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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dark and bright modes, and their coherent control in dipolar metasurface bilayers

Several plasmonic nanoparticles supporting dipolar resonances can couple to form normal modes. Here, we develop an analytical model to explain the formation of nonradiative “dark” and radiative “bright” modes through radiative coupling in bilayers consisting of dipolar nanoantenna arrays that are separated by a subwavelength distance. We also include near-field contributions in our model and show that the absorption and reflectance spectra obtained from our model agree reasonably well with the respective finite-difference time-domain simulation results for both perfectly aligned and misaligned bilayers. Here, the ability to vary the reflection and absorption spectra of these bilayers by changing the material and geometrical parameters has potential applications in the design of efficient spectral filters. We also show that we can selectively excite these modes by adjusting the phase between two counterpropagating normally incident fields, which has applications in all-optical modulators and switches based on purely linear interferometric effects.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Flashback Studies of High-Hydrogen Flames using High-Speed OH Planar Laser-Induced Fluorescence

Flame flashback is a crucial challenge during the application of high-hydrogen fuels for the development of next-generation lean premixed combustors. The fundamentals of stable flame configuration, flashback phenomena, and spatiotemporal information of flame dynamics in a premixed, swirl-stabilized burner are investigated experimentally at atmospheric pressure conditions using high-repetition-rate nanosecond (ns)-duration hydroxyl radical planar laser-induced fluorescence (OH-PLIF) measurements. The inlet conditions are varied systematically with respect to equivalence ratio (ϕ), hydrogen percentage in a hydrogen-methane mixture (50%–90%) and pre-mixer velocities and the experiments are performed on the burner modified to provide optical access to the premixing section. Signal interferences such as saturation effects, background chemiluminescence, and laser non-uniformity issues were minimized or corrected during data acquisition and subsequent data processing steps. A stable flame characterization was performed at 20 kHz-repetition-rate for varied pre-mixer velocities, hydrogen content and ϕ in the reactant mixture and lift-off length (L) investigation showed dependence on each of these parameters. Flame dynamics such as flame flashback events, local ignition, local extinction, flame curvature as well as the main reaction zone of the combustion mechanism are well characterized. Flashback ϕ showed an expected linearly increasing trend with increasing pre-mixer velocity and decreasing hydrogen content and the conclusions drawn aligned well with detailed L investigation. Such spatially and temporally resolved kHz-rate OH-PLIF is a promising technique to observe rapidly occurring flashback dynamics and can further validate turbulence-chemistry interaction models of swirling flames.

Parajuli, Pradeep↗
DOE OSTI2025

Study of Quadrupole Fringe Fields in the Interaction Region of the Hadron Storage Ring of the Electron Ion Collider

Fringe fields in quadrupole magnets are usually neglected in studies of beam dynamics at accelerators. However, the extreme optical parameters present in the final focus of a collider such as the Electron–Ion Collider (EIC) may give rise to effects that should not be overlooked. The calculation of quadrupole fringe fields presented in this study follows the procedure outlined in Ref. [1], specialized to the case of a straight reference orbit (i.e., with no dipole field component). A right-handed Cartesian coordinate system is employed, with the $z$-axis aligned with the quadrupole axis and $x$ and $y$ denoting the horizontal and vertical transverse coordinates, respectively. The magnetic quadrupole field gradient, $G = \partial B_y / \partial x$, transitions from its peak value inside the quadrupole—where it is nearly independent of the longitudinal coordinate $z$—to zero at some distance beyond the magnet edge. Consequently, $G$ is treated as a function of $z$. The region over which this variation occurs is defined as the quadrupole fringe field region. The study begins with the development of a description of the magnetic field in the fringe region using a power-series expansion in the transverse coordinates $x$and $y$, consistent with the longitudinally varying gradient. A model for the $z$-dependence of the gradient is then proposed and adjusted to reproduce magnetic field data obtained from three-dimensional field calculations. To evaluate the impact of the fringe fields on beam dynamics, the corresponding vector potential is derived and incorporated into a Hamiltonian formulation of particle motion. The significance of the fringe fields is quantified by calculating the amplitude-dependent tune shift from the Hamiltonian. Using linear beam optics parameters of the Hadron Storage Ring (HSR) of the EIC, the tune shift due to the fringe fields of all quadrupole magnets in the IR-6 interaction region is evaluated. Finally, the resulting tune shifts are compared with those arising from other nonlinear field components present in the HSR.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

