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DOE OSTI2026

arco (Assembled Resource-Constrained Optimization) [SWR-26-030]

Arco (Assembled Resource-Constrained Optimization) is a memory-smart optimization DSL and solver for LP and MIP problems on constrained hardware. The software is an optimization framework built around a KDL-based domain-specific language and a CLI compiler/solver. You write optimization models in .kdl files, and the arco CLI compiles, validates, inspects, and solves them. Language bindings (Python today, more planned) provide programmatic access to the same engine. Built for harder optimization problems on constrained resources, Arco is intentional about every allocation, careful with stack and heap behavior, and relentless about minimizing memory usage so more systems can run real workloads. Arco is built primarily for internal use within our organization. You are welcome to try it, but we make no guarantees about API stability or robustness at this stage

Sanchez Perez, Pedro Andres [National Laboratory o↗

DOE OSTI2026

HdsaLib

HdsaLib performs hyper-differential sensitivity analysis in optimization problems that are constrained by partial differential equation problems. The software aids researchers in understanding the impact of uncertainties on their optimization models. The tool has been applied for use in ice sheet modeling, fluid flow modeling, atmospheric tracer transport modeling, and subsurface flow modeling. 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.

van Bloemen Waanders, Bart [Sandia National Lab. (↗

DOE OSTI2017

Requirements Document for Development of a Livermore Tomography Tools Interface

In this document, we outline an exercise performed at LLNL to evaluate the user interface deficits of a LLNL-developed CT reconstruction software package, Livermore Tomography Tools (LTT). We observe that a difficult-to-use command line interface and the lack of support functions compound to generate a bottleneck in the CT reconstruction process when input parameters to key functions are not well known. Through the exercise of systems engineering best practices, we generate key performance parameters for a LTT interface refresh, and specify a combination of back-end (“test-mode” functions) and front-end (graphical user interface visualization and command scripting tools) solutions to LTT’s poor user interface that aim to mitigate issues and lower costs associated with CT reconstruction using LTT. Key functional and non-functional requirements and risk mitigation strategies for the solution are outlined and discussed.

42 ENGINEERING↗

DOE OSTI2021

Optimization-based Design for Manufacturing

This report provides detailed documentation of the algorithms that where developed and implemented in the Plato software over the course of the Optimization-based Design for Manufacturing LDRD project.

42 ENGINEERING↗

DOE OSTI2024

A Review on Protection Challenges on Transmission Lines Connected to Inverter Based Resources

The increased penetration of inverter-based resources (IBRs) connected to transmission grids is challenging how traditional electric power systems operate. Such systems were originally designed based on the dominant presence of synchronous generators. Some main challenges include the increased concerns about system stability due to the reduced system inertia caused by IBRs and the reduced protection reliability caused by the non-deterministic fault current response of IBRs. The protection relays’ algorithms have been designed and validated based on well-known fault current characteristics of synchronous generations, while the short-circuit responses of IBRs heavily depend on their vendor-specific control schemes, which are mainly set to protect inverter semiconductor switches and DC components. The magnitude of short current that IBRs contribute is typically between 1.1–1.5 times the rated current that may behave unstably and incoherently with the voltages. The control scheme of the IBRs also controls the active (P) and reactive (Q) support during system voltage sag and swell conditions. These characteristics challenge not only protective relay schemes but also existing short-circuit software tools to correctly model IBRs for fault studies and protection coordination analyses. Utilities, university researchers, research institutes, and relay manufacturers have performed studies to investigate different aspects of high IBR penetration. Almost all studies support 1) creating international and national standards to regulate the IBRs, 2) revising engineering tools to address shortcomings, and 3) adjusting the protective relay settings to resolve protection problems. This paper summarizes the studies and research conducted in recent years to quantify the impact of IBR penetration on transmission line protection and to identify potential solutions to improve the dependability and reliability of grid protection systems.

14 SOLAR ENERGY↗

DOE OSTI2024

pCubit

SAND2025-01894O pCubit is a software tool that can easily place particles or pores into a given geometry using desired statistics and the Poisson point process. It reduces the need for users to manually create complex geometry creation and placement. 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.

Buche, Michael↗

DOE OSTI2013

ADVANCED SIMULATION CAPABILITY FOR ENVIRONMENTAL MANAGEMENT- CURRENT STATUS AND PHASE II DEMONSTRATION RESULTS

The U.S. Department of Energy (USDOE) Office of Environmental Management (EM), Office of Soil and Groundwater, is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high-performance computing tool facilitates integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of computer software capabilities with an emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Toolsets and High-Performance Computing (HPC) Multiprocess Simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, toolsets for interaction with Platform, and verification and model confidence testing. The Platform and HPC capabilities are being tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities. The Phase I demonstration focusing on individual capabilities of the initial toolsets was completed in 2010. The Phase II demonstration completed in 2012 focused on showcasing integrated ASCEM capabilities. For Phase II, the Hanford Site deep vadose zone (BC Cribs) served as an application site for an end-to-end demonstration of capabilities, with emphasis on integration and linkages between the Platform and HPC components. Other demonstrations, addressing attenuation-based remedies at the Savannah River Site F Area and performance assessment for a representative waste tank, illustrate integration of linked ASCEM capabilities and initial integration efforts with tools from the Cementitious Barriers Partnership.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

