Conventionally, the deep beam shear strength is analyzed with codes (mechanics and empirical models). The purpose of this investigation is to provide an alternative way of accurately estimating the shear capacity of Reinforced Concrete Deep Beams (RCDBs), including those with and without shear reinforcements (WOR and WWR), by adopting machine learning models. Four machine learning algorithms: k-Nearest Neighbor (kNN), Random Forest, M5Rules, and Sequential Minimal Optimization for Regression (SMOReg), were considered, and the selection was based on their performance in previous related studies. A database of 733 samples for WWR and 378 samples for WOR was compiled, utilizing 14 and 8 input features, respectively, in each case. WEKA, an open-source software suite, was used in preprocessing the data and also tuning the hyperparameters. SMOReg beat other models for WOR with an R² value of 0.9607, while Random Forest did best for WWR with an R² value of 0.9667 in the testing sets. The shear strengths predicted by the machine learning models were compared to four traditional standard codes. The results show that the machine learning models beat conventional methods by a large margin, while also being consistent with earlier models generated using machine learning. This demonstrates the model's prediction accuracy and robustness.

This research focused on the die exit width, ram speed and temperature effects on extruded Al 6063 alloy mechanical properties. It is a multiple approach that involves numerical, experimental and simulation methods in optimizing the extrusion process. The Q-Form was used in extruded sample flow stress and strain distribution analysis. The result revealed die exit width as the parameter with the most significant influence on Al 6063 alloy tensile strength and hardness, followed by extrusion temperature and then ram speed. The die width increase from 6mm to 8mm yields 73.5 % and 75.8 % tensile strength and hardness increase. The optimized process parameters predicted by the model are a speed of 16.2567 mm/s, a temperature of 526.334 °C, and a die exit diameter of 7.1862 mm, which yields a tensile strength of 151.031 MPa and a hardness of 183.644 HB, respectively. Based on Qform findings, the sample extruded using these optimal parameters yielded uniform metal flow products with low stress concentration. The research enables deep knowledge into the extrusion parameters and mechanical properties relationship, leading to aluminum alloy hot extrusion process optimization. This research has contributed to the more effective and efficient extrusion process development that can be applied in many aluminum extrusion industries. The product quality can be improved through optimized process parameters, thereby reducing the cost of production and boosting the extrusion process's overall efficiency.

The study employs the Technology, Organisational, and Environmental (TOE) theory to examine the role of SMEs’ adoption of social media on financial and non-financial marketing performance in Ghana. Data were collected from SMEs in Accra, Ghana. The study tested seven hypotheses and two moderators. A total of 452 usable sample size were analyzed using structural equation modelling (SEM). The outcome reveals a positive and significant relationship between social media adoption and SMEs' financial and non-financial performance in Ghana. Additionally, a direct relationship between the TOE and SMEs’ social media adoption was confirmed. Although the generalizability of this study is limited due to a single country study, it is still relevant in contributing to a better understanding of social media adoption literature among SMEs, especially from a developing country context. This study is part of the few studies that have used the Technology, Organisational, and Environmental theory to understand social media adoption and marketing performance in the context of an emerging country.

This article reports on the failure analysis of the geothermal steam pipe. Macro and micro examination of failed pipelines was studied using optical and scanning electron microscopy. The energy-dispersive spectroscopy studied the elemental composition of the corroded surface. Further, the study measured the pipe thickness on the failed pipeline section. Visual examination showed a significant thinning of the outer section of the failed pipe to 3 mm from 12.7 mm of the original pipe. The chemical composition results show that the steel meets the minimum requirements for API 5L Grade B steels used in steam pipelines for geothermal power plants. The microstructural analysis of the investigated steel shows that the steel had pearlite and ferrite phases. The steel failure mechanism was due to erosion-corrosion, which caused localised wall thinning near the drain port and elbow section. The study recommends creep-resistant steel for the drain port and elbow for geothermal power plant application.

This study reports on microstructure evolution and mechanical properties of weld joints of two ASTM A335 P92 steels with varying chromium and tungsten content influenced by heat treatment. Physical simulation samples for fine-grain and intercritical heat-affected zones were done using the Gleeble® 3500 equipment. A peak temperature of 900°C (intercritical zone) and 950°C (fine-grained zone) simulated different heat-affected zones. After physical simulation, the test samples underwent two heat treatment schedules: post-weld heat treatment (PWHT) and normalisation, followed by tempering. The results show that the two steels had similar martensite microstructure. The microstructure further exhibited the presence of M23C6 carbides along the grain and lath boundaries. The P92-B steel had the highest hardness values after heat treatment except at FGHAZ + PWHT condition, which had a lower hardness value (271.9 ± 5.0 HV0.5). In this condition (FGHAZ + PWHT), P92-B steel had a higher Charpy toughness value (180J), slightly higher than the base metal (178J) due to fully formed martensite microstructure. ICHAZ + heat treatment, P92-B steel had the lowest toughness values (74J for r-PWHT and 83J for PWHT), but these values were higher than the minimum toughness value of 47J of the weld joint required for hydro-testing of the vessels. The study revealed no marked significant differences between the two steels. The heat treatment method (r-PWHT) is applicable in the industry for Type IV crack mitigation of the weld joint.

