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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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DOE OSTI2026

T&D LIBRA: Simulation Framework for Transmission and Distribution Load and IBR Assessment

This paper introduces T&D LIBRA, a HELICS-based dynamic co-simulation framework designed for transmission and distribution (T&D) load and inverter-based resource assessment. This framework is designed to model interactions between single-phase induction motors (i.e., Motor-D), distributed energy resources (DERs) and the transmission network, emphasizing system stability during fault conditions. The primary objective of this research is to study the fault-induced delayed voltage recovery (FIDVR) behavior of the T&D networks using the co-simulation framework and to compare the results with conventional PSS/E only simulations. Simulations are validated using T&D co-simulations with a single distribution node and the IEEE 123-bus distribution test case. The co-simulation results demonstrate the value of using T&D co-simulations to capture motor stalling, DER tripping and other sources of voltage diversity on distribution networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

An Evaluation of Co-Simulation for Modeling Coupled Natural Gas and Electricity Networks

Reliance on natural gas for power generation has increased the coupling between gas and power networks. While this coupling can bring operational and economic benefits, it can also yield challenges, as the constraints in one system can impact the other. Co-simulation can capture the constraints and interactions between these systems, but so far, there has been limited comparison of co-simulation results to those of an integrated model. In this work, we develop a new co-simulation framework using the HELICS platform and the SAInt tool for modeling transient gas and AC optimal power flow. We evaluate this co-simulation framework against a fully integrated version of the SAInt power and gas simulators, thus providing a benchmarking of the co-simulation approach. We compare results across the two approaches for two test networks and a network representing the Belgian power and gas networks, testing both normal operating conditions and cases with compressor disruptions. In each of the cases tested, we find nearly identical results from the two approaches across various metrics of interest, such as nodal pressure, gas flow rates, and active power generation. This alignment suggests that co-simulation can yield comparable results to fully integrated models for modeling coupled gas and electricity networks.

03 NATURAL GAS↗
DOE OSTI2016

GLOBAL HIGH-RESOLUTION N-BODY SIMULATION OF PLANET FORMATION. I. PLANETESIMAL-DRIVEN MIGRATION

We investigated whether outward planetesimal-driven migration (PDM) takes place or not in simulations when the self-gravity of planetesimals is included. We performed N-body simulations of planetesimal disks with a large width (0.7–4 au) that ranges over the ice line. The simulations consisted of two stages. The first-stage simulations were carried out to see the runaway growth phase using the planetesimals of initially the same mass. The runaway growth took place both at the inner edge of the disk and at the region just outside the ice line. This result was utilized for the initial setup of the second-stage simulations, in which the runaway bodies just outside the ice line were replaced by the protoplanets with about the isolation mass. In the second-stage simulations, the outward migration of the protoplanet was followed by the stopping of the migration due to the increase of the random velocity of the planetesimals. Owing to this increase of random velocities, one of the PDM criteria derived in Minton and Levison was broken. In the current simulations, the effect of the gas disk is not considered. It is likely that the gas disk plays an important role in PDM, and we plan to study its effect in future papers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Determining pitch-angle diffusion coefficients from test particle simulations

The transport and acceleration of charged particles in turbulent media are topics of great interest in space physics and interstellar astrophysics. These processes are dominated by the scattering of particles off magnetic irregularities. The scattering process itself is usually described by small-angle scattering, with the pitch-angle coefficient D{sub μμ} playing a major role. Since the diffusion coefficient D{sub μμ} can be determined analytically only for the approximation of quasilinear theory, the determination of this coefficient from numerical simulations has become more important. So far these simulations have yielded particle tracks for small-scale scattering, which can then be interpreted using the running diffusion coefficients. This method has a limited range of validity. This paper presents two new methods that allow for the calculation of the pitch-angle diffusion coefficient from numerical simulations. These methods no longer analyze particle trajectories and instead examine the change of particle distribution functions. It is shown that these methods provide better resolved results and allow for the analysis of strong turbulence. The application of these methods to Monte Carlo simulations of particle scattering and hybrid MHD-particle simulations is presented. Both analysis methods are able to recover the diffusion coefficients used as input for the Monte Carlo simulations and provide better results in MHD simulations, especially for stronger turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Effect of Corner Modes in the Initial Conditions of Cosmological Simulations

