Compressive Strength Of Concrete Samples Research Articles

Effect of solvothermal-treated polyethylene on the mechanical properties of sandcrete blocks and concrete

In building construction, seepage and dampness in walls present serious problems since they can cause structural failures and damage in both residential and commercial contexts. Finding more affordable options is necessary as mitigating these problems frequently requires expensive fixes. This study aims to evaluate the effects of solvothermal-treated polyethylene added at concentrations ranging from 0 to 1.0% on the mechanical properties of concrete and sandcrete blocks. In addition to assessing the workability, split tensile strength, and compressive strength of concrete samples at different levels of the polyethylene (PE) inclusion, the study looked into the water absorption capacity, density, and compressive strength of sandcrete blocks. The blocks’ compressive strength and water absorption capacity reduced as the amount of polyethylene additives rose, although there was a slight increase in the density. These changes remain well within the Nigerian Industrial Standards’ specified limits. Hardened concrete shows a drop in density, compressive strength, and split tensile strength with increasing polyethylene content, while fresh concrete's workability decreases as the percentage increases. 0.4% incorporation of the treated polyethylene achieved the target strength of 20 N/mm2 while Sandcrete blocks with up to 1% of the solvothermal treated polyethylene had compressive strengths more than the 2.5 N/mm2 minimum required for non-load-bearing walls. About 61% reduction in water absorption was achieved in 48 h by the blocks, presenting a promising and cost-effective solution for seepage-related issues in building construction.

Investigating the Effect of Various Fibers on Plasticity and Compressive Strength of Concrete Samples

Investigating the Effect of Various Fibers on Plasticity and Compressive Strength of Concrete Samples

INFLUENCE OF PLASTICIZING AND AIR-ENTRAINING ADMIXTURES ON CONCRETE PROPERTIES

In the modern construction industry of Kazakhstan, to ensure the needs of the market, there is an urgent essential to improve the quality of concrete and expand its functional purpose. To a large extent, this is achieved by designing concrete as composite materials with different structures, quantities and nature of components. The multicomponent composition makes it possible to effectively manage the structure formation processes of the concrete cementing matrix and obtain concretes with the required properties. This article presented the effect of plasticizing and air-entraining admixtures on the properties of heavy concrete. The compositions of concrete mixture with plasticizing and air-entraining admixtures were selected. The results of study of plasticizing and air-entraining admixtures effect on average density, workability, compressive strength of concrete samples are presented. The effectiveness of introduction of a complex admixtures was evaluated in order to further improve operational properties of concrete. The plasticizing effect makes it possible to increase workability of concrete mortar while by reducing water-cement ratio from 0,5 to 0,38. Due to this, density and strength of concrete increased while improving operational characteristics. The combined effect of plasticizing and air-entraining admixtures had a positive effect on mobility of concrete mortar and its strength of concrete samples. The significant strength of 47,2 MPa was achieved with the combined introduction of a plasticizing and air-entraining admixtures in the amount of 1,2% and 0,5% of the cement weight, thereby increasing the strength of concrete samples by 32% compared to the control sample.

Machine learning predictions for optimal cement content in sustainable concrete constructions

The designated concrete compressive strength at 28 days plays an important role in determining the quantity of cement (water to cement ratio) needed in concrete mix designs. Whilst a 28-day target is common, some structural elements receive deferred loads during construction, allowing a reduced cement content and the possibility to optimize the concrete mix to target full strength at 90 days. Machine learning techniques are used in this study to optimize the concrete mix design of structural elements that commonly receive deferred loads, e.g., foundation and pavements, targeting a 90-day full strength. Specifically, the compressive strength of concrete samples cured for 28 and 90 days are considered to estimate the cement content per m3 of concrete using Artificial Neural Network and Regression algorithms. The proposed machine learning and deep learning methods are proved to be capable of predicting the cement content with 94% and 90% accuracy, respectively. The Elastic Net algorithm shows the best performance in cement content optimization to a target 90-days compressive strength. This algorithm is hence employed to assess the carbon reduction benefits in a real case study: a typical mid-sized reinforced concrete structure is considered as a baseline to quantify the environmental benefit of optimizing the cement content for a 90-days target compressive strength. Results of the case study show that the proposed method may result in a reduction of approximately 10% in cement usage, consequently leading to a parallel reduction of about 10% in carbon emissions.