An experimental study of the existence regions and non-linear interactions of drift wave and Kelvin–Helmholtz instabilities in a linear magnetized plasma

Experimental observations of the intrinsic excitation and non-linear interactions of drift wave (DW) and Kelvin–Helmholtz (KH) instabilities in a linear magnetized plasma column are presented. The experiments are carried out in the inverse mirror plasma experimental device (IMPED)—a cylindrical, magnetized, linear plasma machine designed to study low-frequency waves and instabilities in plasma. A novel feature of IMPED is the ability to control plasma profiles, such as the density n(r)⁠, electron temperature T e (r)⁠, and plasma potential V p (r) by varying the ratio Rm of the magnetic field in the main chamber to that in the source chamber. At high values of Rm, higher-density gradient scale length promotes the drift wave (DW) instability while lower Rm value results in a higher radial electric field, inducing a sheared poloidal flow that enhances the dominance of the Kelvin–Helmholtz (KH) mode. The background and fluctuating plasma parameters are characterized using various configurations of multiple in situ electric probes at different spatial locations to quantify the local gradients that excite the low-frequency primary instabilities. Statistical, spectral, and bispectral analysis of the density and potential signals help identify these modes in terms of wave number, frequency, phase, and amplitude and also delineate the nature of their non-linear interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Empirical Model of Puncture Energy for Metals

The purpose of this work is to fit a previously developed empirical equation for puncture energy to simulation data. The conservative puncture energy equation could be used to expedite the process of performing calculations in the development of safety measures, avoiding the need to create complex finite element models for specific puncture scenarios. A total of 108 simulations are developed by varying coupon thickness, coupon material, probe shape, and probe diameter. The simulations are comprised of a low-velocity probe puncturing the coupons, from which the probe kinetic energy change is calculated. The empirical equation is fit to the dimensions, material properties, and energy results using a non-linear least-squares regression method within Python, which determines the two constant parameters for each fit. More statistically significant fit results are achieved by separating the data by probe shape and coupon material.

42 ENGINEERING↗
DOE OSTI2023

Gas–Liquid Chemical Reactions with Nanosecond Pulses: Role of Frequency and Pulse Delivery Modes

The effects of changes in the mode of delivery of nanosecond pulses in a gas-liquid plasma reactor on the formation of hydrogen peroxide, H 2 O 2 , and, as an indicator for ·OH radicals, the decoloration of methylene blue, MB, were determined for pulse delivery by a) increasing frequency with uniform pulses (5-50 kHz), b) variation of the time between bursts of pulses (burst period), c) changing the inner burst frequency (1 over the time between the pulses in the burst), and d) variation of number of pulses in a burst (N-cycles). H 2 O 2 peroxide formation was not affected by the method of pulse delivery in the range of parameters studied here and all data followed an approximately linear increase in H 2 O 2 production rate with discharge power. In contrast, the MB decoloration rate was affected by the burst modes. In terms of discharge power, the MB decoloration rate was highest for the uniform pulse mode; however, the linear trend in increase of MB decoloration with power when the burst period was varied, suggest that at higher power the burst mode may be more effective than the uniform pulsing. Consideration of the per pulse decoloration with energy per pulse and with number of pulses suggest that the burst mode can affect reactions differently from applying a uniform pulse.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

