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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Progress towards an Optimization Methodology for Combustion-Driven Portable Thermoelectric Power Generation Systems

Enormous military and commercial interests exist in developing quiet, lightweight, and compact thermoelectric (TE) power generation systems. This paper investigates design integration and analysis of an advanced TE power generation system implementing JP-8 fueled combustion and thermal recuperation. Design and development of a portable TE power system using a JP-8 combustor as a high temperature heat source and optimal process flows depend on efficient heat generation, transfer, and recovery within the system are explored. Design optimization of the system required considering the combustion system efficiency and TE conversion efficiency simultaneously. The combustor performance and TE sub-system performance were coupled directly through exhaust temperatures, fuel and air mass flow rates, heat exchanger performance, subsequent hot-side temperatures, and cold-side cooling techniques and temperatures. Systematic investigation of this system relied on accurate thermodynamic modeling of complex, high-temperature combustion processes concomitantly with detailed thermoelectric converter thermal/mechanical modeling. To this end, this work reports on design integration of systemlevel process flow simulations using commercial software CHEMCADTM with in-house thermoelectric converter and module optimization, and heat exchanger analyses using COMSOLTM software. High-performance, high-temperature TE materials and segmented TE element designs are incorporated in coupled design analyses to achieve predicted TE subsystem level conversion efficiencies exceeding 10%. These TE advances are integrated with a high performance microtechnology combustion reactor based on recent advances at the Pacific Northwest National Laboratory (PNNL). Predictions from this coupled simulation established a basis for optimal selection of fuel and air flow rates, thermoelectric module design and operating conditions, and microtechnology heat-exchanger design criteria. This paper will discuss this simulation process that leads directly to system efficiency power maps defining potentially available optimal system operating conditions and regimes. This coupled simulation approach enables pathways for integrated use of high-performance combustor components, high performance TE devices, and microtechnologies to produce a compact, lightweight, combustion driven TE power system prototype that operates on common fuels.

Heat Transfer↗
DOE OSTI2014

Phenomenological model of photoluminescence degradation and photoinduced defect formation in silicon nanocrystal ensembles under singlet oxygen generation

We propose a phenomenological model to explain photoluminescence degradation of silicon nanocrystals under singlet oxygen generation in gaseous and liquid systems. The model considers coupled rate equations, which take into account the exciton radiative recombination in silicon nanocrystals, photosensitization of singlet oxygen generation, defect formation on the surface of silicon nanocrystals as well as quenching processes for both excitons and singlet oxygen molecules. The model describes well the experimentally observed power law dependences of the photoluminescence intensity, singlet oxygen concentration, and lifetime versus photoexcitation time. The defect concentration in silicon nanocrystals increases by power law with a fractional exponent, which depends on the singlet oxygen concentration and ambient conditions. The obtained results are discussed in a view of optimization of the photosensitized singlet oxygen generation for biomedical applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Conformal freeze-in, composite dark photon, and asymmetric reheating

Large classes of dark sector models feature mass scales and couplings very different from the ones we observe in the Standard Model (SM). Moreover, in the freeze-in mechanism, often employed by the dark sector models, it is also required that the dark sector cannot be populated during the reheating process like the SM. This is the so called asymmetric reheating. Such disparities in sizes and scales often call for dynamical explanations. In this paper, we explore a scenario in which slow evolving conformal field theories (CFTs) offer such an explanation. Building on the recent work on conformal freeze-in (COFI), we focus on a coupling between the Standard Model Hypercharge gauge boson and an anti-symmetric tensor operator in the dark CFT. We present a scenario which dynamically realizes the asymmetric reheating and COFI production. With a detailed study of dark matter production, and taking into account limits on the dark matter (DM) self-interaction, warm DM bound, and constraints from the stellar evolution, we demonstrate that the correct relic abundance can be obtained with reasonable choices of parameters. The model predicts the existence of a dark photon as an emergent composite particle, with a small kinetic mixing also determined by the CFT dynamics, which correlates it with the generation of the mass scale of the dark sector. At the same time, COFI production of dark matter is very different from those freeze-in mediated by the dark photon. This is an example of the physics in which a realistic dark sector model can often be much richer and with unexpected features.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