Prediction of the compressive strength of lightweight concrete containing industrial and waste steel fibers using a multilayer synthetic neural network

The use of waste and industrial steel fibers as part of the materials used in concrete can increase resistance and reduce cost and air pollution. It also saves energy. One of the important measures for technical inspections and assessment of the existing condition of structures, especially bridges, which is the most important communication factor, is to check the compressive strength. Considering that the calculation of compressive strength in the laboratory is done with the intervention of human power and is undoubtedly affected by human error, we decided to use it through.Predicting the mechanical properties of concrete reinforced with steel fibers based on artificial neural network models without the need to conduct any laboratory studies will save money in construction projects. Unlike classical methods in statistical theories, neural networks do not require any specific model or function along with limiting assumptions to linearize problems.For this purpose, this research was done with the aim of compensating this problem and with the aim of building a neural network with high accuracy that can make the desired predictions with the least error. In this research, this modeling was done using artificial neural networks (ANN) and Levenberg algorithm. The data used to train the neural network was collected from 45 different mixing schemes. Then the compressive strength of the sample is determined experimentally. The parameters considered for the ANN inputs are the values of steel fiber, water, water-cement ratio, cement and superlubricant. The objective data of this study included the compressive strength of each of these mixing designs at the ages of 7, 28 and 60 days. Then, to design the neural network, 75% of the data were considered as training data, 15% as target data and 15% as validation data. The compressive strength of concrete samples made from waste steel fibers increases. One of the reasons for this result is the placement and uniform distribution of fibers in the cement matrix, or in other words, the optimal amount of desired fibers in concrete. For experimental information and data, results can be seen with the help of neural network in data analysis. It was observed that the validation is correlated with a correlation coefficient above 99% and the constructed neural network has sufficient accuracy and validity.

Properties of Recycled Concrete utilizing Waste Rubber

Globally, billions of tires are being disposed of, representing a natural danger. Until now, a little part of that waste is reused, and most tires are simply accumulated. The present paper studies the durability phenomena of recycled concrete with partial substitution of fine aggregate by waste rubber tires. Silica fume, fly ash, and Cement Kiln Dust (CKD) were utilized as substitutions for the binding material. The overall substitution material reached about 30% of the cement content. The long-term behavior was surveyed by methods for water retention, chloride ions penetrability at 28 and 90 days, and protection from aggressive media (sulfate) at 1, 7, 14, and 28 days. Likewise, the compressive strength of concrete samples at 7, 14, 28, and 90 days was measured. The presence of cementitious framework, CKD, silica fume, and fly ash limit the utilization of waste rubber. Substitution percentages of up to 10% rubber fraction and 30% paste framework accomplish a satisfying strength level (35 MPa). These blends also exhibit higher protection from sulphuric corrosive assault than the reference blend.

Modification of Concrete Composition Doped by Sewage Sludge Fly Ash and Its Effect on Compressive Strength.

