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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2021

Universal Utility Data Exchange (UUDEX) Phase 4 Demonstration Environment and Results

This report provides an overview of the environment used by the Pacific Northwest National Laboratory (PNNL) in the Universal Utility Data Exchange (UUDEX) Phase 4 demonstration, and description of the demonstrations performed in the environment. The UUDX Phase 4 demonstration took place on March 31, 2021, with representatives from PNNL and the two project sub-contractors, OATI and MITRE, performing the demonstration for members of the UUDEX Industry Advisory Board (IAB). The demonstration tasks were based on the previous Phase 3 demonstration but conducted in a multi-site environment. Additional demonstrations showed features that were developed since the Phase 3 demonstration. The development environment was constructed by PNNL programming staff using the previously developed UUDEX Functional Design, Protocol Design, and Workflow Design documents as a starting point. The environment was augmented with subject creation management and access control security data structures and workflows, and data exchange structure documents developed as part of Phase 3 and Phase 4.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Closeout report for statistics for environmental sampling

This Project Closure Report is the final project document required to complete the project record and to close the project in the office’s web-based project management system. This report is for use by senior management to assess major project outcomes and their impact, identify best practices and other useful insights for future projects, and identify any open issues meriting attention. In accordance with DOE Order 243.1B, Records Management Program, this report will be managed in accordance with all prescribed laws, regulations, directives, and processes to ensure adequate and proper documentation of DOE’s organizations, missions, functions, policies, and decisions (See 44 U.S.C., Chapters 21, 29, 31, 33, and 35; 36 CFR Subchapter B, Records Management, and all applicable National Archives and Records Administration (NARA) mandated guidance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

DOE Fffice of Nuclear Energy cybersecurity research, development and demonstration program plan

This document describes the Cybersecurity Research Development and Demonstration (RD&D) Program, established by the Department of Energy Office of Nuclear Energy (NE) to provide sciencebased methods and technologies necessary for cost-effective, cyber-secure digital instrumentation, control and communication in collaboration with nuclear energy stakeholders. It provides an overview of program goals, objectives, linkages to organizational strategies, management structure, and stakeholder and cross-program interfaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Overview of the Second Workshop on Scholarly Document Processing

With the ever-increasing pace of research and high volume of scholarly communication, scholars face a daunting task. Not only must they keep up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. These needs have motivated an increasing focus on computational methods for enhancing search, summarization, and analysis of scholarly documents. However, the various strands of research on scholarly document processing remain fragmented. To reach out to the broader NLP and AI/ML community, pool distributed efforts in this area, and enable shared access to published research, we held the 2nd Workshop on Scholarly Document Processing (SDP) at NAACL 2021 as a virtual event (https://sdproc.org/2021/). The SDP workshop consisted of a research track, three invited talks, and three Shared Tasks (LongSumm 2021, SCIVER, and 3C). The program was geared towards the application of NLP, information retrieval, and data mining for scholarly documents, with an emphasis on identifying and providing solutions to open challenges.

Beltagy, Iz↗
DOE OSTI2025

High-Performance Computing Based EMT Simulation: Power Grid with IBRs

Electromagnetic transient (EMT) simulation of power grids with high-fidelity models of inverter-based resources (IBRs) is time-consuming and difficult to scale. The necessity for high-fidelity models of IBRs that incorporate the dynamics of individual inverters within IBRs has been showcased in recent studies. These studies focused on events with partial power reduction in each IBR during a transmission line fault in the power grid. These types of events have been documented in multiple North American Electric Reliability Council (NERC) reports in the past decade. It is imperative then to find solutions to speed-up EMT simulations and scale the size of the region with IBRs studied in EMT simulations. In this paper, a combination of numerical simulation algorithms with high-performance computing techniques are employed in discretization and linear solvers employed in the proposed RE-INTEGRATE EMT simulation platform for power grid with IBRs. For ease of scalability, modular and object-oriented programming is used as these techniques are implemented. Additionally, automation software is developed to convert legacy software codes to the proposed RE-INTEGRATE EMT simulation platform. Thereafter, this platform is evaluated on multi-core central processing units (CPUs). Finally, scale-up tests are performed to showcase the scalability that is possible.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗
DOE OSTI2021

