Department of Civil & Infrastructure Engineering

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IIT Jodhpur

The paper discusses the major limitations of the existing speed–area occupancy curve for multi-class traffic. Any driver will react not to the actual area occupancy, but to a perceived area occupancy based on the spatial arrangement and percentage composition of vehicles. To address multi-class traffic peculiarities, this paper proposes a formulation for perceived area occupancy. Traffic flow is simulated on a road section using a calibrated microsimulation model for Electronics City, Bangalore, India. The speed–concentration curves are plotted for various functional forms using density, area occupancy, and perceived area occupancy. Analysis results showed that the speed–perceived area occupancy curve could capture the speed variation better than by the existing functional forms and could predict traffic flow significantly better than with that by speed–density curves when used with the fundamental equation of traffic flow. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

Transportation Letters

On the modelling of speed–concentration curves for multi-class traffic lacking lane discipline using area occupancy

This paper presents a systematic finite element (FE) based parametric study to quantify the buckling capacity of perforated cold-formed and hot-rolled steel module column. The effects of various key geometric parameters such as eccentricity (location of perforation/column length), shapes (viz. circular, square and hexagonal), sizes (width/diameter) and height (depth) of perforation; and cross-sectional thickness, on the buckling performance of cold-formed and hot-rolled steel stub columns, have been investigated. Based on the analysis, the reduction in column capacity is found to be maximum when the perforation is located at column mid-height, as anticipated. The perforation shapes under consideration have been found to have marginal impact on the buckling capacity of the module stub columns, although the reduction in column capacity is seen to be in the order – square > hexagon > circular perforated columns (having same perforation size). The critical buckling capacity of perforated module column is observed to be linearly decreasing as the perforation size ratio (perforation size/flat-element width) increases. However, for the same width of perforation, increasing the perforation height up to 2.5 times the perforation width, the change in column capacity is found to be negligible. Furthermore, the applicability of existing design for perforated columns has been assessed and found that, although most of the design equations generate conservative and reliable predictions both for cold-formed and hot-rolled steel, the design formulae which are based on effective width method are found to be more accurate as compared to those which are based on total area method. © 2020 Elsevier Ltd

World University root node

Journal of Constructional Steel Research

Effect of access openings on the buckling performance of square hollow section module stub columns

Consecutive failures in the summer monsoon rainfall led to widespread and severe droughts with profound implications for agricultural activities in India. However, the likelihood of successive megadroughts in India's past and future climate remain poorly understood. Using Palmer Drought Severity Index (PDSI) from the Monsoon Asia Drought Atlas (MADA), we show that the major famines that affected millions of people during 1200–2018 were linked with summer monsoon droughts. Four megadroughts covering more than 40% of the country occurred for two consecutive summer monsoon seasons during 1200–2018. The most recent and severe megadrought occurred in 2002–2003. Simulations from the Community Earth System Model (CESM) for the last millennium (850–2005) ensemble (LME) show that the likelihood of two and three-year consecutive megadroughts during the summer monsoon is about 0.7 and 0.3 events per 100 years, respectively. Large ensemble simulations from CESM (CESM-LE) show a decline in the frequency of megadroughts in the future. Summer monsoon megadroughts are strongly associated with the warm sea surface temperature (SST) anomalies over the Pacific Ocean in the past and future climate. Substantial warming under the projected future climate can cause megadroughts under near-normal precipitation during the summer monsoon season. Despite the projected decline in the likelihood of the summer monsoon megadroughts under the warming climate, megadroughts in the future can have considerable implications for India's food production and water availability.

Fulltext

npj Climate and Atmospheric Science

Famines and likelihood of consecutive megadroughts in India

Peninsular Indian agriculture and drinking water availability are critically reliant on seasonal winter rainfall occurring from October to December, associated with the northeastern monsoon (NEM). Over 2016-2018, moderate-to-exceptionally low NEM rainfall gave rise to severe drought conditions over much of southern India and exacerbated water scarcity. The magnitude and dynamics of this drought remain unexplored. Here, we quantify the severity of this event and explore causal mechanisms of drought conditions over South India. Our findings indicate that the 3-year cumulative rainfall totals of NEM rainfall during this event faced a deficit of more than 40% - the driest 3-year period in ∼150 years according to the observational record. We demonstrate that drought conditions linked to the NEM across South India are associated with cool phases in the equatorial Indian and Pacific Oceans. Future changes in these teleconnections will add to the challenges of drought prediction.

Environmental Research Letters

Unprecedented drought in South India and recent water scarcity

A novel adaptive high dimensional model representation (HDMR) is developed for stochastic finite element analysis of composite plate. Uncertainty propagating through the physical system is quantified using this technique where only the significant dimensions are retained. Influence of these dimensions is modeled by different orders which are preferred to be low for computational tractability. These dimensions are identified by a sensitivity analysis using support points in the sparse grid which are generated using multiple levels of hierarchy, joint or marginal probability distributions and dimension adaptiveness. This multi level hierarchical generation of support points fill the domain of the input variables with major emphasis on the regions of interest which may be the entire space, limit state, maxima/minima or tail ends of the probability distribution function for rare events depending upon the nature of the problem. The hybrid characteristics of the proposed dimension decomposition is introduced in this paper where the component functions are expressed using orthogonal bases and the error term which is further modeled using Gaussian random process (i.e. Kriging). The performance of the proposed Hybrid dimension adaptive HDMR (hdA-HDMR) is illustrated using stochastic finite element analysis of laminated composite plate whose material properties are considered as homogeneous non-normal random fields. © 2020 Elsevier Ltd

