Burner Efficiency Research Articles

Numerical and experimental investigation of the correlation between inlet flow rates, temperature, and [formula omitted] emissions in pure hydrogen combustion

Many industrial burners currently in use have been designed for fossil fuels and have not been tested with hydrogen. The successful utilization of hydrogen fuel in industrial applications demands the optimization of operating conditions. Optimizing the inlet flow rate is important particularly for industrial burners to ensure safe and efficient operation over a long period. This study investigates the effects of inlet flow rate on temperature distribution and NOx emissions in a multi-purpose pure hydrogen-fueled industrial burner through numerical simulations and experiments. The numerical simulations, employing the realizable k-ε turbulence model and the eddy dissipation concept for turbulence and combustion modeling, are validated against experimental data, achieving a mean absolute percentage error of approximately 5 % for temperature and less than 2 % for NOx emissions at 4 % O2. The results demonstrated that increasing the inlet flow rate enhances reaction intensity and heat release, subsequently increasing combustion temperatures and promoting NOx formation. However, with a substantial increase in the inlet flow rate, the rate of temperature growth diminishes, and NOx emissions reach a plateau. This suggests that the burner is approaching maximum capacity, with the combustion process becoming limited by the burner’s ability to efficiently mix and react the fuel and oxidizer. Finally, an optimal inlet flow rate of 50.4 LPM for hydrogen in the fuel inlet and 200 LPM for air in the oxidizer inlet, balancing temperature and NOx emissions, was identified through the weighted sum performance indicator proposed in this work. This study provides critical insights into pure hydrogen burner performance, advancing previous efforts by offering quantitative data essential for improving burner efficiency and reducing harmful emissions in carbon-free combustion.

Enhancing Gas Burner Efficiency and Reducing Exhaust Emissions: An Experimental Study on the Use of Nebulized Carbon Nanoparticles

Enhancing Gas Burner Efficiency and Reducing Exhaust Emissions: An Experimental Study on the Use of Nebulized Carbon Nanoparticles

A sensitivity study on the starting simulations of turbojet engines

AbstractGas turbine engine starting models require a lot of calibration to represent reality with acceptable accuracy due to the lack of high-quality component rig data in the sub-idle region. A detailed sensitivity study is presented in this paper to guide such calibration efforts. A thermodynamic component-matching type transient model of a single-spool turbojet engine with shaft and heat-soakage dynamics is employed for this purpose. Turbomachinery component maps are extended to sub-idle using an in-house map smoothing tool and the strategies presented by Kurzke recently. These extension strategies make use of the correlations hidden in the already available regions of the maps and ensure physical consistency. However, they contain some uncertainty, even when an experimentally obtained zero-speed line is available. Combustor sub-idle efficiency, stability limits, and delay are taken from the literature. Due to the chaotic nature of a combustor in the sub-idle region, a precise prediction of the combustor efficiency seems impossible. Effects of uncertainties related to sub-idle turbomachinery map extensions, burner efficiency, and heat soakage are investigated in this paper. Two popular fuel control strategies are employed and compared to see how controls deal with these uncertainties. It is concluded that turbomachinery torque characteristics and turbine capacities are the most important parameters when calibrating a starting model with a control based on rotational acceleration while burner efficiency and heat soakage are added on top of these with a control based on fuel flow rate.

CFD and RSM Assist in Reducing the LPG Consumption of Burners for Agarwood Oil Production in Thailand

