Yes / The work presented in this paper is motivated by a complex multivariate engineering problem associated with engine mapping experiments, which require efficient Design of Experiment (DoE) strategies to minimise expensive testing. The paper describes the development and evaluation of a Permutation Genetic Algorithm (PermGA) to support an exploration-based sequential DoE strategy for complex real-life engineering problems. A known PermGA was implemented to generate uniform OLH DoEs, and substantially extended to support generation of Model Building–Model Validation (MB-MV) sequences, by generating optimal infill sets of test points as OLH DoEs, that preserve good space filling and projection properties for the merged MB + MV test plan. The algorithm was further extended to address issues with non-orthogonal design spaces, which is a common problem in engineering applications. The effectiveness of the PermGA algorithm for the MB-MV OLH DoE sequence was evaluated through a theoretical benchmark problem based on the Six-Hump-Camel-Back (SHCB) function, as well as the Gasoline Direct Injection (GDI) engine steady state engine mapping problem that motivated this research. The case studies show that the algorithm is effective at delivering quasi-orthogonal space-filling DoEs with good properties even after several MB-MV iterations, while the improvement in model adequacy and accuracy can be monitored by the engineering analyst. The practical importance of this work, demonstrated through the engine case study, also is that significant reduction in the effort and cost of testing can be achieved. / The research work presented in this paper was funded by the UK Technology Strategy Board (TSB) through the Carbon Reduction through Engine Optimization (CREO) project.

Yes / In this perspective paper, we present challenges and opportunities that the chemical, biochemical and related industries pose to the process system engineering community to help deliver reliable and novel sustainable alternatives. More specifically, we highlight the need for a systems approach where model-based sustainable process synthesis, design, and analysis serve as opportunities to tackle the challenges. Three technology areas (interlinked to each other) that impact the sustainability of earth, namely, chemical processes linked with CO2 capture and utilization, biorefineries and water desalination are selected to highlight our views as well as the need for further development of computer-aided tools to efficiently solve the large and complex mathematical systems the problems represent. Analysis of these problems and their reported solutions indicate that opportunity exists for development of a new class of model-based methods and tools and their integration with the currently available ones to obtain the desired sustainability development goals.

The Tempo machine plants seeds at controlled intervals using the PowerShoot system. Model-based diagnosis utilizes relationships between measured states and system model estimations to detect and isolate faults. This thesis, conducted in collaboration with Väderstad AB, focuses on developing a model-based diagnosis system for the Tempo L. A system model was created and validated using data from a dedicated testing machine, demonstrating the ability to estimate most machine states from hydraulic pressure as the sole input. Using the validated models, the MATLAB Fault Diagnosis Toolbox was employed to generate state comparisons and residuals linked to common faults. Residuals were evaluated using CUSUM tests to detect faults while minimizing false alarms. The diagnosis system identified 15 faults, of which 13 were detectable and 9 fully isolable, with major faults including leakages and blockages affecting seeding quality. The thesis also explores the use of optical sensors in each row unit to predict pressure based on seed velocity, presenting promising diagnostic abilities. Additionally, different sensor configurations were evaluated to assess the benefits of adding more sensors to the machine. This work represents an initial effort to improve the diagnostics of the Tempo L planter, providing insight into more reliable and efficient agricultural machinery.

This study is a two part research project that describes and evaluates the efforts of the researcher to bring change in Cyprus' educational system, in the field of simple electric circuits. The objective of the first part was the assessment and evaluation of Cypriot STVE students' perceptions about simple electric circuits. The objective of the second part was to measure the effectiveness that conceptual change model-based instructional activities designed by the researcher had on changing students' misconceptions about simple electric circuits towards scientifically accepted ideas. Transformative mixed methods research design was used consisting mainly from an one-group pre-test post-test design with Determining and Interpreting Resistive Electric Circuits Concepts Test 1.2 as a research instrument, while interviews and field notes were used for triangulation. The findings showed that there was a significant improvement in students' understanding of simple electric circuit concepts that were taught using conceptual change model-based instructional activities. / Science and Technology Education / M. Sc. (Mathematics, Science and Technology Education)

This work is intended to investigate the Aircraft Technical Diagnostics Systems by focusing on Central Maintenance Systems and the Fault Detection and Isolation (FDI) process among the avionic components. A review about the Computer Control Systems and background about the Avionic Architecture is presented prior to introducing to most popular FDI method; model-based diagnosis. The discussions about the onboard FDI practices are followed by a maintenance hangar FDI perspective which was concluded as a result of the field research. The outcomes of the field research and pointing the “real” fault isolation are analyzed to point the practical needs of a hangar FDI tools. Subsequently, a proposal technique, which can improve fault isolation by preventing No-Fault-Found (NFF), is given by discussing the methods to implement it. Finally, the results of investigation and conclusions of analysis are presented. / Baigiamajame darbe lietuviškos anotacijos nepateikta.

