Eng, Volume 4, Issue 3 (September 2023) – 41 articles

A quantitative evaluation of the musical timbre and its variations is important for the analysis of audio recordings and computer-aided music composition. Using the FFT acoustic descriptors and their representation in an abstract timbral space, variations in a sample of monophonic sounds of chordophones (violin, cello) and aerophones (trumpet, transverse flute, and clarinet) sounds are analyzed. It is concluded that the FFT acoustic descriptors allow us to distinguish the timbral variations in the musical dynamics, including crescendo and vibrato. Furthermore, using the Random Forest algorithm, it is shown that the FFT-Acoustic provides a statistically significant classification to distinguish musical instruments, families of instruments, and dynamics. We observed an improvement in the FFT-Acoustic descriptors when classifying pitch compared to some timbral features of Librosa. Full article

The accurate prediction of underground formation lithology class and tops is a critical challenge in the oil industry. This paper presents a machine-learning (ML) approach to predict lithology from drilling data, offering real-time litho-facies identification. The ML model, applied via the web app “GeoVision”, achieves remarkable performance during its training phase with a mean accuracy of 95% and a precision of 98%. The model successfully predicts claystone, marl, and sandstone classes with high precision scores. Testing on new data yields an overall accuracy of 95%, providing valuable insights and setting a benchmark for future efforts. To address the limitations of current methodologies, such as time lags and lack of real-time data, we utilize drilling data as a unique endeavor to predict lithology. Our approach integrates nine drilling parameters, going beyond the narrow focus on the rate of penetration (ROP) often seen in previous research. The model was trained and evaluated using the open Volve field dataset, and careful data preprocessing was performed to reduce features, balance the sample distribution, and ensure an unbiased dataset. The innovative methodology demonstrates exceptional performance and offers substantial advantages for real-time geosteering. The accessibility of our models is enhanced through the user-friendly web app “GeoVision”, enabling effective utilization by drilling engineers and marking a significant advancement in the field. Full article

Adopting a multiscale approach is crucial for optimizing urban and building performance, prompting inquiries about the link between a technology’s local efficiency (building scale) and its broader impact (city-wide). To investigate this correlation and devise effective strategies for enhancing building and city energy performance, we experimentally examined a commercial nano-ceramic Thermal Barrier Coating (TBC) on a small-scale building and assessed numerically its influence on mitigating Urban Heat Islands (UHIs) at a city scale, translated in our case by the use of the thermal comfort index: the Universal Thermal Climate Index (UTCI). Our results reveal that the coating significantly curbs heat transfer locally, reducing surface temperatures by over 50 ${}^{\circ }$C compared to traditional roofs and attenuating more than 70% of heat flux, potentially alleviating air conditioning demands and associated urban heat effects. However, implementing such coatings across a city does not notably advance overall efficiency and might trigger minor overheating on thermal perception. Hence, while nano-ceramic coatings indirectly aid UHI mitigation, they are not a standalone fix; instead, an integrated strategy involving efficient coatings, sustainable urban planning, and increased vegetation emerges as the optimal path toward creating enduringly sustainable, pleasant, and efficient urban environments to counter urban heat challenges effectively. Full article

