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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
NASA NTRSDate not supplied

Vanadium Valence in MgAl2O4 Spinels at Reducing Conditions (IW to IW-5)

Vanadium is commonly a major or minor element in spinel structured oxides from a wide range of planetary materials [1-3]. Vanadium is stable in multiple valence states of 5+, 4+, 3+, and 2+ in natural systems, and spinel-structured oxides are known to host vanadium in 4+, 3+, and 2+ [4-6]. However, the understanding of 2+ stability at lower fO2 conditions has been hindered by lack of experiments at or below IW-1 conditions [5]. Insufficient experimental data is available due to the difficulty in controlling fO2 at low conditions in general, and the lack of appropriate standards for comparison to natural materials. Our progress on controlling fO2 in high pressure experimental samples has allowed us to create reducing conditions that are appropriate to studying V valence in spinels at fO2 relevant to natural reducing systems [7]. Here we extend this approach to study V in reduced conditions, at high temperatures. After at-tempting shorter durations and lower temperatures, we demonstrated the need for equilibration times > 6 hours at 1600 °C in order to approach equilibrium. Only then can we produce highly equilibrated samples that provide new insights into V valence at low fO2.

oxygen fugacity↗
NASA NTRS2023

Influences of Varied Electrical Discharge Machining Operations on Surface Conditions of Several Nickel-Based Superalloys

Nickel-based superalloys designed for use in gas turbine engines blades are difficult and expensive to properly machine without undue surface damage, due in part to their superior mechanical properties at high temperatures. Numerically controlled electrical discharge machining (EDM) has progressed to commonly be used as a machining process for initial sectioning, detailed roughing, and even some finishing operations. The objective of this study was to examine the effect of EDM on resulting surface conditions of superalloy 718 after slicing using typical rough, semi-finish, and finish condition sets with a typical wire EDM machine. Surface roughness, residual stress, and microstructures were compared for these conditions. The varied EDM conditions influenced surface roughness as intended. The residual stresses and surface roughness directly corresponding to the EDM steps were determined. While roughness decreased when progressing from rough to finish EDM conditions, tensile residual stresses unexpectedly increased. Brief assessments after EDM of two higher performance powder metallurgy disk superalloys ME209 and LSHR indicated this inverse relationship of roughness versus tensile residual stress was also present for these superalloys, where tensile residual stresses were significantly enhanced.

superalloys↗
NASA NTRS2023

Multiphysics Modeling of Electrode Dissolution under Hydrodynamic Conditions in Low Conductivity Water

Efficient plug-flow electrochemical reactors are characterized by their ability to effectively convert species with significant ionic strength and/or with the assistance of a well-behaved electrolyte. Because of the classic electroconductivity requirement, electrochemical reactors are not particularly attractive options for applications with low-conductivity conditions, especially for low-pressure feeds. However, these reactors can still find application in dedicated processes such as ultra-clean water conditioning and biological-coupled separation systems. Consequently, a multi-physics model was developed using COMSOL Multiphysics to characterize different reactor-design conditions based on the Tertiary Current Distribution which accounts for the effects of expected variations in electrolyte composition and ionic strength on the electrochemical process, as well as solution resistance and electrode kinetics. The modelling framework presented here employs single-phase laminar fluid flow, the Nernst-Planck equation, the water-based electroneutrality condition, and concentration-dependent overpotentials. This investigation particularly explores the electrolysis process of “anodic dissolution,” in which elemental species dissociate from the solid matrix of the electrode and enter the liquid phase of the electrolyte as soluble ions. The reactor configuration of interest has a rectangular parallel-electrode design and is operated galvanostatically. A series of parametric studies are carried out to inspect the response of the system when hydrodynamic, kinetic, and geometric conditions are changed. The parametric sweep resulted in variable effluent concentrations and system voltage, which reveal underlaying optimization patterns for electrode dissolution in low conductivity water.

