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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 667 records · Page 37

SIMWEST - A simulation model for wind energy storage systems

This paper describes a comprehensive and efficient computer program for the modeling of wind energy systems with storage. The level of detail of SIMWEST (SImulation Model for Wind Energy STorage) is consistent with evaluating the economic feasibility as well as the general performance of wind energy systems with energy storage options. The software package consists of two basic programs and a library of system, environmental, and control components. The first program is a precompiler which allows the library components to be put together in building block form. The second program performs the technoeconomic system analysis with the required input/output, and the integration of system dynamics. An example of the application of the SIMWEST program to a current 100 kW wind energy storage system is given.

Edsinger, R. W.↗

infrastore [SWR-26-077]

Infrastore is time-series storage for energy-systems simulations, backed by HDF5 + SQLite, with Rust, Python, Julia, gRPC, and CLI bindings. It is a Rust library for managing time-series data in power-systems and energy simulations. Numerical arrays are persisted in HDF5, and the metadata associating each array with its owning component lives in SQLite. Identical arrays are stored once and shared through content addressing. It ships native Rust, Python (PyO3), and Julia (C ABI) interfaces, the infrastore command-line tool, and a read-only gRPC server with a Rust client. Documentation: https://natlabrockies.github.io/infrastore/latest/ — start with the Quick Start or the Architecture.

Thom, Daniel [National Laboratory of the Rockies (↗

Evaluation of solar thermal power plants using economic and performance simulations

An energy cost analysis is presented for central receiver power plants with thermal storage and point focusing power plants with electrical storage. The present approach is based on optimizing the size of the plant to give the minimum energy cost (in mills/kWe hr) of an annual plant energy production. The optimization is done by considering the trade-off between the collector field size and the storage capacity for a given engine size. The energy cost is determined by the plant cost and performance. The performance is estimated by simulating the behavior of the plant under typical weather conditions. Plant capital and operational costs are estimated based on the size and performance of different components. This methodology is translated into computer programs for automatic and consistent evaluation.

El-Gabawali, N.↗

Annual Energy Savings and Peak Power Reduction Simulated for CCHP Design and Baseline HP in Cold Climate Cities

This report assesses energy savings and peak power reduction of three heat pumps in multiple US cold climate cities and building types. The three heat pumps comprise a baseline heat pump and two high efficiency cold climate heat pumps (CCHP). The DOE/ORNL Heat Pump Design Model was used to simulate the heat pumps and generate performance curves for EnergyPlus building energy simulations. The annual energy simulations were performed over seven cold climates: 1) Minneapolis, MN; 2) Duluth, MN; 3) Fairbanks, AK; 4) Helena, MT; 5) Indianapolis, IN; 6) Peoria, IL and 7) Eagle County, CO. In order to assess impact of residential building types matching different energy codes, we simulated six single-family houses in Indianapolis, IN, including : 1) single-family house having a crawlspace; 2) having a slab foundation; 3) having a heated basement; 4) having an unheated basement; 5) one single-family house having a heated basement matching IECC code of 2009, 6) and one single-family house having a heated basement matching IECC code of 2012. The former 4 houses match the IECC 2006 code.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Simulation Toolkit for Renewable Energy Advanced Materials Modeling

STREAMM is a collection of python classes and scripts that enables and eases the setup of input files and configuration files for simulations of advanced energy materials. The core STREAMM python classes provide a general framework for storing, manipulating and analyzing atomic/molecular coordinates to be used in quantum chemistry and classical molecular dynamics simulations of soft materials systems. The design focuses on enabling the interoperability of materials simulation codes such as GROMACS, LAMMPS and Gaussian.

