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NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity

The transition between gravity environments will involve one of the most complex, high-risk phases of exploration missions. The reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Specifically, two high-risk scenarios may be required to be performed soon after gravity transitions: 1) nominal and/or emergency unassisted capsule egress task after return to Earth, and 2) planetary extravehicular activity (EVA) soon after landing on Mars or the Moon. Quantification of crewmember’s functional performance after long-duration spaceflight is necessary to inform concepts of operations for future exploration missions. The overarching aim of this study is to quantify post-landing functional performance with deconditioning after long-duration ISS missions. This study is broken down into two phases. Phase 1 includes a pilot study to assess the overall feasibility and demonstrate the capability to perform mission-like tasks shortly after landing. Phase 2, the Egress Fitness study, which is part of the Complement of Integrated Protocols for Human Exploration Research (CIPHER), uses a task-based approach to characterize functional performance in long-duration ISS crewmembers before flight and shortly after return to Earth. The pilot and full Egress Fitness study includes pre-flight and post-flight testing of simulated emergency egress out of a functional capsule mockup and a Mars gravity EVA simulation at the Active Response Gravity Offload System (ARGOS) facility. The EVA simulation tasks include suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. The post-flight simulated capsule egress test occurs 1–4 h after landing and the planetary EVA simulation occurs 18–36 h after landing. The full CIPHER Egress Fitness study has additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. The Pilot Egress Fitness study has completed baseline and post-flight testing on four crewmembers. All subjects were able to complete the post-flight simulated planetary EVA; three subjects were able to complete the postflight capsule egress simulation. CIPHER study data collection is ongoing. This study will quantify post-landing functional performance in operationally relevant simulations to help inform future planetary concepts of operations shortly after landing.

egress↗
NASA NTRSDate not supplied

Cardiovascular Responses to Simulated Spaceflight: Molecular Signatures and Surrogate Outputs to Measure CVD Risk

During extended space missions beyond low Earth orbit, astronauts will encounter prolonged periods of weightlessness and low dose space radiation. Previous studies have shown that exposure to small doses of high LET radiation (< 50 cGy) can lead to both short-term and long-term alterations in heart function, structure and underlying molecular mechanisms. In this study, we aim to identify the molecular signature associated with the cardiovascular response to simulated galactic cosmic radiation (5-ion GCR) alone or in combination with simulated weightlessness at time intervals relevant to mission length and recovery. Additionally, we aim to determine whether sex impacts cardiovascular responses to these spaceflight factors. Our overarching goal is to enhance our understanding of the cardiovascular risks associated with extended space missions and the clinical endpoints they suggest. We hypothesize that exposure to simulated space radiation leads to enduring alterations in the transcriptome, redox signaling and cytokine environment of cardiovascular tissue, some which have known links with reduced cardiovascular performance, aging, and increased risk of cardiovascular disease (CVD). Furthermore, we posit that simulated space radiation exposure in combination with simulated microgravity exacerbates cardiovascular deficits compared to single factor exposure. Female and male C57BL/6J mice, aged 23-24 weeks, were exposed to a single dose of 5, 15, or 50 cGy of 5-ion GCR, or sham-treated (0 cGy). Euthanasia was performed at 14 days and ~4 months post-irradiation. Hearts, aorta and blood plasma were collected shortly thereafter. RNA-sequencing of left ventricles at ~4 months post-GCR exposure revealed sex differences in the heart transcriptome with a few genes showing radiation-dependent changes in expression levels. Notably, some of the differentially expressed genes in 15 and 50 cGy GCR groups are known to play roles in the development of CVD. Analysis of protein levels of a subset of inflammatory cytokines in the heart indicated sex differences but no differences between sham and 50 cGy groups. Results also showed correlations among differentially expressed genes and a subset of inflammatory cytokines, with some correlations altered by GCR exposure. These findings suggest that GCR exposure can modify protein and gene networks linked to inflammation and CVD progression. In the aorta, telomere lengths were comparable across treatment groups sexes. Mitochondrial copy number is a biomarker for mitochondrial function with decreased copy numbers associated with cardiometabolic disease traits. Mitochondrial copy numbers of aorta also showed no sex nor dose differences. In a second study, mice underwent one week of simulated microgravity by hindlimb unloading (HU) and then exposed to a single dose of 15 cGy of 5-ion GCR. HU was conducted for an additional two weeks following GCR exposure. Single factor exposure groups (HU or GCR only) also were included in the study. Euthanasia was then performed and the same tissues were collected. Protein levels of select inflammatory cytokines in the heart showed sex-dependent differences in expression. In the aorta, telomere lengths and mitochondrial copy number also showed sex differences. In summary, our results indicate differences between sexes in biomarkers related to cardiovascular health. Exposure to 5-ion GCR or HU, alone or in combination, did not result in changes in most of the cardiovascular biomarkers that were examined. However, in the heart, simulated space radiation at doses of 15 and 50 cGy led to long-term alterations in the expression levels of a small group of genes known to be associated with the progression of CVD. The long-term transcriptomic changes resulting from exposure to simulated space radiation should be carefully investigated to mitigate adverse cardiovascular events during and after deep space missions. Our results also highlight the importance of sex-specific strategies in monitoring and maintaining cardiovascular health during and after deep space missions.

