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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Hydrogeological Interpretation of Candidate Origin Sites for Martian Meteorite ALH84001

Barlow (this meeting) has identified two potential source craters for the martian meteorite ALH84001. The craters are at 11.7 deg S, 243.3 deg W (Mare Tyrrhenum site) and 14.0 deg S, 343.5 deg W (Sinus Sabaeus site). As noted by Barlow, both craters lie in the heavily cratered terrain (HCT) and are adjacent to fluvial valleys, Here I explore the fluvial history of these areas based upon the surrounding valley morphology. The most prominent valley network at the Sabaeus site is Evros Vallis. This wide, flat-floored valley is approximately 600 km long with an average width of 2.5 km and a depth of 220 m. The eroded volume of the entire Evros network is approximately 6 x 10(exp 11) cc. This is typical for networks located in the heavily cratered terrain (e.g. Warrego and Parana Valles). Evros is also an isolated valley system. No similar networks are found in the surrounding terrain. Thus it is unlikely that Evros formed as a result of widespread rainfall. A localized water source, such as discharge of a hydrothermal system or localized melting of snowfall, seems more consistent Previous modeling has demonstrated that only hydrothermal systems associated with high permeability subsurfaces can discharge sufficient water to form a valley network. The bulk of the discharge from such systems is consequently low temperature, slightly heated water Precipitation of calcium carbonate by low temperature fluids is consistent with most interpretations of the geochemistry of ALH84001. Available imagery at the Tyrrhenum site is of lesser quality. While eroded units of the HCT are nearby, there are no comparable well developed valley networks at this site. Erosion is instead manifested predominantly as gullies on slopes. This style of erosion suggests that water was not present at this site for the length of time as at the more integrated Sabaeus site. The superposition of fluidized ejecta blankets suggests however that ground water or ground ice was still present at this locality fairly recently, if the chosen crater is indeed correct.

Gulick, Virginia C.↗
NASA NTRS2019

Simulation-Based Assessment of a Full-Scale Installed Quiet Landing Gear

Full-scale simulations of a Gulfstream G-III aircraft, performed in support of the NASA Acoustic Research Measurements flights, are presented to complement results discussed in earlier studies. The flow solver employed in those studies, Dassault Systèmes’ lattice Boltzmann PowerFLOW®, was also used during this investigation to conduct time-dependent simulations of the entire aircraft in landing configuration with a fully dressed landing gear. The high-fidelity simulations, performed at a Mach number of 0.23 and a Reynolds number of 10.5 × 106 based on mean aerodynamic chord, captured all relevant airframe noise sources. The computations were used to assess the aeroacoustic performance of the main landing gear, with and without noise reduction fairings installed, of a G-III aircraft equipped with Adaptive Compliant Trailing Edge technology and conventional Fowler flaps. To facilitate comparison of predicted noise signatures with effective perceived noise levels obtained from flight test measurements, the “as-flown” nose landing gear geometry, missing in our earlier studies, was added to the simulated G-III aircraft configurations. The high fidelity, synthetic data were post-processed using a Ffowcs-Williams and Hawkings integral approach to estimate farfield acoustic behavior, with pressures on the model solid surface or pressure and velocity components on a permeable surface enveloping the acoustic near field used as input.

Duda, Benjamin↗
NASA NTRS2023

An Evaluation of A Physics-Based Firn Model and A Semi-Empirical Firn Model Across the Greenland Ice Sheet (1980–2020)

