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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Irradiation induced creep in nanocrystalline high entropy alloys

Irradiation induced creep (IIC) compliance in NiCoFeCrMn high entropy alloys is measured as a function of grain size (30 < x < 80 nm) and temperature (23–500 °C). For 2.6 MeV Ag 3+ irradiation at a dose rate of 1.5×10 – 3 dpa – 1 s – 1 the transition from the recombination to sink limited regimes occurs at ~ 100 °C. In the sink-limited regime, the IIC compliance scales inversely with grain size, consistent with a recently proposed model for grain boundary IIC. The thermal creep rate is also measured; it does not become comparable to the IIC rate, however, until ~ 650 °C. Here, the results are discussed in context of defect kinetics in irradiated HEA systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Nuclear microreactor transient and load-following control with deep reinforcement learning

The economic feasibility of nuclear microreactors will depend on minimizing operating costs through advancements in autonomous control, especially when these microreactors are operating alongside other types of energy systems (e.g., renewable energy). This study explores the application of deep reinforcement learning (RL) for real-time drum control in microreactors, exploring performance in regard to load-following scenarios. By leveraging a point kinetics model with thermal and xenon feedback, we first establish a baseline using a single-output RL agent, then compare it against a traditional proportional–integral–derivative (PID) controller. This study demonstrates that RL controllers, including both single- and multi-agent RL (MARL) frameworks, can achieve similar or even superior load-following performance as traditional PID control across a range of load-following scenarios. In short transients, the RL agent was able to reduce the tracking error rate in comparison to PID by one half to one third. Over extended 300-minute load-following scenarios in which xenon feedback becomes a dominant factor, PID maintained better accuracy, but RL still remained within a 1% error margin despite being trained only on short-duration scenarios. This highlights RL’s strong ability to generalize and extrapolate to longer, more complex transients, affording substantial reductions in training costs and reduced overfitting. Furthermore, when control was extended to multiple drums, MARL enabled independent drum control as well as maintained reactor symmetry constraints without sacrificing performance---an objective that standard single-agent RL could not learn. We also found that, as increasing levels of Gaussian noise were added to the power measurements, the RL controllers were able to maintain lower error rates than PID, and to do so with at least 10% and upwards of 150% less control effort. These findings illustrate RL's potential for autonomous nuclear reactor control, laying the groundwork for future integration into high-fidelity simulations and experimental validation efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Detecting Multipartite Entanglement Patterns Using Single-Particle Green’s Functions

Here, we present a protocol for detecting multipartite entanglement in itinerant many-body electronic systems using single-particle Green’s functions. To achieve this, we first establish a connection between the quantum Fisher information and single-particle Green’s functions by constructing a set of witness operators built out of single electron creation and destruction operators in a doubled system. This set of witness operators is indexed by a momentum k. We compute the quantum Fisher information for these witness operators and show that for thermal ensembles it can be expressed as an autoconvolution of the single-particle spectral function. We then apply our framework to a one-dimensional fermionic system to showcase its effectiveness in detecting entanglement in itinerant electron models. We observe that the detected entanglement level is sensitive to the wave vector associated with witness operator. Our protocol will permit detecting entanglement in many-body systems using scanning tunneling microscopy and angle-resolved photoemission spectroscopy, two spectroscopies that measure the single-particle Green’s function. It offers the prospect of the experimental detection of entanglement through spectroscopies beyond the established route of measuring the dynamical spin response.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Design of a Novel Variable Geometry Divertor for Tokamaks

The divertor is a key component of fusion reactors, allowing exhaust of gas, impurities, and helium ash to preserve plasma purity. The divertor geometry strongly affects plasma performance, and it is designed to be compatible with different plasma shapes in present-day fusion experiments. Here, we present a novel concept for a variable geometry divertor, in which the divertor baffle tiles are reorientable by external actuation. Implementation of this concept in a medium-sized research tokamak would uniquely provide the flexibility to tailor divertor geometry to the plasma configuration and also enable study of the effect of divertor closure on plasma performance. To ensure compatibility with typical tokamak operations, the adjustable divertor must withstand the effects of significant mechanical and thermal stresses such as MW/m 2 -scale heat fluxes and large electromagnetic fields, e.g., disruption forces. The technological solutions for actuation mechanisms, cooling system, gas baffling and plasma-facing components are assessed. A functional reduced-scale model with movable outer divertor target baffle tiles is developed and the actuation mechanism is tested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Oxy-Combustion System Process Optimization

