Anupam Bhandari
@upes.ac.in
Assistant Professor
University of Petroleum and Energy Studies Dehradun
EDUCATION
Ph D NIT Kurukshetra
RESEARCH INTERESTS
Ferrohydrodynamics, Mathematical Modeling and Simulation
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Manoj K. Singh, Shshank Chaube, Sangeeta Pant, Sanjeev Kumar Singh, and Anuj Kumar
Elsevier BV
Anuj Kumar, Sangeeta Pant, Manoj K. Singh, Shshank Chaube, Mangey Ram, and Akshay Kumar
MDPI AG
The last few decades have witnessed advancements in intelligent metaheuristic approaches and system reliability optimization. The huge progress in metaheuristic approaches can be viewed as the main motivator behind further refinement in the system reliability optimization process. Researchers have intensively studied system reliability optimization problems (SROPs) to obtain the optimal system design with several constraints in order to optimize the overall system reliability. This article proposes a modified wild horse optimizer (MWHO) for SROPs and investigates the reliability allocation of two complex SROPs, namely, complex bridge system (CBS) and life support system in space capsule (LSSSC), with the help of the same process. The effectiveness of this framework based on MWHO is demonstrated by comparing the results obtained with the results available in the literature. The proposed MWHO algorithm shows better efficiency, as it provides superior solutions to SROPs.
Jyoti Verma, Sangeeta Pant, Suman Kumari, Vinod Belwanshi, Jasvir Dalal, and Anuj Kumar
Springer Science and Business Media LLC
Present work investigates the trench edge termination in Ga 2 O 3 -based Schottky diode utilizing SiO 2 as a dielectric material. Various models such as Shockley Read Hall (SRH) and Auger recombination, concentration- and field-dependent mobility, Fermi Dirac, and Selberherr impact ionization are considered to optimize device structure. Owing to electric field crowding, the breakdown voltage in unterminated structure is determined as ~ 715 V. For trench-terminated device, the breakdown voltage is found increasing with trench depth and decreasing with trench width. Our results revealed that the optimum value for trench depth and width as 100 nm and 10 µm, respectively, which gives a breakdown voltage of 1505 V. In addition, the effect of interface charges (positive and negative) on the breakdown voltage is also investigated.
Tina Sharma, Anuj Kumar, Sangeeta Pant, and Ketan Kotecha
Institute of Electrical and Electronics Engineers (IEEE)
Incorporating numerous technical, economic, environmental, and social benchmarks makes multi-criteria decision-making (MCDM) a reliable decision-making tool in sustainable development. To achieve sustainability target six, related to clean water and sanitation, wastewater technology comes into play. They bring complicated scenarios with several indicators, criteria, and conflicting objectives. This article provides a thorough review of MCDM methods, including pure techniques such as AHP, TOPSIS, VIKOR, ELECTRE, and others, as well as hybrid MCDM approaches like the non-structural fuzzy decision support system (NSFDSS) in conjunction with Artificial Neural Network (ANN), applied to wastewater treatment technologies or processes to remove water contamination. This review draws upon articles sourced from the “Scopus” and “Web of Science (WoS)” databases, covering the period from 2015 to 2023. The primary aim of this endeavor is to offer a current and comprehensive review of the literature about MCDM to aid researchers and environmental engineers in their quest to identify the most appropriate techniques for tackling the complex challenges associated with wastewater treatment (WWT). The results demonstrate the versatile application of MCDM in various scenarios to remove water contaminants effectively. For example, these applications encompass assessing the efficacy of adsorbents for the removal of pollutants and effluents from wastewater, determining the optimal WWT technology from a range of alternatives, evaluating the performance of both metallic (such as ZnO and MnO) and non-metallic (like activated carbon) nanomaterial adsorbents, and scrutinizing strategies to minimize water consumption. Furthermore, within the context of specific WWT technologies, MCDM identifies and highlights critical criteria that are instrumental in enhancing system efficiency for removing pollutants. Ultimately, MCDM methods represent a contemporary decision support system. In future research, the potential utilization of MCDM can extend to tracking the environmental impacts of nanomaterial adsorbents released from treatment plants into the surrounding ecosystem.