Composite Structures

Development of hybrid dimension adaptive sparse HDMR for stochastic finite element analysis of composite plate

EGU General Assembly Conference Abstracts, EGU

Future Changes in extreme precipitation over South Asia and its causes

Pullout behaviour of geogrids is critical to understand in the design of mechanically stabilized earth walls. The pullout coefficients are determined through laboratory testing on geogrids embedded in structural fill. Random forest (RF) is a data-driven ensemble learning method that uses decision trees for classification and regression tasks. In the present study, the use of random forest regression technique for estimation of pullout coefficient of geogrid embedded in different structural fills and at variable normal stress based on 198 test results has been investigated using five-fold cross-validation. 80 % of the data has been trained on the model algorithm and the accuracy of the model is then tested on 20 % of the remaining dataset. The performance of the model has been checked using statistical indices, namely R2, mean square error, as well as external validation methods. The validity of the model has also been checked against laboratory tests conducted on geogrid embedded in four different fills. The results of the RF model have been compared to results obtained with three other regression models namely, Multivariate Adaptive Regression Splines, Multilayer Perceptron, and Decision Tree Regressor. The results demonstrate superiority of the RF-based regression model in predicting pullout coefficient values of geogrid. © 2021 Thomas Telford Ltd.

Geosynthetics International

Novel Application of Machine Learning for Estimation of Pullout Coefficient of Geogrid

Many cities in India experience severe deterioration of air quality in winter. Particulate matter is a key atmospheric pollutant that impacts millions of people. In particular, the high mass concentration of particulate matter reduces visibility, which has severely damaged the economy and endangered human lives. But the underlying chemical mechanisms and physical processes responsible for initiating haze and fog formation remain poorly understood. Here we present the measurement results of chemical composition of particulate matter in Delhi and Chennai. We find persistently high chloride in Delhi and episodically high chloride in Chennai. These measurements, combined with thermodynamic modelling, suggest that in the presence of excess ammonia in Delhi, high local emission of hydrochloric acid partitions into aerosol water. The highly water-absorbing and soluble chloride in the aqueous phase substantially enhances aerosol water uptake through co-condensation, which sustains particle growth, leading to haze and fog formation. We therefore suggest that the high local concentration of gas-phase hydrochloric acid, possibly emitted from plastic-contained waste burning and industry, causes some 50% of the reduced visibility. Our work implies that identifying and regulating gaseous hydrochloric acid emissions could be critical to improve visibility and human health in India. © 2021, The Author(s), under exclusive licence to Springer Nature Limited.

School of Liberal Arts (SoLA)

Nature Geoscience

Enhanced aerosol particle growth sustained by high continental chlorine emission in India

In this Perspective, we explore the instability of a meandering channel with variable width and curvature. The analysis employs the depth-averaged formulations for the flow and sediment transport. Unlike the conventional instability analysis that considers mainly the bedload transport, we consider the generic sediment transport including both the bedload and suspended load. The analysis addresses the variations of the near-bank excess azimuthal velocity and the bed topography deviation with the meander wavenumber for different pertinent parameters, such as Shields number, relative roughness number, channel aspect ratio, width-variation amplitude, and shear Reynolds number. The analysis detects a resonance phenomenon for certain critical values of the pertinent parameters and explores the sensitivity of the resonant wavenumber to the pertinent parameters. In a hydraulically smooth flow regime, the sediment suspension is found to play a stabilizing role. On the contrary, in hydraulically transitional and rough flow regimes, the sediment suspension offers a destabilizing effect. The stability diagrams reveal that the stable zone enlarges as the Shields number and relative roughness number increase, while it contracts with an increase in width-variation amplitude. For a given shear Reynolds number in a hydraulically smooth flow regime, the stability diagram predicts various stable zones. By contrast, for a given shear Reynolds number in hydraulically transitional and rough flow regimes, a unique stable zone exists. © 2021 Author(s).

Physics of Fluids

Instability of a meandering channel with variable width and curvature: Role of sediment suspension

When a turbulent shear flow above a plane sand surface entrains sand grains, it generates a variety of sand patterns. Fluvial sand forms two major interfacial patterns: meso-scale dunes and antidunes, and large-scale bars. Measurements have evidenced that under erosive conditions, meso-scale patterns either change to or coexist with large-scale patterns. However, it remains elusive what exactly drives the switching of interfacial patterns and how the switching occurs. Here, we show—combing a flow model with a grain transport model, allowing for both the surface and suspended sand fluxes—that the switching of patterns emerges from the shear-driven complex feedback between grain transport and topographic perturbations. The switching predominantly depends on the magnitudes of the Rouse number and the grain size to undisturbed flow depth ratio. The model offers quantitative predictions of the maximum amplification of sand patterns and unveils a new attraction–repulsion phenomenon. © 2020 International Research and Training Centre on Erosion and Sedimentation / the World Association for Sedimentation and Erosion Research