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DOE OSTI2016

Sierra Toolkit Manual Version 4.42

This report provides documentation for the SIERRA Toolkit (STK) modules. STK modules are intended to provide infrastructure that assists the development of computational engineering software such as finite-element analysis applications. STK includes modules for unstructured-mesh data structures, reading/writing mesh files, geometric proximity search, and various utilities. This document contains a chapter for each module, and each chapter contains overview descriptions and usage examples. Usage examples are primarily code listings which are generated from working test programs that are included in the STK code-base. A goal of this approach is to ensure that the usage examples will not fall out of date.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Evaluation of China Experimental Fast Reactor Start-up Tests (Final Report, Revision 1)

This report documents the results and observations on the Coordinated Research Project (CRP) of the International Atomic Energy Agency (IAEA) on “Neutronics Benchmark of CEFR Start-Up Tests.” The China Experimental Fast Reactor (CEFR) is a 65MWt sodium-cooled fast reactor with highly enriched uranium oxide fuel. The reactor achieved first criticality in 2010, and a series of start-up tests were conducted to measure various reactor physics parameters. In 2018, the IAEA launched the CRP for validation and qualification of member states' computation capabilities in the field of fast reactor simulation by utilizing the measured data in the CEFR start-up test. Twenty-nine international organizations from eighteen member countries, including Argonne National Laboratory, have participated in the CRP. The CEFR start-up tests offer a rare opportunity to validate U.S. nuclear engineering software because it is a well-specified benchmark with corresponding measurements for a recently built fast reactor starting up with a known fuel composition (fresh fuel). Previous fast reactor validation benchmarks frequently involve reactors that have already been started up and contain irradiated fuel that is difficult to characterize with high certainty.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Smart Contract Architectures and Templates for Blockchain-based Energy Markets (V.1.0)

Within the field of Transactive Energy Systems (TES), there is an active need for tools that can support and accelerate the development of these new grid solutions. Among the many tools available, blockchain stands out as a viable instrument that can help researchers develop decentralized, autonomous, and tamper-resistant grid applications. In this work, we explore the use of smart contracts (SCs), a subset of blockchain technology, and analyze their applicability to facilitating the implementation of TES solutions. In particular, we focus on presenting areas of opportunity and potential drawbacks, along with use cases that can benefit from this technology building upon previous research developed by Pacific Northwest National Laboratory and other research organizations. This work builds upon the fundamentals of TES and smart contract technology to develop a series of software templates that can be used by industry to build TES-oriented grid solutions. These templates are intended to be platform agnostic and take into consideration the unique properties of SCs and distributed ledger storage mechanisms to ensure actual code implementations remain aware of the limitations of the technology. The proposed templates have the potential to enable software architects to mix and match components to satisfy their application requirements, thereby reducing the number of resources required to implement blockchain-based solutions. These templates are divided into two main components—data and behavioral models. The data models are intended to help software engineers represent the underlying grid objects along with their properties in a ledger-based storage system. The behavioral models are used to describe the processes and actions that actors within a system must perform to achieve a given outcome such as registering an asset, placing a bid, and performing bid clearances. These two components are documented in a Unified Modeling Language (UML) format and are intended for use in SC-based implementations, with special behavioral considerations to account for the asynchronous properties of the underlying ledger and the typical execution model of smart contracts. Finally, future research ideas and potential extensions to this work are discussed. In particular, known limitations and potential improvements of the developed product are identified and expected to be addressed in future revisions of the template model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Graph Contractions for Calculating Correlation Functions in Lattice QCD

