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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Discovering Blind Geothermal Systems in the Great Basin Region: An Integrated Geologic and Geophysical Approach for Establishing Geothermal Play Fairways: All Phases

Most geothermal resources in the Great Basin region of the western USA are blind, and thus the discovery of new commercial-grade systems requires synthesis of favorable characteristics for geothermal activity. The geothermal play fairway concept involves integration of multiple parameters indicative of geothermal activity to identify promising areas for new development. This project integrated multiple datasets to apply the play fairway concept and assess geothermal potential in a large region of the Great Basin in Nevada. It is therefore referred to as the Nevada play fairway project. This project was a strong collaborative effort between several organizations, led by the Nevada Bureau of Mines and Geology at the University of Nevada, Reno, but with key support from the U.S. Geological Survey, ATLAS Geosciences, Inc,, Hi-Q Geophysical, Inc., Lawrence Berkeley National Laboratory, Utah Geological Survey, and Innovative Geothermal Ltd. In Budget Period 1 of this project, available data for nine geologic, geochemical, and geophysical parameters were initially synthesized to produce a new detailed geothermal potential map of 96,000 km2 from west-central to eastern Nevada. These parameters were grouped into subsets and individually weighted to delineate rankings for local permeability, intermediate permeability, regional permeability, and thermal potential, which collectively defined geothermal play fairways (i.e., most likely locations for significant geothermal fluid flow). This initial work was aimed at reducing the risks in regional exploration and therefore facilitating discovery of new commercial-grade systems in blind settings, as well as in areas with surface expressions of geothermal activity. Budget Period 2 of the project involved detailed analysis of some of the most promising areas identified in Phase 1. Twenty-four highly prospective areas, including both known undeveloped systems and previously undiscovered potential blind systems, were identified for further analysis. After reconnaissance of these areas, five of the most promising sites were selected for detailed studies. Multiple techniques were employed in the detailed studies, including geologic mapping, shallow temperature surveys, gravity surveys, Lidar, geochemical studies, seismic reflection analysis, and 3D modeling. The goal of the detailed studies was to identify specific areas with the highest likelihood for high permeability and thermal fluids, such that drill sites could be targeted. Three main sets of predictive maps were generated for each detailed study area: 1) play fairway maps, 2) play fairway error maps, and 3) direct evidence maps. Local- and intermediate-scale permeability models were revised to reflect results of the detailed geologic, geophysical, and geochemical analyses. Budget Period 3 of the project involved more detailed geophysical analyses and temperature-gradient (TG) drilling in southeastern Gabbs Valley and northern Granite Springs Valley, deemed the two most promising sites, with the goal of providing preliminary validation of the play fairway methodology. In southeastern Gabbs Valley, the collocation of a favorable structural setting (displacement transfer zone and fault intersections), Quaternary faults, intersecting and terminating gravity gradients, magnetic low, shallow (2 m) temperature anomaly, low resistivity anomaly, and promising geothermometry from nearby water wells provided evidence for a blind system. Drilling of six TG holes defines an apparent geothermal system at this locality with temperatures as high as 124°C at 152 m. This system is blind, with no surface hot springs, fumaroles, or paleo-geothermal deposits. For northern Granite Springs Valley, a favorable structural setting (termination of a major Quaternary normal fault), terminating gravity gradient, magnetic gradient, newly discovered sinter deposits, nearby warm water wells, previously drilled TG holes in the vicinity, and promising geothermometry suggest a hidden system. Drilling of six new TG holes yields temperatures of ~96°C at ~250 m, suggesting the presence of a geothermal system. Major lessons learned in the course of this project include: 1) initially identified sites commonly include multiple favorable structural settings at a finer scale; 2) promising sites in Cenozoic basins cannot be recognized without detailed geophysical surveys; and 3) play fairway analysis should be refined as the exploration program vectors into the most promising sites and finer-scale data are acquired. In addition to producing copious amounts of data, this project resulted in 16 published papers, 10 abstracts, more than 40 presentations across the U.S. and abroad (including several keynote addresses), 2 Masters theses, and 7 media reports.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Optimization of a traveling wave superconducting radiofrequency cavity for upgrading the International Linear Collider

