Topology Optimization of Structural Systems Considering Both Compliance and Input Observability

2017 ◽  
Author(s):  
Yi Ren ◽  
Houpu Yao ◽  
Xinfan Lin
Keyword(s):  
Intelligent Systems ◽  
Pareto Frontier ◽  
Material Design ◽  
Soft Materials ◽  
System Level ◽  
Mechanical And Thermal Properties ◽  
Static Loads ◽  
Input Estimation ◽  
Intelligent Structures ◽  
Actuator Design

Recent advances in flexible and wireless sensors, soft materials, and additive manufacturing, have stimulated demands for developing intelligent systems that can achieve multidisciplinary objectives (e.g., mechanical strength, thermal conductivity, state and input estimation, controllability, and others). Existing studies often decouple these objectives through sub-system level design, e.g., topology and material design for mechanical and thermal properties, and filter and sensor/actuator design for observability and controllability, assuming that the sub-systems have minimal influences to each others. To investigate the validity of this assumption, we take a unique angle at studying how the topology of the system influences both structural performance (e.g., compliance under static loads) and input observability (e.g., the error in estimating the loads). We reveal a tradeoff between these two objectives and derive the Pareto frontier with respect to the topology. This preliminary result suggests the necessity of a multiobjective formulation for designing intelligent structures, when significant tradeoffs among system objectives exist.

A Systematic Material Design Approach to Develop Self-Lubricating Ceramic-Composite Tool Inserts for Dry Cutting Conditions

2019 ◽  
Author(s):  
Syed Sohail Akhtar
Keyword(s):  
Fracture Toughness ◽  
Thermal Properties ◽  
Volume Fraction ◽  
Mean Field ◽  
Material Design ◽  
Ceramic Materials ◽  
Ceramic Composites ◽  
Design Stage ◽  
Mechanical And Thermal Properties ◽  
Dry Cutting

Abstract A systematic approach is the focus of the current work in order to design and develop ceramic composites for cutting tool inserts with a balanced combination of structural and thermal properties together with enhanced antifriction characteristics. In the material design stage, various combinations of ceramic materials and inclusions with optimum self-lubricating attributes are selected based on predictions of mechanical and thermal properties using in-house built codes. A mean-field homogenization scheme is used to predict the constitutive behavior while J-integral based fracture toughness model is used to predict the effective fracture toughness of the ceramic composites. An effective medium approximation is used to predict the potential optimum thermal properties. The current strategy incorporates thermal and structural properties of composites as a constraint on the design process together with self-lubrication property. Among various metallic and carbon-based fillers, silicon carbide (SiC) together with titanium oxide (TiO2) and graphite are found the most suitable candidate fillers in alumina (Al2O3) matrix to produce cutting inserts with best combinations of thermal, structural and tribological properties. As a validation, various combinations of Al2O3-SiC-TiO2 and Al2O3-SiC-TiO2 composites are developed in line with the designed range of filler size and volume fraction using Spark Plasma Sintering (SPS) process to complement the material design.

scholarly journals INTERACTIVITY OF MODERN COMMUNICATIVE GRAPHIC DESIGN PRODUCTS

2020 ◽  
pp. 14-14
Author(s):  
Tigran O. Gabrielyan
Keyword(s):  
Digital Media ◽  
20Th Century ◽  
Graphic Design ◽  
Intelligent Systems ◽  
Material Design ◽  
Design Program ◽  
Media Communications ◽  
The Individual

The article discusses various types of interactivity in the context of communicative design. Its emergence in the mid-20th century and modern interpretation as a media communicator are considered. The division into printed and electronic (analog and digital) media communications is emphasized. Principal attention is paid to material (printed and graphic) design products: toy books, packaging, posters, and illustrations. In general form, interactivity is understood as interaction (action of cooperation) between the individual and the design product. Linear interactivity, reactive interactivity and dialogue interactivity are analyzed. Linear interactivity is regarded as metaphysical interaction between the consumer and the design product. Reactive interactivity allows the consumer to bring to completion the design program as conceived by the author and obtain a finished design product. Dialogue interactivity cannot be implemented in a material design product without its integration with digital algorithmic or intelligent systems.

