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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sensitivity analysis of thermal contact conductance modeling to inform MiniFuel irradiation capsule designs

The MiniFuel irradiation platform has been developed by Oak Ridge National Laboratory as a flexible, high-throughput separate effects testing capability within the High Flux Isotope Reactor (HFIR). Finite element thermal models are relied upon to design MiniFuel experiments to achieve a specific time-averaged irradiation temperature for experimental objectives. A previous study identified that uncertainty in the component heat generation rates and thermal contact conductance (TCC) model are the most significant contributors to predicted fuel temperature variance. To address both sources of uncertainty, this work performs sensitivity analysis on the TCC model to identify high-impact, high-uncertainty parameters that contribute to fuel temperature variance. The TCC model is analyzed in increasing detail, first using a standalone Python code, then again after coupling Python to the BISON fuel performance code. Furthermore, the parameters with the largest contributions to fuel temperature variance which can be reduced through design changes are identified as the initial subcapsule gas pressure, contact pressure between the fuel and dish, and the effective surface roughness of the interface. A set of design recommendations for future capsule designs has been established and applied to reduce the previously quantified average fuel temperature uncertainty ranges of ± 40 °C in the HFIR vertical experiment facilities (VXF) and ± 80 °C in the removable beryllium (RB) reflector to approximately ± 32 °C and ± 53 °C, respectively. This equates to a 21 % and 33 % reduction in the uncertainty range of the average fuel temperature for VXF and RB, respectively.

BISON↗
DOE OSTI2020

Where Are White Roofs More Effective in Cooling the Surface?

Solar reflective roofs (also called white or cool roofs) are a common heat mitigation strategy. By reflecting more sunlight than regular roofs, cool roofs experience lower surface temperatures and produce less heating of the surrounding air. The effectiveness of cool roofs, quantified by the surface temperature difference between cool roofs and regular roofs ??????, is known to vary spatially. A common perception is that ?????? is controlled by solar radiation that reaches the roof surface. Here we use an Earth System Model and a surface energy balance model to show that the spatial variability of ??????, when normalized by the albedo difference between cool roofs and regular roofs (????), is in fact more controlled by an energy distribution factor that encodes the efficiencies of surface energy balance components in dissipating heat. Our results suggest that painting the roof white is more effective in reducing the roof surface temperature when the roof has less water holding capacity and smaller thermal admittance and is located in places with more solar radiation, less precipitation, and lower wind speed.

Wang, Linying↗
DOE OSTI2025

Thermal Gradient Effects on Local Hotspot Ignition in 1,3,5,7‐Tetranitro‐1,3,5,7‐tetrazocane (HMX)

Understanding hotspot ignition, growth, and criticality, as well as the timescales of each, is crucial for parameterizing mesoscale and continuum‐level models that rely on a statistical understanding of hotspots. However, these models often consider hotspots to have uniform temperatures or for hotspots of a given temperature and size to always behave the same. Therefore, using molecular dynamics simulations, we assess the influence of thermal distribution effects on hotspot local ignition and time to ignition in 1,3,5,7‐tetranitro‐1,3,5,7‐tetrazocane (HMX) nanoscale hotspots. Finally, by assessing hotspots with a gradient driven from an initial two‐temperature core–shell setup, we show that small increases in the core temperature under a constant average temperature can lead to order‐of‐magnitude effects on reaction and local ignition timescales.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Giant Isotope Effect of Thermal Conductivity in Silicon Nanowires

Isotopically purified semiconductors potentially dissipate heat better than their natural, isotopically mixed counterparts as they have higher thermal conductivity (κ). But the benefit is low for Si at room temperature, amounting to only ~10% higher κ for bulk 28 Si than for bulk natural Si ( nat Si). Here we show that in stark contrast to this bulk behavior, 28 Si (99.92% enriched) nanowires have up to 150% higher κ than nat Si nanowires with similar diameters and surface morphology. Using a first-principles phonon dispersion model, this giant isotope effect is attributed to a mutual enhancement of isotope scattering and surface scattering of phonons in nat Si nanowires, correlated via transmission of phonons to the native amorphous SiO 2 shell. The Letter discovers the strongest isotope effect of κ at room temperature among all materials reported to date and inspires potential applications of isotopically enriched semiconductors in microelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mesoscale Modeling for Restructuring and Fragmentation in High Burnup UO 2

