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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Barriers to adopting artificial intelligence and machine learning technologies in nuclear power

Artificial intelligence and machine learning (AI/ML) technologies offer unique opportunities to transform nuclear plant operations and power generation. Benefits will be felt not only within existing analog and digital instrumentation and control, but also within work processes, the integration of people with technology and most importantly, the business case. The application of this new technology can help simplify complex problems and produce more effective decision-making, making nuclear power safer, more efficient, and more economically viable in the current energy market. Nonetheless, there are potential barriers to its adoption that must be overcome. The purpose of this paper is to categorize, review, and discuss barriers to AI/ML adoption within the nuclear power industry, with a focus on existing commercial reactors. Unique considerations for advanced reactors are also offered. Here we provide a comprehensive overview of the historical, technical, and business barriers that the industry faces, as well as stakeholder readiness, and end-user acceptance. We underscore the importance of user experience and offer potential solutions in overcoming each barrier. These include provisions for easier plant data access, a friendly regulatory environment, and investment in user trust and explainable AI.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Programmable soft valves for digital and analog control

In soft devices, complex actuation sequences and precise force control typically require hard electronic valves and microcontrollers. Existing designs for entirely soft pneumatic control systems are capable of either digital or analog operation, but not both, and are limited by speed of actuation, range of pressure, time required for fabrication, or loss of power through pull-down resistors. Using the nonlinear mechanics intrinsic to structures composed of soft materials—in this case, by leveraging membrane inversion and tube kinking—two modular soft components are developed: a piston actuator and a bistable pneumatic switch. These two components combine to create valves capable of analog pressure regulation, simplified digital logic, controlled oscillation, nonvolatile memory storage, linear actuation, and interfacing with human users in both digital and analog formats. Three demonstrations showcase the capabilities of systems constructed from these valves: 1) a wearable glove capable of analog control of a soft artificial robotic hand based on input from a human user’s fingers, 2) a human-controlled cushion matrix designed for use in medical care, and 3) an untethered robot which travels a distance dynamically programmed at the time of operation to retrieve an object. This work illustrates pathways for complementary digital and analog control of soft robots using a unified valve design.

42 ENGINEERING↗
DOE OSTI2020

Nanofabrication of synthetic nanoporous geomaterials: from nanoscale-resolution 3D imaging to nano-3D-printed digital (shale) rock

Abstract Advances in imaging have made it possible to view nanometer and sub-nanometer structures that are either synthesized or that occur naturally. It is believed that fluid dynamic and thermodynamic behavior differ significantly at these scales from the bulk. From a materials perspective, it is important to be able to create complex structures at the nanometer scale, reproducibly, so that the fluid behavior may be studied. New advances in nanoscale-resolution 3D-printing offer opportunities to achieve this goal. In particular, additive manufacturing with two-photon polymerization allows creation of intricate structures. Using this technology, a creation of the first nano-3D-printed digital (shale) rock is reported. In this paper, focused ion beam-scanning electron microscopy (FIB-SEM) nano-tomography image dataset was used to reconstruct a high-resolution digital rock 3D model of a Marcellus Shale rock sample. Porosity of this 3D model has been characterized and its connected/effective pore system has been extracted and nano-3D-printed. The workflow of creating this novel nano-3D-printed digital rock 3D model is described in this paper.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Results of an interlaboratory study on the working curve in vat photopolymerization

The working curve informs resin properties and print parameters for stereolithography, digital light processing, and other photopolymer additive manufacturing (PAM) technologies. First demonstrated in 1992, the working curve measurement of cure depth vs radiant exposure of light is now a foundational measurement in the field of PAM. Despite its widespread use in industry and academia, there is no formal method or procedure for performing the working curve measurement, raising questions about the utility of reported working curve parameters. Here, an interlaboratory study (ILS) is described in which 24 individual laboratories performed a working curve measurement on an aliquot from a single batch of PAM resin. The ILS reveals that there is enormous scatter in the working curve data and the key fit parameters derived from it. Further, the measured depth of light penetration D p varied by as much as 7x between participants, while the critical radiant exposure for gelation E c varied by as much as 70x. This significant scatter is attributed to a lack of common procedure, variation in light engines, epistemic uncertainties from the Jacobs equation, and the use of measurement tools with insufficient precision. The ILS findings highlight an urgent need for procedural standardization and better hardware characterization in this rapidly growing field.