cardiovascular↗
NASA NTRS2024

Evaluating Differences Among Crop Models in Simulating Soybean in-Season Growth

Crop models are useful tools for simulating agricultural systems that require continued model development and testing to increase their robustness and improve how they describe our current understanding of processes. Coordinated and “blind” evaluation of multiple models using same protocols and experimental datasets provides unique opportunities to further improve models and enhance their reliability. For soybean [Glycine max (L.) Merr.], there has been limited coordinated multi-model evaluations for the simulation of in-season plant growth dynamics. We evaluated ten dynamic soybean crop models for their simulation of in-season plant growth using data from five experiments conducted in Argentina, Brazil, France, and USA. We evaluated models after a Blind (using only phenology data) and a Full calibration (with in-season and end-of-season variables). Calibration reduced model uncertainty by reducing standard bias for the simulation of in-season variables (biomass, leaf, pod, and stem weights, and leaf area index, LAI). However, we found that most models had difficulty in reproducing leaf growth dynamics, with normalized root mean squared error (nRMSE) of 56% for leaf weight and 43% for LAI (across locations and models after Full calibration). Models with different levels of complexity and experience were capable of simulating final seed yield at maturity with reasonable accuracy (nRMSE of 8–31% after Full calibration). However, the nRMSE for pod weight (of 17–64% after Full calibration) was two-fold larger than that of seed yield. Moreover, the models differed in how they simulated timing from sowing to beginning seed growth (47–93 days) and effective seed filling period (18–54 days), owing to model structural differences in defining the reproductive developmental stages. Overall, we identified the following processes that can benefit from further model improvement: leaf expansion and senescence, reproductive phenology, and partitioning to reproductive growth. Simulation of pod wall tissue and individual seed cohorts is another aspect that many models currently lack. Model improvement can benefit from high-temporal resolution experimental datasets that concurrently account for phenology, plant growth, and partitioning. Further, we recommend collecting reproductive phenology in the field consistent with actual dry matter allocation to organs in the models and collecting multiple observations of seed and pod weight to aid model improvement for simulation of seed growth and yield formation.

Agricultural Model Intercomparison and Improvement↗
DOE OSTI2017

Real-Time Digital Simulation of Inertial Response with Hardware-in-the-Loop Implementation on the CART3 Wind Turbine at the National Wind Technology Center

