Concrete Mix Proportion Research Articles

단일변수 Bayesian 방법을 이용한 성능중심형 배합설계법의 개발

Dept. of Civil and Environmental System Engineering, Yonsei University, Seoul 120-749, KoreaABSTRACT This paper presents a systematic approach for estimating material performance and designing mix proportion ofconcrete based on an application of Bayesian method in the form of satisfaction curves. The one-parameter satisfaction curve rep-resents a satisfaction probability of a concrete performance criterion as a function of concrete material parameter. An analysismethod to combine multiple satisfaction curves to form one unique satisfaction curve that can relate the performance of concreteto a single evaluating value called Goodness value is proposed. A proposed PBMD procedure and examples of application of thePBMD method for concrete mix proportion design are carried out to verify the validity of the proposed method. Finally, the com-parison between the expected performance results of a concrete mix proportion designed using PBMD to the ACI estimation equa-tion calculated results are performed to check the applicability of the method to actual construction.Keywords : performance based design, Bayesian method, satisfaction curve, concrete mix proportion design

A study of concrete properties using phyllite as coarse aggregates

Nowadays, industrial activities generate a huge amount of waste. One such activity is underground mining which generates phyllite wastes that are recycled as coarse aggregates for use in concrete production. Aggregate use in concrete is dependent on availability. This paper reports of an experimental study on some of the physical and mechanical properties of phyllite aggregate concrete as compared to granite (conventional) aggregate concrete. The obtained physical and mechanical properties of both aggregates for specific gravity, water absorption (%), dry density, aggregate impact value (%), aggregate crushing value (%), 10% fines, elongation index (%), flakiness index (%) and Los Angeles abrasion values satisfied minimum requirements for aggregates suitable for concrete production. Five mixes of concrete mix proportions designated M1, M2, M3, M4 and M5 were cast using phyllite and granite aggregates. A total of 400 concrete cubes and 210 modulus of rupture beams were cast and cured by total submerging in water for ages 3, 7, 14, 28, 56, 90, 180 and 360 days before compression and bending tests were performed. The results show that the trends in the development of compressive and bending strengths of plain phyllite concrete were similar to those in granite (conventional) aggregate concrete. However the compressive and bending strengths of phyllite concrete mixes were on the average 15–20% lower than those of the corresponding granite concrete mixes at all ages. The same concrete mix proportions gave lower concrete classes for phyllite compared to granite with the exception of the lowest grade. This was probably because the flakiness and elongation properties coupled with reactive materials in phyllite aggregates affect the absorption and bond characteristics of its concrete.

Effect of Concrete Compositions in Energy Transmission of Surface Waves for Nondestructive Crack Depth Evaluation

The amount and magnitude of absorption and scattering of stress waves in concrete, mainly due to internal friction and aggregate inclusions, may be different when concrete mix proportions vary. In this study, we investigate the effect of concrete composition on the measurements of self-calibrated surface wave transmission functions (TRFs) and spectral energy transmission ratios (SETRs) which are used for crack depth estimation in concrete slabs. A series of experiments is carried out on a range of concrete specimens having more realistic crack (not a notch). It is found that the self-calibrated TRFs are very sensitive to both the concrete composition and the crack depth. However, the SETR is less sensitive to the concrete composition and more sensitive to the changes of crack depths. In conclusion the spectral energy transmission method can be effectively used for crack depth estimation in concrete regardless of their material compositions.

