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At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Quasi-Static Time Series Fatigue Simulation for PV Inverter Semiconductors with Long-Term Solar Profile

Power system simulations with long-term data tend to have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stresses cycle is with line frequency. This requires the time step of the fatigue simulation to be much smaller than the line period. This small time step results in poor simulation speed, especially for long-term simulations. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The fatigue analysis typically focuses on the peak and valley values of a strain and neglect the transients from peaks to valleys. The proposed simulation utilizes this property of fatigue analysis and calculates the steady state of the semiconductor junction temperature only. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset without losing accuracy.

fast simulation↗
DOE OSTI2022

Electromagnetic Transient (EMT) Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (T&D Models)

Simulation of high-fidelity models of extreme fast charging (XFC) systems and large-area power grids with many XFCs can be time consuming in traditional simulators. Traditional simulators use a single method of discretization for all the components that results in imposing a large computational burden of inverting a large matrix as well as increased computations related to single method of discretization (that is typically a trapezoidal method). To overcome the problem of simulating large-area power grids with many XFCs, in this paper, advanced numerical simulation algorithms are applied for the first time together to reduce the dimension of matrix inversion. Here, the algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. These algorithms apply multiple discretization algorithms rather than a single discretization algorithm that further reduces the computational burden. The approaches mentioned here have resulted in speed-up of up to 18x in the simulation of a single distribution system with 15 XFCs and of up to 271x in the simulation of a transmission-distribution system with 300 XFCs in multiple distribution feeders with respect to conventional simulators (like power systems computer aided design [PSCAD]).

42 ENGINEERING↗
DOE OSTI2015

Sample-morphology effects on x-ray photoelectron peak intensities. III. Simulated spectra of model core–shell nanoparticles

The National Institute of Standards and Technology database for the simulation of electron spectra for surface analysis has been used to simulate Cu 2p photoelectron spectra for four types of spherical copper–gold nanoparticles (NPs). These simulations were made to extend the work of Tougaard [J. Vac. Sci. Technol. A 14, 1415 (1996)] and of Powell et al. [J. Vac. Sci. Technol. A 31, 021402 (2013)] who performed similar simulations for four types of planar copper–gold films. The Cu 2p spectra for the NPs were compared and contrasted with analogous results for the planar films and the effects of elastic scattering were investigated. The new simulations were made for a monolayer of three types of Cu/Au core–shell NPs on a Si substrate: (1) an Au shell of variable thickness on a Cu core with diameters of 0.5, 1.0, 2.0, 5.0, and 10.0 nm; (2) a Cu shell of variable thickness on an Au core with diameters of 0.5, 1.0, 2.0, 5.0, and 10.0 nm; and (3) an Au shell of variable thickness on a 1 nm Cu shell on an Au core with diameters of 0.5, 1.0, 2.0, 5.0, and 10.0 nm. For these three morphologies, the outer-shell thickness was varied until the Cu 2p{sub 3/2} peak intensity was the same (within 2%) as that found in our previous work with planar Cu/Au morphologies. The authors also performed similar simulations for a monolayer of spherical NPs consisting of a CuAu{sub x} alloy (also on a Si substrate) with diameters of 0.5, 1.0, 2.0, 5.0, and 10.0 nm. In the latter simulations, the relative Au concentration (x) was varied to give the same Cu 2p{sub 3/2} peak intensity (within 2%) as that found previously. For each morphology, the authors performed simulations with elastic scattering switched on and off. The authors found that elastic-scattering effects were generally strong for the Cu-core/Au-shell and weak for the Au-core/Cu-shell NPs; intermediate elastic-scattering effects were found for the Au-core/Cu-shell/Au-shell NPs. The shell thicknesses required to give the selected Cu 2p{sub 3/2} peak intensity for the three types of core–shell NPs were less than the corresponding film thicknesses of planar samples since Cu 2p photoelectrons can be detected from the sides and, for the smaller NPs, bottoms of the NPs. Elastic-scattering effects were also observed on the Au atomic fractions found for the CuAu{sub x} NP alloys with different diameters.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Radiation doses in volume-of-interest breast computed tomography—A Monte Carlo simulation study