ABSTRACT This research aimed to optimize LPG consumption in Thai commercial burners used in agarwood oil production, specifically focusing on the KB-10, S-10, and EB-10 burners. Enhancing burner efficiency is crucial due to rising energy costs and environmental concerns. A dual approach using Response Surface Methodology (RSM) and Computational Fluid Dynamics (CFD) was employed in order to achieve the best burner. Central Composite Design (CCD) within the RSM framework determined the optimal swirl and inclination angles combinations. Modified burners with variant combination angles, as suggested by RSM, were numerically investigated. CFD simulations with Ansys Fluent, utilizing the k-ε turbulence and discrete ordinates (DO) radiation models, provided detailed insights into the combustion and heat transfer processes of those modified burners. The modified burners, SB10–1, SS10–3, and SEB10–7, demonstrated significant improvements. Laboratory and field tests indicated energy savings of 16.15%, 23.74%, and 20.75%, respectively. Statistical analysis confirmed these savings with p-values < .05. The 95% confidence intervals for LPG savings were 31.31 ± 0.8%, 33.42 ± 0.7%, and 31.84 ± 0.6%, corresponding to payback periods of approximately 2.99, 4.21, and 8.95 months. Additionally, CO and NOx emissions were kept below 350 ppm and 100 ppm, respectively. The novelty of this study lies in the combined use of RSM and CFD to optimize burner performance, leading to significant energy savings and emission reductions. These findings highlight the potential of these methods for burner optimization, offering both economic and environmental benefits. This research underscores the importance of integrating advanced modeling techniques to achieve sustainable and cost-effective industrial processes.

Kiln-Furnace System: Validation of a Technology for Producing Charcoal with Less Environmental Impact in Brazil

Brazil is the world’s largest producer of charcoal. Therefore, there is need for improvement in the gravimetric yield of conversion and the reduction of gas emissions, including greenhouse gases (GHGs), released during carbonization. The objective was to apply the methodology of Measurement, Reporting and Verification (MRV) to evaluate the emission of GHG, mainly CO2 and CH4. The charcoal production kiln-furnace system used was composed of 4 kilns with a capacity of ~6 t of wood, each. The MRV cluster of coal gravimetric yield and gas burners were used to determine the gravimetric yield and burner efficiency and thus evaluate the emission of GHGs generated in the carbonization system. The carbonization was performed in an isolated way producing, in total, 3.34 t of charcoal, with an average gravimetric yield of 25.82%. The MRV methodology was effective for evaluating the GHG emissions. The wood burner reduced by 50% the methane burning and provided a reduction of 0.392 tCO2 eq (23.91%). The humidity of wood and high precipitation were the main limiting factors in this research, and responsible for the decrease in the gravimetric yield. The kiln-furnace system was effective for a sustainable production with the use of non-continuous carbonization gas burners.

Integration of a Gamma-Type Stirling Engine with LPG Cooking Stove for Micro-Scale Combined Heat and Power Generation

The Stirling engine is one of the most versatile micro-scale prime movers for combined heat and power applications, adaptable to different levels of heat sources. This study started a unique journey that included developing, experimenting, and analyzing the Gamma-type Stirling engine. Notably, the engine design ingeniously harnesses heat from a customized cooking stove burner powered by liquefied petroleum gas. The engine fabrication resulted in a compression ratio 2.014, accommodating a volumetric capacity of 181 cc. The Stirling engine test used air as the working gas, and the initial conditions were at atmospheric pressure. Stirling engine performance was analyzed using an ideal thermodynamic cycle model and burner efficiency using the water boiling method. The modified burner attains an average temperature of 699.5°C, producing a burner power output of 5.702 kW and a thermal efficiency of 32.7% or around 1.867 kW of heat for operating the engine and cooking activities. Simultaneously, tests of the Stirling engine revealed an average air temperature difference of 146.2°C between the expansion and compression phases. The flywheel rotation speed ranges from 158 to 369 rpm. During testing, the Stirling engine obtained an average thermal efficiency of 31.08%, accompanied by an ideal power spectrum ranging from 0.3 W to 42.6 W. The highlight of this study was the maximum pressure achieved at the end of the heat absorption stage, recorded at 296.1 kPa. Importantly, these findings underscore the promising potential of micro-Combined Heat and Power systems. Integrating the gamma-type Stirling engine with the LPG stove represents novelty and paves the way for further development and advancement in sustainable energy solutions.

