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This study aims to investigate the feasibility of using industrial waste plastics, polypropylene (PP), polyethylene (PE) and poly-amide (PA), obtained from recycling factory, as reinforcement for mortar. As one of the main problems of using waste plastics in cementitious composites is the hydrophobic properties of the surface of the plastics, because it prevents the formation of adequate interfacial adhesion with cement paste. Surface treatment of waste plastics was applied using diluted solution of isopropanol. Three parameters were considered when designing the mortar mixtures; type of waste plastic (PP, PE, PA), their addition ratio and surface treatment. Bending and compression tests were conducted. 1.5% volume addition of PP and PE to mortars the flexural strength was increased, however, surface treatment of waste plastics did not affected this strength. As the waste plastic volume ratio increased, the flexural toughness of mortars reinforced with PP, PE and PA plastics was also increased. For the 1.5% volume ratio, there was the increase of flexural toughness with respect to the reference mortar and the highest influence had the PP. For the untreated waste plastics, there was significant increase in flexural toughness, while reduction in the compressive strength and compressive toughness was found, however, this surface treatment enhanced the compressive strength and compressive toughness with respect to untreated plastics. Waste plastics can be used for mortars and concretes reinforcement to improve the ductility and energy absorption capacity while eliminating pollution and regaining them in the economy as a structural material.

Structural health monitoring is important for the safety of lives and asset management. In this study, numerical models were developed for the piezoresistive behavior of smart concrete based on finite element (FE) method. Finite element models were calibrated with experimental data collected from compression test. The compression test was performed on smart concrete cube specimens with 75 mm dimensions. Smart concrete was made of cement CEM II 42.5 R, silica fume, fine and coarse crushed limestone aggregates, brass fibers and plasticizer. During the compression test, electrical resistance change and compressive strain measurements were conducted simultaneously. Smart concrete had a strong linear relationship between strain and electrical resistance change due to its piezoresistive function. The piezoresistivity of the smart concrete was modeled by FE method. Twenty-noded solid brick elements were used to model the smart concrete specimens in the finite element platform of Ansys. The numerical results were determined for strain induced resistivity change. The electrical resistivity of simulated smart concrete decreased with applied strain, as found in experimental investigation. The numerical findings are in good agreement with the experimental results.

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According to a report published in USA, 30% of the bridges in USA were found to be structurally de cient while concrete infrastructures have a state of material deterioration before the design life is reached (1). Earthquakes, material degradations and other environmental effects decrease the performance of the structures. The assessment of structures by structural health monitoring is very important to protect the lives of people. The best decision about a damaged structure after an earthquake can be made by use of structural tests and structural health monitoring. Structural tests and structural health monitoring are important steps in the decision making of asset management for maintenance and repair of infrastructures. The classical sensors (strain gauges, piezo-electric sensors) have low durability, low sensitivity and high cost. The low durability of classical sensors disables long term measurement while their high cost limits the amount of sensors that can be used (2). The addition of carbon ber to cement based material decreases the electrical resistance of the material. By application of load, the electrical resistance of the material changes (3-5)., Scientific and Technological Research Council of Turkey (TUBITAK) 110M221

Structural health monitoring has crucial importance to protect the lives and to organize the management of concrete structures. Development of self-sensing smart materials will enable cost effective, robust and reliable solutions for structural health monitoring of concrete. In this study, twenty one cement mortars without and with carbon fibers reinforcement were produced and their compressive strength was tested. Simultaneously, the correlations between strain and electrical resistance change of all mortars were determined. Performance parameters of a strain sensor, which are gauge factor, linearity and strain limit, were evaluated for these cement mortars. The results showed that the cement mortars were much more sensitive to strain than commercial metal strain gauges, while they had a little error of strain estimation. The strain limits were found to be high enough for the mortars without and with carbon fibers reinforcement to be used as strain sensors for concrete structures. This study is a contribution to develop smart materials as sensors for the concrete constructions.

The smart structural materials are enable to health monitoring of concrete with reduced expenses and high sensitivity. In this study, steel fibre concretes were produced and their examination was showing that their electrical resistance is increasing with the curing age. The measurements possibilities of these sensors, which are gage factor (sensitivity), linearity and strain limit were determined. The gage factor of the commercial metal strain gages is K=2 while gage factor of steel fibre concrete was high, equal K=156. Thus, the steel fibre concretes are much more sensitive to strain than commercial metal strain gages. Even after the repeated loading of concrete samples to considerable stress levels, the gage factor remains high which shows that the cement composite can be used as a smart structural material.

Konferans Bildirisi -- Teorik ve Uygulamalı Mekanik Türk Milli Komitesi, 2013, Conference Paper -- Theoretical and Applied Mechanical Turkish National Committee, 2013, Depremler, malzeme bozulmaları ve diğer çevresel etkiler yapıların performansını düşürmektedir. Yapıların performansının yapısal izleme ile takip edilmesi, insanların can güvenliği açısından son derece önemlidir. Yapısal izlemede kullanılan klasik sensörler (gerinim pulları, piezo-elektrik ve benzeri sensörler) düşük dayanıklılığa, düşük duyarlılığa ve yüksek maliyete sahiptirler. Klasik sensörlerin düşük dayanıklılığı, uzun dönem ölçümler alınmasına engel olurken, yüksek maliyetleri sınırlı sayıda kullanılmalarını gerektirir. Bu çalışmada değişik oranlarda karbon lif içeren beş adet çimentolu kompozit karışımı tasarlanmıştır. Her karışımdan 3 er adet 4*4*16 cm ebatlı prizma hazırlanmıştı, toplam 15 örnek hazırlanmıştır. Örneklere çentikli eğilme testi uygulanırken, eş zamanlı olarak elektriksel dirençleri ölçülmüştür. Çatlak boyu ile elektriksel direnç değişimi arasındaki korelasyonlar belirlenmiştir. Çatlak ölçümü için duyarlılık ve doğrusallık performans parametreleri tanımlanmıştır. Çatlak boyu ile elektriksel direncin ölçüldüğü çentikli eğilme testleri, çimentolu kompozitlere ilk defa bu projede uygulandı. Bu çalışma, kendi hasarını ölçen akıllı malzemelerin inşaat sektöründe kullanılmasını hedeflemektedir.

In this study, the correlations between crack length and electrical resistance change were investigated for cement matrix composites. A mix without fibers and another mix with 6 mm long steel fibers, 1% volume fraction were produced. Three samples from each mix were cast and cured. Three point bending test was applied to the samples. Crack length and electrical potential measurements were conducted simultaneously with the bending tests. The results have shown that both mixes have strong correlation between crack length and electrical resistance change. The strong correlation holds for even high crack lengths; as high as 20 mm for samples of cross section 40 mm x 40 mm. The samples with steel fiber has a higher correlation coefficient of 0.97 while the specimens without fiber have correlation coefficient of at most 0.96.