Purpose: Cone beam breast computed tomography (breast CT) with true three-dimensional, nearly isotropic spatial resolution has been developed and investigated over the past decade to overcome the problem of lesions overlapping with breast anatomical structures on two-dimensional mammographic images. However, the ability of breast CT to detect small objects, such as tissue structure edges and small calcifications, is limited. To resolve this problem, the authors proposed and developed a volume-of-interest (VOI) breast CT technique to image a small VOI using a higher radiation dose to improve that region’s visibility. In this study, the authors performed Monte Carlo simulations to estimate average breast dose and average glandular dose (AGD) for the VOI breast CT technique. Methods: Electron–Gamma-Shower system code-based Monte Carlo codes were used to simulate breast CT. The Monte Carlo codes estimated were validated using physical measurements of air kerma ratios and point doses in phantoms with an ion chamber and optically stimulated luminescence dosimeters. The validated full cone x-ray source was then collimated to simulate half cone beam x-rays to image digital pendant-geometry, hemi-ellipsoidal, homogeneous breast phantoms and to estimate breast doses with full field scans. 13-cm in diameter, 10-cm long hemi-ellipsoidal homogeneous phantoms were used to simulate median breasts. Breast compositions of 25% and 50% volumetric glandular fractions (VGFs) were used to investigate the influence on breast dose. The simulated half cone beam x-rays were then collimated to a narrow x-ray beam with an area of 2.5 × 2.5 cm{sup 2} field of view at the isocenter plane and to perform VOI field scans. The Monte Carlo results for the full field scans and the VOI field scans were then used to estimate the AGD for the VOI breast CT technique. Results: The ratios of air kerma ratios and dose measurement results from the Monte Carlo simulation to those from the physical measurements were 0.97 ± 0.03 and 1.10 ± 0.13, respectively, indicating that the accuracy of the Monte Carlo simulation was adequate. The normalized AGD with VOI field scans was substantially reduced by a factor of about 2 over the VOI region and by a factor of 18 over the entire breast for both 25% and 50% VGF simulated breasts compared with the normalized AGD with full field scans. The normalized AGD for the VOI breast CT technique can be kept the same as or lower than that for a full field scan with the exposure level for the VOI field scan increased by a factor of as much as 12. Conclusions: The authors’ Monte Carlo estimates of normalized AGDs for the VOI breast CT technique show that this technique can be used to markedly increase the dose to the breast and thus the visibility of the VOI region without increasing the dose to the breast. The results of this investigation should be helpful for those interested in using VOI breast CT technique to image small calcifications with dose concern.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-F-CAMPUS-I-03: GPU Accelerated Monte Carlo Technique for Fast Concurrent Image and Dose Simulation

Purpose: To develop an accurate and fast Monte Carlo (MC) method of simulating CT that is capable of correlating dose with image quality using voxelized phantoms. Methods: A realistic voxelized phantom based on patient CT data, XCAT, was used with a GPU accelerated MC code for helical MDCT. Simulations were done with both uniform density organs and with textured organs. The organ doses were validated using previous experimentally validated simulations of the same phantom under the same conditions. Images acquired by tracking photons through the phantom with MC require lengthy computation times due to the large number of photon histories necessary for accurate representation of noise. A substantial speed up of the process was attained by using a low number of photon histories with kernel denoising of the projections from the scattered photons. These FBP reconstructed images were validated against those that were acquired in simulations using many photon histories by ensuring a minimal normalized root mean square error. Results: Organ doses simulated in the XCAT phantom are within 10% of the reference values. Corresponding images attained using projection kernel smoothing were attained with 3 orders of magnitude less computation time compared to a reference simulation using many photon histories. Conclusion: Combining GPU acceleration with kernel denoising of scattered photon projections in MC simulations allows organ dose and corresponding image quality to be attained with reasonable accuracy and substantially reduced computation time than is possible with standard simulation approaches.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Measurement with microscopic MRI and simulation of flow in different aneurysm models

