C. K. Tan

Use of artificial intelligence techniques for optimisation of co-combustion of coal with biomass

AbstractThe optimisation of burner operation in conventional pulverised-coal-fired boilers for co-combustion applications represents a significant challenge This paper describes a strategic framework in which Artificial Intelligence (AI) techniques can be applied to solve such an optimisation problem. The effectiveness of the proposed system is demonstrated by a case study that simulates the co-combustion of coal with sewage sludge in a 500-kW pilot-scale combustion rig equipped with a swirl stabilised low-NOx burner. A series of Computational Fluid Dynamics (CFD) simulations were performed to generate data for different operating conditions, which were then used to train several Artificial Neural Networks (ANNs) to predict the co-combustion performance Once trained, the ANNs were able to make estimations of unseen situations in a fraction of the time taken by the CFD simulation. Consequently, the networks were capable of representing the underlying physics of the CFD models and could be executed efficien...

Effect of fuel characteristics and operating conditions on NOx emissions during fluidised bed combustion of high moisture biomass with coal

combustor over a wide range of operating conditions. The wood chips were blended with the coal in 50/50 (wt/wt) ratio. The overall moisture content of the blends was 10?3 and 30?3%. The pulp was blended with the coal in 70/30, 60/40 and 50/50 (coal/pulp, wt/wt) ratios. The overall moisture content of the blends was 25?2, 31?8 and 38?3% respectively. Emissions of NOx for the tests are compared with those from coal only firing. The emissions of NOx are found to be lower during cofiring as compared to coal only firing due to lower nitrogen content of biomass fuels. The emissions increased with increase in bed temperature when only coal was fired but decreasde with increase in bed temperature when coal pulp blends were cofired. Moreover, the emissions increase with increase in the amount of excess air. The effect of moisture on the emissions is found to be negligible. The effect of individual fuel characteristics on NOx emissions could not be quantified due to interference of other operating parameters.

Development of an intelligent flame monitoring system for steel reheating burners

This article describes the development of a system to indirectly monitor the combustion characteristics of individual burners based on measurement and analysis of the signals detected from photodiodes detecting flame radiation signals. A series of experiments were conducted on a 500 kW pilot-scale furnace and on two 4 MW industrial burners located in two steel reheating furnaces. The flame radiation signals were monitored using a lens that transmitted the flame radiation to ultraviolet, visible and infrared photodiodes through a trifurcated optical fibre. The experiments covered a wide range of burner operating conditions including; variations in the burner load and excess air levels and simulations of burner imbalance. The relationships between the dynamic flame radiation signals and the burner operating parameters and conditions were made off-line using neural network models. The present work indicates that the measurement of flame radiation characteristics, coupled with neural networks, provides a promising means of monitoring and adjusting burner performance.

An Improved Mathematical Model to Predict the Real Time Transient Performance of a Large Steel Reheating Furnace

This paper describes the development and application of a two-dimensional model based on the zone method of radiation analysis to simulate the thermal behaviour of a large steel reheating furnace at Tata Steel. The furnace has a maximum throughput of 160 t/hr of steel blooms and is equipped with a total of 75 burners firing a mixture of combustible fuel gases arising from the steelmaking process. The model was validated for two different furnace throughput rates using experimental and plant data supplied by Tata Steel. Following validation it was then used to assess the furnace performance at a wider range of throughputs as well as examining the effect of the distribution of heat input along the furnace on furnace efficiency and stock temperature uniformity. The model differs from previous work since it takes into account the radiation interchange between the top and bottom firing sections of the furnace and also allows for enthalpy exchange due to the flows of combustion products between these sections. The results to-date showed that the model predictions are in good agreement with typical heating profile of the stock encountered in the actual furnace and are potentially suitable for incorporation into a model based furnace control system due to its relatively fast computing time.Copyright

Development of a Spectral Radiation Model to Predict the Transient Performance of a Metal Reheating Furnace

