Department of Civil & Infrastructure Engineering

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IIT Jodhpur

Mode-I fracture toughness (FT) is an important property to model fracture propagation in rocks and it has wide application in a plethora of rock mechanics problems such as hydraulic fracturing design, tunneling, geothermal energy extraction, CO2 sequestration, blasting and drilling activities, well-bore stability analysis etc. Determination of fracture toughness from different individual index geomechanical properties is an ongoing research area. Multiple past research have established simple regression relations between FT and individual mechanical parameters with various degree of success. But these were found to be rock and site specific and lack wide acceptance. In this paper, multiple regression analysis, and three types of soft computing methods (e.g. artificial neural network, fuzzy inference system, and adaptive neuro-fuzzy inference system) have been employed to predict mode-I fracture toughness from a set of common geomechanical properties. Based on Pearson's correlation coefficient, three index geomechanical properties, namely, tensile strength, P-wave velocity, and S-wave velocity were chosen to estimate the mode-I FT. As the results suggest, a single model is sufficient to estimate FT in all the sedimentary and crystalline rocks. Such model is capable of predicting fracture toughness irrespective of strength or compositional heterogeneity that is encountered in field. Statistical analysis of the predictions using correlation coefficient (R2), root mean square error (RMSE), mean absolute percentage error (MAPE), and variance accounted for (VAF) show that all the soft computing methods performed better than the multiple regression models. However, among the soft computing methods, adaptive neuro-fuzzy inference system, which incorporates elements of both the artificial neural network and fuzzy inference system, constructs the best model for prediction. This is the first ever reported instance, where soft computing has been used to predict mode-I fracture toughness of dry rocks from the mechanical properties, and the results confirmed that this is an easier, efficient but highly accurate tool for prediction. © 2018 Elsevier Ltd

World University root node

Measurement: Journal of the International Measurement Confederation

Predicting mode-I fracture toughness of rocks using soft computing and multiple regression

Young's modulus of coal is a very important deformational property which dictates how the material will behave in presence of sub- and super-critical carbon dioxide during sequestration. But this is also a difficult property to measure due to the extensive instrumental requirements, and wide compositional and structural heterogeneity of the coal. Therefore, an indirect method to measure the saturated Young's modulus of coals has been developed in the present research using artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). Low and high rank specimens from three different basins of India and Australia have been used for the analysis. Saturation pressure and the compressive strength (UCS) of the coal specimens have been used as the input parameters to build the models. The performance of the models were evaluated against the multivariate regression model using four different types of statistical parameters such as root mean square error (RMSE), coefficient of determination (R2), mean absolute error percentage (MAPE), and variables accounted for (VAF). Results show that ANFIS model is the best performing one with the least RMSE and MAPE, and highest VAF and R2. This research demonstrates that it is possible to develop soft computing models that can successfully estimate some of the critical rock mechanics parameters essential for the technical evaluation of the sequestration projects on coal. This generalized model is also excellent in incorporating the possible effect of heterogeneity in specimens and performs well for samples that show similar data distribution. If applied, this can potentially reduce the requirement of extensive, complex and expensive instruments that are required for similar investigations. © 2018 Elsevier Ltd

Regression and soft computing models to estimate young's modulus of CO2 saturated coals

This study focuses on evaluating the flow behavior of conventional and polymer modified asphalt binders in steady- and dynamic-shear domain, for a temperature range of 20–70 °C, using a Dynamic Shear Rheometer (DSR). Steady-shear viscosity and frequency sweep tests were carried out on two conventional (VG 10 and VG 30) and two polymer (SBS and EVA) modified asphalt binders. Applicability of the Cox–Merz principle was evaluated and complex viscosity master curves were analyzed at five different reference temperatures. Cross model was used to simulate the complex viscosity master curves at different temperatures. It was found that asphalt binders exhibited shear-thinning behavior at all the test temperatures. The critical shear rate increased with increase in temperature and was found to be lowest for plastomeric modified asphalt binder. The Cox–Merz principle was found to be valid in the zero-shear viscosity (ZSV) domain and deviated at higher frequency/shear rate for all the binders. Results from the study indicated that the ratio of ZSV can be successfully used as shift factors for construction of master curves at different reference temperatures. Cross model was found to be suitable in simulating the complex viscosity master curves at all the test temperatures. Analysis of model parameters indicated that a strong relationship exists between ZSV and the critical shear rate. ZSV and critical shear rate varied exponentially with temperature. This relationship was used to propose a simple equation for assessing the shift factors for construction of master curves. © 2017, Springer Science+Business Media B.V.

