Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and Multiscale Dynamics (American Scientific Publishers

Modelling of the Military Helicopter Operation Process in Terms of Readiness

The processes of exploitation of military objects are usually characterised by the specificity of the operation and the complexity of both the process itself and the object. This specificity may relate both to the type of tasks that these objects carry out and to the environment in which these processes take place. Complexity is usually reflected in the very structure of an object (for example, a ship, an aircraft or a helicopter) and, consequently, in its operation/maintenance system. The above mentioned features, as well as the limited access to data, naturally limits the set of publications available on this subject. In this article, the authors have presented a method of assessing the readiness of military helicopters operated by the Armed Forces of the Republic of Poland. The readiness of technical objects used in military exploitation systems is a basic indicator of equipment preparation for executing tasks. In exploitation process research, the mathematical models are usually discrete in states and continuous in time stochastic processes, in the set of which Markov models are included. The paper presents an example of using Markov processes with discrete time and with continuous time to assess the readiness of a technical object performing tasks appearing in random moments of time. At the same time, the aim of the examined system to achieve a state of balance is presented

Reliability-constrained design optimisation of extra-large offshore wind turbine support structures

The offshore wind industry has evolved significantly over the last decade, contributing considerably to Europe’s energy mix. For further penetration of this technology, it is essential to reduce its costs to make it competitive with conventional power generation technologies. To this end, optimising the design of components while simultaneously fulfilling design criteria is a crucial requirement for producing more cost-effective strategies. Traditional design optimisation techniques rely on the optimisation of design variables against constraints such as stresses or deformation in the form of limit states and to minimise an objective function such as the total mass of a component. Although this approach leads to more optimal designs, the presence of uncertainties, for instance, in material properties, manufacturing tolerances and environmental loads, requires more systematic consideration of these uncertainties. A combination of optimisation methods with concepts of structural reliability can be a suitable approach if challenges such as the approximation of the load effect concerning global input loads and computational requirements are addressed accordingly. In this study, a reliability-constrained optimisation framework for offshore wind turbine (OWT) support structures is developed, applied, and documented for the first time. First, a parametric finite element analysis (FEA) model of OWT support structures is developed, considering stochastic material properties and environmental loads. The parametric FEA model is then combined with response surface and Monte Carlo (MC) to create an assessment model in the Six Sigma module in ANSYS, which is then further integrated with an optimisation algorithm to develop a fully coupled reliability-constrained optimisation framework. The framework is applied to the NREL 5MW OWT and OC3 sub-structure. Results indicate that the proposed optimisation framework can effectively reduce the mass of OWT support structures meeting target reliability levels focusing on realistic limit states. At the end of the optimisation loop, an LCOE comparison is done to see the effect of mass reduction on the wind turbine cost. The study expanded with a scaling-up approach and investigated the technical feasibility of increasing the system’s power and size in deeper water depth for bottom-fixed support structures. Additionally, parametric equations have been developed to estimate the wind turbine rating and weight considering water depth in the conceptual design stage. Furthermore, the sensitivity analysis was performed on the latest reference support structure of the IEA 15MW turbine to see the effect of water depth between 30m to 60m. The results showed the influences of water depth on the current structural response of the monopile. It revealed that utilising the proposed support structure is not feasible for water-depth above 50m as the analysis did not fulfil design criteria.The offshore wind industry has evolved significantly over the last decade, contributing considerably to Europe’s energy mix. For further penetration of this technology, it is essential to reduce its costs to make it competitive with conventional power generation technologies. To this end, optimising the design of components while simultaneously fulfilling design criteria is a crucial requirement for producing more cost-effective strategies. Traditional design optimisation techniques rely on the optimisation of design variables against constraints such as stresses or deformation in the form of limit states and to minimise an objective function such as the total mass of a component. Although this approach leads to more optimal designs, the presence of uncertainties, for instance, in material properties, manufacturing tolerances and environmental loads, requires more systematic consideration of these uncertainties. A combination of optimisation methods with concepts of structural reliability can be a suitable approach if challenges such as the approximation of the load effect concerning global input loads and computational requirements are addressed accordingly. In this study, a reliability-constrained optimisation framework for offshore wind turbine (OWT) support structures is developed, applied, and documented for the first time. First, a parametric finite element analysis (FEA) model of OWT support structures is developed, considering stochastic material properties and environmental loads. The parametric FEA model is then combined with response surface and Monte Carlo (MC) to create an assessment model in the Six Sigma module in ANSYS, which is then further integrated with an optimisation algorithm to develop a fully coupled reliability-constrained optimisation framework. The framework is applied to the NREL 5MW OWT and OC3 sub-structure. Results indicate that the proposed optimisation framework can effectively reduce the mass of OWT support structures meeting target reliability levels focusing on realistic limit states. At the end of the optimisation loop, an LCOE comparison is done to see the effect of mass reduction on the wind turbine cost. The study expanded with a scaling-up approach and investigated the technical feasibility of increasing the system’s power and size in deeper water depth for bottom-fixed support structures. Additionally, parametric equations have been developed to estimate the wind turbine rating and weight considering water depth in the conceptual design stage. Furthermore, the sensitivity analysis was performed on the latest reference support structure of the IEA 15MW turbine to see the effect of water depth between 30m to 60m. The results showed the influences of water depth on the current structural response of the monopile. It revealed that utilising the proposed support structure is not feasible for water-depth above 50m as the analysis did not fulfil design criteria

