Research - Dept. of Civil Engg.

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Application of Principles of lean management in Construction Industry, A technique in the Indian construction industry
(International Journal of Recent Advances in Engineering & Technology (IJRAET), 2016) Pillai, Karuna; Shukla, Manojkumar; Magar, Rajendra
The construction industry has been severely vexed by several problems, and one of the major attributors being ‘the construction waste’. There is a severe need for identifying the sources of wastes and to improve the competence and to cut back on these wastes. For this Lean construction and its tools have been introduced as a new management principle for better implementation. These include reducing variability in production and production cycles. The tools that shall be used to achieve this include following a push-pull approach, use of multifunctional, multi skilled teams, and scrutiny of the following by just in time schedules. There are countless challenges in the implementation of lean concept in construction industry. The implementation of lean management in Indian construction industry is scarce. Due to lack of attention and illiteracy towards the lean management principles and application of its tools the owner, contractor, engineers etc. are still acquiring training to implement this principle in their projects. This project mainly focuses on to identify the possibilities of implementation of lean management in construction industry. It will be achieved by preparing the questionnaire and also conducting the interview with the project personals like top management, engineers and site supervisors etc., via cyber mass media. The questionnaires shall then be evaluated to adopt the best suited techniques through statistical methods. This paper focuses on the possibilities of effective utilization of lean management principles in construction industry, which can surely increase the quality of work and profit rate by eliminating the wastage of material.
Artificial Intelligent Techniques in Rainfall-Runoff Process
(5 International Conference on Water Resources and Arid Environments (ICWRAE 5), 2013-01-07) Magar, Rajendra
The use of rainfall-runoff (R-R) models in the decision making process of water resources planning and management has become increasingly indispensable. R-R modeling is still one of the most difficult issues in hydrological sciences due to the dynamic, uncertain and non-linear characteristics and relationship among the processes. In the broad sense R-R modeling has started at the end of 19th century and till today various types of models have been developed and applied based on their mechanism, input data and other modeling requirements. Fairly a large number of empirical, conceptual and physically based models having their own merits and demerits have been developed and applied to map the R-R relationship. In the real world, temporal variations in data do not exhibit simple regularities and thus R-R process is difficult to analyze and model accurately by conventional modeling approach. Hence R-R modeling approach has been shifted from process based technique to data-driven based Artificial Intelligent (AI) techniques like Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Inference System (ANFIS), Genetic Programming (GP) and Model Tree (MT). The primary aim of this paper is to highlight the merits and demerits of those recent works on R-R modeling using AI techniques. As a value addition, a graphical user interface (GUI) has been developed as a decision support system.
Design and cost economic analysis of self compacting concrete for mivan shuttering
(International Journal of Engineering Development and Research, 2016) Syed, Mehdi Abbas (14CEM16); Magar, Rajendra; Patil, Dada S.
This paper summarizes the experimental work performed to design a self-compacting concrete for Mivan shuttering and cost analysis of cost of the designed per m3 mineral and chemical admixtures. Workability tests such as Flow table test, V funnel test and U box tests were conducted. Compressive Strength test was performed out on hardened 150mm concrete cubes after 3, 7, & 28 days curing in water. The output of the research work was a highly workable concrete which could be used for densely reinforced sections of Mivan shuttering.
Earn Value Management a Boon to Indian Construction Industry
(Tech-Chronicle, 2016-09) Magar, Rajendra; Shukla, Manojkumar
Earned Value Management (EVM) is a systematic approach to the integration and measurement of cost, schedule, and technical (scope) accomplishments on a project or task. It provides both the government and contractors the ability to examine detailed schedule information, critical program and technical milestones, and cost data. .EVM technique can do forecasting of duration for a project .It gives a well-defined pathway of existence to the project and when to take precautionary measures for updating the project if project is behind the schedule. It can be used to identify the cost overruns and time overruns. EVM technique can be applied using certain software's like MSP, Primavera, etc.
