Journal of Engineering

This work investigates individual and social concerns regarding the integral sustainability of an alternative low-carbon cement. The framework of Integral Philosophy was used for the investigation. Social surveys were conducted in Australian, American, and Sri Lankan contexts. The data was collected through both closed-ended and open-ended questions in a questionnaire. Analysis of responses was carried out using fuzzy techniques and grounded theory techniques. Results indicate that individuals and societies in all three countries are more concerned about market price, quality standards, sustainability issues, and recommendations from professionals when selecting a new cement. In all three contexts, they also indicate that there is generally high support among individuals and societies for accepting low-carbon cement as an integrally sustainable cement. Combining the top-down Integral Theory approach with the bottom-up Grounded Theory is a valuable tool for social science research.

The most significant challenges wireless broadcasting systems face are channel effects and Inter Symbol Interference (ISI). Many different kinds of channel coding are employed to get around these issues. Digital Video Broadcasting for Satellite Telecommunication Second Generation (DVB-S2) uses a serial concatenation of Bose, Ray-Chaudhuri, and Hocquenghem (BCH) code and Low-Density Parity-Check (LDPC) code as a Forward Error Correction (FEC) for error detection purpose and correction. In this work, a MATLAB code (m-files) is constructed to simulate the standard DVB-S2 Bit-Interleaved Coded Modulation (BICM) system according to the ETSI Technical Report (EN 302 307 1). Then, the traditional design is redesigned with a Parallel Concatenation Convolutional (PCC) Turbo coding in concatenation with LDPC coding to enhance the (FEC). The two approaches have been tested under the official modulation types QPSK, 8PSK, 16APSK, and 32APSK with 2/3, 3/4, 3/5, 4/5, and 5/6 code rates (RC). Over a Rayleigh Fading channel, the two models are compared. The proposed model performed better than the standard model regarding bit error rate (BER) mitigation when operating at varying signal-to-noise ratio (SNR) levels, especially in 8PSK 3/5 MODCODE. The proposed model achieved (2.6272×10 -3) BER mitigation value with power gain equal to 4 dB.

Premature failure in asphalt concrete pavement has been the main concern for pavement construction companies and engineers in recent years because of the large rise in traffic volume and loads and the temperature extremes in the summer and winter. The use of modifiers in asphalt concrete mixtures has attracted much attention to increase the performance and lifespan of pavements. As nanotechnology developed, several researchers concentrated on how these materials can help increase pavement serviceability by minimizing rutting and moisture damage. This study evaluates the Hydrated Lime (HL) effect by two methods (wet and dry hydrated lime) on the durability of the warm mix asphalt. The first method, HL, has been supplemented to the asphalt binder with three ratios (0.5%, 1%, and 1.5%) by weight of asphalt (Wet HL). Then, the second method was added via the aggregate weight as a replacement filler using three percentages (1%, 2%, and 3%) (Dry HL). The mechanical qualities, including Marshall Mix design, moisture susceptibility, and permanent deformation, were evaluated through experimental tests. Results showed that the mechanical characteristics and the fineness of the HL particle sizes are positively correlated.

This study aims to find the best conditions of resistance spot welding in commercial Aluminium AA1050 to obtain the maximum tensile shear strength of the joint using a low-power supply welding machine. The chosen parameters for this study were welding current, welding time, and electrode force using a 90 kVA welding machine. The investigation used the DoE method with Taguchi’s technique to reduce the number of experiments where two sheet thicknesses (1 mm and 2 mm) were used in this work. The software program Minitab 18 analyzed the results using the main effects plots and the interaction plots to identify the most significant parameters and their effect on the joint strength. The best conditions for maximum tensile shear force were 14.85 kA welding current and 0.79 kN electrode force for both thicknesses and two cycles and 12 cycles welding time for 1 mm and 2 mm sheet thickness, respectively. The maximum tensile strength obtained was 250 N and 225 N for 1mm and 2mm sheet thickness, respectively. A mathematical equation was developed to predict the shear force with 19.9 % and 17.9 % error for 1 mm and 2 mm thicknesses, respectively. The best conditions were applied in ANSYS 2022R1 multi-physics to obtain the temperature distribution with time history, where the result shows the nugget size according to the molten temperature. The percentage of discrepancy between actual and numerical nugget size was 8 %.

