Ruba Ahmad Odeh

The success of a construction project depends on several critical success factors in such a hazardous scenario characterized by COVID-19 and its consequent stress. One important factor is supervision by a competent project manager with higher emotional intelligence (EI) skills especially in these pandemic times of uncertainty. The selection of this kind of project manager is, by nature, one of the most important and, at the same time, most complicated decisions to be made due to a multi-criteria decision-making (MCDM) problem. Based on previous studies, the human emotion element is often overlooked in the decision-making process. Modern evaluation would require a multimodal dataset to evaluate a competent candidate for the position. In addition, it is identified that classical MCDM is static and unable to quantify real-time human emotion. Hence, in this study, our approach uses an integrated techniques for MCDM and deep learning to address the managers’ selection problem. Accordingly, a number of techniques, such as convolutional neural networks and other variations of algorithms, will be tested and compared. The emotion in our facial emotion recognition intensities value will be forwarded to MCDM as part of the input and eventually yield a non-bias and quality decision. It is anticipated that this study will enable employers to simplify and implement an effective decision-making process by embedding EI into the decision-making process to improve the quality of their hires and source the perfect candidate for construction project managers. Therefore, this study is aligned with the national construction agenda under the Construction 4.0 Strategic Plan (2021–2025), which requires changes to be made within the construction industry in tandem with the rapid development of technology and smarter systems. It emphasizes the utilization of digital technology as well as skills and knowledge enhancement.

A hybrid data-driven machine learning framework of artificial neural network and gene expression programming for predicting RHA concrete compressive strength.

Worldwide concern and ascendancy of emissions and carbon footprints have propelled a substantial number of explorations into green concrete technology. Furthermore, construction material costs have increased along with their gradual impact on the environment, which has led researchers to recognize the importance of natural fibers in improving the durability and mechanical properties of concrete. Natural fibers are abundantly available making them relatively relevant as a reinforcing material in concrete. Presently, it should be recognized that most construction products are manufactured using resources that demand a high quantity of energy and are not sustainable, which may lead to a global crisis. Consequently, the use of plant fibers in lightweight foamed concrete (LFC) is deemed a practical possibility for making concrete a sustainable material that responds to this dilemma. The main objective of this study is to investigate the effect of the addition of lignocellulosic fibers on the performance of LFC. In this investigation, four different types of lignocellulosic plant fibers were considered which were kenaf, ramie, hemp and jute fibers. A total of ten mixes were made and tested in this study. LFC samples with a density of 700 kg/m³ and 1400 kg/m³ were fabricated. The weight fraction for the lignocellulosic plant fibers was kept at 0.45%. The durability parameters assessed were flowability, water absorption capability, porosity and ultrasonic pulse velocity (UPV). The results revealed that the presence of cellulosic plant fibers in LFC plays an important role in enhancing all the durability parameters considered in this study. For workability, the addition of ramie fiber led to the lowest slump while the inclusion of kenaf fiber provided optimum UPV. For porosity and water absorption, the addition of jute fiber led to the best results.

Currently, the cost of construction rises along with the ongoing impact on the environment, and it has led the researchers to the acceptance of biomass natural fibers, such as biomass frond fiber (BFF), for the improvement of the mechanical properties of cement-based materials. BFF is abundantly accessible, making it relatively pertinent as a reinforcing material in foamed concrete (FC). In addition, natural fiber-reinforced concrete has been progressively employed in construction for several decades to reduce the crack growth under the static load. This paper intends to experimentally investigate the effectiveness of the addition of BFF to FC to improve its mechanical properties. The FC samples were strengthened with BFF at the weight fractions of 0.12%, 0.24%, 0.36%, 0.48%, and 0.60%. This study used three FC densities: 600 kg/m³, 800 kg/m³, and 1000 kg/m³, with fixed constitutions with 0.45 and 1:1.5 cement-to-water and cement-to-sand ratios, respectively. The evaluated strength characteristics included bending, splitting tensile, and compressive strengths. The experimental outcomes indicated that adding 0.36% BFF to FC facilitates optimal splitting tensile, compressive, and bending strength results. BFF enhances material strength by filling the spaces, microcracks, and gaps inside the FC structure. The BFF helped to reduce crack spreading when the plastic state of the FC cementitious matrix was loaded. Furthermore, the optimum level of BFF inclusion and the accumulation and the non-uniform distribution of BFF were detected, which caused the lowering of the strengths of the FC significantly. Beyond the optimum level of BFF, the agglomeration and the non-uniform dispersion of the BFF were seen, which resulted in a drop in mechanical properties. The output from this research will give a better insight into the potential utilization of plant fiber in FC. It is of profound significance to guide the sustainable development and application of FC material and infrastructures.

Recently, self-compacting concrete (SCC) has been increasingly used in high-rise buildings and industrial units, susceptible to accidental fires. The probable degradation of these structures necessitates understanding SCC behavior under elevated temperatures. For this, an extensive experimental investigation was undertaken to evaluate the effect of elevated temperature (300–600 °C) on the mechanical compressive properties of SCC; considering the effect of water-to-cement ratio (0.40–0.50), type of mineral aggregate and filler (limestone and basalt), and internal humidity. Standard cylinder (150 mm × 300 mm) and prism (100 mm × 100 mm × 300 mm) specimens were prepared from various SCC mixtures, cured for 28 d in limewater, and then stored at different environments for an additional 90 d to create varying internal humidity levels; ranging from 28 to 95%. Later, specimens were subjected to elevated temperatures in an electrical furnace, then cooled and tested for compressive mechanical response or non-destructively using resonance frequency, ultrasonic pulse velocity, and rebound hammer evaluation techniques. The results showed significant reduction in residual compressive strength, and elastic modulus, and an increase in compressive strain at peak stress and toughness as elevated temperature was increased. The SCC mixtures at upper water-to-cement ratios with basalt aggregate showed higher resistance to elevated temperatures than corresponding ones with limestone. Internal humidity in SCC had a detrimental impact on compressive strength and elastic modulus; especially at exposure temperatures below 400 °C. The statistical correlations between residuals for compressive strength or elastic modulus and nondestructive damage indices can be classified as very good. Furthermore, the nonlinear empirical models, developed to predict residuals for compressive strength and elastic modulus in terms of the study parameters, showed relatively high prediction potential, hence are recommended to be used in designing SCC mixtures for best resistance against possible fire attack.