The sustainable development of construction materials is an essential aspect of current worldwide trends. Reusing post-production waste in the building industry has numerous positive effects on the environment. Since concrete is one of the materials that people manufacture and use the most, it will continue to be an integral element of the surrounding reality. In this study, the relationship between the individual components and parameters of concrete and its compressive strength properties was assessed. In the experimental works, concrete mixes with different contents of sand, gravel, Portland cement CEM II/B-S 42.5 N, water, superplasticizer, air-entraining admixture, and fly ash from the thermal conversion of municipal sewage sludge (SSFA) were designed. According to legal requirements in the European Union, SSFA waste from the sewage sludge incineration process in a fluidized bed furnace should not be stored in landfills but processed in various ways. Unfortunately, its generated amounts are too large, so new management technologies should be sought. During the experimental work, the compressive strength of concrete samples of various classes, namely, C8/10, C12/15, C16/20, C20/25, C25/30, C30/37, and C35/45, were measured. The higher-class concrete samples that were used, the greater the compressive strength obtained, ranging from 13.7 to 55.2 MPa. A correlation analysis was carried out between the mechanical strength of waste-modified concretes and the composition of concrete mixes (the amount of sand and gravel, cement, and FA), as well as the water-to-cement ratio and the sand point. No negative effect of the addition of SSFA on the strength of concrete samples was demonstrated, which translates into economic and environmental benefits.

Engineering properties and durability of concrete samples designed by densified mixture design algorithm (DMDA) method incorporating steel reducing slag aggregate

This research aimed to examine concrete specimens' mechanical and durability properties that included the steel reducing slag aggregate (SRSA) as a complete replacement for natural fine and coarse aggregate. The concrete samples were designed using the DMDA method with water content controlled around 160 kg/m3 and the water to binder (W/B) ratio at 0.3 and 0.4. The SRSA was used as a total replacement for natural fine aggregate, natural coarse aggregate, etc. The experimental tests including slump, slump flow, fresh unit weight, compressive strength, splitting tensile strength, water absorption and porosity, electrical surface resistivity (ESR), thermal conductivity (TC), drying shrinkage, sulfate attack resistance were used to conduct the engineering properties and durability of concrete samples, while microstructure analysis was observed by using scanning electron microscopy (SEM) micrographs. The experimental results illustrated that using SRSA improved the compressive strength of concrete samples in early and reduced in later age. The incorporating SRSA reduced the mechanical properties and durability of concrete specimens. However, all the concrete exhibited a good corrosion resistance with a high ESR value and stable mass change under sulfate attack solution. Besides, the utilization of fine SRSA showed a better performance than coarse SRSA.

Karakteristik Kuat Tekan Buis Beton Ditinjau dari Komposisi Campuran

Research has been carried out on the characteristics of the compressive strength of concrete in terms of the composition of the mixture using firewood ash and without a mixture of firewood ash. This study aims to determine the compressive strength of concrete with the addition of firewood ash and to compare the compressive strength of concrete without the addition of wood ash using different ratios of sand. The composition of the wood ash variations added were 0%, 5%, 10%, 15% and 20% of the cement mass using a ratio between cement and sand of 1:4. While the composition of buis concrete without the addition of firewood ash uses a ratio of 1:2, 1:3, 1:4, 1:5 and 1:6. Testing of the concrete buis sample was carried out at the age of 28 days. The test results showed that the compressive strength of the concrete sample with the addition of firewood ash was 18 MPa, 15 MPa, 17 MPa, 15 MPa and 13.5 MPa, respectively. While the compressive strength of concrete samples without the addition of firewood ash using different sand ratios, respectively, is 31 MPa, 20 MPa, 18 MPa, 15 MPa and 13 MPa. The results show that the more additional wood ash used, the lower the compressive strength value. While the sample without the addition of wood ash shows that the more cement used, the higher the value of the compressive strength. However, when viewed from an economic point of view, the optimal level of firewood ash addition is 10% of the cement mass with a compressive strength value of 17 MPa.

