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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Assessing Adaptive Irrigation Impacts on Water Scarcity in Nonstationary Environments—A Multi‐Agent Reinforcement Learning Approach

Abstract One major challenge in water resource management is to balance the uncertain and nonstationary water demands and supplies caused by the changing anthropogenic and hydroclimate conditions. To address this issue, we developed a reinforcement learning agent‐based modeling (RL‐ABM) framework where agents (agriculture water users) are able to learn and adjust water demands based on their interactions with the water systems. The intelligent agents are created by a reinforcement learning algorithm adapted from the Q‐learning algorithm. We illustrated this framework in a case study where the RL‐ABM is two‐way coupled with the Colorado River Simulation System (CRSS), a long‐term planning model used for the administration of the Colorado River Basin, for assessing agriculture water uses impacts on water scarcity. Seventy‐eight intelligent agents are simulated, which can be grouped into three categories based on their parameter values: the “aggressive” (swift actions; low regrets), the “forward‐looking conservative” (mild actions; high regrets; fast learning), and the “myopic conservative” (mild actions; median regrets; slow learning). The ABM‐CRSS results showed that the major reservoirs in the Upper Colorado Basin might experience more frequent water shortages due to the increasing water uses compared to the original CRSS results. If the drought continues, the case study also demonstrates that agents can learn and adjust their demands.

Hung, Fengwei↗
DOE OSTI2015

A COMPUTERIZED OPERATOR SUPPORT SYSTEM PROTOTYPE

A computerized operator support system (COSS) is proposed for use in nuclear power plants to assist control room operators in addressing time-critical plant upsets. A COSS is a collection of technologies to assist operators in monitoring overall plant performance and making timely, informed decisions on appropriate control actions for the projected plant condition. A prototype COSS was developed in order to demonstrate the concept and provide a test bed for further research. The prototype is based on four underlying elements consisting of a digital alarm system, computer-based procedures, piping and instrumentation diagram system representations, and a recommender module for mitigation actions. The initial version of the prototype is now operational at the Idaho National Laboratory using the Human System Simulation Laboratory.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Pressure Simulations for the EIC Interaction Region

Background detector rates in the Electron Ion Collider depend in part on the pressure in the interaction region. Materials choice, synchrotron radiation induced desorption, conditioning time and pumping configuration all affect the pressure in the system. Simulations of the region using Synrad and Molflow+ coupled simulation codes will be presented for various configruations and conditioning times.

Stutzman, M. L.↗
DOE OSTI2025

Data-driven emulation of modal aerosol microphysics via neural operator-based modeling

The complexity and the small characteristic scales of aerosol microphysical processes pose a big challenge for accurate and efficient Earth system simulations at regional and global scales. In this work, we construct and evaluate a surrogate model: the aerosol deep operator network (ADON), a physics-inspired dual-net architecture for emulating the aerosol microphysics parameterization suite in the version 2 of the Energy Earth System Model (E3SMv2). The current version of the surrogate model is trained on a dataset comprising 9.8 million samples obtained from a global E3SMv2 simulation with the horizontal resolution of about one degree under cloud-free conditions. Incorporating domain spatial and temporal coordinates, as well as principle components extracted from training data, the dual-net surrogate model effectively captures the intricate representations of aerosol and the relationship with atmospheric state variables, achieving an R-squared score over $$95.7\%$$ for all the lognormal aerosol modes in the extrapolated regime. The validated model provides feature importance of input variables and their impact on the predictive capacity of the surrogate model in relation to the E3SM. The computational cost of online inference time deployed on CPUs and GPUs with lower precisions highlights ADON’s efficiency and potential in robust predictive modeling for large-scale Earth system computations.

