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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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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Nuclear Quality Assurance Certification of the MCNP-ORIGEN Activation Automation tool

The MCNP-ORIGEN Activation Automation (MOAA) tool couples MCNP and ORIGEN-S, allowing to support ATR and TREAT experiments by predicting their composition and activity before their irradiation takes place. MOAA is developed and maintained by the Irradiation Experiment Neutronics Analysis group (C-150) at INL. This poster presents the motivation behind the development of MOAA, its main workflow, as well as the software quality assurance (SQA) efforts required by LWP-13620, "Managing Information Technology Assets."

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Toolpath considerations for DED: Arc and laser welding

Directed energy deposition (DED) is a form of additive manufacturing that uses localized melted metal, similar to traditional arc welding, to construct an object. In comparison to polymer systems, metal systems can exert additional control over the build process through manipulation of the pool of melted metal, called the “melt pool.” This is especially important to maintain appropriate layer heights and create high quality builds. Additionally, metal systems allow site-specific control of the printed part, which enables advanced construction techniques that would otherwise not be possible. However, both of these types of control require support from the slicing software and, potentially, sensor feedback. This chapter will discuss these control processes and their basic implementation in a slicing program. The processes described here lay the foundation for more advanced solutions, particularly sensor feedback, that will be discussed later.

Borish, Michael↗
DOE OSTI2024

Standardized Protocol for Real-Time APIs as Required by Title 23 CFR 680.116(c)

Improving the ability of drivers to easily locate working and available chargers is key to improving the public charging experience. Electric vehicle charging providers who are recipients of federal funds through the National Electric Vehicle Infrastructure (NEVI) Formula Program, Charging and Fueling Infrastructure (CFI) Discretionary Grant Program, and other funding programs as identified under Title 23 of the U.S. Code must deploy and maintain an application programming interface (API) to access information about charging stations they operate.1 This includes information about individual charging ports, pricing, and availability in accordance with the Federal Highway Administration’s National Electric Vehicle Infrastructure Standards and Requirements, 23 CFR 680.116(c), herein referred to as the minimum standards (Federal Highway Administration 2023). Specifically outlined in the minimum standards, states and other designated recipients are required to ensure that charging station information including location, connector type, power level, real-time status, and real-time price to charge are available free of charge to third-party software developers through an API. These requirements are intended to enable effective communication with consumers about available charging stations and help consumers make informed decisions about trip planning, including when and where to charge. This document provides a standardized protocol for how to structure data, data update frequency, and practices for making the data required to be shared via API usable for improving public transparency and the customer experience. These are recommendations only and do not modify the Federal Highway Administration’s minimum standards in any way.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Requirements for Cataloging Hanford Geophysical Datasets

Environmental management activities at the Hanford Site produce extensive data about site conditions, contaminants, cleanup, and more. Managing and archiving that data requires a high degree of collaboration among site contractors and a high level of awareness by project managers and staff. Part of that effort is developing a Hanford Environmental Information and Data Index (HEIDI) to organize the data and maximize its value by making it findable and available for reuse. The objective is to catalog the disparate data sets collected to address the evolving needs of planning, executing, and documenting cleanup over several decades up to the present day, including links to active data sources when available. A properly implemented data catalog makes finding environmental datasets related to an area or theme a routine, reliable process, without requiring the searcher to have special knowledge that a data set exists and where it may be stored. In this project, a working group, including the U.S. Department of Energy, the Hanford Site contractors, and Pacific Northwest National Laboratory staff, identified needs and requirements for handling complex site data. Geophysical data was chosen as a test case because it can be large and complex and often involves multiple processing steps to extract the information incorporated into deliverables. The ability to document those steps was one of the requirements identified for the catalog. In addition to developing requirements, other activities included selecting a metadata schema and initial testing with the objective of determining whether the workflow and capabilities of selected data catalog software platforms were sufficient to implement and impose the identified requirements. This initial testing involved running the default catalog instance using the software platform of interest and altering the configuration to achieve each requirement, if possible. Where configuration alone was insufficient, the possibility of modifying the software by changing the code was examined, but not implemented. A follow-on task is planned to reprogram the code as necessary to implement requirements in a prototype catalog.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Quantum Application Specifications and Benchmarks

This software describes computational tasks for quantum computers that are derived from LANL basic science research applications such as the modeling of materials, chemicals and compounds at atomic scales. The computations focus on quantum simulation tasks, such as quantum dynamics, thermal state preparation and ground state estimation. The primary function of the software is to develop estimates of the requirements for large-scale fault-tolerant quantum computers to solve these scientific computations. The secondary focus of the software are codes for assessing the limitations of conducting quantum computations on classical computers.