Computing correlation functions for many-particle systems in Lattice QCD is vital to extract nuclear physics observables like the energy spectrum of hadrons such as protons. However, this type of calculation has long been considered to be very challenging and computing-resource intensive because of the complex nature of a hadron composed of quarks with many degrees of freedom. In particular, a correlation function can be calculated through a sum of all possible pairs of quark contractions, each of which is a batched tensor contraction, dictated by Wick's theorem. Because the number of terms of this sum can be very large for any hadronic system of interest, fast evaluation of the sum faces several challenges: an extremely large number of contractions, a huge memory footprint at runtime, and the speed of tensor contractions. In this paper, we present a Lattice QCD analysis software suite, Redstar, which addresses these challenges by utilizing novel algorithmic and software engineering methods targeting modern computing platforms such as many-core CPUs and GPUs. In particular, Redstar represents every term in the sum of a correlation function by a graph, applies efficient graph algorithms to reduce the number of contractions to lower the cost of computations, and minimizes the total memory footprint. Moreover, Redstar carries out the contractions on either CPUs or GPUs utilizing an internal and highly efficient Hadron contraction library. Specifically, we illustrate some important algorithmic optimizations of Redstar, show various key design features of Hadron library, and present the speedup values due to the optimizations along with performance figures for calculating six correlations functions on four computing platforms.

Chen, Jie↗

DOE OSTI2024

Application of a Prize Mechanism to Address Data Utilization Challenges at Utilities

The electric industry sector is facing an “explosion” of data from a variety of sources. Electric sector stakeholders need to define how to capitalize on large datasets, both those they create and those from other sources (like data on weather, buildings, electric vehicles, etc.), to improve reliability and resilience and meet the changing system dynamics from renewable integration. For the electricity sector to fully utilize these vast new datasets, it must undergo a transformation in how it manages data quality, storage, and processing. The U.S. Department of Energy (DOE) Office of Electricity (OE) is committed to accelerating research, development, and demonstration of new technologies and tools within the electricity sector to advance reliability, resilience, and affordable operation of the power system. Through the prize mechanism, OE identified two widespread data-related challenges for utilities—load modeling and data analysis automation—and offered an opportunity for utilities and teams of software engineers to identify additional challenges faced by utilities. After completing one round of the American-Made Digitizing Utilities Prize, OE, the National Renewable Energy Laboratory (NREL) as the prize administrator, and Pacific Northwest National Laboratory (PNNL) as the domain experts have compiled the results and lessons learned to feed into the second round of the prize.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Refinement and Modeling of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing experiment searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, a sub-experiment of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD reflector setup allows for the focusing of all converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within 50 $\mu$m in three dimensions.

Rao, Shardul↗

DOE OSTI2024

Git and Software Tools for CTS

This presentation will provide an overview of the progress made helping the EDX4CCS, SMART, and NRAP projects virtualize their CO2 Transport and Storage software tools to boost their stakeholder availability through the DisCO2ver platform. This presentation will also cover helpful software development tools with a focus on researchers and developers who have not had formal training or many years of experience in software engineering best practices.

Zaengle, Dakota↗

DOE OSTI2024

Integration of the NCRC Database and Other INL Databases

The Nuclear Computational Resource Center provides a portal by which industry professionals, educational staff, students, national laboratory employees, and others may request access to certain engineering software tools. As the tools provided through the Nuclear Computational Resource Center portal are not open-source and freely available, a set of approvals are necessary before access is granted. All code recipients must be associated with an institution that has a license with Idaho National Laboratory for the code requested. Information about these licenses is controlled by Idaho National Laboratory’s Technology Deployment organization and housed in a Technology Deployment database. Those requesting code access who are not citizens of the United States must also have a security plan, mandated by Idaho National Laboratory policy. Security plans are managed by the International Access Program and are stored in an International Access Program database known as IFacts. Granting access to software thus depends on information stored in the Technology Deployment database and IFacts. In the past, no connection between the Nuclear Computational Resource Center portal and these databases existed, making checking the status of license agreements and security plans time consuming and error prone. This report demonstrates that the Nuclear Computational Resource Center portal now connects to both the Technology Deployment database and IFacts, greatly improving the ease of use of the Nuclear Computational Resource Center system for administrators, which leads to a better overall experience for those requesting code access.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Sandia Toolkit Manual (V.5.21.1)

