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DOE OSTI2021

Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization

We discuss the value of collaborative, immersive visualization for the exploration of scientific datasets and review techniques and tools that have been developed and deployed at the National Renewable Energy Laboratory (NREL). We believe that collaborative visualizations linking statistical interfaces and graphics on laptops and high-performance computing (HPC) with 3D visualizations on immersive displays (head-mounted displays and large-scale immersive environments) enable scientific workflows that further rapid exploration of large, high-dimensional datasets by teams of analysts. We present a framework, PlottyVR, that blends statistical tools, general-purpose programming environments, and simulation with 3D visualizations. To contextualize this framework, we propose a categorization and loose taxonomy of collaborative visualization and analysis techniques. Finally, we describe how scientists and engineers have adopted this framework to investigate large, complex datasets.

collaborative visualization↗

DOE OSTI2016

Large eddy simulations of a transcritical round jet submitted to transverse acoustic modulation

This article reports numerical computations of a turbulent round jet of transcritical fluid (low temperature nitrogen injected under high pressure conditions) surrounded by the same fluid at rest under supercritical conditions (high temperature and high pressure) and submitted to transverse acoustic modulations. The numerical framework relies on large eddy simulation in combination with a real-gas description of thermodynamics and transport properties. A stationary acoustic field is obtained by modulating the normal acoustic velocity at the lateral boundaries of the computational domain. This study specifically focuses on the interaction of the jet with the acoustic field to investigate how the round transcritical jet changes its shape and mixes with the surrounding fluid. Different modulation amplitudes and frequencies are used to sweep a range of conditions. When the acoustic field is established in the domain, the jet length is notably reduced and the jet is flattened in the spanwise direction. Two regimes of oscillation are identified: for low Strouhal numbers a large amplitude motion is observed, while for higher Strouhal numbers the jet oscillates with a small amplitude around the injector axis. The minimum length is obtained for a Strouhal number of 0.3 and the jet length increases with increasing Strouhal numbers after reaching this minimum value. The mechanism of spanwise deformation is shown to be linked with dynamical effects resulting from reduction of the pressure in the transverse direction in relation with increased velocities on the two sides of the jet. A propagative wave is then introduced in the domain leading to similar effects on the jet, except that a bending is also observed in the acoustic propagation direction. A kinematic model, combining hydrodynamic and acoustic contributions, is derived in a second stage to represent the motion of the jet centerline. This model captures details of the numerical simulations quite well. These various results can serve to interpret observations made on more complex flow configurations such as coaxial jets or jet flames formed by coaxial injectors.

42 ENGINEERING↗

DOE OSTI2015

Effects of Field of View and Visual Complexity on Virtual Reality Training Effectiveness for a Visual Scanning Task

Virtual reality training systems are commonly used in a variety of domains, and it is important to understand how the realism of a training simulation influences training effectiveness. The paper presents a framework for evaluating the effects of virtual reality fidelity based on an analysis of a simulation’s display, interaction, and scenario components. Following this framework, we conducted a controlled experiment to test the effects of fidelity on training effectiveness for a visual scanning task. The experiment varied the levels of field of view and visual realism during a training phase and then evaluated scanning performance with the simulator’s highest level of fidelity. To assess scanning performance, we measured target detection and adherence to a prescribed strategy. The results show that both field of view and visual realism significantly affected target detection during training; higher field of view led to better performance and higher visual realism worsened performance. Additionally, the level of visual realism during training significantly affected learning of the prescribed visual scanning strategy, providing evidence that high visual realism was important for learning the technique. The results also demonstrate that task performance during training was not always a sufficient measure of mastery of an instructed technique. That is, if learning a prescribed strategy or skill is the goal of a training exercise, performance in a simulation may not be an appropriate indicator of effectiveness outside of training—evaluation in a more realistic setting may be necessary.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Expanding Activity Allocation Models to Daily Activities: Tracking Simulated Agent Trips to Exercise Locations in Clarksville, TN

Exercise facilities have been proven to have numerous physical, mental, and psychological benefits, yet exercise facilities are still inaccessible to a large portion of the population. This study serves to explore the accessibility of fitness centres through geographical, demographic, and temporal lenses through an expansion of the UrbanPop framework that seeks to allocate simulated agents to fitness centres in the Clarksville metro to explore the effects of travel distances on different demographics throughout the week. Findings indicate that senior and retired demographics consistently travel longer distances to exercise in the larger Clarksville area, likely due to tendencies to live further from the center of the metropolitan area. Furthermore, all demographics tend to travel further distances to exercise on the weekends rather than the weekdays, indicating that travel distance can affect likelihood of agents to travel, especially on weekdays when many agents are in the workforce or participating in schooling.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Dynamic modeling and simulation of pressure swing adsorption processes using toPSAil

