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H₂O, CO₂ and CO are three main species in combustion systems which have high volume fractions. In addition, soot has strong absorption in the infrared band. Thus, H₂O, CO₂, CO and soot may take important roles in radiative heat transfer. To provide calculations with high accuracy, all of the participating media should be considered non-gray media. Thus, the purpose of this paper is to study the effect of non-gray participating gases and soot on radiative heat transfer in an inhomogeneous and non-isothermal system.

To solve the radiative heat transfer, the fluid flow as well as the pressure, temperature and species distributions were first computed by FLUENT. The radiative properties of the participating media are calculated by the Statistical Narrow Band correlated K-distribution (SNBCK), which is based on the database of EM2C. The calculation of soot properties is based on the Mie scattering theory and Rayleigh theory. The radiative heat transfer is calculated by the discrete ordinate method (DOM).

Using SNBCK to calculate the radiative properties and DOM to calculate the radiative heat transfer, the influence of H₂O, CO₂, CO and soot on radiation heat flux to the wall in combustion system was studied. The results show that the global contribution of CO to the radiation heat flux on the wall in the kerosene furnace was about 2 per cent, but that it can reach up to 15 per cent in a solid fuel gasifier. The global contribution of soot to the radiation heat flux on the wall was 32 per cent. However, the scattering of soot has a tiny influence on radiation heat flux to the wall.

This is the first time H₂O, CO₂, CO and the scattering of soot were all considered simultaneously to study the radiation heat flux in combustion systems.

Reports that major advances have been achieved on computational simulations of multidimensional fluid flow, heat and mass transfer during the last 20 years. Focuses on the numerical prediction of fluid flow, combustion and gas radiation in a combustion chamber of a typical industrial glass‐melting furnace. Carries out the flow simulation in a three‐dimensional calculation domain by using computer models in conjunction with the standard k ‐ ε turbulence model. Tests the predictions of spectral intensity by solving the equation of radiative transfer. Employs the Goody statistical narrow band model with the Curtis‐Godson approximation to calculate radiative properties for inhomogeneous gas mixtures.

Aero-engine exhaust plume length can be more than the aircraft length, making it easier to detect and track by infrared seeker. Aim of this study is to analyze the effect of free stream Mach number (M_∞) on length of potential core of plume. Also, change in infrared (IR) signature of plume and aircraft surface with variation in elevation angle (θ) is examined.

Convergent divergent (CD) nozzle is located outside the rear fuselage of the aircraft. A two dimensional axisymmetric computational fluid dynamics (CFD) study was carried out to study effect of M_∞ on potential core. The CFD data with aircraft and plume was then used for IR signature analysis. The sensor position is changed with respect to aircraft from directly bottom towards frontal section of aircraft. The IR signature is studied in mid wave IR (MWIR) and long wave IR (LWIR) band.

The potential plume core length and width increases as M_∞ increases. At higher altitudes, the potential core length increases for a fixed M_∞. The plume emits radiation in the MWIR band, whereas the aerodynamically heated aircraft surface emits IR in the LWIR band. The IR signature in the MWIR band continuously decreases as the sensor position changes from directly bottom towards frontal. In the LWIR band the IR signature initially decreases as the sensor moves from the directly bottom to the frontal, as the sensor begins to see the wing leading edges and nose cone, the IR signature in the LWIR band slightly increases.

The novelty of this study comes from the data reported on the effect of free stream Mach number on the potential plume core and variation of the overall IR signature of aircraft with change in elevation angle from directly below towards frontal section of aircraft.

This paper aims to numerically analyze the effect of non-gray gas radiation on mixed convection in a horizontal circular duct with isothermal partial heating from the sidewall. The influence of heater location on heat transfer, fluid flow and entropy generation is given and discussed in this study.

The numerical computation of heat transfer and fluid flow has been developed by the commercial finite element software COMSOL Multiphysics. Radiation code is developed based on the T₁₀ Ray-Tracing method, and the radiative properties of the medium are computed based on the statistical narrow band correlated-k model.

The obtained results depicted that the radiation considerably contributes to the temperature homogenization of the gas. The findings highlight the impact of the heater location on swirling flow. It is also shown that the laterally heating process provides better energy efficiency than heating from the top of the enclosure.

This study is performed to improve heat transfer and to minimize entropy generation. Therefore, it is conceivable to improve the model design of industrial applications.

This paper seeks to review the literature on methods for solving the radiative transfer equation (RTE) and integrating the radiant energy quantities over the spectrum required to predict the flow, the flame and the thermal structures in chemically reacting and radiating combustion systems.

