Effects of Tire Crumb Rubber and Steel Fiber on Punching Shear Behavior of Two-way Alkali-activated Concrete Flat Slabs

As a result of the rapid increase in the demand for transportation vehicles recently, the accumulation of waste tires causes environmental problems. One of the methods that can contribute to the reduction of this environmental problem is the recycling of waste tires as a construction material in aggregate form. This research investigated the impacts of waste tire crumb rubber with/out steel fiber (SF) on the two-way punching-shear behavior alkali-activated concrete (AAC) flat slabs and performed center point load tests. In the study, one-type of SF and two kinds of scrap tire waste i.e., crumb rubber (CR) and tire particles, were used on the producing of rubberized AAC slabs obtained by 100% as binder made of ground-granulated blast furnace slag (GGBFS). Also, while both fine crumb rubber (FCR) and coarse crumb rubber (CCR) were used together in the AAC slabs, tire crumb rubber (TCR) was used alone at the same proportion. Additionally, the fine aggregate was substituted with 10% and 15% FCR and CCR, and coarse aggregate was substituted with TCR in the same proportions. Additionally, AAC slabs with recycled tire rubber (RTR) were produced as fibrous and non-fibrous using 1% by volume hook-end SF. In total, nine AAC slabs with sizes of 50 x 50 x 6 cm3 were manufactured for the study. Experimental data showed that the inclusion of RTR only slightly reduced the punching shear strength of AAC slabs and the punching shear strength of the slabs increased when SF was added to the mixtures containing RTR

Prediction of rutting potential of dense bituminous mixtures with polypropylene fibers via repeated creep testing by using neuro-fuzzy approach

This study investigates the potential use of the neuro-fuzzy (NF) approach to model the rutting prediction by the aid of repeated creep testing results for polypropylene modified asphalt mixtures. Marshall specimens, fabricated with M-03 type polypropylene fibers at optimum bitumen content have been tested in order to predict their rutting potential under different load values and loading patterns at 50°C. Throughout the testing phase, it has been clearly shown that the addition of polypropylene fibers results in improved Marshall stabilities and decrease in the flow values, providing an eminent increase of the service life of samples under repeated creep testing. The performance of the accuracy of proposed neuro-fuzzy model is observed to be quite satisfactory. In addition, to obtain the main effects plot, a wide range of detailed two and three dimensional parametric studies have been performed

Genetik Programlama Yardimi İle Kı’nin Açik Formülasyonu

Konferans Bildirisi -- Teorik ve Uygulamalı Mekanik Türk Milli Komitesi, 2008Conference Paper -- Theoretical and Applied Mechanical Turkish National Committee, 2008Bu çalışmada, kırılma mekaniğinde açılma moduna (Kı) göre Gerilme Şiddet Çarpanı’nın (GŞÇ) formülasyonu için Genetik Programlama (GP) kullanılmıştır. GP için eğitim setleri ANSYS paket programı kullanılarak hazırlanmıştır. GP modellenmesi için gerekli tüm işlemler hazır paket program kullanılarak yapılmıştır. Kırılma Mekaniğinde yaygın olarak kullanılan üç değişik geometri için bir GŞÇ formülasyonu elde edilmiştir. Elde edilen bu açık formülasyonun sonuçlarının, ANSYS sonuçları ile oldukça uyumlu sonuçlar verdiği görülmüştür.In this study, Genetic Programming (GP) is used for the analysis and the formulation of the Stress Intensity Factor (SIF) for the opening mode (KI) of fracture mechanics. The training patterns for Genetic Programming are prepared using ANSYS. All necessary processes for Genetic Programming are conducted using ready package software. A SIF formulation for the three different geometries which are commonly used in fracture mechanics has been obtained. It is shown that the results of the explicit formulation are in good agreement with, ANSYS results

Experimental Study on Direct Shear Strength of Fiber Reinforced Self Compacting Concrete under Acid and Sulfate Attack

This study primary is to investigate the shear strength of self-compacting concrete (SCC) reinforced by steel-fiber (SF) and polypropylene-fiber (PPF) in different environmental conditions: the air, sulfate (MgSO4 with a concentration of 5%) and acid (H2SO4 with a concentration of 5%). The study also examines the effect of fiber volume fraction on the workability, shear strength, compressive strength, and splitting tensile strength of fiber reinforced SCC. The article aims to determine the durability effects of both fibers and their resistance to aggressive environmental conditions. The contribution of this article is an experimental investigation on the shear strength of SCC reinforced by SF as well as PPF in 3 different environmental conditions after 30 days of exposure. The study also investigated the fresh and mechanical properties of 5 different mixtures of SCC with/out 0.1% and 0.2% fibers. The study also concluded that PPF decreased the workability of SCC badly, and special care must be taken when selecting its volume fraction. Also, it was found that generally shear strength of SCC mixes enhanced with increasing SF and PPF volume fraction. Moreover, it was found that both fibers have good durability effects, and resist aggressive environmental conditions, with the best results obtained from samples containing 0.2% SF. In the air condition, while the compressive strength, shear strength and tensile strength results were 52.6MPa, 6.43MPa and 3.91MPa, in the sulfate condition those were 46.37MPa, 6.55MPa and 3.59MPa, and in the acid condition those were 34.4MPa, 5.5MPa and 3.46MPa, respectively

