Department of Civil Engineering

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Studies on instance based learning models for liquefaction potential assessment
(EJCE, 2002) Barai, Sudhir Kumar
Environmental implications of the use of bio-cement treated recycled aggregate in concrete
(Elsiever, 2021-04) Barai, Sudhir Kumar
Use of aggregates from recycled construction and demolition wastes in concretes alleviates the disposal problem and reduces the cost of concrete significantly. However, excessive water absorption, weak interfacial transition zone, and high porosity are its shortcomings. This study explores a bacterial cement and conventional cement slurry coating treatment on recycled coarse aggregates (RCA) for overcoming these shortcomings. In the first method, microbial carbonate precipitation (MCP) through bio-mineralization treatment has been utilized. Four different concretes were made using both control and treated aggregates. Once the performance of these concrete mixes was found adequate, a life cycle assessment was conducted using ISO14040–44 guideline to determine their environmental impacts. The experimental results confirmed that concrete with MCP treated aggregate offered better material performance than the untreated recycled aggregate based concrete mixes and possessed similar properties as natural aggregate concrete. While MCP process avoided the use of energy intensive cement, this research discovers that concrete with MCP treated aggregates was found to produce marginally higher environmental impacts than other concrete mixes mainly due to additional emissions associated with the bio-cement treatment of RCA. Further environmental mitigation strategies for concrete with MCP treated aggregates has considered to improve its environmental performance in terms of global warming impact and cumulative energy demand. This study demonstrates that the use of 100% RCA delivers significant environmental benefits in terms of ecological footprints, land conservation and biodiversity in a densely populated region like India.
Prediction of Compressive Strength of Concrete: Machine Learning Approaches
(Springer, 2018-08-02) Barai, Sudhir Kumar
Abrams’ law is commonly used to predict the compressive strength of concrete with respect to the water content of the mix, but it is largely inaccurate. High-performance concrete, with its complex additional ingredients, makes the prediction more difficult. The goal of the paper is to find the most accurate model for prediction of the compressive strength of a given concrete mix using machine learning (ML). First, the various ML models are explained along with their working principles. Second, the evaluation methods used for the error analysis in the study are discussed. Third, the findings of the study are displayed and inferences are drawn from them. It is found that the 2-nearest-neighbour performs the best with an error of 8.5% and a standard deviation of 1.55.
Compressive Strength of Nano-Silica Incorporated Recycled Aggregate Concrete
(ISJR, 2014) Barai, Sudhir Kumar
The present work is based on analysis of the influence of incorporation of Nano-Silica on compressive strength of recycled aggregate concrete using two factorial designs. In this study, recycled coarse aggregate (%), Nano-silica (%) and Specimen Type are selected as factors and each having two levels. Four numbers of mixes with three replicates are designed and compressive strength at seven and 28 days are selected as responses. Analyses of Variance (ANOVA) of experimental results are carried out to study the influence of factors and various plots are used to demonstrate the results of the analysis. The outcome of the study depicts that the selected factors are significantly affecting the compressive strength of concrete. However, the analysis indicates that interaction of factors has no substantial influence on compressive strength of concrete.
Prediction of Compressive Strength of Cement Using Gene Expression Programming
(Springer, 2009) Barai, Sudhir Kumar
Gene Expression Programming is employed to predict the 28 days compressive strength of cement mortar. The input parameters considered are C3S, SO3, Blaine and Alkali and the output parameter is the 28 days compressive strength. The model was able to predict successfully with a root mean square error of 1.4956. This model is compared with the Fuzzy Logic Model and ANN-GA model. The GEP model is proved to perform better than the Fuzzy Logic Model. It yields an expression that relates the inputs to outputs thereby overcoming the disadvantages of the artificial neural networks.
Influence of Incorporation of Colloidal Nano-Silica on Behaviour of Concrete
(Springer, 2020-03-24) Barai, Sudhir Kumar
The current research work is based upon the experimental study of the effect of the use of nano-sized particles of colloidal nano-silica (NS) on various properties of concrete. The concrete mixes are designed by substituting cement with 0.75%, 1.5% and 3% of colloidal NS. The analysis of experimental outcomes of this investigation illustrates that the compressive and tensile strength is enhanced with the increasing NS (%). Moreover, increase in density and decline in volume of voids and water absorption have been found due to the introduction of NS in concrete. Increase in mechanical properties and improved non-destructive test results indicates the qualitative improvement in concrete owing to the incorporation of NS. However, the inclusion of NS has no substantial impact on modulus of elasticity of concrete.