The Greenland Ice Sheet's (GrIS) firn layer buffers the ice sheet's contribution to sea level rise by storing meltwater in its pore space. However, available pore space and meltwater retention capability is lost due to ablation of the firn layer and refreezing of meltwater as near-surface ice slabs in the firn. Understanding how firn properties respond to climate is important for constraining the GrIS's future contribution to sea level rise in a warming climate. Observations of firn density provide detailed information about firn properties, but they are spatially and temporally limited. Here we use two firn models, the physics-based SNOWPACK model and the Community Firn Model configured with a semi-empirical densification equation (CFM-GSFC), to quantify firn properties across the GrIS from 1980 through 2020. We use an identical forcing (Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) atmospheric reanalysis) for SNOWPACK and the CFM-GSFC in order to isolate firn model differences. To evaluate the models, we compare simulated firn properties, including firn air content (FAC), to measurements from the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset of snow and firn density. Both models perform well (mean absolute percentage errors of 14 % in SNOWPACK and 16 % in the CFM-GSFC), though their performance is hindered by the spatial resolution of the atmospheric forcing. In the ice-sheet-wide simulations, the 1980–1995 average spatially integrated FAC (i.e., air volume in the firn) for the upper 100 m is 34 645 km 3 from SNOWPACK and 28 581 km 3 from the CFM-GSFC. The discrepancy in the magnitude of the modeled FAC stems from differences in densification with depth and variations in the sensitivity of the models to atmospheric forcing. In more recent years (2005–2020), both models simulate substantial depletion of pore space. During this period, the spatially integrated FAC across the entire GrIS decreases by 3.2 % (−66.6 km 3 yr −1 ) in SNOWPACK and 1.5 % (−17.4 km 3 yr −1 ) in the CFM-GSFC. These differing magnitudes demonstrate how model differences propagate throughout the FAC record. Over the full modeled record (1980–2020), SNOWPACK simulates a loss of pore space equivalent to 3 mm of sea level rise buffering, while the CFM-GSFC simulates a loss of 1 mm. The greatest depletion in FAC is along the margins and especially along the western margin where observations and models show the formation of near-surface, low-permeability ice slabs that may inhibit meltwater storage.

Megan Thompson-Munson↗
DOE OSTI2020

Analysis of Hydraulic Fracturing on the 4100 Level at the Sanford Underground Research Facility

A series of hydrofractures were performed on the 4100 ft. level of the Sanford Underground Research Facility (SURF) to quantify the minimum principal stress and stress orientation. The motivation for this work was to determine the suitability of the site as a second testbed for the EGS Collab project and to inform the testbed design. EGS Collab is a meso-scale project where experiments are being performed to increase permeability in low-permeability rock and improve our understanding of appropriate techniques and models required for developing enhanced geothermal systems. In order to design the second testbed, a ~50 m vertical HQ (96 mm) pilot borehole was drilled in June, 2019, to perform a series of mini-frac tests to determine rock stress state. Utilizing an elastic model based on the ISIP (Instantaneous Shut In Pressure), testing indicates that the minimum principal stress is 20.4 MPa oriented NNE (24°) and plunges at an angle of approximately 28°.

