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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DRDMannTurb: A Python package for scalable, data-driven synthetic turbulence

Synthetic turbulence models (STMs) are used in wind engineering to generate realistic flow fields and are employed as inputs to industrial wind simulations. Examples include prescribing inlet conditions in large eddy simulations that model loads on wind turbines and tall buildings. We are interested in STMs capable of generating fluctuations based on prescribed second-moment statistics since such models can simulate environmental conditions that closely resemble on-site observations. To this end, the widely used Mann model (see Mann, 1994, 1998) is the inspiration for DRDMannTurb. The Mann model is described by three physical parameters: a magnitude parameter influencing the global variance of the wind field and corresponding to the Kolmogorov constant multiplied by the rate of viscous dissipation of the turbulent kinetic energy to the two-thirds, αϵ 2/3 , a turbulence length scale parameter L, and a nondimensional parameter Γ related to the lifetime of the eddies. A number of studies, as well as international standards (e.g., those by the International Electrotechnical Commission (IEC)), include recommended values for these three parameters with the goal of standardizing wind simulations according to observed energy spectra. Yet, having only three parameters, the Mann model faces limitations in accurately representing the diversity of observable spectra. This Python package enables users to extend the Mann model and more accurately fit field measurements through flexible neural network models of the eddy lifetime function. Following Keith et al. (2021), we refer to this class of models as Deep Rapid Distortion (DRD) models. DRDMannTurb also includes a general module implementing an efficient method for synthetic turbulence generation based on a domain decomposition technique. This technique is also described in Keith et al. (2021).

17 WIND ENERGY↗
DOE OSTI2021

Glass/glass photovoltaic module reliability and degradation: a review

Glass/glass (G/G) photovoltaic (PV) module construction is quickly rising in popularity due to increased demand for bifacial PV modules, with additional applications for thin-film and building-integrated PV technologies. G/G modules are expected to withstand harsh environmental conditions and extend the installed module lifespan to greater than 30 years compared to conventional glass/backsheet (G/B) modules. With the rapid growth of G/G deployment, understanding the outdoor performance, degradation, and reliability of this PV module construction becomes highly valuable. In this review, we present the history of G/G modules that have existed in the field for the past 20 years, their subsequent reliability issues under different climates, and methods for accelerated testing and characterization of both cells and packaging materials. We highlight some general trends of G/G modules, such as greater degradation when using poly(ethylene-co-vinyl acetate) (EVA) encapsulants, causing the industry to move toward polyolefin-based encapsulants. Transparent backsheets have also been introduced as an alternative to the rear glass for decreasing the module weight and aiding the effusion of trapped gaseous degradation products in the laminate. New amendments to IEC 61215 standard protocols for G/G bifacial modules have also been proposed so that the rear side power generation and UV exposure will be standardized. We further summarize a suite of destructive and non-destructive characterization techniques, such as current-voltage scans, module electro-optical imaging, adhesion tests, nanoscale structural/chemical investigation, and forensic analysis, to provide deeper insights into the fundamental properties of the module materials degradation and how it can be monitored in the G/G construction. This will set the groundwork for future research and product development.

14 SOLAR ENERGY↗
DOE OSTI2021

Glass/Glass Photovoltaic Module Reliability and Degradation: A Review - Figures

Glass/glass (G/G) photovoltaic (PV) module construction is quickly rising in popularity due to increased demand for bifacial PV modules, with additional applications for thin-film and building-integrated PV technologies. G/G modules are expected to withstand harsh environmental conditions and extend the installed module lifespan to greater than 30 years compared to conventional glass/backsheet (G/B) modules. With the rapid growth of G/G deployment, understanding the outdoor performance, degradation, and reliability of this PV module construction becomes highly valuable. In this review, we present the history of G/G modules that have existed in the field for the past 20 years, their subsequent reliability issues under different climates, and methods for accelerated testing and characterization of both cells and packaging materials. We highlight some general trends of G/G modules, such as greater degradation when using poly(ethylene-co-vinyl acetate) (EVA) encapsulants, causing the industry to move toward polyolefin-based encapsulants. Transparent backsheets have also been introduced as an alternative to the rear glass for decreasing the module weight and aiding the effusion of trapped gaseous degradation products in the laminate. New amendments to IEC 61215 standard protocols for G/G bifacial modules have also been proposed so that the rear side power generation and UV exposure will be standardized. We further summarize a suite of destructive and non-destructive characterization techniques, such as current-voltage scans, module electro-optical imaging, adhesion tests, nanoscale structural/chemical investigation, and forensic analysis, to provide deeper insights into the fundamental properties of the module materials degradation and how it can be monitored in the G/G construction. This will set the groundwork for future research and product development.

