Global Trajectory Optimisation : Can We Prune the Solution Space When Considering Deep Space Manoeuvres? [Final Report]

This document contains a report on the work done under the ESA/Ariadna study 06/4101 on the global optimization of space trajectories with multiple gravity assist (GA) and deep space manoeuvres (DSM). The study was performed by a joint team of scientists from the University of Reading and the University of Glasgow

Aerodynamic optimisation of a hypersonic reentry vehicle based on solution of the Boltzmann–BGK equation and evolutionary optimisation

Over the past decade there has been a surge in the interest, both academic and commercial, in supersonic and hypersonic passenger transport. This paper outlines an original approach for solving the problem of optimal design and configuration of a space vehicle operating in rarefied hypersonic flow. The approach utilises a novel flow solver based on the solution of the Boltzmann–BGK equation. For the first time this solver has been coupled to an evolutionary optimiser to assist in navigation of the unfamiliar hypersonic design space.The Boltzmann–BGK solver is rigorously tested on a number of examples and is shown to handle rarefied gas dynamics examples across a range of length scales. The examples, presented here for the first time, include: a Riemann–type gas expansion problem, drag prediction of a nano–particle and supersonic flow across an aerofoil. Finally the solver is coupled to the evolutionary optimiser Modified Cuckoo Search approach. The coupled solver–optimiser design tool is then used to explore the optimum configuration of the forebody of a generic space reentry vehicle under a range of design conditions.In all examples considered the flow solver produces valid solutions. It is also found that the evolutionary optimiser is successful in navigating the unfamiliar design space

A Study of Integrated UWB Antennas Optimised for Time Domain Performance

Antennas for impulse radio ultra-wideband based portable devices are required to be compact and able to transmit or receive waveforms with minimal distortion in order to support proximity ranging with a centimetre-scale precision. The first part of thesis characterises several pulse types for use in the generation of picosecond-scale signals in respect to the regulatory power and frequency standards while the principles of antenna transient transmission and reception are stated. The proximity effect of planar conductors on the performance of an ultra-wideband antenna is investigated in both spectral and temporal domain demonstrating the relationship between the antenna-reflector separation and the antenna performance. Balanced and unbalanced antennas are also investigated for integration into asset-tracking tag applications and are designed to operate in close proximity to PCB boards while meeting realistic dimensional constraints and acceptable time domain performances. Monopole antenna designs are reported with performances optimized for minimum pulse dispersion. Minimization of pulse dispersion effects in the antenna designs is achieved using pulses with optimal spectral fit to the UWB emission mask. The generation of these waveforms are reported for the first time. An antenna de-embedding method is reported enabling validation of the simulated fidelity factor of radiated patterns. Novel differentially-fed planar dipole and slot antennas are reported for direct IC output integration. Design objectives and optimisation are focused on bandwidth enhancement and pulse dispersion minimisation. Finally, time- and frequency-domain measurements are carried out using an approach based on the superposition principle

Interactive optimisation for high-lift design.

Interactivity always involves two entities; one of them by default is a human user. The specialised subject of human factors is introduced in the context of computational aerodynamics and optimisation, specifically a high-lift aerofoil. The trial and error nature of a design process hinges on designer’s knowledge, skill and intuition. A basic, important assumption of a man-machine system is that in solving a problem, there are some steps in which the computer has an advantageous edge while in other steps a human has dominance. Computational technologies are now an indispensable part of aerospace technology; algorithms involving significant user interaction, either during the process of generating solutions or as a component of post-optimisation evaluation where human decision making is involved are increasingly becoming popular, multi-objective particle swarm is one such optimiser. Several design optimisation problems in engineering are by nature multi-objective; the interest of a designer lies in simultaneous optimisation against two or more objectives which are usually in conflict. Interactive optimisation allows the designer to understand trade-offs between various objectives, and is generally used as a tool for decision making. The solution to a multi-objective problem, one where betterment in one objective occurs over the deterioration of at least one other objective is called a Pareto set. There are multiple solutions to a problem and multiple betterment ideas to an already existing design. The final responsibility of identifying an optimal solution or idea rests on the design engineers and decision making is done based on quantitative metrics, displayed as numbers or graphs. However, visualisation, ergonomics and human factors influence and impact this decision making process. A visual, graphical depiction of the Pareto front is oftentimes used as a design aid tool for purposes of decision making with chances of errors and fallacies fundamentally existing in engineering design. An effective visualisation tool benefits complex engineering analyses by providing the decision-maker with a good imagery of the most important information. Two high-lift aerofoil data-sets have been used as test-case examples; a multi-element solver, an optimiser based on swarm intelligence technique, and visual techniques which include parallel co-ordinates, heat map, scatter plot, self-organising map and radial coordinate visualisation comprise the module. Factors that affect optima and various evaluation criteria have been studied in light of the human user. This research enquires into interactive optimisation by adapting three interactive approaches: information trade-off, reference point and classification, and investigates selected visualisation techniques which act as chief aids in the context of high-lift design trade studies. Human-in-the-loop engineering, man-machine interaction & interface along with influencing factors, reliability, validation and verification in the presence of design uncertainty are considered. The research structure, choice of optimiser and visual aids adapted in this work are influenced by and streamlined to fit with the parallel on-going development work on Airbus’ Python based tool. Results, analysis, together with literature survey are presented in this report. The words human, user, engineer, aerodynamicist, designer, analyst and decision-maker/ DM are synonymous, and are used interchangeably in this research. In a virtual engineering setting, for an efficient interactive optimisation task, a suitable visualisation tool is a crucial prerequisite. Various optimisation design tools & methods are most useful when combined with a human engineer's insight is the underlying premise of this work; questions such as why, what, how might help aid aeronautical technical innovation.PhD in Aerospac

