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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 1,207 records · Page 67

The distribution of precipitation and the spread in tropical upper tropospheric temperature trends in CMIP5/AMIP simulations

Abstract Reconciling observations and simulations of tropical upper tropospheric temperature trends remains an important problem in climate science. Examining atmospheric models running over observed sea surface temperatures (SSTs), Flannaghan et al. (2014) show that this reconciliation is affected by the SST data set used and that a precipitation‐weighted SST (PSST) is valuable in explaining this result. Here we show that even for Coupled Model Intercomparison Project Phase 5 Atmospheric Model Intercomparison Project (CMIP5 AMIP) simulations forced with identical SSTs, tropical upper tropospheric temperature trends across models (and between ensemble members) show a substantial spread (standard deviation ∼10% of the average trend). About 60% of this spread between ensemble means, as well as deviations from the ensemble means, can be explained by PSST calculated from the time‐evolving precipitation in each model run. Both PSST and atmospheric temperature trends show statistical evidence for systematic differences between models. We conclude that the response of precipitation patterns to changes in SST patterns is a significant source of uncertainty for tropical temperature trends.

Fueglistaler, S.↗

Mechanical and Electrochemical Implications of Drying Temperature on Lithium‐Ion Battery Electrodes

Abstract Lithium‐ion battery (LIB) electrodes are typically produced with n‐methyl‐2‐pyrrolidone, a toxic solvent that is a known carcinogen and reproductive hazard. Accordingly, aqueous processing has been an expanding area of research interest in the field of LIB manufacturing. Although aqueous processing has been widely successful in anode processing, serious challenges remain in processing the cathode. In this work, the drying mechanics of cathode processed with both solvents is investigated though implementation of a chemical‐engineering‐based model to better understand the utilization of heat provided by experimentally determining the heat and mass transfer coefficients. Electrochemical performance is also evaluated to determine the impact of drying temperature on cycling performance. Binder distribution is determined via various methods to confirm differences in binder homogeneity as a function of both solvent and drying temperature. Identified is the large difference in the efficiency in which the heat is used as well as an ideal drying temperature for both aqueous and non‐aqueous processed cathodes. Also identified is the increased sensitivity to processing temperature for aqueous processed electrodes compared to non‐aqueous processed counterparts, pointing to the possibility of tuned drying regimes which would capitalize on the potential cost savings of aqueous processing for cathodes.

25 ENERGY STORAGE↗

Effective climate sensitivity distributions from a 1D model of global ocean and land temperature trends, 1970–2021

Abstract Current theoretically based Earth system models (ESMs) produce Effective Climate Sensitivities (EffCS) that range over a factor of three, with 80% of those models producing stronger global warming trends for 1970–2021 than do observations. To make a more observationally based estimate of EffCS, a 1D time-dependent forcing-feedback model of temperature departures from energy equilibrium is used to match measured ranges of global-average surface and sub-surface land and ocean temperature trends during 1970–2021. In response to two different radiative forcing scenarios, a full range of three model free parameters are evaluated to produce fits to a range of observed surface temperature trends (± 2σ) from four different land datasets and three ocean datasets, as well as deep-ocean temperature trends and borehole-based trend retrievals over land. Land-derived EffCS are larger than over the ocean, and EffCS is lower using the newer Shared Socioeconomic Pathways (SSP245, 1.86 °C global EffCS, ± 34% range 1.48–2.15 °C) than the older Representative Concentration Pathway forcing (RCP6, 2.49 °C global average EffCS, ± 34% range 2.04–2.87 °C). The strongest dependence of the EffCS results is on the assumed radiative forcing dataset, underscoring the role of radiative forcing uncertainty in determining the sensitivity of the climate system to increasing greenhouse gas concentrations from observations alone. The results are consistent with previous observation-based studies that concluded EffCS during the observational period is on the low end of the range produced by current ESMs.