Bai, Zhe↗
DOE OSTI2023

Hardware-in-the-loop Testing of Network Protectors for Low-Voltage Networks with Distributed Energy Resources

In this report, we developed and validated a network protector relay digital twin model and interfaced a commonly used network protector relay hardware with our real-time simulation system. Hardware-in-the-loop protection studies are performed to assess the impact of distributed energy resources (DER) and benchmark a rate-of-change-based mitigation strategy. Simulation results suggest that the network protector reverse trip and auto-reclose functions are negatively impacted by the high distributed energy resource penetration. To accommodate DER backfeed while remaining secure and reliable for faults on primary feeders, we recommend options for a rate-of-change-based blocking scheme and a protection setting change. Finally, future mitigation ideas and standard revisions are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Neural Network-Based Power Mismatch Elimination Strategy for Integrated Solar and ESS AC/DC Systems (MARS)

The multiport autonomous reconfigurable solar power plant (MARS) is a promising concept for the integration of photovoltaic (PV) and energy storage system (ESS) to the transmission ac grid and a high-voltage direct current (HVdc) link. The presence of PV and ESS in each arm of the MARS results in uneven distribution of active power among different submodules (SMs), thereby leading to unbalanced SM capacitor voltages and potentially compromising the system stability. Moreover, in the case of partial shadings, shaded PV SMs will suffer from decreased power injections causing power mismatch in the MARS system. To address this issue, a neural-network-based power mismatch elimination (NNPME) strategy is proposed in this article. The proposed NNPME strategy optimizes ESS usage and leverages both dc and ac circulating currents to facilitate power transfer among the SMs, arms, and phases of the MARS system. Simulation and control hardware-in-the-loop (cHIL) experiments demonstrate the effectiveness of the proposed NNPME strategy. Compared with the traditional approaches, the proposed NNPME strategy can significantly enhance system efficiency and ensure stable and continuous operation, even in the presence of uneven power distribution within the MARS system.

14 SOLAR ENERGY↗
DOE OSTI2014

RELAP-7 User's Guide

The document contains a user's guide on how to run the RELAP-7 code. The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory. RELAP-7 will become the main reactor systems simulation toolkit for the LWRS (Light Water Reactor Sustainability) program’s RISMC (Risk Informed Safety Margin Characterization) effort and the next generation tool in the RELAP reactor safety/systems analysis application series. RELAP-7 is written with object oriented programming language C++. A number of example problems and their associated input files are presented in this document to guide users to run the RELAP-7 code starting with simple pipe problems to problems with increasing complexity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Sorption Modeling and Verification for Off-Gas Treatment

The project has made progress toward developing a comprehensive modeling capability for the capture of target species in off gas evolved during the reprocessing of nuclear fuel. The effort has integrated experimentation, model development, and computer code development for adsorption and absorption processes. For adsorption, a modeling library has been initiated to include (a) equilibrium models for uptake of off-gas components by adsorbents, (b) mass transfer models to describe mass transfer to a particle, diffusion through the pores of the particle and adsorption on the active sites of the particle, and (c) interconnection of these models to fixed bed adsorption modeling which includes advection through the bed. For single-component equilibria, a Generalized Statistical Thermodynamic Adsorption (GSTA) code was developed to represent experimental data from a broad range of isotherm types; this is equivalent to a Langmuir isotherm in the two-parameter case, and was demonstrated for Kr on INL-engineered sorbent HZ PAN, water sorption on molecular sieve A sorbent material (MS3A), and Kr and Xe capture on metal-organic framework (MOF) materials. The GSTA isotherm was extended to multicomponent systems through application of a modified spreading pressure surface activity model and generalized predictive adsorbed solution theory; the result is the capability to estimate multicomponent adsorption equilibria from single-component isotherms. This advance, which enhances the capability to simulate systems related to off-gas treatment, has been demonstrated for a range of real-gas systems in the literature and is ready for testing with data currently being collected for multicomponent systems of interest, including iodine and water on MS3A. A diffusion kinetic model for sorbent pellets involving pore and surface diffusion as well as external mass transfer has been established, and a methodology was developed for determining unknown diffusivity parameters from transient uptake data. Two parallel approaches have been explored for integrating the kernels described above into a mass-transport model for adsorption in fixed beds. In one, the GSTA isotherm kernel has been incorporated into the MOOSE framework; in the other approach, a focused finite-difference framework and PDE kernels have been developed. Issues, including oscillatory behavior in MOOSE solutions to advection-diffusion problems, and opportunities have been identified for each approach, and a path forward has been identified toward developing a stronger modeling platform. Experimental systems were established for collection of microscopic kinetics and equilibria data for single and multicomponent uptake of gaseous species on solid sorbents. The systems, which can operate at ambient temperature to 250°C and dew points from -69 to 17°C, are useful for collecting data needed for modeling performance of sorbents of interest. Experiments were conducted to determine applicable models and parameters for isotherms and mass transfer for water and/or iodine adsorption on MS3A. Validation experiments were also conducted for water adsorption on fixed beds of MS3A. For absorption, work involved modeling with supportive experimentation. A dynamic model was developed to simulate CO 2 absorption with chemical reaction using high alkaline content water solutions. A computer code was developed to implement the model based upon transient mass and energy balances. Experiments were conducted in a laboratory-scale column to determine model parameters. The influence of geometric parameters and operating variables on CO 2 absorption was studied over a wide range of conditions. This project has resulted in 7 publications, with 3 manuscripts in preparation. Also, 15 presentations were given at national meetings of ANS and AIChE and at Material Recovery and Waste Forms Campaign Working Group meetings.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum system simulators in a classical computer. In this work, we fill this gap by proposing a low-level, easy-to-use benchmark suite called QASMBench based on the OpenQASM assembly representation. It consolidates commonly used quantum routines and kernels from a variety of domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, and so on, trading-off between generality and usability. To analyze these kernels in terms of NISQ device execution, in addition to circuit width and depth, we propose four circuit metrics including gate density, retention lifespan, measurement density, and entanglement variance, to extract more insights about the execution efficiency, the susceptibility to NISQ error, and the potential gain from machine-specific optimizations. Applications in QASMBench can be launched and verified on several NISQ platforms, including IBM-Q, Rigetti, IonQ and Quantinuum. For evaluation, we measure the execution fidelity of a subset of QASMBench applications on 12 IBM-Q machines through density matrix state tomography, comprising 25K circuit evaluations. In addition we also compare the fidelity of executions among the IBM-Q machines, the IonQ QPU and the Rigetti Aspen M-1 system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Multi-Split Variable Refrigerant Flow (VRF) System Building Energy Simulations Using Performance Maps