Artificial Neural Network Model for Predicting Compressive Strength of Concrete

Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS), and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature. The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c) is the most significant factor affecting the output of the model. The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

Mix Proportioning of High Performance Self-Compacting Concrete using Response Surface Methodology

High performance self compacting concrete (HPSCC) is typically proportioned with mineral and chemical admixtures leading to relatively high material cost. Such cost can be tolerated in high value added applications specially when cost savings can be realized using HPSCC in terms of reduction in size of reinforced concrete members. Efforts are still needed to reduce material cost of HPSCC to gain wider acceptance in variety of applications. Proper material selection and sound mixture proportioning can achieve this [1]. The derived statistical Response Surface Methodology (RSM) is targeted to develop cost effective HPSCC mixtures [2]. RSM can be used effectively in analyzing the cause and effect of the process parameters on response. This paper presents an experimental program in which RSM are employed to optimize a four-component concrete containing fly-ash subjected to six performances criteria. The four key mixture constituents used in the models included cement, fly-ash, and high range water reducer and water binder ratio. The modeled response that included were the compaction factor, compressive strength, split tensile strength and flexural strength at 28 days. The anticipated responses are not expected to vary in linear manner with selected variables; a central composite plan was selected to enable the model of any response in a quadratic manner. Therefore each of the four selected mixture constituents is studied in five distinct levels corresponding to codified value-2,-1,0,1,2.A total of 31 mixture combinations were used in the experimental design which consisted initially of a matrix 24(=16) factorial design plus seven central points and eight star points. The derived models are valid for a wide range of mixtures with ranges of water binder ratio of 0.28-0.44, cement content of 400 to 600 kg/m3, fly-ash 0 to 10% (by weight of mass cement and HRWR dosage of 1 to 3% (by weight of mass cement).

Artificial Neural Network Model for Predicting Compressive

Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28 th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS), and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature. The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c) is the most significant factor affecting the output of the model. The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

Combined use of MSWI bottom ash and fly ash as aggregate in concrete formulation: Environmental and mechanical considerations

This paper reports the experimental results obtained after casting concrete formulated with different mix proportions of municipal solid waste incineration (MSWI) by-products, bottom ash (BA) and air pollution control fly ash (APCFA), as aggregates. Several tests were performed to determine the properties of the mixed proportions. Mechanical properties of the formulations, such as compressive strength, were also determined, and two different leaching tests were performed to study their environmental effects. Some suitable concrete formulations were obtained for the 95/5 and 90/10 BA/APCFA mix proportions. These formulations showed the highest compressive strength test results, above 15 MPa, and the lowest amount of released trace metals in reference to the leaching test. The leaching mechanisms involved in the release of trace metals for the best formulations were also studied, revealing that the washing-off process may play an important role. Given the experimental data it can be concluded that these concrete mix proportions are suitable for use as non-structural concrete.

Effect of Initial Curing on Surface Deterioration of Concrete Caused by Salt Diffusion and Crystallization Pressure

Crystallization pressure under dry condition after absorption of salts contained in seawater or rainwater causes surface deteriorations of concrete. This deterioration is emphasized under repetition of wetting and drying by propagation of micro cracks. However the deterioration has been hardly researched on concrete. On the other hand, initial curing condition must play an important role in the deterioration because the deterioration starts from surface and the curing has a major affect on the quality of surface concrete rather than inside concrete. In this study, the influence of initial curing condition, the kind of salt, type of cement and concrete mix proportion on the surface deterioration caused by salt crystallization pressure has been investigated. The salts investigated in wetting and drying test were Na2SO4, K2SO4, MgSO4, NaNO3, KNO3, Mg(NO3)2, NaCl, KCl and MgCl.

The Study of Mixing for Underground High Performance Concrete in Coastal Environment

The paper discussed the mix principle, performance target and the technical demands for the underground high performance concrete combined the Shenzhen side-connection item of Shenzhen-Hong Kong West Channel project. The better mix proportion of underground high performance concrete is brought forward, which can direct the construct units and the concrete servers to produce the high quality concrete that fit for the underground project.

Modified Harmony Search Algorithm and Neural Networks for Concrete Mix Proportion Design

This study proposes a new methodology with harmony search (HS) algorithm and neural networks (NNs) for concrete mix proportioning. The basic procedure for the methodology consists of four steps: (1) constructing a database of mix designs; (2) establishing appropriate models for strength and workability; (3) optimizing mix proportion using the modified HS algorithm; and (4) refining the mixture using NNs. The proposed methodology could be a useful decision-making tool for concrete mix design.