Mechanics of Time-Dependent Materials

Study on viscosity of conventional and polymer modified asphalt binders in steady and dynamic shear domain

This paper describes an experimental study to estimate the stub columns capacity of cold–formed square (SHS) and rectangular hollow sections (RHS) containing two opposite central circular perforations at column mid–height. The stub columns were extracted from commercially available Tata Structura–YSt 310 tubular sections, with minimum yield strength of 310 MPa, conforming to Indian Standard 4923. The influence of two opposite central circular perforations on the structural performance of tubular steel stub columns under concentric loading was investigated for perforation size to flat width ratios up to 0.9 The local geometric imperfections, load–end shortening curves, strain distributions at mid height of column and typical failure modes observed from the present test programme are documented in this paper. Further, the ultimate column capacities recorded from the test programme are compared with codified design predictions as well as design equations proposed by various researchers. Based on the comparison, it is observed that the predictions made by most of the currently available design equations are conservative and reliable but generally scattered for design of cold–formed tubular structural steel stub columns having central circular perforations. © 2018 Elsevier Ltd

Thin-Walled Structures

Experimental investigation on performance of perforated cold–formed steel tubular stub columns

India has witnessed some of the most devastating extreme precipitation events, which have affected urban transportation, agriculture and infrastructure. Despite the profound implications and damage due to extreme precipitation events, the influence of anthropogenic warming on the intensity and frequency of extreme precipitation events over India remains poorly constrained. Here using the gridded observations and simulations from the Coupled model intercomparison project 5 (CMIP5) and Climate of 20th century plus (C20C+) detection and attribution (D&A) project, we show that the frequency and intensity of extreme precipitation events have increased in India during the last few decades. Along with the extreme precipitation, dew point temperature has also increased during 1979–2015. The scaling relationship between extreme precipitation and dew point temperature shows a super (more than 7% increase per unit rise in dew point temperature) Clausius-Clapeyron (C-C) relationship for the majority of south India. Moreover, southern and central India show a higher (10%/°C) scaling relationship than north India (3.5%/°C). Our analysis using the Hist (historic) and HistNat (historic natural) simulations from the CMIP5 and C20C+ projects confirms an increase in the frequency of extreme precipitation events under the anthropogenic warming. Moreover, we show that 1–5 day precipitation maxima at 5–500 year return period increases (10–30%) under the anthropogenic warming. The frequency of precipitation extremes is projected to rise more prominently in southern and central India in the mid and end of the 21st century under the representative concentration pathway (RCP) 8.5. Our results show a significant contribution of anthropogenic warming in the rise of the frequency of extreme precipitation, which has implications for infrastructure, agriculture and water resources in India.

Weather and Climate Extremes

Increase in extreme precipitation events under anthropogenic warming in India

Abstract. Extreme precipitation events and flooding that cause losses to human lives and infrastructure have increased under the warming climate. In August 2018, the state of Kerala (India) witnessed large-scale flooding, which affected millions of people and caused 400 or more deaths. Here, we examine the return period of extreme rainfall and the potential role of reservoirs in the recent flooding in Kerala. We show that Kerala experienced 53% above normal rainfall during the monsoon season (till August 21st) of 2018. Moreover, 1, 2 and 3-day extreme rainfall in Kerala during August 2018 had return periods of 75, 200 and 100 years. Six out of seven major reservoirs were at more than 90% of their full capacity on August 8, 2018, before extreme rainfall in Kerala. Extreme rainfall at 1&ndash;15 days durations in August 2018 in the catchments upstream of the three major reservoirs (Idukki, Kakki and Periyar) had the return period of more than 500 years. Extreme rainfall and almost full reservoirs resulted in a significant release of water in a short-span of time. Therefore, above normal seasonal rainfall (before August 8, 2018), high reservoir storage and unprecedented extreme rainfall in the catchments where reservoirs are located worsened the flooding in Kerala. Reservoir operations need be improved using a skillful forecast of extreme rainfall at the longer lead time (4&ndash;7 days).

