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The purpose of this paper is to predict and control the composition during laser additive manufacturing, since composition control is important for parts manufactured by laser additive manufacturing. Aluminum and steel functionally graded material (FGM) were manufactured by laser metal deposition, and the composition was analyzed by means of spectral analysis simultaneously.

The laser metal deposition process was carried out on a 5 mm thick 316L plate. Spectral line intensity ratio and plasma temperature were chosen as two main spectroscopic diagnosis parameters to predict the compositional variation. Single-trace single-layer experiments and single-trace multi-layer experiments were done, respectively, to test the feasibility of the spectral diagnosis method.

Experiment results showed that with the composition of metal powder changing from steel to aluminum, the spectral intensity ratio of the characteristic spectral line is proportional to the elemental content in the plasma. When the composition of deposition layers changed, the characteristic spectrum line intensity ratio changed obviously. And the linear chemical composition analysis results confirmed the gradient composition variation of the additive manufacturing parts. The results verified the feasibility of composition analysis based on spectral information in the laser additive manufacturing process.

The composition content of aluminum and steel FGM was diagnosed by spectral information during laser metal deposition, and the relationship between spectral intensity and composition was established.

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.

The presented principal objective is information retrieval from tepetitiously generated data sets. In contrast to conventional, formally statistical analysis, the genesis of data is postulated as the principal feature of analysis for obtaining the optimum of information from any data set. Consequently, arbitrary randomization of naturally sequential data, formal averaging, and “amplitude‐classification” of formal statistics are rejected because of suppression of information. Preservation of information is accomplished by pattern classification of coherent data sets into characteristic pattern prototypes. Examples are given.

The purpose of the study is to investigate and reveal this relationship of various engineering demand parameters (EDPs) of this structural type and intensity measures (IMs) under intra-plate earthquakes.

The nonlinear finite element model used was calibrated first to the existing results of the shaking table test to verify the modeling technique.

This paper investigated the relationship between intensity measures and various engineering demand parameters of cable-stayed bridges using intra-plate earthquakes. The correlation analysis and Pearson coefficient are used to study the correlation between EDPs and IMs. The results showed that peak ground velocity (PGV)/peak ground acceleration, peak ground displacement and root-mean-square of displacement showed weak correlation with IMs. PGV, sustained maximum velocity, a peak value of spectral velocity, A95 parameter, Housner intensity and spectral acceleration at the fundamental period, the spectral velocity at the fundamental period and spectral displacement at the fundamental period were determined to be better predictors for various EDPs.

This paper investigated the correlation between the intensity measures of intra-plate earthquakes with the seismic responses of a typical long-span cable-stayed bridge in China. The nonlinear finite element model used was calibrated to the existing results of the shaking table test to verify the modeling technique. In total, 104 selected ground motions were applied to the calibrated model, and the responses of various components of the bridge were obtained. This study proposed PGV as the optimal IM.

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.

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.

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.

The aim of this paper is to present advanced experimental–numerical methods for identification of spectral absorption and scattering properties of highly porous ceria ceramics in the range of semi-transparency at room and elevated temperatures.

At room temperature, a period of quasi-steady oscillations of the sample surface temperature generated in response to recurrent laser heating at fixed values of the maximum and minimum temperature of the irradiated surface is measured along with the normal-hemispherical reflectance. Radiative properties are then identified using a combined heat transfer model. At elevated temperatures, an analytical solution proposed in an earlier study for zirconia ceramics is used to retrieve spectral absorption coefficient of ceria ceramics from the measured normal emittance.

This method can be used to obtain small absorption coefficient of ceria ceramics at room temperature. The required measurements of both the normal-hemispherical reflectance and the period of quasi-steady oscillations of the irradiated surface temperature of the ceramics sample between fixed values of the maximum and minimum temperatures can be readily conducted using thermal laboratory equipment. Another method has been suggested for identification of the spectral absorption coefficient of ceria ceramics at elevated temperatures. This method is based on a relation between the measured normal emittance of an isothermal sample and the absorption coefficient.

A new way of solving the steady‐state coupled radiative‐conductive problem in semi‐transparent media is proposed. An angular discretization technique is applied in order to express the radiative transfer equation (RTE) in an inhomogeneous system of linear differential equations associated with Dirichlet boundary conditions. The system is solved by a direct method, after diagonalizing the characteristic matrix of the medium. The RTE is coupled with the nonlinear heat conduction equation. A simulation of a real semi‐transparent medium composed of silica fibers is illustrated. Comparison with results of other methods validates the new model. Moreover, the general scheme is easy to code and fast. The algorithm proved to be robust and stable.

Output stability or drift overtime has long been a major performance deficiency for gas sensors irrespective of what technology or methodology is used for their conception. Software correction may alleviate the problem somewhat but it is not always applicable. It has long been the objective of many researchers in this field to overcome this problem fundamentally and for good. The purpose of this paper is to show that this objective has now finally been achieved.

Conventional non‐dispersive infrared (NDIR) dual beam methodology utilizes the ratio of signal channel output over reference channel output for signal processing. The signal filter overlaps the absorption band of the gas of interest while the reference filter does not. However, this ratio changes as the source ages. The current methodology uses an absorption bias between signal and reference channel outputs. This absorption bias is created by using a path length for the signal channel greater than that for the reference channel. Both the signal and reference detectors carry an identical spectral filter overlapping the absorption band of the gas to be measured.

Implementation of the currently patented NDIR gas‐sensing methodology has been carried out in different gas sensor configurations for over a year in the laboratory. Performance results for these sensors showing insignificant output drifts overtime have been repeatedly demonstrated via simulated aging for the source.

The paper puts forward the view that the recent breakthrough of the Near Zero Drift methodology for NDIR gas sensors will very quickly change the hierarchy of technology dominance and utility for gas sensors at large.