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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Plasma-arc lamp high heat flux cycling exposure of neutron irradiated tungsten materials

Thick plate, unalloyed W was neutron irradiated in the High Flux Isotope Reactor (HFIR) at 550 °C to a fast fluence of 1.24 × 10 25 n m -2 E > 0.1 MeV (~0.24 dpa). Unirradiated and irradiated specimens of the material were high heat flux (HHF) tested in the Plasma Arc Lamp (PAL) facility. The PAL uses a high-power photon source to provide a broad and even heat distribution on the sample surface. To simulate on/off cycling of normal operating plasma, the samples were exposed to approximately 800 cycles at 4.73 MW m -2 absorbed heat flux (incident heat fluxes of 10.95 MW m -2 ). Additionally, after PAL exposure, slight changes were observed on the surfaces of the samples with SEM. The samples showed some annealing in the near surface polished region, but they were all below the damage threshold for cracking or other destructive features. The PAL has a large parameter space for future testing. The use of the HFIR and PAL to sequentially expose neutron irradiated samples to HHF will be a powerful tool for understanding materials behavior in a fusion-like environment.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Analysis and Support for LANL Technology Testbed: High Altitude Balloon Gondola and Orion Eagle Gamma Ray Detection Instrument

The Analysis and Support for LANL Technology Testbed: High Altitude Balloon Gondola and Orion Eagle Gamma-Ray Detection Instrument is a project where Los Alamos National Laboratory (LANL), in conjunction with the University of Michigan, are looking into gamma-ray detection in a space-like environment. The purpose of the detection is to work on instruments that can assist with planetary exploration and nuclear deterrents using a High-Altitude Balloon (HAB). For this paper, the main focus is on the mechanical aspects related to the structural analysis of the gondola. It is vital to understand the structural analysis because it helps determine if the gondola can survive the changes in the environment and the different forces or shocks that it will experience when the parachute is deployed and at landing. Additionally, NASA's Balloon Program Office (BPO) has specific requirements to meet to achieve flight certifications. Part of those certifications requires the gondola to simulate different scenarios at specific conditions with various forces applied and orientations. Therefore, it is necessary to adjust the calculations of each method and the force applied to get the right results. Once that is done, the information is inputted into the structural analysis modeling system. The system will aid the mechanical team in assessing the conditions of the gondola at each scenario and determine its margin of safety. After the gondola and instrument are certified, the payload will be able to fly. The HAB and payload are launched from NASA's Columbia Scientific Balloon Facility (CSBF) at Fort Sumner, NM. The official flight was on September 26th, 2021.

42 ENGINEERING↗
DOE OSTI2026

Geothermal-integrated thermally anisotropic building envelope for energy and peak-demand reduction

Buildings consume large amounts of energy for heating and cooling, while peak electricity demand places significant stress on the power grid. This paper presents a reduced-order co-simulation framework and load-oriented supervisory control strategy for a geothermal-integrated thermally anisotropic building envelope with a ground loop (TABE+GL). In TABE+GL, a hydronic loop embedded in the building envelope is directly coupled with a geothermal ground loop, allowing for bidirectional heat exchange between the envelope, the ground, and the indoor environment. A hybrid co-simulation framework was established by coupling a reduced-order resistor–capacitor (RC) thermal network model with EnergyPlus augmented with GHEDesigner modules. The RC model generated feasible heat flux options under three operating modes, and EnergyPlus predicted sensible loads, energy use, and pump energy demand. At each simulation step, a supervisory control algorithm selected the optimal loop configuration and duty factor that maximizes useful TABE geothermal utilization without exceeding the predicted sensible load, thereby avoiding overheating or cooling. Case studies were conducted for Los Angeles, California, Charleston, South Carolina, and Denver, Colorado. Results showed that the proposed framework reduced HVAC electricity consumption by 43%–67%, natural gas use for space heating by 11%–38%, and peak electricity demand by 43%–88%. These results highlight the potential of combining reduced-order envelope modeling, direct geothermal coupling, and load-oriented supervisory control to improve whole building energy performance and reduce peak demand across diverse weather conditions.