Effect of Colloidal Nanosilica on High Strength Rice Husk
(Journals Pub, 2017-01) Magar, Rajendra; Khan, Afroz; Gupta, Vipin (16DME138); Gupta, Vinay; Sayyed, Firoz Khalil (16DCES83)
Nowadays, supplementary cementitious materials (SCMs) are used in concrete because it reduces CO2 emission during. The husks, which are production of cement, reduces cement contents, improve workability, increase strength and enhance durability. Pozzolanic reaction takes place when siliceous or aluminous material comes in contact with calcium hydroxide in the presence of moisture to form compounds possessing cementitious properties approximately 50 percent cellulose, 30 percent lignin and 20 percent silica, are incinerated by controlled combustion leaving behind an ash that predominantly consists of amorphous silica. Rice husk ash is highly pozzolanic due to its extremely high surface area (50,000 to 100,000 m2/kg). The colloidal nano silica (CNS) which is nano material and behaved not only as a filler to improve cement micro-structure (porosity decrease), but also as a promoter of pozzolanic reaction used in cement for accelerating pozzolanic action due to which the cement sets faster than conventional mix. In the present study, the mineral admixture, rice husk ash (RHA) was used as 5, 10, 15% replacement for OPC in M60 grade of concrete. The 10% RHA was taken as optimum dose on the basis of workability and compressive strength. To this 10% RHA concrete, effect of 1, 2, 4, and 6% CNS addition were experimentally studied with various properties like workability, compressive strength and split tensile strength.
Estimation of Discharge Using LS-SVM and Model Trees
(Journal of Water Resources and Ocean Science, 2016-11) Magar, Rajendra
In planning and management of any water resource systems prediction or estimation of runoff over the catchment is considered as a crucial factor. Many researchers over the past two decades addressed these problems by traditional methods as well as with some new techniques. This paper is describable and is focused on the capability of some data driven techniques such as Least Square Support Vector Machines (LS-SVM) and Model Trees with M5 algorithm. These methods were used to estimate runoff of various stations in the catchment area in Upper Krishna basin, Maharashtra State, India, and discussed here two stations namely Shigaon and Gudhe. The specialty of these catchment areas is Shigaon has large area and Gudhe has small area. This was done to see the model performance in both conditions. Additionally metrological data was used in the process to see the performance of models. The quantitative analysis was carried out to check the performance of the accuracy by considering standard statistical performance evaluation metrics and the scatter plots are drawn for evaluating qualitative performances of the developed models. The effect of the various metrological parameters as an input parameter for the rainfall was also investigated.The performance of both the tools was judged with various performance measures and it is found that the results are quite encouraging. LS-SVM models performed better since it has captured all the higher peak discharges for both catchments, indicating LS-SVM is best suited for large sized catchments and MT tool is best suited for the smaller sized catchments. However LS-SVM performance is better as compared to MT as modeling approaches are examined, using the long-term observations of yearly river flow discharges.
Estimation of some meteorological parameters using hard and soft computing tools
(International Journal of Recent Advances in Engineering & Technology (IJRAET), 2016) Magar, Rajendra
Study of meteorological parameters is essential in deciding the effect on each other while finding out the best possible solution and the estimations for hydrological and meteorological parameters. The study involves in correlating all the measured parameters at Shivade catchment area of Narmada basin. The correlation on the observed parameters is carried out to perform overall sensitivity analysis. Out of al metrological parameters two of them are analyzed in this paper namely Dry bulb temperature and wet bulb temperature. The Dry Bulb and Wet Bulb Temperatures are important to determine the state of humid air. The knowledge of only two of these values is enough to determine the state including the content of water vapour and the sensible and latent energy. The meteorological parameters have been estimated using Multiple linear regression and artificial neural network (ANN). The meteorological parameters collected from Shivade catchment area. The data extended over a period from January 2002 to December2010 including only the monsoon months. Amongst the two methods, the ANN model exhibited better estimation values of the meteorological parameters.
Experimental Investigation and Prediction of Compressive Strength of HPC with SCMs
(Journal of Advance Research Construction and Urban Architecture, 2017) Magar, Rajendra; Khan, Afroz Rahat Naeem; Khan, Rahil; Ansari, Shahbaz; Khan, Haroon
Due to environmental concern, the use of supplementary cementitious materials (SCMs) is increasing at a high rate in construction industry. In this study, an experimental investigation has been carried out to assess the compressive strength of high performance ternary mix concrete with judicious replacement of cement with (SCMs), which include industrial waste products such as fly ash (FA), ground granulated blast furnace slag (GGBS) and micro silica. Replacement of cement was done up to 40%, 45%, 50%, by incorporating P100 fly ash as an ultrafine material with GGBS as SCMs. Each replacement was further divided into three sub parts (40%F. A-60%GGBS), (45%F.A-55%GGBS) and (50%FA-50%GGBS). Experimental results showed that Mix T3 (60%Cement-20%F.A-20%GGBS) produced maximum strength of 89.4 MPa and 100 MPa at 14 days’ and 28 days’ curing respectively. Experimentally generated data in the laboratory was used for the development of the multiple linear regression models. Keywords: Cement; P100 fly ash; FA; GGBS; HPC; Compressive Strength
Intermittent reservoir daily-inflow prediction using lumped and distributed data multi-linear regression models
(Indian Academy of Science, 2011-12) Magar, Rajendra
In this study, multi-linear regression (MLR) approach is used to construct intermittent reservoir daily inflow forecasting system. To illustrate the applicability and effect of using lumped and distributed input data in MLR approach, Koyna river watershed in Maharashtra, India is chosen as a case study. The results are also compared with autoregressive integrated moving average (ARIMA) models. MLR attempts to model the relationship between two or more independent variables over a dependent variable by fitting a linear regression equation. The main aim of the present study is to see the consequences of development and applicability of simple models, when sufficient data length is available. Out of 47 years of daily historical rainfall and reservoir inflow data, 33 years of data is used for building the model and 14 years of data is used for validating the model. Based on the observed daily rainfall and reservoir inflow, various types of time-series, cause-effect and combined models are developed using lumped and distributed input data. Model performance was evaluated using various performance criteria and it was found that as in the present case, of well correlated input data, both lumped and distributed MLR models perform equally well. For the present case study considered, both MLR and ARIMA models performed equally sound due to availability of large dataset.
Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data.
(Journal of Hydrology, 2012) Magar, Rajendra
Reservoir inflow forecast is a key component in planning development, design, operation and maintenance of the available water resources. Inflow forecast models are useful in many water resources applications such as flood control, drought management, optimal reservoir operation, hydropower generation (Yeh, 1985).
Nash IUH parameters estimation using method of moments - A case study
(Journal of Water Resources Society, 2014-04) Magar, Rajendra
Flood forecasting plays an important role in mitigating the natural disaster. Among the available methods for flood forecasting, the unit hydrograph (UH), and instantaneous unit hydrograph (IUH), is widely and successfully used. In case of IUH it is assumed that the hydrograph generation was affected by number of ‘n’ linear reservoirs having similar/same storage coefficient ‘K’ value. The IUH proposed by Nash has been widely used in rainfall-runoff (RR) simulation as well as for flood forecasting. However the success of application of Nash IUH model is based on the accuracy of the estimated parameters ‘n’ and ‘K’ for a given catchment. This study describes the development and application of Nash IUH for the Koyna watershed in Maharashtra, India. The parameters are estimated using method of moments (MOM). This IUH may be useful for predicting the flash flood in to the reservoir for a given rainfall. The obtained direct runoff hydrograph (DRH) estimated from IUH derived is compared with the observed DRH and found to be in good agreement with each other. The performance of the IUH model has been assessed using coefficient of correlation (R), Root mean square error (RMSE), error in peak inflow prediction (%MF) and time to peak flow.
Prediction of unconfined compressive and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes using multiple linear regression and artificial neural network
(Advances in Computational Design, Vol. 2, No. 3 (2017) 225-240., 2017) Magar, Rajendra
This paper presents the application of multiple linear regression (MLR) and artificial neural network (ANN) techniques for developing the models to predict the unconfined compressive strength (UCS) and Brazilian tensile strength (BTS) of the fiber reinforced cement stabilized fly ash mixes. UCS and BTS is a highly nonlinear function of its constituents, thereby, making its modeling and prediction a difficult task. To establish relationship between the independent and dependent variables, a computational technique like ANN is employed which provides an efficient and easy approach to model the complex and nonlinear relationship. The data generated in the laboratory through systematic experimental programme for evaluating UCS and BTS of fiber reinforced cement fly ash mixes with respect to 7, 14 and 28 days‟ curing is used for development of the MLR and ANN model. The data used in the models is arranged in the format of four input parameters that cover the contents of cement and fibers along with maximum dry density (MDD) and optimum moisture contents (OMC), respectively and one dependent variable as unconfined compressive as well as Brazilian tensile strength. ANN models are trained and tested for various combinations of input and output data sets. Performance of networks is checked with the statistical error criteria of correlation coefficient (R), mean square error (MSE) and mean absolute error (MAE). It is observed that the ANN model predicts both, the unconfined compressive and Brazilian tensile, strength quite well in the form of R, RMSE and MAE. This study shows that as an alternative to classical modeling techniques, ANN approach can be used accurately for predicting the unconfined compressive strength and Brazilian tensile strength of fiber reinforced cement stabilized fly ash mixes. Keywords: artificial neural network (ANN); back propagation algorithm; multiple linear regression (MLR); fly ash; unconfined compressive strength (UCS); Brazilian tensile strength (BTS)
Probabale maximum flood at Nira-Deoghar dam site in India
(Sardar Vallabhbhai National Institute of Technology, 2016-10-14) Shah, Dhaval; Magar, Rajendra
Estimation of inflow design flood i.e. Probable maximum flood (PMF) for major storage reservoirs is most important parameter. The consequences of a failure of the structure due to improper estimation of PMF could be calamitous in terms of loss of human lives and damage to property. PMF which is estimated from probable maximum precipitation (PMP) is used as inflow design flood for major projects. PMP is the greatest depth of precipitation for a given duration which is physically possible for an area. Various methods such as statistical, empirical, storm maximisation and transposition approach, and dynamic approach are used for estimation of PMP. This paper presents unit hydrograph method which reflects all physical characteristics of the catchment for obtaining PMF hydrograph. The study area selected is Nira-Deoghar dam which is located on River Nira in the Krishna basin, Maharashtra, India. The outcome of PMF in Indian scenario is very much important since it is directly related to dam safety.
