Civil Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

The present study aims at conducting a comprehensive seismic risk assessment for the North Eastern Region of India at regional and sub-regional levels by integrating probabilistic seismic hazard and social vulnerability assessments. Bedrock-level peak ground acceleration varied from 0.14 to 0.69g for the return period of 475 years. Using PCA, the social vulnerability index (SVI) was generated considering district-level socioeconomic indicators. Built environment quality, illiteracy, access to amenities, dependent population, and employment opportunities contributed to high SVI. Most vulnerable districts were concentrated in the Brahmaputra floodplains, Tripura fold belt, and Imphal valley. At the regional level, significant parts of Assam, Meghalaya, Arunachal Pradesh, and Tripura lie in moderate to very high-risk zones. At the sub-regional level, Nagaland accounts for the highest proportion of areas in high to very high-risk zones. The findings will aid site-specific resilient infrastructure design, disaster risk reduction, and effective resource allocation for the risk-prone areas. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

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(SoE) School of Engineering

Sustainable and Resilient Infrastructure

Seismic risk assessment for the North Eastern Region of India by integrating seismic hazard and social vulnerability

Two-dimensional thin structural elements, such as plates, shells, and membranes, are used to introduce pre-stress while loading. Lateral vibrations and elastic stability are very common problems associated with thin-walled industrial structures, posing a high risk of structural failure in the buckling mode. This paper aims to test the possibility of detecting bucking failure of steel plates utilising vibration response obtained from surface-bonded lead zirconate titanate (PZT) patches and the global vibration and electromechanical impedance (EMI) approach. Experimental proof-of-concept testing is carried out on elastically constrained flat plates in the form of steel columns. The plates are loaded under compression till the onset of the buckling phenomenon. In addition, the test specimens are subjected to both EMI and global vibration techniques, in order to find critical buckling parameters for thin structural elements. While structural instability creeps into the system, the fundamental frequencies of global vibrations are calibrated and compared to see whether there is any shift. It is found that both the PZT-based low-frequency global vibration and the EMI technique are capable to detect the buckling prognosis, though the former technique is more expedient. This study also included the arrangement of pin-pin end connection through an experimental setup to yield the thin plate buckling. The sensor results for the Global vibration technique and Electro-mechanical impedance (EMI) technique are satisfactory for the pin-pin connection. © 2022, Springer Nature Switzerland AG.

Innovative Infrastructure Solutions

Vibration-based pre-emptive detection of plate buckling using piezo-transducers

The recent application of deep learning for structural health monitoring systems for damage detection has potential for improvised structure performance and maintenance for long term durability, and reliable strength. Advancements in electro-mechanical impedance (EMI) techniques have sparked attention among researchers to develop novel monitoring techniques for structural monitoring and evaluation. This study aims to determine the performance of EMI techniques using a piezo sensor to monitor the development of bond strength in reinforced concrete through a pull-out test. The concrete cylindrical samples with embedded steel bars were prepared, cured for 28 days, and a pull-out test was performed to measure the interfacial bond between them. The piezo coupled signatures were obtained for the PZT patch bonded to the steel bar. The damage qualification is performed through the statistical indices, i.e., root-mean-square deviation (RMSD) and correlation coefficient deviation metric (CCDM), were obtained for different displacements recorded for axial pull. Furthermore, this study utilizes a novel Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM)-based hybrid model, an effective regression model to predict the EMI signatures. These results emphasize the efficiency and potential application of the deep learning-based hybrid model in predicting EMI-based structural signatures. The findings of this study have several implications for structural health diagnosis using a deep learning-based model for monitoring and conservation of building heritage. © 2022 by the authors.