This report summarizes the mesoscale modeling conducted in fiscal year 2025 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, focusing on the microstructural evolution and restructuring in high burnup UO 2 nuclear fuel and its impact on fuel fragmentation. We developed a pioneering phase-field model to simulate restructuring behavior across different regions of high burnup fuel, including the dark zone and rim region. A grand-potential-based phase-field model is employed to concurrently evaluate subgrain formation and the growth of fission gas bubbles within the fuel. An energy-based subgrain formation criterion was introduced to simulate the restructuring process. The effects of temperature and burnup rate were studied to capture how each of these parameters influences the characteristics of the restructured fuel. Subgrain formation was observed to initiate around existing fission gas bubbles and proceed toward triple junctions, grain boundaries, and grain interiors. Under a given subgrain formation rate, the rate of restructuring increases with rising fuel temperature. The restructuring occurs faster with higher burnup rate. A restructuring bias was observed within the microstructure, due to the variation in defect accumulation when comparing different grains. Microstructures corresponding to the dark zone and rim region can be obtained by parameterizing the model with the appropriate defect production rate, as determined based on the burnup rate and temperature. The predicted microstructures are consistent with experimental observations of the restructured regions. Based on the mesoscale simulations, a mechanistic model for restructuring and grain size evolution was implemented in BISON. Thus, this work provides a first-of-its-kind restructuring model for different regions of high-burnup fuel to BISON. It was shown that the model predicts appropriate grain size evolution along fuel radius as those observed in experiments. This model enables BISON to predict the effect of restructuring on the fission gas release. Finally, the phase-field fracture simulation with dark zone specific microstructures were presented to provide the fragmentation criteria for the dark zone. This work introduces a first-of-its-kind restructuring model for high burnup fuel, significantly enhancing BISON's predictive capabilities.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Optimization of direct air capture processes using reactive transport models of adsorption-desorption cycles

In this study, we develop and implement a reactive transport model in COMSOL Multiphysics® to address the challenges of direct air carbon capture. The model is validated against experimental data and used to simulate the cyclic steady state of the adsorption-desorption process. The optimization of this model is achieved through advanced trust-region methods integrated with Gaussian Processes. Key decision variables, including adsorption and desorption times, desorption temperature and pressure, input velocity, bed porosity, column length, and radius were optimized to minimize the capture cost. After optimization, a sensitivity analysis revealed the complex interplay between the decision variables and their effect on the specific energy and cost of removing the CO 2 . We optimized the capture cost while taking into account the trade-off between energy consumption and productivity. The resulting minimum capture cost was determined to be 265.2 $/t-CO 2 , which aligns with expected values reported in the literature. Numerical results suggest the effectiveness of the optimization strategies applied, and underscore the importance of simultaneous decision variable selection in improving the performance in direct air capture processes. We also extend the modeling approach to a 2D axisymmetric model to better visualize CO₂ uptake and temperature profiles, revealing significant radial gradients during the regeneration step. As a main drawback, this enhanced model comes with a computational cost approximately 40 times higher than that of the 1D model.

Adsorption-desorption process↗
DOE OSTI2023

Spin-orbital correlations from complex orbital order in MgV 2⁢ O 4

MgV 2 ⁢O 4 is a spinel based on magnetic V 3+ ions, which host both spin (𝑆 = 1) and orbital (𝑙 eff = 1) moments. Owing to the underlying pyrochlore coordination of the magnetic sites, the spins in MgV 2 ⁢O 4 only antiferromagnetically order once the frustrating interactions imposed by the 𝐹⁡𝑑⁢$\overline{3}$⁢𝑚 lattice are broken through an orbitally-driven structural distortion at T 𝑆 ≃ ⁢60 K. Consequently, a Néel transition occurs at T 𝑁 ≃ ⁢40 K. Low-temperature spatial ordering of the electronic orbitals is fundamental to both the structural and magnetic properties; however, considerable discussion on whether it can be described by complex or real orbital ordering is ambiguous. We apply neutron spectroscopy to resolve the nature of the orbital ground state and characterize hysteretic spin-orbital correlations using x-ray and neutron diffraction. Neutron spectroscopy finds multiple excitation bands and we parametrize these in terms of a multilevel (or excitonic) theory based on the orbitally degenerate ground state. Meaningful for the orbital ground state, we report an “optical-like” mode at high energies that we attribute to a crystal-field-like excitation from the spin-orbital 𝑗 eff = 2 ground-state manifold to an excited 𝑗 eff =1 energy level. We parametrize the magnetic excitations in terms of a Hamiltonian with spin-orbit coupling and local crystalline electric field distortions resulting from deviations from perfect octahedra surrounding the V 3+ ions. We suggest that this provides compelling evidence for complex orbital order in MgV 2⁢ O 4 . We then apply the consequences of this model to understand hysteretic effects in the magnetic diffuse scattering where we propose that MgV 2⁢ O 4 displays a high-temperature orbital memory of the low-temperature spin order.

