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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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This software is being developed to support data analysis, modeling, and simulation for the growing field of heliosphere physics. In particular, this software will implement data analysis, modeling, inference, and simulation of physical mechanisms describing how energetic neutral atoms behave within the Earth’s heliosphere and in the interstellar medium beyond.
The LMDT software automates the process of the load composite model data preparation in the format supported by the major power system software vendors (GE and Siemens). Proper representation of the load composite model in power system dynamic analysis is very important. Software tools for power system simulation like GE PSLF and Siemens PSSE already include algorithms for the load composite modeling. However, these tools require that the input information on composite load to be provided in custom formats. Preparation of this data is time consuming and requires multiple manual operations. The LMDT software enables to automate this process. Software is designed to generate composite load model data. It uses the default load composition data, motor information, and bus information as an input. Software processes the input information and produces load composition model. Generated model can be stored in .dyd format supported by GE PSLF package or .dyr format supported by Siemens PSSE package.
There is increasing interest in alternate arm converter (AAC) due to the fault-tolerant characteristics it could offer in high-voltage direct current (HVdc) systems. The simulation of AACs is important to assist with the design of hardware, control systems, and planning of power system expansions. However, simulation of AAC-HVdc using existing software takes a long time due to the presence of a large number of states and non-linear devices. An ultra-fast single-or multi-CPU simulation algorithm to simulate the AAC-HVdc system based on state-space models and using hybrid discretization algorithm with a relaxation technique that reduces the imposed computational burden is presented in this paper. The developed algorithm is validated with respect to reference PSCAD/EMTDC model.
This report presents the modeling and simulation capabilities of Argonne National Laboratory’s PERSENT (PERturbation and SENsitivity for Transport) code [1] that is used in modern commercial deployment reactor technologies. The identified capabilities will be used to establish the set of PERSENT verification tasks necessary to verify PERSENT for usage on commercial projects. A similar path was followed for the REBUS [2] and DIF3D [3] software packages.
Purpose: In proton therapy, the relative biological effectiveness (RBE) – compared with conventional photon therapy – is routinely set to 1.1. However, experimental in vitro studies indicate evidence for the variability of the RBE. To clarify the impact on patient treatment, investigation of the RBE in a preclinical case study should be performed. Methods: The Monte Carlo software TOPAS was used to simulate the radiation field of an irradiation setup at the experimental beamline of the proton therapy facility (OncoRay) in Dresden, Germany. Simulations were performed on cone beam CT-data (CBCT) of a xenogeneous mouse with an orthotopic lung carcinoma obtained by an in-house developed small animal image-guided radiotherapy device. A homogeneous physical fraction dose of 1.8Gy was prescribed for the contoured tumor volume. Simulated dose and linear energy transfer distributions were used to estimate RBE values in the mouse based on an RBE model by Wedenberg et al. To characterize radiation sensitivity of normal and tumor tissue, α/β-ratios were taken from the literature for NB1RGB (10.1Gy) and human squamous lung cancer (6.2Gy) cell lines, respectively. Results: Good dose coverage of the target volume was achieved with a spread-out Bragg peak (SOBP). The contra-lateral lung was completely spared from receiving radiation. An increase in RBE towards the distal end of the SOBP from 1.07 to 1.35 and from 1.05 to 1.3 was observed when considering normal tissue and tumor, respectively, with the highest RBE values located distal to the target volume. Conclusion: Modeled RBE values simulated on CBCT for experimental preclinical proton therapy varied with tissue type and depth in a mouse and differed therefore from a constant value of 1.1. Further translational work will include, first, conducting preclinical experiments and, second, analogous RBE studies in patients using experimentally verified simulation settings for our clinically used patient-specific beam conforming technique.
Verification and validation are crucial software quality control procedures when developing and implementing models. This is particularly important as a variety of stakeholders rely on accurate predictions from building simulation programs. This study uses the BEopt Automated Residential Simulation Test Suite (BARTS) to facilitate comparison of two energy simulation engines across various building components and includes models that isolate the impacts of specific building components on annual energy consumption. As a case study, BARTS has been used to identify important discrepancies between the engines for several components of the building models; these discrepancies are caused by differences in the models used by the engines or coding errors.
CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical “doses” of the HealtheRx shared their information with others (“social doses”). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population (“agents”) using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.
Hydro-mechanical models appear in simulation of many environmental problems related to construction of engineering barriers for contaminant spreading. The presented work aims in modelling bentonite-sand barriers, which can be used for nuclear waste isolation and similar problems. Particularly, we use hydro-mechanical model coupling unsaturated flow and (nonlinear) elasticity, implement such model in COMSOL software and show application in simulation of an infiltration test (2D axisymmetric model) and the SEALEX Water test WT1 experiment (3D model). Finally, we discuss the needs and possibilities of parallel high performance computing.
This report documents thirteen of Sandia's contributions to the Computational Systems and Software Environment (CSSE) within the Advanced Simulation and Computing (ASC) program between fiscal years 2009 and 2012. It describes their impact on ASC applications. Most contributions are implemented in lower software levels allowing for application improvement without source code changes. Improvements are identified in such areas as reduced run time, characterizing power usage, and Input/Output (I/O). Other experiments are more forward looking, demonstrating potential bottlenecks using mini-application versions of the legacy codes and simulating their network activity on Exascale-class hardware. The purpose of this report is to prove that the team has completed milestone 4467-Demonstration of a Legacy Application's Path to Exascale. Cielo is expected to be the last capability system on which existing ASC codes can run without significant modifications. This assertion will be tested to determine where the breaking point is for an existing highly scalable application. The goal is to stretch the performance boundaries of the application by applying recent CSSE RD in areas such as resilience, power, I/O, visualization services, SMARTMAP, lightweight LWKs, virtualization, simulation, and feedback loops. Dedicated system time reservations and/or CCC allocations will be used to quantify the impact of system-level changes to extend the life and performance of the ASC code base. Finally, a simulation of anticipated exascale-class hardware will be performed using SST to supplement the calculations. Determine where the breaking point is for an existing highly scalable application: Chapter 15 presented the CSSE work that sought to identify the breaking point in two ASC legacy applications-Charon and CTH. Their mini-app versions were also employed to complete the task. There is no single breaking point as more than one issue was found with the two codes. The results were that applications can expect to encounter performance issues related to the computing environment, system software, and algorithms. Careful profiling of runtime performance will be needed to identify the source of an issue, in strong combination with knowledge of system software and application source code.
Verification and validation are crucial software quality control procedures to follow when developing and implementing models. This is particularly important because a variety of stakeholders rely on accurate predictions from building simulation programs. This study uses the BEopt Automated Residential Simulation Test Suite (BARTS) to facilitate comparison of two energy simulation engines across various building components and includes building models that isolate the impacts of specific components on annual energy consumption. As a case study, BARTS has been used to identify important discrepancies between the engines for several components of the building models. These discrepancies are caused by differences in the algorithms used by the engines or coding errors.
Integration of large numbers of distributed photovoltaic (PV) systems in electric distribution circuits often requires advanced functions (e.g. volt-VAR, frequency-Watt etc.). However, significant concerns have been raised about potential for PV inverters with such controls to interact with one another in a way that could cause grid instability. The lack of standardized inverter models makes it hard to simulate such transient interactions in software. Similarly it is very hard to test these dynamic inverter interactions in the laboratory. In this paper, unique Power Hardware-in-the-Loop (PHIL) techniques are presented to experimentally test for interactions of multiple PV inverters connected to multiple points-of-common-coupling (PCCs) with grid impedances between them. Sample test results are provided from simulation-only scenarios and PHIL testing. Though simulation results indicated possible harmful interactions between inverters' volt-VAR controllers; no such interactions were found in the limited hardware testing.