Fulltext

Sensors

A Novel CNN-LSTM Hybrid Model for Prediction of Electro-Mechanical Impedance Signal Based Bond Strength Monitoring

A comprehensive year-round field campaign was conducted in the coastal city of Ningbo, China to examine the driving factors of oxidative potential (OP) of PM2.5 and hence its potential health impacts. Using dithiothreitol (DTT) cell-free assay, OP of water-soluble (OPws) and methanol-soluble components (OPmeth) of PM2.5-based samples were measured. Volume-normalised OP (OPvws and OPvmeth) were higher in heating seasons, and mass-normalised OP (OPmws and OPmmeth) peaked in summer. Five sources were identified to be DTT active in OPvws, with road dust (RD) being dominant, while four sources contributed to OPvmeth, with industrial emission (IE) as the largest contributor. Water extracted more toxic components from RD while toxic components in IE and vehicle emission (VE) were more soluble in methanol. We further compared OP values between PM2.5 of similar concentrations and observed that OPvws prevailed in PM2.5 toxicity during clean days (PM2.5 concentration &lt; 38.5 µg m−3), while OPvmeth became dominant when PM2.5 concentration was larger than 69.1 µg m−3, implying the need to extract whole PM2.5 using both solvents to develop the mitigation strategy for reducing the overall PM2.5 toxicity. Efforts should be devoted to controlling the emissions from dominant sources of both OP indicators in specific episode. © 2022 Elsevier B.V.

Journal of Hazardous Materials

Chemical constituents, driving factors, and source apportionment of oxidative potential of ambient fine particulate matter in a Port City in East China

Isogeometric collocation (IGA-C) method is a computational approach to solve boundary value problems. In this method (IGA-C), the differential equations are solved in strong form instead of the weak form approach adopted by Galerkin based formulations. IGA-C method is computationally efficient in comparison to conventional finite element method and Galerkin-Isogeometric approaches. IGA-C method does not involve the process of assembling global stiffness matrix from element stiffness matrix. Another advantage of IGA-C is that it requires a single integration point per element irrespective of the order of Non-Uniform Rational B-Spline functions (NURBS) adopted. Isogeometric collocation has also been demonstrated as a stable, efficient and accurate higher order computational method for explicit problems. For a wider adoption of isogeometric collocation method, beam/plate/shell finite elements within the framework of IGA-C method need to be formulated. Owing to the extensive adoption of laminated composites in structural components, development of beam finite elements for laminated composite beams based on isogeometric collocation method will prove useful during analysis of composite structures. IGA-C method is proposed in this study for the static bending, free vibration and buckling analysis of laminated composite beams. Classical laminated plate theory (CLPT), first order shear deformation theory (FSDT) and higher order shear deformation theory (HSDT) are considered for all the three analyses. The computational approach proposed for laminated beam based on HSDT contains two Degrees of Freedom (DOF) per node. Computational approach for analysing laminated composite beams based on each of these kinematic theories and using IGA-C method is presented. Accuracy of the proposed computational approaches is checked by solving different numerical examples. Values of normalized transverse displacement, normalized stresses, normalized natural frequencies and normalized critical buckling loads are compared with results from the literature and are found to be accurate. © 2022 Elsevier Masson SAS

European Journal of Mechanics, A/Solids

Static, free vibrational and buckling analysis of laminated composite beams using isogeometric collocation method

The aim of this experimental study is to investigate the interaction between turbulent flow and a gravel-bed that mimics the actual roughness structures of a natural bed and its implication on sediment transport. In particular, the response of the Reynolds stresses and the role of intermittency to the bed roughness is the primary focus of the current study. To this end, the flow field, measured with an Acoustic–Doppler Velocimeter (ADV), is thoroughly examined, considering the conditional Reynolds shear stresses and the high-order structure functions of velocity. The study results show that the features and the roughness structure of the water-worked gravel-bed (WWGB) have a strong impact on bursting events. The reason for this is attributed to the flow layer above the crest in the WWGBs being primarily affected by sweep events rather than ejection events, although the latter events are prevalent in this flow layer in an immobile, man-made, gravel-bed. These coherent structures, which are primarily responsible for sediment transport, also are the key cause of the presence of an intermittency excess that breaks the Kolmogorov self-similarity hypothesis, leading to multi-fractal behavior of the velocity structure functions. © 2021 International Research and Training Centre on Erosion and Sedimentation / the World Association for Sedimentation and Erosion Research

International Journal of Sediment Research

Response of Reynolds stresses and scaling behavior of high-order structure functions to a water-worked gravel-bed surface and its implication on sediment transport

