With ever-increasing numbers of engine actuators to calibrate within increasingly stringent emissions legislation, the engine mapping and calibration task of identifying optimal actuator settings is much more difficult. The aim of this research is to evaluate the feasibility and effectiveness of the Multidisciplinary Design Optimisation (MDO) frameworks to optimise the multi-attribute steady state engine calibration optimisation problems. Accordingly, this research is concentrated on two aspects of the steady state engine calibration optimisation: 1) development of a sequential Design of Experiment (DoE) strategy to enhance the steady state engine mapping process, and 2) application of different MDO architectures to optimally calibrate the complex engine applications. The validation of this research is based on two case studies, the mapping and calibration optimisation of a JLR AJ133 Jaguar GDI engine; and calibration optimisation of an EU6 Jaguar passenger car diesel engine. These case studies illustrated that: -The proposed sequential DoE strategy offers a coherent framework for the engine mapping process including Screening, Model Building, and Model Validation sequences. Applying the DoE strategy for the GDI engine case study, the number of required engine test points was reduced by 30 – 50 %. - The MDO optimisation frameworks offer an effective approach for the steady state engine calibration, delivering a considerable fuel economy benefits. For instance, the MDO/ATC calibration solution reduced the fuel consumption over NEDC drive cycle for the GDI engine case study (i.e. with single injection strategy) by 7.11%, and for the diesel engine case study by 2.5%, compared to the benchmark solutions. / UK Technology Strategy Board (TSB)

Objective: The multidisciplinary follow-up of patients with cleft lip with or without palate (CL/P) is organized differently in specialized centers worldwide. The aim of this study was to evaluate the different treatment needs of patients with different manifestations of CL/P and to potentially adapt the frequency and timing of checkup examinations accordingly. Design:We retrospectively analyzed the data of all patients attending the CL/P consultation hour at a tertiary care center between June 2005 and August 2020 (n=1126). We defined 3 groups of cleft entities: (1) isolated clefts of lip or lip and alveolus (CL/A), (2) isolated clefts of the hard and/or soft palate, and (3) complete clefts of lip, alveolus and palate (CLP). Timing and type of therapy recommendations given by the specialists of different disciplines were analyzed for statistical differences. Results: Patients with CLP made up the largest group (n=537), followed by patients with cleft of the soft palate (n=371) and CL ±A (n=218). There were significant differences between the groups with regard to type and frequency of treatment recommendations. A therapy was recommended in a high proportion of examinations in all groups at all ages. Conclusion: Although there are differences between cleft entities, the treatment need of patients with orofacial clefts is generally high during the growth period. Patients with CL/A showed a similarly high treatment demand and should be monitored closely. A close follow-up for patients with diagnosis of CL/P is crucial and measures should be taken to increase participation in followup appointments.