Mining plays a pivotal role in economies worldwide, contributing to employment, infrastructure, and the supply of essential raw materials. Chile’s global mining powerhouse, particularly in copper production, exemplifies this industry’s economic significance. The supplier selection process in the mining industry, a complex and multifaceted task, is explored in detail, specifically focusing on explosives procurement, a critical component for mineral extraction. The paper underscores the importance of informed supplier selection decisions, especially for SMEs, which often need more resources and capabilities for efficient management. To address these challenges, the study proposes applying the Analytic Hierarchical Process (AHP), a multi-criteria decision-making methodology, to identify and prioritize the criteria and sub-criteria pertinent to choosing explosives suppliers. A case study in the Coquimbo Region, Chile, involving SMEs in the mining sector is the empirical foundation for this research. Our research highlights that the foremost criterion for SMEs in the Coquimbo Region’s mining sector is “relationship with the environment and communities”. This reflects the national context of mining community tensions and the rising environmental standards and social expectations, which can profoundly impact mining operations. “Quality of products and services” is the second most crucial criterion, underscoring SMEs’ drive to enhance productivity and efficiency. “Contractual compliance” follows closely, signifying the integration of SMEs into broader social and environmental sustainability efforts. Conversely, “innovation” ranks as the least relevant criterion, indicating that SMEs prioritize traditional processes due to limited resources and cost constraints. These insights are valuable for mining supplier company managers, emphasizing the need for sustainability, corporate social responsibility, and management control systems. Full article

The science of catalysis has a direct impact on the world economy and the energy environment that positively affects the environmental ecosystem of our universe. Any catalyst, before being tested in a reaction, must undergo a specific characterization protocol to simulate its behavior under reaction conditions. In this work, these steps that must be carried out are presented, both generically and with examples, to the support and to the catalyst itself before and after the reaction. The first stage consists of knowing the textural and structural properties of the support used for the preparation of the catalysts. The specific surface area and the pore volume are fundamental properties, measured by N₂ adsorption at −196 °C when preparing the catalyst, dispersing the active phase, and allowing the diffusion and reaction of the reactants and products on its surface. If knowing the structure of the catalyst is important to control its behavior against a reaction, being able to analyze the catalyst used under the reaction conditions is essential to have knowledge about what has happened inside the catalytic reactor. The most common characterization techniques in heterogeneous catalysis laboratories are those described in this work. As an application example, the catalytic conversion of CO₂ to CH₄ has been selected and summarized in this work. In this case, the synthesis and characterization of Cu and Ni catalysts supported on two Al₂O₃ with different textural properties, 92 and 310 m²/g, that allow for obtaining various metallic dispersions, between 3.3 and 25.5%, is described. The catalytic behavior of these materials is evaluated from the CO₂ methanation reaction, as well as their stability from the properties they present before and after the reaction. Full article

Because textile industries are intensely water-consuming and generate a huge quantity of wastewater, the present study examines the scope of using solar thermal technology to treat wastewater from textile industries. A hybrid technology, comprising a compound parabolic concentrator-based solar thermal system in conjunction with a Membrane Distillation (MD) system, is experimented with for wastewater treatment in textile industries. The MD system requires a water temperature of around 90 °C for efficient functioning. The advanced MD technology using waste heat combined with solar heat to meet the system’s thermal load is technologically evaluated for an experimental textile industry in India. Moreover, the present study critically analyses the techno economics of the proposed hybrid technology. A detailed financial analysis has revealed that, besides technological superiority, the recommended technology is also financially rewarding for wastewater treatment in the textile industry. To cope with the delayed payback period, financial incentives are recommended so that the system becomes a lucrative technological option. Full article

The business world is becoming more competitive. Therefore, it is crucial to increase the flexibility of production by decreasing the time used in the processes of preparing the production lines for new items’ production, reducing changeover and setup times. This paper presents a case study where the main goal is to reduce the setup time of welding robots. Single Minute Exchange of Die (SMED) was implemented, using other tools such as the Spaghetti Diagram, ERCS Analysis (Eliminate, Rearrange, Combine, Simplify), Gemba Walk, Standardized Work, Flowcharts, and Pareto Diagram. The setup time decreased by 36% in the welding robots studied, decreasing the motions by 43% during the changeover process and reducing the time from the categories: “transportation”, “main”, “other”, and “waiting”. In addition to SMED implementation, this study offers an integrated study of several Lean tools and Quality tools to achieve the maximum reduction of changeover and setup times. Full article

