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At least 1,423 records · Page 79

Spectrophotometry and organic matter on Iapetus. 1: Composition models

Iapetus shows a greater hemispheric albedo asymmetry than any other body in the solar system. Hapke scattering theory and optical constants measured in the laboratory are used to identify possible compositions for the dark material on the leading hemisphere of Iapetus. The materials considered are poly-HCN, kerogen, Murchison organic residue, Titan tholin, ice tholin, and water ice. Three-component mixtures of these materials are modeled in intraparticle mixture of 25% poly-HCN, 10% Murchison residue, and 65% water ice is found to best fit the spectrum, albedo, and phase behavior of the dark material. The Murchison residue and/or water ice can be replaced by kerogen and ice tholin, respectively, and still produce very good fits. Areal and particle mixtures of poly-HCN, Titan tholin, and either ice tholin or Murchison residue are also possible models. Poly-HCN is a necessary component in almost all good models. The presence of poly-HCN can be further tested by high-resolution observations near 4.5 micrometers.

Wilson, Peter D.↗

Crystal plasticity including a phase-field deformation twinning model for the high-rate deformation of cyclotetramethylene tetranitramine

A new finite strain thermomechanical model for the high-rate deformation of the β-polymorph of cyclotetramethylene tetranitramine (β-HMX) has been developed and applied to simulations of plate impact experiments. The crystal plasticity model is based on a model developed previously for RDX (Luscher et al. 2017), which is extended to incorporate deformation twinning. Twinning during normal plate impacts is simulated with a phase-field twin model. First, material parameters governing the kinetics of dislocation slip are calibrated on the subset of simulations which had negative Schmid factors for the twin system. Second, a parametric study of the twin material parameters was performed to find suitable values. Overall, the results of the simulations with the phase-field twinning model are reported for impacts on several crystal orientations. We find that the twin growth decreases with increasing distance from the impact surface because of dissipation of the shock front via dislocation-mediated plasticity, and that the simulated interface velocity with and without phase-field twinning do not show appreciable differences. These modeling results suggest that the significance of twinning in β-HMX cannot be determined with traditional loading configurations and diagnostics.

36 MATERIALS SCIENCE↗

Carbonation of model cement pastes: The mineralogical origin of microstructural changes and shrinkage

This study explored the reactive processes of atmospheric carbonation and the consequences with respect to cementitious materials. Two model pastes were used: hydrated C{sub 3}S (including C-S-H and portlandite) and a paste prepared by hydrating a blend of C{sub 3}S and nanosilica (including C-S-H only). The two pastes were carbonated under accelerated conditions in the laboratory. The resulting mineralogical assemblage was examined using X-ray diffraction, thermogravimetric analysis and nuclear magnetic resonance. The microstructural changes were studied by X-ray tomography and porosimetry, and their macroscopic impacts were evaluated through gas diffusion and shrinkage measurements. The use of model pastes allowed for the evaluation of the change in solid volume induced by the carbonation of C-S-H. C-S-H decalcification and subsequent silica chain polymerisation were found responsible for carbonation shrinkage (and potentially cracking). Finally, the results highlight the protective role of portlandite: portlandite helped in limiting C-S-H decalcification and then reducing carbonation shrinkage and cracking.

36 MATERIALS SCIENCE↗

Tethers as Debris: Simulating Impacts of Kevlar Tethers on Shuttle Tiles

In a previous paper I examined the effects of impacts of polymer tethers on aluminum plates using the SPHC hydrodynamic code. In this paper I apply tether models to a new target - models of Space Shuttle tiles developed during the STS 107 accident investigation. In this three-dimensional simulation, a short tether fragment strikes a single tile supported on an aluminum backing plate. A tile of the LI-900 material is modeled. Penetration and damage to the tile and the backwall are characterized for three normal impact velocities. The tether is modeled as a bundle of eight 1-mm strands, with the bundle having dimensions 2-mm x 4-mm x 20-cm. The bulk material properties used are those of Kevlar(TradeMark) 49, for which a Mie-Gruneisen multiphase equation of state (eos) is used. In addition, the strength model is applied in a linear sense, such that tensile loads along the strand length are supported, but there is no strength in the lateral directions. Tile models include the various layers making up the tile structure. The outermost layer is a relatively dense borosilicate glass, known as RCG, 0.5-mm thick. The RCG layer is present on the top and four sides of the tile. Below this coating is the bulk of the tile, 1.8- in thick, made of LI-900, a product consisting of rigidized fiberous silica with a density of 9 lWft3. Below the main insulating layer is a bottom layer of the same material that has been treated to increase its density by approximately 69% to improve its strength. This densified layer is bonded to a Strain Isolation Pad (SIP), modeled as a refractory felt fabric. The SIP is bonded to an aluminum 2024 wall 0.1-in thick. The tile and backwall materials use a Me-Gruneisen multiphase eos, with the exception of the SIP felt, which uses a fabric equation of state. Fabrics must be crushed to the full bulk material density before bulk material properties and a Mie-Gruneisen eos are applied. Tether fragment impact speeds of 3,7, and 10 km/s are simulated, with impact velocities normal to the tile face. Damage results are presented in tabular format.

