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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Electrothermally Driven Reconfiguration of Microrobotic Beam Structures for the ChipSail System

Solar sailing enables efficient propellant-free attitude adjustment and orbital maneuvers of solar sail spacecraft with high area-to-mass ratios. However, the heavy supporting mass for large solar sails inevitably leads to low area-to-mass ratios. Inspired by chip-scale satellites, a chip-scale solar sail system named ChipSail, consisting of microrobotic solar sails and a chip-scale satellite, was proposed in this work. The structural design and reconfigurable mechanisms of an electrothermally driven microrobotic solar sail made of Al\Ni 50 Ti 50 bilayer beams were introduced, and the theoretical model of its electro-thermo-mechanical behaviors was established. The analytical solutions to the out-of-plane deformation of the solar sail structure appeared to be in good agreement with the finite element analysis (FEA) results. A representative prototype of such solar sail structures was fabricated on silicon wafers using surface and bulk microfabrication, followed by an in-situ experiment of its reconfigurable property under controlled electrothermal actuation. The experimental results demonstrated significant electro-thermo-mechanical deformation of such microrobotic bilayer solar sails, showing great potential in the development of the ChipSail system. Analytical solutions to the electro-thermo-mechanical model, as well as the fabrication process and characterization techniques, provided a rapid performance evaluation and optimization of such microrobotic bilayer solar sails for the ChipSail.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Power Grid Simulation Testbed for Transactive Energy Management Systems

To effectively engage demand-side and distributed energy resources (DERs) for dynamically maintaining the electric power balance, the challenges of controlling and coordinating building equipment and DERs on a large scale must be overcome. Although several control techniques have been proposed in the literature, a significant obstacle to applying these techniques in practice is having access to an effective testing platform. Performing tests at scale using real equipment is impractical, so simulation offers the only viable route to developmental testing at scales of practical interest. Existing power-grid testbeds are unable to model individual residential end-use devices for developing detailed control formulations for responsive loads and DERs. Furthermore, they cannot simulate the control and communications at subminute timescales. To address these issues, this paper presents a novel power-grid simulation testbed for transactive energy management systems. Detailed models of primary home appliances (e.g., heating and cooling systems, water heaters, photovoltaic panels, energy storage systems) are provided to simulate realistic load behaviors in response to environmental parameters and control commands. The proposed testbed incorporates software as it will be deployed, and enables deployable software to interact with various building equipment models for end-to-end performance evaluation at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Regime-oriented causal model evaluation of Atlantic–Pacific teleconnections in CMIP6

The climate system and its spatio-temporal changes are strongly affected by modes of long-term internal variability, like the Pacific decadal variability (PDV) and the Atlantic multidecadal variability (AMV). As they alternate between warm and cold phases, the interplay between PDV and AMV varies over decadal to multidecadal timescales. Here, we use a causal discovery method to derive fingerprints in the Atlantic–Pacific interactions and to investigate their phase-dependent changes. Dependent on the phases of PDV and AMV, different regimes with characteristic causal fingerprints are identified in reanalyses in a first step. In a second step, a regime-oriented causal model evaluation is performed to evaluate the ability of models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in representing the observed changing interactions between PDV, AMV and their extra-tropical teleconnections. The causal graphs obtained from reanalyses detect a direct opposite-sign response from AMV to PDV when analyzing the complete 1900–2014 period and during several defined regimes within that period, for example, when AMV is going through its negative (cold) phase. Reanalyses also demonstrate a same-sign response from PDV to AMV during the cold phase of PDV. Historical CMIP6 simulations exhibit varying skill in simulating the observed causal patterns. Generally, large-ensemble (LE) simulations showed better network similarity when PDV and AMV were out of phase compared to other regimes. Also, the two largest ensembles (in terms of number of members) were found to contain realizations with similar causal fingerprints to observations. For most regimes, these same models showed higher network similarity when compared to each other. This work shows how causal discovery on LEs complements the available diagnostics and statistical metrics of climate variability to provide a powerful tool for climate model evaluation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Retractable Sensor for Reactor Experiments

