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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Metal hydride based thermal energy storage system requirements for high performance concentrating solar power plants

High temperature concentrating solar power plants require suitable thermal energy storage systems to produce electric power efficiently. Thermochemical energy storage based on metal hydrides represents a very appealing prospect for low cost and high efficient solar storage systems. The objective of the paper is to assess the properties required by the metal hydride systems to achieve the U.S. Department of Energy’s SunShot techno-economic targets. A simplified model has been developed to evaluate the cost and the exergetic efficiency of hydridebased storage systems. Results demonstrate that metal hydride materials, operating at temperatures higher than 650 °C, with reaction enthalpy on the order of 95-110 kJ/molH 2 , raw material cost on the order of 1.4-2 $/kg, weight capacities on the order of 3-4% and operating pressures on the order of tens of bars have the potential to closely approach the targets. Selected sensitivity analyses have also been carried out showing that the raw material cost, the material weight capacity and the metal hydride reaction enthalpy are the properties that strongly affect the performance of the storage system.

08 HYDROGEN↗
DOE OSTI2018

Simulation of high temperature thermal energy storage system based on coupled metal hydrides for solar driven steam power plants

Concentrating solar power plants can achieve low cost and efficient renewable electricity production if equipped with adequate thermal energy storage systems. Metal hydride based thermal energy storage systems are appealing candidates due to their demonstrated potential for very high volumetric energy densities, high exergetic efficiencies, and low costs. The feasibility and performance of a thermal energy storage system based on NaMgH 2 F hydride paired with TiCr 1.6 Mn 0.2 is examined, discussing its integration with a solar-driven ultra-supercritical steam power plant. The simulated storage system is based on a laboratory-scale experimental apparatus. It is analyzed using a detailed transport model accounting for the thermochemical hydrogen absorption and desorption reactions, including kinetics expressions adequate for the current metal hydride system. The results show that the proposed metal hydride pair can suitably be integrated with a high temperature steam power plant. The thermal energy storage system achieves output energy densities of 226 kWh/m 3 , 9 times the DOE SunShot target, with moderate temperature and pressure swings. Also, simulations indicate that there is significant scope for performance improvement via heat-transfer enhancement strategies.

14 SOLAR ENERGY↗
DOE OSTI2021

Young Adult Populations Face Yet Another Barrier to Care With Insurers: Limited Access to Proton Therapy

Young patients, including pediatric, adolescent, and young adult (YA) patients, are most likely to benefit from the reduced integral dose of proton beam radiation therapy (PBT) resulting in fewer late toxicities and secondary malignancies. This study sought to examine insurance approval and appeal outcomes for PBT among YA patients compared with pediatric patients at a large-volume proton therapy center.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Grid and basis adaptive polynomial chaos techniques for sensitivity and uncertainty analysis

The demand for accurate and computationally affordable sensitivity and uncertainty techniques is constantly on the rise and has become especially pressing in the nuclear field with the shift to Best Estimate Plus Uncertainty methodologies in the licensing of nuclear installations. Besides traditional, already well developed methods – such as first order perturbation theory or Monte Carlo sampling – Polynomial Chaos Expansion (PCE) has been given a growing emphasis in recent years due to its simple application and good performance. This paper presents new developments of the research done at TU Delft on such Polynomial Chaos (PC) techniques. Our work is focused on the Non-Intrusive Spectral Projection (NISP) approach and adaptive methods for building the PCE of responses of interest. Recent efforts resulted in a new adaptive sparse grid algorithm designed for estimating the PC coefficients. The algorithm is based on Gerstner's procedure for calculating multi-dimensional integrals but proves to be computationally significantly cheaper, while at the same it retains a similar accuracy as the original method. More importantly the issue of basis adaptivity has been investigated and two techniques have been implemented for constructing the sparse PCE of quantities of interest. Not using the traditional full PC basis set leads to further reduction in computational time since the high order grids necessary for accurately estimating the near zero expansion coefficients of polynomial basis vectors not needed in the PCE can be excluded from the calculation. Moreover the sparse PC representation of the response is easier to handle when used for sensitivity analysis or uncertainty propagation due to the smaller number of basis vectors. The developed grid and basis adaptive methods have been implemented in Matlab as the Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm and were tested on four analytical problems. These show consistent good performance both in terms of the accuracy of the resulting PC representation of quantities and the computational costs associated with constructing the sparse PCE. Basis adaptivity also seems to make the employment of PC techniques possible for problems with a higher number of input parameters (15–20), alleviating a well known limitation of the traditional approach. The prospect of larger scale applicability and the simplicity of implementation makes such adaptive PC algorithms particularly appealing for the sensitivity and uncertainty analysis of complex systems and legacy codes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Accelerating Monte Carlo molecular simulations by reweighting and reconstructing Markov chains: Extrapolation of canonical ensemble averages and second derivatives to different temperature and density conditions

