Failure of existing structures with semi-brittle mechanical properties on meso scale and reduction of computational cost using non-linear topology optimization

Cellular Materials and Topology Optimization use a structured distribution of material to achieve specific mechanical properties. The controlled distribution of material often leads to several advantages including the customization of the resulting mechanical properties; this can be achieved following these two approaches. In this work, a review of these two as approaches used with compliance purposes applied at flexure level is presented. The related literature is assessed with the aim of clarifying how they can be used in tailoring stiffness of flexure elements. Basic concepts needed to understand the fundamental process of each approach are presented. Further, tailoring stiffness is described as an evolutionary process used in compliance applications. Additionally, works that used these approaches to tailor stiffness of flexure elements are described and categorized. Finally, concluding remarks and recommendations to further extend the study of these two approaches in tailoring the stiffness of flexure elements are discussed.

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Microstructure and Mechanical Properties at the Unsteady Areas of Non-Linear Friction Stir Welding

Materials Science Forum ◽

10.4028/www.scientific.net/msf.561-565.1059 ◽

2007 ◽

Vol 561-565 ◽

pp. 1059-1062 ◽

Cited By ~ 1

Author(s):

H. Takahara ◽

Masato Tsujikawa ◽

Sung Wook Chung ◽

Y. Okawa ◽

Kenji Higashi

Keyword(s):

Mechanical Properties ◽

Friction Stir Welding ◽

Welding Parameter ◽

Butt Joints ◽

Friction Stir ◽

Non Linear ◽

Linear Friction ◽

Fsw Parameters ◽

Five Axis ◽

Welding Direction

The influence of tool control in non-linear friction stir welding (FSW) on mechanical properties of joints was investigated. FSW is widely applied to linear joints. It is impossible for five axis FSW machines, however, to keep all the FSW parameters in optimum conditions at non-linear welding. Non-linear FSW joints should be made by compromise with the order of priority for FSW parameters. The tensile test results of butt joints with rectangular change in welding direction on plate plane (L-shaped butt joints) with various welding parameter change. It was found that turn to the retreating side is encouraged when welding direction change. And the method of zero inclination tool angle is effective at non-linear and plane welding.

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Investigations on the growth, optical, thermal and mechanical properties of pyridinium (2R,3R)-tartrate non linear optical single crystal

Materials Today Proceedings ◽

10.1016/j.matpr.2021.02.767 ◽

2021 ◽

Author(s):

T. David Willington ◽

S.E. Joema ◽

S. Sindhusha

Keyword(s):

Mechanical Properties ◽

Single Crystal ◽

Thermal And Mechanical Properties ◽

Non Linear ◽

Linear Optical

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Multiscale Topology Optimization With Gaussian Process Regression Models

10.1115/detc2021-66758 ◽

2021 ◽

Author(s):

Joel C. Najmon ◽

Homero Valladares ◽

Andres Tovar

Keyword(s):

Topology Optimization ◽

Gaussian Process ◽

Regression Models ◽

Computational Cost ◽

Gaussian Process Regression ◽

Analytical Sensitivity ◽

Inverse Homogenization ◽

Discrete Location ◽

Unit Cells ◽

Periodic Microstructures

Abstract Multiscale topology optimization (MSTO) is a numerical design approach to optimally distribute material within coupled design domains at multiple length scales. Due to the substantial computational cost of performing topology optimization at multiple scales, MSTO methods often feature subroutines such as homogenization of parameterized unit cells and inverse homogenization of periodic microstructures. Parameterized unit cells are of great practical use, but limit the design to a pre-selected cell shape. On the other hand, inverse homogenization provide a physical representation of an optimal periodic microstructure at every discrete location, but do not necessarily embody a manufacturable structure. To address these limitations, this paper introduces a Gaussian process regression model-assisted MSTO method that features the optimal distribution of material at the macroscale and topology optimization of a manufacturable microscale structure. In the proposed approach, a macroscale optimization problem is solved using a gradient-based optimizer The design variables are defined as the homogenized stiffness tensors of the microscale topologies. As such, analytical sensitivity is not possible so the sensitivity coefficients are approximated using finite differences after each microscale topology is optimized. The computational cost of optimizing each microstructure is dramatically reduced by using Gaussian process regression models to approximate the homogenized stiffness tensor. The capability of the proposed MSTO method is demonstrated with two three-dimensional numerical examples. The correlation of the Gaussian process regression models are presented along with the final multiscale topologies for the two examples: a cantilever beam and a 3-point bending beam.

