Alex Chong

Integration of Power to Methane in a waste water treatment plant – A feasibility study

The integration of a biomethanation system within a wastewater treatment plant for conversion of CO2 and H2 to CH4 has been studied. Results indicate that the CO2 could be utilised to produce an additional 13,420m3/day of CH4, equivalent to approximately 133,826kWh of energy. The whole conversion process including electrolysis was found to have an energetic efficiency of 66.2%. The currently un-optimised biomethanation element of the process had a parasitic load of 19.9% of produced energy and strategies to reduce this to <5% are identified. The system could provide strategic benefits such as integrated management of electricity and gas networks, energy storage and maximising the deployment and efficiency of renewable energy assets. However, no policy or financial frameworks exist to attribute value to these increasingly important functions.

Damage Characterisation of Carbon Fibre Reinforced Composite Plate Using Acoustic Emission

Acoustic Emission (AE) is a sensitive technique which can be used to characterise damage in high strength composite plate. This paper describes an extension to an earlier piece of research work carried out by the ERC which resulted in the successful development of a novel source location methodology for the said material. The previous work concentrated on the source location in plate-like composite structures using acoustic emission. The work presented in this paper focuses on establishing the correlation between the different damage types suffered in the material namely de-lamination, matrix cracking, fibre rupture and stringer to skin debonding with key signal features of the AE activities. Controlled bending tests were initially carried out on laterally grooved slender composite specimens to progressively propagate damage in the weakened region of these specimens. The composite laminate plate itself is made from 16 plies of carbon fibre twill weaved in an epoxy matrix with bidirectional fibre alignments in the 0° and 90° directions with 60/40 fibre-matrix volume composition. These prepared samples were fully instrumented with broad band (100 kHz to 1MHz) Physical Acoustic AE sensors linked to the necessary signal conditioning hardware. The AE events were recorded using a high speed DAQ card accessed by customised software written in LabVIEWTM. Gathered raw data were analysed off-line for key signal features including energy and frequency contents and subsequently correlated to actual damage types. It can be concluded from the empirical evidence that feature vectors are distinct to the type of damage. Results gathered from additional test on the progressive skin-stringer debonding of the same material to failure confirmed the uniqueness of the AE feature trends. An integrated system which is capable of both in-situ location of compromised sites and the diagnostic of flaw types in composite plate can potentially find engineering applications including the structural health monitoring of composite aircraft parts.

Development of fuzzy based methodology to commission co-combustion of unprepared biomass on chain grate stoker fired boilers

AbstractThis paper describes the development of an intelligent commissioning system to enable operators to maximise the utilisation of unprepared biomass by combusting the biomass with the minimum amount of support fuel to achieve a desired boiler output and thermal efficiency on chain grate stoker fired boilers. Tests were conducted on a 0·8 MWth chain grate stoker fired hot water boiler to investigate the combustion of different types of biomass blended with a support fuel over a wide range of boiler operating conditions and biomass moisture contents. The commissioning system was developed using fuzzy logic and expert system type rules developed while gathering the experimental data. The system was validated on untested blends of unprepared biomass with two support fuels where it was shown that it is possible to efficiently burn unprepared, high moisture content biomass with a support fuel on a chain grate stoker. This system could enable operators of chain grate stoker fired boilers to maximise the use...

Combustion optimisation of stoker fired boiler plant by neural networks

AbstractThis paper is concerned with the development of a neural network based controller (NNBC) for chain grate stoker fired boilers. The objective of the controller was to increase combustion efficiency and maintain pollutant emissions below future medium term legislation. Artificial neural networks (ANNs) were used to estimate future emissions from and control the combustion process. Initial tests at Casella CRE Ltd demonstrated the ability of ANNs to characterise the complex functional relationships which subsisted in the data set, and utilised previously gained knowledge to deliver multistep ahead predictions. This technique was built into a carefully designed control strategy, which fundamentally mimicked the actions of an expert boiler operator, to control an industrial chain grate stoker at HM Prison Garth, Lancashire. Test results demonstrated that the developed novel NNBC was able to optimise the industrial stoker boiler plant whilst keeping the excess air level to a minimum. In addition, the AN...