scholarly journals Soft self-assembly of Weyl materials for light and sound

2018 ◽  
Vol 115 (16) ◽  
pp. E3655-E3664 ◽  
Author(s):  
Michel Fruchart ◽  
Seung-Yeol Jeon ◽  
Kahyun Hur ◽  
Vadim Cheianov ◽  
Ulrich Wiesner ◽  
...  
Keyword(s):  
Self Assembly ◽  
Surface States ◽  
Material Design ◽  
Soft Materials ◽  
General Symmetry ◽  
Mesostructured Materials ◽  
Reversal Invariance ◽  
Symmetry Constraints ◽  
Topological Surface ◽  
Self Assembled

Soft materials can self-assemble into highly structured phases that replicate at the mesoscopic scale the symmetry of atomic crystals. As such, they offer an unparalleled platform to design mesostructured materials for light and sound. Here, we present a bottom-up approach based on self-assembly to engineer 3D photonic and phononic crystals with topologically protected Weyl points. In addition to angular and frequency selectivity of their bulk optical response, Weyl materials are endowed with topological surface states, which allow for the existence of one-way channels, even in the presence of time-reversal invariance. Using a combination of group-theoretical methods and numerical simulations, we identify the general symmetry constraints that a self-assembled structure has to satisfy to host Weyl points and describe how to achieve such constraints using a symmetry-driven pipeline for self-assembled material design and discovery. We illustrate our general approach using block copolymer self-assembly as a model system.

Generalized Viscoelastic Material Design With Integro-Differential Equations and Direct Optimal Control

2015 ◽  
Author(s):  
Lakshmi Gururaja Rao ◽  
James T. Allison
Keyword(s):  
Optimal Control ◽  
Differential Equations ◽  
Engineering Design ◽  
Time Derivative ◽  
Material Design ◽  
System Level ◽  
Stage Design ◽  
Derivative Function ◽  
Linear Viscoelastic ◽  
Direct Optimal Control

Rheological material properties are examples of function-valued quantities that depend on frequency (linear viscoelasticity), input amplitude (nonlinear material behavior), or both. This dependence complicates the process of utilizing these systems in engineering design. In this article, we present a methodology to model and optimize design targets for such rheological material functions. We show that for linear viscoelastic systems simple engineering design assumptions can be relaxed from a conventional spring-dashpot model to a more general linear viscoelastic relaxation kernel, K(t). While this approach expands the design space and connects system-level performance with optimal material design functions, it entails significant numerical difficulties. Namely, the associated governing equations involve a convolution integral, thus forming a system of integro-differential equations. This complication has two important consequences: 1) the equations representing the dynamic system cannot be written in a standard state space form as the time derivative function depends on the entire past state history, and 2) the dependence on prior time-history increases time derivative function computational expense. Previous studies simplified this process by incorporating parameterizations of K(t) using viscoelastic models such as Maxwell or critical gel models. While these simplifications support efficient solution, they limit the type of viscoelastic materials that can be designed. This article introduces a more general approach that can explore arbitrary K(t) designs using direct optimal control methods. In this study, we analyze a nested direct optimal control approach to optimize linear viscoelastic systems with no restrictions on K(t). The study provides new insights into efficient optimization of systems modeled using integro-differential equations. The case study is based on a passive vibration isolator design problem. The resulting optimal K(t) functions can be viewed as early-stage design targets that are material agnostic and allow for creative material design solutions. These targets may be used for either material-specific selection or as targets for later-stage design of novel materials.

