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NASA NTRS2013

An Investigation of the Kinematic and Microphysical Control of Lightning Rate, Extent and NOX Production using DC3 Observations and the NASA Lightning Nitrogen Oxides Model (LNOM)

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to quantify the relationship between storm physics, lightning characteristics and the production of nitrogen oxides via lightning (LNOx). The focus of this study is to investigate the kinematic and microphysical control of lightning properties, particularly those that may govern LNOx production, such as flash rate, type and extent across Alabama during DC3. Prior studies have demonstrated that lightning flash rate and type is correlated to kinematic and microphysical properties in the mixed‐phase region of thunderstorms such as updraft volume and graupel mass. More study is required to generalize these relationships in a wide variety of storm modes and meteorological conditions. Less is known about the co‐evolving relationship between storm physics, morphology and three‐dimensional flash extent, despite its importance for LNOx production. To address this conceptual gap, the NASA Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection NetworkTM (NLDN) observations following ordinary convective cells through their lifecycle. LNOM provides estimates of flash rate, flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles. For this study, LNOM is applied in a Lagrangian sense to multicell thunderstorms over Northern Alabama on two days during DC3 (21 May and 11 June 2012) in which aircraft observations of NOx are available for comparison. The LNOM lightning characteristics and LNOX production estimates are compared to the evolution of updraft and precipitation properties inferred from dual‐Doppler and polarimetric radar analyses applied to observations from a nearby radar network, including the UAH Advanced Radar for Meteorological and Operational Research (ARMOR). Given complex multicell evolution, particular attention is paid to storm morphology, cell mergers and possible dynamical, microphysical and electrical interaction of individual cells when testing various hypotheses.

Carey, Lawrence↗

NASA NTRS2014

The Kinematic and Microphysical Control of Lightning Rate, Extent and NOX Production

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to quantify the relationship between storm physics, lightning characteristics and the production of nitrogen oxides via lightning (LNOx). The focus of this study is to investigate the kinematic and microphysical control of lightning properties, particularly those that may govern LNOx production, such as flash rate, type and extent across Alabama during DC3. Prior studies have demonstrated that lightning flash rate and type is correlated to kinematic and microphysical properties in the mixed-phase region of thunderstorms such as updraft volume and graupel mass. More study is required to generalize these relationships in a wide variety of storm modes and meteorological conditions. Less is known about the co-evolving relationship between storm physics, morphology and three-dimensional flash extent, despite its importance for LNOx production. To address this conceptual gap, the NASA Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection Network(TM) (NLDN) observations following ordinary convective cells through their lifecycle. LNOM provides estimates of flash rate, flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles. For this study, LNOM is applied in a Lagrangian sense to multicell thunderstorms over Northern Alabama on two days during DC3 (21 May and 11 June 2012) in which aircraft observations of NOx are available for comparison. The LNOM lightning characteristics and LNOX production estimates are compared to the evolution of updraft and precipitation properties inferred from dual-Doppler and polarimetric radar analyses applied to observations from a nearby radar network, including the UAH Advanced Radar for Meteorological and Operational Research (ARMOR). Given complex multicell evolution, particular attention is paid to storm morphology, cell mergers and possible dynamical, microphysical and electrical interaction of individual cells when testing various hypotheses.

Carey, Lawrence↗

NASA NTRS2014

Very Large Rain Drops from 2D Video Disdrometers and Concomitant Polarimetric Radar Observations