transparent backsheet↗
DOE OSTI2023

Leaving in the lead: Priorities for perovskite photovoltaics

The need for moving electricity generation to a sustainable model requires the development of low cost ubiquitous photovoltaics (PVs) to harvest the planet’s primary energy source, the Sun. Building upon the successes of Si-based and CdTe-based PV technologies, PVs with lower-embodied energy and requiring lower carbon dioxide equivalent to produce will be required to meet long-term sustainability goals. In particular, thin-film technologies, such as high-efficiency metal halide perovskite (MHP) PV modules, provide avenues to reduced embodied energy, lower energy payback times, and enabling energy-dense tandems [H. M. Wikoff et al., Joule 6(7), 1710–1725 (2022) and V. Fthenakis, Renewable Sustainable Energy Rev. 13(9), 2746–2750 (2009)]. The ability to improve efficiency and lower energy payback time of next generation thin-film PV modules is a critical foundation for green H2 and electrification more broadly. In this regard, Pb-based MHP-PVs have separated themselves as a result of the high-efficiencies that can be realized across a range of electronic gaps. Questions regarding Pb-based MHP-PVs that are often asked, as the challenges of efficiency and reliability are met, revolve around the “problem” of the Pb content. Specifically, “does Pb toxicity preclude MHP-PV modules from being deployed at the TW scale?” To provide this sense of scale, in 2021, the United States burned 10.5 quads of coal, with 90% of that used for electricity generation. Given the energy content of coal of 29 MJ/kg and a residual lead content in that coal of 30 mg/kg, electricity generation from coal resulted in more lead emitted into the atmosphere than what would be required to produce over 2 TW of MHP-PV name plate capacity (assuming a 20% module efficiency and an ∼700 nm active layer). This amounts to more PV power than has been deployed across all PV technologies and geographies to date. This only includes US coal consumption; the rest of the world would be much larger. This example illustrates the scale of the material usage relative to the energy production. Imagine a power-generation technology that offsets these Pb emissions from coal and essentially sequesters this Pb content between two sheets of impermeable glass. Why should we let Pb’s history of misuse prevent it from being included in next generation PV modules that can enable a sustainable energy future?

14 SOLAR ENERGY↗
DOE OSTI2024

Situated Visualization of Photovoltaic Module Performance for Workforce Development: Preprint

The rapid growth of the solar energy industry requires advanced educational tools to train the next generation of engineers and technicians. We present a novel system for situated visualization of photovoltaic (PV) module performance, leveraging a combination of PV simulation, sun-sky position, and head-mounted augmented reality (AR). Our system is guided by four principles of development: simplicity, adaptability, collaboration, and maintainability, realized in six components. Users interactively manipulate a physical module's orientation and shading referents with immediate feedback on the module's performance.

augmented reality↗
DOE OSTI2021

Space-Time Quantum Metasurfaces

Metasurfaces have recently entered the realm of quantum photonics, enabling manipulation of quantum light using a compact nanophotonic platform. Realizing the full potential of metasurfaces at the deepest quantum level requires the ability to tune coherent light-matter interactions continuously in space and time. Here, we introduce the concept of space-time quantum metasurfaces for arbitrary control of the spectral, spatial, and spin properties of nonclassical light using a compact photonic platform. We show that space-time quantum metasurfaces allow on-demand tailoring of entanglement among all degrees of freedom of a single photon. We also show that spatiotemporal modulation induces asymmetry at the fundamental level of quantum fluctuations, resulting in the generation of steered and vortex photon pairs out of vacuum. Space-time quantum metasurfaces have the potential to enable novel photonic functionalities, such as encoding quantum information into high-dimensional color qudits using designer modulation protocols, sculpting multispectral and multispatial modes in spontaneous emission, and generating reconfigurable hyperentanglement for high-capacity quantum communications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

CCAT-prime: Designs and status of the first light 280 GHz MKID array and mod-cam receiver