In view of future high-precision large-scale structure surveys, it is important to quantify the percent and subpercent level effects in cosmological N-body simulations from which theoretical predictions are drawn. One such effect involves deciding whether to zero all modes above the one-dimensional Nyquist frequency, the so-called “corner” modes, in the initial conditions. We investigate this effect by comparing power spectra, density distribution functions, halo mass functions, and halo profiles in simulations with and without these modes. For a simulation with a mass resolution of m{sub p}∼10{sup 11} h{sup −1} M{sub ⊙}, we find that at z>6, the difference in the matter power spectrum is large at wavenumbers above ∼80% of k{sub Ny}, reducing to below 2% at all scales by z∼3. Including corner modes results in a better match between low- and high-resolution simulations at wavenumbers around the Nyquist frequency of the low-resolution simulation, but the effect of the corner modes is smaller than the effect of particle discreteness. The differences in mass functions are 3% for the smallest halos at z = 6 for the m{sub p}∼10{sup 11} h{sup −1} M{sub ⊙} simulation, but we find no significant difference in the stacked profiles of well-resolved halos at z⩽6. Thus removing power at |k|>k{sub Ny} in the initial conditions of cosmological simulations has a small effect on small scales and high redshifts, typically below a few percent.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Polarization Signature of Photospheric Magnetic Fields in 3D MHD Simulations and Observations at Disk Center

Before using three-dimensional (3D) magnetohydrodynamical (MHD) simulations of the solar photosphere in the determination of elemental abundances, one has to ensure that the correct amount of magnetic flux is present in the simulations. The presence of magnetic flux modifies the thermal structure of the solar photosphere, which affects abundance determinations and the solar spectral irradiance. The amount of magnetic flux in the solar photosphere also constrains any possible heating in the outer solar atmosphere through magnetic reconnection. We compare the polarization signals in disk-center observations of the solar photosphere in quiet-Sun regions with those in Stokes spectra computed on the basis of 3D MHD simulations having average magnetic flux densities of about 20, 56, 112, and 224 G. This approach allows us to find the simulation run that best matches the observations. The observations were taken with the Hinode SpectroPolarimeter (SP), the Tenerife Infrared Polarimeter (TIP), the Polarimetric Littrow Spectrograph (POLIS), and the GREGOR Fabry–Pèrot Interferometer (GFPI), respectively. We determine characteristic quantities of full Stokes profiles in a few photospheric spectral lines in the visible (630 nm) and near-infrared (1083 and 1565 nm). We find that the appearance of abnormal granulation in intensity maps of degraded simulations can be traced back to an initially regular granulation pattern with numerous bright points in the intergranular lanes before the spatial degradation. The linear polarization signals in the simulations are almost exclusively related to canopies of strong magnetic flux concentrations and not to transient events of magnetic flux emergence. We find that the average vertical magnetic flux density in the simulation should be less than 50 G to reproduce the observed polarization signals in the quiet-Sun internetwork. A value of about 35 G gives the best match across the SP, TIP, POLIS, and GFPI observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine Learning and Simulations

