Department of Civil & Infrastructure Engineering

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Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

Multi-class traffic flow modelling has various approaches several of which have focused on analytical proofs. A key limitation in this field of research is the limited field data applications. This study proposes a speed-gradient-based multi-class second-order model and shows its application to three different road sections, a mid-block section, a section with a bottleneck, and a section with a signal at the end, in Chennai, India. The model captures the congestion formation and dissipation phenomena well and could predict outflow and speed fluctuations generally observed in the field scenarios accurately. The prediction of traffic flow dynamics by the proposed model is also observed to be better when compared with two existing higher-order multi-class models. © The Institution of Engineering and Technology 2020

World University root node

IET Intelligent Transport Systems

Field data application of a non-lane-based multi-class traffic flow model

Indian Institute of Technology Gandhinagar

Drought risk in South Asia under observed and projected future climate

Observed and projected changes in potential evapotranspiration (PET) and drought are not well con-strained in South Asia. Using five PET estimates [Thornthwaite (PET-TH), Hargreaves–Samani (PET-HS), Penman–Monteith (PET-PM), modified Penman–Monteith (PET-MPM) and energy (PET-EN)] for the observed (1979–2018, from ERA5) and future warming climate, we show that significant warming has occurred in South Asia during 1979–2018. PET changes show considerable uncertainty depending on the method used. For instance, PET-TH has increased significantly while all the other four methods show a decline in PET in the majority of South Asia during the observed period of 1979–2018. The increase in PET-TH is substantially higher than PET-HS, PET-PM and PET-MPM due to a higher (3–4 times) sensitivity of PET-TH to warming during the observed period. Under the 1.58, 2.08 and 2.58C warming worlds, global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5 GCMs) project in-creases in PET and drought frequency over the majority of the regions. Drought estimates based on PET-EN and PET-MPM are consistent with soil moisture–based drought estimates and project a substantial increase in the frequency of severe droughts under warming climate in South Asia. In addition, the projected frequency of severe drought based on PET-TH, which is an outlier, is about 5 times higher than PET-EN and PET-MPM. Methods to estimate PET contribute the most in the overall uncertainty of PET and drought projections in South Asia, primarily due to PET-TH. Drought estimates based on PET-TH are not reliable for the observed and projected future climate. Therefore, future drought projections should be either based on PET-EN/PET-MPM or soil moisture.

Journal of Hydrometeorology

Increased drought risk in south asia under warming climate: Implications of uncertainty in potential evapotranspiration estimates

Intensive irrigation in India has been demonstrated to decrease surface temperature, but the influence of irrigation on humidity and extreme moist heat stress is not well understood. Here we analysed a combination of in situ and satellite-based datasets and conducted meteorological model simulations to show that irrigation modulates extreme moist heat. We found that intensive irrigation in the region cools the land surface by 1 °C and the air by 0.5 °C. However, the decreased sensible heat flux due to irrigation reduces the planetary boundary layer height, which increases low-level moist enthalpy. Thus, irrigation increases the specific and relative humidity, which raises the moist heat stress metrics. Intense irrigation over the region results in increased moist heat stress in India, Pakistan and parts of Afghanistan—affecting about 37–46 million people in South Asia—despite a cooler land surface. We suggest that heat stress projections in India and other regions dominated by semi-arid and monsoon climates that do not include the role of irrigation overestimate the benefits of irrigation on dry heat stress and underestimate the risks.

Nature Geoscience

Moist heat stress extremes in India enhanced by irrigation

Drought is among the costliest natural disasters that affect the economy, food and water security and socioeconomic well-being of about 1.4 billion people in India. Despite the profound implications of droughts, the propagation of meteorological to hydrological droughts in India is not examined. Here, we use observations and simulations from a well-calibrated and evaluated Variable Infiltration Capacity (VIC) model to estimate drought propagation in India. Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSMI) and Standardized Streamflow Index (SSI) were estimated for 223 catchments in India to represent meteorological, agricultural and hydrological droughts, respectively. We estimated drought propagation time for these catchments located in 18 major Indian subcontinental river basins. Internal propagation of hydrological drought was estimated using optimal hydrological Instantaneous Development Speed (IDS) and Instantaneous Recovery Speed (IRS) from onset to the termination. Indus, Sabarmati and Godavari river basins have higher propagation time of meteorological to hydrological droughts. The high (low) development rate of hydrological drought is followed by the high (low) recovery rate for most of the locations. We find significant influence of Seasonality Index (SI) and Base Flow Index (BFI) on propagation time of meteorological to hydrological droughts in the Indian subcontinental river basins. Overall, understanding of drought propagation, development/recovery speed and their deriving factors can assist in the management and planning of water resources in India.

