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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 OSTI2020

Solving the duck curve in a smart grid environment using a non-cooperative game theory and dynamic pricing profiles

With the intermittency that comes with electricity generation from renewables, utilizing dynamic pricing will encourage the demand-side to respond in a smart way that would minimize the electricity costs and flatten the net electricity demand curve. Determining the optimal dynamic pricing profile that would leverage distributed storage to flatten the curve is a novel idea that needs to be studied. Moreover, the economic feasibility of utilizing distributed electrical energy storage is still not given in the literature. Therefore, in this paper, a novel way of solving a citywide dynamic model using a bilevel programming algorithm is introduced. The problem is developed as a novel non-cooperative Stackelberg game that utilizes air-conditioning systems and electrical storage through the end-users to determine the optimal dynamic pricing profile. The results show that the combined effect of utilizing demand-side air-conditioning systems and distributed storage together can flatten the curve while employing the optimal dynamic pricing profile. An economic study is performed to determine the economic feasibility of 20 different cases with different battery designs and the level of solar penetration. Three metrics were used to evaluate the economic performance of each case: the levelized cost of storage, the levelized cost of energy, and the simple payback period. Most cases had levelized cost of storage values lower than 0.457 $/kWh, which is the lower bound available in the literature. Seven out of 16 cases have a simple payback period shorter than the lifetime of the system (25 years). The case with a 100 MW PV power plant and a battery storage of size 597 MWh, was found to be the most promising case with a simple payback period of 12.71 years for the photovoltaic plant and 19.86 years for the demand-side investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

On the Breakdown of ENSO's Relationship With Thermocline Depth in the Central-Equatorial Pacific

Recent classification of El Nino-Southern Oscillation (ENSO) into two types, Eastern (EP) and Central (CP) events, has highlighted the importance of the central Pacific. We show here that the local correlation between ENSO subsurface temperatures (T sub ) in the upper 100-m and thermocline depth anomalies breaks down in the central equatorial Pacific, whereas T sub remains well correlated with sea surface height anomalies. This observed difference in the central equatorial Pacific is simulated by almost all climate models. It arises from a vertically slanted Tsub anomaly structure that is unique to the central equatorial Pacific. We show that this feature is an adiabatic response to wind-driving that is even present in a linear dynamic model, as long as the model has enough baroclinic modes to adequately represent the observed vertical complexity. Our findings have implications for better understanding the different importance of thermocline feedback in CP and EP events.

58 GEOSCIENCES↗
DOE OSTI2022

Investigation of the thermal conductivity of molten LiF-NaF-KF with experiments, theory, and equilibrium molecular dynamics

Molten salts are being proposed for numerous advanced energy applications, including advanced nuclear reactors, concentrating solar power plants, thermal energy storage, and fusion reactors. Accurate knowledge of the thermophysical properties of molten salts directly impact the performance of these energy systems and are essential for design and safety analyses. Thermal conductivity data for fluoride molten salts and mixtures are especially lacking. In this work, experimental measurements of thermal conductivity using the steady-state variable gap technique were performed on eutectic LiF-NaF-KF from 834 to 1195 K. The experiment accounts for radiative, convective, and conductive heat losses. In addition, theoretical and molecular dynamics models are used, from 750 K up to 1300 K, to estimate the thermal conductivity for comparison with the experimental results. The results of experiments show a weak negative deviation of thermal conductivity with temperature, unlike previous experimental results in the literature. The measured thermal conductivity magnitudes agree with the theoretical and molecular dynamics predictions, aside from the data above 1100 K, where heat losses and radiative errors are the most significant, having a 16% maximum deviation from theory. These experimental results provide new thermal conductivity data for the LiF-NaF-KF system and further validation of the predictive models. The theoretical model was used to map the composition and temperature dependent thermal conductivity of LiF-NaF-KF and the mapping’s deviation from a linear additivity estimation of thermal conductivity. Additionally, this mapping showed the highest deviations from linearity for KF-LiF rich mixtures and increasing deviation with temperature. Notably, the deviation from linearity near the LiF-NaF-KF eutectic composition was around 25%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Phase field modeling of discontinuous dynamic recrystallization in hot deformation of magnesium alloys

