Thermal Effects at Continent-Ocean Transform Margins: A 3D Perspective

Continental breakup along transform margins produces a sequence of (1) continent-continent, (2) continent-oceanic, (3) continent-ridge, and (4) continent-oceanic juxtapositions. Spreading ridges are the main sources of heat, which is then distributed by diffusion and advection. Previous work focused on the thermal evolution of transform margins built on 2D numerical models. Here we use a 3D FEM model to obtain the first order evolution of temperature, uplift/subsidence, and thermal maturity of potential source rocks. Snapshots for all four transform phases are provided by 2D sections across the margin. Our 3D approach yields thermal values that lie in between the previously established 2D end-member models. Additionally, the 3D model shows heat transfer into the continental lithosphere across the transform margin during the continental-continental transform stage ignored in previous studies. The largest values for all investigated quantities in the continental area are found along the transform segment between the two ridges, with the maximum values occurring near the transform-ridge corner of the trailing continental edge. This boundary segment records the maximum thermal effect up to 100 km distance from the transform. We also compare the impact of spreading rates on the thermal distribution within the lithosphere. The extent of the perturbation into the continental areas is reduced in the faster models due to the reduced exposure times. The overall pattern is similar and the maximum values next to the transform margin is essentially unchanged. Varying material properties in the upper crust of the continental areas has only a minor influence.

Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients

Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disease. Chest X-ray is currently accepted to be one of the reliable means for such a detection purpose. However, most of the available methods utilize large training data, and there is a need for improvement in the detection accuracy due to the limited boundary segment of the acquired images for symptom identifications. In this study, a robust and efficient method based on transfer learning techniques is proposed to identify normal and COVID-19 patients by employing small training data. Transfer learning builds accurate models in a timesaving way. First, data augmentation was performed to help the network for memorization of image details. Next, five state-of-the-art transfer learning models, AlexNet, MobileNetv2, ShuffleNet, SqueezeNet, and Xception, with three optimizers, Adam, SGDM, and RMSProp, were implemented at various learning rates, 1e-4, 2e-4, 3e-4, and 4e-4, to reduce the probability of overfitting. All the experiments were performed on publicly available datasets with several analytical measurements attained after execution with a 10-fold cross-validation method. The results suggest that MobileNetv2 with Adam optimizer at a learning rate of 3e-4 provides an average accuracy, recall, precision, and F-score of 97%, 96.5%, 97.5%, and 97%, respectively, which are higher than those of all other combinations. The proposed method is competitive with the available literature, demonstrating that it could be used for the early detection of COVID-19 patients.

Seismicity, Stress State, and Style of Faulting of the Ridgecrest-Coso Region from the 1930s to 2019: Seismotectonics of an Evolving Plate Boundary Segment

ABSTRACT Decadal scale variations in the seismicity rate in the Ridgecrest-Coso region, part of the Eastern California Shear Zone, included seismic quiescence from the 1930s to the early 1980s, followed by increased seismicity until the 2019 Mw 6.4 and 7.1 Ridgecrest sequence. This sequence exhibited complex rupture on almost orthogonal faults and triggered aftershocks over an area of ∼90 km long by ∼5–10 km wide, which is a fraction of the area of the previously seismically active Indian Wells Valley and Coso range region. During the last 40 yr, the seismicity has been predominantly the result of strike-slip motion, extending north from the Garlock fault, along the Little Lake and Airport Lake fault zones, and approaching the southernmost Owens Valley fault to the north. The Coso range forms an extensional stepover between these two strike-slip fault systems. This evolution of a plate boundary zone is driven by the northwestward motion of the Sierra Nevada, and crustal extension along the southwestern edge of the Basin and Range Province. Stress inversion of focal mechanisms shows that the postseismic stress state consists of almost horizontal σ1 and vertical σ2. The σ1 is spatially rotated across the Coso range stepover with σ1-trending ∼N17° E to the north, whereas, along the Mw 7.1 mainshock rupture, the trend is ∼N6° E. The friction angles as measured between fault strikes and the σ1 trends correspond to a frictional coefficient of 0.75, suggesting average fault strength. In comparison, the mature Garlock fault has a smaller frictional coefficient of 0.28, similar to weak faults like the San Andreas fault. Thus, it appears that the heterogeneously oriented and spatially distributed but strong Ridgecrest-Coso faults accommodate seismicity at seemingly random places and times within the region and are in the process of self-organizing to form a major throughgoing plate-boundary segment.

Intergranular Fracture Prediction and Microstructure Design

A model based on discrete unit events coupled with a graph search algorithm is developed to predict intergranular fracture. The model is based on two hypotheses: (i) the key unit event associated with intergranular crack propagation is the interaction of a grain boundary crack with a grain boundary segment located at an angle with the initial crack plane; and (ii) for a given crack path, the overall crack growth resistance can be calculated using the crack growth resistance of a collection of unit events. Next, using a directed graph containing the connectivity of grain boundary junctions and the distances between them, and crack deflection versus crack growth resistance data, a directed graph in the J-resistance space is created. This graph contains information on the crack growth resistance for all possible crack paths in a given grain microstructure. Various crack growth resistance curves are then calculated including those corresponding to: (i) a local resistance minimum; (ii) a global minimum; and (iii) for verification, a path specified by microstructure-based finite element calculations. The results show that the proposed method based on discrete unit events and graph search can predict the crack path and the crack growth resistance for cracks that propagate from one grain boundary junction to another. The proposed computationally inexpensive model can be used to design material microstructures with improved intergranular fracture resistance, and/or to assess the overall crack growth resistance of materials with a known distribution of grain morphology.