3D pattern formation of a protein–membrane suspension

Many essential cellular processes, including cell division and the establishment of cell polarity during embryogenesis, are regulated by pattern-forming proteins. These proteins often need to bind to a substrate, such as the cell membrane, onto which they interact and form two-dimensional (2D) patterns. It is unclear how the membrane’s continuity and dimensionality impact pattern formation. Here, we address this gap using the MinDE system, a prototypical example of pattern-forming membrane proteins. We show that when the lipid substrate is fragmented into submicrometer-sized diffusive liposomes, adenosine triphosphate-driven protein–protein interactions generate three-dimensional (3D) spatially extended patterns, despite the complete loss of membrane continuity. Remarkably, these 3D patterns emerge at scales four orders of magnitude larger than the individual liposomes. By systematically varying protein concentration, liposome size, and density, we observed and characterized a variety of 3D dynamical patterns not seen on continuous 2D membranes, including traveling waves, dynamical spirals, and a coexistence phase. Simulations and linear stability analysis of a coarse-grained model revealed that the physical properties of the dispersed membrane effectively rescale both the protein–membrane binding rates and diffusion, two key parameters governing pattern formation and wavelength selection. These findings highlight the robustness of Min’s pattern-forming ability, suggesting that protein–membrane suspensions could serve as an adaptable template for studying out-of-equilibrium self-organization in 3D, beyond in vivo contexts.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermodynamics of the Inner Heliosheath

We derive annual sky maps of the proton temperature in the inner heliosheath (IHS), and track their temporal evolution over the years 2009–2016 of Interstellar Boundary Explorer observations. Other associated thermodynamic parameters also determined are the density, kappa (the parameter that characterizes kappa distributions), temperature rate, polytropic index, and entropy. We exploit the theory of kappa distributions and their connection with polytropes, to (i) express a new polytropic quantity Π that remains invariant along streamlines where temperature and density may vary, (ii) parameterize the proton flux in terms of the Π invariant and kappa, and (iii) derive the temperature and density, respectively, from the slope and intercept of the linear relationship between kappa and logarithm of Π. We find the following thermodynamic characteristics: (1) temperature sky maps and histograms shifted to their lowest values in 2012 and their highest in 2015; (2) temperature negatively correlated with density, reflecting the subisothermal polytropic behavior; (3) temperature positively correlated with kappa, revealing characteristics of the mechanism responsible for generating kappa distributions; (4) processes in IHS are subisothermal tending toward isobaric, consistent with previously published results; (5) linear relationship between kappa and polytropic indices, revealing characteristics of the particle potential energy; and (6) entropy positively correlated with polytropic index, aligned with the underlying theory that entropy increases toward the isothermal state where the kappa distribution reduces to the Maxwell–Boltzmann description.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Development of an All-Aqueous Thermally Regenerative Redox Flow Battery to Support Fossil Fuel Assets

Low-temperature thermal energy, a largely untapped resource, holds significant promise for large-scale electrical power generation globally. Various stationary sources, including industrial entities and thermal power plants, emit considerable low-temperature heat that currently remains unutilized. This energy is often overlooked because its low temperature renders it unsuitable for efficient power generation using conventional methods. However, current research is exploring diverse technologies capable of converting low-temperature heat into grid-scale power, aiming to enhance grid efficiency, further decarbonization initiatives, and facilitate a shift toward more decentralized power systems. One such innovative technology is the thermally regenerative battery (TRB), noted for its high power and energy densities compared to similar technologies, positioning it as a potential game-changer in power generation. TRBs integrate two scalable and well-established unit operations: a redox flow battery and a distillation column. This integration suggests that once an effective TRB chemistry is established, the pathway to commercialization could be expedited. The copper-based thermally regenerative ammonia battery (Cu aq -TRAB) stands out as the first TRB that circumvents electrodeposition/dissolution reactions, stabilizing Cu(I) and Cu(II) within the electrolyte and maintaining stability of all electroactive species in an aqueous phase. This stabilization has led to improvements in coulombic efficiency, open circuit potential, and copper solubility, thereby enhancing power density, energy density, and overall energy efficiency. Preliminary tests were conducted to determine the effects of various electrolyte species on the performance metrics of the battery, both theoretically and experimentally. These tests revealed that the solubility of copper in the Cu aq -TRAB electrolyte was constrained by the Cu(I)-NH 3 complex. Adjusting the background electrolyte to 5 M NH4Br and the ligand concentration to 4 M NH 3 enabled the copper concentration to reach a maximum of 0.6 M. This modification led to an estimated theoretical maximum energy density of 9.5 Wh L -1 for the Cu aq -TRAB. Additionally, full cell testing indicated a tradeoff between peak power and energy density with varying copper and ammonia concentrations. Increasing the applied current density during discharge linearly raised the average power output, with a minimal reduction in energy density due to a balance between higher ohmic overpotential and reduced time for undesirable ammonia crossover. Furthermore, a comprehensive numerical sensitivity analysis of the complete Cu aq -TRAB system was performed. This analysis aimed to assess how the battery and the distillation column responded to changes in system input parameters, providing insights into optimal research directions for enhancing system performance. The analysis revealed that at room temperature, battery power was significantly more sensitive to ohmic losses than to mass transfer, with reaction rates having minimal impact. This trend continued even at higher temperatures. Also, the thermal energy required for ammonia separation was studied, showing that increased temperatures generally reduced energy requirements, except in low-pressure scenarios above 65 °C. An investigation into membrane performance in the Cu aq -TRAB was undertaken, given the significant impact of ammonia transport control and ohmic losses on system performance. Various membranes were evaluated to identify key performance metrics. Among the tested membranes, Selemion CMVN exhibited the highest performance, with a peak power density of 84 mW cm -2 and average values of 26 ± 6.8 mW cm -2 for power density and 2.9 Wh L -1 for energy density at an applied current density of 50 mA cm -2 . An economic assessment indicated a levelized cost of storage at $410 per MWh under optimal conditions, highlighting the commercial potential of the Cu aq -TRAB when utilizing cost-effective, readily available materials.

