Part 1 MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 1.) Theoretical aspects

Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

Part 2. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 2.) Numerical aspects and implementation of model test cases

These lecture notes describe the use and implementation of a framework in which mathematical as well as engineering optimisation problems can be analysed. The foundations of the framework and algorithms described -Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) - lie upon traditional evolution strategies and incorporate the concepts of a multi-objective optimisation, hierarchical topology, asynchronous evaluation of candidate solutions , parallel computing and game strategies. In a step by step approach, the numerical implementation of EAs and HAPEAs for solving multi criteria optimisation problems is conducted providing the reader with the knowledge to reproduce these hand on training in his – her- academic or industrial environment.

Part 3. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 3.) Practical application to the design and optimisation of UAV systems

These lecture notes highlight some of the recent applications of multi-objective and multidisciplinary design optimisation in aeronautical design using the framework and methodology described in References 8, 23, 24 and in Part 1 and 2 of the notes. A summary of the methodology is described and the treatment of uncertainties in flight conditions parameters by the HAPEAs software and game strategies is introduced. Several test cases dealing with detailed design and computed with the software are presented and results discussed in section 4 of these notes.

Talk2Me : the art of augmenting conversations

This paper describes an interactive installation work set in a large dome space. The installation is an audio and physical re-rendition of an interactive writing work. In the original work, the user interacted via keyboard and screen while online. This rendition of the work retains the online interaction, but also places the interaction within a physical space, where the main 'conversation' takes place by the participant-audience speaking through microphones and listening through headphones. The work now also includes voice and SMS input, using speech-to-text and text-to-speech conversion technologies, and audio and displayed text for output. These additions allow the participant-audience to co-author the work while they participate in audible conversation with keyword-triggering characters (bots). Communication in the space can be person-to-computer via microphone, keyboard, and phone; person-to-person via machine and within the physical space; computer-to- computer; and computer-to-person via audio and projected text.

Energy efficiency in nanoscale synthesis using nanosecond plasmas

We report a nanoscale synthesis technique using nanosecond-duration plasma discharges. Voltage pulses 12.5 kV in amplitude and 40 ns in duration were applied repetitively at 30 kHz across molybdenum electrodes in open ambient air, generating a nanosecond spark discharge that synthesized well-defined MoO 3 nanoscale architectures (i.e. flakes, dots, walls, porous networks) upon polyamide and copper substrates. No nitrides were formed. The energy cost was as low as 75 eV per atom incorporated into a nanostructure, suggesting a dramatic reduction compared to other techniques using atmospheric pressure plasmas. These findings show that highly efficient synthesis at atmospheric pressure without catalysts or external substrate heating can be achieved in a simple fashion using nanosecond discharges.

Monoclinic β-MoO3 nanosheets produced by atmospheric microplasma : application to lithium-ion batteries

Porous high surface area thin films of nanosheet-shaped monoclinic MoO 3 were deposited onto platinized Si substrates using patch antenna-based atmospheric microplasma processing. The films were characterized by high resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM) and electrochemical analysis. The electrochemical analysis shows original redox peaks and high charge capacity, and also indicates a reversible electrochemical behaviour particularly beneficial for applications in Li-ion batteries. SEM shows that the films are highly porous and consist of nanosheets 50-100 nm thick with surface dimensions in the micrometre range. HRTEM reveals that the MoO3 nanosheets consist of the monoclinic beta phase of MoO3. These intricate nanoarchitectures made of monoclinic MoO3 nanosheets have not been studied previously in the context of applications in Li-ion batteries and show superior structural and morphological features that enable effective insertion of Li ions.

A multi-criteria approach for hospital capacity analysis

Hospitals are critical elements of health care systems and analysing their capacity to do work is a very important topic. To perform a system wide analysis of public hospital resources and capacity, a multi-objective optimization (MOO) approach has been proposed. This approach identifies the theoretical capacity of the entire hospital and facilitates a sensitivity analysis, for example of the patient case mix. It is necessary because the competition for hospital resources, for example between different entities, is highly influential on what work can be done. The MOO approach has been extensively tested on a real life case study and significant worth is shown. In this MOO approach, the epsilon constraint method has been utilized. However, for solving real life applications, with a large number of competing objectives, it was necessary to devise new and improved algorithms. In addition, to identify the best solution, a separable programming approach was developed. Multiple optimal solutions are also obtained via the iterative refinement and re-solution of the model.