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DOE OSTI2012

Award ER25844: Minimizing System Noise Effects for Extreme-Scale Scientific Simulation Through Function Delegation

In software running on distributed computing clusters, time spent on communication between nodes in the cluster can be a significant portion of the overall computation time; background operating system tasks and other computational noise on the nodes of the system can have a significant impact on the amount of time this communication takes, especially on large systems. The research completed in this period has improved understanding of when such noise will have a significant impact. Specifically, it was demonstrated that not just noise on the nodes, but also noise on the network between nodes can have a significant impact on computation time. It was also demonstrated that noise patterns matter more than noise intensity: very regular noise can cause less disruption than lighter (on average) but less regular noise. It was also demonstrated that the effect of noise is more prominent as the speed of the network between nodes is increased. Furthermore, a tracing tool, Netgauge, was improved via our work, and a system simulator, LogGOPSim, was developed; they can be used by application developers to improve performance of their program and by system designers to mitigate the effects of noise by adjusting the noise characteristics of the operating system. Both have been made freely available as open source programs. In the course of developing these tools, we demonstrated weaknesses in existing methodologies for modeling communication, and we introduced a more detailed model, LogGOPS, for simulating systems. Not only were the deleterious effects of noise explored but we have also offered solutions. Our studies of simulations of system noise have led to specific recommendations on tuning systems to mitigate noise. We have also improved existing approaches to mitigating noise. Non-blocking collective communication avoids the effects of noise by letting communication continue simultaneously with computation (thus being non-blocking), so that the delays in communication introduced by noise have a smaller impact on overall computation time. Potentially, noise can be reduced much further by offloading communication tasks to a separate processing element than the operating system is using. We have improved our library LibNBC, which provides an implementation of non-blocking collectives, via this work. During this research, our proposal to include non-blocking collectives (which used LibNBC as a reference implementation) in the upcoming MPI-3 standard was accepted. As MPI is a ubiquitous and important standard for communication in parallel computing, this demonstrates a certain acceptance of the practicality and desirability of non-blocking collectives. Now that non-blocking collectives are a part of the standard we can expect to see optimized platform-specific implementations of non-blocking collectives. Also as part of this work we have also developed a language GOAL (Global Operation Assembly Language) that can be used as a starting point for defining languages to express optimized communication algorithms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Catalyst: Fast and flexible modeling of reaction networks

We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Nuclear Thermal Propulsion Dynamic Modeling with Modelica

Oak Ridge National Laboratory (ORNL) is participating in the nuclear thermal propulsion (NTP) research and development effort supported by the National Aeronautics and Space Administration (NASA). This effort involves collaboration between multiple research groups, representing various government agencies and industry partners. ORNL has developed a Modelica-based modeling package for dynamic system modeling of nuclear reactors called the Transient Simulation Framework of Reconfigurable Models (TRANSFORM). While this software has been successfully demonstrated in simulations of traditional pressurized-water reactors, boiling-water reactors, liquid-metal reactors and molten-salt reactors, it has also been adapted for non-traditional use in modeling hybrid energy systems, and tritium transport. This versatility is being applied to the current NTP project, where specific modules within TRANSFORM are being developed for and applied to transient modeling of the NASA NTP design. This paper presents the current state of the ORNL-NTP model, the utility of TRANSFORM methodologies in NTP transient simulations, the ability to develop NTP-specific modules, and future work for the model.

Rader, Jordan↗

DOE OSTI2022

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↗

DOE OSTI2016

FAST Modularization Framework for Wind Turbine Simulation: Full-System Linearization: Preprint

The wind engineering community relies on multiphysics engineering software to run nonlinear time-domain simulations e.g. for design-standards-based loads analysis. Although most physics involved in wind energy are nonlinear, linearization of the underlying nonlinear system equations is often advantageous to understand the system response and exploit well-established methods and tools for analyzing linear systems. This paper presents the development and verification of the new linearization functionality of the open-source engineering tool FAST v8 for land-based wind turbines, as well as the concepts and mathematical background needed to understand and apply it correctly.