Evans, Steven W.↗

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Abstract Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecular structures. Training an accurate and comprehensive GCNN surrogate for molecular design requires large-scale graph datasets and is usually a time-consuming process. Recent advances in GPUs and distributed computing open a path to reduce the computational cost for GCNN training effectively. However, efficient utilization of high performance computing (HPC) resources for training requires simultaneously optimizing large-scale data management and scalable stochastic batched optimization techniques. In this work, we focus on building GCNN models on HPC systems to predict material properties of millions of molecules. We use HydraGNN, our in-house library for large-scale GCNN training, leveraging distributed data parallelism in PyTorch. We use ADIOS, a high-performance data management framework for efficient storage and reading of large molecular graph data. We perform parallel training on two open-source large-scale graph datasets to build a GCNN predictor for an important quantum property known as the HOMO-LUMO gap. We measure the scalability, accuracy, and convergence of our approach on two DOE supercomputers: the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) and the Perlmutter system at the National Energy Research Scientific Computing Center (NERSC). We present our experimental results with HydraGNN showing (i) reduction of data loading time up to 4.2 times compared with a conventional method and (ii) linear scaling performance for training up to 1024 GPUs on both Summit and Perlmutter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Micromechanical simulation of damage progression in carbon phenolic composites

Carbon/phenolic composites are used extensively as ablative insulating materials in the nozzle region of solid rocket motors. The current solid rocket motor (RSRM) on the space shuttle is fabricated from woven rayon cloth which is carbonized and then impregnated with the phenolic resin. These plies are layed up in the desired configuration and cured to form the finished part. During firing, the surface of the carbon/phenolic insulation is exposed to 5000 F gases from the rocket exhaust. The resin pyrolizes and the material chars to a depth which progresses with time. The rate of charring and erosion are generally predictable, and the insulation depth is designed to allow adequate safety margins over the firing time of the motor. However, anomalies in the properties and response of the carbon/phenolic materials can lead to severe material damage which may decrease safety margins to unacceptable levels. Three macro damage modes which were observed in fired nozzles are: ply lift, 'wedge out', and pocketing erosion. Ply lift occurs in materials with plies oriented nearly parallel to the surface. The damage occurs in a region below the charred material where material temperatures are relatively low - about 500 F. Wedge out occurs at the intersection of nozzle components whose plies are oriented at about 45 deg. The corner of the block of material breaks off along a ply interface. Pocketing erosion occurs in material with plies oriented normal to the surface. Thermal expansion is restrained in two directions resulting in large tensile strains and material failure normal to the surface. When a large section of material is removed as a result of damage, the insulation thickness is reduced which may lead to failure of the nozzle due to excessive heating of critical components. If these damage events cannot be prevented with certainty, the designer must increase the thickness of the insulator thus adding to both weight and cost. One of the difficulties in developing a full understanding of these macro damage mechanisms is that the loading environment and the material response to that environment are extremely complex. These types of damage are usually only observed in actual motor firings. Therefore, it is difficult and expensive to evaluate the reliability of new materials. Standard material tests which measure mechanical and thermal properties of test specimens can only provide a partial picture of how the material will respond in the service environment. The development of the ANALOG test procedure which can combine high heating rates and mechanical loads on a specimen will improve the understanding of the interactive effects of the various loads on the system. But a mechanistic model of material response which can account for the heterogeneity of the material, the progression of various micromechanical damage mechanisms, and the interaction of mechanical and thermal stresses on the material is required to accurately correlate material tests with response to service environments. A model based on fundamental damage mechanisms which is calibrated and verified under a variety of loading conditions will provide a general tool for predicting the response of rocket nozzles. The development of a micromechanical simulation technique was initiated and demonstrated to be effective for studying across-ply tensile failure of carbon/phenolic composites.

