Experimental Demonstration of Deterministic Chaos in a Waste Oil Biodiesel Semi-Industrial Furnace Combustion System

In this paper, the nonlinear dynamic characteristics of the oxygen-enriched combustion of waste oil biodiesel in semi-industrial furnaces were tested by the power spectrum, phase space reconstruction, the largest Lyapunov exponents, and the 0-1 test method. To express the influences of the system parameters, experiments were carried out under different oxygen content conditions (21%, 25%, 28%, 31%, and 33%). Higher oxygen enrichment degrees contribute to finer combustion sufficiency, which produces flames with high luminance. Flame luminance and temperature can be represented by different gray scale values of flame images. The chaotic characteristics of gray scale time series under different oxygen enrichment degrees were studied. With increased oxygen content, the chaotic characteristics of flame gradually developed from weak chaos to strong chaos. Furthermore, the flame maintained a stable combustion process in a high-temperature region. The stronger the chaotic characteristics of the flame, the better the combustion effect. It can be seen that the change of initial combustion conditions has a great influence on the whole combustion process. The results of several chaotic test methods were consistent. Using chaotic characteristics to analyze the waste oil biodiesel combustion process can digitize the combustion process, find the best combustion state, optimize, and precisely control it

Online boiler convective heat exchanger monitoring: a comparison of soft sensing and data-driven approaches

Online monitoring supports plant reliability and performance management by providing real time information about the condition of equipment. However, the intricate geometries and harsh operating environment of coal fired power plant boilers inhibit the ability to do online measurements of all process related variables. A low-cost alternative lies in the possibility of using knowledge about boiler operation to extract information about its condition from standard online process measurements. This approach is evaluated with the aim of enhancing online condition monitoring of a boiler’s convective pass heat exchanger network by respectively using a soft sensor and a data-driven method. The soft sensor approach is based on a one-dimensional thermofluid process model which takes measurements as inputs and calculates unmeasured variables as outputs. The model is calibrated based on design information. The data-driven method is one developed specifically in this study to identify unique fault signatures in measurement data to detect and quantify changes in unmeasured variables. The fault signatures are initially constructed using the calibrated one-dimensional thermofluid process model. The benefits and limitations of these methods are compared at the hand of a case study boiler. The case study boiler has five convective heat exchanger stages, each composed of four separate legs. The data-driven method estimates the average conduction thermal resistance of individual heat exchanger legs and the flue gas temperature at the inlet to the convective pass. In addition to this, the soft sensor estimates the average fluid variables for individual legs throughout the convective pass and therefore provides information better suited for condition prognosis. The methods are tested using real plant measurements recorded during a period which contained load changes and on-load heat exchanger cleaning events. The cleaning event provides some basis for validating the results because the qualitative changes of some unmeasured monitored variables expected during this event are known. The relative changes detected by both methods are closely correlated. The data-driven method is computationally less expensive and easily implementable across different software platforms once the fault signatures have been obtained. Fault signatures are easily trainable once the model has been developed. The soft sensors require the continuous use of the modelling software and will therefore be subject to licencing constraints. Both methods offer the possibility to enhance the monitoring resolution of modern boilers without the need to install any additional measurements. Implementation of these monitoring frameworks can provide a simple and low-cost contribution to optimized boiler performance and reliability management

Online monitoring instantaneous 2D temperature distributions in a furnace using acoustic tomography based on frequency division multiplexing

The online and accurate capture of dynamic changes in furnace temperature distribution is crucial for production efficiency improvement and international environmental policy compliance in power plants. To achieve this, a measurement system with a reliable online reconstruction capability and high temporal resolution is necessary. This paper presents a novel technique that can improve the temporal resolution of the currently existing acoustic tomography (AT) system using frequency division multiplexing (FDM). This method allows for concurrent transmissions of acoustic signals in several different frequency bands instead of a sequential manner, which leads to more efficient channel utilization and allows all acoustic signals to be acquired at the same time, so that a better temporal uniformity of multipath acoustic signals can be realized. Theoretical analysis and experiments have been conducted to verify the effectiveness of this technique. The results prove that the proposed method can significantly improve the temporal resolution of the AT system while maintaining the accuracy and robustness of the reconstruction

Integration of a model for volatile release in the CFD simulation of an industrial biomass boiler