Reinforced concrete deep beams (RCDBs) investigations are often complex because of the highly disturbed zones which may aggravate the shear performance under variable loadings. The shear capacity enhancement of RCDB using different aggregate sizes of 19 mm, 25 mm, and 50 mm has been investigated under three-point monotonic loading. Nine RCDBs with 750 × 170 × 225 mm dimensions were considered, and the beam was loaded at a 1.4 shear span to depth ratio. Three of the beams were designed without web reinforcement, and six were designed for web reinforcement with varied aggregate sizes. There was no significant difference in the shear strength of RCDBs considered however, a 50 mm aggregate beam was found capable of reducing the multiple crack propagations when compared to other aggregate-size beams. Additionally, the shear reinforcement increased the ductility and strength by over 30% and 20%, respectively. The applicability of 3-dimensional FEM extended to the investigation acceded with the shear response of the experiment exercising shear stiffening behavior. The estimated model from the modified ACI 318:05 can predict the shear capacity of the RCDB with higher accuracy. Since aggregate resists the load by aggregate interlock action, it is crucial to choose the right aggregate when building concrete structural components. The results of this study will help engineers choose the best aggregate for a certain structural element.

Many industries rely heavily on the availability and reliability of complex structural and functional components to execute operations efficiently. However, failure of components during service occurs due to exposure to unfavourable operating conditions, causing wear and tear of these components. The damage will result in costly downtime and potential safety hazards. Repairing, remanufacturing and refurbishing these complex parts is critical. Restoring broken structures into operation ensures the smooth operation of the industry, thus preventing losses. Conventionally, repairing parts poses a challenge. However, Wire-arc additive manufacturing (WAAM), which employs the welding principle, has revolutionised component repairing or remanufacturing. This paper reviews the literature on manufacturing complex parts, repair, remanufacture and refurbishment of broken structural and functional parts using WAAM technology. This paper also highlights the various strategies and techniques currently used to improve the quality of WAAM 3D printed parts. The study further covers the immense potential of WAAM in revolutionising the remanufacturing and repair of components. The review study has provided a roadmap for future research and development to take full advantage of this new cutting-edge manufacturing technology.

The combined effect of serial dependency and measurement errors is known to negatively affect the statistical efficiency of any monitoring scheme. However, for the recently proposed homogenously weighted moving average (HWMA) scheme, the research that exists concerns independent and identically distributed observations and measurement errors only. Thus, in this paper, the HWMA scheme for monitoring the process mean under the effect of within-sample serial dependence with measurement errors is proposed for both constant and linearly increasing measurement system variance. Monte Carlo simulation is used to evaluate the run-length distribution of the proposed HWMA scheme. A mixed-s&m sampling strategy is incorporated to the HWMA scheme to reduce the negative effect of serial dependence and measurement errors and its performance is compared to the existing Shewhart scheme. An example is given to illustrate how to implement the proposed HWMA scheme for use in real-life applications.

Without a doubt, lightweight materials of high strength are in high demand in the automotive, aerospace, biomedical, and other industries that require such materials. Processing or manufacturing such materials has been a vital topic in contemporary research, as well as material development in the industry. A possible solution for the processing of lightweight materials of high strength is to target lightweight materials by nature such as magnesium and improve their mechanical properties such as stiffness, strength, and hardness. The aforementioned properties are sometimes achieved by processing soft and light materials through High-Pressure Torsion. In this work, Magnesium with Silicon Carbide nanoparticles (Mg-SiC) was strengthened and hardened through the High-Pressure Torsion (HPT) processing technique. The samples were compressed with a pressure of 6.0 GPa and twisted at the rotating speed of 1 rpm with varying numbers of turns N = 0, N = 1, N = 5 and N = 10 at a temperature of 23°C. The processed samples were prepared for the experimental investigation of microstructural characterization and hardness test examinations. Microstructural results showed that grain refinements of material can be achieved through HPT processing methods, which reduced the average grain sizes of unprocessed (N = 0) Mg alloy samples from 149.9 µm to 27.1 µm after processing ten turns. However, hardness test results do not indicate any significant improvement after one HPT processing turn although homogeneity is attained at five processing turns within the nanocomposites.

For the past 19 years, high entropy alloys (denoted as HEAs) have piqued the interest of many researchers due to their unique properties. Sputtering High Entropy Alloys on bulk materials, on the other hand, have been widely utilized due to their low cost of manufacture. This paper reviews the most recent trends and advancements in sputtered HEA coatings, thin film research, and development. Firstly, HEA coating and thin films were introduced. Then, a look at sputtering technologies and procedures is presented, followed by a summary of recent research on sputtered HEA thin films, properties, and applications. From reviewed literature, it can be deduced that HEAs that include the full nitride element have greater mechanical and elastic properties, and HEAs generally have the potential for structural, industrial, biomedical, and energy applications. Finally, it is suggested that new stable HEA films and coating research initiatives with various materials be undertaken to widen its applications.