Multiphysics↗
DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗
DOE OSTI2025

Order conditions for nonlinearly partitioned Runge-Kutta methods

Recently, a new class of nonlinearly partitioned Runge–Kutta (NPRK) methods was proposed for nonlinearly partitioned systems of autonomous ordinary differential equations y' = F(y, y). The target class of problems are those in which different scales, stiffnesses, or physics are coupled in a nonlinear way, wherein the desired partition cannot be written in a classical additive or component-wise fashion. Here we use a rooted-tree analysis to derive full-order conditions for NPRKM methods, where M denotes the number of nonlinear partitions. Due to the nonlinear coupling and thereby the mixed product differentials, it turns out that the standard node-colored rooted tree analysis used in analyzing ODE integrators does not naturally apply. Instead we develop a new edge-colored rooted-tree framework to address the nonlinear coupling. The resulting order conditions are enumerated, are provided directly for up to fourth order with M = 2 and third order with M = 3, and are related to existing order conditions of additive and partitioned RK methods. We conclude with an example that shows how the nonlinear order conditions can be used to obtain an embedded estimate of the state-dependent nonlinear coupling strength in a dynamical system.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Survival of B. Horneckiae Spores Under Ground-simulated Space Conditions

To prevent forward contamination and maintain the scientific integrity of future life detection missions, it is important to characterize and attempt to eliminate terrestrial microorganisms associated with exploratory spacecraft and landing vehicles. Among the organisms isolated from spacecraft-associated habitats, spore-forming microbes are highly resistant to various physical and chemical conditions, which include ionizing and UV radiation, desiccation and oxidative stress, and the harsh environment of outer space or planetary surfaces. Recently a radiation resistant, spore forming bacterial isolate, Bacillus horneckiae, was isolated from a clean room of the Kennedy Space Center where the Phoenix spacecraft was assembled. The exceptionally high tolerance of extreme conditions demonstrated by sporeforming bacteria highlighted the need to assess the viability of these microbes in situ (in real) space. The proposed BOSS (Biofilm Organisms Surfing Space) project aims to understand the mechanisms by which biofilm forming organisms, such as B. horneckiae, will potentially be able to withstand harsh space conditions. As previously stated, the spore producing ability of these species gives them increased survivability to harsh conditions. Some of the spores will have the protective exosporium layer artificially removed before the test to determine if the existence of this layer significantly changes the survivability during the mission. In preparation for that experiment, we analyzed spores which were exposed during a ground simulation, the EXPOSE R2 Biofilm Organisms Surfing Space (BOSS). Previous to exposure, spores were deposited onto spacecraft grade aluminum coupons in a spore suspension calculated to contain between 10(exp 7) and 10(exp 8) spores. This precursor series will be used to establish a baseline survivability function for comparison with the future flight tests during EXPOSE-R. For each coupon, a 10% polyvinyl alcohol (PVA) film was applied and peeled from the coupon to recover the spores. One hundred μl of sterile 10% PVA was applied to the surface of the coupon and allowed to dry for 1 hour at 37 C. The films were then removed using sterile scalpel and forceps and placed into a glass test tube containing 2 milliliters of sterile deionized water. The PVA film process was then repeated on each coupon one additional time to ensure recovery of the majority of spores. The second PVA film was added in the same glass tube as in the previous round. If the spores remained 100% viable, the test tubes should now contain between 5 X 10(exp 6) and 5 X 10(exp 7) spores per millimeter; however, it is expected that some loss of viability has occurred. In order to assess this loss, the number of colony forming, viable spores was counted. To count the colony forming units (CFUs), the spore containing solution was diluted in a process of 10-fold serial dilution by mixing successive solutions in a 100 microliter spore suspension to 900 microliter deionized H2O ratio. A sample dilution series revealed that 10(exp -3) and 10(exp -4) concentrations would be necessary for an accurate CFU count to be taken. For those two concentrations, a spread on a TSA plate was prepared and incubated at 32 C. For the samples exposed to UV radiation, the cell survivability was too low to establish a count from 100 microliter spread plating. Instead, no dilutions were performed and the entire 2 milliliter spore suspension was plated and incubated at 32 C. The plate's CFU counts were taken at 24 hours and 48 hours from the time of plating. At the end of the CFU counting the total surviving spores in each sample were calculated based on the number of CFUs that were observed per 100 microliters, or per 2 milliliters for the UV irradiated samples. The results of these calculations are shown in Figures 1 and 2.

cleanroom↗
NASA NTRS2020

INVESTIGATING THE FEASIBILITY AND STABILITY FOR MODELING ACOUSTIC WAVE SCATTERING USING A TIME-DOMAIN BOUNDARY INTEGRAL EQUATION WITH IMPEDANCE BOUNDARY CONDITION