Doctoral Thesis for PhD degree in Leaders for Technical IndustriesMotivada por sua disponibilidade, abundância generalizada e preocupações ambientais, a biomassa sólida tornou-se uma opção competitiva para diversificar a produção de eletricidade entre os recursos de energia renovável. Este trabalho tem como objetivo caraterizar o comportamento da combustão de espécies de biomassa frequentemente utilizadas em centrais termoelétricas para suportar o desenvolvimento de um modelo numérico para modelação eficiente e precisa da conversão de biomassa numa caldeira industrial a grelha. A eficiência da caldeira numa central de 35 MWth foi calculada como sendo aproximadamente 80%. Amostras selecionadas de biomassa de eucalipto, pinheiro, acácia e oliveira foram testadas com o analisador térmico Hot Disk TPS 2500S. A condutividade térmica ficou compreendida entre 0,239 e 0,404 W/mK. Além disso, a capacidade calorífica apresentou uma variação entre 0,855 e 2,442 MJ/m3K, e a difusividade térmica entre 0,187 e 0,258 mm2/s. Para a análise final e aproximada foram utilizados os equipamentos LECO TruSpec CHN Macro e LECO CS-200 e uma mufla, respetivamente. Os dados revelaram uma maior reatividade do eucalipto, cerca de 2 vezes superior aos outros combustíveis, e a propensão da acácia a produzir emissões poluentes (principalmente à base de azoto) e problemas de deposição de cinzas devido à sua composição química. Amostras de pequenas dimensões (cerca de 10 mg) foram usadas para medir a perda de massa e a sua reatividade num analisador termogravimétrico (TGA) da TA Instruments, modelo SDT 2960. Os testes foram realizados em atmosfera oxidante, a uma taxa de aquecimento entre 5 e 100 ºC/min, até 900 ºC. Observou-se que numa ampla faixa de temperaturas, a conversão do combustível segue uma sequência de secagem, desvolatilização e combustão do resíduo carbonoso. Amostras de maiores dimensões foram testadas num reator construído para esse fim, e que simula o processo de desvolatilização de forma controlável. Neste, a perda de massa foi medida continuamente ao longo do tempo enquanto os compostos da fase gasosa foram recolhidos em sacos para posterior análise num cromatógrafo gasoso da Bruker Scion 456-GC equipado com um detetor de condutividade térmica. Ao contrário dos dados do TGA, concluiu-se que na oxidação de biomassas, utilizando partículas maiores, não é possível distinguir as sucessivas etapas de conversão, devido à maior resistência interna de difusão. Avaliando a influência da esbelteza da amostra (rácio comprimento/espessura), concluiu-se que a taxa de desvolatilização depende apenas da sua espessura e não do volume. Além disso, para temperaturas mais altas do reator, a taxa de perda de massa é independente do tipo de biomassa. Os compostos gasosos libertados durante a conversão térmica do eucalipto apresentaram forte correlação com a temperatura do reator, sendo CO2 e CO sempre os principais produtos de desvolatilização. A dependência da temperatura de ambos os compostos apresentam, para o CO, um aumento de 8 a 13% entre 600 e 800°C, enquanto o de CO2 aumenta apenas ligeiramente de 11 a 12%. O modelo eXtended Discrete Element Method foi usado para descrever a desvolatilização no reator. Os resultados foram comparados com os dados experimentais e, embora tenha sido observada uma boa concordância, concluiu-se que a oxidação do resíduo carbonoso necessita de um modelo de difusão. A simulação do escoamento no interior da caldeira foi feita utilizando o software ANSYS Fluent. Neste, um modelo empírico externo para prever a conversão de biomassa ao longo da grelha é acoplado a um modelo CFD para prever o escoamento reativo dentro da caldeira. Os resultados destacaram a contribuição da contração na seção intermédia da fornalha, e a necessidade de um maior caudal de ar secundário para reduzir as emissões de CO. Os resultados mostram que modificando a razão entre o ar primário e secundário de 79/21 para 40/60, obteve-se uma redução da fração mássica de CO de 0.009 para 0.0003.Motivated by their availability, widespread abundance, and environmental concerns, solid biomass has become a competitive option to diversify electricity production amongst the renewable energy resources. This work aims to characterize the combustion behavior of solid biomass species frequently used in power plants as a route to support the development of a numerical model for efficient and accurate modeling of biomass conversion in an industrial grate-fired boiler. The boiler efficiency of a power plant rated at 35 MWth was calculated as approximately 80%. Selected samples of biomass (eucalyptus, pine, acacia, and olive) were tested with a Hot Disk Thermal Constants Analyzer TPS 2500S. The thermal conductivity, varied in the range of 0.239 to 0.404 W/mK. In addition, the heat capacity is within 0.855 to 2.442 MJ/m3K, and the thermal diffusivity is between 0.187 and 0.258 mm2/s. The ultimate and proximity analysis was carried out on the fuel samples using LECO TruSpec CHN Macro and LECO CS-200 equipment and a muffle furnace, respectively. The data revealed a higher reactivity of eucalyptus, which is around 2 times higher than that of other fuels, and the propensity of the acacia to produce pollutant emissions (mostly Nitrogen based) and ash deposition problems due to their chemical composition. Small size samples (around 10 mg each) were used to measure the mass loss and their reactivity in a thermogravimetric analyzer (TGA) from TA Instruments, model SDT 2960. The tests were carried out on an oxidizing atmosphere at a heating rate between 5 and 100 ºC/min up to 900 ºC. It was observed that over a wide range of temperatures, fuel conversion follows a sequence of drying, devolatilization, and char combustion. Larger samples of heartwood were tested in a purpose built reactor that simulates the devolatilization process under a controllable manner. In this, the mass loss was continuously measured along the time while the gas phase compounds were collected in bags for subsequent analysis in a gas chromatograph Bruker Scion 456-GC equipped with a thermal conductivity detector. As opposed to the TGA data, it was concluded that all fuels show that the combustion of large particles does not exhibit separate consecutive conversion stages, due to internal diffusion resistance. This was further highlighted by varying the sample aspect ratio. It was concluded that the devolatilization rate depends on the smallest dimension and not on the bulk size. Furthermore, at higher reactor temperatures, the mass loss profile is independent of the biomass. The gas compounds released with eucalyptus presented a strong correlation with the reactor temperature, being CO2 and CO always the main devolatilization products. The temperature dependence of both compounds shows, for CO, an increase from 8 to 13% between 600 and 800 °C, while the CO2 yield is only slightly increasing from 11 to 12%. The eXtended Discrete Element Method model was implemented to describe the devolatilization inside the reactor. The results were compared with the experimental data and, while a good agreement was observed, it was concluded that the char oxidation needs to be also represented by a diffusion model. The numerical model was developed using the ANSYS Fluent software. In this, a user defined empirical model to predict the biomass conversion along the grate was coupled with a freeboard model to predict reactive flow inside the boiler. The results highlighted the contribution of the converging sections in the middle section of the furnace and the need for a higher secondary air flow rate to reduce CO emissions. The results show that a reduction of the CO mass fraction from 0.009 to 0.0003 was possible with a modification of the primary to secondary air split ratio from 79/21 to 40/60.Fundação para a Ciência e a Tecnologia for sponsoring my research, through the grant SFRH/BD/130588/2017