On the drastic improvement of porous burner efficiency

On the drastic improvement of porous burner efficiency

Optimization of lower air inlet tube configuration for maximizing burner efficiency based on gas dynamics, and heat transfer potency in a Rotary Hearth Furnace

Optimization of lower air inlet tube configuration for maximizing burner efficiency based on gas dynamics, and heat transfer potency in a Rotary Hearth Furnace

FULL-SCALE CFD STUDY OF SWIRL NUMBER EFFECT ON PARTICLE AND FLOW BEHAVIOR IN INTERACTION WITH COMBUSTION DYNAMICS INSIDE COAL PULVERIZED BURNER

The present paper reports a numerical investigation of an atmospheric pulverized coal combustor. The main goal is to study the effects of flow behavior and gas-particle interaction on combustion dynamics for various swirl numbers (SN). This will help in better understanding of the combustion properties inside a large-scale facility. The RANS and quick discretization scheme are combined during this numerical simulation. For turbulence, the realizable k-&amp;epsilon; model is adopted. Turbulence and chemistry interaction are modeled using the finite rate/eddy dissipation model along with reduced global reaction mechanism. Four swirl numbers were investigated. The numerical results are validated with previous experimental data. Good agreement between both results is found for temperature distribution and species concentration along the center axis of the nozzle. Flow topology, temperature, particle trajectory, and species concentrations in several locations downstream the injection nozzle are presented and analyzed for the considered swirl numbers. Analysis of the flow velocity and the particle trajectory showed that the combustion behavior and flame shape were directly related to the particle trajectory inside the nozzle. The numerical results also outlined that the variation of swirl number has changed the particle trajectory and consequently the flame topology. Thus, the swirl number significantly influences the burner efficiency.

Clean cooking with downdraft biomass gasifier cookstove: Effect of gasifier performance

Two downdraft gasifier cookstoves, one of 4 kWth and another of 2.5 kWth input power ratings have been developed by the authors for domestic cookstove application. The downdraft gasifier cookstove has a gasifier unit followed by a partially aerated burner. Thus, the efficiency of the gasifier cookstove is the product of the gasification efficiency of the gasifier unit and the burner efficiency. The present work reports the effects of the output parameters of the gasifier, viz. gas flow rate, gas composition as reflected by the lower calorific value (LCV) of producer gas, and the gas temperature, on thermal performance and emissions of the cookstoves. Laboratory-based water boiling tests were conducted on both the cookstoves to study the effect of these parameters on cookstove efficiency, burner efficiency and emission factors of CO and PM2.5. The turn down ratios of 4 kWth and 2.5 kWth gasifier cookstoves were 2.2 and 2.8 respectively. The maximum efficiency for 4 kWth cookstove (44.6%) occurred at input power of 4.4 kW whereas that for 2.5 kWth cookstove (45.1%) occurred at 3.2 kW. Average CO emission factor for 4 kWth and 2.5 kWth cookstoves was 4.2 g/MJd and 2.84 g/MJd respectively.

Optimization of Liquid Organic Hydrogen Carrier (LOHC) dehydrogenation system

In this paper, the perhydrodibenzyltoluene dehydrogenation flowsheet has been simulated. Modelling of the dehydrogenation reactor has been performed using the 1-D model. External and internal mass transfer resistances are also considered. Non-isothermal pellet condition has been considered for simulating the dehydrogenation reactor. The flowsheet simulation has been carried out in DW-Sim v 6.5.2 integrated with the reactor model coded in Python. NET. The dehydrogenation reactor is operated at a feed temperature between 523 K −613 K, a wall temperature of 623 K and 653 K, and a reactor pressure maintained at 1.2 atm. The amount of catalyst required for the perhydrodibenzyltoluene (PDBT) dehydrogenation reactor is evaluated such that the conversion reaches 99%. The process flowsheet has been simulated to produce 10 Nm3/hr of industrial-grade hydrogen. The effects of feed temperature, wall temperature, and hydrogen burner efficiency on various system requirements, including catalyst weight, energy supplied to the dehydrogenation reactor, areas of the heat exchanger, and hydrogen production from the reactor, have been discussed. Preliminary cost optimization based on the heat exchangers and catalyst at various feed temperatures, reactor wall temperature, and hydrogen burner efficiency has been carried out.