We have developed a quantitative phase field model of discontinuous dynamic recrystallization (PF-DDRX) for investigating grain structure evolution and its impact on mechanical response in magnesium alloy during hot deformation. A set of isothermal compression tests were conducted by Gleeble thermo-mechanical simulator and used to determine PF-DDRX model parameters such as critical stresses of recrystallization, activation energies of dislocation, grain boundaries and recrystallization grain nucleation. In the simulations, the experimentally measured average grain size and distribution were used to generate initial microstructures. The results show that the typical ‘necklace’ microstructures observed in DDRX forms at the earlier stage of recrystallization. The inhomogeneity of microstructures first increases rapidly and then decreases gradually and reaches a constant with the increase of dynamic recrystallization volume fraction. Both predicted grain structure and mechanical response are in good agreement with experimental results. This demonstrates that the model parameters determined by experimental data are reliable for the developed PF-DDRX model to predict the grain structure evolution and flow behavior of AZ80 magnesium alloy under hot deformation. This work presents a path to combine experiments and modeling to give quantitative prediction and minimize experimental cost.

magnesium alloy, Phase field method, dynamic recry↗
DOE OSTI2023

Hardware-based Advanced Electromagnetic Transient Simulation for A Large-Scale PV Plant in Real Time Digital Simulator

Power electronics-based resources, such as high-voltage direct current (HVdc) substations, photovoltaic (PV) plants, wind plants, electric vehicle charging stations, and energy storage systems, are increasingly being integrated within the power grid. Recently, multiple reports have emphasized the necessity for high-fidelity electromagnetic transient (EMT) simulations of these large-scale power electronics-based resources to accurately understand their behavior in power grids. However, performing hardware-based EMT simulations with high-fidelity models for such large power electronics systems is challenging due to the small time-step requirements and the involvement of a large number of states. This paper presents the implementation of hardware-based high-fidelity EMT dynamic model of a large-scale PV plant, accomplished through custom model development using the specific-C language in real-time digital simulator hardware (RTDS) and software (RSCAD).

Choi, Jongchan↗
DOE OSTI2025

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗
DOE OSTI2022

Dynamic mass accountancy modeling of a molten salt reactor using equilibrium thermodynamics

A mechanistic-based mass accountancy model in the context of liquid-fueled molten salt reactors was implemented in the dynamic systems modeling software library TRANSFORM by way of coupling with the equilibrium thermodynamics code Thermochimica. Liquid-fueled molten salt reactors present new challenges for mass accountancy because of the dissolution of fuel and evolved fission products, which may be soluble in the salt, off-gas, or precipitate. Two cases of mass loss from the molten salt were addressed: off-gassing and precipitation. The software implementation was tested through a series of increasingly complex demonstration problems, culminating in a model of the primary fuel and primary coolant loops of the molten salt demonstration reactor. Analysis shows that negligible mass was lost from the salt under normal operating conditions, but an overheating event caused by partial loss of fuel loop cooling resulted in release of measurable amounts of uranium (among other elements) via off-gassing. The tools developed here are primarily aimed at capability development but are readily available for use in further modeling of molten salt reactor concepts. As a result, these tools have not yet been validated, and future experimental work to perform this validation is recommended.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Scalable simulation of coupled adsorption and transport of methane in confined complex porous media with density preconditioning

The growing significance of shales and tight formations in the transition to less carbon-intensive and clean energy drives the research endeavor to understand the physics of gas flow within these systems. However, shales are composed of massively heterogeneous physical and chemical features. Most nano-sized pores connect to millimeter-scale fractures, leading to multiscale transport. These nano-scale pore throats demonstrate non-classical flow behavior, such as non-negligible slip velocities and adsorbed gas layers at the boundary. As a result, classical computational fluid dynamics models do not capture the physics. In this work, we develop a coupling scheme for the multiple-relaxation-time (MRT) lattice Boltzmann (LB) method that integrates the Peng-Robinson equation of state into a pseudo-potential interaction model to capture the physics of methane flow in irregular networks of channels that represent nano-scale porous media. We use atomistic simulations to calibrate and validate our model in slit nano-channels. We propose a preconditioning scheme to initialize the coupled transport and adsorption simulation of methane in complex porous media. The results of this implementation of LB agree with Direct Simulation Monte Carlo (DSMC) and Molecular Dynamics (MD) simulations. We then scale up the LB implementation through vectorization and indirect addressing. We parallelize it using Message Passing Interface (MPI) and OpenMP frameworks to simulate transport and adsorption in complex media with a million lattices. Additionally, we analyze the differences between coupled and transport-only simulations in two case studies and show that considering phase behavior, i.e., adsorption, can significantly change the flow behavior. This work constitutes an important step towards bridging the gap between molecular flow and system-scale behavior of complex disordered porous media.