The digital transformation of engineering design processes is essential for the aerospace industry to remain competitive in the global market. Multidisciplinary design optimization (MDO) frameworks play a crucial role in this transformation by integrating various engineering disciplines and enabling the optimization of complex spacecraft structures. Since the design team consists of multiple entities from different domains working together to build the final product, the design and analysis tools must be readily available and compatible. An integrated approach is required to handle the problem's complexity efficiently. Additionally, most aerospace structures are made from composite panels. It is challenging to optimize such panels as they require the satisfaction of constraints where the design ply thicknesses and orientations can only take discrete values prescribed by the manufacturers. Heuristics such as particle swarm or genetic algorithms are inefficient because they provide sub-optimal solutions when the number of design variables is large. They also are computationally expensive in handling the combinatorial nature of the problem. To overcome these challenges, this work proposes a two-fold solution that integrates multiple disciplines and efficiently optimizes composite spacecraft structures by building a rapid design framework. The proposed model-based design framework for spacecraft structures integrates commercially available software from Siemens packages such as NX and HEEDS and open-source Python libraries. The framework can handle multiple objectives, constraint non-linearities, and discrete design variables efficiently using a combination of black-box global optimization algorithms and Mixed Integer Programming (MIP)-based optimization techniques developed in this work. Lamination parameters and MIP are adopted to optimize composite panels efficiently. The framework integrates structural, thermal and acoustic analysis to optimize the spacecraft's overall performance while satisfying multiple design constraints. Its capabilities are demonstrated in optimizing a small spacecraft structure for required structural performance under various static and dynamic loading conditions when the spacecraft is inside the launch vehicle or operating in orbit. / Doctor of Philosophy / The design of new spacecraft takes several years and requires significant resources. The primary design objective is to minimize spacecraft mass/cost while satisfying the mission requirements. This is done by altering the structure's geometric and material properties. Most spacecraft panels are made from composite materials where the orientations of fiber paths and the thickness of the panel determine its strength and stiffness. Finding the best values for these parameters cannot be done efficiently using existing optimization algorithms, as several combinations of orientations can give a similar performance which can be subpar. In this dissertation, mathematical programming is adopted for fast evaluation of optimum panel properties, thereby saving a significant amount of resources compared to conventional techniques. Moreover, the requirements that govern the design process are handled one at a time in an organization. This leads to discrepancies in the various teams' designs that satisfy all requirements. A framework is built to integrate all requirements to account for their conflicting nature and quickly give the best possible spacecraft structural design configuration.

Automotive companies are exposed to tough competition and therefore strive to design better products in a cheaper and faster manner. This challenge requires continuous improvements of methods and tools, and simulation models are therefore used to evaluate every possible aspect of the product. Optimization has become increasingly popular, but its full potential is not yet utilized. The increased demand for accurate simulation results has led to detailed simulation models that often are computationally expensive to evaluate. Metamodel-based design optimization (MBDO) is an attractive approach to relieve the computational burden during optimization studies. Metamodels are approximations of the detailed simulation models that take little time to evaluate and they are therefore especially attractive when many evaluations are needed, as e.g. in multidisciplinary design optimization (MDO). In this thesis, state-of-the-art methods for metamodel-based design optimization are covered and different multidisciplinary design optimization methods are presented. An efficient MDO process for large-scale automotive structural applications is developed where aspects related to its implementation is considered. The process is described and demonstrated in a simple application example. It is found that the process is efficient, flexible, and suitable for common structural MDO applications within the automotive industry. Furthermore, it fits easily into an existing organization and product development process and improved designs can be obtained even when using metamodels with limited accuracy. It is therefore concluded that by incorporating the described metamodel-based MDO process into the product development, there is a potential for designing better products in a shorter time.

The mining industry generates billions of tonnes of waste annually, which is often stored in tailings storage facilities (TSF). This waste is generated from the extraction of ore from surface or underground mines, as well as from metallurgical processing and low-grade stockpiles. TSF can have significant environmental impacts, as they can cause acid mine drainage resulting in the leaching and transport of heavy metals into ground and surface waters. With increasing demand for critical raw material, recent studies have shown that the valorisation of mine waste can be a potential secondary source of critical raw materials. The valorisation of mine waste is possible when the waste is accurately characterised.A novel method that uses multispectral satellite remote sensing and machine learning to estimate the mineral resource in a defunct TSF in the Witwatersrand Basin, South Africa is proposed in this research. Four machine learning models: 1) random forest (RF); 2) adaptive boosting (AB); 3) extra trees (ET); and 4) k-nearest neighbours are developed using supervised machine learning. The models are trained using training data acquired from a TSF with known gold concentration located 3 kilometres from the TSF and deployed on the TSF to predict the gold grades. The results of the machine learning model predictions indicates that machine learning models had high performances for predicting gold grades in the TSF. The AB, RF and ET, models performed best. Their performances were evaluated using the coefficient of determination (R2) value. The R2 values for the machine learning models were 0.95, 0.92, 0.87 and 0.70 for AB, ET, RF and kNN respectively. The mean gold grade predicted was 0.44 g/t by all machine learning models. This was compared to a 2D surficial geostatistical model which estimated 0.35g/t gold in the TSF using ordinary kriging and a 2D vertically averaged geostatistical model with an estimated 0.4 g/t mean gold grade. The short-wave infrared (SWIR) - band 11 at a 20 m spatial resolution had the highest correlation with the reflectance of gold in the TSF. This study demonstrated the value of leveraging multi-spectral remote sensing data and machine learning to perform mineral resource estimation in defunct TSF.