Prediction of combustion state through a semi-supervised learning model and flame imaging

Accurate prediction of combustion state is crucial for an in-depth understanding of furnace performance and optimize operation conditions. Traditional data-driven approaches such as artificial neural networks and support vector machine incorporate distinct features which require prior knowledge for feature extraction and suffers poor generalization for unseen combustion states. Therefore, it is necessary to develop an advanced and accurate prediction model to resolve these limitations. This study presents a novel semi-supervised learning model integrating denoising autoencoder (DAE), generative adversarial network (GAN) and Gaussian process classifier (GPC). The DAE network is established to extract representative features of flame images and the network trained through the adversarial learning mechanism of the GAN. Structural similarity (SSIM) metric is introduced as a novel loss function to improve the feature learning ability of the DAE network. The extracted features are then fed into the GPC to predict the seen and unseen combustion states. The effectiveness of the proposed semi-supervised learning model, i.e., DAE-GAN-GPC was evaluated through 4.2 MW heavy oil-fired boiler furnace flame images captured under different combustion states. The averaged prediction accuracy of 99.83% was achieved for the seen combustion states. The new states (unseen) were predicted accurately through the proposed model by fine-tuning of GPC without retraining the DAE-GAN and averaged prediction accuracy of 98.36% was achieved for the unseen states. A comparative study was also carried out with other deep neural networks and classifiers. Results suggested that the proposed model provides better prediction accuracy and robustness capability compared to other traditional prediction models