17 WIND ENERGY↗

DOE OSTI2017

Dynamic Analysis of the Next Generation Molten-Salt Breeder Reactor System

The conceptual design of a 1000 MWe two-fluid molten-salt breeder reactor (MSBR) station was performed during 1966-1970 at Oak Ridge National Laboratory (ORNL) with the goal of using the U-233 fuel cycle. This modular design with four reactor modules has an electrical output of 250 MW/module. The abundance of Th-232 was attractive in converting it to U-233 in a thermal breeder reactor. The two-fluid reactor is graphite-moderated 'with a {sup 7}LiF-BeF{sub 2}-UF{sub 4} fuel salt circulated through the core and a {sup 7}LiF-ThF{sub 4}-BeF{sub 2} blanket salt circulated through separate flow channels distributed throughout the core, as well as in a surrounding under-moderated region'. This reactor design has the advantages of not producing Pu isotopes and easy chemical separation of U-233 in the blanket material. The low fuel cost and the graphite replacement cost are attractive for such a design, with an estimated cost of $141/kW at 1968-dollar value. Potential non-proliferation features of MSBR, the low costs of raw materials, and established chemical separation of fission products are important factors in further development of MSBRs as an alternative to current light water reactors. These reactors are often referred to as liquid fluoride thorium reactor (LFTR). The current research on the modeling of the MSBR is based on an earlier work on the preliminary dynamic model of the MSBR concept. Revisions are made to the original model. The physics parameters have been modified for the current modeling effort based on additional information including more recent values of model parameters from and several typographical misprints in equations and values. Details of this effort will be presented in a full follow-up paper. This work presents the detailed nodal models of reactor fluid core, blanket fluid loop, graphite moderator, fuel fluid heat exchanger, and the blanket fluid heat exchanger. A set of simulations has been performed to validate the model using the commercial software MATLAB{sup TM}-Simulink. Simulations were performed for the cases of source perturbation and reactivity perturbation. The model is inherently nonlinear. A description of the MSBR conceptual design, along with a tabulation of relevant system parameters, is presented. The results of simulation demonstrate stable behavior of the MSBR dynamics, temperature feedback effects, and load-following capability of the MSBR system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

MOOSE ProbML: Parallelizable Probabilistic Machine Learning and Uncertainty Quantification Capabilities

The Multiphysics Object Oriented Simulation Environment (MOOSE) is a widely used open- source finite element software for performing multiphysics multiscale simulations in a massively parallel fashion. Recently, the computational team at Idaho National Laboratory (INL) has implemented Probabilistic Machine Learning (ProbML) capabilities in MOOSE—in a parallelized fashion—and enable active learning with large-scale computational models for tasks such as surrogate model development, scale bridging, forward/inverse uncertainty quantification (UQ), Bayesian optimization, etc. This presentation summarizes these developments in MOOSE along with demonstrations on several real applications relevant to nuclear energy. At the fundamental level, samplers like Monte Carlo/Latin Hypercube, variance reduction, parallelized Markov Chain Monte Carlo (MCMC) support uncertainty propagation in both forward and inverse settings. These samplers can be integrated with the Gaussian processes (GP) suite in MOOSE, which offer several variants like scalar GPs, multi-output GPs, and deep GPs, to enable active learning. These GPs can be tuned using gradient-based optimization methods like Adam and its variants or gradient-free methods like the elliptical slice sampler (a variant of MCMC adept under Gaussian settings) for more complex covariance kernels or likelihoods whose gradient computations can be cumbersome. A variety of batch acquisition functions permit parallelized evaluation of the computational model and support different learning objectives with high efficiency like Bayesian inference, global surrogate development, optimization, etc. Furthermore, libtorch integration supports training, evaluation, and re-training of neural networks and other complex machine learning models in active learning settings. The impacts of these developments are shown on several real applications: (1) nuclear fuel inverse UQ and model inadequacy assessment using the Kennedy O’Hagan framework; (2) uncertainty aware surrogate modeling for additive manufacturing to predict field quantities; (3) nuclear reactor rare events analysis; and (4) complex fluid flow prediction using a global surrogate with quantified prediction uncertainty. Finally, the outlook of MOOSE ProbML is discussed for both outer-loop and inner-loop computations in the broad view to accelerate fuels and materials qualification, address gaps in knowledge and data, and assess new reactor/fuel systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2012