A Co-Design Study Of Fusion Whole Device Modeling Using Code Coupling

Complex workflows consisting of multiple simulation and analysis codes running concurrently through in-memory coupling is becoming popular due to inherent advantages in online management of large-scale data, resilience, and the code development process. However, orchestrating such a multi-application workflow to efficiently utilize resources on a heterogeneous architecture is challenging. In this paper, we present our results with running the Fusion Whole Device Modeling benchmark workflow on Summit, a pre-exascale supercomputer at Oak Ridge National Laboratory. We explore various resource distribution and process placement mechanisms, including sharing compute nodes between processes from separate applications. We show that fine-grained process placement can have a significant impact towards efficient utilization of the compute power of a node on Summit, and conclude that sophisticated tools for performing co-design studies of multi-application workflows can play an important role towards efficient orchestration of such workflows.

Choi, Jong Youl↗
NASA NTRS2006

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
DOE OSTI2013

Microstructure and Property Evolution in Advanced Cladding and Duct Materials Under Long-Term Irradiation at Elevated Temperature: Critical Experiments

The in-service degradation of reactor core materials is related to underlying changes in the irradiated microstructure. During reactor operation, structural components and cladding experience displacement of atoms by collisions with neutrons at temperatures at which the radiation-induced defects are mobile, leading to microstructure evolution under irradiation that can degrade material properties. At the doses and temperatures relevant to fast reactor operation, the microstructure evolves by microchemistry changes due to radiation-induced segregation, dislocation loop formation and growth, radiation induced precipitation, destabilization of the existing precipitate structure, as well as the possibility for void formation and growth. These processes do not occur independently; rather, their evolution is highly interlinked. Radiation-induced segregation of Cr and existing chromium carbide coverage in irradiated alloy T91 track each other closely. The radiation-induced precipitation of Ni-Si precipitates and RIS of Ni and Si in alloys T91 and HCM12A are likely related. Neither the evolution of these processes nor their coupling is understood under the conditions required for materials performance in fast reactors (temperature range 300-600°C and doses to 200 dpa and beyond). Further, predictive modeling is not yet possible, as models for microstructure evolution must be developed along with experiments to characterize these key processes and provide tools for extrapolation. To extend the range of operation of nuclear fuel cladding and structural materials in advanced nuclear energy and transmutation systems to that required for the fast reactor, the irradiation-induced evolution of the microstructure, microchemistry, and the associated mechanical properties at relevant temperatures and doses must be understood. This project builds upon joint work at the proposing institutions, under a NERI-C program that is scheduled to end in September, to understand the effects of radiation on these important materials. The objective of this project is to conduct critical experiments to understand the evolution of microstructural and microchemical features (loops, voids, precipitates, and segregation) and mechanical properties (hardening and creep) under high temperature and full dose range radiation, including the effect of differences in the initial material composition and microstructure on the microstructural response, including key questions related to saturation of the microstructure at high doses and temperatures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Development and evaluation of a variably saturated flow model in the global E3SM Land Model (ELM) version 1.0

Abstract. Improving global-scale model representations of near-surface soil moisture and groundwater hydrology is important for accurately simulating terrestrial processes and predicting climate change effects on water resources. Most existing land surface models, including the default E3SM Land Model (ELMv0), which we modify here, routinely employ different formulations for water transport in the vadose and phreatic zones. Clark et al. (2015) identified a variably saturated Richards equation flow model as an important capability for improving simulation of coupled soil moisture and shallow groundwater dynamics. In this work, we developed the Variably Saturated Flow Model (VSFM) in ELMv1 to unify the treatment of soil hydrologic processes in the unsaturated and saturated zones. VSFM was tested on three benchmark problems and results were evaluated against observations and an existing benchmark model (PFLOTRAN). The ELMv1-VSFM's subsurface drainage parameter, fd, was calibrated to match an observationally constrained and spatially explicit global water table depth (WTD) product. Optimal spatially explicit fd values were obtained for 79 % of global 1.9∘ × 2.5∘ grid cells, while the remaining 21 % of global grid cells had predicted WTD deeper than the observationally constrained estimate. Comparison with predictions using the default fd value demonstrated that calibration significantly improved predictions, primarily by allowing much deeper WTDs. Model evaluation using the International Land Model Benchmarking package (ILAMB) showed that improvements in WTD predictions did not degrade model skill for any other metrics. We evaluated the computational performance of the VSFM model and found that the model is about 30 % more expensive than the default ELMv0 with an optimal processor layout. The modular software design of VSFM not only provides flexibility to configure the model for a range of problem setups but also allows for building the model independently of the ELM code, thus enabling straightforward testing of the model's physics against other models.

