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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Regional Oil and gas Aerial Methane Synthesis model (Analytica) (ROAMS Analytica) v1.5.2

The Regional Oil and gas Aerial Methane Synthesis model (Analytica) is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). This version is written in the Analytica programming language, and this version accompanies a correction in preparation for submission to Sherwin et al. 2024 (Nature). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗
DOE OSTI2018

Crosscut report: Exascale Requirements Reviews, March 9–10, 2017 – Tysons Corner, Virginia. An Office of Science review sponsored by: Advanced Scientific Computing Research, Basic Energy Sciences, Biological and Environmental Research, Fusion Energy Sciences, High Energy Physics, Nuclear Physics

The mission of the U.S. Department of Energy Office of Science (DOE SC) is the delivery of scientific discoveries and major scientific tools to transform our understanding of nature and to advance the energy, economic, and national security missions of the United States. To achieve these goals in today’s world requires investments in not only the traditional scientific endeavors of theory and experiment, but also in computational science and the facilities that support large-scale simulation and data analysis. The Advanced Scientific Computing Research (ASCR) program addresses these challenges in the Office of Science. ASCR’s mission is to discover, develop, and deploy computational and networking capabilities to analyze, model, simulate, and predict complex phenomena important to DOE. ASCR supports research in computational science, three high-performance computing (HPC) facilities — the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory and Leadership Computing Facilities at Argonne (ALCF) and Oak Ridge (OLCF) National Laboratories — and the Energy Sciences Network (ESnet) at Berkeley Lab. ASCR is guided by science needs as it develops research programs, computers, and networks at the leading edge of technologies. As we approach the era of exascale computing, technology changes are creating challenges for science programs in SC for those who need to use high performance computing and data systems effectively. Numerous significant modifications to today’s tools and techniques will be needed to realize the full potential of emerging computing systems and other novel computing architectures. To assess these needs and challenges, ASCR held a series of Exascale Requirements Reviews in 2015–2017, one with each of the six SC program offices,1 and a subsequent Crosscut Review that sought to integrate the findings from each. Participants at the reviews were drawn from the communities of leading domain scientists, experts in computer science and applied mathematics, ASCR facility staff, and DOE program managers in ASCR and the respective program offices. The purpose of these reviews was to identify mission-critical scientific problems within the DOE Office of Science (including experimental facilities) and determine the requirements for the exascale ecosystem that would be needed to address those challenges. The exascale ecosystem includes exascale computing systems, high-end data capabilities, efficient software at scale, libraries, tools, and other capabilities. This effort will contribute to the development of a strategic roadmap for ASCR compute and data facility investments and will help the ASCR Facility Division establish partnerships with Office of Science stakeholders. It will also inform the Office of Science research needs and agenda. The results of the six reviews have been published in reports available on the web at http://exascaleage.org/. This report presents a summary of the individual reports and of common and crosscutting findings, and it identifies opportunities for productive collaborations among the DOE SC program offices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

BuildingSync® [SWR-18-28]

BuildingSync® is a standardized language for commercial building energy audit data that software developers can use to exchange data between audit tools. Taking the form of an XML schema, BuildingSync can be required by building owners and audit program managers to allow data analysis and aggregation across multiple buildings in order to evaluate program performance and analyze trends. BuildingSync was developed using the standard energy data terminology defined in the Building Energy Data Exchange Specification (BEDES). BuildingSync is one of the first implementations of BEDES Version 1.0, and it was developed in close collaboration with the BEDES working groups. BuildingSync standardizes the format of the energy audit data itself. It is not intended to standardize the calculations performed on these data by engineers, analysts, software packages, or other audit tools. For more, see: https://buildingsync.net/

Long, Nicholas↗
DOE OSTI2017

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Hoobas: A highly object-oriented builder for molecular dynamics