Accurate determination of thermodynamic properties of petroleum reservoir fluids is of great interest to many applications, especially in petroleum engineering and chemical engineering. Molecular simulation has many appealing features, especially its requirement of fewer tuned parameters but yet better predicting capability; however it is well known that molecular simulation is very CPU expensive, as compared to equation of state approaches. We have recently introduced an efficient thermodynamically consistent technique to regenerate rapidly Monte Carlo Markov Chains (MCMCs) at different thermodynamic conditions from the existing data points that have been pre-computed with expensive classical simulation. This technique can speed up the simulation more than a million times, making the regenerated molecular simulation almost as fast as equation of state approaches. In this paper, this technique is first briefly reviewed and then numerically investigated in its capability of predicting ensemble averages of primary quantities at different neighboring thermodynamic conditions to the original simulated MCMCs. Moreover, this extrapolation technique is extended to predict second derivative properties (e.g. heat capacity and fluid compressibility). The method works by reweighting and reconstructing generated MCMCs in canonical ensemble for Lennard-Jones particles. In this paper, system's potential energy, pressure, isochoric heat capacity and isothermal compressibility along isochors, isotherms and paths of changing temperature and density from the original simulated points were extrapolated. Finally, an optimized set of Lennard-Jones parameters (ε, σ) for single site models were proposed for methane, nitrogen and carbon monoxide.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Moment-based adaptive time integration for thermal radiation transport

Here, in this paper we develop a framework for moment-based adaptive time integration of deterministic multifrequency thermal radiation transpot (TRT). We generalize our recent semi-implicit-explicit (IMEX) integration framework for gray TRT to multifrequency TRT, and also introduce a semi-implicit variation that facilitates higher-order integration of TRT, where each stage is implicit in all components except opacities. To appeal to the broad literature on adaptivity with Runge–Kutta methods, we derive new embedded methods for four asymptotic preserving IMEX Runge–Kutta schemes we have found to be robust in our previous work on TRT and radiation hydrodynamics. We then use a moment-based high-order-low-order representation of the transport equations. Due to the high dimensionality, memory is always a concern in simulating TRT. We form error estimates and adaptivity in time purely based on temperature and radiation energy, for a trivial overhead in computational cost and memory usage compared with the base second order integrators. We then test the adaptivity in time on the tophat and Larsen problem, demonstrating the ability of the adaptive algorithm to naturally vary the timestep across 4–5 orders of magnitude, ranging from the dynamical timescales of the streaming regime to the thick diffusion limit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Frames induced by the action of continuous powers of an operator

We investigate systems of the form {A t g : g ϵ $\mathcal{G}$, t ϵ [0, L]} where A ϵ $\mathcal{B}$($\mathcal{H}$) is a normal operator in a separable Hilbert space $\mathcal{H}$, $\mathcal{G}$ c $\mathcal{H}$ is a countable set, and L is a positive real number. While the main goal of this work is to study the frame properties of {A t g : g ϵ $\mathcal{G}$, t ϵ [0, L]}, as intermediate steps, we investigate the completeness and Bessel properties of such systems from a theoretical perspective, which are of interest by themselves. Beside the theoretical appeal of investigating such systems, their connections to dynamical and mobile sampling make them fundamental for understanding and solving several major problems in engineering and science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A semiparametric latent factor model for large scale temporal data with heteroscedasticity