36 MATERIALS SCIENCE↗
DOE OSTI2021

EMERGING CYBER-PHYSICAL LANDSCAPE OF TRANSPORTATION TECHNOLOGY

Technology is rapidly progressing in transportation and shipping industries across the globe, including the nuclear, radioactive and hazardous material transportation sectors. With this progress comes unprecedented opportunities for improved transparency, safety, and security in transportation, as well as novel threat surfaces and attack vectors. Therefore, the transport safety and security interface is affected through the application of these technologies. We provide an investigative overview of the developing fields of “trans-tech” or “freight- tech” with a look towards technology development and adoption over the next 3-5 years across three primary categories: Transportation IoT (Internet of Things), Smart Infrastructure, and digitization of transportation management. We also investigate the safety and security implications of utilizing these technologies. Each of these categories presents novel threats as well as opportunities. We examine the role of technology in each as an emerging cyber-physical threat to nuclear and radioactive material transportation security, and plausible mitigation considerations at both the state and operator levels in additional to opportunities for addressing the interface between safety and security.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

2022 roadmap on 3D printing for energy

The energy transition is one of the main challenges of our society and therefore a major driver for the scientific community. To ensure a smart transition to a sustainable future energy scenario different technologies such as energy harvesting using solar cells or windmills and chemical storage in batteries, super-capacitors or hydrogen have to be developed and ultimately deployed. New fabrication approaches based on additive manufacturing and the digitalization of the industrial processes increase the potential to achieve highly efficient and smart technologies required to increase the competitiveness of clean energy technologies against fossil fuels. In this frame, the present roadmap highlights the tremendous potential of 3D printing as a new route to fully automate the manufacturing of energy devices designed as digital files. Additionally, this article gives numerous guidelines to maximize the performance and efficiency of the next generation of 3D printed devices for the energy transition while reducing the waste of critical raw materials. In particular, the paper is focused on the current status, present challenges and the expected and required advances of 3D printing for the fabrication of the most relevant energy technologies such as fuel cells and electrolysers, batteries, solar cells, super-capacitors, thermoelectric generators, chemical reactors and turbomachinery.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Maximizing dynamic range and performance of anatase TiO 2 ECRAM through structure and programming

Here, in this study, we investigate the structure-dependent modulation characteristics of all-solid-state three-terminal electrochemical random-access memory (ECRAM) based on an anatase Li x TiO 2 channel. By directly comparing “asymmetric” and “symmetric” ECRAM device architectures, we reveal significant insight into the impact of a non-zero gate-drain open-circuit voltage and its influence on voltage vs. current-controlled gating. We also explore the impact of potentiation/depression write parameters on the symmetry, linearity, and dynamic range of the device response. Together, initial results from optimizing structure and programming approaches yielded unprecedented G max /G min ratios of >1,000 for ECRAM and hundreds of tunable memory states with excellent linearity and symmetry. Simulations based on these ECRAM devices further illustrate the promise of this analog memory technology, achieving near 2% classification error in the MNIST digit recognition benchmark for a range of training parameters compared to a theoretical best of 1.66% and outperforming other device models extracted from the literature.

AIHWKit↗
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 OSTI2024

Time interval distributions of nuclear events in a digital spectrometer

This study compares the theoretical formula for time interval density distributions (TIDs) in counters with pileup rejection to TIDs measured using a digital spectrometer with trapezoid filtering. The TIDs were derived from successive time stamps of 60 Co and 133 Ba γ rays detected with a HPGe spectrometer. The results demonstrate that the theoretical formula is applicable up to 40% count loss and can be used to retrospectively deduce the incident event rate.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Cross-domain digital twin architecture for predictive maintenance via machine learning and Large Language Models

