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At least 775 records · Page 43

On Parallelizing Single Dynamic Simulation Using HPC Techniques and APIs of Commercial Software

Time-domain simulations are heavily used in today’s planning and operation practices to assess power system transient stability and post-transient voltage/frequency profiles following severe contingencies to comply with industry standards. Because of the increased modeling complexity, it is several times slower than real time for state-of-the-art commercial packages to complete a dynamic simulation for a large-scale model. With the growing stochastic behavior introduced by emerging technologies, power industry has seen a growing need for performing security assessment in real time. This paper presents a parallel implementation framework to speed up a single dynamic simulation by leveraging the existing stability model library in commercial tools through their application programming interfaces (APIs). Several high performance computing (HPC) techniques are explored such as parallelizing the calculation of generator current injection, identifying fast linear solvers for network solution, and parallelizing data outputs when interacting with APIs in the commercial package, TSAT. The proposed method has been tested on a WECC planning base case with detailed synchronous generator models and exhibits outstanding scalable performance with sufficient accuracy.

Diao, Ruisheng↗

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗

TaskAMR

TaskAMR is a Cartesian Block Adaptive Mesh Refinement (AMR) code, written using the Regent/Legion parallel programming system, that solves Finite Volume calculations. We provide implementations for linear advection and gas dynamics.

Pietarila, Jonathan↗

Latent Variable Network Modeling

lvnm Is a library for fitting latent variable network models within the R programming language. The code focuses on the Stochastic Block Model, Weighted Stochastic Block Model, and Dynamic Stochastic Block Model. Features include simulation methods, estimation methods, diagnostic plots and anomaly detection routines for network data.

Dabbs, Beau↗

Status Report on FY2022 Model Development within the Integrated Energy Systems HYBRID Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of a pebble bed high temperature gas reactor (HTGR), liquid air energy storage (LAES), and compressed air energy storage (CAES) in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to flexibly operate in ways consistent with IES operation expectations. When these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multi-Fidelity Stochastic Economic Dispatch for Operating Low Carbon Power Grids

Grid operators can address the inherently stochastic nature of renewables by solving a two-stage stochastic programming model that minimizes the cost of dispatch decisions while accounting for the complex grid dynamics. It is common to use a sample average approximation to estimate the expectation of the second stage costs in this model. However, the large sample count needed for numerical accuracy makes effective modeling large-scale electric grids computationally intractable. We introduce a control variate multi-fidelity estimator for the second-stage recourse that enables high quality dispatch decisions in real-time with a reduced computational burden. We obtain a hierarchy of model fidelities by linearizing the AC power flow system representation to DC power flow, and by relaxing transmission and voltage network constraints. We evaluate the performance of our proposed method on a synthetic grid with 73 buses against a deterministic baseline with persistence forecast and a high-fidelity reference. Our analysis shows a computational speed-up of 7.62x with a minimal loss in accuracy. The multi-fidelity method is well suited to fidelity combinations that use a simplified network topology in their lower fidelity model and is an attractive option for applications where accurate grid modeling needed on a limited computational budget.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Follow-On Status Report on FY2022 Model Development within the Integrated Energy Systems Hybrid Repository

This publication details newly created energy storage and reactor models developed within the HYBRID modeling repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of a pebble bed high temperature gas reactor (HTGR), compressed air energy storage (CAES), and Modelica standard library based two-tank sensible heat storage (SHS) in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to flexibly operate in ways consistent with IES operation expectations. When these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Briefing Book: Office of Experimental Sciences

Key to OES science is the advancement of experimental capabilities and vibrant partnerships with other elements of NNSA’s Defense Programs. OES fosters an experimental portfolio that spans the space from small scale studies utilizing tabletop instruments through complex and dynamic high energy density; hydrodynamic; and subcritical experiments on flagship national facilities like Los Alamos Neutron Science Center (LANSCE), National Ignition Facility (NIF), Z machine at Sandia National Laboratories, Dual Axis Radiographic Hydrodynamic Test (DARHT), and the U1a Complex in Nevada. Essential to meeting the deterrence challenges that drive OES is a functional strategy for integration of OES with Defense Programs pursuits in modeling and simulation, engineering and technology maturation, and stockpile and production modernization.