58 GEOSCIENCES↗
DOE OSTI2021

Modeling heat transport processes in enhanced geothermal systems: Validation study from EGS Collab Experiment 1

Heat recovery from enhanced geothermal systems (EGS) is a complex process involving heat transport in both fracture networks and rock formations. A comprehensive understanding of and the ability to model the underlying heat transport mechanisms is important for the success of EGS but remains challenging in practice due to the generally insufficient characterization of EGS reservoirs. In the present study, we analyze an extensively monitored intermediate-scale EGS field experiment performed in a well-characterized testbed. The high-resolution, high-quality measurements from the field experiment enable the development of a high-fidelity model incorporating a well-constrained fracture network. Based on the field experiment, we investigate the complex heat transport processes in an EGS-relevant environment and validate the capability of a numerical approach in simulating these inherently coupled heat transport processes. A series of numerical simulations were performed to study the effects of different heat transport mechanisms, including thermal convection with fracture flow, thermal conduction in rock formations, and the Joule-Thomson effect. The agreement of thermal responses between field measurements and simulation results indicates that our numerical approach can appropriately model the heat transport processes pertaining to heat recovery from EGS reservoirs.

Wu, Hui↗
NASA NTRS1997

Satellite Sensed Skin Sea Surface Temperature

Quantitative predictions of spatial and temporal changes the global climate rely heavily on the use of computer models. Unfortunately, such models cannot provide the basis for climate prediction because key physical processes are inadequately treated. Consequently, fine tuning procedures are often used to optimize the fit between model output and observational data and the validation of climate models using observations is essential if model based predictions of climate change are to be treated with any degree of confidence. Satellite Sea Surface Temperature (SST) observations provide high spatial and temporal resolution data which is extremely well suited to the initialization, definition of boundary conditions and, validation of climate models. In the case of coupled ocean-atmosphere models, the SST (or more correctly the 'Skin' SST (SSST)) is a fundamental diagnostic variable to consider in the validation process. Daily global SST maps derived from satellite sensors also provide adequate data for the detection of global patterns of change which, unlike any other SST data set, repeatedly extend into the southern hemisphere extra-tropical regions. Such data are essential to the success of the spatial 'fingerprint' technique, which seeks to establish a north-south asymmetry where warming is suppressed in the high latitude Southern Ocean. Some estimates suggest that there is a greater than 80% chance of directly detecting significant change (97.5 % confidence level) after 10-12 years of consistent global observations of mean sea surface temperature. However, these latter statements should be qualified with the assumption that a negligible drift in the observing system exists and that biases between individual instruments required to derive a long term data set are small. Given that current estimates for the magnitude of global warming of 0.015 K yr(sup -1) - 0.025 K yr(sup -1), satellite SST data sets need to be both accurate and stable if such a warming trend is to be confidently detected. Some of these activities are focussed to develop and deploy instrumentation suitable for the collection of precise in situ measurements of the SSST which can be used to improve the accuracy of satellite measurements, while others develop techniques to generate improved global analyses of sea surface temperature using historical data.

Donlon, Craig↗
NASA NTRS2006

Remote Sensing and Spatial Growth Modeling Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how ozone and air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗
DOE OSTI2016

Collider study on the loop-induced dark matter mediation

Collider experiments are one of the most promising ways to constrain Dark Matter (DM) interactions. For DM couplings involving light mediators, especially for the loop-mediated interactions, a meaningful interpretation of the results requires to go beyond effective field theory. In this note we discuss the study of the magnetic dipole interacting DM, focusing on a model with anarchic dark flavor structure. By including the momentum-dependent form factors that mediate the coupling – given by the Dark Penguin – in collider processes, we study bounds from monophoton, diphoton, and non-pointing photon searches at the LHC. We also compare our results to constraints from the direct detection experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Modeling Mesoscale Processes of Scalable Synthesis

Brown University is part of the Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4), led by PNNL. The Collaboratory focuses on developing rigorous mathematical foundations for understanding and controlling fundamental mechanisms in mesoscale processes to enable scalable synthesis of complex materials, through the design of efficient modeling methods and corresponding scalable algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Field-free Magnetization Switching by Utilizing the Spin Hall Effect and Interlayer Exchange Coupling of Iridium