Transparent Concrete (LiTraCon)

Abstract: This article especially covenant with the translucent concrete and also future advantages usage of smart construction world, usages of transparent concrete is a concrete based building material with having light-Trans missive properties due to embedded light optical elements usually Optical fibers. Light is conducted through the stone from one end to the other. Therefore the fibers are need to arrange through the whole object. Transparent concrete is also known as the translucent concrete and light transmitting concrete because of its properties. It is used in fine architecture as a front of building material and for cladding of interior walls. In this report, to integrate the merits of concrete and optical fiber, for developing transparent concrete by arranging the high numerical aperture Plastic Optical Fibers (POF) or big diameter glass optical fiber into concrete. The main purpose is to use sunlight as a light source to reduce the non-renewable energy consumption of illumination and to use the optical fibre to sense the stress of structures and also use this concrete as an architectural purpose for good aesthetic view of the building. The binding material in transparent concrete which is able to transmit light by using clear resins the concrete mix. The Paper circumscribe with the need of transparent concrete at present to utilize the sunlight and for architecture technologies. The new type of concrete can satisfy the green energy saving with its own Natural properties. The work presented in this project reports an investigation on the behaviour of concrete and mortar with optical fibre. Concrete and mortar cube are casted with fibers to study the properties and to compare the compressive strength between normal mix concrete with optical fibre and normal mortar with optical fibre after 7 days, 14 days and 28 days respectively. The compressive strength of concrete samples made with different fibre amount varies from 4% to 5% . The compressive strength of translucent concrete depends upon the amount of fibre content present. The samples with fibers of 4% showed better results in comparison with the others.

Influence of curing temperatures on the performances of fiber-reinforced concrete

In cold regions or even permafrost areas, it shows growing interests in engineering infrastructures, and more engineering projects have been constructing, e.g. Sichuan-Tibet railway. Undoubtedly, the concrete needs to be cured at the temperature below the conventional curing temperature (about 20 °C). This paper investigated the effect of curing temperatures (i.e. −6 °C, −2 °C, 2 °C and 6 °C) on the performances (compressive strength, stress–strain relationship, microstructure, and hydration products) of steel fiber-reinforced concrete (SFRC), polypropylene fiber-reinforced concrete (PPFRC), and basalt fiber-reinforced concrete (BFRC). The results show that the curing temperature and curing age have positive effects on the compressive strength of concrete samples, and the compressive strength increases with the curing temperatures and curing ages. Besides, regardless of curing temperatures, the type and dosage of added fibers would greatly affect the compressive strength, and there is an optimum fiber content for the compressive strength of FRCs cured at the low temperature to resist loads, and the optimum fiber contents for the SFRC, PPFRC and BFRC are 2.0%, 2.0‰ and 0.5‰, respectively. Additionally, the axial stress–strain curves can be divided into four-section characteristics, i.e. linear ascending stage, plastic yield stage, descending stage and residual stress stage. The addition of fibers into concrete remarkably improves the ductility of concrete due to the fiber bridging effect. Moreover, the negative curing temperatures drastically inhibit the hydration reaction of concrete. Denser microstructure, more hydration products and good fiber–matrix binding quality can be observed in the concrete samples cured at the higher temperatures.

Workability dan Sifat Mekanik Self Compacting Geopolimer Concrete (SCGC)

The purpose of this study was to investigate the relationship between molarity and workability in Self-Compacting Geopolymer Concrete (SCGC), as well as mechanical properties. Compressive strength and split tensile strength tests are used to characterize the mechanical characteristics in this research. Additionally, the study investigates the optimal molarity for self-compacting geopolymer concrete. Fly ash was used in lieu of cement in this research. On new concrete self-compacting geopolymer, workability is determined using the EFNARC standard, which includes the Slump Flow, V-Funnel, and L-Box tests. ASTM 39/C 39M-99 standard is used to determine the compressive strength of self-compacting concrete geopolymer. On new concrete, workability is determined using the EFNARC standard, which comprises the Slump Flow Test, a V-funnel, and an L-Box. The compressive strength of concrete samples is determined according to the ASTM 39/C 39M – 99 standard. The SNI 03-2491-2002 standard is used to determine the split tensile strength of concrete. At the ages of 7, 14, and 28 days, tests were conducted. The findings indicated that new concrete at 11M-13M satisfied the criteria for SCGC workability. The compressive and split tensile strengths of SCGC grow as the concrete ages. In self-compacting geopolymer concrete, the optimal molarity is 13 M.