Polydispersity and random sequences are ubiquitous features of polymers, and molecular dynamics simulations can help elucidate the impact of disorder in polymer systems. However, currently available packages for building polymer topologies do not enable the user to include randomness in a straightforward fashion. Here, we introduce Hoobas, a molecular builder package that easily handles polydispersity using a prototype-builder design pattern. This enables fast and easy building of systems comprised of thousands of distinct objects. It is written in the Python programming language, which ensures compatibility with a wide range of molecular dynamics packages and tools, as well as easy integration into most workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Developing energy flexibility in clusters of buildings: A critical analysis of barriers from planning to operation

This paper examines building energy flexibility at an aggregated level and addresses the main barriers and research gaps for the development of this resource across three design and development phases: market and policy, early planning and design, and operation. We review methodologies and tools and discuss barriers, challenges, and opportunities, incorporating policy, economic, technical, professional, and social perspectives. Although various legal and regulatory frameworks exist to foster the development of energy flexibility for small buildings, financing mechanisms are limited with a significant number of perceived risks undermining private investment. For the early planning and design phase, planners and designers lack appropriate tools and face interoperability challenges, which often results in insufficient consideration of demand response programs. The review of the operational phase highlighted the socio-technical challenges related to both the complexity of deployment and communication, as well as privacy and acceptability issues. Finally, the paper proposes a number of targeted research directions to address challenges and promote greater energy flexibility deployments, including capturing building demand side dynamics, improving baseline estimations and developing seamless connectivity between buildings and districts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

P3A

Portably Performant Physical Algebra (P3A) is a C++ library that provides classes representing variables in a physical algebra equation. These equations are the fundamental way that physics models are written ("f = ma" for example). P3A provides a way to write in the C++ programming language similar to how one would do math on paper. P3A provides support tools for rapidly solving equations in a way that is common in scientific computing. 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. SAND2021-3183 O

Ibanez-Granados, Daniel↗
DOE OSTI2011

Strategic Plan for Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

The Nuclear Energy Computational Fluid Dynamics Advanced Modeling and Simulation (NE-CAMS) system is being developed at the Idaho National Laboratory (INL) in collaboration with Bettis Laboratory, Sandia National Laboratory (SNL), Argonne National Laboratory (ANL), Utah State University (USU), and other interested parties with the objective of developing and implementing a comprehensive and readily accessible data and information management system for computational fluid dynamics (CFD) verification and validation (V&V) in support of nuclear energy systems design and safety analysis. The two key objectives of the NE-CAMS effort are to identify, collect, assess, store and maintain high resolution and high quality experimental data and related expert knowledge (metadata) for use in CFD V&V assessments specific to the nuclear energy field and to establish a working relationship with the U.S. Nuclear Regulatory Commission (NRC) to develop a CFD V&V database, including benchmark cases, that addresses and supports the associated NRC regulations and policies on the use of CFD analysis. In particular, the NE-CAMS system will support the Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, which aims to develop and deploy advanced modeling and simulation methods and computational tools for reliable numerical simulation of nuclear reactor systems for design and safety analysis. Primary NE-CAMS Elements There are four primary elements of the NE-CAMS knowledge base designed to support computer modeling and simulation in the nuclear energy arena as listed below. Element 1. The database will contain experimental data that can be used for CFD validation that is relevant to nuclear reactor and plant processes, particularly those important to the nuclear industry and the NRC. Element 2. Qualification standards for data evaluation and classification will be incorporated and applied such that validation data sets will result in well-defined, well-characterized data. Element 3. Standards will be established for the design and operation of experiments for the generation of new validation data sets that are to be submitted to NE-CAMS that addresses the completeness and characterization of the dataset. Element 4. Standards will be developed for performing verification and validation (V&V) to establish confidence levels in CFD analyses of nuclear reactor processes; such processes will be acceptable and recognized by both CFD experts and the NRC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Gulf Coast Clean Energy Application Center

