Department Of Civil Engineering

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Soil moisture plays an important role in partitioning rainfall into runoff and evapotranspiration. Due to advancements in remotely sensed soil moisture data acquisition techniques, many soil moisture data assimilation (SMDA) studies have been conducted to improve streamflow prediction. It is thus expected that the outcome of a SMDA exercise will be determined by the quality of soil moisture data in hand and the hydrology of the catchment. Our study begins with the hypothesis that it is possible to determine the usefulness of a satellite-based soil moisture data product for areas where paramaterizing a complex model is difficult due to availability of limited information. To this end, we use satellite-based GLDAS root-zone soil moisture data with dynamic Budyko (DB), rainfall-runoff model, to improve streamflow prediction for 60 US basins. Our results suggest that there is a reasonably good one-to-one or universal relationship between instantaneous dryness-index (φ), the key state variable of the DB model, and root-zone soil moisture (θ), which implies that the model can directly use soil moisture information for predicting streamflow. To check the robustness of the universal φ-θ relationship, we also developed basin specific φ-θ relationships. Model performance, expressed in terms of Nash-Sutcliffe efficiency (NSE), improved in 34 basins when we considered the universal φ-θ relationship and in 51 basins when we considered the basin specific relationships. Multiple linear regression (MLR) analysis reveals that change in NSE due to the use of soil moisture information is predicted quite well by certain basin characteristics. In particular, it is found that available water capacity and forest area positively influence NSE, whereas average sand, silt and clay contents, latitude, and longitude affect it negatively. A slightly stronger MLR relationship was observed while considering soil moisture deficit (the difference between saturated soil moisture and actual soil moisture) in place of soil moisture. From the stepwise MLR analysis, it is observed that the vegetation and runoff generation mechanism control the parameters of the φ-θ relationship. Overall, our study provides a framework to determine the suitability of remotely-based soil moisture data for hydrological modelling. © 2020 Elsevier B.V.

World University root node

Journal of Hydrology

A novel framework to determine the usefulness of satellite-based soil moisture data in streamflow prediction using dynamic Budyko model

Accurate and reliable forecasting of reservoir inflows is crucial for efficient reservoir operation to decide the quantity of the water to be released for various purposes. In this paper, an artificial neural network (ANN) model has been developed to forecast the weekly reservoir inflows along with its uncertainty, which was quantified through accounting the model’s input and parameter uncertainties. Further, to investigate how the effect of uncertainty is translated in the process of decision making, an integrated simulation–optimization framework that consists of (i) inflow forecasting model; (ii) reservoir operation model; and (iii) crop simulation model was developed to assess the impacts of uncertainty in forecasted inflow on the irrigation scheduling and total crop yield from the irrigation system. A genetic algorithm was used to derive the optimal reservoir releases for irrigation and the area of irrigation. The proposed modeling framework has been demonstrated through a case example, Chittar river basin, India. The upper, lower, and mean of forecasted inflow from the ANN model were used to arrive at the prediction interval of the depth of irrigation, total crop yield, and area of irrigation. From the analysis, the ANN model forecast error of ± 69% to the mean inflow was estimated. However, the error to mean value of simulation for total irrigation, total yield, and area of irrigation was ± 13.3%, ± 6.5%, and ± 4.6%, respectively. The optimizer mainly contributed to the reduction in the errors (i.e., maximizing the total production with the optimal water releases from the reservoir irrespective of inflow to the reservoir). The results from this study suggested that the information on the uncertainty quantification helps in better understanding the reliability of the systems and for effective decision making. © 2020, The International Society of Paddy and Water Environment Engineering.

Department Of Physics

Paddy and Water Environment

Implications of uncertainty in inflow forecasting on reservoir operation for irrigation

This paper presents an experimental investigation of ten deep beams with a shear span-to-depth ratio of 1.0. Nine of the ten deep beams were provided with web reinforcement, which improves the load carrying capacity of deep beams to a maximum of 15%. Diagonal crack width of 0.3 mm was observed at beam's service load with a web reinforcement ratio of more than 0.46% in both vertical and horizontal directions. Addition of web reinforcement in both directions controls diagonal crack width effectively. ACI 318–19 strut-and-tie model provisions for deep beams with web reinforcement were analysed using experimental investigations of the present study and extensive deep beam data points from literature. It is observed that ACI 318–19 predicts shear capacity of deep beams with a better mean strength ratio of 0.67 compared to AASHTO, EC2, fib MC 2010. Shear strength limits of ACI 318–19 are found to be highly conservative. ACI 318–19 strut coefficient has been evaluated from database of beams that are failed other than yielding of tie. It has been found that the strut coefficient strongly depends on concrete strength, and use of a single strut factor may produce an unsafe estimation of deep beam capacity. Strut coefficient is proposed in this study for strut-node interface with adequate transverse reinforcement as a function of concrete strength. Proposed strut coefficient improves the capacity estimation of deep beam compare to ACI 318–19, AASHTO, EC2, and fib MC 2010. Proposed method has the lowest coefficient of variation for shear strength estimation, and overestimation percentage is within 5%. © 2021 Institution of Structural Engineers

