(SoE) School of 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

Biomimetic and soft robotics research has been inspired by many biological organisms focusing on soft structural composites reinforced by stiff constituents. In the case of synthetic soft structural materials, hydrogels are very similar to the biological soft tissues/organs, owing to their “wet and soft” properties, their elastic performance, biodegradability, and biocompatibility. However, the current scope of hydrogel applications is usually hampered by their feeble mechanical properties. Although significant progress has been made in developing intense, challenging, and stretchable hydrogels, it is still challenging to realize the optimal magnitude of physical and mechanical properties altogether in synthetic hydrogels. This review briefly focuses on the hydrogel fibrous shape-morphing composite structure and its functionalities. The nature-inspired, fiber-reinforced soft hydrogel shape-morphing functional composite structure delivers them a cartilage-like anisotropic behavior. They could have broad potential applications in various areas, including tissue engineering, soft robotics, stretchable and bio-integrated electronics, microfluidics, and biomedical devices. Copyright © 2022 Goyal and Mitra.

World University root node

Mechanical Engineering

Fulltext

Frontiers in Materials

A Brief Overview of Bioinspired Robust Hydrogel Based Shape Morphing Functional Structure for Biomedical Soft Robotics

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)

Civil Engineering

Journal of Asian Earth Sciences: X

A GIS-based assessment of active tectonics from morphometric parameters and geomorphic indices of Assam Region, India

Reliability aspects such as bias temperature instability (BTI) and hot carrier injection (HCI) affecting devices in advanced CMOS-based technology have been the subject of active research in recent decades. Due to these reliability issues, various digital and analog circuits were investigated for degradation. However, circuit blocks like the neuron circuits of neuromorphic systems are not fully explored. This work is inclined toward examining the collective degradation impact of BTI and HCI due to aging in an adaptive exponential “integrate and fire” (I&F) model-based, neuromorphic neuron circuit. Detailed degradation analysis of the stimulated neuron circuit aided in identifying possible mismatches/faults associated with neuron spikes. These factors could reduce the efficiency of the neuronal circuit by potentially affecting the transmission of information in a neuromorphic system. Various performance parameters were then derived to quantify the extent of circuit deterioration. The proposed reliability-aware design aims to improve the circuit degradation through its effectiveness in alleviating the overall reliability impact. It demonstrates enhanced circuit operation in spike generation even after aging. The circuit performance is validated through simulations at “Time0” (pre-degradation) and “Aged” (post-degradation) neuron netlists, which is then compared with the proposed reliability-aware circuit. © 2022 John Wiley & Sons Ltd.

Electrical Engineering

International Journal of Circuit Theory and Applications

Enabling efficient rate and temporal coding using reliability-aware design of a neuromorphic circuit

This paper presents a comprehensive study on the effect of spatial variability of the elastic modulus on vertical stress distribution in an elastic half-space due to strip loading. The modulus of elasticity is considered as a random variable which follows a log-normal probability distribution. A random field theory based on a Cholesky decomposition technique is used to generate a two-dimensional random field in the elastic half-space. Monte Carlo simulation is performed to generate various random fields with spatially varying elastic modulus. A two-dimensional random finite-element model is developed for a strip loading on an elastic half-space by coupling the random fields generated by Monte Carlo simulation with finite-element analysis. A detailed investigation of the effect of statistical variables defining spatial random variation of the elastic modulus on the vertical stress distribution and the settlement analysis in random elastic half-space is performed. The present study indicates that the spatial random variation of elastic modulus of the soil has a significant effect on the vertical stress distribution and the settlement analysis in the elastic half-space. © 2022 American Society of Civil Engineers.

International Journal of Geomechanics

Uncertainties in Vertical Stress Distribution in Spatially Varying Random Elastic Half-Space

Understanding software size distribution is critical to software cost estimation using COCOMO model and design of reliable production function model. This paper proposes and validates a theoretical framework based on the maximization of Shannon entropy to learn component size distribution of software systems when partial information about the moments is given. Specification of appropriate moment constraints either in the form of shifted geometric mean or arithmetic mean or both geometric and arithmetic means are considered. The models are validated using 30 real datasets. The analysis reveals that software systems where component sizes depict power-law behavior are governed by shifted geometric mean whereas those systems in which component size distribution shows exponential behavior are described by arithmetic mean. Another type of software system is also considered where the component size distribution is found to depict gamma distribution. Such systems are characterized by specification of both arithmetic and geometric means. The study underlines that the use of modern object-oriented programming languages adheres to power-law distribution indicating the existence of team synergies leading to substantial containment of software costs when compared to the use of traditional procedural programming languages. © 1976-2012 IEEE.