Bayesian Monte-Carlo Evaluation Framework for Imperfect Nuclear Data [Slides]

BMC evaluation is a tool used to address imperfect data and models, non-linear models, and non-normal PDFs. ENDF-6 format does not allow non-normal parameter PDFs. Storing posterior sets allows for variance, covariance, skewness, etc. To better predict criticality, we should document non-normal parameter PDFs (i.e. asymmetric uncertainty) and consider non-linear sensitivity of $k_{\text{eff}}$ to resonance parameters.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

FAST-1.0.1 User Installation and Verification Guide

The purpose of this document is to provide the user information about the installation of FAST-1.0.1 on their computers or servers. General information about the code and supported operating systems is described in Section 1.0.1. Self-service oriented FAST-1.0.1 software licensing steps are described in Section 2.0. An installation verification test suite is provided with FAST-1.0.1 and described in Section 3.0. A convenience script for converting FRAPCON to FAST inputs is discussed in Section 4.0. FAST-1.0.1 was developed and released under a software quality assurance program based upon NQA-1-2017. FAST-1.0.1 is the latest baseline code and the result of a bug fixes to FAST-1.0 with other software and methodology developments. The installation verification test suite contains both steady state and transient Anticipated Operation Occurrences (AOOs). Capability to model accident conditions, such as Reactivity Initiated Accidents (RIAs) and Loss Of Coolant Accidents (LOCAs), are targeted for a later release of FAST. FRAPTRAN-2.0 will continue to be used for accident conditions until the release of FAST with accident condition modeling capabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI1978

Plant Engineers Solar Energy Handbook: Southern California Region

Discussed in order after the introduction are solar components and systems (collectors, storage, service hot water systems, space heating with liquid and air systems, space cooling, heat pumps and controls); computer programs for system optimization; local solar and weather data; a description of buildings and plants in Southern California applying solar technology; current Federal and California solar legislation; standards, codes and performance testing information; a listing of manufacturers, distributors, and professional services available in Southern California region; and information access. Finally, solar design check lists for those engineers who wish to design their own systems. The program for the Solar Workshop for the Plant Engineer, March 30, 1978, Los Angeles, California is included.

14 SOLAR ENERGY↗
DOE OSTI2019

Optimization and Verification of FRAM (V.6.1) Parameter Sets

FRAM (Fixed-energy Response-function Analysis with Multiple efficiency) is a program developed at Los Alamos National Laboratory that determines actinide isotopic composition by analyzing gamma-ray spectra of special nuclear material. This report documents the creations of the parameter sets and the performance (bias and precision) of FRAM version 6.1, scheduled for release in late 2019 – early 2020.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications

Run to run variability in parallel programs caused by floating-point non-associativity has been known to significantly affect reproducibility in iterative algorithms, due to accumulating errors. Non-reproducibility can critically affect the efficiency and effectiveness of correctness testing for stochastic programs. Recently, the sensitivity of deep learning training and inference pipelines to floating-point non-associativity has been found to sometimes be extreme. It can prevent certification for commercial applications, accurate assessment of robustness and sensitivity, and bug detection. New approaches in scientific computing applications have coupled deep learning models with high-performance computing, leading to an aggravation of debugging and testing challenges. Here we perform an investigation of the statistical properties of floating-point non-associativity within modern parallel programming models, and analyze performance and productivity impacts of replacing atomic operations with deterministic alternatives on GPUs. We examine the recently-added deterministic options in PyTorch within the context of GPU deployment for deep learning, uncovering and quantifying the impacts of input parameters triggering run to run variability and reporting on the reliability and completeness of the documentation. Finally, we evaluate the strategy of exploiting automatic determinism that could be provided by deterministic hardware, using the Groq LPUTM accelerator for inference portions of the deep learning pipeline. We demonstrate the benefits that a hardware-based strategy can provide within reproducibility and correctness efforts.