Ambient vibration testing of civil engineering structures: development of a Python module and applications to case studies

This thesis treats ambient vibration testing of civil engineering structures with a special attention given to timber structures. It presents an open-source Python module that allows to perform two very much used output-only dynamic identification techniques. One of the reasons behind the open-source release of the module is the hope to attract other persons willing to help extending the module’s capabilities also to continuous monitoring applications. Furthermore, the work presents and discusses the application of Operational Modal Analysis methods to three case studies, highlighting the usefulness and potential of such methods. The cases are a prestressed short span concrete girder, an eight storey CLT building and a lightweight timber floor sub-assembly. Through the applications it is shown how Operational Modal Analysis may be of use not only to theoretical research oriented applications, but also very practical tasks. For instance in the framework of maintenance plans it is shown how ambient vibration testing results may be used to infer on the state of health of a bridge. Moreover, experimental modal properties are used to perform sensitivity analysis, update finite element models and draw comparison with analytical solutions. In fact, it is also shown how ambient vibration testing can be a viable and cheaper alternative to force vibration tests. All in all the goals of this work are to highlight the importance and potential of output-only identification methods and broaden the data-base present with applications to timber structures

Optimization of building performance via model-based predictive control

Il controllo predittivo basato su modello (MPC) è una tecnica di controllo avanzata che ha svolto un ruolo importante nella gestione di molti processi nel settore industriale. Oggi, nell’ottica di una gestione energetica efficiente degli edifici, l’utilizzo di questa strategia si sta dimostrando una soluzione promettente per ridurre al minimo i consumi e i costi energetici complessivi. Tuttavia, gli studi sulla sua fattibilità tecnica in edifici esistenti sono ancora in una fase iniziale. Pertanto, il risultato principale di questa tesi è la progettazione e lo sviluppo di un prototipo hardware e software per la verifica sul campo di un sistema di controllo predittivo, basato su modello, integrando un modello predittivo virtuale della porzione dell'edificio in esame, il controllore e l'interfaccia grafica per i dispositivi di monitoraggio e regolazione utilizzati. Inoltre, particolare attenzione è stata posta sulla fattibilità tecnica relativa all'implementazione di un tipico sistema MPC, che include un sottosistema di monitoraggio, un set di acquisizione dati e un metodo di identificazione del sistema per ottenere il modello per il controllore, mediante un approccio di modellazione grey-box. La fase di modellazione e l'approccio empirico sviluppato sono presentati nella prima parte di questa tesi di ricerca, mentre la parte centrale riguarda: lo sviluppo del prototipo di controllo predittivo, basato su modello, all'interno di uno strumento virtuale del software LabVIEW e la descrizione del test sperimentale, effettuato durante la stagione di riscaldamento, garantendo la normale operatività dell’edificio durante l'intero periodo di monitoraggio. Infine, è presentato lo studio sviluppato in ambiente di simulazione per indagare il potenziale della logica di controllo per la valutazione di scenari di riqualificazione. Il focus è sulla definizione dei principali componenti del simulatore MPC e sui risultati ottenuti testando uno degli scenari di intervento.Model Predictive Control (MPC) is an advanced control technique which has played an important role in the management of many processes in the industry sector. Nowadays, in the perspective of an efficient building energy management, the exploitation of this strategy is proving to be a promising solution for minimising overall energy consumptions and costs. However, investigations on the feasibility of the technique in real existing buildings are at an initial stage. Hence, the main outcome of this dissertation is the design and development of a prototype hardware and software set up for on-field testing of a model-based predictive control system, integrating a virtual predictive model of the portion of the building under investigation, the controller and the interface to the monitoring and regulation devices used. Moreover, this research is addressed to investigate the technical feasibility of the development and deployment of a typical MPC system, which includes a monitoring sub-system, a data acquisition set up and a system identification method to obtain the model for the controller by means of a grey-box modelling approach. The modelling phase and the empirical approach developed are presented in the first part of this research thesis, while the core part concerns: the development of the MPC prototype, within a virtual instrument of LabVIEW software and the description of the experimental test, which was carried out during heating season, ensuring normal building operation during the entire monitoring period. Finally, this dissertation presents the study developed in simulation environment to investigate the potential of the control logic for the evaluation of retrofitting scenarios. The focus is on the definition of the main MPC simulator components and on the results obtained by testing one of the intervention scenarios

Screening of reservoir types for decision-making on the application of intelligent wells

Abstract unavailable please refer to PD