Experimental Investigations and Critical Observations On The Use of Modal Parameters For Structural Damage
(CACE, 2014) Barai, Sudhir Kumar
The global nature of the dynamic properties hasattracted much attention in the structural damage detectionfrom the changes in modal parameters of a structure. Thepopularity behind the use of natural frequencies and modeshapes as damage indicators is that they are easy to interpretphysically. However, both the frequency-based and modeshape-based damage identification methods have their own setof advantages and limitations. This paper examines naturalfrequency as the diagnostic parameter in single and doublecrack situations for a cantilever beam using experimental data.It is shown that the sensitivity of natural frequency to theseverity of damage is dependent on the location of crack. It isalso shown that the changes in frequency follow a nonlinearrelation with the crack depth combinations for the doublecrack situation. Finally, it incorporates some criticalobservations on the vibration-based damage detectiontechniques
Effect of loading condition, specimen geometry, size-effect and softening function on double-K fracture parameters of concrete
(Springer, 2012-04-04) Barai, Sudhir Kumar
This paper presents numerical investigation of the influence of the specimen geometry, loading condition, size-effect and softening function of concrete on double-K fracture parameters. The input data needed for computation of the double-K fracture parameters are obtained from the well-known version of Fictitious Crack Model (FCM). FCM is developed for three standard specimens: three-point bend test, compact tension specimen and four-point bend test of size range 100–600 mm at relative size of initial crack length 0.3. The analysis of numerical results shows some interesting behaviour of double-K fracture parameters.
Defect detection and classification using machine learning classifier
(2004) Barai, Sudhir Kumar
In steel industry, hot rolling is the first and major step in flat strip production. In addition to standard measurement, precise information concerning the complete hot strip surface quality has become increasingly important for several reasons. Visual inspection of the hot strip by an inspector is, in most cases not possible because of the high speeds and high temperature involved. In recent times, only video monitors and video recorders have been used where inspectors check on-line or taped video sequences for defects. Developing automatic detection and classification of surface defects of hot strips has been really a challenging problem. Real time image processing typically involves the application of high-speed camera, which may give the defect images in real time. Human experts evaluate this information and give the level of defects, types of defects of the hot strips and will suggest remedial measure to over come those defects. This paper highlights the initial steps in developing a Decision Support System for hot strip evaluation in the manufacturing plant based on the process carried out in the practice. As a first step, a methodology is developed for defect image classifier using machine-learning model - Artificial Neural Networks (ANN). ANN has an excellent generalization capability to learn from the set of data obtained during real-time images. However, while developing ANN model for industrial application many unresolved issues come into pictures. In this study our objectives are issues related to data collection, data modeling, neural networks modeling, reliability of neural models, etc. for automatic detection and classification of defects of hot strips. The proposed study intends to develop general guidelines for developing ANN model for automatic surface inspection for hot strip mills.
Sustainable self compacting hybrid fiber reinforced concrete using waste materials
(Wiley, 2018-11-08) Barai, Sudhir Kumar
The current study investigates the behavior of hybrid fiber reinforced self compacting concrete (HyFRSCC) with crimped steel fibers (CSF) and polypropylene fibers (PPF) along with class F type fly ash (FA) and colloidal nano silica (CNS). To ascertain the fresh properties of self compacting concrete, the maximum volume of fiber content is restricted. The L16 orthogonal array of Taguchi method is followed to avoid the huge amount of experiments. In comparison to the control mix, mechanical properties of concrete are increased due to the combined effect of FA, CNS, CSF, and PPF. Rapid chloride penetration test is conducted to study the durability aspect of hardened concrete. Non-destructive tests like ultrasonic pulse velocity and rebound hammer tests are conducted for the characterization of the properties of concrete. Based on the present study, a combination of FA, CNS, CSF, and PPF is proposed for an optimal recommendation in producing a ready-mix type of HyFRSCC.