Versatile Formulation for Multiobjective Reliability-Based Design Optimization

2005 ◽  
Vol 128 (6) ◽  
pp. 1217-1226 ◽  
Author(s):  
T. Zou ◽  
S. Mahadevan
Keyword(s):  
Multiobjective Optimization ◽  
Design Optimization ◽  
Reliability Analysis ◽  
Pareto Frontier ◽  
System Level ◽  
Reliability Based Design Optimization ◽  
Component Reliability ◽  
Reliability Based Design ◽  
Uncertainty Model ◽  
Optimization Methodology

This paper develops a multiobjective optimization methodology for system design under uncertainty. Model-based reliability analysis methods are used to compute the probabilities of unsatisfactory performance at both component and system levels. Combined with several multiobjective optimization formulations, a versatile reliability-based design optimization (RBDO) approach is used to achieve a tradeoff between two objectives and to generate the Pareto frontier for decision making. The proposed RBDO approach uses direct reliability analysis to decouple the reliability and optimization iterations, instead of inverse first-order reliability analysis as other existing decoupled approaches. This helps to solve a wide variety of RBDO problems with competing objectives, especially when system-level reliability constraints need to be considered. The approach also allows more accurate methods to be used for reliability analysis, and reliability terms to be included in the objective function. Two important automotive quality objectives, related to the door closing effort (evaluated using component reliability analysis) and the wind noise (evaluated using system reliability analysis), are used to illustrate the proposed method.

scholarly journals Flexoelectricity in soft elastomers and the molecular mechanisms underpinning the design and emergence of giant flexoelectricity

2021 ◽  
Vol 118 (21) ◽  
pp. e2102477118
Author(s):  
Matthew Grasinger ◽  
Kosar Mozaffari ◽  
Pradeep Sharma
Keyword(s):  
Electric Fields ◽  
Flexible Electronics ◽  
Molecular Mechanisms ◽  
Material Design ◽  
Deformation Mode ◽  
Soft Materials ◽  
Electric Polarization ◽  
Electric Stimulus ◽  
Flexoelectric Effect ◽  
External Stimuli

Soft robotics requires materials that are capable of large deformation and amenable to actuation with external stimuli such as electric fields. Energy harvesting, biomedical devices, flexible electronics, and sensors are some other applications enabled by electroactive soft materials. The phenomenon of flexoelectricity is an enticing alternative that refers to the development of electric polarization in dielectrics when subjected to strain gradients. In particular, flexoelectricity offers a direct linear coupling between a highly desirable deformation mode (flexure) and electric stimulus. Unfortunately, barring some exceptions, the flexoelectric effect is quite weak and rather substantial bending curvatures are required for an appreciable electromechanical response. Most experiments in the literature appear to confirm modest flexoelectricity in polymers although perplexingly, a singular work has measured a “giant” effect in elastomers under some specific conditions. Due to the lack of an understanding of the microscopic underpinnings of flexoelectricity in elastomers and a commensurate theory, it is not currently possible to either explain the contradictory experimental results on elastomers or pursue avenues for possible design of large flexoelectricity. In this work, we present a statistical-mechanics theory for the emergent flexoelectricity of elastomers consisting of polar monomers. The theory is shown to be valid in broad generality and leads to key insights regarding both giant flexoelectricity and material design. In particular, the theory shows that, in standard elastomer networks, combining stretching and bending is a mechanism for obtaining giant flexoelectricity, which also explains the aforementioned, surprising experimental discovery.

Capabilities of Mean-Field Approaches for the Description of the Elasto-Plastic Behavior of Composite Materials

2019 ◽  
Vol 820 ◽  
pp. 1-8 ◽  
Author(s):  
Zoubida Sekkate ◽  
Ahmed Aboutajeddine ◽  
Abbass Seddouki
Keyword(s):  
Composite Materials ◽  
Mean Field ◽  
Material Design ◽  
High Volume ◽  
System Level ◽  
Plastic Behavior ◽  
Two Phase ◽  
Elastoplastic Behavior ◽  
Speed Up ◽  
Micromechanical Models

