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Gas-side fouling and corrosion problems occur in all of the energy intensive industries including the chemical, petroleum, primary metals, pulp and paper, glass, cement, foodstuffs, and textile industries. Topics of major interest include: (1) heat exchanger design procedures for gas-side fouling service; (2) gas-side fouling factors which are pres...
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... The second element is less important, as demonstrated here, moreover it is much easier to find values in the literature with limited variation between different sources. Indeed, in Table 7, we refer to the data provided by a NASA review [35] on thermal fouling resistance for large boilers depending on the fuel used and the service conditions; a work from Marner et al. [36] also report similar values. In the table the fouling factor are expressed in terms of thermal resistance in British units taken from [35] (2nd column), and also, for the sake of clarity, we convert it in terms of overall equivalent HTC expressed in SI units (3rd column) which is the parameter used for the CFD boundary condition, and finally in terms of equivalent thickness of fouling deposit layer assuming a reasonable conductivity of 1 [W/(m⋅K)] (4th column) to give an idea to the reader. ...
... Indeed, in Table 7, we refer to the data provided by a NASA review [35] on thermal fouling resistance for large boilers depending on the fuel used and the service conditions; a work from Marner et al. [36] also report similar values. In the table the fouling factor are expressed in terms of thermal resistance in British units taken from [35] (2nd column), and also, for the sake of clarity, we convert it in terms of overall equivalent HTC expressed in SI units (3rd column) which is the parameter used for the CFD boundary condition, and finally in terms of equivalent thickness of fouling deposit layer assuming a reasonable conductivity of 1 [W/(m⋅K)] (4th column) to give an idea to the reader. In our case, the most appropriate choice is the last service condition from Table 7 (not so much difference between NG and Refinery Gas operations in terms of fouling). ...
... However, the assumption of HTC = 0.7 kW/(m 2 ⋅K) is far from reality under given operating conditions, unless there is abnormal Table 6 Comparison of furnace output data between testing, 1-D code and CFD results. Table 7 Recommended fouling factors and cleaning provisions for various fuels and service conditions from [35]. The fitting curves are all in the form: ...
In the present study we develop a complete Computational Fluid Dynamics (CFD) modeling procedure suitable for accurate simulations of industrial boilers fed alternatively with gaseous and liquid fuels. The model is developed and validated by means of data from on-site testing.
Two different boilers are considered: a 6-burner steam generator of a refinery for the model definition, and a 32-burner thermal power plant boiler for validation, fed by flare-gas/natural-gas or Heavy-Fuel-Oil (HFO). Selected reliable experimental data coming from performance testing are used for both the set-up of the CFD simulations as well as to compute the Flue Exit Gas Temperatures (FEGTs) employed as validation criteria. The flare-gas testing on the 6-burner boiler allows us to accurately determine that a membrane wall emissivity around 0.60 is appropriate as a boundary condition for radiation. By a sensitivity analysis, the relevance of wall emissivity with respect to fouling thermal resistance on the overall heat transfer inside the furnace is established. For boilers alternatively operating with gaseous fuel and HFO a value of 2.8 kW/(m2·K) has been found appropriate. HFO testing on the 6-burner boiler provides data to develop the additional soot modeling, crucial to properly catch oil flame emissivity, based on the model of Khan and Greeves. This allows the matching of a mean soot mass fraction of 1%–3% in the flame zone, a range found by in-flame measurements in the literature and confirmed in the present study by overall heat exchange data in the whole furnace coming from HFO boiler testing. Finally, the 32-burner boiler is considered for validation: using the same procedure and parameters, excellent agreement is found between experimental and CFD results, both on a 100% load natural gas and on a 107% load HFO performance testing.
The study demonstrates how field data can be used to validate CFD simulations and confirms that the use of physically meaningful parameters and models exempts from repeated tuning: no change is needed for emissivity and fouling thermal resistance between gaseous and liquid fuel operation, and even a simple soot modeling can be used, just ensuring physically consistent particulate concentration in the oil flame.
... The r w can be calculated for flat wall and cylindrical walls using Eqs. (5) and (6), respectively. ...
A heat exchanger is a unit operation used to transfer heat between two or more fluids at different temperatures. There are many different types of heat exchangers that are categorized based on different criteria, such as construction, flow arrangement, heat transfer mechanism, etc. Heat exchangers are optimized based on their applications. The most common criteria for optimization of heat exchangers are the minimum initial cost, minimum operation cost, maximum effectiveness, minimum pressure drop, minimum heat transfer area, minimum weight, or material. Using the data modeling, the optimization of a heat exchanger can be transformed into a constrained optimization problem and then solved by modern optimization algorithms. In this chapter, the thermal design and optimization of shell and tube heat exchangers are presented.
