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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Energy based fracture initiation criterion for strain-crystallizing rubber-like materials with pre-existing cracks

Fracture prediction is indispensable for polymers, like rubbers, which have a broad range of applications mainly due to their high extensibility. The phenomenon known as strain-induced crystallization further contributes to the fracture toughness of certain rubbers. Here in this study, a criterion based on internal bond energy, incorporating the effects of crystallization, is proposed to predict fracture initiation in rubber-like materials with pre-existing cracks. First, a multi-scale mechanical model is developed for characterizing the behavior of rubber when subjected to both uniaxial and biaxial deformation states. At the microscale, both the amorphous and crystalline chain segments are modeled as elastic in order to consider the energy contribution by the molecular bond distortions. This internal energy is considered along with the entropic and crystalline free energy for each chain. In the chain model, the effects of loading condition and the relative orientation of a chain on its crystallinity are taken into account. At the macroscopic scale, an existing crystallinity distribution function is adapted and a mixed finite element formulation with an augmented Lagrangian multiplier is utilized to impose the incompressibility constraint. A non-affine maximal advance path constraint based homogenization model is utilized for bridging the two scales. Its potential to account for anisotropy in the stretched network compels the model to be preferable due to its physical significance, for the purpose of fracture modeling. The rigidity of the crystallites is accounted for by proposing a crystallite distortion energy in addition to the critical bond dissociation energy, for fracture initiation to occur. The model is validated by comparison with existing experimental results for both crystallizing and non-crystallizing rubbers. In addition to its potential to predict the material behavior when subjected to uniaxial and biaxial loading, the capability of the model to quantitatively estimate the effect of crystallization on fracture initiation is also verified.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A biradical-tagged phospholipid as a polarizing agent for solid-state MAS Dynamic Nuclear Polarization NMR of membrane proteins

We report a novel Dynamic Nuclear Polarization (DNP) NMR polarizing agent ToSMTSL-PTE representing a phospholipid with a biradical TOTAPOL tethered to the polar head group has been synthesized, characterized, and employed to enhance solid-state Nuclear Magnetic Resonance (SSNMR) signal of a lipid-reconstituted integral membrane protein proteorhodopsin (PR). A matrix-free PR formulation for DNP improved the absolute sensitivity of NMR signal by a factor of ca. 4 compared to a conventional preparation with TOTAPOL dispersed in a glassy glycerol/water matrix. DNP enhancements measured at 400 MHz/263 GHz and 600 MHz/395 GHz showed a strong field dependence but remained moderate at both fields, and comparable to those obtained for PR covalently modified with ToSMTSL. Additional continuous wave (CW) X-band electron paramagnetic resonance (EPR) experiments with ToSMTSL-PTE in solutions and in lipid bilayers revealed that an unfavorable conformational change of the linker connecting mononitroxides could be one of the reasons for moderate DNP enhancements. Further, differential scanning calorimetry (DSC) and CW EPR experiments indicated an inhomogeneous distribution and/or a possibility of a partial aggregation of ToSMTSL-PTE in DMPC:DMPA bilayers when the concentration of the polarizing agent was increased to 20 mol% to maximize the DNP enhancement. Thus, conformational changes and an inhomogeneous distribution of the lipid-based biradicals in lipid bilayers emerged as important factors to consider for further development of this matrix-free approach for DNP of membrane proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Exploring the Relationship of Microstructure and Conductivity in Metal Halide Perovskites via Active Learning-Driven Automated Scanning Probe Microscopy

Electronic transport and hysteresis in metal halide perovskites (MHPs) are key to the applications in photovoltaics, light emitting devices, and light and chemical sensors. These phenomena are strongly affected by the materials microstructure including grain boundaries, ferroic domain walls, and secondary phase inclusions. Here, we demonstrate an active machine learning framework for “driving” an automated scanning probe microscope (SPM) to discover the microstructures responsible for specific aspects of transport behavior in MHPs. In our setup, the microscope can discover the microstructural elements that maximize the onset of conduction, hysteresis, or any other characteristic that can be derived from a set of current–voltage spectra. Furthermore, this approach opens new opportunities for exploring the origins of materials functionality in complex materials by SPM and can be integrated with other characterization techniques either before (prior knowledge) or after (identification of locations of interest for detail studies) functional probing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Orientation and Stability of Asymmetric Magnetic Reconnection X Line

