DOCSLIB.ORG

Generative Design: Advanced Design Optimization Processes for Aeronautical Applications S

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Generative Design: Advanced Design Optimization Processes for Aeronautical Applications S GENERATIVE DESIGN: ADVANCED DESIGN OPTIMIZATION PROCESSES FOR AERONAUTICAL APPLICATIONS S. Bagassi*, F. Lucchi*, F. De Crescenzio*, F. Persiani* *Industrial Engineering Department, University of Bologna Keywords: Design Methods, Aircraft Design, Generative Design, Additive Manufacturing, Materials and Processes Abstract Current researches on aircraft design aim to 1 Introduction reduce airplanes and components weights, optimizing aircraft performances and More flights, more potential passengers, fewer contributing to the challenge of reducing fuel emissions and shorter travel time will mark consumption and operational costs. future and challenges of aviation. According to In this perspective novel materials and such a vision, aircraft design is a balance technologies are developed, but also advances between costs, environmental aspects, in design methods and tools. Generative Design regulations, airliners’ requirements and aircraft is a novel approach to automatically optimize performances. Design methods and tools have to component design. The design process has to be develop accordingly. Innovative technologies designed itself to achieve the optimal solution, and materials will support designers in in relation to design parameters, requirements searching new solutions and processes. In this and limits. way, innovation in design methods changes Which peculiar features justify considering this common paradigms: the cross fertilization technique to be a substantial step forward with coming from incorporating concepts derived respect to classical MDO? Could Generative from many disciplines and their integration with Design be only an important, but not advanced manufacturing systems and materials particularly differentiated approach for the may improve design results. design of (aerospace) structures and possibly Inspired by the natural design processes and systems of a higher level? For example, when patterns of nature, Generative Design is a design the design goal is to find the best configuration method for capturing the designer’s intent, of a structure, does generative design lead to generating new solutions. Characterized by the discovery of new concepts, or types of data-driven collaborative cloud-based structures, or it is a particular application of technology, it relies upon a highly automated genetic algorithms to topological optimization? activity. A set of parameters and rules This paper aims to contribute to give an answer (commands to the designer) is considered as the to the previous questions. Specifically, the DNA of the design process; rules and generative design approach is expected to be parameters are considered as the “genes”. They able to select between basic concepts and use are combined by evolutionary algorithms or these as the basic instructions and ingredients even “brute force” computations. The of a recipe for the design of a new system. introduction of such procedures into the design By these considerations, in this paper, we process allows the development of novel design revised the improvements brought by solutions by modifying the rules that define a Generative Design principles within the final design, difficult or impossible to achieve traditional design procedure in aeronautics, via other methods. Grammar-based techniques considering Additive Manufacturing technology. exploit the principle of database amplification, 1 S.BAGASSI, F.LUCCHI, F.DE CRESCENZIO, F.PERSIANI the identification of rules, generating complex performance [2]. Furthermore, AM’s impact on forms and patterns from simple specifications. economies of scale and scope make it a natural Generative design principles received a fit for Aerospace, which is largely geared particular attention in architecture; some good toward customized production. A synthetic definitions coming from that field are reported overview of current and potential applications is here [1]: reported in Figure 1. Ø “Generative design is not about designing the building – It’s about designing the system that builds a building.” – Lars Hesselgren; Ø “Generative Design Processes is about the modelling of initial conditions of an object (its “genetics”) instead of modelling the final form.” – Paola Fontana; Fig.1 – Current and future applications of AM in Ø “Generative design systems are aimed at Aerospace industries creating new design processes that produce spatially novel yet efficient and buildable The new system, once manufactured thanks to designs through exploitation of current AM, should satisfy to the functional computing and manufacturing capabilities” – requirements in an innovative and more Kristina Shea. efficient way, targeting also a simpler design and a substantial cost reduction. Novel structural materials and advanced AM 1.1 Generative Design within the Design for techniques make these technologies ready to be Additive Manufacturing approach introduced within the generative design process Nowadays it is generally accepted that in also for safety critical context, such as the Aerospace and Industrial applications, we can aeronautical. achieve the main advantages from the Even if the advantages from the introduction of introduction of advanced design procedures, if the couple Generative Design and Additive we combine them with Additive Manufacturing Manufacturing has been widely considered, (AM) processes and techniques. only some case studies have been provided in Therefore, we have to take into account also the architecture, styling and biomedical coupling of evolutionary algorithms with applications, but has not be explored enough in innovative