Quality improvement by using quality control indicators in high rise building
(International Advanced Research Journal in Science, Engineering and Technology, 2018-02) Shaikh, Mohammed Ayyaz Mohammed Qasim (15CEM13); Magar, Rajendra; Mahajan, Girish
Three important parameters such as time, cost and quality are essentially necessary for successful completion of construction projects. Quality is the real parameter that is responsible for safety and overall health of construction projects. Maximum defect occurs during execution phase only due to non-compliance of desired specifications. It is observed that, on many sites, executors are not aware about quality control checklist and its significance. This is the reason why defects occur in even newly constructed structures. To overcome this, Android application, have been developed for Quality Control Indicator by using the Six-sigma process. The Six Sigma processes that are generally used in manufacturing plants, however its implementation has started in the construction industry. In the Android application, quality control checklist prepared by a construction company had taken for reference. Project authorities can apply quality control checklist on the activities and can give their remarks about the performance of particular construction activity such as Satisfactory (S ), Unsatisfactory (US ) and Not Available (NA). If any defect occurs in the activity and if it is not mitigated by site engineer or supervisor then the higher authority may take appropriate corrective action. By using this, Quality Control Indicator Application time required for lengthy conventional quality control process can be considerably reduced. Through this application, six sigma levels for particular performance are obtained immediately as well as cause s and effects of particular defect is also recorded in the application. Hence, this study covers the entire process of quality control indicators and android application for obtaining six sigma levels of various activities of the project. This study focusses on use to quality control indicator for various construction activities. QC Indicators indicates the quality status of the activity for facilitating the application of remedial measures in order to improve quality.
Reservoir inflow modeling using artificial intelligence techniques and its use in real life.
(GII, 2012-01-19) Magar, Rajendra
Operational planning of water resources systems like reservoirs and hydro power plants calls for real-time reservoir inflow forecasting. In spite of large number of works, the underlying phenomena are extremely complex, non-linear and uncertain, as a result of which the outcome may not always yield entirely satisfactory results.
Resource optimization for sustainable construction: A state of art
(International Advanced Research Journal in Science, Engineering and Technology, 2018-02-03) Tiwari, Shivendra (16CEM13); Magar, Rajendra; Honnutagi, Abdul Razak
The estimated cost of construction material on any construction project is about 40-60% of the total construction project cost in which approximately construction material’s waste contributes 30-35% of the material cost, which in result leads to project cost overrun and loss of materials. Lesser studies have been done for the construction material waste reduction or optimization directly at the time of its use on site. The basic aim of this study is to describe the methods by which the construction material as a resource can be used sustainably reducing the wastages and prevention at site during construction. The study discloses that selection of less experienced working method and the poor quality of materials to be used on site also results in material wastage during sudden design stage. The major beginning of material wastages during construction stage are improper uses of material as well as labors. Similarly, while procurement, wastages are caused during loading, unloading and transportation processes and unavailability to order small quantities of material. Also, lack of knowledge and improper security for materials procured causes the same even before its use on site. Thus, the study can be used further in co-ordination of optimization techniques on site to reduce the wastages and cost of materials during construction.
Review of IGBC Rating System for New Green Buildings
(Shree L.R. Tiwari College of Engineering, Bhayandar, 2017-03) Magar, Rajendra; Shah, Dhaval; Srivastava, Ashish
The green building concept ensures the minimum wastage in every stage of construction and operation of the new green building resulting in initial higher cost of approximately 16% as compared to the saving in long term with recovery within 2 to 5 years of the life cycle of the building. The green building is so planned and design so as to reduce the overall impact of construction material on natural environment and human health by efficiently using energy, water and other resources and also by protecting occupant’s health and increasing the overall productivity of the institution, it also helps in reducing the waste, pollution and environmental degradation. The adoption of green feature considered while planning create lowest effect to the existing landscape and the site layout, the building materials proposed to be used shall be either a recycled product or an environmentally sustainable material, avoiding use of toxic material and maximum utilization of recycled or recyclable materials, the use of water efficiently and recycling the same for reuse, maximum use of renewable energy, eco-friendly use of equipment, fresh air inside building, highest safety norm adoption for human use and providing maximum comfort to the users, with the use of building management system. The review involves the evaluation of realistic rating aimed for the proposed new building, as per overall requirements as required for fulfilling the IGBC rating program. This involves the identification for the reduction of greenhouse gases with financial implications and tangible benefits to a client over a life cycle period of the building in a specified time frame. To carry out the above study in accordance to ASHRAE 90.1-2004/ECBC, performance rating method a simulation would considered appropriate modelling assumptions, schedule for the project for various occupancies, air changes per hour, lighting density and U-factors for fenestration etc.