ADVANCED SIMULATION CAPABILITY FOR ENVIRONMENTAL MANAGEMENT – CURRENT STATUS AND PHASE II DEMONSTRATION RESULTS

DOE Environmental Management, advanced simulation,↗

DOE OSTI2013

Advanced Simulation Capability for Environmental Management - Current Status and Phase II Demonstration Results - 13161

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater, is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high-performance computing tool facilitates integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of computer software capabilities with an emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) Multi-process Simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The Platform and HPC capabilities are being tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities. The Phase I demonstration focusing on individual capabilities of the initial tool-sets was completed in 2010. The Phase II demonstration completed in 2012 focused on showcasing integrated ASCEM capabilities. For Phase II, the Hanford Site deep vadose zone (BC Cribs) served as an application site for an end-to-end demonstration of capabilities, with emphasis on integration and linkages between the Platform and HPC components. Other demonstrations, addressing attenuation-based remedies at the Savannah River Site F Area and performance assessment for a representative waste tank, illustrate integration of linked ASCEM capabilities and initial integration efforts with tools from the Cementitious Barriers Partnership. (authors)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Microstructural Characterization of Irradiated Fuels and Materials for the United States High Performance Research Reactor Fuel Development Program and the Fuel Cycle Research and Development Program

In an effort to contribute to the development of advanced nuclear fuel for research reactors, monolithic and dispersion plate fuels will be examined to determine how irradiation parameters such as fission density, fission rate, and irradiation temperature, as well as mechanical parameters such as composition and fabrication, affect the final microstructure of the fuel, post irradiation. Electron Backscatter Detection (EBSD) analysis capabilities of irradiated materials will be developed as well as improvements on irradiated sample preparation in order to provide higher quality samples for SEM, FIB, and TEM. In addition, image analysis techniques developed at Idaho National Laboratory (INL) will be employed to examine microstructural features such as fission product precipitates and fission gas bubbles. The main goals are to further develop EBSD capabilities on irradiated material; characterize microstructure of irradiated fuel to support qualification; develop a consistent, effective process for image analysis using INL developed software; and provide repeatable, statistically-confident, critically assessed data to further modeling efforts. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Phase 1 Development Report for the SESSA Toolkit.

The Site Exploitation System for Situational Awareness ( SESSA ) tool kit , developed by Sandia National Laboratories (SNL) , is a comprehensive de cision support system for crime scene data acquisition and Sensitive Site Exploitation (SSE). SESSA is an outgrowth of another SNL developed decision support system , the Building R estoration Operations Optimization Model (BROOM), a hardware/software solution for data acquisition, data management, and data analysis. SESSA was designed to meet forensic crime scene needs as defined by the DoD's Military Criminal Investigation Organiza tion (MCIO) . SESSA is a very comprehensive toolki t with a considerable amount of database information managed through a Microsoft SQL (Structured Query Language) database engine, a Geographical Information System (GIS) engine that provides comprehensive m apping capabilities, as well as a an intuitive Graphical User Interface (GUI) . An electronic sketch pad module is included. The system also has the ability to efficiently generate necessary forms for forensic crime scene investigations (e.g., evidence submittal, laboratory requests, and scene notes). SESSA allows the user to capture photos on site, and can read and generate ba rcode labels that limit transcription errors. SESSA runs on PC computers running Windows 7, but is optimized for touch - screen tablet computers running Windows for ease of use at crime scenes and on SSE deployments. A prototype system for 3 - dimensional (3 D) mapping and measur e ments was also developed to complement the SESSA software. The mapping system employs a visual/ depth sensor that captures data to create 3D visualizations of an interior space and to make distance measurements with centimeter - level a ccuracy. Output of this 3D Model Builder module provides a virtual 3D %22walk - through%22 of a crime scene. The 3D mapping system is much less expensive and easier to use than competitive systems. This document covers the basic installation and operation of th e SESSA tool kit in order to give the user enough information to start using the tool kit . SESSA is currently a prototype system and this documentation covers the initial release of the tool kit . Funding for SESSA was provided by the Department of Defense (D oD), Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) Rapid Fielding (RF) organization. The project was managed by the Defense Forensic Science Center (DFSC) , formerly known as the U.S. Army Criminal Investigation Laboratory (USACIL) . ACKNOWLEDGEMENTS The authors wish to acknowledge the funding support for the development of the Site Exploitation System for Situational Awareness (SESSA) toolkit from the Department of Defense (DoD), Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) Rapid Fielding (RF) organization. The project was managed by the Defense Forensic Science Center (DFSC) , formerly known as the U.S. Army Criminal Investigation Laboratory (USACIL). Special thanks to Mr. Garold Warner, of DFSC, who served as the Project Manager. Individuals that worked on the design, functional attributes, algorithm development, system arc hitecture, and software programming include: Robert Knowlton, Brad Melton, Robert Anderson, and Wendy Amai.