Ingraham, Mathew↗
DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are exploring hidden geothermal resources in the U.S.A. and designing profitable enhanced geothermal systems (EGS). Many processes and parameters control geothermal exploration and energy production from geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize subsurface geothermal conditions. Sparse and multi-scale characteristics of these datasets prohibit properly leveraging these datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) promise to resolve these issues. The tremendous challenges and risks of geothermal exploration and production bring the demand for novel ML methods and tools that can (1) analyze large field datasets, (2) assimilate model simulations (large inputs and outputs), (3) process sparse datasets, (4) perform transfer learning (between sites with different exploratory levels), (5) extract hidden geothermal signatures in the field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. To address these necessities, ML-based geothermal resources exploration and enhanced geothermal systems (EGS) design tools have been developed. The exploration tool is called GeoThermalCloud and EGS design tool is called GeoDT-ML. GeoThermalCloud (https://github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. Also, it enables the identification of critical measurements needed to identify geothermal resource signatures. Alternatively, GeoDT-ML (https://github.com/SmartTensors/GeoThermalCloud.jl/tree/master/EGS) is an ML-based alternative to GeoDT (https://github.com/GeoDesignTool/GeoDT.git), a fast, simplified multi-physics solver to evaluate EGS project designs in uncertain geologic systems. GeoDT-ML leverages recent advances in deep learning and high-performance computing. It is a faster and simpler version of GeoDT. To make this project a success, we used capabilities of LANL, PNNL, Google, Stanford, and Julia Computing. We analyzed eight datasets of the U.S.A. using GeothermalCloud and demonstrated potential highly prospective geothermal resources and identified key factors defining highly prospective sites. The first data set includes 44 locations in southwest New Mexico and 18 geological, hydrogeological, geophysical, geothermal, geochemical attributes. We defined low- and medium-temperature hydrothermal systems and discovered a new highly prospective site. The second data set analyzed 18 shallow water chemistry attributes at 14,342 locations in the Great Basin. It demarcated modestly, moderately, and highly prospective sites including key attributes for each type of prospectivity. The third data set analyzed Utah FORGE data including satellite (InSAR), geophysical (gravity, seismic), geochemical, and geothermal attributes. Here, we performed prospectivity analysis to identify future drilling locations using geological, geochemical, and geophysical attributes. Maps of temperature at depth and heat flow are constructed based on the available data. Prospectivity maps were generated, and drilling locations were proposed for future geothermal field exploration. The fourth data set analyzed 21 attributes at 120 locations in Tularosa Basin, New Mexico; data comes from past play fairway analyses in this region. ML analyses identified geothermal signatures associated with modestly, moderately, and highly hydrothermal systems. We also defined dominant attributes and spatial distribution of the geothermal signatures. The fifth, sixth, seventh, and eighth datasets include Tohatchi Springs, New Mexico, Hawaii, Brady site, Nevada, and EGS Collab, respectively. Moreover, we coupled GeothermalCloud and magnetotellurics data to pinpoint drilling locations for developing geothermal projects in the Tularosa Basin, New Mexico. GeothermalCloud found potential prospective locations for geothermal resources near White Sands Missile Range and McGregor Range at Fort Bliss. Magnetotellurics data determined the potential depth (~1800m) of geothermal prospects at McGregor Range based on apparent resistivity structures/layers in the subsurface. The McGregor Range consists of three resistivity layers and two resistivity structures. Magnetotellurics data also helps identify that the western portion of the McGregor Range has thick and low-resistivity earth materials. The low resistivity to the west is most likely for a fault system. Assuming temperature is consistent with a geothermal reservoir, the west-central part of the McGregor Range has the highest geothermal potential because of the increase in porosity and associated permeability attributed to the interpreted fault system. Also, we devised a coupling strategy between a process model and GeothermalCloud to characterize hydrogeological conditions and geothermal conditions, respectively. The process model characterizes hydrogeological and geothermal conditions on highly prospective geothermal sites provided by GeothermalCloud. We developed a physics-informed neural network (PINN) version of the Burns equation that can be easily coupled with GeothermalCloud. Furthermore, we performed an optimal design decision maximizing the economic value of an EGS power plant. This study optimized the range of well spacing between injection and production wells maximizing net present value in dollars (NPV). For this task, we used the GeoDT to simulate the Utah FORGE EGS development cycle from the initial well design to the end of production. Next, we accomplished another crucial task, which is predicting permeability of geothermal reservoirs. Predicting permeability of geothermal reservoirs is a non-trivial task because of huge computational runtime of simulation and lack of measurements. To avoid these limitations, we used easy-to-measure chemical concentrations in the subsurface as measurement data and convolutional neural network based ML model of a high-fidelity model. Next, we predicted permeability using Markov chain Monte Carlo simulation. We found that Markov chain Monte Carlo simulation predicts permeability with a high certainty if the prediction zone in the simulation area has chemical concentration data. Finally, we analyzed the DOE funded INGENIOUS and GeoDAWN projects data. For discovering hidden geothermal systems in the Great Basin, the INGENIOUS project accumulated old data, collected new data, and released them in 2022. The dataset includes a total of 24 geological, geophysical, and geochemical attributes. Data resolution and scale significantly vary prohibiting an appropriate usage. To avoid such limitations, we brought all data in the same resolution and scale by applying the inverse distance weighting interpolation technique for predicting data in unsampled locations. Subsequently, we analyzed LiDAR data of the GeoDAWN project. We received data in tiles format. The DOE’s overarching goal is to use ML on LiDAR data for finding favorable geological structures (e.g., step up faults in Brady, Nevada). To serve the purpose, we need to label favorable geologic structures that correspond to LiDAR data. We wrote an algorithm to label the LiDAR data with the favorable geologic structures.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Transient evolution of permeability and friction in a slowly slipping fault activated by fluid pressurization