Large scale temporal data have flourished in a vast array of applications, and their sophisticated structures, especially the heteroscedasticity among subjects with inter- and intra-temporal dependence, have fueled a great demand for new statistical models. In this paper, with covariate information, we consider a flexible model for large scale temporal data with subject-specific heteroscedasticity. Formally, the model employs latent semiparametric factors to simultaneously account for the subject-specific heteroscedasticity and the contemporaneous and/or serial correlations. The subject-specific heteroscedasticity is modeled as the product of the unobserved factor process and subject’s covariate effect, which is further characterized via additive models. For estimation, we propose a two-step procedure. First, the latent factor process and nonparametric loading are recovered through projection-based methods, and following, we estimate the regression components by approaches motivated from the generalized least squares. By scrupulously examining the non-asymptotic rates for recovering the factor process and its loading, we show the consistency and efficiency of estimated regression coefficients in the absence of prior knowledge of latent factor process and subject’s covariate effect. Here, the statistical guarantees remain valid even for finite time points that makes our method particularly appealing when the subjects significantly outnumber the observation time points. Using comprehensive simulations, we demonstrate the finite sample performance of our method, which corroborates the theoretical findings. Finally, we apply our method to a data set of air quality and energy consumption collected at 129 monitoring sites in the United States in 2015.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Determining local thermal transport in a composite uranium-nitride/silicide nuclear fuel using square-pulse transient thermoreflectance technique

Laser-based techniques have become an appealing option for determining the thermal diffusivities (D) and conductivities (k) of nuclear materials that would otherwise prove too hazardous or difficult to measure otherwise. These techniques have enabled non-destructive and non-contact thermal transport measurements with micron-level spatial resolution. In this study, a new time-domain technique known as square-wave pulse thermoreflectance (SPTR) is described and used to determine D values of both uranium sesquisilicide (U 3 Si 2 ) and uranium nitride (UN) phases in a composite fuel. An extensive sensitivity analysis was conducted that identified the optimal measurement parameters of standard materials with a range of thermal transport properties comparable to those of various fuel types. The standards were measured using both SPTR as well as a spatial-domain thermoreflectance technique (SDTR). Several U 3 Si 2 and UN phase regions of polished UN/U 3 Si 2 (70/30 vol.%) samples were measured using both methods, and the resulting calculated D and k values are reported, with both techniques showing excellent agreement between samples. Finally, the ability to use the technique for local diffusivity mapping was demonstrated over a multiphase region, and could be used to determine thermal transport properties in precipitates, secondary phases, and irradiation-damaged regions of post-irradiated fuel samples.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Heavy ion irradiation response of an additively manufactured 316LN stainless steel

Additive manufacturing has become an appealing technique to fabricate three-dimensional metallic materials and components for nuclear reactors. However, response of additively manufactured alloys to high-dose heavy ion irradiations at elevated temperatures is still not well understood. Here, an additively manufactured 316LN austenitic stainless steel with high-density solidification cells was irradiated using 3.5 MeV Fe ion to a peak dose of 220 dpa at 450 °C. Microscopy studies show a lower Frank loop density and smaller size in the additively manufactured sample compared with its cold worked counterpart, and the cellular structures may largely suppress the formation of perfect loops and dislocation networks and reduce the magnitude of solute segregations comparing with high angle grain boundaries. In conclusion, the present work advances the understanding on the high-temperature irradiation response of additively manufactured steels for nuclear reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Single-source pulsed laser-deposited perovskite solar cells with enhanced performance via bulk and 2D passivation

Single-source vapor deposition of halide perovskites has, to date, remained challenging due to the dissimilar volatilities of the precursors, limiting the controlled transfer of multiple elements at once. Here, we demonstrate that pulsed laser deposition (PLD) addresses the rate-control challenges of single-source evaporation, enabling perovskite solar cells with power conversion efficiencies above 19% after passivation. Combining dry mechanochemical synthesis and PLD, we fabricated (Cl-passivated) MA1−xFAxPbI3 films from a single-source target. These films grow on hole-selective self-assembled monolayers, initially forming a thin PbI2-rich layer, which fully converts to perovskite. An oleylammonium iodide (OAmI) post-treatment is then applied to passivate the perovskite’s top surface by forming a 2D perovskite film. Incorporating PbCl2 in the target and applying OAmI-based 2D passivation results in a remarkable 19.7% efficiency for p-i-n perovskite solar cells with enhanced device stability. This highlights the appeal of PLD to fully unlock the potential of single-source vapor-deposited perovskites.