Pressure swing adsorption (PSA) has attracted significant recent interest for chemical process intensification due to its potential for high energy efficiency and amenability to small, modular designs. However, the lack of simulation tools that are readily available, transparent, and trusted, has been identified as a serious impediment to widespread adoption of PSA, as well as to further research on PSA modeling, numerical solution, optimization, and control. This paper presents a complete framework for dynamic modeling and simulation of PSA processes and its implementation in an open-source simulator called toPSAil. Further, the presentation is tutorial and includes many modeling and implementation details often overlooked in existing literature. Novel methods are presented for handling flow reversals and implementing various pressure–flow relationships, along with controlled boundary conditions. Finally, the code contains several innovations designed to improve efficiency and reduce the extensive trial-and-error tuning often required to produce a working PSA cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Acquire and Test IDAES Framework Components

The cooperation under the Grid Modernization Initiative and the Applied Energy Tri-Laboratory umbrellas requires mutual understanding of capabilities and a common effort to identify gaps existing in the available computational modeling and analysis tools. In this work, we report acquisition and testing of the National Energy Technology Laboratory’s Institute for the Design of Advanced Energy Systems (IDAES) framework, particularly including both electric power systems production cost model simulator Prescient as well as system optimization IDAES itself. Further, we consider the methods in which developments in Prescient and IDAES for grid-energy simulation and optimization may be included in the Framework for Optimization of ResourCes and Economics (FORCE) ecosystem that has been under collaborative development by Idaho National Laboratory, Argonne National Laboratory, and Oak Ridge National Laboratory. We propose two integration methods to introduce Prescient and IDAES into existing FORCE automated workflows. One integration involves using Prescient as a market reduced-order model and IDAES models similar to how existing Modelica models are used. The other integration involves wrapping the Prescient-IDAES dispatch optimization process with the stochastic capacity optimization workflow in FORCE.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Development of a MOOSE thermal model of the MPC-32 canister and HI-STORM overpack

Nuclear power is a significant source of electricity in the United States, but the average age of nuclear power plants is around 40 years old. The safe management of the spent nuclear fuel (SNF) is a key aspect of the back-end of the nuclear fuel cycle. Spent fuel dry storage systems are becoming a popular and effective solution in this area, given the absence of a final disposal system. The spent fuel cask system (dry cask method) provides a feasible solution to maintain spent fuel for 60 years before final disposal. Dry cask storage has many characteristics that make it attractive. It fulfills the safety requirements of the Nuclear Regulatory Commission (NRC) while providing modularity and flexibility to contractors. The HI-STORM overpack and MPC-32 canister are the main parts of the HI-STORM 100 dry cask storage system. These components remove heat from the system using natural circulation, requiring no human intervention. This is the characteristic that provides passive heat removal and low maintenance features in dry cask storage systems. To develop a thermal model for a dry cask storage system, the physics behind the system should be defined clearly. There are two natural circulation loops in the system; circulation of helium cools down the nuclear assemblies in the MPC, while circulation of air cools down the walls of the MPC. This work aims to develop a thermal model of the MPC-32 canister and HI-STORM overpack using the Multiphysics Object-Oriented Simulation Environment (MOOSE). MOOSE is an open-source framework developed by Idaho National Laboratory (INL) for multiscale, multiphysics simulations. In this study, we will investigate and demonstrate the thermal-hydraulics modeling capabilities of the MOOSE framework, including natural circulation, heat transfer, and porous flow.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Toward a Climate OSSE Framework for Satellite Mission Design

The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here, we outline a new framework for climate OSSEs that leverages the use of machine learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA’s GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth’s planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Simulations of space charge neutralization in a magnetized electron cooler

Magnetized electron cooling at relativistic energies and Ampere scale current is essential to achieve the proposed ion luminosities in a future electron-ion collider (EIC). Neutralization of the space charge in such a cooler can significantly increase the magnetized dynamic friction and, hence, the cooling rate. The Warp framework is being used to simulate magnetized electron beam dynamics during and after the build-up of neutralizing ions, via ionization of residual gas in the cooler. The design follows previous experiments at Fermilab as a verification case. We also discuss the relevance to EIC designs.