The standing wave TESLA niobium-based superconducting radio frequency structure is limited to an accelerating gradient of about 50 MV/m by the critical rf magnetic field. To break through this barrier, we explore the option of niobium-based traveling wave (TW) structures. Optimization of TW structures was done considering experimentally known limiting electric and magnetic fields. It is shown that a TW structure can have an accelerating gradient above 70 MeV/m that is about 1.5 times higher than contemporary standing wave structures with the same critical magnetic field. The other benefit of TW structures shown is R/Q about 2 times higher than the TESLA structure that reduces the dynamic heat load by a factor of 2. A method is proposed how to make TW structures multipactor-free. Some design proposals are offered to facilitate fabrication. Further increase of the real-estate gradient (equivalent to 80 MV/m active gradient) is also possible by increasing the length of the accelerating structure because of higher group velocity and cell-to-cell coupling. Realization of this work opens paths to International Linear Collider energy upgrades beyond 1 to 3 TeV in competition with CLIC. The paper will discuss corresponding opportunities and challenges.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

AGR-3/4 TRISO Fuel Compact Ceramography

The combined third and fourth irradiation in the Advanced Gas Reactor (AGR) program (AGR-3/4) contained tristructural isotropic (TRISO)-coated particle fuel and designed-to-fail (DTF) fuel particles. The DTF particles were only coated with highly anisotropic pyrocarbon (PyC) so they would purposely fail during the AGR-3/4 irradiation and provide a source of fission products for measurement. To observe the post-irradiation morphology of these DTF particles and the TRISO-coated particles, three AGR-3/4 compacts were mounted in epoxy, sectioned above their centerlines, and ground/polished. Three rounds of grinding/polishing and optical microscopy were performed so that the particles could be observed at multiple planes. Each compact contained approximately 1,872 TRISO particles and exactly 20 DTF particles. The three AGR-3/4 compacts examined covered a wide temperature range and featured both the hottest average irradiation temperature (1375°C) and the coldest/lowest burnup (872°C and 5.5% fissions per initial metal atom) of any compacts to undergo post-irradiation examination (PIE) in the AGR program to date. A total of 29 DTF particles were located and observed via microscopy across the three compacts. All the DTF particles observed via microscopy had completely failed PyC coatings. Some different DTF kernel and PyC morphologies were observed that have been attributed to the differences in irradiation temperature and/or burnup. At low and medium irradiation temperatures (roughly 850 to 1050°C), it appears irradiation-induced dimensional changes in the DTF PyC caused it to fracture and fold in on itself, and the kernel deformed to accommodate this PyC deformation. The extent of DTF kernel deformation to accommodate DTF PyC buckling tended to be greater for the medium-temperature fuel compared to the cold fuel. In the high-irradiation-temperature compact (1375°C), the DTF PyC layer appears to have completely reacted chemically with the kernel material. The only material surrounding the DTF particles in this hot compact resembles the compact matrix material. Observations of the TRISO-coated driver fuel particles and fuel compact graphitic matrix were also made. The TRISO particle kernels in the medium-temperature compact (1047°C), and many in the high-temperature compact (1375°C), showed morphologies consistent with what was seen in AGR-1 and AGR-2. In other TRISO particles from the high-temperature compact, a spatial gradient in the kernel appearance was evident. Here the cool side of the kernel (away from the center of the compact) had a much darker appearance (like that of the buffer and pyrocarbon). This is the first observation of this kind of kernel spatial gradient in AGR fuel. It is believed that the high irradiation temperature of that compact (an average of 1375°C) activates or accelerates an unidentified chemical reaction, and the temperature gradient within the fuel causes a sharp spatial gradient. The low-temperature/low-burnup compact also showed unique kernel morphologies where the TRISO-coated particles had clearly distinguishable oxide and carbide phases at the center of the kernel, an oxide rind surrounding this, and remnants of a carbide skin surrounding the oxide rind. These are features observed in the as-fabricated fuel that are no longer present in higher burnup fuel. Occasional gaps between the outer pyrolytic carbon (OPyC) and graphitic matrix material were observed in all compacts. Gaps were most often found in the small, matrix-filled spaces between adjacent particles. Finally, buffer morphologies in AGR-3/4 TRISO particles were like those observed in AGR-1 and AGR-2, and the buffer fracture frequencies in AGR-3/4 and AGR-2 TRISO particles were plotted versus fast neutron fluence and irradiation temperature. In AGR-3/4 the buffer fracture rate was highest (23%) for an irradiation temperature of 1047°C and a fast fluence of 5.18E25 n/m 2 . Increasing the irradiation temperature to 1375°C reduced the buffer fracture rate to 14%. Reducing the irradiation temperature to 872°C and the fast fluence by a factor of 3 reduced the buffer fracture rate to 7%. The temperature and fluence dependencies observed for AGR-3/4 buffer fracture were consistent with those observed in AGR-2. Lower fluences and/or higher temperatures significantly reduced the buffer fracture frequencies. Lower buffer fracture frequencies were also observed at lower temperatures as long as the fluence was also significantly reduced. This is believed to be due to lower fluence resulting in less irradiation-induced dimensional change (shrinkage) of the buffer, and a higher temperature promoting enhanced creep relaxation of stresses within the buffer, leading to less buffer fracture.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Mo-100 Disk Structural Integrity Tests II