42 ENGINEERING↗
DOE OSTI2023

EMT and Phasor-Domain Co-simulation of a Low Frequency AC Transmission System for Offshore Wind Integration

This work investigates system level interactions of multi-terminal low frequency high-voltage alternating current (LF-HVac) system using back-to back converters and grid-level 60 Hz system. A co-simulation framework by integrating high- fidelity dynamic model of multi-terminal LF-HVac system in electromagnetic transient (EMT) simulation platform and phasor model of IEEE 39 bus system in transient-stability (phasor) program. The co-simulation framework for multi-terminal LF- HVac system with offshore wind integrated in a bulk power system is developed successfully and its steady state and dynamic operation is demonstrated and compared with EMT simulation. The co-simulation results show accurate representation of the dynamic responses with reduced computation burden and time compared to EMT platform.

low-frequency transmission, co-simulation, electro↗
DOE OSTI2024

Autonomous Inverter Controls for Resilient and Secure Grid Operation: Vector Control Design for Grid Forming

The project addresses both fundamental and practical challenges of GFM/GFL inverter control for the power grids with high inverter based resources (IBRs) penetration. A data- driven modeling technique is applied to accurately model dynamics of PWM inverters, including electromagnetic-transient (EMT). Systematic and integrative designs of grid- forming (GFM) and grid-following (GFL) primary controls are developed to guarantee system performance under either normal or abnormal operating conditions without violating constraints. This modeling and control framework provides black-start capability in case of an outage without relying on rotating generators, and its secondary control is also shown to enhance resilience against cyber-physical attacks.

14 SOLAR ENERGY↗
DOE OSTI2024

A Simulation Modeling Approach to Optimizing Nuclear Waste Dispositioning

The dispositioning of nuclear waste generated at facilities across the country is an ongoing battle that affects us all. National laboratories and research centers dealing in medical research, clean energy, and other nuclear activities such as the Department of Energy (DOE) facilities face the need to properly manage and dispose of nuclear waste. A dynamic modeling solution would enable the DOE and others to make decisions on waste disposal and technological options. In doing so, this research explores modeling techniques using available data to address these situations. The focus being on developing an initial robust and adaptable discrete event model using the ExtendSim tool. This modeling effort will target the dispositioning of transuranic waste at the Savannah River National Laboratory (SRNL) which can be expanded to represent the current state of disposition process for waste generated at other DOE facilities. The model aims to assess resource allocation and waste processing options to stabilize productivity and cut the backlog of nuclear waste. By assessing the results of different scenarios, this research aims to provide actionable insights for the DOE. This approach has the potential to significantly improve the management of radioactive waste, offering the capability of evaluating options for optimizing the process for nuclear waste disposal. The findings of this study can serve as a valuable resource for decision-makers and other national laboratories, or research entities engaged in nuclear operations by enabling them to make more informed choices.

