scholarly journals Perceptions on construction-related factors that affect concrete quality, costs and production

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Jorge Luis Santamaria ◽  
Vanessa Valentin

Structured and unstructured factors affect concrete product. Structured factors are related to concrete production and unstructured factors are related to the construction process. This study focuses on examining the perceived importance of unstructured factors (i.e., construction-related factors) on concrete compressive strength, concrete costs and production rates on the jobsite and understanding the influence of construction experts’ characteristics, such as profession, on their perceptions. A comprehensive literature review was performed to identify unstructured factors. A survey was then designed and deployed to 297 experts from the construction industry and academia to examine the importance of the identified factors through the relative importance index (RII) method and to further identify additional unstructured factors. Likert aggregation and tests for equality of odds were used to compare and analyze responses of two groups of participants, namely architects and engineers. Curing humidity, crew experience and compaction method are the top three factors perceived to affect concrete compressive strength, whereas crew experience, mixing time and compaction method are the factors perceived to affect concrete costs and production rates the most. Crew experience, compaction method and mixing time dominate the global ranking of perceived affecting factors for concrete compressive strength, costs and production rates. Architects were found to be more likely to perceive high or very high impacts of these factors on concrete. The present study increases our understanding of construction-related factors to facilitate project management and preserve concrete characteristics.

2020 ◽  
Vol 13 (1) ◽  
pp. 45-53
Author(s):  
Sajid Kamil Zemam

This study seeks to develop a sustainable construction technique based on the introduction of a specific method for improving concrete compressive strength through a proposed multi-vibration compaction method. An experimental program is performed to evaluate the effect of the proposed compaction technique on fresh silica fume concrete undergoing the initial setting. Multi-vibration intends to minimize concrete production cost because it upgrades the compressive strength of the same materials with better utilization of the vibration energy required for compaction. The collected experimental data presented assign relationships among vibration duration, vibration cycles or phases, and compressive strength upgrading of single vibrated, revibrated, and multi-vibrated specimens for analysis and discussion. This study shows that multi-vibration phases, rather than single vibration or revibration techniques, are powerful techniques for improving concrete compressive strength. The results indicated that the existence of an optimum multi-vibration mode was dominated by phase number and vibration duration and confirm the reliability vibration overall time duration recommended by ACI 309 which relates to a single vibration time limit to be considered in the case of multi vibration technique. Multi-vibration Mode 8 (subjected to three vibration phases 10, 20, and 30 sec ) has the best effect for the considered mixtures among the specific vibration modes. The maximum improvement ratio is 1.25, which is associated with the plastic mixture.   


2014 ◽  
Vol 3 (2) ◽  
pp. 224 ◽  
Author(s):  
Mohammad Awwad

We analyze results of two experiments that tested effect of adding Silica on the compressive strength of concrete at early stage and after long period. The two experiments evaluated different silica/cement ratios for different mixing periods. Adding Silica to concrete mix produce high early strength material which is highly desirable in airports and highways. More than 90 samples of different silica/cement ratios are tested for compressive strength at 3 and 28 days. Test results showed high early up to 60 MPa. Strength increase is proportional with the increase of silica/cement ratio and mixing time with maximum at ratio of 15/100 and 30 minutes mixing time. A relevance Vector Machine (RVM) model is developed to predict concrete compressive strength using concrete mixture inputs information. RVM model predictions matched experimental data closely. The developed model can be used to predict compressive strength in future periods based on initial information related to cement mixture. Keywords: Relevance Vector Machine, Silicate Percent, Prediction Model, Milling Time, Compressive Strength, Concrete.


