An Artificial Intelligent Bot that Hacks Simulated Cyber-Physical Networks in the Power Grid
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Fragkos, Georgios↗
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Results for “Network 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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Bridging the Gap between Cosmological Simulations with Graph Neural Networks and Domain Adaptation
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Roncoli, Andrea↗
Synthetic Data Generation for High-Fidelity HPC Healthcare Simulation: Beneficiary-Provider Network Example (WIP)
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Agent-based↗
A novel approach to exponential speedup of simulation events in wireless networks.
Abstract not provided.
Onunkwo, Uzoma↗
A Novel Approach to Exponential Speedup of Simulation Events in Wireless Networks.
Abstract not provided.
Onunkwo, Uzoma↗
HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks
This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation
As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the model size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.
interconnection networks↗
Discrete Fracture Network Modeling to Estimate Upscaled Parameters for the Topopah Spring, Lava Flow, and Tiva Canyon Aquifers at Pahute Mesa, Nevada National Security Site
This report describes the results of Discrete Fracture Network (DFN) simulations for the Topopah Spring Aquifer (TSA), Lava Flow Aquifer, and Tiva Canyon Aquifer (TCA), at Pahute Mesa on the Nevada National Security Site (NNSS), formerly the Nevada Test Site. The research focuses on calculating upscaled groundwater flow and contaminant transport parameters using DFNs generated according to fracture characteristics observed in the TSA, LFA and TCA at Pahute Mesa. The highly fractured and heterogeneous nature of these aquifers makes them candidates for stochastic DFN modeling of radionuclide transport on a small scale with subsequent upscaling. One hundred independent DFN realizations are generated for each aquifer, and the upscaled parameters for continuum simulations of subsurface flow and transport in fractured media at Pahute Mesa are calculated. Our goal is to implement a modeling approach that can translate parameters to larger-scale models that account for local-scale flow and transport processes, such as channelization of flow and transport along a few well connected, large fractures. Additionally, to simulate advective and advective-diffusive transport through the fracture networks, the Time Domain Random Walk (TDRW) approach is applied to account for matrix diffusion into a finite half-space. Moreover, a novel approach to calculate dynamic (active) fracture surface area to reflect flow channeling is implemented. This work will improve the representation of radionuclide transport processes in largescale, regulatory-focused models by providing estimates of hard-to-measure flow and contaminant transport parameters at large scales. In this report, we (1) show recent results of flow and transport simulations on multiple DFN realizations of the TSA, LFA, TCA; (2) discuss the resulting distributions of estimated upscaled parameters; (3) describe the estimation of upscaled parameters for an equivalent parallel-plate continuum model and (4) present a comparison between simulated transport from the equivalent continuum model and an actual DFN.
54 ENVIRONMENTAL SCIENCES↗
Gaseous flow through heterogeneous, partially connected networks of pipes
Simulations of flow of an ideal gas through heterogeneous simple cubic pipe networks with different pipe radius distributions and variable bond coordination numbers were performed. Networks with monomodal and bimodal radius distributions were constructed. A very wide range of Knudsen numbers was achieved. Flow simulations of purely viscous gases and incompressible liquids were also carried out for comparison. The permeability to gas in the purely viscous regime was larger than the permeability to an incompressible liquid. Based on a variety of computational tests, this result was likely not a numerical artifact. The simulated macroscopic flow behavior differed from the underlying single pipe model, depending on the radius distribution, network connectivity and magnitude of the externally applied pressure gradient, and was compatible with the Klinkenberg analysis only when the maximum Knudsen number used in each simulation was lower than 1. In this condition, the Klinkenberg coefficient was nearly proportional to the inverse of the network hydraulic radius while the effect of the radius distribution was weak and that of the network connectivity essentially negligible. Here, the bimodal simulations displayed a typical percolation behavior, with the Klinkenberg coefficient remaining constant as long as the large pipe population was connected.
