Realistic Material Properties Research Articles

Statistical Modeling and Probable Calculation of the Strength of Materials with Random Distribution of Surface Defects

Based on the solutions of deterministic fracture mechanics and the methods of probability theory, the algorithm for calculating the probabilistic strength characteristics of plate elements of structures with an arbitrary stochastic distribution of surface defects is outlined. On the plate surface, there are uniformly distributed cracks that do not interact with each other, the plane of which is normal to the surface, and the depth is much less than its length on the surface. The cracks’ depth and angle of orientation are random values, and their joint distribution density is specified. Plates made of this material are under the influence of biaxial loading. The probability of failure, along with the mean value, the dispersion, and the variation coefficient of the plate’s strength, taking into account the surface defects under different types of stress, were determined. Their dependence on the type of loading, the size of the plate, and the surface structural heterogeneity of the material were studied graphically. Joint consideration of the influence of the interrelated properties of real materials, such as defectiveness and stochasticity, on strength and fracture, opens up new opportunities in creating a theory of strength and fracture of deformable solids.

Study on the effect of geometry and material property on collapse pressure of a helical steam generator tube under external pressure

In this paper, a numerical study was conducted to analyze the effect of the geometry (tube thickness, ovality, and helical diameter) and material properties of once through steam generator tubes subjected to external pressure on collapse pressure. The outer diameter of the steam generator tube was fixed at 17 mm, and the tube thickness was changed to 2.5 mm, 2.29 mm, and 1.27 mm. Ovality was considered for three cases of 0 %, 4 %, and 8 %, and three cases for helical diameter were considered: 577 mm, 937 mm, and 1297 mm. As material properties, elastic perfectly plastic property that ignores plastic hardening and real material property that reflect plastic hardening were considered. At the helical diameter (Dm/do ≥ 34) considered in this paper, the effect of collapse pressure due to helical bending did not appear on ovalities and both material properties. On the other hand, the wall thickness affected the collapse pressures according to the material properties when ovality occurred (>0 %). This is explained because the collapse mechanism varies depending on the thickness.

THERMAL SIMULATION OF THE CZOCHRALSKI PROCESS FOR SILICON CRYSTAL GROWTH USING FINITE ELEMENT MODELING APPROACH

This study investigates the thermal dynamics of the Czochralski (CZ) process for silicon crystal growth through numerical simulations. The simulation method of this study is based on finite element method (FEM) heat transfer simulation. The FEM simulation was performed using triangular mesh in half cross section of CZ system with real material properties. The analysis of heat transfer mechanisms includes conduction, convection, and radiation which reflect the impact of cooled argon convection on crystal growth. The simulations reveal that convection currents driven by cooled argon has a crucial role to promote uniform cooling which control crystal growth. This leads to enhanced mono-crystalline silicon ingot crystal quality and purity. Ultimately, insights gained from this study can inform optimization efforts in semiconductor manufacturing, facilitating advancements in electronic device fabrication.

Seismic Fragility Analysis of Existing Old Newari Brick Masonry Building in Pokhara Valley

Most of the building stock in Nepal is based on masonry construction, which includes monumental, administrative, and residential structures. These structures are vulnerable during earthquakes, as evidenced by the massive structural damage, loss of human life, and property damage due to a lack of proper assessment and appropriate strengthening measures. An analysis of the seismic vulnerability of existing old Newari brick masonry buildings in the Pokhara Valley is presented. These buildings were built using indigenous knowledge and technology. The investigation is based on analytical studies, with some material properties obtained from field tests. Proper modeling of a masonry structure is crucial for reliable seismic resistance and structural design. However, modeling a real masonry structure is a challenging and computationally demanding task due to its complicated framework, requiring in-depth knowledge, realistic material properties, and relevant information. The aim of this research is to assess the seismic performance of old Newari masonry buildings using stress level and fragility curves. The research issues are addressed analytically through linear time history analysis using the finite element program-based software Sap 2000 v20. In dynamic analysis, numerical building models were subjected to three synthetic earthquakes. The performance status of the building based on various stress levels is evaluated, and weak regions are identified. The fragility curve of the structure is assessed, considering the ground motion parameters in the locality. The fragility function is plotted with the probability of failure at an interval of 0.10 g. The results of the analysis highlight that the studied structure is vulnerable compared to the codal provisions and standard recommendations.

