Data-driven nonlinear MPC using dynamic response surface methodology

For many complex processes, it is desirable to use a nonlinear model in the MPC design, and the recently proposed Dynamic Response Surface Methodology (DRSM) is capable of accurately modeling nonlinear continuous processes over semi-infinite time horizons. We exploit the DRSM to identify nonlinear data-driven dynamic models that are used in an NMPC. We demonstrate the ability and effectiveness of the DRSM data-driven model to be used as the prediction model for a nonlinear MPC regulator. This DRSM model is efficiently used to solve a non-equally-spaced finite-horizon optimal control problem so that the number of decision variables is reduced. The proposed DRSM-based NMPC is tested on a representative nonlinear process, an isothermal CSTR in which a second-order irreversible reaction is taking place. It is shown that the obtained quadratic data-driven model accurately represents the open-loop process dynamics and that DRSM-based NMPC is an effective data-driven implementation of nonlinear MPC

Electron Depletion Due to Bias of a T-Shaped Field-Effect Transistor

A T-shaped field-effect transistor, made out of a pair of two-dimensional electron gases, is modeled and studied. A simple numerical model is developed to study the electron distribution vs. applied gate voltage for different gate lengths. The model is then improved to account for depletion and the width of the two-dimensional electron gases. The results are then compared to the experimental ones and to some approximate analytical calculations and are found to be in good agreement with them.Comment: 16 pages, LaTex (RevTex), 8 fig

Sol-gel immobilization of glutathione transferase: efficient tool for bioremediation

Glutathione transferases are multi-functional enzymes with an important role in xenobiotic detoxification. They catalyse the nucleophilic addition of the sulfur atom of glutathione (γ-L-Glu-L-Cys-Gly, GSH) to the electrophilic groups of a large variety of hydrophobic molecules including organic halides, epoxides, arene oxides, α- and β-unsaturated carbonyls, organic nitrate esters, and organic thiocyanates. The conjugation of GSH to such molecules increases their solubility and reduces their toxicity. GSTs represent a versatile tool with a variety of biotechnological applications, in the field of bioremediation to clean up environmentally contaminated sites. The purpose of this project was the study of GST immobilization for the biodegradation of toxic compounds

Stepping into safety: a systematic review of extended reality technology applications in enhancing vulnerable road user safety

Purpose: In alignment with the European Union’s Vision Zero initiative to eliminate road fatalities by 2050, leveraging technological advancements becomes crucial for addressing the challenges of vulnerable road users (VRUs), and for mitigating the impact of human error. Despite increasing scholarly interest in applications of extended reality (XR), a research gap persists, particularly in the role of XR in transportation safety. Therefore, the aim of the study was to fill this gap through a systematic literature review to evaluate comprehensively the potential scope and practical applicability of XR technologies in enhancing the safety of VRUs. Design/methodology/approach: A systematic review was undertaken, following PRISMA guidelines meticulously, in which 80 relevant articles from databases, such as Scopus and Science Direct, were identified and analysed. Findings: The results of the analysis revealed the potential of XR beyond pedestrians and cyclists, and highlighted a lack of research about the impact of XR with regard to the personal traits or abilities of VRUs. The results of a thorough analysis confirmed the potential of XR as a promising solution for an approach to collaborative co-creation in addressing the safety challenges of VRUs. In addition, the integration of eye-tracking with virtual reality emerged as a promising innovation for enhancing the safety of vulnerable road users. Research limitations/implications: Theoretical implications include enhancing the understanding of applications of XR in VRUs’ safety and providing insights into future research possibilities and methodological approaches. Valuable insights into search strategies and inclusion-exclusion criteria can guide future research methodologies. Practical implications: Practically, the findings from the study offer insights to assist urban planners and transportation authorities in incorporating XR technologies effectively for VRUs safety. Identifying areas for further development of XR technology could inspire innovation and investment in solutions designed to meet the safety needs of VRUs, such as enhanced visualisation tools and immersive training simulations. Originality/value: The findings of previous research underscore the vast potential of XR technologies within the built environment, yet their utilisation remains limited in the urban transport sector. The intricacies of urban traffic scenarios pose significant challenges for VRUs, making participation in mobility studies hazardous. Hence, it is crucial to explore the scope of emerging technologies in addressing VRUs issues as a pre-requisite for establishing comprehensive safety measures

Modeling and Optimization of Lactic Acid Synthesis by the Alkaline Degradation of Fructose in a Batch Reactor

The present work deals with the determination of the optimal operating conditions of lactic acid synthesis by the alkaline degradation of fructose. It is a complex transformation for which detailed knowledge is not available. It is carried out in a batch or semi-batch reactor. The ‘‘Tendency Modeling’’ approach, which consists of the development of an approximate stoichiometric and kinetic model, has been used. An experimental planning method has been utilized as the database for model development. The application of the experimental planning methodology allows comparison between the experimental and model response. The model is then used in an optimization procedure to compute the optimal process. The optimal control problem is converted into a nonlinear programming problem solved using the sequencial quadratic programming procedure coupled with the golden search method. The strategy developed allows simultaneously optimizing the different variables, which may be constrained. The validity of the methodology is illustrated by the determination of the optimal operating conditions of lactic acid production