manufacturing processes, like aerospace. Additive Manufacturing, and new materials. This combination introduces more degrees of freedom in the final design concept: for 2 Generative Design approach in product example, the mixing of materials with different development and aeronautical industry properties allows having different properties Typical Aircraft design practices consider the distributed in different zones of the same part, design process spread into three main phases: leading to multi-functional concepts. the conceptual design, the preliminary design The opportunities offered by AM are not and the detailed design. The design solution is restricted to multi-functional concepts. Consider proposed throughout the typical diverging – that, over the last years, AM’s adoption has converging process, in relation to design increased across industries, with the aerospace requirements and limits. Multidisciplinary industry contributing about 10.2% of AM’s optimization processes are currently being global revenues in 2012. AM provides the developed to support designer in assessing the flexibility to create complex part geometries optimal solution, in relation to all design that are difficult to build using traditional features and parameters. manufacturing, such as internal cavities or Generative Design is a novel form-finding lattice structures that help reduce parts’ weight process that takes into account structural without compromising their mechanical performances, material properties and 2 GENERATIVE DESIGN: ADVANCED DESIGN OPTIMIZATION PROCESSES FOR AERONAUTICAL APPLICATIONS ergonomic demand, throughout an automatic iterative holistic approach for component topology optimization [3]. The design approach is grammar based, and the design activity itself has to be designed, on the basis of evolutionary algorithms in order to meet the optimal scoring for an objective fitness function [4]. Evolutionary design approaches limits to performing the numerical optimization on the set of design parameters [5]. On the other side, Topology Optimization intends to find an optimal structural configuration within a given design domain for specified objectives, constraints, loads and Fig.2 – Scheme of Generative Design role in the design boundary conditions. In general, it relates to size activity or shape optimization issues [6], , with particular regards to component weight Even if in simpler case studies, the generative reduction: optimized configurations are defined representation derived from evolutionary re-distributing the material in the design design, where the Evolutionary Design System domains with the prescribed loads and boundary is able to explore the space of design topologies, conditions. advanced Generative Design System and Tools Generative Design includes both Evolutionary should include some key aspects both in the Design and Topological Optimization, but it is design features and in the representation of the not limited to that. solutions: modularity, regularity and hierarchy. After years of research and development, some Modules are at the base of the design specialized Generative Design tools are representation and they are hierarchically becoming part of CAD/CAE platforms and are formed and could be combined or reused to entering the market [8]. define the final topology optimization [9]. A company developed software to be integrated From a computer programming language point of view, rule-based design-construction with industry-leading Building Information programs define the design-programming tool. Model (BIM) and CAD platforms. This Subprocedure-like elements are at the basis of software includes “two classes of tools: the first the modularity feature; iterative loops and sub- class connects existing tools together to allow procedures enable the regularity role and a nest- seamless execution of complex workflows, and base approach defines the hierarchy, to link all the second class
Load more

Recommended publications
  • MSC Apex Generative Design Brochure
    Brochure MSC Apex Generative Design Bridge the gap between design and manufacturing with Smart Generative Design At a glance MSC Apex Generative Design is the fully automated generative design solution built on the most intuitive CAE environment in the world, MSC Apex. It exploits all the easy-to-use and easy-to-learn features of MSC Apex while employing an innovative generative design engine in the background. Thus, it dramatically decreases the effort required in the design optimisation workflow. Simplicity Import and validation No expert knowledge required for conducting Import existing geometries or mesh, find optimisations through a high user-focused optimised design candidates, and perform software design design validation - all inside a single CAE environment. Automated design Direct output Almost automatically generate multiple smoothed design candidates that all satisfy the Export geometry that can be directly design criteria while minimising the weight. manufactured and used immediately without manual re-work. One process Import the resulting geometries in Simufact Additive or Digimat AM to achieve cost-efficient first-time-right result for every part MSC Apex Generative Design Design for Additive Manufacturing (DfAM) without expert knowledge MSC Apex Generative Design is designed specifically to generate the detailed and highly complex structures that only additive processes can manufacture. The optimised designs exhibit perfect transitions between structure elements such as struts and shells as well as they contain usually self- supporting structures that ensure the results can be sent straight to print. However, in cases where further manufacturing and design validation is necessary, MSC Apex Generative Design is interoperable with Simufact Additive, Digimat AM, and MSC Nastran.
