The usual design approaches employed in industry are based on experimental trial-and-error procedures. As a consequence, the design process demands a large amount of resources (time, material and equipment), and heavily relies on the experience of the human resources involved. This framework has a considerable impact on the cost and time-to-market of new products. With the purpose of increasing the production efficiency, the use of numerical codes/optimization methodologies increased significantly over the last decades, which was additionally motivated by the development of better and faster computers that allow resorting to more realistic models. Nowadays, several free and open-source numerical modelling codes are available, which, due to the absence of licences, have been motivating companies to invest in acquiring the required knowledge to use them. This symposium aims to hear, from the users/developers of free and open-source computational modelling tools, the gains which are being obtained on the design process, when using these computational tools, covering not only results obtained on specific applications but also recent developments, which are expected to have a positive impact on computational modelling related activities.

In addition to design, best efficiency with minimum costs is a vital goal of an engineer. While computing engineering problems, selecting several design variables are depended to the decision of engineers. By using optimization techniques, it is possible to find best suitable design variables. Also, optimization techniques can be used for solving uncertain and nonlinear problems. In structural and earthquake engineering, uncertainties and nonlinearities are a great problem for researchers. Especially, structural control applications must be optimally tuned for efficiency on reduction of structural vibrations.

New optimization approaches and applications of existing methods on engineering problems are developing subjects. The aim of this mini-symposium is to bring academicians working on structural and earthquake engineering together in order to present and discuss their researches. The scope of the mini-symposium includes mathematical optimization techniques, metaheuristic algorithms and search techniques. In addition to that, structural and earthquake engineering studies propose efficient design approaches according to numerical analyses and experiments may be also presented in the mini-symposium.    

This Minisymposium wants to promote scientific discussions about Game Theory topics that are used or potentially useful for solving societal and industrial optimization problems. Game Theory studies studies strategic interactions between two or more participants (players). Multi-person decision scenarios, where each player chooses actions which guarantee the best possible rewards for self and anticipating the rational actions from other players, are studied in non-cooperative games, and describe several situations of interest: network flow optimization (congestion control), cyber security issues, facility location models etc.

The contributions will deal with (not limited to) solution concepts as Nash equilibrium or Stackelberg solution, properties as existence, efficiency, stability and computational approaches as GAs, EAs, metaheuristics, as well as their use for solving applicative problems in Engineering, Economics, Aeronautics, Computer Science, Physics, among the others.

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

• non-cooperative games
• evolutionary games
• min-max problems
• multilevel optimization
• efficiency and Pareto optimality
• dynamics and stability
• cooperative solutions
• cybersecurity
• networks
• facility location

Key words: Multidisciplinary Optimization, adjoint method, Computational Fluid Dynamics

The proposed symposium is dedicated to the development, validation and applications of multidisciplinary adjoint-based optimization methods. Until today, adjoint-based methods were mainly used in industry for pure aerodynamic design. In order to meet in a near future, the industrial objectives in terms of competitiveness and environmental impact, multi-disciplinary aspects and couplings will become key design drivers, among other, for aircraft and engine manufacturers.

The aim of this symposium is to present the progresses made on multi-disciplinary adjoint based optimization ranging from academic developments up to industrial and complex applications. In this symposium, several partners of the European MADELEINE project [1] will present their most relevant results after three years of work but the objective is also to have other contributions from European or international universities, research centres, SMEs and industrial companies among the ‘adjoint community’ .

Due to the multi-disciplinary nature of the subject, contributions from sectors other than aeronautics are also expected (car, and energy industries for instance).

REFERENCES

1) https://www.madeleine-project.eu/

Keywords

                  - Uncertainty quantification
                  - Optimization under uncertainty
                  - Robust design
                  - Reliability-based design methods.

Robust or reliability-based optimization is acquiring an increasingly important role in the engineering and industrial fields since it allows us to tackle problems that would otherwise be out of the reach of classical optimization techniques. Real-world design optimization problems often require that the solution meets stringent requirements of robustness and reliability when a significant deviation from the nominal project conditions is present in the actual operating conditions. In these cases, it is necessary to characterize the uncertainty and take it into account in the optimization process. Of different nature and equally important is the uncertainty introduced in the optimization process by the intrinsic uncertainties of the numerical prediction models employed. The continued progress and advancement of the computational capabilities of modern computer systems make increasingly attractive the idea of introducing uncertainty quantification techniques directly into the optimization loop.

This mini-symposium aims to host research contributions, both theoretical and applicative, in the field of robust optimization or reliability-based both in the presence of stochastic and epistemic sources of uncertainty. It aims to be a forum of discussion between the research community and industry on the perspectives of the rapidly growing field of optimization under uncertainty. The 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 of optimization under uncertainty in industrial contexts or to present the latest developments of basic research in this exciting field.

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 the 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​

Soft computing methods are problem-solving strategies that are used to find approximate solutions to complex problems. Biologically-Inspired methods such as Artificial Neural Networks (ANN), Evolutionary Algorithms (EA), and Fuzzy Logic are a few examples of soft computing methods, which are also collectively referred to as Computational Intelligence. These methods are inspired by the strategies that nature uses to solve problems. Most frequently, they are employed to substitute or enhance complex and computationally intensive mathematical models that have proved intractable for conventional analysis based on hard-computing strategies.

In recent years, an increasing role of soft computing in different engineering fields has been observed, leading to many exciting and innovative applications. This Minisymposium aims to bring together scientists and engineers working in different areas of soft computing, covering all of its aspects, with focus in civil and structural engineering. The topics of the Minisymposium include but are not limited to:

• Genetic Programming
• Evolutionary Computation
• Evolutionary Algorithms
• Artificial Intelligence
• Neural Networks
• Machine Learning
• Perceptrons
• Fuzzy Set Theory
• Fuzzy Systems
• Fuzzy Optimization
• Swarm Intelligence
• Chaos Theory and Chaotic Systems

Objectives

The objectives of a neutral climate aviation (a very ambitious target in the next EC FP9 Horizon Europe program) can only be achieved through close cooperation between the network of industry and science .

Global aviation is responsible for about 2.5% of man-made CO2 emissions and further contributes to global warming through its non- CO2 effects. The central challenge of emission-free aviation is therefore to minimise the consequences for people and the environment.

Increasing digitalized methods in Multidisciplinary/ Multiphysics optimization and control in Aviation targeting emissions reduction for innovation in advanced aircraft configurations and environmentally efficient aero engines are the main design tools used in this MS. Among them, adjunct based optimization, evolutionary optimization , data driven computing, AI tools including Machine Learning, Deep Learning and Bid data analysis , intelligent systems , Active devices or Morphing Technologies ,….

Multidisciplinary integrated 2-D and 3-D configurations including Airframe, Airframe and Engine interactions and Propulsion will be computed and their performances ,quality and usability evaluated with the above innovative methods by technologists and scientists in the fields of Aeronautics, Computational and Computer sciences disciplines.