In this Final Report, we the researchers of the high energy physics group at Tufts University summarize our works and achievements in three frontier areas of elementary particle physics: (i) Neutrino physics at the Intensity Frontier, (ii) Collider physics at the Energy Frontier, and (iii) Theory investigations of spin structure and quark-gluon dynamics of nucleons using quantum chromodynamics. With our Neutrino research we completed, or else brought to a useful state, the following: Data-taking, physics simulations, physics analysis, physics reporting, explorations of matter effects, and detector component fabrication. We conducted our work as participants in the MINOS, NOvA, and LBNE neutrino oscillation experiments and in the MINERvA neutrino scattering experiment. With our Collider research we completed or else brought to a useful state: Data-taking, development of muon system geometry and tracking codes, software validation and maintenance, physics simulations, physics analysis, searches for new particles, and study of top-quark and B-quark systems. We conducted these activities as participants in the ATLAS proton-proton collider experiment at CERN and in the CDF proton-antiproton collider experiment at Fermilab. In our Theory research we developed QCD-based models, applications of spin phenomenology to fundamental systems, fitting of models to data, presenting and reporting of new concepts and formalisms. The overarching objectives of our research work have always been: 1) to test and clarify the predictions of the Standard Model of elementary particle physics, and 2) to discover new phenomena which may point the way to a more unified theoretical framework.
The main goal of this activity is to test the dynamic coupling of the SAS4A/SASSYS-1 (SAS) and CFD models, using a recently patched version of the SAS code intended to address an undocumented limitation that hindered the Versatile Test Reactor (VTR) simulation efforts in FY21. As described in previous VTR calculation reports, the undocumented limitation in SAS v5.4 does not allow the user to activate the CFD coupling option during restart calculations. Since the analysts were unaware of this limitation, prior SAS-CFD simulation results for the protected station blackout (PSBO) transient were erroneous. Root-cause analysis was performed to determine the cause of this undocumented limitation in SAS v5.4, the SAS software was updated in a new patch, and the SAS-CFD simulations were repeated with this patched software. The results of the SAS-CFD simulations documented in this report show that the software patch does address the cited issue, and that the patched software indeed supports the activation of the CFD coupling model in restart calculations. The SAS development team will determine the schedule for implementing the patch in an official software release. This report documents updated SAS-CFD simulations of the PSBO transient response in the VTR. The hot pool is modeled with the CFD code STAR-CCM+, which is coupled at the flow boundaries to the SAS model of the primary heat transport system. SAS computes the mass flow rate and temperature at each core subassembly outlet, the thermal insulation cavity bypass, and the IHX inlet windows. CFD in turn computes the absolute pressure and temperature at each of these boundaries. The SAS code will ignore the temperature data at flow boundaries where flow is directed into the hot pool, i.e., at the core subassembly outlets unless flow reversal occurs. Similarly, CFD will ignore temperature data at boundaries where the flow is directed out of the hot pool, i.e., at the IHX inlets except under flow reversal. The focus of this work is to ensure that the SAS software patch addresses the undocumented limitation described in prior VTR calculation reports, rather than the accurate assessment of thermal stratification in the VTR during protected transients. This motivates the development of a new, simplified CFD model with a coarser mesh to accelerate the testing process. The updated model, and simplifying assumptions, are documented in this report. In future work, the thermal stratification assessment should be performed in more detail. The simplified CFD model can be improved by performing grid convergence studies sensitivity studies of turbulence parameters (e.g., Prandtl number, turbulence production and dissipation parameters) on temperature distributions and thermal stratification.
This report provides documentation for the completion of the Sandia portion of the ASC Level II Visualization on the platform milestone. This ASC Level II milestone is a joint milestone between Sandia National Laboratories and Los Alamos National Laboratories. This milestone contains functionality required for performing visualization directly on a supercomputing platform, which is necessary for peta-scale visualization. Sandia's contribution concerns in-situ visualization, running a visualization in tandem with a solver. Visualization and analysis of petascale data is limited by several factors which must be addressed as ACES delivers the Cielo platform. Two primary difficulties are: (1) Performance of interactive rendering, which is most computationally intensive portion of the visualization process. For terascale platforms, commodity clusters with graphics processors(GPUs) have been used for interactive rendering. For petascale platforms, visualization and rendering may be able to run efficiently on the supercomputer platform itself. (2) I/O bandwidth, which limits how much information can be written to disk. If we simply analyze the sparse information that is saved to disk we miss the opportunity to analyze the rich information produced every timestep by the simulation. For the first issue, we are pursuing in-situ analysis, in which simulations are coupled directly with analysis libraries at runtime. This milestone will evaluate the visualization and rendering performance of current and next generation supercomputers in contrast to GPU-based visualization clusters, and evaluate the performance of common analysis libraries coupled with the simulation that analyze and write data to disk during a running simulation. This milestone will explore, evaluate and advance the maturity level of these technologies and their applicability to problems of interest to the ASC program. Scientific simulation on parallel supercomputers is traditionally performed in four sequential steps: meshing, partitioning, solver, and visualization. Not all of these components are necessarily run on the supercomputer. In particular, the meshing and visualization typically happen on smaller but more interactive computing resources. However, the previous decade has seen a growth in both the need and ability to perform scalable parallel analysis, and this gives motivation for coupling the solver and visualization.