Soto-Montero, Tatiana↗
DOE OSTI2022

Diffusional lithium trapping as a failure mechanism of aluminum foil anodes in lithium-ion batteries

Aluminum foils are an appealing anode for lithium-ion batteries due to high capacity and low-cost, but their viability has been limited due to poor cyclability arising from pulverization and solid-electrolyte interphase growth. Here, we show that significant capacity degradation of aluminum foil anodes during electrochemical cycling also occurs due to diffusional lithium trapping. Scanning electron microscopy of cross-sectioned, cycled foils in the delithiated state reveals large regions of β-LiAl that are passivated by a surface layer of α-Al, which has poor Li + diffusivity. It is found that lithium diffusion occurs preferentially along the β-LiAl grain boundaries, so the grain structure after initial lithiation significantly affects the trapping behavior. Diffusional lithium trapping is exacerbated by both higher delithiation rates and higher areal capacity, presenting a challenge towards commercialization of aluminum foil anodes. We further demonstrate that diffusional trapping in aluminum foil anodes can be mitigated through alloy design, with the addition of 2–3 wt% Li yielding improved first cycle efficiency, and the addition of 1 wt% Si yielding improved cycle life. These results provide a mechanistic understanding of diffusional lithium trapping in aluminum foil anodes and highlight compositional design of alloys as a promising strategy to overcome it.

25 ENERGY STORAGE↗
DOE OSTI2020

Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration

Model predictive control (MPC) has been proven in simulations and pilot case studies to be a superior control strategy for large buildings. MPC can utilize the weather and occupancy schedule forecasts, together with the system model, to predict the future thermal behavior of the building and minimize the overall energy use and maximize thermal comfort. However, these advantages come with the cost of increased modeling effort, computational demands, communication infrastructure, and commissioning efforts. Thus a typical approach is to, often rapidly, simplify the building modeling and MPC optimization problem while paying a price of not reaching the full performance potential. It has been shown that by employing accurate physics-based models, MPC performance can be notably increased closer to its theoretical performance bound. However, implementation of such high-fidelity MPC in real buildings remains a challenge, resulting in a lack of successful field test studies. This work presents the methodology and field test demonstration of a computationally efficient implementation of the white-box MPC in an office building in Belgium. The detailed model of the building is based on first-principle physical equations. The deployment and supervision of MPC operation in a practical setting are supported by an automated cloud-based communication infrastructure. The motivating factor behind the cloud-based architecture is its compatibility with a commercially appealing control as a service concept. The building is equipped with a ground source heat pump (GSHP) and thermally activated building structures (TABS), where the combination of both is also known as GEOTABS. From a control perspective, GEOTABS buildings are particularly challenging systems due to large scale, complex heating, ventilation and air conditioning (HVAC) system, and slow dynamics with time delays. On the other hand, there is an increased potential for energy savings due to the high thermal mass, which acts as thermal storage. The MPC operation is demonstrated during the challenging transient seasons (switching between heating and cooling), and its performance is compared to a traditional rule-based controller (RBC). We provide a proof of concept of real MPC operation for the most difficult seasons with notable GSHP energy use savings equal to 53.5% and thermal comfort improvement by 36.9%. Other MPC applications found in the literature describe tests for only cooling or only heating, and up to now only for a black-box or a grey-box approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Electric-field effect on photoluminescence of lead-halide perovskites