The overall objective of this work is to develop a new chemical absorbent-based, high pressure, CO 2 purification system to remove the residual oxygen that currently contaminates the recovered CO 2 , and to optimize the Pressurized Oxy-Combustion (POxC) process to minimize the Cost of Electricity (COE) generated in this advanced combustion process. TDA developed and validated the performance of the oxygen removal system for CO 2 purification. In collaboration with the Advanced Power & Energy Program (APEP) of University of California, Irvine (UCI), we optimized the POxC process, including thermal management, heat integration, and power cycle optimization using process design and modeling supported with Aspen Plus® process simulations. The techno-economic analysis results indicate that the pressurized oxycombustion coal power plant with Ion-transport membrane (ITM) air separation unit (ASU) (Case 2 – 30.55%) does not show an advantage over a cryogenic ASU (Case 1 – 31.24%) while TDA’s sorption-based ASU (Case 4 - 32.61%) shows a significant advantage over the cryogenic ASU (Case 1 – 331.24%). The specific plant costs show a wide range with a low of $2544/kW for Case 11C (TDA ASU, co-sequestering the SO x , and ultra-supercritical steam cycle) to a high of $2975/kW for Case 12A (cryogenic ASU and sCO 2 cycle). In general, the ITM ASU based cases have lower specific plant costs than the corresponding cryogenic ASU based cases while the TDA ASU based cases show the lowest specific plant costs. The main reason for lowering these costs is the higher overall plant thermal efficiency which decreases the plant cost on a $ per kW basis. Next comparing the cases with different power cycle working fluid conditions in terms of temperature and pressure while all utilizing steam, similar trends as the plant costs may be observed. However, with the supercritical CO 2 (sCO 2 ) cycle, the increase in thermal efficiency of the sCO 2 cycle was not able to offset its increase in plant cost making the plant costs higher than those of the corresponding steam cycle cases. The Cost of Electricity (COE) again shows similar trends as the specific plant costs. The COE for Case 11C at $110.1/MWh is also the lowest, but among all cases that do not co-sequester the SO x , Case 12C (TDA ASU and sCO 2 cycle) has the lowest COE at $\$$117.5/MWh while the highest is for Case 8A (cryogenic ASU and supercritical steam cycle) at $130.4/MWh.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Integrating Concentrating Solar Power Technologies into the Hybrid Optimization and Performance Platform (HOPP)

As the world increases renewable energy deployment, there is an increasing interest in hybridizing various generation and storage technologies to maximize net benefit to the developer and/or off-taker. A particularly interesting combination of renewable technologies is concentrating solar power (CSP) with thermal energy storage (TES), photovoltaics (PV), and electrochemical battery energy storage (BESS). Due to the system complexity of CSP technology, it is difficult to evaluate the technological and financial performance of a CSP-PV hybrid system without detailed modeling of annual operations. To address this challenge, we have developed a modeling framework for evaluating the performance and financial viability of CSP systems hybridized with PV and battery technologies. This modeling effort incorporates CSP tower and trough systems into an existing modeling tool recently developed by NREL referred to as the Hybrid Optimization and Performance Platform (HOPP). This report outlines the modeling methodology as well as preliminary results from example case studies conducted using the model. The methodology describes: (i) the integration of CSP tower and troughs into HOPP using python interfaces to access System Advisor Model (SAM) underlining technology models, (ii) the mathematical formulation of the mixed integer linear program dispatch optimization model which optimizes operations of storage asset to either maximize system revenue or minimize operating cost while load following, (iii) the design analysis methods implemented within HOPP, and (iv) simulation clustering for the purposes of reducing computational expense. We exercise the model using a case study of a future scenario where we assume (i) CSP and PV technologies achieve the 2030 cost targets provided by the Solar Energy Technologies Office (SETO), (ii) battery costs reduce to the 2030 mid cost projection presented by NREL. Lastly, (iii) electricity prices for southern California in 2030 are provided by NREL's Cambium database, and (iv) a capacity payment of $150/kW-yr based on the system capacity factor during the to 100 net-load hours.