Reducing aircraft noise is a major objective in the field of computational aeroacoustics. When designing next generation quiet and environmentally friendly aircraft, it is important to be able to accurately and efficiently predict the acoustic scattering by an aircraft body from a given noise source. Acoustic liners are an effective tool for aircraft noise reduction and are characterized by a frequency-dependent impedance. Converted into the time-domain using Fourier transforms, an impedance boundary condition can be used to simulate the acoustic wave scattering by geometric bodies treated with acoustic liners. This work considers using either an impedance or an admittance (inverse of impedance) boundary condition to allow for acoustic scattering problems to be modeled with geometries consisting of both un-lined and lined surfaces. Three acoustic liner models are discussed: the Extended Helmholtz Resonator Model, the Three-Parameter Impedance Model, and the Broadband Impedance Model. In both the Helmholtz and Three-Parameter models, liner impedance is specified at a given frequency, whereas the Broadband model allows for the investigation of multiple frequencies simultaneously. The impedance and admittance boundary conditions for acoustic liners are derived for each model and coupled with a time-domain boundary integral equation. The scattering solution is obtained iteratively using a boundary element method with constant spatial and third-order temporal basis functions. Time-domain boundary integral equations are unfortunately prone to numerical instabilities due to resonant frequencies resulting from non-trivial solutions in the interior domain. When reformulated with the Burton-Miller method, the instabilities are eliminated. Using a Burton-Miller reformulation, the stability of the boundary element method assuming a liner boundary condition is assessed using eigenvalue analysis. The stability of each liner model is discussed, and it is shown that the Three-Parameter and Broadband models are sufficient for modeling an acoustic liner on the surface of scattering bodies. The Helmholtz model demonstrates strict limitations for stability, whereas the Three-Parameter and Broadband models are stable for most cases. Also included in this work is an assessment of the spatial accuracy of the time-domain boundary element method with respect to the surface element basis functions, as well as a performance study of the numerical algorithm.

computational mathematics↗
NASA NTRSDate not supplied

An Extension of the Truncated Ingard-Myers Impedance Boundary Condition for High Mach Number Grazing Flows

The Ingard-Myers impedance boundary condition is widely recognized to be prone to hydrodynamic Kelvin-Helmholtz-type instability, primarily due to its use of a vortex sheet to model the flow at the boundary. Recently, a stabilized approximation of the Ingard-Myers condition, called the Truncated Ingard-Myers Impedance Boundary Condition (TIMIBC), has been introduced. This approximation offers a good representation of the Ingard-Myers condition for grazing flows characterized by low to mid subsonic Mach numbers. This paper explores an extension of the TIMIBC, referred to as TIMIBC-ext, designed for liners in grazing flows with high subsonic Mach numbers. The TIMIBC-ext introduces a tunable parameter and demonstrates that by judiciously selecting the parameter value, the accuracy of the TIMIBC can be improved for either upstream or downstream propagating waves in grazing flows with high subsonic Mach numbers. Consequently, the TIMIBC-ext represents an enhancement to the TIMIBC when the location of the source relative to the liner (upstream or downstream) is known. Time domain implementations of the TIMIBC-ext are also provided, employing a multipole expansion model for the impedance function. A numerical example is provided to assess the performance of the TIMIBC-ext, comparing computational results with measurements from a recent set of measurements in the NASA Langley Grazing Flow Impedance Tube.

time domain acoustic scattering↗
DOE OSTI2024

Imaging the initial condition of heavy-ion collisions and nuclear structure across the nuclide chart