54 ENVIRONMENTAL SCIENCES↗

Heat and Mass Transfer in the Drying of a Cylindrical Body in an Oscillating Magnetic Field

A problem on the heating of a cylindrical body of infinite length in an oscillating electromagnetic field in the process of its drying has been formulated and solved analytically with account of the intermittence of irradiation of the body defined by the Heaviside unit function, the exponential-law absorption of electromagnetic energy by it, and the convective heat and mass exchange between the surface of the body and the environment having constant parameters. The intensity of evaporation of moisture from the surface of the body was determined on the basis of analytical solution of the problem on the mass transfer (moisture diffusion) in it on the assumption that the phase transformations of the body proceed near its surface. Solutions of the problem on the heating of the cylindrical body have been obtained for the cases of nonuniform and uniform distributions of its local temperature, the temperature of the body averaged over its volume, and the temperature gradient near the surface of the body. The 'serviceability' of these solutions was verified on the basis of numerical simulation, with them, of the drying of a seed shaped as a cylinder under the action of an oscillating infrared radiation. As a result of the numerical simulation performed, a technological regime of drying of seeds at minimum and maximum temperatures of their heating by on oscillating infrared radiation for a definite period of time in a cycle, providing not only the drying of the seeds but also substantial improvement of their sowing properties (the sprouting energy and the germination power), has been found. It is shown that the oscillating infrared heating of seeds can be used for their drying in pseudofluidized and vibrofluidized beds.

42 ENGINEERING↗

Coupled Monte Carlo and thermal-fluid modeling of high temperature gas reactors using Cardinal

Cardinal is an open-source application that couples OpenMC Monte Carlo transport and NekRS computa-tional fluid dynamics to the Multiphysics Object-Oriented Simulation Environment (MOOSE), closing neutronics and thermal-fluid gaps in conducting high-resolution multiscale and multiphysics analyses of nuclear systems. Here, we provide an introduction to Cardinal's software design, data mapping, and multi -physics coupling strategy to highlight our approach to overcoming common challenges in multiphysics simulation. We then describe an application of Cardinal to prismatic High Temperature Gas Reactors (HTGRs) with various combinations of NekRS, OpenMC, BISON, and THM. A high-resolution coupling of NekRS, OpenMC, and BISON provides a reference solution at the unit cell level and shows excellent agree-ment with a lower-resolution coupling of THM, OpenMC, and BISON. A full core coupling of THM, OpenMC, and BISON resolving the three-dimensional conjugate heat transfer and sub-pin power distri-bution then provides detailed predictions of HTGR temperatures and the fission distribution.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Autonomous control for Heat-Pipe microreactor using Data-Driven model predictive control

To enable a self-regulating capability for heat pipe (HP) microreactors, an anticipatory control strategy achieved via model predictive control (MPC) could proactively respond to potential disturbances and deviations in operating setpoints. This paper demonstrates data-driven methods for predicting the distribution and transient of temperatures and heat fluxes at selected components and regions in a 37-HP system, based on which the optimal control actions in response to changes in user-defined setpoints can be found. We present the development and validation of linear state-space model, feedfoward, and recurrent neural networks. Here, we compare the performance of MPCs with different modeling approaches in terms of following setpoints for temperatures and averaged output heat fluxes. The accuracies of the three data-driven models are similar, but the control actions initiated by neural-network-based MPC can better adapt to drastic changes in setpoints yet generate the smallest errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Experimental demonstration of a dispatchable latent heat storage system with aluminum-silicon as a phase change material

In this work, we present the design, construction, and experimental results of a prototype latent heat thermal energy storage system. The prototype consists of a thermal storage tank with 100 kg of the aluminum-silicon eutectic as a phase change material, a valved thermosyphon that controls heat flow from the thermal storage tank to the power block, and thermoelectric generators for conversion of heat to electricity. We tested the prototype over four simulated days, where each day consisted of four phases of operation: charging, discharging, simultaneous charging and discharging, and storage. Our results show three major conclusions. First, the thermal energy storage system was able to receive and distribute heat with small temperature gradients - less than 5 degrees C throughout the thermal storage tank. Second, the valved thermosyphon was able to effectively control heat transfer, demonstrating an on/off thermal conductance ratio of 430. Third, the interfaces between subsystems had small temperature drops: of the ~ 560 degrees C temperature drop from the thermal storage tank to the heat rejection system, ~ 525 degrees C occurred across the power block. This work overcomes the challenges of integrating previously-developed subsystems together, providing a proof-of-concept of this system.