Coffrin, Carleton↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

ORNL Package Testing Program Software Quality Assurance Plan

The Oak Ridge National Laboratory (ORNL) Package Testing Program (PTP) uses commercial off-the-shelf (COTS) software in performing data collection of thermal test results for package designs that contain radioactive materials. Specifically, this software is used to collect temperature data from the furnace, packages, and ambient air to prepare and execute the thermal test specified in 10 CFR 71.73, “Thermal Test.” This software quality assurance (SQA) plan sets forth the guidelines, standards, and procedures that shall be used to provide SQA for PTP software applications. This is a living document that will be maintained for the lifecycle of the PTP program. The SQA plan follows the requirements set forth in ORNL Standards Based Management System (SBMS): Information Technology; Subject Area: Software Quality Assurance. When applicable to the requirements as described in ORNL SBMS, Software Quality Assurance, the software shall be listed in the ORNL Software Registration System (SRS). Exemptions to this SBMS are COTS and firmware that are not modified; spreadsheet applications and personal productivity tools that do not have a utility or safety application, research applications, legacy software, system software, vendor-supplied software used to interface with the vendor’s services, software used within the organization to facilitate processing or management of information, and software developed for applications not specific to the US Department of Energy (DOE).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Walnut v1.2 Code Abstract

Abstract for publication for copyright assertion for Walnut v1.2 software code to satisfy prime contract requirements. HQ approval to assert copyright on this code was granted to NNSS on 9/30/2024

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Python Group Additivity (pGrAdd) software for estimating species thermochemical properties

ncreasingly complex chemistry models require thermochemical data for many species often estimated from costly first-principles DFT computations. Here we introduce the Python Group Additivity software (pGrAdd) that implements comprehensive group additivity in a simple, modular, lightweight Python package that is extensible and easy to implement. It includes 6 group additivity databases for gas species and Pt(111) adsorbates allowing users to immediately compute thermochemical properties for a wide range of molecules and build new databases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

DR-RINS: Digital real-time relative intensity noise suppressor for pump–probe spectroscopy and microscopy

Relative intensity noise (RIN) inherent in fiber lasers poses a serious obstacle to their use in pump–probe spectroscopy and imaging. RIN can be removed through an analog balanced detector, or, as we have previously shown, software adaptive noise cancellation (ANC) on digitized signals. One major drawback to software ANC is the added time required for digitizing and post-processing. In this article, we describe a design for ANC on a field-programmable gate array (FPGA), making use of high-level synthesis tools and fixed-point arithmetic to achieve real-time laser RIN suppression at 25 MHz sample rates. Unlike the software-ANC approach, the FPGA-ANC device can serve as a dedicated drop-in denoiser, placed between the detectors and a commercial lock-in amplifier. We demonstrate its application to transient absorption spectroscopy and microscopy, lowering the noise floor to ~17 dB above the shot noise limit. Furthermore, we demonstrate a dramatic improvement in data acquisition time from ~6 h to ~5 min in a real-time imaging scenario.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Implementing a Hardware Testbed Using 3-Level ANPC Software Defined Inverters for Fault Analysis of a Transmission Network

In this paper, we propose the implementation of a hardware testbed using 3-level active neutral point clamped (ANPC) software-defined inverters for fault analysis. A test case transmission network equipped with two grid forming (GFM) inverters and four resistive loads is considered in this research. Firstly, grid forming control laws including PI feedback control and droop control are implemented to operate the inverters in parallel. Then, we implement a fault ride-through (FRT) logic and perform a simulation of the test system by applying a three-phase fault. Simulation results show the effectiveness of the fault recovery algorithm upon clearance of the fault. Finally, a 3-level ANPC software-defined inverter is programmed with required control laws and characterized through various lab experiments.

