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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 1,675 records · Page 93

Real-Time Regional PV Spinning Reserve Estimator with AGC Look-Ahead Windows: Preprint

Curtailed PV generation is a zero-marginal cost spinning reserve that can be used for a number of active power control services. However, unlike the traditional spinning reserve providers, i.e., fossil-fueled generators, who have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate forecasts of the PV PHL are essential. A novel reference-control grouping based scaling method has been proposed by NREL to estimate the PV PHL in real-time. This work further enhances the methodology by: 1) improving the model accuracy through machine learning; 2) considering look-ahead windows introduced by the computation and communication latencies; 3) applying the method to regional spinning reserve estimation. A significant performance improvement, over 1.6% of estimation error reduction, has been observed based on real-world data collected by CAISO and PV plant operators.

potential high limit↗

Data-Driven State of Health Estimation for Second-Life Batteries Using Interpolated Synthetic Data and Feature Selection

Accurate estimation of the State of Health (SOH) for second-life batteries (SLBs) is crucial given their increasing use in energy storage applications. Precise SOH prediction is essential for safe operation and robust battery management systems. A major challenge is the limited availability of datasets for building reliable degradation models. To address this, synthetic data generation through linear interpolation is performed to extend the available data, making it more representative of real-world battery operating conditions. By analyzing feature correlation with SOH, the most relevant features are selected for the model. The proposed approach employs a convolutional neural network (CNN) model trained on this interpolated, feature-selected dataset, using time series data of voltage, temperature, and current over a cycle. By focusing on highly correlated features, the model achieves over 95% accuracy, with mean absolute error and root mean squared error up to 2.27% and 2.64%, respectively, in SOH estimation for two battery datasets tested. These results highlight the potential of combining synthetic data generation and feature selection to enhance SOH predictions, showcasing the superior performance of the proposed CNN model for both new batteries and SLBs.

feature selection↗

Charge Concentration Limits the Hydrogen Evolution Rate in Organic Nanoparticle Photocatalysts

Colloidal organic nanoparticles have proven to be a promising class of photocatalyst for performing the Hydrogen Evolution Reaction (HER) due to their dispersibility in aqueous environments, their strong absorption within the visible region, and the tunabilty of their component materials' redox potentials. Currently, there is little understanding of how charge generation and accumulation in organic semiconductors change when these materials are formed into nanoparticles that share a high interfacial area with water, nor is it known what mechanism limits the hydrogen evolution efficiency in recent reports on organic nanoparticle photocatalysts. Herein, we use Time-Resolved Microwave Conductivity to study aqueous-soluble organic nanoparticles and bulk thin films composed of various blend ratios of the non-fullerene acceptor EH-IDTBR and conjugated polymer PTB7-Th and examine the relationship between composition, interfacial surface area, charge carrier dynamics, and photocatalytic activity. We quantitatively measure the rate of Hydrogen Evolution Reaction by nanoparticles composed of various donor:acceptor blend ratio compositions and find that the most active blend ratio displays a Hydrogen Quantum Yield of 0.83% per photon. Moreover, we find that nanoparticle photocatalytic activity corresponds directly to charge generation, and that nanoparticles have 3x more long-lived accumulated charges relative to bulk samples of the same material composition. Here these results suggest that, under our current reaction conditions, with approximately 3x solar flux, catalytic activity by these nanoparticles is limited by the concentration of electrons and holes in operando and not a finite number of active surface cites or the catalytic rate at the interface. This provides a clear design goal for the next generation of efficient photocatalytic nanoparticles.

08 HYDROGEN↗

Explosive volcanism, shock metamorphism and the K-T boundary

The issue of whether shocked quartz can be produced by explosive volcanic events is important in understanding the origin of the K-T boundary constituents. Proponents of a volcanic origin for the shocked quartz at the K-T boundary cite the suggestion of Rice, that peak overpressures of 1000 kbars can be generated during explosive volcanic eruptions, and may have occurred during the May, 1980 eruption of Mt. St. Helens. Attention was previously drawn to the fact that peak overpressures during explosive eruptions are limited by the strength of the rock confining the magma chamber to less than 8 kbars even under ideal conditions. The proposed volcanic mechanisms for generating pressures sufficient to shock quartz are further examined. Theoretical arguments, field evidence and petrographic data are presented showing that explosive volcanic eruptions cannot generate shock metamorphic features of the kind seen in minerals at the K-T boundary.