Strain Analysis of RC T-beams Strengthened in Shear with Variation of U-wrapped GFRP Sheet and Transverse Steel
(Springer, 2015) Barai, Sudhir Kumar
The strengthening of concrete structures with fibre reinforced polymer (FRP) composites has existed since last two decade. The most common way to strengthen structures is in bending, shear and retrofitting of columns. FRP offers excellent corrosion resistance to environmental agents as well as the advantages of high stiffness-to-weight ratio and strength-to-weight ratio. This paper presents an experimental investigation on strain analysis of a reinforced concrete (RC) T-beams strengthened in shear with U-wrapped glass fibre reinforced polymer (GFRP) sheet. A total of eighteen (18) full scale simply supported RC T-beams are tested. Nine beams are used as control beam with three different stirrups spacing (transverse steel) without GFRP wrap and rest nine beams are strengthened in shear with one, two, and three layers of GFRP sheet in U-configuration for each type of stirrup spacing. This study focuses on strain analysis of U-wrapped GFRP sheet, transverse steel reinforcement and longitudinal steel reinforcement. It is observed that the strain in the U-wrapped GFRP sheet is higher in the specimens strengthened with one layer of GFRP, as compared to two and three layers in all the series. The stiffness of GFRP sheet is indirectly proportional to the strain.
Editorial on construction information technology in emerging economies
(ITcon, 2007) Barai, Sudhir Kumar
In the near future a major part of global construction will take place in what is often called emerging economies. This term covers both developing countries and nations in rapid transition to become major global industrial powers. In terms of geography Latin America, Africa, the middle East and most of Asia as well as Russia and the new and candidate members of the EU are included in this group. Nevertheless the vast majority of construction and construction IT research is carried out in a few countries in North America and Western Europe and deals primarily with problems high up on the agenda in these
Microstructural Changes in Concrete: Postfire Scenario
(ASCE, 2021-02) Barai, Sudhir Kumar
The thermal and mechanical properties of coarse aggregates, cement mortar, and cement concrete specimens of varying mix proportions were studied after exposure to a range of high temperatures. For the tests, 70.6-mm mortar cubes, concrete cubes of 100 and 150 mm, and concrete cylinders of 100 and 150 mm diameters and 200 and 300 mm heights, respectively, were cast. The water to binder ratio was varied from 0.35 to 0.5. These specimens were exposed to a wide range of temperatures varying from room temperature (24°C±2°C) to 1,000°C and tested to understand the degradation in strength and spalling behavior of normal-strength concrete (NSC) and high-strength concrete (HSC). The crack initiation and propagation was studied using micrographs obtained from scanning electron microscopy (SEM). Changes in the porosity of coarse aggregates and concrete at elevated temperatures is quantified by incorporating digital image processing on the SEM micrographs. The influence of high temperature on the physical and chemical properties of concrete and concrete constituents at the macroscale and microscale are discussed. Simple empirical relationships to compute residual compressive strength of NSC and HSC at elevated temperatures are proposed. It is concluded from the results that the degradation in the concrete strength at high temperatures is primarily a result of nonuniform thermal expansion of concrete and its individual constituents leading to porosity changes in the cement–sand matrix, coarse aggregates, and interface between the two
Use of machine learning based technique to X-ray microtomographic images of concrete for phase segmentation at meso-scale
(Elsiever, 2020-07) Barai, Sudhir Kumar
The paper discusses the technical limitation of the gray value thresholding technique to detect the voids, aggregate and mortar phases. A two-stage image processing methodology is proposed for the segmentation of the three phases of concrete using the X-ray microtomographic images. In the first stage, the gray value thresholding technique is used to detect the voids. A machine learning based technique is proposed in the second stage for the segmentation of aggregate and mortar. The training data is used to model a planar decision boundary using the logistic regression method. For this, the radial distance from the centre of the image, gray value, and gray value of the filtered embossed image features are considered. The accuracy of the model to quantify the voids is validated with the commercial software. The machine learning model based on logistic regression method exhibits very good accuracy () in detecting the aggregate.