42 ENGINEERING↗

Symposium: Quantum Theory, Quantum Materials, Quantum Computing (Final Report, DE-SC0022551)

Quantum mechanics is fundamental to understanding, predicting, and controlling many physical processes in a vast range of scientific and technological areas. In molecules and materials, the quantum mechanics of Coulombic many-body systems determines far more than the ground state and bulk properties. Quantum mechanics governs magnetism, electron and spin transport, chemical reactions and catalysis, superconductivity, photosynthesis, etc. Each plays a vital role in modern society. As digital technologies push both temporal and length-scale limits, fundamental quantum principles become the current focus for a new class of technologies: quantum computing, quantum sensing, quantum encryption, etc. This oncoming quantum information sciences wave is manifest recently in frontier foci of all six Department of Energy Office of Science programs. The Sanibel Symposium offers a proven, influential platform for facilitating and advancing cross-fertilization among theoretical and computational chemists and physicists, computer scientists, and materials engineers. The Symposia have a long, successful record of driving progress on theory and computation of materials, nanostructures, and their molecular constituents. The Symposia thus are well-suited for advancing the quantum information science thrust in the Office of Basic Energy Sciences (BES). With that QIS thrust as the focus, we propose five sessions of the 61st Sanibel Symposium on the theme Quantum Theory, Quantum Materials, Quantum Computing. From a longer perspective, this thematic program for 2022 is the second year of a five year plan of program segments addressed at challenges in quantum information sciences and quantum materials. The rest of the Symposium program will be of considerable relevance, with, for example, sessions on quantum molecular and material dynamics, and new directions in coupled cluster theory. New ideas for methods and applications can be expected to emerge from the stimulus of the formal presentations and informal discussions. The proposed award is targeted at students, post-docs, and junior scientists. Conscious effort, characteristic of the Sanibel Symposia, to stimulate the participation of women and under-represented minorities will continue.

36 MATERIALS SCIENCE↗

Nano Filters for Selective Metal Capture (CRADA Final Report)

As part of the Cyclotron Road program, Sunchem investigated novel nanoporous materials and their metal extraction performance in both batch and dynamic continuous flow operations. The proposed project developed novel nanoporous materials for selective metal extraction from complex industrial mixtures. The technical objectives were to synthesize and characterize the nanoporous materials, structure the nanoporous materials with binders along with structuring techniques and evaluate its performance in both a batch and dynamic continuous flow operation. The nanoporous material was structured through a disc granulation method to obtain particles in the size range of 250 to 500 micron diameter. This structured material was packed into a continuous flow column which achieved up to 48 wt% of gold capture. This work aimed to address the key technical risk of the materials’ capability to be employed in an industrial operation with competitive performance compared to other adsorbents.

36 MATERIALS SCIENCE↗

Drosophila Nanos acts as a molecular clamp that modulates the RNA-binding and repression activities of Pumilio

Collaboration among the multitude of RNA-binding proteins (RBPs) is ubiquitous, yet our understanding of these key regulatory complexes has been limited to single RBPs. We investigated combinatorial translational regulation by Drosophila Pumilio (Pum) and Nanos (Nos), which control development, fertility, and neuronal functions. Our results show how the specificity of one RBP (Pum) is modulated by cooperative RNA recognition with a second RBP (Nos) to synergistically repress mRNAs. Crystal structures of Nos-Pum-RNA complexes reveal that Nos embraces Pum and RNA, contributes sequence-specific contacts, and increases Pum RNA-binding affinity. Nos shifts the recognition sequence and promotes repression complex formation on mRNAs that are not stably bound by Pum alone, explaining the preponderance of sub-optimal Pum sites regulated in vivo . Our results illuminate the molecular mechanism of a regulatory switch controlling crucial gene expression programs, and provide a framework for understanding how the partnering of RBPs evokes changes in binding specificity that underlie regulatory network dynamics.