Drop size distribution (DSD) measurements using ground-based disdrometers (point measurements) have often been used to derive equations to relate radar observations to the integral rainfall parameters (Atlas et al. 1999, Bringi et al., 2003, Kozu et al., 2006, Tokay and Short, 1996, Ajayi and Owolabi, 1987, Battan, 1973). Disdrometers such as JWD, MRR and several others have a major limitation in measuring drops with equi-volume diameters (D(sub eq)) larger than 5 mm because they often rely on the velocity-diameter relationship which plateaus beyond this diameter range (Atlas et al., 1973, Gunn & Kinzer, 1949). Other disdrometers such as Parsivel also lack accuracy beyond this diameter range. The 2D video disdrometer (2DVD: Schönhuber et al., 2008) on the other hand gives drop-shape contours and velocities for each individual drop/hydrometeor falling through its sensor area; this provides a unique opportunity to study the role of very-large drops on radar measurements in particular those with polarimetric radar capability where DSDs with a significant component of very large drops may require special consideration given that the differential reflectivity and other polarimetric radar parameters including attenuation-correction methods will be sensitive to the concentrations of these large drops. A recent study on the occurrence of large drops by Gatlin et al. (2014) has compiled a large and diverse set of measurements made with the 2D video disdrometers from many locations around the globe. Some of the largest drops found in this study were 9 mm D(sub eq) and larger, and in this paper, we report on three such events, with maximum D(sub eq's) of 9.0, 9.1 and 9.7 mm, which occurred in Colorado, Northern Alabama, and Oklahoma, respectively. Detailed examination of the 2DVD data - in terms of shapes and fall velocities - has confirmed that these are fully-melted hydrometeors, although for the last case in Oklahoma, a bigger and non-fully-melted hydrometeor was also observed. All three events were also captured by polarimetric radars, namely the S-band CHILL radar operated by Colorado State University (Brunkow et al., 2000), the C-band ARMOR radar (Petersen et al., 2007) operated by University of Alabama in Huntsville, and NEXRADKVNX, operated by the US National Weather Service, respectively. For the last event, several other radar observations were also made, including two X-band radars operated by the US Dept. of Energy. Analyses of 2DVD data in conjunction with the corresponding radar observations are presented, along with some discussion on sampling issues related to the measurements of such large rain drops. The latter is addressed using maximum diameter D(sub max) measurements from 1-minute DSDs using two collocated 2DVDs for 37 events in Huntsville.

Thurai, Merhala↗

NASA NTRS2014

Manufacturing Challenges Associated with the Use of Metal Matrix Composites in Aerospace Structures

Metal Matrix Composites (MMCs) consist of a metal alloy reinforced with ceramic particles or fibers. These materials possess a very high strength to weight ratio, good resistance to impact and wear, and a number of other properties which make them attractive for use in aerospace and defense applications. MMCs have found use in the space shuttle orbiter's structural tubing, the Hubble Space Telescope's antenna mast, control surfaces and propulsion systems for aircraft, and tank armors. The size of MMC components is severely limited by difficulties encountered in joining these materials using fusion welding. Melting of the material results in formation of an undesirable phase (formed when molten Aluminum reacts with the reinforcement) which leaves a strength depleted region along the joint line. Friction Stir Welding (FSW) is a relatively nascent solid state joining technique developed at The Welding Institute (TWI) in 1991. The process was first used at NASA to weld the super lightweight external tank for the Space Shuttle. Today FSW is used to join structural components of the Delta IV, Atlas V, and Falcon IX rockets as well as NASA's Orion Crew Exploration Vehicle and Space Launch System. A current focus of FSW research is to extend the process to new materials, such as MMCs, which are difficult to weld using conventional fusion techniques. Since Friction Stir Welding occurs below the melting point of the workpiece material, this deleterious phase is absent in FSW-ed MMC joints. FSW of MMCs is, however, plagued by rapid wear of the welding tool, a consequence of the large discrepancy in hardness between the steel tool and the reinforcement material. This chapter summarizes the challenges encountered when joining MMCs to themselves or to other materials in structures. Specific attention is paid to the influence of process variables in Friction Stir Welding on the wear process characterizes the effect of process parameters (spindle speed, traverse rate, and length of joint) on the wear process. A phenomenological model of the wear process was constructed based on the rotating plug model of Friction Stir Welding. The effectiveness of harder tool materials (such as Tungsten Carbide, high speed steel, and tools with diamond coatings) to combat abrasive wear is also explored. In-process force, torque, and vibration signals are analyzed to assess the feasibility of in situ monitoring of tool shape changes as a result of wear (an advancement which would eliminate the need for off-line evaluation of tool condition during joining). Monitoring, controlling, and reducing tool wear in FSW of MMCs is essential to implementation of these materials in structures (such as launch vehicles) where they would be of maximum benefit. The work presented here is extendable to machining of MMCs, where wear of the tool is also a limiting factor.

