Modelling and experimental verification of a solar-powered liquid desiccant cooling system for greenhouse food production in hot climates

Experiments and theoretical modelling have been carried out to predict the performance of a solar-powered liquid desiccant cooling system for greenhouses. We have tested two components of the system in the laboratory using MgCl2 desiccant: (i) a regenerator which was tested under a solar simulator and (ii) a desiccator which was installed in a test duct. Theoretical models have been developed for both regenerator and desiccator and gave good agreement with the experiments. The verified computer model is used to predict the performance of the whole system during the hot summer months in Mumbai, Chittagong, Muscat, Messina and Havana. Taking examples of temperate, sub-tropical, tropical and heat-tolerant tropical crops (lettuce, soya bean, tomato and cucumber respectively) we estimate the extensions in growing seasons enabled by the system. Compared to conventional evaporative cooling, the desiccant system lowers average daily maximum temperatures in the hot season by 5.5-7.5 °C, sufficient to maintain viable growing conditions for lettuce throughout the year. In the case of tomato, cucumber and soya bean the system enables optimal cultivation through most summer months. It is concluded that the concept is technically viable and deserves testing by means of a pilot installation at an appropriate location.

Similarity between class A and class B G-protein-coupled receptors exemplified through calcitonin gene-related peptide receptor modelling and mutagenesis studies

Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A-class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg(2.39), His(2.43) and Glu(3.46), which makes a polar lock with T(6.37). These alignments and models provide useful tools for understanding class B GPCR function.

The definition, theoretical modelling and empirical research of front-line service employee corporate identity within a UK national grocery retailer:determining the FLE corporate brand identification construct

Over the past forty years the corporate identity literature has developed to a point of maturity where it currently contains many definitions and models of the corporate identity construct at the organisational level. The literature has evolved by developing models of corporate identity or in considering corporate identity in relation to new and developing themes, e.g. corporate social responsibility. It has evolved into a multidisciplinary domain recently incorporating constructs from other literature to further its development. However, the literature has a number of limitations. It remains that an overarching and universally accepted definition of corporate identity is elusive, potentially leaving the construct with a lack of clear definition. Only a few corporate identity definitions and models, at the corporate level, have been empirically tested. The corporate identity construct is overwhelmingly defined and theoretically constructed at the corporate level, leaving the literature without a detailed understanding of its influence at an individual stakeholder level. Front-line service employees (FLEs), form a component in a number of corporate identity models developed at the organisational level. FLEs deliver the services of an organisation to its customers, as well as represent the organisation by communicating and transporting its core defining characteristics to customers through continual customer contact and interaction. This person-to-person contact between an FLE and the customer is termed a service encounter, where service encounters influence a customer’s perception of both the service delivered and the associated level of service quality. Therefore this study for the first time defines, theoretically models and empirically tests corporate identity at the individual FLE level, termed FLE corporate identity. The study uses the services marketing literature to characterise an FLE’s operating environment, arriving at five potential dimensions to the FLE corporate identity construct. These are scrutinised against existing corporate identity definitions and models to arrive at a definition for the construct. In reviewing the corporate identity, services marketing, branding and organisational psychology literature, a theoretical model is developed for FLE corporate identity, which is empirically and quantitatively tested, with FLEs in seven stores of a major national retailer. Following rigorous construct reliability and validity testing, the 601 usable responses are used to estimate a confirmatory factor analysis and structural equation model for the study. The results for the individual hypotheses and the structural model are very encouraging, as they fit the data well and support a definition of FLE corporate identity. This study makes contributions to the branding, services marketing and organisational psychology literature, but its principal contribution is to extend the corporate identity literature into a new area of discourse and research, that of FLE corporate identity

The role of ECL2 in CGRP receptor activation:a combined modelling and experimental approach

The calcitonin gene-related peptide (CGRP) receptor is a complex of a cal-citonin receptor-like receptor (CLR), which is a family B G-protein-coupled receptor (GPCR) and receptor activity modifying protein 1. The role of the second extracellular loop (ECL2) of CLR in binding CGRP and coupling to Gs was investigated using a combination of mutagenesis and modelling. An alanine scan of residues 271-294 of CLR showed that the ability of CGRP to produce cAMP was impaired by point mutations at 13 residues; most of these also impaired the response to adrenomedullin (AM). These data were used to select probable ECL2-modelled conformations that are involved in agonist binding, allowing the identification of the likely contacts between the peptide and receptor. The implications of the most likely structures for receptor activation are discussed. © 2013 The Authors.