Mixture model-based clustering has become an increasingly popular data analysis technique since its introduction almost fifty years ago. Families of mixture models are said to arise when the component parameters, usually the component covariance matrices, are decomposed and a number of constraints are imposed. Within the family setting, it is necessary to choose the member of the family --- i.e., the appropriate covariance structure --- in addition to the number of mixture components. To date, the Bayesian information criterion (BIC) has proved most effective for this model selection process, and the expectation-maximization (EM) algorithm has been predominantly used for parameter estimation. We deviate from the EM-BIC rubric, using variational Bayes approximations for parameter estimation and the deviance information criterion (DIC) for model selection. The variational Bayes approach alleviates some of the computational complexities associated with the EM algorithm. We use this approach on the most famous family of Gaussian mixture models known as Gaussian parsimonious clustering models (GPCM). These models have an eigen-decomposed covariance structure. Cluster-weighted modelling (CWM) is another flexible statistical framework for modelling local relationships in heterogeneous populations on the basis of weighted combinations of local models. In particular, we extend cluster-weighted models to include an underlying latent factor structure of the independent variable, resulting in a novel family of models known as parsimonious cluster-weighted factor analyzers. The EM-BIC rubric is utilized for parameter estimation and model selection. Some work on a mixture of multivariate t-distributions is also presented, with a linear model for the mean and a modified Cholesky-decomposed covariance structure leading to a novel family of mixture models. In addition to model-based clustering, these models are also used for model-based classification, i.e., semi-supervised clustering. Parameters are estimated using the EM algorithm and another approach to model selection other than the BIC is also considered. / NSERC PGS-D

This research study presents a new vibration-based non-destructive global structural damage identification and condition monitoring technique that can be used for detection, localization and quantification of damage. A two-stage damage identification process that combines non-model based and model-based damage identification approaches is proposed to overcome the main difficulties associated with the solution of structural damage identification problems. In the first stage, performance assessment of various response parameters obtained from the time-domain, frequency-domain and spectral-domain analysis is conducted using a non model-based damage detection and localization approach. In addition, vibration response parameters that are sensitive to local and global damage and that possess strong physical relationships with key structural dynamic properties are identified. Moreover, in order to overcome the difficulties associated with damage identification in the presence of structural nonlinearity and response nonstationarity, a wavelet transform based damage-sensitive parameter is presented for detection and localization of damage in the space domain. The level of sensitivity and effectiveness of these parameters for detection and localization of damage are demonstrated using various numerical experimental data determined from one-dimensional and two-dimensional plate-like structures.

Dieser Beitrag erläutert die Umsetzung der Digitalisierung speziell im Anwendungsgebiet des Engineering. Dabei wird die Digitalisierung, sowohl des eigentlichen Produktes als auch der im Rahmen von Service-orientierten Geschäftsmodellen entwickelten Dienstleistung, vorgestellt. Ein weiterer wesentlicher Punkt der Digitalisierung sind die horizontale und vertikale Integration der technischen und administrativen Arbeitsprozesse entlang des Produktlebenszyklus. Bei den vertikalen Integrationen handelt es ich um die Integrationen der Autorensysteme entlang den Lebenszyklusphasen Anforderungsmanagement, Systemarchitektur, CAD in Mechanik, Elektronik, Softwareentwicklung, Simulation, Test, Prozessplanung und Digitale Fabrik. Bei der horizontalen Integration stehen die administrativen Funktionen wie Freigabe-, Änderungs- und Konfigurationsmanagement über den gesamten Produklebenszyklus und die technische Integration der in den einzelnen Produktlebenszyklus-Phasen erzeugten Informationen im Vordergrund. Hier ist vor allem die Verteilung und Orchestrierung der Funktionen zwischen SysLM, MES und PPS relevant.

This study is a two part research project that describes and evaluates the efforts of the researcher to bring change in Cyprus' educational system, in the field of simple electric circuits. The objective of the first part was the assessment and evaluation of Cypriot STVE students' perceptions about simple electric circuits. The objective of the second part was to measure the effectiveness that conceptual change model-based instructional activities designed by the researcher had on changing students' misconceptions about simple electric circuits towards scientifically accepted ideas. Transformative mixed methods research design was used consisting mainly from an one-group pre-test post-test design with Determining and Interpreting Resistive Electric Circuits Concepts Test 1.2 as a research instrument, while interviews and field notes were used for triangulation. The findings showed that there was a significant improvement in students' understanding of simple electric circuit concepts that were taught using conceptual change model-based instructional activities. / Science and Technology Education / M. Sc. (Mathematics, Science and Technology Education)

L'organisation classique en silos disciplinaires des industries atteint ses limites pour maîtriser la complexité. Les problèmes sont découverts trop tard et le manque de communication entre les experts empêche l'émergence précoce de solutions. C'est pourquoi, il est urgent de fournir de nouvelles approches collaboratives et des moyens d' interactions entre les disciplines d'ingénierie, au début et tout au long du cycle de développement. Dans ce contexte, nous avons étudié l'approche synchronisation de modèles entre deux domaines d'ingénierie : la conception d'architecture de systèmes et la sûreté de fonctionnement. Elle a pour but de construire et maintenir la cohérence entre les modèles.Ces travaux proposent, étudient et analysent une démarche collaborative de synchronisation de modèles. Ils tiennent compte des contextes d’études, des processus, des méthodes appliqués et des points de vue produits par les ingénieurs. Les contributions répondent à des problématiques au niveau des pratiques, des concepts, de la mise en œuvre, des applications et l’implémentation de la synchronisation de modèles. / Classical organization in disciplinary silos in the industry reaches its limits to manage and control complexity. Problems are discovered too late and the lack of communication between experts prevents the early emergence of solutions. This is why it is urgent to provide new collaborative approaches and ways to exchange the models contents between various engineering fields, early and all along the development cycle. In this context, we are particularly interested in a synchronization approach of models between two engineering fields: system architecture design and dependability analysis.This work proposes a collaborative approach of synchronization of models. It takes into account the study contexts, applied processes, applied methods and viewpoint produced by engineers. Contributions address issues at levels of practices, concepts, implementation, applications and implementation of model synchronization.