14 SOLAR ENERGY↗

Integration and validation of some modules for modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures

Three modules are integrated into the built-in OpenFOAM rhoCentralFoam solver towards accurate and efficient modelling of high-speed chemically reactive flows in two-phase gas-droplet mixtures within the OpenFOAM 10.0 framework. The first module is the mixture-averaged diffusion model. The second module is the built-in OpenFOAM Lagrangian solver coupled with optimised droplet drag coefficient and convective heat transfer coefficient sub-models. The last module is a sparse stiff chemistry solver based on dynamic adaptive hybrid integration (AHI-S). The optimised droplet sub-models are first verified in correct implementation for subsequent simulations in this work. Further, they show good accuracy against experimental and analytical data in the modelling of ammonia droplet acceleration and cooling in the flowing and/or low-temperature air. The accuracy and efficiency gains related to the mixture-averaged diffusion model and the AHI-S chemistry solver are examined by simulating 1-D detonation propagation in ammonia droplet-free/laden ammoniaoxygen mixtures. Numerical results of detonation propagation speed, gaseous temperature, density, and species distributions around the induction zone show good agreement with experimental data and analytical solutions. Compared to the built-in OpenFOAM diffusion model, the mixture-averaged diffusion model provides different numerical predictions of pulsating instabilities in detonation propagation. It shows better accuracy in depicting the detonation structure within the droplet-free section attributed to improved multi-component diffusion modelling. Compared to the built-in OpenFOAM solver EulerImplicit (backward Euler), the AHI-S chemistry solver reduces the computational cost by around 50%. It achieves satisfactory accuracy in calculating detonation propagation speed within the droplet-free section with the optimal efficiency when the safety factor, β, equals 0.5.

42 ENGINEERING↗

Insights on the structure and properties of sodium iron phosphate glasses from molecular dynamics simulations

Iron phosphate glasses are promising nuclear waste forms while more detailed understanding of their structures and structure-property relations are still needed to better design waste glass compositions. In this work we report studies of three series of sodium iron phosphate (NFP) glasses: 60P 2 O 5 -(40-x)Fe 2 O 3 -xNa 2 O (x = 0→40), (100–2x)P 2 O 5 -xFe 2 O 3 -xNa 2 O (x = 5→17.5) and one with different iron redox ratio, to understand the composition as well as the iron redox effects on the structure and properties of these glasses using molecular dynamics simulations with effective two-body and three-body potentials. Structural analyses, including pair distribution function, bond angle distribution, Q n distribution, and polyhedral connectivity, were performed to obtain in-depth information on short-range and medium-range structural features. The P-O pair distributions showed a first peak splitting with phosphorus-bridging and non-bridging oxygen contributions. This and the average P-O and other cation-oxygen bond distances are in excellent agreement with experiments. The coordination number of P 5+ remained four while that of Fe 3+ increased from 4.30 to 4.72 with decreasing Fe/Na ratio. Polyhedral linkage analysis showed [PO 4 ] units linked with [PO 4 ] and [FeO x ] through corner-sharing while the [PO 4 ]-[FeO x ] linkages become dominant for compositions with Fe 2 O 3 larger than 15 mol%. The effect of iron redox ratio on the structure of NFP glasses was also studied and it was found that bond lengths and coordination numbers were not strongly affected, while the reduction of iron introduced higher network distortions, as evident by O-P-O bond angle and Q n distribution. The glass transition temperature (T g ) showed a monotonic increase with Fe 2 O 3 in the first series, in good agreement with experiments, while those of the second series showed a maximum at P 2 O 5 = 82 mol%. Here, calculated elastic moduli were found to increase with Fe 2 O 3 in the first glass series, which was be explained by the increase of network connectivity, while those of the second series decrease with Fe 2 O 3 due to decrease of P 2 O 5 .

36 MATERIALS SCIENCE↗

Optimizing energy yield of monolithic perovskite/silicon tandem solar cells in real-world Conditions: The impact of luminescent coupling

Efficient light management is key to maximizing power conversion efficiency (PCE) in monolithic perovskite/silicon tandem solar cells. Achieving peak efficiency requires closely matched current generation in all junctions, especially in integrated configurations. However, real-world conditions vary significantly due to factors such as sunlight spectrum, diffuse-to-direct sunlight ratio, angular distribution of light, subcell temperature coefficients, and ground reflection. This study introduces a comprehensive optical and device simulation to optimize perovskite/silicon tandem cells, considering experimental luminescent coupling (LC) efficiency and its dependence on working conditions, alongside variations in radiative recombination, effect of temperature on absorptivity spectra, and cloud cover. Our results show potential energy yield improvements of up to 1.4 % with LC, based on current perovskite radiative recombination records, and up to 4 % with direct bandgap materials. Although radiative recombination's dependence on excitation intensity reduces output power and requires thicker absorbers, LC compensates for these losses. LC also lowers the optimized bandgap for the perovskite top cell from 1.72 eV to 1.64–1.68 eV, or even lower in regions with redshifted irradiance. Additionally, optimization revealed that thinner silicon bottom cells require a higher perovskite top cell bandgap, impacting the balance between fabrication cost and cell stability.