The rising complexity of CubeSat missions and the unique challenges faced by educational CubeSat programs lead to high rates of mission failure. Implementing project management and systems engineering practices can alleviate these challenges and improve mission success rates for educational CubeSat developers. However, existing project management and systems engineering resources are too cumbersome and often assume the student has a base-level understanding of project management and systems engineering fundamentals. A new universal project management and systems engineering framework was created and tailored specifically to the needs of an educational CubeSat mission. The framework was designed to accommodate first-time CubeSat developers, has no base-level assumptions, and uses software accessible by the majority of university CubeSat programs. The framework was implemented on an educational CubeSat mission being designed by a first-time CubeSat developer. The framework was iteratively updated based on the developer’s feedback and experience using the templates, tools, and trainings. The universal project management and systems engineering framework for educational CubeSat missions demonstrated that it was effectively tailored to the needs of educational CubeSat missions, taught students the value of project management and systems engineering, enhanced students’ professional development, and was accessible for first-year undergraduate students to utilize with minimal intervention.

Modeling and simulation tools are exceptionally useful for designing aerospace systems because they allow engineers to test and iterate designs before committing the massive resources required for system realization. The Horizon Simulation Framework (HSF) is a time-driven modeling and simulation tool which attempts to optimize how a modeled system could perform a mission profile. After 15 years of development, the HSF team aims to achieve a wider user and developer base by releasing the software open source. To ensure a successful release, the software required extensive testing, and the main scheduling algorithm required protections against new code breaking old functionality. The goal of the work presented in this thesis is to satisfy these requirements and officially release the software open source. The software was tested with > 80% coverage and a continuous integration pipeline which runs build and unit/integration tests on every new commit was set up. Finally, supporting documentation and user resources were created and organized to promote community adoption of the software, making Horizon ready for an open source release.

Mémoire de maîtrise présenté en vue de l'obtention de la maîtrise en psychologie (M. Sc) / Contexte : L’hémianopsie homonyme (HH) a un impact significatif sur les activités quotidiennes, et les méthodes actuelles d’évaluation des personnes ayant une amputation du champ visuel ne permettent pas de combiner l’évaluation de la vision centrale et périphérique. Objectifs : Cette étude visait à valider un film d’animation innovant comme nouvel outil d’évaluation pour mesurer l’étendue du champ visuel aveugle, à établir une norme auprès d’une population contrôle en bonne santé visuelle et à déterminer le niveau de faisabilité du test. Méthodologie : La vidéo d’animation présentait une série de personnages à détecter. Elle était présentée sur 160° répartis sur 3 moniteurs d’ordinateur. Un eye-tracker était utilisé pour vérifier la stabilisation de la tête et le contrôle de la fixation. Quarante participants en bonne santé, âgés de 18 à 75 ans, ont été recrutés. Résultats : La plupart des animations ont été perçues par des participants contrôle sains, ce qui a permis d’établir une norme pour le test. Concernant l’appréciation du test, 60 % des participants l’ont beaucoup apprécié, 29 % l’ont aimé et 11 % ont eu une opinion neutre. Conclusion : Cet outil écologique évalue simultanément la vision centrale et la vision périphérique à l’aide d’un film d’animation. Avec des normes établies à partir d’une population générale ayant une vision saine et un accueil positif des participants, cet outil pourrait être utilisé pour évaluer et dépister les personnes suspectées d’avoir une HH, en particulier chez les enfants. / Background: Homonymous hemianopia (HH) has a significant impact on daily activities, and current methods of assessing people with visual field amputation don’t combine assessment of central and peripheral vision. Objectives: The aim of this study was to validate an innovative animated film as a new assessment tool for measuring the extent of the blind visual field, to establish a standard in a visually healthy control population, and to determine the test’s feasibility. Methodology: The animated video presented a series of characters that needed to be detected. It was presented in 160 degrees on 3 computer monitors. An eye tracker was used to check head stabilization and fixation control. Forty healthy participants aged between 18 and 75 were recruited. Results: Most of the animations were perceived by healthy control participants, helping to establish a standard for the test. In terms of appreciation of the test, 60% of participants liked it a lot, 29% liked it and 11% had a neutral opinion. Conclusion: This ecological tool simultaneously assesses central and peripheral vision using an animated film. With standards based on a general population with healthy vision and a positive reception from participants, this tool could be used to assess and screen people suspected of having HH, particularly in children.

