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

Abstract The main objective of this study was to develop, derive, and estimate the phase angle (Pdbl) parameter from resilient modulus (Mr) test, designated PdblMr, at various temperatures and frequencies for eleven types of asphalt mixtures: two conventional dense-graded (DGAC), four polymer-modified gap-graded (P-Gap), four asphalt-rubber gap-graded (AR-Gap), and one asphalt-rubber open-graded (AR-Open) mix. PdblMr were estimated for the eleven mixes with three replicates per mix totalling 33 samples at 15, 25 and 35 C and at 0.5, 1, and 1.5 Hz. AR-Open mixes had the highest PdblMr followed by AR-Gap and P-Gap, and then followed by DGAC mixes. Principally, with an increase in the asphalt content from conventional to modified mixes, there was an increase in PdblMr, suggestive of the fact that the mixes that had higher asphalt contents have extra-viscous response or are highly viscoelastic. Furthermore, PdblMr predictive model was developed based on asphalt material properties totalling 99 data points provided by R2adj (adjusted coefficient of estimation) = 0.8390, and Se/Sy (ratio of standard error to standard deviation indicative of relative accuracy of the predictive model) = 0.3820; depicting very good correlation between the estimated and predicted ∅Mr, and with low bias and high precision. Additionally, PdblMr master curves were constructed for the mixes with 35 C as reference. Overall, it is envisioned that PdblMr parameter obtained in this study will be helpful to comprehensively understand the viscoelastic properties of different asphalt mixtures, and incorporate PdblMr as a viscoelastic characteristic assessor in futuristic flexible pavement designs. © 2015 Elsevier Ltd. All rights reserved.

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Construction and Building Materials

Estimation of phase angles of asphalt mixtures using resilient modulus test

Organizers

Climate change impacts on coastal urban road networks: A methodological approach

Advances in Structural Engineering

Dynamic Response of Block Foundation Resting on Layered System Under Coupled Vibration

International Conference on "Engineering Geology in New Millennium" 2015, At …

Geological and Engineering Behavior of Oil Shales

El Ni{\~{n}}o Southern Oscillation (ENSO) is one of the major climate variability cycles around the world and is responsible for droughts in the Southeast United States. These ENSO- induced droughts have been responsible for agricultural losses, water disputes and promotion of water restrictions in the Southeast. In the Apalachicola- Chattahoochee-Flint (ACF) River Basin, in addition to drought, rapid population growth, urban sprawl and increased agricultural production are threatening the availability of freshwater resources and causing endangered species concerns. As a result, Alabama, Georgia and Florida have been fighting over the allocation of ACF River Basin water for the past two decades. The water conflict heats up every time there is drought in the basin. This research was conducted to study the effects of ENSO- induced droughts and irrigation pumpage on groundwater levels and groundwater budget components of the Upper Floridan Aquifer (UFA) in the lower ACF River Basin. Results indicate that ENSO exhibits teleconnection with groundwater levels in the UFA. The teleconnection was more prominent during the winter season. The study also found that prolonged droughts severely affect groundwater levels and the groundwater recovery periods can be as much as 2 years. The groundwater model, MODular Finite-Element Model (MODFE), was used to study the effect of irrigation water withdrawal during droughts years of 2010 – 2012. The results showed that groundwater levels and stream-aquifer flux are affected by irrigation water withdrawal. Most of the irrigation water pumped is contributed by loss in aquifer storage and losses in stream-aquifer flux. The results also showed that irrigation during the year 2012resulted in groundwater levels to fall by as much as 6 ft and in areas with endangered species concerns. Finally, MODFE was also used to study the effect of possible future increased irrigation levels on groundwater levels and stream-aquifer flux in the study area during the drought water year of 2012. The effect of application of irrigation restrictions in vulnerable regions was also studied. Results showed that elevated irrigation levels severely affect groundwater levels in the vulnerable regions. Doubling of irrigation resulted in as much as 11 ft decline in groundwater levels in the Spring Creek subwatershed. Additionally, the study also found that irrigation water-withdrawal exhibits a linear relationship with stream-aquifer flux in the study area.

Anthropogenic and Climate Impacts on Groundwater Resources in the Lower Apalachicola-Chattahoochee-Flint River Basin

Construction projects are complex undertakings. They are characterised by multiple and diverse natured components, processes and people; hence a high dependence on information and often leading to inefficiencies in the project delivery process. The level of management of these complexities therefore greatly impinges on the performance of projects. In the past decade, implementing Building Information Modelling has been advocated as a veritable way of addressing these challenges. However, its implementation is fraught with many challenges, prominent among which is the lack of clarity as to how it impacts the existing project delivery workflows. To an effort to overcome this, the paper presents a theoretical framework for understanding and evaluating the demands for change in existing work practices and workflows. Second, it proposes a framework for decompose and populate an MDM model within which BIM change propagation may be evaluated.