This research introduces a comprehensive framework for creating and deploying a digital twin platform for continuous monitoring and predictive maintenance within industrial settings. Through utilizing advanced technologies, including Unreal Engine 5, Unity 3D, the Message Queue Telemetry Transport protocol, Random Forest machine learning algorithms, and Large Language Models (LLMs), we establish a platform that digitally reproduces physical equipment and translates digital controls into real-world actions. This facilitates preventive maintenance approaches and improves operational effectiveness. The digital twin platform gathers sensor data from operational equipment, analyzes it using machine learning, and delivers practical insights to prevent potential malfunctions and enhance equipment performance. Furthermore, the incorporation of a web portal enables efficient monitoring and access to historical data, educational materials, and equipment status information. Preliminary findings indicate that digital twins can transform industrial equipment management and maintenance methodologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Laser 3D printing of highly compacted protonic ceramic electrolyzer stack

Solid oxide electrolysis cells (SOECs) for H 2 production is a core technology for H2@scale. However, its conventional manufacturing methods adapted from the manufacture of solid oxide fuel cells (SOFC) need high cost, especially for small-volume production. The emerging laser 3D printing (L3DP) technology with computer-aided 3D printing and computer-controlled laser processing can fulfill layer-by-layer digital shaping and rapid in-situ consolidating feedstock into complicated geometries. L3DP, a promising additive manufacturing (AM) technology, has achieved significant success in manufacturing plastic and metal parts, which is currently attracting considerable attention for the cost-effective, rapid, and flexible manufacturing of heterogeneous multilayered ceramic devices (e.g., SOECs, SOFCs, and solid-state batteries). It is believed that the L3DP can integrate the advantages of selective consolidation of heterogeneous layers, accurate control of layer microstructures, high processing heat efficiency, high processing speed, high stack compactness, high stack design flexibility, and low stack sealing area for cost-effective, rapid, and flexible manufacturing of SOECs to meet DOE’s electrolyzer target.

08 HYDROGEN↗
DOE OSTI2025

An Approach to Automate tools for the Risk Assessment of Digital Instrumentation and Control Systems

Reliable digital instrumentation and control systems (DI&C) are integral for sustaining the continued operation of nuclear power plants. These systems ensure that nuclear reactors operate safely, efficiently, and within regulatory requirements. Yet, the cost of designing and licensing new nuclear DI&C can be prohibitively expensive. Under the U.S. Department of Energy Light Water Reactor Sustainability Program, Idaho National Laboratory has developed a framework for supporting the risk-informed design of DI&C systems by offering methods to support the identification, quantification, and evaluation of risks for various DI&C design architectures. The framework indicates potential software failure modes and provides pathways for quantifying the potential for these software failures, including common cause failures. Using the framework’s systematic approach, challenges for assessing risks within new and existing nuclear DI&C systems can be reduced. Nevertheless, the current framework can be further improved using the convenience of automation. This paper introduces the development of Software for the Hazard Identification and Evaluation of Digital Systems (SHIELDS). SHIELDS is an engineering software package that enables the identification, elimination, and mitigation of potential risks and reduces the burden of deploying reliable DI&C systems. This work introduces plans and techniques to digitize and improve the manual risk assessment modules of the framework. These improvements will save time and increase the repeatability and usability of the framework, making it more accessible to a wider range of users. Ultimately, this introduces SHIELDS and how its modules support efficient development of safe and reliable DI&C systems.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2021