14 SOLAR ENERGY↗

Laser-Generated Ag Nanoparticles in Mesoporous TiO 2 Films: Formation Processes and Modeling-Based Size Prediction

Controlling the formation of nanoparticles (NPs) by direct laser writing ensures an efficient way of engineering the optical responses of nanocomposite materials through adjusting laser parameters such as power, focusing, and writing speed. The growth of NPs, photo-oxidation, and reduction affect the light absorption by an ensemble of laser-activated NPs. However, those self-consistent processes are not well understood. Previous studies explained the growth or shrinkage of silver NPs by neglecting heat diffusion. It remained unclear, however, how the NP size can be controlled by the laser writing speed. In this work, based on the coupled calculations of size variation, heat diffusion, and light absorption by an ensemble of NPs, we propose a two-dimensional model taking into account the spatial information of size and temperature. The spatial size distribution is revealed to be nonuniform, leading to the transmission inhomogeneity along the laser written lines. This fact is confirmed by the in situ transmission experiments. The performed study also depicts a novel view in which NPs grow ahead of the laser beam center because of the heat diffusion. The nonlinear growth never stops until it exhausts the majority of the free Ag 0 in the matrix, while the amount of Ag 0 by reduction cannot compensate the consumption. After that, the photo-oxidation dominates the process and finally controls the writing speed dependency of NP's size. Finally, the simulations also show that it is not the activation energy of Ag 0 diffusion, but the ionization efficiency affects the final NP size, which helps to understand how to improve the laser processing of differently prepared samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗

Sub-micrometre Particulate Matter is Primarily in Liquid Form over Amazon Rainforests

Particulate matter (PM) occurs in the Earth’s atmosphere both in liquid and non-liquid forms. The physical state affects the available physical and chemical mechanisms of growth and reactivity, ultimately affecting the number, size, and composition of the atmospheric particle population. Herein, the physical state, including the response to relative humidity (RH), was investigated on-line and in real time for PM (< 1 μm) over the tropical rain forest of central Amazonia during both the wet and dry seasons of 2013. The results show that the PM was liquid for RH > 80% across 296 to 300 K. These results, in conjunction with the distributions of RH and temperature in Amazonia, imply that near-surface submicron PM in Amazonia is liquid most of the time. The observations are consistent with laboratory experiments showing that PM produced by isoprene photo-oxidation is liquid across these meteorological conditions. The findings have implications for the mechanisms of new particle production in Amazonia, the growth of submicron particles and hence dynamics of the cloud life cycle, and the sensitivity of these processes to anthropogenic activities. An approach for inclusion of particle physical state in chemical transport models is presented.

Bateman, Adam P.↗

Molecular beam scattering of ammonia from a dodecane flat liquid jet

The evaporation and scattering of ND 3 from a dodecane flat liquid jet are investigated and the results are compared with previous studies on molecular beam scattering from liquid surfaces. Evaporation is well-described by a Maxwell–Boltzmann flux distribution with a cos θ angular distribution at the liquid temperature. Scattering experiments at E i = 28.8 kJ mol -1 over a range of deflection angles show evidence for impulsive scattering and thermal desorption. Further, at a deflection angle of 90°, the thermal desorption fraction is 0.49, which is higher than that of other molecules previously scattered from dodecane and consistent with work performed on NH 3 scattering from a squalane-wetted wheel. ND 3 scattering from dodecane results in super-specular scattering, as seen in previous experiments on dodecane. The impulsive scattering channel is fitted to a “soft-sphere” model, yielding an effective surface mass of 55 amu and an internal excitation of 5.08 kJ mol -1 . Overall, impulsively scattered ND 3 behaves similarly to other small molecules scattered from dodecane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning for Optimized Polarization at Jefferson Lab