Novel Computational Design of Polymer Micromachined Insect-Mimetic Wings for Flapping-Wing Nano Air Vehicles.

The flapping wings of insects undergo large deformations caused by aerodynamic forces, resulting in cambering. Insect-mimetic micro wings for flapping-wing nano air vehicles mimic these characteristic deformations. In this study, a 2.5-dimensional insect-mimetic micro wing model for flapping-wing nano air vehicles is proposed to realize this type of wing. The proposed model includes a wing membrane, a leading edge, a center vein, and a root vein, all of which are modeled as shell elements. The proposed wing is a 2.5-dimensional structure and can thus be fabricated using polymer micromachining. We conducted a design window search to demonstrate the capabilities of the wing. The design windows, which are areas of desirable design solutions in the design parameter space, are iteratively searched using nonlinear finite-element analysis under quasi-steady aerodynamic modeling. Here, thickness is selected as a design parameter. The properties of real insects, polymer materials, and fabrication conditions are used to determine the other parameters. A fabricable design solution that generates sufficient camber is found from the design windows.

Performing FEM Analysis to Evaluate the Static and Thermal Characteristics of a Piston

This study presents a comprehensive Finite Element Method (FEM) analysis conducted using Fusion 360 software to evaluate the static and thermal characteristics of pistons fabricated from alumina and Aluminum 6061. The research aims to compare and contrast the performance of these two materials under typical engine operating conditions. The static analysis investigates stress distribution, deformation, and overall structural integrity of the pistons when subjected to mechanical forces and pressures experienced during engine operation. Simultaneously, the thermal analysis assesses temperature distribution and thermal stresses, providing insights into the pistons’ ability to withstand high temperatures. Detailed simulations were performed with realistic boundary conditions and material properties, allowing for a direct comparison of the performance of alumina, known for its high hardness and thermal stability, against Aluminum 6061, recognized for its lightweight and good thermal conductivity. The findings reveal distinct differences in stress handling, thermal management, and potential failure points between the two materials. This study offers critical insights into material selection and design optimization for enhancing piston performance and durability in modern engines.

Realistic material property prediction using domain adaptation based machine learning

Scientists aim to predict properties for a known subset of related out-of-distribution materials rather than universally distributed samples. Introducing target material information enhances machine learning models.

Used Isolation System to Reduce the Response of Offshore Structure Considering Soil Structure Interaction

Abstract Fixed offshore platforms are structures of steel or concrete located in the middle of the sea used to export oil, trade, or military. These are designed to withstand all types of weather and dynamic loads. The response was very high under applied these loads. This paper includes a proposal to apply a new isolation system to be placed in different places on the offshore platform to reduce vibrations from high water waves. Three cases that be used, fixed-based (column connect directly to the pile), isolation system in the pile head (isolation between column and pile), and isolation system in the pile head and the middle of columns. The dynamic movements in waves were simulated using ABAQUS programs. More accurate elements and real material properties were used to bring the results closer to reality. The Computational Fluid Dynamics (CFD) method was used to study the effect of water-structure interaction and soil-structure interaction. The results show that the use of the isolation system at the base of the offshore platform has a very significant effect on decreasing the response of the platform to the loads placed on it. Where the isolation system works as a hinge at the pile head and is not allowed to move and rotate for the pile, also the moments are zero. As for the shear force, it is the least that can be compared with the other cases.

Finite element solutions for bending analysis of simply supported two layered un-symmetric cross-ply (0/90) square plate under uniformly distributed transverse load

Laminated composite plates are extensively used in aerospace, military, civil infrastructure, and automotive industries due to their benefits, including superior fatigue resistance, high strength, and lightweight properties. Customizable fiber orientation, materials, and stacking patterns are additional advantages. Therefore, conducting rigorous analyses to evaluate deflections and stress levels in these plates is essential for maintaining structural integrity and optimal performance across various applications. The solutions presented in this study rely on the utilization of a higher-order shear deformation theory (HSDT), which offers a notably precise depiction of the plate's behavior. The theoretical model employed in this research accounts for deformations and the variation of stresses along the thickness direction. Finite element formulations are employed to derive the solutions. In order to ascertain the accuracy and reliability of the current formulations and solution methodologies, the obtained results are systematically compared with those documented in the existing literature. This rigorous comparison serves as a robust validation of the approach applied in this study. Once the accuracy of the solutions is established, numerical results for two layered cross-ply composites with real material properties are presented. These results are in good agreement with the findings reported in the literature. By incorporating Higher Order Shear Deformation Theory (HSDT), the accuracy of predictions is significantly enhanced. This improvement ensures a more dependable foundation for the design and optimization of composite structures.