Prater, Tracie↗

NASA NTRS2018

Relative Sputtering Rates of FeS, MgS, and Mg Silicates: Implications for ISM Gas Phase Depletions of Rock-Forming Elements

Astronomical measurements of S abundances in the diffuse interstellar medium (ISM) indicate ionized S is a dominant species with little (< 5%) S residing in grains (e.g. Jenkins 2009). This is an enigmatic result, given that abundant Fe-sulfide grains are observed in dust around pre- and post-main sequence stars and are also observed as major components of primitive meteoritic and cometary samples. These disparate observations suggest that the lifetime of sulfide grains in the ISM is short because of destruction processes. Our previous work has shown that FeS and MgS retain their crystallinity and do not amorphize during radiation processing, whereas enstatite and forsterite are readily amorphized. We have extended this study to measure the relative sputtering rates of FeS and MgS compared to enstatite and forsterite. Irradiation of FeS with 4 keV He+ results in preferential sputtering of S and the formation of a thin 2-3 nm, compact Fe metal layer that armors the surface. The zone of S loss extends to a depth of ~8-10 nm below the exposed surface. Despite this S loss, the FeS retains its crystallinity and shows no sign of incipient amorphization. Irradiation of FeS with 5kV Ga+ in a focused ion beam (FIB) instrument resulted in preferential sputtering of S and the formation of a 5-8-nm thick surface layer of nanophase Fe metal. X-ray mapping shows that the zone of S sputtering extends to a depth of nearly 20 nm, but there is no evidence for FeS amorphization, consistent with our previous work. The irradiation experiments show that the relative sputtering rate of FeS and MgS are much higher than olivine or enstatite. Sputtering experiments utilizing 30 kV and 5 kV Ga ions in the FIB produced volume loss in troilite that was ~4X greater than in enstatite or forsterite. The sputter yield under these conditions is such that for every Si atom sputtered from enstatite, ~14 S atoms are sputtered from FeS. We have performed similar sputtering experiments on Fe-bearing niningerite (MgS) and co-existing enstatite from the ALH 84170 EH3 chondrite. MgS also sputters much more rapidly than enstatite with a relative Si:S sputter yield of 1:8. For MgS, sulfur is highly depleted at the surface and the S-depletion zone extends to a depth of ~15 nm (using 5 kV Ga+). There is a corresponding zone of Mg and especially Fe enrichment that extends from 5 to ~10 nm below the surface, respectively. The dominant grain destruction mechanism in the ISM is sputtering from passage of supernova-generated shock waves. This process also results in the amorphization of crystalline silicates in the ISM. Our results indicate that FeS and MgS grains produced in evolved stars and injected into the ISM will be destroyed more rapidly than crystalline silicates. This process may account for the lack of significant depletion of S from the gas phase in the ISM. However, rare nanophase FeS grains occur as inclusions in circumstellar amorphous silicate grains found in comet dust particles analyzed in the laboratory. These results show that a finite amount of S in the ISM is sequestered in solid grains.

SPUTTERING RATES↗

NASA NTRS2022

Predicting Unreinforced Fabric Mechanical Behavior with Recurrent Neural Networks