Purpose: The impact and the development of aneurysms depend to a significant degree on the exchange of liquid between the regular vessel and the pathological extension. A better understanding of this process will lead to improved prediction capabilities. The aim of the current study was to investigate fluid-exchange in aneurysm models of different complexities by combining microscopic magnetic resonance measurements with numerical simulations. In order to evaluate the accuracy and applicability of these methods, the fluid-exchange process between the unaltered vessel lumen and the aneurysm phantoms was analyzed quantitatively using high spatial resolution. Methods: Magnetic resonance flow imaging was used to visualize fluid-exchange in two different models produced with a 3D printer. One model of an aneurysm was based on histological findings. The flow distribution in the different models was measured on a microscopic scale using time of flight magnetic resonance imaging. The whole experiment was simulated using fast graphics processing unit-based numerical simulations. The obtained simulation results were compared qualitatively and quantitatively with the magnetic resonance imaging measurements, taking into account flow and spin–lattice relaxation. Results: The results of both presented methods compared well for the used aneurysm models and the chosen flow distributions. The results from the fluid-exchange analysis showed comparable characteristics concerning measurement and simulation. Similar symmetry behavior was observed. Based on these results, the amount of fluid-exchange was calculated. Depending on the geometry of the models, 7% to 45% of the liquid was exchanged per second. Conclusions: The result of the numerical simulations coincides well with the experimentally determined velocity field. The rate of fluid-exchange between vessel and aneurysm was well-predicted. Hence, the results obtained by simulation could be validated by the experiment. The observed deviations can be caused by the noise in the measurement and by the limited resolution of the simulation. The resulting differences are small enough to allow reliable predictions of the flow distribution in vessels with stents and for pulsed blood flow.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-149: Development of the Monte Carlo Simulation Platform Using Geant4 for Designing Heavy Ion Therapy Beam Nozzle

Purpose: The significant issue of particle therapy such as proton and carbon ion was a accurate dose delivery from beam line to patient. For designing the complex delivery system, Monte Carlo simulation can be used for the simulation of various physical interaction in scatters and filters. In this report, we present the development of Monte Carlo simulation platform to help design the prototype of particle therapy nozzle and performed the Monte Carlo simulation using Geant4. Also we show the prototype design of particle therapy beam nozzle for Korea Heavy Ion Medical Accelerator (KHIMA) project in Korea Institute of Radiological and Medical Science(KIRAMS) at Republic of Korea. Methods: We developed a simulation platform for particle therapy beam nozzle using Geant4. In this platform, the prototype nozzle design of Scanning system for carbon was simply designed. For comparison with theoretic beam optics, the beam profile on lateral distribution at isocenter is compared with Mont Carlo simulation result. From the result of this analysis, we can expected the beam spot property of KHIMA system and implement the spot size optimization for our spot scanning system. Results: For characteristics study of scanning system, various combination of the spot size from accerlator with ridge filter and beam monitor was tested as simple design for KHIMA dose delivery system. Conclusion: In this report, we presented the part of simulation platform and the characteristics study. This study is now on-going in order to develop the simulation platform including the beam nozzle and the dose verification tool with treatment planning system. This will be presented as soon as it is become available.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Evaluation of the Fitch Wind-Farm Wake Parameterization with Large-Eddy Simulations of Wakes Using the Weather Research and Forecasting Model

Abstract Wind-farm parameterizations in weather models can be used to predict both the power output and farm effects on the flow; however, their correctness has not been thoroughly assessed. We evaluate the wind-farm parameterization of the Weather Research and Forecasting Model with large-eddy simulations (LES) of the wake performed with the same model. We study the impact on the velocity and turbulence kinetic energy (TKE) of inflow velocity, roughness, resolution, number of turbines (one or two), and inversion height and strength. We compare the mesoscale with the LES by spatially averaging the LES within areas correspondent to the mesoscale horizontal spacing: one covering the turbine area and two downwind. We find an excellent agreement of the velocity within the turbine area between the two types of simulations. However, within the same area, we find the largest TKE discrepancies because in mesoscale simulations, the turbine-added TKE has to be highest at the turbine position to be advected downwind. Within the downwind areas, differences between velocities increase as the wake recovers faster in the LES, whereas for the TKE both types of simulations show similar levels. From the various configurations, the impact of inversion height and strength is small for these heights and inversion levels. The highest impact for the one-turbine simulations appears under the low-speed case due to the higher thrust, whereas the impact of resolution is low for the large-eddy simulations but high for the mesoscale simulations. Our findings demonstrate that higher-fidelity simulations are needed to validate wind-farm parameterizations.

