Coupling hybrid-game strategies with particle swarm optimisation for multi-objective high lift systems design optimisation

This paper investigates the High Lift System (HLS) application of complex aerodynamic design problem using Particle Swarm Optimisation (PSO) coupled to Game strategies. Two types of optimization methods are used; the first method is a standard PSO based on Pareto dominance and the second method hybridises PSO with a well-known Nash Game strategies named Hybrid-PSO. These optimization techniques are coupled to a pre/post processor GiD providing unstructured meshes during the optimisation procedure and a transonic analysis software PUMI. The computational efficiency and quality design obtained by PSO and Hybrid-PSO are compared. The numerical results for the multi-objective HLS design optimisation clearly shows the benefits of hybridising a PSO with the Nash game and makes promising the above methodology for solving other more complex multi-physics optimisation problems in Aeronautics.

Advanced Computational Intelligence System for inverse aeronautical design optimisation

Abstract—Computational Intelligence Systems (CIS) is one of advanced softwares. CIS has been important position for solving single-objective / reverse / inverse and multi-objective design problems in engineering. The paper hybridise a CIS for optimisation with the concept of Nash-Equilibrium as an optimisation pre-conditioner to accelerate the optimisation process. The hybridised CIS (Hybrid Intelligence System) coupled to the Finite Element Analysis (FEA) tool and one type of Computer Aided Design(CAD) system; GiD is applied to solve an inverse engineering design problem; reconstruction of High Lift Systems (HLS). Numerical results obtained by the hybridised CIS are compared to the results obtained by the original CIS. The benefits of using the concept of Nash-Equilibrium are clearly demonstrated in terms of solution accuracy and optimisation efficiency.

Efficient hybrid-game strategies coupled to evolutionary algorithms for robust multidisciplinary design optimization in aerospace engineering

A number of game strategies have been developed in past decades and used in the fields of economics, engineering, computer science, and biology due to their efficiency in solving design optimization problems. In addition, research in multiobjective and multidisciplinary design optimization has focused on developing a robust and efficient optimization method so it can produce a set of high quality solutions with less computational time. In this paper, two optimization techniques are considered; the first optimization method uses multifidelity hierarchical Pareto-optimality. The second optimization method uses the combination of game strategies Nash-equilibrium and Pareto-optimality. This paper shows how game strategies can be coupled to multiobjective evolutionary algorithms and robust design techniques to produce a set of high quality solutions. Numerical results obtained from both optimization methods are compared in terms of computational expense and model quality. The benefits of using Hybrid and non-Hybrid-Game strategies are demonstrated.

Robust multidisciplinary UAS design optimisation

There are many applications in aeronautical/aerospace engineering where some values of the design parameters states cannot be provided or determined accurately. These values can be related to the geometry(wingspan, length, angles) and or to operational flight conditions that vary due to the presence of uncertainty parameters (Mach, angle of attack, air density and temperature, etc.). These uncertainty design parameters cannot be ignored in engineering design and must be taken into the optimisation task to produce more realistic and reliable solutions. In this paper, a robust/uncertainty design method with statistical constraints is introduced to produce a set of reliable solutions which have high performance and low sensitivity. Robust design concept coupled with Multi Objective Evolutionary Algorithms (MOEAs) is defined by applying two statistical sampling formulas; mean and variance/standard deviation associated with the optimisation fitness/objective functions. The methodology is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing and asynchronous evaluation. It is implemented for two practical Unmanned Aerial System (UAS) design problems; the flrst case considers robust multi-objective (single disciplinary: aerodynamics) design optimisation and the second considers a robust multidisciplinary (aero structures) design optimisation. Numerical results show that the solutions obtained by the robust design method with statistical constraints have a more reliable performance and sensitivity in both aerodynamics and structures when compared to the baseline design.

