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At least 1,261 records · Page 70

SIERRA Low Mach Module: Fuego Verification Manual - Version 4.52

The SIERRA Low Mach Module: Fuego along with the SIERRA Participating Media Radiation Module: Syrinx, henceforth referred to as Fuego and Syrinx, respectively, are the key elements of the ASCI fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Syrinx represents the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

42 ENGINEERING↗

SIERRA Low Mach Module: Fuego User Manual (V.5.6)

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

42 ENGINEERING↗

SIERRA Low Mach Module: Fuego Theory Manual - Version 5.8

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

42 ENGINEERING↗

SIERRA Low Mach Module: Fuego User Manual - Version 5.8

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

42 ENGINEERING↗

SIERRA Low Mach Module: Fuego Verification Manual - Version 5.8

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

42 ENGINEERING↗

SIERRA Low Mach Module: Fuego Verification Manual (V.5.10)

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

42 ENGINEERING↗

SIERRA Low Mach Module: Fuego Theory Manual (V.5.10)

The SIERRA Low Mach Module: Fuego, henceforth referred to as Fuego, is the key element of the ASC fire environment simulation project. The fire environment simulation project is directed at characterizing both open large-scale pool fires and building enclosure fires. Fuego represents the turbulent, buoyantly-driven incompressible flow, heat transfer, mass transfer, combustion, soot, and absorption coefficient model portion of the simulation software. Using MPMD coupling, Scefire and Nalu handle the participating-media thermal radiation mechanics. This project is an integral part of the SIERRA multi-mechanics software development project. Fuego depends heavily upon the core architecture developments provided by SIERRA for massively parallel computing, solution adaptivity, and mechanics coupling on unstructured grids.

42 ENGINEERING↗

Sandia National Laboratories Facilities Management and Operations Center Design Standards Manual

At Sandia National Laboratories in New Mexico (SNL/NM), the design, construction, operation, and maintenance of facilities is guided by industry standards, a graded approach, and the systematic analysis of life cycle benefits received for costs incurred. The design of the physical plant must ensure that the facilities are "fit for use," and provide conditions that effectively, efficiently, and safely support current and future mission needs. In addition, SNL/NM applies sustainable design principles, using an integrated whole-building design approach, from site planning to facility design, construction, and operation to ensure building resource efficiency and the health and productivity of occupants. The safety and health of the workforce and the public, any possible effects on the environment, and compliance with building codes take precedence over project issues, such as performance, cost, and schedule. These design standards generally apply to all disciplines on all SNL/NM projects. Architectural and engineering design must be both functional and cost-effective. Facility design must be tailored to fit its intended function, while emphasizing low-maintenance, energy-efficient, and energy-conscious design. Design facilities that can be maintained easily, with readily accessible equipment areas, low maintenance, and quality systems. To promote an orderly and efficient appearance, architectural features of new facilities must complement and enhance the existing architecture at the site. As an Architectural and Engineering (A/E) professional, you must advise the Project Manager when this approach is prohibitively expensive. You are encouraged to use professional judgment and ingenuity to produce a coordinated interdisciplinary design that is cost-effective, easily contractible or buildable, high-performing, aesthetically pleasing, and compliant with applicable building codes. Close coordination and development of civil, landscape, structural, architectural, fire protection, mechanical, electrical, telecommunications, and security features is expected to ensure compatibility with planned functional equipment and to facilitate constructability. If portions of the design are subcontracted to specialists, delivery of the finished design documents must not be considered complete until the subcontracted portions are also submitted for review. You must, along with support consultants, perform functional analyses and programming in developing design solutions. These solutions must reflect coordination of the competing functional, budgetary, and physical requirements for the project. During design phases, meetings between you and the SNL/NM Project Team to discuss and resolve design issues are required. These meetings are a normal part of the design process. For specific design-review requirements, see the project-specific Design Criteria. In addition to the design requirements described in this manual, instructive information is provided to explain the sustainable building practice goals for design, construction, operation, and maintenance of SNL/NM facilities. Please notify SNL/NM personnel of design best practices not included in this manual, so they can be incorporated in future updates. You must convey all documents describing work to the SNL/NM Project Manager in both hard copy and in an electronic format compatible with the SNL/NM-prescribed CADD and other software packages, and in accordance with a SNL/NM approved standard format. Print all hard copy versions of submitted documents (excluding drawings and renderings) double-sided when practical.