Polarized cryo-targets and polarized photon beams are widely used in experiments at Jefferson Lab. Traditional methods for maintaining the optimal polarization involve manual adjustments throughout data taking by human shift takers. This may introduce some level of inconsistency simply due to the wide variety of experience and expertise of the shift takers themselves. Implementing machine learning-based control systems can improve the stability of the polarization without relying on human intervention. The cryo-target polarization is influenced by temperature, microwave energy, the distribution of paramagnetic radicals, as well as operational conditions including the radiation dose. Diamond radiators are used to generate linearly polarized photons from a primary electron beam. The energy spectrum of these photons can drift over time due to changes in the primary electron beam conditions and diamond degradation. As a first step towards automating the continuous optimization and control processes, uncertainty aware surrogate models have been developed to predict the polarization based on historical data. This talk will provide an overview of the use cases and models developed, highlighting the collaboration between data scientists and physicists at Jefferson Lab.

Jeske, Torri [Thomas Jefferson National Accelerato↗

Self-assembled Ag nanoparticle network passivated by a nano-sized ZnO layer for transparent and flexible film heaters

We investigated a self-assembled Ag nanoparticle network electrode passivated by a nano-sized ZnO layer for use in high-performance transparent and flexible film heaters (TFFHs). The low temperature atomic layer deposition of a nano-sized ZnO layer effectively filled the uncovered area of Ag network and improved the current spreading in the self-assembled Ag network without a change in the sheet resistance and optical transmittance as well as mechanical flexibility. The time-temperature profiles and heat distribution analysis demonstrate that the performance of the TFTH with the ZnO/Ag network is superior to that of a TFFH with Ag nanowire electrodes. In addition, the TFTHs with ZnO/Ag network exhibited better stability than the TFFH with a bare Ag network due to the effective current spreading through the nano-sized ZnO layer.

36 MATERIALS SCIENCE↗

Oxide or carbide nanoparticles synthesized by laser ablation of a bulk Hf target in liquids and their structural, optical, and dielectric properties

Laser ablation of a bulk Hf target in deionized (DI) water, ethanol, or toluene was carried out for the production of nanoparticles' colloidal solutions. Due to the interaction of the ablation plasma plume species with the species which are produced by the liquid decomposition at the plume-liquid interface, hafnia (HfO{sub 2}) nanoparticles are synthesized in DI water, hafnium carbide (HfC) nanoparticles in toluene, and a mixture of these in ethanol. The hafnia nanoparticles are in the monoclinic low temperature phase and in the tetragonal and fcc high temperature phases. Their size distribution follows log-normal function with a median diameter in the range of 4.3–5.3 nm. Nanoparticles synthesized in DI water have band gaps of 5.6 and 5.4 eV, in ethanol 5.72 and 5.65 eV (using low and high pulse energy), and in toluene 3 eV. The values for the relative permittivity in the range of 7.74–8.90 were measured for hafnia nanoparticles' thin films deposited on substrates by drop-casting (self-assembled layers) in parallel plate capacitor structures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Transport modeling of convection dominated helicon discharges in Proto-MPEX with the B2.5-Eirene code

Data-constrained interpretative analyses of plasma transport in convection dominated helicon discharges in the Proto-MPEX linear device, and predictive calculations with additional Electron Cyclotron Heating/Electron Bernstein Wave (ECH/EBW) heating, are reported. The B2.5-Eirene code, in which the multi-fluid plasma code B2.5 is coupled to the kinetic Monte Carlo neutrals code Eirene, is used to fit double Langmuir probe measurements and fast camera data in front of a stainless-steel target. The absorbed helicon and ECH power (11 kW) and spatially constant anomalous transport coefficients that are deduced from fitting of the probe and optical data are additionally used for predictive simulations of complete axial distributions of the densities, temperatures, plasma flow velocities, particle and energy fluxes, and possible effects of alternate fueling and pumping scenarios. The somewhat hollow electron density and temperature radial profiles from the probe data suggest that Trivelpiece-Gould wave absorption is the dominant helicon electron heating source in the discharges analyzed here. There is no external ion heating, but the corresponding calculated ion temperature radial profile is not hollow. Rather it reflects ion heating by the electron-ion equilibration terms in the energy balance equations and ion radial transport resulting from the hollow density profile. With the absorbed power and the transport model deduced from fitting the sheath limited discharge data, calculated conduction limited higher recycling conditions were produced by reducing the pumping and increasing the gas fueling rate, resulting in an approximate doubling of the target ion flux and reduction of the target heat flux.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