Applying the Random Forest Method to Improve Burner Efficiency

Fuel power plants are one of the main sources of pollutant emissions, so special attention should be paid to improving the efficiency of the fuel combustion process. The mathematical modeling of processes in the combustion chamber makes it possible to reliably predict and find the best dynamic characteristics of the operation of a power plant, in order to quantify the emission of harmful substances, as well as the environmental and technical and economic efficiency of various regime control actions and measures, and the use of new types of composite fuels. The main purpose of this article is to illustrate how machine learning methods can play an important role in modeling and predicting the performance and control of the combustion process. The paper proposes a mathematical model of an unsteady turbulent combustion process, presents a model of a combustion chamber with a combined burner, and performs a numerical study using the STAR-CCM+ multidisciplinary platform. The influence of various input indicators on the efficiency of burner devices, which is evaluated by several parameters at the output, is investigated. In this case, three possible states of the burners are assumed: optimal, satisfactory and unsatisfactory.

Simulation numérique d'un bruleur à biogaz destiné aux moteurs Stirling

The design of a biogas burner for Stirling engines depends on its ability to provide a sufficient heat which is not produced by conventional burners because of the limitation of the contact surface between flame-hot head and the low methane content in the biogas. Therefore, a special microscale combustion chamber for this kind of burner is necessary. In this work, we studied numerically the biogas combustion by a Swiss-roll burner in a small-scale combustor. The temperature distribution versus the biogas injection rate is investigated. A significant increase of the flame temperature is obtained with an improvement of the uniformity of the temperature distribution and the burner efficiency.

Thermal characterization of straight and curve edge blade liquid fuel swirl burner

Accurate monitoring and controlling of the temperature in the combustion chamber can raise the burner efficiency, combustion intensity, fuel consumption and reduce pollutant emission. However, except combustion is accurately monitored and controlled, high concentration of pollutant gases and products like carbon monoxide (CO) and soot can form in the combustion chamber. This paper compares the combustion thermal profiles in a liquid fuel swirl burner using developed straight edge and curve edge blade swirlers at (20, 30, 40, 50 and 60)° for 6, 8, 10 and 12 number of blades in order to optimize the temperature of the burner. Measurements were made in straight and curve blades liquid fuel swirl burner in order to study and compare the thermal characteristics of the straight and curve edge blades in optimizing the combustion dynamics. Similarly, measurements were made for burner without swirl generator and the combustion temperature assessed. Thermal profile was measured in the direction of flow via the six axial ports at distance ((d) =150, 350, 550, 750, 950 and 1150 mm) from the burner exit using Chromium-Zinc thermocouple. Results showed that the wavelength and oscillation of temperature decay in the same type of blade followed the same trend and the peak of combustion intensity is nearer the nozzle for curve edge blades than the straight edge blade. Six (6) blades performed best with the highest temperature in all the ports, while 12 blades gave the least performance. Findings further show that curve edge blade swirlers gave better performance than straight edge blade swirlers with highest temperature of (1065 and 1015) °C, respectively. Hence, it is recommended especially where high temperature and stability application is desirable

Effect of coherent jet burner on scrap melting in electric arc furnace

Modern electric arc furnace (EAF) steelmaking relies on the coherent jet burner to melt scrap at the cold spots inside the furnace, but the relevant computational fluid dynamics (CFD) modeling of this process has not been reported and systematically studied. The present work established an innovative comprehensive CFD model including a scrap melting model and a coherent jet model based on the detailed physical principles, which couples the solid–liquid-gas three-phase system with coherent jet and scrap melting/re-solidification for the investigations of key evaluation factors including burner efficiency, scrap heating rate, and scrap melting cavity. An experiment was designed and implemented specifically in an industrial-scale EAF for validating the proposed model. The model was employed to explore the impacts of burner power, scrap porosity, scrap preheat temperature, and scrap blockage on burner energy utilization. An understanding and guidance of coherent jet burner operations were provided based on the studies for more effective scrap melting.