14 SOLAR ENERGY↗
DOE OSTI2023

Demonstrate FARM supervisory capabilities for a thermal energy storage problem for the DETAIL facility: IES Simulation Ecosystem Control System Development

The goal of the power dispatch problem for an Integrated Energy System (IES) is to adjust the power output and the heat flow of each component to maximize the profitability of the whole unit. Facilities that can integrate real-time digital signals, mock nuclear power, thermal energy storage and industrial heat use via high-temperature electrolysis were constructed at INL to support the research activities. The Dynamic Energy Technology and Integration Laboratory (DETAIL) houses the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET) and the Thermal Energy Distribution System (TEDS). In this report, the hierarchical control system architecture proposed in June 2023 milestone for the flexible operation of DETAIL facility is finalized and demonstrated. A brief description of the components and the corresponding Dymola models from the HYRBID repository is first provided. Then, the current control strategy is presented. In particular, the approach for generating the set-point trajectories to be fed to the PI controllers is analyzed, and its limits were identified. To preserve safe operation over both long-time and real-time horizons, the integration of a Supervisory Control layer embedding a modified version of FARM (Feasible Actuator Range Modifier) module is proposed. FARM is a component of the RAVEN-based FORCE framework designed to support HERON module at optimizing the operation of IES units. The proposed control system for DETAIL foresees FARM to be applied twice, i.e., the original version (“FARM-Validator”) aiding the solution of the power dispatch problem, and a modified version (“FARM-Supervisory”) coordinating the PID controllers. Despite the kernel of the two modules is the same, their tasks are quite different. The former intervenes at the beginning of each hour to prevent constraint violations over long time periods, the latter addresses real-time control tasks and monitors the response of constrained variables at a much finer time resolution. A tentative procedure for training the embedded Digital Twins with the experimental data is also proposed. Finally, the capabilities of the designed architecture and the impact of the added Supervisory Control layer are demonstrated by simulating a representative power dispatch scenario.

25 ENERGY STORAGE↗
DOE OSTI2026

Potential of Data Center Controls in Grid Services

The rapid proliferation of large data centers brings both challenges and opportunities for grid reliability. The data center resources and their potential flexibility have the potential to contribute resources to grid operations. Through capabilities like energy shifting and resource coordination, data centers can help reduce their net demand on the transmission network, as well as provide additional grid services to support reliable operation on the grid. While transient and long-term grid planning and operations are the scenarios that draw most attention, the quasi-steady state timeseries (QSTS) operation of data centers and grid bring interesting scenarios that can help evaluate the data center controls to aid grid services. This work is focused on modeling data centers for QSTS applications – incorporating the AI data center load profiles and building on the PNNL digital twin model for the thermal management loads to enable simulation studies to reveal the impact of data center controls on grid performance. This includes the integration of a QSTS battery and natural gas generator model to incorporate local resource impacts to the system. The simulation study is performed with a modified IEEE 24-Bus transmission system. Scenarios are focused on evaluating the data center load impacts on the transmission system and leveraging both data center and local generation controls to mitigate those impacts and provide additional grid services. The data center controls revealed the ability to contribute to two main kinds of grid services: preventing congestion on a weak grid by coordinating the data center resources with the collocated BESS and onsite generation; and the ability to help the grid operations during stressed times of operation like during a contingency. Leveraging these and other capabilities has the potential to help data centers become grid responsive assets, aiding in both their integration into the power system and grid reliability.

power grid simulation↗
DOE OSTI2025

Improving Thermal Management Strategies for Data Centers: A Physical Testbed Incorporating Small Modular Reactor and Microreactor Technology

This study aims to accelerate the demonstration of various thermal management systems for data centers using nuclear-generated heat to enhance energy and grid reliability. Utilizing mobile containerized and stationary test beds at INL's High Performance Computing (HPC) facility, this project integrates with various nuclear-related energy systems testing facilities. Key components include immersion cooling apparatus, absorption chillers, and adjustable thermal management simulators. Tasks involve acquiring necessary hardware, sensors, and cooling apparatus, engaging with data center industry stakeholders, and providing a testing platform for algorithms, models, tools, and software. The objective is to expedite the deployment of nuclear-powered data centers, thereby improving energy reliability and affordability.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2025

EGS Reservoir Modeling for Developing Geothermal District Heating at Cornell University