We introduce the DaRk mattEr and Astrophysics with Machine learning and Simulations (DREAMS) project, an innovative approach to understanding the astrophysical implications of alternative dark matter (DM) models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of cosmological hydrodynamic simulations that simultaneously vary over DM physics, astrophysics, and cosmology in modeling a range of systems—from galaxy clusters to ultra-faint satellites. Such extensive simulation suites can provide adequate training sets for machine-learning-based analyses. This paper introduces two new cosmological hydrodynamical suites of warm dark matter (WDM), each comprising 1024 simulations generated using the arepo code. One suite consists of uniform-box simulations covering a ${(25\,{h}^{-1}\,{\rm{Mpc}})}^{3}$ volume, while the other consists of Milky Way zoom-ins with sufficient resolution to capture the properties of classical satellites. For each simulation, the WDM particle mass is varied along with the initial density field and several parameters controlling the strength of baryonic feedback within the IllustrisTNG model. We provide two examples, separately utilizing emulators and convolutional neural networks, to demonstrate how such simulation suites can be used to disentangle the effects of DM and baryonic physics on galactic properties. The DREAMS project can be extended further to include different DM models, galaxy formation physics, and astrophysical targets. In this way, it will provide an unparalleled opportunity to characterize uncertainties on predictions for small-scale observables, leading to robust predictions for testing the particle physics nature of DM on these scales.

cosmological parameters↗
DOE OSTI2019

The Outer Rim Simulation: A Path to Many-core Supercomputers

Herein we describe the Outer Rim cosmological simulation, one of the largest high-resolution N-body simulations performed to date, aimed at promoting science to be carried out with large-scale structure surveys. The simulation covers a volume of (4.225 Gpc) 3 and evolves more than one trillion particles. It was executed on Mira, a BlueGene/Q system at the Argonne Leadership Computing Facility. We discuss some of the computational challenges posed by a system such as Mira, a many-core supercomputer, and how the simulation code, Hardware/Hybrid Accelerated Cosmology Code, has been designed to overcome these challenges. We have carried out a large range of analyses on the simulation data and we report on the results as well as the data products that have been generated. The full data set generated by the simulation totals more than 5 PB of data, making curation and handling of the data a large challenge in itself. The simulation results have been used to generate synthetic catalogs for large-scale structure surveys, including Dark Energy Spectroscopic Instrument and eBOSS, as well as experiments on the cosmic microwave background. A detailed catalog for the data challenges of the Large Synoptic Survey Telescope Dark Energy Science Collaboration has been created as well. We publicly release some of the Outer Rim halo catalogs, downsampled particle information, and lightcone data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Comparing XRISM Cluster Velocity Dispersions with Predictions from Cosmological Simulations: Are Feedback Models Too Ejective?

The dynamics of the intracluster medium (ICM), the hot plasma that fills galaxy clusters, are shaped by gravity-driven cluster mergers and feedback from supermassive black holes (SMBHs) in the cluster cores. XRISM measurements of ICM velocities in several clusters offer insights into these processes. We compare XRISM measurements for nine galaxy clusters (Virgo, Perseus, Centaurus, Hydra-A, PKS 0745–19, A2029, Coma, A2319, and Ophiuchus) with predictions from three state-of-the-art cosmological simulation suites, TNG-Cluster, the Three Hundred Project GADGET-X, and GIZMO-SIMBA, that employ different models of feedback. In cool cores, XRISM reveals systematically lower velocity dispersions than the simulations predict, with all 10 measurements below the median simulated values by a factor of 1.5–1.7 on average and all falling within the bottom 10% of the predicted distributions. The observed kinetic-to-total pressure ratio is also lower, with a median value of 2.2%, compared to the predicted 5.0%–6.5% for the three simulations. Outside the cool cores and in non-cool-core (NCC) clusters, simulations show better agreement with XRISM measurements, except for the outskirts of the relaxed, cool-core cluster A2029, which exhibits an exceptionally low kinetic pressure support (<1%), with none of the simulated systems in either of the three suites reaching such low levels. The NCC Coma and A2319 exhibit dispersions at the lower end but within the simulated spread. Our comparison suggests that the three numerical models may overestimate the kinetic effects of SMBH feedback in cluster cores. Additional XRISM observations of NCC clusters will clarify if there is a systematic tension in the gravity-dominated regime as well.

