Visualization of Time-Varying Data from Atomistic Simulations and Computational Fluid Dynamics

Time-varying data from simulations of dynamical systems are rich in spatio-temporal information. A key challenge is how to analyze such data for extracting useful information from the data and displaying spatially evolving features in the space-time domain of interest. We develop/implement multiple approaches toward visualization-based analysis of time-varying data obtained from two common types of dynamical simulations: molecular dynamics (MD) and computational fluid dynamics (CFD). We also make application case studies. Parallel first-principles molecular dynamics simulations produce massive amounts of time-varying three-dimensional scattered data representing atomic (molecular) configurations for material system being simulated. Rendering the atomic position-time series along with the extracted additional information helps us understand the microscopic processes in complex material system at atomic length and time scales. Radial distribution functions, coordination environments, and clusters are computed and rendered for visualizing structural behavior of the simulated material systems. Atom (particle) trajectories and displacement data are extracted and rendered for visualizing dynamical behavior of the system. While improving our atomistic visualization system to make it versatile, stable and scalable, we focus mainly on atomic trajectories. Trajectory rendering can represent complete simulation information in a single display; however, trajectories get crowded and the associated clutter/occlusion problem becomes serious for even moderate data size. We present and assess various approaches for clutter reduction including constrained rendering, basic and adaptive position merging, and information encoding. Data model with HDF5 and partial I/O, and GLSL shading are adopted to enhance the rendering speed and quality of the trajectories. For applications, a detailed visualization-based analysis is carried out for simulated silicate melts such as model basalt systems. On the other hand, CFD produces temporally and spatially resolved numerical data for fluid systems consisting of a million to tens of millions of cells (mesh points). We implement time surfaces (in particular, evolving surfaces of spheres) for visualizing the vector (flow) field to study the simulated mixing of fluids in the stirred tank

Visual Analytics and Modeling of Materials Property Data

Due to significant advancements in experimental and computational techniques, materials data are abundant. To facilitate data-driven research, it calls for a system for managing and sharing data and supporting a set of tools for effective data analysis and modeling. Generally, a given material property M can be considered as a multivariate data problem. The dimensions of M are the values of the property itself, the conditions (pressure P, temperature T, and multi-component composition X) that control the concerned property, and relevant metadata I (source, date). Here we present a comprehensive database considering both experimental and computational sources and an innovative visual analytics system for melt viscosity (η), which can be represented by M (η, P, T, X1, X2, …, I1, I2, …). We implemented the parallel coordinates plot (PCP) method by introducing new non-standard features, such as derived axes/sub-axes, dimension merging, binary scaling, and nested plots. Thus enhanced PCP offers many insights of relevance to underlying physics, data modeling, and guiding future experiments/computations. The construction of viscosity models is a non-trivial process, and extant models are often limited to a sub-parameter space, such as the ambient pressure conditions. To develop a generalized model which applies to wider parameter space, we trained various machine learning models, including neural network, Decision Tree, Random Forest, and XGBoost. We evaluated model performance based on loss function, error distribution, and model continuity. Our results show that neural network models outperformed the physics-based models as well as all tree-based models. A small neural network with two hidden layers, each containing 64 nodes, was found to be sufficient to model both the ambient pressure and complete dataset. Despite a marginal decrease in RMSE, a larger neural network consisting of four hidden layers with 128 nodes in each layer could provide an even better fit for the complete dataset in terms of model continuity and error distribution. Tree-based models could follow the training data, but the model results show high variations with small changes in parameter space, making them less applicable for continuous numerical data. Our data visualization and modeling approach is expected to be useful to researchers who explore and model material data, for instance, the density property can be incorporated as a new attribute in our system

Boston College Environmental Center Summer Institute on Surtsey and Iceland

Studying geology, geochemistry, and biology of Iceland and Surtsey as examples of new and extreme environment