This presentation is to orient a mechanical or nuclear engineering senior design team so that they can help solve an instrumentation problem found in high power test reactors. Test reactors such as the Advanced Test Reactor (ATR) at the Idaho National Laboratory are used to irradiate nuclear fuels and materials to evaluate performance after high levels of exposure to a reactor in-pile environment. The purpose of the experiments is to determine property changes as the materials or fuels are bombarded with fast neutrons (and thermal (slow) neutrons as well). Typically, the irradiation must take place at a very specific temperature. Sometimes other parameters are monitored as well as properties such as creep, or gas composition, etc. However, the fast neutrons cause changes in not only the materials, but also in the transducers that are placed in the neutron flux, e.g., thermocouples or optical fibers. This task will be limited to considering temperature measurements. Thermocouples experience decalibration from not only the neutron flux, but also from the very high temperatures that are sometimes measured. Optical fibers darken in a neutron or gamma flux. However, it takes quite a few hours, or days for these changes to manifest. High power test reactors typically run at a constant power and so the temperature in an experiment is fairly stable over time. Because the changes are typically very slow, even a single temperature measurement per day, would provide 95% of a perfect data set. The basic concept of this effort is to push a very small diameter thermocouple or optical fiber into the location to be measured, leave it for 30 seconds or so for it to come to equilibrium, and transmit the signal, and then pull it up and away from the high neutron flux and high temperature region. The distance the thermocouple or fiber would need to move is on the order of 50 – 100 cm. By doing this, the thermocouple junction or optical fiber would spend only a few hours in the high flux/high temperature environment over the life of the irradiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Model based co-simulation platform for integrated building system control and design optimization

Both steady-state and dynamic simulations have been widely used by HVAC&R industry to support product/equipment development for decades. Steady-state simulation focuses on the system mass, energy and momentum balance of an equilibrium state. It is based on high-fidelity components models, and thus is suitable for system and component design optimization. Dynamic simulation studies the system transient response and is generally used for controls development and verification. It usually does not require rigorous component models of high accuracy because 1) the commonly used PID control is feedback control whose control performance evaluation doesn’t require high fidelity system/plant model; 2) high-fidelity dynamic model significantly increases the number of equations and variables and creates tremendous challenge for math solver. For supervisory control, transactive control or optimization of an integrated building system, the HVAC&R equipment is often one of the sub-components to be controlled. High-fidelity equipment models are required for accurately evaluating control strategies. In addition, building equipment manufacturers have developed a lot of high-fidelity steady-state equipment/component models per their expertise. Thus, a platform that can integrate OEM high-fidelity steady-state model with dynamic building simulation and/or electric power system & grid simulation to support the development and verification of supervisory control for integrated building systems is necessary. In this study, ORNL’s heat pump design tool (HPDM) is utilized to develop a co-simulation platform for supervisory control and optimization in integrated building systems. It is based on a model that integrates high-fidelity steady-state simulation equipment models with dynamic building simulation. A practical case of using the proposed co-simulation platform to develop and evaluate the supervisory control and optimization is presented and discussed.

Sun, Jian↗
DOE OSTI2022

High Entropy Alloys: Advanced Synchrotron X-Ray and Neutron Scattering Studies

Synchrotron high energy X-rays and neutrons are powerful complementary tools for structure-property relationship studies by probing materials under complex external stimuli and measuring the bulk-average materials properties and response mechanism, thanks to the high brightness and advanced instrumentations. The research of using the high energy X-ray or neutron scattering instruments at large facilities in high entropy alloys has greatly increased in alloy design, synthesis, property evaluation, performance testing, and predictive model validation, and thus accelerates the next generation structural material discoveries.

An, Ke↗
DOE OSTI2022

Methods and algorithms of cyclic coulometry

Systems, devices, and methods of diagnosing an electrochemical cell using cyclic coulometry are discussed. An exemplary battery diagnostic system comprises a current generator to generate symmetric charge current and discharge current to excite an electrochemical cell, and a cyclic coulometer to evaluate performance of the electrochemical cell. The cyclic coulometer can adjust at least one of a charge time for applying the charge current, or a discharge time for applying the discharge current, to keep a monitored cell voltage toward a specific setpoint. The adjustment of charge or discharge time can be achieved by changing a current switch timing for reversing current from a first to a second current direction. The cyclic coulometer measures one or more electrical parameters during the charge or discharge cycle, and generates a performance metric using the measured electrical parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

WETO Resilience Research: Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

INL focuses on resilience and cybersecurity for distributed wind under the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project. Following the development of a resilience framework, INL has developed an application for resilience planning that includes automated hazard simulations to evaluate performance of various configurations. Additionally, INL is exploring the resilience of advanced distributed wind systems that leverage advanced controls and hybrid resources.

