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

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Resolving Ice Cloud Optical Thickness Biases Between CALIOP and MODIS Using Infrared Retrievals

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g approx. = 0.75 in the mid-visible spectrum, 5-15% smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products.This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28%), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Cloud↗
DOE OSTI2022

Computational Estimation by Scientific Data Mining with Classical Methods to Automate Learning Strategies of Scientists

Experimental results are often plotted as 2-dimensional graphical plots (aka graphs) in scientific domains depicting dependent versus independent variables to aid visual analysis of processes. Repeatedly performing laboratory experiments consumes significant time and resources, motivating the need for computational estimation. The goals are to estimate the graph obtained in an experiment given its input conditions, and to estimate the conditions that would lead to a desired graph. Existing estimation approaches often do not meet accuracy and efficiency needs of targeted applications. We develop a computational estimation approach called AutoDomainMine that integrates clustering and classification over complex scientific data in a framework so as to automate classical learning methods of scientists. Knowledge discovered thereby from a database of existing experiments serves as the basis for estimation. Challenges include preserving domain semantics in clustering, finding matching strategies in classification, striking a good balance between elaboration and conciseness while displaying estimation results based on needs of targeted users, and deriving objective measures to capture subjective user interests. These and other challenges are addressed in this work. The AutoDomainMine approach is used to build a computational estimation system, rigorously evaluated with real data in Materials Science. Our evaluation confirms that AutoDomainMine provides desired accuracy and efficiency in computational estimation. It is extendable to other science and engineering domains as proved by adaptation of its sub-processes within fields such as Bioinformatics and Nanotechnology.

Computer Science↗
DOE OSTI2021

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging (GPI) at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g. ELM filaments) in the scrape-off layer and the at the plasma edge with 2.5 us temporal and 10 mm optical resolution.A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics, and then extended to a database of 169 ELM events.Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average an ELM crash consists of a filament with a circular cross-section which is propelled outwards with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100us until the radial propulsion settles back to the pre-ELM level. The experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current-filament interaction model.

correlation↗
DOE OSTI2016

Hydrothermal Liquefaction and Upgrading of Municipal Wastewater Treatment Plant Sludge: A Preliminary Techno-Economic Analysis, Rev.1

A preliminary process model and techno-economic analysis (TEA) was completed for fuel produced from hydrothermal liquefaction (HTL) of sludge waste from a municipal wastewater treatment plant (WWTP) and subsequent biocrude upgrading. The model is adapted from previous work by Jones et al. (2014) for algae HTL, using experimental data generated in fiscal year 2015 (FY15) bench-scale HTL testing of sludge waste streams. Testing was performed on sludge samples received from Metro Vancouver’s Annacis Island WWTP (Vancouver, B.C.) as part of a collaborative project with the Water Environment and Reuse Foundation (WERF). The full set of sludge HTL testing data from this effort will be documented in a separate report to be issued by WERF. This analysis is based on limited testing data and therefore should be considered preliminary. In addition, the testing was conducted with the goal of successful operation, and therefore does not represent an optimized process. Future refinements are necessary to improve the robustness of the model, including a cross-check of modeled biocrude components with the experimental GCMS data and investigation of equipment costs most appropriate at the relatively small scales used here. Environmental sustainability metrics analysis is also needed to understand the broader impact of this technology pathway. The base case scenario for the analysis consists of 10 HTL plants, each processing 100 dry U.S. ton/day (92.4 ton/day on a dry, ash-free basis) of sludge waste and producing 234 barrel per stream day (BPSD) biocrude, feeding into a centralized biocrude upgrading facility that produces 2,020 barrel per standard day of final fuel. This scale was chosen based upon initial wastewater treatment plant data collected by PNNL’s resource assessment team from the EPA’s Clean Watersheds Needs Survey database (EPA 2015a) and a rough estimate of what the potential sludge availability might be within a 100-mile radius. In addition, we received valuable feedback from the wastewater treatment industry as part of the WERF collaboration that helped form the basis for the selected HTL and upgrading plant scales and feedstock credit (current cost of disposal). It is assumed that the sludge is currently disposed of at $16.20/wet ton ($46/dry ton at 35% solids; $50/ton dry, ash-free basis) and this is included as a feedstock credit in the operating costs. The base case assumptions result in a minimum biocrude selling price of $3.8/gge and a minimum final upgraded fuel selling price of $4.9/gge. Several areas of process improvement and refinements to the analysis have the potential to significantly improve economics relative to the base case: •Optimization of HTL sludge feed solids content •Optimization of HTL biocrude yield •Optimization of HTL reactor liquid hourly space velocity (LHSV) •Optimization of fuel yield from hydrotreating •Combined large and small HTL scales specific to regions (e.g., metropolitan and suburban plants) Combined improvements believed to be achievable in these areas can potentially reduce the minimum selling price of biocrude and final upgraded fuel by about 50%. Further improvements may be possible through recovery of higher value components from the HTL aqueous phase, as being investigated under separate PNNL projects. Upgrading the biocrude at an existing petroleum refinery could also reduce the MFSP, although this option requires further testing to ensure compatibility and mitigation of risks to a refinery. And finally, recycling the HTL aqueous phase product stream back to the headworks of the WWTP (with no catalytic hydrothermal gasification treatment) can significantly reduce cost. This option is uniquely appropriate for application at a water treatment facility but also requires further investigation to determine any technical and economic challenges related to the extra chemical oxygen demand (COD) associated with the recycled water.

