OpenDSSDirect.py [SWR-17-42]
A Python direct-mode interface to OpenDSS, a distribution system simulator for electric power systems.
Krishnamurthy, Dheepak↗
SEARCH · Engineering Papers
Results for “distributed simulation”
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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OTM-MPI (Open Traffic Models - MPI)
This software is an extension to OTM (Open Traffic Models), which is an open-source traffic simulator maintained at the Institute of Transportation Studies at U.C. Berkeley. OTM-MPI provides functionality for running OTM simulations in distributed computing environments. Its functionality includes min-cut division of traffic networks (using METIS), deployment of sub-networks on multiple compute nodes, and inter-node MPI communications.
Ugirumurera, Juliette↗
OpenDSSDirect.jl
OpenDSSDirect.jl is a cross-platform Julia package implements a "direct" library interface to OpenDSS using dss_capi. OpenDSS is an open-source distribution system simulator. See OpenDSSDirect.py for a similar package in Julia. This package is now available for Windows, Mac, and Linux.
Krishnamurthy, Dheepak↗
Regression of 3D Sky Map to Cosmological Parameters (CosmoFlow) v1.0
The neural network constructed of 3D convolutional and fully connected layers was trained on the simulated mass distribution of the Universe with the purpose to recover the values of cosmological parameters used to generate the Universe.
Balewski, Jan↗
CyMEpy [SWR-21-20]
CYMEpy is a high-level Python package that provides users HELICS bindings for CYMEDIST, CYME’s distribution system simulator.
Latif, Aadil↗
Adaptive Computing (AC) [SWR-24-106]
The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.
Griffin, Kevin [National Renewable Energy Laborato↗
DISTRI: Distributed Multi-Facility HPC Simulator (DISTRI) v2.1
DISTRI is an advanced network simulator designed for multi-facility computational infrastructures with agentic behavior. It simulates HPC facilities where computational resources act as autonomous agents, making intelligent decisions about job scheduling, load balancing, and resource allocation. The simulator focuses on developing and testing decentralized algorithms that promote resilience and efficiency in multi-facility environments. Key Features: - Agentic Resource Behavior: Processors and DTNs act as autonomous agents with decision-making capabilities - Pheromone-Based Load Balancing: Decentralized load balancing inspired by ant colony optimization - Dual Topology Support: Mesh (normal operations) and Dumbell (network testing) topologies - Comprehensive TCP Simulation: Realistic TCP implementations with multiple congestion control algorithms - Failure Resilience Testing: Processor failure simulation with automatic job reassignment - Extensive Visualization: Detailed performance analysis and metrics collection - Research-Ready: Designed for algorithm development and benchmarking
Bez, Jean Luca [Lawrence Berkeley National Laborat↗
Adaptive Computing (AC) (Open Source) [SWR-24-106]
The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly, adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.
Griffin, Kevin [National Laboratory of the Rockies↗
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↗
Statistical ensemble analysis for simulating extrinsic noise-driven response in NF-κB signaling networks
Background: Gene expression profiles and protein dynamics in single cells have a large cell-to-cell variability due to intracellular noise. Intracellular fluctuations originate from two sources: intrinsic noise due to the probabilistic nature of biochemical reactions and extrinsic noise due to randomized interactions of the cell with other cellular systems or its environment. Presently, there is no systematic parameterization and modeling scheme to simulate cellular response at the single cell level in the presence of extrinsic noise. Results: In this paper, we propose a novel statistical ensemble method to simulate the distribution of heterogeneous cellular responses in single cells. We capture the effects of extrinsic noise by randomizing values of the model parameters. In this context, a statistical ensemble is a large number of system replicates, each with randomly sampled model parameters from biologically feasible intervals. We apply this statistical ensemble approach to the well-studied NF-κB signaling system. We predict several characteristic dynamic features of NF-κB response distributions; one of them is the dosage-dependent distribution of the first translocation time of NF-κB. Conclusion: The distributions of heterogeneous cellular responses that our statistical ensemble formulation generates reveal the effect of different cellular conditions, e.g., effects due to wild type versus mutant cells or between different dosages of external stimulants. Distributions generated in the presence of extrinsic noise yield valuable insight into underlying regulatory mechanisms, which are sometimes otherwise hidden.