Background: Artificial Intelligence has been an area of great interest and investment in the industrial sector, offering numerous possibilities to enhance efficiency and accuracy in production processes. In this regard, this study aimed to identify the adoption challenges of Artificial Intelligence and determine which of these challenges apply to the industrial context of an emerging economy, considering the aspects of Industry 4.0. Methods: To achieve this objective, a literature review was conducted, and a survey was carried out among professionals in the industrial field operating within the Brazilian context. The collected data were analyzed using a quantitative approach through Cronbach’s alpha and the Lawshe method. Results: The results indicate that to enhance the adoption of Artificial Intelligence in the industrial context of an emerging economy, taking into account the needs of Industry 4.0, it is important to prioritize overcoming challenges such as “Lack of clarity in return on investment,” “Organizational culture,” “Acceptance of AI by workers,” “Quantity and quality of data,” and “Data protection”. Conclusions: Therefore, based on the achieved results, it can be concluded that they contribute to the development of strategies and practical actions aimed at successfully driving the adoption of Artificial Intelligence in the industrial sector of developing countries, aligning with the principles and needs of Industry 4.0. Full article

In the present study, the concept of utilizing two circular cam-track disks, of the same central angle, in combination with one circular roller is presented. The roller is restrained to move within a vertical groove, and at the same time it rotates with rolling-contact on both cam tracks. When the upper cam is fully travelled by the roller, the same occurs with the lower one, despite their different lengths. Therefore, during the rolling contact, the two cams always sweep the same central angle. The aforementioned configuration of the two circular arcs may be considered as a unit cell, which can be repeated an even number of times, and when folded forms a closed circular groove between two cam-track disks. For better understanding, a manufactured prototype and 3D CAD-models have been developed. The operation of this setup as a gearless automotive differential is demonstrated by performing two bench experiments, which are then explained by a simplified mechanical model. The latter focuses on the implementation of the principle of the inclined plane, in which an upper limit of the inclination angle is imposed in accordance with the coefficient of friction at the friction disks. Previous patents on gearless differentials are discussed and other possible applications in mechanical engineering are outlined. Full article

This article examines the comparative effectiveness of three indoor node localization techniques—Multilateration, the Weighted Centroid algorithm, and Grid-based Received Signal Strength (RSS)—in wireless networking applications. The comparison is based on their performance against localization accuracy using RSS Indicator (RSSI) data in three experiments. The experiments utilized internally generated or real-world datasets with RSSI values for the unknown tag nodes. The datasets were obtained from various sources and evaluated in different scenarios to determine the efficiency of the three localization techniques. The results were evaluated and compared using mean error and standard deviation metrics. The findings indicate that trilateration achieves superior localization accuracy and precision in a Bluetooth Low Energy (BLE) environment compared to Wi-Fi and ZigBee. The Centroid technique showed the highest resistance to noise and outliers but is positioned biased (unlike Trilateration). Besides that, the Grid-based RSS technique is highly sensitive to noise, and theoretical RSS. These findings can greatly assist researchers and network operators in carefully selecting the most suitable localization technique for their wireless networking applications, taking into account the specific wireless technology utilized and their unique needs and limitations. Full article

This paper presents a new methodology to evaluate the performance of an electric vehicle hybrid power system consisting of a fuel cell and a supercapacitor. The study compares the results to those obtained for a battery electric vehicle. The methodology extends to three driving modes, ECO, NORMAL, and SPORT, corresponding to conservative, moderate, and aggressive acceleration, and three driving conditions, low, medium, and high energy demand. We develop a simulation process to evaluate the energy consumption and the energy rate of a specific electric vehicle used as a prototype for the study. The methodology applies to a driving route that includes acceleration, deceleration, braking, and constant speed segments, reproducing standard driving conditions in urban journeys. The proposed method considers combined driving modes, ECO, NORMAL, and SPORT, in each acceleration process, with variable fractions, from 0% to 100%, for each mode. This methodology optimizes the simulation results for the current driving patterns in urban environments. The simulation results show an average reduction in energy consumption of 37% and 27.1% in vehicle weight, contributing to lower energy use. The study concludes that using a hybrid power system, a fuel cell/supercapacitor, instead of a battery in electric vehicles is beneficial, especially in journeys with frequent acceleration processes. Full article

