An application of bi-directional evolutionary structural optimisation for optimising energy absorbing structures using a material damage model

The Bi-directional Evolutionary Structural Optimisation (BESO) method is a numerical topology optimisation method developed for use in finite element analysis. This paper presents a particular application of the BESO method to optimise the energy absorbing capability of metallic structures. The optimisation objective is to evolve a structural geometry of minimum mass while ensuring that the kinetic energy of an impacting projectile is reduced to a level which prevents perforation. Individual elements in a finite element mesh are deleted when a prescribed damage criterion is exceeded. An energy absorbing structure subjected to projectile impact will fail once the level of damage results in a critical perforation size. It is therefore necessary to constrain an optimisation algorithm from producing such candidate solutions. An algorithm to detect perforation was implemented within a BESO framework which incorporated a ductile material damage model.

Characterisation of pavement profile heights using accelerometer readings and a combinatorial optimisation technique

Pavement surface profiles induce dynamic ride responses in vehicles which can potentially be used to classify road surface roughness. A novel method is proposed for the characterisation of pavement roughness through an analysis of vehicle accelerations. A combinatorial optimisation technique is applied to the determination of pavement profile heights based on measured accelerations at and above the vehicle axle. Such an approach, using low-cost inertial sensors, would provide an inexpensive alternative to the costly laser-based profile measurement vehicles. The concept is numerically validated using a half-car roll dynamic model to infer measurements of road profiles in both the left and right wheel paths.

Optimisation of Environment-friendly SCFRC mixes use in precast Concrete Industry

The concept of green concrete has been progressively introduced in concrete technology. At the same time, new generations of superplasticisers have become widely available and self-compacting concrete is being increasingly implemented. The aim of this research is to study the impact that different sustainable materials have on both fresh and hardened properties of Self-Compacting Fibre Reinforced Concrete (SCFRC) in order to implement their use in a precast concrete company. Different combinations of cement, mineral additions (active and inert), polypropylene fibres, superplasticisers, and aggregates have been considered. Fresh state performance has been assessed by means of: slump flow test, V-funnel, and J-ring. Concrete compressive strength values at different ages have been retained as representative of the material's performance in its hardened state. All these properties have been correlated with SCFRC proportioning parameters. The importance of interactions between mineral additions and between these and superplasticiser is emphasised, as well as the different consequences of using powders as cement replacement or as mineral additions.

Optimisation of Environment-friendly SCFRC mixes use in precast Concrete Industry (PDF Download Available). Available from: http://www.researchgate.net/publication/263304799_Optimisation_of_Environment-friendly_SCFRC_mixes_use_in_precast_Concrete_Industry [accessed Jun 5, 2015].

Taguchi optimisation approach for production of activated carbon from phosphoric acid impregnated palm kernel shell by microwave heating

Taguchi method was applied to investigate the optimal operating conditions in the preparation of activated carbon using palm kernel shell with quadruple control factors: irradiation time, microwave power, concentration of phosphoric acid as impregnation substance and impregnation ratio between acid and palm kernel shell. The best combination of the control factors as obtained by applying Taguchi method was microwave power of 800 W, irradiation time of 17 min, impregnation ratio of 2, and acid concentration of 85%. The noise factor (particle size of raw material) was considered in a separate outer array, which had no effect on the quality of the activated carbon as confirmed by t-test. Activated carbon prepared at optimum combination of control factors had high BET surface area of 1,473.55 m² g-1 and high porosity. The adsorption equilibrium and kinetic data can satisfactorily be described by the Langmuir isotherm and a pseudo-second-order kinetic model, respectively. The maximum adsorbing capacity suggested by the Langmuir model was 1000 mg g-1.

