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At least 19 records

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A. Liever↗

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the predictive simulation capability, the GCD Program also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper will present the status of implementing and maturing particle-particle interaction constituent physics models essential in simulating the landing surface granular material flow under PSI effects. This gas-particle multi-phase interaction modeling of plume impingement flow on the extra-terrestrial soil material is performed with the Gas-Granular Flow Solver (GGFS) addressed in a companion paper. The response of regolith particle flow induced by lander PSI requires accurate representation of the regolith granular material fluidic behavior and gas-granular interactions. The lunar regolith, as the extreme example, is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking particle shapes for the very jagged particles. The combination of particle shape and size distribution has been identified as major drivers in the complex particle flow response and resulting crater shape characteristics of extraterrestrial granular material. Constituent models for spherical particles can be formulated directly from particle kinetics theory. Complex particle shapes can be modeled by gluing together elemental spherical shapes into composite particles, requiring a Discrete Element Model (DEM) particle kinetics modeling approach to extract data and formulate constituent models. Mixture constituent models for poly-disperse mixtures (i.e, containing distribution of particle sizes) have recently been developed. The required non-spherical particle mixture granular material response closure models are then obtained through small-scale unit physics DEM simulations for the range of particle shapes, mixtures and packing densities. The granular material response closure models are then implemented in the Eulerian granular flow formulation. This DEM-based constituent model extraction process and formulation of poly-disperse particle mixtures has been successfully developed by small business and academic partners in the development of the Gas-Granular Flow Solver (GGFS) simulation program simulation framework. The currently implemented capabilities have reached the capability level of modeling bi-disperse, non-spherical particle mixtures is being continuously extended towards computational modeling of full range irregular particle mixtures. Under the GCD project, this technology is being further developed, transferred to NASA analysts, and matured towards application readiness. The predictive simulation capability team under the GCD project has acquired the modeling tools and processes of the DEM based constituent model formulation from the GGFS development team and is developing the capability to replicate the existing process. This is the first important step towards the ability of the NASA team to independently perform such model development in a production setting. Further efforts are underway to migrate the DEM based model simulation process performed with the academic based tools to more capable Open Source, highly parallelized simulation tools for efficient operation on NASA HPC assets. Evaluation of the currently implemented (such as mono-disperse and bi-disperse spherical and irregular shape particle constituent model applications) and continuously evolving full-range particle physics models in the GGFS tool is performed by the NASA team to advance application readiness of the simulations. Application testing for complex PSI erosions and cratering scenarios such as the Apollo LM is performed for axi-symmetric and full 3D simulations to aid the tool developers in achieving practical application readiness for NASA projects. Important validation and application testing will further be performed against experimental data generated under the GCD PSI project experimental component.

Peter A Liever↗

Effect of particle shape on stratification in drying films of binary colloidal mixtures

The role of particle shape in evaporation-induced auto-stratification in polydisperse colloidal suspensions is explored with molecular dynamics simulations of mixtures of spheres and aspherical particles. A unified framework based on the competition between diffusion and diffusiophoresis is proposed to understand the effects of shape and size dispersity. In general, particles diffusing more slowly (e.g., larger particles) tend to accumulate more strongly at the evaporation front. However, larger particles have larger surface areas and therefore greater diffusiophoretic mobility. Hence, they are more likely to be driven away from the evaporation front via diffusiophoresis. For a rapidly dried bidisperse suspension containing small and large spheres, the competition leads to “small-on-top” stratification. Here, we employ a computational model in which the diffusion coefficient is inversely proportional to particle mass. For a mixture of spheres and aspherical particles with similar mass, the diffusion contrast is reduced, and the spheres are always enriched at the evaporation front as they have the smallest surface area for a given mass and, therefore, the lowest diffusiophoretic mobility. Furthermore, for a mixture of solid and hollow spheres that have the same outer radius and thus the same surface area, the diffusiophoretic contrast is suppressed, and the system is dominated by diffusion. Consequently, the solid spheres, which have a larger mass and diffuse more slowly, accumulate on top of the hollow spheres. Finally, for a mixture of thin disks and long rods that differ significantly in shape but have similar mass and surface area, both diffusion and diffusiophoresis contrasts are suppressed, and the mixture does not stratify.