Experimental analysis of gas to water two phase closed thermosyphon based heat exchanger

P structures have been studied since the 1960’s by many scholars, most prominently, by Prof. Mead of the Institute of Sound and Vibration, Southampton University in the UK. In 2000, the author embarked on a journey with periodic structures, it took quite a while until he understood how it works, after those years, he realized, at last, that have not yet reached a good understanding! In this talk, he will be presenting an understanding of the concepts of propagation and stop bands widely used in the world of periodic structures, the forward and reverse approaches for analysis of periodic structures, conclusions of experimental and numerical research conducted by the author with his colleagues and students on periodic beams and plates, and finally, a general conclusion on the finding of the research.N play an important role in determining the hardness, fracture toughness, and strength of materials. Nanoparticles with size ranging from 1-100 nm are beginning to play a strong role as additives in metals and alloys, contributing to their high hardness and low plasticity. This presentation focuses on a class of nanomaterials called ‘nanodiamond’. Nanodiamond additives have been shown to improve tribological properties and enhance mechanical properties in varied classes of materials such as polymer composites, engine oils and lubricants. Although experimentally shown to improve mechanical properties, the nanoscale origins of how these nanoparticles interact with their host atoms and molecules is unknown. In this presentation, we explore scanning probe microscopy as a tool to study interaction between nanodiamond particles, throwing greater light on interaction forces at the nanoscale. As an example, using force-distance spectroscopy, we show that nanodiamonds show reduced adhesion with a scanning probe tip, thus making them effective as lubricant additives.Wickless heat pipes have been attracting increased attention in the last two decades due to their reliability and high heat transfer potential per unit area. Their most common application is in the process industry, when coupled to waste heat recovery devices. Heat pipe based heat exchangers offer many advantages when compared with conventional waste heat recovery systems; advantages that are detailed in the current work. The design of such devices, however, is not a straightforward process due to the complex modes of heat transfer mechanisms involved. In this paper, the characterisation of a cross-flow heat pipe based heat exchanger is studied experimentally, using correlations currently available in literature. A design tool with the purpose of predicting the performance of the test unit was also developed and validated through comparison with the experimental results. The design tool was validated with the use of a purpose-built experimental facility.F is the process by which a liquid or gas flows through a particulate solid phase, keeping it under suspension and showing fluid-like behavior. Among applications of FBs, process of energy conversion such as combustion and gasification are the focus of much research nowadays. Research in Computational Fluid Dynamics (CFD) applied to the simulation of FBs has grown in the last few years in view of the need to perform a large number of tests to define appropriate, if not optimal, operational conditions. CFD could provide a low cost test bench in FBs applications. Nevertheless, the mathematical modeling of multiphase and often reactive flows in this kind of system is indeed very complex. A possible approach that is much employed is the Euler-Granular modeling, which describes solid and gaseous phases as interpenetrating continua. Furthermore, the stresses of the solid phase, are translated into a stress tensor in the form of a fluid stress tensor, with parameters such as pressure and viscosity obtained from the Kinetic Theory of Granular Flows (KTGF). KTGF is derived from the kinetic theory for dense gases, extrapolated to describe the behavior of small particles inserted in a fluid medium. In this project we have studied the features of the Euler-Granular model and the influence of model parameters in numerical results of flows in bubbling and circulating FBs. We have employed factorial plans to quantify the influence of restitution and specularity coefficients and gas-solid drag laws, and also the interaction among these parameters.C parallel manipulator (CPM) is a 3-Dof parallel manipulator that consists of a platform which is connected to the fixed base by limbs in three perpendicular planes. In this paper smooth singularity free trajectory planning optimization of the CPM is investigated. The forward and inverse kinematic equations of CPM are obtained by the robot geometrical constraints and its dynamic equations of motion are derived using Kane’s method. Considering the actuators’ limitation and kinematical constraints originated from the closed-chain nature of the CPM, an algorithm for trajectory definition and optimization for the robot end-effector is proposed using B-Spline functions without requiring any information about the geometry of CPM endeffector. The total required energy, maximum actuator’s jerk and total time of motion are defined as three objective functions in terms of B-Spline parameters and non-dominated sorting genetic algorithm-II (NSGA-II) is used to solve the nonlinear constrained multi-objective optimization problem and calculate the optimal values of the trajectory parameters. Finally, the proposed algorithm is implemented in MATLAB software and its results are demonstrated and discussed which confirm the effectiveness of the presented method.The present study deals with the force and stress distribution within the anteromedial (AM) and posterolateral (PL) bundles of the anterior cruciate ligament (ACL) in response to an anterior tibial load with the knee at full extension was calculated using a validated three dimensional finite element model (FEM) of a human ACL. The interaction between the AM and PL bundles, as well as the contact and friction caused by the ACL wrapping around the bone during knee motion, were included in the model. The AM and PL bundles of the ACL were simulated as incompressible homogeneous and isotropic hyperelastic materials. The validated FEM was then used to calculate the force and stress distribution within the ACL under an anterior tibial load at full extension. The AM and PL bundles shared the force, and the stress distribution was non-uniform within both bundles with the highest stress localized near the femoral insertion site. The contact and friction caused by the ACL wrapping around the bone during knee motion played the role of transferring the force from the ACL to the bone, and had a direct effect on the force and stress distribution of the ACL. This validated model will enable the analysis of force and stress distribution in the ACL in response to more complex loading conditions and has the potential to help design improved surgical procedures following ACL injuries.

