Minisymposia

main content

Potential contributors can find the descriptions of the approved minisymposia here below (click on the title to open the description), and are invited to contact as soon as possible one of the organisers at the provided email to communicate the intention to submit.

Extended abstracts/draft papers, and final full papers submitted within the framework of anyone of the minisimposia have to have the same format of the standard contributions and must be submitted within the standard deadlines through the centralised conference management system (page for abstract submissions). The reviews of the MS contributions will be managed by the MS organisers, who will follow the same rules adopted for the standard contributions.

For each minisymposium the delivery format will be agreed between the MS organisers and the Conference organisers, with the idea to optimise the knowledge exchange in the area.

1. Surrogate-Based Optimization in Aerodynamic Design

ORGANISERS

E. Iuliano (Centro Italiano Ricerche Aerospaziali - CIRA, e.iuliano@cira.it),
E. Andrés (Spanish National Institute for Aerospace Technology - INTA, eandres@isdefe.es)

ABSTRACT

Aerodynamic design, with particular reference to its early stages, requires exploring the design space in a global sense in order to locate the optimal candidate. Global optimization methods (e.g., evolutionary algorithms) can meet this requirement as they have the ability to work with noisy objective functions without assumptions on continuity and with a high potential to find the optimum of complex problems. However, they involve a vast number of evaluations even for a small number of design variables. As each evaluation requires a CFD complete analysis, this would make the method infeasible, in terms of computational cost, for real-world applications. Therefore, there has been a raising interest in surrogate modelling which promises to provide sufficiently accurate solution of complex problems with limited or reduced computational efforts. Surrogate modelling methods are widely recognized as supporting tools easing the designer task in design space exploration, parametric studies, visualization and optimization. With the term “surrogate” it is usually meant an analysis method which, in some sense, is “alternative” to the high-fidelity one (e.g., CFD) and, with respect to it, is able to provide a quicker and sufficiently accurate estimation of the quantities of interest of the simulation (e.g., the aerodynamic coefficients) and, hence, of the fitness function in an optimization process. Recently, a GARTEUR Action Group has been established to explore surrogate-based global optimization approaches. The main objective of the AG work [1] is, by means of a European collaborative research, to make a deep evaluation and assessment of surrogate-based global optimization methods for aerodynamic shape optimization, dealing with the main challenges as the curse of dimensionality, reduction of the design space and error metrics for model validation, amongst others. The special session will provide a chance to share recent progresses and results in the field of surrogate-based aerodynamic optimization, to meet up with other researchers in the related field and to exchange ideas on the topic in a fruitful discussion.

Key words:Aerodynamic shape design, Surrogate Modeling, Global optimization methods

TOPICS

The special session is aimed at collecting and disseminating contributions and new ideas in surrogate modelling and surrogate-based optimization for aerodynamic design. A particular emphasis is put on the development of fast and efficient meta-models for CFD-based optimization applications where multimodality, high non-linearity, non-differentiability, high dimensionality and high computational cost are expected features. For these reasons, real-world industrial applications are welcome.

Authors are invited to submit papers on one or more of the following topics:

  • Data fitting surrogate modeling
  • Multi-fidelity surrogate modeling
  • Global and Local Surrogate-based optimization (SBO)
  • Efficient Global Optimization
  • Adaptive sampling strategies
  • Trust region approaches
  • Proper Orthogonal Decomposition methods
  • Reduced Order modeling
  • Evolutionary search methods

REFERENCES

[1] GARTEUR EG67 members. Proposal for the establishment of a GARTEUR Action Group: Surrogate-based global optimization methods in preliminary aerodynamic design, November 2012.

2. Adjoint Methods for Steady & Unsteady Optimization

ORGANISERS

J. Mueller (Queen Mary Univ. London, j.mueller@qmul.ac.uk),
K. Giannakoglou (National Technical University of Athens - NTUA, kgianna@central.ntua.gr)

ABSTRACT

An essential ingredient for an efficient CFD optimisation method is the adjoint method which allows to compute these gradients at near constant cost, independent of the number of design variables. The major European industries and research institutions have developed adjoint CFD solvers, and the EC is currently funding the MC-ITN project About Flow: Adjoint-based optimisation of industrial and unsteady flows, http://aboutflow.sems.qmul.ac.uk, which supports this minisymposium with a number of contributions.