galaxy clusters↗
DOE OSTI2020

An Empirical Study on the Use of the Rancor Microworld Simulator to Support Full-scope Data Collection

A lack of data has been identified as a major challenge in human reliability analysis (HRA). Accordingly, several institutes and researchers have tried to collect HRA data from different data sources such as actual historical measurements, expert judgements, or simulator studies. While the most recent studies predominantly focus on collecting data using full-scope simulators with actual operators, Idaho National Laboratory (INL) has begun to collect HRA data using a simplified simulator, i.e., the Rancor Microworld simulator, with student participants. Full-scope studies have been known to have several intrinsic challenges to securing enough quantity of the data due to many reasons like the high cost for performing experiments or requiring actual operators’ cooperation. The ultimate goal of INL’s effort aims to infer actual operators’ data collected from a full-scope simulator on the basis of microworld data with student subjects as well as collect additional data that could be missed in the full-scope research. As a first step to achieve this goal, this paper projects an experimental plan for investigating the differences in human performance between individuals in two groups: 1) an actual operator and 2) a student when using the Rancor Microworld simulator. A randomized factorial experiment design has been developed with two independent variables, i.e., type of scenario and type of subject. Six human performance measures, i.e., 1) time, 2) error, 3) workload, 4) situation awareness, 5) patterns of attention and 6) the number of manipulations were selected. A couple of scenarios and their procedures available to the Rancor Microworld simulator have been developed.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Understanding Contamination; Twenty Years of Simulating Radiological Contamination

A wide variety of simulated contamination methods have been developed by researchers to reproducibly test radiological decontamination methods. Some twenty years ago a method of non-radioactive contamination simulation was proposed at the Idaho National Laboratory (INL) that mimicked the character of radioactive cesium and zirconium contamination on stainless steel. It involved baking the contamination into the surface of the stainless steel in order to 'fix' it into a tenacious, tightly bound oxide layer. This type of contamination was particularly applicable to nuclear processing facilities (and nuclear reactors) where oxide growth and exchange of radioactive materials within the oxide layer became the predominant model for material/contaminant interaction. Additional simulation methods and their empirically derived basis (from a nuclear fuel reprocessing facility) are discussed. In the last ten years the INL, working with the Defense Advanced Research Projects Agency (DARPA) and the National Homeland Security Research Center (NHSRC), has continued to develop contamination simulation methodologies. The most notable of these newer methodologies was developed to compare the efficacy of different decontamination technologies against radiological dispersal device (RDD, 'dirty bomb') type of contamination. There are many different scenarios for how RDD contamination may be spread, but the most commonly used one at the INL involves the dispersal of an aqueous solution containing radioactive Cs-137. This method was chosen during the DARPA projects and has continued through the NHSRC series of decontamination trials and also gives a tenacious 'fixed' contamination. Much has been learned about the interaction of cesium contamination with building materials, particularly concrete, throughout these tests. The effects of porosity, cation-exchange capacity of the material and the amount of dirt and debris on the surface are very important factors. The interaction of the contaminant/substrate with the particular decontamination technology is also very important. Results of decontamination testing from hundreds of contaminated coupons have lead to certain conclusions about the contamination and the type of decontamination methods being deployed. A recent addition to the DARPA initiated methodology simulates the deposition of nuclear fallout. This contamination differs from previous tests in that it has been developed and validated purely to simulate a 'loose' type of contamination. This may represent the first time that a radiologically contaminated 'fallout' stimulant has been developed to reproducibly test decontamination methods. While no contaminant/methodology may serve as a complete example of all aspects that could be seen in the field, the study of this family of simulation methods provides insight into the nature of radiological contamination.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Communication Simulations for Power System Applications