25 ENERGY STORAGE↗
DOE OSTI2020

MFNets: Multifidelity data-driven networks for Bayesian learning and prediction

This paper presents a multifidelity uncertainty quantification framework called MFNets. We seek to address three existing challenges that arise when experimental and simulation data from different sources are used to enhance statistical estimation and prediction with quantified uncertainty. Specifically, we demonstrate that MFNets can (1) fuse heterogeneous data sources arising from simulations with different parameterizations, e.g simulation models with different uncertain parameters or data sets collected under different environmental conditions; (2) encode known relationships among data sources to reduce data requirements; and (3) improve the robustness of existing multi-fidelity approaches to corrupted data. MFNets construct a network of latent variables (LVs) to facilitate the fusion of data from an ensemble of sources of varying credibility and cost. These LVs are posited as explanatory variables that provide the source of correlation in the observed data. Furthermore, MFNets provide a way to encode prior physical knowledge to enable efficient estimation of statistics and/or construction of surrogates via conditional independence relations on the LVs. We highlight the utility of our framework with a number of theoretical results which assess the quality of the posterior mean as a frequentist estimator and compare it to standard sampling approaches that use single fidelity, multilevel, and control variate Monte Carlo estimators. We also use the proposed framework to derive the Monte Carlo-based control variate estimator entirely from the use of Bayes rule and linear-Gaussian models -- to our knowledge the first such derivation. Finally, we demonstrate the ability to work with different uncertain parameters across different models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Scoping review of Culex mosquito life history trait heterogeneity in response to temperature

Abstract Background Mosquitoes in the genus Culex are primary vectors in the US for West Nile virus (WNV) and other arboviruses. Climatic drivers such as temperature have differential effects on species-specific changes in mosquito range, distribution, and abundance, posing challenges for population modeling, disease forecasting, and subsequent public health decisions. Understanding these differences in underlying biological dynamics is crucial in the face of climate change. Methods We collected empirical data on thermal response for immature development rate, egg viability, oviposition, survival to adulthood, and adult lifespan for Culex pipiens, Cx. quinquefasciatus, Cx. tarsalis , and Cx. restuans from existing literature according to the PRISMA scoping review guidelines. Results We observed linear relationships with temperature for development rate and lifespan, and nonlinear relationships for survival and egg viability, with underlying variation between species. Optimal ranges and critical minima and maxima also appeared varied. To illustrate how model output can change with experimental input data from individual Culex species, we applied a modified equation for temperature-dependent mosquito type reproduction number for endemic spread of WNV among mosquitoes and observed different effects. Conclusions Current models often input theoretical parameters estimated from a single vector species; we show the need to implement the real-world heterogeneity in thermal response between species and present a useful data resource for researchers working toward that goal. Graphical Abstract

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Peridynamic modeling of cementitious materials for nuclear waste management