Modeling and Managing Complex Systems - Proceedings of the 17th International DSM Conference

Identification of process, team and tool dependencies in building information modelling (BIM) implementation using multi-domain mapping (MDM) - A theoretical framework

(Figure Presented). This study demonstrates the use of Liquid Crystal coated Polaroid Glass Electrode (LCPGE) material collected from disposed liquid-crystal display (LCD) computer monitor as electrodes in microbial fuel cell (MFC) for the simultaneous reduction/recovery of Cr+6 from chromium wastewater. Fourier transform infrared spectrum (FT-IR) confirms the presence of NH2, C≡N, C=O and O-C and/or C-O-C functional groups in LCPGE. An excellent electrochemical performance with distinct redox peaks were observed in cyclic voltammetry test (100 mV/s). The maximum current density of 110 mA/m2 (10 mW/m2) was achieved by operating MFC in batch mode. At the cathode LCPGE (10.5 cm2) interface, toxic Cr+6 ions readily accepted electrons and formed nontoxic Cr2O3 as confirmed by FT-IR and X-ray photoelectron spectroscopy analysis. Moreover, electrochemical impedance analysis shows that bacteria were readily attached to the surface of LCPGE (10.5 cm2) within 24 h in a Bioelectrochemical System (BES). © 2015 Elsevier Ltd.

Bioresource Technology

Liquid crystal polaroid glass electrode from e-waste for synchronized removal/recovery of Cr+6 from wastewater by microbial fuel cell

There are many aspects of urban transportation that represent sources of uncertainty in the design of roadways, such as the level of capacity needed to ensure efficient traffic flow. As a result of uncertainty in roadway capacity, an urban road network can be deemed to operate at different capacity levels. Some of these levels will have unused capacity, whereas some others will not be enough to cater traffic from all origins to all destinations. Past models assume knowledge over the pattern of these uncertainties. However, it is difficult to gather such knowledge from field observations, and it is absent for majority of the world's urban areas. We present an alternative methodology in which the capacities are considered as variables that can take any value from zero to a practically realizable maximum. Using a minimax optimization formulation, we determine bounds on urban roadway capacity levels, below which the traffic demand will go unmet. We call this the critical state, and define it as a state of link capacities which effects in the maximum irreducible operational cost on the network with the demand getting fulfilled. We prove that at a critical state, the total travel time (or cost) of the system will be a unique value; i.e. for a given urban road network and a given traffic demand, there is an associated unique critical travel time. We illustrate that this unique travel time-which is an aggregate value of the travel times from all roads on the network-can be used as a benchmark to create various metrics for the urban road network. As an illustrative example on the applicability of critical state, we compare the unique travel time with the best possible travel time on the network, and develop a metric for network resilience. Network resilience is calculated as a normalized difference of the critical and best operation costs. Two-space genetic algorithm is used to solve the problem formulation. The formulation and the solution methodology are illustrated on test networks and results are presented. © 2015 Elsevier Ltd.

Computers, Environment and Urban Systems

Capacity uncertainty on urban road networks: A critical state and its applicability in resilience quantification

Roadways, the links of transportation networks, are susceptible to a variety of degradations. Some degradation patterns are severe; they make the network incapable of meeting origin- destination (OD) demands. Most others are non-severe; they increase the network operational cost while OD demands remain met. In other words, the network structure is resilient to such degradations. It is important for planners to quantify this resilience of a network. The authors have, in a previous study, framed a minimax optimization problem to find the network operational cost— the minimax value—which is irreducible even by re-assignment. The relative difference of the minimax value and the best possible value is interpreted as the network’s resilience. This resilience measure is demand-specific. To generalize the resilience measure, its sensitivity to change in demand should be studied. As it is difficult to analytically establish the sensitivity of resilience to demand, the authors perform computational experiments on different network topologies to bring out a relationship between network resilience and demand. The authors observe that the resilience- demand curve, irrespective of the difference in network size or network topology, follows a trend very much comparable to negative exponential curve. With this result, one needs to compute the demand-specific resilience values at only a given number of demand levels to attain generality. Finally, the authors introduce a generalized index of resilience (GIR) incorporating the demand-spread. The authors compare the GIR to traditional network indicators and find that it is better in modeling topological and dynamic properties of a network.