Polymer concrete reinforced with luffa fibers: effect of gamma radiation

The interest of many research groups regarding manufacture of composite materials by using natural fibers is increasing world-wide. The main objectives involve the improvement of mechanical properties, mainly those related to resistance and elasticity. In the present study in a first stage, polymer concrete specimens were elaborated by using an unsaturated polyester resin, silica sand and luffa fibers; after, they were gamma irradiated at different doses and their mechanical properties were evaluated. Two different silica particle sizes (0.15 mm and 0.6 mm), and four different luffa fiber concentrations (0.3, 0.6, 0.9 and 1.2 wt%) were used, as well as 50 and 100 kGy of radiation dose. The results show a gradually diminution of compressive strength and modulus of elasticity when adding luffa fiber concentration. Nevertheless, such mechanical features are increasing when polymer concrete is gamma irradiated.Autonomous University of the State of Mexico (UAEM), Grant 3408/2013M (Megaproyecto

Atık Olivin Mineralinin Asfalt Betonunda Filler Olarak Kullanımı

Bu çalışmada ferrokrom tesislerinde kromit cevherinin zenginleştirilmesi sürecinde ortaya çıkan atık olivin malzemesinin esnek üstyapılarda filler olarak kullanılabilirliği araştırılmıştır. İlk aşamada geleneksel kırmataş kalker agregası tozu kullanılarak elde edilen gradasyonda sabit filler oranı %4.7 olarak alınmış ve bitüm oranı %3,5, %4,0, %4,5, %5,0, %5,5 alınarak optimum bitüm yüzdesi elde edilmiştir. İkinci aşamada, ilk aşamada bulunan optimum bitüm yüzdesi ile geleneksel kırmataş kalker agregası tozuna %0, %25, %50, %75 ve %100 oranlarında olivin ikame edilerek oluşturulan numunelere; stabilite, akma, pratik özgül ağırlık, boşluk yüzdesi, asfalt dolu boşluk yüzdesi ve agregalar arası boşluk yüzdesi deneyi yapılmıştır. Elde edilen sonuçlara göre geleneksel kırmataş kalker agregası filler malzemesiyle ikame edilen olivin yüzdelerine göre asfalt betonunun mühendislik özelliklerinin değişimi karşılaştırılmıştır. Sonuç olarak olivinin sıcak karışım asfalt betonlarda filler malzeme olarak kullanılabileceği görülmüştür

Load-Deflection Behavior of Over- and Under-Reinforced Concrete Beams with Hybrid FRP-Steel Reinforcements

The present study pertains to the load-deflection behavior and cracking moments of concrete beams with hybrid FRP-steel reinforcement. Under and over-reinforced hybrid beams were tested for failure along with reference beams with only steel or FRP reinforcement. The first-cracking moments of the beams were estimated analytically by using different uncracked moments of the inertia and modulus of rupture definitions. The uncracked moment of inertia definitions include the gross and uncracked transformed moments. The adopted modulus definitions are comprised of the experimental values from tests on prisms and the analytical values from the equations in different concrete codes. Furthermore, analytical methods were developed for estimating the deflections of concrete beams with hybrid FRP-steel or only FRP reinforcement. Two different types of elastic moduli, namely the secant modulus corresponding to the extreme compression fiber strain and the ACI 318M-19 modulus, were used in deflection calculations. Closer estimates were obtained by using the secant modulus, particularly in hybrid-reinforced beams. In the post-yielding region of the steel tension reinforcement, the deflection estimates were established to lay in closer proximity to the experimental curve when obtained by adding up the deflection increments instead of directly calculating the total deflections from the elastic curve equation. Accurate estimation of the cracking moment was found to be vital for the close prediction of deflections

Assessment of pipe powder in soil improvement applications: an optimization by response surface methodology

Experimental design methods have become very popular approaches in engineering studies thanks to providing some advantages to reduce time period of experiments. In this study, shear strength characteristics of sandy soils were investigated by using central composite design (CCD) approach which is one of the response surface methods. Shear box test results performed at different time intervals were used to design CCD. In model application, the effect of time period under constant load (TPUL) and pipe powder (PP) content (8-12-16%) were used as independent factors to observe shear strength characteristics. Regression equations, variance analysis results, and factor interactions of response variables were used as statistical parameters to analyze CCD performance. Experimental results showed that TPUL is a significant parameter. CCD analysis also determined the importance of TPUL and suggested 14 days as the best time period. CCD results also showed that the optimum PP content can be selected as 12%

IMPORTANCE OF TEACHING STATISTICAL OPTIMIZATION IN ENGINEERING EDUCATION: A CASE STUDY ON THE CONTRIBUTION OF A PHD STUDENT FOR A GEOTECHNICAL DESIGN

In engineering education, the students are often guided by their advisors to take courses related to their areas of expertise. In addition to the courses related to their areas of expertise, especially in the fields of applied engineering, taking math-based statistics or artificial intelligence courses improves students' analytical thinking skills significantly. For this reason, new perspectives for teaching in engineering education are required. In this study, the importance of teaching mathematically based statistical optimization techniques in engineering education has been discussed through an experimental case study. Within the study, the disposal of Drinking Water Treatment Sludge (DWTS) through its use in sandy soil improvement was studied experimentally and it was discussed whether the sludge usage improves the engineering properties of sandy soils. Besides, the experimental process of this research was supported by a Response Surface Methodology (RSM) analysis, thanks to the knowledge of a Ph.D. student

Artificial Intelligence Methods and Their Applications in Civil Engineering

Simulation of material properties generally involves the development of a mathematical model derived from experimental data. In structural mechanics and construction materials contexts, recent experiments have reported that fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithm (GA), and fuzzy genetic (FG) may offer a promising alternative. They are known as artificial intelligence (AI). In civil engineering, AI methods have been extensively used in the fields of civil engineering applications such as construction management, building materials, hydraulic, optimization, geotechnical and transportation engineering. Many studies have examined the applicability of AI methods to estimate concrete properties. This chapter described the principles of FL methods that can be taught to engineering students through MATLAB graphical user interface carried out in a postgraduate course on Applications of Artificial Intelligence in Engineering, discussed the application of Mamdani type in concrete technology and highlighted key studies related to the usability of FL in concrete technology