Performance optimisation of small antenna arrays

This thesis addresses radiation pattern synthesis problems for small linear periodic phased arrays (with array elements less then 10). Due to the small array size conventional pattern synthesis techniques fail to produce the required results. In the case of practical small arrays, mutual coupling and element pattern asymmetric effect degrade the array radiation performance. The main performance metrics considered in this thesis include side lobe level (SLL), gain, halfpower beamwidth (HPBW) and mainbeam scan direction. The conventional pattern synthesis approaches result in sub optimal gain, SLL and HPBW due to the limited number of elements and the mutual coupling involved. In case of difference pattern synthesis these factors resulted in lower difference pattern slope, degraded SLL and difference peak asymmetry. The sum and difference patterns are used in monopulse arrays and a simplified feed that could produce both patterns with acceptable radiation properties is of interest and has been examined (chapter 5). A conventional technique is applied to small arrays to synthesise a sector beam and there is limited control over the radiation pattern. It is shown that the mutual coupling has significant effect on the array radiation pattern and mitigation is necessary for optimum performance (chapter 6). Furthermore, wideband phased arrays may have a natural limitation of the HPBW in low gain applications and minimisation of the variation becomes important. Also the SLL variations for wideband antenna arrays in the presence of mutual coupling considerably degrade the radiation pattern. The mutual coupling degrades significantly the radiation pattern performance in case of small scanning wideband arrays (chapter 7). It is the primary goal of this thesis to develop an optimisation scheme thatis applied in the above scenarios (chapters 3 & 4). The only degree of freedom assumed is the array excitation. Optimised amplitude and phase for each element in the array are determined by the proposed scheme, concurrently. The deterministic optimisation techniques reported in the literature for the pattern synthesis may involve complicated problem modelling. The heuristic opti-misation techniques generally are computationally expensive. The proposedIntelligent z-space Boundary Condition-Particle Swarm Optimiser (IzBC-PSO)is based on a heuristic algorithm. This scheme can be applied to a wider rangeof problems without significant modifications and requires fewer computationscompared to the competing techniques.In order to verify the performance of IzBC-PSO antenna array measure-ments were performed in the receiving mode only using the online and offlinedigital beamforming setups described in chapter 8. The measurement resultsshow that the proposed scheme may be successfully applied with both onlineand offline digital beamformers for a practical small array (chapter 8).EThOS - Electronic Theses Online ServiceCOMSATS Institute of Information Technology (CIIT), Islamabad, PakistanGBUnited Kingdo

Modelling and aerodynamic design of optimisation of the twin-boom aegis UAV.