High-energy nuclear collisions encompass three key stages: the structure of the colliding nuclei, informed by low-energy nuclear physics, the initial condition , leading to the formation of quark–gluon plasma (QGP), and the hydrodynamic expansion and hadronization of the QGP, leading to final-state hadron distributions that are observed experimentally. Recent advances in both experimental and theoretical methods have ushered in a precision era of heavy-ion collisions, enabling an increasingly accurate understanding of these stages. However, most approaches involve simultaneously determining both QGP properties and initial conditions from a single collision system, creating complexity due to the coupled contributions of these stages to the final-state observables. To avoid this, we propose leveraging established knowledge of low-energy nuclear structures and hydrodynamic observables to independently constrain the QGP’s initial condition. By conducting comparative studies of collisions involving isobar-like nuclei—species with similar mass numbers but different ground-state geometries—we can disentangle the initial condition’s impacts from the QGP properties. This approach not only refines our understanding of the initial stages of the collisions but also turns high-energy nuclear experiments into a precision tool for imaging nuclear structures, offering insights that complement traditional low-energy approaches. Opportunities for carrying out such comparative experiments at the Large Hadron Collider and other facilities could significantly advance both high-energy and low-energy nuclear physics. Additionally, this approach has implications for the future electron-ion collider. While the possibilities are extensive, we focus on selected proposals that could benefit both the high-energy and low-energy nuclear physics communities. Originally prepared as input for the long-range plan of U.S. nuclear physics, this white paper reflects the status as of September 2022, with a brief update on developments since then.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A survey study on arsenic speciation in coal fly ash and insights into the role of coal combustion conditions

Coal fly ashes (CFAs) are the low-density byproducts of the coal combustion process. Improper or uncontrolled CFA disposal poses significant environmental and health concerns due to the potential leaching of toxic heavy metals such as arsenic (As). Previous studies have investigated the content and speciation of As in different CFA samples, yet systematic information on As speciation in CFA with representative coal source and combustion conditions is still missing. Based on a recent survey study on the typical coal sources and combustion conditions across the U.S., this study selected 19 representative CFA samples to systematically investigate As speciation and potential correlations with these parameters. The composition, morphology, mineralogy, and As speciation of these CFA samples were characterized by complementary analytical, microscopic, and spectroscopic techniques. Synchrotron X-ray spectroscopy and microscopy analyses revealed the dominant As oxidation state to be As(V) and with strong associations to Ca, with the exception of 3 samples that had 19–51% As(III), likely due to the use of selective catalytic reduction (SCR) process. Principal component analysis was conducted to identify potential correlations of As concentration and oxidation state with parameters such as major element content, loss on ignition (LOI), average particle size, coal source, and combustion condition. Al 2 O 3 and FeO content were found to capture a majority of the variability. Further, results from this study provide fundamental basis for understanding the correlations between coal source, combustion conditions, CFA characteristics, and As speciation, and providing insights for downstream beneficial utilization or disposal management.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Burn parameters affect PAH emissions at conditions relevant for prescribed fires

Wildfire smoke is a health hazard as it contains carcinogenic volatile compounds and fine particulate matter. In particular, exposure to polycyclic aromatic hydrocarbons (PAHs) is a major concern, since these compounds have been recognized as important contributors to the overall carcinogenic risk. In this work, gas and particle-phase PAH emissions from combustion of Eastern White Pine (Pinus strobus) were quantified using time-of-flight mass spectrometry over a range of burn conditions representative of wildfires and prescribed fires, including fuel moisture, heat flux, and oxygen concentration. We found that changing the burn environment lead to a variability of up to 77% in phenanthrene/anthracene emissions. This could explain a large part of the variability in PAH emission factors from biomass combustion reported in the literature. Here, we found that optimal conditions for fuel moisture content of 20–30%, sample heat load of 60 - 70 kW m -2 , and oxygen concentrations of 5–15% can significantly reduce the emissions of heavy molar weight PAHs. Our analysis showed that the relative carcinogenic risk from PAH exposure can be reduced by more than 50% under optimal conditions. In light of the increasing use of prescribed fire for forest management, the relationship between emissions and burn conditions that we have established provides a guidance for assessing the expected health impact from prescription burns, and can inform strategies to reduce PAH emissions from prescribed fire activities.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Influence of extreme temperature conditions on CO 2 direct air capture using amino-acid solutions