Andaverde, Alexis↗
DOE OSTI2021

Modeling and Analysis for Spent Nuclear Fuel Seismic Testing

Note: This is the final public release version of PNNL-31671 Draft, which was previously released to the sponsor for review. The intent is the public release version will be PNNL-31671. There are no significant changes from the earlier draft version. This unlimited distribution report is the deliverable for M3SF-21PN010202014: Modeling and Analysis for Spent Nuclear Fuel Seismic Testing. This report summarizes the modeling, analysis, and test plan support completed by Pacific Northwest National Laboratory for the spent nuclear fuel dry storage system seismic test plan through May of 2021. Test plan preparation is planned to continue until the seismic test is completed in July of 2022. This report covers preliminary structural dynamic model development and computer-aided design of test hardware. Based on preliminary modeling, the strongest earthquakes under consideration in this test program provide mechanical loading on the spent nuclear fuel that is comparable to the 30 cm cask drop scenario, although the loads do not appear to be strong enough to cause significant permanent deformation of the fuel assembly spacer grids. The potential for grid deformation during the test will be assessed when the proposed shake table motion becomes available. The weakest earthquakes considered in this test are expected to be comparable to the mechanical loads witnessed in the multimodal transportation test of 2017. The horizontal canister system is predicted to provide nearly-uniform loading condition on the fuel assemblies it contains, while the vertical cask system is predicted to cause non-uniform dynamic loads on the fuel assemblies. In the horizontal case, gravity keeps the fuel assemblies in contact with one basket wall surface unless the loads are strong enough to cause a separation. In the vertical case, the fuel assemblies are relatively long and slender, and seismic motion in the anticipated test range is predicted to cause the assemblies to lean, tilt, and impact the basket walls throughout the seismic event. These gap closures are a nonlinear force transmission condition, so the vertical system is expected to have more variation and variability than the horizontal system. While the horizontal system is expected to have a relatively more linear response than the vertical system, there is still the potential for nonlinear behavior in the horizontal system because the fuel assemblies are free to slide, bounce, and impact the basket walls if the seismic loads are strong enough. One major conclusion of this study is that the use of mixed fuel assemblies in the canister will be acceptable. There are differences in overall system response when the mass, center of gravity, or gaps are changed, but the changes in response are within the bounds of a system that contains completely homogeneous fuel assemblies. One important observation is that the loading for each individual fuel assembly within the vertical canister is expected to be different from that of the others because of nonlinearities in the system. The horizontal canister system is expected to have a more uniform and more predictable response than the vertical canister, making variations in fuel assembly characteristics easier to account for. One important recommendation that comes from this modeling work is to repeat some of the strongest shake tests at different angles, particularly for the vertical cask system. Modeling predicts that strong seismic motion will cause the fuel assemblies to close initial gaps and impact the fuel basket walls when the canister is in the vertical cask configuration. Each shake test will impose a pre-defined three-dimensional time history on the cask system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Agent-Based Modeling for the Circular Economy: Lessons Learned From Three Case Studies

The circular economy (CE) aims at decoupling human activities from resource use, creating wealth in the process. Recently, many scholars have questioned the link between increased circularity and sustainability, resulting in many methodological approaches being developed for that purpose. This presentation summarizes the insights gained from the application of agent-based modeling (ABM) to study the techno-economic and social conditions promoting circularity and sustainability of three technologies: photovoltaic (PV) modules, hard disk drives (HDDs), and wind blades. Four main categories of agents are defined in the ABM: asset owners, service providers (e.g., refurbishers), recyclers, and manufacturers. Two main CE strategies are represented: lifetime extension (through repair or reuse) and recycling. The developed models start by projecting installed capacities and end-of-life (EOL) quantities. Then the theory of planned behavior - a social psychology model explaining behavior adoption based on attitude, peer influence, and costs - is used to model the asset owners' EOL decision (i.e., landfill, recycle or extend the lifetime of the asset). Then, the quantities of assets flowing to the recycler and service provider agents and quantities of materials flowing to manufacturers are computed. Recyclers' economies of scale are dynamically modeled, and the value generated by the CE strategies for the recyclers, service providers, and manufacturers is computed within the model. When data are available, avoided greenhouse gas emissions resulting from the CE strategies adoption are calculated exogenously from the ABM simulations. Results show that with improved used PV modules warranties, the reuse CE strategy adoption increases from 1% to 23% between 2020 and 2050. Similarly, improved standards could enhance HDDs end-users trust in data-wiping - a prerequisite to reuse - leading to a 3-fold increase in the reuse rate and avoid about 5 million tons of CO2 eq by 2050. Regarding wind blades, 5-15 years lifetime extension could reduce EOL blade quantities by 13%. High costs and logistic issues prevent blades from being recycled in greater quantities. One insight from the case studies is the necessity to have mature secondary markets for reuse to be a viable option. Interestingly, PV reuse is limited by the willingness of PV owners to purchase used modules (on the demand side), while HDDs reuse is constrained by the lack of trust toward data-wiping (limiting the supply of used HDDs). The six limits of the CE concepts presented by Korhonen et al. (2018) are finally used to interpret the results. The HDD case study is an exemplary lock-in, where the first accepted practice (shredding) retains most of the market. The PV results illustrate the technical limitation to reuse, as the growing demand cannot be supplied entirely with used PV modules. The wind case study shows the relevance of clearly defining physical flows - what type of waste should wind blades be considered, how should they be transported and landfilled? - a crucial consideration that also applies to PV modules. Finally, the three case studies highlight the relevance of studying a technology's technical, economic, and market material efficiency potentials altogether and the potential benefit of coupling ABM to life cycle assessment.