Howard, Daniel [Southern Adventist University]↗
DOE OSTI2021

Validation and Demonstration of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an integrated energy system (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. The new RAVEN plugin for grid and capacity optimization (HERON) only addresses the limits that affect the production variables and the corresponding rates of variation (explicit constraints). However, other variables are subject to constraints, and the associated limits should be accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response affects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. To obtain a more accurate approximation of the nonlinear dynamic behavior, a parametric version of the dynamic mode decomposition with control (DMDc) algorithm was developed to derive the state-space representation matrices of the IES components at different scheduling parameter. Thanks to this approach, a more accurate approximation of the system response can be obtained, the limits imposed by thermal mechanical implicit constraints can be translated into power dispatch limits, and the feedbacks to HERON power dispatcher can be provided. To assess the developed methodology, a power dispatching test case composed of three power generating and storage units (Balance of Plant, Secondary Energy Source, Thermal Energy Storage) was developed. The power output of each one of the three units was optimized to meet the imposed time-dependent load demand trajectory and to maximize the IES profitability by meeting both the explicit and implicit constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗
DOE OSTI2024

On hydromagnetic wave interactions in collisionless, high- β plasmas

We describe the interaction of parallel-propagating Alfvén waves with ion-acoustic waves and other Alfvén waves, in magnetized, high- β collisionless plasmas. This is accomplished through a combination of analytical theory and numerical fluid simulations of the Chew–Goldberger–Low (CGL) magnetohydrodynamic (MHD) equations closed by Landau-fluid heat fluxes. An asymptotic ordering is employed to simplify the CGL-MHD equations and derive solutions for the deformation of an Alfvén wave that results from its interaction with the pressure anisotropy generated either by an ion-acoustic wave or another, larger-amplitude Alfvén wave. The difference in time scales of acoustic and Alfvénic fluctuations at high- β means that interactions that are local in wavenumber space yield little modification to either mode within the time it takes the acoustic wave to Landau damp away. Instead, order-unity changes in the amplitude of Alfvénic fluctuations can result after interacting with frequency-matched acoustic waves. Additionally, we show that the propagation speed of an Alfvén-wave packet in an otherwise homogeneous background is a function of its self-generated pressure anisotropy. This allows for the eventual interaction of separate co-propagating Alfvén-wave packets of differing amplitudes. The results of the CGL-MHD simulations agree well with these predictions, suggesting that theoretical models relying on the interaction of these modes should be reconsidered in certain astrophysical environments. Applications of these results to weak Alfvénic turbulence and to the interaction between the compressive and Alfvénic cascades in strong, collisionless turbulence are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

The execution of agent-based simulations (ABSs) on hardware accelerator devices such as graphics processing units (GPUs) has been shown to offer great performance potentials. However, in heterogeneous hardware environments, it can become increasingly difficult to find viable partitions of the simulation and provide implementations for different hardware devices. To automate this process, we present OpenABLext, an extension to OpenABL, a model specification language for ABSs. By providing a device-aware OpenCL backend, OpenABLext enables the co-execution of ABS on heterogeneous hardware platforms consisting of central processing units, GPUs, and field programmable gate arrays (FPGAs).We present a novel online dispatching method that efficiently profiles partitions of the simulation during run-time to optimize the hardware assignment while using the profiling results to advance the simulation itself. In addition, OpenABLext features automated conflict resolution based on user-specified rules, supports graph-based simulation spaces, and utilizes an efficient neighbor search algorithm. We show the improved performance of OpenABLext and demonstrate the potential of FPGAs in the context of ABS. We illustrate how co-execution can be used to further lower execution times. OpenABLext can be seen as an enabler to tap the computing power of heterogeneous hardware platforms for ABS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Data-Driven Specification of Earth's Magnetic Field