09 BIOMASS FUELS↗
NASA NTRS2017

Experimental Evaluation of Acoustic Engine Liner Models Developed with COMSOL Multiphysics

Accurate modeling tools are needed to design new engine liners capable of reducing aircraft noise. The purpose of this study is to determine if a commercially-available finite element package, COMSOL Multiphysics, can be used to accurately model a range of different acoustic engine liner designs, and in the process, collect and document a benchmark dataset that can be used in both current and future code evaluation activities. To achieve these goals, a variety of liner samples, ranging from conventional perforate-over-honeycomb to extended-reaction designs, were installed in one wall of the grazing flow impedance tube at the NASA Langley Research Center. The liners were exposed to high sound pressure levels and grazing flow, and the effect of the liner on the sound field in the flow duct was measured. These measurements were then compared with predictions. While this report only includes comparisons for a subset of the configurations, the full database of all measurements and predictions is available in electronic format upon request. The results demonstrate that both conventional perforate-over-honeycomb and extended-reaction liners can be accurately modeled using COMSOL. Therefore, this modeling tool can be used with confidence to supplement the current suite of acoustic propagation codes, and ultimately develop new acoustic engine liners designed to reduce aircraft noise.

Schiller, Noah H.↗
DOE OSTI2022

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Predicting the thermodynamic stability of double-perovskite halides from density functional theory

Recently, a series of double-perovskite halide compounds such as Cs 2 AgBiCl 6 and Cs 2 AgBiBr 6 have attracted intensive interest as promising alternatives to the solar absorber material CH 3 NH 3 PbI 3 because they are Pb-free and may exhibit enhanced stability. The thermodynamic stability of a number of double-perovskite halides has been predicted based on density functional theory (DFT) calculations of compound formation energies. In this paper, we found that the stability prediction can be dependent on the approximations used for the exchange-correlation functionals, e.g., the DFT calculations using the widely used Perdew, Burke, Ernzerhof (PBE) functional predict that Cs 2 AgBiBr 6 is thermodynamically unstable against phase-separation into the competing phases such as AgBr, Cs 2 AgBr 3 , Cs 3 Bi 2 Br 9 , etc., obviously inconsistent with the good stability observed experimentally. The incorrect prediction by the PBE calculation results from its failure to predict the correct ground-state structures of AgBr, AgCl, and CsCl. By contrast, the DFT calculations based on local density approximation, optB86b-vdW, and optB88-vdW functionals predict the ground-state structures of these binary halides correctly. Furthermore, the optB88-vdW functional is found to give the most accurate description of the lattice constants of the double-perovskite halides and their competing phases. Given these two aspects, we suggest that the optB88-vdW functional should be used for predicting thermodynamic stability in the future high-throughput computational material design or the construction of the Materials Genome database for new double-perovskite halides. As a result, using different exchange-correlation functionals has little influence on the dispersion of the conduction and the valence bands near the electronic bandgap; however, the calculated bandgap can be affected indirectly by the optimized lattice constant, which varies for different functionals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thermodynamic re-modeling of the Yb-Sb system aided by first-principles calculations