2017 Summer Intern Program for Undergraduates

Sponsored by Lunar and Planetary Institute, NASA Johnson Space CenterSediment Transport and Aqueous Alteration in a Mars-Analog Glacial System / Emily Bamber--Geology of the Lunar Moscoviense Basin / Samuel Cartwright--Shallow Subsurface Investigations of Schrodinger Basin's Peak Ring Using Grail Gravity Data / Samuel Courville--Effects of Martian Surface Materials on the Thermal Decomposition of Hydrogen Peroxide / Rudger Dame--Integrating Diverse Datasets to Assess Approaches for Characterizing Mare Basalts / Sarah Deitrick--Water Retention in Mature and Immature Lunar Regolith / Abigail Flom--A Petrological Assessment of Shock Deformation in Uplifted Wall Rock Strata at Barringer Meteorite Crater, Arizona / Justine Grabiec--Age of Volcanism North and East of the Aristarchus Crater / Maia Madrid--An Impact Origin for the Bakisat Radar Dark Streak on Venus / Sabrina Martinez--Petrological Investigations of Volatile-Bearing Lunar Granophyres / Megan Mouser--Coordinated Analysis of Organic Matter in Primitive Meteorites / Nicole Nevill--Formation and Characterization of Akaganeite with Mars-Relevant Anions / Michelle Pan--Aqueous Alteration of Clay Minerals / Amanda Rudolph--Topographical Analyses of the Mercurian Hollows and Lunar Irregular Mare Patches / Jason Tremblay--Survival of Carbon Delivered to the Martian Surface from Interplanetary Dust Particles / Anna Zhuravlova

The Mistastin Lake Impact Structure As A Terrestrial Analogue Site For Lunar Science And Exploration

The impact cratering record on the Moon is important for many reasons, from understanding early solar system chronology to probing the lunar interior. In order to maximize scientific return from future lunar missions, it is useful to: 1) study terrestrial impact craters to better understand impact processes and products, and 2) develop appropriate human and robotic exploration strategies aligned with geological goals. This research shows that the intermediate-size Mistastin Lake impact structure, in northern Labrador, Canada, is an unparalleled lunar analogue site, which includes both an anorthositic target and an almost complete suite of impact lithologies, including proximal ejecta deposits. New remote sensing, field mapping, and microscopy data are used to develop new structural and geological models of the Mistastin Lake impact structure. The results of this study show that a multi-stage ejecta emplacement model is required to explain the observations. It is also shown that impact melt-bearing breccias or “suevites” at Mistastin were emplaced as flows, were never airborne, and were formed from the mixing of impact melt flows with underlying lithic materials. In order to maximize scientific return from future lunar missions, this work also focused on developing appropriate human and robotic exploration strategies aligned with geological goals. We show that precursor reconnaissance missions provide surface geology visualization at resolutions and from viewpoints not achievable from orbit. Within such a mission concept, geological tasks are best divided between fixed-executional approaches, in which tasks are fairly repetitive and are carried out by an unskilled surface agent, and an adaptive-exploratory approach, where a skilled agent makes observations and interpretations and the field plan can adapt to these findings as the agent progresses. Operational considerations that help increase scientific return include: extensive pre-mission planning using remote sensing data; defining flexible plans and science priorities to respond to changing conditions; including mutually cross-trained scientists and engineers on the field team; and adapting traverses to accommodate field crew input and autonomy. A phased approach for human exploration proved successful in incorporating astronaut feedback and allowed more autonomy for astronauts to determine optimal sampling localities and sites for detailed observations

Spatial-Statistical Properties of Geochemical Variability as Constraints on Magma Transport and Evolution Processes at Ocean Ridges