Desilva, S. L.↗

Supercontinuum generation in oxide and semiconductor materials (InP, Si, GaN, GaAs, PbMoO 4 , YVO 4 , ZGP, TiO 2 , diamond) pumped by radiation of the Cr:ZnS fs-MOPA system

Ultrashort light sources in the middle-infrared range are highly beneficial for applications such as gas molecular spectroscopy, remote sensing, atmospheric science, medical treatments, and light–matter interaction studies. Ultrafast lasers utilizing chromium-doped ZnS/Se (Cr:ZnS/Se) have proven to be robust and stable solutions within this spectral region. Nonlinear spectral broadening is fundamentally important, as it pushes the pulse duration limits imposed by the bandwidth of laser media. In this study, we demonstrate the spectral broadening and supercontinuum generation in several bulk materials, including InP, Si, GaN, GaAs, PbMoO 4 , YVO 4 , diamond, and TiO 2 , using pump radiation with up to 4 W average power centered at 2.35 µm from a Cr:ZnS femtosecond MOPA system. Some of the investigated materials have excellent potential as effective media for middle-infrared supercontinuum generation, demonstrating the feasibility of developing a single-cycle pulse middle-infrared laser system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Diagnostic Methodologies of Laser-Initiated 11 B(p,α)2α Fusion Reactions

The detection of the ionic products of low-rate fusion reactions, and in particular of the 11 B(p,α)2α, is one of the recognized main problems in experiments where these reactions are initiated by tailored interaction of intense and high-energy lasers with matter. A thorough description of this important issue, with a critical comparison of the diagnostic opportunities, is indeed so far. In this work, we describe the common diagnostic methodologies used for the detection of the alpha particles generated by the 11 B(p,α)2α reaction and, for each, we outline advantages and limitations, with considerations that can also be applied to other low-rate fusion reactions. We show here that, in general, the univocal characterization of the α products coming from this reaction can be achieved by the simultaneous use of several diagnostic tools placed in close proximity.

11B(p,α)2α reactions↗

An Improved Genetic Algorithm approach to the Unit Commitment/Economic Dispatch problem

The deployment of new technologies, the importance of accurately modeling the dynamics of the generating units and the introduction of new policies are making the solution of the Unit Commitment/Economic Dispatch problem more and more complicated.In the present scenario, traditionally followed scheduling criteria might not lead to the optimal fleet configuration any more. In addition, most of the widely used techniques have limited capabilities at modeling the nonlinear dynamics of committed power plants. When realistic power systems comprising of several tens of generating units are modeled, the resulting optimization problem turns to be computationally intensive for the current computing capabilities. In this paper, an improved version of a GA-based optimization algorithm is presented. A detailed methodology aimed at obtaining a more efficient version of the GA, and a more detailed and accurate description of the flexible operation flexibility of the power plants is described.

genetic algorithm↗

Probing the flavour structure of dimension-6 EFT operators in multilepton final states in proton-proton collisions at $\sqrt{s}=13$ TeV

An analysis of the flavour structure of dimension-6 effective field theory (EFT) operators in multilepton final states is presented, focusing on the interactions of quarks with Z bosons. For the first time, the flavour structure of these operators is disentangled by simultaneously probing the interactions with different quark generations. The analysis targets the associated production of a top quark pair and a Z boson, as well as diboson processes in final states with at least three leptons, which can be electrons or muons. The data were recorded by the CMS experiment in the years 2016–2018 in proton-proton collisions at a centre-of-mass energy of 13 TeV and correspond to an integrated luminosity of 138 fb −1 . Consistency with the standard model of particle physics is observed and limits are set on the selected Wilson coefficients, split into couplings to light- and heavy-quark generations.