Structures

Experimental investigation of RC deep beams with web reinforcement and improvement of ACI 318–19 strut coefficient

This article presents an experimental investigation on 11 reinforced concrete (RC) deep beams without web reinforcement. Shear spandepth ratio (a/d), beam depth, and percentage of tension reinforcement are the variables. Beams with a/d less than 1.5 could carry loads beyond the diagonal cracking of concrete due to the formation of a diagonal concrete strut. Diagonal cracking of deep beams with an a/d of 1.0 was observed at a load of approximately 20% of ultimate capacity. Further, 607 more RC deep beam experimental results were collected from the literature. Strut-and-tie model provisions of ACI 318-14 and ACI 318-19 were validated with a database of 618 RC deep beam results. The capacity of beams with a/d higher than 1.5, and concrete strengths higher than 60 MPa was overestimated by ACI 318-19 even after the reduction of strut efficiency factor from 0.6 to 0.4. However, the percentage overestimation by ACI 318-19 is within 5.0%. ACI 318-14 predicts the capacity more accurately than ACI 318-19 with a strut efficiency factor of 0.6, with only 6.0% of overestimation, if the maximum shear strength limit is considered. The maximum shear strength limit of ACI 318-14 is found to be highly conservative. The reduction of strut efficiency factor in ACI 318-19 without modifying maximum shear strength limit results in highly conservative estimations. Copyright © 2021, American Concrete Institute. All rights reserved.

ACI Structural Journal

Experimental verification of ACI 318 strut-and-tie method for design of deep beams without web reinforcement

Unsymmetric composite laminates exhibit two or more stable equilibrium shapes with opposite curvature as a result of residual thermal stresses induced during the curing process. Surface bonded Macro Fibre Composite (MFC) actuators are generally employed to trigger snap-through between one stable shape to another by applying external voltages. However, these actuators require high actuation voltage input to change from one stable shape to another, especially when used in morphing applications. If the snap-through voltage is too high, morphing becomes infeasible or may require several actuators, which is contrary to the weight requirements. Variable Stiffness (VS) laminates provide the possibility for an enlarged design space with the possibility to tailor stiffness parameters, leading to lower snap-through loads and consequently reducing the size of the actuators. On the prediction of snap-through voltages, the existing semi-analytical models have shown reasonably high discrepancies between numerical and experimental results. An improved analytical model is proposed in this study to predict the snap-through of bistable VS laminates with MFC actuators. In the improved model, the equations resulting from the compatibility and the in-plane equilibrium are described equivalent to a standard plane elasticity problem which can be solved using a standard finite element (FE) approach. In addition, the total potential energy is written in terms of curvatures. The improved semi-analytical results are compared with a full geometrically nonlinear FE calculation. © 2021 Elsevier Ltd

Composite Structures

Snap-through of bistable variable stiffness laminates using MFC actuators

Tensile properties of geomaterials often play an important role in many geotechnical engineering problems. Compacted soil layers in dams, clay liners in landfills, reinforced earth-retaining wall systems, cement stabilized crushed rocks in pavements, etc. are constantly checked for tensile cracking. This type of cracking happens when the developed tensile stress exceeds the tensile strength of the material. Usually, the tensile strength of natural soil is assumed to be negligible. However, it is proven that cement treated soils possess some amount of tensile strength. The determination of tensile strength of cement treated clay, using a newly developed tensile testing apparatus, is focussed in this study. The existence of an optimum cement content for tensile strength is also discussed. © Published under licence by IOP Publishing Ltd.

Fulltext

IOP Conference Series: Earth and Environmental Science

Tensile Strength of Cement Treated Clay

The catalytic pyrolysis of different types of polyoleﬁn and multilayer packaging based plastic wastes in the presence of commercial zeolite catalyst was studied in the batch pilot scale reactor. Different types of multi-layer plastics such as biaxial oriented polypropylene (BOPP), metalized biaxial oriented polypropylene layers (MET/BOPP), poly ethylene terepthalate (PET), metalized polyethylene-terepthalate (MET/PET), PET combined polyethylene (PET/PE) and mixed polyolefin plastic wastes obtained from the municipal corporation were pyrolyzed to determine the oil, gas and char distribution. BOPP based plastic waste exhibited higher oil yield and calorific value (65–70%, 45.14 KJ/g) compared to PET based MLPs (17.8 %, 30 KJ/g) and laminated metalized plastics (13 %, 37 KJ/g). Modifying the feed composition by mixing of polyolefins-based waste plastics with PET based MLPs and BOPP/MET BOPP doubled the liquid yield and notably altered the physicochemical characterization of the resulted pyrolysis oil. Char yield in the polyolefins-based waste is observed to be lesser than the MLP based waste plastics. GC–MS analysis revealed the percentage area of hydrocarbons compounds of the pyrolysis oil obtained from PET based MLP experiments contains high fractions of medium and heavier range hydrocarbons (C11 – C20, C21 – C30). Sulfur content in the oil from different MLPs was measured as below the detection limit. Functional groups of hydrocarbons of oil were analyzed using FT-IR. Solids were characterized for the presence of heavy metals such as Al, Cr, Cu, Co, Pd, and Ni. © 2020 Institution of Chemical Engineers