Weidmann, Chase A.↗

Spatial description of dislocation nucleation in the shock response of single-crystal aluminum

Nonequilibrium molecular dynamics simulations of shock loaded single-crystal Al in the $\langle$100$\rangle$, $\langle$110$\rangle$, $\langle$111$\rangle$, and $\langle$123$\rangle$ orientations are conducted to study elastic and plastic shockwave formation and details associated with dislocation activity. A computer vision-based approach is implemented to capture the presence of dislocations and describe their spatial characteristics in the zone of nucleation behind the propagating shockwave. The methodology developed relies on the sequences of images extracted during shock loading that show dislocation activity within a cross section of the sample. Results reveal that the spacing between activated slip systems is orientation dependent and exhibits a modest reduction for the $\langle$100$\rangle$ and $\langle$111$\rangle$ orientations as shock pressure increases. Comparisons are made to existing theoretical models. Such relationships between shock pressure and dislocation activity, extracted from molecular dynamics simulations, can be used to inform higher length scale simulations or modeling of dislocation-based plasticity during shock.

36 MATERIALS SCIENCE↗

Ab initio molecular dynamics study of liquid sodium and cesium up to critical point

Ab initio modeling of liquid metals Na and K is carried out using the program SIESTA. We have determined the parameters of the model (the optimal step, the number of particles, the initial state etc) and calculated a wide range of properties: the total energy, pair correlation function, coefficient of self-diffusion, heat capacity, statistics of Voronoi polyhedra, the density of electronic states up to the critical temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Current Status of Human Resource Training Program for Fostering RIBiomics Professionals

RI-Biomics is a state-of-the-art radiation fusion technology for evaluating in-vivo dynamics such as absorption, distribution, metabolism and excretion (ADME) of new drug candidates and biomaterials using radioisotope (RI), and quantitative evaluation of their efficacy via molecular imaging techniques and animal models. The RI-Biomics center is the sole comprehensive research and experiment complex in Korea that can simultaneously perform the radio-synthesis of drug candidate with radioisotope, analysis, and molecular imaging evaluation with animal model. Molecular imaging techniques, including nuclear imaging (SPECT and PET), near-infrared fluorescent (NIRF) imaging, and magnetic resonance imaging (MRI), are the cutting-edge technologies for evaluating drug candidates. Since they allow in vivo real-time imaging of the diseased site, monitoring the biodistribution of drug and determining the optimal therapeutic efficacy following treatments, we have integrated RI-ADME and molecular imaging to provide useful information for drug evaluation and to accelerate the development of new drugs and biomaterials. The RI-Biomics center was established with total investment of 18 million $ during four years from 2009 to 2012 in order to develop a comprehensive analyzing system using RI for new drug development as an axis for national growth in the next generation. The RI-Biomics center has labeling synthesis facility for the radiosynthesis of drug candidate with radioisotope such as Tc-99m, I-125, I-131, F-18, H-3 and C-14 using hot cell. It also includes RI-general analysis facilities, such as Radio-HPLC, LC/MS, GC/MS, gamma counter that can analyzing the radio-synthesized materials, and animal image analysis facilities that developed small animal imaging equipment such as SPECT/PET/CT, 7 T MRI, in-vivo optical imaging system and others. In order to achieve the system to verify safety and effectiveness of the new drugs using RI, it is necessary to establish a human resource training program for fostering RI-Biomics professionals in the following key fields; (1) Radio-pharmaceuticals synthesis and labeled compound development, (2) Development of RI-ADME in the living object and image assessment technology. Personnel training program that carries out theoretical education and practical training in the field related to RI-Biomics in parallel is being conducted. Internship training for university students has been administered twice already while educational program for the existing professionals in the RI-Biomics field will be carried out during the summer of 2014. The human resource training program for combination of RIADME and different molecular imaging techniques can offer synergistic advantages to facilitate understanding RIADME and fostering RI-ADME professionals. (authors)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗

RAVEN, a New Software for Dynamic Risk Analysis

RAVEN is a generic software driver to perform parametric and probabilistic analysis of code simulating complex systems. Initially developed to provide dynamic risk analysis capabilities to the RELAP-7 code [1] is currently being generalized with the addition of Application Programming Interfaces (APIs). These interfaces are used to extend RAVEN capabilities to any software as long as all the parameters that need to be perturbed are accessible by inputs files or directly via python interfaces. RAVEN is capable to investigate the system response probing the input space using Monte Carlo, grid strategies, or Latin Hyper Cube schemes, but its strength is its focus toward system feature discovery like limit surfaces separating regions of the input space leading to system failure using dynamic supervised learning techniques. The paper will present an overview of the software capabilities and their implementation schemes followed by same application examples.

97 MATHEMATICS AND COMPUTING↗