Shanmugavelu, Sanjif↗
DOE OSTI2020

Application Note: Mixed Signal Simulation with Xyce™ 7.1

This application note describes how Release 7.1 of the Xyce circuit simulator can be coupled with external simulators via either a Python-based interface that leverages the Python ctypes foreign function library or via the Verilog Procedural Interface (VPI). It also documents the usage of these interfaces on RHEL7 with Python 2.6 or 2.7. These interfaces are still under development and may change in the future. So, a key purpose of this application note is to solicit feedback on these interfaces from both internal Sandia Xyce users and other performers on the DARPA Posh Open Source Hardware (POSH) program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Universal Utility Data Exchange (UUDEX) – Protocol Design - Rev 1

This design document describes protocol related aspects of Universal Utility Data Exchange (UUDEX). The focus of the design is to describe the interactions between UUDEX Clients and UUDEX Servers in the UUDEX Infrastructure. This design is purposely transport and programming language agnostic.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Energy Management Information Systems Cybersecurity Best Practices

Energy management information systems (EMIS) are a broad and rapidly evolving family of tools that monitor, analyze, and control building energy use and system performance. Critical systems are often integrated with or operate on the same networks as EMIS scope systems, necessitating stable, continuous, and secure communication. When connecting EMIS to building automation and utility control systems, there are also many physical assets that could cause harm to the building and its occupants if a malicious act or human error were introduced. It is imperative to ensure all EMIS scope systems are connected securely to the EMIS and do not open vulnerable pathways to other facility networks and operations. The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of EMIS at federal facilities. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. It provides an overview of required EMIS cybersecurity standards for compliance and authority to operate along with additional recommendations.

cybersecurity↗
DOE OSTI2024

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

2020 High Energy Physics Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all of its laboratories and facilities in the United States and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. Throughout 2020,ESnet and the Office of High Energy Physics (HEP) of the DOE SC organized an ESnet requirements review of HEP-supported activities. Preparation for this event included identification of key stakeholders: program and facility management, research groups, technology providers, and a number of external observers. These individuals were asked to prepare formal case study documents about their relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion. ESnet and ASCR use requirements reviews to discuss and analyze current and planned science use cases and anticipated data output of a particular program, user facility, or project to inform ESnet’s strategic planning, including network operations, capacity upgrades, and other service investments. A requirements review comprehensively surveys major science stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Application Note: Mixed Signal Simulation with Xyce™

This application note describes how the Xyce circuit simulator can be coupled with external simulators via either a Python-based interface that leverages the Python ctypes foreign function library or via the Verilog Procedural Interface (VPI). It also documents the usage of these interfaces on RHEL6 and RHEL7, with Python 2.6 or 2.7. These interfaces are still under development and may change in the future. So, a key purpose of this application note is to solicit feedback on these interfaces from both internal Sandia Xyce users and other performers on the DARPA Posh Open Source Hardware (POSH) program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

FrESCO: Framework for Exploring Scalable Computational Oncology

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information from electronic health records. This data is then used to create summary statistics about cancer incidence and mortality to facilitate population health monitoring. Extracting phenotypic information from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating the information extraction process from cancer pathology reports has the potential to improve data quality by extracting information in a consistent manner across registries. It can also improve patient outcomes by reducing the time from diagnosis, enabling rapid case ascertainment for clinical trials. Here we present FrESCO, a modular deep-learning natural language processing (NLP) library initially designed for extracting pathology information from clinical text documents. This repository is not solely limited to clinical medical text, but may also be used by researchers just getting started with NLP methods and those looking for a robust solution for their classification problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Software Quality Assurance Plan: Cardinal

The Cardinal Software Quality Assurance (SQA) Program aims to provide the controls and processes necessary to enable continuous, high-quality software development while meeting user and program sponsor requirements. This SQA Plan (SQAP) delineates the SQA Program framework for Cardinal by describing the Program activities, organization, and documentation, and by clearly defining the interconnection of all Program items. It should be noted that this SQAP is aligned with the current version of the Argonne Quality Assurance Program Plan, which was designed to align with DOE O 414.1D. This SQAP is also aligned with the revision 10 of the SQAP for MOOSE and MOOSE-based applications.

97 MATHEMATICS AND COMPUTING↗