Geological features play a pivotal role in determining the feasibility of deploying CO₂ direct air capture (DAC) technologies, primarily because they influence the availability of cost-effective energy sources, such as natural gas and geothermal energy, and also due to the potential for CO₂ sequestration. Many regions face challenges due to variable weather conditions including seasonal temperature fluctuations, high or low humidity, and sub-ambient temperatures. These extremes can reduce DAC performance or even lead to catastrophic events. Aqueous solvents considered for DAC systems are particularly vulnerable to seasonal variations in colder climates, where the solvent may underperform or freeze. It is therefore essential to investigate the CO₂ capture efficiency of aqueous solvents across a broad range of environmental temperatures, spanning sub-zero to hot conditions (>30 °C). In this study, DAC operation is examined using a high-flux solvent–air crossflow contactor under two major weather scenarios: (i) cold conditions below 0 °C and (ii) hot conditions above 30 °C. A parametric study is conducted to investigate the contactor performance regarding CO₂ removal efficiency, uptake capacity, and reaction kinetics versus temperature when the air velocity through the contactor exceeds 1 m/s. The efficacy of the contactor is systematically investigated using various anti-freeze amino-acid solvent formulations. A mass-transfer mechanistic model is developed to assess the process performance over a wide temperature range and propose scalable design guidelines. Machine learning is also employed to identify key parameters affecting the CO₂ capture efficiency. It is shown that air velocity and temperature are the primary factors influencing CO₂ uptake. Based on performance data obtained under subfreezing temperatures, a technoeconomic analysis is conducted to evaluate the feasibility of using aqueous solvents in seasonal cold regions. In conclusion, the findings of this study provide valuable insights into siting considerations for deploying solvent-based DAC, thereby contributing to the advancement of sustainable carbon removal solutions.

Air–liquid contactor↗
DOE OSTI2024

Flame kinetics at scramjet-engine-relevant conditions: Role of prompt dissociation of weakly-bound radicals

Combustion in high-speed ram-based propulsion engines occurs under distinct thermodynamic conditions of high reactant temperatures (greater than 1000 K) and relatively low pressures (<5 atm). There is a lack of fundamental flame measurements at such conditions that result in adiabatic flame temperatures (T ad ) exceeding 2500 K. In this work, we have measured laminar flame speeds of oxygen-enriched CH 4 /oxidizer mixtures at sub-atmospheric conditions to probe kinetics at high T ad using the isobaric spherically expanding flame approach. Simulations with recent kinetic models revealed increasing differences between data and model predictions with increasing T ad , reaching up to 25 %. Kinetic analyses reveal that at the thermodynamic conditions in these O 2 -enriched flames, i.e., lower pressures and higher T ad , the effects of HCO prompt dissociation are accentuated. In addition to HCO, the prompt dissociations of CH 2 OH and C 2 H 5 are also considered. Here, the prompt dissociations of all three radicals were evaluated and their effects considered in flame speed simulations. Reaction path analysis for the present flames revealed that approximately half of the reaction flux for HCO formation undergoes prompt dissociation to H + CO. Furthermore, these analyses also revealed that the pathways and sensitive reactions are similar between oxygen-enriched fuel/oxidizer mixtures and preheated fuel/air mixtures, if both have similar T ad . Thus, flames of oxygen-enriched mixtures could be a surrogate to probe the flame chemistry of highly preheated mixtures at relatively low pressures that are often encountered in ram-based propulsion engine combustors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Comparative analysis of thermal management systems in electric vehicles at extreme weather conditions: Case study on Nissan Leaf 2019 Plus, Chevrolet Bolt 2020 and Tesla Model 3 2020

With the surge in electric vehicle (EV) adoption and the need for extended driving ranges, optimizing energy efficiency, particularly through thermal management, is critical, especially in extreme weather. Managing the substantial energy needed for cabin climate control and battery temperature regulation can increase energy demands by over 50 %, severely limiting range. This study conducts a comparative analysis of thermal management systems (TMS) in three popular EV vehicles, 2020 Chevrolet Bolt, 2019 Nissan Leaf Plus, and 2020 Tesla Model 3, evaluating their distinct TMS configurations and performance under varied weather conditions. Using both numerical simulations and experimental data collected on a controlled test bench at Argonne National Laboratory, we assess how TMS architecture and operational modes influence energy consumption and range. A comprehensive TMS model was developed, integrating cabin and battery thermal sub-models in the Autonomie software platform, to simulate temperature fluctuations and range impacts. Cabin climate was modeled using a mono-zonal approach, while battery cell temperature distribution was estimated through a 2D nodal structure. Each vehicle's distinct TMS setup was evaluated: the Chevrolet Bolt and Tesla Model 3 use a dual evaporator vapor compression cycle with a PTC heater for the cabin and a coolant loop for battery thermal management; the Nissan Leaf Plus employs a heat pump with a PTC heater for the cabin and air-cooling for the battery. Tests conducted at ambient temperatures of 35°C, 22°C, -7°C, and -18°C reveal significant differences in energy use and range reduction across both configurations and conditions. At 35°C, the Tesla Model 3, Chevrolet Bolt, and Nissan Leaf Plus have a range reduction of 8%, 9%, and 13%, respectively, due to air conditioning. In winter, heating technology is paramount; at -7°C, the Nissan Leaf's heat pump configuration achieves a lower range reduction (19.3%) compared to the Tesla and Chevrolet Bolt PTC heaters, which reduce range by 28.3% and 31%, respectively. Further, this study provides valuable insights for automotive engineers, EV technology researchers, and thermal management system designers aiming to enhance electric vehicle performance by understanding how different weather conditions and TMS architectures impact energy consumption and driving range.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Estimating QSVT angles for matrix inversion with large condition numbers