ECOS 2012

The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology

Biomass co-combustion process assessment using series of flame images

The article presents the way of assessment of biomass coal mixture combustion using information in a form of flame area changes determined for image sequences. The images were captured by a dedicated visual system equipped with CMOS camera and a borescope that enabled observing flame zone located near burner at 45° to flame axis. Several laboratory combustion experiments were carried out when thermal power and excess air coefficient were set independently for fuel mixtures with biomass content of 10% and 20%.У статті представлений метод оцінювання спалювання суміші біомаси та вугілля при використанні площ полум’я, які визначені в серіях зображень. Зображення були зареєстровані спеціальної відео- системою, що складається з КМОП камери і бароскопа. Тому можна було спостерігати зону полум’я безпосередньо близько пальники під кутом 45 градусів до її осі. Проведено серію експериментів, в яких незалежно змінювалися теплова потужність установки і коефіцієнт надлишку повітря для сумішей з вмістом 10% і 20% біомаси.В статье представлен метод оценивания сжигания смеси биомассы и угля при использовании площадей пламени, которые определенные в сериях изображений. Изображения были зарегистрированы специальной видео-системой, состоящей из КМОП камеры и бароскопа. Поэтому можно было наблюдать зону пламени непосредственно около горелки под углом 45 градусов к её оси. Проведено серию экспериментов, в которых независимо изменялись тепловая мощность установки и коэффициент избытка воздуха для смесей с содержанием 10% и 20% биомассы

Biomass for Energy Country Specific Show Case Studies

In many domestic and industrial processes, vast percentages of primary energy are produced by the combustion of fossil fuels. Apart from diminishing the source of fossil fuels and the increasing risk of higher costs and energy security, the impact on the environment is worsening continually. Renewables are becoming very popular, but are, at present, more expensive than fossil fuels, especially photovoltaics and hydropower. Biomass is one of the most established and common sources of fuel known to mankind, and has been in continuous use for domestic heating and cooking over the years, especially in poorer communities. The use of biomass to produce electricity is interesting and is gaining ground. There are several ways to produce electricity from biomass. Steam and gas turbine technology is well established but requires temperatures in excess of 250 °C to work effectively. The organic Rankine cycle (ORC), where low-boiling-point organic solutions can be used to tailor the appropriate solution, is particularly successful for relatively low temperature heat sources, such as waste heat from coal, gas and biomass burners. Other relatively recent technologies have become more visible, such as the Stirling engine and thermo-electric generators are particularly useful for small power production. However, the uptake of renewables in general, and biomass in particular, is still considered somewhat risky due to the lack of best practice examples to demonstrate how efficient the technology is today. Hence, the call for this Special Issue, focusing on country files, so that different nations’ experiences can be shared and best practices can be published, is warranted. This is realistic, as it seems that some nations have different attitudes to biomass, perhaps due to resource availability, or the technology needed to utilize biomass. Therefore, I suggest that we go forward with this theme, and encourage scientists and engineers who are researching in this field to present case studies related to different countries. I certainly have one case study for the UK to present

Three-dimensional visualisation and quantitative characterisation of fossil fuel flames using tomography and digital imaging techniques

