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Recent advances in materials science have led to the development of smart materials that can continuously adapt to different loading conditions and changing environment to meet the growing demand for smart structural systems. The unique characteristics of superelastic NiTi shape memory alloys (SMAs) have attracted the attention of structural engineers worldwide. SMAs are metallic materials that can retrieve their original shape upon exposure to various temperatures or loading/unloading conditions with minimal residual deformation. SMAs have found increasing applications in the building industry because of their high strength, high actuation and damping capacities, good durability, and superior fatigue resistance. Despite the research conducted on the structural applications of SMAs during the previous decades, the existing literature lacks reviews on their recent uses in building industry such as prestressing concrete beams, seismic strengthening of footing-column connections, and fiber-reinforced concrete. Furthermore, scarce research exists on their performance under corrosive environments, elevated temperatures, and intensive fires. Moreover, the high manufacturing cost of SMA and the lack of knowledge transfer from research to practice are the main obstacles behind their limited use in concrete structures. This paper sheds light on the latest progress made in the applications of SMA in reinforced concrete structures during the last two decades. In addition, the paper concludes with the recommendations and future opportunities associated with expanding the use of SMA in civil infrastructures.
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BACKGROUND: Joint pain is one of the most frequent complaints among adults and older people in primary healthcare settings worldwide. There are many causes for joint pain, osteoarthritis (OA) is so far the most prevalent form of arthritis that causes joint pain. It can attack almost any joint, but the most frequently affected joints are the hands, knees, hips, and spine. This study aimed to identify public knowledge of OA and its associative variables in Al-Qunfudah governorate, Saudi Arabia. MATERIALS AND METHODS: A cross-sectional descriptive community-based study was carried out among the general population in the Al-Qunfudah governorate. The research data were collected over two months, from November to December 2022, via an Arabic version of a self-administrated online survey of 29 items. RESULTS: A total of 746 respondents were included in this study. The majority of them were females (78%). The age group 18-29 was predominant. In terms of education, 69.9% were holding university degrees. The overall participants' knowledge of OA was poor at 36.1%, fair at 36.8%, and good at 26.9%. The associative variables with better participants' knowledge were; holding university degrees (P=0.021), being a student (P<0.001) and living in urban areas (P=0.020), having normal BMI (P=0.018), and depending on the school topics as a source of information (P<0.001). Good knowledge was significantly higher among healthy individuals and non-smokers (P<0.001) for each variable. CONCLUSION: This study reveals the lack of knowledge of osteoarthritis among the general population in Al-Qunfudah governorate, Saudi Arabia. Being a student, university educated, from urban areas, and having a normal BMI, all were associative factors with good knowledge. Therefore, this study highlights the necessity for providing awareness and educational campaigns for the public, focusing on the rural population.
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Concrete is classified as a multi-composite material comprising three phases: coarse aggregate, mortar, and interfacial transition zone (ITZ). Fine and coarse aggregates occupy approximately 70-85% by volume, of which coarse aggregate typically constitutes more than two-thirds of the total quantity of aggregate by volume. The current study investigates the concrete performance produced using various recycled construction and by-product industrial waste coarse aggregates. Six types of coarse aggregates: manufactured limestone, quartzite, natural scoria, by-product industrial waste aggregate, and two sources of recycled concrete aggregates with densities ranging from 860 to 2300 kg/m3 and with different strength properties were studied. To determine the coarse aggregate contribution to the overall concrete performance, lean and rich concrete mixtures (Mix 1 and Mix 2) were used. Mix 1 (lean mixture) consisted of a ratio of water to cement (w/c) of 0.5 and cement content of 300 kg/m3, whereas a higher quantity of cement of 500 kg/m3 and a lower w/c ratio of 0.3 were used for Mix 2 (rich mixture). The results showed that while the compressive strength for different aggregate types in Mix 1 was comparable, the contribution of aggregate to concrete performance was very significant for Mix 2. Heavyweight aggregate produced the highest strength, while the lightweight and recycled aggregates resulted in lower mechanical properties compared to normal weight aggregates. The modulus of elasticity was also substantially affected by the coarse aggregate characteristics and even for Mix 1. The ACI 363R-92 and CSA A23.3-04 appeared to have the best model for predicting the modulus of elasticity, followed by the ACI-318-19 (density-based formula) and AS-3600-09. The density of coarse aggregate, and hence concrete, greatly influenced the mechanical properties of concrete. The water absorption percentage for the concrete produced from various types of aggregates was found to be higher for the aggregates of higher absorption capacity.
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The shortage of natural aggregates has compelled the developers to devote their efforts to finding alternative aggregates. On the other hand, demolition waste from old constructions creates huge land acquisition problems and environmental pollution. Both these problems can be solved by recycling waste materials. The current study aims to use recycled brick aggregates (RBA) to develop eco-friendly pervious concrete (PC) and investigate the new concrete's structural performance and pore structure distributions. Through laboratory testing and image processing techniques, the effects of replacement ratio (0%, 20%, 40%, 60%, 80%, and 100%) and particle size (4.75 mm, 9.5 mm, and 12.5 mm) on both structural performance and pore feature were analyzed. The obtained results showed that the smallest aggregate size (size = 4.75 mm) provides the best strength compared to the large sizes. The image analysis method has shown the average pore sizes of PC mixes made with smaller aggregates (size = 4.75 mm) as 1.8-2 mm, whereas the mixes prepared with an aggregate size of 9.5 mm and 12.5 mm can provide pore sizes of 2.9-3.1 mm and 3.7-4.2 mm, respectively. In summary, the results confirmed that 40-60% of the natural aggregates could be replaced with RBA without influencing both strength and pore features.