The CCAT-prime project's first light array will be deployed in Mod-Cam, a single-module testbed and first light cryostat, on the Fred Young Submillimeter Telescope (FYST) in Chile's high Atacama desert in late 2022. FYST is a six-meter aperture telescope being built on Cerro Chajnantor at an elevation of 5600 meters to observe at millimeter and submillimeter wavelengths. 1 Mod-Cam will pave the way for Prime-Cam, the primary first generation instrument, which will house up to seven instrument modules to simultaneously observe the sky and study a diverse set of science goals from monitoring protostars to probing distant galaxy clusters and characterizing the cosmic microwave background (CMB). At least one feedhorn-coupled array of microwave kinetic inductance detectors (MKIDs) centered on 280 GHz will be included in Mod-Cam at first light, with additional instrument modules to be deployed along with Prime-Cam in stages. The first 280 GHz detector array was fabricated by the Quantum Sensors Group at NIST in Boulder, CO and includes 3,456 polarization- sensitive MKIDs. Current mechanical designs allow for up to three hexagonal arrays to be placed in each single instrument module. We present details on this first light detector array, including mechanical designs and cold readout plans, as well as introducing Mod-Cam as both a testbed and predecessor to Prime-Cam.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Fourth Generation MPDV and MBR at DARHT

A new experimental setup for diagnosing hydrotest performance was designed, built, and implemented at DARHT. The setup consists of 128 points of fourth generation (Gen4) multiplexed photonic Doppler velocimetry (MPDV) and 128 separate points of modulation based ranging (MBR) to serve as a direct complement to the MPDV. The diagnostics were designed to overcome limitations in the third generation of the MPDV diagnostic that limited laser launch power to ~10 mW per point. As the main failure mechanism identified in the third generation MPDV system arose from stimulated Brillouin scattering, a nonlinear optical phenomenon inherent in standard single mode fiber, the fourth generation MPDV system reduced the number of time-multiplexed channels by a factor of two. This has allowed laser launch power to be increased to as much as 200 mW per channel which is a 20 times increase in the signal to noise ratio (SNR) as compared with the third generation system. This document will first discuss the previous limitations and describe the design of the system. This will be followed by the results of a simple flyer plate experiment used to demonstrate the improved SNR as well as calibrate the phase errors in the system that MBR is sensitive to.

42 ENGINEERING↗
DOE OSTI2024

Mixing of the Connecticut River Plume During Ambient Flood Tides: Spatial Heterogeneity and Contributions of Bottom–Generated and Interfacial Mixing

The Connecticut River plume is influenced by energetic ambient tides in the Long Island Sound receiving waters. The objectives of this modeling study are (a) characterizing the spatial heterogeneity of turbulent buoyancy fluxes, (b) partitioning turbulent buoyancy fluxes into bottom-generated and interfacial shear contributions, and (c) quantifying contributions to plume-integrated mixing within the tidal plume. The plume formed during ambient flood tides under low river discharge, spring tides, and no winds is analyzed. Turbulent buoyancy fluxes (B) and depth-integrated B through the plume (Bd) are characterized by pronounced spatial heterogeneity. Strong mixing (Bd ~ 10 –5 -10 –4 m 3 /s 3 ) occurs near the mouth, in the nearfield plume turning region, over shoals, and nearshore shallow areas. Low to moderate mixing (Bd ~ 10 –8 -10 –6 m 3 /s 3 ) occupies half the plume. Buoyancy fluxes are first partitioned based on the depth of the shear stress minimum between plume-generated and bottom-generated shear maxima. Four other tested partitioning methods are based on open channel flow and stratified shear flow parameterizations. Interfacial and bottom-generated shear contribute to different areas of intense and moderate mixing. All methods indicate a significant plume mixing role for bottom-generated mixing, but interfacial mixing is a bigger contributor. Plume-integrated total and interfacial mixing peak at max ambient flood and the timing of peak bottom-generated mixing varies among partitioning methods. Two-thirds of the mixing occurs in concentrated intense mixing areas. A parameter space with the ambient tidal Froude number and plume thickness to depth ratio as axes indicates many tidally modulated plumes are moderately to dominantly influenced by bottom-generated tidal mixing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Automated defect identification in electroluminescence images of solar modules