Journal of Geophysical Research: Atmospheres

Propagation of Meteorological to Hydrological Droughts in India

Recent studies based on the ensemble mean of Coupled Model Intercomparison Project 6 (CMIP6) General Circulation Models (GCMs, CMIP6-GCMs hereafter) reported a decline in drought frequency over South Asia in the projected future climate. Here using the simulations from 16 CMIP6-GCMs, we examine the potential causes of declining droughts in South Asia. We show that the projections based on the multimodel ensemble mean CMIP6-GCMs are not reliable over South Asia. The multimodel ensemble mean is influenced mainly by the low-skill GCMs, which show high bias in simulating the monsoon (June–September) season precipitation during the observed period (1951–2014). The low-skill GCMs show a higher (20–30%) increase in the convective precipitation with a rise in the global mean temperature under the warming (1.5°C, 2.0°C and 2.5°C worlds) climate. The GCMs with less bias (BEST-GCMs) in the monsoon season precipitation and better seasonal cycle representation show lower sensitivity of convective precipitation to rise in global mean temperature. BEST-GCMs exhibit significantly different projections in comparison to the multimodel ensemble mean from all 16 GCMs (ALL-GCMs). In contrast to ALL-GCMs, BEST-GCMs project an increase in the frequency of droughts in South Asia under the future climate. Therefore, the projected risk of droughts over South Asia under the 1.5°C, 2.0°C and 2.5°C warming levels is higher than previously reported based on the ensemble mean of CMIP6-GCMs. A projected increase in the drought frequency in South Asia will have considerable implications for agricultural production and water availability.

On the Projected Decline in Droughts Over South Asia in CMIP6 Multimodel Ensemble

This paper presents mesoscale thermo-mechanical analyses of plain (unreinforced) concrete based on the discrete element method (DEM). The proposed discontinuum modelling strategy represents the aggregates and matrix as a system of deformable polyhedral blocks, interacting along their boundaries. The nodal velocities of each block are calculated via the explicit integration scheme of DEM, and contact stresses are computed based on the relative contact displacements of the adjacent blocks. To better predict the thermo-mechanical behaviour of concrete, fracture energy-based contact constitutive models are implemented by considering temperature dependency at the zone and contact properties. First, the discrete meso models are tested under uniaxial compression loading at room temperature. Then, transient thermo-mechanical tests are performed considering different load levels. The results of the computational models are compared with the macroscopic response quantities of concrete obtained from the available experimental studies in the literature. The results indicate that the developed DEM framework predicts the complex mesoscale thermo-mechanical response history and the typical damage progression observed in concrete. Furthermore, the fracture patterns, crack propagation with temperature, and the differential thermal expansion phenomena are studied in detail. © 2020 Elsevier Ltd

Engineering Fracture Mechanics

A meso-scale discrete element method framework to simulate thermo-mechanical failure of concrete subjected to elevated temperatures

This paper presents a 2-D finite element (FE) based micro modelling framework for thermo-mechanical response history analysis of solid brick masonry structures subjected to fire. The 2-D FE framework considers geometric and material nonlinearities, and transient states of strain in conjunction with the temperature-dependent material properties. Material nonlinearity within the 2-D FE model is considered by the temperature-dependent total strain rotating crack model. The FE framework is validated against the thermo-mechanical response of a half-scale masonry wall subjected to one-sided fire exposure, and it is observed that the predictions of the FE framework are reasonably accurate. Utilizing the validated FE framework, thermo-mechanical response history characterization is performed on a full-scale masonry wall subjected to one-sided fire exposure. Critical physical phenomena which include thermal bowing, heat diffusion, unit-mortar thermo-mechanical interaction, cracking and stress profiles within the masonry structures are studied intricately. Furthermore, thermo-mechanics within representative volumes enclosing unit as well as mortar and their correlation with the global thermo-mechanical response is studied. Such 2-D micro-scale thermo-mechanical computations on masonry walls followed by a detailed discussion on their thermo-mechanics are one of the novel features of the present study. It is observed that thermal bowing resulted from a complex interaction between thermal dilation and cracking and crushing in the mortar and unit within the masonry structure. © 2020 Elsevier Ltd