17 WIND ENERGY↗
DOE OSTI2023

Optimization of a Residential Air Source Heat Pump using Refrigerants with GWP <150 for Improved Performance and Reduced Emission

Using low-GWP refrigerants can reduce the Green House Gas (GHG) emission of heat pump systems. Heat exchangers and compressors are the key components and have a prominent impact on system performance, significant research is devoted to reducing the cost of the heat exchangers while achieving the same or better system performance with refrigerant charge reduction.To better understand the environmental impacts of optimized systems with low-GWP refrigerants, Life Cycle Climate Performance (LCCP) evaluation method was used to evaluate the direct and indirect emissions of the system over the course of its lifetime from manufacturing to disposal. The DOE/ORNL Heat Pump Design Model (HPDM) is used to evaluate the performance of heat pumps. Multi-objective optimizations using Particle Swarm Optimization (PSO) algorithm are performed on a 3-ton R410A residential air source heat pump on market. Seven R410A alternatives, i.e., R32, R454B, R454C, R455A, R457A, R1234yf and R1234ze(E) are investigated. The last five fluids have GWP lower than 150.As a result, 5.5%-12.8% seasonal energy efficiency ratio 2 (SEER2) improvement is achieved, and the optimized systems reduce life cycle CO2 emission by 8.5%-28.6% with GWP lower than 150 refrigerants. The optimal heat exchangers can fit into the original R410A fan-coil units; therefore, the proposed design method establishes a production and installation path to produce cost-effective low-GWP heat pumps easily accepted by end users.

Li, Zhenning↗
DOE OSTI2023

Construction and Commissioning of Gas Electron Multiplier (GEM) Detectors in Advanced Assembly Design for Low-Energy Applications at High Rates and Analysis of GEM Data From the Muse Experiment at PSI

The search beyond the Standard Model explores dark matter and a potential fifth force. DarkLight@ARIEL investigates the dark photon as a mediator between ordinary and dark matter. The experiment aims to measure the process e?Ta ? e?TaX ? e?Ta(e?e+), by detecting a charged lepton pair in the final state. The spectrometers will be instrumented with Gas Electron Multiplier (GEM) detectors with minimal material budget for tracking. A novel GEM construction technique is employed for fabricating 25 cm x 40 cm GEM detectors, where all layers are mechanically stretched and assembled within a double frame. The dissertation outlines physics motivation, methods, experimental setup, and the role of GEM detectors in DarkLight. A comprehensive discussion on GEM detectors, focusing on the "NS2" technique, including design, parts, assembly, testing, and performance evaluation will be discussed. The proton has garnered attention due to discrepancies in measuring its charge radius using muonic hydrogen and electron-based methods. The 2010 muonic hydrogen measurement of the proton charge radius Rp = 0.84184(67) fm, showed a significant 7? discrepancy compared to the previously known value of Rp = 0.8775(51) fm, giving rise to the proton radius puzzle. Through simultaneous measurements of e ? p and ? ? p elastic scattering, MUSE facilitates a precise and direct comparison of the proton radius. The physics background of the proton radius puzzle, measurement techniques, the approach adopted by the MUSE experiment, its significance and the experimental setup will be discussed. Furthermore, the role of GEM detectors, along with an in-depth analysis of their data and efficiency will be discussed and evaluated.

Mohammed Prem Nazeer, Sahara↗
DOE OSTI2023

Directed Energy Deposition Process Modeling, Validation, and Process-Informed Optimization