Magnetization switching by spin-orbit torque (SOT) via spin Hall effect represents as a competitive alternative to that by spin-transfer torque (STT) used for magnetoresistive random access memory (MRAM), as it doesn’t require high-density current to go through the tunnel junction. For perpendicular MRAM, however, SOT driven switching of the free layer requires an external in-plane field, which poses limitation for viability in practical applications. Here we demonstrate field-free magnetization switching of a perpendicular magnet by utilizing an Iridium (Ir) layer. The Ir layer not only provides SOTs via spin Hall effect, but also induce interlayer exchange coupling with an in-plane magnetic layer that eliminates the need for the external field. Such dual functions of the Ir layer allows future build-up of magnetoresistive stacks for memory and logic applications. Experimental observations show that the SOT driven field-free magnetization reversal is characterized as domain nucleation and expansion. Micromagnetic modeling is carried out to provide in-depth understanding of the perpendicular magnetization reversal process in the presence of an in-plane exchange coupling field.

Science & Technology - Other Topics↗
NASA NTRSDate not supplied

Additive Manufacturing Model-Based Process Metrics: Reduced Order Modeling of the Laser Powder Bed Fusion Process

The multi-scale and complex process of printing additively manufactured (AM) parts can have unexpected, but predictable, build conditions that result in material microstructure variability. In this work, we describe a fully parallel reduced order modeling approach that has been developed to evaluate the evolution of AM processes, termed the AM moment measure method. This method couples the known sequence of the AM process with a physically informed nearest neighbors’ calculation to map the conditions of a part-scale build. The result is a map of the build that is derived directly from build files or in-situ process monitoring sensors. The methodology and terminology of the approach will be described, and computed build maps will be calculated and compared for various laser powder bed fusion (LPBF) builds of Ti-6Al-4V. Such comparative results develop understanding of how the sequential process actions can affect the LPBF-AM build quality and microstructure variability.

Laser Powder Bed Fusion↗
DOE OSTI2023

From BEYONDPLANCK to COSMOGLOBE: Preliminary WMAP Q -band analysis

We present the first application of the COSMOGLOBE analysis framework by analyzing nine-year WMAP time-ordered observations that uses similar machinery to that of BEYONDPLANCK for the Planck Low Frequency Instrument (LFI). We analyzed only the Q-band (41 GHz) data and report on the low-level analysis process based on uncalibrated time-ordered data to calibrated maps. Most of the existing BEYONDPLANCK pipeline may be reused for WMAP analysis with minimal changes to the existing codebase. The main modification is the implementation of the same preconditioned biconjugate gradient mapmaker used by the WMAP team. Producing a single WMAP Q1-band sample requires 22 CPU-hrs, which is slightly more than the cost of a Planck 44 GHz sample of 17 CPU-hrs; this demonstrates that a full end-to-end Bayesian processing of the WMAP data is computationally feasible. In general, our recovered maps are very similar to the maps released by the WMAP team, although with two notable differences. In terms of temperature, we find a ~2 μK quadrupole difference that most likely is caused by different gain modeling, while in polarization we find a distinct 2.5 μK signal that has been previously referred to as poorly measured modes by the WMAP team. In the COSMOGLOBE processing, this pattern arises from temperature-to-polarization leakage from the coupling between the CMB Solar dipole, transmission imbalance, and sidelobes. No traces of this pattern are found in either the frequency map or TOD residual map, suggesting that the current processing has succeeded in modeling these poorly measured modes within the assumed parametric model by using Planck information to break the sky-synchronous degeneracies inherent in the WMAP scanning strategy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Ab Initio Investigation of Charge Trapping Across the Crystalline- Si -Amorphous- Si O 2 Interface