Finite Element Simulation and Experimental Assessment of Laser Cutting Unidirectional CFRP at Cutting Angles of 45° and 90°.

Laser cutting of carbon fibre-reinforced plastics (CFRP) is a promising alternative to traditional manufacturing methods due to its non-contact nature and high automation potential. To establish the process for an industrial application, it is necessary to predict the temperature fields arising as a result of the laser energy input. Elevated temperatures during the cutting process can lead to damage in the composite's matrix material, resulting in local changes in the structural properties and reduced material strength. To address this, a three-dimensional finite element model is developed to predict the temporal and spatial temperature evolution during laser cutting. Experimental values are compared with simulated temperatures, and the cutting kerf geometry is examined. Experiments are conducted at 45° and 90° cutting angles relative to the main fibre orientation using a 1.1 mm thick epoxy-based laminate. The simulation accurately captures the overall temperature field expansion caused by multiple laser beam passes over the workpiece. The influence of fibre orientation is evident, with deviations in specific temperature data indicating differences between the estimated and real material properties. The model tends to overestimate the ablation rate in the kerf geometry, attributed to mesh resolution limitations. Within the parameters investigated, hardly any expansion of a heat affected zone (HAZ) is visible, which is confirmed by the simulation results.

Porous Melt Flow in Continental Crust—A Numerical Modeling Study

AbstractIn continental crust, rapid melt flow through macroscopic conduits is usually envisaged as the most efficient form of melt transport. In contrast, there is growing evidence that in hot continental crust, grain‐scale to meso‐scale porous melt flow may operate over long distances and over millions of years. Here, we investigate the dynamics of such porous melt flow by means of two‐dimensional thermo‐mechanical numerical models using the code ASPECT. Our models are crustal‐scale and describe the network of pores through which the melt flows by permeability that depends on the spacing of the pores. Our results suggest that assuming realistic material properties, melt can slowly migrate in the hot and thick continental crust through pores with a characteristic spacing of 1 mm or larger. Despite its low velocity (millimeters to centimeters per year), over millions of years, such flow can create large partially molten zones in the middle‐lower crust and significantly affect its thermal state, deformation, and composition. We examined the role of the permeability, melt and solid viscosities, the slope of the melting curve and temperature conditions. We obtained contrasting styles of melt distribution, melt flow, and solid deformation, which can be categorized as melt‐enhanced convection, growth of partially molten diapirs and melt percolation in porosity waves. Our numerical experiments further indicate that grain‐scale porous flow is more likely in rocks where the melt productivity increases slowly with temperature, such as in metaigneous rocks.

Design of a novel carbon/carbon composite microvascular solar receiver

Solar thermal power tower systems are the primary technology being proposed for solar electricity from thermal energy. Operational limits on these towers are often driven by mechanical properties under significant thermal loads, particularly at the receiver where incoming flux is converted to thermal energy. While the solar receiver’s efficiency is largely driven by its optical properties, thermomechanical stresses on the receiver limits the operational envelope. One pathway to higher efficiency is greater allowable solar fluxes on the receiver but novel materials are required. The present study uses computational fluid dynamics to describe a parametric design space for a microvascular carbon/carbon composite solar receiver as a new material option for high flux solar receivers. Simulations are conducted for different microvascular geometries considering the role of material properties and heat transfer fluids, for the impact on thermal efficiency, and allowable strain. Results show that microscale receiver modules made of the proposed carbon/carbon composite could achieve thermal efficiencies over 90% and full-scale receivers can achieve up to 85% thermal efficiency for the design explored considering realistic strain limits, flux levels, and material properties. These values are highly dependent on the heat transfer fluid pairing, the through plane thermal conductivity of the carbon/carbon composite, the path architecture of the microscale receiver, and the incident solar flux profiles.