Here, the thermodynamic description of the Yb-Sb binary system is developed by means of the CALculations of PHAse Diagrams (CALPHAD) method by combining experimental data in the literature and predictions from first-principles calculations based on density functional theory (DFT) in the literature and the present work. Two pseudopotentials of Yb are compared in the present DFT-based calculations with 14 and 13 f-electrons frozen in the core, i.e., 5p 6 6s 2 and 5p 6 6s 2 5 d 1 electrons as valence electrons, termed Yb_2 and Yb_3, respectively. It is shown that the phonon spectrum of the YbSb phase calculated using the Yb_3 pseudopotential does not have imaginary phonon modes and is subsequently used to predict its temperature dependent thermodynamic properties by the DFT-based quasiharmonic phonon calculations. The present thermodynamic database includes the Yb 16 Sb 11 phase in addition to five intermetallic phases that were considered in previous modeling studies, i.e., YbSb 2 , YbSb, Yb 11 Sb 10 , Yb 4 Sb 3 , and Yb 5 Sb 3 . The high temperature orthorhombic structure of the Yb 5 Sb 3 phase is not considered in the present work as it was stabilized by hydrogen. The associate solution model is used to describe the short-range ordering behavior in the liquid phase. The calculations from the present thermodynamic model show good agreement with thermochemical and phase equilibrium data from both the present work and the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2012

A first-principles theoretical approach to heterogeneous nanocatalysis

A theoretical approach to heterogeneous catalysis by sub-nanometre supported metal clusters and alloys is presented and discussed. Its goal is to perform a computational sampling of the reaction paths in nanocatalysis via a global search in the phase space of structures and stoichiometry combined with filtering which takes into account the given experimental conditions (catalytically relevant temperature and reactant pressure), and corresponds to an incremental exploration of the disconnectivity diagram of the system. The approach is implemented and applied to the study of propylene partial oxidation by Ag3 supported on MgO(100). First-principles density-functional theory calculations coupled with a Reactive Global Optimization algorithm are performed, finding that: (1) the presence of an oxide support drastically changes the potential energy landscape of the system with respect to the gas phase, favoring configurations which interact positively with the electrostatic field generated by the surface; (2) the reaction energy barriers for the various mechanisms are crucial in the competition between thermodynamically and kinetically favored reaction products; (3) a topological database of structures and saddle points is produced which has general validity and can serve for future studies or for deriving general trends; (4) the MgO(100) surface captures some major features of the effect of an oxide support and appears to be a good model of a simple oxide substrate; (5) strong cooperative effects are found in the co-adsorption of O2 and other ligands on small metal clusters. The proposed approach appears as a viable route to advance the role of predictive computational science in the field of heterogeneous nanocatalysis.

Chemistry↗
DOE OSTI2021

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g., ELM filaments) in the scrape-off layer and at the plasma edge with 2.5 μs temporal and 10 mm optical resolution. A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics and then extended to a database of 159 ELM events. Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average, an ELM crash consists of a filament with a circular cross section, which is propelled outward with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100 μs until the radial propulsion settles back to the pre-ELM level. Furthermore, the experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current–filament interaction model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1995

Upper Thermosphere Winds and Temperatures in the Geomagnetic Polar Cap: Solar Cycle, Geomagnetic Activity, and Interplanetary Magnetic Field Dependencies