Shear Behavior of Fly-Ash-Incorporated Recycled Aggregate Concrete Beams
(ACI, 2020-01) Barai, Sudhir Kumar
Shear behavior of a reinforced concrete (RC) beam designed without transverse reinforcement is significantly influenced by the properties of concrete. This paper investigates the effect of fly ash incorporation as 20 and 30% of the total binder content in 100% recycled aggregate concrete (RAC) beams designed without stirrups. To achieve greater packing density with higher aggregate proportions, particle packing mixture design was employed. Load-deflection diagram, load-strain diagram, and crack distri- butions with critical crack formations were examined to study the shear contributing mechanisms in RAC beams. Natural aggregate concrete (NAC) equivalent failure shear (within 10% variation) was obtained at low tension reinforcement percentage (ρ). However, 30% fly ash substituted RAC beams showed significant reduction in shear (approximately 20%) at high ρ. Applicability of shear resistance predictions of major standards (for NAC) to RAC beams are confirmed for the condition of low shear span-depth ratio and high ρ
Impact of particle packing mix design method on fracture properties of natural and recycled aggregate concrete
(Wiley, 2008-11-26) Barai, Sudhir Kumar
The fracture properties of four types of concrete prepared using natural coarse aggregate and recycled coarse aggregate and conventional and particle packing method (PPM) of mix design approaches are studied. The three-point bending (TPB) test is performed using three different sizes of single edge notched beam. The fracture energy is calculated from the load-CMOD curve obtained in the TPB test, and in this process the load-CMOD curve is curtailed at 2% of the depth of the beam. Based on CTODc and w1 relationship, appropriate softening function is used to estimate the double-K fracture parameters. The fracture energy and fracture toughness parameters of recycled aggregate concrete (RAC) is inferior to the natural aggregate concrete (NAC). The PPM mix design improves the fracture properties of concrete in comparison to the conventional mix design approach. The fracture properties of PPM mix designed RAC are comparable to that of NAC prepared using conventional method.
Neural Networks and Genetic Algorithms in Structural Health Monitoring
(CRC, 2016) Barai, Sudhir Kumar
Partially fly ash incorporated recycled coarse aggregate based concrete: Microstructure perspectives and critical analysis
(Elsiever, 2021-04-05) Barai, Sudhir Kumar
This paper presents experimental investigation of the microstructure of partial cement substituted fly ash incorporated recycled aggregate concrete (FARAC). Testing techniques such as thermo-gravimetric analysis, scanning electron microscopy, nano-indentation and X-ray tomography were adopted for this study. Effects of parameters like (i) percentage of fly ash (20% and 30% as cement replacement by weight), (ii) particle packing mix design and conventional method, (iii) curing ages (7, 28 and 90 days), and (iv) coarse aggregate types (100% natural or recycled) are examined. Degree of hydration of FARAC, though higher than natural aggregate concrete, did not translate directly into compressive strength due to formation of more loosely connected low density C-S-H confirmed by SEM images. It is observed that micro-cracks pass mostly through the old and fresh bulk paste rather than the old ITZ in 90 days cured concrete. Thickness of the old ITZ as well as heterogeneities of the new ITZ reduced in FARAC. Upto 30% fly ash can compensate higher porosity of RAC through formation of spherical smaller-size pores.
Prediction of asymmetric cyclic-plastic behaviour for cyclically stable non-ferrous materials
(Wiley, 2019-09-10) Barai, Sudhir Kumar
Investigation on asymmetric cyclic-plastic or ratcheting behaviour of non-ferrous materials has received relatively little attention compared with ferrous materials. Ratcheting behaviour of materials is generally simulated using isotropic-kinematic hardening models; however, for materials showing cyclically stable response, isotropic hardening is often not accounted for the constitutive modelling. A methodology based on Chaboche's isotropic-kinematic hardening (CIKH) model with the consideration of genetic algorithm for optimization of initial estimates of the CIKH parameters is used in this study. The investigated plastic responses incorporate both symmetric strain-controlled hysteresis loops and ratcheting behaviour. The suggested approach satisfactorily predicts the reported plastic response of cyclically stable non-ferrous alloys based on aluminum, zirconium, and titanium.
Demolition Techniques and Production of Recycled Aggregate
(Springer, 2018-06-17) Barai, Sudhir Kumar
Construction industry generates huge quantity of waste throughout the year and most of the times the construction and demolition waste (C&DW) ends up in landfills which affects the economic, environmental and social life cycle. In this chapter a sequential method of demolition of structures/buildings is discussed. Further, different methods such as non-engineering and engineering demolition of buildings/structures are discussed. The scheme of recycling of construction and demolition waste is elaborated. Various recycling equipment used for production of recycled aggregates are described. A complete recycling technology process for the production of end product i.e. recycled aggregate is described sequentially.