Flavour Physics↗

New generation bunch shape monitor for ion accelerators

Measuring longitudinal beam parameters is important for operation and development of high intensity linear accelerators, but it is notoriously difficult for proton and ion beams at non-relativistic energies. The Bunch Shape Monitor (BSM) is a device used for measuring the longitudinal bunch distribution in ion linacs. The existing BSM models have poor electron collection efficiency from the wire and are limited to one-dimensional measurements of the phase coordinate. In response to this problem, we have developed a new generation BSM with improved performance. The proposed design incorporates three major innovations: First, the collection efficiency was improved by adding a focusing field between the wire and the entrance slit, which will also allow measurements over a much wider dynamic range. Second, an improvement in the measurement speed was achieved by sampling longitudinal profiles of multiple energy slices simultaneously, where the BSM wire is placed at the exit of an ion spectrometer so that ions with different energies hit the wire at different horizontal coordinates along the wire. Finally, the design incorporates a motion system that can shift the wire and deflecting cavity together, enabling transverse profile measurements like a wire scanner. Here, in this paper, we will provide the design of the new BSM and report on its beam test results at the Spallation Neutron Source facility in Oak Ridge National Laboratory.

43 PARTICLE ACCELERATORS↗

Multi-Stage and Multi-Timescale Robust Co-Optimization Planning for Reliable and Sustainable Power Systems. Final Report

In this project, Clarkson University, in collaboration with Southern Methodist University and University of Pittsburgh, conducted the research to model, design, and implement a sophisticated generation and transmission co-optimization planning decision tool, called Multi-stage and Multi-timescale robust Co-Optimization Planning (MMCOP). The MMCOP decision tool intends to facilitate generation and transmission co-optimization planning of emerging power systems, while mitigating risks and uncertainties in both short-term operation dynamics and long-term policy and technology changes. Long-term power system planning aims at optimizing asset utilization by investing in a proper mix of various generation technologies and transmission lines to supply the future load growth. In particular, the Clean Power Plan (CPP), which is designed to combat climate change and reduce carbon emissions by setting a national limit on carbon pollution from power plants, may dramatically change the landscape of the power industry by further promoting clean energy and phasing out emissions-intensive generation technologies. In addition, novel non-wire alternatives (e.g., demand response (DR), distributed generation (DG), energy efficiency (EE), and smart grid technologies) and the computational complexity for large-scale systems significantly complicate the system planning procedure even further. However, existing conventional planning approaches neglect short-term variability and uncertainty of renewable energy, hourly chronological operation details, and physical nonlinear characteristics of the alternating current transmission network. As a result, existing conventional planning approaches may not work properly, and power systems reliability could be in jeopardy. In observing the limitations of existing conventional planning approaches and addressing new challenges of emerging power systems, the main scope of this project to develop co-optimization planning models within a multi-stage and multi-timescale framework. In particular, random contingencies, key uncertainty factors, and AC power flows are included to derive expansion plans while considering both long-term reliability and short-term flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multitask methods for predicting molecular properties from heterogeneous data

Data generation remains a bottleneck in training surrogate models to predict molecular properties. We demonstrate that multitask Gaussian process regression overcomes this limitation by leveraging both expensive and cheap data sources. In particular, we consider training sets constructed from coupled-cluster (CC) and density functional theory (DFT) data. We report that multitask surrogates can predict at CC-level accuracy with a reduction in data generation cost by over an order of magnitude. Of note, our approach allows the training set to include DFT data generated by a heterogeneous mix of exchange–correlation functionals without imposing any artificial hierarchy on functional accuracy. More generally, the multitask framework can accommodate a wider range of training set structures—including the full disparity between the different levels of fidelity—than existing kernel approaches based on Δ-learning although we show that the accuracy of the two approaches can be similar. Consequently, multitask regression can be a tool for reducing data generation costs even further by opportunistically exploiting existing data sources.

Chemistry↗

Motion planning of mobile multi-limb robotic systems subject to force and friction constraints

A method is presented to generate motions for a class of multilimb robotic systems enabling them to apply large static forces over large ranges of motion without saturating actuator effort limits, system-environment friction constraints, kinematic joint limits, or geometric workspace obstacles. The approach, termed the force-workspace (FW) approach, maps these constraints into the system C-space to form constraint obstacles using a recursive subdivision process. To generate motions along which actuator efforts can be specified without violating system constraints, paths are planned that avoid these constraint obstacles. The method permits the shape of the paths to be controlled using any configuration-dependent performance criterion. The FW approach was applied to a proposed three-limb planar climbing robot whose task is to climb upwards between two vertical walls by pushing outwards to generate frictional support. Motions were planned automatically within the system FW, enabling it to lift itself upwards using two limbs at a time, and a gait was planned to enable it to switch limbs and climb continuously.