This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for the three-dimensional (3-D) visualisation and quantitative characterisation of fossil fuel flames. A review of methodologies and technologies for the 3-D visualisation and characterisation of combustion flames is given, together with a discussion of main difficulties and technical requirements in their applications. A strategy incorporating optical sensing, digital image processing and tomographic reconstruction techniques is proposed. The strategy was directed towards the reconstruction of 3-D models of a flame and the subsequent quantification of its 3-D geometric, luminous and fluid dynamic parameters. Based on this strategy, a flame imaging system employing three identical synchronised RG B cameras has been developed. The three cameras, placed equidistantly and equiangular on a semicircle around the flame, captured six simultaneous images of the flame from six different directions. Dedicated computing algorithms, based on image processing and tomographic reconstruction techniques have been developed to reconstruct the 3-D models of a flame. A set of geometric, luminous and fluid dynamic parameters, including surface area, volume, length, circularity, luminosity and temperature are determined from the 3-D models generated. Systematic design and experimental evaluation of the system on a gas-fired combustion rig are reported. The accuracy, resolution and validation of the system were also evaluated using purpose-designed templates including a high precision laboratory ruler, a colour flat panel and a tungsten lamp. The results obtained from the experimental evaluation are presented and the relationship between the measured parameters and the corresponding operational conditions are quantified. Preliminary investigations were conducted on a coal-fired industry-scale combustion test facility. The multi-camera system was reconfigured to use only one camera due to the restrictions at the site facility. Therefore the property of rotational symmetry of the flame had to be assumed. Under such limited conditions, the imaging system proved to provide a good reconstruction of the internal structures and luminosity variations inside the This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for the three-dimensional (3-D) visualisation and quantitative characterisation of fossil fuel flames. A review of methodologies and technologies for the 3-D visualisation and characterisation of combustion flames is given, together with a discussion of main difficulties and technical requirements in their applications. A strategy incorporating optical sensing, digital image processing and tomographic reconstruction techniques is proposed. The strategy was directed towards the reconstruction of 3-D models of a flame and the subsequent quantification of its 3-D geometric, luminous and fluid dynamic parameters. Based on this strategy, a flame imaging system employing three identical synchronised RG B cameras has been developed. The three cameras, placed equidistantly and equiangular on a semicircle around the flame, captured six simultaneous images of the flame from six different directions. Dedicated computing algorithms, based on image processing and tomographic reconstruction techniques have been developed to reconstruct the 3-D models of a flame. A set of geometric, luminous and fluid dynamic parameters, including surface area, volume, length, circularity, luminosity and temperature are determined from the 3-D models generated. Systematic design and experimental evaluation of the system on a gas-fired combustion rig are reported. The accuracy, resolution and validation of the system were also evaluated using purpose-designed templates including a high precision laboratory ruler, a colour flat panel and a tungsten lamp. The results obtained from the experimental evaluation are presented and the relationship between the measured parameters and the corresponding operational conditions are quantified. Preliminary investigations were conducted on a coal-fired industry-scale combustion test facility. The multi-camera system was reconfigured to use only one camera due to the restrictions at the site facility. Therefore the property of rotational symmetry of the flame had to be assumed. Under such limited conditions, the imaging system proved to provide a good reconstruction of the internal structures and luminosity variations inside the This thesis describes the design, implementation and experimental evaluation of a prototype instrumentation system for the three-dimensional (3-D) visualisation and quantitative characterisation of fossil fuel flames. A review of methodologies and technologies for the 3-D visualisation and characterisation of combustion flames is given, together with a discussion of main difficulties and technical requirements in their applications. A strategy incorporating optical sensing, digital image processing and tomographic reconstruction techniques is proposed. The strategy was directed towards the reconstruction of 3-D models of a flame and the subsequent quantification of its 3-D geometric, luminous and fluid dynamic parameters. Based on this strategy, a flame imaging system employing three identical synchronised RG B cameras has been developed. The three cameras, placed equidistantly and equiangular on a semicircle around the flame, captured six simultaneous images of the flame from six different directions. Dedicated computing algorithms, based on image processing and tomographic reconstruction techniques have been developed to reconstruct the 3-D models of a flame. A set of geometric, luminous and fluid dynamic parameters, including surface area, volume, length, circularity, luminosity and temperature are determined from the 3-D models generated. Systematic design and experimental evaluation of the system on a gas-fired combustion rig are reported. The accuracy, resolution and validation of the system were also evaluated using purpose-designed templates including a high precision laboratory ruler, a colour flat panel and a tungsten lamp. The results obtained from the experimental evaluation are presented and the relationship between the measured parameters and the corresponding operational conditions are quantified. Preliminary investigations were conducted on a coal-fired industry-scale combustion test facility. The multi-camera system was reconfigured to use only one camera due to the restrictions at the site facility. Therefore the property of rotational symmetry of the flame had to be assumed. Under such limited conditions, the imaging system proved to provide a good reconstruction of the internal structures and luminosity variations inside the flame. Suggestions for future development of the technology are also reported