Unreinforced woven fabrics are widely employed in various high-performance applications, including parachute deployment systems, airbags, and ballistic armor. The analysis of such materials is inherently complex due to the multiscale structure of these materials, and the dependence of macroscale behavior on changes that occur at lower scales. Previously, NASA’s Multiscale Analysis Tool (NASMAT) showed its capability in predicting unreinforced fabric behavior at the macroscale by capturing finite rotations that occur at the mesoscale. Though effective, the tool can face high computational cost for large, complex problems, motivating the need for the development of a surrogate model that can capture the same behavior. A recurrent neural network (RNN) was developed and trained on virtual NASMAT data to mimic the physics-based solutions while improving the computational runtime. The architecture of the RNN to best simulate the fabric behavior was carefully crafted based on heuristic knowledge of predicting physics-based temporal data, manual hyperparameter case studies, and Hyperband optimization.. The resultant model was able to predict a variety of stress-strain curves for fabrics with different mesoscale geometries, and was further validated by comparing to experimental data for the K706 style Kevlar plain-weave fabric, demonstrating the ability of the model to effectively capture the geometric changes in the fabric without explicitly calculating them, as is done in NASMAT. Furthermore, the tool showed its ability to improve on the runtime by a factor of 10 for fabric solutions compared to the multiscale tool, which would further enable the simulation of complex loading scenarios on unreinforced fabrics.

Fabric↗

NASA NTRSDate not supplied

Keweenaw Bay Water Resources: Turbidity Data Decision Support for Shoreline Assessment and Management in Lake Superior's Keweenaw Bay

Community Concerns: Keweenaw Bay is vulnerable to flooding and erosion, which threaten wetland restoration projects that provide a critical habitat for wildlife and fish. Erosion and flooding threaten the loss of public beaches and shoreline, coastal infrastructure, and impacts to coastal highways, which has driven shoreline armoring projects. Our goals were to first, produce a seasonal turbidity analysis to understand the sediment redistribution patterns in the bay during snow melt and rainy seasons to provide insight into coastal sediment dynamics. KBIC has completed an Environmental Protection Agency (EPA) - funded project titled "Long-Term Coastal Dynamic Collaborative for Tribal Resiliency" which has thus far produced detailed shoreline maps of the area. The NASA DEVELOP project is taking place in between phase 1 and 2 of the EPA-funded project.

Khaim Syed-Raza↗

NASA NTRSDate not supplied

Multiscale Prediction of Yarn Pullout Failure Mode in Unreinforced Textile Fabrics

Unreinforced woven fabrics have been implemented in a variety of high performance applications, including body armor, deployable structures, and as the reinforcement material in composites. Multiscale modeling techniques have significantly improved the capabilities of simulation-based tools to capture fabric mechanics efficiently and accurately, but often lack in their prediction of failure and require pairing with finite element analysis (FEA) software, limiting their application to the design of ‘fit-for-purpose’ materials. NASA’s Multiscale Analysis Tool (NASMAT) is a standalone multiscale program that has been traditionally used in the analysis of reinforced composites materials. More recently, it has been amended to simulate unreinforced fabric behavior by allowing the geometric state of the tows to change with applied loading due to the lack of a reinforcement material, such as the matrix seen in composites. Previous work has shown the ability of NASMAT to capture nonlinear macroscale behavior by predicting geometric changes in the state of each subcell as a function of the applied loading and allowing each subcell in the analysis to rotate according to these predicted changes, as well as predict nonlinear behavior due to the fiber breakage failure mode. In this work, the capability of predicting the onset and propagation of failure in plain woven fabrics in NASMAT is presented for the yarn pullout failure mode, which occurs when a fabric is loaded at an off-axis angle relative to the warp of weft tow direction. Yarn pullout behavior is initiated by determining the applied load in which the shear resistance of the contact area between yarn families is overcome. When failure is initiated, yarn pullout is determined to have occurred when the applied displacement, calculated from global strain, exceeds the deformed position of a given contact points between yarn families, determined from pin-joint kinematics. Contact points where pullout has occurred contribute to a global damage parameter used to modify the homogenized stiffness of the fabric, resulting in nonlinear behavior observed at the macroscale. The off-axis loading behavior and yarn pullout failure theory have been developed and implemented into NASMAT such that users can simulate off-axis tensile behavior of fabrics in a single, standalone multiscale tool. Simulations are compared to uniaxial tensile tests at various off-axis angles to demonstrate the capability of the tool in its prediction of both the onset of failure at each off-axis angles and the stress-strain behavior as failure progresses.

