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DOE OSTI2024

Neural network kinetics for exploring diffusion multiplicity and chemical ordering in compositionally complex materials

Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. The inherent chemical complexity in compositionally complex materials poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network kinetics (NNK) scheme that predicts and simulates diffusion-induced chemical and structural evolution in complex concentrated chemical environments. The framework is grounded on efficient on-lattice structure and chemistry representation combined with artificial neural networks, enabling precise prediction of all path-dependent migration barriers and individual atom jumps. To demonstrate the method, we study the temperature-dependent local chemical ordering in a refractory NbMoTa alloy and reveal a critical temperature at which the B2 order reaches a maximum. The atomic jump randomness map exhibits the highest diffusion heterogeneity (multiplicity) in the vicinity of this characteristic temperature, which is closely related to chemical ordering and B2 structure formation. The scalable NNK framework provides a promising new avenue to exploring diffusion-related properties in the vast compositional space within which extraordinary properties are hidden.

36 MATERIALS SCIENCE↗

NASA NTRS2001

Working Toward Nanotube Composites

One of the most attractive applications of single-wall carbon nanotubes (SWNT) is found in the area of structural materials. Nanotubes have a unique combination of high strength, modulus, and elongation to failure, and therefore have potential to significantly enhance the mechanical properties of today's composites. This is especially attractive for the aerospace industry looking for any chance to save weight. This is why NASA has chosen to tackle this difficult application of SWNT. Nanotube properties differ significantly from that of conventional carbon fibers, and a whole new set of problems, including adhesion and dispersion in the adhesive polymer matrix, must be resolved in order to engineer superior composite materials. From recent work on a variety of applications it is obvious that the wide range of research in nanotubes will lead to advances in physics, chemistry, and engineering. However, the possibility of ultralightweight structures is what causes dreamers to really get excited. One of the important issues in composite engineering is aspect ratio of the fibers, since it affects load transfer in composites. Nanotube length was a gray area for years, since they are formed in bundles, making it impossible to monitor individual nanotube length. Even though bundles are observed to be tens and hundreds of microns long, they can be built of relatively short tubes weakly bound by Van der Waals forces. Nanotube length can be affected by subsequent purification and ultrasound processing, which has been necessary in order to disperse nanotubes and introduce them into a polymer matrix. Some calculations show that nanotubes with 10(exp 5) aspect ratio may be necessary to achieve good load transfer. We show here that nanotubes produced in our laser system are as much as tens of microns long and get cut into lengths of hundreds of nanometers during ultrasound processing. Nanotube length was measured by AFM on pristine nanotube specimens as well, as after sonication. In each case great care was taken to measure individual nanotubes, rather than bundles. Pristine nanotubes were collected on quartz substrates placed directly in the laser oven and exposed for 0.5 s. This results in an equal mix of bundles and individual nanotubes. Nanotube length measurements were limited practically by the lateral span of the AFM scanner, but nanotube length is certainly in excess of 20 micrometers.

Arepalli, Sivaram↗

NASA NTRS2006

Improving Thermomechanical Properties of SiC/SiC Composites

Today, a major thrust toward improving the thermomechanical properties of engine components lies in the development of fiber-reinforced silicon carbide matrix composite materials, including SiC-fiber/SiC-matrix composites. These materials are lighter in weight and capable of withstanding higher temperatures, relative to state-of-the-art metallic alloys and oxide-matrix composites for which maximum use temperatures are in the vicinity of 1,100 C. In addition, the toughness or damage tolerance of the SiC-matrix composites is significantly greater than that of unreinforced silicon-based monolithic ceramics. For successful application in advanced engine systems, the SiC-matrix composites should be able to withstand component service stresses and temperatures for the desired component lifetimes. Inasmuch as the high-temperature structural lives of ceramic materials are typically limited by creep-induced growth of flaws, a key property required of such composite materials is high resistance to creep under conditions of use. Also, the thermal conductivity of the materials should be as high as possible so as to minimize component thermal gradients and thermal stresses. A state-of-the-art SiC-matrix composite is typically fabricated in a three-step process: (1) fabrication of a component-shaped architectural preform reinforced by thermally stable high-performance fibers, (2) chemical-vapor infiltration (CVI) of a fiber-coating material such as boron nitride (BN) into the preform, and (3) infiltration of an SiC-based matrix into the remaining porosity in the preform. Generally, the matrices of the highest-performing composites are fabricated by initial use of a CVI SiC matrix component that is typically more thermally stable and denser than matrix components formed by processes other than CVI. As such, the initial SiC matrix component made by CVI provides better environmental protection to the coated fibers embedded within it. Also, the denser CVI SiC imparts to the composite better resistance to propagation of cracks, enhanced thermal conductivity, and higher creep resistance.