... Compared with results obtained at AFR of 26.5064, a level of improvement in exergy efficiency and a reduction in irreversibility are achievable at AFR of 16.1. However, some major limitation to the actual improvement achievable includes maintenance culture, fouling caused by the boiler's age, and other forms of heat losses that are not considered in this study (Johnson et al. 2008;Marner and Suitor 1983;Singh et al. 2018). In other words, the simulation outcomes based on the simplifying assumptions made indicate better performance at AFR of 16.1. ...
The possibility of efficiently utilizing various fossil fuels that foster economic competitiveness is desirous in industrial boiler operations for uninterrupted and sustainable power generation. In this study, an oil-fired and gas-fired boiler designed to produce 653900 kg/h of superheated steam and 585450 kg/h of reheat steam at a temperature of 540 °C to generate electricity was simulated using HYSYS V 8.8. At a varied air-fuel mass ratio, the boiler’s comparative performance when it fires natural gas and low pour fuel oil (LPFO) was conducted using a number of thermodynamic performance criteria. An exergy-based costing of running the boiler with both fuels was also carried out. For the samples of natural gas and LPFO considered in this study, an air-fuel ratio slightly above 16.1 should be adequate for the fuel combustion. Air-fuel ratio requirement below or far above 16.1 may portend malfunctioning boiler components or even an ineffective boiler design. Furthermore, at AFR of 16.1, it costs US 7.22E-06/kJ for the case of firing LPFO. These values reflect an improvement on the economic implications at AFR of 26.5, predominantly operational in the power plant. However, a form of subsidy (like a reduction in LPFO import duties) which lowers the overhead costs of power generation using LPFO will be required to make LPFO an attractive backup alternative to natural gas in instances where there is short or nonsupply of natural gas.
... On the downside, the potential efficiency and cost benefits of a HAT or a CCGT system heavily rely on a number of heat exchanger units as part of the cycle. These heat exchangers are susceptible to fouling which may cause notable penalties on their effectiveness and have a detrimental effect on the thermal performance of the whole system [18][19][20][21]. More specifically, various types of deposits on the inner walls of the heat exchangers can reduce its heat transfer coefficient with notable effects on the overall effectiveness of the unit. ...
... The level of deterioration is characterised by the Degradation Coefficient (DC) defined in Eq.(1). The fouling resistance of both sides and the pressure drop penalty coefficient are normalised against the reference values [20,[28][29][30] shown in Table 3. For the current analysis, the imposed DC ranges from 0 to 2.0 which drives the cycle to offdesign, while the turbine inlet temperature of 1600 K was kept constant across both combustors. ...
This paper aims to analyse the impact of air-water heat exchanger's degradation on the performance of a reheated humid air turbine system for power generation applications. A number of thermal models to simulate the performance of the various sub-systems was put together and validated against experimental data. The performance degradation of the heat exchangers is characterised by means of a degradation coefficient, which is used to drive the cycle into off-design and part-load conditions when degradation is accounted for. Three heat exchanger design scenarioswere investigated, namely a low, a medium and a high effectiveness in order for the impact of the degradation penalties on cycle thermal efficiency to be determined. The performance deterioration of the heat exchangers is also analysed from an exergetic point of view in order to identify the key sources that penalise the thermal efficiency of the humid air turbine system. The degradation analysis shows that typical levels of intercooler deterioration cause notable penalties in the cycle performance, reducing its thermal efficiency and power output by 1.8 percentage points and 28% respectively compared to the un-degraded operation. The exergy analysis showed that the deterioration of the intercooler also penalises the efficiency of the low pressure compressor and reheater, which contribute to the performance penalty of the cycle too. It is also found that the degradation of the intercooler can also lead to operability penalties at the low pressure compressor by reducing its surge margin. The effects of the deterioration of the aftercooler and economiser were found to only have a weak effect on the system's performance. The outcome of the work constitutes a step forward in understanding of the performance behaviour of an advanced cycle when heat exchanger degradation is present.
... In the design of heat exchangers, fouling factors are often used, and additional surface areas should be considered in order to make up the degradation of heat transfer performance caused by fouling. However, most of the fouling factors are based on experience [3,4]. So this method has certain limitations. ...
The issues of fouling, erosion and corrosion are commonly occurring phenomena on the flue gas heat exchangers for middle/low temperature waste heat utilization due to the special properties of high ash content, viscous and corrosive components. How to solve these problems effectively has been the subject of many researches in recent years. This paper summarized the development of the simulations and experimental studies for the fouling, erosion and corrosion of heat exchangers. To begin with, the fundamental mechanisms, the prediction models and methods, the simulations with these models and relevant experiments of fouling, erosion and corrosion were introduced. In addition, the prediction processes of the fouling, erosion and corrosion rate were introduced by taking authors’ studies as illustrations among them. Finally, it should be noted that for the fouling, erosion and corrosion issues, there are still some key works to be done to better understand the fouling, erosion and corrosion mechanisms, and propose the novel heat exchangers for anti-fouling, anti-erosion and anti-corrosion. It would be desirable that the future heat exchanger designs can overcome the problems, and therefore to promote the development of technologies that can efficiently recovery the flue gas waste heat to improve the overall energy utilization efficiency.
