In that paper, this convergence limit was evaded through the use of a partially Galerkin coarse-grid approximation. However, relying on a Galerkin coarse-grid approximation is not ideal as constructing the coarse-grid discretization in this approach is complicated. The motivation for this summary is to find a method that can work without the need for a Galerkin coarse-grid approximation. The Full Multigrid (FMG) method is well known as a method that can theoretically solve a problem to its discretization accuracy with optimal linear computational complexity, that is in just O(N) operations for N unknowns. Indeed, we develop an FMG method for the 2-D SAAF equation that yields discretization accuracy and does not require the use of a Galerkin coarse-grid approximation. Until recently, aside from proofs about the order of the error for FMG, little work had been done in quantifying when and how FMG can obtain discretization accuracy. However, recent work by Rodrigo et al. has introduced a Fourier analysis technique called worst-case right-hand side analysis used to calculate the FMG accuracy measure. The FMG accuracy measure is the upper bound on the constant of proportionality between the error of the FMG solution and the discretization error. In this summary, we develop and implement an FMG method for the 2-D Cartesian SAAF equations. We then perform worst-case right-hand side analysis and give numerical examples that demonstrate under what circumstances the method can solve the 2-D SAAF equations to discretization accuracy, for optically thin cells, without the need for a Galerkin coarse-grid approximation. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques on two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.

clustering, k-means, power grid, graphs↗
DOE OSTI2020

Automated Integration of Continental-Scale Observations in Near-Real Time for Simulation and Analysis of Biosphere–Atmosphere Interactions

The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.

Durden, David J.↗
DOE OSTI2016

ACCELERATED FITTING OF STELLAR SPECTRA

Stellar spectra are often modeled and fitted by interpolating within a rectilinear grid of synthetic spectra to derive the stars’ labels: stellar parameters and elemental abundances. However, the number of synthetic spectra needed for a rectilinear grid grows exponentially with the label space dimensions, precluding the simultaneous and self-consistent fitting of more than a few elemental abundances. Shortcuts such as fitting subsets of labels separately can introduce unknown systematics and do not produce correct error covariances in the derived labels. In this paper we present a new approach—Convex Hull Adaptive Tessellation (chat)—which includes several new ideas for inexpensively generating a sufficient stellar synthetic library, using linear algebra and the concept of an adaptive, data-driven grid. A convex hull approximates the region where the data lie in the label space. A variety of tests with mock data sets demonstrate that chat can reduce the number of required synthetic model calculations by three orders of magnitude in an eight-dimensional label space. The reduction will be even larger for higher dimensional label spaces. In chat the computational effort increases only linearly with the number of labels that are fit simultaneously. Around each of these grid points in the label space an approximate synthetic spectrum can be generated through linear expansion using a set of “gradient spectra” that represent flux derivatives at every wavelength point with respect to all labels. These techniques provide new opportunities to fit the full stellar spectra from large surveys with 15–30 labels simultaneously.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Interleaved Cuk Converter Wave Energy System With Advanced Control and Grid Support Functions for Seamless Integration: Preprint

This paper presents an innovative wave energy conversion system employing an interleaved Cuk converter and advanced nonlinear control for seamless integration with the grid. The proposed system utilizes the interleaved Cuk converter for efficient power extraction on the DC side, while an inverter facilitates power transfer to the grid or load on the AC side. A sophisticated nonlinear control architecture based on Lyapunov energy functions ensures stable and optimal operation under varying wave conditions. Case study results demonstrate the effectiveness of the proposed system, highlighting its ability to efficiently harness wave energy and seamlessly integrate with the grid, thus paving the way for sustainable and reliable renewable energy generation. The overall system is verified via computer simulations based on MATLAB/Simulink and various case study results are presented.

HYDRO ENERGY,TIDAL AND WAVE POWER↗
DOE OSTI2024

Influence of alloy solidification path on melt pool behavior in additive manufacturing

Numerical models used to study transport phenomena in laser-powder bed fusion processes often rely on assumptions and simplifications to reduce their computational expense. One common simplification is in the description of latent heat evolution during the solid-liquid phase change (i.e., the solidification pathway), justified by the fact that the mushy zone thickness is similar to the numerical grid spacing used for continuum transport models. The lack of resolution of transport phenomena in the mushy zone motivates the use of computationally convenient solidification paths such as linear or sigmoidal relationships over pathways derived from fundamental solidification theory such as equilibrium or Scheil models. In the present work, an uncertainty quantification (UQ) framework is used to analyze the influence of solidification pathway selection on the solidification dynamics and melt pool geometries in laser based additive manufacturing (AM) of IN625. Results show the solidification pathway has a quantifiable influence on the cooling rate at the liquidus isotherm, mushy zone thickness, and solidification time. Due to similarities in the latent heat evolution at the beginning of solidification, the equilibrium and Scheil models predict similar cooling rates near the liquidus isotherm, however the wider freezing range of Scheil leads to a wider mushy zone compared to equilibrium. The non-physical latent heat release profiles of sigmoidal and linear paths lead to significant overpredictions of cooling rates at the liquidus isotherm compared to equilibrium and Scheil. Finally, these results indicate that careful consideration should be given to the choice of solidification pathway to ensure reliable model predictions.

36 MATERIALS SCIENCE↗