Delhi Technological University

About: Delhi Technological University is a education organization based out in New Delhi, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 4427 authors who have published 6761 publications receiving 71035 citations. The organization is also known as: Delhi College of Engineering & DTU.

Detailed parametric analysis of solar driven supercritical CO2 based combined cycle for power generation, cooling and heating effect by vapor absorption refrigeration as a bottoming cycle

Abstract: The present study investigates the exergy and energy centered parametric performance of parabolic trough collectors (PTC) driven combined Supercritical CO2 (SCO2) cycle/vapor absorption refrigeration (VAR) system in order to produce power, cooling and heating effect. Selected independent parameters such as direct normal irradiance (DNI), maximum cycle temperature, and the compressor pressor ratio has an incremental effect on the system efficiency in contrast to the compressor inlet temperature, generator temperature, and absorber and condenser temperature due to the inverse effect of these variables on the efficiency. Additionally, the effect of the local apparent time (LAT) has also been assessed on the performance of combined cycle (SCO2-VAR cycle) and reveal that for the location of Mumbai, the maximum value of exergy and thermal efficiency was about 75.71% and 42.18% at LAT (h) = 1230, respectively on the April 15 and 70.1% and 39.05% at LAT (h) = 1130 & 1230, respectively for the December 15. Apart from this, study concludes that the maximum value of exergy and thermal efficiency of PTC was about 33.9% and 65.32% at DNI of 0.96 kW/m2, respectively. Whereas, the exergy destruction rate follows the reverse behaviour from exergy efficiency and the maximum amount of exergy destructions have been noticed in a PTC field (i.e. 3696 kW) as compared to other components. Furthermore, at the maximum cycle temperature of 650 K, the exergy and thermal efficiency of the SCO2-VAR cycle was about 75.2% and 41.89%, respectively, however, the coefficient of performance (COP) of VAR cycle for cooling and heating was about 0.4675 and 1.435, respectively. Moreover, the network output of the SCO2-VAR cycle was found to be as 1570 kW at 650 K.

$L_{1}$ Adaptive Droop Control for AC Microgrid With Small Mesh Network

Abstract: The proposed paper is mainly focused on achieving stable operation of microgrid having reconfigurable architecture leading to huge variation in network parameters. The variation in network parameters may not be easily handled by conventional droop controllers, which are mainly designed while assuming fixed network configuration. However, these assumptions become invalid for a microgrid having small mesh network with reconfigurable structure. Therefore, it is most important for a microgrid to remain stable not only during various changes in droop characteristics but also during dynamic topological changes. The $L_1$ controllers are well known for their robustness under wide parametric variations. Therefore, a novel $L_{1}$ adaptive controller has been designed to achieve enhanced stability of microgrid under the varying network configuration and variable droop controller characteristics. The proposed method is simulated in MATLAB/ Simulink and verified on field programmable gate array (FPGA)-based real world hardware platform.

Integrated approach for human action recognition using edge spatial distribution, direction pixel and -transform

Abstract: In this article, a simple yet proficient approach for the recognition of human action and Activity is presented. This method is based on the integration of translation and rotation of the human body. The proposed framework undergoes three major steps: (i) the shape of the human action/activity is represented through the computation of average energy images using edge spatial distribution of gradients along with the directional variation of the pixel values, (ii) the orientation-based rotational information of the human action is computed through -transform and (iii) a descriptor is developed by the fusion of translational features with rotational features. The fusion of features possesses the advantages exhibited by both local and global features of the silhouette and thus provides the discriminating feature representation for human activity recognition. The performance of descriptor is evaluated through a hybrid approach of support vector machine and the nearest neighbour classifiers on standard data set...

Coupling Characteristics of Multicore Photonic Crystal Fiber-Based 1 $\,\times\,$ 4 Power Splitters

Abstract: A new design of multicore photonic crystal fibers (PCFs) is proposed and investigated through full-vectorial finite-element method and finite-element beam propagation method. The fiber design comprises four identical cores surrounding a central core. The optical power launched into the central core is equally divided into other neighboring four cores with a 25% of coupling ratio. The coupled-mode analysis is also carried out to understand the supermode patterns and the coupling characteristics. Through numerical simulations, it is demonstrated that the optical power can be divided equally in a 5.8-mm-long multicore PCF. The power coupling characteristics obtained through coupled-mode analysis are in very good agreement with those calculated from beam propagation method solver.

Crack-pot: Autonomous Road Crack and Pothole Detection

Abstract: With the advent of self-driving cars and autonomous robots, it is imperative to detect road impairments like cracks and potholes and to perform necessary evading maneuvers to ensure fluid journey for on-board passengers or equipment. We propose a fully autonomous robust real-time road crack and pothole detection algorithm which can be deployed on any GPU based conventional processing boards with an associated camera. The approach is based on a deep neural net architecture which detects cracks and potholes using texture and spatial features. We also propose pre-processing methods which ensure real-time performance. The novelty of the approach lies in using texture-based features to differentiate between crack surfaces and sound roads. The approach performs well in large viewpoint changes, background noise, shadows, and occlusion. The efficacy of the system is shown on standard road crack datasets.