42 ENGINEERING↗
Probing black hole microstate evolution with networks and random walks
We model black hole microstates and quantum tunneling transitions between them with networks and simulate their time evolution using well-established tools in network theory. In particular, we consider two models based on Bena-Warner three-charge multi-centered microstates and one model based on the D1-D5 system; we use network theory methods to determine how many centers (or D1-D5 string strands) we expect to see in a typical late-time state. We find three distinct possible phases in parameter space for the late-time behaviour of these networks, which we call ergodic, trapped, and amplified, depending on the relative importance and connectedness of microstates. We analyze in detail how these different phases of late-time behavior are related to the underlying physics of the black hole microstates. Our results indicate that the expected properties of microstates at late times cannot always be determined simply by entropic arguments; typicality is instead a highly non-trivial, emergent property of the full Hilbert space of microstates.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Analysis of Hybrid Smart Grid Communication Network Designs for Distributed Energy Resources Coordination
The rapid growth of distributed energy resources (DERs) has prompted increasing interest in the monitoring and control of DERs through hybrid smart grid communications. This paper develops a new method to investigate the impact of DER penetrations and applications on hybrid communications network designs. A suite of hybrid communications simulation models are developed using Network Simulator 3 (ns-3). The smart grid communications topologies with different DER penetrations are built on the utility-scale distribution grid. The simulation results show that (i) with increasing photovoltaic penetrations, nine hybrid communications designs achieve the expected latency albeit with higher packet loss rate; and (ii) both BPLC-Ethernet and BPLC-WiMAX designs can accommodate the DER applications with a high data rate up to 100 Mbps.
24 POWER TRANSMISSION AND DISTRIBUTION↗
NetFlow Dynamics
NetFlow Dynamics is a web-accessible analysis environment for simulating dynamic flows of materials on model networks. Performing a simulation requires both the NetFlow Dynamics application and a network model which is a description of the structure of the nodes and edges of a network including the flow capacity of each edge and the storage capacity of each node, and the sources and sinks of the material flowing on the network. NetFlow Dynamics consists of databases for storing network models, algorithms to calculate flows on networks, and a GIS-based graphical interface for performing simulations and viewing simulation results. Simulated flows are dynamic in the sense that flows on each edge of the network and inventories at each node change with time and can be out of equilibrium with boundary conditions. Any number of network models could be simulated using Net Flow Dynamics. To date, the models simulated have been models of petroleum infrastructure. The main model has been the National Transportation Fuels Model (NTFM), a network of U.S. oil fields, transmission pipelines, rail lines, refineries, tank farms, and distribution terminals. NetFlow Dynamics supports two different flow algorithms, the Gradient Flow algorithm and the Inventory Control algorithm, that were developed specifically for the NetFlow Dynamics application. The intent is to add additional algorithms in the future as needed. The ability to select from multiple algorithms is desirable because a single algorithm never covers all analysis needs. The current algorithms use a demand-driven capacity-constrained formulation which means that the algorithms strive to use all available capacity and stored inventory to meet desired flows to sinks, subject to the capacity constraints of each network component. The current flow algorithms are best suited for problems in which a material flows on a capacity-constrained network representing a supply chain in which the material supplied can be stored at each node of the network. In the petroleum models, the flowing materials are crude oil and refined products that can be stored at tank farms, refineries, or terminals (i.e. the nodes of the network). Examples of other network models that could be simulated are currency flowing in a financial network, agricultural products moving to market, or natural gas flowing on a pipeline network.
Corbet Jr., Thomas F↗
Structure Development in Cross-Linked, Soybean Oil-based Waterborne Polyurethanes
Development of waterborne polyurethanes (WPU) using bio-based sources represents a step towards sustainable materials science and industry. We synthesized bio-based cationic water-dispersed crosslinked polyurethanes from high oleic soybean oil (HOSO) polyol, isophorone diisocyanate, and methyldiethanol amine, with varying ionic group contents after neutralization with acetic acid. Our primary objective was to analyze how crosslinking affects the dispersion process and film properties in multifunctional systems. The synthesis-structure-property relationship is elucidated through comprehensive analyses of the products at different stages of the synthesis. The dispersion of the WPU particles in water must occur prior to gelation during the final preparation, leading to incomplete conversion and the formation of imperfect networks. Insight into the synthesis process and polymer structure was gained by simulating polymer network parameters. Morphological analyses using synchrotron-based X-ray scattering and atomic force microscopy revealed a hierarchical structure within the WPU films. Importantly, all the films prepared in this study, without using coalescence agents, have low water absorption and high water contact angles, demonstrating their potential for textile and leather coatings and other applications.
bio-based polymers↗
MeshGraphNets
A PyTorch implementation of "Learning Mesh-based Simulation with Graph Networks" (Pfaff et al., 2021) to build and train graph neural network surrogates for CFD simulation.