Here, the orientation and stability of the reconnection x line in asymmetric geometry is studied using three-dimensional (3-D) particle-in-cell simulations. We initiate reconnection at the center of a large simulation domain to minimize the boundary effect. The resulting x line has sufficient freedom to develop along an optimal orientation, and it remains laminar. Companion 2-D simulations indicate that this x line orientation maximizes the reconnection rate. The divergence of the nongyrotropic pressure tensor breaks the frozen-in condition, consistent with its 2-D counterpart. We then design 3-D simulations with one dimension being short to fix the x line orientation but long enough to allow the growth of the fastest growing oblique tearing modes. This numerical experiment suggests that reconnection tends to radiate secondary oblique tearing modes if it is externally (globally) forced to proceed along an orientation not favored by the local physics. Finally, the development of oblique structure easily leads to turbulence inside small periodic systems.

3-D magnetic reconnection↗
DOE OSTI2020

Exploration of lattice Hamiltonians for functional and structural discovery via Gaussian process-based exploration–exploitation

Statistical physics models ranging from simple lattice to complex quantum Hamiltonians are one of the mainstays of modern physics that have allowed both decades of scientific discovery and provided a universal framework to understand a broad range of phenomena from alloying to frustrated and phase separated materials to quantum systems. Traditionally, exploration of the phase diagrams corresponding to multidimensional parameter spaces of Hamiltonians was performed using a combination of basic physical principles, analytical approximations, and extensive numerical modeling. However, exploration of complex multidimensional parameter spaces is subject to the classic dimensionality problem, and the behaviors of interest concentrated on low dimensional manifolds remain undiscovered. Here, we demonstrate that a combination of exploration and exploration–exploitation with Gaussian process modeling and Bayesian optimization allows effective exploration of the parameter space for lattice Hamiltonians and effectively maps the regions at which specific macroscopic functionalities or local structures are maximized. We argue that this approach is general and can be further extended well beyond the lattice Hamiltonians to effectively explore the parameter space of more complex off-lattice and dynamic models.

42 ENGINEERING↗
DOE OSTI2023

Improved microwave SQUID multiplexer readout using a kinetic-inductance traveling-wave parametric amplifier

We report on the use of a kinetic-inductance traveling-wave parametric amplifier (KITWPA) as the first amplifier in the readout chain of a microwave superconducting quantum interference device (SQUID) multiplexer (μmux). This μmux is designed to multiplex signals from arrays of low temperature detectors, such as superconducting transition-edge sensor microcalorimeters. When modulated with a periodic flux-ramp to linearize the SQUID response, the flux noise improves, on average, from 1.6 μ $\Phi$ 0 /$\sqrt{Hz}$ with the KITWPA off to 0.77 μ $\Phi$ 0 /$\sqrt{Hz}$ with the KITWPA on. When statically biasing the μmux to the maximally flux-sensitive point, the flux noise drops from 0.45 μ $\Phi$ 0 /$\sqrt{Hz}$ to 0.2 μ $\Phi$ 0 /$\sqrt{Hz}$⁠. We validate this new readout scheme by coupling a transition-edge sensor microcalorimeter to the μmux and detecting background radiation. In conclusion, the combination of μmux and KITWPA provides a variety of new capabilities including improved detector sensitivity and more efficient bandwidth utilization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Dielectric performance of high permitivity nanocomposites: impact of polystyrene grafting on BaTiO 3 and TiO 2