The focus is on methods that are fast and compatible with the numerical algorithms for solving the transport equations using the computational fluid dynamics techniques. In the methods discussed, the interaction of turbulence and radiation is ignored.

The overview is limited to four methods (differential approximation, discrete ordinates, discrete transfer, and finite volume) for predicting radiative transfer in multidimensional geometries that meet the desired requirements. Greater detail in the radiative transfer model is required to predict the local flame structure and transport quantities than the global (total) radiation heat transfer rate at the walls of the combustion chamber.

The RTE solution methods and integration of radiant energy quantities over the spectrum are assessed for combustion systems containing only the infra‐red radiating gases and gas particle mixtures. For strongly radiating (i.e. highly sooting) and turbulent flows the neglect of turbulence/radiation interaction may not be justified.

Methods of choice for solving the RTE and obtaining total radiant energy quantities for practical combustion devices are discussed.

The paper has identified relevant references that describe methods capable of accounting for radiative transfer to simulate processes arising in combustion systems.

The purpose of this paper is to present a new approach of evaluation of the absorption line black body distribution function (ALBDF) for a mixture of gases. Currently published correlations, which are used to reproduce the ALBDF, treat only single gases.

A discrete form of the ALBDF is generated using line by line (LBL) calculations. The latest spectroscopic database HITEMP 2010 is used for the generation of the absorption coefficient histogram, which is cumulated later in order to produce a tabulated form of the ALBDF. The proper orthogonal decomposition (POD) statistical method is employed for the reproduction of the ALBDF. Interpolation property of the POD allows to reproduce the ALBDF for arbitrary gas mixture parameters.

POD proved to possess optimal interpolation properties. Results obtained by using POD are in very good agreement with LBL integration.

One have to be aware that the model generated with the POD method can be used only within the range of parameters used to build the model. The POD does not perform any property extrapolation. The model is limited to a mixture of two gases, namely CO₂ and H₂O. Expanding the number of gases used in the mixture may lead to a relatively large matrix system, which is difficult to process with the POD approach.

The presented approach can be used to produce absorption coefficients values and their weights, which can be applied in the gas radiative properties description using the weighted sum of gray gas (WSGG) concept. The proposed model can be used with any radiative transfer equation solver which employs the WSGG approach.

For the first time, radiative properties of gas mixtures are reproduced using the POD approach.

This study aims to investigate the insights of soot formation such as rate of soot coagulation, rate of soot nucleation, rate of soot surface growth and soot surface oxidation in ethylene/hydrogen/nitrogen diffusion jet flame at standard atmospheric conditions, which is very challenging to capture even with highly sophisticated measuring systems such as Laser Induced Incandescence and Planar laser-induced fluorescence. The study also aims to investigate the volume of soot in the flame using soot volume fraction and to understand the global correlation effect in the formation of soot in ethylene/hydrogen/nitrogen diffusion jet flame.

A large eddy simulation (LES) was performed using box filtered subgrid-scale tensor. A filtered and residual component of the governing equations such as continuity, momentum, energy and species are resolved and modeled, respectively. All the filtered and residual components are numerically solved using the ILU method by considering PISO pressure–velocity solver. All the hyperbolic flux uses the QUICK algorithm, and an elliptic flux uses SOU to evaluate face values. In all the cases, Courant–Friedrichs–Lewy (CFL) conditions are maintained unity.

The findings are as follows: soot volume fraction (SVF) as a function of a flame-normalized length for three different Reynolds number configurations (Re = 15,000, Re = 8,000 and Re = 5,000) using LES; soot gas phase and particulate phase insights such as rate of soot nucleation, rate of soot coagulation, rate of soot surface growth and soot surface oxidation for three different Reynolds number configurations (Re = 15,000, Re = 8,000 and Re = 5,000); and soot global correction using total soot volume in the flame volume as a function of Reynolds number and Froude number.

The originality of this study includes the following: coupling LES turbulent model with chemical equilibrium diffusion combustion conjunction with semi-empirical Brookes Moss Hall (BMH) soot model by choosing C6H6 as a soot precursor kinetic pathway; insights of soot formations such as rate of soot nucleation, soot coagulation rate, soot surface growth rate and soot oxidation rate for ethylene/hydrogen/nitrogen co-flow flame; and SVF and its insights study for three inlet fuel port configurations having the three different Reynolds number (Re = 15,000, Re = 8,000 and Re = 5,000).

This work proposes a tertiary wavelet model based automatic epilepsy classification system using electroencephalogram (EEG) signals.

