Advances in Science and Technology Vol. 129

Abstract: The scarcity of drinking water is currently a critical issue in many parts of the world. Providing clean/urgent longer limited to natural sources. Wastewater treatment has become an urgent necessity in many countries, particularly in the Middle East and North African regions characterized by a desert climate. Hence, the development of effective methods for wastewater treatment is vital to overcome this water shortage. The present study attempts to explore the use of local clay from the United Arab Emirates (UAE) to prepare porous ceramic membranes (flat disk shape) for the purpose of removing toxic heavy metals from contaminated water. Two types of ceramic membranes were prepared by powder metallurgy method; the first type was prepared by uniaxial compression of the clay powder with particle size ≤ 250 μm, followed by sintering. The second type of membrane was composed of an activated carbon/clay powder mixture at different ratios (0.5%, 3% w/w). The activated carbon was used as an agent to form porosity in the plain clay membrane. The activated carbon was found to affect the final characteristics of the flat disk membranes sintered at 1000°C. 3% w/w activated carbon/clay powder was found to induce 19% porosity in the flat disc. The flat disc membranes were also characterized by X-ray diffraction, and scanning electron microscopy, X-ray fluorescence. The plain clay and 3% w/w activated carbon membranes were tested for their efficiency for water permeation. The results proved that the UAE clay could be considered as a promising material for the fabrication of ceramic membranes for prospective use in the removal of water contaminated with heavy metals.

Abstract: Water shortage has been a severe problem affecting the globe for the past decade. Therefore, appropriate and efficient technologies should be implemented to tackle the water shortage dilemma and to acquire clean water. Several desalination techniques are implemented across the world; among them is capacitive deionization (CDI). CDI is an energy-efficient and cost-effective electrochemical process employed for extracting charged ions from aqueous solutions using a pair of electrodes. Electrode materials strongly influence the CDI's desalination efficiency and conductivity. The CDI electrodes are composed of carbon materials such as activated carbon, carbon aerogel, carbon nanofibers, and porous carbon. However, in this study, carbon nanofibers that possess several advantages and properties over the existing materials have been examined to be used as CDI electrode material due to their high electrical conductivity, large surface area, dimensional stability, and low production cost. Furthermore, different conductive additives could be added to the carbon nanofibers to increase the electrical conductivity and capacitance. In particular, this paper discusses the effect of adding graphene oxide (GO) and carbon nanotubes (CNT) as additives to carbon nanofibers.

Abstract: Capacitive deionization is an emerging electrochemical technology employed in water desalination applications. Multiple water desalination technologies include reverse osmosis, multi-stage flash, humidification-dehumidification, and nanofiltration. Capacitive deionization is appreciably increased the desalination efficiency compared to other technologies while promising energy-efficient and cost-effective operation. In the CDI system, the charged ions are extracted from feedwater by applying an electrical voltage across electrodes, in which the charged ions are attracted to the oppositely charged electrodes. This paper demonstrates the concept of capacitive deionization (CDI), the components of CDI cell, working principal, and performance metrics for the CDI system. Furthermore, the paper reviews the state of technology of the CDI cell and the development of the system since the mid-1960, including the concepts of membrane and flow electrode CDI. Finally, a cost analysis framework of CDI, MCDI, and FCDI is demonstrated based on the Levelized cost of water.

Abstract: Modulus of Elasticity (Ec’) is a key parameter in structural engineering concrete designs. In concrete as a composite material, Ec’ is a function of compressive strength and the proportions of components in the concrete matrix (percentages of aggregates and cement). The inaccuracy and dispersity in estimating Ec’ from models provided by the existing codes of practice strongly affect the performance and design of the concrete structures. In this study, a dataset of 189 experimental concrete compressive strength results were collected from the available literature. The data set includes curing time (in days) for the concrete specimens, concrete density, experimental compressive strength (fc’), experimental Ec’ and several additives (e.g., slag, gypsum…etc.) with a total of 13 variables. Deep artificial neural networks (DANN) were used to model and analyze the effects of these variables on Ec’. A grid search over 2 hidden layers of DANNs was conducted to compute the best performed DANN. A total of 49 DANN models were developed in this study to predict concrete Ec’. The best performed DANN had a coefficient of determination (R²) of 0.81 and was selected for further analysis. Importance scoring was performed on the best DANN and results revealed that compressive strength had the highest importance score followed by water/cement ratio (w/c). Interestingly, the specimen sizes and curing days had the 6th and 8th scoring respectively from the 13 investigated variables. Ground pumice had the highest scoring compared to other additives. Sensitivity analyses were conducted revealing that at low specimen sizes of 10 mm, the Ec’ may vary by ~50%, while at higher size (150 mm), the Ec’ had less scatter and more reliable values.