Sides, Scott↗

Development of HELICS-Based High-Performance Cyber-Physical Co-Simulation Framework for Distributed Energy Resources Applications

The rapid growth of distributed energy resources (DERs) has prompted increasing interest in the monitoring and control of DERs through hybrid smart grid communications resulting in the typical smart grid cyber-physical system. To fully understand the interdependency between them, we propose to integrate the Network Simulator 3 (NS3) into the High Engine for Large-Scale Infrastructure Co-Simulation (HELICS), a new open-source, cyber-physical-energy co-simulation platform. This paper aims to the development and case study of the HELICS-based high performance distribution-communication co-simulation framework for the DER coordination. The novel co-simulation framework for the NS3 integrating into the HELICS is developed. The DER monitoring application about hybrid smart grid communication network design is simulated and validated on this proposed HELICS-based cyber-physical co-simulation platform.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Reactor Subsystem Simulation for Nuclear Hybrid Energy Systems

Nuclear Hybrid Energy Systems (NHES) could be a key part of the solution to achieving energy security, may provide reliable power availability even with increasing renewable energy penetration into the power grid, and may allow repurposing excess electricity in times of low demand. Incorporating a fission-based power source in a multi-output system (electricity and process heat) can offer significant advantages over carbon-based production sources, such as coal or natural gas, including reduction in atmospheric carbon emissions. In an integrated multi-output system, thermal energy from the nuclear reactor subsystem can be diverted to industrial applications in times of low electricity demand. High temperature, high quality heat from advanced reactor designs might be used for hydrogen production or synthetic fuel production (coal-to-liquid or natural gas-to-liquid processes). Low temperature heat from advanced reactor designs or the current and future fleet of light water reactors (LWRs) might be applied to desalination processes or be stored for later use in low temperature ammonia or hydrocarbon-based thermal cycles. The NHES research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation. Many computational tools and methods are available for modeling a nuclear reactor, power conversion systems and associated process applications. One method is to develop a single program capable of modeling the entire system. Another is to combine two or more existing computer programs, each modeling a portion of the system for which it is validated, where the programs exchange information to compute the solution. The former method requires a lengthy development and verification and validation process. The latter method leverages industry standard software to reduce development and funding requirements. Preliminary system models have been developed by Idaho National Laboratory researchers and are currently being enhanced to assess integrated system performance given multiple sources (e.g., nuclear + wind) and multiple applications (i.e., electricity + process heat). Initial efforts to integrate a Fortran-based simulation of a small modular reactor (SMR) with the balance of plant model have been completed in FY12. This initial effort takes advantage of an existing SMR model developed at North Carolina State University to provide initial integrated system simulation for a relatively low cost. The SMR subsystem simulation details are discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Nuclear Energy Advanced Modeling and Simulation (NEAMS) Accident Tolerant Fuels High Impact Problem: Engineering Scale Models and Analysis

As part of the Department of Energy's Nuclear Energy Advanced Modeling and Simulation program, an Accident Tolerant Fuel High Impact Problem was initiated at the beginning of fiscal year 2015 to investigate the behavior of \usi\ fuel and iron-chromium-aluminum (FeCrAl) cladding under normal operating and accident reactor conditions. The High Impact Problem was created in response to the United States Department of Energy's renewed interest in accident tolerant materials after the events that occurred at the Fukushima Daiichi Nuclear Power Plant in 2011. The High Impact Problem is a multinational laboratory and university collaborative research effort between Idaho National Laboratory, Los Alamos National Laboratory, Argonne National Laboratory, and the University of Tennessee, Knoxville. This report summarizes the latest recommended material models to be used for engineering scale simulations based upon lower length scale analyses described elsewhere. Comparative analyses between traditional fuel rods (U 3 Si 2 /Zircaloy-4) and the proposed accident tolerant fuel rods (UO 2 /FeCrAl and U 3 Si 2 /Zircaloy-4) under normal operation, loss of coolant, and reactivity insertion conditions have been revisited using the latest state-of-the-art models implemented into the Bison fuel performance code. Sensitivity analyses have also been redone to take into account the latest knowledge on uncertain parameters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Power Grid Simulation Testbed for Transactive Energy Management Systems