The use of computational fluid dynamics for simulation of combustion processes has made significant advances in recent years particularly for the design of individual burners and the prediction of pollutant formation and emission. However, the computational requirements of these models can still be too great for overall furnace thermal design purposes particularly if the transient performance is required. Thermal radiation is usually the dominant mode of heat transfer to the load or stock in industrial fuel-fired furnaces since the contribution of convection is relatively small. Thus prediction of the thermal performance of a furnace requires an accurate calculation of the complex radiation interchange between the surfaces and the combustion products. This can be achieved by the so-called Hottel zone method of radiation analysis and as a result this method has been applied to a wide range of industrial heating processes. The method sub-divides the non-isothermal furnace enclosure into a series of isothermal volume and surface zones and energy balances are then formulated and solved simultaneously for each zone. The computational demands are modest so that the process can be repeated successively throughout a period of furnace operation to simulate the transient behaviour of the system. However in these models all the surfaces are usually assumed to be grey and the radiation properties of the combustion products are normally represented by a mixture of grey and clear gases. These assumptions can lead to errors in the predictions, in applications such as the installation of high emissivity coatings on the furnace lining, where it is necessary to allow for the spectral variation in surface emissivity and the banded nature of the radiation properties of carbon dioxide and water vapour in the combustion gases. Consequently the proposed paper describes the development of “spectral” zone model, which takes these effects into account, to predict the transient performance of a furnace heating steel bars to a discharge temperature of 1200°C. The model also allows for broadening of the spectral bands with changes in the temperature of the combustion products. The work differs from that in previous papers on this type of model, which have been confined to steady-state simulations and do not allow for broadening. Finally the model is applied to investigate the effect of coating the refractory lining of the furnace with high emissivity materials.Copyright

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.

Detecting Burner Instabilities Using Joint-Time Frequency Methods Whilst Co-Firing Coal and Biomass

Conventional coal-fired burners are designed to operate within specific limits that, in part, result from the need to efficiently burn the fuel. These designs have been developed to ensure stable combustion, lower NOx emissions and increase the combustion efficiency through techniques such as air staging and adding swirl to the combustion air. Recent requirements to reduce CO2 emissions from coal-fired boiler plant has focussed on the co-firing of biomass, primarily wood, either by delivering the pulverised biomass with the coal or through separate burners. To date this approach has typically taken place at substitution levels of around 5% by mass and at these levels the operation of the burners and boiler is not adversely affected. However, as the proportion of biomass increases the fuel characteristics of the blend moves further away from the burner design parameters. This can lead to combustion instabilities and in extreme cases extinction of the flame. In order to co-fire higher concentrations of biomass a system or technique is required that can detect the onset of these instabilities and warn before the combustion conditions become dangerous. In this paper a novel technique based around the Wigner-Ville transform is presented that shows promise at being able to temporarily resolve the conditions that could result in the onset of burner instabilities for three cases; the first will present results from the combustion of 100% bituminous coal, whilst the second and third cases will present the results from experiments where the proportion of biomass was set at 10% and 20% by mass with the same bituminous coal. In each experiment the secondary combustion air was first reduced from a nominal stable condition and then subsequently increased from the same stable condition. It was found that the Wigner transform was able to resolve flicker frequency changes as the airflow rate was reduced. These changes were subsequently used in a neural network to automatically detect drastic changes in the air flow rates to the burner and could provide a means by which utility operators could detect dangerous flame instability conditions in real-time.Copyright

Monitoring and Diagnosis of Steel Reheating Burners

This paper describes the development of an intelligent Flame Diagnostic System which is able to monitor the combustion characteristics of individual burners based on direct measurement and analysis of the flame radiation signals. A series of experiments were conducted on a 500 kW pilot-scale furnace fitted with both a single burner and also two burners firing in a regenerative manner. The experiments covered a wide range of burner operating conditions including variations in the burner firing-rate and excess air level. A fibre-optic based optical instrument, incorporating broad ultraviolet, visible and infrared photo diodes was developed and used to acquire the dynamic flame signals through a data acquisition system. These flame signals were then analysed off-line, using simple signal processing methods, to yield a set of flame features. Correlation of these flame features with respect to the excess air level and NOx emissions were made using neural network models. The present work indicates that the measurement of flame radiation characteristics, coupled with advanced data modelling techniques such as neural networks, provides a promising means of monitoring and optimising burner performance.Copyright

Development of a Monitoring System for Near Burner Slag Formation

A series of experiments on two different coals at a range of burner conditions have been conducted to investigate the behaviour of pf coal combustion on a 150kW pulverised fuel (pf) coal burner with a simulated eyebrow (a growth of slag in the near burner region). The simulation of a burner eyebrow was achieved by inserting an annulus of refractory material immediately in front of the face of the original burner quarl. Results obtained from monitoring the infrared (IR) radiation and sound emitted by the flame were processed into a number of features which were then used to train and test a self organising map neural network. Results obtained from the neural network demonstrated a classification success, never lower than 99.3%, indicate that it is not only possible to detect the presence of an eyebrow by monitoring the flame, but it is also possible to give an indication as to its size, over a reasonably large range of conditions.© 2002 ASME