The mechanisms of permeability and friction evolution in a natural fault are investigated in situ. During three fluid injection experiments at different places in a fault zone, we measured simultaneously the fluid pressure, fault displacements and seismic activity. Changes in fault permeability and friction are then estimated concurrently. Results show that fault permeability increases up to 1.58 order of magnitude as a result of reducing effective normal stress and cumulative dilatant slip, and 19-to-60.8% of the enhancement occurs without seismic emissions. When modeling the fault displacement, we found that a rate-and-state friction and a permeability dependent on both slip and slip velocity together reasonably fit the fault-parallel and fault-normal displacements. This leads to the conclusion that the transient evolution of fault permeability and friction caused by a pressure perturbation exerts a potentially dominant control on fault stability during fluid flow.

58 GEOSCIENCES↗
NASA NTRS1991

A Martian global groundwater model

A global groundwater flow model was constructed for Mars to study hydrologic response under a variety of scenarios, improving and extending earlier simple cross sectional models. The model is capable of treating both steady state and transient flow as well as permeability that is anisotropic in the horizontal dimensions. A single near surface confining layer may be included (representing in these simulations a coherent permafrost layer). Furthermore, in unconfined flow, locations of complete saturation and seepage are determined. The flow model assumes that groundwater gradients are sufficiently low that DuPuit conditions are satisfied and the flow component perpendicular to the ground surface is negligible. The flow equations were solved using a finite difference method employing 10 deg spacing of latitude and longitude.

Howard, Alan D.↗
DOE OSTI2023

Simulation toolkit for digital material characterization of large image-based microstructures

In this paper, an efficient image-based simulation toolkit for material characterization is presented, which is scalable to work from personal computers to workstations. The effective thermal conductivity, elasticity, and permeability are evaluated employing a computational homogenization framework based on the Finite Element Method (FEM). Two complementary open-source packages are presented: one developed in Python, which can convert digital images into voxel meshes (pyTomoviewer); the other developed in Julia, that can run numerical simulations to compute effective material properties (chpack). Also, a CUDA C version of chpack is provided (chfem_gpu). They were designed to deal with large multi-phase models, so strategies were devised to minimize their memory footprint, while avoiding a high toll on execution time. The voxel-based approach significantly simplifies the FEM meshes and allows efficient matrix-free implementations. In that sense, to handle large linear systems of equations, the element-by-element (EBE) technique is adopted, in conjunction with a low-memory implementation of the Preconditioned Conjugate Gradient (PCG) method. Finally, the code was thoroughly tested on an artificial geometry made of a square array of cylinders, for which analytical solutions exist, as well as on a real micro-tomographic reconstruction of FiberForm TM , a carbon preform commonly used in thermal protection systems.

36 MATERIALS SCIENCE↗
NASA NTRS1992

An infiltration/cure model for manufacture of fabric composites by the resin infusion process

A 1-D infiltration/cure model was developed to simulate fabrication of advanced textile composites by the resin film infusion process. The simulation model relates the applied temperature and pressure processing cycles, along with the experimentally measured compaction and permeability characteristics of the fabric preforms, to the temperature distribution, the resin degree of cure and viscosity, and the infiltration flow front position as a function of time. The model also predicts the final panel thickness, fiber volume fraction, and resin mass for full saturation as a function of compaction pressure. Composite panels were fabricated using the RTM (Resin Transfer Molding) film infusion technique from knitted, knitted/stitched, and 2-D woven carbon preforms and Hercules 3501-6 resin. Fabric composites were fabricated at different compaction pressures and temperature cycles to determine the effects of the processing on the properties. The composites were C-scanned and micrographed to determine the quality of each panel. Advanced cure cycles, developed from the RTM simulation model, were used to reduce the total cure cycle times by a factor of 3 and the total infiltration times by a factor of 2.