Ground-based Fabry-Perot interferometers located at Thule, Greenland (76.5 deg. N, 69.0 deg. W, lambda = 86 deg.) and at Sondre Stromfjord, Greenland (67.0 deg. N, 50.9 deg. W, lambda = 74 deg.) have monitored the upper thermospheric (approx. 240-km altitude) neutral wind and temperature over the northern hemisphere geomagnetic polar cap since 1983 and 1985, respectively. The thermospheric observations are obtained by determining the Doppler characteristics of the (OI) 15,867-K (630.0-nm) emission of atomic oxygen. The instruments operate on a routine, automatic, (mostly) untended basis during the winter observing seasons, with data coverage limited only by cloud cover and (occasional) instrument failures. This unique database of geomagnetic polar cap measurements now extends over the complete range of solar activity. We present an analysis of the measurements made between 1985 (near solar minimum) and 1991 (near solar maximum), as part of a long-term study of geomagnetic polar cap thermospheric climatology. The measurements from a total of 902 nights of observations are compared with the predictions of two semiempirical models: the Vector Spherical Harmonic (VSH) model of Killeen et al. (1987) and the Horizontal Wind Model (HWM) of Hedin et al. (1991). The results are also analyzed using calculations of thermospheric momentum forcing terms from the Thermosphere-ionosphere General Circulation Model TGCM) of the National Center for Atmospheric Research (NCAR). The experimental results show that upper thermospheric winds in the geomagnetic polar cap have a fundamental diurnal character, with typical wind speeds of about 200 m/s at solar minimum, rising to up to about 800 m/s at solar maximum, depending on geomagnetic activity level. These winds generally blow in the antisunward direction, but are interrupted by episodes of modified wind velocity and altered direction often associated with changes in the orientation of the Interplanetary Magnetic Field (IMF). The central polar cap (greater than approx. 80 magnetic latitude) antisunward wind speed is found to be a strong function of both solar and geomagnetic activity. The polar cap temperatures show variations in both solar and geomagnetic activity, with temperatures near 800 K for low K(sub p) and F(sub 10.7) and greater than about 2000 K for high K(sub p) and F(sub 10.7). The observed temperatures are significantly greater than those predicted by the mass spectrometer/incoherent scatter model for high activity conditions. Theoretical analysis based on the NCAR TIGCM indicates that the antisunward upper thermospheric winds, driven by upstream ion drag, basically 'coast' across the polar cap. The relatively small changes in wind velocity and direction within the polar cap are induced by a combination of forcing terms of commensurate magnitude, including the nonlinear advection term, the Coriolis term, and the pressure gradient force term. The polar cap thennospheric thermal balance is dominated by horizontal advection, and adiabatic and thermal conduction terms.

Killeen, T. L.↗
NASA NTRS1999

Advanced Subsonic Technology (AST) Area of Interest (AOI) 6: Develop and Validate Aeroelastic Codes for Turbomachinery

AlliedSignal Engines, in cooperation with NASA GRC (National Aeronautics and Space Administration Glenn Research Center), completed an evaluation of recently-developed aeroelastic computer codes using test cases from the AlliedSignal Engines fan blisk and turbine databases. Test data included strain gage, performance, and steady-state pressure information obtained for conditions where synchronous or flutter vibratory conditions were found to occur. Aeroelastic codes evaluated included quasi 3-D UNSFLO (MIT Developed/AE Modified, Quasi 3-D Aeroelastic Computer Code), 2-D FREPS (NASA-Developed Forced Response Prediction System Aeroelastic Computer Code), and 3-D TURBO-AE (NASA/Mississippi State University Developed 3-D Aeroelastic Computer Code). Unsteady pressure predictions for the turbine test case were used to evaluate the forced response prediction capabilities of each of the three aeroelastic codes. Additionally, one of the fan flutter cases was evaluated using TURBO-AE. The UNSFLO and FREPS evaluation predictions showed good agreement with the experimental test data trends, but quantitative improvements are needed. UNSFLO over-predicted turbine blade response reductions, while FREPS under-predicted them. The inviscid TURBO-AE turbine analysis predicted no discernible blade response reduction, indicating the necessity of including viscous effects for this test case. For the TURBO-AE fan blisk test case, significant effort was expended getting the viscous version of the code to give converged steady flow solutions for the transonic flow conditions. Once converged, the steady solutions provided an excellent match with test data and the calibrated DAWES (AlliedSignal 3-D Viscous Steady Flow CFD Solver). However, efforts expended establishing quality steady-state solutions prevented exercising the unsteady portion of the TURBO-AE code during the present program. AlliedSignal recommends that unsteady pressure measurement data be obtained for both test cases examined for use in aeroelastic code validation.