Frustrated magnetism↗
DOE OSTI2021

Trends in best-in-class energy-efficient technologies for room air conditioners

Improving the efficiency of room air conditioners (RACs) could provide significant energy and associated emissions savings, particularly in emerging economies with hot climates where the cooling demand is expected to increase dramatically. To help accelerate efficiency improvements, this study identifies “best-in-class” high-efficiency RAC components and products. The findings show that manufacturers tend to minimize manufacturing costs by using RAC designs that are readily available or standardized to their production, and they share components across various models. High-efficiency RAC models use advanced compressor technologies optimized at a low frequency, large heat exchangers with thermodynamically effective materials and designs, highly efficient direct current fan motors, advanced metering devices, and smart sensors for temperature and humidity control. Recently RAC manufacturers have been improving seasonal efficiency – better reflecting part-load operation – especially via variable-speed (inverter) drives for compressor motors. Recent highest-efficiency RAC models use low global warming potential (GWP) refrigerants, having transitioned from conventional high-GWP refrigerants, in regions where RACs that use these low-GWP refrigerants are commercially available. Recently demonstrated innovative technologies show trends toward smart hybrid designs, evaporative cooling, and solid-state materials beyond the conventional vapor-compression technology. This information could help policymakers improve their RAC market-transformation programs to align with the most-efficient global technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Enhancement of ECCD by the current condensation effect for stabilizing large magnetic islands caused by neoclassical tearing modes in tokamak plasmas

The radio frequency current condensation effect reported in Reiman and Fisch (2018 Phys. Rev. Lett. 121 225001) is modeled in the nonlinear resistive magnetohydrodynamic code. A series of numerical investigations have been performed to investigate the enhancement of electron cyclotron current drive (ECCD) by the current condensation effect during the control of neoclassical tearing mode (NTM) in tokamak plasmas. In the numerical model, both the parallel transport and the perpendicular transport of electron temperature are considered. The EC driven current and driven perturbed electron temperature can nonlinearly evolve within the given magnetic configuration and eventually reach saturation states. The input power threshold of ECCD and the fold bifurcation phenomenon are numerically verified via nonlinear simulations. The numerical results show good agreements with the analytical results. Moreover, spatial distributions of EC current for the two solutions at different condensed level are displayed. The control effectiveness of ECCD for large NTM islands has been evaluated while considering the current condensation effect. While taking into account current condensation effect, for a sufficiently large input power, a larger island can be more effectively stabilized than a smaller one, which suggests a reassessment of the previous idea that the ECCD should always be turned on as early as possible. The potential physics mechanism behind the ECCD control have all been discussed in detail. Furthermore, the condensation effect is found to have favorable effects on the radial misalignment of ECCD. In the consideration of the situation for extremely localized control needs, a highly peaked heating profile is adopted to verify that the fold bifurcation phenomenon still exists and the current condensation effect can still take effect in this extreme condition.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Structure/property relationship of semicrystalline polymers during tensile deformation: a molecular dynamics approach

Molecular dynamics (MD) simulation with an ab initio numerical model is conducted to study the structure–property relationship of semicrystalline polymers during uniaxial deformation. The effects of chain length, temperature, and strain rate on mechanical properties are discussed. The influences of microstructural evolution such as bond length, entanglement density, and chain orientation are also studied quantitatively. The temperature will greatly affect the chain conformation in amorphous domains, and the results revealed that the interaction of amorphous and crystalline domains played a crucial role during stretching. Accordingly, the yielding of semicrystalline polymers follows different mechanisms at temperatures above and below T g . A melt-recrystallization scheme is observed during yielding at higher temperatures, while destruction of crystal structures is observed at lower temperatures at the yield point. The correlated effects of different temperatures and strain rates on mechanical properties are examined. This research is part of our efforts to develop a digital twin of a real experiment for efficient optimization of polymer material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