Weideman, Mark H.↗
NASA NTRSDate not supplied

Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 3 - Aerodynamic Validation and Noise Source Identification

Wind tunnel test data were used to validate the predicted aerodynamic behavior of a 15%-scale version of a generic, low-boom aircraft. The test was conducted in the NASA Langley 14- by 22-Foot Subsonic Tunnel to determine the low-speed aerodynamic characteristics of the model. Measured steady surface pressures and global forces were used to validate predicted aerodynamic results obtained from high-fidelity simulations of the model as installed in the tunnel. Very good agreement between predicted and measured aerodynamic trends was demonstrated, providing the impetus to proceed with companion airframe noise simulations that were conducted in a free-air setting. Computed near-field flow variables acquired on a permeable data surface were used to generate synthetic pressure records for two 800-element phased microphone arrays positioned overhead and to the side of the model. The array data were beamformed to generate noise source localization maps for the clean model and several landing configurations. Primary and secondary airframe sources were identified and their relative strengths were determined. Far-field integrated noise spectra for the full aircraft, as well as individual components, were obtained from the source maps via integration of tailored regions. The analysis showed that noise produced by the landing gear was the dominant contributor to the far-field acoustic signature of the model, followed by flap noise. The effects of permeable data surface end caps, spatial resolution, array orientation, angle of attack, component interaction, velocity scaling, and numerical precision on synthetic far-field spectra were also evaluated.

low boom↗
DOE OSTI2021

Precambrian Crystalline Basement Properties From Pressure History Matching and Implications for Induced Seismicity in the US Midcontinent

Injection-induced seismicity across the US midcontinent has almost exclusively occurred in the crystalline basement that underlies the Arbuckle Group aquifer and its equivalents, the primary wastewater disposal zone in this region. However, the properties of the basement are not well known. Newly compiled data, from Class I wells in Kansas, provide a unique record of pressures in the Arbuckle and an opportunity to constrain the reservoir-scale properties of the basement such as permeability, diffusivity, and specific storage. Constraints on these parameters are critical for modeling fluid flow and pressures across the entire Arbuckle-basement system, and are necessary for accurate evaluation and prediction of injection-induced earthquakes. Here, we present a detailed, three-dimensional geological and pressure history-matched numerical model for the Arbuckle and basement, based on data from >400 wells covering a large region in south-central Kansas, where injection-induced seismicity has been concentrated since 2014. Simulations of dynamic data from 319 wells indicate that Arbuckle pressures have increased by 1.1 MPa in high injection rate areas and an overpressure of <0.1 MPa may be the cause of seismicity in the basement. Pressure-history matching also yields the likely range in porosity (0.3%–7%), permeability (0.1–0.7 mD), and diffusivity (0.004–0.07 m2 /s) for the basement. The resulting estimates suggest reservoir-scale properties of the basement are enhanced by faults and fractures. Importantly, the diffusivities determined in this study are lower than estimates derived from Kansas earthquake triggering fronts, and suggest that such seismicity-based techniques may have limitations, particularly where spacetime patterns between injection and seismicity are complex.

58 GEOSCIENCES↗
DOE OSTI2025

Molecular Modeling and Molecular Dynamics Simulation of a Packed and Intact Bacterial Microcompartment

Bacterial microcompartments (BMCs) are protein-bound organelles found in some bacteria which encapsulate enzymes for enhanced catalytic activity. These compartments spatially sequester enzymes within semipermeable shell proteins and are packed full of enzyme cargoes and metabolites as they fulfill their function. Coupling together recent SAXS and proteomics work, it is possible to develop molecular models for these microcompartments and interrogate enzyme and metabolite dynamics within. Our primary goal of this study is to quantify the permeability of metabolite glyceraldehyde-3-phosphate (G3P) and dihydroxyacetone phosphate (DHAP) across the BMC shell through classical molecular dynamics simulation. The Haliangium ochraceum model of BMC shell (PDB: 6MZX) was used to model an intact BMC of approximately 10 million atoms. Working at this scale presented its own challenges in managing large data sets, with multiple challenges and hardware advances discussed that facilitated this work. Over approximately 750 ns of aggregate simulation, we see multiple permeation events for these metabolites that were added at high concentration through the pores present within BMC shell tiles. When compared to independent permeability estimates for the same metabolites determined through replica exchange umbrella sampling simulations, the permeabilities varied by approximately 3 orders of magnitude. Regardless, the permeability coefficients for both G3P and DHAP are highly similar and very high, such that only very small concentration gradients can be maintained across the BMC shell between the cytosol and BMC interior. The large simulation systems also facilitated comparisons for molecular diffusivity in the crowded environment within the BMC shell. By our estimates, the viscosity within a packed BMC shell is at least 10-fold higher than it would be in neat solution and is the real driver for varying permeability estimates we obtained through simulation. These findings will be used as design inputs for future bioengineering efforts to make products from BMCs, highlighting how permeable BMC shells can be.