Madhani, Akhil↗

Preventing Molecular and Particulate Infiltration in a Confined Volume

Contaminants from an instrument's self-generated sources or from sources external to the instrument may degrade its critical surfaces and/or create an environment which limits the instrument's intended performance. Analyses have been carried out on a method to investigate the required purging flow of clean, dry gas to prevent the ingestion of external contaminants into the instrument container volume. The pressure to be maintained and the required flow are examined in terms of their effectiveness in preventing gaseous and particulate contaminant ingestion and abatement of self-generated contaminants in the volume. The required venting area or the existing volume venting area is correlated to the volume to be purged, the allowable pressure differential across the volume, the external contaminant partial pressure, and the sizes of the ambient particulates. The diffusion of external water vapor into the volume while it was being purged was experimentally obtained in terms of an infiltration time constant. That data and the acceptable fraction of the outside pressure into the volume indicate the required flow of purge gas expressed in terms of volume change per unit time. The exclusion of particulates is based on the incoming velocity of the particles and the exit flow speed and density of the purge gas. The purging flow pressures needed to maintain the required flows through the vent passages are indicated. The purge gas must prevent or limit the entrance of the external contaminants to the critical locations of the instrument. It should also prevent self- contamination from surfaces, reduce material outgassing, and sweep out the outgassed products. Systems and facilities that can benefit from purging may be optical equipment, clinical facilities, manufacturing facilities, clean rooms, and other systems requiring clean environments.

Scialdone, John J.↗

Shock Capturing via Limiting for High-Order Methods Including Discontinuous Galerkin

As is well-known, popular high-order methods such as discontinuous Galerkin (DG) and flux reconstruction (FR) tend to generate oscillations near shocks and discontinuities, which can lead to negative pressure or density, ultimately causing code breakdown. For standard second-order methods, one approach to mitigating oscillations is to impose constraints on the calculated slopes, ensuring they do not become excessively steep. This limiting process is rooted in the idea of preserving monotonicity introduced by Van Leer (1974): when the data are monotone, limiting the slopes result in a monotone piecewise linear solution. However, a drawback of this approach is the loss of accuracy near extrema, where the non-monotone solution is somewhat flattened and achieves only first-order accuracy.

numerical methods↗

Current EBC Development and Testing at NASA

SiC SiC Ceramic Matrix Composites (CMCs) are a game changer for advanced power generation equipment because of their high temperature capability, oxidation resistance, and light weight that translate to significant reduction in fuel consumption and emission. Limitations of SiC SiC CMCs include surface recession and component cracking and associated chemical and physical degradation in the CMC. The solution pursued to mitigate surface recession of SiC SiC CMCs is the incorporation of coating systems that provide surface protection, which has become known as an Environmental Barrier Coating (EBC). The development of EBCs for the protection of SiC SiC CMCs was a continuation of coating development work for corrosion protection of silicon-based monolithics. The first and second generation EBCs developed in mid 1990s-early 2000s laid the foundation for current EBCs. Environmental degradation that limits EBC life includes surface recession by steam, oxidation in steam environments, and CMAS-EBC reactions. Many engine tests have been conducted since late 1990s and a first CMC component entered into service in 2016 in a commercial engine. The introduction of CMCs represents significant challenges as failure of the EBC means rapid reduction in component life. A reliable lifing method and engine-relevant testing methods to validate life need to be developed. This paper will current activities on EBC development and testing at NASA.

