Navdeep Singh

Bio: Navdeep Singh is an academic researcher from Madan Mohan Malaviya University of Technology. The author has contributed to research in topics: Control theory & Nonlinear system. The author has an hindex of 19, co-authored 181 publications receiving 1411 citations. Previous affiliations of Navdeep Singh include Dr. B. R. Ambedkar National Institute of Technology Jalandhar & Motilal Nehru National Institute of Technology Allahabad.

Influence of coal bottom ash as fine aggregates replacement on various properties of concretes: A review

Abstract: In the current phase, the engineering and construction industry has successfully engaged in a challenge for consuming “sustainable, green and recycled products” in manufacturing of concrete. The utilization of Coal Bottom Ash (CBA) in concrete industry is one of the best feasible options to minimize the environmental concerns raised due to its presence. The use of CBA in manufacturing of concrete has been increased in last decade. Coal bottom ash has a potential to be used as concrete material in place of fine aggregates. The present investigation has focused on reviewing some of the fresh, mechanical and durability properties of Normally Vibrated Concrete (NVC) and Self-Compacting Concrete (SCC) made with incorporation of CBA as replacement of fine aggregates. Most of the studies have described that the use of CBA lowers the overall performance of NVC/SCC, whereas few of them have reported its successful use in attaining similar/better performance to that of the concretes made without incorporation of CBA.

Impact of Topology on the Propagation of Cascading Failure in Power Grid

Abstract: In the past two decades the frequent occurrences of large scale blackouts and catastrophic events has reduced the reliability of power grid to a great extent. A thorough analysis of the propagation of failures, in terms of line outages, combined with the topological characteristics of the grid aids, has been done to take corrective actions to save the system from complete collapse. It also helps to investigate the progress and understand the nature and intensity of blackouts. This motivates to establish the relationship between the network topological characteristics and cascading failure in the power grid. In this paper, the basic topological characteristics of the power network are studied in detail and the average propagation of failure under varying topological conditions is calculated as a branching process parameter. The variation in the mean propagation is studied in detail using a number of test bed networks with the alternate realistic networks derived from the standard IEEE networks imitating the real network conditions. The results confirm a qualitative agreement between the variations in topological parameter and the failure propagation rate in the cascading regime. Based on the analysis mentioned above, data clearly shows that the average failure propagation factor varies linearly with the variations in the statistical metrics.

Reviewing the behaviour of high volume fly ash based self compacting concrete

Abstract: The current review article focuses on the behaviour of High Volume Fly Ash (HVFA) based Self Compacting Concrete (SCC) prepared with Natural Coarse Aggregates (NCA) and Recycled Concrete Aggregates (RCA). The overall performance of HVFA based SCC has been estimated from the observations of the available literature in terms of fresh, mechanical and durability properties. The utilization of coal ashes i.e. Fly Ash (FA) and Coal Bottom Ash (CBA) in SCC has become an attractive substitute for disposal, thus their impact on aforementioned properties has also been summarised briefly. The study also encompasses the characteristics and applications of coal ashes (used as binder and fine aggregates) and RCA (coarse aggregates). The outcomes of the various investigations depict that replacement of binder and aggregates affects the fresh; mechanical as well as durability properties of HVFA based SCC. The literature signifies that HVFA based SCC made with specified levels of coal ashes (FA/CBA) and non-conventional aggregates (RCA) do not inhibit the overall performance. Further, the study also supports in minimization of over pounding of natural assets for achieving the desired sustainability.

Utilization of coal bottom ash in recycled concrete aggregates based self compacting concrete blended with metakaolin

Abstract: Conservation of natural products and recycling in concrete industry wastes are the foremost needs of the current period. Intense utilization of alternate materials in concrete manufacturing has already been initiated from the past few decades. The present investigation has been piloted to evaluate the overall feasibility of Self Compacting Concrete (SCC) prepared with Coal Bottom Ash (CBA) and Recycled Coarse Concrete Aggregates (RCA) by replacing of Normal Fine Aggregates (NFA) and Normal Coarse Aggregates (NCA) respectively. The performance of SCC prepared with coal industry by-products [Fly Ash (FA), CBA] and construction industry wastes (RCA) has been evaluated experimentally. Various mechanical (compressive and tensile) and long-term (chloride permeability, capillary suction, accelerated carbonation, electrical resistivity, ultrasonic pulse velocity) properties of SCC prepared with different proportions of RCA and CBA have been estimated. The investigation inferences that the incorporation of constant amount of CBA (10%) along with varying content of RCA (up to 50%) has been proved to be advisable for the use in construction industry as enhanced/equivalent performance compared to that of control SCC has been achieved. Ample variation in the results of experiments conducted on SCC mixes has been noticed with increase in content of RCA. To capture the observed loss in the behavior of SCC prepared with higher alternate levels (>50% RCA) and CBA, Metakaolin (MK) has been inculcated. The attained findings revealed that the inclusion of MK (along with other by-products) results in comparable/at-par performance for SCC prepared up to full alternate levels (100%) of NCA with RCA.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Modern Applied Statistics With S

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Properties Of Concrete

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Energy function analysis for power system stability

Abstract: (1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

Particle-in-Cell Charged Particle Simulations, plus Monte Carlo Collisions with Neutral Atoms, PIC-MCC

Abstract: Many-particle charged-particle plasma simulations using spatial meshes for the electromagnetic field solutions, particle-in-cell (PIC) merged with Monte Carlo collision (MCC) calculations, are coming into wide use for application to partially ionized gases. The author emphasizes the development of PIC computer experiments since the 1950s starting with one-dimensional (1-D) charged-sheet models, the addition of the mesh, and fast direct Poisson equation solvers for 2-D and 3-D. Details are provided for adding the collisions between the charged particles and neutral atoms. The result is many-particle simulations with many of the features met in low-temperature collision plasmas; for example, with applications to plasma-assisted materials processing, but also related to warmer plasmas at the edges of magnetized fusion plasmas. >