Deep-Learning Technique Monitors Well-Testing Burner Efficiency

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 19714, “Deep Learning for Monitoring Well-Testing Burner Efficiency,” by Darine Mansour, SPE, Hakim Arabi, and Yingwei Yu, SPE, Schlumberger, et al., prepared for the 2020 International Petroleum Technology Conference, Dhahran, Saudi Arabia, 13-15 January. The paper has not been peer reviewed. Copyright 2020 International Petroleum Technology Conference. Reproduced by permission. During well-testing operations, incorrect burner combustion could have an adverse effect on the environment or personal safety. Combustion efficiency is assessed by personnel who observe the flame. This practice lacks consistency and poses challenges, including environmental and safety considerations and issues with data. In the complete paper, the authors propose a solution that uses a deep neural network that learns from flame videos to define the quality of the combustion. The results are promising and show that this solution is a good candidate for real-time burner-efficiency monitoring and automatic alarm triggering and optimization. Introduction Automation of the evaluation of combustion efficiency would promote consistent combustion efficiency and timely reaction to undesirable combustion. In field operations, cameras are positioned for a direct view of the burner flames. The authors use a data set of video images captured by the cameras and labeled by domain experts as images of acceptable or undesirable combustion. The goal of the study is to automate human monitoring of the combustion by processing these images and classifying them automatically as images of acceptable or undesirable combustion. A supervised learning approach is applied to the problem. The approach consists of extracting the flame features from each image and feeding the features to a classifier that categorizes the combustion. The classifier is trained using the extracted features and labeled combustion images as input. The traditional approach to feature extraction is manual feature engineering, involving the extraction of handcrafted features using image-processing algorithms and domain knowledge. The process is tedious and time-consuming. Much effort is required to extract all relevant features in various contextual and environmental conditions. The extracted features are problem-dependent, and the process may require revisiting algorithms to adapt to new data that hold new features or new representations of existing features. Approach To achieve classification, a convolutional neural network (CNN) is trained using a data set of images labeled by domain experts. Using the image data set captured by well-testing cameras, a CNN with an architecture similar to VGG-16 that learns to extract powerful features from natural images is fine-tuned.

Part A: Advances in tools and techniques for estimating biogas production and treatment in anaerobic-based STPs Technical Note 5 - Direct combustion of biogas in burners

The direct combustion of biogas in burners must be carried out whenever its energy recovery is not technically or economically feasible. Even in STPs that have biogas energy recovery systems, the burners are indispensable (necessary) and must be activated temporarily when there is an excess of biogas production or stops in the systems that process it. The biogas combustion reduces minimizes methane emissions to the atmosphere, contributing to the management of greenhouse gas emissions, in addition to reducing emissions of odorous and corrosive gases, especially hydrogen sulfide. Burners are, therefore, essential to reduce environmental and social impacts inherent to biogas emissions and are even essential for the safety of the STPs infrastructure and the occupational health of operators. In that context, this Technical Note (TN) aims to present the technical elements associated with the direct combustion of biogas in burners, reporting: (i) fundamentals about biogas burning; (ii) types and main characteristics of burners available on the market; (iii) methods for determining burner efficiency; and (iv) criteria for the installation and operation of burners in STPs.