Slattery, Kerry T.↗

A large deformation multiphase continuum mechanics model for shock loading of soft porous materials

A large deformation, coupled finite-element (FE) model is developed to simulate the multiphase response of soft porous materials subjected to high strain-rate loading. The approach is based on the theory of porous media (TPM) at large deformations. Simplifications to the one-dimensional regime studied in the numerical simulations follow. An overview of several different time integration schemes is presented for the purpose of solving the nonlinear dynamic coupled balance of momenta (mixture and fluid) and balance of mass of the mixture equations. Numerical examples are presented for (i) verification against closed-form analytical solutions assuming small loads, (ii) demonstrating large deformation effects at high strain-rate, and (iii) showing differences in deformations between a single-phase elastodynamics model with occluded compressible pore fluid and a multiphase poroelastodynamics model at high strain-rate. The multiphase model shows that the relative motion of the pore fluid significantly dampens the deformation response of the solid skeleton as compared to the single-phase model, and makes it possible to extract quantitative values for the stresses of the different constituents, thereby allowing one to form preliminary conclusions about the onset of damage in the solid skeleton. The novelty of the current work is developing a multiphase, large deformation, mixture theory numerical model for high strain-rate loading of soft porous materials. It was discovered that explicit, adaptive time-stepping Runge–Kutta schemes offer high accuracy at relatively low cost when compared to traditional implicit or explicit central difference time-stepping schemes for shock-like loadings. Here, shock viscosity is added to the mixture momentum balance equation to regularize the shock front, and a stabilization term is added to the mixture mass balance equation to stabilize equal order interpolation finite elements for the coupled finite element solution of multiphase materials.

Engineering↗

Model for thermal stress resistance of truly elastic materials containing more than one crack

The model was developed upon the physical properties of surface energy and intrinsic modulus of elasticity of a material containing a number of equal sized microcracks which are independent of one another. The effect of these cracks upon the strain energy per unit volume of material necessary to continue simultaneous crack growth as well as the measured physical properties was established, and the thermal stress resistance is developed in terms of this energy. The model is expressed in its final form in terms of the measured physical properties of fracture strength, effective modulus of elasticity, and coefficient of thermal expansion. The model was applied to existent thermal stress data of ceramic materials for which these physical properties had been measured. On the basis of these data it was concluded that the thermal stress resistance of a material may be improved by increasing the fracture strength.

Lineback, L. D.↗

Physics-based Entry, Descent and Landing Risk Model

A physics-based risk model was developed to assess the risk associated with thermal protection system failures during the entry, descent and landing phase of a manned spacecraft mission. In the model, entry trajectories were computed using a three-degree-of-freedom trajectory tool, the aerothermodynamic heating environment was computed using an engineering-level computational tool and the thermal response of the TPS material was modeled using a one-dimensional thermal response tool. The model was capable of modeling the effect of micrometeoroid and orbital debris impact damage on the TPS thermal response. A Monte Carlo analysis was used to determine the effects of uncertainties in the vehicle state at Entry Interface, aerothermodynamic heating and material properties on the performance of the TPS design. The failure criterion was set as a temperature limit at the bondline between the TPS and the underlying structure. Both direct computation and response surface approaches were used to compute the risk. The model was applied to a generic manned space capsule design. The effect of material property uncertainty and MMOD damage on risk of failure were analyzed. A comparison of the direct computation and response surface approach was undertaken.