Materials↗

NASA NTRS2022

Snapping Shrimp Have Helmets That Protect Their Brains By Dampening Shock Waves

Shock waves are supersonic high-amplitude pressure waves that cause barotrauma when they transfer kinetic energy to the tissues of animals.1–4 Snapping shrimp (Alpheidae) produce shock waves and are exposed to them frequently, so we asked if these animals have evolved mechanisms of physical protection against them. Snapping shrimp generate shock waves by closing their snapping claws rapidly enough to form cavitation bubbles that release energy as an audible ‘‘snap’’ and a shock wave when they collapse.5–8 We tested if snapping shrimp are protected from shock waves by a helmet-like extension of their exoskeleton termed the orbital hood. Using behavioral trials, we found shock wave exposure slowed shelterseeking and caused a loss of motor control in Alpheus heterochaelis from which we had removed orbital hoods but did not significantly affect behavior in shrimp with unaltered orbital hoods. Shock waves thus have the potential to harm snapping shrimp but may not do so under natural conditions because of protection provided to shrimp by their orbital hoods. Using pressure recordings, we discovered the orbital hoods of A. heterochaelis dampen shock waves. Sealing the anterior openings of orbital hoods diminished how much they altered the magnitudes of shock waves, which suggests these helmet-like structures dampen shock waves by trapping and expelling water so that kinetic energy is redirected and released away from the heads of shrimp. Our results indicate orbital hoods mitigate blast-induced neurotrauma in snapping shrimp by dampening shock waves, making them the first biological armor system known to have such a function.

Alexandra C.N. Kingston↗

DOE OSTI2020

Numerical Simulation and Experimental Validation of Joint Performance in Aluminum-Steel Lap Welds Formed by Friction Stir Dovetailing

Friction stir dovetailing (FSD) is a new dissimilar material joining process that simultaneously forms a mechanical interlock and metallurgical bond at the dissimilar material interface. This work presents development of a modeling and simulation approach to predict mechanical performance of FSD thick section aluminum to steel joints. A finite element analysis (FEA) was carried out in order to predict the load-carrying capacity and failure location for aluminum thicknesses between 12.7 mm and 50.8 mm with different numbers of dovetails. The numerical results and corresponding experimental investigation are in agreement and suggest that the developed methods can be used effectively for design and analysis of FSD joints using standard FEA tools.

Friction stir dovetailing, Friction stir welding, ↗

DOE OSTI2020

Structure and Mechanical Adaptability of a Modern Elasmoid Fish Scale from the Common Carp

The carp (Cyprinus carpio) has typical elasmoid scales commonly found on teleosts. They provide protection while retaining flexibility and maneuverability of the fish. The exterior surface of the scale consists of an ultrathin discontinuous mineral layer on top of mineralized woven collagen fibrils. The underlying foundation is composed of two collagenous components. The major one consists of a single-twisted ‘‘Bouligand’’ structure with a twisting angle of 36°. A secondary ‘‘sheet-like’’ structure, formed by thinner collagen fibrils oriented along the thickness direction, acts to increase the integrity of the scale. In this work, we identify the deformation and failure mechanisms of the carp scale, revealing slight tensile anisotropy. Using in situ small-angle X-ray scattering during tensile testing, the toughening mechanisms of the scale, including the adaptive structural reorientation of lamellae as well as fibrillar sliding and elastic deformation, are quantified and compared with those of other fish scales.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)

In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.

03 NATURAL GAS↗

DOE OSTI2021

Digital Infrastructure Migration Framework Report

This document presents a full-scope Digital Infrastructure implementation and associated lifecycle support recommendations that enable a plant life of 80+ years. Specific technologies and software applications are researched, developed, selected, implemented, and then integrated by utilities to enhance safety, reliability, and economic performance such that the result provides much more than the sum of its parts. Specific selection of these technologies is driven by business case analyses which are utility, station, and unit specific.

42 ENGINEERING↗