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PM 2.5 modelling during paddy stubble burning months using artificial intelligence techniques

Sangwan V., Deswal S.

Journal of Achievements in Materials and Manufacturing Engineering

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2022

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Vol. 110, nr 1

16--26

EN

Purpose: In this study, the artificial intelligence techniques namely Artificial Neural Network, Random Forest, and Support Vector Machine are employed for PM 2.5 modelling. The study is carried out in Rohtak city of India during paddy stubble burning months i.e., October and November. The different models are compared to check their respective efficacies and also sensitivity analysis is performed to know about the most vital parameter in PM 2.5 modelling. Design/methodology/approach: The air pollution data of October and November months from the year 2016 to 2020 was collected for the study. The months of October and November are chosen as paddy stubble burning and major festivities using fireworks occur during these months. The untoward data entries viz. zero values, blank data, etc. were eliminated from the gathered data set and thereafter 231 observations of each parameter were left for the conduct of the presented study. The different models i.e., ANN, RF, SVM, etc. had PM 2.5 as an output variable while relative humidity, sulfur dioxide, nitrogen dioxide, nitric oxide, carbon monoxide, ozone, temperature, solar radiation, wind direction and wind speed acted as input variables. The prototypes created from the training data set are verified on the testing data set. A sensitivity analysis is also done to quantify impact of various parameters on output variable i.e., PM 2.5. Findings: The performance of the SVM_RBF based model turned out to be the best with the performance parameters being the coefficient of determination, root mean square error, and mean absolute error. In the sensitivity test, sulphur dioxide (SO2) was adjudged as the most vital variable. Research limitations/implications: The quantification capacity of the generated models may go beyond the used data set of observations. Practical implications: The artificial intelligence techniques provide precise estimation and forecasting of PM 2.5 in the air during paddy stubble burning months of October and November. Originality/value: Unlike the past research work that focus on modelling of various air pollution parameters, this study in specific focuses on the modelling of most vital air pollutant i.e., PM 2.5 that too specifically during the paddy stubble burning months of October and November when the air pollution is at its peak in northern India.

2

Reflection of plane waves from a free surface of a generalized magneto-thermoelastic solid half-space with diffusion

Singh B., Singh L., Deswal S.

Journal of Theoretical and Applied Mechanics

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2014

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Vol. 52 nr 2

385--394

EN

Green-Naghdi’s theory of generalized thermoelasticity is applied to study the reflection of P and SV waves from the free surface of a magneto-thermoelastic solid half-space. The boundary conditions are satisfied by appropriate potential functions to obtain a system of four non-homogeneous equations in reflection coefficients. The reflection coefficients depend upon the angle of incidence of P and SV waves, magnetic field, thermal field, diffusion parameters and other material constants. The numerical values of the modulus of the reflection coefficients are shown graphically with the angle of incidence of P and SV waves. The effect of magnetic field is observed significantly on various reflected waves.

3

Distributed loads in an elastic solid with generalized thermodiffusion

Choudhary S., Deswal S.

Archives of Mechanics

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2008

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Vol. 60, nr 2

139-160

EN

The linear theory of generalized thermoelastic diffusion with one relaxation time is employed to study the interactions in a homogeneous, isotropic elastic solid, when a distributed instantaneous source is acting on the free surface of the body. The eigenvalue approach is adopted for the solution of a two-dimensional problem. The Laplace-Fourier transform technique is used. The expansions of the stresses, displacement components, temperature, concentration and chemical potential are obtained analytically. Numerical results are given and illustrated graphically, employing numerical methods for the inversion for transforms. Comparisons are made with the results predicted by the theory of generalized thermoelasticity and elasticity.

4

Axi-symmetric problem in a micropolar generalized thermoelastic half-space

Kumar R., Deswal S.

International Journal of Applied Mechanics and Engineering

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2007

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Vol. 12, no 2

413-429

EN

The disturbance due to mechanical and thermal sources in a homogeneous isotropic micropolar generalized thermoelastic half space is investigated by the use of Laplace-Hankel transform techniques. The integral transforms are inverted by using a numerical technique. The displacement components, temperature field, normal and tangential stresses are obtained in the physical domain for Lord-Shulman (L-S), Green-Lindsay (G-L) and Green-Naghdi (G-N) theońes of micropolar generalized thermoelasticity and are shown graphically for magnesium crystal like material.