59 BASIC BIOLOGICAL SCIENCES↗
Validating quantum-classical programming models with tensor network simulations
The exploration of hybrid quantum-classical algorithms and programming models on noisy near-term quantum hardware has begun. As hybrid programs scale towards classical intractability, validation and benchmarking are critical to understanding the utility of the hybrid computational model. In this paper, we demonstrate a newly developed quantum circuit simulator based on tensor network theory that enables intermediate-scale verification and validation of hybrid quantum-classical computing frameworks and programming models. We present our tensor-network quantum virtual machine (TNQVM) simulator which stores a multi-qubit wavefunction in a compressed (factorized) form as a matrix product state, thus enabling single-node simulations of larger qubit registers, as compared to brute-force statevector simulators. Our simulator is designed to be extensible in both the tensor network form and the classical hardware used to run the simulation (multicore, GPU, distributed). The extensibility of the TNQVM simulator with respect to the simulation hardware type is achieved via a pluggable interface for different numerical backends (e.g., ITensor and ExaTENSOR numerical libraries). We demonstrate the utility of our TNQVM quantum circuit simulator through the verification of randomized quantum circuits and the variational quantum eigensolver algorithm, both expressed within the eXtreme-scale ACCelerator (XACC) programming model.
97 MATHEMATICS AND COMPUTING↗
Stochastic parametric skeletal dosimetry model for humans: General approach and application to active marrow exposure from bone-seeking beta-particle emitters
The objective of this study is to develop a skeleton model for assessing active marrow dose from bone-seeking beta-emitting radionuclides. This article explains the modeling methodology which accounts for individual variability of the macro- and microstructure of bone tissue. Bone sites with active hematopoiesis are assessed by dividing them into small segments described by simple geometric shapes. Spongiosa, which fills the segments, is modeled as an isotropic three-dimensional grid (framework) of rod-like trabeculae that “run through” the bone marrow. Randomized multiple framework deformations are simulated by changing the positions of the grid nodes and the thickness of the rods. Model grid parameters are selected in accordance with the parameters of spongiosa microstructures taken from the published papers. Stochastic modeling of radiation transport in heterogeneous media simulating the distribution of bone tissue and marrow in each of the segments is performed by Monte Carlo methods. Model output for the human femur at different ages is provided as an example. The uncertainty of dosimetric characteristics associated with individual variability of bone structure was evaluated. An advantage of this methodology for the calculation of doses absorbed in the marrow from bone-seeking radionuclides is that it does not require additional studies of autopsy material. The biokinetic model results will be used in the future to calculate individual doses to members of a cohort exposed to 89,90 Sr from liquid radioactive waste discharged to the Techa River by the Mayak Production Association in 1949–1956. Further study of these unique cohorts provides an opportunity to gain more in-depth knowledge about the effects of chronic radiation on the hematopoietic system. In addition, the proposed model can be used to assess the doses to active marrow under any other scenarios of 90 Sr and 89 Sr intake to humans.
59 BASIC BIOLOGICAL SCIENCES↗
Comparison of Gas Puff Imaging Data in NSTX with the DEGAS 2 Simulation
Gas-Puff-Imaging (GPI) is a two dimensional diagnostic which measures the edge D α light emission from a neutral D 2 gas puff nears the outer mid-plane of NSTX. DEGAS 2 is a 3-D Monte Carlo code used to model neutral transport and atomic physics in tokamak plasmas. In this paper we compare measurements of the Dα light emission obtained by GPI on NSTX with DEGAS 2 simulations of D α light emission for specific experiments. Both the simulated spatial distribution and absolute intensity of the D α light emission agree well with the experimental data obtained between ELMs in H-mode.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Comparison of Gas Puff Imaging Data in NSTX with the DEGAS 2 Simulation
Gas-Puff-Imaging (GPI) is a two dimensional diagnostic which measures the edge D α light emission from a neutral D 2 gas puff nears the outer mid-plane of NSTX. DEGAS 2 is a 3-D Monte Carlo code used to model neutral transport and atomic physics in tokamak plasmas. In this paper we compare measurements of the D α light emission obtained by GPI on NSTX with DEGAS 2 simulations of D α light emission for specific experiments. Both the simulated spatial distribution and absolute intensity of the D α light emission agree well with the experimental data obtained between ELMs in H-mode.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Molecular level structure in water-alcohol mixtures; from shots to pints: L’Chaim!
