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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Demonstrate FARM supervisory capabilities for a thermal energy storage problem for the DETAIL facility: IES Simulation Ecosystem Control System Development

The goal of the power dispatch problem for an Integrated Energy System (IES) is to adjust the power output and the heat flow of each component to maximize the profitability of the whole unit. Facilities that can integrate real-time digital signals, mock nuclear power, thermal energy storage and industrial heat use via high-temperature electrolysis were constructed at INL to support the research activities. The Dynamic Energy Technology and Integration Laboratory (DETAIL) houses the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET) and the Thermal Energy Distribution System (TEDS). In this report, the hierarchical control system architecture proposed in June 2023 milestone for the flexible operation of DETAIL facility is finalized and demonstrated. A brief description of the components and the corresponding Dymola models from the HYRBID repository is first provided. Then, the current control strategy is presented. In particular, the approach for generating the set-point trajectories to be fed to the PI controllers is analyzed, and its limits were identified. To preserve safe operation over both long-time and real-time horizons, the integration of a Supervisory Control layer embedding a modified version of FARM (Feasible Actuator Range Modifier) module is proposed. FARM is a component of the RAVEN-based FORCE framework designed to support HERON module at optimizing the operation of IES units. The proposed control system for DETAIL foresees FARM to be applied twice, i.e., the original version (“FARM-Validator”) aiding the solution of the power dispatch problem, and a modified version (“FARM-Supervisory”) coordinating the PID controllers. Despite the kernel of the two modules is the same, their tasks are quite different. The former intervenes at the beginning of each hour to prevent constraint violations over long time periods, the latter addresses real-time control tasks and monitors the response of constrained variables at a much finer time resolution. A tentative procedure for training the embedded Digital Twins with the experimental data is also proposed. Finally, the capabilities of the designed architecture and the impact of the added Supervisory Control layer are demonstrated by simulating a representative power dispatch scenario.

25 ENERGY STORAGE↗
DOE OSTI2016

Simulation for a Coevolved System-of-Systems Meta-Architecture

This paper describes a simulation of a system-of-systems for counter-smuggling. The simulation is described and results are provided. The results demonstrate the applicability of the agent based modeling paradigm to understand key factors influencing SoS performance.

simulation↗
DOE OSTI2022

Modeling Integrated Electricity and Natural Gas Systems Using Co-Simulation

One approach for modeling natural gas and electricity networks as integrated systems is co-simulation, which involves separating a single model into subproblems that are solved iteratively, with coupling information passed between then. Although a fully integrated problem might be more direct, co-simulation offers advantages in that it can sometimes be more computationally tractable, and can also leverage existing simulation tools to represent the subproblems. Here we present a framework for co-simulation of natural gas and electricity networks using the HELICS tool. We provide validation of the co-simulation approach by comparing results with a fully integrated approach that uses the same simulation tool, finding that the two approaches provide identical results for a range of test cases. We then present results from natural gas and electricity network co-simulation case study of the Colorado Front Range, with an evaluation of the present-day system and also a future system with higher shares of renewable power. The presentation will close with a discussion on future avenues of work for co-simulation of gas and power networks.

co-simulation↗
DOE OSTI2018

Advanced EMT and Phasor-Domain Hybrid Simulation With Simulation Mode Switching Capability for Transmission and Distribution Systems

Conventional electromagnetic transient (EMT) and phasor do-main hybrid simulation approaches presently exist for transmission system level studies and their simulation efficiency is generally constrained by the EMT simulation. With an increasing number of distributed energy resources and non-conventional loads being installed in the distribution systems, it is imperative to ex-tend the hybrid simulation application to include distribution systems and integrated transmission and distribution systems. Meanwhile, it is equally important to improve the simulation efficiency as the modeling scope and complexity of the detailed system in the EMT simulation increases. To meet both requirements, this paper introduces an advanced electromagnetic transient (EMT) and phasor domain hybrid simulation approach. This approach has two outstanding features: 1) a comprehensive phasor domain modeling framework which supports positive-sequence, three-sequence, three-phase and mixed three-sequence/three-phase representations; 2) a robust and flexible simulation mode switching scheme which enables simulation switching from hybrid simulation mode back to pure phasor domain dynamic simulation mode to achieve significantly improved simulation efficiency. The proposed method has been tested on integrated transmission and distribution systems, and the results show that with the developed simulation switching feature, the total computational time is significantly reduced compared to running the hybrid simulation for the whole simulation period, while good accuracy is maintained.