PENGARUH SUBSTITUSI CANGKANG KEMIRI PADA SEBAGIAN AGREGAT HALUS UNTUK BETON K-250 TERHADAP KUAT TEKAN

Concrete is one of the most widely used materials in the construction industry. Concrete building blocks are materials that are widely found in nature, including sand and gravel and cement constituents. Candlenut shell is one of the additives or substitutes for aggregate which has recently been used. began to investigate the impact of its use on the mixture in concrete. The use of candlenut shells can be treated as a substitute for coarse or fine aggregate depending on the size of the pecan shell grains used. and to determine the optimum compressive strength of concrete by mixing candlenut shells as a partial substitute for fine aggregate with a percentage of 0%, 10%, 20%o and 30% of the weight of the fine aggregate. The research method is testing the compressive strength of concrete samples by carrying out laboratory test result. From the results of the concrete experiments that have been carried out and the data that has been obtained with the normal quality of fc 20.75 Mpa concrete and concrete with candlenut shell substitution for coarse aggregate in a mixture of 10%, 20%, and 30%, there are several conclusions, namely the age of concrete is 7, 14.28 days of mixed concrete of 10%, 20%, and 30% of the compressive strength experienced a decrease in the normal concrete compressive strength in every variation of the percentage. The results of the research of normal concrete and candlenut shell mixture on normal concrete 7,14,28 days are 10,74 MPa,13,86 MPa. 14.42 MPa, in 10% candlenut shell mixture 7.14.28 days which is 7.35 MPa. 10.75 MPa. 11.03 MPa, in the mixture of 20%% candlenut shells 7.14.28 days, namely 6.19 MPa, S.48 MPa 9.33 MPa, and in the mixture of 30%% candlenut shells, which is 6.79 MPa. 7,36 MPa, 8,77 Mpa/ Use candlenut shell for partial substitution of fine aggregate in concrete cannot be used as a material as a constituent of concrete.

Neuro-swarm and neuro-imperialism techniques to investigate the compressive strength of concrete constructed by freshwater and magnetic salty water

To construct concrete in recent decades, the reducing freshwater is one of the basic requirements. Feasibility of replacing freshwater with seawater has been confirmed in literature. This study aims to investigate the effects of fresh and salty water on the compressive strength of the concrete samples after 28 days. Then, two hybrid artificial intelligence techniques namely neuro-swarm and neuro-imperialism are proposed to predict the concrete compressive strength. In these two hybrid models, the particle swarm optimization and imperialist competitive algorithm were used to optimize the weights and biases of the artificial neural network to get a higher performance prediction results. For the purpose of this study, a series of experiments were carried out in laboratory based on different values of cement content, magnetic field intensity, water rotation time, and water to cement ratio. According to the results obtained in laboratory, the mentioned parameters had a deep impact on compressive strength of concrete samples. Therefore, these parameters were set as model inputs to estimate the compressive strength of concrete samples. Several hybrid intelligent models with different effective parameters were built to obtain the most accurate model in estimating compressive strength of concrete. The proposed models were assessed using some statistical indices e.g., system error and coefficient of determination (R2). As a result, both hybrid intelligence models were able to provide a high accuracy level for predicting compressive strength of concrete. However, neuro-swarm model received a better results compared to neuro-imperialism model. Considering R2 values for train and test phases, values of (0.9811 and 0.9668) and (0.9785 and 0.9706) were obtained for the neuro-swarm and the neuro-imperialism models, respectively which confirmed the better performance of the neuro-swarm intelligence model in predicting compressive strength values of concrete samples.