Classical molecular dynamic simulations↗

Gas-Granular Simulation Framework for Spacecraft Landing Plume-Surface Interaction and Debris Transport Analysis

The Gas-Granular Flow Solver (GGFS) multi-phase flow computational framework has been developed to enable simulations of particle flows complex extra-terrestrial regolith materials. Particle flows of interest include the damage of unprepared landing sites from rocket plume impingement on Moon, Mars, and asteroids. The flow solver implements an Eulerian-Eulerian two-fluid model with fluid representation of the gas phase and granular phase to avoid the need to model billions of particle interactions. The granular phase is modeled as an Eulerian fluid with constituent physics closure models derived from first-principle Discrete Element Model (DEM) particle interaction simulations that capture the complex, non-linear granular particle interaction effects. Granular phase constituent models have been developed and integrated that address the complex, non-linear granular material mechanics complexities resulting from both: the irregular, jagged particle shapes and poly-disperse mixture effects encountered in extra-terrestrial regolith, with lunar regolith as the extreme. The GGFS capabilities are being integrated into a proven NASA plume-surface interaction and debris transport simulation framework featuring the Loci/CHEM CFD program and Debris Transport Analysis (DTA) post-processing tools for applications in robotic and human Moon and Mars lander development. Integration of the three simulation tool components. Loci/CHEM, GGFS, and DTA, into a coordinated simulation framework will enable time-accurate spacecraft landing simulations that account for the alteration of the landing surface through plume-induced cratering and the resulting redirection of plume impingement flow and debris transport. Initial implementation of this simulation framework and application examples will be presented.

Liever, Peter A.↗

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

The Predictive Simulation Capability development team of the STMD Game Changing Development sponsored PSI project is implementing computational simulation capability for the efficient and accurate prediction of Plume-Surface Interaction induced surface erosion and cratering in Martian and Lunar environments. The status of the Focus Area 3 of the PSI project in the generation and efficient application of accurate soil particle composition modeling in the Gas-Granular Flow Solver (GGFS) computational framework is presented. The process of constitutive closure model database generation using DEM particle interaction modeling for capturing the effects of irregular particle shape and poly-disperse mixture distribution effects is outlined. This capability has now been ported to NASA supercomputer assets and NASA engineers successfully demonstrated technology and skillset transfer in model generation for spherical and irregularly shaped, mono-disperse and bi-disperse mixture compositions. Assessment of the computational efficiency and practicality of the academic serially executed DEM tools on NASA supercomputers identified the need to migrate to a DEM framework capable of performing parallel simulations in a simultaneous process orchestrated in an automated setup, execution, database extraction, and dataset delivery ready for application simulations. The LIGGGHTS DEM toolset has been selected as the most suitable tool to migrate the DEM simulations. Once the soil model generation process is implemented, models capturing the shape and poly-dispersity effects will be generated to perform much refined validation simulations against the experiments performed under the PSI project. The application readiness of the soil models currently operational in GGFS was presented for the example of a full scale, 3-D simulation of the plume induced erosion and crater formation of the Apollo LM at an elevation of 5m above ground in a low pressure, near vacuum background.

Peter A Liever↗

Particle Interaction Physics Model Formulation for Plume-Surface Interaction Erosion and Cratering

The Predictive Simulation Capability development team of the STMD Game Changing Development sponsored PSI project is implementing computational simulation capability for the efficient and accurate prediction of Plume-Surface Interaction induced surface erosion and cratering in Martian and Lunar environments. The status of the Focus Area 3 of the PSI project in the generation and efficient application of accurate soil particle composition modeling in the Gas-Granular Flow Solver (GGFS) computational framework is presented. The process of constitutive closure model database generation using DEM particle interaction modeling for capturing the effects of irregular particle shape and poly-disperse mixture distribution effects is outlined. This capability has now been ported to NASA supercomputer assets and NASA engineers successfully demonstrated technology and skillset transfer in model generation for spherical and irregularly shaped, mono-disperse and bi-disperse mixture compositions. Assessment of the computational efficiency and practicality of the academic serially executed DEM tools on NASA supercomputers identified the need to migrate to a DEM framework capable of performing parallel simulations in a simultaneous process orchestrated in an automated setup, execution, database extraction, and dataset delivery ready for application simulations. The LIGGGHTS DEM toolset has been selected as the most suitable tool to migrate the DEM simulations. Once the soil model generation process is implemented, models capturing the shape and poly-dispersity effects will be generated to perform much refined validation simulations against the experiments performed under the PSI project. The application readiness of the soil models currently operational in GGFS was presented for the example of a full scale, 3-D simulation of the plume induced erosion and crater formation of the Apollo LM at an elevation of 5m above ground in a low pressure, near vacuum background.