With the development of novel semiconductors for optoelectronic applications, new device functionalities utilizing unique characteristics of emerging materials can be particularly appealing. Here, we demonstrate a reversible control of photoluminescence (PL) emission from lead-halide perovskites achieved in perovskite electric-double-layer transistors. PL in several prototypical lead-halide perovskite compounds is shown to be reversibly tuned by a small gate voltage in the range ±1.2 V applied to the ionic-liquid gel on the perovskite surface, with the intensity modulation that can reach one to two orders of magnitude. This effect may be mediated by a reversible migration of oxygen ions affecting the crystal region near the interface with the ion gel. The resulting passivation (or activation) of non-radiative recombination centers (traps) by oxygen ions would then modulate the population of mobile photogenerated electrons and holes that give rise to PL, which is thus tuned with an electric “knob” (the gate) in these devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

On the effect of strain rate during the cyclic compressive loading of liquid crystal elastomers and their 3D printed lattices

Nematic liquid crystal elastomers (LCEs) are a unique class of network polymers with the potential for enhanced mechanical energy absorption and dissipation capacity over conventional network polymers because they exhibit both conventional viscoelastic behavior and soft-elastic behavior (nematic director changes under shear loading). This additional inelastic mechanism makes them appealing as candidate damping materials in a variety of applications from vibration to impact. The lattice structures made from the LCEs provide further mechanical energy absorption and dissipation capacity associated with packing out the porosity under compressive loading. Understanding the extent of mechanical energy absorption, which is the work per unit mass (or volume) absorbed during loading, versus dissipation, which is the work per unit mass (or volume) dissipated during a loading cycle, requires measurement of both loading and unloading response. Here, in this study, a bench-top linear actuator was employed to characterize the loading-unloading compressive response of polydomain and monodomain LCE polymers and polydomain LCE lattice structures with two different porosities (nominally, 62% and 85%) at both low and intermediate strain rates at room temperature. As a reference material, a bisphenol-A (BPA) polymer with a similar glass transition temperature (9 °C) as the nematic LCE (4 °C) was also characterized at the same conditions for comparing to the LCE polymers. Based on the loading-unloading stress-strain curves, the energy absorption and dissipation for each material at different strain rates (0.001, 0.1, 1, 10 and 90 s -1 ) were calculated with considerations of maximum stress and material mass/density. The strain-rate effect on the mechanical response and energy absorption and dissipation behaviors was determined. The energy dissipation ratio was also calculated from the resultant loading and unloading stress-strain curves. All five materials showed significant but different strain rate effects on energy dissipation ratio. The solid LCE and BPA materials showed greater energy dissipation capabilities at both low (0.001 s -1 ) and high (above 1 s -1 ) strain rates, but not at the strain rates in between. The polydomain LCE lattice structure showed superior energy dissipation performance compared with the solid polymers especially at high strain rates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Probing the potential of type V Deep eutectic solvents as sustainable electrolytes

The increasing interest within the scientific community in environmentally friendly solvents has led to a focus on Deep Eutectic Solvents (DES), which have natural components. DES are viewed as alternatives to traditional organic solvents and have the potential to be used as electrolytes. For the first time, transport properties of four Type V Deep Eutectic Salt Solutions (DESS) were accessed to investigate the potential of this technology, selecting precursors ranked as excellent in Eco-Scale metrics. The DESS were composed of terpene and trioctylphosphine oxide (TOPO), and varying concentrations of lithium bis(trifluoromethane)sulfonimide (LiTFSI), and their properties were assessed through self-diffusion, viscosity, density, and conductivity measurements. While Type V DESS are capable of dissolving significant amounts of LiTFSI (up to 30 % molar), their ionic conductivity is low, with values ranging from 3.6·10 –3 to 9.3·10 –2 mS·cm –1 at 25 °C, thus limiting their suitability as electrolytes, for instance, for lithium-ions batteries applications. Similar diffusion coefficients for Li + and TFSI – ions suggest the formation of long-lived ion pairs moving as a neutral species. As a result, future research aims to introduce additives to disrupt contact ion pairs and enhance transport properties, leveraging the sustainable appeal of DES and their use in advanced energy storage technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