3-level ANPC inverter↗
DOE OSTI2024

Multi-Tiered Estimation for Correlation Spectroscopy in 3D (MTECS3D) v0.1

This innovative software estimates rotational diffusion coefficients of particles from X-ray photon correlation spectroscopy (XPCS) data of monodispersed particle systems. It is the first method capable of extracting rotational diffusion information from three-dimensional particle systems using XPCS. Using the angular-temporal cross-correlation of the XPCS images, this software is able to estimate the rotational diffusion coefficients with only a few percent relative errors while requiring minimal prior knowledge of particle structures. This software enhances XPCS analysis capabilities, allowing researchers to study translational and rotational Brownian dynamics of particles in suspension across various temporal and spatial scales.

Hu, Zixi↗
DOE OSTI2023

2023 FORCE Development Status Update

Technical and economic analysis of integrated energy systems (IES) using software models is a complex process requiring multiple commodity market decision analysis, optimal control, process modeling, and stochastic analysis. Many assumptions used in traditional energy analysis tools do not hold in future energy markets with significant storage and variable renewable energy sources (VRE), let alone with multiple commodity markets. Capturing these intricate elements for accurate techno-economic analysis of IES led to the development of the Framework for Optimization of ResourCes and Economics (FORCE) tool suite under the U.S. Department of Energy’s Integrated Energy Systems crosscutting technology program. With the aim of a full framework release in 2025, many improvements to the FORCE tool suite were developed in fiscal year 2023 (FY23). These improvements broadly fit into three focuses for development of FORCE: capability, accessibility, and reliability. Capability refers to the ability of FORCE to accurately model the technical and economic viability of various IES. Accessibility refers to ease-of-use for new and existing IES analysts to efficiently set up, analyze, and produce results using FORCE. Reliability refers to the consistency of the software, allowing consistency to analysis regardless of erstwhile changes to the software. In addition to many smaller changes, there are three major capability improvements in FORCE in FY23. In summary, FORCE developments in FY23 have moved us close to all the capability requirements for FORCE 1.0 to be delivered in FY25. Inclusion of Bayesian optimization, resilience metrics, and levelized cost analysis expand the capability, accessibility, and reliability of FORCE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation (Workshop Report)

The Artificial Intelligence Enhanced Co-Design for Next Generation Microelectronics virtual workshop was held April 4-5, 2023, and attended by subject matter experts from universities, industry, and national laboratories. This was the third in a series of workshops to motivate the research community to identify and address major challenges facing microelectronics research and production. The 2023 workshop focused on a set of topics from materials to computing algorithms, and included discussions on relevant federal legislation and such as the Creating Helpful Incentives to Produce Semiconductors and Science Act (CHIPS Act) which was signed into law in the summer of 2022. Talks at the workshop included edge computing in radiation environments, new materials for neuromorphic computing, advanced packaging for microelectronics, and new AI techniques. We also received project updates from several of the Department of Energy (DOE) microelectronics co-design projects funded in the fall of 2021, and from three of the Energy Frontier Research Centers (EFRCs) that had been funded in the fall of 2022. The workshop also conducted a set of breakout discussions around the five principal research directions (PRDs) from the 2018 Department of Energy workshop report: 1) define innovative material, device, and architecture requirements driven by applications, algorithms, and software; 2) revolutionize memory and data storage; 3) re-imagine information flow unconstrained by interconnects; 4) redefine computing by leveraging unexploited physical phenomena; 5) reinvent the electricity grid through new materials, devices, and architectures. We tasked each breakout group to consider one primary PRD (and other PRDs as relevant topics arose during discussions) and to address questions such as whether the research community has embraced co-design as a methodology and whether new developments at any level of innovation from materials to programming models requires the research community to reevaluate the PRDs developed back in 2018.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Energy Material Network Data Hubs