Huang, Qiuhua (ORCID:0000000184577429)↗
DOE OSTI2017

Characterization of methane oxidation in a simulated landfill cover system by comparing molecular and stable isotope mass balances

Highlights: • Quantification of bacterial methane oxidation was investigated by isotope analysis. • Independent approaches (mass balancing, stoichiometry, and stable isotope analysis). • Robust statistical validation of calculated biodegradation in experimental reactor. • Thermal imaging to locate bacterial methane oxidation along with isotope analysis. - Abstract: Biological methane oxidation may be regarded as a method of aftercare treatment for landfills to reduce climate relevant methane emissions. It is of social and economic interest to estimate the behavior of bacterial methane oxidation in aged landfill covers due to an adequate long-term treatment of the gas emissions. Different approaches assessing methane oxidation in laboratory column studies have been investigated by other authors recently. However, this work represents the first study in which three independent approaches, ((i) mass balance, (ii) stable isotope analysis, and (iii) stoichiometric balance of product (CO{sub 2}) and reactant (CH{sub 4}) by CO{sub 2}/CH{sub 4}-ratio) have been compared for the estimation of the biodegradation by a robust statistical validation on a rectangular, wide soil column. Additionally, an evaluation by thermal imaging as a potential technique for the localization of the active zone of bacterial methane oxidation has been addressed in connection with stable isotope analysis and CO{sub 2}/CH{sub 4}-ratios. Although landfills can be considered as open systems the results for stable isotope analysis based on a closed system correlated better with the mass balance than calculations based on an open system. CO{sub 2}/CH{sub 4}-ratios were also in good agreement with mass balance. In general, highest values for biodegradation were determined from mass balance, followed by CO{sub 2}/CH{sub 4}-ratio, and stable isotope analysis. The investigated topsoil proved to be very suitable as a potential cover layer by removing up to 99% of methane for CH{sub 4} loads of 35–65 g m{sup –2} d{sup –1} that are typical in the aftercare phase of landfills. Finally, data from stable isotope analysis and the CO{sub 2}/CH{sub 4}-ratios were used to trace microbial activity within the reactor system. It was shown that methane consumption and temperature increase, as a cause of high microbial activity, correlated very well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Efficient learning of accurate surrogates for simulations of complex systems

Machine learning methods are increasingly deployed to construct surrogate models for complex physical systems at a reduced computational cost. However, the predictive capability of these surrogates degrades in the presence of noisy, sparse or dynamic data. Here, we introduce an online learning method empowered by optimizer-driven sampling that has two advantages over current approaches: it ensures that all local extrema (including endpoints) of the model response surface are included in the training data, and it employs a continuous validation and update process in which surrogates undergo retraining when their performance falls below a validity threshold. We find, using benchmark functions, that optimizer-directed sampling generally outperforms traditional sampling methods in terms of accuracy around local extrema even when the scoring metric is biased towards assessing overall accuracy. Finally, the application to dense nuclear matter demonstrates that highly accurate surrogates for a nuclear equation-of-state model can be reliably autogenerated from expensive calculations using few model evaluations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Dalton Project: A Python platform for molecular- and electronic-structure simulations of complex systems

The Dalton Project provides a uniform platform access to the underlying full-fledged quantum chemistry codes Dalton and LSDalton as well as the PyFraME package for automatized fragmentation and parameterization of complex molecular environments. The platform is written in Python and defines a means for library communication and interaction. Intermediate data such as integrals are exposed to the platform and made accessible to the user in the form of NumPy arrays, and the resulting data are extracted, analyzed, and visualized. Complex computational protocols that may, for instance, arise due to a need for environment fragmentation and configuration-space sampling of biochemical systems are readily assisted by the platform. The platform is designed to host additional software libraries and will serve as a hub for future modular software development efforts in the distributed Dalton community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Development of a 100 kV pulse generator for driving an electron scanner used in proton beam profile measurements

The Spallation Neutron Source (SNS) utilizes an electron scanner in the accumulator ring for nondestructive transverse profiling of the proton beam. The electron scanner consists of a high voltage pulse generator driving an electron gun, a medium voltage ramp generator, and a CCD camera. A new high voltage pulse generator that provides negative 100 kV pulses with rise times of less than 200 ns, +/-0.5% flattop of greater than 100 ns has been designed, delivered, and undergone extensive testing. The pulse generator has been operationally verified with the existing control system and simulated loads. Full system testing with the actual electron scanner is planned. This paper details the requirements, design, setup, and test results of the high voltage pulse generator.