Peter A Liever↗

Heat conduction in metal-filled polymers - The role of particle size, shape, and orientation

This paper presents a new type of analysis for predicting the thermal conductivity of disperse composites from the properties of the component phases and elementary characterizations of particle shapes and orientation. This analysis successfully predicted the sensitivity to particle shape which was confirmed by experiments also reported in this paper. These results suggest that highly elongated particles may be used to achieve dramatic modifications of thermal conductivity and the analysis presented here may be a useful tool in the design or development of disperse composites of specific thermal conductivity. The analysis may also apply to other properties such as electrical conductivity or magnetic permeability.

Hansen, D.↗

Particle shape and magnetization of chondrite meteorites, lunar samples, and impactites

Extra terrestrial materials, certain materials which have their origin at the earth's surface due to meteoritic impact, or under highly reducing conditions, such as in the case of basaltic flows in contact with coal beds or serpentenites, all contain Fe and FeNi phases with high magnetization values and spherical shape. Normally, the demagnetizing field (H sub D = NI sub S: where N is the demagnetizing factor and I is the saturation magnetization) is corrected for. In disperse systems, such as most natural materials, the particle shape effects are analyzed in terms of the saturation fields, Hs = H sub D = NI sub S and the magnetization differences (Delta I sub S). Discrete size modes of superparamagnetic (SP), multidomain (MD), and single domain (SD) particles result in reduced coercive force (Hc), increase in the value R sub H (ratio of remanent coercive force, H sub R, to H sub C), and decrease in the value R sub I (ratio of remanent magnetization, I sub R, to saturation magnetization, T sub S). The main distinctions between the various natural materials can be made by this approach. Hysteresis loops for terrestrial basalts, Fe and Ni rods and spheres, chondrite meteorites, lunar samples, impactites, and chondritic fusion crust are presented.

Wasilewski, P.↗

Global quantification of the dispersion effect with POLDER satellite data

Increased aerosols can modify the shape of the cloud Particle Size Distribution (PSD), thereby influencing the radiative properties of clouds, known as the Dispersion Effect (DE). However, a global, observation-based quantification of its impact on Aerosol-Cloud Interactions (ACI) is lacking, leading to DE being typically ignored in satellite-based estimates of ACI forcing. Here we propose a physics-based method that combines polarimetric satellite data on cloud PSD to achieve global observational quantification of DE’s impact on ACI in liquid-phase stratiform clouds. Globally, DE offsets ACI changes induced by droplet number concentration variation and liquid water path adjustment by 7% and −1.4%, respectively. Furthermore, a parameterization based on the global dataset of PSD shape parameters is developed to improve DE estimation in large-scale models. Both the quantification and parameterization enhance our understanding of DE and facilitate the inclusion of this non-negligible impact of DE on ACI in estimating aerosol climate forcing.

54 ENVIRONMENTAL SCIENCES↗

Identifying Sample Provenance From SEM/EDS Automated Particle Analysis via Few-Shot Learning Coupled With Similarity Graph Clustering

Automated particle analysis (APA) provides a vast amount of compositional data via energy-dispersive X-ray spectroscopy along with size and shape data via scanning electron microscopy for individual particles in a sample. In many instances, APA data are leveraged to support identification of the source of a sample based on the detection of particles of a specific composition. Often, the particles that provide context make up a minuscule portion of the sample. Additionally, the interpretation of complex samples can be difficult due to the diversity of compositions both in the mixture and within a particle. In this work, we demonstrate a method to compute and cluster similarity graphs that describe inter-particle relationships within a sample using a multi-modal few-shot learning neural network. Here, as a proof-of-concept, we show that samples known to have been exposed to gunshot residue can be distinguished from samples occasionally mistaken for gunshot residue. Our workflow builds upon standard APA techniques and data processing methods to unveil additional information in a readily interpretable and quantitatively comparable format.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Chiral, Topological, and Knotted Colloids in Liquid Crystals