Gardner, Kevin D.↗
NASA NTRS2003

Fiber Reinforcement Architectures of PMCs on the Hygrothermal-Mechanical Performance for Aeropropulsion Applications

A rigid lightweight sandwich support structure, for the combustor chamber of a new generation liquid propellant rocket engine, was designed and fabricated using Polymer Matric Composite (PMC) facesheet on a Ti honeycomb or Carbon foam core. The facesheet consisted of high stiffness carbon fiber, M40JB, and high temperature Polyimides, such as PMR-11-50 and HFPE-II. Six different fiber architectures; 4HS woven fabric, uni-fabric, woven-uni hybrid, stitched woven fabric, stitched uni-fabric and tri-axial braided structures have been investigated for optimum stiffness-thickness-weight-performance design criteria for the hygrothermal-mechanical propulsion service exposure conditions including rapid heating up to 200 F/sec, maximum operating temperature of 600 F, internal pressure up to 100 psi. An extensive property and performance database including dry-wet mechanical properties at both 25 F and 600 F in various loading modes, thermal and physical properties including blistering onset condition was developed for fiber architecture down-selection and design guidelines. Various optimized process methods including vacuum bag compression molding, solvent assistant RTM (SaRTM), resin film infusion (RFI) were utilized for PMC panel fabrication depending on the architecture type. In the case of stitched woven fabric architecture, the optimal stitch pattern was chosen in terms of stitch density and yarn size, based on both in-plane mechanical properties and blistering performance. Potential reduction of the in-plane properties transverse to the line of stitching was also evaluated. Attempt to correlate the experimental results with theoretical micro-mechanics predictions will be presented.

Shin, Eugene↗
NASA NTRS2003

Effects of Fiber Reinforcement Architecture on the Hygrothermal-Mechanical Performance of Polyimide Matrix Composites for Aeropropulsion Applications

A lightweight sandwich support structure, for the combustor chamber of a new generation liquid propellant rocket engine, was designed and fabricated using a polymer matrix composite (PMC) facesheet on a Ti honeycomb core. The PMC facesheet consisted of high stiffness carbon fiber, M40JB, and high temperature Polyimides, such as PMR-II-50 and HFPE-II-52. Six different fiber architectures; four harness satin (4HS) woven fabric, uni-tape, woven-uni hybrid, stitched woven fabric, stitched uni-tape and triaxial braided structures have been investigated for optimum stiffness-thickness-weight-hygrothermal performance design criteria for the hygrothermal-mechanical propulsion service exposure conditions including rapid heating up to 200 F/sec, maximum operating temperature of 600 F, internal pressure up to 100 psi. One of the specific objectives in this study is to improve composite blistering resistance in z-direction at minimum expense of in-plane mechanical properties. An extensive property-performance database including dry-wet mechanical properties at various temperatures, thermal-physical properties, such as blistering onset condition was generated for fiber architecture down-selection and design guidelines. Various optimized process methods such as vacuum bag compression molding, solvent assistant resin transfer molding (SaRTM), resin film infusion (RFI) and autoclaving were utilized for PMC panel fabrication depending on the architecture type. In the case of stitched woven fabric architecture, the stitch pattern in terms of stitch density and yarn size was optimized based on both in-plane mechanical properties and blistering performance. Potential reduction of the in-plane properties transverse to the line of stitching was also evaluated. Efforts have been made to correlate the experimental results with theoretical micro-mechanics predictions. Changes in deformation mechanism and failure sequences in terms of fiber architecture will be discussed.