DiCarlo, James A.↗

DOE OSTI2024

Quantifying the cooperative evolution of microphase segregation and nanostructural order in annealed polyurethanes of MDI-BDO-PTHF

Here, we quantify the relationship between microphase segregation and local structure development in thermoplastic polyurethanes. Samples were prepared with varying ratios of 4,40 -methylene diphenyl diisocyanate (MDI) and 1,4-butanediol (BDO) to polytetrahydrofuran (PTHF) and annealed at temperatures T a between RT–140 °C for 20 h each. Distinct populations of smaller and larger ordered domains are distinguished by pair distribution func tion analysis. The intermediate-range order of nanoscale hard domains in the paracrystalline state (form I) is directly extracted and characterized. The results suggest that form I of the MDI-BDO:PTHF system presents a conformational and packing order similar to the form III structure, typically obtained from stretching/annealing, but with limited spatial coherence of 3–7 nm. Heating above T g of the hard segments is necessary to achieve a substantial structural response from the annealing treatment. Increasing T a promotes purification of the soft phase via microphase segregation, coalescence of the hard blocks, and growth of paracrystalline phase, while a minority fraction of longer-range ordered domains left over from production remains relatively constant. We observe a composition-dependent decrease in the average nearest-neighbor dis tance that can be correlated with the greater number of C C, C N, and C O bonds with increased hard segment content. A non-linear deviation in the trend is observed to correlate with sample densification. The mechanical and thermal behavior of the samples is intimately tied to the segregation state.

processing-structure-properties↗

DOE OSTI2024

Roadmap on methods and software for electronic structure based simulations in chemistry and materials

This Roadmap article provides a succinct, comprehensive overview of the state of electronic structure methods and software for molecular and materials simulations. Seventeen distinct sections collect insights by 51 leading scientists in the field. Each contribution addresses the status of a particular area, as well as current challenges and anticipated future advances, with a particular eye towards software related aspects and providing key references for further reading. Foundational sections cover density functional theory and its implementation in real-world simulation frameworks, Green's function based many-body perturbation theory, wave-function based and stochastic electronic structure approaches, relativistic effects and semiempirical electronic structure theory approaches. Subsequent sections cover nuclear quantum effects, real-time propagation of the electronic structure, challenges for computational spectroscopy simulations, and exploration of complex potential energy surfaces. The final sections summarize practical aspects, including computational workflows for complex simulation tasks, the impact of current and future high-performance computing architectures, software engineering practices, education and training to maintain and broaden the community, as well as the status of and needs for electronic structure based modeling from the vantage point of industry environments. Overall, the field of electronic structure software and method development continues to unlock immense opportunities for future scientific discovery, based on the growing ability of computations to reveal complex phenomena, processes and properties that are determined by the make-up of matter at the atomic scale, with high precision.

36 MATERIALS SCIENCE↗

NASA NTRS1998

Geologic Landforms and Processes on Icy Satellites

During the first reconaissence of the satellites of the outer solar system conducted by the Voyager missions (1979-1989), a surprising diversity of unusual geologic landforms were observed, in some cases with bewildering complexity (e.g., Triton). Impact features were certainly expected but the variety of volcanic, diapiric, tectonic, impact, and erosional landforms was only remotely suggested by some early theoretical works. These diagnostic features are manifestations of the internal composition, thermal history, and dynamical evolution of these bodies. It is the job of the geologist to interpret the morphology, stratigraphy, and composition of these deposits and structures to ascertain what materials were mobilized in the interior, in what amount, and the mechanism and cause of their mobilization. In this chapter, we review what is know about these features and what constraints can be placed on composition and thermal history. Particular emphasis is placed on volcanic features, as these are most directly related to satellite composition and thermal history. The surface spectra, high albedos, and low bulk densities of the satellites of the outer solar system indicate that water and other ices are abundant on these bodies, particularly on their surfaces. Ices, particularly water ice, are less dense than silicates and will tend to float and form crusts during differentiation or partial melting of the interior. Ices therefore take the place of silicates as 'crust-forming' minerals and dominate geologic processes on icy satellites. Melted ices form magma bodies, and sometimes are extruded as lavas, an unusual but still valid perspective for terrestrial geologists. The unusual properties of some ices, including their low melting temperatures, and low strengths (as well as the decrease in density on the freezing of water ice), will ultimately be very important in interpreting this record.