This report is a continuation of the work performed in the report, Mo-100 Disk Structural Integrity Tests I [1]. The NorthStar pressed and sintered 29 mm diameter, 0.5 mm thick Mo-100 disks will be subjected to large temperature gradients when in-beam during production. These large temperature gradients cause high stress and deformation within the disks that could prove detrimental to the target assembly’s cooling performance. Disk fracture is also a possibility that must be understood. Therefore, disk structural integrity tests were performed to understand the thermal induced behavior of these disks. In order to replicate the in-beam conditions, the Mo-100 disks were subjected to large temperature gradients using a 30kW induction heater and coil. A series of transient tests were conducted in a similar fashion as the previous work, as well as an attempt to create steady state conditions for more accurate temperature gradients. The transient thermal test setup and results are described in this report.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The Thermal Response of a Packed Bed Thermal Energy Storage System upon Saturated Steam Injection Using Distributed Temperature Sensing

The effectiveness of a thermal energy storage (TES) system is typically characterized with the help of thermal stratification or temperature gradients along the direction of heat injection, which is typically the flow direction of heat transfer fluid. The steepness of temperature gradients are a direct indicator of the effectiveness or efficiency of the heat storage or dispatch process. The temperature gradient evolution along the packed bed of ceramic particles upon saturated steam injection is presented in this work. Distributed temperature sensing based on optical frequency domain reflectometry was deployed in a packed bed of ceramic particles to capture the thermal front evolution in the axial direction. The physical processes accompanying steam injection in packed beds are complex due to phase change, transitioning two-phase flow, and changes in condensate accumulation. Therefore, the variation of thermal response of the TES system for various steam injection flow rates was experimentally studied using a high-resolution distributed temperature sensing system in a chemically inert alumina particle-packed bed. Distinct zones of different heat transfer modes were observed during the steam injection experiments. A distinct conduction zone, evident from diffuse thermal fronts, was observed at low flow rates, and these thermal gradients became sharper as the flow rate increased. The diffuse thermal fronts in the heat storage media suggest a low exergy efficiency of the TES system, as energy losses started initiating before a significant fraction of the bed was saturated with steam.

25 ENERGY STORAGE↗
DOE OSTI2022

WALLABY Pre-pilot Survey: The Effects of Tidal Interaction on Radial Distribution of Color in Galaxies of the Eridanus Supergroup