Multi-split variable refrigerant flow (VRF) systems are highly energy-efficient HVAC (heating, ventilation and air conditioning) technologies that connect a single outdoor unit to multiple independent indoor terminal units using a common refrigerant circuit and a variable-speed compressor. Building energy simulations that incorporate VRF systems help model their unique operational characteristics and predict energy consumption in specific building designs. Traditionally, EnergyPlus models these systems by employing multiple sets of performance curves to characterize both individual terminal units and the outdoor unit. However, producing these curves is labor intensive and error prone, and they often do not capture all the key input and output variables. This paper introduces a novel approach that uses multi-dimensional performance maps to model VRF systems in building environments for space cooling. In this approach, performance maps are developed at the component level—separately for the outdoor unit and for each indoor terminal. The new modeling method is validated within EnergyPlus via a Python plug-in that contains a simple solver loop to coordinate the component-level, indoor, and outdoor unit maps. Furthermore, because performance maps can span more variables than traditional performance curves, they offer the opportunity to implement advanced controls, such as enhanced dehumidification and compressor modulation. A VRF air conditioner’s hardware system was modeled using the DOE/ORNL Heat Pump Design Model, which was automated to produce extensive performance maps for both the indoor and outdoor units.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗
DOE OSTI2024

Performance evaluation of underground thermal storage integrated dual-source heat pump systems

The increasing demand for electricity stresses the existing electric grids. Buildings consume 73% of all U.S. electricity and are responsible for 30% of U.S. greenhouse gas emissions. Integrating thermal energy storage (TES) in building heating/cooling systems, which consume considerable electricity, can mitigate the challenges to electric grids. Here, this study reports on a novel thermal energy storage device integrated heat pump system to reshape the building electricity demand profile while maintaining thermal comfort. The annual performance of the proposed system has been evaluated through a dynamic system simulation with high fidelity in the Modelica platform. The dynamic model of the novel hybrid component named ‘dual purpose underground thermal battery’ was developed and validated. It was then incorporated into the system model. Given a time-of-use tariff, a rule-based control strategy was designed to shift the electric demand and switch the heat pump source for a typical single-family house in different climate zones of the United States. The system performance of the new TES-integrated dual-source heat pump was compared with that of a conventional air-source heat pump system. The results indicate that the proposed system can reduce the annual HVAC electricity cost by up to 52% while saving 45.2% on electricity consumption. In the Northern areas, the annual peak load of the HVAC system can be reduced by 64.9%. However, this reduction is less in the Southern areas as the system’s higher efficiency in winter dominates the overall energy-saving potential.