This report provides documentation for the Sandia Toolkit (STK) modules. STK modules are intended to provide infrastructure that assists the development of computational engineering software such as finite-element analysis applications. STK includes modules for unstructured-mesh data structures, reading/writing mesh files, geometric proximity search, transfers, MPMD coupling support, and various other utilities. This document contains a chapter for each module, and each chapter contains overview descriptions and usage examples. Usage examples are primarily code listings which are generated from working test programs that are included in the STK code-base. A goal of this approach is to ensure that the usage examples will not fall out of date.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Sandia Toolkit Manual Version 5.15.6

This report provides documentation for the Sandia Toolkit (STK) modules. STK modules are intended to provide infrastructure that assists the development of computational engineering software such as finite-element analysis applications. STK includes modules for unstructured-mesh data structures, reading/writing mesh files, geometric proximity search, and various utilities. This document contains a chapter for each module, and each chapter contains overview descriptions and usage examples. Usage examples are primarily code listings which are generated from working test programs that are included in the STK code-base. A goal of this approach is to ensure that the usage examples will not fall out of date.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

OpenCSP Step-by-Step: Getting Started Guide for Windows (V.1.0)

This document provides a step-by-step tutorial on how to set up OpenCSP for both users and developers. It is meant to support novice users and does not require software engineering experience. It is a detailed extension of the OpenCSP getting started on-line documentation, found here: https://opencsp.readthedocs.io/en/main/contributing.html#getting-started. For an overview of OpenCSP overall, see the OpenCSP website: https://opencsp.sandia.gov. For details on OpenCSP components and algorithm, see the references.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Blueprint: Coordinated Vulnerability Disclosure (CVD) Adoption for Information Sharing and Analysis Center (ISAC)-Like Groups

The electric vehicle supply equipment (EVSE) industry is an incredibly diverse set of participants (EVSE manufacturers, charge network operators (CNOs), original equipment manufacturers (OEMs), etc.), and with the potential for an Information Sharing and Analysis Centers (ISAC) or ISAC-like group, it requires a series of guidance for doing a multiparty coordinated vulnerability disclosure (CVD) such that a group like this could be successful. This blueprint provides a template and guidance to stakeholders in the EVSE industry for conducting a multiparty CVD. It also formalizes what multiparty CVD could look like in an ISAC-like group with multiple entities as well as vulnerability coordinators by specifically calling out who in the ISAC-like group may be involved, and which industry members it may apply to. This blueprint leverages tools such as Vultron, VINCE, etc. along with open resources such as the Software Engineering Institutes guide for coordinated vulnerability disclosure, for the stakeholder in the EVSE industry to start up a CVD program of their own.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Blueprint: Coordinated Vulnerability Disclosure (CVD) Adaption and Adoption Guide for Industry To Create Their Own CVD Program

This guide provides a series of steps and guidance for electric vehicle supply equipment (EVSE) industry members to set up their own coordinated vulnerability disclosure (CVD) program by utilizing the Software Engineering Institute/Computer Emergency Response Team (SEI/CERT)’s CVD how-to guide. Due to the complexity of CVD, and with the existing resources out there, this guide is intended that this portion of the blueprint is an extension of the CVD how-to guide, not meant as a replacement. This guide is meant to outline a process for what to do when you discover a vulnerability on EVSE equipment. It is written for developers, vendors and security researchers as well as management. This is not a technical document. It is meant to be accessible for both technical and non-technical roles.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

The Benefits and Weaknesses of Containerizing Software for HPC

Containerization technology has emerged as a transformative tool for software engineers, offering consistent development and deployment environments, simplifying dependency management, and enhancing scalability and portability across diverse systems. However, its application in High-Performance Computing (HPC) presents unique challenges, including the management of virtualization overhead, the need for efficient resource allocation, and the maintenance of optimal performance for compute-intensiv

Ho, Eric Victor [Sandia National Laboratories (SNL↗

DOE OSTI2026

Reference Hardware and Software Architecture for a Solenoid Pulser for Scientific Instrumentation at the National Ignition Facility