To effectively engage demand-side and distributed energy resources (DERs) for dynamically maintaining the electric power balance, the challenges of controlling and coordinating building equipment and DERs on a large scale must be overcome. Although several control techniques have been proposed in the literature, a significant obstacle to applying these techniques in practice is having access to an effective testing platform. Performing tests at scale using real equipment is impractical, so simulation offers the only viable route to developmental testing at scales of practical interest. Existing power-grid testbeds are unable to model individual residential end-use devices for developing detailed control formulations for responsive loads and DERs. Furthermore, they cannot simulate the control and communications at subminute timescales. To address these issues, this paper presents a novel power-grid simulation testbed for transactive energy management systems. Detailed models of primary home appliances (e.g., heating and cooling systems, water heaters, photovoltaic panels, energy storage systems) are provided to simulate realistic load behaviors in response to environmental parameters and control commands. The proposed testbed incorporates software as it will be deployed, and enables deployable software to interact with various building equipment models for end-to-end performance evaluation at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analysis and Simulation of a Blue Energy Cycle

The mixing process of fresh water and seawater releases a significant amount of energy and is a potential source of renewable energy. The so called ‘blue energy’ or salinity-gradient energy can be harvested by a device consisting of carbon electrodes immersed in an electrolyte solution, based on the principle of capacitive double layer expansion (CDLE). In this study, we have investigated the feasibility of energy production based on the CDLE principle. Experiments and computer simulations were used to study the process. Mesoporous carbon materials, synthesized at the Oak Ridge National Laboratory, were used as electrode materials in the experiments. Neutron imaging of the blue energy cycle was conducted with cylindrical mesoporous carbon electrodes and 0.5 M lithium chloride as the electrolyte solution. For experiments conducted at 0.6 V and 0.9 V applied potential, a voltage increase of 0.061 V and 0.054 V was observed, respectively. From sequences of neutron images obtained for each step of the blue energy cycle, information on the direction and magnitude of lithium ion transport was obtained. A computer code was developed to simulate the process. Experimental data and computer simulations allowed us to predict energy production.

30 DIRECT ENERGY CONVERSION↗

Functional uncertainty quantification for isobaric molecular dynamics simulations and defect formation energies

Functional uncertainty quantification (FunUQ) was recently proposed to quantify uncertainties in models and simulations that originate from input functions, as opposed to parameters. This paper extends here FunUQ to quantify uncertainties originating from interatomic potentials in isothermal-isobaric molecular dynamics (MD) simulations and to the calculation of defect formation energies. We derive and verify a computationally inexpensive expression to compute functional derivatives in MD based on perturbation theory. We show that this functional derivative of the quantities of interest (average internal energy, volume, and defect energies in our case) with respect to the interatomic potential can be used to predict those quantities for a different interatomic potential, without re-running the simulation. The codes and scripts to perform FunUQ in MD are freely available for download. In addition, to facilitate reproducibility and to enable use of best practices for the approach, we created Jupyter notebooks to perform FunUQ analysis on MD simulations and made them available for online simulation in nanoHUB. The tool uses cloud computing resources and users can view, edit, and run end-to-end workflows from a standard web-browser without the need to download or install any software.

36 MATERIALS SCIENCE↗

Vertically Resolved Analysis of the Madden-Julian Oscillation Highlights the Role of Convective Transport of Moist Static Energy

We simulate the Madden-Julian oscillation (MJO) over an aquaplanet with uniform surface temperature using the multiscale modeling framework (MMF) configuration of the Energy Exascale Earth System Model (E3SM-MMF). The model produces MJO-like features that have a similar spatial structure and propagation behavior to the observed MJO. To explore the processes involved in the propagation and maintenance of these MJO-like features, we perform a vertically resolved moist static energy (MSE) analysis for the MJO (Yao et al., 2022, https://doi.org/10.1175/jas-d-20-0254.1). Unlike the column-integrated MSE analysis, our method emphasizes the local production of MSE variance and quantifies how individual physical processes amplify and propagate the MJO's characteristic vertical structure. We find that radiation, convection, and boundary layer (BL) processes all contribute to maintaining the MJO, balanced by the large-scale MSE transport. Furthermore, large-scale dynamics, convection, and BL processes all contribute to the propagation of the MJO, while radiation slows the propagation. Additionally, we perform mechanism-denial experiments to examine the role of radiation and associated feedbacks in simulating the MJO. We find that the MJO can still self-emerge and maintain its characteristic structures without radiative feedbacks. This study highlights the role of convective MSE transport in the MJO dynamics, which was overlooked in the column-integrated MSE analysis.