In early 2015 the United States Department of Energy conceived of a consortium of collaborative bodies based on shared expertise, data, and resources that could be targeted towards the more difficult problems in energy materials research. The concept of virtual laboratories had been envisioned and discussed earlier in the decade in response to the advent of the Materials Genome Initiative and similar scientific thrusts. To be effective, any virtual laboratory needed a robust method for data management, communication, security, data sharing, dissemination, and demonstration to work efficiently and effectively for groups of remote researchers. With the accessibility of new, easily deployed cloud technology and software frameworks, such individual elements could be integrated, and the required collaboration architecture is now possible. The developers have leveraged open-source software frameworks, customized them, and merged them into a platform to enable collaborative energy materials science, regardless of the geographic dispersal of the people and resources. After five years in operations, the systems are demonstratively an effective platform for enabling research within the Energy Material Networks (EMN). This paper will show the design and development of a secured scientific data sharing platform, the ability to customize the system to support diverse workflows, and examples of the enabled research and results connected with some of the Energy Material Networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Verification of the REBUS Software

Ongoing design activities at Argonne National Laboratory are requiring a thorough verification of the Argonne Reactor Computation codes be performed. REBUS is central to this system. The driver for this effort requires the Triangular-Z and hexagonal-Z core geometry options of REBUS to be verified. Previous work identified the REBUS features required to be verified to support current design activities, features of which are generally applicable to hexagonal-Z fast reactor designs. The scope of this verification effort includes verifying REBUS’s ability to correctly intepret the user input model, verifying that the features identified yield the intended results, and verifying the correctness of the REBUS output tables. The REBUS software verification relies heavily upon the accuracy of the embedded DIF3D software, the verification of which was completed and documented elsewhere. Given that DIF3D produces an accurate solution, the primary focus of the verification in the REBUS software is to ensure that it properly uses the DIF3D solution and that the depletion system (Bateman equations) are correctly implemented. This manuscript reiterates the verification tasks and displays results with respect to the features needed for current design activities. Analytic solutions of the Batemen equations are displayed and the results calculated with REBUS are displayed demonstrating the accuracy. Since coupled Bateman and neutron diffusion/transport solutions are extremely difficult to obtain, much of the focus is placed on how REBUS uses a given DIF3D solution assuming the accuracy of the DIF3D solution. The verification effort identified no issues that are debilitating or otherwise impactful to the design usage of REBUS, and thus REBUS version 11.0, release 3012 is considered verified. It is important to note that several outputs of REBUS are identified to be inaccurate, such as burnup in MWD/MT. Most of the relevant ones for VTR are generally accurate with 10-20% errors which is not impactful as all regular REBUS users are aware of this issue and know how to hand calculate the results. The REBUS manual further makes it clear that these values are consistent with the methodology being used by REBUS and thus the “errors” are more of an inconsistent definition with respect to what a user would expect given a definition in literature. Other issues that were identified included unclear documentation and software bugs all of which were inconsequential to the final results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

DFT-based QM/MM with Particle-Mesh Ewald for Direct, Long-Range Electrostatic Embedding

In this work, we present a DFT-based, QM/MM implementation with long-range electrostatic embedding achieved by direct real-space integration of the particle mesh Ewald (PME) computed electrostatic potential. The key transformation is the interpolation of the electrostatic potential from the PME grid to the DFT quadrature grid, from which integrals are easily evaluated utilizing standard DFT machinery. We provide benchmarks of the numerical accuracy with choice of grid size and real-space corrections, and demonstrate that good convergence is achieved while introducing nominal computational overhead. Furthermore, the approach requires only small modification to existing software packages, as is demonstrated with our implementation in the OpenMM and Psi 4 software. After presenting convergence benchmarks, we evaluate the importance of long-range electrostatic embedding in three solute/solvent systems modeled with QM/MM. Water and BMIM/BF 4 ionic liquid were considered as "simple" and "complex" solvents respectively, with water and p-phenylenediamine (PPD) solute molecules treated at QM level of theory. While electrostatic embedding with standard real-space truncation may introduce negligible error for simple systems such as water solute in water solvent, errors become more significant when QM/MM is applied to complex solvents such as ionic liquids. An extreme example is the electrostatic embedding energy for oxidized PPD in BMIM/BF 4 for which real-space truncation produces severe error even at 2-3 nm cutoff distances. This latter example illustrates that utilization of QM/MM to compute redox potentials within concentrated electrolytes/ionic media requires carefully chosen long-range electrostatic embedding algorithms, with our presented algorithm providing a general and robust approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