Finding an alternative to materials that pollute during manufacturing, most notably cement, is vital to executing the idea of sustainability in the building sector. It was vital to develop concrete that assists in the reduction of CO2 (Carbon dioxide) in the atmosphere because industrial wastes contain calcium, silica, and aluminous minerals, such as silica fume, that are employed in the production of high-strength concrete and have parameters that are identical to those of regular concrete. As a substitute for Portland cement, lime cement was utilized, and 15% of the cement's weight was substituted with silica fume. Environmentally friendly fibers (Copper Fiber) created from old electrical and electronic equipment were also employed. The purpose of the study is to produce High Strength Green Fiber Concrete (HSGFC) by incorporating silica fume as a replacement and study the effect of adding fiber on some mechanical attributes. The task needed the creation of a high strength concrete mixture of cement with a compressive strength of 65 MPa in accordance with ACI 211.4R, as well as the development of numerous experimental mixtures that relied on the findings of earlier researchers. The mechanical properties (compressive strength, flexural strength and split tensile strength) of samples are tested at 7, 28 and 60 days with standard curing. The results show that adding sustainable fiber to concrete mix enhances the mechanical properties such as compressive strength by 16% at 28 days, flexural strength by 35% and spilt tensile strength by 44% at 28 days Compared with concrete mix with no fiber. Also, the outcomes showed that it is feasible to develop High Strength Concrete (HSC) using sustainable copper fiber possessing exceptional stress resistance, tensile strength, and flexural strength.

This paper proposes a biometric system to identify people by handprint, especially the palm area, using deep learning technology via a pre-trained model on the PolyU-IITD dataset. The proposed system goes through several basic stages, namely data pruning, processing, training, and prediction, and the results were promising, as the system's accuracy reached 90% based on the confusion matrix measures.

Several techniques are used to improve the channels' heat transfer coefficient and Nusselt number. One of the methods used for these improvements is porous media (PM). This research deals with an experimental study of heat transfer by forced convection inside a square-shaped channel (0.12 x 0.12 m²) with a length of (0.5 m) and a hydraulic diameter of (0.12 m). The heat flux (4791.7 W/m²) is exposed below the test section, and other walls are thermally insulated. The air was used as the working fluid for the Reynolds number range (2689.6 to 5806.3). The channel was partially filled with the PM (glass spheres with 5mm diameter) by taking three different heights layers (20, 40, and 60 mm) and knowing its effect on the temperature distribution, the local heat transfer coefficient, locally Nusselt number, and the average heat transfer coefficient and Nusselt number. Also, the same parameters were studied without PM inside the channel (plain). The results showed that the PM improved the heat transfer coefficient and the Nusselt number. Also, the temperature distribution decreased gradually with the Reynolds number increase for each height layer, the local heat transfer coefficient and local Nusselt number gradually reduced with the length of the test section increase for each Reynolds number, average Nusselt number increased gradually with the growth of the Reynolds number for each height layer. The PM layer at a height of (60 mm) gave the best improvement in the heat transfer coefficient and Nusselt number compared to the other layers. In addition, the friction factor across the test section at this layer decreases gradually with increasing fluid velocity.

In this work, a single Semi-Recurrent Spike Neural Network (SRSNN) supervised learning method based on time coding is proposed to classify visual terrain encountered by the mobile robot. To this end, the features are extracted using the Local Binary Pattern (LBP) method. Then, the SRSNN is trained to classify multi-class of terrains. This training is used to classify six classes of terrain: hydrop, gravel, asphalt, grass, mud, and sand. The proposed training algorithm is based on adaptive synaptic weights that reach the threshold value. The feature extracted method and SRSNN form the proposed Intelligent structure. This structure effectively evaluates the accuracy, precision, recall, and F1 score. The simulation results achieve good performance in minimizing the mean square error in the training phase and maximizing the overall accuracy to 87.22%, especially in dangerous terrain (i.e. hydrop). The effectiveness of the proposed model is proved by the efficiency of the training algorithm which can learn fast with accurate results.