Composite materials offer potential avenues for tailoring materials with desired properties intended to innovative applications. To speed up this scheme, trial and error practice is evolving to a more rational and organized material design process. This trend depends on our ability to bridge the micro-scale to the system level. An important brick of this process is constituted of micromechanical models that bridge the gap between micro and macro scales in materials. Unfortunately, to forecast the behavior of complex composite materials microstructures, these models remain rudimentary, particularly for the nonlinear regime. Accordingly, our ambition is to highlight the limitations of existing micromechanical models and examine their respective capabilities to predict elastoplastic behavior of composite materials. The assessment reveals that in order to reduce the disparity between micromechanical models predictions and corresponding numerical or experimental results, new robust and efficient micromechanical models are needed. These models have to accurately describe different interactions in the composite and deal with multiphase and two-phase composites with high volume fractions under different loading paths.

Setting Performance Targets Based on Subsystem Pareto Frontiers in Multilevel Optimization

2006 ◽  
Author(s):  
Huibin Liu ◽  
Christopher Hoyle ◽  
Xiaolei Yin ◽  
Wei Chen
Keyword(s):  
Design Process ◽  
Pareto Frontier ◽  
System Level ◽  
Engineering System ◽  
Multilevel Optimization ◽  
Performance Targets ◽  
Target Values ◽  
Target Cascading ◽  
Complex Engineering ◽  
Complex Engineering System

The design of a complex engineering system typically involves tradeoffs among multiple design criteria or disciplinary performance to achieve the optimal design. The design process is usually an iterative procedure with individual discipline sub-systems designed concurrently to meet target values assigned from the system level. One of the most challenging issues is the large number of iterations in this design process, especially when uncertainty is taken into account. To improve the design concurrency while maintaining preferred tradeoffs at the system level, a new method is developed that identifies proper targets based on disciplinary design capability information while optimizing the design goal at the system level. The design capability of a discipline or criterion is represented by the achievable area bounded by its Pareto frontier. Using target values obtained from this method using Pareto information, the number of design iterations can be reduced in both deterministic and probabilistic design scenarios compared to existing approaches, such as Analytical Target Cascading (ATC). To demonstrate applications and benefits of the developed method this approach is applied to the design of a two-bar truss structure.

scholarly journals Data-Centric Mixed-Variable Bayesian Optimization for Materials Design

2019 ◽  
Author(s):  
Akshay Iyer ◽  
Yichi Zhang ◽  
Aditya Prasad ◽  
Siyu Tao ◽  
Yixing Wang ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Latent Variable ◽  
Pareto Frontier ◽  
Material Design ◽  
Materials Design ◽  
Bayesian Optimization ◽  
Data Uncertainty ◽  
Expected Improvement ◽  
Nonlinear Design ◽  
Mixed Variable

Abstract Materials design can be cast as an optimization problem with the goal of achieving desired properties, by varying material composition, microstructure morphology, and processing conditions. Existence of both qualitative and quantitative material design variables leads to disjointed regions in property space, making the search for optimal design challenging. Limited availability of experimental data and the high cost of simulations magnify the challenge. This situation calls for design methodologies that can extract useful information from existing data and guide the search for optimal designs efficiently. To this end, we present a data-centric, mixed-variable Bayesian Optimization framework that integrates data from literature, experiments, and simulations for knowledge discovery and computational materials design. Our framework pivots around the Latent Variable Gaussian Process (LVGP), a novel Gaussian Process technique which projects qualitative variables on a continuous latent space for covariance formulation, as the surrogate model to quantify “lack of data” uncertainty. Expected improvement, an acquisition criterion that balances exploration and exploitation, helps navigate a complex, nonlinear design space to locate the optimum design. The proposed framework is tested through a case study which seeks to concurrently identify the optimal composition and morphology for insulating polymer nanocomposites. We also present an extension of mixed-variable Bayesian Optimization for multiple objectives to identify the Pareto Frontier within tens of iterations. These findings project Bayesian Optimization as a powerful tool for design of engineered material systems.

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