• International Journal of Concrete Structures and Materials
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• 제4권1호
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• pp.17-23
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• 2010

The feasibility of the use of scrap tire rubber in concrete was investigated. The tests conducted in two groups: replacing of coarse aggregates with crumb rubber and cement particles with rubber powder. To distinguish the properties of new concrete, the following mechanical and durability tests were designed: compressive, tensile and flexural strength, permeability and water absorption. Rubber addition could affect the concrete properties depend on the type and percentage of the rubber added. Although the rubber addition modifies the mechanical characteristics of concrete in a way, but higher rubber content could not be useful. Concrete durability showed more dependency to the type of rubber instead of percentage of rubber. Moreover, to optimize the mechanical and durability of rubberized concrete, the useful percentage of rubber has been recommended.

• Computers and Concrete
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• 제18권1호
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• pp.1-16
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• 2016

In this study, an Artificial Neural Network (ANN) and Adaptive Network-based Fuzzy Inference Systems (ANFIS) prediction models for flexural strength of the cement mortars have been developed. For purpose of constructing this models, 12 different mixes with 144 specimens of the 2, 7, 28 and 90 days flexural strength experimental results of cement mortars containing pure Portland cement (PC), blast furnace slag (BFS), waste tire rubber powder (WTRP) and BFS+WTRP used in training and testing for ANN and ANFIS were gathered from the standard cement tests. The data used in the ANN and ANFIS models are arranged in a format of four input parameters that cover the Portland cement, BFS, WTRP and age of samples and an output parameter which is flexural strength of cement mortars. The ANN and ANFIS models have produced notable excellent outputs with higher coefficients of determination of $R^2$, RMS and MAPE. For the testing of dataset, the $R^2$, RMS and MAPE values for the ANN model were 0.9892, 0.1715 and 0.0212, respectively. Furthermore, the $R^2$, RMS and MAPE values for the ANFIS model were 0.9831, 0.1947 and 0.0270, respectively. As a result, in the models, the training and testing results indicated that experimental data can be estimated to a superior close extent by the ANN and ANFIS models.

• 타이어
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• 통권23호
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• pp.14-20
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• 1969

• Advances in concrete construction
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• 제6권1호
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• pp.87-102
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• 2018

Utilization of waste tires may be considered as one of the solution to the problems faced by the local authorities in disposing them. Reclaimed rubber (RR) is being used in concrete for replacing conventional aggregates. This research work is focused on the strength prediction of reclaimed rubber concrete using a Genetic Algorithm (GA) for M40 grade of concrete and comparing it with experimental results. 1000 sets were taken and 100 iterations were run during training of GA models. A base study has been carried out in this research work partially replacing cement with three types of fillers such as Plaster of Paris (POP), Fly Ash (FA) and Silica Fume (SF). A total of 243 cubes were cast and tested for compression using a Universal Testing Machine. It was found that SF produced maximum strength in concrete and was used in the main study with reclaimed rubber. Tests were conducted on 81 cube samples with a combination of optimum SF percent and various proportions of RR replacing coarse aggregates in concrete mix. Compressive strength tests of concrete at 7, 14 and 28 days reveal that the maximum strength is obtained at 12 percent replacement of cement and 9 percent replacement of coarse aggregates respectively. Moreover the GA results were found to be in line with the experimental results obtained.

• The Journal of Advanced Prosthodontics
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• 제5권3호
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• pp.234-240
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• 2013

PURPOSE. This study evaluated the effectiveness of various methods for removing provisional cement from implant abutments, and what effect these methods have on the retention of prosthesis during the definitive cementation. MATERIALS AND METHODS. Forty implant fixture analogues and abutments were embedded in resin blocks. Forty cast crowns were fabricated and divided into 4 groups each containing 10 implants. Group A was cemented directly with the definitive cement (Cem-Implant). The remainder were cemented with provisional cement (Temp-Bond NE), and classified according to the method for cleaning the abutments. Group B used a plastic curette and wet gauze, Group C used a rubber cup and pumice, and Group D used an airborne particle abrasion technique. The abutments were observed using a stereomicroscope after removing the provisional cement. The tensile bond strength was measured after the definitive cementation. Statistical analysis was performed using one-way analysis of variance test (${\alpha}$=.05). RESULTS. Group B clearly showed provisional cement remaining, whereas the other groups showed almost no cement. Groups A and B showed a relatively smooth surface. More roughness was observed in Group C, and apparent roughness was noted in Group D. The tensile bond strength tests revealed Group D to have significantly the highest tensile bond strength followed in order by Groups C, A and B. CONCLUSION. A plastic curette and wet gauze alone cannot effectively remove the residual provisional cement on the abutment. The definitive retention increased when the abutments were treated with rubber cup/pumice or airborne particle abraded to remove the provisional cement.