In recent years, many city centers have experienced severe traffic congestion due to focusing on personal transportation, with cars being the easiest and fastest means of travel. The excessive use of cars has led to neglect of social and environmental aspects, further exacerbating the issue. Historical city centers are particularly affected as they are often commercial hubs with an organic network of roads that increase the difficulty of access and movement. As a result, congestion has intensified, and cars have become the only means of transportation between different parts of the city. This research aims to analyze the effects of traffic congestion in city centers by focusing on a case study of AlKarkh. The study relied on observing and collecting information available at the site, calculating movement densities during peak times on five busy days, and analyzing the data. Additionally, the study compared the results with data from 2014 to assess changes in movement densities. The findings from this research can provide evidence for urban planning that aims to develop the road network in historical city centers and improve transportation policies.

This review provides a detailed look at the current knowledge and approaches related to Dynamic Soil-Structure Interaction (DSSI) in machine foundation design, focusing on its substantial impact on seismic response and structural stability. The significance of this interaction in structural design, especially in areas prone to seismic activity, is pivotal. The paper begins by exploring various modeling methods, like the Finite Element Method (FEM), highlighting their importance in understanding the intricate aspects of DSSI, such as energy loss and interface behavior. It is evident from the studies that FEM is particularly effective in analyzing settlement under reciprocating loads. Soil-structure interaction (SSI) is a complex phenomenon that can positively and negatively affect the seismic performance of machine foundations. Several factors, including embedment depth, soil stiffness, and foundation properties, govern the influence of SSI. This review discusses the dual nature of SSI and highlights the importance of considering the interaction between soil properties, foundation design, seismic loads, and interaction effects. In addition, it identifies the limitations of the current research and advocates for more accurate and inclusive models and extensive empirical studies to address real-world complexities and uncertainties. In conclusion, this review offers crucial insights and foundational knowledge for future innovative design solutions and advanced research methodologies and significantly contributes to developing resilient and reliable structural designs in seismic-prone regions. The emphasis is on the need for more nuanced and comprehensive studies to further the understanding and application of DSSI in machine foundation design.

Incorporating the LiDAR sensor in the most recent Apple devices represents a substantial development in 3D mapping technology. Meanwhile, Apple's Lidar is still a new sensor. Therefore, this article reviews the potential uses of the Apple Lidar sensor in various fields, including engineering and construction, focusing on indoor and outdoor as-built 3D mapping and cultural heritage conservation. The affordable cost and shorter observation times compared to traditional surveying and other remote sensing techniques make the Apple Lidar an attractive choice among scholars and professionals. This article highlights the need for continued research on the Apple LiDAR sensor technology while discussing its specifications and limitations. A comprehensive review found that the Apple LiDAR sensor has shown promise in capturing 3D point clouds of small to medium-sized objects with exceptional detail. This technology offers a cost-effective and accessible option to scan areas faster and analyze data more quickly and automatically for 3D mapping and modelling in indoor and outdoor environments, particularly in areas with restricted access when using other traditional techniques. It also opens the door for more sophisticated applications in future studies, including cultural heritage conservation, archaeological investigations and feature detection, building health monitoring and many more.

This study examined experimentally and numerically the performance of five concrete beams reinforced with longitudinal and transverse bars made of Glass Fiber Reinforced Polymer (GFRP) or steel. All beams had the same dimensions of 2700 mm in length, 180 mm in width, and 260 mm in depth. The beams were classified into two groups with different variables and compared with a reference beam reinforced with longitudinal and transverse steel bars. The first group consisted of two beams with longitudinal GFRP bars and no stirrups, varying the main reinforcement ratio. The second group comprised two beams with longitudinal GFRP bars and transverse GFRP or steel stirrups, varying the stirrup type. The results indicated that the beams with GFRP bars improved their flexural strength for different ratios but had limited shear resistance when using GFRP stirrups because increased deflection causes the number and width of cracks to grow, reducing the shear strength. All the tested beams exhibited linear elastic behavior until failure, with GFRP being more brittle than steel due to no yield point or plastic behavior in GFRP. The numerical simulation of the five beams using ABAQUS software showed good agreement with the experimental data obtained in the laboratory.