With increasing penetrations of wind power on electric grids, the stability and reliability of interconnected power systems may be impacted. In some countries that have developed renewable energy sources and systems, grid codes have been revised to require wind power plants (WPPs) to provide ancillary services to support the power system frequency in case of severe grid events. To do this, wind turbine generators (WTGs) should be deloaded to reserve a certain amount of active power for primary frequency response; however, deloading curtails annual energy production, and the market for this type of service needs to be further developed. In this report, we focus on the temporary frequency support provided by WTGs through inertial response. WTGs have potential to provide inertial response, but appropriate control methods should be implemented. With the implemented inertial control methods, wind turbines are capable of increasing their active power output by releasing some of their stored kinetic energy when a frequency excursion occurs. Active power can be temporarily boosted above the maximum power points, after which the rotor speed decelerates, and subsequently an active power output reduction restores the kinetic energy. In this report, we develop two types of models for wind power systems: the first is common, based on the wind power aerodynamic equation, and the power coefficient can be regressed using nonlinear functions; the second is much more complicated, wherein the wind turbine system is modeled using the Fatigue, Aerodynamics, Structures, and Turbulence Modeling (FAST) tool with several degrees of freedoms. A nine-bus test power system is built in Simulink and the Real-Time Digital Simulator, respectively, which are used to evaluate the frequency support performance of the WPPs. We implement two distinct types of inertial control methods in the modeled wind turbines: frequency-based inertial control (FBIC) and stepwise inertial control (SIC). We compare the performances of the two methods in terms of their frequency nadirs, rates of change of frequency, and recovery times. We conclude the results under various wind speeds and penetration cases, which provide insight into designing the inertial response of WTGs. Further, we discuss the impact of the parameters on the performance of the inertial control methods. We evaluate both the scaling factors for the FBIC method and the slope values for the TLIC methods. The simulation work shows the characteristics of different inertial responses compared to conventional synchronous generators. Based on the simulation results, we modify, improve, and test the inertial control methods under a more realistic wind turbine model based on FAST. We then validate the inertial responses under highly turbulent wind conditions generated by TurbSim, and we examine their influences on the turbine mechanical components. The extensive simulation proves the effectiveness of the proposed inertial control methods as well as the nine-bus test power system. We then reconsider the parameters. We rebuild the same test power system using Real time Simulator Computer Aided Design (RSCAD), and we implement the inertial control methods in the real Controls Advanced Research Turbine (CART3), which is prepared for the hardware-in-the-loop field-test simulation. After the setups for the hardware and software hybrid simulation platform are complete, the inertial response is further tested on a real wind turbine for the first time, in which CART3 release the controlled inertial response against the emulated frequency excursion, provided by the real-time simulated power system test bed in RTDS.

17 WIND ENERGY↗
DOE OSTI2017

Simulating, visualizing, and searching traffic in a software defined network

The present disclosure pertains to systems and methods for simulating data packet routing within a software defined network (“SDN”), visualizing the results of the simulation, and permitting a user to search the resulting simulation. In one specified embodiment, a system may receive from a user a simulation parameter associated with a packet to be simulated in the SDN. A packet based on the at least one simulation parameter may be generated. A response of the SDN to the packet may be simulated by identifying applicable traffic routing rules and identifying a subsequent destination based on the applicable traffic routing rules. A record of the subsequent destination may be added to the simulation result, and the process may continue until a terminating condition is satisfied.

42 ENGINEERING↗
DOE OSTI2020

Hybrid EMT-TS Simulation Strategies to Study High Bandwidth MMC-Based HVdc Systems

Modular multilevel converters (MMCs) are widely used in the design of modern high-voltage direct current (HVdc) transmission system. High-fidelity dynamic models of MMCs-based HVdc system require small simulation time step and can be accurately modeled in electro-magnetic transient (EMT) simulation programs. The EMT program exhibits slow simulation speed and limitation on the size of the model and brings certain challenges to test the high-fidelity HVdc model in system-level simulations. This paper presents the design and implementation of a hybrid simulation framework, which enables the co-simulation of the EMT model of Atlanta-Orlando HVdc line and the transient stability (TS) model of the entire Eastern Interconnection system. This paper also introduces the implementation of two high-fidelity HVdc line models simulated at different time steps and discusses a dedicated method for sizing the buffer areas on both sides of the HVdc line. The simulation results of the two HVdc models with different sizes of buffer areas are presented and compared.

Liu, Yuan↗
DOE OSTI2020

Real-time simulator and controller of power system using distributed data streaming server

Systems and methods for simulating and controlling a power system in real time, using a controller, are provided. The controller includes a simulation layer to simulate an operation of the power system, a disturbance generation layer to provide data to the simulation layer to disturb the simulated operation of the power system, an application layer to display the simulated operation of the power system and generate a control signal to control, based on the simulated operation of the power system, at least one element of the power system, and a distributed data streaming server (D2S2) to allow interoperability among the simulation layer, the disturbance layer, and the application layer.