Gerity, James↗

DOE OSTI2022

Phase transformation path in Aluminum under ramp compression; simulation and experimental study

Abstract We present a framework based on non-equilibrium molecular dynamics (NEMD) to reproduce the phase transformation event of Aluminum under ramp compression loading. The simulated stress-density response, virtual x-ray diffraction patterns, and structure analysis are compared against the previously observed experimental laser-driven ramp compression in-situ x-ray diffraction data. The NEMD simulations show the solid–solid phase transitions are consistent to experimental observations with a close-packed face-centered cubic (fcc) (111), hexagonal close-packed (hcp) structure (002), and body-centered cubic bcc (110) planes remaining parallel. The atomic-level analysis of NEMD simulations identifiy the exact phase transformation pathway happening via Bain transformation while the previous in situ x-ray diffraction data did not provide sufficient information for deducing the exact phase transformation path.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Hybrid Programming for Near-Term Quantum Computing Systems

Recent computations involving quantum processing units (QPUs) have demonstrated a series of challenges inherent to hybrid classical-quantum programming, compilation, execution, and verification and validation. Despite considerable progress, system-level noise, limited low-level instructions sets, remote access models, and an overall lack of portability and classical integration presents near-term programming challenges that must be overcome in order to enable reliable scientific quantum computing and support robust hardware benchmarking. In this work, we draw on our experience in programming QPUs to identify common concerns and challenges, and detail best practices for mitigating these challenges within the current hybrid classical-quantum computing paradigm. Following this discussion, we introduce the XACC quantum compilation and execution framework as a hardware and language independent solution that addresses many of these hybrid programming challenges. XACC supports extensible methodologies for managing a variety of programming, compilation, and execution concerns across the increasingly diverse set of QPUs. We use recent nuclear physics simulations to illustrate how the framework mitigates programming, compilation, and execution challenges and manages the complex workflow present in QPU-enhanced scientific applications. Finally, we codify the resulting hybrid scientific computing workflow in order to identify key areas requiring future improvement.

Mccaskey, Alex↗

DOE OSTI2020

Union: An Automatic Workload Manager for Accelerating Network Simulation

With the rapid growth of the machine learning applications, the workloads of future HPC systems are anticipated to be a mix of scientific simulation, big data analytics, and machine learning applications. Simulation is a great research vehicle to understand the performance implications of co-running scientific applications with big data and machine learning workloads on large-scale systems. In this paper, we present Union, a workload manager that provides an automatic framework to facilitate hybrid workload simulation in CODES. Furthermore, we use Union, along with CODES, to investigate various hybrid workloads composed of traditional simulation applications and emerging learning applications on two dragonfly systems. The experiment results show that both message latency and communication time are important performance metrics to evaluate network interference. Network interference on HPC applications is more reflected by the message latency variation, whereas ML application performance depends more on the communication time.

heterogeneous workloads↗

DOE OSTI2020

Janus: A Python Package for Agent-Based Modeling of Land Use and Land Cover Change

Janus is an open source Python package for agent-based modeling (ABM) of land use and land cover change (LULCC). Many ABMs of LULCC have been created across platforms, some of which are not ideal for large scale, high resolution scenarios. This model provides a simple object-oriented framework for creating ABMs specific to LULCC. The organizational philosophy of the modeling framework is to create software objects (agents) that are associated with specific and contextual attributes which are isolated from where those agents exist in the spatial setting of the model, yet provide clear linkages between the agent, their environment, and other agents in the simulation. In this way, the framework allows for assembly of LULCC ABMs with low (programmatic) overhead, making the models extensible and providing clear mechanisms for integrating them with process-oriented biophysical models. Provided with Janus is a suite of geospatial data preprocessing tools that can use arbitrary land cover products as an input. Crop choice decisions are based on potential crop prices, these can be created synthetically, or drawn from integrated human-Earth systems models such as the GCAM. Janus is publicly accessible through GitHub and provides an example dataset for testing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Solving complex maintenance planning optimization problems using stochastic simulation and multi-criteria fuzzy decision making

One of the most important factors in the operations of many cooperations today is to maximize profit and one important tool to that effect is the optimization of maintenance activities. Maintenance activities is at the largest level divided into two major areas, corrective maintenance (CM) and preventive maintenance (PM). When optimizing maintenance activities, by a maintenance plan or policy, we seek to find the best activities to perform at each point in time, be it PM or CM. We explore the use of stochastic simulation, genetic algorithms and other tools for solving complex maintenance planning optimization problems in terms of a suggested framework model based on discrete event simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2013

