Department of Civil Engineering

Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

This study is contemplation into prevailing BIM (Building Information Modelling) development practices, especially at the pre-maturity level. Firstly, the authors investigate the incentives that are set based on quantitative techniques and illustrate that rational models could not assist practitioners to make decisions on BIM adoption. Secondly, the survey-based methodology, which is predominantly used to assess industry readiness, was also reviewed to evaluate the amount of attention given towards externalities, such as procurement, policy, technical and organizational environments-which have a greater influence on BIM adoption. Further, the authors argue that the externalities are given a minimum consideration under the prevailing assessment criteria. The 'contextual-reflection' is used to describe externalities and a qualitative study was done in the South African context to evaluate the contextual reflection comprehensively. Integrating the findings with the Technology Adoption Model and Bew Richard BIM Maturity Model, the authors suggest a conceptual framework at the end of this study which could be repeated successfully in other contexts to evaluate industry readiness in a holistic manner.

World University root node

Creative Construction Conference

Measuring BIM readiness with comprehension at the pre-maturity

Microbial fuel cell (MFC) technology is utilized to treat hexavalent chromium (Cr(VI)) from wastewater and to generate electricity simultaneously. The Cr(VI) is bioelectrochemically reduced to non-toxic Cr(III) form in the presence of an organic electron donor in a dual-chambered MFC. The Cr(VI) as catholyte and artificial wastewater inoculated with anaerobic sludge as anolyte, Cr(VI) at 100 mg/L was completely removed within 48 h (initial pH value 2.0). The total amount of Cr recovered was 99.87% by the precipitation of Cr(III) on the surface of the cathode. In addition to that 78.4% of total organic carbon reduction was achieved at the anode chamber within 13 days of operation. Furthermore, the maximum power density of 767.01 mW/m2 (2.08 mA/m2) was achieved by MFCs at ambient conditions. The present work has successfully demonstrated the feasibility of using MFCs for simultaneous energy production from wastewater and reduction of toxic Cr(VI) to non-toxic Cr(III). © IWA Publishing 2015.

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Water Science and Technology

Hexavalent chromium reduction and energy recovery by using dual-chambered microbial fuel cell

Droughts have been a major factor leading to the Tri-State Water Wars in the southeastern United States. One of the primary issues related to the conflict is the reduction in baseflow levels in the Flint River during droughts. This affects the availability of freshwater resources to support the endangered mussel species in the Flint and Apalachicola Rivers and threatens the shellfish industry in the Apalachicola Bay. Study of large-scale climate phenomena as well as the interactions of interannual with decadal and multidecadal oceanic-atmospheric phenomena can provide valuable information regarding regional climatic conditions such as droughts and their impact on water resources. This study was conducted to quantify the impacts of climate variability cycles on baseflow levels in the Flint River. The individual and coupled impacts of the El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and North Atlantic Oscillation (NAO) on baseflow were quantified. The non-parametric Joint Rank Fit (JRFit) procedure was used to provide a robust test of the significance of interactions between the phases of ENSO-PDO, ENSO-AMO and ENSO-NAO baseflows. Simple-main effect comparisons were also performed using the JRFit model to estimate significant difference between the positive and negative phase baseflows of PDO, AMO and NAO associated with El Niño or La Niña phases. The results indicate that the phases of ENSO, AMO and NAO significantly affect baseflows in the Flint River. Interaction tests showed that the PDO and AMO phases modulate ENSO phase baseflows. La Niña associated with positive phases of PDO and AMO resulted in greater decrease in baseflow levels of approximately 28% and 33%, respectively. However, La Niña associated with negative phase of AMO showed above normal baseflows. The results illustrate the importance of coupled analyses of climate variability by providing a better understanding of the severity of droughts and their impact on baseflows. The results obtained from this study can be used by water managers in the region as a guide for the issuance of drought severity-based water restrictions. © 2015 Elsevier B.V.

Journal of Hydrology

Baseflow response to climate variability induced droughts in the Apalachicola-Chattahoochee-Flint River Basin, U.S.A.