The geometric shape, symmetry, and topology of colloidal particles often allow for controlling colloidal phase behavior and physical properties of these soft matter systems. In liquid crystalline dispersions, colloidal particles with low symmetry and nontrivial topology of surface confinement are of particular interest, including surfaces shaped as handlebodies, spirals, knots, multi-component links, and so on. These types of colloidal surfaces induce topologically nontrivial three-dimensional director field configurations and topological defects. Director switching by electric fields, laser tweezing of defects, and local photo-thermal melting of the liquid crystal host medium promote transformations among many stable and metastable particle-induced director configurations that can be revealed by means of direct label-free three-dimensional nonlinear optical imaging. The interplay between topologies of colloidal surfaces, director fields, and defects is found to show a number of unexpected features, such as knotting and linking of line defects, often uniquely arising from the nonpolar nature of the nematic director field. This review article highlights fascinating examples of new physical behavior arising from the interplay of nematic molecular order and both chiral symmetry and topology of colloidal inclusions within the nematic host. Furthermore, the article concludes with a brief discussion of how these findings may lay the groundwork for new types of topology-dictated self-assembly in soft condensed matter leading to novel mesostructured composite materials, as well as for experimental insights into the pure-math aspects of low-dimensional topology.

chirality↗

An ET Origin for Stratospheric Particles Collected during the 1998 Leonids Meteor Shower

On 17 November 1998, a helium-filled weather balloon was launched into tfle strato- sphere, equipped with a xerogel microparticle collector. The three-hour flight was designed to sample the dust environment in the stratosphere during the Leonid meteor shower, and possibly to capture Leonid meteoroids. Environmental Scanning Election Microscope analyses of the returned collectors revealed the capture of a -30-pm particle. with a smooth, multigranular shape, and partially melted, translucent rims; similar to known Antarctic micrometeorites. Energy-dispersive X-ray Mass Spectroscopy shows en- riched concentrations of the non-volatile elements, Mg, Al, and Fe. The particle possesses a high magnesium to iron ratio of 2.96, similar to that observed in 1998 Leonids meteors (Borovicka, et al. 1999) and sharply higher than the ratio expected for typical material from the earth's crust. A statistical nearest-neighbor analysis of the abundance ratios Mg/Si, Al/Si, and Fe/Si demonstrates that the particle is most similar in composition to cosmic spherules captured during airplane flights throucrh the stratosphere. The mineralogical class is consistent with a stony (S) type of silicates. olivine [(Mg, Fe)2SiO4] and pyroxene [(Mg,Fe)SiO3]-or oxides, herecynite [(Fe,Mg) Al2O4]. Attribution to the debris stream of the Leonids' parent body, comet Tempel-Tuttle, would make it the first such material from beyond the orbit of Uranus positively identified on Earth.

Noever, David A.↗

Electron Beam Welding of Pure Tungsten Hex Cans for Nuclear Thermal Propulsion Engines

Nuclear thermal propulsion (NTP) is an in-space propulsion method currently being developed at the NASA Marshall Space Flight Center (MSFC). NTP systems are a high specific impulse (750–1,100 s), high thrust (15,000–250,000 lbf ) method of propulsion which have the potential to allow for faster transit times when optimizing for high ΔV. In the nuclear rocket engine, the heat from the nuclear fission reaction is transferred to a low molecular mass propellant (such as hydrogen). Hot propellant is expanded through a nozzle to generate thrust. Development of ceramic metal (cermet) fuel systems for NTP applications is currently ongoing at MSFC. In cermet fuel systems, ceramic fissile fuel particles such as uranium nitride or uranium dioxide are dispersed within a net-shaped, high-density structural matrix. The composite material is cladded by a protective metal structure to make up an NTP fuel element. Cladding materials must be able to withstand the demanding operating conditions required of the engine as well as retain a hermetic seal to allow for retention of fuel element structural integrity, prevent hydrogen attack or migration of the ceramic fuel, and limit release of fission products during operation. For NTP applications, tungsten is a prime material for both the metal matrix and cladding in cermet fuel systems because of its high melting point, high temperature strength, and compatibility with hot hydrogen. If a weld in tungsten with the capability of holding a hermetic seal is achievable, tungsten becomes a strong candidate for NTP applications. This Technical Memorandum focuses on determining the weldability of pure tungsten using electron beam welding (EBW). Tungsten appears well suited for NTP applications, but it has a high ductile to brittle transition temperature (DBTT) dependent upon chemical composition, structure/stress distribution, and mechanical conditions. Therefore, it is highly subject to brittle fracture. Because of its high susceptibility to brittle fracture, it is very difficult to weld. EBW was chosen for joining pure tungsten because of its low heat input compared to gas tungsten arc welding. Reduced heat input can be directly correlated with an increase in ductility of a tungsten weld. EBW is a high energy density welding process in which a stream of electrons penetrates a weld joint in a deep, narrow spike in contrast to a broad gas tungsten arc weld pool. The investigation initially focused on EBW of tungsten plates of both 0.01 in and 0.03 in thickness to determine if EBW could weld pure tungsten without the presence of visual defects—particularly cracking—in the welds. Variation in the weld procedure and post-weld heat treatment (PWHT) was used to improve the surface appearance of flat EBWs on a pure tungsten sheet. The investigation moved on to weld 0.05-in-thick hexagonal tungsten cans with a weld joint thickness of 0.025 in. The goal for welding the pure tungsten hex cans was to avoid any visual surface defects and generate a weld capable of a hermetic seal. This proved difficult. Cold welds commonly exhibited porosity that leaked air. Hot welds exhibited cracks, typically observed immediately after welding. Later welds were preheated to increase ductility and decrease the likelihood of through-thickness cracking. PWHT was used to arrest microcrack growth both in the flat weld samples and hexagonal weld samples.