Reduction of computational error by optimizing SVR kernel coefficients to simulate concrete compressive strength through the use of a human learning optimization algorithm

This research presents a new model for finding optimal conditions in the concrete technology area. To do that, results of a series of laboratory investigations on concrete samples were considered and used to design several artificial intelligence (AI) models. The data samples include 8 parameters i.e., silica fume replacement ratio, fly ash replacement ratio, fine aggregate, water content, high rate water reducing agent, coarse aggregate, total cementitious material, and age of samples, were used to predict and optimize the compressive strength of concrete samples. For optimization purposes, this study used a human learning optimization (HLO) algorithm to find the optimal results as well as optimizing the kernel coefficients of the support vector regression (SVR) models. Initially, to form the core of this research, various models were constructed and proposed to design the required relationship between the data using SVR. Since different SVR kernels have their own coefficients, using optimization theory, the probability of error in the models was reduced and the models were identified and executed with the highest accuracy. Finally, the polynomial model was selected as the model with the lowest computational error and the highest accuracy for evaluating the compressive strength of the concrete samples. The accuracy of the proposed SVR model for training and testing data was obtained as the coefficient of determination (R2) = 0.9694 and R2 = 0.9470, respectively. This function was considered as a relation, to be developed by the HLO algorithm to find optimal options under different conditions. The results for 14 samples, which are the most important examples of this research, showed that the optimal states are obtained with a high level of accuracy. This confirms the proper use/develop of the SVR-HLO algorithm in designing the predictive model as well as finding optimal conditions in the concrete technology area.

Prospects of Replacing Natural Sand with Crushed Rock Fines in the Composition of Fine-Grained Concrete


 
 
 The expediency of replacing natural quartz Sands, whose reserves are gradually exhausted, by rock screenings as part of fine-grained concretes is shown. In particular, the characteristics of granite and quartzite crushing screenings in comparison with quartz river sand are presented, as well as the results of studying the strength and abrasion of the fine-grained concrete obtained. To exclude the effect of the grain composition on the properties of concrete, aggregate samples were pre-fractionated, and the conditions for producing concrete (cement consumption, water-cement ratio, concrete mix mobility) were the same. It was found that quartz sand having rounded grains with a relatively smooth surface promotes the formation of dense particle packing and increases the strength of fine-grained concrete by 9-14%, but at the same time reduces the abrasion of similar standard samples by 20-30% compared to screenings crushing of granite and quartzite. The maximum abrasion resistance showed concrete containing quartzite screening. Quartzite – metamorphic (metasomatic) dense rock crushing which produces angular particles with a rough surface. The absence of dense packaging reduces the compressive strength of concrete samples containing quartzite aggregate compared to quartz sand. At abrasion of similar samples in a thin layer the resistance to sliding of filler particles one relative to another increases. Therefore, when choosing crushed rock fines instead of natural quartz Sands, it is important to consider the purpose of the designed fine-grained concrete.
 Keywords: crushing screenings, quartz sand, granite, quartzite, fine-grained concrete, strength, abrasion
 
 

Carbon dioxide sequestration in concrete and its effects on concrete compressive strength

In recent years, the production of cement has grown globally in a very rapid manner due to the modernization of the world we live in, and after fossil fuels and land-use change, cement production is the third-largest source of anthropogenic emissions of carbon dioxide, CO2. Cement being the primary binding material for concrete and with the prospects for the concrete industry continues to grow so will the emissions of CO2. Hence, a method to reduce the CO2 production while keeping up with the progression of the concrete industry is very crucial in current times. This is where CO2 sequestration comes in. It is a process where CO2 is converted into a mineral which will then be trapped into the concrete forever. Required data to carry out the research between CO2 sequestered concrete and concrete without CO2 have been observed, obtained and tabulated as necessary. These data are then used to compare the concrete samples with one another and also prove the theoretical effects of CO2 exposure to concrete. Hence, experimental results on the compressive strength of the concrete samples for 7, 14 and 28 days has also been tabulated, graphed and further disputed. The objective of this research is mainly to determine the compressive strength of CO2 sequestered concrete in comparison with concrete without CO2 in order to decrease the effects the concrete industry has on the environment. The compressive strength of concrete samples with sequestration of CO2 gas is expected to be higher than of the concrete without CO2.