Solar photovoltaic (PV) modules are susceptible to manufacturing defects, mishandling problems or extreme weather events that can limit energy production or cause early device failure. Trained professionals use electroluminescence (EL) images to identify defects in modules, however, field surveys or inline image acquisition can generate millions of EL images, which are infeasible to analyze by rote inspection. Here, we develop a rapid automatic computer vision pipeline (~0.5 seconds/module) to analyze EL images and identify defects including cracks, intra-cell defects, oxygen-induced defects, and solder disconnections. Defect identification is achieved with a machine learning model (Random Forest, ResNet models and YOLO) trained on 762 manually-labeled EL images of PV modules. We compare model performance on an imbalanced real-world validation set containing 134 EL images and determine that ResNet18 and YOLO are the optimal models; we next evaluated these models on a dedicated testing set (129 module images) with resulting macro F1 scores of 0.83 (ResNet18) and 0.78 (YOLO). Using a field EL survey of a PV power plant damaged in a vegetation fire, we analyze 18,954 EL images (2.4 million cells) and inspect the spatial distribution of defects on the solar modules. The results find increased frequency of ‘crack’, ‘solder’ and ‘intra-cell’ defects on the edges of the solar module closest to the ground after fire. We also find an abnormal increase of striation rings on cells which were assumed to be caused mainly in fabrication process. Our methods are published as open-source software. It can also be used to identify other kinds of defects or process different types of solar cells with minor modification on models by transfer learning.

14 SOLAR ENERGY↗
DOE OSTI2023

Carbonic anhydrase textile structured packing for efficient CO 2 absorption in methyldiethanolamine solvent

Carbonic anhydrase (CA) is an attractive biodegradable catalyst for CO 2 absorption in solvent–based CO 2 capture. However, maintaining the stability of CA as a homogeneous component of the solvents is a challenge. Solvent regeneration temperature typically exceeds the enzyme thermal tolerance, which leads to CA deactivation. To reduce the need for frequent CA replenishment and to avoid inactive CA accumulation in the solvent, this work shows the benefits of an immobilization strategy where CA is fixed in a second–generation design of textile structured packing (CATSP–2) modules. The enzyme–immobilized packing showed 1.5 times better performance in CO 2 separation compared with traditional structured packing with a corresponding increased CO 2 loading in the rich solvent. The modules exhibited good CA activity retention of ~80% during the tests without any CA replenishment. As a result, applying CATSP–2 could potentially decrease the packing height and absorber column size for a lower cost per amount of CO 2 captured.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra

A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A review on the sizing and selection of control valves for thermal hydraulics for reactor system applications

This study presents an overview regarding how to model/size, choose, and maintain control valves (CVs) for a reactor system thermal hydraulics experimentation—specifically simulating pipe break(s) and a loss of coolant accident (LOCA) analysis. In a thermal hydraulics test loop, CVs modulate fluid flow according to the control signal generated by the controller to control the process parameter. The selection of a CV in industrial applications involves many factors, including process diversity, safety, and reliability. Further, the key issues and challenges for performing proper mathematical modeling, installation, servicing, and calibration are also discussed for the benefit of operators and end-users. Additionally, this research includes case studies illustrating major plant-level accidents associated with the malfunctioning of valves. Therefore, the study will serve as a knowledge base or reference guide for young professionals and operators who wish to better understand process control applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Hydrogen-Bond-Driven Chemical Separations: Elucidating the Interfacial Steps of Self-Assembly in Solvent Extraction

Chemical separations, particularly liquid extractions, are pervasive in academic and industrial laboratories, yet a mechanistic understanding of the events governing their function are obscured by interfacial phenomena that are notoriously difficult to measure. In this work, we investigate the fundamental steps of ligand self-assembly as driven by changes in the interfacial H-bonding network using vibrational sum frequency generation. Our results show how the bulk pH modulates the interfacial structure of extractants at the buried oil/aqueous interface via the formation of unique H-bonding networks that order and bridge ligands to produce self-assembled aggregates. These extended H-bonded structures are key to the subsequent extraction of Co2+ from the aqueous phase in promoting micelle formation and subsequent ejection of the said micelle into the oil phase. The combination of static and time-resolved measurements reveals the events underlying complexities of liquid extractions at high [Co2+]:[ligand] ratios by showing an evolution of interfacially assembled structures that are readily tuned on a chemical basis by altering the compositions of the aqueous phase. The results of this work point to new principles to design-applied separations through the manipulation of surface charge, electrostatic screening, and the associated H-bonding networks that arise at the interface to facilitate organization and subsequent extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Discovery and molecular basis of subtype-selective cyclophilin inhibitors