Numerical simulation of steady state groundwater flow field in discretely fractured rocks using the Green element method with the concept of multiple interacting normal flux

<p>Numerical simulation is an effective tool for estimating the groundwater flow field in discretely fractured rocks (DFR). Unlike most numerical simulation methods that require the discretization of the model domain, boundary element method (BEM) is renowned of waiving the spatial discretization task but focusing on solving the integral form of the governing groundwater flow equation. However, for groundwater flow simulation in DFR, the solution obtained by BEM tends to have large error in the vicinity of fracture intersection. Therefore, a new numerical scheme, the green element method (GEM) is adopted in this study. GEM is built on the same mathematical background as BEM but turns the domain discretization back on as a necessary task. Using the second Green’s identity, GEM produces a general equation that applies to each grid block by integrating the governing equation. By making use of the singular characteristic of the Green’s function, GEM transforms the integral equation into a discretized system of equations with nodal head or nodal head gradient as unknowns. The cost of discretizing the model domain is compensated by the convenience of handling the heterogeneity of the medium. Conventional GEM manages the normal flux across a boundary segment by differentiating head values from 2 nodes in an individual grid block. This approximation overlooks the mechanism of normal flux as the exchange of fluid mass between grid blocks. To take this mechanism into consideration, a modified model of normal flux is proposed if the fracture plane is discretized into triangular elements. This model expresses the normal flux across a grid boundary segment in terms of the difference of head values in two grid blocks that are connected to this segment. For convenience, the head value at the centroid of a triangular element is used to calculate the normal flux. In other words, the unknowns of a triangular element are three nodal heads plus one centroidal head. Thus, the modified normal flux will be able to consider the interaction of all grid blocks that are connected to a target grid block. More importantly, the resulting global coefficient matrix is a square one and the system of equations is closed. The solution obtained from the closed system of equations will be exact but not a least-square approximated one. This modified GEM will be applied to simulate the steady state groundwater flow field in discretely fractured rocks.</p>

Predicting nucleation sites in chemotaxing Dictyostelium discoideum

Blebs, pressure driven protrusions of the plasma membrane, facilitate the movement of cell such as the soil amoeba Dictyostelium discoideum in a three dimensional environment. The goal of the article is to develop a means to predict nucleation sites. We accomplish this through an energy functional that includes the influence of cell membrane geometry (membrane curvature and tension), membrane-cortex linking protein lengths as well as local pressure differentials. We apply the resulting functional to the parameterized microscopy images of chemotaxing Dictyostelium cells. By restricting the functional to the cell boundary influenced by the cyclic AMP (cAMP) chemo-attractant (the cell anterior), we find that the next nucleation site ranks high in the top 10 energy values. More specifically, if we look only at the boundary segment defined by the extent of the expected bleb, then 96.8% of the highest energy sites identify the nucleation.Author summaryThis work concerns the prediction of nucleation sites in the soil amoeba-like Dictyostelium discoideum. We define a real valued functional combining input from cortex and membrane geometry such as membrane curvature and tension, cortex to membrane separation and local pressure differences. We show that the functional may be used to predict the location of bleb nucleation. In the region influenced by the cAMP gradient (the cell anterior), the next blebbing site lies in the ten highest energy functional values 70% of the time. The correctness increases to 96.8% provided we restrict attention to the segment in the general location of the next bleb. We verify these claims through the observation of microscopy images. The images are sequential at 1.66 and 0.8 seconds per image. We first identify the earliest sign of the bleb. We then use several observational factors to identify the nucleation site and estimate the corresponding location in the prior image.

Designing a waveform using LFM, NLFM for MIMO radar

We propose a waveform that includes Linear frequency modulation and non linear frequency modulation wave applicable for MIMO radar. The wave form consists of three segments where the boundary segment consists of LFM content and the middle segment consists of NLFM. The time frequency component in the middle segment is controlled. The range and Doppler side lobe suppression is improved. The genetic algorithm is implemented to suppress the side lobes in the auto correlation and cross correlation functions. The performance is analysed by using ambiguity function.

Application of the Particle Finite Element Method in Machining Simulation Discussion of the Alpha-Shape Method in the Context of Strength of Materials

In particle finite element simulations, a continuous body is represented by a set of particles that carry all physical information of the body, such as the deformation. In order to form this body, the boundary of the particle set needs to be determined. This is accomplished by the α-shape method, where the crucial parameter α controls the level of detail of the detected shape. However, in solid mechanics, it can be observed that α has an influence on the structural integrity as well. In this paper, we study a single boundary segment of a body during a deformation and it is shown that α can be interpreted as the maximum stretch of this segment. On the continuum level, a relation between α and the eigenvalues of the right Cauchy–Green tensor is presented.