Polymer nanocomposites are a promising concept to improve energy storage density of capacitors, but realizing their hypothetical gains has proved challenging. The introduction of high permittivity fillers often leads to reduction in breakdown strength due to field exclusion, which intensifies the applied electric field within the polymer matrix near nanoparticle interfaces. This has prompted research in developing new nanoparticle functionalization chemistries and processing concepts to maximize particle separation. Herein, we compare the dielectric performance of blended nanocomposites to matrix free assemblies of hairy (polymer-grafted) nanoparticles (HNPs) that exhibit comparable overall morphology. The dielectric breakdown strength of polystyrene-grafted BaTiO3 (PS@BaTiO3) systems was over 40% greater than a blended nanocomposite with similar loading (~25% v/v BaTiO3). Hairy nanoparticles with TiO2 cores followed similar trends in breakdown strength as a function of inorganic loading up to 40% v/v. Dielectric loss for PS@BaTiO3 HNPs was 2-5 times lower than analogous blended films for a wide frequency spectrum (1 Hz to 100 kHz). For BaTiO3 content above 7% v/v, grafting the polymer chains to the nanoparticle significantly improved energy storage density and efficiency, likely due to the polymer canopy mitigating interfacial transport and restricting particle-particle hot-spots by establishing a finite minimum particle separation.

25 ENERGY STORAGE↗
DOE OSTI2026

Cohort organized learning: clustering through agreement

In this article we describe cohort organized learning (CoOL), a method for clustering data without explicit distance or similarity computations. Herein, we will describe CoOL, derive the gradients determined by expectation maximization to train the networks, show how to monitor convergence during training and evaluate the clusters after training, and discuss a series of examples and use cases. We also discuss CoOL’s limitations and future prospects on related tasks. Because CoOL uses neural networks to estimate the clusters, it can be used to cluster any data that can be made compatible and we illustrate this on vector data and images.

clustering↗
DOE OSTI2018

Multi-Timescale Three-Phase Unbalanced Distribution System Operation With Variable Renewable Generations

This paper proposes a multi-timescale operational approach for a three-phase unbalanced distribution system, which contains hourly scheduling at substation level and minutes power flow operation at feeder level. In the substation scheduling model, the objective is to minimize the system cost with variable renewable generations. The given error distribution model of renewable generation is formulated as a chance constraint, and derived into a deterministic form by Gaussian mixture model (GMM) with genetic algorithm-based expectation-maximization (GAEM). In the feeder scheduling model, the system cost is further reduced with the optimal power flow (OPF) at a timescale of minutes. Considering the nonconvexity of the three-phase unbalanced OPF problem in distribution systems, the semidefinite programming (SDP) is used to relax the problem into a convex problem, and a distributed computation approach is built based on alternating direction method of multiplier (ADMM). The IEEE 123-bus distribution system, DU (University of Denver) campus distribution system, and the IEEE 8500-bus distribution system are used as the test bench for the proposed approach. And the numerical results demonstrate the effectiveness and validity of the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Multi-Objective Bayesian Optimized Human Assessed Multi-Target Generated Spectral Recommender System for Rapid Pareto Discoveries of Material Properties

Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.

Biswas, Arpan↗
DOE OSTI2021

Measurement of the Higgs boson production rate in association with top quarks in final states with electrons, muons, and hadronically decaying tau leptons at $\sqrt{s} =$ 13 TeV

