Coupled Multi-Material and Joint Topology Optimization: A Proof of Concept

2018 ◽  
Author(s):  
Vlad Florea ◽  
Vishrut Shah ◽  
Stephen Roper ◽  
Garrett Vierhout ◽  
Il Yong Kim
Keyword(s):  
Topology Optimization ◽  
Cost Effective ◽  
Material Design ◽  
Optimization Methods ◽  
Manufacturing Constraints ◽  
Proof Of Concept ◽  
Efficient Design ◽  
Engineering Costs ◽  
Increasing Demand ◽  
Material Layout

Over the past decade there has been an increasing demand for light-weight components for the automotive and aerospace industries. This has led to significant advancement in Topology Optimization methods, especially in developing new algorithms which can consider multi-material design. While Multi-Material Topology Optimization (MMTO) can be used to determine the optimum material layout and choice for a given engineering design problem, it fails to consider practical manufacturing constraints. One such constraint is the practical joining of multi-component designs. In this paper, a new method will be proposed for simultaneously performing MMTO and Joint Topology Optimization (JTO). This algorithm will use a serial approach to loop through the MMTO and JTO phases to obtain a truly optimum design which considers both aspects. A case study is performed on an automotive ladder frame chassis component as a proof of concept for the proposed approach. Two loops of the proposed process resulted in a reduction of components and in the number of joints used between them. This translates into a tangible improvement in the manufacturability of the MMTO design. Ultimately, being able to consider additional manufacturing constraints in the Topology Optimization process can greatly benefit research and development efforts. A better design is reached with fewer iterations, thus driving down engineering costs. Topology Optimization can help in determining a cost effective and efficient design which address existing structural design challenges.

scholarly journals A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects

2020 ◽  
Vol 33 (1) ◽  
Author(s):  
Jie Gao ◽  
Mi Xiao ◽  
Yan Zhang ◽  
Liang Gao
Keyword(s):  
Topology Optimization ◽  
Computer Aided Design ◽  
Numerical Technique ◽  
Optimization Methods ◽  
Negative Influence ◽  
Comprehensive Overview ◽  
Promising Alternative ◽  
Computer Aided ◽  
Optimal Material ◽  
Material Layout

AbstractTopology Optimization (TO) is a powerful numerical technique to determine the optimal material layout in a design domain, which has accepted considerable developments in recent years. The classic Finite Element Method (FEM) is applied to compute the unknown structural responses in TO. However, several numerical deficiencies of the FEM significantly influence the effectiveness and efficiency of TO. In order to eliminate the negative influence of the FEM on TO, IsoGeometric Analysis (IGA) has become a promising alternative due to its unique feature that the Computer-Aided Design (CAD) model and Computer-Aided Engineering (CAE) model can be unified into a same mathematical model. In the paper, the main intention is to provide a comprehensive overview for the developments of Isogeometric Topology Optimization (ITO) in methods and applications. Finally, some prospects for the developments of ITO in the future are also presented.

Incorporating Manufacturing Constraints in Topology Optimization Methods: A Survey

2017 ◽  
Author(s):  
Alok Sutradhar ◽  
Jaejong Park ◽  
Payam Haghighi ◽  
Jacob Kresslein ◽  
Duane Detwiler ◽  
...  
Keyword(s):  
Topology Optimization ◽  
Additive Manufacturing ◽  
Optimization Methods ◽  
Manufacturing Processes ◽  
Complex Geometries ◽  
Manufacturing Constraints ◽  
Post Processing ◽  
Optimization Framework ◽  
Manufacturing Methods ◽  
Traditional Manufacturing

Topology optimization provides optimized solutions with complex geometries which are often not suitable for direct manufacturing without further steps or post-processing by the designer. There has been a recent progression towards linking topology optimization with additive manufacturing, which is less restrictive than traditional manufacturing methods, but the technology is still in its infancy being costly, time-consuming, and energy inefficient. For applications in automotive or aerospace industries, the traditional manufacturing processes are still preferred and utilized to a far greater extent. Adding manufacturing constraints within the topology optimization framework eliminates the additional design steps of interpreting the topology optimization result and converting it to viable manufacturable parts. Furthermore, unintended but inevitable deviations that occur during manual conversion from the topology optimized result can be avoided. In this paper, we review recent advances to integrate (traditional) manufacturing constraints in the topology optimization process. The focus is on the methods that can create manufacturable and well-defined geometries. The survey will discuss the advantages, limitations, and related challenges of manufacturability in topology optimization.