ASABE 1st Climate Change Symposium: Adaptation and Mitigation Conference {\ldots}

Effects of Irrigation Pumpage during Droughts on Groundwater Levels and Groundwater Budget Components in the Lower Apalachicola-Chattahoochee-Flint River Basin

The quantification of uncertainty in the simulations from complex physically based distributed hydrologic models is important for developing reliable applications. The generalized likelihood uncertainty estimation method (GLUE) is one of the most commonly used methods in the field of hydrology. The GLUE helps reduce the parametric uncertainty by deriving the probability distribution function of parameters, and help analyze the uncertainty in model output. In the GLUE, the uncertainty of model output is analyzed through Monte Carlo simulations, which require large number of model runs. This induces high computational demand for the GLUE to characterize multi-dimensional parameter space, especially in the case of complex hydrologic models with large number of parameters. While there are a lot of variants of GLUE that derive the probability distribution of parameters, none of them have addressed the computational requirement in the analysis. A method to reduce such computational requirement for GLUE is proposed in this study. It is envisaged that conditional sampling, while generating ensembles for the GLUE, can help reduce the number of model simulations. The mutual relationship between the parameters was used for conditional sampling in this study. The method is illustrated using a case study of Soil and Water Assessment Tool (SWAT) model on a watershed in the USA. The number of simulations required for the uncertainty analysis was reduced by 90 % in the proposed method compared to existing methods. The proposed method also resulted in an uncertainty reduction in terms of reduced average band width and high containing ratio. © 2014, Springer-Verlag Berlin Heidelberg.

Stochastic Environmental Research and Risk Assessment

A method to reduce the computational requirement while assessing uncertainty of complex hydrological models

Structural Assessment of "D" Regions Affected by Premature Concrete Deterioration: Technical Report

This paper presents a methodology to quantify resilience of transportation networks that are subject to recurring capacity disruptions. System-optimal total travel time at full-capacities is usually adopted as a performance-benchmark on networks. Capacity degradation results in different capacity combinations, and thus, there can be different travel times. We thus compare the best network performance with an upper bound of network performance—indicating how much disruptions the network can take in before it displaces from a demand-meeting state to a demand-not-meeting state—and construct an index of network resilience. For this, we establish a critical state which is an upper bound of network cost under recurring capacity degradation. We define discrete capacity levels and search for probability values over those levels that would result in a critical state. We formulate the critical state link disruption problem as a minimax optimisation problem, where expected system travel time is maximised with respect to probability of recurrence and minimised with respect to link flow. We prove that the network cost is unique at the critical state, although the critical degradation need not be. We solve the minimax problem using a coevolutionary algorithm. We exemplify the formulation on test networks and quantify the improvement in network resilience by retrofitting the Sioux Falls network. © 2015 Hong Kong Society for Transportation Studies Limited.

Transportmetrica A: Transport Science

Quantifying resilience using a unique critical cost on road networks subject to recurring capacity disruptions

5th Young Indian Geotechnical Engineers Conference

Engineering behavior of oil shale at elevated temperature and confining pressure

Young Geotechnical Engineers' Symposium on Finite Element Method

Deformation behaviour of composite barriers of clay based landfill covers

Application of innovative smart control technology is becoming increasingly popular among researchers and practitioners particularly for a structure under wind or seismic excitation. However, the active control technology for a structure subjected to an underground blast loading has not been done so far. A typical blast-induced loading generates high frequency waves (having a very short duration with large amplitude acceleration) that significantly excite the high frequency modes of a structure during the forced regime. However, the transient part of the structural response is governed by the low frequency modes of the structure. As a result, the structure first suffers large floor acceleration responses followed by a large displacement response. In this study two algorithms, namely, pole placement and LQG control are used in order to control both the displacement and acceleration of a three-story building. For active conrod mechanism, a real time single input force is applied through an actuator. The performance of the system under these control methodologies is then compared to judge the suitability and effectiveness of a smart control scheme over widely used passive controlled system. © Springer India 2015. All rights reserved.