High current, high voltage solenoid pulser power systems for the generation of magnetic fields in a solenoid is not a radical or new concept. Despite being a cornerstone of scientific and weapons research for over 100 years, a commercial off the shelf unit easily configurable for a broad set of applications has yet to appear on the open market. Pulser systems are instead designed for specific target requirements. For gigawatt to terawatt systems, this is unavoidable. For megawatt systems however, many hundreds of thousands of dollars are wasted designing pulser systems from the ground up for clients, when it is possible to simply architect a modular system once that can have its capacitors swapped for many possible target applications. The National Ignition Facility (NIF) at the Lawrence Livermore National Laboratory (LLNL) is one such institution that would benefit from such a system, having bought such pulsers for several imaging systems. Ideally, all such a system would require is only a bachelors-level circuit analysis to find the correct capacitor values, as well as a written procedure to calibrate the software to correctly deliver the voltages required by the application. In this work, systems architecture and software engineering techniques are used to design and analyze such a system. Such a design, it is the hope of this author, will be used in scientific and engineering purposes in the future to build solenoid pulsers at the National Ignition Facility and other institutions to drastically cut development costs of scientific instrumentation.

42 ENGINEERING↗

DOE OSTI2026

Knowledge Graph for End-to-End Traceability of an Integrated Human-Earth System Model

Integrated human-Earth system models inform energy-water-land system dynamics and policies, yet their results are difficult to trace through input-data, model structure, scenario configurations, and solved outputs. Because this information is siloed across disconnected artifacts, process-based IAMs have historically lacked a unified, queryable representation. Such lack of traceability prevents researchers from systematically isolating the multi-sector drivers of complex outcomes (such as tracing water-scarcity results back to distant energy-system dynamics) or conducting holistic uncertainty attribution across hundreds of interacting parameters. To address this concern, our work documents the software engineering process of a knowledge graph that unifies these four layers for the Global Change Analysis Model (GCAM-USA_Reference scenario, GCAM v9.1). The graph was built as a relational property graph in DuckDB from the run’s own artifacts: the input-preparation dependency map (gcamdata chunk map), the model’s XML input files, the run configuration, and the results database (BaseX), successfully mapping the model’s declared structure. The resulting graph comprises 204,321 nodes and 1,687,814 edges across 16 node types and 15 edge types, with approximately 16.3 million time-series values stored separately to maintain structural efficiency. To ensure representation fidelity, every edge carries an epistemic-status annotation recording the warrant for the relationship (structural, provenance, dependency, or model-derived), and a machine-readable provenance ledger classifying the origin of every schema element. Evaluation against a fixed five-benchmark suite with locked baselines reports zero structural orphans, zero dangling edge endpoints, and 100% of output-producing technologies traceable to raw input files. Two interactive interfaces present the graph, including a serverless browser application built on DuckDB-Wasm. By establishing the first end-to-end provenance framework for an IAM, this work enables researchers and scientists to systematically audit complex policy scenarios, debug model structures, and trace policy-relevant outputs to their data origins in real time.

Artifical Intelligence↗

DOE OSTI2022

How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

Space weather refers to conditions around a star, like our Sun, and its interplanetary space that may affect space- and ground-based assets as well as human life. Space weather can manifest as many different phenomena, often simultaneously, and can create complex and sometimes dangerous conditions. The study of space weather is inherently trans-disciplinary, including subfields of solar, magnetospheric, ionospheric, and atmospheric research communities, but benefiting from collaborations with policymakers, industry, astrophysics, software engineering, and many more. Effective communication is required between scientists, the end-user community, and government organizations to ensure that we are prepared for any adverse space weather effects. With the rapid growth of the field in recent years, the upcoming Solar Cycle 25 maximum, and the evolution of research-ready technologies, we believe that space weather deserves a reexamination in terms of a “risk and resiliency” framework. By utilizing open data science, cross-disciplinary collaborations, information systems, and citizen science, we can forge stronger partnerships between science and industry and improve our readiness as a society to mitigate space weather impacts. The objective of this manuscript is to raise awareness of these concepts as we approach a solar maximum that coincides with an increasingly technology-dependent society, and introduce a unique way of approaching space weather through the lens of a risk and resiliency framework that can be used to further assess areas of improvement in the field.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