The two objectives of this work are to look at the molecular level mixing in water-alcohol liquid mixtures and to determine how well the Effective Fragment Potential (EFP) method performs at describing small, heterogenous water-alcohol mixtures. In this work we look both at small clusters, size 2 – 24 molecules, as well as bulk mixtures, 64 or more molecules. For small clusters (2 – 24 molecules), the molecular structure was studied using the EFP method and MP2. Extensive Monte Carlo/simulated annealing (MC/SA) global optimizations were used to locate low energy structures for all water, alcohol, and water-alcohol mixtures. The alcohols studied include the small, straight-chain, primary alcohols: methanol, ethanol, propanol, and 1-butanol as well as the secondary alcohol 2-butanol, and tertiary butanol. It is shown that a number of low energy mixed clusters retain the structural characteristics of the pure clusters. It is also shown that the EFP method performs well at describing small, heterogenous water-alcohol mixtures. The molecular structure in bulk water, alcohol, and water-alcohol mixtures is studied with the EFP method and molecular dynamics simulations. Radial distribution functions are used to analyze structure and to benchmark the EFP method against experimental results. The effect of alcohol concentration and alcohol chain length on the local structure of water is investigated. Preliminary results indicate that the EFP method can potentially model bulk water-alcohol systems well as compared to experiment. Results on the effects of alcohol chain length are forthcoming.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Future Grid State Modeling for Transactive Systems
The simulation design and evaluation of a transactive energy system is contingent on the setting in which it would exist, which could vary significantly with the many drivers that impact the potential future states of the power system. This report summarizes the development of the Transactive Future Grid State (TFGS) model, which is a lightweight capacity expansion model that will support transactive energy research by allowing users to explore alternative future states. The TFGS model determines the long-term generation capacity needs of a given power system that satisfy specified constraints and support a least cost hourly dispatch. This is accomplished by solving a single optimization problem that simultaneously finds the generation fleet with capacity sufficient to meet peak load and the flexibility to meet hourly operational dispatch, all at lowest cost. The TFGS model was applied to a larger ongoing study taking place that will be simulating how distribution system operators (DSOs) could use a transactive energy system to manage distributed energy resources. The larger study, commonly referred to as the DSO+T study, involves two parallel analyses; one that represents the system today and one that represents a future system with a high degree of renewable energy penetration. The TFGS model provided the generation mix of the high renewable base case. As the TFGS model was being used to provide inputs to the DSO+T study, two issues became apparent. First, additional functionality would have been useful, and second, a larger-than-anticipated amount of user inputs and data were required to successfully use the TFGS model. These discoveries have lead to the recommendation of specific functionality that can be added in future development of the tool.
24 POWER TRANSMISSION AND DISTRIBUTION↗
FY2022 Progress on Imbibition Testing in Containment Science
Estimation of two-phase fluid flow properties is important to understand and predict water and gas movement through the vadose zone for agricultural, hydrogeological, and engineering applications, such as for vapor-phase contaminant transport and/or containment of noble gases in the subsurface. In this second progress report of FY22, we present two ongoing activities related to imbibition testing on volcanic rock samples. We present the development of a new analytical solution predicting the temperature response observed during imbibition into dry samples, as discussed in our previous first progress report for FY22. We also illustrate the use of a multi-modal capillary pressure distribution to simulate both early- and late-time imbibition data collected on tuff core that can exhibit multiple pore types. These FY22 imbibition tests were conducted for an extended period (i.e., far beyond the time required for the wetting front to reach the top of the sample), which is necessary for parameter estimation and characterization of two different pore types within the samples.
42 ENGINEERING↗
Simulations Supporting the Development of Northstar's Indirect Beam Parameters Monitoring System
NorthStar Medical Radioisotopes, LLC is planning to produce the important medical radioisotope molybdenum-99 (Mo-99), the parent of technetium-99m (Tc-99m), through photonuclear reactions in molybdenum-100 (Mo-100). In this approach, a target comprising multiple thin disks of enriched molybdenum metal is bombarded with a 40-MeV electron beam. Electrons impinged on the molybdenum target produce bremsstrahlung X-rays that cause the nuclear reaction. Because enriched Mo-100 is expensive, there is a desire to utilize as much beam power as possible to achieve maximum production yield and minimize the size of the target. This requirement leads to very high beam power density (and heat deposition in the target), which creates challenging requirements for the cooling of the target. The critical part of the target is the target window. It separates the high-pressure helium cooled target from the vacuum beamline and the subject of structural and thermal stress. The temperature of the target window is proportional to the energy density deposited by the beam, so it is critical to maintain the desired beam profile on the target window. The feasibility of indirectly monitoring the maximum energy density of the beam on the beam window through beam losses at the main collimator (Collimator) before the production target was verified. A model of the NorthStar beam transport line was constructed for this purpose using MAD-X and Tao/Bmad codes. Beam optics were computed for the standard operational scenario, followed by an investigation involving approximately 400 cases with parameter variations in the last tuning quadrupoles. This was done to assess the correlation between losses in the collimator and the peak energy density on the target. We developed a model to explore the potential application of Optical transition radiation (OTR) for controlling beam parameters in the NorthStar beam delivery system. This model was based on a generic formula derived from the fundamental solution of the inhomogeneous wave equation of the vector potential, and allowed us to consider various surfaces, even those with irregular or random features, using numerical integration. We applied the model to OTR generated by relativistic electrons impacting an Inconel® 718 beam window. We examined cases with different levels of the window’s surface roughness, ranging from 0.5 to 3.0 microns of root square mean (RMS) deviation. The results of the OTR simulations provided distributions of OTR photons that can be used to study the limitations of optical systems for controlling beam parameters.
43 PARTICLE ACCELERATORS↗