Aerofoil Optimisation Using CST Parameterisation in SU2

This paper describes an implementation of the popular method of Class-Shape Transformation for aerofoil design within SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities from the new parameterisation is introduced, enabling the calculation of gradients with respect to new design variables. To assess the accuracy and efficiency of the alternative approach, two transonic optimisation problems are investigated: an inviscid problem with multiple constraints and a viscous problems without any constraints. Results show the new parameterisation obtaining reliable optimums, with similar levels of
performance of the software native parameterisations.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Optimisation of a two-liquid component pre-filled acrylic bone cement system: A design of experiments approach to optimise cement final properties

The initial composition of acrylic bone cement along with the mixing and delivery technique used can influence its final properties and therefore its clinical success in vivo. The polymerisation of acrylic bone cement is complex with a number of processes happening simultaneously. Acrylic bone cement mixing and delivery systems have undergone several design changes in their advancement, although the cement constituents themselves have remained unchanged since they were first used. This study was conducted to determine the factors that had the greatest effect on the final properties of acrylic bone cement using a pre-filled bone cement mixing and delivery system. A design of experiments (DoE) approach was used to determine the impact of the factors associated with this mixing and delivery method on the final properties of the cement produced. The DoE illustrated that all factors present within this study had a significant impact on the final properties of the cement. An optimum cement composition was hypothesised and tested. This optimum recipe produced cement with final mechanical and thermal properties within the clinical guidelines and stated by ISO 5833 (International Standard Organisation (ISO), International standard 5833: implants for surgery—acrylic resin cements, 2002), however the low setting times observed would not be clinically viable and could result in complications during the surgical technique. As a result further development would be required to improve the setting time of the cement in order for it to be deemed suitable for use in total joint replacement surgery.

Tailoring the nonlinear frequency coupling between odd harmonics for the optimisation of charged particle dynamics in capacitively coupled oxygen plasmas

The influence of nonlinear frequency coupling in an oxygen plasma excited by two odd harmonics at moderate pressure is investigated using a numerical model. Through variations in the voltage ratio and phase shift between the frequency components changes in ionization dynamics and sheath voltages are demonstrated. Furthermore, a regime in which the voltage drop across the plasma sheath is minimised is identified. This regime provides a significantly higher ion flux than a single frequency discharge driven by the lower of the two frequencies alone. These operating parameters have potential to be exploited for plasma processes requiring low ion bombardment energies but high ion fluxes. 

Constrained Multi-Objective Aerofoil Design Using a Multi-Level Optimisation Strategy

A novel approach for the multi-objective design optimisation of aerofoil profiles is presented. The proposed method aims to exploit the relative strengths of global and local optimisation algorithms, whilst using surrogate models to limit the number of computationally expensive CFD simulations required. The local search stage utilises a re-parameterisation scheme that increases the flexibility of the geometry description by iteratively increasing the number of design variables, enabling superior designs to be generated with minimal user intervention. Capability of the algorithm is demonstrated via the conceptual design of aerofoil sections for use on a lightweight laminar flow business jet. The design case is formulated to account for take-off performance while reducing sensitivity to leading edge contamination. The algorithm successfully manipulates boundary layer transition location to provide a potential set of aerofoils that represent the trade-offs between drag at cruise and climb conditions in the presence of a challenging constraint set. Variations in the underlying flow physics between Pareto-optimal aerofoils are examined to aid understanding of the mechanisms that drive the trade-offs in objective functions.

Facilities management: Tracing its development trajectory

Purpose – The purpose of this paper is to provide facilities management (FM) practitioners and researchers with a better understanding of the FM industry sector by analyzing the trend of its development.
Design/methodology/approach – Semi-structured interview is adopted in this research as the main methodology. In total, 30 FM professionals in the UK were interviewed to explore the past, present and future of FM. The analysis of interview results helps to identify the key areas in which FM has changed, is changing and will change. It also helps to explain the implications of FM development in each key area.
Findings – FM evolves and matures continuously. It is important for FM organizations and practitioners to recognize the dynamic nature of this industry sector, based on which they can develop appropriate strategies to adapt to changing circumstances. This is probably the only way for them to
keep pace with the times.
Originality/value – Both backward looking and forward looking are crucial to the development of an industry sector. However, existing studies on FM development are conducted through either review or outlook. On the other hand, most of these studies focus on one particular management area or one particular industry sector. Based on 30 expert interviews, this research attempts to bridge the knowledge gap and analyze the trend of FM development in a systematic way. A better understanding of the trend provides a possibility and a guide for FM organizations and practitioners to pursue best practice.