Modelling Marshall Design Test Results of Polypropylene Modified Asphalt by Genetic Programming Techniques

Determining Marshall design test results is time consuming. If the researchers can obtain stability and flow values by mechanical testing, rest of the calculations will just be mathematical manipulations. Marshall stability and flow tests were carried out on specimens fabricated with dierent type of polypropylene fibers. It has been shown that addition of polypropylene fibers improved Marshall stabilities and Marshall quotient values in a considerable manner. Input variables in the developed genetic programming model use the physical properties of standard Marshall specimens such as polypropylene type, polypropylene percentage, bitumen percentage, specimen height, calculated unit weight, voids in mineral aggregate, voids filled with asphalt and air voids. Performance of the genetic programming model is quite satisfactory. Besides, to obtain main eects plot, a wide range of parametric studies have been performed.The presented closed form solution will also help further researchers willing to perform similar studies, without carrying out destructive tests

A Detailed Investigation of the Bond Performance of Basalt Fiber-Reinforced Polymer Bars in Geopolymer Concrete

This comprehensive experimental study aimed to determine the bond performance of basalt fiber reinforced polymer (BFRP) bars in geopolymer concrete (GC). The study examined the bond performance of BFRP bars and GC by considering several parameters, including bar diameters of 8, 10, and 12 mm, embedment lengths of 4, 8, and 12 db mm (where db is the diameter of the bar), concrete covers of 20, 40, and 70 mm and compressive strengths of 21.7 and 34.4 MPa. The study also compared the effect of the bar surface and bar type on GC bond performance. Eventually, the results were compared with ordinary concrete (OC). The obtained results indicated that an increase in the BFRP bar diameter results in a decrease in the average bond stress. Similarly, an increase in the length of the bond leads to a reduction in the bond stress. The specimen possessing a short embedment length failed due to bar pullout, while the specimens with a longer embedment length failed as a result of concrete splitting. The outcomes also showed that the strength of bond increases with an increase in compressive strength and cover thickness. Furthermore, the results also indicated that BFRP-reinforced GC has comparable bond performance to steel-reinforced GC and BFRP-reinforced OC and performed better than OC. Last, Comparisons between the existing bond-slip models were offered to demonstrate the best bond stress-slip model for FRP bars and GC for ascending branch up to ultimate bond stress of the bond slip curves and for whole curves

The Effects of Recycled Tire Rubbers and Steel Fibers on the Performance of Self-compacting Alkali Activated Concrete

In this study, the effects of recycled tire rubbers (RTR) and steel fiber (SF) on the fresh and hardened state properties of the self-compacted alkali activated concrete (SCAAC) were investigated. The ground granulated blast furnace slag, 1 % hooked-end SF, and two types of RTR were utilized. The crumb rubbers (CR) and tire rubber chips (TCR) were used as a substation to natural aggregates at substation levels of 10 % and 15 %. The fresh state performances were evaluated by T50 value, slump flow, V-funnel, and L-Box tests, while mechanical performances were assessed through compressive, flexural, and splitting tensile strength tests. Also, detailed crack and microstructural analyses were conducted. The RTR adversely affected the fresh state properties, which reduced more with SF inclusions. Among the RTR, the TR specimens exhibited lower fresh state performance than the CR specimens. Similar mechanical strengths were obtained on the TR and CR specimens under the same replacement ratios. However, TR specimens exhibited higher deformation capacities than the CR specimens, when SF was utilized. The SCAAC specimens with 1 % SF and 15 % RTR showed more and wider flexural cracks, higher mechanical strength, and deformation capacity, which can be utilized in structural applications, particularly in high seismic zones

Support vector machines in structural engineering: a review

Recent development in data processing systems had directed study and research of engineering towards the creation of intelligent systems to evolve models for a wide range of engineering problems. In this respect, several modeling techniques have been created to simulate various civil engineering systems. This study aims to review the studies on support vector machines (SVM) in structural engineering and investigate the usability of this machine learning based approach by providing three case studies focusing on structural engineering problems. Firstly, the concept of SVM is explained and then, the recent studies on the application of SVM in structural engineering are summarized and discussed. Next, we performed three case studies using the experimental studies provided. Applicability of SVM in structural engineering is confirmed by these case studies. The results showed that SVM is superior to various other learning techniques considering the generalization capability of produced model