FLAMES─Fast, Low-Storage, Accurate, and Memory-Efficient Adaptive Sampling─Approach to Resolve Spatially Dependent Dynamics of Molecular Liquids

Many critical phenomena in soft matter occur at large length scales, necessitating the resolution of their structure and dynamics at low wavenumbers. However, resolving wavenumber-dependent dynamics computationally via molecular dynamics simulations presents significant challenges, as these phenomena span several orders of magnitude in both time and length scales, resulting in high computational costs and memory demands. Here, this work highlights the computational and memory challenges associated with analyzing molecular trajectories in reciprocal space and demonstrates a method to address them. We introduce FLAMESFast, Low-storage, Accurate, and Memory-Efficient adaptive Sampling, which is a direct method for calculation of structure factors, allowing us to select only the required number of wavevectors for binning. We also use wavenumber-dependent time steps to extract dynamics. Our FLAMES approach effectively mitigates computational and memory/storage bottlenecks. We demonstrate the method using simulations of a model system, liquid octane, at various temperatures. Comparisons with experimental data and real space computation show that the FLAMES technique achieves high accuracy in resolving temperature- and spatially dependent dynamics while being significantly more computationally efficient and requiring less memory and storage than methods based on a uniform wavevector grid and fixed temporal spacing.

Chen, Guang [Argonne National Laboratory (ANL), Ar↗
DOE OSTI2025

Ab Initio Simulation of Medium-Range Ordering in Ionic Glass Electrolytes LiSiPON and LiNaSiPON

Ionic glasses can exhibit a unique combination of optical transparency, electronic resistivity, ionic conductivity, and mechanical ductility. The origin of the relatively high ionic conductivity and ductility is poorly understood. Recently, these ionic glasses were found to have medium-range ordering (MRO) similar to that of metallic glasses. This MRO significantly impacts the properties of metallic glasses and is also expected to significantly impact the properties of ionic glasses. Here, this work used ab initio molecular dynamics (AIMD) simulations to study the effect of ionic glass composition on the MRO. The AIMD models showed that the degree of MRO increased as the temperature of the LiSiPON ionic glass decreased. The modeling also showed that the MRO is suppressed when 50% of Li is substituted with Na. This work lays the foundation for using AIMD to identify clear structure–property relationships in ionic glasses, allowing their properties to be optimized.

Osetsky, Yuri N. [Oak Ridge National Laboratory (O↗
DOE OSTI2021

Effect of water models on structure and dynamics of lignin in solution

Lignin, a major biomass component, can be an excellent source for different monomers in the polymer industry. However, the complex and heterogeneous structure of lignin poses a significant challenge for designing energy-efficient processes for depolymerization. As many proposed depolymerization processes are solvothermal, it is essential to understand the structure and dynamics of lignin in solution, in particular aqueous solution. Here, we utilize molecular dynamics simulations to understand the effect of water models on the structure and dynamics of different model lignin oligomers (softwood and hardwood) as a function of temperature. We have examined three different water models: TIP3P, TIP4P/Ew, and flexible SPC/Fw. We find that the diffusion constant of lignin oligomers in an aqueous solution differs significantly depending on the water model used. The diffusion constant of lignin in the TIP3P water model is almost twice as large as that in SPC/Fw and TIP4P/Ew. The softwood and hardwood oligomers adopt an extended structure in TIP3P water compared to SPC/Fw and TIP4P/Ew. Given the different levels of sensitivity of transport and structural properties of aqueous lignin on water models, it is important to take these into account when discussing results from a specific water model.

09 BIOMASS FUELS↗
DOE OSTI2022

Report Summarizing Progress in Digital Image Correlation Analysis of Burst Phenomenon

This report is an update on the progress made towards utilizing in-situ methods to observe and quantify Zry-4 deformation behavior during burst testing. A heavily modified burst test was developed that allows both digital image correlation and infrared thermography to be utilized during testing to quantify strain and axial thermal gradient data during burst. A variety of tests ranging from 6.2-15.9 MPa internal pressure and utilizing both constant and transient pressure conditions were conducted and presently reported on. The test modifications, which are detailed extensively in a previous report, are effectively found to have no discernible impact on burst temperatures when compared to historical Zircaloy burst data. To support future modeling studies, the IR thermography data was used to approximate the thermal gradient down the axial length at burst for all the claddings. Then, DIC is first correlated to thermocouple temperature for a 10.3 MPa Transient pressure test, and then DIC correlated to IR thermal gradient data down the axial length of a 8.2 MPa Transient pressure test at several points.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Thermal Analysis of the Bus Bars for the 800MeV Injection Era (Fermilab Summer School 2023)