Impact of Interface Recombination on Time Resolved Photoluminescence (TRPL) Decays in CdTe Solar Cells (Numerical Simulation Analysis): Preprint

Using Sentaurus Device Software, we analyze how bulk and interface recombination affect time-resolved photoluminescence (TRPL) decays in CdTe solar cells. This modeling analysis could improve the interpretation of TRPL data and increase the possibility of rapid defect characterization in thin-film solar cells. By illuminating the samples with photons of two different wavelengths, we try to deducethe spatial origin of the dominant recombination loss. Shorter-wavelength photons will be more affected by the interface recombination and drift compared to the longer ones. Using the two-wavelength TRPL characterization method, it may be possible to determine whether a specific change in deposition process has affected the properties of interface or the bulk of the absorber.

14 SOLAR ENERGY↗

DOE OSTI2012

Rapid Application Development with OpenStudio: Preprint

This paper presents several case studies of rapidly implemented, audience-specific applications for whole building energy modeling and standards analysis. By tailoring each application to the audience and the task at hand, the required learning curve for new users was greatly reduced. Each case study used OpenStudio, the U.S. Department of Energy's middleware software development kit (SDK).OpenStudio provides an easy interface to the EnergyPlus whole building simulation engine, while extending its capability and providing higher-level functionality such as software interoperability, standards, analysis, and optimization. Each case study is unique in the technology employed to interface with OpenStudio as well as the methods used for user interaction and data presentation. Fourcase studies are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Virtual Engineering of Low-Temperature Conversion

In this work, we present the development of an overarching software framework and supporting multiphysics models to simulate the end-to-end process of biomass conversion. This virtual engineering (VE) software is designed with the goal of accelerating research and development and reducing risk for market-relevant biomass conversion processes. We currently support multiple models, computing paradigms, and fidelities representing the steps of feedstock pretreatment, enzymatic hydrolysis, and bioconversion. Although this VE approach was developed to support a biomass workflow, we have designed each component in a way that allows us to easily support new domains, unit models, and feedstocks. We begin by presenting the user-facing aspects of the VE software and highlight how simulated elements are defined and linked by VE functions. We then present an overview of the high-fidelity computational fluid dynamics (CFD) models developed to support our target domain before segueing into our efforts to develop accurate and fast surrogate models, capturing the salient outcomes from the CFD simulations in a significantly less computationally demanding manner. We then present how VE calculations interface with a commercial techno-economic analysis software, Aspen Plus. We conclude by presenting VE case studies that leverage these methods and discuss how our methods can be extended to support a wide variety of accelerated biofuel commercialization pathways in the future.

biofuel↗

DOE OSTI2020

Modeling Tree Foliage for Microwave Radar Transparency Study

The motivation for this report is to discuss and present some realistic tree models employed in computational electromagnetics (EM) simulations to study foliage penetration (FOPEN) at Ku-band. The detail obtained in these trees is unprecedented in FOPEN modeling since many studies in this area focus on lower frequencies where precise tree parameters are not required due to the associated large wavelengths relative to the tree dimensions. The focus of this study is in the Ku-band range where the wavelength is notably smaller and the details of the trees have more of an influence on EM waves (i.e. scattering, attenuating, reflecting, diffracting etc.). Therefore, explicit tree parameters are modeled. Also, moderate foliage is of most interest because with less dense foliage t here is a higher percentage of Ku-band transmission. The EM wave and foliage interaction s are simulated with the computational electromagnetics (CEM) Altair FEKO software. The realistic tree model s implemented for simulations are created in the computer-aided design (CAD) software Arbaro and the module CADFEKO that is offered in FEKO. Details of these tree models are provided, and EM simulation results will be discussed in a follow-on report

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Twenty Years On!: Updating the IEA BESTEST Building Thermal Fabric Test Cases for ASHRAE Standard 140