Radioactive and hazardous waste generated from fuel processing plants, nuclear reactors, and hospitals, requires effective management strategies. Cementitious materials are widely applied for these needs, serving as structural materials, reactive barriers, or waste forms. In these applications cracking poses a significant risk to performance, driven by inconsistent shrinkage of the components and the varying strength and permeability of their interfaces. Traditional modeling approaches face challenges in representing the complex fracture behavior of cementitious materials due to the reliance on spatial derivatives and difficulties with mesh generation. Here, to overcome these limitations, we employ peridynamics, a novel continuum mechanics formulation that uses integrals to describe mechanical equilibrium, avoiding discontinuities associated with traditional methods. Through incorporation of a bi-linear softening model and quasistatics, an experimentally validated model for Portland cement concrete samples was created. Mechanical parameters, including compressive strength and elastic modulus were validated and variation due to aggregate packing was evaluated. Additionally, sensitivity analysis of the peridynamic parameters to the bulk material properties was established. The results lay the groundwork for evaluating the impact of unique conditions of cementitious waste forms that can be assessed to improve the reliability of waste management strategies.

Aggregates↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
DOE OSTI2024

Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems

Abstract We present an innovative approach called boosting Barlow Twins reduced order modeling (BBT‐ROM) to enhance the reliability of machine learning surrogate models for multiphase flow problems. BBT‐ROM builds upon Barlow Twins reduced order modeling that leverages self‐supervised learning to effectively handle linear and nonlinear manifolds by constructing well‐structured latent spaces of input parameters and output quantities. To address the challenge of high contrast data in multiphase flow problems due to injection wells and faults, we employ a boosting algorithm within BBT‐ROM. This algorithm sequentially trains a set of weak models (i.e., inaccurate models), improving prediction accuracy through ensemble learning. To evaluate the performance of BBT‐ROM, we conduct three three‐dimensional multiphase flow problems, including waterflooding and geologic carbon storage (GCS), with varying numbers of input parameter cases and model domain features. The results demonstrate that BBT‐ROM excels at predicting non‐wetting phase saturation (e.g., oil or saturation) and fluid pressure, with average relative errors ranging from 0.5% to 3%. Importantly, BBT‐ROM showcases robustness when faced with limited input parameter space during GCS testing.

58 GEOSCIENCES↗
DOE OSTI2023

Evaluation of Potential DAS Array Geometries for the Source Physics Experiment, Phase III

Distributed Acoustic Sensing (DAS) is a rapidly developing technology that can record acoustic wavefields at high sampling rates and with dense spatial spacing difficult to achieve with seismometers. However, the geophysical community has not fully explored DAS survey parameters to characterize the ideal array design. A better quantitative understanding of DAS array behavior prior to SPE Phase III acquisition can help improve the quality of the data recorded by guiding the DAS array design. Here we use array response functions as well as beamforming and backprojection results from forward modelling calculations to assess the performance of varying DAS array geometries to record regional and local sources. A seven-sided polygon DAS array demonstrated improved capabilities for recording regional sources over segmented linear arrays, with potential improvements in recording and locating local sources. These results help reveal DAS array performance as a function of geometry.

58 GEOSCIENCES↗
DOE OSTI2023

Optimization of Energy Storage System Economics and Controls by Incorporating Battery Degradation Costs in REopt