As our society is increasingly dependent on technologies in space, predicting space weather becomes ever more important. We have come to rely on technologies such as cellphones, GPS, the Internet, and other commercial and military assets. In order to protect these systems a high priority is to develop better understanding of the harmful conditions of space weather encountered in the near-Earth radiation environment which are mostly dictated by the dynamics of energetic charged particles. The main objective of our proposal was to improve the specification and forecast of the particle distribution in the Earth’s inner magnetosphere using data assimilation together with machine learning (ML) algorithms in our ring current-atmosphere interactions model with self-consistent magnetic and electric fields (RAM-SCBE). Specifically, we explored the application of machine learning algorithms to emulate and improve, through infusion of observational data, the magnetic field (SCBE) of our ring current model. Our work advanced towards the characterization of the RAM-SCBE particle flux field and its potentially different simulation scenarios. We explored how the model behaves in a number of simulation scenarios in order to better understand how the model reacts to perturbations in the solar wind. We were able to capture this behavior through the simulation of an ensemble of RAM-SCB model solutions. The ensemble showed the important correlations between the particle fluxes and the magnetic field. We were able to start the training of a neural network (Autoencoder) to identify the dominant features of the magnetic field, and the main correlations (linear and non-linear) between the particle fluxes and the magnetic field. Our next steps consists of training a neural network to capture the time evolution of the dominant features and obtain a consistent surrogate model for the RAM-SCB.

42 ENGINEERING↗
DOE OSTI2022

Physics-based model of irradiation creep for ferritic materials under fusion energy operation conditions

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this paper, we develop a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. Here, we carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum with average recoil energies of 20 keV and a damage dose rate of ≈3×10 –7 dpa/s at temperatures between 300 and 800 K.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Irradiation creep model for α-Fe: Dislocation climb in the presence of stress fields (Final Report)

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this work, we present a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. We carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum at temperatures between 300 and 800°K.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Operational space for lower hybrid heating scenarios in the full tungsten environment of WEST

In tungsten—W—Environment in Steady-state Tokamak (WEST), the lower hybrid current drive (LHCD) system is key for achieving long pulse operation by providing most of the non-inductive plasma current, as well as a crucial source of electron heating. Therefore, determining the operational space for its application is fundamental. In the present study, the LHCD operational space is deeply analyzed for 0.5 MA pulses. This space is bounded by three limits: (i) the ratio of the LHCD power over density must be above a threshold to compensate tungsten radiation with enough core heating, (ii) the line-averaged density must be high enough to allow good coupling of the hybrid wave with the plasma, and (iii) fast electron ripple losses must be below a limit to avoid reaching a thermal threshold on plasma-facing components. If the tungsten radiation peak or burn-through phase is not safely overcome, a maximum electron temperature of 1.5 keV is obtained, confinement is degraded, and magnetohydrodynamic activity is frequently triggered, potentially causing a disruption. From experimental measurements and interpretative simulations, we highlight the main mechanisms that prevent the plasma from heating up during LHCD power ramp-up. Three parameters play a major role: plasma density, tungsten concentration and LHCD power deposition. A strategy to overcome this limitation is found: a precise density ramp-up performed simultaneously with the increase in LHCD power. Additionally, we show that boronization greatly facilitates the burn-through of tungsten by lowering its content during the heating phase. Finally, taking into account the three constraints given above, the LHCD operational space is determined at power ramp-up and during constant heating phases.

lower hybrid heating and current drive↗
DOE OSTI2022

Real-Space Local Dynamics of Molten Inorganic Salts Using Van Hove Correlation Function