New smart grid technologies and concepts, such as dynamic pricing, demand response, dynamic state estimation, and wide area monitoring, protection, and control, are expected to require considerable communication resources. As the cost of retrofit can be high, future power grids will require the integration of high-speed, secure connections with legacy communication systems, while still providing adequate system control and security. While considerable work has been performed to create co-simulators for the power domain with load models and market operations, limited work has been performed in integrating communications directly into a power domain solver. The simulation of communication and power systems will become more important as the two systems become more inter-related. This paper will discuss ongoing work at Pacific Northwest National Laboratory to create a flexible, high-speed power and communication system co-simulator for smart grid applications. The framework for the software will be described, including architecture considerations for modular, high performance computing and large-scale scalability (serialization, load balancing, partitioning, cross-platform support, etc.). The current simulator supports the ns-3 (telecommunications) and GridLAB-D (distribution systems) simulators. Ongoing and future work will be described, including planned future expansions for a traditional transmission solver. A test case using the co-simulator, utilizing a transactive demand response system created for the Olympic Peninsula and AEP gridSMART demonstrations, requiring two-way communication between distributed and centralized market devices, will be used to demonstrate the value and intended purpose of the co-simulation environment.

co-simulation↗
DOE OSTI2014

Simulating Microbial Community Patterning Using Biocellion

Mathematical modeling and computer simulation are important tools for understanding complex interactions between cells and their biotic and abiotic environment: similarities and differences between modeled and observed behavior provide the basis for hypothesis forma- tion. Momeni et al. [5] investigated pattern formation in communities of yeast strains engaging in different types of ecological interactions, comparing the predictions of mathematical modeling and simulation to actual patterns observed in wet-lab experiments. However, simu- lations of millions of cells in a three-dimensional community are ex- tremely time-consuming. One simulation run in MATLAB may take a week or longer, inhibiting exploration of the vast space of parameter combinations and assumptions. Improving the speed, scale, and accu- racy of such simulations facilitates hypothesis formation and expedites discovery. Biocellion is a high performance software framework for ac- celerating discrete agent-based simulation of biological systems with millions to trillions of cells. Simulations of comparable scale and accu- racy to those taking a week of computer time using MATLAB require just hours using Biocellion on a multicore workstation. Biocellion fur- ther accelerates large scale, high resolution simulations using cluster computers by partitioning the work to run on multiple compute nodes. Biocellion targets computational biologists who have mathematical modeling backgrounds and basic C++ programming skills. This chap- ter describes the necessary steps to adapt the original Momeni et al.'s model to the Biocellion framework as a case study.

metabolic interaction↗
DOE OSTI2014

FNCS: A Framework for Power System and Communication Networks Co-Simulation

This paper describes the Fenix framework that uses a federated approach for integrating power grid and communication network simulators. Compared existing approaches, Fenix al- lows co-simulation of both transmission and distribution level power grid simulators with the communication network sim- ulator. To reduce the performance overhead of time synchro- nization, Fenix utilizes optimistic synchronization strategies that make speculative decisions about when the simulators are going to exchange messages. GridLAB-D (a distribution simulator), PowerFlow (a transmission simulator), and ns-3 (a telecommunication simulator) are integrated with the frame- work and are used to illustrate the enhanced performance pro- vided by speculative multi-threading on a smart grid applica- tion. Our speculative multi-threading approach achieved on average 20% improvement over the existing synchronization methods

Co-simulation↗
DOE OSTI2017

Optimizing for Large Planar Fractures in Multistage Horizontal Wells in Enhanced Geothermal Systems Using a Coupled Fluid and Geomechanics Simulator