Abstract Although cyclophilins are attractive targets for probing biology and therapeutic intervention, no subtype-selective cyclophilin inhibitors have been described. We discovered novel cyclophilin inhibitors from the in vitro selection of a DNA-templated library of 256,000 drug-like macrocycles for cyclophilin D (CypD) affinity. Iterated macrocycle engineering guided by ten X-ray co-crystal structures yielded potent and selective inhibitors (half maximal inhibitory concentration (IC 50 ) = 10 nM) that bind the active site of CypD and also make novel interactions with non-conserved residues in the S2 pocket, an adjacent exo-site. The resulting macrocycles inhibit CypD activity with 21- to >10,000-fold selectivity over other cyclophilins and inhibit mitochondrial permeability transition pore opening in isolated mitochondria. We further exploited S2 pocket interactions to develop the first cyclophilin E (CypE)-selective inhibitor, which forms a reversible covalent bond with a CypE S2 pocket lysine, and exhibits 30- to >4,000-fold selectivity over other cyclophilins. These findings reveal a strategy to generate isoform-selective small-molecule cyclophilin modulators, advancing their suitability as targets for biological investigation and therapeutic development.

Biochemistry & Molecular Biology↗
DOE OSTI2020

Theory of edge localized mode suppression by static resonant magnetic perturbations in the DIII-D tokamak

According to a recent paper [Hu et al ., Phys. Plasmas 26, 120702 (2019)], mode penetration at the top of the pedestal is a necessary and sufficient condition for the suppression of edge localized modes (ELMs) by a resonant magnetic perturbation (RMPs) in an H-mode tokamak discharge. This paper employs asymptotic matching theory to model a particular DIII-D discharge in which ELMs were suppressed by an externally generated, static, n ¼ 2, RMP whose amplitude was modulated at a frequency of 1 Hz. It is demonstrated that the response of the plasma to the applied RMP, in the immediate vicinities of the rational (i.e., resonant) surfaces, is governed by nonlinear, rather than by linear, physics. This is the case because the magnetic island widths associated with driven reconnection exceed the linear layer widths, even in cases where driven reconnection is strongly suppressed by plasma rotation. The natural frequency at a given rational surface (i.e., the helical frequency at which the locally resonant component of the RMP would need to propagate in order to maximize driven reconnection) is found to be offset from the local E B frame in the ion diamagnetic direction. The size of the offset is mostly determined by neoclassical poloidal rotation. Finally, the predictions of a fully nonlinear plasma response model are found to be broadly consistent with the DIII-D experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Cross-scale interaction between microturbulence and meso-scale reversed shear Alfvén eigenmodes in DIII-D plasmas

Abstract This paper reports global nonlinear gyrokinetic simulations that couple meso-scale reversed shear Alfvén eigenmodes (RSAEs) driven by energetic particles (EPs) and ion temperature gradient (ITG) microturbulence driven by thermal plasma, using equilibrium and profiles from DIII-D discharge #159243. In simulations focusing only on the ITG, electrostatic ITG drives a huge thermal ion heat transport, which is reduced by a factor of 10 to a level close to the experimental value in electromagnetic simulation due to finite β effect. In the simulations coupling the RSAE and ITG, ITG can scatter the resonant EP nonlinearly trapped by the RSAE and damp the zonal flows generated by the RSAE. The regulation of the RSAE by the ITG greatly reduces the initial saturation amplitude of the RSAE but increases the RSAE amplitude and associated EP transport to experimental levels in the quasi-steady state. The RSAE effects on the ITG, specifically the stronger zonal flows generated by the RSAE and the RSAE frequency modulation of the ITG-induced thermal ion heat transport, in turn, leads to a reduction of the thermal ion heat transport by more than a factor of 2 . For a stronger background ITG, the regulation of the RSAE by the ITG is stronger, while the RSAE effects on the ITG are weaker. This work highlights the importance of cross-scale coupling in the dynamics of the AE turbulence and EP transport.

Physics↗