    [Show full text]
  • Eesof EDA Advanced Design System
    Keysight Technologies Keysight EEsof EDA Advanced Design System The Industry’s Leading RF, Microwave, Signal Integrity and Power Integrity Design Platform 02 | Keysight | EEsof EDA Advanced Design System - Brochure Table of Contents Advanced Design System ����������������������������������������������������������������������������������������������������������������������������03 More than 30 Years of Enabling Innovation ������������������������������������������������������������������������������������������������04 Design with Confidence �������������������������������������������������������������������������������������������������������������������������������05 Complete Design Flow ���������������������������������������������������������������������������������������������������������������������������������07 Create Custom 3D Components for Simulation with ADS Layout Designs ����������������������������������������������� 10 Most Complete Solution ������������������������������������������������������������������������������������������������������������������������������ 11 ADS Provides a Cohesive Workflow for Signal Integrity and Power Integrity Analyses ��������������������������� 12 Integrated Solutions ������������������������������������������������������������������������������������������������������������������������������������ 13 Seamless Integration with Keysight’s EDA Tools and Measurement Instrumentation ������������������������������ 14 Making Your Job Easier with Worldwide Technical Keysight EDA Experts ������������������������������������������������
    [Show full text]
  • Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions
    applied sciences Review Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions Yanbin Li 1, Gang Lei 2,* , Gerd Bramerdorfer 3 , Sheng Peng 1, Xiaodong Sun 4 and Jianguo Zhu 5 1 School of Electronic and Information, Zhongyuan University of Technology, Zhengzhou 450007, China; [email protected] (Y.L.); [email protected] (S.P.) 2 School of Electrical and Data Engineering, University of Technology Sydney, Ultimo, NSW 2007, Australia 3 Department of Electrical Drives and Power Electronics, Johannes Kepler University Linz, Linz 4040, Austria; [email protected] 4 Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China; [email protected] 5 School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW 2006, Australia; [email protected] * Correspondence: [email protected] Abstract: This paper reviews the recent developments of design optimization methods for electromag- netic devices, with a focus on machine learning methods. First, the recent advances in multi-objective, multidisciplinary, multilevel, topology, fuzzy, and robust design optimization of electromagnetic devices are overviewed. Second, a review is presented to the performance prediction and design optimization of electromagnetic devices based on the machine learning algorithms, including artifi- cial neural network, support vector machine, extreme learning machine, random forest, and deep learning. Last, to meet modern requirements of high manufacturing/production quality and lifetime Citation: Li, Y.; Lei, G.; reliability, several promising topics, including the application of cloud services and digital twin, are Bramerdorfer, G.; Peng, S.; Sun, X.; discussed as future directions for design optimization of electromagnetic devices.
    [Show full text]
  • State of the Art of Generative Design and Topology Optimization and Potential Research Needs
    NordDesign 2018 August 14 – 17, 2018 Linköping, Sweden State of the art of generative design and topology optimization and potential research needs Evangelos Tyflopoulos1, David Tollnes Flem2, Martin Steinert 3, Anna Olsen 4 1 Department of Mechanical and Industrial Engineering, NTNU [email protected] 2 Department of Mechanical and Industrial Engineering, NTNU [email protected] 3 Department of Mechanical and Industrial Engineering, NTNU [email protected] 4 Department of Mechanical and Industrial Engineering, NTNU [email protected] Abstract Additive manufacturing allows us to build almost anything; traditional CAD however restricts us to known geometries and encourages the re-usage of previously designed objects, resulting in robust but nowhere near optimum designs. Generative design and topology optimization promise to close this chasm by introducing evolutionary algorithms and optimization on various target dimensions. The design is optimized using either 'gradient-based' programming techniques, for example the optimality criteria algorithm and the method of moving asymptotes, or 'non gradient- based' such as genetic algorithms SIMP and BESO. Topology optimization contributes in solving the basic engineering problem by finding the limited used material. The common bottlenecks of this technology, address different aspects of the structural design problem. This paper gives an overview over the current principles and approaches of topology optimization. We argue that the identification of the evolutionary probing of the design boundaries is the key missing element of current technologies. Additionally, we discuss the key limitation, i.e. its sensitivity to the spatial placement of the involved components and the configuration of their supporting structure. A case study of a ski binding, is presented in order to support the theory and tie the academic text to a realistic application of topology optimization.