Courtright, Z. S.↗

Hematite at Meridiani Planum and Gusev Crater as identified by the Moessbauer Spectrometer MIMOS II

The Moessbauer (MB) spectrometers on the MER rovers Opportunity and Spirit, which landed on Mars in January 2004, have identified the iron-containing mineral hematite (a-Fe2O3) at both landing sites. On Earth, hematite can occur either by itself or with other iron oxides as massive deposits, in veins , and as particles dispersed through a silicate or other matrix material. Hematite particle size can range from nanophase (superparamagnetic) to multidomain and particle shape ranges from equant to acicular to platy. Fine-grained hematite is red in color and is a pigmenting agent. Coarse-grained hematite can be spectrally neutral (gray) at visible wavelengths. Substitutional impurities, particularly Al, are common in hematite. Chemically pure, coarse-grained, and well-crystalline hematite has a magnetic transition (the Morin transition) at ~260 K. Moessbauer spectra, recorded as a function of temperature, provide a way to characterize Martian hematite with respect to some of the physical and chemical characteristics. At Meridiani Planum besides the iron-sulfate mineral jarosite also the Fe-oxide hematite has been identified by the Moessbauer spectrometer, mainly in three distinct types of reservoir: - outcrop matrix material dominated by the mineral jarosite in the MB spectrum, certain basaltic soils, and mm-sized spherules dubbed blueberries. Moessbauer spectra of each reservoir yield a distinct set of hyperfine parameters for hematite, suggesting different degrees of crystallinity and particle size. The hematite found by MB instrument MIMOS II in the outcrop material shows the Morin transition at relatively high temperatures (ca. 250 K) which is an indication of pure and well-crystallized hematite. The source of the hematite in the Blueberries as identified by Moessbauer spectroscopy, and also by MiniTES, is not known. These spherules, covering nearly the whole landing site area (Eagle crater, plains, Endurance crater), may be concretions formed in the outcrop involving aqueous processes. They are dispersed throughout the hematite containing jarositic outcrop material. According to Moessbauer analysis the dominating iron-bearing mineral in the spherules is hematite, and jarosite not been detected so far in significant amounts. But there are some places with hematite showing characteristics different from the hematite described above: (1) the soil at B023_HematiteSlope_Hema2 has some blueberries, but the MB did not seem to intercept any. The temperature dependence of its MB parameters are different from those of blueberries. (2) B049_RasberryNewton_Filling shows a unique Hm MB signature, as well as (3) B051_RealSharksTooth_Enamel1.

Klingelhoefer, G.↗

Rheological properties of nondilute suspensions of deformable particles

The creeping flow equations have been solved to account for effects of shear on drop shape when the influence of neighboring drops is considered. A cell model is used to account for finite concentrations of the dispersed phase. From these results a constitutive equation is derived and implications for several flows are discussed. The shape and orientation of drops are computed and compared with existing data. Finally, dynamic viscosity and rigidity are obtained for nondilute suspensions of viscoelastic particles in an oscillatory shear flow.-

Choi, S. J.↗