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.

Hierarchical robust design optimisation of shock control bump devices for airfoil drag reduction

The paper investigates a detailed Active Shock Control Bump Design Optimisation on a Natural Laminar Flow (NLF) aerofoil; RAE 5243 to reduce cruise drag at transonic flow conditions using Evolutionary Algorithms (EAs) coupled to a robust design approach. For the uncertainty design parameters, the positions of boundary layer transition (xtr) and the coefficient of lift (Cl) are considered (250 stochastic samples in total). In this paper, two robust design methods are considered; the first approach uses a standard robust design method, which evaluates one design model at 250 stochastic conditions for uncertainty. The second approach is the combination of a standard robust design method and the concept of hierarchical (multi-population) sampling (250, 50, 15) for uncertainty. Numerical results show that the evolutionary optimization method coupled to uncertainty design techniques produces useful and reliable Pareto optimal SCB shapes which have low sensitivity and high aerodynamic performance while having significant total drag reduction. In addition,it also shows the benefit of using hierarchical robust method for detailed uncertainty design optimization.

Optimisation of Banana streak virus (BSV) diagnostic assays

Bananas are one of the world�fs most important crops, serving as a staple food and an important source of income for millions of people in the subtropics. Pests and diseases are a major constraint to banana production. To prevent the spread of pests and disease, farmers are encouraged to use disease�] and insect�]free planting material obtained by micropropagation. This option, however, does not always exclude viruses and concern remains on the quality of planting material. Therefore, there is a demand for effective and reliable virus indexing procedures for tissue culture (TC) material. Reliable diagnostic tests are currently available for all of the economically important viruses of bananas with the exception of Banana streak viruses (BSV, Caulimoviridae, Badnavirus). Development of a reliable diagnostic test for BSV is complicated by the significant serological and genetic variation reported for BSV isolates, and the presence of endogenous BSV (eBSV). Current PCR�] and serological�]based diagnostic methods for BSV may not detect all species of BSV, and PCR�]based methods may give false positives because of the presence of eBSV. Rolling circle amplification (RCA) has been reported as a technique to detect BSV which can also discriminate between episomal and endogenous BSV sequences. However, the method is too expensive for large scale screening of samples in developing countries, and little information is available regarding its sensitivity. Therefore the development of reliable PCR�]based assays is still considered the most appropriate option for large scale screening of banana plants for BSV. This MSc project aimed to refine and optimise the protocols for BSV detection, with a particular focus on developing reliable PCR�]based diagnostics Initially, the appropriateness and reliability of PCR and RCA as diagnostic tests for BSV detection were assessed by testing 45 field samples of banana collected from nine districts in the Eastern region of Uganda in February 2010. This research was also aimed at investigating the diversity of BSV in eastern Uganda, identifying the BSV species present and characterising any new BSV species. Out of the 45 samples tested, 38 and 40 samples were considered positive by PCR and RCA, respectively. Six different species of BSV, namely Banana streak IM virus (BSIMV), Banana streak MY virus (BSMYV), Banana streak OL virus (BSOLV), Banana streak UA virus (BSUAV), Banana streak UL virus (BSULV), Banana streak UM virus (BSUMV), were detected by PCR and confirmed by RCA and sequencing. No new species were detected, but this was the first report of BSMYV in Uganda. Although RCA was demonstrated to be suitable for broad�]range detection of BSV, it proved time�]consuming and laborious for identification in field samples. Due to the disadvantages associated with RCA, attempts were made to develop a reliable PCR�]based assay for the specific detection of episomal BSOLV, Banana streak GF virus (BSGFV), BSMYV and BSIMV. For BSOLV and BSGFV, the integrated sequences exist in rearranged, repeated and partially inverted portions at their site of integration. Therefore, for these two viruses, primers sets were designed by mapping previously published sequences of their endogenous counterparts onto published sequences of the episomal genomes. For BSOLV, two primer sets were designed while, for BSGFV, a single primer set was designed. The episomalspecificity of these primer sets was assessed by testing 106 plant samples collected during surveys in Kenya and Uganda, and 33 leaf samples from a wide range of banana cultivars maintained in TC at the Maroochy Research Station of the Department of Employment, Economic Development and Innovation (DEEDI), Queensland. All of these samples had previously been tested for episomal BSV by RCA and for both BSOLV and BSGFV by PCR using published primer sets. The outcome from these analyses was that the newly designed primer sets for BSOLV and BSGFV were able to distinguish between episomal BSV and eBSV in most cultivars with some B�]genome component. In some samples, however, amplification was observed using the putative episomal�]specific primer sets where episomal BSV was not identified using RCA. This may reflect a difference in the sensitivity of PCR compared to RCA, or possibly the presence of an eBSV sequence of different conformation. Since the sequences of the respective eBSV for BSMYV and BSIMV in the M. balbisiana genome are not available, a series of random primer combinations were tested in an attempt to find potential episomal�]specific primer sets for BSMYV and BSIMV. Of an initial 20 primer combinations screened for BSMYV detection on a small number of control samples, 11 primers sets appeared to be episomal�]specific. However, subsequent testing of two of these primer combinations on a larger number of control samples resulted in some inconsistent results which will require further investigation. Testing of the 25 primer combinations for episomal�]specific detection of BSIMV on a number of control samples showed that none were able to discriminate between episomal and endogenous BSIMV. The final component of this research project was the development of an infectious clone of a BSV endemic in Australia, namely BSMYV. This was considered important to enable the generation of large amounts of diseased plant material needed for further research. A terminally redundant fragment (.1.3 �~ BSMYV genome) was cloned and transformed into Agrobacterium tumefaciens strain AGL1, and used to inoculate 12 healthy banana plants of the cultivars Cavendish (Williams) by three different methods. At 12 weeks post�]inoculation, (i) four of the five banana plants inoculated by corm injection showed characteristic BSV symptoms while the remaining plant was wilting/dying, (ii) three of the five banana plants inoculated by needle�]pricking of the stem showed BSV symptoms, one plant was symptomless while the remaining had died and (iii) both banana plants inoculated by leaf infiltration were symptomless. When banana leaf samples were tested for BSMYV by PCR and RCA, BSMYV was confirmed in all banana plants showing symptoms including those were wilting and/or dying. The results from this research have provided several avenues for further research. By completely sequencing all variants of eBSOLV and eBSGFV and fully sequencing the eBSIMV and eBSMYV regions, episomal BSV�]specific primer sets for all eBSVs could potentially be designed that could avoid all integrants of that particular BSV species. Furthermore, the development of an infectious BSV clone will enable large numbers of BSVinfected plants to be generated for the further testing of the sensitivity of RCA compared to other more established assays such as PCR. The development of infectious clones also opens the possibility for virus induced gene silencing studies in banana.