Assessment of water absorption and chloride ion penetration of pavement quality concrete admixed with wollastonite and microsilica

Wollastonite with or without microsilica was evaluated as a new material for partial replacement of cement in M40 grade pavement quality concrete. Wollastonite is abundantly available in the Udaipur belt of Rajasthan state in the Indian union as a low cost material. Its physical and chemical properties were analyzed. This particular wollastonite consists of 45.6% of CaO and 48% of SiO 2, mainly in amorphous form and has an average specific surface area of 842.7 m 2/kg. Five finalized concrete mix proportions including the control mix were investigated for saturated water absorption, rate of water absorption, coefficient of water absorption and chloride ion penetration. Test results indicate that up to 15% of wollastonite and 7.5% microsilica can be advantageously admixed with cement to significantly improve the water tightness of concrete due to reduction in pore space and refinement of microstructure. Mathematical relationships existing between these parameters were studied and predictive graphs were developed.

Multi-objective optimization on mix proportions of HSHPC applied to SRC composite structures

The fine bond behaviour between steel shape and concrete is the base of their cooperation. For designing high strength and high performance concrete (HSHPC) applied to steel reinforced concrete (SRC) structures, a mathematical model of multi-objective and nonlinear optimization is established based on the bond-slip theory between steel shape and concrete, which takes the materials' cost and bond strength as objective functions, and takes the other performance indexes of HSHPC as constraint conditions. Opti- mal mix design is implemented with an application of convergent sequential quadratic programming and based on Matlab language. The optimized concrete mix proportions can satisfy all the specifications, and especially can raise the bond strength between steel shape and concrete and reduce unit cost of HSHPC.

再生粗骨材の付着モルタルの物性が再生骨材コンクリートの品質に与える影響

The quality and quantity of the residual mortar greatly influence the quality of the recycled coarse aggregate and change with the mix proportion of the original concrete. In this study, an experimental examination was performed focusing on the water binder ratio and the fine aggregate content of the original concrete that influence the quality of recycled coarse aggregate and recycled aggregate concrete. As a result, it was found that the quality of the recycled coarse aggregate containing the residual mortar of the original concrete is almost equal to that of the original aggregate when the water binder ratio and the fine aggregate content of the original concrete are low.

The Potentials of Cassava Flour as a Set-Retarding Admixture in Concrete

The potentials of cassava flour as a set-retarding admixture in concrete were investigated. Concrete mix proportion of 1:2:4 by weight of cement, sand and coarse aggregate and, water/cement ratio of 0.46 was made with six different dosage levels of cassava flour as admixture. The properties tested include setting time, workability of the fresh concrete and compressive strength of the hardened concrete. These properties were compared with those of similar concrete mix made without cassava flour admixture. It was observed that cassava flour considerably improved the workability of the fresh concrete and delayed the setting time of cement by up to 6 hours. Results of the tests also show that while cassava flour reduced the early strength of concrete, the long-term strength was improved. Cassava flour dosage level of 3% was also found to be the optimum level of addition of the admixture.

Reuse of thermosetting plastic waste for lightweight concrete

This paper presents the utilization of thermosetting plastic as an admixture in the mix proportion of lightweight concrete. Since this type of plastic cannot be melted in the recycling process, its waste is expected to be more valuable by using as an admixture for the production of non-structural lightweight concrete. Experimental tests for the variation of mix proportion were carried out to determine the suitable proportion to achieve the required properties of lightweight concrete, which are: low dry density and acceptable compressive strength. The mix design in this research is the proportion of plastic, sand, water-cement ratio, aluminum powder, and lignite fly ash. The experimental results show that the plastic not only leads to a low dry density concrete, but also a low strength. It was found that the ratio of cement, sand, fly ash, and plastic equal to 1.0:0.8:0.3:0.9 is an appropriate mix proportion. The results of compressive strength and dry density are 4.14N/mm2 and 1395 kg/m3, respectively. This type of concrete meets most of the requirements for non-load-bearing lightweight concrete according to ASTM C129 Type II standard.