Li, Fangxing↗
DOE OSTI2021

Comparison of Electromagnetic Transient and Phasor-based Simulation for the Stability of Grid-Forming-Inverter-based Microgrids

The increasing interest in studying feeder-level, inverter-based microgrids requires appropriate simulation methods that can effectively simulate the dynamics of distribution feeders that typically have thousands of nodes. To examine the accuracy of phasor-based simulation for the stability of feeder-level, inverter-based microgrids, a comparative study between electromagnetic transient (EMT) and phasor-based simulation was conducted. Case studies of a two-inverter small microgrid and a modified version of the IEEE 34-Node Test System that has seven grid-forming inverters show that phasor-based simulation agrees well with EMT simulation when the P-f droop gains of grid-forming inverter controllers are within normal ranges. However, under extremely high P-f droop gains, phasor-based simulation can result in over-optimistic stability results. This study provides insight into the applicability of phasor-based simulation for the stability of feeder-level, inverter-based microgrids.

Du, Wei↗
DOE OSTI2021

Incorporation of Thermal Hydraulic Models for Thermal Power Dispatch into a PWR Power Plant Simulator

This report describes the development, modeling, and results of a generic pressurized water reactor power plant simulator that incorporates coupled electrical and thermal power dispatch to an industrial process located approximately one kilometer from the nuclear power plant. The simulator is a commercial PWR simulator that has been modified to include thermal power dispatch as described in past milestone reports [ , ]. The commercial PWR simulator is a generic simulator available from GSE SYSTEMS® (Sykesville, MD, USA) that is built using RELAP5-HDTM Real-Time Solution and in-house software developed by GSE Systems. This generic PWR (GPWR) simulator performs real-time simulation of the complete power plant from the reactor neutronics to the electricity generation and distribution. All primary, secondary, and auxiliary systems are modeled including all control logic in order to provide the most accurate representation of actual nuclear power plant (NPP) operation, and the simulator results have been rigorously verified by an actual NPP operating at approximately 1 GWe. This report is a continuation of worked performed in previous years, and supplemental information from previous reports is included in the appendix for reference.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Snowmass2021 Computational Frontier White Paper: Cosmological Simulations and Modeling

Powerful new observational facilities will come online over the next decade, enabling a number of discovery opportunities in the "Cosmic Frontier", which targets understanding of the physics of the early universe, dark matter and dark energy, and cosmological probes of fundamental physics, such as neutrino masses and modifications of Einstein gravity. Synergies between different experiments will be leveraged to present new classes of cosmic probes as well as to minimize systematic biases present in individual surveys. Success of this observational program requires actively pairing it with a well-matched state-of-the-art simulation and modeling effort. Next-generation cosmological modeling will increasingly focus on physically rich simulations able to model outputs of sky surveys spanning multiple wavebands. These simulations will have unprecedented resolution, volume coverage, and must deliver guaranteed high-fidelity results for individual surveys as well as for the cross-correlations across different surveys. The needed advances are as follows: (1) Development of scientifically rich and broadly-scoped simulations, which capture the relevant physics and correlations between probes (2) Accurate translation of simulation results into realistic image or spectral data to be directly compared with observations (3) Improved emulators and/or data-driven methods serving as surrogates for expensive simulations, constructed from a finite set of full-physics simulations (4) Detailed and transparent verification and validation programs for both simulations and analysis tools. (Abridged)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Efficient Subset Simulation using Hamiltonian Neural Network enhanced Markov Chain Monte Carlo Methods

The Monte Carlo method delivers an unbiased estimate of the probability of failure. However, the variance of the estimate depends on the number of evaluated samples. This number must be very large for estimations of a low probability of failure. If the evaluation of each sample is computationally expensive, the crude Monte Carlo simulation strategy is impracticable. Therefore, subset simulations are used to reduce the required number of evaluations. Subset simulations require a Markov Chain Monte Carlo sampler, such as the random walk Metropolis-Hastings algorithm. The algorithm, however, struggles with sampling in low-probability regions, especially if they are narrow. As a consequence, advanced Markov Chain Monte Carlo simulations have been developed. In particular, the Hamiltonian Monte Carlo method explores the target distribution rapidly. Driven by the idea of Hamiltonian dynamics, this sampler provides a non-random walk through the target distribution. The incorporation of subset simulation and Hamiltonian Monte Carlo methods has shown promising results for reliability analysis. One downside of the Hamiltonian Monte Carlo method is that gradient evaluations are computationally expensive, especially when dealing with high-dimensional problems and evaluating long trajectories. We show that integrating Hamiltonian neural networks in Hamiltonian Monte Carlo simulations significantly speeds up the sampling task. Furthermore, the enhancement of adaptive trajectory length within the Hamiltonian Monte Carlo results in the efficient proposal of the following states. Based on this recent enhancement, we provide a fast sampling strategy for subset simulations using Hamiltonian neural networks to replace the evaluation of the gradient and significantly speed up the Hamiltonian Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Buffer-IPyC separation process in TRISO fuel particles simulated with Bison code