The Gulf Coast Clean Energy Application Center was initiated to significantly improve market and regulatory conditions for the implementation of combined heat and power technologies. The GC CEAC was responsible for the development of CHP in Texas, Louisiana and Oklahoma. Through this program we employed a variety of outreach and education techniques, developed and deployed assessment tools and conducted market assessments. These efforts resulted in the growth of the combined heat and power market in the Gulf Coast region with a realization of more efficient energy generation, reduced emissions and a more resilient infrastructure. Specific t research, we did not formally investigate any techniques with any formal research design or methodology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Overview of the Tusas Code for Simulation of Dendritic Solidification

The aim of this project is to conduct a parametric investigation into the modeling of two dimensional dendrite solidification, using the phase field model. Specifically, we use the Tusas code, which is for coupled heat and phase-field simulation of dendritic solidification. Dendritic solidification, which may occur in the presence of an unstable solidification interface, results in treelike microstructures that often grow perpendicular to the rest of the growth front. The interface may become unstable if the enthalpy of the solid material is less than that of the liquid material, or if the solute is less soluble in solid than it is in liquid, potentially causing a partition [1]. A key motivation behind this research is that a broadened understanding of phase-field formulation and microstructural developments can be utilized for macroscopic simulations of phase change. This may be directly implemented as a part of the Telluride project at Los Alamos National Laboratory (LANL), through which a computational additive manufacturing simulation tool is being developed, ultimately to become part of the Advanced Simulation and Computing Program within the U.S. Department of Energy [2].

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Proxy App Prospectus for ECP Application Development Projects

The Exascale Computing Project (ECP) includes 25 application development (AD) projects1 and five co-design centers funded by the Office of Science, NNSA, and National Cancer Institute. Their full code bases are large and complex, and can be difficult for co-design partners to assimilate for use in collaboration for Exascale challenges. To alleviate this challenge, proxy applications (“apps”) are being developed: these are small, self-contained, simplified codes that are intended to model the performance-critical computations within applications. Proxy apps also capture programming methods and styles that drive requirements for compilers and other elements of the tool chain. Within ECP, application teams, co-design centers, software technology (ST) projects and vendors all plan to use proxies as a major mechanism to drive collaborations and co-design solutions for exascale challenges.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

PUMA: Plutonium Modeling and Analysis Theory Manual Rev 1.0

The high rate of alpha decay of the plutonium-238 isotope lends the material to be used for many unique space applications where the reach of solar radiation is either too weak or unavailable. With a power density of 0.54 watts per gram, plutonium-238 has been used to power space exploration satellites from mars rovers to deep space probes. Los Alamos National Laboratory (LANL) has remained the primary location for fabrication of the plutonium oxide pellets. In an effort to apply modern techniques and tools towards supporting LANL’s fabrication responsibilities, PUMA was created under an LDRD funded program to gain understanding of plutonium oxide heat source pellets during fabrication.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Comparison of Non-EOR and EOR Life Cycle Assessments

The Energy & Environmental Research Center worked with The CETER Group, Inc., through the Plains CO 2 Reduction Partnership to evaluate whether life cycle greenhouse gas (GHG) emissions associated with incremental oil produced by enhanced oil recovery (EOR) using anthropogenic carbon dioxide (CO 2 ) are less than GHG emissions associated with conventional oil production. A cradle-to-grave approach was used to quantify the full life cycle GHG emissions for four scenarios: conventional natural gas production and conventional oil production (i.e., the current conventional approach), natural gas processing with CO 2 capture coupled with typical West Texas EOR, natural gas processing at Shute Creek plant and conventional oil production, and natural gas processing at Shute Creek plant with CO 2 capture coupled with EOR at the Bell Creek oil field. Two tools were used to conduct the life cycle analysis (LCA), including 1) a customized programming of the Argonne National Laboratory Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation model, known as the GREET model, and 2) Microsoft Excel ® spreadsheet models using emission factors from peer-reviewed literature and U.S. Department of Energy National Energy Technology Laboratory publications. The modeling results show that the scenarios with CO 2 capture and CO 2 EOR produce both natural gas and oil with lower life cycle emissions than conventional systems producing natural gas and oil independently. These results are supported using both different modeling approaches and sets of modeling inputs. While considerable effort was put into acquiring necessary detail for accurate models, much of the data used were obtained from secondary sources. Significantly greater detail and more rigorous treatment would be required to produce an LCA for use as proof of CO 2 emission reduction.