The NRCS-CN method, integrated with GIS and remote sensing, can be used for estimating curve numbers (CN) and surface runoff in geohydrological systems. The study area is divided into 63 sub-basins, and the land use land cover (LULC)-hydrologic soil group (HSG) complex is identified for each sub-basin. The CN values for three antecedent soil moisture (AMC) conditions are calculated and corrected for surface slope variations. The surface runoff depth is determined using the rainfall data for 16 years (2005–2020). The average runoff depth and mean annual precipitation ranges from 444.50 to 1960.55 mm and 936.99 to 3520.55 mm, respectively. For all sub-basins, strong correlations between runoff depth and rainfall (R2 ≥ 0.8) as well as between simulated runoff and measured runoff (R2 ≥ 0.8) are observed. The Nash–Sutcliffe model efficiency coefficient (NSE) values suggest that the model's efficiency is good to satisfactory. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of Journal of Maps.

Journal of Maps

Estimation of rainfall-induced surface runoff for the Assam region, India, using the GIS-based NRCS-CN method

Diverting or deflecting sediments is an essential part of river training. Under the effect of an induced helical motion, the submerged vanes are best known for deflecting sediments. This study presents current state-of-the-art information on employing submerged vanes for sediment deflection, as well as concluding notes outlining the current knowledge’s limitations and suggestions for future research on sediment deflection using submerged vanes. The analytical background for basic physics of submerged vanes’ operation is first described. The paper then moves on to a thorough examination of vane design parameters based on analytical relationships. A brief overview of the applications of submerged vanes is also included in the paper. A review of recent studies aims at designing a layout of submerged vanes to assist in river training tasks, such as river bends protection, sediment exclusion at water intakes, improving safety at bridges on waterways, improving inland navigation is provided to this end. The study also presented a future program of research on submerged vanes for improving inland navigation in braided rivers. The major lag in literature is a lack of information on macro turbulence and the associated sediment motion induced by the wake of the submerged vane. © 2022 Indian Society for Hydraulics.

ISH Journal of Hydraulic Engineering

A review of sediment deflection in rivers using submerged vanes

Floods are frequently occurring events in the Assam region due to the presence of the Brahmaputra River and the heavy monsoon period. An efficient and reliable methodology is utilized to prepare a GIS-based flood risk map for the Assam region, India. At the regional and administrative level, the flood hazard index (FHI), flood vulnerability index (FVI), and flood risk index (FRI) are developed using multi-criteria decision analysis (MCDA)–analytical hierarchy process (AHP). The selected indicators define the topographical, geological, meteorological, drainage characteristics, land use land cover, and demographical features of Assam. The results show that more than 70%, 57.37%, and 50% of the total area lie in moderate to very high FHI, FVI, and FRI classes, respectively. The proposed methodology can be applied to identify high flood risk zones and to carry out effective flood risk management and mitigation strategies in vulnerable areas. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Geocarto International

A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level

Assam region is mainly formed by the deposit and erosion process of the Brahmaputra River. The frequency of seismic events results in landform deformation, which highly influences the drainage basin pattern and causes drainage anomalies, having a subsequent effect on the flood distribution pattern. In the present study, morphometric parameters and geomorphic indices for the Assam region are derived from SRTM DEM data of 30 m resolution using GIS to characterize the tectonic activity, which in turn influences the drainage pattern. The indices are classified into three tectonic activity classes, and the average of the classes is combined to generate the indices of relative active tectonics (IRAT). The four classes of IRAT are defined for the study area as (i) very high; Class 1 (1.57–1.80), (ii) high; Class 2 (1.81–2.06), (iii) moderate; Class 3 (2.07–2.26), and (iv) low; Class 4 (2.27–2.30). Class 1 corresponds to basins 1 and 6. Basins 2, 4, and 5 fall under Class 2. Class 3 consists of basins 7, 8, and 9, and Class 4 comprises basins 3 and 10. Results show that most of the study area lies in very high to moderate active tectonic zones and the identified zones are consistent with significant faults and thrusts present in the basins. The combined approach of GIS-based morphometric and geomorphic study allows for identifying deformed landforms resulting from active tectonics. The results can also be employed for the development of watershed management and sustainable land use planning. © 2022 The Author(s)