Schenk, Paul M.↗

NASA NTRS2011

AC Electric Field Activated Shape Memory Polymer Composite

Shape memory materials have drawn interest for applications like intelligent medical devices, deployable space structures and morphing structures. Compared to other shape memory materials like shape memory alloys (SMAs) or shape memory ceramics (SMCs), shape memory polymers (SMPs) have high elastic deformation that is amenable to tailored of mechanical properties, have lower density, and are easily processed. However, SMPs have low recovery stress and long response times. A new shape memory thermosetting polymer nanocomposite (LaRC-SMPC) was synthesized with conductive fillers to enhance its thermo-mechanical characteristics. A new composition of shape memory thermosetting polymer nanocomposite (LaRC-SMPC) was synthesized with conductive functionalized graphene sheets (FGS) to enhance its thermo-mechanical characteristics. The elastic modulus of LaRC-SMPC is approximately 2.7 GPa at room temperature and 4.3 MPa above its glass transition temperature. Conductive FGSs-doped LaRC-SMPC exhibited higher conductivity compared to pristine LaRC SMP. Applying an electric field at between 0.1 Hz and 1 kHz induced faster heating to activate the LaRC-SMPC s shape memory effect relative to applying DC electric field or AC electric field at frequencies exceeding1 kHz.

Kang, Jin Ho↗

NASA NTRS1995

A Probabilistic Design Method Applied to Smart Composite Structures

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

Shiao, Michael C.↗

NASA NTRS1999

Effects of Microgravity on the Formation of Aerogels

This paper describes research to investigate fundamental aspects of the effects of microgravity on the formation of the microstructure of metal oxide alcogels and aerogels. We are studying the role of gravity on pore structure and gel uniformity in collaboration with Marshall Space Flight Center (MSFC) on gelling systems under microgravity conditions. While this project was just initiated in May 1998, related research performed earlier is described along with the plans and rationale for the current microgravity investigation to provide background and describe newly developing techniques that should be useful for the current gellation studies. The role of gravity in materials processing must be investigated through the study of well-mastered systems. Sol-gel processed materials are near-perfect candidates to determine the effect of gravity on the formation and growth of random clusters from hierarchies of aggregated units. The processes of hydrolysis, condensation, aggregation and gellation in the formation of alcogels are affected by gravity and therefore provide a rich system to study under microgravity conditions. Supercritical drying of the otherwise unstable wet alcogel preserves the alcogel structure produced during sol-gel processing as aerogel. Supercritically dried aerogel provides for the study of material microstructures without interference from the effects of surface tension, evaporation, and solvent flow. Aerogels are microstructured, low density open-pore solids. They have many unusual properties including: transparency, excellent thermal resistance, high surface area, very low refractive index, a dielectric constant approaching that of air, and extremely low sound velocity. Aerogels are synthesized using sol-gel processing followed by supercritical solvent extraction that leaves the original gel structure virtually intact. These studies will elucidate the effects of microgravity on the homogeneity of the microstructure and porosity of aerogel. The presence of poorly controlled microporosity in aerogel leads to material non-uniformity that gives rise to increased light scattering. Investigation of the effect of gravity driven solute flows within microclusters and their effect on condensation and agglomeration reactions will enable us to improve the preparation and properties of aerogel. Increased clarity of images viewed through aerogel and decreased scattering from the pores of aerogel will significantly improve the prospects for large-scale adoption of aerogel in such applications as transparent insulating windows, high performance thermal insulation, and Cherenkov detectors.

Hunt, A. J.↗

NASA NTRS2001

Micromechanics-Based Inelastic Finite Element Analysis Accomplished Via Seamless Integration of MAC/GMC

A critical issue in the micromechanics-based analysis of composite structures becomes the availability of a computationally efficient homogenization technique: one that is 1) Capable of handling the sophisticated, physically based, viscoelastoplastic constitutive and life models for each constituent; 2) Able to generate accurate displacement and stress fields at both the macro and the micro levels; 3) Compatible with the finite element method. The Generalized Method of Cells (GMC) developed by Paley and Aboudi is one such micromechanical model that has been shown to predict accurately the overall macro behavior of various types of composites given the required constituent properties. Specifically, the method provides "closed-form" expressions for the macroscopic composite response in terms of the properties, size, shape, distribution, and response of the individual constituents or phases that make up the material. Furthermore, expressions relating the internal stress and strain fields in the individual constituents in terms of the macroscopically applied stresses and strains are available through strain or stress concentration matrices. These expressions make possible the investigation of failure processes at the microscopic level at each step of an applied load history.