As photovoltaics (PV), also known as solar electricity, has been growing over the years, the energy markets have been gradually moving toward decentralization. However, recent media accusations suggest that decentralized renewable energy is slowly becoming unpopular because of the hidden fees being charged to owners of installed PV systems. In response, this paper investigates the potential for alternative approaches to incentivize owners using peer-to-peer (P2P) sharing. This study provides an analytical comparison between the use of the P2P mechanism, the net-metering mechanism, and a combination of these in the commercial sector. Through the use of a simulation, this case study presents the possible outcomes of the implementation of these models in a microgrid. Using technical and economic indexes the comparison was made by looking at the following indexes: peak power, energy balance, economic benefit, and transaction index. Based on a microgrid of 28 commercial buildings, readings of consumption were taken at intervals of one hour, and a Python model was made to find PV size and compare trading mechanisms. It was found that the combination of P2P and net-metering had the best overall performance, followed by net-metering itself, with the best season being all for both, and summer for net-metering by itself. This shows that a P2P model implemented in a microgrid helps create more energy balance, although the combination would achieve the highest performance. This study can be used by policymakers for proposing renewable energy policies and regulations that are more beneficial to all prosumers and consumers. Full article

Lateral distortional buckling (LDB) is an instability phenomenon characteristic of steel-concrete composite beams (SCCB) that occurs in the presence of hogging moments in regions close to internal supports. The LDB behavior in SCCB is not yet fully understood. The procedures for determining the LDB strength are based on the classic lateral torsional buckling theory or on the inverted U-frame model. In addition, the standard procedures make use of the classic design curves of the SSRC (Structural Stability Research Council) and ECCS (European Convention for Constructional Steelwork) developed to analyze the stability behavior of steel elements. However, studies indicate that the use of the same empirical curves obtained for the analysis of steel elements leads to the conservative results of the LDB strength in SCCB. Therefore, this article aims to assess the LDB strength in SCCB through the development of post-buckling numerical analysis using the ABAQUS software. In the parametric study, four types of steel with different mechanical properties were analyzed. In addition, the I-section, the unrestrained length, and the reinforcement rate in the concrete slab were varied. The results showed the influence of the steel type on the LDB strength and deviations from the standard procedures. A small influence of the longitudinal reinforcement area variation was verified in the LDB strength in the FE analyses; however, this factor is significantly important in the standard procedures, causing considerable divergences. These results can provide a reference for future research and specification reviews. Full article

The study examines decentralized waste treatment in an urban setting with a high-density population of 2500 inhab./km². The co-digestion of food and garden waste was assumed by using several mid-size digesters, while centralized biogas and digestate valorization was considered. The studied configuration generates electricity and thermal energy, covering 1.3% of the residential electricity demand and 3.2% of thermal demand. The use of double-turbocharged engines under the most favorable scenario aids cities in reaching sustainability goals. However, the location of treatment plants is a factor that may raise social discomfort and cause a nuisance to citizens. Locating waste plants near residential areas causes discomfort due to possible odors, gaseous emissions, and housing market distortions. Such problematic aspects must be addressed for the decentralized alternative to work. These factors are of great relevance and must be given a practical solution if the circular economic model is to be implemented by considering the insertion of waste streams into the production system and generating local energy sources and raw materials. Full article