BioSecure Digital Twin: Manufacturing Innovation and Cybersecurity Resilience

U.S. national security, prosperity, economy, and well-being require secure, flexible, and resilient Biopharmaceutical Manufacturing. The COVID-19 pandemic reaffirmed that the biomedical production value-chain is vulnerable to disruption and has been under attack from sophisticated nation-state adversaries. Current cyber defenses are inadequate, and the integrity of critical production systems and processes are inherently vulnerable to cyber-attacks, human error, and supply chain disruptions. The following chapter explores how a BioSecure Digital Twin will improve U.S. manufacturing resilience and preparedness to respond to these hazards by significantly improving monitoring, integrity, security, and agility of our manufacturing infrastructure and systems. The BioSecure Digital Twin combines a scalable manufacturing framework with a robust platform for monitoring and control to increase U.S. biopharma manufacturing resilience. Then, the chapter discusses some of the inherent vulnerabilities and challenges at the nexus of health and advanced manufacturing. Next, the chapter highlights that as the Pandemic evolves, we need agility and resilience to overcome significant obstacles. This section highlights an innovative application of Cyber Informed Engineering to developing and deploying a BioSecure Digital Twin to improve the resilience and security of the biopharma industrial supply chain and production processes. Finally, the chapter concludes with a process framework to complement the Digital Twin platform, called the Biopharma (Observe, Orient, Decide, Act) OODA Loop Framework (BOLF), a four-step approach to decision-making outputs from the Digital Twin. The BOLF will help end users leverage twin technology by distilling the available information, focusing the data on context, and rapidly making the best decision while remaining cognizant of changes that can be made as more data becomes available.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Roadmap to Automated Mobility Systems: Informing the Planning of a Sustainable, Resilient Transportation Ecosystem for Dallas/Fort Worth International Airport

The National Renewable Energy Laboratory (NREL) developed this report to provide Dallas/Fort Worth International Airport (DFW) assistance toward a vision that considers the maturation and proliferation of mobility automation, electrification, and infrastructure integrated with Internet of Things (IoT) technologies as they present themselves on the path to 2035. In planning ongoing infrastructure investments, DFW has goals to accommodate and leverage these enabling technologies toward greater sustainability and enhanced traveler and employee experiences, ensuring that infrastructure investments are fully utilized into the future. The objective of this document is to assist DFW to anticipate and envision future airport access by travelers, employees, and goods by examining existing needs and exploring opportunities enabled by technology that informs longer-term infrastructure planning. The vast infrastructure of DFW, which includes buildings, roadways, and other physical structures, as well as growing digital and energy network infrastructures, requires long-term planning and strategy to fully leverage technology advancement and avoid abandoning assets due to functional obsolescence.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A custom high-stability pulse generator for the test of a novel in-situ magnetic sensor developed to detect radiation damage in undulators

High-performance analog-to-digital converters (ADC) have been widely applied in many areas of science. For instance, magnetic field measurements based on the Faraday’s induction law require high-precision voltmeters to measure induced voltages. In this study in the context of free-electron lasers technology, the Magnetic Measurements Team at SLAC National Accelerator Laboratory proposed a novel in-situ radiation damage detection system (RDDS) for detecting small field variations in undulators. The system measures the flux change in a flexible printed-circuit coil attached to the magnet array during the undulator gap movement. The gap movement changes the magnetic field, which induces a voltage signal in the coil that is measured and integrated with an ADC. Although the system is capable of detecting relative flux changes better than 100 ppm, drift in the ADC’s gain or offset can cause apparent changes in the relative flux. This paper describes the first attempt to developed a high-precision verification circuit to perform ADC testing in the framework of the novel RDDS. The circuit generates a reference voltage pulse with a voltage–time integral relative precision better than 50 ppm for a few hundreds of mVs — the typical order of magnitude measured with the RDDS. The circuit’s design combines a fast and precise switch with a low-noise voltage reference. Long-term measurements allowed statistical analysis and showed that averaging the voltage–time integral of ten pulses gives the required 50 ppm stability. Moreover, reproducibility tests confirmed that the circuit’s output is invariable under small power supply instabilities and equipment shutdown. Instruments and applications designed to quantify the magnetic field by integrating voltage signals may use the pulse generator proposed in this paper for verification purposes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Results of Application Demonstration of Autonomous Offshore Power System Supporting Multiple Mobile and Static Assets

Over the last decade, several technology trends have dominated the innovation cycle within the terrestrial economy. Electrification, cloud computing, decarbonization, digitization, and autonomy are representative examples of macro trends that have had a rapid and fundamental impact; an impact felt not only in user-facing technologies, such as electric vehicles and software-as-a-service, but also in the infrastructure required to deliver those technologies. However, the scale of the impact and rollout has not been felt equally between the terrestrial and ocean economies. Here, the innovation cycle in the ocean economy is significantly slower. What accounts for the difference and are there solutions to this issue?

16 TIDAL AND WAVE POWER↗