Shin, E. Eugene↗
DOE OSTI2026

Physics insights from a large-scale 2D UEDGE simulation database for detachment control in KSTAR

A large-scale database of two-dimensional UEDGE simulations has been developed to study detachment physics in KSTAR and to support surrogate models for control applications. Nearly 70 000 steady-state solutions were generated, systematically scanning upstream density, input power, plasma current, impurity fraction, and anomalous transport coefficients, with magnetic and electric drifts across the magnetic field included. The database identifies robust detachment indicators, with strike-point electron temperature at detachment onset consistently T e,target ~ 3-4 eV, largely insensitive to upstream conditions. Scaling relations reveal weaker impurity sensitivity than one-dimensional models and show that heat flux widths follow Eich’s scaling only for uniform, low D and χ. Distinctive in–out divertor asymmetries are observed in KSTAR, differing qualitatively from DIII-D. Complementary time-dependent simulations quantify plasma response to gas puffing, with delays of 5 - 15 ms at the outer strike point and ∼ 40 ms for the low-magnetic-field-side radiation front. These dynamics are well captured by first-order-plus-dead-time models and are consistent with experimentally observed detachment-control behavior in KSTAR (Gupta et al 2025 Plasma Phys. Control. Fusion (submitted)).

Physics - Plasma physics↗
DOE OSTI2018

Collaborative atomic-scale design, analysis, and nanofabrication for record breaking, single-crystal Zn(x)Cd(1-x)Te solar cell arrays

Cadmium telluride (CdTe) based photovoltaics provide a viable solar energy solution because of their short payback time, low manufacturing cost, and high theoretical efficiency ~29%. However, the highest record laboratory efficiency is only 22.1% and long-term performance degradation is ~1 % per year which hinders greater economic viability. Higher open circuit voltage (Voc) and fill factor (FF) are needed to increase the efficiency of the solar cell. Cells with record energy conversion efficiencies report short current (Jsc) values close to their theoretical maximum. However, Voc and FF in these devices remain well below their anticipated optimum. These electrical parameters depend on the quality of the various layers in the solar cell. In particular they depend on the crystalline quality including the defect and impurity concentrations. Therefore understanding how defects and impurities form and evolve in the material layers is important to design devices with higher efficiency and stability. The aim of this project is to create a novel path around the fundamental barriers to achieve high open-circuit voltages (VOC ≥ 1.0 V) in CdTe/CdS solar cells. The idea of the project was to combine nanopatterned crystal growth and alloy compositional grading (with concomitant lattice parameter and energy band gap grading) to reduce the defect density and dramatically improve spatial uniformity of ZnxCd(1-x)Te/CdS cells. The lattice mismatch between ZnTe and CdS is 3.9% compared to a much larger 9.2% between CdTe and CdS. Importantly, when crystal growth is contained to the nanoscale, the strain in each layer is reduced by a factor of two due to strain partitioning and 3D strain relief mechanisms that come into play. This reduces the strain in the ZnTe from 3.9% to 1.95% which is within the range of metamorphic crystal growth. In preliminary studies, molecular dynamics simulation of ZnTe/CdS islands predicted dislocation-free material when the patterning was reduced to ~80 nm in diameter. The energy band gap of ZnxCd(1-x)Te is also graded in conjunction with alloy composition. ZnTe has an energy band gap of 2.3 eV. Finally, an added benefit of patterned growth is that it enables direct one-to-one study of the relationships between fabrication, microstructure and performance of individual crystal grains within the array. Experimental characterization techniques such as atomic probe tomography (APT) and transmission electron microscopy (TEM) have elucidated much about the microstructure of the layers. However, the techniques are destructive, costly and have limitations on the information they convey. For example, TEM gives information with atomic scale resolution but on 2-dimensional substrates. On the other hand, APT gives 3-dimensional information but is not able to resolve atomic scale structure. Alternatively, Molecular Dynamics (MD) simulations offer a solution to rapidly generate time-resolved, 3-dimensional, atomic scale structures of crystal growth. Direct MD simulations of microstructures of Cu-doped II-VI compound multilayers can impact the research on CdTe/CdS solar cells. Such MD simulations require an interatomic potential database that includes at least four elements Cu, Cd, Te, and S. The Stillinger-Weber (SW) potential is the most widely used interatomic potential for semiconductors. However, while SW potentials have been developed for Ga-In-As-Se-Te, Al-Ga-In-P-As-Sb, Cd-Te-Zn-As-Si, In-Ga-N systems, no potentials existed to simulate Cd-Zn-Hg-Se-S-Te-Cu. The goal of this effort was to fill the knowledge gap by developing a Zn-Cd-Hg-S-Se-Te-Cu SW potential database to enable MD simulations of microstructures of Cu-doped CdTe/CdS solar cells. The new potential was then applied, via MD crystal growth simulations, to study the growth mechanisms and atomic structures of the ZnTe/Cu/CdTe/CdS multilayers under various conditions. The objective of the project was to inform the solar cell community on crystal growth and defect formation at the interface between CdTe-based epilayers grown on CdS substrates. MD simulations offered a unique opportunity to analyze the 3-dimensional crystal growth evolution of Cu doped ZnxCd(1-x)TeyS(1-y) alloys with atomic scale resolution under a variety of conditions. The effect of substrate orientation and polycrystallinity on crystal growth was studied. Substrates with grain boundaries were created and the growth evolution on these substrates were analyzed. Another focus was to elucidate the effect of dopant incorporation on the nature of polycrystallinity crystal growth. Dopants available through the Stillinger-Weber potential developed in this project included Cu, Zn, S, Se, Hg and native vacancies.

