Novel predictive tools for design of radiant and convective sections of direct fired heaters

Bahadori, Alireza; Vuthaluru, Hari

doi:10.1016/j.apenergy.2009.11.028

Cited by 27 publications

(10 citation statements)

References 16 publications

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“…To do so, the mathematical model of fired heater (section 2.1.1) and direct method equations for calculating thermal efficiency are used to obtain the design and performance parameters of the fired heater. Compared to previous estimation methods [26,28], the indirect method gives the best prediction with a deviation of 2.22% from experimental values.…”

Section: Model Validationmentioning

confidence: 76%

“…To evaluate applying indirect method for estimating heater efficiency, the thermal efficiency of mentioned gas-fired heater [17] is calculated and compared with that of experimental methods proposed by previous design models [26,28], which is presented in Table 6. In these studies [26,28], the thermal efficiency of the fired heater is calculated using the direct method, which depends on stack temperature and excess air fraction. To do so, the mathematical model of fired heater (section 2.1.1) and direct method equations for calculating thermal efficiency are used to obtain the design and performance parameters of the fired heater.…”

Section: Model Validationmentioning

confidence: 99%

“…Moreover, these studies have employed a direct method in their design model to calculate thermal efficiency, which depends on stack temperature and excess air fraction. The accuracy of mentioned methods for predicting thermal efficiency subsides with increased stack temperature and excess air fraction [28]. Therefore, the novelty of this work is to propose a new design model of fired heaters associated with the combustion sub-model.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multi-objective Optimal Design of Gas-fired Heater Based on Modified Design Model of Fired Heater Taking into Account Exergy, Economic and Environmental Factors

Saryazdi

Rezaei

Saboohi

et al. 2021

IJE

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Heaters are one of the central parts of natural gas reduction stations using turboexpanders to prevent the formation of hydrate and corrosion failure. This study intends to design a fired heater by applying a combustion sub-model to derive an optimal model for this kind of application. This model is developed to accurately consider all subsections of the fired heater namely radiation, convection, and shield sections, as well as flue gas composition, and its volume. Within this context, a multi-objective optimization is employed to identify the optimal design of the gas-fired heater in the natural gas reduction station for the Ramin power plant case study. The total economic and environmental costs, together with modified exergy efficiency, are selected as objective functions. Multi-criteria-decisionmaking-method is employed on Pareto frontiers optimal curve to suggest the optimal solution. Results show that the developed model can outperform previous models in thermal efficiency with relatively similar costs. Besides, the optimal point in Pareto suggested by the decision-making-method accounts for a higher modified exergy efficiency (1.3%) than the counterpart, which thermal efficiency is regarded as an objective function. At the same time, its total cost remained almost constant. The effects of changes in each of the design parameters on the objective functions are also evaluated.

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Section: Model Validationmentioning

confidence: 76%

Section: Model Validationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-objective Optimal Design of Gas-fired Heater Based on Modified Design Model of Fired Heater Taking into Account Exergy, Economic and Environmental Factors

Saryazdi

Rezaei

Saboohi

et al. 2021

IJE

View full text Add to dashboard Cite

show abstract

“…The following methodology (Bahadori and Vuthaluru, 2010a, 2010b, 2010c using MATLAB (version 7.6.0.324, MathWorks, Inc., Natick, Mass., USA) was applied to develop this correlation. First, configuration factor data (Drysdale, 2011) are correlated as a function of a parameters for different S parameter values, and then the calculated coefficients for these equations are correlated as a function of S parameter.…”

Section: Methodology For Development Of Novel Predictive Toolmentioning

confidence: 99%

Estimation of Configuration Factor for Radiation From a Rectangle to a Parallel Small Element of Surface Lying on the Perpendicular to a Corner of the Radiator

Bahadori

Zendehboudi

Zahedi

et al. 2013

Chemical Engineering Communications

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To calculate the radiant intensity at a point distant from a radiator, a geometrical or configuration factor must be used. If the temperature is known, then the emissive power can be calculated using the mean equivalent beam length, but before the radiant heat flux at a distance can be estimated, a configuration factor must be calculated. In this article a simple predictive tool is developed to estimate the configuration factor for a geometry including a receiving element lying on the perpendicular to one corner of a radiant rectangle. The results are found to be in excellent agreement with reported data in the literature with average absolute deviation being around 2%. The results can be used in follow up calculations to estimate heat fluxes on surfaces exposed to radiation. The tool developed in this study can be of immense practical value for engineers as a quick check on the configuration factor for a geometry including a receiving element lying on the perpendicular to one corner of a radiant rectangle without opting for any experimental trials. In particular, engineers would find the approach to be user-friendly with transparent calculations involving no complex expressions.

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“…Furthermore, applying artificial failures to inservice fired-heaters to acquire the necessary data is practically impossible [14,15]. In this case, mathematical models could be employed to investigate the effects of many different failures and firing rate scenarios on heat distribution inside the furnace and optimize the process conditions to cope with abnormal situations [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Flame Failures and Recovery in Industrial Furnaces: A Neural Network Steady-State Model for the Firing Rate Setpoint Rearrangement

Tahmineh

Rostamnezhad

Chaibakhsh

et al. 2018

International Journal of Chemical Engineering

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Burner failures are common abnormal conditions associated with industrial fired heaters. Preventing from economic loss and major equipment damages can be attained by compensating the lost heat due to burners' failures, which can be possible by defining appropriate setpoints to rearrange the firing rates for healthy burners. In this study, artificial neural network models were developed for estimating the appropriate setpoints for the combustion control system to recover an industrial fired-heater furnace from abnormal conditions. For this purpose, based on an accurate high-order mathematical model, constrained nonlinear optimization problems were solved using the genetic algorithm. For different failure scenarios, the best possible excess firing rates for healthy burners to recover the furnace from abnormal conditions were obtained and data were recorded for training and testing stages. e performances of the developed neural steady-state models were evaluated through simulation experiments. e obtained results indicated the feasibility of the proposed technique to deal with the failures in the combustion system.

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Novel predictive tools for design of radiant and convective sections of direct fired heaters

Cited by 27 publications

References 16 publications

Multi-objective Optimal Design of Gas-fired Heater Based on Modified Design Model of Fired Heater Taking into Account Exergy, Economic and Environmental Factors

Multi-objective Optimal Design of Gas-fired Heater Based on Modified Design Model of Fired Heater Taking into Account Exergy, Economic and Environmental Factors

Estimation of Configuration Factor for Radiation From a Rectangle to a Parallel Small Element of Surface Lying on the Perpendicular to a Corner of the Radiator

Flame Failures and Recovery in Industrial Furnaces: A Neural Network Steady-State Model for the Firing Rate Setpoint Rearrangement

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