Prediction of crystallographic texture evolution and anisotropic stress-strain response during large plastic deformation in [alpha]-titanium alloys

A new Taylor-type polycrystalline model has been developed to simulate the evolution of crystallographic texture and the anisotropic stress-strain response during large plastic deformation in α-titanium alloys at room temperature. Crystallographic slip, deformation twinning, and slip inside twinned regions were all considered as contributing mechanisms for the plastic strain in the model. This was accomplished by treating the dominant twin systems in a given crystal as independent grains once the total twin volume fraction in that crystal reached a predetermined saturation value. The newly formed grains were allowed to independently undergo further slip and the concomitant lattice rotation, but further twinning was prohibited. New descriptions have been established for slip and twin hardening and the complex coupling between them. Good predictions were obtained for the overall anisotropic stress-strain response and texture evolution in several different monotonic deformation paths on annealed, initially textured samples of two different chemical compositions of α-titanium alloys.The polycrystalline plasticity model presented here is built on the Taylor assumption of uniform deformation gradient in all of the constituent grains. The effects of this gross simplification have been evaluated by comparing the predicted stress and strain distributions between Taylor model and the more sophisticated finite element models that relax the assumption of the uniform strain. The anisotropy of the plastic behavior was observed to strongly influence the deviation of the Taylor model predictions from the finite element model predictions when comparing the stress and strain distributions in deformed polycrystalline α-titanium with initially random texture.The slip parameters established using the crystal plasticity model developed here were utilized in a novel spectral framework, called Microstructure Sensitive Design (MSD), for constructing elastic-plastic property closures in hexagonal polycrystals. The main focus was on the influence of the crystallographic texture (in the hcp polycrystals) on the components of the macroscale anisotropic elastic stiffness, macroscale anisotropic tensile yield, and the macroscale R-ratios (ratio of the transverse strains in tensile deformation mode) exhibited by the material.Ph.D., Materials Science and Engineering -- Drexel University, 200

Prediction of crystallographic texture evolution and anisotropic stress-strain response during large plastic deformation in [alpha]-titanium alloys

A new Taylor-type polycrystalline model has been developed to simulate the evolution of crystallographic texture and the anisotropic stress-strain response during large plastic deformation in α-titanium alloys at room temperature. Crystallographic slip, deformation twinning, and slip inside twinned regions were all considered as contributing mechanisms for the plastic strain in the model. This was accomplished by treating the dominant twin systems in a given crystal as independent grains once the total twin volume fraction in that crystal reached a predetermined saturation value. The newly formed grains were allowed to independently undergo further slip and the concomitant lattice rotation, but further twinning was prohibited. New descriptions have been established for slip and twin hardening and the complex coupling between them. Good predictions were obtained for the overall anisotropic stress-strain response and texture evolution in several different monotonic deformation paths on annealed, initially textured samples of two different chemical compositions of α-titanium alloys.The polycrystalline plasticity model presented here is built on the Taylor assumption of uniform deformation gradient in all of the constituent grains. The effects of this gross simplification have been evaluated by comparing the predicted stress and strain distributions between Taylor model and the more sophisticated finite element models that relax the assumption of the uniform strain. The anisotropy of the plastic behavior was observed to strongly influence the deviation of the Taylor model predictions from the finite element model predictions when comparing the stress and strain distributions in deformed polycrystalline α-titanium with initially random texture.The slip parameters established using the crystal plasticity model developed here were utilized in a novel spectral framework, called Microstructure Sensitive Design (MSD), for constructing elastic-plastic property closures in hexagonal polycrystals. The main focus was on the influence of the crystallographic texture (in the hcp polycrystals) on the components of the macroscale anisotropic elastic stiffness, macroscale anisotropic tensile yield, and the macroscale R-ratios (ratio of the transverse strains in tensile deformation mode) exhibited by the material.Ph.D., Materials Science and Engineering -- Drexel University, 200

DF4LCZ: A SAM-Empowered Data Fusion Framework for Scene-Level Local Climate Zone Classification

Recent advancements in remote sensing (RS) technologies have shown their potential in accurately classifying local climate zones (LCZs). However, traditional scene-level methods using convolutional neural networks (CNNs) often struggle to integrate prior knowledge of ground objects effectively. Moreover, commonly utilized data sources like Sentinel-2 encounter difficulties in capturing detailed ground object information. To tackle these challenges, we propose a data fusion method that integrates ground object priors extracted from high-resolution Google imagery with Sentinel-2 multispectral imagery. The proposed method introduces a novel Dual-stream Fusion framework for LCZ classification (DF4LCZ), integrating instance-based location features from Google imagery with the scene-level spatial-spectral features extracted from Sentinel-2 imagery. The framework incorporates a Graph Convolutional Network (GCN) module empowered by the Segment Anything Model (SAM) to enhance feature extraction from Google imagery. Simultaneously, the framework employs a 3D-CNN architecture to learn the spectral-spatial features of Sentinel-2 imagery. Experiments are conducted on a multi-source remote sensing image dataset specifically designed for LCZ classification, validating the effectiveness of the proposed DF4LCZ. The related code and dataset are available at https://github.com/ctrlovefly/DF4LCZ