Molten inorganic salts are attracting resurgent attention because of their unique physicochemical properties, making them promising media for next-generation concentrating solar power systems and molten salt reactors. The dynamics of these highly disordered ionic media is largely studied by theoretical simulations, while the robust experimental techniques capable of observing local dynamics are not well-developed. To provide fundamental insights into the atomic-scale transport properties of molten salts, we report the real-space dynamics of molten magnesium chloride at high temperatures employing the Van Hove correlation function obtained by inelastic neutron scattering. Overall, our results directly depict the distance-dependent dynamics of a molten salt on the picosecond time scale. This study demonstrates the capability of the developed approach to describe the locally correlated- and self-dynamics in molten salts, significantly improving our understanding of the interplay between microscopic structural parameters and their dynamics that ultimately control physical properties of condensed matter in extreme environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Distributed electric field sensing using fibre optics in borehole environments

In the past decade, rapid advances in distributed optical fibre sensing technologies have made it possible to record various geophysical data (e.g. strain, temperature and pressure) continuously in both time and space along the fibre, providing an unprecedented quantity and spatial density of data compared to traditional geophysical measurements as well as reducing data acquisition cost. To date, no distributed fibre-based electromagnetic field sensing system has been implemented although electromagnetic sensing could have a broad range of applications to geophysical imaging and monitoring in borehole environments. The goal of this paper is to provide a theoretical feasibility study regarding the design and use of an electromagnetic sensing optical fibre for geophysical applications. First, we present the sensitivity analysis of a ‘hypothetical’ optical fibre coated with polyvinylidene fluoride, a polymer that provides relatively high piezoelectric properties, yet unlike ceramics, is flexible. Next, using a two-dimensional electromagnetic modelling algorithm, we simulate the earth electric-field-to-fibre-strain transfer function and estimate the theoretical sensitivity of the optical fibre to electric fields. Given the state-of-the-art distributed acoustic sensing strain sensitivities in the picometres strain range, our numerical modelling analysis suggests that a perfectly coupled polyvinylidene fluoride–coated optical fibre can measure electric field values in the mV/m to V/m amplitude range. We then apply a cylindrically symmetric modelling algorithm to simulate numerical models demonstrating the applicability of such a fibre in an oilfield environment. Scenarios investigated employ an electric field source and suggest that the measurements can be used to distinguish the oil versus water ratio with a fibre mounted inside a producing steel cased oil well as well as distinguishing between brine and hydrocarbon filled reservoir zones with a fibre located outside of the casing.

58 GEOSCIENCES↗
DOE OSTI2025

Robust preparation of ground state phases under noisy imaginary time evolution

Nonunitary state preparation protocols such as imaginary time evolution (ITE) offer substantial advantages relative to unitary ones, including the ability to prepare certain long-range correlated states more efficiently. Here, we ask whether such protocols are also robust to noise arising due to coupling to the environment. We consider a nonunitary ITE “circuit” subjected to a variety of noise models and investigate whether the resulting steady state remains in the same phase as the target state of the ITE at finite noise strength. Taking the one-dimensional quantum Ising model as a concrete example, we find that the ground-state order and associated phase transition persist in the presence of noise, provided the noise does not explicitly break the symmetry that protects the phase transition. That is, the noise must possess the protecting symmetry in a weak (or average) form. Our analysis is facilitated by a mapping to an effective Hamiltonian picture in a doubled Hilbert space. We discuss possible implications of these findings for quantum simulation on noisy quantum hardware. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Observations and Modeling of the Onset of Fast Reconnection in the Solar Transition Region

Magnetic reconnection is a fundamental plasma process that plays a critical role not only in energy release in the solar atmosphere, but also in fusion, astrophysics, and other space plasma environments. One of the challenges in explaining solar observations in which reconnection is thought to play a critical role is to account for the transition of the dynamics from a slow quasi-continuous phase to a fast and impulsive energetic burst of much shorter duration. Despite the theoretical progress in identifying mechanisms that might lead to rapid onset, a lack of observations of this transition has left models poorly constrained. High-resolution spectroscopic observations from NASA's Interface Region Imaging Spectrograph now reveal tell-tale signatures of the abrupt transition of reconnection from a slow phase to a fast, impulsive phase during UV bursts or explosive events in the Sun's atmosphere. Our observations are consistent with numerical simulations of the plasmoid instability, and provide evidence for the onset of fast reconnection mediated by plasmoids and new opportunities for remote-sensing diagnostics of reconnection mechanisms on the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Neural network kinetics for exploring diffusion multiplicity and chemical ordering in compositionally complex materials

Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. The inherent chemical complexity in compositionally complex materials poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network kinetics (NNK) scheme that predicts and simulates diffusion-induced chemical and structural evolution in complex concentrated chemical environments. The framework is grounded on efficient on-lattice structure and chemistry representation combined with artificial neural networks, enabling precise prediction of all path-dependent migration barriers and individual atom jumps. To demonstrate the method, we study the temperature-dependent local chemical ordering in a refractory NbMoTa alloy and reveal a critical temperature at which the B2 order reaches a maximum. The atomic jump randomness map exhibits the highest diffusion heterogeneity (multiplicity) in the vicinity of this characteristic temperature, which is closely related to chemical ordering and B2 structure formation. The scalable NNK framework provides a promising new avenue to exploring diffusion-related properties in the vast compositional space within which extraordinary properties are hidden.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Fast neutron irradiation capability in existing thermal test reactors

In today’s nuclear industry, momentum towards the design, licensing, and construction of advanced nuclear demonstration plants, including fast reactors, is at a remarkably high level. However, there are currently no dedicated fast spectrum irradiation test facilities in the United States to support the development of fast spectrum technologies. As a result, a unique situation is developing where most of these plants will likely be designed by leveraging historic nuclear material technologies, but where the further optimization and advancement is impeded by the lack of fast neutron irradiation test facilities. While these circumstances present a challenge, there are some near-term opportunities that, if seized, can still help develop advanced fast reactor materials to a meaningful level of readiness to support future commercial fast reactors. Here, in this paper, we assess the feasibility of using thermal neutron filtering materials in existing experiment positions in the Advanced Test Reactor (ATR) at Idaho National Laboratory and the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory to simulate fast reactor test environments for nonfuel test specimens. Items investigated include the incident neutron flux (both fast and thermal), the total neutron fluence and cumulative atom displacements, helium production rate due to thermal neutron capture in nickel, and the potential impact that the thermal neutron filter material has on the cycle length of a given reactor. It is concluded that while HFIR provides the highest fast flux of all the options investigated, it is limited in the amount of thermal neutron filtering material that can be introduced into an experiment position without significantly affecting the operation of the reactor. Irradiation in Outboard-A positions in the ATR was found to be the most realistic near-term experiment avenue due to having ample space for several capsules in a moderately fast flux.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Stochastic equation of motion approach to fermionic dissipative dynamics. I. Formalism

In this work, we establish formally exact stochastic equation of motion (SEOM) theory to describe the dissipative dynamics of fermionic open systems. The construction of the SEOM is based on a stochastic decoupling of the dissipative interaction between the system and fermionic environment, and the influence of environmental fluctuations on the reduced system dynamics is characterized by stochastic Grassmann fields. Meanwhile, numerical realization of the time-dependent Grassmann fields has remained a long-standing challenge. To solve this problem, we propose a minimal auxiliary space (MAS) mapping scheme with which the stochastic Grassmann fields are represented by conventional c-number fields along with a set of pseudo-levels. This eventually leads to a numerically feasible MAS-SEOM method. The important properties of the MAS-SEOM are analyzed by making connection to the well-established time-dependent perturbation theory and the hierarchical equations of motion theory. The MAS-SEOM method provides a potentially promising approach for the accurate and efficient simulation of fermionic open systems at ultra-low temperatures.

Han, Lu (ORCID:0000000339002225)↗