... to guarantee the performance of engines, devices and machines all along their service life. The amount of research studies analyzing the degradation and efficiency losses of the equipment during their lifetime [2] has grown. Understanding the mechanisms involving deterioration, fouling formation and deposition is very important in this field. ...
... The other observation made is that, at some point of time, there is an increase in the value of heat transfer coefficient. This maybe because, fouling also considers the phenomenon of soot coming out of the surface [9], which we are unable to predict exactly at this point of time. ...
This paper studies the application of soft sensing (state estimation) in estimating the soot depositions in the boiler super heater sections of coal fired power plant. In purpose to find an appropriate dynamic indication for soot blowing in the super heater sections even in the unsteady state conditions, a mathematical model of the super heater section is modeled. The model is extended and solved to get a response to match the process behavior. We take an approach of kalman filtering to estimate the soot depositions. This estimation model is applied to two different super heater sections of a boiler and shown to produce, good results when tested with the plant measurement data. It also demonstrated how actually the soot blowing affects the efficiency of heat transfer. Finally the possibility of a better control of main steam temperature is being discussed. INTRODUCTION To achieve optimum boiler performance and efficiency, control of soot deposition is necessary. Soot blowing is a process to resolve this problem in a coal fired power plant. Usually soot deposition occurs in two levels, namely slagging at the down comer and riser (water Walls) where the radiation is the primary heat transfer medium, and fouling at the super heater sections. Typical indication for the furnace slagging appears indirectly to operator incase of an increase in spray flow at super heater sections. Slagging leads to reduction in heat absorption at water walls resulting in high flue gas and steam temperatures, leading to an increase in attemprator flow. But, for fouling there is no such indication for the operator. The soot blowing for super heater sections is done randomly based on operator's experience. In order to feed to an optimizing soot blower sequencer, with an indication of soot deposition in the super heater sections, an observer is designed. The other main benefit of fouling monitoring is in reducing the soot blowing medium i.e., blow down steam. In practice, heat flux meters and strain-gauges are used in power plants as an indirect measurement for soot accumu-lation. One of the short coming in using these sensors is the cost. It is also observed that, if two sensors are placed at same place they indicate different readings due to the randomness of fouling [3]. There are some distributed models [1], [7] for indicating the spatial distribution in fouling or slagging. But the main idea of these models is to find the amount of accumulation on the steel pipes. Physically the heat transfer efficiency is not only based on the amount of fouling but also on the physical properties of fouling [2]. For steady load demand, there are some indirect methods to calculate the overall dirtiness based on the exit gas temperature and boiler efficiency[3]. Figure 1. Heat exchanger with soot deposition
There remain major concerns over the increasing use and waste of materials and energy resources in multiple manufacturing sectors. To address these concerns, some manufacturers have begun to align their R&D efforts with the circular economy principles: Reduce, Reuse, Recycle and Replace (RRRR). Focusing on advanced composites manufacturing sector, this paper presents an innovative approach for process design and analysis of a new waste heat recovery system for carbon fiber manufacturing. Namely, the stabilization process is known to be one of the most critical steps in the production of carbon fibers, as it consumes the most energy, has the largest factory footprint, is a complex system composed of many components, and is the largest capital investment within the factory line. The heat recovery system in this step of the manufacturing can notably reduce energy consumption, emission, cost, and conversion time, while aiming to maintain the mechanical properties of the final product. Here, via an actual industry-scale fibre production setting, the energy consumption factors were obtained and used to model the total energy and its balance in the thermal stabilization step. Two machine learning approaches, Artificial Neural Network and Non-Linear Regression were then constructed to predict the energy consumption. Results suggested that using the recovery system by means of a heat exchanger, can yield over 62.7 kW recovery, corresponding to 64% of total exhausted energy from the entire process. The electric energy consumption was reduced from 73.3 kW to 10.2 kW, which corresponded to an 86% improvement in the total energy efficiency. The model also confirmed that, by preheating the make-up air with the recovered energy, the energy performance index of the thermal stabilization can be increased from 0.08 to 0.44, along with a reduction in the process carbon footprint by 28.5 t/y. This is especially crucial as we are turning on smart digitalisation in manufacturing inspired by industry 4.0 concept.