Accurate microscopic description of the charge-trapping process from semiconductor to defects in the dielectric-oxide layer is of paramount importance for understanding many microelectronic devices such as complementary metal-oxide-semiconductor (CMOS) transistors, as well as electrochemical reactions. Unfortunately, most current microscopic descriptions of such processes are based on empirical models with parameters fitted to experimental device performance results or simplified approximations like the Wentzel-Kramers-Brillouin (WKB) method. Some critical questions are still unanswered, including: What controls the charge-hopping rate, the coupling strength between the defect level to semiconductor level, or the energy difference? How does the hopping rate decay with defect-semiconductor distance? What is the fluctuation of the defect level, especially in amorphous dielectrics? Many of these questions can be answered by ab initio calculations. However, to date, there are few ab initio studies for this problem mainly due to technical challenges from atomic-structure construction to large-system calculations. Here, using the latest advances in calculation methods and codes, we study the carrier-trapping problem using density-functional theory (DFT) based on the Heyd-Scuseria-Ernzerhof (HSE) exchange correlation functional. The valence bond random-switching method is used to construct the crystalline-Si-amorphous-SiO2 (c-Si/a-SiO2) interfacial atomic structure, and the HSE yields a band offset that agrees well with experiments. The hopping rate is calculated with the Marcus theory, and the hopping-rate dependences on the gate potential and defect distances are revealed, as well as the range of fluctuation results from amorphous structural variation. We also analyze the result with the simple WKB model and find a major difference in the description of the coupling constant decay with the defect-semiconductor distance. Our results provide the ab initio simulation insights for this important carrier-trapping process for device operation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

A reaction–diffusion model for grayscale digital light processing 3D printing

We report that digital light processing (DLP) 3D printing is an additive manufacturing process that utilizes light patterns to photopolymerize a liquid resin into a solid. Due to the accuracy of modern digital micromirror devices (DMD) and recent advances in resin chemistry, it is now possible to create functionally graded structures using different light intensity values, also known as grayscale DLP (g-DLP). Different intensities of light lead to differences in the polymer crosslinking density after curing, which ultimately produces a part with gradients of material properties. However, g-DLP is a complicated process. First, the DLP printing is a highly coupled chemical and physical process that involves light propagation, chemical reactions, species diffusion, heat transfer, volume shrinkage, and changes in mechanical behaviors of the curing resin. Second, in g-DLP, light gradients create strong in plane gradients of chemical species concentrations in the curing liquid resin due to the strong dependence of light intensity on the rate of monomer crosslinking. Furthermore, light gradients through the depth create concentration gradients due to the degree of cure dependent light absorption and the use of photoabsorbers. These complex physical features of the printing process must be understood in order to properly control printing parameters such as light exposure time, printing speed, and grayscale variations to achieve accurate mechanical properties. In this paper, a photopolymerization reaction–diffusion model is developed and used in conjunction with experiments to investigate the coupled effects of light propagation, chemical reaction rates, and species diffusion during g-DLP 3D printing. The model is implemented numerically utilizing the finite difference method and simulation results are compared to experimental findings of simple printed structures. The agreement between experimental and model predictions of simple quantities of interest, such as geometric feature sizes, shows that the model can capture the overcure due to free-radical and other species diffusion during printing when grayscale patterns are employed. This model lays the groundwork for future extensions that can incorporate more complex coupled physics such as heat transfer, volume shrinkage, and material property evolution, which are critically important in utilizing g-DLP 3D printing for the fabrication of high-performance parts which excellent geometric and material property tolerances.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Structural Control on Downdip Locking Extent of the Himalayan Megathrust

Here, geologic reconstructions of the Main Himalayan Thrust in Nepal show a laterally extensive midcrustal ramp, hypothesized to form the downdip boundary of interseismic locking. Using a recent compilation of interseismic GPS velocities and a simplified model of fault coupling, we estimate the width of coupling across Nepal using a series of two-dimensional transects. We find that the downdip width of fault coupling increases smoothly from 70 to 90 km in eastern Nepal to 100–110 km in central Nepal, then narrows again in western Nepal. The inferred coupling transition is closely aligned with geologic reconstructions of the base of the midcrustal ramp in central and eastern Nepal, but in western Nepal, the data suggest that the location is intermediate between two proposed ramp locations. The result for western Nepal implies either an anomalous coupling transition that occurs along a shallowly dipping portion of the fault or that both ramps may be partially coupled and that a proposed crustal-scale duplexing process may be active during the interseismic period. We also find that the models require a convergence rate of 15.5 ± 2 mm/year throughout Nepal, reducing the geodetic moment accumulation rate by up to 30% compared with earlier models, partially resolving an inferred discrepancy between geodetic and paleoseismic estimates of moment release across the Himalaya.

58 GEOSCIENCES↗