Function-Oriented Material Design for Next-Generation Ground Vehicles

2003 ◽  
Author(s):  
Zheng-Dong Ma ◽  
Hui Wang ◽  
Noboru Kikuchi ◽  
Christophe Pierre ◽  
Basavaraju Raju
Keyword(s):  
Cost Effective ◽  
Material Design ◽  
Optimization Process ◽  
Ground Vehicles ◽  
Ground Vehicle ◽  
Cost Constraints ◽  
Vehicle Systems ◽  
Optimal Material ◽  
Material Layout ◽  
Oriented Material

A systematic approach, referred to as function-oriented material design (FOMD), is presented in this paper, which can be used to design materials for the specific tasks demanded of structures in future ground vehicle systems. In order to carry out the FOMD process, first the functions of a structure in the vehicle system need to be explicitly defined in a systematic way. Then these functions must be quantified, so as to define the objective and constraint functions in the optimization process. Finally, an advanced optimization process needs to be carried out, and the material layout has to be finalized by the design engineer. Typically a number of constraints, such as manufacturing and cost constraints, need to be considered in the optimal material design process. A major objective of this research is to outline these constraints, as well as to find ways to ameliorate the optimization process to produce improved, cost-effective, and manufacturable engineered materials.

Topology Optimization of Micromachined Structures With Surface Micromachining Manufacturing Constraints

2006 ◽  
Author(s):  
Aravind Alwan ◽  
G. K. Ananthasuresh
Keyword(s):  
Topology Optimization ◽  
Optimization Methods ◽  
Manufacturing Cost ◽  
Manufacturing Constraints ◽  
Surface Micromachining ◽  
Out Of Plane ◽  
Gradient Based ◽  
Plane Direction ◽  
New Formulation ◽  
Design Parameterization

Topology optimization methods have been shown to have extensive application in the design of microsystems. However, their utility in practical situations is restricted to predominantly planar configurations due to the limitations of most microfabrication techniques in realizing structures with arbitrary topologies in the direction perpendicular to the substrate. This study addresses the problem of synthesizing optimal topologies in the out-of-plane direction while obeying the constraints imposed by surface micromachining. A new formulation that achieves this by defining a design space that implicitly obeys the manufacturing constraints with a continuous design parameterization is presented in this paper. This is in contrast to including manufacturing cost in the objective function or constraints. The resulting solutions of the new formulation obtained with gradient-based optimization directly provide the photolithographic mask layouts. Two examples that illustrate the approach for the case of stiff structures are included.

scholarly journals A Two-Scale Multi-Resolution Topologically Optimized Multi-Material Design of 3D Printed Craniofacial Bone Implants

Micromachines ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 101
Author(s):  
Jaejong Park ◽  
Tareq Zobaer ◽  
Alok Sutradhar
Keyword(s):  
Topology Optimization ◽  
Material Design ◽  
Implant Design ◽  
Patient Specific ◽  
Optimization Approach ◽  
Efficient Design ◽  
Physiological Loading ◽  
Maximum Stiffness ◽  
Good Potential ◽  
Craniofacial Defects

Bone replacement implants for craniofacial reconstruction require to provide an adequate structural foundation to withstand the physiological loading. With recent advances in 3D printing technology in place of bone grafts using autologous tissues, patient-specific additively manufactured implants are being established as suitable alternates. Since the stress distribution of these structures is complicated, efficient design techniques, such as topology optimization, can deliver optimized designs with enhanced functionality. In this work, a two-scale topology optimization approach is proposed that provides multi-material designs for both macrostructures and microstructures. In the first stage, a multi-resolution topology optimization approach is used to produce multi-material designs with maximum stiffness. Then, a microstructure with a desired property supplants the solid domain. This is beneficial for bone implant design since, in addition to imparting the desired functional property to the design, it also introduces porosity. To show the efficacy of the technique, four different large craniofacial defects due to maxillectomy are considered, and their respective implant designs with multi-materials are shown. These designs show good potential in developing patient-specific optimized designs suitable for additive manufacturing.

Integrated method for performance analysis of reliability-based topologically optimized components

2019 ◽  
Vol 233 (19-20) ◽  
pp. 7019-7040
Author(s):  
Arshad Javed ◽  
Joshua Amrith Raj ◽  
BK Rout
Keyword(s):  
Topology Optimization ◽  
Design Of Experiments ◽  
Volume Fraction ◽  
Signal To Noise Ratio ◽  
Statistical Significance ◽  
Optimization Methods ◽  
Von Mises Stress ◽  
Efficient Design ◽  
Integrated Method ◽  
Design Factors

The available robust and reliable topology optimization methods provide quick and efficient design output in an uncertain environment. However, the whole domain of performance function remains hidden during this design process. In the interest of the designer, it is required to know the overall behavior of performance functions in deterministic as well as uncertain/realistic environment. The current work achieves this by proposing an integrated methodology, which combines the design of experiments approach and reliability-based topology optimization. The proposed method enables the designer to simulate performance functions in a desired design-factors space, including uncertainties, via reliability value. For this analysis, compliance, maximum deflection, mechanical advantage, and von Mises stress values are selected as performance functions. Volume fraction, applied force, and dimensions or aspect ratio are chosen as design/control factors. The uncertainties of these design factors are captured using reliability-based topology optimization. The uncertainties due to noncontrollable factors such as material property, load direction, and magnitude are incorporated using the design of experiments approach. Under these uncertainties, the performance of topologically optimized problem is simulated for different experimental combinations of the design factors. The experimental combinations for uncertainties and design factors are generated using Taguchi's orthogonal array. Simulated results are analyzed using techniques such as analysis of mean and variance, signal-to-noise ratio, and response surface method. These analyses help in identifying statistical significance of factors and uncertainties, performance variations, and equivalence relation of performance vs. factor. The proposed methodology is illustrated by selecting monolithic structures such as, on MBB, cantilever beam, and force inverter mechanism.