The rate for Higgs (${\mathrm{H}} $) bosons production in association with either one (${\mathrm{t}} {\mathrm{H}} $) or two (${\mathrm{t}} {{\overline{{{\mathrm{t}}}}}} {\mathrm{H}} $) top quarks is measured in final states containing multiple electrons, muons, or tau leptons decaying to hadrons and a neutrino, using proton–proton collisions recorded at a center-of-mass energy of $13\,\text {Te}\text {V} $ by the CMS experiment. The analyzed data correspond to an integrated luminosity of 137$\,\text {fb}^{-1}$. The analysis is aimed at events that contain ${\mathrm{H}} \rightarrow {\mathrm{W}} {\mathrm{W}} $, ${\mathrm{H}} \rightarrow {\tau } {\tau } $, or ${\mathrm{H}} \rightarrow {\mathrm{Z}} {\mathrm{Z}} $ decays and each of the top quark(s) decays either to lepton+jets or all-jet channels. Sensitivity to signal is maximized by including ten signatures in the analysis, depending on the lepton multiplicity. The separation among ${\mathrm{t}} {\mathrm{H}} $, ${\mathrm{t}} {{\overline{{{\mathrm{t}}}}}} {\mathrm{H}} $, and the backgrounds is enhanced through machine-learning techniques and matrix-element methods. The measured production rates for the ${\mathrm{t}} {{\overline{{{\mathrm{t}}}}}} {\mathrm{H}} $ and ${\mathrm{t}} {\mathrm{H}} $ signals correspond to $0.92 \pm 0.19\,\text {(stat)} ^{+0.17}_{-0.13}\,\text {(syst)} $ and $5.7 \pm 2.7\,\text {(stat)} \pm 3.0\,\text {(syst)} $ of their respective standard model (SM) expectations. The corresponding observed (expected) significance amounts to 4.7 (5.2) standard deviations for ${\mathrm{t}} {{\overline{{{\mathrm{t}}}}}} {\mathrm{H}} $, and to 1.4 (0.3) for ${\mathrm{t}} {\mathrm{H}} $ production. Assuming that the Higgs boson coupling to the tau lepton is equal in strength to its expectation in the SM, the coupling $y_{{\mathrm{t}}}$ of the Higgs boson to the top quark divided by its SM expectation, $\kappa _{{\mathrm{t}}}=y_{{\mathrm{t}}}/y_{{\mathrm{t}}}^{\mathrm {SM}}$, is constrained to be within $-0.9< \kappa _{{\mathrm{t}}}< -0.7$ or $0.7< \kappa _{{\mathrm{t}}}< 1.1$, at 95% confidence level. This result is the most sensitive measurement of the ${\mathrm{t}} {{\overline{{{\mathrm{t}}}}}} {\mathrm{H}} $ production rate to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

TEAMER: MADWEC Techno-Economic Analysis

The objective of this project was for the facility to conduct a techno-economic assessment (TEA) of the Maximal Asymmetric Drag Wave Energy Converter (MADWEC), developed by the University of Massachusetts Dartmouth (UMass Dartmouth). MADWEC is used for powering remote monitoring and Autonomous Underwater Vehicle (AUV) charging systems compared to other existing power supply options. The assessment estimates capital expenditures (CapEx), operational expenditures (OpEx), and power performance for 18 scenarios with the purpose of identifying key cost drivers, comparing total system cost, and comparing the power performance of the power supply options in terms of required installed capacity and estimated theoretical annual energy performance. The 18 assessed scenarios include two end-uses: 1) AUV charging and 2) offshore remote monitoring); three power sources: 1) MADWEC), 2) photovoltaic (PV) solar buoy, 3) and traditional battery swapping); and three locations; 1) nearshore, 2) far-offshore, and 3) high-latitude). In addition, other project goals included developing high level installation, operation, and maintenance plans for each scenario. The techno-economic model, created in Microsoft Excel, estimates CapEx, OpEx, and the power performance of each power supply source. The model has a dynamic format that allows custom inputs to accommodate future changes to the systems being assessed. This is a TEA for the MADWEC project, TEAMER RFTS 7 (request for technical support) program.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Telematics Framework for Federal Agencies: Lessons from the Marine Corps Fleet

Executive Order 13693 requires federal agencies to acquire telematics for their light- and medium-duty vehicles as appropriate. This report is intended to help agencies that are deploying telematics systems and seeking to integrate them into their fleet management process. It provides an overview of telematics capabilities, lessons learned from the deployment of telematics in the Marine Corps fleet, and recommendations for federal fleet managers to maximize value from telematics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Aeroelastic Modelling of Large Wind Turbines: Towards a Unified OpenFAST-SEAHOWL Approach

In recent years, the scale of wind turbines has significantly increased to maximize energy capture for a given site (particularly offshore), presenting new challenges in terms of structural design and dynamics. As towers grow taller and blades grow longer, flexion and torsion of the latter have a non-negligible impact on the behavior and performance of the turbine in terms of overall loads, power production, and control. When representing large-scale wind turbines numerically to capture these important effects, particular attention must therefore be given to the level of fidelity for representing each structural component, as well as the coupling scheme used between them to keep simulations accurate, stable, and efficient. To address this issue, we combine here the two following tools: (1) OpenFAST, the reference whole-turbine simulation tool from NREL with standalone modules covering each physics and the choice between loose coupling and a new tight coupling scheme for structural dynamics, and (2) SEAHOWL, the whole-turbine simulation tool from TotalEnergies with monolithic coupling of structural dynamics through Project Chrono and partitioned coupling for multiphysics interactions.