25 ENERGY STORAGE↗
DOE OSTI2014

FINAL SCIENTIFIC REPORT Southwest United States of America – Distributed Technology Training Consortia (SWUSA-DTTC) Contract Number: DE-EE0006339

The Southwest United States of America – Distributed Technology Training Consortia (SWUSA-DTTC) leveraged the highest concentration of renewable resources in the U.S. as well as operation of the leading independent microgrid installations and other distributed technologies to collect and analyze real-time data streams, advance power system simulations and analysis, identify educational and training gaps and develop solutions-focused curricula. The SWUSA-DTTC consortium posed a unique collaboration between universities and utilities to ensure that classes were focused on subjects and topics of interest to the utilities and ones that had practical benefit related to the preparedness for accommodating high penetration of solar and other distributed energy technologies. This approach to have a close collaboration and shared effort to develop the course content and curriculum is unique and a significant departure from conventional course development. This coursework and training was intended to endure over a long time horizon (10-20 year time frame), and include professionals over the entire Southwest region and the rest of the US, and even outreach into foreign countries. Project Objectives In order to support the increase in power systems research, development, and analytical capacity, the SWUSA-DTTC brought together respected professors in Power Systems education, student/professor research and development, and valuable industry and utility experience. Through this program, the partnered universities created and/or modified existing curricula available to students and professionals in the form of university courses, short courses, videos, consortia-led training, and online materials. During this time, the supporting vendors and utilities provided the SWUSA-DTTC with technical advisory roles as well as providing input and feedback in terms of utility and related energy industry needs. The goals were to create power and energy systems training, curricula, and workforce preparedness through the inclusion of data collection and analysis, power systems expertise, and application-specific training activities which build on fundamental principles, modeling and simulation tools, field-immersed training and methods of performance validation. The outcome of the program was to result in better prepared and greater number of graduates ready to contribute to the field of power systems which depend upon the safe, reliable and efficient generation sources which make up an increasingly diverse mix of renewable power. Additionally, the program was to deliver critical training modules which are intended to support mid-career professionals and be woven into utility training programs used all over the country. Discontinuation Summary On September 29, 2014, Electricore received notice of discontinuation of federal funding under subject Award DE-EE0006339. DOE’s notice of discontinuation was the first indication provided to Electricore that the work completed against Task 1 - Program Planning and Evaluation during Budget Period 1 was inadequate. Significantly, the discontinuation was based in large part on the erroneous assertion that many of the tasks were incomplete as indicated in the Continuation Application. However, the Continuation Application was submitted July 29, 2014, while the period of performance for this last quarter in Budget Period 1 did not end until September 30, 2014. Accordingly, the performance for this last quarter in Budget Period 1 will be reported in the upcoming Quarterly Report which is not due until October 30, 2014. Nevertheless, in response to DOE’s letter and in further support of Electricore’s Continuation Application, we are providing a detailed status demonstrating adherence to all program requirements for each Task 1, Budget Period 1 SOPO activity and milestones in response to the DOE review.

14 SOLAR ENERGY↗
DOE OSTI2021

Software Tools for Energy Storage Valuation and Design

Abstract Purpose of Review As the application space for energy storage systems (ESS) grows, it is crucial to valuate the technical and economic benefits of ESS deployments. Since there are many analytical tools in this space, this paper provides a review of these tools to help the audience find the proper tools for their energy storage analyses. Recent Findings There are many software tools for valuating ESS. These tools can be classified into two groups: (1) power system simulation and planning tools for analyzing the technical contributions of ESSs, and (2) techno-economic analysis tools for valuating the economic benefits of ESS deployment and specifying the optimal design of energy systems that include ESSs. While many of the tools, developed by the national laboratories, are free to use, the commercial tools are also of great importance in meeting the customers’ specific needs. Summary This paper provides a review of software tools for ESS valuation and design. A review of analysis tools for evaluating the technical impacts of energy storage deployments is also provided, as well as a discussion of development trends for valuation and design tools.

Nguyen, Tu A. (ORCID:0000000181148063)↗
DOE OSTI2021

Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1

PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.