02 PETROLEUM↗
DOE OSTI2011

Scale 6.1 Enhancements for Nuclear Criticality Safety

The Scale code system developed at Oak Ridge National Laboratory provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used Scale for safety analysis and design. Scale provides a 'plug-and-play' framework with 89 computational modules, including three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution. Scale's graphical user interfaces assist with accurate system modeling and convenient access to desired results. Scale 6.1 builds on the existing capabilities and ease-of-use of Scale and provides several new features such as improved options and capabilities for sensitivity and uncertainty analysis calculations, improved flexibility in shielding and criticality accident alarm system calculations with automated variance reduction, and new options for the definition of group structures for depletion calculations. The Scale 6.1 development team has focused on improved robustness via substantial additional regression testing and verification for new and existing features, providing improved performance relative to Scale 6.0, especially in reactor physics calculations and in the nuclear data used for source term characterization and shielding calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

How Can Cities Use Urban-Scale Building Energy Modeling?

Whole-building energy modeling (BEM) is a multi-purpose tool for building energy efficiency, supporting design, code development and compliance, green labeling, incentive programs, and even building operations. A new buzz-prefix making its way around the BEM community is 'urban-scale'. But what is urban-scale BEM (UBEM)? And can it help cities--or other entities--save energy? We describe a taxonomy of UBEM based on the interactions that are modeled between buildings and between buildings and other systems. Each type of UBEM supports different analyses and applications. We describe each UBEM type and, using a survey of sustainability managers in major U.S. cities, give examples of how it is currently used in practice or could be used in the future. The four types of UBEM are 'Portfolio', 'District', 'Weather', and 'System' BEM. Portfolio BEM considers no interactions between buildings and no other systems. It is conventional BEM repeated on multiple buildings. It is also by far the most commonly used UBEM with applications to retrofit screening and targeting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Reconstruction and Selection Tools for Charged-Current Muon Neutrino Cross Sections in SBND

SBND Near detector for the Short-Baseline Neutrino program [1] searching for sterile neutrinos in the Booster Neutrino Beam. Data taking starts in 2020. Primary detector is a liquid argon time projection chamber with a central cathode and two drift regions (TPCs). Ionization caused by charged particles is drifted in a strong electric field and detected on wire planes. Readout triggered by the neutrino beam timing and the photon detector system (PDS). Equipped with a suite of cosmic ray taggers (CRTs) [2] surrounding the central detector. Cross-sections and backgrounds SBND will provide world leading neutrino-argon cross-sections with 7,000,000 neutrino events in three years. Charged-current muon neutrino interactions will be the most abundant. The detector is on the surface with a small overburden so there is a high flux of cosmic rays (mostly muons). Cosmic ray muons can be significant background because the electron drift velocity is slow. Reconstruction Charged deposited in the TPC is reconstructed into track and shower objects with calorimetry and interaction topology information [3]. Unambiguous cosmic rays are removed. Particle-CRT intersections are reconstructed as CRT hits, trajectories of through-going particles are reconstructed as CRT tracks. Cosmic background removal SBND will see 2-3 cosmic muon interactions in the TPC for every neutrino interaction after reconstruction and initial cosmic rejection. A number of selection cuts utilizing TPC, CRT and PDS information have been developed to further reduce this background. Particles in the detector before or after the trigger time will have a shifted reconstructed X-position, most rejection methods involve finding the true crossing time (t0).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

SEED Platform for Building Performance Standards Implementation Guide (Spanish Translation)

This guide provides an overview of the Standard Energy Efficiency Data (SEED) Platform. The SEED Platform developed by the U.S. Department of Energy (DOE) to provide a low-cost, user-friendly tool for jurisdictions to launch and manage energy benchmarking and Building Performance Standard (BPS) programs. It has been translated into Spanish. This is the Spanish translation of NREL/FS-5500-90691.

benchmarking↗