The directed energy deposition (DED) process, one of the most popular additive manufacturing techniques in use today, involves various complex physical mechanisms that are not yet well understood. In this regard, computational tools show promise for elucidating the manufacturing process and enabling nondestructive performance evaluations of manufactured parts. To better control and optimize the DED process?thereby improving the manufactured product? the present work develops and demonstrates a novel artificial intelligence (AI)-based process control and optimization technique. Specifically, a geometry-free thermo-mechanical model with adaptive subdomain construction is developed to accurately capture the material?s thermo-mechanical response under cyclical reheating and high cooling rates [1]. The model is demonstrated and validated with experimental measurements, in light of various geometries and processing parameters. Moreover, based on this thermo-mechanical model, a physics-informed reduced-order model is developed to enable quick predictions of the temperature field at every time step. Furthermore, an AI-based controller is developed that can adapt to the ever-changing system states by automatically adjusting the manufacturing process parameters. This entire work is based on the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) [2] and its recent integration with Libtorch (the C++ frontend of PyTorch [3]). The combined development of the adaptive material deposition scheme, thermo-mechanical model, associated reduced-order model, and AI-based process controller carries great potential for improving advanced manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigation of Nonflammable Electrolytes for Behind-the-Meter Storage Batteries

Behind-the-Meter Storage (BTMS) is a battery-based, stationary energy storage system that is connected to the residential or industrial customer's side of the electrical grid utility service meter. BTMS systems enable consumers to (A) economically schedule charging and usage of stored energy, (B) store and use energy from on-site generation, especially from inconstant, renewable sources like solar and wind, and (C) avoid overloading the grid during peak hours via supplementation with stored energy. BTMS battery performance requirements and general priorities differentiate from other applications, like EVs, which has prompted the development of batteries with tailored electrode and electrolyte materials. These materials prioritize low cost, avoiding critical materials; longevity, achieving 8000 cycle and 20-year shelf lives; and importantly, high safety. Nonflammable electrolytes show promise to improve safety by mitigating thermal runaway, yet often come with sacrifices to battery performance. In this presentation (1) primary categories of nonflammable electrolytes will be discussed; (2) a rational design of experiment will be presented for efficient performance evaluation of several nonflammables electrolyte in BTMS-relevant battery chemistry, Li4Ti5O12- and LiNi0.90Mn0.10O2; and (3) preliminary results will be presented.

battery↗
DOE OSTI2024

DOE Advanced Gas Reactor Fuel Development and Qualification Program Overview

DOE AGR fuel development and qualification program overview to include TRISO fuel development and program elements, AGR timeline, Irradiation test results, performance evaluation results, major accomplishments and milestones over 12 months, and university-led TRISO related research projects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Performance Investigation of High-temperature Latent Heat Storage for Integration with Advanced Nuclear Reactors

Integrating thermal energy storage (TES) with advanced nuclear reactors enhances the flexible use of nuclear energy, facilitating its expansion beyond conventional electricity generation. High-temperature TES, capable of storing heat above 400 degree C, emerges as a vital carbon-free energy solution for decarbonizing industrial sector, especially when combined with low-emission energy sources like advanced nuclear reactors. Idaho National Laboratory (INL) has recently developed a novel design for high-temperature latent heat storage system, called Heat pipe Integrated Thermal Battery (HITB), and efforts are underway to experimentally demonstrate the concept. HITB employs liquid-metal heat pipes to establish thermal linkage between TES and nuclear systems without direct fluid exchange, minimizing the potential risk of the integrated systems such as cross-contamination. HITB is designed to achieve high charging and discharging efficiency as well as high energy storage density by employing metal alloys as Phase Change Material (PCM). Initial proof-of-concept experiments are being undertaken using an aluminum alloy (Al59%-Mg35%-Zn6%). This paper discusses current progress of the HITB project at INL, seeking to develop high-temperature TES for versatile integration with advanced nuclear reactors, and shares insights from the performance evaluations via numerical modeling and analysis.

25 ENERGY STORAGE↗
DOE OSTI2024

FENIX: Towards a Fully Integrated Multiphysics Framework for Plasma Facing Component Modeling