Adaptive wing/aerofoil design optimisation using MOEA coupled to uncertainty design method

The use of adaptive wing/aerofoil designs is being considered as promising techniques in aeronautic/aerospace since they can reduce aircraft emissions, improve aerodynamic performance of manned or unmanned aircraft. The paper investigates the robust design and optimisation for one type of adaptive techniques; Active Flow Control (AFC) bump at transonic flow conditions on a Natural Laminar Flow (NLF) aerofoil designed to increase aerodynamic efficiency (especially high lift to drag ratio). The concept of using Shock Control Bump (SCB) is to control supersonic flow on the suction/pressure side of NLF aerofoil: RAE 5243 that leads to delaying shock occurrence or weakening its strength. Such AFC technique reduces total drag at transonic speeds due to reduction of wave drag. The location of Boundary Layer Transition (BLT) can influence the position the supersonic shock occurrence. The BLT position is an uncertainty in aerodynamic design due to the many factors, such as surface contamination or surface erosion. The paper studies the SCB shape design optimisation using robust Evolutionary Algorithms (EAs) with uncertainty in BLT positions. The optimisation method is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing and asynchronous evaluation. Two test cases are conducted; the first test assumes the BLT is at 45% of chord from the leading edge and the second test considers robust design optimisation for SCB at the variability of BLT positions and lift coefficient. Numerical result shows that the optimisation method coupled to uncertainty design techniques produces Pareto optimal SCB shapes which have low sensitivity and high aerodynamic performance while having significant total drag reduction.

A sequential Monte Carlo approach to design for population pharmacokinetics studies

Here we present a sequential Monte Carlo approach that can be used to find optimal designs. Our focus is on the design of phase III clinical trials where the derivation of sampling windows is required, along with the optimal sampling schedule. The search is conducted via a particle filter which traverses a sequence of target distributions artificially constructed via an annealed utility. The algorithm derives a catalogue of highly efficient designs which, not only contain the optimal, but can also be used to derive sampling windows. We demonstrate our approach by designing a hypothetical phase III clinical trial.

A review of optimization techniques used in the design of fibre composite structures for civil engineering applications

Fibre composite structures have become the most attractive candidate for civil engineering applications. Fibre reinforced plastic polymer (FRP) composite materials have been used in the rehabilitation and replacement of the old degrading traditional structures or build new structures. However, the lack of design standards for civil infrastructure limits their structural applications. The majority of the existing applications have been designed based on the research and guidelines provided by the fibre composite manufacturers or based on the designer’s experience. It has been a tendency that the final structure is generally over-designed. This paper provides a review on the available studies related to the design optimization of fibre composite structures used in civil engineering such as; plate, beam, box beam, sandwich panel, bridge girder, and bridge deck. Various optimization methods are presented and compared. In addition, the importance of using the appropriate optimization technique is discussed. An improved methodology, which considering experimental testing, numerical modelling, and design constrains, is proposed in the paper for design optimization of composite structures.

Shear in reinforced and unreinforced masonry : response, design and construction

This paper describes the vulnerability of masonry under shear; first the mechanisms of in-plane and out-of-plane shear performance of masonry are reviewed; both the unreinforced and lightly reinforced masonry wall systems are considered. Factors affecting the response of unreinforced and reinforced masonry to shear are described and the effect of the variability of those factors to the failure mode of masonry shear walls is also discussed. Some critique is provided on the existing design provisions in various masonry standards.

Water sensitive urban design through the lens of urban metabolism

Stormwater pollution has been recognised as one of the main causes of aquatic ecosystem degradation and poses a significant threat to both the goal of ecological sustainable development as well as human health and wellbeing. In response, water sensitive urban design (WSUD) practices have been put forward as a strategy to mitigate the detrimental impacts of urban stormwater runoff quality and to safeguard ecosystem functions. However, despite studies that support its efficiency in urban stormwater management, the mainstreaming of WSUD remains a significant challenge. This paper proposes that viewing WSUD through the lens of the integrated urban metabolism framework which encourages an interdisciplinary approach and facilitates dialogue through knowledge transfer is a strategy in which the implementation of WSUD can be mainstreamed.