Combustion monitoring in an industrial cracking furnace based on combined CFD and optical techniques

Ethylene is one of the most important building blocks of current chemical industry with a global production of 150 million tons in 2016. Most ethylene nowadays is produced via thermal cracking with steam of fossil feedstocks in cracking furnaces. This process accounts for approximately 8% of the petrochemical sector primary energy consumption making it the single most energy-consuming process in the chemical industry. Combustion of hydrocarbon fuels supplies the required energy to cracking units resulting in substantial CO2 emissions. Also, new emission regulations have a strong influence on older units with partially premixed burners, which produce larger amounts of NOx than modern designs. Therefore, an improvement of energy efficiency and a reduction of pollutants in cracking furnaces are environmentally and economically driven. In this work, both issues have been addressed based on numerical (CFD) techniques and experimental measurements at the plant. Firstly, to monitor burner efficiency a new methodology based on CFD calculation of OH- and CH- radicals via reduced chemical kinetics, combined with industrial-scale experimental validation through flame spectroscopic measurements and UV CCD cameras, has been carried out. Based on these measurements, a quick diagnosis of combustion performance by flame emission chemiluminescence can be made, which has successfully tested for the first time at full-scale industrial cracking furnaces. Secondly NOx emissions have been simulated by the usual approach of reduced chemistry and post-processing over the CFD fields, demonstrating with plant data at the stack that reasonable predictions can be achieved in this context. The method has been used to study modifications of burner geometry to abate NOx formation.

Design and Development of Solar-biogas Hybrid Dryer for Onion Drying

A solar-biogas hybrid dryer was designed, developed and tested for onion drying with a capacity of 8 kg/batch. Solar energy was utilized as primary energy for onion drying in a greenhouse type drying chamber (direct solar) and biogas powered air heater used as a supplementary heat source for continuous operation. The hybrid dryer consists of greenhouse type drying chamber, concentric pipe air heater and biogas burner. The greenhouse type drying chamber has floor area of 1300 mm×900 mm and collector area of 3 m2. The dryer was operated as a solar dryer during normal sunny day and hybrid mode whenever sunlight is insufficient to maintain desired 60°C inside the drying chamber. The results indicated that the moisture content of onion slices reduced from 80.06% (wb) to 9.88% (wb) in 12 hours in hybrid mode drying. A biogas powered air heater operated for 3 hours in a day with effectiveness of 0.87 and biogas burner efficiency of 47.59%. The dryer was techno-economically feasible with a benefit cost ratio of 1.12 and payback period of 2.1 years.

On-Design Operation and Performance Characteristic of Custom Engine

The purpose of this study is to investigate the design point performance of a custom engine via GasTurb software. In this study, a turbojet engine model is simulated without afterburners and limited to design point (DP) simulation at a speed of 15,000 rpm. The input parameters such as pressure ratio (PR) for the main components, the mechanical and burner efficiency, and isotropic PR for compressor and turbine have been identified for a custom engine as a design point. The results compared at different levels of the condition using GasTurb-13 and GSP-11 software. It was found that each software was able to provide similar results at various conditions tested. There are small differences in the values for the fuel flow and specific fuel consumption. Also, the same results were obtained at the baseline point. Furthermore, the heating value has a primary effect on specific fuel consumption. It was also found that the optimal thrust value was at 34.2 kN, and the best value for optimal specific fuel consumption was 20.9 g/kN.s. The main factors affecting biofuel properties are calorific value and viscosity. When the calorific value of the fuel is reduced, the thrust FN and specific fuel consumption increase. For example, Methanol and Ethanol recorded the highest amount of fuel consumption, which is 54.72 g/KN.s and 47.56 g/(KN.s), respectively. This is because they have the highest mass fuel flow ( 1.79 kg/s for Methanol, and 1.54 kg/s for Ethanol) than other types of fuel, while the mass fuel flow for green diesel (0.78 kg/s) was lower than other fuels, so its specific fuel consumption (22.11 g/(KN.s) was lesser than other fuels.