ANSI/ASHRAE Standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs applies the IEA BESTEST building thermal fabric test cases and example simulation results originally published in 1995. These software accuracy test cases and their example simulation results, which comprise the first test suite adapted for the initial 2001 version of Standard 140, are approaching their 20th anniversary. In response to the evolution of the state of the art in building thermal fabric modeling since the test cases and example simulation results were developed, work is commencing to update the normative test specification and the informative example results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2013

Twenty Years On!: Updating the IEA BESTEST Building Thermal Fabric Test Cases for ASHRAE Standard 140: Preprint

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2014

SU-F-18C-08: A Validation Study of a Commercially Available Software Package's Absorbed Dose Estimates in a Physical Phantom

Purpose: This study assesses the accuracy of the absorbed dose estimates from CT scans generated by Monte Carlo (MC) simulation using a commercially available radiation dose monitoring software program. Methods: Axial CT studies of an anthropomorphic abdomen phantom with dose bores at a central location and 4 peripheral locations were conducted using a fixed tube current at 120 kV. A 100 mm ion chamber and a 0.6 cc ion chamber calibrated at diagnostic energy levels were used to measure dose in the phantom at each of the 5 dose bore locations. Simulations using the software program's Monte Carlo engine were run using a mathematical model of the anthropomorphic phantom to determine conversion coefficients between the CTDIvol used for the study and the dose at the location of the dose bores. Simulations were conducted using both the software's generic CT beam model and a refined model generated using HVL and bow tie filter profile measurements made on the scanner used for the study. Results: Monte Carlo simulations completed using the generalized beam model differed from the measured conversion factors by an absolute value average of 13.0% and 13.8% for the 100 mm and 0.6 cc ion chamber studies, respectively. The MC simulations using the scanner specific beam model generated conversion coefficients that differed from the CTDIvol to measured dose conversion coefficients by an absolute value average of 7.3% and 7.8% for the 100 mm and 0.6 cc ion chamber cases, respectively. Conclusion: A scanner specific beam model used in MC simulations generates more accurate dose conversion coefficients in an anthropomorphic phantom than those generated with a generalized beam model. Agreement between measured conversion coefficients and simulated values were less than 20% for all positions using the universal beam model.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2011

Simulation of Distortion and Residual Stress Development During Heat Treatment of Steel Castings

Heat treatment and associated processing, such as quenching, are critical during high strength steel casting production. These processes must be managed closely to prevent thermal and residual stresses that may result in distortion, cracking (particularly after machining), re-work, and weld repair. The risk of casting distortion limits aggressive quenching that can be beneficial to the process and yield an improved outcome. As a result of these distortions, adjustments must be made to the casting or pattern design, or tie bars must be added. Straightening castings after heat treatments can be both time-consuming and expensive. Residual stresses may reduce a casting's overall service performance, possibly resulting in catastrophic failure. Stress relieving may help, but expends additional energy in the process. Casting software is very limited in predicting distortions during heat treatment, so corrective measures most often involve a tedious trial-and-error procedure. An extensive review of existing heat treatment residual stress and distortion modeling revealed that it is vital to predict the phase transformations and microstructure of the steel along with the thermal stress development during heat treatment. After reviewing the state-of-the-art in heat treatment residual stress and distortion modeling, an existing commercial code was selected because of its advanced capabilities in predicting phase transformations, the evolving microstructure and related properties along with thermal stress development during heat treatment. However, this software was developed for small parts created from forgings or machined stock, and not for steel castings. Therefore, its predictive capabilities for heat treatment of steel castings were investigated. Available experimental steel casting heat treatment data was determined to be of insufficient detail and breadth, and so new heat treatment experiments were designed and performed, casting and heat treating modified versions of the Navy-C ring (a classical test shape for heat treatment experiments) for several carbon and low alloy steels in order to generate data necessary to validate the code. The predicted distortions were in reasonable agreement with the experimentally measured values. However, the final distortions in the castings were small, making it difficult to determine how accurate the predictions truly are. It is recommended that further validation of the software be performed with the aid of additional experiments with large production steel castings that experience significant heat treatment distortions. It is apparent from this research that the mechanical properties of the bonded sand used for cores and sand molds are key in producing accurate stress simulation results. Because of this, experiments were performed to determine the temperature-dependent elastic modulus of a resin-bonded sand commonly utilized in the steel casting industry. The elastic modulus was seen to vary significantly with heating and cooling rates. Also, the retained room temperature elastic modulus after heating was seen to degrade significantly when the sand was heated above 125°C. The elastic modulus curves developed in this work can readily be utilized in casting simulation software. Additional experiments with higher heating rates are recommended to determine the behavior of the elastic modulus in the sand close to the mold-metal interface. The commercial heat treatment residual stress and distortion code, once fully validated, is expected to result in an estimated energy savings of 2.15 trillion BTU's/year. Along with these energy savings, reduction of scrap and improvement in casting yield will result in a reduction of the environmental emissions associated with the melting and pouring of the metal which will be saved as a result of this technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Efficient end-to-end simulation of time-dependent coherent X-ray scattering experiments