We study the tidal interaction of galaxies in the Eridanus supergroup, using H i data from the pre-pilot survey of the Widefield ASKAP L-band Legacy All-sky Blind surveY. We obtain optical photometric measurements and quantify the strength of tidal perturbation using a tidal parameter S sum . For low-mass galaxies of M * ≲ 10 9 M ⊙ , we find a dependence of decreasing H i to optical disk size ratio with increasing S sum , but no dependence of H i spectral line asymmetry with S sum . This is consistent with the behavior expected under tidal stripping. We confirm that the color profile shape and color gradient depend on the stellar mass, but there is an additional correlation of low-mass galaxies having their color gradients within 2R 50 increasing with higher S sum . For these low-mass galaxies, the dependence of color gradients on S sum is driven by the color becoming progressively redder in the inner disk when tidal perturbations are stronger. For high-mass galaxies, there is no dependence of color gradients on S sum , and we find a marginal reddening throughout the disks with increasing S sum . Our result highlights tidal interaction as an important environmental effect in producing the faint end of the star formation suppressed sequence in galaxy groups.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Effect of radial pressure corrugations and profile shearing on turbulence in Fusion plasmas

Microturbulence can produce stationary fine-scale radial corrugations on the plasma density and temperature gradients in magnetic confinement fusion devices. We show that these structures play a significant role in regulating turbulent transport. We focus on the pedestal, studying electron-temperature-gradient (ETG) mode destabilisation and saturation in the presence of radial corrugations on the electron temperature gradient that could result from microtearing turbulence. A linear dispersion relation is derived for a shearless slab case, which indicates that in the presence of a sinusoidal background corrugation, each ETG mode splits into three distinct eigenvalues, with one being the original, one being more unstable and one being less unstable. However, despite the presence of more unstable linear modes, nonlinear gyrokinetic simulations of ETG with corrugated background electron temperature show a reduction of fluxes. Our investigation reveals a radial variation of the phase velocity of the modes that is proportional to the diamagnetic drift velocity and the local pressure gradient. The associated profile shearing breaks the turbulent eddies apart, reducing the transport level. This profile shearing resulting from fine-scale pressure corrugations could be a ubiquitous turbulence saturation mechanism not just in Fusion plasmas, but in Astrophysics and other areas.

FOS: Physical sciences↗
DOE OSTI2023

The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences

Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time-evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find nonlinear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient, although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single-forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single-forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The nonlinear changes in ENSO SST variability found in many models demonstrate the importance of characterizing this time-dependent behavior, as it implies that ENSO impacts may vary dramatically throughout the 21st century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Experiments On A Conduction Cooled Superconducting Radio Frequency Cavity With Field Emission Cathode

To achieve Ampere-class electron beam accelerators the pulse delivery rate need to be much higher than the typical photo injector repetition rate of the order of a few kilohertz. We propose here an injector which can, in principle, generate electron bunches at the same rate as the operating RF frequency. A conduction-cooled superconducting radio frequency (SRF) cavity operating in the CW mode and housing a field emission element at its region of high axial electric field can be a viable method of generating high-repetition-rate electron bunches. In this paper, we report the development and experiments on a conduction-cooled Nb3Sn cavity with a niobium rod intended as a field emitter support. The initial experiments demonstrate 0.4 MV/m average accelerating gradient, which is equivalent of peak gradient of 3.2 MV/m. The measured RF cavity quality factor is 1.4 x 10$^8$ slightly above our goal. The achieved field gradient is limited by the relatively low input RF power and by the poor coupling between the external power supply and the RF cavity. With ideal coupling the field gradient can be as high as 0.6 MV/m still below our goal of about 1 MV/m.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Total-internal reflection elastic metasurfaces: design and application

An acoustic shield for protecting a vibrational sensitive device includes a first unit cell and a second unit cell. The first unit cell includes a first locally resonant unit. The first locally resonant unit controls a first phase gradient and the first unit cell includes a first surface. The second unit cell includes a second surface proximate to the first surface. The second unit cell includes a second locally resonant unit embedded along the second interface. The second locally resonant unit controls a second phase gradient. The first phase gradient is different from the second phase gradient. The first unit cell and the second unit cell comprise a super cell. The acoustic shield is configured such that a vibrational wave from a first side of the super cell to a second side of the super cell is substantially attenuated.