During High Temperature Gas-cooled Reactor (HTGR) operation, tristructural isotropic (TRISO) coated-particle fuel undergoes irradiation-induced changes in morphology and thermomechanical properties. Experimental results from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program show, among other things, the mechanism of gap formation between the buffer and inner pyrolytic carbon (IPyC) layers, which could be explored further via computational simulations using the Bison code. Two simulation models were developed, the debonding restricted model, where no gap formation between buffer and IPyC layers is permitted, and the debonding enabled model, where the gap between those layers is created. The inputs of the simulated models are based on the irradiation conditions from the AGR-1 experiment. The research included simulations on spherical and aspherical fuel types. Under the specific temperatures and fluences of the AGR-1 irradiation experiment, and the Bison simulations, it was concluded that the most common scenario is a gap formation along the buffer-IPyC interface, while the least possible scenario is the situation where there is no gap formation at the buffer-IPyC junction. The computational results confirmed that the sphericity of the fuel influences the thickness of the gap that occurs at the buffer-IPyC junction, in a way that with increasing aspect ratio the gap thickness increases. The results obtained for spherical and aspherical fuel are nearly identical. Finally, performed simulations match conclusions observed from the AGR-1 experiment, which as such shows that the Bison code is a good computational method for simulating the TRISO fuel. Future simulations will include the validation of performed research and comparison of the results between Bison and PARFUME codes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Progress Toward Simulating Departure from Nucleate Boiling at High-Pressure Applications with Selected Wall Boiling Closures

Recently, a Eulerian-based two-fluid computational fluid dynamics (CFD) framework with a wall heat flux partitioning approach has been intensively investigated for departure from nucleate boiling (DNB) simulation under the U.S. Department of Energy–funded Consortium for Advanced Simulation of Light Water Reactors (CASL) program. Understanding of the DNB characteristics over a range of pressurized water reactor–like operating conditions and accurate prediction of boiling crisis in the nuclear power system have been grand challenges because of the large impact of DNB on reactor safety and operational economics. The ultimate goal of this task in the CASL program is to introduce a robust multiphase CFD–based DNB modeling framework that is capable of characterizing an entire boiling history in which the wall boiling mode experiences the following through multiple stages of heat transfer mode: (1) single-phase convective heat transfer, (2) nucleate boiling heat transfer, and (3) identification of the departure of nucleate boiling. To validate the CASL boiling model, we have benchmarked simulated DNB over three different flow channel configurations (pipe flow, 5 × 5 fuel bundle with mixing vane tests, and 5 × 5 fuel bundle without mixing vane tests) against experimental measurements, and the validation result with open literature is reported. The DNB detection criteria in the simulation are checked by monitoring the peak wall temperature, wall dryout factor, and net energy balance. In addition to the DNB performance test, some preliminary sensitivity results on closure model selection are reported to address the prediction capability of local void profile against measurements. The boiling simulation tested in this study exhibits a maximum deviation of 24% from the measured DNB value in a high-pressure (i.e., 138 bars) subcooled pipe flow test. The ranges of operating conditions are as follows: 1650 to 2650 kg/m 2 ·s for mass flux and 8.5 to 96 K for subcooled inlet temperature. The deviation is even reduced to 7% when the subcooled temperature is less than 40 K. Besides accuracy, base practice guidelines for DNB detection criteria are tested by monitoring three simulation variables: (1) maximum wall temperature, (2) wall dryout factor (i.e., K-value), and (3) energy balance. Numerical robustness of DNB simulation is largely achieved in most of the validation test except for a few high subcooled test cases.