agent-based modeling↗
DOE OSTI2023

An Investigation of Time Distributions for Task Primitives to Support the HUNTER Dynamic Human Reliability Analysis

As an effort to support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method. GOMS-HRA was developed to provide cognition-based time and human error probability information for dynamic HRA calculation in the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework. HUNTER is a framework to support the dynamic modelling of human error in conjunction with other modelling tools. In this paper, we investigate time distributions using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which suggests an HRA data collection framework to complement full-scope simulator research as well as collect input data for dynamic HRA using simplified simulators such as the Rancor Microworld Simulator. In this study, time required for GOMS-HRA task primitives to satisfy thirteen statistical distributions is investigated. Then, the time distributions from student operators and professional operators are compared and discussed. As a result, this study identified several time distributions on five GOMS-HRA task primitives at a statistically significant level. According to analyses to date, a greater number of significant time distributions was found in abnormal or emergency operating procedures rather than standard operating procedures. In the future, it is expected that the result of this study can provide objective reference on elapsed time data for task primitives as well as help to realistically simulate scenarios within dynamic HRA.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

MODELLING FIBER ORIENTATION DURING ADDITIVE MANUFACTURING COMPRESSION MOLDING PROCESSES

The production of high-performance thermoplastic composites reinforced with short carbon fibers can be achieved by a novel “additive manufacturing-compression molding” technique. An advantage of such combination is two-fold: controlled fiber orientation in additive manufacturing and less void content by compression molding. In this study, a computational fluid dynamics model has been developed to predict the behavior of printed layers during fiber-reinforced thermoplastic extrusion and subsequent compression molding. The fiber orientation was modelled with a simple quadratic closure model. The interaction between the fibers is included using a rotary diffusion coefficient which becomes significant in concentrated regimes. Finally, the second order orientation tensor is coupled with the momentum equation as an anisotropic part of the stress term. The effect of processing parameters on the behavior of printed layers was investigated to determine the favorable printing scenarios. The developed numerical model enables design of high-performance composites with tunable mechanical properties.

Seta, Berin↗
DOE OSTI2025

Correlated dynamic disorder, octahedral tilts, and acoustic phonon softening in CsSnBr 3 and CsPbBr 3

Metal halide perovskites (MHPs) have emerged as highly promising materials for optoelectronic applications, with all-inorganic MHPs presenting enhanced stability compared to their hybrid counterparts. Here, in this study, we investigate the atomic dynamics and structural fluctuations in single crystals of CsSnBr⁢ 3 and CsPbBr⁢ 3 through systematic inelastic neutron scattering (INS) measurements as a function of temperature. Our experiments are compared with first-principle simulations, augmented with large-scale molecular dynamics modeling, based on machine-learned neural network potentials. Through both INS and simulations, we find quasi-elastic diffuse rods in reciprocal space in both compounds, originating from fluctuating planar domains featuring correlated tilts of Br octahedron. The diffuse rods exhibit a slow, overdamped dynamic process, modulated across 𝑸 space, reflecting the strong lattice anharmonicity of the inorganic framework. We do not find evidence for dynamic off-centering of the Sn 2+ ions besides phonon vibrations at the center of the Br octahedron. These results offer valuable insights into the unusual anharmonic atomic dynamics and intricate correlated structural distortions in MHPs, which will be critical for rationalizing and further tailoring their thermal and optoelectronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration (Final Report)

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗
DOE OSTI2022

IMoFi (Intelligent Model Fidelity): Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Updated Accomplishments

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO), including some updates from the previous report SAND2022-0215, to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