Walsh, Timothy↗
DOE OSTI2022

Estimation of the Surface Fluxes for Heat and Momentum in Unstable Conditions with Machine Learning and Similarity Approaches for the LAFE Data Set

Abstract Measurements of three flux towers operated during the land atmosphere feedback experiment (LAFE) are used to investigate relationships between surface fluxes and variables of the land–atmosphere system. We study these relations by means of two machine learning (ML) techniques: multilayer perceptrons (MLP) and extreme gradient boosting (XGB). We compare their flux derivation performance with Monin–Obukhov similarity theory (MOST) and a similarity relationship using the bulk Richardson number (BRN). The ML approaches outperform MOST and BRN. Best agreement with the observations is achieved for the friction velocity. For the sensible heat flux and even more so for the latent heat flux, MOST and BRN deviate from the observations while MLP and XGB yield more accurate predictions. Using MOST and BRN for latent heat flux, the root mean square errors (RMSE) are 107 Wm $$^{-2}$$ - 2 and 121 Wm $$^{-2}$$ - 2 , respectively, as well as the intercepts of the regression lines are $$\approx 110$$ ≈ 110 Wm $$^{-2}$$ - 2 . For the ML methods, the RMSEs reduce to 31 Wm $$^{-2}$$ - 2 for MLP and 33 Wm $$^{-2}$$ - 2 for XGB as well as the intercepts to just 4 Wm $$^{-2}$$ - 2 for MLP and $$-1$$ - 1 Wm $$^{-2}$$ - 2 for XGB with slopes of the regression lines close to 1, respectively. These results indicate significant deficiencies of MOST and BRN, particularly for the derivation of the latent heat flux. In fact, in contrast to the established theories, feature importance weighting demonstrates that the ML methods base their improved derivations on net radiation, the incoming and outgoing shortwave radiations, the air temperature gradient, and the available water contents, but not on the water vapor gradient. The results imply that further studies of surface fluxes and other turbulent variables with ML techniques provide great promise for deriving advanced flux parameterizations and their implementation in land–atmosphere system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Mode connectivity in the loss landscape of parameterized quantum circuits

Variational training of parameterized quantum circuits (PQCs) underpins many workflows employed on near-term noisy intermediate scale quantum (NISQ) devices. It is a hybrid quantum-classical approach that minimizes an associated cost function in order to train a parameterized ansatz. In this work we adapt the qualitative loss landscape characterization for neural networks introduced in Goodfellow et al. (2014); Li et al. (2017) and tests for connectivity used in Draxler et al. (2018) to study the loss landscape features in PQC training. We present results for PQCs trained on a simple regression task, using the bilayer circuit ansatz, which consists of alternating layers of parameterized rotation gates and entangling gates. Multiple circuits are trained with 3 different batch gradient optimizers: stochastic gradient descent, the quantum natural gradient, and Adam. We identify large features in the landscape that can lead to faster convergence in training workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Differentiating densities on smooth manifolds

Lebesgue integration of derivatives of strongly-oscillatory functions is a recurring challenge in computational science and engineering. Integration by parts is an effective remedy for huge computational costs associated with Monte Carlo integration schemes. In case of Lebesgue integrals over a smooth manifold, however, integration by parts gives rise to a derivative of the density implied by charts describing the domain manifold. This paper focuses on the computation of that derivative, which we call the density gradient function, on general smooth manifolds. We analytically derive formulas for the density gradient and present examples of manifolds determined by popular differential equation-driven systems. Furthermore, we highlight the significance of the density gradient by demonstrating a numerical example of Monte Carlo integration involving oscillatory integrands.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

When and why PINNs fail to train: A neural tangent kernel perspective

Physics-informed neural networks (PINNs) have lately received great attention thanks to their flexibility in tackling a wide range of forward and inverse problems involving partial differential equations. However, despite their noticeable empirical success, little is known about how such constrained neural networks behave during their training via gradient descent. More importantly, even less is known about why such models sometimes fail to train at all. Here in this work, we aim to investigate these questions through the lens of the Neural Tangent Kernel (NTK); a kernel that captures the behavior of fully-connected neural networks in the infinite width limit during training via gradient descent. Specifically, we derive the NTK of PINNs and prove that, under appropriate conditions, it converges to a deterministic kernel that stays constant during training in the infinite-width limit. This allows us to analyze the training dynamics of PINNs through the lens of their limiting NTK and find a remarkable discrepancy in the convergence rate of the different loss components contributing to the total training error. To address this fundamental pathology, we propose a novel gradient descent algorithm that utilizes the eigenvalues of the NTK to adaptively calibrate the convergence rate of the total training error. Finally, we perform a series of numerical experiments to verify the correctness of our theory and the practical effectiveness of the proposed algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Understanding improved cycling and thermal stability of compositionally graded Ni-rich layered LiNi 0.6 Mn 0.2 Co 0.2 O 2 cathode materials