Arnold, Steven M.↗

NASA NTRS2008

Modeling Creep Effects within SiC/SiC Turbine Components

Anticipating the implementation of advanced SiC/SiC ceramic composites into the hot section components of future gas turbine engines, the primary objective of this on-going study is to develop physics-based analytical and finite-element modeling tools to predict the effects of constituent creep on SiC/SiC component service life. A second objective is to understand how to possibly select and manipulate constituent materials, processes, and geometries in order to minimize these effects. In initial studies aimed at SiC/SiC components experiencing through-thickness stress gradients, creep models were developed that allowed an understanding of detrimental residual stress effects that can develop globally within the component walls. It was assumed that the SiC/SiC composites behaved as isotropic visco-elastic materials with temperature-dependent creep behavior as experimentally measured in-plane in the fiber direction of advanced thin-walled 2D SiC/SiC panels. The creep models and their key results are discussed assuming state-of-the-art SiC/SiC materials within a simple cylindrical thin-walled tubular structure, which is currently being employed to model creep-related effects for turbine airfoil leading edges subjected to through-thickness thermal stress gradients. Improvements in the creep models are also presented which focus on constituent behavior with more realistic non-linear stress dependencies in order to predict such key creep-related SiC/SiC properties as time-dependent matrix stress, constituent creep and content effects on composite creep rates and rupture times, and stresses on fiber and matrix during and after creep.

DiCarlo, J. A.↗

NASA NTRS2007

Nanorod-Based Fast-Response Pressure-Sensitive Paints

A proposed program of research and development would be devoted to exploitation of nanomaterials in pressuresensitive paints (PSPs), which are used on wind-tunnel models for mapping surface pressures associated with flow fields. Heretofore, some success has been achieved in measuring steady-state pressures by use of PSPs, but success in measuring temporally varying pressures has been elusive because of the inherent slowness of the optical responses of these materials. A PSP contains a dye that luminesces in a suitable wavelength range in response to photoexcitation in a shorter wavelength range. The luminescence is quenched by oxygen at a rate proportional to the partial pressure of oxygen and thus proportional to the pressure of air. As a result, the intensity of luminescence varies inversely with the pressure of air. The major problem in developing a PSP that could be easily applied to a wind-tunnel model and could be useful for measuring rapidly varying pressure is to provide very high gas diffusivity for rapid, easy transport of oxygen to and from active dye molecules. Most PSPs include polymer-base binders, which limit the penetration of oxygen to dye molecules, thereby reducing responses to pressure fluctuations. The proposed incorporation of nanomaterials (somewhat more specifically, nanorods) would result in paints having nanostructured surfaces that, relative to conventional PSP surfaces, would afford easier and more nearly complete access of oxygen molecules to dye molecules. One measure of greater access is effective surface area: For a typical PSP as proposed applied to a given solid surface, the nanometer-scale structural features would result in an exposed surface area more than 100 times that of a conventional PSP, and the mass of proposed PSP needed to cover the surface would be less than tenth of the mass of the conventional PSP. One aspect of the proposed development would be to synthesize nanorods of Si/SiO2, in both tangle-mat and regular- array forms, by use of chemical vapor deposition (CVD) and wet chemical processes, respectively. The rods would be coated with a PSP dye, and the resulting PSP signals would be compared with those obtained from PSP dye coats on conventional support materials. Another aspect of the proposed development would be to seek to exploit the quantum properties of nanorods of a suitable semiconductor (possibly GaN), which would be synthesized by CVD. These quantum properties of semiconductor nanorods include narrow-wavelength-band optical absorption and emission characteristics that vary with temperature. The temperature sensitivity might enable simultaneous measurement of fluctuating temperature and pressure and to provide a temperature correction for the PSP response.