North Pacific Mesoscale Coupled Air-Ocean Simulations Compared with Observations

Executive summary The main objective of the study was to investigate atmospheric and ocean interaction processes in the western Pacific and, in particular, effects of significant ocean heat loss in the Kuroshio and Kuroshio Extension regions on the lower and upper atmosphere. It is yet to be determined how significant are these processes are on climate scales. The understanding of these processes led us also to development of the methodology of coupling the Weather and Research Forecasting model with the Parallel Ocean Program model for western Pacific regional weather and climate simulations. We tested NCAR-developed research software Coupler 7 for coupling of the WRF and POP models and assessed its usability for regional-scale applications. We completed test simulations using the Coupler 7 framework, but implemented a standard WRF model code with options for both one- and two-way mode coupling. This type of coupling will allow us to seamlessly incorporate new WRF updates and versions in the future. We also performed a long-term WRF simulation (15 years) covering the entire North Pacific as well as high-resolution simulations of a case study which included extreme ocean heat losses in the Kuroshio and Kuroshio Extension regions. Since the extreme ocean heat loss occurs during winter cold air outbreaks (CAO), we simulated and analyzed a case study of a severe CAO event in January 2000 in detail. We found that the ocean heat loss induced by CAOs is amplified by additional advection from mesocyclones forming on the southern part of the Japan Sea. Large scale synoptic patterns with anomalously strong anticyclone over Siberia and Mongolia, deep Aleutian Low, and the Pacific subtropical ridge are a crucial setup for the CAO. It was found that the onset of the CAO is related to the breaking of atmospheric Rossby waves and vertical transport of vorticity that facilitates meridional advection. The study also indicates that intrinsic parameterization of the surface fluxes within the WRF model needs more evaluation and analysis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Simulation Study of High-Precision Characterization of MeV Electron Interactions for Advanced Nano-Imaging of Thick Biological Samples and Microchips

The resolution of a mega-electron-volt scanning transmission electron microscope (MeV-STEM) is primarily governed by the properties of the incident electron beam and angular broadening effects that occur within thick biological samples and microchips. A precise understanding and mitigation of these constraints require detailed knowledge of beam emittance, aberrations in the STEM column optics, and energy-dependent elastic and inelastic critical angles of the materials being examined. This simulation study proposes a standardized experimental framework for comprehensively assessing beam intensity, divergence, and size at the sample exit. This framework aims to characterize electron-sample interactions, reconcile discrepancies among analytical models, and validate Monte Carlo (MC) simulations for enhanced predictive accuracy. Our numerical findings demonstrate that precise measurements of these parameters, especially angular broadening, are not only feasible but also essential for optimizing imaging resolution in thick biological samples and microchips. By utilizing an electron source with minimal emittance and tailored beam characteristics, along with amorphous ice and silicon samples as biological proxies and microchip materials, this research seeks to optimize electron beam energy by focusing on parameters to improve the resolution in MeV-STEM/TEM. This optimization is particularly crucial for in situ imaging of thick biological samples and for examining microchip defects with nanometer resolutions. Our ultimate goal is to develop a comprehensive mapping of the minimum electron energy required to achieve a nanoscale resolution, taking into account variations in sample thickness, composition, and imaging mode.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Hamiltonian simulation in Zeno subspaces

Here, we investigate the quantum Zeno effect as a framework for designing and analyzing quantum algorithms for Hamiltonian simulation. We show that frequent projective measurements of an ancilla qubit register can be used to simulate quantum dynamics on a target qubit register with a circuit complexity similar to randomized approaches. The classical sampling overhead in the latter approaches is traded for ancilla qubit overhead in Zeno-based approaches. A second-order Zeno sequence is developed to improve scaling and implementations through unitary kicks are discussed. We derive rigorous error bounds that allow for identifying the associated circuit complexities for the first- and second-order Zeno sequences. We show that the circuits over the combined register can be identified as a subroutine commonly used in post-Trotter Hamiltonian simulation methods. We build on this observation to reveal connections between different Hamiltonian simulation algorithms.

Hamiltonian simulation↗

DOE OSTI2022

ANS MultiApps tutorial

The Multiphysics Object-Oriented Simulation Environment (MOOSE) [1] is an open-source, parallel finite element framework which provides the foundation formany advanced modeling and simulation tools developed under the Department of Energy’s (DOE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [2] for the analysis of advanced reactors. The MOOSE framework provides the common foundational capability on which many NEAMS codes for reactor analysis are built. The MOOSE framework also includes several systems to assemble unique workflows and coupling amongMOOSE-based applications. In particular, the MultiApp and Transfer systems are widely used to assemble different MOOSE-based or MOOSE- wrapped physics applications together to perform loosely or tightly coupled multiphysics simulations. The National Reactor Innovation Center’s (NRIC’s) Virtual Test Bed (VTB) [3] hosts publicly available nuclear reactor multiphysics simulation examples which leverage MOOSE’s MultiApp system to meet the modeling needs of different reactor types. The flexibility and robustness of coupling provided by MOOSE permits rapid development of coupled physics models for a wide range of reactor types and events.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