The concentration gradient is a strategic design, adjusting the distribution of Ni, typically with a higher Ni content in the core and a higher Mn content toward the surface. This design leverages the pivotal role of the Ni/Mn ratio, seeking to optimize cathode performance by balancing Ni's high capacity with Mn's stabilizing effects, particularly at the surface where degradation commonly occurs during cycling. Here, our study delves into the intricate structural and chemical transformations within concentration gradient cathode materials during electrochemical cycling. Utilizing advanced synchrotron X-ray techniques, including hard and soft X-ray absorption spectroscopy (hXAS, sXAS), and nanoscale X-ray imaging, we investigate buried changes in concentration gradient LiNi 0.6 Mn 0.2 Co 0.2 O 2 (CG NMC622). Contrary to conventional assumptions, our findings challenge the notion that cycling stability relies solely on Mn stability. Unraveling the roles of Ni and Mn, we uncover how their individual and collective contributions impact the cathode's overall performance. This investigation transcends established paradigms, shedding light on the crucial mechanisms governing the enhanced cycling stability of Nirich layered cathode materials.

25 ENERGY STORAGE↗
DOE OSTI2022

What lies beneath: Vertical temperature heterogeneity in a Mediterranean woodland savanna

As the availability of satellite and airborne thermal infrared remote sensing (TIR-RS) data increases and their spatial, temporal, and spectral resolutions improve, researchers are finding diverse applications for TIR-RS measurements. TIR-RS is now commonly applied in regional- and continental-scale analyses, such as those focused on fire and surface energy balance. However, its application lags in plant physiology and ecology, for which a finer-scale understanding of plant canopy temperatures would be useful to elucidate plant water dynamics, for example. In particular, while methods to disaggregate TIR-RS pixels in horizontal space have advanced, possible vertical stratification of plant canopy temperature and its implications for understanding the correspondence between TIR-RS and finer-scale, field-based thermal measurements (e.g. made with a thermal camera) remain unexplored. Here, we use data from a thermal camera deployed concurrently with the recent ECOSTRESS mission to quantify vertical temperature gradients within tree canopies and temperatures of over- vs. under-story plants in a Mediterranean woodland savanna. We then leverage diverse ancillary data to maximize the geometric comparability of ECOSTRESS and thermal camera measurements, in order to assess the extent to which the two forms of thermal measurements correspond. Specifically, we ask: (1) What are the patterns of intra-canopy and over- vs. under-story vertical temperature in a Mediterranean woodland savanna?, and (2) How can vertically-resolved, but spatially-limited field-based temperature measurements be reconciled with spatially-extensive, but surface-only, temperature measurements of a space-borne remote sensor? Further, we found consistent patterns of vertical thermal heterogeneity both within tree canopies and between ecosystem over- and under-stories. The daytime difference between the top and bottom thirds of blue oak canopies was, on average, 0.48 ° C – and sometimes several times larger. Notably, canopy tops are cooler, likely associated with the under-story grass reaching daytime temperatures often exceeding over-story temperatures by 10° C. Given the consistency of the intra-canopy temperature gradients, we expected the ECOSTRESS sensor would be in better agreement with camera measurements of canopy tops than bulk canopies or canopy bottoms. However, within-canopy gradients were overwhelmed by other sources of disagreement between the measurements, in part associated with upscaling camera measurements across space. Overall, thermal camera and ECOSTRESS measurements were largely in agreement at night (pixel RMSE = 1.1°C), but they were more divergent during times of low (but >0 W/m2) and high incoming solar radiation (daytime pixel RMSE = 3.5°C).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Formulation and solution approach for calibrating activity-based travel demand model-system via microsimulation

This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Lastly, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.

97 MATHEMATICS AND COMPUTING↗