2018 ◽  
Vol 195 ◽  
pp. 01003
Author(s):  
Agus Maryoto

SNI 2493:2011 is the Indonesian National Standard containing the procedures for the manufacture and maintenance of concrete specimens in the laboratory. This standard regulates the way that compaction of compressive specimens is performed using internal vibrators in addition to manual compaction. Unfortunately, the amount and duration of vibrator compaction using an internal vibrator are not specified in the standard. This study examines the effect of vibrator duration when using an internal vibrator to compact concrete compressive strength specimens. The specimens used are of cylinders with diameter 15 cm and height 30 cm. 30 specimens were formed by each of the three concrete compaction methods used. The first type is where concrete is compacted manually by a tamping rod, 25 times each layer. The tamping rod is of 16 mm diameter and 62 cm height. The second type is compaction is by using internal vibrator, with 3 compactions per layer, each for 2 seconds. The third type also uses the internal vibrator, except the duration of each compaction is for 5 seconds. The results of compressive strength tests show that the compressive strength of the concrete compacted with the internal vibrator is about 10% higher than when manually compacting the concrete using a tamping rod. This proposed compaction of concrete by using an internal vibrator can be used as an alternative to manual compaction in the manufacture of concrete compressive strength specimens.


Materials ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 4577 ◽  
Author(s):  
Andrzej Ambroziak ◽  
Patryk Ziolkowski

The technological process of concrete production consists of several parts, including concrete mix design, concrete mix production, transportation of fresh concrete mix to a construction site, placement in concrete framework, and curing. Proper execution of these steps provides good quality concrete. Some factors can disturb the technological process, mainly temperature and excessive precipitation. Changing daily temperature and rainfall during fabrication, transportation, and placement can shape not only the properties of the concrete mix but also the compressive strength of hardened concrete. In this paper, we tried to answer the question of how temperature and precipitation affect concrete production. The scope of this study was to determine the change of compressive strength of the hardened concrete in a specific period for selected concrete mix recipes, taking into account changing daily temperature and precipitation magnitude. The investigated concrete mixes concrete compressive strength beyond that of the concrete grade, termed “concrete superstrength”. This concrete post limiting behaviour of concrete is also discussed.


2019 ◽  
Vol 4 (12) ◽  
pp. 53-56
Author(s):  
John Ayibatunimibofa TrustGod ◽  
Akosubo Iwekumo Stevyn ◽  
Ann Diri Manfred

The amounts of waste glass in the Bayelsa State metropolis have been growing noticeably without being reutilized increasing the danger to public well-being because of the shortage of land area. This rising challenge of waste glass in the Bayelsa State metropolis can be improved if new dumping possibilities other than landfill can be discovered. This study is geared toward the better use of waste glass material as admixture in concrete as a means to improve the concrete compressive strength. To achieve research objectives, the broken waste glasses were obtained from aluminum fabrication workshop in Amassoma. Bayelsa state Nigeria, the glasses were then milled to a fine powder smaller than 0.075mm and burnt at a controlled temperature of 200, 400, and 6000C respectively. A total of 156 concrete cubes of 150mm x 150mm x 150mm were produced employing different contents of calcined or burnt waste glass powder as admixture. The quantity of calcined waste glass powder used as admixture was varied from 0-20% at step of 5% for three different temperatures, 2000C, 4000C and 6000C. The samples were cured for 7, 14, 21 and 28days and tested in the laboratory for compressive strength. Results obtained from the study showed that the best addition dosage of calcined waste glass powder at 2000C, 4000C and 6000C are 20%, 5% and 5%. A 20% addition of Calcined waste glass powder at 2000C exhibited about 23% increase in compressive strength than the control. Base on the findings, it is recommended that the use of calcined waste glass powder as pozzolanic material should be embraced for production of concrete and can be utilized in concrete production as admixture with 5% - 20% for 2000C 4000Cand 4000C respectively.


2018 ◽  
Vol 162 ◽  
pp. 02018 ◽  
Author(s):  
Dhiyaa Mohammed ◽  
Sameh Tobeia ◽  
Faris Mohammed ◽  
Sarah Hasan

Increasing amount of construction waste and, concrete remnants, in particular pose a serious problem. Concrete waste exist in large amounts, do not decay and need long time for disintegration. Therefore, in this work old demolished concrete is crashed and recycled to produce recycled concrete aggregate which can be reused in new concrete production. The effect of using recycled aggregate on concrete compressive strength has been experimentally investigated; silica fume admixture also is used to improve recycled concrete aggregate compressive strength. The main parameters in this study are recycled aggregate and silica fume admixture. The percent of recycled aggregate ranged from (0-100) %. While the silica fume ranged from (0-10) %. The experimental results show that the average concrete compressive strength decreases from 30.85 MPa to 17.58 MPa when the recycled aggregate percentage increased from 0% to 100%. While, when silica fume is used the concrete compressive strength increase again to 29.2 MPa for samples with 100% of recycled aggregate.