The aircraft industry gives considerable attention to computational optimisation tools in order to enhance the design process and product quality in terms of efficiency and performance, respectively. In reality, most real-world applications contain many complicating factors and constraints that affect system behaviour. Consequently, finding optimal solutions, or even only those viable for a given design problem, in an economical computational time is a difficult task, even with the availability of superfast computers. Thus, it is important to optimise the use of available computational resources. This research project presents a method for using stochastic multi-objective optimisation approaches combined with Artificial Intelligence and Interactive Design techniques to support the decision-making process. The improved ability of the developed methods to accelerate the search while retaining all the useful information in the design space was the main area of work. Both the efficiency and reliability of the proposed methodology have been demonstrated through the aerodynamic design of the Aegis-UAV. Initially, the optimisation platform Nimrod/O was deployed to enable the designer to manipulate and better understand different design scenarios. This happened before any commitment to a specific design architecture to allow for a wider exploration of the design space before a decision was made for a more detailed study of the problem. This had the potential to improve the quality of the product and reduce the design cycle time. The optimisation was performed using the Multi-Objective Tabu Search (MOTS) algorithm, chosen for its suitability for this type of complex aerodynamic design problem. Prior to the optimisation process, a parametric study was performed using the Sweep Method (SM) to explore the design space and identify design limitations. Analysis and investigation of the SM results were used to help determine the formulation of the design problem. SM was chosen because it has been proven to be reliable, effective, and able to provide a large amount of structured information about the design problem to the decision maker (DM) at this stage. Next, since most decisions of a DM in practical applications concern regions of the Pareto front, an interactive optimisation framework was proposed where the DM was involved with the optimisation process in real time. The framework used the Multi-Objective Particle Swarm Optimisation (MOPSO) algorithm for its suitability to this type of design problem. The results obtained confirmed the ability of the DM to use its preferences effectively, to steer the search to the Region of Interest (ROI) without degrading the aerodynamic performance of the optimised configurations. Even using only half the evaluations, the DM was able to obtain results similar to, or better than those obtained by the non-interactive use of MOTS and MOPSO. Furthermore, it was possible for the DM to stop the search at any iteration, which is not possible in non-interactive approaches even though the solutions do not converge or may be infeasible. Finally an Artificial Neural Network (ANN) was introduced to guide the MOPSO algorithm in deciding whether the trial solution was worthy of full evaluation, or not. The results obtained showed the success of the ANN in recognising non-valid particles. Consequently, the solver avoided wasting computational efforts on non-worthwhile particles. The optimisation process provides particles that are more valid for almost the same computational time. Demonstrating the algorithm’s effectiveness was done by comparing results of the ANN-MOPSO solutions with those obtained by the other approaches for the same design problems. In conclusion, future avenues of research have been identified and presented in the final chapter of the thesis.PhD in Aerospac

Detection, Prediction and Modelling of Mental Fatigue in Naturalistic Environment

Operator mental fatigue in workplace can result in serious mistakes which have dangerous and life-threatening consequences. Fatigue assessment and prediction are, therefore, considered critical safety requirements that cut across modes and operations of numerous high-risk environments and industries such as nuclear and transportation. However, robust, accurate and timely assessment of fatigue (or alertness) is still a challenging task for many reasons. The majority of operator fatigue studies are still being carried out in simulation environments, overlooking operator's naturalistic behaviour and fatigue growth. Moreover, most of the available systems rely on using a single fatigue-related data source, which is clearly a major drawback that affects operation, performance, accuracy and reliability of the system in case this source fails. With multi-data sources in an integrated system, the system might stop working in the event of losing one or more data sources or at least becomes inaccurate or unreliable. Furthermore, paying no attention to human individual differences working as an operator in mission-critical jobs related to fatigue growth and in response to fatigue deleterious effect is another serious issue with the current fatigue assessment and prediction systems. The research work presented in this thesis proposes a novel fatigue assessment approach, which addresses the aforementioned issues with fatigue detection and prediction system. This is achieved by developing and realising algorithms based on data collected from participants in naturalistic environments. Numerous experiments have been conducted to cover a wide range of fatigue-related tasks which are broadly grouped into two categories: biological and behavioural (performance) experiments. The biological-based experiments employ various data types such as heart rate, skin temperature, skin conductance and heart rate variability. These fatigue-related data types are used to build the proposed fatigue detection system, and the obtained results have demonstrated high accuracy and reliability (94.5% accuracy in naturalistic environments). The behavioural-based category includes two experiments: keyboard typing and driving task. The typing experiments have been carried out using computer keyboard and smartphone virtual keyboard, and have confirmed enhanced operator fatigue detection accuracy (94%). The driving experiments were conducted in naturalistic driving environments, and the used algorithms have demonstrated a new framework for driver fatigue detection using smartphone inertial sensors based on a novel vehicle heading algorithm. A prototype system was designed and built with a modular structure so as to allow the addition of multiple fatigue-related biological and behavioural sources. This modular structure was tested under different situations that involve losing one or more sources. In addition, the circadian rhythm, which is a main input to fatigue/alert regulators, was customised for each operator and modelled based on biological data collected from wearable devices. The constructed model captures individual differences of operators, which is a challenge in current systems. Such multi-source, modular and non-intrusive approach for fatigue/alertness assessment and prediction is expected to be of superior performance, low-cost and favourable by users compared to existing systems. Furthermore, it addresses other challenges of current fatigue systems by carrying out fatigue assessment in naturalistic environments and considering operator individual differences in response to fatigue. In addition, the modular structure of the proposed system helps improving robustness and accuracy against losing one or more input sources (accuracy for 4 sources: 91%, 3 sources: 87%, 2 sources: 77%). Following the proposed approach will definitely enhance the reliability of fatigue assessment systems, improve operator safety, productivity and reduce financial fatigue impacts. Moreover, the proposed system has proven to be non-intrusive in nature and of low implementation cost. The results obtained after testing the proposed system have been very promising to support the aforementioned benefits