17 WIND ENERGY↗
DOE OSTI2020

Simulation as a sustainable trading zone: Aiming at intergenerational justice

The paper, drawing on the example of simulation codes used in nuclear physics and high-energy physics, seeks to call attention to the ethical implications of discontinuing support for simulation codes and the loss of knowledge embodied in them. Predicated on the concept of trading zones and actor network models, the paper addresses the problem of extinction of simulation codes and attempts to understand their evolution and development within those frameworks. We show that simulation codes of closed type develop to the level of creoles, becoming local languages and standards of scientific centers and disappearing as their few main developers leave, whereas codes of open types become universal languages, imposing problemsolving patterns on the entire community and crowding out other codes. The paper suggests that because of simulations’ reliance on tacit knowledge, practices entrenched in codes cannot be exhaustively explicated or transmitted through writing alone; on the contrary, the life cycle of a simulation code is determined by the life cycle of its trading zone. We examine the extent to which both of these phenomena pose a risk to the preservation of knowledge. Bearing upon intergenerational ethics, we draw analogies between the pure intergenerational problem (PIP) and the problem of preserving the knowledge implemented in simulation codes and transmitting it to future generations. We argue that for the complete transfer of knowledge, it is necessary to develop and maintain inhabitability and sustainability of simulation trading zones in a controllable way, at least until the demand for these codes is warranted to cease in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Ground-motions site and event specificity: Insights from assessing a suite of simulated ground motions in the San Francisco Bay Area

This article presents the results of a research that is part of a larger collaborative effort between the Lawrence Berkeley National Laboratory and the Pacific Earthquake Engineering Research Center, funded by the US Department of Energy Office of Cybersecurity, Energy Security and Emergency Response. The main objective of this study is to assess a suite of near and far-field simulated ground motions obtained from 20 realizations of an M7 Hayward Fault earthquake in the San Francisco Bay Area, California USA, and inform the selection of rupture simulation parameters leading to strong motions. To this aim, comparisons are conducted with NGA-W2 and directivity ground-motion models and a selected population of records. An archetypal steel moment-resisting frame is utilized to assess infrastructure response distributions. The analyses carried out for each simulated event and subdomain with consistent properties in terms of shallow shear-wave velocity proved to be instrumental for better interpreting the differences between simulated motions and empirical models. The main reasons identified for variances between simulations and empirical relationships included (1) directivity effects fully captured by the simulations across the full breadth of rupture models; (2) site vicinity to ruptures that incorporate large-slip patches, particularly if these are in the forward-directivity direction; and (3) presence of geologic structures that can “trap” seismic waves and produce ground motions with large amplitude and long signal duration. The analyses carried out in this work provide a path for interpreting ground-motion site and event specificity obtained from a suite of physics-based simulations, differing only in the rupture model characterization, to inform the selection of simulation scenarios for site-specific engineering analyses under strong excitations. Evidence from this work points to the possibility that current hazard models may underestimate ground-motion intensities in areas where the combined effect of directivity and site conditions results in large ground-motion amplitudes.

58 GEOSCIENCES↗
DOE OSTI2022

Simulation of SPND Beta-Current in AP1000 core

The Self-Powered Neutron Detectors (SPNDs) are widely used in Generation-III commercial PWR due to its small size and external-power free character. It can measure the in-core neutron flux density immediately to obtain the power profile in the core. To better understand the actual state of the simulated core, a SPND beta-current simulation module has been established in the NECP-Bamboo code. Firstly, neutron simulation is carried out in the lattice code Bamboo-Lattice together with nuclide depletion simulation to obtain the depleted composition of the entire lattice including the SPND, and the few-group parameters including density and cross section of emitter material. Secondly, the depleted lattice can then be piped into a Monte-Carlo code for neutron-photon-electron simulation to obtain the electron escape efficiency from the emitter of the SPND to the corresponding collector. Thirdly, the electron escape efficiency can be parameterized into the function of the lattice state parameters similarly to the common few-group constants. Finally, the beta-current was calculated by the core code Bamboo-Core simultaneously with the simulation of the core operation process. The beta-current of the Vanadium SPND in the AP1000 core was simulated and analyzed in this paper. Comparison between simulation and measurement of the beta-current distribution in the specific core state is shown in this paper to verify the effectiveness of the method and the code. The radial normalized current distribution is in good agreement with the measurement. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Latent Space Simulation for Carbon Capture Design Optimization