    [Show full text]
  • Design Thinking for User-Centric Website Optimization
    Paper to be presented at the DRUID Academy Conference 2018 at University of Southern Denmark, Odense, Denmark January 17-19, 2018 Design thinking for user-centric website optimization Vella Verónica Somoza Sanchez University of Southern Denmark Department of Marketing and Management/CI2M [email protected] Stefan Daniel Suivei University of Southern Denmark The Maersk Mc-Kinney Moller Institute [email protected] René Chester Goduscheit SDU Department of Marketing and Management [email protected] Peter Schneider-Kamp University of Southern Denmark IMADA [email protected] Abstract Title: Design thinking for user-centric website consequently, improve their user experience. The optimization. A case study. case considered in this study focuses on a Name: Vella Somoza company from the retail banking industry offering Affiliation: CI2M, SDU loans through comparison websites. Year of enrolment: 2017. First, to find a solution to this wicked problem we Expected final date: 2019 adapt the process of design thinking to the E-mail address: [email protected] context studied, i.e., to the design optimization of retail banking web sites. Second, we provide insights in how big data can aid the development This paper presents results from a pilot study, of a website design that optimizes the user which is part of a larger research project where we experience of the customers. As the creation of study the process innovation of website these user-centric websites is a never confronted optimization as a service through the use of big task for this type of organization, a variety of data. Over a process of design thinking we methods is applied.
    [Show full text]
  • The Role of Multidisciplinary Design Optimization (Mdo) in the Development Process of Complex Engineering Products
    21ST INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED17 21-25 AUGUST 2017, THE UNIVERSITY OF BRITISH COLUMBIA, VANCOUVER, CANADA THE ROLE OF MULTIDISCIPLINARY DESIGN OPTIMIZATION (MDO) IN THE DEVELOPMENT PROCESS OF COMPLEX ENGINEERING PRODUCTS Papageorgiou, Athanasios; Ölvander, Johan Linköping University, Sweden Abstract The work presented in this paper explores several concepts related to the design of complex engineering products and emphasizes on the effects of considering Multidisciplinary Design Optimization (MDO) in the development process. This paper is by no means a comprehensive literature review, but instead, the aim is to discuss some key points through theory and references to common MDO applications. In this respect, the central topics which are addressed herein are the enhancement of the generic product development process, the road towards a better integration of the organization’s functions, the methods to manage complex system architectures, and finally, the shortcomings of the MDO field. As a link to more tangible industrial applications, Unmanned Aerial Vehicles (UAVs) are chosen as an illustrative example due to their technical complexity as well as the demanding requirements of the corresponding market. Overall, the paper shows that despite the current state-of-the-art limitations, MDO can be a valuable tool within the “traditional” design process that has the potential to enable products of better quality while simultaneously reducing the total development time and effort. Keywords: Design methods, Design process, Optimisation, New product development, Multidisciplinary Design Optimization Contact: Athanasios Papageorgiou Linköping University Management and Engineering Sweden [email protected] Please cite this paper as: Surnames, Initials: Title of paper. In: Proceedings of the 21st International Conference on Engineering Design (ICED17), Vol.
    [Show full text]
  • Towards an Integrated Generative Design Framework
    Towards an integrated generative design framework Vishal Singh, School of Architecture and Building, Deakin University, 1 Geringhap Street, Geelong, Victoria 3220, Australia Ning Gu, School of Architecture and Built Environment, University of Newcastle, New South Wales 2308, Australia Design creativity techniques encourage divergent thinking. But how well do the existing generative design techniques support this requirement? How can these general techniques be augmented for supporting design exploration and creativity? This paper investigates these questions through a review of five different generative design techniques used in architectural design that includes cellular automata, genetic algorithms, L-systems, shape grammars, and swarm intelligence. Based on the literature on design cognition and the recent theoretical works on digital design thinking, this paper proposes the need for an integrated generative design framework to enhance design exploration support for human designers. Potential challenges and strategies towards developing such an integrated framework are discussed. Ó 2011 Elsevier Ltd. All rights reserved. Keywords: generative design, architectural design, digital design, design cognition, reflective practise he main incentives for adopting generative design (GD) systems in Tarchitecture are to use computational capabilities to support human designers and (or) automate parts of the design process. The ability to explore larger design space and support design generation is one of the main objectives besides achieving efficiency
    [Show full text]
  • TOOLS for CONVIVIALITY Transcribing Design
    TOOLS FOR CONVIVIALITY Transcribing design elif Kendir, tim schork Spatial Information Architecture Laboratory School of Architecture and Design Royal Melbourne Institute of Technology Melbourne, Australia abstract: This paper presents the outcomes and findings of a semester long trans- disciplinary design studio recently taught at RMIT University, involving students from the disciplines of architecture, industrial design and landscape design. The focus of the studio was to investigate the creation and appropriation of tools for innovative design processes. Drawing on craft theory and theories of design and computation, this paper illustrates how tools can transgress disciplinary boundaries and investigates how an understanding of the intricate relationship between tools, techniques, the media they operate in and the design outcome is the premise of a more informed design approach. keywords: Craft Theory, Design and Computation, Design studio pedagogy, Tooling résumé : Cet article présente les résultats et conclusions d’un atelier de design transdiciplinaire donné à la RMIT University avec des étudiants en architecture, en design industriel et en design de paysage. L’objectif était d’examiner la création et l’appropriation d’outils consacrés aux processus innovateurs en design. S’appuyant sur la théorie des métiers et sur les théories en design et informatique, cet article illustre comment les outils peuvent dépasser les limites des disciplines qui leur sont propres, et il explore comment une compréhension de la relation com- plexe unissant outils, techniques et médias est la prémisse d’une approche de design mieux informée. mots-clés : Théorie des métiers, design et informatique, pédagogie en atelier de design, équi- pement CAAD Futures 2009_compile.indd 740 27/05/09 10:47:13 tooL for conviviaLitY 741 1.