Anisotropic nanomechanical properties of bovine horn using modulus mapping

Bovine horns are durable that they can withstand an extreme loading force which with special structures and mechanical properties. In this paper, we apply quasi-static nanoindentation and modulus mapping techniques to research the nanomechanical properties of bovine horn in the transverse direction (TD) and longitudinal direction (LD). In quasi-static nanoindentation, the horn’s modulus and hardness in the inner layer and the outer layer demonstrated a gradual increase in both TD and LD. Laser scanning confocal microscopy (LSCM) revealed microstructure in the horn with wavy morphology in the TD cross-section and laminate in the LD cross-section. When using tensile tests or quasi-static nanoindentation tests alone, the anisotropy of the mechanical properties of bovine horn were not obvious. However, when using modulus mapping, storage modulus (E′), loss modulus (E″) and loss ratio (tan δ) are clearly different depending on the position in the TD and LD. Modulus mapping is proposed as accurately describing the internal structures of bovine horn and helpful in understanding the horn’s energy-absorption, stiffness and strength that resists forces during fighting

SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints

Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise information for diverse down-stream applications. Recent development of the Segment Anything Model (SAM), an advanced general-purpose segmentation model, has revolutionized this field, presenting new avenues for accurate and efficient segmentation. However, SAM is limited to generating segmentation results without class information. Consequently, the utilization of such a powerful general vision model for semantic segmentation in remote sensing images has become a focal point of research. In this paper, we present a streamlined framework aimed at leveraging the raw output of SAM by exploiting two novel concepts called SAM-Generated Object (SGO) and SAM-Generated Boundary (SGB). More specifically, we propose a novel object loss and further introduce a boundary loss as augmentative components to aid in model optimization in a general semantic segmentation framework. Taking into account the content characteristics of SGO, we introduce the concept of object consistency to leverage segmented regions lacking semantic information. By imposing constraints on the consistency of predicted values within objects, the object loss aims to enhance semantic segmentation performance. Furthermore, the boundary loss capitalizes on the distinctive features of SGB by directing the model's attention to the boundary information of the object. Experimental results on two well-known datasets, namely ISPRS Vaihingen and LoveDA Urban, demonstrate the effectiveness of our proposed method. The source code for this work will be accessible at https://github.com/sstary/SSRS.Comment: 10 pages, 4 figure

Transport properties and anisotropy in rare earth doped CaFe2As2 single crystals with Tc above 40 K

In this paper we report the superconductivity above 40 K in the electron doping single crystal Ca1-xRexFe2As2 (Re = La, Ce, Pr). The x-ray diffraction patterns indicate high crystalline quality and c-axis orientation. the resistivity anomaly in the parent compound CaFe2As2 is completely suppressed by partial replacement of Ca by rare earth and a superconducting transition reaches as high as 43 K, which is higher than the value in electron doping FeAs-122 compounds by substituting Fe ions with transition metal, even surpasses the highest values observed in hole doping systems with a transition temperature up to 38 K. The upper critical field has been determined with the magnetic field along ab-plane and c-axis, yielding the anisotropy of 2~3. Hall-effect measurements indicate that the conduction in this material is dominated by electron like charge carriers. Our results explicitly demonstrate the feasibility of inducing superconductivity in Ca122 compounds via electron doping using aliovalent rare earth substitution into the alkaline earth site, which should add more ingredients to the underlying physics of the iron-based superconductors.Comment: 21 pages, 7 figure

Facile synthesis of monodisperse Cu3SbSe4 nanoparticles and thermoelectric performance of Cu3SbSe4 nanoparticle-based materials

International audienceIn this study, large-scale synthesis of Cu3SbSe4 and Cu3Sb0.98Sn0.02Se4 nanoparticles with a narrow size distribution was achieved through a rapid-injection route. These nanoparticles showed a monodisperse and quasi-spherical morphology. The Cu3SbSe4 and Cu3Sb0.98Sn0.02Se4 nanoparticle-based bulk materials were then prepared by hot-pressed sinter of the nanoparticles, and their thermoelectric performances were systematically studied. Due to the reduced lattice thermal conductivity from enhanced phonon scattering at the grain interfaces of the bulk materials, the maximum ZT value of the Cu3Sb0.98Sn0.02Se4 bulk materials reached 0.50 at 575

Self-Repair of Rat Cortical Bone Microdamage after Fatigue Loading In Vivo

Bone microdamage can be repaired through bone remodeling induced by loading. In this study, a loading device was developed for improved efficiency and the self-repair process of bone microdamage was studied in ovariectomized rats. First, four-point bending fixtures capable of holding two live rats simultaneously were designed. Rats were loaded and subjected to a sinusoidal wave for 10,000 cycles. They were then divided into four groups to evaluate time points from 1 to 4 weeks in the microdamage repair process. The loaded right ulna was used for microdamage parameter analysis, and the loaded right radius was tested for mechanical properties. In all groups, microdamage consisted primarily of microcracks, which were observed in bone surrounding the force-bearing point. The values of the microdamage parameters were significantly lower at 3 weeks than at 2 weeks. However, none of the differences in mechanical properties between any four groups were statistically significant. This study shows that the improved application of loading in the form of bending for double-rat simultaneous administration was practical and efficient. These results suggest that microdamage was repaired between 2 weeks to 3 weeks after fatigue damage and microdamage is a more sensitive index of bone quality than mechanical properties