Hydrology and Earth System Sciences Discussions

The Kerala flood of 2018: combined impact of extreme rainfall and reservoir storage

The phenomenological theory of turbulence (PTT) remains a long-standing and fascinating theory in turbulence research. In this review article, we highlight the state-of-the-science of the impact of the PTT on the pragmatic approach to fluvial hydraulics, explored over recent decades, discussing the salient and the subtle roles that the turbulence plays in governing many physical processes. To acquire a theoretical explanation of this pragmatic approach necessitates an intuitive thought that can bring together the background mechanisms of all the physical processes under one law - a thought that is capable of finding their inextricable links with the turbulent energy spectrum. We begin here with emphasizing the spectral and the co-spectral origin of the well-recognized laws of the wall, the resistance equation, and the turbulence intensities by portraying the typical momentum transfer mechanism of eddies in a turbulent flow. Next, we focus on the scaling laws of key fluvial processes derived from the perspective of the PTT, enlightening their physical insight and ability to judge how far the so-called empirical formulas can be used with confidence. The PTT has been able to disclose the origin of several primeval empirical formulas that have been used over many years without having any theoretical clarification and confirmation. Finally, we make an effort to describe some unsolved issues to be resolved as a future scope of research. © 2018 Author(s).

Physics of Fluids

Impact of phenomenological theory of turbulence on pragmatic approach to fluvial hydraulics

The areas of glacial lakes in the Himalayas continue to increase alarmingly due to global warming with consequent risk of glacial lake outburst flood (GLOF). The outburst is most common for moraine-dammed lakes as a result of a failure of the dam by overtopping and erosion or piping due to seepage. In the present context, GLOF events, especially for the moraine dam failure process needs to be predicted to assess the drastic and detrimental impacts on the downstream river valley. This study focuses on validating an integrated model for simulating the failure of moraine dam by overtopping and erosion using a coupled numerical simulation model. The proposed numerical methodology is validated with the data from experiments in laboratory scale physical models. The results of the model are compared for both the erosional profiles during collapse of the dam and the resulting outflowing flood hydrograph. The primary finding is that the moraine dam height and the volume of the lake upstream of the dam are the most sensitive parameters influencing the GLOF peak. The model is also applied to the field problem of the Tangjiashan lake outburst and dam failure and shows reasonably good agreement with observations. The validated model is also run for the South Lhonak glacial lake in the Sikkim Himalayas, India to obtain the probable flood hydrograph in case of failure of the moraine dam. © 2018 Elsevier B.V.

Journal of Hydrology

Moraine dam breach and glacial lake outburst flood generation by physical and numerical models

this study, a mathematical model for the Reynolds stress profiles in different regions of a submerged turbulent plane offset jet was developed. The two-dimensional Reynolds-averaged Navier-Stokes and the continuity equations were solved for the determination of the velocity and the Reynolds stress profiles within the jet layer in different regions of a submerged offset jet. The theoretical derivations involved a boundary layer approximation. The velocity profiles in the preattachment region obeyed an exponential function, whereas those in the impingement and wall jet regions followed a combination of a power function for the inner layer and an exponential function for the outer layer of the jet. The computed velocity and the Reynolds stress profiles corresponded well with the previous experimental results of the flow in submerged turbulent plane offset jets. © 2018 American Society of Civil Engineers.

Journal of Engineering Mechanics

Reynolds stress in submerged turbulent plane offset jets: Mathematical model

The nonlinear momentum equation for turbulent far-wake flow downstream of a cylinder is derived from the Reynolds averaged Navier–Stokes equations and solved by iteration and generalized similarity solution. The first-order Oseen-type linearization yields for the wake boundary layer width a series, whose terms vary as x1∕2, x−1∕2, x−3∕2 etc., where x is the streamwise distance from the center of cylinder. The velocity deficit from the free-stream velocity is similarly obtained as a series and the iteration is carried over to a second-order. This method is then applied to the problem of an array of cylinders. Both turbulent and laminar far-wake flow cases are analyzed. The series solutions broadly extend the earlier findings. The first-order solutions agree in form with those stated in the book of Schlichting (1979). © 2017 Elsevier Masson SAS