Bencic, Timothy↗

NASA NTRS2001

Soot Optical Property Study

Recent past studies of soot reaction processes in laminar premixed and nonpremixed flames generally have used the intrusive technique of thermophoretic sampling and analysis by transmission electron microscopy (TEM) to observe soot structure and obtain important fundamental information about soot particle properties, such as soot primary particle diameters, the rate of change of soot primary particle diameter as a function of time (or rate of soot surface growth or oxidation), the amount of soot particle reactive surface area per unit volume, the number of primary soot particles per unit volume, and the rate of formation of primary soot particles (or the rate of soot primary particle nucleation). Given the soot volume per unit volume of the flame (or the soot volume fraction), all these properties are readily found from a measurement of the soot primary particle diameter (which usually is nearly a constant for each location within a laminar flame). This approach is not possible within freely propagating flames, however, because soot properties at given positions in such flames vary relatively rapidly as a function of time in the soot formation and oxidation regions compared to the relatively lengthy sampling times needed to accumulate adequate soot samples and to minimize effects of soot collected on the sampling grid as it moves to and from the sampling position through other portions of the flame. Thus, nonintrusive optical methods must be used to find the soot primary particle diameters needed to define the soot surface reaction properties mentioned earlier. Unfortunately, approximate nonintrusive methods used during early studies of soot reaction properties in flames, found from laser scattering and absorption measurements analyzed assuming either Rayleigh scattering or Mie scattering from polydisperse effective soot particles having the same mass of soot as individual soot aggregates, have not been found to be an effective way to estimate the soot surface reaction area per unit volume. Thus, alternative nonintrusive optical methods of finding these properties must be sought, which was the objective of this phase of the investigation. The alternative method used here involves use of the Rayleigh-Debye-Gans-Polydisperse-Fractal-Aggregate (RDG-PFA) scattering approximation for soot aggregates in flames. Thus, the development of this method will be discussed next before describing its evaluation as a means of nonintrusively measuring soot primary particle diameters in soot-containing flames.

Aung, K. T.↗

NASA NTRS2000

Laminar Diffusion Flame Studies (Ground- and Space-Based Studies)

Laminar diffusion flames are of interest because they provide model flame systems that are far more tractable for analysis and experiments than more practical turbulent diffusion flames. Certainly, understanding flame processes within laminar diffusion flames must precede understanding these processes in more complex turbulent diffusion flames. In addition, many properties of laminar diffusion flames are directly relevant to turbulent diffusion flames using laminar flamelet concepts. Laminar jet diffusion flame shapes (luminous flame boundaries) have been of particular interest since the classical study of Burke and Schumann because they are a simple nonintrusive measurement that is convenient for evaluating flame structure predictions. Thus, consideration of laminar flame shapes is undertaken in the following, emphasizing conditions where effects of gravity are small, due to the importance of such conditions to practical applications. Another class of interesting properties of laminar diffusion flames are their laminar soot and smoke point properties (i.e., the flame length, fuel flow rate, characteristic residence time, etc., at the onset of soot appearance in the flame (the soot point) and the onset of soot emissions from the flame (the smoke point)). These are useful observable soot properties of nonpremixed flames because they provide a convenient means to rate several aspects of flame sooting properties: the relative propensity of various fuels to produce soot in flames; the relative effects of fuel structure, fuel dilution, flame temperature and ambient pressure on the soot appearance and emission properties of flames; the relative levels of continuum radiation from soot in flames; and effects of the intrusion of gravity (or buoyant motion) on emissions of soot from flames. An important motivation to define conditions for soot emissions is that observations of laminar jet diffusion flames in critical environments, e.g., space shuttle and space station facilities, cannot involve soot emitting flames in order to ensure that test chamber windows used for experimental observations are not blocked by soot deposits, thereby compromising unusually valuable experimental results. Another important motivation to define conditions where soot is present in diffusion flames is that flame chemistry, transport and radiation properties are vastly simplified when soot is absent, making such flames far more tractable for detailed numerical simulations than corresponding soot-containing flames. Motivated by these observations, the objectives of this phase of the investigation were as follows: (1) Observe flame-sheet shapes (the location of the reaction zone near phi=1) of nonluminous (soot free) laminar jet diffusion flames in both still and coflowing air and use these results to develop simplified models of flame-sheet shapes for these conditions; (2) Observe luminous flame boundaries of luminous (soot-containing) laminar jet diffusion flames in both still and coflowing air and use these results to develop simplified models of luminous flame boundaries for these conditions. In order to fix ideas here, maximum luminous flame boundaries at the laminar smoke point conditions were sought, i.e., luminous flame boundaries at the laminar smoke point; (3) Observe effects of coflow on laminar soot- and smoke-point conditions because coflow has been proposed as a means to control soot emissions and minimize the presence of soot in diffusion flames.