Enhanced Geothermal Systems (EGS) could potentially use technological advancements in coupled implementation of horizontal drilling and multistage hydraulic fracturing techniques in tight oil and shale gas reservoirs along with improvements in reservoir simulation techniques to design and create EGS reservoirs. In this study, a commercial hydraulic fracture simulation package, Mangrove by Schlumberger, was used in an EGS model with largely distributed pre-existing natural fractures to model fracture propagation during the creation of a complex fracture network. The main goal of this study is to investigate optimum treatment parameters in creating multiple large, planar fractures to hydraulically connect a horizontal injection well and a horizontal production well that are 10,000 ft. deep and spaced 500 ft. apart from each other. A matrix of simulations for this study was carried out to determine the influence of reservoir and treatment parameters on preventing (or aiding) the creation of large planar fractures. The reservoir parameters investigated during the matrix simulations include the in-situ stress state and properties of the natural fracture set such as the primary and secondary fracture orientation, average fracture length, and average fracture spacing. The treatment parameters investigated during the simulations were fluid viscosity, proppant concentration, pump rate, and pump volume. A final simulation with optimized design parameters was performed. The optimized design simulation indicated that high fluid viscosity, high proppant concentration, large pump volume and pump rate tend to minimize the complexity of the created fracture network. Additionally, a reservoir with 'friendly' formation characteristics such as large stress anisotropy, natural fractures set parallel to the maximum horizontal principal stress (SHmax), and large natural fracture spacing also promote the creation of large planar fractures while minimizing fracture complexity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Fast Learning for Immersive Engagement in Energy Simulations

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximation methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Multi-physics Object Oriented Simulation Environment (MOOSE)

This two-day workshop is a hands-on introduction to the Multi-Physics Object Oriented Simulation Environment (MOOSE). MOOSE is a simulation framework built from PETSc that enables efficient simulation of complex physical systems with minimal programming background. Attendees are encouraged to visit the MOOSE website at www.mooseframework.org and walk through the step by step process of installing the framework on their computer. Support through this process is provided through the MOOSE Google Group message board. The workshop itself will consist of interactive modules where instructors from the MOOSE development team will work with attendees to build a simple plasma model. Each module will build on previous modules to introduce fundamental MOOSE features that will combine to demonstrate simulation capabilities for low temperature plasma modeling. The intention is not to provide an exhaustive overview of simulation capabilities but to instead provide attendees with the necessary tools to build unique simulation capabilities for their specific research challenges. Users should attend the workshop with laptop computers with MOOSE installed to allow for interactive instruction. At the completion of the workshop attendees will be able to install and run MOOSE and associated applications as well as carry out plasma simulations studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

VALIDATION AND DETERMINATION OF SIGNIFICANT SIMULATION PARAMETERS USING THE SMOOTHED PARTICLE HYDRODYNAMIC CODE NEUTRINO

In recent years there has been an increase in flooding concern to nuclear power plants; thus, tools to reduce the cost of mitigation efforts are valuable to industry. Simulating flooding events is achieved through different methods and at varied levels of detail. However, these simulations must be able to match application conditions, which requires code validation as well as knowledge of which parameters affect the accuracy of the simulation. To validate and determine the significant parameters for these tools, a sloshing experiment was conducted at the George Washington University and then simulated with the smoothed particle hydrodynamic code Neutrino. The simulation setup was constructed to match the experiment as closely as possible, and the end-wall pressure results were analysed. The 90% and 50% end-wall pressure bounds were compared along with the pressure impulse. The simulation bounds fell mostly within the experimental bounds, with exceptions in insignificant low-pressure areas, such as at the beginning (~40% difference) and the end of the cycle (~40% difference). Another exception was seen at a point in the peak pressure (~75% difference). The simulated pressure impulse matched the experiments well and was within 10%. Additionally, seven parameters were qualitatively assessed and then investigated to determine their significance. The parameters’ significance was determined by sampling five values across the parameters’ range using the Risk Analysis Virtual Environment, then comparing the average pressure for each run. All seven parameters were identified as having some significance. However, the particle size, interaction-radius to particle-size ratio, and fluid settling seem to have a greater effect due to the larger fluctuation of the results. Now that the significant parameters are identified, further research is being done to quantify the significance of each parameter.

97 MATHEMATICS AND COMPUTING↗