The CO2 capture efficiency in solvent-based carbon capture systems (CCSs) critically depends on the gas-solvent interfacial area (IA), making maximization of IA a foundational challenge in CCS design. While the IA associated with a particular CCS design can be estimated via a computational fluid dynamics (CFD) simulation, using CFD to derive the IAs associated with numerous CCS designs is prohibitively costly. However, previous works such as Deep Fluids (Kim et al., 2019) show that large simulation speed-ups and low error are achievable by replacing CFD simulators with neural-network (NN) surrogates that mimic the CFD simulation process. This raises the possibility for a fast, accurate replacement for a CFD simulator, and thus computationally feasible IA-based CCS-design optimization. As such, here, we explore whether an existing NN-surrogate approach (and variants we develop) can successfully be applied to our complex carbon-capture CFD simulations, with the ultimate goal of obtaining a fast and accurate simulator for our CCS-design application. Our experiments build on the Deep Fluids approach and find that resulting surrogates can produce large speed ups (4000x) while maintaining IA relative errors as low as 4% on unseen CCS configurations (interpolating between configurations seen during training). Thus, despite less faithfulness to the underlying physics of the problem, NN surrogates may be a promising tool for our CCS design optimization problem. Notably, though, the Deep Fluids approach has limitations for our application (such as model non-transferability to CCS-packing changes), which we discuss. We conclude with potential directions for future work that may, like innovations we introduced here (e.g., transformer-based dynamics prediction), improve performance on our complicated dataset of CCS CFD simulations.

AI Surrogate Simulation, Carbon Capture, design op↗
DOE OSTI2016

Evaporation Of Hanford Waste Treatment Plant Direct Feed Low Activity Waste Effluent Management Facility Core Simulant

The Hanford Waste Treatment and Immobilization Plant (WTP) Low Activity Waste (LAW) vitrification facility will generate an aqueous condensate recycle stream (LAW Melter Off-Gas Condensate, LMOGC) from the off-gas system. The baseline plan for disposition of this stream during full WTP operations is to send it to the WTP Pretreatment Facility, where it will be blended with LAW, concentrated by evaporation, and recycled to the LAW vitrification facility. However, during the Direct Feed LAW (DFLAW) scenario, planned disposition of this stream is to evaporate it in a new evaporator, in the Effluent Management Facility (EMF), and then return it to the LAW melter. It is important to understand the composition of the effluents from the melter and new evaporator, so that the disposition of these streams can be accurately planned and accommodated. Furthermore, alternate disposition of the LMOGC stream would eliminate recycling of problematic components, and would reduce the need for closely integrated operation of the LAW melter and the Pretreatment Facilities. Long-term implementation of this option after WTP start-up would decrease the LAW vitrification mission duration and quantity of glass waste, amongst the other operational complexities such a recycle stream presents. In order to accurately plan for the disposition path, it is key to experimentally determine the fate of contaminants. To do this, testing is needed to accurately account for the buffering chemistry of the components, determine the achievable evaporation end point, identify insoluble solids that form, and determine the distribution of key regulatory-impacting constituents. The LAW Melter Off-Gas Condensate stream will contain components that are volatile at melter temperatures, have limited solubility in the glass waste form, and represent a materials corrosion concern, such as halides and sulfate. Because this stream will recycle within WTP, these components will accumulate in the Melter Condensate stream, exacerbating their impact on the number of LAW glass containers that must be produced. Diverting the stream reduces the halides and sulfates in the recycled Condensate and is a key outcome of this work. This overall program examines the potential treatment and immobilization of this stream to enable alternative disposal. The objective of this task was to demonstrate evaporation of a simulant of the LAW Melter Off-gas Condensate expected during DFLAW operations, in order to predict the composition of the effluents from the EMF evaporator to aid in planning for their disposition. This document describes the results of that test using the core simulant. This simulant formulation is designated as the “core simulant”; other additives will be included for specific testing, such as volatiles for evaporation or hazardous metals for measuring leaching properties of waste forms. The results indicate that the simulant can easily be concentrated via evaporation. During that the pH adjustment step in simulant preparation, ammonium is quickly converted to ammonia, and most of the ammonia was stripped from the simulated waste and partitioned to the condensate. Additionally, it was found that after concentrating (>12x) and cooling that a small amount of LiF and Na 3 (SO 4 )F precipitate out of solution. With the exception of ammonia, analysis of the condensate indicated very low to below detectable levels of many of the constituents in the simulant, yielding very high decontamination factors (DF).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Blade-Resolved, Single-Turbine Simulations Under Atmospheric Flow

