The objective of this research work is to isolate and identify calcite precipitating bacteria and to check the suitability of these bacteria for use in concrete to improve its strength. Bacteria to be incorporated in concrete should be alkali resistant to endure the high pH of concrete and endospore forming to withstand the mechanical stresses induced in concrete during mixing. They must exhibit high urease activity to precipitate calcium carbonate in the form of calcite. Bacterial strains were isolated from alkaline soil samples of a cement factory and were tested for urease activity, potential to form endospores and precipitation of calcium carbonate. Based on these results, three isolates were selected and identified by 16S rRNA gene sequencing. They were identified as Bacillus megaterium BSKAU, Bacillus licheniformis BSKNAU and Bacillus flexus BSKNAU. The results were compared with B. megaterium MTCC 1684 obtained from Microbial Type Culture Collection and Gene Bank, Chandigarh, India. Experimental work was carried out to assess the influence of bacteria on the compressive strength and tests revealed that bacterial concrete specimens showed enhancement in compressive strength. The efficiency of bacteria toward crack healing was also tested. Substantial increase in strength and complete healing of cracks was observed in concrete specimens cast with B. megaterium BSKAU, B. licheniformis BSKNAU and B. megaterium MTCC 1684. This indicates the suitability of these bacterial strains for use in concrete. The enhancement of strength and healing of cracks can be attributed to the filling of cracks in concrete by calcite which was visualized by scanning electron microscope.

Health monitoring of concrete including, detecting defects such as cracking, spalling on fire affected concrete structures plays a vital role in the maintenance of reinforced cement concrete structures. However, this process mostly uses human inspection and relies on subjective knowledge of the inspectors. To overcome this limitation, a deep learning based automatic crack detection method is proposed. Deep learning is a vibrant strategy under computer vision field. The proposed method consists of U-Net architecture with an encoder and decoder framework. It performs pixel wise classification to detect the thermal cracks accurately. Binary Cross Entropy (BCA) based loss function is selected as the evaluation function. Trained U-Net is capable of detecting major thermal cracks and minor thermal cracks under various heating durations. The proposed, U-Net crack detection is a novel method which can be used to detect the thermal cracks developed on fire exposed concrete structures. The proposed method is compared with the other state-of-the-art methods and found to be accurate with 78.12% Intersection over Union (IoU).

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Fire accidents in the concrete structures affect the safety of human beings and structural components. Due to higher temperatures, thermal cracks are conceived in concrete elements. Crack identification, localization, and quantification are the three major components in the damage assessment system. This paper aims to detect thermal cracks of fire-affected concrete structures using ripplet transform-based computer vision method. Initially, the concrete images are decomposed with discrete ripplet transform (DRT). The low frequency subbands are approximated with column filtering-based gray level difference metric. It removes the uneven concrete background. Ripplet coefficient variance parameter (RCVP) is used to differentiate the crack pixels from noisy pixels which is used to eliminate the noises. Finally, in the reconstructed image, the major and minor thermal cracks are detected. The obtained thermal cracks are quantified with the crack properties of length, width, area, and perimeter. The novelty of the proposed method relays on the usage of ripplet transform for the detection of thermal cracks for different concrete grades and different durations of temperature profile. The experimental results are compared with four transform domain state-of-the-method crack detection methods. The proposed method yields better results in terms of the accuracy and average execution time. K E Y W O R D S crack detection, crack properties, discrete ripplet transform, temperature, thermal crack 1 | INTRODUCTION Many automatic methods are being developed to monitor the structural health. The automatic methods are developed with the objective of reducing the manpower requirement and to perform effective analysis, so as to minimize the human errors in the concrete structures. Periodical evaluation is done through automatic systems to identify the damage of concrete structures. Assessment of damages in various infrastructure is possible through structural health monitoring (SHM) approaches. 1,2 Cracks are present in all type of concrete structures. Concrete structures are often affected by stress, environmental factors, heavy loading, and aging. In extreme cases, the damages to concrete structures may result in loss of the life of occupants. Identification and quantification of cracks are paramount to evaluate the present conditions of structures and to take necessary actions for retrofitting the structures.

Self-compacting concrete (SCC) is a form of concrete that is capable of flowing into the congested interior of formwork and consolidating under the action of its own weight without segregation and bleeding. In the present investigation, an attempt has been made to study the effect of elevated temperature on mechanical properties of SCC specimens made with different mineral admixtures that were heated from 27 to 900°C and cooled by air or water. Silica fume, flyash, metakaolin were used as mineral admixtures. Master Glenium was used as superplasticizer, and Glenium Stream 2 was used as viscosity modifying agent. Mechanical properties of the cooled specimens such as compressive strength, tensile strength, flexural strength, and modulus of elasticity were found. Compressive, tensile, and flexural strengths of specimens were found to decrease by 73.18%, 65.05%, and 63.2%, and 85.2%, 83.52%, and 83.56% for the specimens with metakaolin that were heated and cooled by air and water, respectively. Similar reductions were found for the SCC specimens made with silica fume and flyash. Microstructure investigation has been carried out on SCC samples using scanning electron microscope and X-ray diffraction analytical techniques to understand the effect of temperature on decrease in strength.not exhibit the same level of performance as NSC under fire. Literature on this topic is scanty, and hence, an attempt has been made to understand the reduction in the strength of self-compacting concrete (SCC) made with different mineral admixtures that were exposed to higher temperature.Sivaraja [1] studied the effect of high temperature on mechanical strength properties of five different SCC mixes such as normal concrete, SCC with flyash (FA), SCC with silica fume (SF), SCC with rice husk ash, and SCC with 20% quarry sand. Mechanical properties such as compressive strength, split tensile strength, and modulus of rupture were obtained by conducting respective tests as per Indian standards. The strengths of the specimens subjected to high temperature were compared with those of unheated specimens.Neelam Pathak and Rafat Siddique [2] made an investigation on the properties of SCC such as compressive strength, splitting tensile strength, rapid chloride permeability, porosity, and mass loss when exposed to elevated temperatures. Mixes were prepared with three percentages of class F FA ranging from 30% to 50%. Test results clearly indicated that there was little improvement in compressive strength within temperature range of 200-300°C as compared with 20-200°C. A slight reduction in splitting tensile strength was found for the temperature ranging from 20 to 300°C with the increase in percentage of FA.Y. F. Chang et al.[3] carried out an investigation to obtain complete compressive stress-strain relationship for concrete after heating to temperatures of 100 to 800°C. From the results, a single equation for the complete stress-strain curves of heated concrete was developed. Through the regression analysis, the relationships of the mechanical pr...