Development of an integrated framework for satisfaction assessment of construction project teams

With increasing competitive pressures in today‟s market, it has become critical for businesses to recognise the significance of satisfying their customers so as to ensure their economic stability. Various studies have emphasised on the need for customer focus and project satisfaction in the construction industry sector. The industry, however, has not fully embraced the practice of project satisfaction, which is grounded on meeting the needs of the customer. Though most research on project satisfaction has focussed on the client, it is essential that the satisfaction of the project delivery team and in the wider context, the stakeholders be considered. In this case, the client is the centre of gravity of the project team. In order to satisfy the project team, there are challenges in assessing their requirements. This necessitates the need to develop a unique and robust method for capturing and analysing the level of integrated project team satisfaction. In this research, the project delivery team and the stakeholders have been lumped together as an integrated project team. Therefore, integrated project team satisfaction entails recognising the client and project participants‟ requirements that guarantees project successful completion and acceptance by the team. In view of this, this research presents a framework, which has been developed to plug these needs and challenges. The framework, known as the Satisfaction Assessment Integrated Framework (SAIF) involves an integrated approach that considers the participants of a construction project as a tree structure, and each member of that tree as an intermediate or top element. Relationships and interactions of the elements, and how these affect the overall satisfaction levels of a single project, are analysed based on understanding their requirements and invoking modern satisfaction attainment theory. The framework includes a method for understanding and identifying the satisfaction attributes; multi-attribute analysis for prioritising the satisfaction attributes of the clients and project participants; fault tree analysis strategy for defining the satisfaction relationship in a particular project team; and an assessment scoring system (a combination of multi-attribute analysis, and failure mode and effects analysis methodical approach) that evaluates how much each member of the project team meets the requirements or satisfaction attributes of other participants. Hence, SAIF, a novel assessment methodology, investigates and identifies possible links and the influence of integrating the construction project team and their satisfaction attributes with the aim of improving their satisfaction levels as a team. Through the findings of this research, recommendations are made to further explore the implications of satisfying a given participant against dissatisfying the participant; and subsequently improve the satisfaction assessment process.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

MultiModal route planning in mobility as a service

This is an accepted manuscript of an article published by ACM in Proceedings 2019 IEEE/WIC/ACM International Conference on Web Intelligence Workshops (WI 2019 Companion) in October 2019, available online: https://doi.org/10.1145/3358695.3361843 The accepted version of the publication may differ from the final published version.Mobility as a Service (MaaS) is a new approach for multimodal transportation in smart cities which refers to the seamless integration of various forms of transport services accessible through one single digital platform. In a MaaS environment there can be a multitude of multi modal options to reach a destination which are derived from combinations of available transport services. Terefore, route planning functionalities in the MaaS era need to be able to generate multi-modal routes using constraints related to a user's modal allowances, service provision and limited user preferences (e.g. mode exclusions) and suggest to the traveller the routes that are relevant for specific trips as well as aligned to her/his preferences. In this paper, we describe an architecture for a MaaS multi-modal route planner which integrates i) a dynamic journey planner that aggregates unimodal routes from existing route planners (e.g. Google directions or Here routing), enriches them with innovative mobility services typically found in MaaS schemes, and converts them to multimodal options, while considering aspects of transport network supply and ii) a route recommender that filters and ranks the available routes in an optimal manner, while trying to satisfy travellers' preferences as well as requirements set by the MaaS operator (e.g. environmental friendliness of the routes or promotion of specific modes of transport).Published versio

Heuristic-based journey planner for mobility as a service (Maas)

© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/su122310140The continuing growth of urbanisation poses a real threat to the operation of transportation services in large metropolitan areas around the world. As a response, several initiatives that promote public transport and active travelling have emerged in the last few years. Mobility as a Service (MaaS) is one such initiative with the main goal being the provision of a holistic urban mobility solution through a single interface, the MaaS operator. The successful implementation of MaaS requires the support of a technology platform for travellers to fully benefit from the offered transport services. A central component of such a platform is a journey planner with the ability to provide trip options that efficiently integrate the different modes included in a MaaS scheme. This paper presents a heuristic that implements a scenario-based journey planner for users of MaaS. The proposed heuristic provides routes composed of different modes including private cars, public transport, bike-sharing, car-sharing and ride-hailing. The methodological approach for the generation of journeys is explained and its implementation using a microservices architecture is presented. The implemented system was trialled in two European cities and the analysis of user satisfaction results reveal good overall performance.This research was funded by the European Union’s Horizon 2020 research and innovation programme grant number No 723176. And the APC was funded by the European Commission.Published versio