Residential building energy simulations are increasingly used for energy-efficient building design, codes and standards analysis, home certifications and ratings, utility programs, and technology assessments. Various software tools exist to perform residential building simulations, and these tools often use different models, inputs, and assumptions. This leads to inconsistencies that can undermine confidence in the predicted results. Validation of these tools can increase confidence by ensuring their accuracy and consistency. One way to validate simulation tools is through empirical testing, which compares predicted energy usage to measured utility billing data. This paper describes the process of data collection, data standardization, and empirical validation, and illustrates its use with our residential EnergyPlus (R)-based software. The data and process can be extended to other simulation tools and contribute to improving residential building simulations more broadly.
Voltage Reduction (CVR) is the reduction of energy consumption resulting from a reduction of the service voltage. While there have been numerous CVR deployments in North America, there has been little substantive analytic analysis of the effect; the majority of the published results are based on empirical field measurements. Due to the lack of analytic study, it is difficult to determine the impacts of CVR outside of sites that have conducted demonstration projects. This panel paper will examine a framework for the analysis of CVR using the open source software package GridLAB-D. An open source simulation environment is used to highlight the effectiveness of open source software programs and their ability to be used for evaluating multi-disciplinary smart grid technologies.
Hydrological models and geophysical measurements are widely used tools for understanding subsurface hydrological processes relevant to water resource management, yet they typically remain disconnected due to technical barriers. We present PyHydroGeophysX, an open-source Python platform bridging this gap by providing standardized interfaces between hydrological modeling software (MODFLOW, ParFlow) and geophysical simulation tools (PyGIMLi, SimPEG). The platform implements bidirectional workflows: translating hydrological outputs into simulated geophysical responses through petrophysical models, and extracting hydrological information from geophysical inversions. Key features include bidirectional workflow modules, configurable petrophysical models, time-lapse inversion with temporal regularization, parallel computing, and mesh utilities for property transfer between geophysical and hydrological grids. The modular architecture of PyHydroGeophysX enables researchers to incorporate additional models and methods, fostering broader adoption of integrated hydrogeophysical approaches. The software is freely available on GitHub and is intended for researchers and practitioners working at the intersection of hydrology and geophysics.
NREL has developed a software tool to enable Renewance to estimate the degradation of batteries from basic information such as the type of battery and the application of that battery during its first life, so that used batteries may be evaluated for potential repurposing at low cost. This software tool utilizes NREL's BLAST-Lite battery degradation modeling code, which was updated with additional models for commercially produced lithium-ion batteries as a part of this CRADA. The software tool enables users to input details such as battery type and application so that lifetime estimates can be made without any programming or expert battery knowledge. The application input loads in saved values for parameters such as cycles per year, depth-of-discharge, and other battery operating parameters from a file defined by Renewance. These parameters may be modified to refine simulations for specific batteries. The software tool also incorporates a degradation model optimization tool, whereby existing battery degradation models may be tuned according to measured battery health. This ensures that new models still predict degradation behaviors expected from a certain battery chemistry, but with the overall degradation rate tuned to a specific battery make and model. The new model can then be saved for estimating the degradation of other similar batteries. An additional task was planned to utilize machine-learning to enable battery health diagnosis from rapid EIS measurements to accelerate the screening of used batteries. This task was not completed due to lack of available data for training a machine-learning model. CRADA benefit to DOE, Participant, and US Taxpayer: Further development of open-source software tool BLAST-Lite for predicting the lifetime of commercially produced Lithium-ion batteries (NREL SWR-22-69).