In this paper, a three-stage system has been proposed for automated classification of epilepsy signals. In the first stage, a tertiary wavelet model uses the orthonormal M-band wavelet transform. This model decomposes EEG signals into three bands of different frequencies. In the second stage, the decomposed EEG signals are analyzed to find novel statistical features. The statistical values of the features are demonstrated using multi-parameters graph comparing normal and epileptic signals. In the last stage, the features are inputted to different conventional classifiers that classify pre-ictal, inter-ictal (epileptic with seizure-free interval) and ictal (seizure) EEG segments.

For the proposed system the performance of five different classifiers, namely, KNN, DT, XGBoost, SVM and RF is evaluated for the University of BONN data set using different performance parameters. It is observed that RF classifier gives the best performance among the above said classifiers, with an average accuracy of 99.47%.

Epilepsy is a neurological condition in which two or more spontaneous seizures occur repeatedly. EEG signals are widely used and it is an important method for detecting epilepsy. EEG signals contain information about the brain's electrical activity. Clinicians manually examine the EEG waveforms to detect epileptic anomalies, which is a time-consuming and error-prone process. An automated epilepsy classification system is proposed in this paper based on combination of signal processing (tertiary wavelet model) and novel features-based classification using the EEG signals.

This paper seeks to examine the potential for simplified market value and non market value based banded approaches to be utilised for residential property tax purposes. The broad aim is to ascertain whether relatively low complexity approaches to establishing a property tax base can perform adequately in comparison to established best practice – in essence whether there is evidence of equifinality (equivalent performance from approaches of substantially different complexity) between simpler and more complex approaches.

The research comprises empirical analysis of a database of property sales and property attribute data drawn from a UK District Council area. Several simplified methods are used to create different tax base scenarios and the outflowing tax incidence is compared with that of using a complex, industry standard market value approach. The methods of comparison are regression and spline regression based models testing for tax inequity, drawn from the literature. The approach here differs from previous work in that it occurs at the actual tax bill level allowing the comparison of value, non‐value and banded approaches.

The findings of the research indicate that simplified approaches to establishing a property tax base can perform in a broadly similar fashion to more complex systems currently practiced in developed economies and therefore evidence of equifinality exists.

The research provides useful tools to property tax policy makers and practitioners in developing and transitional economies in furthering their aspirations of embedding robust property taxes for the furtherance of socio‐economic and political development and the general wellbeing of society and they are of value to property tax policy makers and to academics in the field.

The paper provides evidence of the efficacy of simplified and banded approaches as an option for jurisdictions in developing and transitional economic circumstances or elsewhere in circumstances which mitigate against full scale appraisal of the property tax base to discrete market values. The approaches and techniques pioneered open up opportunities to carry out a range of new comparative analysis of tax base options.

To develop a new method for estimation of damage configuration in composite laminate structure using acoustic wave propagation signal and a reduction‐prediction neural network to deal with high dimensional spectral data.

A reduction‐prediction network, which is a combination of an independent component analysis (ICA) and a multi‐layer perceptron (MLP) neural network, is proposed to quantify the damage state related to transverse matrix cracking in composite laminates using acoustic wave propagation model. Given the Fourier spectral response of the damaged structure under frequency band‐selective excitation, the problem is posed as a parameter estimation problem. The parameters are the stiffness degradation factors, location and approximate size of the stiffness‐degraded zone. A micro‐mechanics model based on damage evolution criteria is incorporated in a spectral finite element model (SFEM) for beam type structure to study the effect of transverse matrix crack density on the acoustic wave response. Spectral data generated by using this model is used in training and testing the network. The ICA network called as the reduction network, reduces the dimensionality of the broad‐band spectral data for training and testing and sends its output as input to the MLP network. The MLP network, in turn, predicts the damage parameters.

Numerical demonstration shows that the developed network can efficiently handle high dimensional spectral data and estimate the damage state, damage location and size accurately.

Only numerical validation based on a damage model is reported in absence of experimental data. Uncertainties during actual online health monitoring may produce errors in the network output. Fault‐tolerance issues are not attempted. The method needs to be tested using measured spectral data using multiple sensors and wide variety of damages.

The developed network and estimation methodology can be employed in practical structural monitoring system, such as for monitoring critical composite structure components in aircrafts, spacecrafts and marine vehicles.

A new method is reported in the paper, which employs the previous works of the authors on SFEM and neural network. The paper addresses the important problem of high data dimensionality, which is of significant importance from practical engineering application viewpoint.