Cornell University is pursuing development of an enhanced geothermal system (EGS) for providing heating to its main campus in Upstate New York. A ~10,000 ft (~3 km) deep vertical observation well ('CUBO') was drilled in 2022 to characterize the subsurface using wellbore logging, borehole imaging, fluid sampling, mini-frac tests, coring and drill cutting analysis. Down-hole temperatures measured at 3 km depth are about 80 degrees C, sufficiently high for direct-use heating. The well drilled through generally low porosity and low permeability Paleozoic sedimentary formations and into metamorphic basement rock, encountered at about 9,400 ft depth. Leveraging subsurface data obtained through CUBO, we investigated technical feasibility and design requirements of a doublet well system with horizontal laterals connected to a fracture network created through hydraulic fracturing. The EGS reservoir is sized to provide a nominal heat output in the range 5 to 10 MWth of continuous heating over a 15 year-lifetime with limited thermal drawdown. We applied the Gringarten Multiple parallel fracture model, the Cornell Discrete Fracture Simulator FOXFEM and the commercial simulator ResFrac to estimate required heat transfer area and design a potential hydraulic stimulation treatment. Reservoir simulations indicate that, depending on fluid flow rate and injection temperature, 2 to 3 km2 of effective fracture heat transfer area is required to supply the target heat output of 5 to 10 MWth over 15 years.

district heating↗
DOE OSTI2024

A principle of maximum ignorance for semiclassical gravity

The principle of maximum ignorance posits that the coarse-grained description of a system is maximally agnostic about its underlying microscopic structure. We briefly review this principle for random matrix theory and for the eigenstate thermalization hypothesis. We then apply this principle in holography to construct ensembles of random mixed states. This leads to an ensemble of microstates which models our microscopic ignorance, and which on average reproduces the effective semiclassical physics of a given bulk state. We call this ensemble the state-averaging ansatz. The output of our model is a prediction for semiclassical contributions to variances and higher statistical moments over the ensemble of microstates. The statistical moments provide coarse-grained — yet gravitationally non-perturbative — information about the microstructure of the individual states of the ensemble. We show that these contributions exactly match the on-shell action of known wormhole configurations of the gravitational path integral. These results strengthen the view that wormholes simply parametrize the ignorance of the microstructure of a fundamental state, given a fixed semiclassical bulk description.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Local models of two-temperature accretion disc coronae – II. Ion thermal conduction and the absence of disc evaporation

We use local stratified shearing-box simulations with magnetic field-aligned thermal conduction to study an idealized model of the coupling between a cold, radiatively efficient accretion disc, and an overlying, hot, two-temperature corona. Evaporation of a cold disc by conduction from the hot corona has been proposed as a means of mediating the soft-to-hard state transitions observed in X-ray binary systems. We model the coronal plasma in our local disc patch as an MHD fluid subject to both free-streaming ion conduction and a parametrized cooling function that captures the collisional transfer of energy from hot ions to colder, rapidly cooling leptons. In all of our models, independent of the initial net vertical magnetic flux (NF) threading the disc, we find no evidence of disc evaporation. The ion heat flux into the disc is radiated away before conduction can heat the disc’s surface layers. When an initial NF is present, steady-state temperature, density, and outflow velocities in our model coronae are unaffected by conduction. Instead of facilitating disc evaporation, thermal conduction is more likely to feed the disc with plasma condensing out of the corona, particularly in flows without NF. Our work indicates that uncertainties in the amount of NF threading the disc hold far greater influence over whether or not the disc will evaporate into a radiatively inefficient accretion flow compared to thermal conduction. We speculate that a change in net flux mediates disc truncation/evaporation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

EGS Reservoir Modeling for Developing Geothermal District Heating at Cornell University: Preprint

Cornell University is pursuing development of an enhanced geothermal system (EGS) for providing heating to its main campus in Upstate New York. A ~10,000 ft (~3 km) deep vertical observation well ("CUBO") was drilled in 2022 to characterize the subsurface using wellbore logging, borehole imaging, fluid sampling, mini-frac tests, coring and drill cutting analysis. Down-hole temperatures measured at 3 km depth are about 80 degrees C, sufficiently high for direct-use heating. The well drilled through generally low porosity and low permeability Paleozoic sedimentary formations and into metamorphic basement rock, encountered at about 9,400 ft depth. Leveraging subsurface data obtained through CUBO, we investigated technical feasibility and design requirements of a doublet well system with horizontal laterals connected to a fracture network created through hydraulic fracturing. The EGS reservoir is sized to provide a nominal heat output in the range 5 to 10 MWth of continuous heating over a 15 year-lifetime with limited thermal drawdown. We applied the Gringarten Multiple parallel fracture model, the Cornell Discrete Fracture Simulator FOXFEM and the commercial simulator ResFrac to estimate required heat transfer area and design a potential hydraulic stimulation treatment. Reservoir simulations indicate that, depending on fluid flow rate and injection temperature, 2 to 3 km2 of effective fracture heat transfer area is required to supply the target heat output of 5 to 10 MWth over 15 years.