Dai, Z.↗

DOE OSTI2024

Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile

Polyacrylonitrile (PAN) is an important commercial polymer, bearing atactic stereochemistry resulting from nonselective radical polymerization. As such, an accurate, fundamental understanding of governing interactions among PAN molecular units is indispensable for advancing the design principles of final products at reduced processability costs. While ab initio molecular dynamics (AIMD) simulations can provide the necessary accuracy for treating key interactions in polar polymers, such as dipole–dipole interactions and hydrogen bonding, and analyzing their influence on the molecular orientation, their implementation is limited to small molecules only. Herein, we show that the neural network interatomic potentials (NNIPs) that are trained on the small-scale AIMD data (acquired for oligomers) can be efficiently employed to examine the structures and properties at large scales (polymers). NNIP provides critical insight into intra- and interchain hydrogen-bonding and dipolar correlations and accurately predicts the amorphous bulk PAN structure validated by modeling the experimental X-ray structure factor. Furthermore, the NNIP-predicted PAN properties, such as density and elastic modulus, are in good agreement with their experimental values. Overall, the trend in the elastic modulus is found to correlate strongly with the PAN structural orientations encoded in the Hermans orientation factor. In conclusion, this study enables the ability to predict the structure–property relations for PAN and analogues with sustainable ab initio accuracy across scales.

36 MATERIALS SCIENCE↗

NASA NTRS2004

Progress in Understanding the Pre-Earthquake Associated Events by Analyzing IR Satellite Data

We present latest result in understanding the potential relationship between tectonic stress, electro-chemical and thermodynamic processes in the Earths crust and atmosphere with an increase in IR flux as a potential signature of electromagnetic (EM) phenomena that are related to earthquake activity, either pre-, co- or post seismic. Thermal infra-red (TIR) surveys performed by the polar orbiting (NOAA/AVHRR MODIS) and geosynchronous weather satellites (GOES, METEOSAT) gave an indication of the appearance (from days to weeks before the event) of "anomalous" space-time TIR transients that are associated with the location (epicenter and local tectonic structures) and time of a number of major earthquakes with M>5 and focal depths less than 50km. We analyzed broad category of associated pre-earthquake events, which provided evidence for changes in surface temperature, surface latent heat flux, chlorophyll concentrations, soil moisture, brightness temperature, emissivity of surface, water vapour in the atmosphere prior to the earthquakes occurred in Algeria, India, Iran, Italy, Mexico and Japan. The cause of such anomalies has been mainly related to the change of near-surface thermal properties due to complex lithosphere-hydrosphere-atmospheric interactions. As final results we present examples from the most recent (2000-2004) worldwide strong earthquakes and the techniques used to capture the tracks of EM emission mid-IR anomalies and a methodology for practical future use of such phenomena in the early warning systems.

Ouzounov, Dimitar↗

NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗

NASA NTRS2008

Further Developments in Modeling Creep Effects Within Structural SiC/SiC Components

Anticipating the implementation of advanced SiC/SiC composites into turbine section components of future aero-propulsion engines, the primary objective of this on-going study is to develop physics-based analytical and finite-element modeling tools to predict the effects of constituent creep on SiC/SiC component service life. A second objective is to understand how to possibly manipulate constituent materials and processes in order to minimize these effects. Focusing on SiC/SiC components experiencing through-thickness stress gradients (e.g., airfoil leading edge), prior NASA creep modeling studies showed that detrimental residual stress effects can develop globally within the component walls which can increase the risk of matrix cracking. These studies assumed that the SiC/SiC composites behaved as isotropic viscoelastic continuum materials with creep behavior that was linear and symmetric with stress and that the creep parameters could be obtained from creep data as experimentally measured in-plane in the fiber direction of advanced thin-walled 2D SiC/SiC panels. The present study expands on those prior efforts by including constituent behavior with non-linear stress dependencies in order to predict such key creep-related SiC/SiC properties as time-dependent matrix stress, constituent creep and content effects on composite creep rates and rupture times, and stresses on fiber and matrix during and after creep.

Lang, Jerry↗