descent and landing↗

Solar White Thermal Coating for Cryogenic Propulsion Systems

NASA is currently conducting research into the potential of storing cryogenic fluid in low Earth orbit (LEO). Having cryogenic propellant readily available for high-performance propulsion systems can be very beneficial for deep space missions in the near future. One of the key challenges to storing cryogenic fluid in LEO is minimizing boil-off. To address the challenge, NASA is evaluating new concepts in thermal insulation. One recent experimental study evaluated the feasibility of using Yttrium Oxide (Y2O3), formed into tiles or spray coating that can potentially be used as a thermal coating for cryogenic propellant storage applications in deep space. Due to its temperature and wavelength dependent optical properties, this “solar white” material can reflect a vast majority of the Sun’s radiative energy while having a very high infrared emissivity for rejecting heat to deep space. As a part of the material development and proof of concept testing, multiple tests have been run at KSC and GRC to demonstrate the performance of the material. At GRC, the tests were run using the Deep Space Solar Simulator (DS3) which contains a thermal vacuum chamber in which the solar white sample was exposed to a deep space environment (< 10 K, optically dense walls) while under full illumination via solar lamp. In order to improve the use of the test results and apply them to spacecraft, there is a need to be able to model the material properties within NASA’s standard thermal modeling tools. As such, it was set out to verify a thermal model of one of the experiments using Thermal Desktop with Sinda. The thermal model of the DS3 test setup includes the solar white sample along with a solar lamp simulator capable of outputting heat at varying wavelengths. The model was developed in order to validate the test results and also to help predict results that will be obtained in future tests. This paper will review the modeling methods and thermal analysis results for various test cases that were run within the DS3 facility.

Cryogenic↗

A Risk-Based Approach for Aerothermal/TPS Analysis and Testing

The current status of aerothermal and thermal protection system modeling for civilian entry missions is reviewed. For most such missions, the accuracy of our simulations is limited not by the tools and processes currently employed, but rather by reducible deficiencies in the underlying physical models. Improving the accuracy of and reducing the uncertainties in these models will enable a greater understanding of the system level impacts of a particular thermal protection system and of the system operation and risk over the operational life of the system. A strategic plan will be laid out by which key modeling deficiencies can be identified via mission-specific gap analysis. Once these gaps have been identified, the driving component uncertainties are determined via sensitivity analyses. A Monte-Carlo based methodology is presented for physics-based probabilistic uncertainty analysis of aerothermodynamics and thermal protection system material response modeling. These data are then used to advocate for and plan focused testing aimed at reducing key uncertainties. The results of these tests are used to validate or modify existing physical models. Concurrently, a testing methodology is outlined for thermal protection materials. The proposed approach is based on using the results of uncertainty/sensitivity analyses discussed above to tailor ground testing so as to best identify and quantify system performance and risk drivers. A key component of this testing is understanding the relationship between the test and flight environments. No existing ground test facility can simultaneously replicate all aspects of the flight environment, and therefore good models for traceability to flight are critical to ensure a low risk, high reliability thermal protection system design. Finally, the role of flight testing in the overall thermal protection system development strategy is discussed.

Wright, Michael J.↗

Facile Electrodeposition and Aging to Generate 3-Dimensional α-MnO 2 Battery Cathodes

Conventional tape casting forms 2-dimensional (2D) electrodes containing active material, conductive additive, and binder with restricted ion access as electrodes increase in thickness. To improve the transport properties, 3D architectures were developed using electrodeposition to ensure contact between the active material with the substrate, and provide enhanced electrolyte access. This paper investigates electrodeposition of cryptomelane ( α -MnO 2 ) as a model cathode material to efficiently accommodate (de)lithation and increase areal capacity vs conventional 2D coatings. Electodeposited samples on titantium (Ti) foil substrates were characterized using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) and show a linear increase of the average oxidation of Mn (3.5–3.8) and active mass loading (1.27–9.9 mg) with deposition and aging times (0–120 min). The initial deposition is amorphous and forms the crystalline material during the elevated temperature aging step. The active material, α -MnO 2 , was also deposited on C-cloth and these cathodes at deposition times of 3, 6, and 9 min deliver 9, 36, and 69% higher areal capacities, respectively, at 0.2 mA cm −2 compared to conventional 2D electrodes with a mass loading equal to the 3 min sample. These results demonstrate the benefit of α -MnO 2 within a porous architecture providing enhanced transport properties.