• 공업화학
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• 제8권6호
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• pp.979-984
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• 1997

폴리머 혼화제로서 styrene-butadiene rubber(SBR)라텍스, ethylene-vinyl acetate(EVA)에멀젼 및 polyacrylic ester(PAE)에멀젼을 사용하여 동일한 스럼프에서 폴리머-시멘트비를 변화시켜 공시체를 제조하여, 압축과 휨강도시험, 흡수시험, 세공분포측정 및 미세구조 관찰 등을 실시하였다. 그 결과 폴리머-시멘트비의 증가와 더불어 압축과 휨강도 모두 향상되었고, 동해에 큰 영향을 주는 모세관 공극범위의 세공량은 감소되었으며, 폴리머 시멘트비 15wt% 이상에서 연속적인 폴리머필름이 형성되었다.

• 한국세라믹학회지
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• 제28권7호
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• pp.509-516
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• 1991

The effect of various polymers on the freeze-thaw resistance of hardened cement mortar was investigated. For this study, styrene butadiene rubber (SBR), ethylene vinyl acetate (EVA), polyvinyl alcohol (PVA) were used to prepare cement mortar specimen, and then freeze-thaw experiment was carried out. By adding SBR adn EVA to the specimen, the freeze-thaw resistance of specimens was improved, but when PVA was added to the specimen, its freeze-thaw resistance was lowered. Particularly, the specimens which were added 5, 10% of SBR and 5% of EVA showed excellent freeze-thaw resistance in the salt environment.

• 콘크리트학회지
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• 제3권3호
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• pp.101-110
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• 1991

이 연구는 피치계 탄소섬유 보강 플라이애쉬.시멘트 복합체의 여러 가지 특성을 실험적으로 구명하고, 그 제조방법을 제시한 것이다. 복합체는 조강시멘트, 시리카 분말, 스티렌 부타디엔 러버 라텍스, 기포제와 탄소섬유 및 플라이애쉬를 사용하여 제조하였고, 배합조건별로 그 특성을 검토하였다. 연구결과, 경량 탄소섬유 보강 플라이애쉬.시멘트 복합체의 압축강도, 인장강도, 휨강도, 흡수성 및 특수성 그리고 건조수축과 같은 물리적.역학적 성질은 스티렌 부타디엔 러버 라텍스를 첨가하므로써 현저히 개선되었으며, 아울러 복합체를 제조하는데는 기건양생보다 오토클래브 양생이 유리한 것으로 나타났다. 이결과, 앞으로 경량 탄소섬유 보강 플라이애쉬.시멘트 복합체를 이용한 프리캐스트 제품의 개발에 크게 기여할 수 있을 것으로 기대된다.

• Computers and Concrete
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• 제19권3호
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• pp.275-282
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• 2017

The aim of this study is to build Machine Learning models to evaluate the effect of blast furnace slag (BFS) and waste tire rubber powder (WTRP) on the compressive strength of cement mortars. In order to develop these models, 12 different mixes with 288 specimens of the 2, 7, 28, and 90 days compressive strength experimental results of cement mortars containing BFS, WTRP and BFS+WTRP were used in training and testing by Random Forest, Ada Boost, SVM and Bayes classifier machine learning models, which implement standard cement tests. The machine learning models were trained with 288 data that acquired from experimental results. The models had four input parameters that cover the amount of Portland cement, BFS, WTRP and sample ages. Furthermore, it had one output parameter which is compressive strength of cement mortars. Experimental observations from compressive strength tests were compared with predictions of machine learning methods. In order to do predictive experimentation, we exploit R programming language and corresponding packages. During experimentation on the dataset, Random Forest, Ada Boost and SVM models have produced notable good outputs with higher coefficients of determination of R2, RMS and MAPE. Among the machine learning algorithms, Ada Boost presented the best R2, RMS and MAPE values, which are 0.9831, 5.2425 and 0.1105, respectively. As a result, in the model, the testing results indicated that experimental data can be estimated to a notable close extent by the model.

• 한국세라믹학회지
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• 제31권9호
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• pp.949-956
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• 1994

In order to investigate the relationship between pore size distribution and freezing-thawing resistance of mortars, polymer-cement mortars were prepared by using styrene-butadiene rubber latex, ethylene-vinyl acetate emulsion and polyacrylic ester emulsion with various polymer-cement ratios at constant flow. From the results of the test, polymer-cement mortars had a good pore size distribution for freezing-thawing resistance compared with unmodified mortars because of having a small pore volume in the pore radius range of 103~104 $\AA$ affecting on the frost damage. And the freezing-thawing resistance of polymer-cement mortars was improved with increasing polymer-cement ratio.