district heating↗
DOE OSTI2023

Energy Model of an Air Source Heat Pump to Explore Performance Improvements under Cold Conditions: A Python Framework: Preprint

Replacing combustion appliances with heat pumps can be part of a strategy to electrify buildings. When their electricity is supplied by renewables, the adoption of heat pumps for space heating may help curb the carbon dioxide emissions inherent to traditional heating systems that burn natural gas or coal. When operating in very cold climates, however, heat pump performance deteriorates, sometimes requiring backup heating supplied by electric resistances or other sources to continue to function. To avoid the use of electric resistances, complementary technologies, like thermal energy storage, solar collectors, or alternative refrigerants, have been explored in recent years. In this study, we present an open-source Python-based numerical model developed to evaluate the annual hourly performance of an air source heat pump (ASHP) operating in the USA. Simulation results include coefficient of performance and heating capacity. The model, validated with experimental results, will be employed in the future to investigate the feasibility of integrating thermal energy storage and other technologies into ASHPs operating in cold climates.

cold climate↗
DOE OSTI2024

Addressing Failures in Molten Salt Thermal Energy Storage Tank for Central Receiver Concentrating Solar Power Plants

The thermal energy storage (TES) system is a critical component in concentrated solar power (CSP) plants that increases the plant's capacity factor and economic competitiveness by reducing the levelized cost of energy (LCOE) while simultaneously increasing the value of the delivered energy. Failures including molten-salt leaks and diverse localized cracking after several months to a few years of operation have been reported in hot tanks for CSP plants operating around the world. A model of a molten salt thermal energy storage tank was developed and validated to analyze the impact of different tank design features on the temperature and stress distributions as a function of typical plant operation conditions. Design features included the floor plate thicknesses, friction coefficients between the tank floor and the foundation, and the sparger ring location. Maximum stresses in the tank floor frequently surpassed the yield point of the material during operation, leading to a detriment of the tank's lifetime. Recommendations on design features to improve the reliability of new molten salt tanks for CSP plants are provided.

concentrating solar power↗
DOE OSTI2023

Effective dissipation rate in a Liouvillian-graph picture of high-temperature quantum hydrodynamics

At high temperature, generic strongly interacting spin systems are expected to display hydrodynamics: local transport of conserved quantities, governed by classical partial differential equations like the diffusion equation. I argue that the emergence of this dissipative long-wavelength dynamics from the system's unitary microscopic dynamics is controlled by the structure of the Liouvillian graph of the system's Hamiltonian, that is, the graph induced on Pauli strings by commutation with that Hamiltonian. The Liouvillian graph decomposes naturally into subgraphs of Pauli strings of constant diameter, and the coherent dynamics of these subgraphs determines the rate at which operator weight spreads to long operators. In conclusion, this argument provides a quantitative theory of the emergence of a dissipative effective dynamics from unitary microscopic dynamics; it also leads to an effective model with Hilbert space dimension linear in system size and exponential in the UV cutoff for diffusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Optimal control of polar sea-ice near its tipping points

Abstract Several Earth system components are at a high risk of undergoing rapid, irreversible qualitative changes or “tipping” with increasing climate warming. It is therefore necessary to investigate the feasibility of arresting or even reversing the crossing of tipping thresholds. Here, we study feedback control of an idealized energy balance model (EBM) for Earth’s climate, which exhibits a “small icecap” instability responsible for a rapid transition to an ice-free climate under increasing greenhouse gas forcing. We develop an optimal control strategy for the EBM under different forcing scenarios to reverse sea-ice loss while minimizing costs. Control is achievable for this system, but the cost nearly quadruples once the system tips. While thermal inertia may delay tipping, leading to an overshoot of the critical forcing threshold, this leeway comes with a steep rise in requisite control once tipping occurs. Additionally, we find that the optimal control is localized in the polar region.

54 ENVIRONMENTAL SCIENCES↗