TOPICS

This minisymposium focuses on the topic of adjoint-based optimisation for steady and unsteady flows. Contributions are welcome on:

  • Improving robustness and versatility of the adjoint solvers,
  • Progress toward with adjoints for unsteady flows,
  • Integration into the workflow with parametrisation, optimisation and return to CAD,
  • Applications of adjoint design in industrial cases.
3. Multi-disciplinary Design Optimization

ORGANISERS

A. Riccardi (University of Strathclyde, annalisa.riccardi@strath.ac.uk),
E. Minisci (University of Strathclyde, edmondo.minisci@strath.ac.uk),
M. Vasile (University of Strathclyde, massimiliano.vasile@strath.ac.uk)

ABSTRACT

Across all fields of Engineering Sciences, many design problems are multidisciplinary in nature. An optimal design can be achieved if all the disciplines are concurrently considered in an integrated approach. In MDO the whole is more than the sum of the parts, therefore the optimum of the integrated problem is superior to the design found by optimizing each discipline independently. However, including all disciplines simultaneously significantly increases the complexity of the problem. The optimal design of each discipline can be in itself a hard and computationally intensive optimization problem. In addition, the definition of the level of fidelity of the model for each discipline, the interexchange of variables of different nature (the output of one discipline can become the input to another) and the increased dimensionality, contribute to make the problem considerably harder. Assessing the best trade-off between model accuracy and efficiency, model sensitivity and the definition of the optimization problem and MDO architecture are among the main designer decisions.
The largest number of applications of MDO techniques is in the field of aerospace engineering, such as aircraft and spacecraft design in which aerodynamics, structural analysis, propulsion, control theory, and economics are integrated in a single optimization process. But many techniques have been developed and applied in a number of different fields, including automobile design, naval architecture, electronics, computers, and electricity distribution.

TOPICS

This special session intends to collect many, diverse efforts made in the development of methods and techniques for multidisciplinary design optimization across all the fields of engineering and physical sciences. The session seeks to bring together researchers from around the globe for a stimulating discussion on recent advances in MDO methods for the solution of any engineering problem. The session looks with particular interest for (but not limited to) nature inspired methods specifically devised, adapted or tailored to address problems in MDO applications or nature inspired methods that were demonstrated to be particularly effective at solving MDO related problems. Furthermore, new examples of real-world applications of MDO techniques are welcome. Authors are invited to submit papers on one or more of the following topics:

  • Multi-Objective Optimization Methods in MDO
  • Uncertainty Treatment in MDO
  • Integrated System and Control Design
  • Optimization by Multi-fidelity Modelling
  • Optimization by Space Reduction Techniques
  • Concurrent Engineering and Distributed CE
  • Distributed and Parallel MDO
  • Cloud based MDO
  • Game Theory Approaches to MDO
  • Topology MDO
  • Knowledge Based Engineering for MDO
4. Holistic Optimization in Marine Design

ORGANISERS

E. Boulougouris (University of Strathclyde, evangelos.boulougouris@strath.ac.uk),
A. Papanikolaou (National Technical University of Athens (NTUA), papa@deslab.ntua.gr)

ABSTRACT

It is well known that ship design is a “complex endeavour requiring the successful coordination of many disciplines, of both technical and non-technical nature, and of individual experts to arrive at valuable design solutions” [1]. Inherently coupled with the design process is design optimization as the tendency to optimise is a human characteristic [2]. From the moment the designers find a feasible solution the next thought in their mind is to examine the possibility of finding better solutions within the particular design space, given the imposed constraints. When this is done with a methodological approach which makes sure that the best solution(s) have been identified then we may characterise this as an optimisation approach. However, as Harries [3] notes, the term optimization is used ambiguously as many would claim that a design is optimized once a handful of feasible solutions had been considered. Nowadays the introduction of powerful modelling tools, optimisation algorithms, simulation codes and the increased computing power of the hardware systems made possible the materialisation of global optimisation technics (e.g. evolutionary algorithms) within the typically noise, diffracted and discontinuous design space found in naval architecture, ocean and marine engineering. The engineers can now build parametric models and use multiple objectives generating thousands of virtual designs, identifying complex multi-dimension Pareto fronts. In cases where the problem required the use of expensive simulation codes and the first derivatives of the objective function are not available hybrid methods based on filled function algorithm and Particle Swarm Optimisation have been proposed [4]. However, there is now a new kind of problem that engineers have to solve. It is the management of the uncertainty arising because of a number of uncertain parameters like payload, sea state, fuel price etc typical present in a ship optimisation problem [5]. To overcome this limitation, researchers have proposed the two-stage stochastic programming paradigm [5]. The Minisymposium on Holistic Optimisation in Marine Design will provide an opportunity to share views, recent development and results in the field of holistic marine design, to meet up with other researchers in the related field and to exchange ideas on the topic in a fruitful discussion. The delivery format will be optimised to maximise the knowledge exchange in the research area, with the idea to have a number of presentations as a start for a more intensive "discussion round" afterwards on the key issues.