14 SOLAR ENERGY↗
DOE OSTI2018

A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning

Many geological materials, such as shale, mudstone, carbonate rock, limestone and rock salt are multi-porosity porous media in which pores of different scales may co-exist in the host matrix. When fractures propagate in these multi-porosity materials, these pores may enlarge and coalesce and therefore change the magnitude and the principal directions of the effective permeability tensors. The pore-fluid inside the cracks and the pores of host matrix may interact and exchange fluid mass, but the difference in hydraulic properties of these pores often means that a single homogenized effective permeability tensor field is insufficient to characterize the evolving hydraulic properties of these materials at smaller time scale. Furthermore, the complexity of the hydro-mechanical coupling process and the induced mechanical and hydraulic anisotropy originated from the micro-fracture and plasticity at grain scale also makes it difficult to propose, implement and validate separated macroscopic constitutive laws for numerical simulations. Here this article presents a hybrid data-driven method designed to capture the multiscale hydro-mechanical coupling effect of porous media with pores of various different sizes. At each scale, data-driven models generated from supervised machine learning are hybridized with classical constitutive laws in a directed graph that represents the numerical models. By using sub-scale simulations to generate database to train material models, an offline homogenization procedure is used to replace the up-scaling procedure to generate cohesive laws for localized physical discontinuities at both grain and specimen scales. Through a proper homogenization procedure that preserves spatial length scales, the proposed method enables field-scale simulations to gather insights from meso-scale and grain-scale micro-structural attributes. This method is proven to be much more computationally efficient than the classical DEM–FEM or FEM2 approach while at the same time more robust and flexible than the classical surrogate modeling approach. Due to the usage of bridging-scale technique, the proposed model may provide multiple opportunities to incorporate different types of simulations and experimental data across different length scales for machine learning. Numerical issues will also be discussed.

42 ENGINEERING↗
DOE OSTI2018

Magnetism of new metastable cobalt-nitride compounds

The search for new magnetic materials with high magnetization and magnetocrystalline anisotropy is important for a wide range of applications including information and energy processing. There is only a limited number of naturally occurring magnetic compounds that are suitable. This situation stimulates an exploration of new phases that occur far from thermal-equilibrium conditions, but their stabilization is generally inhibited due to high positive formation energies. Here a nanocluster-deposition method has enabled the discovery of a set of new non-equilibrium Co–N intermetallic compounds. The experimental search was assisted by computational methods including adaptive-genetic-algorithm and electronic-structure calculations. Conventional wisdom is that the interstitial or substitutional solubility of N in Co is much lower than that in Fe and that N in Co in equilibrium alloys does not produce materials with significant magnetization and anisotropy. By contrast, our experiments identify new Co–N compounds with favorable magnetic properties including hexagonal Co 3 N nanoparticles with a high saturation magnetic polarization ($J_s$ = 1.28 T or 12.8 kG) and an appreciable uniaxial magnetocrystalline anisotropy ($K_1$ = 1.01 MJ m -3 or 10.1 Mergs per cm 3 ). This research provides a pathway for uncovering new magnetic compounds with computational efficiency beyond the existing materials database, which is significant for future technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