Optimisation of bio-oil extraction process from Beauty Leaf (Calophyllum inophyllum) oil seed as a second generation biodiesel source

The Beauty Leaf tree (Calophyllum inophyllum) is a potential source of non-edible vegetable oil for producing future generation biodiesel because of its ability to grow in a wide range of climate conditions, easy cultivation, high fruit production rate, and the high oil content in the seed. This plant naturally occurs in the coastal areas of Queensland and the Northern Territory in Australia, and is also widespread in south-east Asia, India and Sri Lanka. Although Beauty Leaf is traditionally used as a source of timber and orientation plant, its potential as a source of second generation biodiesel is yet to be exploited. In this study, the extraction process from the Beauty Leaf oil seed has been optimised in terms of seed preparation, moisture content and oil extraction methods. The two methods that have been considered to extract oil from the seed kernel are mechanical oil extraction using an electric powered screw press, and chemical oil extraction using n-hexane as an oil solvent. The study found that seed preparation has a significant impact on oil yields, especially in the screw press extraction method. Kernels prepared to 15% moisture content provided the highest oil yields for both extraction methods. Mechanical extraction using the screw press can produce oil from correctly prepared product at a low cost, however overall this method is ineffective with relatively low oil yields. Chemical extraction was found to be a very effective method for oil extraction for its consistence performance and high oil yield, but cost of production was relatively higher due to the high cost of solvent. However, a solvent recycle system can be implemented to reduce the production cost of Beauty Leaf biodiesel. The findings of this study are expected to serve as the basis from which industrial scale biodiesel production from Beauty Leaf can be made.

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

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].