A novel deep-learning-based objective function for inverse identification of material properties

Inverse methods are critical in exploring the constitutive models of materials. In the traditional finite element model updating method, an objective function is often established in the form of mean square error, which is simple and easy to use. However, this approach does not fully consider the prior knowledge of the material, leading to low computational stability and sensitivity to noise. To address these limitations, a novel objective function that considers deep semantic information and mechanical constraints was proposed based on deep learning techniques in this study. Compared with the traditional method, the proposed objective function can significantly reduce the effect of noise on inversion performance without any loss in computational efficiency. The method was validated through simulated experiments and successfully applied to the inverse identification of damage properties of real nuclear graphite materials under simple and complex stress states. The results demonstrated that the proposed objective function can significantly enhance the stability of the finite element model updating method, leading to a rapid convergence with high accuracy.

CRSS determination combining ab-initio framework and Surrogate Neural Networks

Critical Resolved Shear Stress (CRSS), fundamentally linked to the dislocation glide stress, is a crucial measure in dictating plastic deformation in metallic materials. A recent ab-initio predictive model for dislocation glide stress in Face-Centered Cubic (FCC) materials is developed which accurately predicts available experimental data, considering the anisotropic continuum energy, the atomistic misfit energy, and the minimum energy path for the intermittent motion of Shockley partials. The CRSS of a material is predominantly controlled by six parameters, namely, lattice constant, unstable/stable stacking-fault energies, and three anisotropic elastic constants for cubic materials, which are inputs to the predictive model. In this work, a large material dataset is produced incorporating properties of real materials and generating hypothetical combinations, subsequently calculating the CRSS for each combination using the predictive model. The hypothetical combinations of properties are employed to train a machine learning-based Surrogate Neural Network (SNN), and the ones of real materials are utilized to validate the SNN model yielding a 94% accuracy for 1,033 materials. The generated dataset is used to unravel the sensitivity of each material parameter to the predicted CRSS establishing a general trend for the FCC materials for the first time guiding the field in achieving superior mechanical properties.

Sub-nanometer-scale mapping of crystal orientation and depth-dependent structure of dislocation cores in SrTiO3

Defects in crystals play a fundamental role in modulating mechanical, electrical, luminescent, and magnetic behaviors of materials. However, accurate measurement of defect structures is hindered by symmetry breaking and the corresponding complex modifications in atomic configuration and/or crystal tilt at the defects. Here, we report the deep-sub-angstrom resolution imaging of dislocation cores via multislice electron ptychography with adaptive propagator, which allows sub-nanometer scale mapping of crystal tilt in the vicinity of dislocation cores and simultaneous recovery of depth-dependent atomic structure of dislocations. The realization of deep-sub-angstrom resolution and depth-dependent imaging of defects shows great potential in revealing microstructures and properties of real materials and devices.

The numerical study on performance evaluation of a thermal switch capacitor in a magnetocaloric cooling device.

Compact, solid thermal control devices offer a new way to control the intensity and direction of heat flow between the components of a system, which is crucial for both optimized performance and safety. In this work we study a thin, silicon thermal switch capacitor (TSC) used for heat transport in a magnetocaloric cooling system. A numerical model was developed to quantify the effects of various operating conditions and design parameters on the performance of a magnetocaloric device with an embedded TSC. Based on realistic material properties, a maximum cooling-power density of 4000 Wm-2 (2025 ) was obtained for a zero temperature span and an operating frequency of 20Hz. The use of the presented device was demonstrated on a battery system, motivating further experimental studies to develop a new, compact cooling device that can be directly attached to a heat reservoir, making it desirable for a variety of applications.

ERGOBOSS: Ergonomic Optimization of Body-Supporting Surfaces.

Humans routinely sit or lean against supporting surfaces and it is important to shape these surfaces to be comfortable and ergonomic. We give a method to design the geometric shape of rigid supporting surfaces to maximize the ergonomics of physically based contact between the surface and a deformable human. We model the soft deformable human using a layer of FEM deformable tissue surrounding a rigid core, with measured realistic elastic material properties, and large-deformation nonlinear analysis. We define a novel cost function to measure the ergonomics of contact between the human and the supporting surface. We give a stable and computationally efficient contact model that is differentiable with respect to the supporting surface shape. This makes it possible to optimize our ergonomic cost function using gradient-based optimizers. Our optimizer produces supporting surfaces superior to prior work on ergonomic shape design. Our examples include furniture, apparel and tools. We also validate our results by scanning a real human subject's foot and optimizing a shoe sole shape to maximize foot contact ergonomics. We 3D-print the optimized shoe sole, measure contact pressure using pressure sensors, and demonstrate that the real unoptimized and optimized pressure distributions qualitatively match those predicted by our simulation.