Computational tools have a crucial role to play in accelerating the deployment of fusion as a clean, reliable, abundant, and sustainable energy source. Multiphysics, high-fidelity simulation capabilities can help model, study, and predict intricate interactions between materials performance, plasma exposure, neutron irradiation, and engineering processes. As such, they can assist in the resolution of scientific and engineering challenges underpinning design, construction, and commission of fusion power plants. To address these needs, ongoing efforts are leveraging the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework and delivering new computational tools for the fusion community. These tools inherit crucial attributes from MOOSE. They are open-source, modular, integrated with nuclear industry-standard software quality assurance processes, and enable multiphysics, multi-fidelity, fully integrated, zero- to three-dimensional, and massively parallel simulations. After a short overview of these capabilities, we will present the development of Fusion ENergy Integrated multiphys-X (FENIX), a MOOSE-based application designed to enable plasma facing component design and performance evaluation. Throughout their lifetime, plasma facing components are exposed to extreme thermal loads, repeated thermal shocks, and irradiation by plasma ions, neutral particles, and high-energy neutrons. Consequently, designing a plasma facing component with acceptable lifetime degradation is extremely challenging. FENIX aims to model the multiphysics environment in which plasma facing components evolve to accelerate their design studies. To that end, FENIX couples existing MOOSE capabilities such as heat transfer, thermomechanics, and thermal hydraulics, with tritium transport via the MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8), with neutronics via the MOOSE-based high-fidelity neutron-photon transport and fluid dynamics code Cardinal, and finally with Particle-in-Cell plasma simulation capabilities being developed in this project. In this study, we present the current FENIX capabilities and preliminary results of its application to model the Tritium Plasma Experiment set up at Idaho National Laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Automating Anomaly Detection for Target systems at Spallation Neutron Source

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory, produces the world’s most intense pulse neutrons beams. An accelerated proton beam is directed into a mercury target to generate neutrons via spallation. The target system accounted for over 40% of the overall downtime of the facility in 2022. Thus, early detection in anomalies in the target systems can enable taking corrective actions to avoid failures and reduce downtime. Fault prognostics and anomaly detection in accelerators, both at SNS and outside, has largely focused on the beam side. This paper presents one the first studies exploring leveraging machine learning to automate the detection of anomalies in the target system. The target system consists of over 30 different interconnected subsystems, and the present work focuses on the mercury process system as a use case. Analyzing data from 28 process variables from 2022 and 2023, tree-based and reconstruction-based algorithms are employed to detect anomalies in archived data. The algorithms detected previously unreported anomalies, several of which were deemed alert worthy by human experts, particularly those found by reconstruction-based algorithms. Using data from each production run in the accelerator increased the generalizability of the models in time. Efforts are now underway to implement a workflow for incorporating human feedback to update the models and evaluating performance on unseen data. The models will eventually be integrated into the existing System Tracking and Reliability system with a web interface for automated anomaly detection and reporting along with a pathway for incorporating human feedback for model updates.

Raj, Anant [ORNL] (ORCID:0000000306711244)↗
DOE OSTI2025

Enhancing Security and Resiliency in Operational Technology Environments Through Network Slicing and Federated Learning

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation. The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, security, and architectural implications of introducing network slicing into traditionally static OT infrastructures such as Industrial Control Systems (ICS) and SCADA. Through simulated deployments and case studies, the research demonstrates how slicing enables better isolation between critical and non-critical services, thereby improving response time, throughput, and security in sensitive environments. The second question considers: How to dynamically implement network slicing and take advantage of network resources towards integrating decentralized machine learning? In response, this thesis proposes a framework that combines Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Federated Learning (FL) to enable real-time analytics while maintaining data locality. The proposed approach reduces the burden on centralized infrastructure and minimizes privacy risks by supporting on-site training of models across distributed OT nodes, coordinated through dynamically allocated network slices. The third focus explores: How slicing helps to increase the resiliency of OT networks through the orchestration of a dynamic DMZ? To answer this, the thesis presents a method for creating and managing Dynamic Demilitarized Zones (DMZs) using network slicing. This enables flexible and automated isolation of sensitive subsystems during threat scenarios or high-risk operations. Coupled with intelligent orchestration and containerized security services, the dynamic DMZ significantly enhances the system's ability to respond to cyber incidents without halting production. Ultimately, this thesis contributes a comprehensive architecture that blends network slicing with machine learning, secure segmentation, and automation, paving the way for resilient, adaptive, and intelligent OT environments. Performance evaluations across multiple scenarios show improvements in system reliability, threat response time, model accuracy, and resource utilization, providing a strong foundation for future industrial automation systems.

Rodiles Delgado, Brian G↗
DOE OSTI2024

FENIX: An Open-Source Multiphysics Integrated Framework Enabling Collaborative Development of Plasma Facing Component Modeling Capabilities

Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