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Meso-scale stochastic modeling for mechanical properties of structural lightweight aggregate concrete

Materials and Structures ◽

10.1617/s11527-021-01874-9 ◽

2022 ◽

Vol 55 (1) ◽

Author(s):

Tao Wu ◽

Yang Liu ◽

Xi Liu ◽

Binfeng Zhang

Keyword(s):

Mechanical Properties ◽

Stochastic Modeling ◽

Lightweight Aggregate ◽

Lightweight Aggregate Concrete ◽

Aggregate Concrete ◽

Structural Lightweight Aggregate Concrete ◽

Meso Scale

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Approximate Dynamic Programming Based Control of Proppant Concentration in Hydraulic Fracturing

Mathematics ◽

10.3390/math6080132 ◽

2018 ◽

Vol 6 (8) ◽

pp. 132 ◽

Cited By ~ 17

Author(s):

Harwinder Singh Sidhu ◽

Prashanth Siddhamshetty ◽

Joseph Kwon

Keyword(s):

Mechanical Properties ◽

Dynamic Programming ◽

Hydraulic Fracturing ◽

Young’S Modulus ◽

Large Scale ◽

Approximate Dynamic Programming ◽

Young's Modulus ◽

Computational Cost ◽

Control Technique ◽

Rock Mechanical Properties

Hydraulic fracturing has played a crucial role in enhancing the extraction of oil and gas from deep underground sources. The two main objectives of hydraulic fracturing are to produce fractures with a desired fracture geometry and to achieve the target proppant concentration inside the fracture. Recently, some efforts have been made to accomplish these objectives by the model predictive control (MPC) theory based on the assumption that the rock mechanical properties such as the Young’s modulus are known and spatially homogenous. However, this approach may not be optimal if there is an uncertainty in the rock mechanical properties. Furthermore, the computational requirements associated with the MPC approach to calculate the control moves at each sampling time can be significantly high when the underlying process dynamics is described by a nonlinear large-scale system. To address these issues, the current work proposes an approximate dynamic programming (ADP) based approach for the closed-loop control of hydraulic fracturing to achieve the target proppant concentration at the end of pumping. ADP is a model-based control technique which combines a high-fidelity simulation and function approximator to alleviate the “curse-of-dimensionality” associated with the traditional dynamic programming (DP) approach. A series of simulations results is provided to demonstrate the performance of the ADP-based controller in achieving the target proppant concentration at the end of pumping at a fraction of the computational cost required by MPC while handling the uncertainty in the Young’s modulus of the rock formation.

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Macro-meso scale simulations of 3D woven composite reinforcements during the forming process

10.25518/esaform21.496 ◽

2021 ◽

Author(s):

Jie Wang ◽

Peng Wang ◽

Nahiène Hamila ◽

Philippe Boisse

Keyword(s):

Computational Cost ◽

Constitutive Law ◽

Forming Process ◽

Multi Scale ◽

Rtm Process ◽

Macroscopic Simulation ◽

Deformations And Orientations ◽

High Computational Cost ◽

Meso Scale ◽

Composite Reinforcements

During the forming stage in the RTM process, deformations and orientations of yarns at the mesoscopic scale are essential to evaluate mechanical behaviors of final composite products and calculate the permeability of the reinforcement. However, due to the high computational cost, it is very difficult to carry out a mesoscopic draping simulation for the entire reinforcement. In this paper, a macro-meso scale simulation of composite reinforcements is presented in order to predict mesoscopic deformations of the fabric in a reasonable calculation time. The proposed multi-scale method allows linking the macroscopic simulation of the reinforcement with the mesoscopic modelling of the RVE through a macromeso embedded analysis. On the base of macroscopic simulations using a hyperelastic constitutive law of the reinforcement, an embedded mesoscopic geometry is first deduced from the macroscopic simulation of the draping. To overcome the inconvenience of the macro-meso embedded solution which leads to unreal excessive yarn extensions, local mesoscopic simulations based on the embedded analysis are carried out on a single RVE by defining specific boundary conditions. Finally, the multi-scale forming simulations are investigated in comparison with the experimental results, illustrating the efficiency of the proposed approach, in terms of accuracy and CPU time.

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