The authors present a case study of the investigation of a transient signal that appeared in the testing of a radar receiver. The characteristics of the test conditions and data are first discussed. The authors then proceed to outline the methods for detecting and analyzing transients in the data. For this, they consider several methods based on modern signal processing and evaluate their utility. The initial method used for identifying transients is based on computer vision techniques, specifically, thresholding spectrograms into binary images, morphological processing, and object boundary extraction. The authors also consider deep learning methods and methods related to optimal statistical detection. For the latter approach, since the transient in this case was chirp-like, the method of maximum likelihood is used to estimate its parameters. Each approach is evaluated, followed by a discussion of how the results could be extended to analysis and detection of other types of transient radio-frequency interference (RFI). The authors find that computer vision, deep learning, and statistical detection methods are all useful. However, each is best used at different stages of the investigation when a transient appears in data. Computer vision is particularly useful when little is known about the transient, while traditional statistically optimal detection can be quite accurate once the structure of the transient is known and its parameters estimated. Full article

Thermal images are highly dependent on outside environmental conditions. This paper proposes a method for improving the accuracy of the measured outside temperature on buildings with different surrounding parameters, such as air humidity, external temperature, and distance to the object. A model was proposed for improving thermal image quality based on KMeans and the modified generative adversarial network (GAN) structure. It uses a set of images collected for objects exposed to different outside conditions in terms of the required weather recommendations for the measurements. This method improves the diagnosis of thermal deficiencies in buildings. Its results point to the probability that areas of heat loss match multiple infrared measurements with inconsistent contrast for the same object. The model shows that comparable accuracy and higher matching were reached. This model enables effective and accurate infrared image analysis for buildings where repeated survey output shows large discrepancies in measured surface temperatures due to material properties. Full article

The tomato processing industry is focused on product yield maximization, keeping energy costs and waste effluents to a minimum while maintaining high product quality. In our study, cold atmospheric plasma (CAP) pretreatment enhanced tomato processing to facilitate peelability, a specific peeling process, and enhance peel drying. Peeling force analysis determined that CAP pretreatment of whole tomatoes improved peelability under the conditions used. The specific peeling force after CAP treatment decreased by more than three times. It was observed that cold atmospheric plasma pretreatment reduced the duration of infrared drying of tomato peels by 18.2%. Along with that, a positive effect on the reduction of the specific energy consumption of peel drying was shown for CAP-pretreated tomato peels. The obtained data show that the technology of cold atmospheric plasma pretreatment, in particular, when processing whole tomatoes and tomato peels, has a promising application in industry, as it can significantly reduce the specific energy consumption for peeling and drying procedures. Full article

This paper begins with an introduction to porcelain tiles. A review of the major scientific and technological features of mullite-based porcelain tiles (MPTs) and anorthite-based porcelain tiles (APTs), focusing primarily on the raw material, processing, phase evolution and mechanical behavior, is then presented. Based on the porcelain tile firing behavior and a series of physical and chemical changes that can occur, a comprehensive comparison is described. In the last part, the prospects for further developments related to MPTs and APTs are discussed. Full article

Low-cost sorption materials based on the clay mineral of the smectite group—montmorillonite—were used for the removal of radionuclides uranium (VI) and strontium (II) from contaminated water. A wide range of industrial methods such as thermal treatment, acid activation, and mechanochemical activation were applied. Complex methods, such as SEM microscopy analysis, X-ray powder diffraction (XRD), thermal analysis, and nitrogen adsorption–desorption at −196 °C, were used to assess the characteristics of the structure of the obtained materials. The thermal treatment, acid activation, and mechanochemical activation resulted in changes in the surface properties of the clay minerals: specific surface area, porosity, and distribution of active sites. It was established that the mechanochemical activation of montmorillonite significantly increases the sorption characteristics of the material for U(VI) and Sr(II) and the acid activation of montmorillonite increases it for U(VI). The appropriateness of the experimental adsorption values for U(VI) and Sr(II) on modified montmorillonite to Langmuir and Freundlich models was found. Independently of the changes induced by acid attack, calcinations, or milling, the sorption of U(VI) and Sr(II) ions on treated montmorillonite occurs on a homogeneous surface through monolayer adsorption in a similar fashion to natural montmorillonite. Water purification technologies and modern environmental protection technologies may successfully use the obtained clay-based sorbents. Full article