Knowlton, Robert G.↗

DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

DOE OSTI2023

KinCat v.1.0

SAND2024-02099O The software is designed to allow researchers to perform kinetic Monte Carlo (KMC) simulations of catalytic reactions on a 2D lattice. The code is written efficiently to run on a variety of shared memory computing architectures (e.g. GPU, multi-core) and to natively express the full complexity of lateral interactions on reaction rates. The software allows researchers to perform KMC simulations of catalytic reactions on a 2D lattice. It uses parallel shared-memory computing architectures to reduce run-times and allows for simultaneous simulation of multiple independent runs. 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.

Najm, Habib↗

DOE OSTI2023

DISCO GUI v.1

SAND2024-08619O The DISCO GUI software, written in MATLAB, allows for data calibration for X-ray diffraction work at Sandia National Labs’ Z Machine. The program manually identifies and manipulates images from seven fiber bundles based on a calibration reticle. 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.

Smith, Anthony↗

DOE OSTI2024

Feature Pathway Graphs using Random Forest Regressors

SAND2025-04671O Feature Pathway Graphs using Random Forest Regressors is a software tool that uses machine learning to determine pathways of influence between features in data sets. It can be used as a surrogate method for casual discovery. The output creates pathway graphs between features of interest. 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.

Peterson, Matthew↗

DOE OSTI2026

MCNPy

SAND2026-20425O MCNPy runs and analyzes simulations from MCNP, a software that models radiation transport of neutrons and gamma rays. MCNPy uses Python to start MCNP, retrieve event data files, and convert them into graph structures for detailed analysis. It offers visualization tools, including 2D views of particle histories, making complex simulation data easier to interpret for researchers and engineers. 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.

Nowack, Aaron [Sandia National Lab. (SNL-CA), Live↗

DOE OSTI2014

Performance Engineering Research Institute SciDAC-2 Enabling Technologies Institute Final Report

Enhancing the performance of SciDAC applications on petascale systems has high priority within DOE SC. As we look to the future, achieving expected levels of performance on high-end com-puting (HEC) systems is growing ever more challenging due to enormous scale, increasing archi-tectural complexity, and increasing application complexity. To address these challenges, PERI has implemented a unified, tripartite research plan encompassing: (1) performance modeling and prediction; (2) automatic performance tuning; and (3) performance engineering of high profile applications. The PERI performance modeling and prediction activity is developing and refining performance models, significantly reducing the cost of collecting the data upon which the models are based, and increasing model fidelity, speed and generality. Our primary research activity is automatic tuning (autotuning) of scientific software. This activity is spurred by the strong user preference for automatic tools and is based on previous successful activities such as ATLAS, which has automatically tuned components of the LAPACK linear algebra library, and other re-cent work on autotuning domain-specific libraries. Our third major component is application en-gagement, to which we are devoting approximately 30% of our effort to work directly with Sci-DAC-2 applications. This last activity not only helps DOE scientists meet their near-term per-formance goals, but also helps keep PERI research focused on the real challenges facing DOE computational scientists as they enter the Petascale Era.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Comparison of Deposition© software predictions to published experimental results for large (152 mm by 152 mm) square ducts

A comparison was performed between experimental aerosol deposition measurements in large air ducts, compared to predictions performed by the US Nuclear Regulatory Commission Deposition© software package. Although the Deposition© code was designed to calculate the transport of radioactive aerosols in small diameter sampling tubes, it was not certain that the software would adequately predict aerosol transport in large air ducts. Two sets of experimental data were used in this comparison, one set of results from small diameter (1.27 mm ID) tubes, and the other data set was from testing on large diameter (152 mm square) ventilation ducts. In general, the Deposition© software performs excellent predictions if the ductwork system has a computed aerosol percent penetration greater than 75% (with a 2.9% average error compared to experiments). For example, shorter duct systems have higher aerosol penetrations than a longer duct system of the same diameter. However, when the Deposition© software calculated an aerosol penetration less than about 75% for a particular duct system, the average percent error increased to 68.3% when compared to experimental measurements. The Deposition© software could therefore be used to ensure that an aerosol would have a high percent penetration through a ductwork system, but it should not be used to make (dosimetric) decisions about ductwork performance if the calculated percent penetration is less than 75%. This document includes a section of attached engineering formulas that explain the structure of the Excel spreadsheet calculations.

61 RADIATION PROTECTION AND DOSIMETRY↗