42 ENGINEERING↗
DOE OSTI2024

HERO WEC V1.0 2024 - WEC-Sim Detailed Simulation Runs and Summary Data

This dataset includes results from simulations of NREL's hydraulic and electric reverse osmosis wave energy converter (HEREO WEC). Simulation runs include 135 wave cases that were based on the updated WEC-Sim model, which is linked below. The data represented in this repository is based on an updated WEC-Sim model using laboratory data to tune and refine the original WEC-Sim model for the V1.0 HERO WEC. The 135 wave cases represent waves with the following wave height and wave period ranges: - Significant Wave Height: 0.25 - 3.75m in 0.25m increments - Wave Period: 5 - 13 sec in 1 sec increments Each run was simulated using a Pierson-Moskowitz irregular wave spectrum with a 100 second ramp time, a total simulation time of 3,100 seconds, and a simulation time-step of 0.005s. A reference table has been included to map each multi condition run (MCR) case with each wave condition. Summary data set includes a spreadsheet and image files with matrices that are associated with data from simulation runs. All matrices cover the same significant wave height and wave periods from the simulation runs, in the same increments. The following matrices are included: - Power Abs: The average absorbed power from the WEC (calculated from anchor reaction force and heave velocity) - Power Hyd: The average hydraulic power output at pump (calculated from pump output flow and pressure) - Power - Hyd ROi: The average hydraulic power measured at the RO system inlet (calculated from RO system pressure and flow (pre-accumulator)) - Flow - Pump out: The average flowrate measured at the pump outlet - Flow - Perm: The average permeate (clean water) production - Flow - RO (pre): The average flowrate measured at the inlet of the RO system before the accumulators - Flow - RO (post): The average flowrate measured after the accumulator bank in the RO system - Pressure - RO: The average pressure measured at the inlet of the RO system This data set has been developed by the National Renewable Energy Laboratory, operated by the Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Regional-Scale 3D Ground-Motion Simulations of M w 7 Earthquakes on the Hayward Fault, Northern California Resolving Frequencies 0–10 Hz and Including Site-Response Corrections

Large earthquake ground-motion simulations in 3D Earth models provide constraints on site-specific shaking intensities but have suffered from limited frequency resolution and ignored site response in soft soils. In this work we report new regional-scale 3D simulations for moment magnitude 7.0 scenario earthquakes on the Hayward Fault, northern California with SW4. Simulations resolved significantly broader band frequencies (0–10 Hz) than previous studies and represent the highest resolution simulations for any such earthquake to date. Seismic waves were excited by a kinematic rupture following Graves and Pitarka (2016) and obeyed wave propagation in a 3D Earth model with topography from the U.S. Geological Survey (USGS) assuming a minimum shear wavespeed, VSmin, of 500 m/s. We corrected motions for linear and nonlinear site response for the shear wavespeed, VS, from the USGS 3D model, using a recently developed ground-motion model (GMM) for Fourier amplitude spectra . At soft soil locations subjected to strong shaking, the site-corrected intensities reflect the competing effects of linear amplification by low V S material, reduction of stiffness during nonlinear deformation, and damping of high frequencies. Sites with near-surface V S of 500 m/s or greater require no linear site correction but can experience amplitude reduction due to nonlinear response. Averaged over all sites, we obtained reasonable agreement with empirical ergodic median GMMs currently used for seismic hazard and design ground motions (epsilon less than 1), with marked improvement at soft sedimentary sites. At specific locations, the simulated shaking intensities show systematic differences from the GMMs that reveal path and site effects not captured in these ergodic models. Results suggest how next generation regional-scale earthquake simulations can provide higher spatial and frequency resolution while including effects of soft soils that are commonly ignored in scenario earthquake ground-motion simulations.

58 GEOSCIENCES↗
DOE OSTI2024

Sensitivity of Simulations of Double-detonation Type Ia Supernovae to Integration Methodology

Abstract We study the coupling of hydrodynamics and reactions in simulations of the double-detonation model for Type Ia supernovae. When assessing the convergence of simulations, the focus is usually on spatial resolution; however, the method of coupling the physics together as well as the tolerances used in integrating a reaction network also play an important role. In this paper, we explore how the choices made in both coupling and integrating the reaction portion of a simulation (operator/Strang splitting versus the simplified spectral deferred corrections method we introduced previously) influences the accuracy, efficiency, and nucleosynthesis of simulations of double detonations. We find no need to limit reaction rates or reduce the simulation time step to the reaction timescale. The entire simulation methodology used here is GPU-accelerated and made freely available as part of the Castro simulation code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