In operational applications, hyperelastic adhesive joints are exposed to environmental conditions (moisture and temperature) that affect their mechanical performance. The understanding of how the environment can influence the joint durability through both static and cyclic loading is a key aspect to ensure safety and avoid over-dimensioning. The current work presents an investigation of the effect of environment conditions on the diffusion and mechanical performance of two different hyperelastic adhesive joints (a polyurethane and a silicon-modified polymer). To assess the process of moisture mass diffusion, pure adhesive samples were weighted for 387 days when subjected to outdoor weathering conditions. An FEA-diffusion procedure method was demonstrated by (i) predicting the saturation concentration at steady conditions of 40 °C/15% r.h. (40/15) and 40 °C/60% r.h. (40/60), and (ii) predicting the experienced mass change due to outdoor weathering. The reversibility of the effect of conditioning at 40 °C/60% r.h. on the mechanical properties of the adhesives was assessed via quasi-static and fatigue tensile shear testing. The results support the conclusion that conditioning with the surrogate climate of 40 °C/60% r.h. does not cause irreversible damage, as any potential decrease in shear modulus, tensile shear strength and fatigue life due to 40/60 conditioning can be reversed by re-drying at 40/15. Full article

One of the most popular power management regulators is the low drop-out voltage regulator (LDO). LDOs have different specifications such as the power supply rejection (PSR) over different frequencies, stability over different load ranges, inrush current spike flows through the input supply, and power consumption. In this work, we present a low power low inrush current LDO design with different techniques for PSR and stability improvement across different frequencies. The LDO presented in this work is a low-power and small area LDO but achieves a high PSR over a wide range of frequencies. The LDO is designed in 65 nm CMOS technology and achieves a PSR better than 80 dB up to 30 MHz for an output load current of 25 mA using an output load capacitor of 4 µF. The design can be used in capless/capped LDOs with wide load current ranges as high as 200 mA and load capacitor range from 1 nF to 12 µF with inrush current improvement by more than 2×. The presented LDO consumes a zero-load quiescent current of 10 µA and its area of 180 µm × 180 µm. Full article

This study reports a bottom-up approach for the conversion of cyclohexane into graphene nanoflakes, which were then deposited onto fiberglass using a non-thermal generator. The composite was characterized using transmission electron microscopy, which revealed the formation of stacked few-layer graphene with a partially disordered structure and a d-spacing of 0.358 nm between the layers. X-ray diffraction confirmed the observations from the TEM images. SEM images showed the agglomeration of carbonaceous material onto the fiberglass, which experienced some delamination due to the synthesis method. Raman spectroscopy indicated that the obtained graphene exhibited a predominance of defects in its structure. Additionally, atomic force microscopy (AFM) analyses revealed the formation of graphene layers with varying levels of porosity. Full article

We propose an unsupervised method for eigen tree hierarchies and quantisation group association for segmentation of corrosion in marine vessel hull inspection via camera images. Our unsupervised approach produces image segments that are examined to decide on defect recognition. The method generates a binary decision tree, which, by means of bottom-up pruning, is revised, and dominant leaf nodes predict the areas of interest. Our method is compared with other techniques, and the results indicate that it achieves better performance for true- vs. false-positive area against ideal (ground truth) coverage. Full article

Mastering construction times is of paramount importance in making vernacular earth construction techniques attractive to modern clients. The work presented here is a contribution towards the optimization of the construction time of cob buildings. Therefore, this paper follows the evolution of a cob’s mechanical properties during its drying process in the case of a double-walling CobBauge system. Laboratory tests and in situ measurements were performed, and further results were described. Volumetric water content sensors were immersed in the walls of a CobBauge prototype building during its construction. The evolution of the cob layer’s compressive strength and Clegg Impact Value (CIV) as a function of its water content has been experimentally studied and discussed. These studies showed that compressive strength and CIV are correlated with water content, and both properties decrease exponentially with time. In this study, a new tool to evaluate cob’s mechanical performances in situ has been proposed, Clegg Impact Soil Tester. This was linked to compressive strength, and a linear relationship between these two properties was found. Finally, appropriate values of compressive strength and CIV to satisfy before formwork stripping and re-lifting were proposed. For this study’s conditions, these values are reached after approximately 27 days. Full article