Effects of small field output factors on IMRT optimisation and dose calculation

Introduction Given the known challenges of obtaining accurate measurements of small radiation fields, and the increasing use of small field segments in IMRT beams, this study examined the possible effects of referencing inaccurate field output factors in the planning of IMRT treatments. Methods This study used the Brainlab iPlan treatment planning system to devise IMRT treatment plans for delivery using the Brainlab m3 microMLC (Brainlab, Feldkirchen, Germany). Four pairs of sample IMRT treatments were planned using volumes, beams and prescriptions that were based on a set of test plans described in AAPM TG 119’s recommendations for the commissioning of IMRT treatment planning systems [1]: • C1, a set of three 4 cm volumes with different prescription doses, was modified to reduce the size of the PTV to 2 cm across and to include an OAR dose constraint for one of the other volumes. • C2, a prostate treatment, was planned as described by the TG 119 report [1]. • C3, a head-and-neck treatment with a PTV larger than 10 cm across, was excluded from the study. • C4, an 8 cm long C-shaped PTV surrounding a cylindrical OAR, was planned as described in the TG 119 report [1] and then replanned with the length of the PTV reduced to 4 cm. Both plans in each pair used the same beam angles, collimator angles, dose reference points, prescriptions and constraints. However, one of each pair of plans had its beam modulation optimisation and dose calculation completed with reference to existing iPlan beam data and the other had its beam modulation optimisation and dose calculation completed with reference to revised beam data. The beam data revisions consisted of increasing the field output factor for a 0.6 9 0.6 cm2 field by 17 % and increasing the field output factor for a 1.2 9 1.2 cm2 field by 3 %. Results The use of different beam data resulted in different optimisation results with different microMLC apertures and segment weightings between the two plans for each treatment, which led to large differences (up to 30 % with an average of 5 %) between reference point doses in each pair of plans. These point dose differences are more indicative of the modulation of the plans than of any clinically relevant changes to the overall PTV or OAR doses. By contrast, the maximum, minimum and mean doses to the PTVs and OARs were smaller (less than 1 %, for all beams in three out of four pairs of treatment plans) but are more clinically important. Of the four test cases, only the shortened (4 cm) version of TG 119’s C4 plan showed substantial differences between the overall doses calculated in the volumes of interest using the different sets of beam data and thereby suggested that treatment doses could be affected by changes to small field output factors. An analysis of the complexity of this pair of plans, using Crowe et al.’s TADA code [2], indicated that iPlan’s optimiser had produced IMRT segments comprised of larger numbers of small microMLC leaf separations than in the other three test cases. Conclusion: The use of altered small field output factors can result in substantially altered doses when large numbers of small leaf apertures are used to modulate the beams, even when treating relatively large volumes.

Design methodologies and architectures of hardware-based evolutionary algorithms for aerospace optimisation applications on FPGAS

This thesis is a study of new design methods for allowing evolutionary algorithms to be more effectively utilised in aerospace optimisation applications where computation needs are high and computation platform space may be restrictive. It examines the applicability of special hardware computational platforms known as field programmable gate arrays and shows that with the right implementation methods they can offer significant benefits. This research is a step forward towards the advancement of efficient and highly automated aircraft systems for meeting compact physical constraints in aerospace platforms and providing effective performance speedups over traditional methods.

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.

Methods to improve the energy output of dye sensitized solar cell arrays

The work examined the operation and optimisation of dye-sensitised solar cell arrays, informing ways to improve performance through materials choices and geometrical design. Methods to improve the output of solar arrays under shading by external objects like trees or building were developed.

New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

Optimisation of in-cell accelerated solvent extraction technique for the determination of organochlorine pesticides in river sediments

Organochlorine pesticides (OCPs) are ubiquitous environmental contaminants with adverse impacts on aquatic biota, wildlife and human health even at low concentrations. However, conventional methods for their determination in river sediments are resource intensive. This paper presents an approach that is rapid and also reliable for the detection of OCPs. Accelerated Solvent Extraction (ASE) with in-cell silica gel clean-up followed by Triple Quadrupole Gas Chromatograph Mass Spectrometry (GCMS/MS) was used to recover OCPs from sediment samples. Variables such as temperature, solvent ratio, adsorbent mass and extraction cycle were evaluated and optimised for the extraction. With the exception of Aldrin, which was unaffected by any of the variables evaluated, the recovery of OCPs from sediment samples was largely influenced by solvent ratio and adsorbent mass and, to some extent, the number of cycles and temperature. The optimised conditions for OCPs extraction in sediment with good recoveries were determined to be 4 cycles, 4.5 g of silica gel, 105 ᴼC, and 4:3 v/v DCM: hexane mixture. With the exception of two compounds (α-BHC and Aldrin) whose recoveries were low (59.73 and 47.66 % respectively), the recovery of the other pesticides were in the range 85.35 – 117.97% with precision < 10 % RSD. The method developed significantly reduces sample preparation time, the amount of solvent used, matrix interference, and is highly sensitive and selective.

Optimisation techniques for planning automatic under frequency load shedding in New Zealand’s power system

Electricity generation is vital in developed countries to power the many mechanical and electrical devices that people require. Unfortunately electricity generation is costly. Though electricity can be generated it cannot be stored efficiently. Electricity generation is also difficult to manage because exact demand is unknown from one instant to the next. A number of services are required to manage fluctuations in electricity demand, and to protect the system when frequency falls too low. A current approach is called automatic under frequency load shedding (AUFLS). This article proposes new methods for optimising AUFLS in New Zealand’s power system. The core ideas were developed during the 2015 Maths and Industry Study Group (MISG) in Brisbane, Australia. The problem has been motivated by Transpower Limited, a company that manages New Zealand’s power system and transports bulk electricity from where it is generated to where it is needed. The approaches developed in this article can be used in electrical power systems anywhere in the world.