Topology optimization in structural mechanics

2013 ◽  
Vol 61 (1) ◽  
pp. 23-37 ◽  
Author(s):  
T. Lewiński ◽  
S. Czarnecki ◽  
G. Dzierżanowski ◽  
T. Sokół
Keyword(s):  
Topology Optimization ◽  
Domain Boundary ◽  
Material Design ◽  
Homogenization Theory ◽  
Structural Topology ◽  
Layout Problem ◽  
Short Introduction ◽  
Applied Loading ◽  
Free Material ◽  
Material Layout

Abstract Optimization of structural topology, called briefly: topology optimization, is a relatively new branch of structural optimization. Its aim is to create optimal structures, instead of correcting the dimensions or changing the shapes of initial designs. For being able to create the structure, one should have a possibility to handle the members of zero stiffness or admit the material of singular constitutive properties, i.e. void. In the present paper, four fundamental problems of topology optimization are discussed: Michell’s structures, two-material layout problem in light of the relaxation by homogenization theory, optimal shape design and the free material design. Their features are disclosed by presenting results for selected problems concerning the same feasible domain, boundary conditions and applied loading. This discussion provides a short introduction into current topics of topology optimization

Ultrasonic Torsion Welding of Aging Resistant Al/CFRP Joints - Concepts, Mechanical and Microstructural Properties

2017 ◽  
Vol 742 ◽  
pp. 395-400 ◽  
Author(s):  
Florian Staab ◽  
Frank Balle ◽  
Johannes Born
Keyword(s):  
Mechanical Properties ◽  
Process Parameters ◽  
Materials Science ◽  
Dissimilar Materials ◽  
Material Design ◽  
Ultrasonic Welding ◽  
Fatigue Properties ◽  
Aviation Industry ◽  
Efficient Design ◽  
Engineering Structures

Multi-material-design offers high potential for weight saving and optimization of engineering structures but inherits challenges as well, especially robust joining methods and long-term properties of hybrid structures. The application of joining techniques like ultrasonic welding allows a very efficient design of multi-material-components to enable further use of material specific advantages and are superior concerning mechanical properties.The Institute of Materials Science and Engineering of the University of Kaiserslautern (WKK) has a long-time experience on ultrasonic welding of dissimilar materials, for example different kinds of CFRP, light metals, steels or even glasses and ceramics. The mechanical properties are mostly optimized by using ideal process parameters, determined through statistical test planning methods.This gained knowledge is now to be transferred to application in aviation industry in cooperation with CTC GmbH and Airbus Operations GmbH. Therefore aircraft-related materials are joined by ultrasonic welding. The applied process parameters are recorded and analyzed in detail to be interlinked with the resulting mechanical properties of the hybrid joints. Aircraft derived multi-material demonstrators will be designed, manufactured and characterized with respect to their monotonic and fatigue properties as well as their resistance to aging.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

scholarly journals An efficient approach to reliability-based topology optimization for the structural lightweight design of planar continuum structures

2021 ◽  
Vol 37 ◽  
pp. 270-281
Author(s):  
Fangfang Yin ◽  
Kaifang Dang ◽  
Weimin Yang ◽  
Yumei Ding ◽  
Pengcheng Xie
Keyword(s):  
Topology Optimization ◽  
Lightweight Design ◽  
Integrated Design ◽  
Optimization Methods ◽  
Filter Function ◽  
Continuum Structures ◽  
Performance Indexes ◽  
Reliability Method ◽  
Economic Indexes ◽  
The Impact

Abstract In order to solve the application restrictions of deterministic-based topology optimization methods arising from the omission of uncertainty factors in practice, and to realize the calculation cost control of reliability-based topology optimization. In consideration of the current reliability-based topology optimization methods of continuum structures mainly based on performance indexes model with a power filter function. An efficient probabilistic reliability-based topology optimization model that regards mass and displacement as an objective function and constraint is established based on the first-order reliability method and a modified economic indexes model with a composite exponential filter function in this study. The topology optimization results obtained by different models are discussed in relation to optimal structure and convergence efficiency. Through numerical examples, it can be seen that the optimal layouts obtained by reliability-based models have an increased amount of material and more support structures, which reveals the necessity of considering uncertainty in lightweight design. In addition, the reliability-based modified model not only can obtain lighter optimal structures compared with traditional economic indexes models in most circumstances, but also has a significant advantage in convergence efficiency, with an average increase of 44.59% and 64.76% compared with the other two reliability-based models. Furthermore, the impact of the reliability index on the results is explored, which verifies the validity of the established model. This study provides a theoretical reference for lightweight or innovative feature-integrated design in engineering applications.

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