Leaf area and biomass are important morphological parameters for in situ plant monitoring since a leaf is vital for perceiving and capturing the environmental light as well as represents the overall plant development. The traditional approach for leaf area and biomass measurements is destructive requiring manual labor and may cause damages for the plants. In this work, we report on the AI-based approach for assessing and predicting the leaf area and plant biomass. The proposed approach is able to estimate and predict the overall plants biomass at the early stage of growth in a non-destructive way. For this reason we equip an industrial greenhouse for cucumbers growing with the commercial off-the-shelf environmental sensors and video cameras. The data from sensors are used to monitor the environmental conditions in the greenhouse while the top-down images are used for training Fully Convolutional Neural Networks (FCNN). The FCNN performs the segmentation task for leaf area calculation resulting in 82% accuracy. Application of trained FCNNs to the sequences of camera images allowed the reconstruction of per-plant leaf area and their growth-dynamics. Then we established the dependency between the average leaf area and biomass using the direct measurements of the biomass. This in turn allowed for reconstruction and prediction of the dynamics of biomass growth in the greenhouse using the image data with 10% average relative error for the 12 days prediction horizon. The actual deployment showed the high potential of the proposed data-driven approaches for plant growth dynamics assessment and prediction. Moreover, it closes the gap towards constructing fully closed autonomous greenhouses for harvests and plants biological safety. Full article

Green building materials have nontoxic properties and are made from recycled materials. This means they are, in most cases, created from renewable resources in comparison to non-renewable resources. This research aims to further improve the justification of green buildings and their materials. This is undertaken to determine the validity of such construction techniques. This research utilizes both qualitative and quantitative methods through five Australian case studies. The case studies, which are based on new and redeveloped structures, are selected via different geological locations and are evaluated via logical argumentation along with correlation research. Further, the research will address the problem by identifying a variety of green building materials that can be used to substitute non-green building materials. With careful comparisons among the five buildings, the green signs and implementation advantages and disadvantages will be evaluated. The result of this comparison will assist in improving the current education around the topic of green building and benefit the overall response to positive change within the construction industry. Although green building initiatives are not difficult to apply, they can be cost efficient. To maximize their cost efficiency, these initiatives need to be fully adopted. This includes the adaptation of specific building orientation, design, and sealing off penetrations to greatly improve passive heating and cooling. Further, the use of rainwater tanks also assists with energy efficiency by reducing the amount of mains water used. The utilization of natural lighting along with an advanced solar power system would further reduce the overall energy usage. Full article

While damping devices can provide supplemental damping to mitigate building vibration due to wind or earthquake effects, integrating them into the design is more complex. For example, the Canadian code does not provide building designs with inline friction dampers. The objective of this present article was to study the overstrength, ductility, and response modification factors of concrete frame buildings with inline friction dampers in the Canadian context. For that purpose, a set of four-, eight-, and fourteen-story ductile concrete frames with inline seismic friction dampers, designed based on the 2015 National Building Code of Canada (NBCC), was considered. The analyses included pushover analysis in determining seismic characteristics and dynamic response history analysis using twenty-five ground motion records to assess the seismic performance of the buildings equipped with inline seismic friction dampers. The methodology considered diagonal braces, including different 6 m and 8 m span lengths. The discussion covers the prescribed design values for overstrength, ductility, and response modification factors, as well as the performance assessment of the buildings. The results revealed that increasing the height of the structure and reducing the span length increases the response modification factors. Full article