Department of Electrical Engineering

Department of Mathematics

Process Safety and Environmental Protection

Catalytic pyrolysis of polyoleﬁn and multilayer packaging based waste plastics: A pilot scale study

In this study, an attempt has been made to explore the influence of four inflow boundary conditions on solute plume migration and compared their concentrations. A numerical model was used to simulate the solute transport for different boundary conditions at the injection well with three different recharge and six hydraulic conductivity scenarios. Dirichlet concentration boundary, constant point source, and two Robin boundary conditions were applied to exemplify their effects on the outcomes. Significant variations were visible in the solute concentration profiles and their respective spreading patterns. Results show discrepancies between solutions obtained from the first-type and the third-type inflow boundary conditions for smaller Peclet numbers. The applicability of the M5′ model tree, a tree-based machine learning approach, was investigated and thereby exploited its capability to interpret the plausible functional dependency among the input parameters. The model tree also produced a dominancy structure within the parameter space with its combined classification and regression features. It was concluded that adopting a general boundary condition or generalization of solutions remained highly challenging, given the different input space parameters dictating a hydrogeological model. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Department of Ocean Engineering

Modeling Earth Systems and Environment

Sensitivity analysis of inflow boundary conditions on solute transport modeling using M5′ model trees

The urge to reduce the carbon footprints from cement production warrants the development of more sustainable approaches in the construction industry. Towards this, the long term corrosion resistance of the embedded steel rebar in a novel ternary-blended reinforced concrete system with 56 wt% Ordinary Portland cement (OPC), 40 wt% fly ash, 2 wt% nanomodifiers, and 2 wt% corrosion inhibitor (referred to as CFNI) was studied by chemical and electrochemical tests in a simulated chloride environment for 180 days. The performance was compared with three other concrete systems (CC (100% OPC), CF (60 wt% OPC and 40 wt% fly ash) and CFN (58 wt% OPC, 40 wt% fly ash and 2 wt% nanomodifiers). The electrochemical results indicated a significant enhancement in the corrosion resistance of steel in the CFNI concrete as compared to other systems. A five times higher value of polarization resistance (Rp) is obtained in CFNI, as compared to the control concrete, indicate the better resistance of CFNI. Further, in CFNI specimen, the chloride ingress rate was significantly lower and the Field Emission Scanning Electron Microscopy (FESEM) images showed no microcracks or pores at the corroded concrete-steel interface of CFNI specimens. The apparent diffusion coefficient (Dcl) of the concrete system was determined using the bulk diffusion test and chloride profiling. The value of Dcl for CFNI concrete was found to be one order less in magnitude than other concrete specimens, indicating the enhanced resistance against chloride attack. These results show that CFNI concrete is a promising ternary-blended concrete mix to achieve long corrosion-free service life for the structures in aggressive chloride environments. © 2020 Elsevier Ltd

Construction and Building Materials

The chloride-induced corrosion of a fly ash concrete with nanoparticles and corrosion inhibitor

Clay liners are provided in waste landfills to prevent the leachate from percolating into underlying soil and ground water and polluting it. Hence, soils used as landfill liners must possess low hydraulic conductivity (< 10-7 cm/s). In the initial as-compacted state, liners satisfy this design criterion. However, in the field, liners are subjected to alternate wet-dry cycles and the initial microstructure of liners change, thereby affecting their hydraulic properties. The present study was conducted on a locally available red soil mixed with bentonite so that it satisfies the requirement of hydraulic conductivity in the as-compacted state. To achieve this objective, identical specimens compacted at optimum moisture content to its maximum dry density were inundated with distilled water under a surcharge load of 12.5 kPa. Upon attainment of maximum swelling, hydraulic conductivity tests were conducted at swollen state under a hydraulic gradient of 20. The soil specimens were then dried at a temperature of 45 2 C. The weight, height and diameter of specimens were measured continuously during drying to study the shrinkage behaviour of the soil. The dried specimens were subjected to subsequent wet-dry cycles until the specimens reached an equilibrium state and the hydraulic conductivity was determined after each wetting cycle. SEM images were also captured to analyse the changes in the soil structure in the as-compacted state and at the end of different wetting cycles. © Published under licence by IOP Publishing Ltd.