Modelling and simulation of biomass gasification in a circulating fluidized bed reactor

Computational Fluid Dynamics (CFD) has found great acceptance among the engineering community as a tool for research and design of processes that are practically difficult or expensive to study experimentally. One of these processes is the biomass gasification in a Circulating Fluidized Bed (CFB). Biomass gasification is the thermo-chemical conversion of biomass at a high temperature and a controlled oxygen amount into fuel gas, also sometime referred to as syngas. Circulating fluidized bed is a type of reactor in which it is possible to maintain a stable and continuous circulation of solids in a gas-solid system. The main objectives of this thesis are four folds: (i) Develop a three-dimensional predictive model of biomass gasification in a CFB riser using advanced Computational Fluid Dynamic (CFD) (ii) Experimentally validate the developed hydrodynamic model using conventional and advanced measuring techniques (iii) Study the complex hydrodynamics, heat transfer and reaction kinetics through modelling and simulation (iv) Study the CFB gasifier performance through parametric analysis and identify the optimum operating condition to maximize the product gas quality. Two different and complimentary experimental techniques were used to validate the hydrodynamic model, namely pressure measurement and particle tracking. The pressure measurement is a very common and widely used technique in fluidized bed studies, while, particle tracking using PEPT, which was originally developed for medical imaging, is a relatively new technique in the engineering field. It is relatively expensive and only available at few research centres around the world. This study started with a simple poly-dispersed single solid phase then moved to binary solid phases. The single solid phase was used for primary validations and eliminating unnecessary options and steps in building the hydrodynamic model. Then the outcomes from the primary validations were applied to the secondary validations of the binary mixture to avoid time consuming computations. Studies on binary solid mixture hydrodynamics is rarely reported in the literature. In this study the binary solid mixture was modelled and validated using experimental data from the both techniques mentioned above. Good agreement was achieved with the both techniques. According to the general gasification steps the developed model has been separated into three main gasification stages; drying, devolatilization and tar cracking, and partial combustion and gasification. The drying was modelled as a mass transfer from the solid phase to the gas phase. The devolatilization and tar cracking model consist of two steps; the devolatilization of the biomass which is used as a single reaction to generate the biomass gases from the volatile materials and tar cracking. The latter is also modelled as one reaction to generate gases with fixed mass fractions. The first reaction was classified as a heterogeneous reaction while the second reaction was classified as homogenous reaction. The partial combustion and gasification model consisted of carbon combustion reactions and carbon and gas phase reactions. The partial combustion considered was for C, CO, H2 and CH4. The carbon gasification reactions used in this study is the Boudouard reaction with CO2, the reaction with H2O and Methanation (Methane forming reaction) reaction to generate methane. The other gas phase reactions considered in this study are the water gas shift reaction, which is modelled as a reversible reaction and the methane steam reforming reaction. The developed gasification model was validated using different experimental data from the literature and for a wide range of operating conditions. Good agreement was observed, thus confirming the capability of the model in predicting biomass gasification in a CFB to a great accuracy. The developed model has been successfully used to carry out sensitivity and parametric analysis. The sensitivity analysis included: study of the effect of inclusion of various combustion reaction; and the effect of radiation in the gasification reaction. The developed model was also used to carry out parametric analysis by changing the following gasifier operating conditions: fuel/air ratio; biomass flow rates; sand (heat carrier) temperatures; sand flow rates; sand and biomass particle sizes; gasifying agent (pure air or pure steam); pyrolysis models used; steam/biomass ratio. Finally, based on these parametric and sensitivity analysis a final model was recommended for the simulation of biomass gasification in a CFB riser.