The ultimate goal of the ExaWind project is to enable scientific discovery through predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The objective of this milestone is to demonstrate a 'production run' of a megawatt-scale turbine to exercise and demonstrate the turbine simulation capabilities that have been developed during the previous two years of the ExaWind project. Demonstrating this simulation capability is the critical first step in enabling Nalu-Wind to be used as a predictive modeling tool that can advance the scientific understanding of wind turbine performance. In Section 2, the milestone description is provided. Next, in Section 3, we present the NREL 5-megawatt (MW) reference turbine that was used to demonstrate Nalu-Wind's capabilities and describe the four computational meshes that were generated. In Section 4, we present results from simulations of the turbine operating under uniform inflow and homogeneous isotropic turbulence (HIT) conditions. Finally, in Section 5, notable achievements, conclusions, and a path forward are described.

17 WIND ENERGY↗
DOE OSTI2024

Integrated Transmission and Distribution Co-Simulation Platform for Demonstration of Bulk Grid Services Using Distributed Energy Resources

In September 2020, the Federal Energy Regulatory Commission (FERC) released Order 2222, which opens wholesale markets to small-capacity distributed energy resources (DERs), recognizing their potential in improving operational efficiency by providing bulk grid services. Therefore, a co-simulation capability that can connect transmission and distribution (T&D) simulations and evaluate the impacts of DER provision of bulk grid services is needed. In this paper, we present a new integrated T&D co-simulation platform that incorporates T&D system simulators, DER aggregator/group strategies, and a co-simulation coordinator. Industry-standard communication protocols are employed to mimic real-world conditions. Secondary frequency regulation is selected as the representative bulk grid service, and we simulate the responses of DERs to the frequency regulation signals. The simulation results for a solar-rich distribution feeder in Colorado, USA, demonstrate how the T&D co-simulation setup is used to evaluate the contributions of DERs to minimize the bulk grid frequency deviation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

ASSESSING ASTROPHYSICAL UNCERTAINTIES IN DIRECT DETECTION WITH GALAXY SIMULATIONS

We study the local dark matter velocity distribution in simulated Milky Way-mass galaxies, generated at high resolution with both dark matter and baryons. We find that the dark matter in the solar neighborhood is influenced appreciably by the inclusion of baryons, increasing the speed of dark matter particles compared to dark matter-only simulations. The gravitational potential due to the presence of a baryonic disk increases the amount of high velocity dark matter, resulting in velocity distributions that are more similar to the Maxwellian Standard Halo Model than predicted from dark matter-only simulations. Furthermore, the velocity structures present in baryonic simulations possess a greater diversity than expected from dark matter-only simulations. We show that the impact on the direct detection experiments LUX, DAMA/Libra, and CoGeNT using our simulated velocity distributions, and explore how resolution and halo mass within the Milky Way’s estimated mass range impact the results. A Maxwellian fit to the velocity distribution tends to overpredict the amount of dark matter in the high velocity tail, even with baryons, and thus leads to overly optimistic direct detection bounds on models that are dependent on this region of phase space for an experimental signal. Our work further demonstrates that it is critical to transform simulated velocity distributions to the lab frame of reference, due to the fact that velocity structure in the solar neighborhood appears when baryons are included. There is more velocity structure present when baryons are included than in dark matter-only simulations. Even when baryons are included, the importance of the velocity structure is not as apparent in the Galactic frame of reference as in the Earth frame.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

The Use of Microgravity Simulators for Space Research

The spaceflight environment is known to influence biological processes ranging from stimulation of cellular metabolism to possible impacts on cellular damage repair, suppression of immune functions, and bone loss in astronauts. Microgravity is one of the most significant stress factors experienced by living organisms during spaceflight, and therefore, understanding cellular responses to altered gravity at the physiological and molecular level is critical for expanding our knowledge of life in space. Since opportunities to conduct experiments in space are scarce, various microgravity simulators and analogues have been widely used in space biology ground studies. Even though simulated microgravity conditions have produced some, but not all of the biological effects observed in the true microgravity environment, they provide test beds that are effective, affordable, and readily available to facilitate microgravity research. A Micro-g Simulator Center is being developed at Kennedy Space Center (KSC) to offer a variety of microgravity simulators and platforms for Space Biology investigators. Assistance will be provided by both KSC and external experts in molecular biology, microgravity simulation, and engineering. Comparisons between the physical differences in microgravity simulators, examples of experiments using the simulators, and scientific questions regarding the use of microgravity simulators will be discussed.

Simulation↗