Arnold, Daniel↗
DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness - An Introduction to the Open-Source Tool and Use Cases

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Human factors and modeling methods in the development of control room modernization concepts - 315

Control room modernization is one of the most challenging and complex upgrade projects that a nuclear power plant can undertake. It can even have a bigger impact on operations than, for example, turbine replacement. The challenges of migrating an analog control system to a distributed control system are already well known and a number of nuclear utilities have embarked upon various levels of effort to upgrade some of the systems in the control room. When planning for control room upgrades, plants have to deal with a multitude of engineering and operational impacts. This will inevitably include several human factors considerations, including physical ergonomics of workstations, viewing angles, lighting, seating, new communication requirements, and new concepts of operation. In helping nuclear power utilities to deal with these challenges, the Idaho National Laboratory (INL) has developed human factors design and evaluation methods to be used in the development of an end-state control room concept and to manage the various phases of the upgrade life cycle. This included interactive sessions with operators in INL's Human System Simulation Laboratory, and three-dimensional modeling to visualize control board changes. To make the various upgrade phases as concrete and as visible as possible, the end-state concept includes a set of visual representations of the control room before and after various upgrade phases to provide the context and a framework within which to consider the various options in the upgrade. This includes the various control systems, human-system interfaces to be replaced, and possible changes to operator workstations. This paper describes how this framework helps to ensure an integrated and cohesive outcome that is consistent with human factors engineering principles and also provide substantial improvement in operator performance. The paper further describes the application of this integrated approach in the strategic modernization program at a nuclear power plant where legacy systems are upgraded to advanced digital technologies through a systematic process that links human factors principles to the systems engineering process. This approach results in an integrated control room architecture beyond what is possible for individual subsystem upgrades alone. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Studying Qubit Interactions with Multimode Cavities Using QuTiP

The project uses QuTiP, a quantum computing framework [1], to simulate interactions between two-qubits coupled with each other via three resonators. The main aim of this project is to build a machinery of techniques to understand complex qubit-cavity interactions using QuTiP’s functionalities. The system simulated mimics the one constructed by McKay et. al. [2] (M15) and the results of the simulations closely agree with M15’s experimental results. The effect of the coupling strength between the qubits and the cavities is studied. It was observed that stronger couplings generated larger separations between the eigen-modes. Studies involving resonance were used to construct the iSWAP gate, a universal quantum logic gate. This study showed the importance of external thermal losses due to cavity dissipation, and qubit decay and dephasing. The Landau-Zener model was tested for the case of multiple crossing; the model motivated the comparison of three scenarios where the 2 qubits were coupled via: 1 cavity, 3 cavities, and 6 cavities. The study concluded that having multiple modes, which is a consequence of having multiple cavities, is advantageous for transferring energy from the qubit to the cavity. Finally, the ac-Stark shift was measured in the system and it’s dynamics showed excellent agreement with the experimental results obtained by M15.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Coupling of Thermochemistry Solver THERMOCHIMICA with MOOSE/BISON

THERMOCHIMICA is a computational library for chemical thermodynamics. It determines a unique combination of phases and their compositions for a prescribed chemical composition, temperature and pressure. The solver and the underlying thermodynamic models can be used to estimate the chemical state and various constitutive and transport properties necessary for nuclear fuel performance modeling. Our NEAMS research project focuses on the development of nuclear fuel thermodynamics models and computational thermodynamics equilibrium solvers, and their implementation into Idaho National Laboratory (INL) nuclear fuel performance simulation system MOOSE/BISON. This report documents the software integration of THERMOCHIMICA with MOOSE/BISON using the current INL development framework GitLab. The THERMOCHIMICA implementation is demonstrated on modeling oxygen related phenomena in irradiated fuel, such as calculation of oxygen to metal ratio in the fluorite phase, oxygen partial pressure, oxygen chemical potential and oxygen transport. Experimental measurements from the open literature were used to validate the implemented models and illustrate functionality of the developed thermodynamics module. The calculations are based on chemical element inventory provided by neutronics, isotopic depletion, transmutation and decay calculations in the SCALE system. The burnup calculation in BISON can also be used for elemental composition although it provides only a limited set. Coupling of THERMOCHIMICA with other codes that can provide chemical composition of irradiated fuel for BISON simulations is currently being explored.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