Noise modelling and outlier detection in satellite scatterometer data

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Statistical models for rainfall:characterisation and forecasting

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Modelling and simulation strategies for the electric systems of large passenger aircraft

The simulation of a power system such as the More Electric Aircraft is a complex problem. There are conflicting requirements of the simulation, for example in order to reduce simulation run-times, power ratings that need to be established over long periods of the flight can be calculated using a fairly coarse model, whereas power quality is established over relatively short periods with a detailed model. An important issue is to establish the requirements of the simulation work at an early stage. This paper describes the modelling and simulation strategy adopted for the UK TIMES project, which is looking into the optimisation of the More Electric Aircraft from a system level. Essentially four main requirements of the simulation work have been identified, resulting in four different types of simulation. Each of the simulations is described along with preliminary models and results.

Performance modelling and analysis of multiple coexisting IEEE 802.15.4 wireless sensor networks

With the features of low-power and flexible networking capabilities IEEE 802.15.4 has been widely regarded as one strong candidate of communication technologies for wireless sensor networks (WSNs). It is expected that with an increasing number of deployments of 802.15.4 based WSNs, multiple WSNs could coexist with full or partial overlap in residential or enterprise areas. As WSNs are usually deployed without coordination, the communication could meet significant degradation with the 802.15.4 channel access scheme, which has a large impact on system performance. In this thesis we are motivated to investigate the effectiveness of 802.15.4 networks supporting WSN applications with various environments, especially when hidden terminals are presented due to the uncoordinated coexistence problem. Both analytical models and system level simulators are developed to analyse the performance of the random access scheme specified by IEEE 802.15.4 medium access control (MAC) standard for several network scenarios. The first part of the thesis investigates the effectiveness of single 802.15.4 network supporting WSN applications. A Markov chain based analytic model is applied to model the MAC behaviour of IEEE 802.15.4 standard and a discrete event simulator is also developed to analyse the performance and verify the proposed analytical model. It is observed that 802.15.4 networks could sufficiently support most WSN applications with its various functionalities. After the investigation of single network, the uncoordinated coexistence problem of multiple 802.15.4 networks deployed with communication range fully or partially overlapped are investigated in the next part of the thesis. Both nonsleep and sleep modes are investigated with different channel conditions by analytic and simulation methods to obtain the comprehensive performance evaluation. It is found that the uncoordinated coexistence problem can significantly degrade the performance of 802.15.4 networks, which is unlikely to satisfy the QoS requirements for many WSN applications. The proposed analytic model is validated by simulations which could be used to obtain the optimal parameter setting before WSNs deployments to eliminate the interference risks.

Optimisation of two-stage raman converter based on phosphosilicate core fibre:Modelling and experiment

Parameter optimization of a two-stage Raman fibre converters (RFC) based on phosphosilicate core fiber was presented. The optimal operational regime was determined and tolerance of the converter against variations of laser parameters was analyzed. Converter was pumped by ytterbium-doped double-clad fibre laser with a maximum output power of 3.8W at 1061 nm. A phosphosilicate-core RFC with enhanced performance was fabricated using the results of numerical modelling.

A modelling and simulation environment for self-aware and self-expressive systems

Self-awareness and self-expression are promising architectural concepts for embedded systems to be equipped with to match them with dedicated application scenarios and constraints in the avionic and space-flight industry. Typically, these systems operate in largely undefined environments and are not reachable after deployment for a long time or even never ever again. This paper introduces a reference architecture as well as a novel modelling and simulation environment for self-aware and self-expressive systems with transaction level modelling, simulation and detailed modelling capabilities for hardware aspects, precise process chronology execution as well as fine timing resolutions. Furthermore, industrial relevant system sizes with several self-aware and self-expressive nodes can be handled by the modelling and simulation environment.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.