42 ENGINEERING↗

Corrosion Detection LDRD Seedling (Final Report)

Automation techniques for recognizing material defects are very common in fields like infrastructure survey and civil engineering; however, the defects are usually easily distinguishable from their background, on a larger scale (e.g. cement bridges), and very specific. Extracting information about a defect that is near or equal to the background of the data can be extremely difficult. Images with heavy background corrosion, pitting, cracking, and man-made defects (such as welding) makes extracting information on a specific defect near-impossible. This is especially true when the defect is on the micron level and the dynamic range of your image taking instrument is low. So, a simplified, Java-based Fiji™ (ImageJ) defect detection program, dependent on a ‘flag’ system, was proposed for data that has a micron level hairline crack that is near or equal to the background. The utilization of the built-in functions, plugins, and macro scripting capability of the Java-based software sends a series of flags to the user that help to identify if the surface contains a defect of interest and to characterize that defect.

42 ENGINEERING↗

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗

ML-ACCEPT: Machine-Learning-enhanced Automated Circuit Configuration and Evaluation of Power Converters

This project, ML-ACCEPT, took a significant step toward achieving the first objective of the DIFFERENTIATE program: to help engineers to more rapidly and cost-effectively consider a wider range of more novel concepts before selecting an engineering-optimal architecture for high-fidelity detailed design and evaluation. Compared to existing methods, the ML-ACCEPT project investigated innovative technologies to make the design of power converters more cost-effective and time-efficient by i) integrating recent breakthroughs in ML, power electronics, simulation software, and optimization to research, develop, and developed a suite of ML-enhanced hypothesis generation tools for power converter design; and ii) facilitating the integration of the proposed software tools into existing power-converter design work-flows. Some existing tools for power-converter design have a certain level of intelligence to aid the design process, but to our knowledge none of them has ML-enhanced capability of automating the electrical circuit design process by selecting, configuring, and tailoring the individual components that enable available resources (e.g., high-voltage DC power) to be converted to the desired output (e.g., lower-voltage DC power with a desired voltage ripple), subject to application-specific (e.g., plasma generation and automotive applications) thermal and packaging considerations. The state-of-the-art circuit design of power converters is still heavily reliant on human experts to select the optimal topology and search for design parameters with human’s experience and intuitions, which can be very time-consuming, inefficient, and labor intensive. The team is composed of University of Michigan-Dearborn (UM-Dearborn), Lawrence Livermore National Laboratory (LLNL), Oak Ridge National Laboratory (ORNL), Modelon Inc., and lighthouse customers.

42 ENGINEERING↗

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗

Microcontroller-based aerosol jet printer control software

This software is used with a microcontroller to control an aerosol jet printing system. It was written for a 32-bit ARM microcontroller, providing greater processing speed and complexity relative to more conventional low-cost printer controllers. The microcontroller software was written using a real-time operating system (FreeRTOS), which simplifies parallel operation of multiple functions and further customization. It supports simultaneous motion planning, pulse generation for stepper motors, reading encoder feedback, communicating with multiple mass flow controllers, controlling solid state relays, handling a software-based emergency stop, and sending data to the client PC. The program is written in C and communicates with the client PC via USB connection. Sandia National Laboratories is a multi-mission 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. SAND2021-0436 O

Secor, EthanBenjamin↗

MOOSE IPL Extensions (Control Logic)

In FY-2015, the development of MOOSE was driven by the needs of the NEAMS MOOSE-based applications, BISON, MARMOT, and RELAP-7. An emphasis was placed on the continued upkeep and improvement MOOSE in support of the product line integration goals. New unified documentation tools have been developed, several improvements to regression testing have been enforced and overall better software quality practices have been implemented. In addition the Multiapps and Transfers systems have seen significant refactoring and robustness improvements, as has the “Restart and Recover” system in support of Multiapp simulations. Finally, a completely new “Control Logic” system has been engineered to replace the prototype system currently in use in the RELAP-7 code. The development of this system continues and is expected to handle existing needs as well as support future enhancements.

