This article explores the influence of corporate social responsibility (CSR) and three green triggers of environment (awareness, concern, and knowledge) on employee well‐being and green behavior. The study engages the stimulus–organism–response model for testing the association between CSR and well‐being of employees that leads to employee green behavior. Furthermore, social exchange theory has been utilized to describe the association between well‐being and green behavior of employees. Data have been gathered through questionnaire from 509 employees working in guest‐service hotels of Pakistan. Structural equation modeling has been used to test the hypotheses. Findings show that CSR, environmental concern, and knowledge have positive effect on employee well‐being, whereas environmental awareness has positive but insignificant effect on employee well‐being. Furthermore, environmental concern, knowledge, and well‐being have a positive influence on green behavior, whereas CSR and environmental knowledge have a positive but insignificant effect. Moreover, well‐being fully mediates the relationship between CSR and green behavior and between environmental awareness and green behavior of employees. However, a partial mediation was observed between environmental concern and green behavior. The findings also indicate that no mediation was found between environmental knowledge and employee green behavior. The findings suggest that the hotel managers should invest to improve employee's awareness regarding green behavior by conducting environmental training for cultivating environmental knowledge and awareness. Moreover, CSR activities should be performed for attaining competitive edge and maintaining a balance between progress and sustainability of environment.

Impact of CSR and environmental triggers on employee green behavior: The mediating effect of employee well-being

Sensing characteristics of electrostatic inductive sensor for flow parameters measurement of pneumatically conveyed particles

Laser-absorption tomography experiments infer the concentration distribution of a gas species from the attenuation of lasers transecting the flow field. Although reconstruction accuracy strongly depends on the layout of optical components, to date experimentalists have had no way to predict the performance of a given beam arrangement. This paper shows how the mathematical properties of the coefficient matrix are related to the information content of the attenuation data, which, in turn, forms a basis for a beam-arrangement design algorithm that minimizes the reliance on additional assumed information about the concentration distribution. When applied to a simulated laser-absorption tomography experiment, optimized beam arrangements are shown to produce more accurate reconstructions compared to other beam arrangements presented in the literature.

Laser-absorption tomography beam arrangement optimization using resolution matrices

We describe a fast optical tomography sensor which has been designed for the investigation of single- and two-phase flows in smaller flow cross-sections, such as pipes and bubble columns. It enables image acquisition at frame rates of up to 4.5 kHz at roughly 2 mm image resolution. The sensor works similar to a conventional CT of the fourth generation with 256 light emitters and 32 light receivers arranged about the object's cross-section. The light emitters are sequentially flashed while the light receiver intensities are recorded synchronously. A primary area of application is single-phase flows with dye tracers. Another potential application is the investigation of bubbly two-phase flows at low gas fractions. Principle tests have been made for both problems.

http://iopscience.iop.org/article/10.1088/0957-0233/19/9/094006/pdf

Design of an optical tomograph for the investigation of single- and two-phase pipe flows

Investigations into sensing characteristics of electrostatic sensor arrays through computational modelling and practical experimentation

This paper presents results for a tomographic system using an array of electrodynamic sensors. Sensitivity maps are derived for the individual sensors and then used by a back-projection algorithm to calculate concentration profiles from measured sensor values. Limitations in linearity over the sensing area are reduced by applying a filter to the images. The filtered back-projection algorithm is tested both on uniformly and on artificially produced non-uniformly distributed solids' flows.

https://iopscience.iop.org/article/10.1088/0957-0233/8/2/014/pdf

Concentration profiles of dry powders in a gravity conveyor using an electrodynamic tomography system

This paper describes measurements made on a gravity drop conveyor using two arrays of axially spaced electrodynamic sensors to measure axial velocities close to the wall of the conveyor and velocity profiles both of flowing sand and of plastic beads. The level of correlation obtained using pixels is investigated. The velocity profile is combined with a tomographic concentration profile to estimate the mass flow profile, which is summed over the measurement cross section to estimate the mass flow rate. A calibration of the tomographically determined mass flow rate versus the actual mass flow rate is presented.

Velocity and mass flow rate profiles of dry powders in a gravity drop conveyor using an electrodynamic tomography system

This paper describes an investigation into the optimum design of optical fibre sensing arrays to be incorporated in an optical tomographic measurement system for on-line monitoring of particles and droplets Two approaches are considered to cover opaque and transparent materials; optical path length and optical attenuation Four flow models are investigated: single-pixel flow representing a single particle or droplet, two-pixel flow as a simple check on aliasing in the reconstructed image, half flow representing half the sensing cross section filled with material and full flow, where the whole sensing cross section is full of material Six projection geometries of the fibre sensors are considered For tomographic imaging, the forward problem, which assumes particles are placed in specific places in the measurement cross section and calculates voltage outputs for the individual sensors, is modelled The solutions from the forward problem are used to solve the inverse problem, which uses actual sensor voltage readings to estimate the spatial distribution of the material in the measurement cross section The solution of the inverse problem is used to derive the linear back projection (LBP) and filtered LBP algorithms In order to improve image quality, a hybrid reconstruction algorithm is implemented This algorithm first checks if any sensors read zero and sets (locks for this estimation) all pixels associated with them to zero (no material) The algorithm then proceeds as for the LBP

Optical sensor configurations for process tomography

Fibre optic lens modelling for optical tomography

This paper describes modelling of optical fibre sensing arrays aimed at optimising the design of the tomography system being built by the authors. Two forms of optical sensing are considered; one relating to optical attenuation due to material with differing optical densities, the second to 'optical path length', which is used for opaque solids in air or liquid. The circular flow pipe is mapped onto an eight by eight rectangular array of pixels. Four flow models are investigated: a single pixel flow, two pixels flow, half flow and full flow models. Different arrangements of the fibre sensors are considered for various projections. The forward problem is solved for all combinations of flow model and sensor arrangement. Back projection and filtered back projection are used to reconstruct the image. A modified reconstruction algorithm combining LBP and a priori knowledge is outlined. Numerical tests, based on the reconstruction, are used to identify the best system to be implemented in hardware.

K Evans

Papers

Concentration profiles of dry powders in a gravity conveyor using an electrodynamic tomography system

Velocity and mass flow rate profiles of dry powders in a gravity drop conveyor using an electrodynamic tomography system

Optical sensor configurations for process tomography

Fibre optic lens modelling for optical tomography

Optical Fibres For Process Tomography: A Design Study