Diffusion↗
DOE OSTI2020

Operational and geological controls of coupled poroelastic stressing and pore-pressure accumulation along faults: Induced earthquakes in Pohang, South Korea

Coupled poroelastic stressing and pore-pressure accumulation along pre-existing faults in deep basement contribute to recent occurrence of seismic events at subsurface energy exploration sites. Our coupled fluid-flow and geomechanical model describes the physical processes inducing seismicity corresponding to the sequential stimulation operations in Pohang, South Korea. Simulation results show that prolonged accumulation of poroelastic energy and pore pressure along a fault can nucleate seismic events larger than M w 3 even after terminating well operations. In particular the possibility of large seismic events can be increased by multiple-well operations with alternate injection and extraction that can enhance the degree of pore-pressure diffusion and subsequent stress transfer through a rigid and low-permeability rock to the fault. This study demonstrates that the proper mechanistic model and optimal well operations need to be accounted for to mitigate unexpected seismic hazards in the presence of the site-specific uncertainty such as hidden/undetected faults and stress regime.

58 GEOSCIENCES↗
NASA NTRS1983

Influence of wall permeability on turbulent boundary-layer properties

Experimental boundary-layer studies of a series of low pressure drop, permeable surfaces have been conducted to characterize their surface interaction with a turbulent boundary layer. The models were flat and tested at nominally zero pressure gradient in low speed air. The surfaces were thin metal sheets with discrete perforations. Direct drag balance measurements of skin friction indicate that the general effect of surface permeability is to increase drag above that of a smooth plate reference level. Heuristic arguments are presented to show that this type of behavior is to be expected. Other boundary-layer data are also presented including mean velocity profiles and conditionally sampled streamwise velocity fluctuations (hot wire) for selected models.

Wilkinson, S. P.↗
DOE OSTI2026

Proton Conducting Silicon Oxide Membranes as a Fluorine Free Alternative to Nafion for Low Temperature Water Electrolysis

Driven by environmental and health concerns related to per- and polyfluoroalkyl substances (PFAS), there has been growing interest in developing fluorine-free proton (H + ) exchange membrane (PEM) materials for fuel cells and water electrolyzers. In this study, we present a side-by-side comparison of the key transport properties of submicron thick, PFAS-free amorphous silicon dioxide (SiO 2 ) membranes to Nafion, a fluorinated polymer electrolyte membrane that represents the industry standard for PEM fuel cells and electrolyzers. Here, measurements of proton (H + ) conductivity (σ H + ), hydrogen (H 2 ) permeability (P H 2 ), and electrical resistivity (ρ e – ) were conducted using model thin films comprised of SiO 2 membranes deposited by atomic layer deposition (ALD). Although the H + conductivity of the SiO 2 membranes is 2–3 orders of magnitude lower than Nafion, the addition of phosphorus dopants (PO x ) improves H + conductivity such that the area specific membrane resistance of thin (<50 nm) PO x -doped SiO 2 membranes is more than an order of magnitude lower than Nafion-117. Importantly, the safe operation of such nanoscale membranes within a PEM electrolyzer is feasible thanks to the low H 2 permeability of dense SiO 2 -based membranes, which are predicted to limit H 2 crossover rates to acceptable levels for pressures up to ≈ 100 bar. As a proof-of-principle demonstration, a chip-scale water electrolyzer based on 100 nm thick PO x -SiO 2 membrane is shown to achieve a current density of 2 A cm –2 at a potential of 2.5 V. If this technology can be successfully scaled up, H + conducting oxide membranes offer an attractive PFAS-free alternative to Nafion for efficient and durable water electrolysis and fuel cell technologies.