Simulation of Hand Anatomy Using Medical Imaging

Precision modeling of the hand internal musculoskeletal anatomy has been largely limited to individual poses, and has not been connected into continuous volumetric motion of the hand anatomy actuating across the hand's entire range of motion. This is for a good reason, as hand anatomy and its motion are extremely complex and cannot be predicted merely from the anatomy in a single pose. We give a method to simulate the volumetric shape of hand's musculoskeletal organs to any pose in the hand's range of motion, producing external hand shapes and internal organ shapes that match ground truth optical scans and medical images (MRI) in multiple scanned poses. We achieve this by combining MRI images in multiple hand poses with FEM multibody nonlinear elastoplastic simulation. Our system models bones, muscles, tendons, joint ligaments and fat as separate volumetric organs that mechanically interact through contact and attachments, and whose shape matches medical images (MRI) in the MRI-scanned hand poses. The match to MRI is achieved by incorporating pose-space deformation and plastic strains into the simulation. We show how to do this in a non-intrusive manner that still retains all the simulation benefits, namely the ability to prescribe realistic material properties, generalize to arbitrary poses, preserve volume and obey contacts and attachments. We use our method to produce volumetric renders of the internal anatomy of the human hand in motion, and to compute and render highly realistic hand surface shapes. We evaluate our method by comparing it to optical scans, and demonstrate that we qualitatively and quantitatively substantially decrease the error compared to previous work. We test our method on five complex hand sequences, generated either using keyframe animation or performance animation using modern hand tracking techniques.

Fueling the Simulation Machine: Considerations for High-Resolution 3D Microscopy to Support Computational Modeling in Battery Research

To meet the rapidly evolving energy needs of a growing population, energy storage and conversion devices such as batteries must rapidly evolve as well. Battery materials and other functional energy materials derive their properties not from their static state, but from how they interact with other materials in their service environment. Furthermore, the microstructure of these materials strongly dictates their performance and how they interact with other components (like electrolytes, binders, etc). In order to accelerate this development cycle, researchers are increasingly integrating computational modeling into their materials and device development efforts.Computational analysis is progressing to the point where simulations can incorporate real material microstructures, simulate statistically equivalent structures, and predict performance changes based on changes to these microstructures. At the same time experimental techniques have emerged that can deliver representative volumes of high-quality, high-resolution 3D microstructural images from real devices and materials. The interplay between advanced computational analysis and evolving characterization capabilities means we are rapidly approaching the realization of the “materials by design” paradigm where new materials are designed and tested digitally with input and validation provided by advanced materials characterization techniques. Within this paradigm, however, it is critical that the experimental techniques provide accurate, realistic, and representative input to the computational models. In the case of microstructural information, this means generating 3-dimensional images that accurately represents the materials in question.One key example of this is for materials, like battery materials and electrodes, which contain micro- and nano-scale porosity. Acquiring image data that can reproduce real material properties and feed accurate simulations is challenging and relies on satisfying several conditions. For example, the volume must be representative of the “bulk” material microstructure. The (2D) image resolution must capture the relevant scope of material features, and the 3D image must accurately represent the material in all 3 dimensions and at appropriate length scales. The focused-ion beam scanning electron microscope (FIB-SEM) is capable of imaging these micro- and nano-scale pore networks in 3D but care must be taken when considering these experiments, especially when the intent is to use the images to feed computational models.We present here a review of the factors researchers must consider when tackling these demanding tasks and highlight experimental recommendations for leveraging FIB-SEM tomography to produce the most relevant imaging data in this context. We use a lithium-ion battery cathode as a test case to demonstrate this approach, but the outcome and methods can be leveraged across the materials research space and beyond.

Modeling Adhesive Wear in Asperity and Rough Surface Contacts: A Review.

Wear is one of the most fundamental topics in tribology and adhesive wear is argued as the least avoidable wear type. Numerical techniques have allowed advances in more realistic simulations of adhesive wear mechanisms and promoted our understanding of it. This paper reviews the classic work on wear modeling by Archard and Rabinowicz, followed by a comprehensive summary of the adhesive wear numerical models and techniques based on physical parameters. The studies on wear mechanisms at the asperity level and rough surfaces are separately presented. Different models and their key findings are presented according to the method type. The advantages and deficiencies of these models are stated and future work, such as considering more realistic geometries and material properties for adhesive wear modeling, is suggested.