My internship at IARC has been focused on the thermal analysis of the bus bars of the Booster. The bus bars are the conductors that bring the bias current from the bias supply to the ferrite tuners in each RF cavity of the synchrotron. Since they are not superconductors, during normal operations they will heat up due to the Joule effect. The goal of my work is to build a model of the bus bars assembly that describes effectively the experimental data and that can be used to predict the temperature increase and distribution among the components of the assembly, in present and future operational conditions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Effects of the next-nearest-neighbor hopping on the low-dimensional Hubbard model: ferromagnetism, antiferromagnetism, and superconductivity

The Hubbard model has attracted considerable interest due to its prototypical role in describing strongly interacting electronic systems, such as high-critical-temperature superconductors as well as many novel quantum materials. By introducing next-nearest-neighbor (NNN) hoppings to the Hubbard model, the phase diagram becomes richer, and fascinating phenomena arise in both, one-dimensional chains and square lattices, such as: antiferromagnetism, ferromagnetism, superconductivity (SC), as well as charge orders, among others. Moreover, NNN hoppings play a fundamental role in understanding effects of doping on magnetism and pairing orders in strongly interacting regimes. In this article, we review the recent progress in understanding the different competing phases of this model in one and two dimensions from a computational perspective. In conclusion, we comment on the pressing technical challenges, illustrate the controversial results concerning the emergence of the SC phase, and conclude with our perspectives on future explorations.

Hubbard model↗
DOE OSTI2022

Magnetic ground states of a model for M Nb 3 S 6 ( M = Co, Fe, Ni)

The transition-metal-intercalated dichalcogenide CoNb 3 S 6 is a triangular antiferromagnet (AFM) that has recently been shown to exhibit a large anomalous Hall effect (AHE) below the Neel temperature, even though the response to an external field is very small. This suggests that there is an interesting magnetic structure that interacts with the electronic structure to yield the AHE, as collinear AFMs cannot exhibit a nonzero AHE. We propose a model for magnetic transition-metal-intercalated dichalcogenides and examine its ground state as a function of interaction parameters. The model exhibits transitions between planar spin spirals, nonplanar spin spirals, and a particular noncoplanar so-called 3q state. Finally, this latter state must exhibit a nonzero AHE, while the spin spirals do not.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Assessing parallel path cooling tower performance via artificial neural networks

Real-time monitoring of a research nuclear reactor, a system in which all generated power is dissipated to the environment, can be performed via analysis of the heat rejection from the cooling system. Given an inlet water temperature and flow rate, the reactor power can be well-approximated from the outlet water temperature; however, the instrumentation to measure outlet conditions may not be robust or accurate. If we know how a cooling tower performs from historical data, but cannot measure the outlet temperature, a mathematical representation of the system can be inverted to obtain the outlet water temperature that describes the cooling capacity. Unfortunately, model inversion processes are computationally expensive. To address this, an artificial neural network (ANN) is implemented to assess the performance of a multi-cell cooling tower for a nuclear reactor. This approach leverages the Merkel model to obtain an extensive data set describing performance of the cooling tower cells throughout a wide array of potential operating conditions. The Merkel model is expressed as a function of four parameters: the inlet and outlet water temperatures, inlet air wet bulb temperature, and ratio of liquid-to-gas mass flow rates (L/G), which together provide a non-dimensional number indicative of cooling tower performance, called the Merkel integral. Computing a 4-dimensional data structure that describes finite combinations of the Merkel integral, an inverse model is then generated using an ANN to determine the cell outlet water temperature from the other three model parameters along with the computed Merkel integral. Compared to traditional model inversion methods, the ANN reduces the computational time by approximately 4 orders of magnitude, with effectively no sacrifice to solution accuracy, and could be applied for different cooling towers in the event the performance curve is known. Finally, three use cases of the ANN are then reviewed: (1) determining the cell outlet water temperatures when gas flow at rated conditions (GFRC) is known, (2) performing the prior case without knowledge of the GRFC, and (3) assessing performance differences between the individual tower cells.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