Computer Science and Engineering

IEEE Transactions on Software Engineering

Learning Component Size Distributions for Software Cost Estimation: Models Based on Arithmetic and Shifted Geometric Means Rules

The suspension strut mount plays a crucial role in any vehicular suspension system, where it acts as a connector (bolted) to the vehicular body and suspension strut. The mount’s purpose is to cushion the Vehicular impacts and reduce the jarring effect, noise, and vibration caused due to vehicle movement over the undulated roads. The self-loosening of bolts results because of the up and down impact of the spring cause the jounce bouncer to push and pull action at the mount interface, cause vibrations transmitted to the vehicle camber. Self-loosening leads to damage of mount followed by clunking noises, noisy steering, tire misalignment, and can cause discomfort to the passenger. Therefore, condition monitoring and assessment of an upper strut mount is necessary for vehicles. This paper studies the feasibility of the piezo Impedance-based Structural health monitoring (SHM) technique to monitor the self-loosening bolts in the upper strut mount of the suspension system (MacPherson strut suspension) of passenger car. The piezo coupled signatures were obtained experimentally by loosening all the three bolts (connected to strut bearing) through control torques through a digital torque wrench. All the experimental signatures were acquired with a single PZT patch bonded to the surface of the upper strut mount for loosening bolts with pre-tight loss. Progressive damage scenarios are simulated along with preload loss of either single bolt or all three bolts, respectively. Three different statistical damage indices were evaluated for damage quantification raised due to bolt loosening. A 3D numerical modeling of strut mount is done using ANSYS WORKBENCH, and piezo impedance signatures were acquired (hence converted to admittance) for validating the experimental signatures. In an overall, this study provides an insight into the loss of structural integrity due to the self-loosening of suspension bolts, which can be threatful to vehicular integrity. © The Author(s) 2021.

Journal of Intelligent Material Systems and Structures

Piezo impedance-based monitoring of loosening of bolts: Experimental and numerical study

An opaque photovoltaic combined with thermoelectric cooler (PV-TEC) collector is presented in this chapter, in which a TEC module is incorporated at the base of a PV module to improve the overall electrical efficiency of the system. A mathematical model has been described with photovoltaic combined thermoelectric cooler with a duct of air and this thermal modeling is used to calculate the thermal and electrical energy gain. On an annual basis, weather data is received from IMD Pune for the month of May. Several types of temperatures such as solar cells, thermoelectric cooler top side, thermoelectric cooler bottom side, duct outlet temperatures have been calculated through the thermal modeling developed for the system. These results show overall electrical efficiency with TEC increasing by 10.34-12.01%. The addition of a thermoelectric module with a photovoltaic module increases the electrical power from 6.93176 W-15.6753 W to 7.64854 W-17.5571 W. The thermal energy gain by the photovoltaic-thermoelectric module along the duct is in the range of 7.89134 W-20.7169 W. © 2023 Nova Science Publishers, Inc.

Energy Conversion: Methods, Technology and Future Directions

Performance analysis of solar energy conversion technology

Rail track derailment has been proven to be the cause of most of the rail accidents in recent years. High-temperature strains in railways caused by rail traction and thermal variation are the main causes of derailment, which lead to buckling. The likelihood of passenger deaths and maintenance costs will be reduced if thermal strains and failure in rails are detected early. This research attempts to provide a preventative strategy for detecting thermal strains and deformation caused by temperature fluctuations at railways. Using the electromechanical impedance (EMI) technique, piezoelectric sensors were used to acquire piezo coupled structural signatures for lab-sized rail samples, i.e. plain rail and rail joints, for gradual temperature escalation and repeat heat cycle. The experimental conductance signatures were obtained for the incremental rise in temperature (30-80 °C) in ambient conditions, and repetitive thermal cycles. To better diagnose structural problems induced only by the effect of heat on the host structure, thermal compensation is proposed. The piezo-coupled signatures for thermal changes in rail and rail junctions (weld and bolt) were found to be particularly effective in detecting incipient structural alterations for both steady and cyclic temperature variations. Statistical damage index was used to quantify the damage for all types of rail-joint bar caused due to temperature variation. Overall, this study has paved an experimental technique that can be used to detect early damage in rail and rail joints due to thermal loading. © 2022 IOP Publishing Ltd.

Engineering Research Express

Monitoring thermal defects in rail and rail joints using piezo impedance-based structural health monitoring (PISHM)

Day by day, the number of blog users and microblog users is increasing worldwide. It is easy to say that blogs have captured a significant portion of other web services. In the past few years, the number of users has exponentially increased. User count of Facebook, Twitter, and Instagram applications is not hidden from anyone. Users on such platforms share ideas, experiences, stories, opinions, and views and want to interact with people with the same set of interests. As per the user's expectation, there is a requirement of two things: content curation and recommendations. The content curation algorithm will find the people and their posts on personalized search results. In addition, the recommendation system will help to find the most appropriate match to interact with. In this paper, both approaches are combined to show the user's curated and recommended results. The article focuses on the hybrid model named S-ANFIS, and the results are compared with the well-known approaches like ANN, Deep Neural Network (DNN), and Recurrent Neural Network (RNN). © 2022 Harsh Khatter et al.

Journal of Sensors

Adaptive and Personalized Web Blog Searching Technique Using S-ANFIS

<p>In this manuscript a compact wide band antenna for sub-THz application is proposed. The antenna is designed on a polyimide substrate using graphene as conducting patch and ground. The antenna has an extremely small overall dimension of 1000μm×1000μm. The proposed H-shaped slot antenna has center frequency 0.57THz and other resonances at 0.465THz, 0.58THz &amp; 0.654THz. The proposed design exhibits good impedance matching as well as large bandwidth of 230GHz (40.35%). The simulation result shows that the proposed antenna has maximum gain and efficiency of 8.58dBi and 95.5% at 0.465THz. This antenna is suitable for applications like 6G technology.</p>