The research presented in this thesis employs spatial and statistical properties of major element variability in basaltic lavas and mantle residues to constrain some of the processes and dynamics occurring beneath ocean ridge magmatic systems. Ocean ridges represent a critical setting for many geochemical fractionation processes involved in the chemical evolution of the silicate Earth, and are fundamental to the plate tectonic cycle. Because of the inherent inaccessibility, it remains an ongoing challenge to interpret the geochemistry of ocean ridge lavas and exposed mantle residues in order to extract information about the petrogenetic and geodynamic workings of ocean ridge magmatic systems. This endeavor continues to require a concerted effort, incorporating field work, laboratory experimentation and quantitative modeling, in which the identification of features in the spatial or statistical distribution of geochemical variability represents an important contribution. In the three main chapters of this thesis, I apply techniques of exploratory data analysis, computational statistics, and petrologic modeling to develop original ideas about the relationship between sampled major element variability and the effects of specific processes, both petrogenetic and scientific: crystallization, melt transport, and sampling. In Chapter 2, I use spatial patterns of mid-ocean ridge basalt (MORB) glass variability to test competing hypotheses about crystallization in the thermal boundary layer beneath ocean ridges. I develop the hypothesis that reactive crystallization (crystallization influenced by chemical exchange with surrounding peridotite) could result in a different geochemical evolution of crystallizing magmas than expected for fractional crystallization. According to this hypothesis, fractionation-corrected MORB variability could be caused largely by sample-to-sample variations in the relative extents of reactive versus fractional crystallization. I demonstrate that MORB major element variability observed within 30-km-scale spatial bins contains 40-70 percent of globally observed variability, consistent with the predicted effects of reactive crystallization, but inconsistent with mantle temperature variations. Chapter 3 considers the effect of spatially heterogeneous sampling on apparent variability in MORB glasses. I demonstrate that MORB variability, as represented by the PetDB MORB glass database, contains large variability in sampling density, leading to significant artifacts in the estimated relative frequency of different MORB compositions. I introduce a method for removing these artifacts, and show that the increase in MORB data availability over the past decades has not been sufficient to increase significantly the resolution with which major element variability systematics can be studied at global or regional length scales, at least in comparison to early syntheses of global MORB data. Chapter 4 examines statistical variability within spatially defined volumes of mantle residue exposed in the Oman ophiolite. I provide a preliminary map of intermediate-scale compositional variability within the southernmost Oman ophiolite massif, in which multiple, spatially coherent, compositionally distinctive, 20-100 sq. km regions are resolved, representing the first mapping of compositional mantle domains at this length scale anywhere in the world. I interpret the observations as the consequence of regionally distinctive internal proportions of different mantle lithologies (e.g., dunite versus harzburgite), in turn reflecting the organization of focused melt transport at mid-ocean ridges into channel-rich and channel-poor zones

Numerical Simulations of Complex Crater Formation in Layered and Mixed Targets

Numerical simulations of hypervelocity impact events provide a unique method of analyzing the mechanics that govern impact crater formation. This thesis describes modifications that were made to the impact Simplified Arbitrary Lagrangian Eulerian (iSALE) shock-physics code in order to more accurately simulate meteorite impacts into layered target sequences and details several applications that were investigated using this improved strength model. Meteorite impacts occur frequently in layered targets but resolving thin layers in the target sequence is computationally expensive and therefore not often considered in numerical simulations. To address this limitation iSALE was modified to include an anisotropic yield criterion and rotation scheme to simulate the effect of thin, weak layers interspersed in the target. A comparison of ~4000 impact simulations shows that this method reduces computational cost while replicating the morphology of the craters formed in the high-resolution simulations with multiple weak layers modelled in the target geometry. Simulating layering via material anisotropy tends to increase the diameter and reduce the depth of the crater relative to a crater formed in an unlayered, isotropic target. In agreement with field observations at the Haughton and Ries impact structures, layering also appears to be partially responsible for suppressing central uplift formation during crater modification. Comparisons of terrestrial impact structures suggest those that formed in sedimentary or mixed targets tend to have a smaller depth-diameter ratio relative to craters formed in purely crystalline targets. Furthermore, several complex craters that formed in relatively thick sedimentary sequences (e.g., Haughton, Ries, Zhamanshin) do not have a central peak. An additional suite of ~60 simulations of impacts into mixed sedimentary-crystalline targets were created to further study the influence of the sedimentary layer on crater formation. A thick sedimentary layer changes the cratering flow field; the enhanced lateral motion of the weakened sedimentary material results in a crater that has a greater final diameter and reduced final depth relative to a crater formed in a purely crystalline target. Stratigraphic uplift tends to increase with in thicker sedimentary targets, but the most uplifted material tends to be found at further radial distances from the point of impact