2018 ◽  
Vol 9 (2) ◽  
pp. 67-73
Author(s):  
M Zainul Arifin

This research was conducted to determine the value of the highest compressive strength from the ratio of normal concrete to normal concrete plus additive types of Sika Cim with a composition variation of 0.25%, 0.50%, 0.75%, 1.00%, 1.25%, 1 , 50% and 1.75% of the weight of cement besides that in this study also aims to find the highest tensile strength from the ratio of normal concrete to normal concrete in the mixture of sika cim composition at the highest compressive strength above and after that added fiber wire with a size diameter of 1 mm in length 100 mm with a ratio of 1% of material weight. The concrete mix plan was calculated using the ASTM method, the matrial composition of the normal concrete mixture as follows, 314 kg / m3 cement, 789 kg / m3 sand, 1125 kg / m3 gravel and 189 liters / m3 of water at 10 cm slump, then normal concrete added variations of the composition of sika cim 0.25%, 0.50%, 0.75%, 1.00%, 1.25%, 1.5%, 1.75% by weight of cement and fiber, the tests carried out were compressive strength of concrete and tensile strength of concrete, normal maintenance is soaked in fresh water for 28 days at 30oC. From the test results it was found that the normal concrete compressive strength at the age of 28 days was fc1 30 Mpa, the variation in the addition of the sika cim additive type mineral was achieved in composition 0.75% of the cement weight of fc1 40.2 Mpa 30C. Besides that the tensile strength test results were 28 days old with the addition of 1% fiber wire mineral to the weight of the material at a curing temperature of 30oC of 7.5%.


2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Sudarmadi Sudarmadi

In this paper a case study about concrete strength assessment of bridge structure experiencing fire is discussed. Assessment methods include activities of visual inspection, concrete testing by Hammer Test, Ultrasonic Pulse Velocity Test, and Core Test. Then, test results are compared with the requirement of RSNI T-12-2004. Test results show that surface concrete at the location of fire deteriorates so that its quality is decreased into the category of Very Poor with ultrasonic pulse velocity ranges between 1,14 – 1,74 km/s. From test results also it can be known that concrete compressive strength of inner part of bridge pier ranges about 267 – 274 kg/cm2 and concrete compressive strength of beam and plate experiencing fire directly is about 173 kg/cm2 and 159 kg/cm2. It can be concluded that surface concrete strength at the location of fire does not meet the requirement of RSNI T-12-2004. So, repair on surface concrete of pier, beam, and plate at the location of fire is required.


2021 ◽  
Vol 11 (9) ◽  
pp. 3866
Author(s):  
Jun-Ryeol Park ◽  
Hye-Jin Lee ◽  
Keun-Hyeok Yang ◽  
Jung-Keun Kook ◽  
Sanghee Kim

This study aims to predict the compressive strength of concrete using a machine-learning algorithm with linear regression analysis and to evaluate its accuracy. The open-source software library TensorFlow was used to develop the machine-learning algorithm. In the machine-earning algorithm, a total of seven variables were set: water, cement, fly ash, blast furnace slag, sand, coarse aggregate, and coarse aggregate size. A total of 4297 concrete mixtures with measured compressive strengths were employed to train and testing the machine-learning algorithm. Of these, 70% were used for training, and 30% were utilized for verification. For verification, the research was conducted by classifying the mixtures into three cases: the case where the machine-learning algorithm was trained using all the data (Case-1), the case where the machine-learning algorithm was trained while maintaining the same number of training dataset for each strength range (Case-2), and the case where the machine-learning algorithm was trained after making the subcase of each strength range (Case-3). The results indicated that the error percentages of Case-1 and Case-2 did not differ significantly. The error percentage of Case-3 was far smaller than those of Case-1 and Case-2. Therefore, it was concluded that the range of training dataset of the concrete compressive strength is as important as the amount of training dataset for accurately predicting the concrete compressive strength using the machine-learning algorithm.


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