97 MATHEMATICS AND COMPUTING↗

MOOSE IPL Extensions (Documentation)

In FY-2015, The development of MOOSE was driven by the needs of the NEAMS MOOSE-based applications, BISON, MARMOT, and RELAP-7. An emphasis was placed on the continued upkeep and improvement MOOSE in support of the product line integration goals. New unified documentation tools have been developed, several improvements to regression testing have been enforced and overall better software quality practices have been implemented. In addition the Multiapps and Transfers systems have seen significant refactoring and robustness improvements, as has the “Restart and Recover” system in support of Multiapp simulations. Finally, a completely new “Control Logic” system has been engineered to replace the prototype system currently in use in the RELAP-7 code. The development of this system continues and is expected to handle existing needs as well as support future enhancements.

99 GENERAL AND MISCELLANEOUS↗

Capturing the full benefits of bifacial modules to approach an LCOE of 3c/kWh through a regional optimization of the electrical architecture (Final Technical Report)

This is the final technical report for the Cypress Creek Renewables project focused on bifacial plant performance. The project consisted of building a heavily instrumented Bifacial test sites with several cell technologies; instrumenting >1 MW scale commercial sites with both monofacial and bifacial arrays in order to understand real-world differences; and to engage with the performance modeling and financial stakeholder community to improve accuracy and increase investor confidence. The data from the test and commercial sites has been used to validate and improve the accuracy of both physics-based and reduced order modeling software. The heavily instrumented nature has been used to understand how light contributions from the sky and reflected from the ground impact different portions of the module and array while the data from the commercial sites has directly impacted how independent engineers model production from bifacial systems. The latter point has led to an increase in over 2% compared to earlier predictions. Even this modest increase has had significant downward pressure on project LCOE. As the data and results are both public, this refined modeling and empirical evidence for a higher bifacial gain than modeled, the benefits to the broader US solar community are assured.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using ASCEM Modeling and Visualization to Inform Stakeholders of Contaminant Plume Evolution and Remediation Efficacy at F-Basin Savannah River, SC – 15156

Communication with stakeholders, regulatory agencies, and the public is an essential part of implementing different remediation and monitoring activities, and developing site closure strategies at contaminated sites. Modeling of contaminant plume evolution plays a critical role in estimating the benefit, cost, and risk of particular options. At the same time, effective visualization of monitoring data and modeling results are particularly important for conveying the significance of the results and observations. In this paper, we present the results of the Advanced Simulation Capability for Environmental Management (ASCEM) project, including the discussion of the capabilities of newly developed ASCEM software package, along with its application to the F-Area Seepage Basins located in the U.S. Department of Energy Savannah River Site (SRS). ASCEM software includes state-of-the-art numerical methods for simulating complex flow and reactive transport, as well as various toolsets such as a graphical user interface (GUI), visualization, data management, uncertainty quantification, and parameter estimation. Using this software, we have developed an advanced visualization of tritium plume migration coupled with a data management system, and simulated a three-dimensional model of flow and plume evolution on a high-performance computing platform. We evaluated the effect of engineered flow barriers on a nonreactive tritium plume, through advanced plume visualization and modeling of tritium plume migration. In addition, we developed a geochemical reaction network to describe complex geochemical processes at the site, and evaluated the impact of coupled hydrological and geochemical heterogeneity. These results are expected to support SRS’s monitoring activities and operational decisions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