Abstract: The building envelope is considered the boundary in which a building interacts with the surrounding environment. This paper aims to enhance building envelope design by biomimicry of the termite mound shape for reducing the energy demand as well as maintaining comfortable indoor temperatures. In this paper, two models with the same internal dimensions, cross-sectional area, and block material were constructed. The first model is a regular block model (RB) that represents a typical house construction. The second model (TM) development including the form and the envelope design is inspired by the termite mounds. The building model used the same principles of ventilation and thermoregulation in the same way as termite responds to extremely hot and humid conditions. Infrared thermography (IR) was carried out to measure the thermal performance of building envelopes throughout a full year. The influence of the termite model on the thermal properties such as the Decrement Factor (DF), Temperature Difference Ratio (TDR), and Time lag (Tlg) was investigated. The results suggest that the termite model (TM) can accumulate time lag for up to three hours on average. Investigation results indicated that the termite model improved for thermal repletion, unlike the regular model. The termite model absorbed more heat while the regular block model (RB) was thermally reflective.

Abstract: In this study, three-dimensional finite element modeling is utilized to simulate suction caisson foundations used for offshore wind turbines. The behavior of suction caissons in normally consolidated clayey soil subjected to lateral loading is investigated. A numerical model is calibrated and validated using experimental laboratory physical model. A parametric study is conducted to evaluate the effect of suction caisson diameter (D) and the ratio of skirt length (L) to caisson diameter (L/D) on the load-deflection response of a full-scale suction caisson. Several caisson diameters and length to diameter ratios were considered. The results of numerical analysis modeling demonstrated that the caisson ultimate load capacity and displacement are significantly affected by caisson geometry. Generally, increasing both the caisson diameter and length has substantially increased both caisson’s ultimate load capacity and displacement at failure. However, the increase in ultimate capacity and displacement reaches a threshold after which the increase in these values is less pronounced as D and L/D are further increased. Additionally, the effect of caisson geometry on relative stiffness is investigated. The relative stiffness of the suction caisson was found to increase proportionally with the increase of both diameter and length of the modeled caissons.

Abstract: This study measures the sustainable performance of ten car manufacturers operating in the U.S. We took into account three dimensions of sustainability: (a) economic, (b) environmental, and (c) social. Our methodology drew on the generalized directional distance function data envelopment analysis in conjunction with the multi-parametric method for bias correction of efficiency estimators. The combination of the two methods reduced the bias of efficiency estimators, which was sourced from the dimensionality of the production set and the sample size. Our analysis revealed that Chrysler-Fiat, GM, and Ford have the worst sustainable performance among firms under review over the years 2014–2018.

Abstract: This study emphasizes the assessment of efficiency and the degree of operating efficiency of mergers and acquisitions in the pharmaceutical industry worldwide. This industry encounters various challenges such as expiring patents, the rise of genetics pharmaceuticals, the entrance of biotechnology companies in the pharmaceutical market, the increasing research and development expenses, government regulations of the pharmaceutical industry, distribution channels, and drug prices. All these challenges result in an intensely competitive environment in which pharmaceuticals suffering from shortcomings (e.g., operational and/or financial inefficiencies) are not easy to catch up with the competition. Mergers and acquisitions are major activities to overcome shortcomings and achieve growth. Mergers and acquisitions have been widely used in the pharmaceutical industry for many years and are expected to accelerate. The objective of this work is to identify whether mergers and acquisitions between pharmaceutical companies can be successful and to highlight the most favourable consolidations. The assessment of mergers and acquisitions is realized through conventional and stochastic data envelopment analysis approaches. The empirical analysis draws on a sample of 371 pharmaceutical companies. The original sample was extended by 870 possible combinations between firms. Our empirical analysis reveals a positive impact of mergers and acquisitions on the efficiency of pharmaceutical companies.

Abstract: The purpose of this study was to explore airport performance and its impact on customers’ and employees’ satisfaction. This study applied a slacks-based measure network DEA (NSBM) model to evaluate the performance of sixteen international airports. Ten variables were incorporated in the two-stage NSBM model. Specifically, five inputs (i.e., number of employees, number of terminals, number of runways, airport area, and capacity) and three outputs (i.e., number of passengers, number of aircraft movements, and cargo) were used for the first stage. In the second stage, all outputs from the previous stage served as inputs (linking activities), while the outputs of this stage are the perceptions of employees and customers about the work environment and the quality of outputs produced by the first stage, respectively. Drawing on our empirical analysis findings, smaller airports perform better than larger counterparts. In particular, the airports that achieved satisfactory employees’ and customers’ satisfaction scores were those operating a comparatively high number of small-size terminals and have a relatively small number of employees.