Applying a meta-heuristic algorithm to predict and optimize compressive strength of concrete samples

The successful use of fly ash (FA) and silica fume (SF) materials has been reported in the design of concrete samples in the literature. Due to the benefits of using these materials, they can be utilized in many industrial applications. However, the proper use of them in the right mixes is one of the important factors with respect to the strength and weight of concrete. Therefore, this paper develops relationships based on meta-heuristic (MH) algorithms (artificial bee colony technique) to evaluate the compressive strength of concrete specimens using laboratory experiments. A database comprising silica fume replacement ratio, fly ash replacement ratio, total cementitious material, water content coarse aggregate, high-rate water-reducing agent, fine aggregate, and age of samples, as model inputs, was used to evaluate and predict the compressive strength of concrete samples. Developed models of the MH technique created relationships between the mentioned parameters. In the new models, the influence of each parameter on the compressive strength was determined. Finally, using the developed model, optimum conditions for compressive strength of concrete samples were presented. This paper demonstrated that the MH algorithms are able to develop relationships that can serve as good substitutes for empirical models.

Strength Conversion Factors for Concrete Based On Specimen Geometry, Aggregate Size and Direction of Loading

The main goal of this study is to find out the effect of effect of specimen shape and size, aggregate size and directions of loading and placement on the compressive strength of M20, M40, M60 and M80 grades of concrete. During the experimental study, different shaped and sized concrete specimens of different concrete mix designs were tested for compressive strength at 28 days. For casting the concrete samples, totally four different moulds were utilized, which were two different sizes of cubes and two different sizes of cylinders. The cubic moulds were 100 and 150 mm. The cylindrical moulds were 150×300 and 100×200 mm. So the relationship between size and shape effect on compressive strength of concrete samples is evaluated. Casted cubes and cylinders are tested for the compressive strength under axial compression on completion of 28 days as per IS: 516-1999.In this study, the effect of specimen sizes, specimen shapes, and placement directions on concrete compressive strengths for various grades widely used is evaluated. In addition, correlations between compressive strengths with size, shape, and placement direction of the specimen are investigated. It was found that with the increase of the size of the concrete specimen, compressive strength tends to decrease. The effect of grade of concrete on the shape effectof the compressive strength decreases as the specimen size increases regardless of strength level. Conversion factors of 0.80 to 0.90 were suggested for converting compressive strength of cylinders to compressive strength of cubes. For cubes, when the placement direction is parallel to the loading direction, the compressive strength is higher than the normal case. As aggregate size increases, compressive strength is found to be increasing.

The Effect of Adding Slag, Achieved from Wastewater Sludge Incineration in Fluidized-Bed Furnace, on the Quality of Concrete

Abstract Due to a constant increase in generating the amount of sewage waste it is necessary to find an alternative method of its use or disposal. One of such methods can be utilization of sewage sludge in construction materials industry, particularly in concrete technology and other materials based on cement. It allows using waste materials as a passive additive (filler) or also as an active additive (replacement of part of bonding material). The article aims at presenting the analysis of the effect of adding slag, achieved from wastewater sludge incineration in sewage treatment plant, on properties and quality of concrete mix and hardened concrete. Using an experimental method, the researcher designed the composition of the control concrete mix, which was then modified by means of slag. For all concrete mixtures determined – air content with the use of pressure method and consistency measured by the use of concrete slump test. For all concrete series the following tests were conducted: compressive strength of concrete after 7, 28 and 56 days of maturing, frost resistance for 100 cycles of freezing and thawing, water absorption. The use of slag, ground once in the disintegrator, causes a decrease of in compressive strength of concrete samples in relation to the control concrete series as well as bigger decrease in compressive strength after frost resistance test.