54 ENVIRONMENTAL SCIENCES↗

Simulation-based design of energy management system with storage battery for a refugee shelter in Japan

Since the massive earthquake hit eastern Japan in March, 2011, our team has participated in the recovery planning for Kesen Association, which is a group of cities in northeastern Japan. As one of our proposals for the recovery planning for the community, we are designing energy management system with renewable energy (RE) and storage batteries. Some public facilities in the area have been used as refugee shelters, but refugees had to put up with life without electricity for a while after the disaster. If RE generator and storage batteries are introduced into the facilities, it is possible to provide refugees with electricity. In this study, the sizes of photovoltaic (PV) appliances and storage batteries to be introduced into one public facility are optimized. The optimization is based on simulation, in which electric energy is managed by charge and discharge of storage battery.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hamiltonian simulation in the low-energy subspace

Abstract We study the problem of simulating the dynamics of spin systems when the initial state is supported on a subspace of low energy of a Hamiltonian H . This is a central problem in physics with vast applications in many-body systems and beyond, where the interesting physics takes place in the low-energy sector. We analyze error bounds induced by product formulas that approximate the evolution operator and show that these bounds depend on an effective low-energy norm of H . We find improvements over the best previous complexities of product formulas that apply to the general case, and these improvements are more significant for long evolution times that scale with the system size and/or small approximation errors. To obtain these improvements, we prove exponentially decaying upper bounds on the leakage to high-energy subspaces due to the product formula. Our results provide a path to a systematic study of Hamiltonian simulation at low energies, which will be required to push quantum simulation closer to reality.

97 MATHEMATICS AND COMPUTING↗

Flexible User-Defined Domain Decomposition in Kilometer-Scale E3SM Land Model Simulation

The Energy Exascale Earth System Model (E3SM) Land Model (ELM) has been extended to kilometer-scale (km-ELM) resolutions, enabling high-fidelity simulations of terrestrial processes at 1 km x 1 km grid spacing. In ELM, domain decomposition partitions the computational domain across processors, ensuring efficient parallel execution. Currently, round-robin decomposition is applied, providing a straightforward way to distribute computational workload. As ELM continues evolving at the kilometer-scale (km-scale), particularly with integrating lateral flow modeling, decomposition strategies must also account for the increased workload and data movement. This paper introduces a flexible user-defined domain decomposition framework, allowing users to customize domain partitioning based on application requirements. The impact of different decomposition strategies is evaluated across various applications concerning computation, communication, and I/O. Results demonstrate that while 1D partitioning yields superior I/O performance, k-nearest neighbors (KNN) clustering effectively reduces inter-process communication overhead. This study lays the groundwork for scalable partitioning in large-scale land surface simulations, enhancing next-generation Earth system modeling.

Wang, Dali [ORNL] (ORCID:0000000168065108)↗

Cosmology with second- and third-order shear statistics for the Dark Energy Survey: Methods and simulated analysis

We present a new pipeline designed for the robust inference of cosmological parameters using both second- and third-order shear statistics. We build a theoretical model for rapid evaluation of three-point correlations using our fastnc code and integrate it into the cosmosis framework. We measure the two-point functions 𝜉 ± and the full configuration-dependent three-point shear correlation functions across all auto- and cross-redshift bins. We compress the three-point functions into the mass aperture statistic ⟨ℳ$^{3}_{ap}$⟩ for a set of 796 simulated shear maps designed to model the Dark Energy Survey Year 3 data. We estimate from it the full covariance matrix and model the effects of intrinsic alignments, shear calibration biases and photometric redshift uncertainties. We apply scale cuts to minimize the contamination from the baryonic signal as modeled through hydrodynamical simulations. We find a significant improvement of 83% on the figure of merit in the Ω m − 𝑆 8 plane when we add the ⟨ℳ$^{3}_{ap}$⟩ data to 𝜉 ± . Here, we present our findings for all relevant cosmological and systematic uncertainty parameters and discuss the complementarity of third-order and second-order statistics.

79 ASTRONOMY AND ASTROPHYSICS↗