Nafion↗
DOE OSTI2022

Three-Dimensional Permeability of Thick-Section Glass Fabric Reinforced Polymer Composite by Vacuum-Assisted Resin Infusion Molding

Abstract Determination of permeability of thick-section glass fabric preforms with fabric layers of different architectures is critical for manufacturing large, thick composite structures with complex geometry, such as wind turbine blades. The thick-section reinforcement permeability is inherently three-dimensional and needs to be obtained for accurate composite processing modeling and analysis. Numerical simulation of the liquid stage of vacuum-assisted resin infusion molding (VARIM) is important to advance the composite manufacturing process and reduce processing-induced defects. In this research, the 3D permeability of thick-section E-glass fabric reinforcement preforms is determined, and the results are validated by a comparison between flow front progressions from experiments and from numerical simulations using ansys fluent software. The orientation of the principal permeability axes were unknown prior to experiments. The approach used in this research differs from those in literature in that the through-thickness permeability is determined as a function of flow front positions along the principal axes and the in-plane permeabilities and is not dependent on the inlet radius. The approach was tested on reinforcements with fabric architectures which vary through-the-thickness direction, such as those in a spar cap of a wind turbine blade. The computational simulations of the flow-front progression through-the-thickness were consistent with experimental observations.

Engineering↗
DOE OSTI2021

Gas transport characteristics of supramolecular networks of metal-coordinated highly branched Poly(ethylene oxide)

Model systems are developed and investigated to better understand the effect of polyether-metal ion interactions on gas separation characteristics. These systems help answer current questions raised by the substantial body of research on metal-organic frameworks (MOFs) dispersed in polyethers to improve gas separation performance, where favorable interactions between the metal centers and polyethers are preferred to improve interfacial compatibility. Specifically, we investigate CO 2 /gas transport properties of supramolecular networks comprising cross-linked poly(ethylene oxide) (XLPEO) and dissociable salts, including LiClO 4 , Ni(BF 4 ) 2 , and Cu(BF 4 ) 2 . Increasing the salt content increases the glass transition temperature (T g ) and generally decreases gas diffusivity and permeability, which can be successfully described using a T g -integrated free volume model with an expression similar to the Vogel-Tammann-Fulcher (VTF) equation. Surprisingly, low loadings of LiClO 4 and Cu(BF 4 ) 2 (2 mass% or less) can increase gas permeability by 30%–70% without affecting the CO 2 /gas selectivity. This increase correlates with polyether-metal ion dynamics as measured by dielectric spectroscopy. Understanding how interaction-mediated dynamics affect gas transport will be instrumental to designing MOF-based mixed matrix materials for gas separations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Encapsulation of highly viscous CO 2 capture solvents for enhanced capture kinetics: Modeling investigation of mass transfer mechanisms

The encapsulation of highly viscous liquid-like Nanoparticle Organic Hybrid Materials (NOHMs) inside a gas permeable polymer to form SIPs (Solvent Impregnated Polymers) significantly enhanced the CO 2 capture kinetics of NOHMs, leading to a remarkable 50-fold increase in CO 2 flux compared to the neat NOHMs. To understand the mechanism for enhanced CO 2 mass transfer within these hybrid materials, kinetic modeling of CO 2 uptake into SIPs containing polyethylenimine functionalized NOHMs, denoted NPEI-SIP, was conducted. CO 2 mass transfer into NPEI-SIP films was found to conform, both qualitatively and quantitatively, with a diffusion-controlled moving front model. The diffusion-controlled model was also used to simulate CO 2 uptake within a fixed bed containing polydisperse NPEI-SIP particles, and this model accurately predicted experimentally measured breakthrough curves at 25 °C and 50 °C. The 50-fold increase in gas flux was shown to be a consequence of the very large CO 2 permeability within the polymer–solvent composite. Furthermore, the increase in gas flux is also dependent on the diffusion–reaction regime in which the chemical solvent operates, and the largest improvement will occur when immobilizing solvents, such as NOHMs, which operate in the instantaneous-reaction regime. The CO 2 capacity (~3 mol CO 2 /kg) and saturation time (~5 min) of 430 μm SIP particles were comparable to popular CO 2 chemisorption materials such as amine grafted silicates, in spite of the slow kinetics of NOHM-I-PEI in liquid form (CO 2 saturation time ~24 h for a 1 mm thin film).

36 MATERIALS SCIENCE↗