Classification of delamination and matrix cracking in carbon fibre composite plates using Acoustic Emission (AE)

Recent publications show that there is an increasing interest in the aircraft industry in monitoring the actual condition of a structure in real time and while the structure is in service. It is hoped that this Structural Health Monitoring (SHM) could make some regular inspections unnecessary and allow maintenance only when required. This is particularly important for CFRP structures for which aircraft manufacturers are increasingly interested. For these new composite structures where the experience of fatigue failure is relatively low, this technique could potentially be economical and improve the safety of the structures. Acoustic Emission is reported to be sensitive to the four failure types in composite materials, namely matrix cracking, delamination, debonding and fibre fracture. These failure modes can have different impacts on structural integrity and it is therefore of interest to identify these failure types before further maintenance steps are conducted. This report discusses different features in AE signals which can be used to identify the actual flaw type. These features were then applied to AE data collected from two different experiments on carbon fibre composite plates. These experiments were designed to induce the two different failure modes of matrix cracking and delamination. The data collected was used to train a neural network to recognise the two failure modes.Copyright

The Effect of Installing Porous Refractory Panels on the Transient Start Up Performance of a Gas-Fired Reheating Furnace

The replacement of part of a conventional refractory lining in a furnace by a porous ceramic panel can enhance the thermal efficiency and increase the furnace throughput. If the hot furnace exhaust gases are passed through the panel (instead of leaving through the normal exhaust) heat is transferred, largely by convection, to the fine porous structure. Most of the heat which is recovered in the porous refractory in this fashion is then re-radiated back into the furnace chamber so that the overall radiative heat transfer to the load is substantially enhanced. The paper describes the development, validation and application of a mathematical model which simulates the installation of such a panel in an intermittently operated, gas-fired furnace heating steel bars to temperatures of approximately 1200°C. The overall model iteratively linked a sub-model of the flow and heat transfer through the porous section with a transient zone model of the radiation heat transfer in the furnace chamber. This procedure is then repeated sequentially throughout the period of the furnace operating cycle to predict the overall thermal performance of the furnace. The model was validated by measurements obtained during a series of tests on a gas-fired furnace. The predicted load temperatures and furnace energy consumptions were in good agreement with the corresponding measurements and indicated that reductions in energy consumption of up to 20% can be obtained depending upon the method of operating the furnace. Following the successful validation of the model it was then employed to predict the thermal behaviour of a small furnace heating steel bars or billets from a “cold start up”. The radiative heat transfer to the load was significantly enhanced throughout the heating period and this led to substantial improvements in the thermal efficiency and reductions in the time required to heat the load to its specified discharge temperature.Copyright

Neural Network Modeling and Control of Stoker-Fired Boiler Plant

The work described in this paper aims to address the development of a Neural Network Based Controller (NNBC) to control chain grate stoker fired boilers. Artificial Neural Networks (ANNs) were used to estimate future emissions from and control the combustion process. The resultant ANNs were able to characterise the dynamics of the process and delivered rational multi-step-ahead predictions wth test data collected at an industrial chain grate stoker at HM Prison Garth, Lancashire. This technique was built into a carefully designed control strategy, to control the industrial stoker. Test results showed that the developed NNBC was able to optimise the industrial stoker boiler plant whilst delivering the load demand required and in so doing, the NNBC also managed to maintain low pollutant emissions.© 2007 ASME