Bartoldson, BrianR.↗
GSAS Tools
SAND2023-06684O GSAS Tools is a web application that manages user access to modeling and simulation tools and promotional material. This software, which is a spiking neural network (SNN) simulator, represents an SNN as a graph of stochastic differential equations and simulates the time-evolution of these equations. It has the capability of reading inputs from file and writing outputs to file, and generally supports experimentation, analysis, and algorithm development using SNNs. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Noel, Todd↗
Device Feasibility Analysis of Multi-level FeFETs for Neuromorphic Computing
As an emerging non-volatile memory device technology, Ferroelectric Field-Effect Transistors (FeFETs) can enable low-power, adaptive intelligent system design. However, device dimension and operating voltage dependent reliability issues of scaled FeFETs can ultimately lead to degraded performance in solving machine learning tasks. In this article, detailed experimental characterization of FeFET devices of different dimensions have been carried out to explicitly evaluate the non-ideal behavior in device conductance programming properties like number of programming states, cycle-to-cycle (C2C) variations, device-to-device (D2D) variations, and state retention. A hardware-aware software simulation approach has been adopted to capture the adversarial effects of the non-idealities on recognition accuracy through algorithm-level performance assessment by including them in NeuroSim, a popular neural network hardware simulator, to execute a neural network model considering all other hardware constraints. With the added non-idealities, significant accuracy degradation has been observed compared to the ideal scenarios where D2D variations play the most critical role. Thereafter, feasibility of a variation-aware training method has been evaluated to tackle the accuracy drop.
42 ENGINEERING↗
Rigidity and soft percolation in the glass transition of an atomistic model of ionic liquid, 1-ethyl-3-methyl imidazolium nitrate, from molecular dynamics simulations—Existence of infinite overlapping networks in a fragile ionic liquid
The typical ionic liquid, 1-ethyl-3-methyl imidazolium nitrate (EMIM-NO{sub 3}), was examined by molecular dynamics simulations of an all-atomistic model to show the characteristics of networks of cages and/or bonds in the course of vitrification of this fragile glass-former. The system shows changes of dynamics at two characteristic temperatures, T{sub B} (or T{sub c}) and the glass transition temperature T{sub g}, found in other fragile glass forming liquids [K. L. Ngai and J. Habasaki, J. Chem. Phys. 141, 114502 (2014)]. On decreasing temperature, the number of neighboring cation-anion pairs, N{sub B}, within the first minimum of the pair correlation function, g(r){sub min}, increases. On crossing T{sub B} (>T{sub g}), the system volume and diffusion coefficient both show changes in temperature dependence, and as usual at T{sub g}. The glass transition temperature, T{sub g}, is characterized by the saturation of the total number of “bonds,” N{sub B} and the corresponding decrease in degree of freedom, F = [(3N − 6) − N{sub B}], of the system consisting of N particles. Similar behavior holds for the other ion-ion pairs. Therefore, as an alternative, the dynamics of glass transition can be interpreted conceptually by rigidity percolation. Before saturation occurring at T{sub g}, the number of bonds shows a remarkable change at around T{sub B}. This temperature is associated with the disappearance of the loosely packed coordination polyhedra of anions around cation (or vice versa), related to the loss of geometrical freedom of the polyhedra, f{sub g}, of each coordination polyhedron, which can be defined by f{sub g} = [(3N{sub V} − 6) − N{sub b}]. Here, 3N{sub v} is the degree of freedom of N{sub V} vertices of the polyhedron, and N{sub b} is number of fictive bonds. The packing of polyhedra is characterized by the soft percolation of cages, which allows further changes with decreasing temperature. The power spectrum of displacement of the central ion in the cage is found to be correlated with the fluctuation of N{sub b} of cation-cation (or anion-anion) pairs in the polyhedron, although the effect from the coordination shells beyond the neighboring ions is not negligible.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