    [Show full text]
  • Substantial Changes in Graphic Design with the Emergence of Generative Design Processes 2019 I Index
    Universidad Internacional de La Rioja Máster Universitario en Diseño Gráfico Digital Substantial Changes in Master in Digital Graphic design Graphic Design with the Emergence of Generative Design Processes Cambios profundos en Diseño Gráfico con la Aparición de los Procesos de Diseño Generativo Master’s thesis/ Trabajo fin de Máster (Trabajo Tipo 1) Presented by / Presentado por: Schimpf, Anna Veronica Donostia, 04.02.2019 Director / Directora: Moñivas Mayor, Esther “Design is where art and science break even.” – Robin Mathew 19/09/2018 Anna Veronica Schimpf _ Máster en diseño Gráfico Digital _Substantial changes in Graphic Design with the emergence of Generative Design processes _2019 i Index 0_ Abstract 1 0_ Resumen 2 1_ Introduction 1_ Introduction 3 1.1 Introduction 3 2_ Framework 1.2 Justification 4 1.3 Approach 6 3_ Goals & Method 1.3.1 Approach of solution 6 1.3.2 Scope and boundaries 7 1.3.3 Goals and focus 7 4_ Design Generative 1.4 Structure 8 2_ Basic Research Framework 9 5_ & Future Present 3_ Goals & Method 11 3.1 Initial hypothesis and general research goal 11 6_ Creation 3.2 Specific research questions 12 3.3 Method 12 3.3.1 A comprehensive literature review for goals 1 and 2 12 7_ Conclusions 3.3.2 A practical approach for goal 3 16 20/09/2018 8_ References Anna Veronica Schimpf _ Máster en diseño Gráfico Digital _Substantial changes in Graphic Design with the emergence of Generative Design processes _2019 ii 4_ Understanding the Generative Design phenomenon 19 4.1 Introduction to Generative Design 19 4.2 Key concepts
    [Show full text]
  • From Design Automation to Generative Design in AEC
    The Journey from Design Automation to Generative Design in AEC Dieter Vermeulen Technical Sales Specialist AEC Generative Design & Engineering @BIM4Struc © 2020 Autodesk, Inc. DESIGNS TODAY @BIM4Struc TRADITIONAL DESIGN PROCESS @BIM4Struc @BIM4Struc @BIM4Struc @BIM4Struc GENERATIVE DESIGN: A form of artificial intelligence, dedicated to the creation of better outcomes for products, buildings, infrastructure and systems. @BIM4Struc GENERATIVE DESIGN PROCESS PEOPLE COMPUTER PEOPLE @BIM4Struc STADIUM DESIGN CONSTRUCTION PLANNING SITE DRAINAGE NEIGHBORHOOD PLANNING SPACE PLANNING FAÇADE DESIGN @BIM4Struc Generative design is a methodology and a process more than a singular product or tool @BIM4Struc Benefits of Generative Design @BIM4Struc What level of design progression ? @BIM4Struc Traditional Design @BIM4Struc Sketching @BIM4Struc Computer Aided Drafting @BIM4Struc Parametric Design @BIM4Struc PARAMETRIC DESIGN Designer/engineer uses computer as passive machine one one limited human + computer = design @BIM4Struc PARAMETRIC MODELING @BIM4Struc Parametric Modeling a = 2 b = 1 a – b = c @BIM4Struc Parametric Modeling a = 2 b = 1 a – b = c f(x) @BIM4Struc Parametric Modeling a = 2 b = 1 a – b = c @BIM4Struc Conceptual Tower Mass – Design Model Assign Parametric Create Geometry Modify Parameters Document the Idea Constraints @BIM4Struc Design Automation @BIM4Struc input design output automation @BIM4Struc Dynamo Ecosystem to increase capabilities REVIT API Difficulty REVIT DYNAMO Expressive Power @BIM4Struc Dynamo to simplify things PROGRAMMING
    [Show full text]
  • Numerical Experience with Two-Point Adaptive Nonlinearity Approximation for Design Optimization