Factors influencing chloride transport in concrete structures exposed to marine environments

Abstract The present study concerns a literature review regarding chloride transport in terms of the diffusion coefficient ( D ) and surface chloride content ( C S ) in concrete structures exposed to a marine environment. In addition, a refined model is proposed for D and C S for time-dependent chloride transport. It is found that both D and C S are time-dependent: D decreases and C S increases with time, due to further cement hydration development. D and C S are significantly influenced by concrete mix proportion, air void content in concrete, curing methods, degree of exposure to seawater and climate. Blended cement concretes are beneficial in decreasing D , but increase C S , presumably due to a refinement of the concrete pore structures and chloride binding. An increase in the air void content in concrete increases D , but decreases C S . The C S depends on curing methods such as water, membrane and aeration. The degree of exposure to seawater does not have a clear relationship with C S : higher exposure levels did not result in a higher level of C S . Exposure in tropical areas results in higher C S in concrete jetty structures with a similar level of D , mainly due to an increased temperature and concentration of salinity. Based on these findings, a refined model for C S was proposed to provide more realistic prediction of the build-up of chlorides by chloride transport in concrete structures exposed to marine environments.

Adaptive Network–Fuzzy Inferencing to Estimate Concrete Strength Using Mix Design

Proportioning of concrete mixes is carried out in accordance with specified code information, specifications, and past experiences. Typically, concrete mix companies use different mix designs that are used to establish tried and tested datasets. Thus, a model can be developed based on existing datasets to estimate the concrete strength of a given mix proportioning and avoid costly tests and adjustments. Inherent uncertainties encountered in the model can be handled with fuzzy based methods, which are capable of incorporating information obtained from expert knowledge and datasets. In this paper, the use of adaptive neuro-fuzzy inferencing system is proposed to train a fuzzy model and estimate concrete strength. The efficiency of the proposed method is verified using actual concrete mix proportioning datasets reported in the literature, and the corresponding coefficient of determination r2 range from 0.970–0.999. Further, sensitivity analysis is carried out to highlight the impact of different mix constituents on the estimate concrete strength.

시멘트 수화 특성 및 탄산화를 고려한 콘크리트의 임계 염소이온량에 대한 해석 기법

초록·키워드 목차 오류제보하기 등록된 정보가 없습니다. ABSTRACT1. 서론2. 임계 염소 이온량의 해석에 대한 이론적 기법3. 결과 및 분석4. 결론참고문헌요약

Modeling Compressive Strength Development in Florida Concrete

The Florida Department of Transportation (FDOT) specifications contain equations of concrete compressive strength to predict equivalent 28-day strengths based on core strengths at other times. The FDOT equations are many years old, and are not likely to represent current FDOT concrete mixes. Compressive strength testing at various ages, by using a typical FDOT concrete mix proportion, was performed in order to derive appropriate strength development models. Variation in the mixes was achieved through the substitution of cement types, slag for fly ash, and coarse aggregate type. Selected existing models from the literature were examined for statistical goodness-of-fit to the test data. The best performing models relating the 28-day compressive strength to strengths of concrete aged more than 42 day were recommended.

Statistical optimisation and durability characteristics of bridge deck overlay concrete

The deterioration of bridge deck pavement appears to be inevitable and is attributable to both the environment and to traffic density and loading. In particular, the intrusion of chlorides or other corrosive solutions can cause corrosion in the reinforcing bars, consequently deteriorating the bridge deck pavement. The current study investigated the optimum mix proportions of mineral admixture concrete for bridge deck overlays. The basic mix proportion was determined using the Box–Behnken design technique, which is a response surface method. The optimum mix proportions were then calculated using a response surface analysis based on a statistical optimisation method. The present study also evaluated the durability performance of the optimum bridge deck overlay mixture. The mixture proved to be highly resistant to chloride intrusion, abrasion, and freeze–thaw deterioration, and it is expected to provide superior long-term service with minimal maintenance.