Physical optics simulations for beamlines and experiments allow users to test experiment feasibility and optimize beamline settings ahead of beam time in order to optimize valuable beam time at synchrotron light sources like NSLS-II. Further, such simulations also help to develop and test experimental data processing methods and software in advance. The Synchrotron Radiation Workshop ( SRW ) software package supports such complex simulations. We demonstrate how recent developments in SRW significantly improve the efficiency of physical optics simulations, such as end-to-end simulations of time-dependent X-ray photon correlation spectroscopy experiments with partially coherent undulator radiation (UR). The molecular dynamics simulation code LAMMPS was chosen to model the sample: a solution of silica nanoparticles in water at room temperature. Real-space distributions of nanoparticles produced by LAMMPS were imported into SRW and used to simulate scattering patterns of partially coherent hard X-ray UR from such a sample at the detector. The partially coherent UR illuminating the sample can be represented by a set of orthogonal coherent modes obtained by simulation of emission and propagation of this radiation through the coherent hard X-ray (CHX) scattering beamline followed by a coherent-mode decomposition. GPU acceleration is added for several key functions of SRW used in propagation from sample to detector, further improving the speed of the calculations. The accuracy of this simulation is benchmarked by comparison with experimental data.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Report for 2.2.1 Task 2: Provide execution support for the human factors studies conducted for the LWRS Control Room Modernization project for PVNGS

INL contracted IFE to develop custom software functionality to support INL’s use of eye movement tracking in simulator studies. This includes the support of remote eye trackers, the support of dynamic Areas of Interest based on simulator events, and a general-purpose communication protocol between a simulator and the eye tracking software. The report summarises the task deliverables, which include a requirements identification workshop at INL, a software package, and instructional videos.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

DIRECT DETECTION OF PRECURSORS OF GAS GIANTS FORMED BY GRAVITATIONAL INSTABILITY WITH THE ATACAMA LARGE MILLIMETER/SUBMILLIMETER ARRAY

Phases of gravitational instability are expected in the early phases of disk evolution, when the disk mass is still a substantial fraction of the mass of the star. Disk fragmentation into sub-stellar objects could occur in the cold exterior part of the disk. Direct detection of massive gaseous clumps on their way to collapse into gas giant planets would offer an unprecedented test of the disk instability model. Here we use state-of-the-art 3D radiation-hydro simulations of disks undergoing fragmentation into massive gas giants, post-processed with RADMC-3D to produce dust continuum emission maps. These are then fed into the Common Astronomy Software Applications (CASA) ALMA simulator. The synthetic maps show that both overdense spiral arms and actual clumps at different stages of collapse can be detected with the Atacama Large Millimeter/submillimeter Array (ALMA) in the full configuration at the distance of the Ophiuchus star forming region (125 pc). The detection of clumps is particularly effective at shorter wavelengths (690 GHz) combining two resolutions with multi-scale clean. Furthermore, we show that a flux-based estimate of the mass of a protoplanetary clump can be comparable to a factor of three higher than the gravitationally bound clump mass. The estimated mass depends on the assumed opacity, and on the gas temperature, which should be set using the input of radiation-hydro simulations. We conclude that ALMA has the capability to detect “smoking gun” systems that are a signpost of the disk instability model for gas giant planet formation.

79 ASTRONOMY AND ASTROPHYSICS↗