The use of stationary electrochemical energy storage systems utilizing lithium-ion batteries has increased rapidly as the production scale and price for lithium-ion batteries has decreased. These energy storage systems are crucial for maintaining grid resiliency, especially for grids operating with high penetration of renewable energy generation assets or for with a variety of distributed energy generation and storage systems. One challenging factor for the development of battery energy storage systems is estimating the proper sizing, in terms of both power and energy, that minimizes total costs over the lifetime of the systems; this calculation is difficult in simple cases, where a battery is costed independently, but is extremely challenging when building loads and electrical generation by photovoltaic resources are also considered. REopt is a techoeconomic optimization tool developed by NREL to address these challenges. Previously, battery degradation has been priced by simply assuming a 10-year replacement schedule for battery systems. However, this does not account for varying degradation trends observed across real-world batteries, or allow for batteries to be operated in a degradation-aware manner that optimizes battery dispatch based on operating costs. This work incorporates a battery life model into REopt. This battery life model is simple, so that it may be solvable within the constrains of a mixed-integer linear optimization problem, but is fit to accelerated aging data recorded in the lab. To achieve the best possible accuracy for lifetime estimates given these constraints, parameters for the battery life model in REopt are estimated by fitting 20-year simulations of battery life after identifying state-space battery degradation model from accelerated aging data. Comparisons of battery life predicted in REopt and from the state-space battery degradation model to ensure validity of lifetime estimates made by REopt. Battery life and cost is optimized by controlling three decision to minimize system life cost: battery sizing, daily state-of-charge, and daily energy-throughput. The cost of battery degradation as a function of these control variables is then estimated assuming two possible maintenance strategies: replacement, where the entire battery system is replaced if cell reach an end-of-life capacity threshold; and augmentation, which establishes a fund to pay for continual purchase of new batteries to maintain the initial energy capacity of the system. These two strategies offer conservative (for replacement) and optimistic (for augmentation) bounds for total system cost. The degradation cost incurred by these strategies is then used to control battery dispatch decisions, operating the battery in a degradation-aware manner that maximizes battery lifetime while also providing energy when favorable. Because the mixed-integer linear program has perfect foresight of future energy needs, batteries with degradation costs are always operated using 'just-in-time' charging, which is unrealistic, as no energy is left in the storage system to perform other energy services or to serve as emergency back-up power. To combat this, an inequality constraint on the average annual state-of-charge is imposed, and the sensitivity of system cost to average stored energy, e.g., the cost of system resiliency, can be quantified. Analysis of results has several conclusions, for instance, oversizing of battery storage systems is not a cost burden when battery storage is an optimal solution, as any additional battery capacity can simply be utilized to avoid costs of purchasing energy from a utility.

battery↗
DOE OSTI2024

Rapid Optimization of Total Variation with Applications in Imaging, Additive Manufacturing, and Qualification

Total Variation optimization penalizes the gradient of a control variable or state. While this work focuses on image processing in particular, it has also found applications in inverse problems and topology optimization. In image processing, the goal is to maintain faithfulness to the original image while denoising and/or deblurring. Additionally, bilevel optimization over the spatially varying regularization weights can illuminate interfaces such as damage regions and other anomalies. We will address two fundamental challenges with TV-optimization: (i) the typical slow convergence of existing TV-optimization methods, and (ii) the selection of spatially varying TV parameters to promote interface detection. Additionally, we will apply such techniques to image data collected in additive manufacturing. In said context, stochasticity in build events induces flaws in the manufactured piece, compromising the integrity of said part. There is a critical need for in-situ monitoring to spot anomalies once they form, and in this setting we apply our total variation and hyperparameter solvers. We will develop a customized algorithm based on for extreme-scale TV-optimization that achieves super-linear or quadratic-convergence, a critical property for real-time, image-by-image analysis. A worst-case outcome is a preprocessing step that enhances image quality in-situ, specifically for out-of-focus and noisy images.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Phase diagram of a bilayer superconductor under an in-plane magnetic field

We study a double layer superconductor in the presence of a parallel magnetic field Bby obtaining self-consistent solutions of the Bogoliubov-de Gennes equations, and also using the Pakrovsky- Talapov model for the free energy expressed in terms of the relative phase, namely the difference in the phases of the superconducting order parameters in the two layers. We find that with increasing B, a continuous transition occurs from the Bardeen-Cooper-Schrieffer (BCS) state, where the relative phase is constant, into a state which contains stripes of the BCS state separated by localized vortices in the relative phase. This state is predicted to manifest through oscillations in the amplitude of the superconducting gap and an alternating pattern of supercurrents. With increasing B, the BCS stripe state continuously evolves into the Fulde-Ferrell-Larkin-Ovchinnikov state with linearly varying relative phase and a constant gap amplitude. Furthermore, these predictions apply to superconductivity in bilayer transition-metal-dichalcogenide systems with Ising spin-orbit coupling, and ought to be testable in a recently studied experimental system.

2-dimensional systems↗