17 WIND ENERGY↗
DOE OSTI2026

Solar-Tracker Diffuse-Response Algorithm for Balancing Energy Gain and Mechanical Wear in Photovoltaic Systems

Single-axis solar tracking maximizes photovoltaic energy production under clear-sky conditions; however, its effectiveness decreases under cloudy and overcast skies, where diffuse irradiance dominates and the optimal module orientation changes. Conventional tracking algorithms either neglect sky conditions or rely on simplified diffuse-response strategies that may trigger frequent tracker repositioning under variable cloud cover, leading to increased mechanical wear with marginal energy gains. This work proposes an enhanced diffuse-response tracking algorithm that explicitly accounts for both the intensity and temporal persistence of cloudiness. By requiring overcast conditions to persist for a minimum duration before reorienting the tracker to a diffuse-stow position, the proposed approach reduces unnecessary movements while preserving the benefits of diffuse-response operation. The algorithm is evaluated through numerical simulations based on historical meteorological data and validated using field measurements on monofacial and bifacial photovoltaic strings. The results show that the proposed strategy reduces excess tracker movement from 114% to 0.16% while maintaining nearly the same energy yield. Compared to a conventional diffuse-response algorithm, the associated energy reduction is minimal (≈0.17%) relative to the ≈0.37% yield gain observed at the studied location. These findings demonstrate that incorporating cloudiness duration enables a practical compromise between energy performance and tracker durability, particularly for monofacial photovoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2019

GPR Imaging for Deeply Buried Objects: A Comparative Study Based on Compositing of Scanning Frequencies and a Chirp Excitation Function

Compositing of ground penetrating radar (GPR) scans of differing frequencies have been found to produce cleaner images at depth using the Gaussian mixture model (GMM) feature of the expectation-maximization (EM) algorithm. GPR scans at various heights (“Stand Off”), as well as ground-based scans, have been studied. In this paper, we compare the GPR response from a chirp excitation function-based radar with the response from the EM GMM algorithm compositing process, using the same mix of frequencies. A chirp excitation pulse was found to be effective in delineating the defined buried object, but the resulting image is less sharp than the GMM EM method.

58 GEOSCIENCES↗
NASA NTRS2017

The CHARIS High-Contrast Integral-Field Spectrograph

One of the leading direct Imaging techniques, particularly in ground-based imaging, uses a coronagraphic system and integral field spectrograph (IFS). The Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) is an IFS that has been built for the Subaru telescope. CHARIS has been delivered to the observatory and now sits behind the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system. CHARIS has 'high' and 'low' resolution operating modes. The "high-resolution" mode is used to characterize targets in J, H, and K bands at ~R70. The "low-resolution" prism is meant for discovery and spans J+H+K bands (1.15-2.37 microns) with a spectral resolution of ~R18. This discovery mode has already proven better than 15-sigma detections of HR8799c,d,e when combining ADI+SDI. Using SDI alone, planets c and d have been detected in a single 24 second image. The CHARIS team is optimizing instrument performance and refining ADI+SDI recombination to maximize our contrast detection limit. In addition to the new observing modes, CHARIS has demonstrated a design with high robustness to spectral crosstalk. CHARIS is in the final stages of commissioning, with the instrument open for science observations beginning February 2017. Here we review the science case, design, on-sky performance, engineering observations of exoplanet and disk targets, and specific lessons learned for extremely high contrast imagers. Key design aspects that will be demonstrated are crosstalk optimization, wavefront correction using the IFS image, lenslet tolerancing, the required spectral resolution to fit exoplanet atmospheres, and the utility of the spectrum in achieving higher contrast detection limits.

Groff, Tyler D.↗