The care of people with Parkinson’s disease (PD) involves input from different healthcare professionals (HCPs). A literature search identified that the HCPs involved in PD multidisciplinary (MDT) clinics, including interdisciplinary team (IDT), varied both in the number and type of HCPs. None of the studies identified involved pharmacists. Pharmacists have shown benefits when working in MDTs for other long-term conditions (LTCs); however, their role in PD MDTs was identified as a gap in the literature. The aim of the study was to determine the role of pharmacists in a PD IDT. Patients attended a PD IDT clinic comprising PD nurse, physiotherapist, occupational therapist and pharmacist. A mixed methods convergent design was used to collect both qualitative and quantitative data. Qualitative focus group and interview data were analysed using The Framework Method. Quantitative data analysis involved counts of HCP interventions. Pharmacists can support PD IDTs as they have in other LTC MDTs by conducting holistic medication reviews. Three new roles were identified for pharmacists in PD IDTs as: 1) independent prescribing, 2) supporting HCPS in their roles by supporting staff knowledge, and 3) leading the PD IDT clinics. Quantitative data showed the pharmacist made a medication review intervention for all patients. HCPs and patients identified the roles and value of involving pharmacists in PD IDTs. The PD IDT clinics offer a holistic approach to patient care and a greater opportunity for patients to be involved. The findings identified a ‘review-shared care template’ for PD IDTs and recommends development of a ‘pharmacist’s PD competency framework’.

The way of representing Earth has changed; two dimensional (2D) maps have turned into three Dimensional (3D) representations. There are many studies in order to create 3D city maps as well as areas where these are applied such as 3D cadastral, 3D visualization and flood simulation, etc. These can be created with the aid of different data sources using photogrammetric Digital Surface Model (DSM) derived from image matching and from Light Detection and Ranging (LiDAR) point clouds or both of them combining orthophotos and building footprints. Several software has been developed to ease and speed up this process. In this study, a current state-of-the art in the 3D city modeling with particular interest to commercial software was analyzed. DSMs from image matching (Satellite and Airborne) were used in order to create a 3D city model of Trento, Italy. The objectivewas to examine the degree of automation and the computation time of two available software: Feature Manipulation Engine (FME) and Building Reconstruction (BREC). Other problem such as the quality of the DSM needed would be discussed for each software and the results would be compared to those achieved using LiDAR data. Recommendations and possible problems would also be addressed. In order to create a 3D city model, the ALDPAT software (Airborne LiDAR Data Processing and Analysis Tool) has been used to separate the ground regions (Digital Terrain Model, DTM) from the man-made objects and trees (Normal Digital Surface Model, nDSM). FME and BREC software have been used to reconstruct the 3D city model. The output results from FME and BREC have been analyzed qualitatively and quantitatively. The comparison between the models generated from photogrammetric and LiDAR DSMs have been performed. The results show that buildings generated by satellite images have poorest quality compared with buildings from LiDAR and airborne data. In particular, the performed tests will be shown that among the Level of Details (LoD), a LoD1 and LoD2 3D city models can be generated using a DSM by image matching. A deeper study should be done in order to analyze the level of detail qualitatively.