CMC↗

A Common Communications, Navigation and Surveillance Infrastructure for Accommodating Space Vehicles in the Next Generation Air Transportation System

Suborbital space flight and space tourism are new potential markets that could significantly impact the National Airspace System (NAS). Numerous private companies are developing space flight capabilities to capture a piece of an emerging commercial space transportation market. These entrepreneurs share a common vision that sees commercial space flight as a profitable venture. Additionally, U.S. space exploration policy and national defense will impose significant additional demands on the NAS. Air traffic service providers must allow all users fair access to limited airspace, while ensuring that the highest levels of safety, security, and efficiency are maintained. The FAA's Next Generation Air Transportation System (NextGen) will need to accommodate spacecraft transitioning to and from space through the NAS. To accomplish this, space and air traffic operations will need to be seamlessly integrated under some common communications, navigation and surveillance (CNS) infrastructure. As part of NextGen, the FAA has been developing the Automatic Dependent Surveillance Broadcast (ADS-B) which utilizes the Global Positioning System (GPS) to track and separate aircraft. Another key component of NextGen, System-Wide Information Management/ Network Enabled Operations (SWIM/NEO), is an open architecture network that will provide NAS data to various customers, system tools and applications. NASA and DoD are currently developing a space-based range (SBR) concept that also utilizes GPS, communications satellites and other CNS assets. The future SBR will have very similar utility for space operations as ADS-B and SWIM has for air traffic. Perhaps the FAA, NASA, and DoD should consider developing a common space-based CNS infrastructure to support both aviation and space transportation operations. This paper suggests specific areas of research for developing a CNS infrastructure that can accommodate spacecraft and other new types of vehicles as an integrated part of NextGen.

VanSuetendael, RIchard↗

Multi-Omics Reveals Temporal Scales of Carbon Metabolism in Synechococcus Elongatus PCC 7942 Under Light Disturbance

Central carbon metabolism in model cyanobacteria involves multiple pathways to adapt to energy-light limitations across diel cycles. However, the success in mechanistic modeling for phenotypic prediction of the protein regulators in the metabolic state depends on capturing the vast possibilities emerging from multiple regulatory pathways in complex biological processes. Here, we developed a physics-informed machine learning approach based on energy-landscape concepts to predict regulatory proteins responding to cyclic circadian and unforeseen light perturbations in cyanobacterial metabolic networks. Our approach provides interpretable de novo models for inferring gene expression dynamics from Synechococcus elongatus over diel cycles and using redox proteome analysis to distinguish immediate light-responsive elements from circadian-regulated processes in carbon metabolism pathways. We identified distinct temporal signatures with the analysis of the redox proteome: there was an immediate shift in cysteine redox states accompanied by a limited change in protein abundance under constant illumination and after 2 hours of darkness. This discovery indicates that the generation of reductants coordinates photoinduced electron transport with redox metabolic pathways in two discernable molecular mechanisms: fast redox-based protein modifications occur immediately after the light disturbance, followed by slow transcriptional regulations across networks. This temporal regulation reveals how metabolic networks integrate rapid light responses with programmed circadian rhythms to maintain cellular homeostasis under the light-energy limitations over the diel cycle.

Biomolecular & subcellular processes↗

Dynamically tunable second-harmonic generation using hybrid nanostructures incorporating phase-change chalcogenides

Nonlinear metasurfaces with high conversion efficiencies have been vastly investigated. However, strong dynamic tunability of such devices is limited in conventional passive plasmonic and dielectric material platforms. Germanium antimony telluride (GST) is a promising phase-change chalcogenide for the reconfiguration of metamaterials due to strong nonvolatile changes of the real and imaginary parts of the refraction index through amorphous-crystalline phase change. The orderly structured GST has an even higher potential in tunable second-harmonic generation (SHG) with a non-centrosymmetric crystal structure at the crystalline phase, while the amorphous phase of GST does not exhibit bulk second-order nonlinearity. Here, we experimentally demonstrate SHG switches by actively controlling the crystalline phase of GST for a GST-based hybrid metasurface featuring a gap-surface plasmon resonance, and a quarter-wave asymmetric Fabry–Perot (F–P) cavity incorporating GST. We obtain SHG switches with modulation depths as high as ~ 20 dB for the wavelengths at the on-state resonance. We also demonstrate the feasibility of multi-level SHG modulation by leveraging three controlled GST phases, i.e., amorphous, semi-crystalline, and crystalline, for the gap-surface plasmon hybrid device, which features stronger light–matter interaction and has higher resonant SHG efficiencies than the asymmetric F–P cavity device at respective GST phases. This research reveals that GST-based dynamic SHG switches can be potentially employed in practical applications, such as microscopy, optical communication, and photonic computing in the nonlinear regime.

42 ENGINEERING↗