Today’s roadways are subject to traffic congestion, the deterioration of surface-assets (often due to the overreliance on private vehicle traffic), increasing vehicle-operation and fuel costs, and pollutant emissions. In Abu Dhabi, private car traffic forms the major share on urban highways, as the infrastructure was built to a high quality and the public transport network needs expansion, resulting in traffic congestion on major highways. These issues are arguably addressable by appropriate decisions at the planning stage. Microsimulation modeling of driving behavior in Abu Dhabi is presented for empirical assessment of traffic management scenarios. This paper presents a technique for developing, calibrating, validating, and the scenario analysis of a detailed VISSIM-based microsimulation model of a 3.5 km section of a 5-lane divided highway in Abu Dhabi. Traffic-count data collected from two sources, i.e., the local transport department (year 2007) and municipality (2007 and 2015–2016) were used. Gaps in traffic-counts between ramps and the highway mainline were noted, which is a common occurrence in real-world data situations. A composite dataset for a representative week in 2015 was constructed, and the model was calibrated and validated with a 15% (<100 vehicles per hour) margin of error. Scenario analysis of a potential public bus transport service operating at 15 min headway and 40% capacity was assessed against the base case, for a 2015–2020 projected period. The results showed a significant capacity enhancement and improvement in the traffic flow. A reduction in the variation between vehicle travel times was observed for the bus-based scenario, as less bottlenecking and congestion were noted for automobiles in the mainline segments. The developed model could be used for further scenario analyses, to find optimized traffic management strategies over the highway’s lifecycle, whereas it could also be used for similar evaluations of other major roads in Abu Dhabi post-calibration. Full article

The redesign of a failed hoisting shaft belonging to a 10 m stroke vertical transfer device (VTD) is presented. Firstly, the operation of the VTD is thoroughly analysed, the variation of loads and moments along the operating cycle is characterised, and transients such as emergency stop loads are calculated. The selection of safety factors and duty cycle factors was followed by the shaft sizing. After an initial rough sizing, the high-cycle fatigue (HCF) design for cyclic bending moments was performed, first considering constant torque and then considering cyclic torque. The number of bending and torsion cycles performed by the hoisting shaft over 10 years was shown to exceed 10⁶, and an infinite life design is mandatory. The analyses showed that the initial shaft diameter was insufficient, thus justifying the failures observed before the present redesign. A classical fatigue model combining torsional shear stresses with bending stresses was used to take into account reversed torsional loading and ensure infinite fatigue life. This work highlights the need to thoroughly understand a machine’s operating cycle so that the wrong premises for fatigue design calculations are not assumed. Full article

The necessity for environmentally friendly transportation systems has prompted the proliferation of electric vehicles (EVs) in low-voltage (LV) distribution networks. However, large-scale integration and simultaneous charging of EVs can create power quality challenges for the distribution grid. It is therefore important to assess the impact of connecting EVs for charging in existing distribution networks and determine the hosting capacity (HC) of such a network. This paper uses a deterministic time-series method and stochastic method based on a simplified Monte Carlo simulation to estimate the HC of single-phase and three-phase EV charging, respectively, for a South African low-voltage distribution network containing 21 households. Voltage drop and equipment loading are the performance indices (PI) considered for the impact assessment and HC estimation in this study. The impact assessment result confirms that increasing EV charging penetration will result in a corresponding movement of the PIs toward the allowable limits. The results show that the HC is 5–8 three-phase EVs charging simultaneously for the worst-case scenario and 9–13 EVs for the best-case scenario. Furthermore, the single-phase HC for the popular 3.7 kW EV charger is 15 and 8 EVs for the best-case and worst-case scenarios, respectively. The result showing the seasonal variation in HC and for other EV charging power is also presented. The difference in HC for the worst-case and best-case scenarios portrays the effect that the location of charging has on the HC. Full article