Electrochemistry↗

Multifidelity methods for uncertainty quantification of a nonlocal model for phase changes in materials

This study is devoted to the construction of a multifidelity Monte Carlo (MFMC) method for the uncertainty quantification of a nonlocal, non-mass-conserving Cahn-Hilliard model for phase transitions with an obstacle potential. Here, we are interested in estimating the expected value of an output of interest (OoI) that depends on the solution of the nonlocal Cahn-Hilliard model. As opposed to its local counterpart, the nonlocal model captures sharp interfaces without the need for significant mesh refinement. However, the computational cost of the nonlocal Cahn-Hilliard model is higher than that of its local counterpart with similar mesh refinement, inhibiting its use for outer-loop applications such as uncertainty quantification. The MFMC method augments the desired high-fidelity, high-cost OoI with a set of lower-fidelity, lower-cost OoIs to alleviate the computational burden associated with nonlocality. Most of the computational budget is allocated to sampling the cheap surrogate models to achieve speedup, whereas the high-fidelity model is sparsely sampled to maintain accuracy. For the non-mass-conserving nonlocal Cahn-Hilliard model, the use of the MFMC method results in, for a given computational budget, about an order of magnitude reduction in the mean-squared error of the expected value of the OoI relative to that of the Monte Carlo method.

97 MATHEMATICS AND COMPUTING↗

Cluster Expansion Analysis of Atomic Order in Li-Ion Battery Cathode Material LiCo y Ni 1-y O 2

A modified cluster-expansion treatment was developed recently to analyze atomic order in LiCo y Ni 1-y O 2 , a model cathode material for Li-ion batteries. In this treatment, referred to as a “spin-atom” cluster expansion, the occupant of a lattice site is identified by its spin state as well as its atomic species. Further, Effective Cluster Interaction (ECI) coefficients are derived from a large training data set (i.e., the set of atomic arrangements for which DFT calculations are performed) which is filtered by an anomaly detection algorithm to eliminate poorly converged DFT calculations. The cluster expansion incorporates Li-Ni (LN) exchange as well as intralayer Co-Ni (CN) exchange. Monte Carlo simulations based on the cluster expansion were applied to the Ni-rich part of the phase diagram. The simulations predict a miscibility gap between y = 0.05 and y = 0.65.

25 ENERGY STORAGE↗

A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions

Modeling of heterogeneous materials and media is a problem of fundamental importance to a wide class of phenomena and systems, ranging from condensed matter physics, soft materials, and composite media to porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science and even in space discoveries. Among the most important materials are granular systems, which have received intense interest from the engineering, physics, and mathematics communities. In this review paper, the recent developments and new advances in experimental, and computational methods on a variety of scales and physics that extend understanding to a wide range of materials and phenomena are reviewed. Experimental advances include computed neutron and nanometer-scale tomography, magnetic resonance imaging, refractive index matching, digital image correlation, acoustic emission analysis, and the most recent 4D techniques. Furthermore, a tremendous shift has occurred from the continuum scale to micro-scale and developing multiscale approaches. As such, various computational methods, including, constitutive modeling, discrete modeling, and multiscale approaches, have been developed. In conclusion, aside from all these evolutions, more complicated modeling called coupled, or multiphysics, systems representing a simultaneous presence of heat, fluid, chemical variation, and mechanical effect are also explored.

36 MATERIALS SCIENCE↗

Accumulation of sedimentary debris in the south polar region of Mars and implications for climate history

A detailed modeling of the observed crater populations in stratigraphic unit mappings of the Martian south pole region is presently used to establish absolute constraints on the age of materials' emplacement. Modeling results indicate that cratered terrains poleward of 65 deg south latitude have subsequently experienced a steady-state net accumulation of materials at about 0.1 km/Ga; equatorial cratered terrains have by contrast retained a virtually pristine form.

Plaut, J. J.↗

Neural Network Molecular Dynamics at Scale

Neural network molecular dynamics (NNMD) simulations could revolutionize atomistic modeling of materials with quantum-mechanical accuracy at a fraction of computational cost. However, popular NNMD frameworks are generally implemented for a single computing node, and conventional energy-based NN models still suffer from large time-to-solution (T2S), prohibiting the application of NNMD to challenging materials simulations encompassing large spatiotemporal scales. Consequently, no leadership-scale NNMD simulation has thus far been reported. Here, we present a scalable parallel NNMD software (RXMD-NN) based on our scalable reactive molecular dynamics simulation engine named RXMD. RXMD-NN has achieved high scalability up to 786,432 IBM BlueGene/Q cores involving 1.7 billion atoms. Furthermore, we have achieved 4.6-fold reduction of T2S by using a novel network that directly predicts atomic forces from feature vectors. Reduced T2S has for the first time allowed the study of large-scale off-stoichiometry effect in a widely used phase change material, Ge 2 Se 2 Te 5 , thereby resolving its "firstsharp diffraction peak mystery".

fist sharp diffraction peak↗