    INTERNATIONAL DESIGN CONFERENCE - DESIGN 2004 Dubrovnik, May 18 - 21, 2004. NUMERICAL EXPERIENCE WITH TWO-POINT ADAPTIVE NONLINEARITY APPROXIMATION FOR DESIGN OPTIMIZATION G. Magazinović Keywords: design optimization, function approximation, TANA-3 1. Introduction During the last decade numerous approximation techniques have taken place for application in optimization. Therefore, function approximation techniques emerge as one of the most important fields of interest. A thorough survey on this topic can be found in [Barthelemy and Haftka 1993]. The main objective of various approximation techniques in design and structural optimization is the reduction of repetitive evaluation of cost and constraint functions. In general, more precise function approximation provides faster convergence and more efficient achievement of optimum design. Consequently, the quality of function approximations emerge as one of the most important issues in the field of design and structural optimization. The main purpose of this paper is to investigate and quantify the accuracy of the Two-Point Adaptive Nonlinearity Approximation, TANA-3 [Xu and Grandhi 1998]. The result could be a valuable tool in comparison with other approximation schemes such as the Generalized Convex Approximation, GCA [Chickermane and Gea 1996], numerically evaluated in [Magazinović 2000]. The outline of the paper is as follows: In Section 2, a brief overview of the Two-Point Adaptive Nonlinearity Approximation algorithm is presented. In Section 3, a description of performed numerical tests is given and finally, in Section 4, numerical results are presented. 2. Two-Point Adaptive Nonlinearity Approximation 2.1 TANA-3 Basics The Two-Point Adaptive Nonlinearity Approximation, TANA-3, is the last and probably the best approximation scheme in a well known series of four function approximations: TANA [Wang and Grandhi 1994], TANA-1 and TANA-2 [Wang and Grandhi 1995], and finally TANA-3 [Xu and Grandhi 1998].
    [Show full text]
  • Generative Adversarial Network-Based Visual Aware Interactive
    GENERATIVE ADVERSARIAL NETWORK-BASED VISUAL-AWARE INTERACTIVE FASHION DESIGN FRAMEWORK By Ashenafi Workie Dessalgn A Thesis Submitted to Department of Computer Science and Engineering School of Electrical Engineering and Computing Office of Graduate Studies Adama Science and Technology University October 2020 Adama, Ethiopia GENERATIVE ADVERSARIAL NETWORK-BASED VISUAL-AWARE INTERACTIVE FASHION DESIGN FRAMEWORK By Ashenafi Workie Dessalgn Advisor: Prof. Yun Koo Chung (Ph.D.) A Thesis Submitted to Department of Computer Science and Engineering School of Electrical Engineering and Computing Office of Graduate Studies Adama Science and Technology University October 2020 Adama, Ethiopia APPROVAL PAGE The author, the undersigned, members of the Board of Examiners of the final open defense by “Ashenafi Workie Dessalgn” have read and evaluated his thesis entitled “GENERATIVE ADVERSARIAL NETWORK-BASED VISUAL-AWARE INTERACTIVE FASHION DESIGN FRAMEWORK” and examined the candidate. This is, therefore, to certify that the thesis has been accepted in partial fulfillment of the requirement of the Degree of Masters in Computer Science and Engineering. Name Signature Date Ashenafi Workie Dessalgn Name of the Student Prof. Yun Koo Chung Advisor External Examiner Internal Examiner Chair Person Head of Department School Dean Post Graduate Dean DECLARATION I hereby declare that this MSc. a thesis is my original work and has not been presented for a degree in any other university, and all sources of material used for this thesis have been duly acknowledged. Name: Ashenafi Workie Signature: _____________________ This MSc. thesis has been submitted for examination with my approval as a thesis advisor. Name: Yun Koo Chung (Ph.D.) Signature: _____________________ Date of submission: ____________________ DEDICATION To those who lost their lives through the pandemic of COVID-19 and Mr.
    [Show full text]