Key words: Holistic Ship Optimisation, Multi-objective optimisation, Genetic Algorithms, Parametric Ship Design, Global Optimisation, Optimisation and Uncertainty

TOPICS

The minisymposium aims at collecting and disseminating contributions and new ideas on parametric modelling and holistic optimization on marine design. A particular emphasis is put on the development of fast and efficient meta-models for CFD and FEA-based optimization applications where multimodality, high non-linearity, non-differentiability, high dimensionality and high computational cost are expected. For these reasons, real-world industrial applications are welcome. Authors are invited to submit papers on one or more of the following topics:

  • Response Surface Methodology (RSM) and Metamodeling
  • Global and Local optimization models
  • Efficient Global Optimization
  • Adaptive sampling strategies
  • Ship Design Optimisation under Uncertainty
  • Evolutionary search methods
  • Simulation-driven design optimisation

REFERENCES

[1] Papanikolaou A., “Holistic ship design optimization”, Journal of Computer-Aided Design Volume 42, Issue 11, November 2010, pg. 1028–1044.
[2] Nowacki H., “Design Synthesis and Optimization-An Historical Perspective”, Optimistic-Optimization in Marine Design, Birk, L. and Harries, S. ed., Mensch & Buch Verlag, ISBN 3-89820-514-2, 2003, pg. 1-27.
[3] Harries S., “Practical Shape Optimization Using CFD”, FRIENDSHIP SYSTEMS White paper, November 2014.
[4] Campana E.F., Peri D., Lucidi S., Pinto A., Liuzzi G. and Piccialli V., “New Global Optimization Methods for Ship Design Problems”, Optimization and Engineering (OPTE), Vol.10, 2009.
[5] Diez, M. and Peri, D., “Two-stage Stochastic Programming Formulation for Ship Design Optimisation under Uncertainty”, Ship Technology Research Schiffstechnik Vol. 57 / No.3 August 2010, pg. 172-181.

5. Game Strategies Combined with Evolutionary Computation - From Theory to Applications

ORGANISERS

J. Periaux (CIMNE/UPC, jperiaux@gmail.com)
D. Greiner (CEANI/IUSIANI, ULPGC, david.greiner@ulpgc.es)

ABSTRACT

The main objective of this Mini Symposium (MS) is to bring together researchers and technologists and to generate interest in delivering lectures on new approaches, in the field of game strategies used in evolutionary computation for solving societal and industrial optimization problems.

TOPICS

The communications will address:

  • Efficiency of game strategies coupled to Evolutionary Algorithms (EAs) like Pareto, Nash and Stackelberg games.
  • Theoretical contributions in EAs, Immune Systems, Neural Networks and PSO
  • Applications for solving single or multi-disciplinary design optimization problems in Applied Sciences and Engineering, namely Aeronautics, Structures, Biomedicine, Environmental problems among others.

REFERENCES

[1] J. Periaux, F. Gonzalez, D.S.C. Lee, "Evolutionary Optimization and Game Strategies for Advanced Multi-Disciplinary Design: Applications to Aeronautics", Intelligent Systems, Control and Automation: Science and Engineering, Vol. 75, Springer, 2015.
[2] D. Greiner, B. Galván, J. Periaux, N. Gauger, K. Giannakoglou, G. Winter, "Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences", Computational Methods in Applied Sciences, Vol. 36, Springer, 2015.

6. Optimization under Uncertainty

ORGANISERS

D. Quagliarella (Centro Italiano Ricerche Aerospaziali (CIRA), d.quagliarella@cira.it)
M. Vasile (University of Strathclyde, massimiliano.vasile@strath.ac.uk)

ABSTRACT

Real world design optimization problems often require that the solution meets stringent requirements of robustness and reliability, and the continued progress and advancement of computational capabilities of modern computer systems make it increasingly attractive the idea of introducing uncertainty quantification techniques directly into the optimization loop. On the other hand, the analysis and quantification of the uncertainty has made enormous progresses in recent years since the seminal work of Taguchi on the application of statistical methods to improve the quality of manufactured goods. This special session is conceived as forum of discussion between the research community and industry on the perspectives of the rapidly growing field of optimization under uncertainty. The present session will focus on both industrial applications and basic research to bring together practitioners in a field that is experiencing enormous broadening. Authors are encouraged to propose either success stories of application od optimization under uncertainty in industrial contexts or to present the latest developments of basic research in this exciting field.

Key words: Uncertainty quantification, Optimization under uncertainty, Robust design, Reliability based design methods

TOPICS

Authors are invited to submit papers on any topic related to optimization under uncertainty. More specifically, they may focus one or more of the following topics:

  • Industrial applications of optimization in presence of uncertainties
  • Large scale problems
  • Worst case scenario
  • Robust design
  • Reliability-based design
  • Multi and many object optimization under uncertainty
  • Evidence-based approaches and decision making
  • Evolvable optimization under uncertainty
  • Innovative/alternative approaches to optimization under uncertainty
  • Methods to speed-up computationally expensive problems

  

Contacts:

edmondo dot minisci at strath dot ac dot uk