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Article
Publication date: 21 July 2020

Kamran Pazand and Kaveh Pazand

The chemical analysis of wells in the Ardabil area, Ardabil Province NW of Iran, was evaluated to determine the hydrogeochemical processes and ion concentration background in the…

503

Abstract

Purpose

The chemical analysis of wells in the Ardabil area, Ardabil Province NW of Iran, was evaluated to determine the hydrogeochemical processes and ion concentration background in the region. The purpose of this study is to analyze the hydrochemical quality of groundwater in Ardabil aquifer in order to assess the suitability of the waters for different uses.

Design/methodology/approach

The chemical analysis of 75 water wells in the Ardabil area, was evaluated. Over the entire area, the dominated hydrochemical types are: Na-Cl, Na-HCO3-Cl-Mg, Ca-SO4, Ca-Mg-SO4-Cl and Ca-Mg-HCO3. The abundance of the major ions is as follows: Na+>Ca2+>Mg2+>K+ and SO42–> Cl>HCO3 and major ion concentrations are below the acceptable level for drinking water. Most of groundwater samples fell in the soft water category. All of groundwaters belong to the excellent category and can be used safely for irrigation.

Findings

The chemical analysis of 75 water wells in the Ardabil area, Ardabil Province NW of Iran, was evaluated to determine the hydrogeochemical processes and ion concentration background in the region. Over the entire area, the dominated hydrochemical types are: Na-Cl, Na-HCO3-Cl-Mg, Ca-SO4, Ca-Mg-SO4-Cl and Ca-Mg-HCO3. The abundance of the major ions is as follows: Na+>Ca2+>Mg2+>K+ and SO42–> Cl>HCO3 and major ion concentrations are below the acceptable level for drinking water. Most of groundwater samples fell in the soft water category. All of groundwaters belong to the excellent category and can be used safely for irrigation.

Originality/value

The chemical analysis of 75 water wells in the Ardabil area, Ardabil Province NW of Iran, was evaluated to determine the hydrogeochemical processes and ion concentration background in the region. Over the entire area, the dominated hydrochemical types are: Na-Cl, Na-HCO3-Cl-Mg, Ca-SO4, Ca-Mg-SO4-Cl and Ca-Mg-HCO3. The abundance of the major ions is as follows: Na+>Ca2+>Mg2+>K+ and SO42–> Cl>HCO3 and major ion concentrations are below the acceptable level for drinking water. Most of groundwater samples fell in the soft water category. All of groundwaters belong to the excellent category and can be used safely for irrigation.

Details

Ecofeminism and Climate Change, vol. 1 no. 3
Type: Research Article
ISSN: 2633-4062

Keywords

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Article
Publication date: 2 October 2017

Kamran Pazand and A.S. Nobari

This paper aims to present a new approach to the fast determination of the effective, dynamic, mechanical properties of an adhesive for linear and nonlinear regions of the…

112

Abstract

Purpose

This paper aims to present a new approach to the fast determination of the effective, dynamic, mechanical properties of an adhesive for linear and nonlinear regions of the adhesive response, for both healthy and damaged states of the bond.

Design/methodology/approach

The proposed approach is based on the measurement of the linear and nonlinear frequency response function (FRF) of adhesive-bonded structure and using artificial neural network identification technique. For this purpose, linear and nonlinear FRFs are measured for several single-lap joint specimens that are fabricated in healthy and damaged configurations of the bond. The measured FRFs of healthy and damaged specimens are then used to identify the natural frequencies of the specimens. The experimental natural frequencies, in turn, would be used to train artificial neural network (ANN) which would be able to predict the effective Young’s and shear moduli and damping of adhesive in healthy and damaged specimens, for any given excitation level and frequency, within the training domain.

Findings

Simultaneous identification of the effective mechanical properties of adhesive for linear and nonlinear response regions, as well as healthy and damages states of the adhesive bond.

Practical implications

The introduced method is effective to model the assembled structures with the viscoelastic adhesive joints, for linear and nonlinear regions.

Originality/value

A fast methodology, using ANN, for identification the effective mechanical properties of adhesives, compared to other methods for both linear and nonlinear regions.

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