Improving service innovation through structured process-oriented knowledge infrastructure design

Formalised service innovation is a central tenet of enterprise systems lifecycle phases. Event driven process models extended with knowledge objects are found to be not useful in early lifecycle phases. When an upgrade is required, a map of the knowledge infrastructure is needed to better design further service innovation because functional maps no longer adequately describe the context adequately. By looking at formal changes to business processes as service innovations, and recognising the knowledge infrastructure inherent in services generally, changes driven through technology such as ES can be better understood with the application of frameworks such as B-KIDE.

Dichotomy in the design studio : adapting to new blended learning environments

In a study aimed at better understanding how staff and students adapt to new blended studio learning environments (BSLE’s), a group of 165 second year architecture students at a large school of architecture in Australia were separated into two different design studio learning environments. 70% of students were allocated to a traditional studio design learning environment (TSLE) and 30% to a new, high technology embedded, prototype digital learning laboratory. The digital learning laboratory was purpose designed for the case-study users, adapted Student-Centred Active Learning Environment for Undergraduate Programs (SCALE-UP) principles, and built as part of a larger university research project. The architecture students attended the same lectures, followed the same studio curriculum and completed the same pieces of assessment; the only major differences were the teaching staff and physical environment within which the studios were conducted. At the end of the semester, the staff and students were asked to complete a questionnaire about their experiences and preferences within the two respective learning environments. Following this, participants were invited to participate in focus groups, where a synergistic approach was effected. Using a dual method qualitative approach, the questionnaire and survey data were coded and extrapolated using both thematic analysis and grounded theory methodology. The results from these two different approaches were compared, contrasted and finally merged, to reveal six distinct emerging themes, which were instrumental in offering resistance or influencing adaptation to, the new BLSE. This paper reports on the study, discusses the major contributors to negative resistance and proposes points for consideration, when transitioning from a TSLE to a BLSE.

The subtropical residential tower: An investigation by Design Charrette

QUT's Centre for Subtropical Design (CSD) partnered with a major developer to bring together some of Brisbane’s most experienced and creative architects and designers in a two-day intensive design charrette to propose innovative design strategies for naturally-ventilated high rise residential buildings. An inner-urban renewal site in Queensland’s capital city Brisbane gave four multi-disciplinary teams the opportunity to address a raft of issues that developers and consultants will confront more and more in the future in warm humid climates. The quest to release apartment dwellers from dependence on energy-hungry air-conditioning and artificial lighting was central to the design brief for the towers. Mentored by Richard Hassell of WOHA, the creative teams focussed on climate-responsive design principles for passive climate control including orientation, cross-ventilation and outdoor living in order to reduce greenhouse gas emissions and offset occupants’ rising energy costs. This article discusses how outcomes of the charrette take their cue from the city’s subtropical climate and demonstrate how high-density high-rise living can be attractive, affordable and sustainable through positive engagement with the subtropical climate’s natural attributes.

How design of the physical environment impacts early learning : educators and parents perspectives

This research explores the quality and importance of the physical environment of two early learning centres on the Sunshine Coast in Queensland, utilising qualitative interviews with parents (n=4) and educators (n=4) to understand how design might impact on children’s development and a quantitative rating (the Early Childhood Physical Environment Rating Scale; ECPERS) to assess the quality of the physical built environment and infrastructure. With an average ECPERS quality rating, thematic analysis of the interviews revealed that educators and parents viewed the physical environment as important to a child’s development, although the quality of staff was predominant. Early learning centres should be ‘homely’, inviting, bright and linked to the outdoors, with participants describing how space “welcomes the child, makes them feel safe and encourages learning”. Four key themes characterised views: Emotional Connection (quality of staff and physical environment), Experiencing Design (impact of design on child development), Hub for Community Integration (relationships and resources) and Future Vision (ideal physical environment, technology and ratings). With participants often struggling to clearly articulate their thoughts on design issues, a collaborative and jargon-free approach to designing space is required. These findings will help facilitate discussion about the role and design of the physical environment in early childhood centres, with the tangible examples of ‘ideal space’ enhancing communication between architects and educators about how best to design and reconfigure space to enhance learning outcomes.

Implementable efficient time and energy consumption trajectories design for an autonomous underwater vehicle

In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.