Review on simulating uncertainties in construction projects
(International Advanced Research Journal in Science, Engineering and Technology, 2018-02) Katrekar, Shweta Sushil (16CEM06); Magar, Rajendra; Khan, Afroz
Uncertainty certainly affects the performance of a construction project. The exact definition of risk and uncertainty is still not known. Everyone has their own perspectives. Though, it is accepted as the results and outcomes are likely to differ from expected values. The values can be considered to be Time, Quality and Economy of the project depending upon the project needs. Therefore, in construction project management, the effects of unidentified risks and uncertainties hamper the project time, quality as well as its economy and ultimately obstruct the project management and thus its development. Identifying the uncertainty and quantitatively analyses the impact on the project performance can notably enhance the exactness, validity and reliability of a project plan. This paper describes a methodology to systemize, model, and diminish uncertainty. Uncertainty management is one of the major problems faced in construction. Most of the solutions aim to solve the problem but it has to meet demands of all project criteria. The uncertainty is always evaluated at the start of the construction project but it should be continuing process with solutions at the time of whole project life cycle. The application of risks and uncertainties management is practiced in construction in developing countries and thus the result poses massive challenges in the project development and management. Therefore, this study provides a brief idea of various research taken place to simulate the identified uncertainties in construction projects. It also recommends the idea of uncertainty and risk and their consequences on construction projects management as one of the challenges faced in the construction industry of developing countries.
Review on simulating uncertainties in construction projects
(International Advanced Research Journal in Science, Engineering and Technology, 2018-02) Katrekar, Shweta (16CEM06); Magar, Rajendra; Khan, Afroz
Uncertainty certainly affects the performance of a construction project. The exact definition of risk and uncertainty is still not known. Everyone has their own perspectives. Though, it is accepted as the results and outcomes are likely to differ from expected values. The values can be considered to be Time, Quality and Economy of the project depending upon the project needs. Therefore, in construction project management, the effects of unidentified risks and uncertainties hamper the project time, quality as well as its economy and ultimately obstruct the project management and thus its development. Identifying the uncertainty and quantitatively analyses the impact on the project performance can notably enhance the exactness, validity and reliability of a project plan. This paper describes a methodology to systemize, model, and diminish uncertainty. Uncertainty management is one of the major problems faced in construction. Most of the solutions aim to solve the problem but it has to meet demands of all project criteria. The uncertainty is always evaluated at the start of the construction project but it should be continuing process with solutions at the time of whole project life cycle. The application of risks and uncertainties management is practiced in construction in developing countries and thus the result poses massive challenges in the project development and management. Therefore, this study provides a brief idea of various research taken place to simulate the identified uncertainties in construction projects. It also recommends the idea of uncertainty and risk and their consequences on construction projects management as one of the challenges faced in the construction industry of developing countries.
Review on weibull analysis for performance evaluation in construction project
(International Advanced Research Journal in Science, Engineering and Technology, 2018-02) Gavaskar, Pradnya (16CEM05); Magar, Rajendra; Honnutagi, Abdul Razak
In construction projects, construction project managers monitor and control the project performance to ensure the project is under control. The Earned Value Management (EVM) method is a tool that integrates three critical elements of project management: scope management, cost management, time management. EVM is traditi onally used to monitor and control the project performance by using cost and schedule indices. EVM is widely used to forecast project cost and time at completion. However, the application of EVM is limited due to poor accuracy in forecasting cost and sched ule performance. Conventional EVM has inability to address the uncertainties as well as their causes and effects. Recently, many EVM - based cost and schedule performance forecasting methods were introduced by many researchers. This study describes the major aspects of EVM and useful statistical techniques to enhance the effective application of EVM in project management. Further it includes the overview of a statistical approach to refine and improve the performance of conventional EVM by introduction of Wei bull Analysis. This can be used in addition with EVM to give probabilistic approach to evaluate cost and schedule performance in construction project

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