Quantum Singular Value Transformation (QSVT) is a state-of-the-art, near-optimal quantum algorithm that can be used for matrix inversion. The QSVT circuit is parameterized by a sequence of angles that must be pre-calculated classically, with the number of angles increasing as the matrix condition number grows. Computing QSVT angles for ill-conditioned problems is a numerically challenging task. Here, we propose a numerical technique for estimating QSVT angles for large condition numbers. This technique allows one to avoid expensive numerical computations of QSVT angles and to emulate QSVT circuits for solving ill-conditioned problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed

The 1997 New Year’s flood was among the most devastating floods in the Truckee River watershed located in western Nevada. This event resulted from complex interactions of flood drivers, such as extreme precipitation, wet antecedent watershed conditions, warm temperatures and rapid snowmelt. We leveraged simulated forcings from the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) and a process-based hydrological model to recreate the 1997 New Year’s flood for the Truckee River watershed across four climate warming levels ranging from the current temperatures to + 4° C. For each scenario, we conducted ensemble simulations with the same forcing but with 100 different seasonal watershed antecedent conditions, which were randomly sampled from long-term hydrological simulations. The results show that the 1997 New Year’s flood can be reproduced or exceeded consistently only when the antecedent watershed conditions are wet, specifically when streamflows are above the 75th percentile of the climatological value. There is negligible change in ensemble mean peakflows for Truckee River near Reno; however, there are increases of 18% and 14% under the warming levels of + 3° C and + 4° C, respectively. The increases in peakflows under future climate warming are attributed to wetter antecedent watershed conditions and enhanced snowmelt. Furthermore, the largest increases in peakflows occur at small, high-elevation headwater basins along the Sierra Nevada crest. This study highlights that changes in extreme flood events will result from the complex interplay of multiple flood drivers. It also demonstrates the potential of storyline approaches to analyze future realizations of these extreme events under different climate scenarios.

Climate change impact study↗
DOE OSTI2025

Insight into the deformation features and capacity loss mechanisms of lithium-ion pouch cells under spherical indentation conditions

Mechanical deformation under extreme conditions is one of the important reasons for the failure of lithium-ion batteries in automotive application. However, the deformation features and component failure of lithium-ion cells to external loading has never been a design consideration. Here, in this study, we conduct spherical indentation tests on a dozen of lithium-ion cells with different capacities under different control mode conditions to investigate their deformation features and capacity loss mechanisms. The experimental results show that, under mechanical deformation conditions, internal faults of cells occur in stages, and energy accumulation and sudden release are two key processes of cell's mechanical failure. The cells' state of charge is the main factor affecting their thermal runaway behaviors. In addition, a finite element model is developed to simulate the deformation features and the failure mechanism of key components of lithium-ion pouch cells; the 3D x-ray computed tomography is employed to demonstrate its internal configuration. With this model, the force-strain response, the deformation features as well as the size of the failure area of lithium-ion cells under spherical indentation conditions are accurately predicted. In 3D x-ray computed tomography images, unique mud cracks in cooper current collector are observed, and the influence mechanisms of the isolated fragments on the cell capacities are revealed. These results may provide useful information for the mechanical structure design of the components of lithium-ion pouch cells.

25 ENERGY STORAGE↗