Morris, B↗
DOE OSTI2023

HQ-Sim: High-performance State Vector Simulation of Quantum Circuits on Heterogeneous HPC Systems

Quantum circuit simulations are applied in more and more circum- stances as the quantum computing community becomes broader. It helps researchers to evaluate quantum algorithms and relieve the burden of limited quantum computing resources. However, most of the state-of-the-art quantum simulators utilize either CPU or GPU to store and calculate the state vector, which results in resource starvation. Moreover, the maximum number of qubits supported by the simulator is bounded by the memory, since the memory utilization increases exponentially with the number of qubits. In this study, we leverage Heterogeneous computing to utilize both CPU and GPU to store and update state vectors. We also integrate lossy data compression to reduce memory requirements. Specifically, we develop a heterogeneous framework that has a dynamic scheduler to fully utilize the computing resources. We apply lossy compression to chunked state vector to make the maximum number of qubits higher than the regular simulators, the compression also benefits the data movement between CPU and GPU.

Zhang, Boyuan↗
DOE OSTI2024

Common Electric Power Transmission System Model JSON Schema Specification

The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic, and error-resistant specification of electric power network components parameter names and units, and relation between components, intended for use by the research community developing new computational methods for power systems operations and simulation. Power system datasets following the CTM specification can be read as dictionaries and manipulated in that form in most programming languages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in multiple power systems domains (e.g., economic operation, reliability assessment, electricity markets, stability assessment, etc.) without requiring conversions between use-case-specific file formats with information loss in the process. This repository specifies CTM as a JSON Schema, provides documentation, derivate (code-generated) implementations of CTM, and example data and usage of the schema for important use cases.

Aravena Solis, Ignacio↗
DOE OSTI2025

LDES-Sizing-and-siting-model (Power grid test cases for long-duration energy storage (LDES) siting) [SWR-25-75]

This repository contains code and data for performing a siting analysis of long-duration energy storage (LDES) in the 5-bus and RTS systems using the Sienna suite developed by the National Renewable Energy Laboratory for production cost modeling (PCM). This analysis involves moving the LDES component to different buses in the system, running a simulation, and considering the production cost of the simulation. Different system configurations are also analyzed with these scripts (such as moving load or renewable dispatch generators to different buses) to observe the impacts the system configuration has on optimal siting. This repository contains three sub directories discussed below. Both the 5-bus and RTS systems have two different initial configurations for the renewable energy components in them, one that is predominantly PV-driven and one that is predominantly wind-driven. Sienna suite can be found here: https://github.com/NREL-Sienna

Cole, David [University of Wisconsin]↗
DOE OSTI2022

Field Sensitivity Analysis of Turbulence Model Parameters for Flow Over a Wing

Reynolds-averaged-Navier-Stokes (RANS) turbulence models are a critical tool in computational-fluid-dynamics simulations of aerodynamic systems, but simulation results can be highly sensitive to RANS-model parameter choices. Sensitivity analysis can be used to quantify these impacts, and the objective of this study is to demonstrate field sensitivity analysis with respect to ten parameters in the 2003 Menter shear-stress-transport (SST) turbulence model. Here, the analysis is demonstrated for an application relevant to wind energy, namely, flow over a NACA 0015 wing at 12 degree angle of attack and a Reynolds number of 1.5 x 10 6 . We quantify sensitivity using Sobol indices and the mean-squared gradient, which are estimated using polynomial chaos and active subspace models, respectively. Our results indicate that there are substantial spatial variations in parameter sensitivities, with different sets of most-sensitive parameters near the wing, as well as in the downstream wake, consistent with the physical interpretations of the turbulence model inputs. We show that, for this particular turbulence model and flow, simultaneous dimension reduction is possible across all quantities of interest, enabling efficient exploration of model outcomes. Ultimately, this analysis provides new insights into turbulence model parameter sensitivities in incompressible flows, and also demonstrates the implementation of field sensitivity analysis for applications relevant to aerodynamics simulations.

17 WIND ENERGY↗