Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 20 for “"Hybrid modelling"”.
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Hybrid modelling of heterogeneous volumetric objects.
Heterogeneous multi-material volumetric modelling is an emerging and rapidly developing field. A Heterogeneous object is a volumetric object with interior structure where different physically-based attributes are defined. The attributes can be of different nature: material distributions, density, …
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Hybrid modelling of time-variant heterogeneous objects.
… Past research was mainly focussed on the modelling of simple homogeneous objects of a uniform constitution. Such research resulted in the development of a number of advanced theoretical concepts and practical techniques for describing such physical objects. As a result, the process of …
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Hybrid Modelling and Optimisation of Oil Well Drillstrings
… the complicated and harsh drilling environment, modelling of the drillstring becomes an essential requirement in studies. Currently, this is achieved by modelling the drillstring as a torsional lumped model (which ignores the length of the drillstring) for real-time measurement and control. In …
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Optimisation of CHO Cell Line Development Using Hybrid Modelling for Antibody Therapeutics
… process scaling up using a data-driven hybrid model that integrates machine learning (ML) with first-principle mechanistic models. The hybrid tool forecasts bioreactor metabolite profiles from simplistic micro- and small-scale cultivation data, improving knowledge, production efficiency, …
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Next-Generation Microalgae Cultivation: Innovative flat panel photobioreactor with tailored light regulation and hybrid modelling approach
L'abstract è presente nell'allegato / the abstract is in the attachment
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Neural network based hybrid modelling and MINLP based optimisation of MSF desalination process within gPROMS: Development of neural network based correlations for estimating temperature elevation due to salinity, hybrid modelling and MINLP based optimisation of design and operation parameters of MSF desalination process within gPROMS
… and Temperature Elevation (TE) due to salinity. Modelling plays an important role in simulation, optimisation and control of MSF processes and within the model, calculation of TE is therefore important for each stages (including the first stage, which determines the TBT). Firstly, in this work, …
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Simulation of the generation and propagation of blast induced shock waves
Hybrid modelling of blast vibration uses the signal produced from a single hole test shot to simulate the vibration that would be produced by a full-scale production blast. This simulation can be used to determine optimum hole timings to minimise the vibration generated at a point of interest. This …
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ADVANCING MULTIPHASE PROCESS DEVELOPMENT WITH HYBRID PHYSICS-BASED – MACHINE LEARNING MODELS
… system performance. This thesis presents a hybrid modelling framework for reactive multiphase processes, demonstrated on a liquid-liquid nitration system, and developed using experimental data guided by strategies for informative experiment selection. Understanding hydrodynamic behaviour is …
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DYNAMIC DECISION MAKING IN AN AUTOMATED CONTAINER YARD BLOCK VIA OPTIMIZATION-EMBEDDED DISCRETE-EVENT-SIMULATION
… requests. An innovative top-down approach to a hybrid modelling formalism is adopted to provide a discrete-event simulation model of yard crane operations. This model is used to compare operational strategies addressing the storage allocation and job scheduling problems. In particular, an …
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EUKARYO: An Agent-Based, Interactive, Virtual Reality Simulation of a Eukaryotic Cell
… and Unreal Engine. Eukaryo utilises mathematical modelling towards modelling enzyme kinetics, and agent-based modelling to illustrate the interaction between the individual proteins in the cell. Using hybrid modelling, Eukaryo is able to model the interactions for a diverse range of biological …
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The production planning problems of flexible manufacturing systems with high tool variety
… a comprehensive FMS simulator which uses a novel hybrid modelling technique is discussed. The use of a graphical post-processor which can be used to enhance the system logic of the FMS is also described number of parameters associated with the tool management system are identified and the methods …
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Digital Twin for Machine Tools and Manufacturing Systems
… Firstly, it proposes a lightweight hybrid modelling approach that fuses finite element analysis with neural networks to predict multi-physics behaviours of machine components. Secondly, it presents a semantic text- analysis pipeline that transforms unstructured maintenance logs into …
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Representing and reasoning about concrete domains with inference fusion.
Description Logic (DL)-based concept modelling formalisms provide a powerful means to represent and reason about taxonomic knowledge. They benefit from unambiguous semantics which make possible the automatic classification of concept definitions. However, the inevitable "trade-off" between the …
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Cluster detection and analysis with geo-spatial datasets using a hybrid statistical and neural networks hierarchical approach
… domains. This methodology is based on a hybrid of statistical methods using properties of probability rather than distance to associate data with clusters. No previous knowledge of the dataset is required and the number of clusters is not predetermined. It performs efficiently in terms of …
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Incorporating sensor measurements using data assimilation and machine learning to improve the accuracy of thermal finite element models
… unsuitable for application in a digital twin. A hybrid model is a combination of physics-based and data-driven models that seeks to exploit the advantages of both approaches, and is a promising candidate for producing a model that is suitable for application in a digital twin. This work …
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Neuro-Fuzzy Based Intelligent Approaches to Nonlinear System Identification and Forecasting
… unpredictable, ill or well defined. Neurofuzzy hybrid modelling approaches have been developed as an ideal technique for utilising linguistic values and numerical data. This Thesis is focused on the development of advanced neurofuzzy modelling architectures and their application to real case …
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Data-led methods for the analysis and interpretation of eddy covariance observations
… general objective of this work is to develop a modelling methodology that synthesises physical process understanding with the information content in canopy scale data as an attempt to overcome the limitations in both carbon exchange models and observations. Similar hybrid modelling approaches …
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Improving the ability of energy systems optimisation modelling to inform national energy policymaking
… are improvements to the state-of-the-art energy modelling methods and applications of the enhanced models to answer key policy questions with convincing evidence. The improvements are demonstrated via two well-established energy systems modelling tools in Ireland and Iran. The thesis concludes …
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A new approach to modelling process and building energy flows in manufacturing industry.
… This research formulates a methodology for modelling energy flows between a factory building, its manufacturing process systems and the materials used. The need for such an approach arises from the gap in knowledge between the understanding of energy consumed by factory buildings and process …
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Aplicaciones de la hidrodinámica suavizada de las partículas al estudio de fenómenos hidráulicos
… and complement these kinds of studies. However, hybrid modelling presents interesting improvements. A first mathematical study provides a initial phenomena analysis and delimits different problems before the physical model test. Moreover, the double physical and numerical experimentation of …