Anuj Kumar, Sangeeta Pant, and Mangey Ram
River Publishers
Nowadays, the transformation of the various energy system is the core objective of the dedicated sustainable development goal related to energy sustainable world within the new United Nations development agenda. Different nuclear regulatory authorities around the globe, sets Technical Specifications (TSs) for ensuring the human and environmental safety of various highly volatile and complex Nuclear Power Generation Plants (NPGPs). TSs define numerous measures and limitations related to safety and sustainability that must be followed by all NPGPs around the world. Reliability, availability and cost components associated with a NPGPs form important bases for the setting of TSs. In this work, a framework based on few recent metaheuristics like Cuckoo Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Hybrid PSO GWO algorithm (HPSOGWO) has been presented for cost optimization and reliability parameter extraction of a complex engineering system named Heat Removal System (HRS) of a nuclear power generation plant safety system (NPGPSS). A multi-criteria decision-making (MCDM) method named Weighted-Sum Method (WSM) has also been employed for prioritizing the available metaheuristics based on available beneficial and non-beneficial criteria’s.
Sadiya Naaz, Rashmi Khanna, Riya Rawat, Neha Negi, Mangey Ram, Akshay Kumar, and Anuj Kumar
SAGE Publications
Microwaves are an example of “electromagnetic” radiation, which is a combination of electromagnetic and electrical waves traveling through space. In this paper, the complex consecutive k-out-of- n:W (where, W stands for working system) convection microwave oven system (CMOS) is proposed and different measures are calculated on the basis of the reliability function via two techniques namely, universal generating function (u-function/UGF) and structure-function approach (SFA). Basically, the main aim of the study is to evaluate the signature reliability analysis of the complex consecutive k-out-of- n:W CMOS system using proposed techniques. To assess the suggested system’s reliability function and related metrics, both methods are applied. The considered system consisted of a total seven components, but the system comprises the k-out-of- n:W robustness strategy that’s why it becomes a complex consecutive 5-out-of-7: W CMOS. With the help of the reliability function, the minimal signature is introduced for the determination of the anticipated lifetime and its cost rate. Also. the purpose of this work is to evaluate all these outcomes and then compare their values, which are yielded by both applied approaches, that is, u-function approach and SFA.
Sangeeta Pant, Priya Garg, Anuj Kumar, Mangey Ram, Akshay Kumar, Hitesh Kumar Sharma, and Yury Klochkov
Springer Science and Business Media LLC
Anuj Kumar and Sangeeta Pant
Elsevier BV
Sudheer Singh Rawat, Sangeeta Pant, Anuj Kumar, Mangey Ram, Hitesh Kumar Sharma, and Akshay Kumar
Ram Arti Publishers
Nowadays, utility of the multi-criteria decision making (MCDM) technique in tackling real-world complex problems has risen tremendously. Even the United Nations is focusing on decision-making in order to accomplish Agenda 2030, as stated in its paragraph 48. The desire to promote sustainable development (SD) necessitates complex decision models, which could be achieved through the use of an efficient MCDM approach. Analytical Hierarchy Process (AHP) is one of the most efficient MCDM techniques that is incorporated in this study. The purpose of this work is to provide a contrasting of AHP's application that emerged between 2011 and 2022, rather than to reflect on its methodological improvements. Its application encompasses a wide range of disciplines including Renewable Energy, Sustainable manufacturing, Natural Hazards, Environmental Pollution, Landfill waste management and many others which lies explicitly or implicitly under the theme of SD. Previously, many reviews have been conducted that concentrated on a single decision topic; moreover, this review explore the comprehensive viewpoint of decision problems. As per statistical results, Middle Eastern countries such as Iran placed top in terms of applying AHP application in different sectors. GIS and fuzzy logic are the most often used approaches to incorporate AHP across all disciplines. Notably, the findings indicate that the most decision problem have selection and assessment as a major concern whereas, environmental, economical, LULC & DFR are more frequently used criteria.
AG Adeeth Cariappa, Kamlesh Kumar Acharya, Chaitanya Ashok Adhav, Sendhil R, P. Ramasundaram, Anuj Kumar, Satyavir Singh, and Gyanendra Pratap Singh
Elsevier BV
Sangeeta Pant, Anuj Kumar, Mangey Ram, Yury Klochkov, and Hitesh Kumar Sharma
MDPI AG
A well-regarded as well as powerful method named the ‘analytic hierarchy process’ (AHP) uses mathematics and psychology for making and analysing complex decisions. This article aims to present a brief review of the consistency measure of the judgments in AHP. Judgments should not be random or illogical. Several researchers have developed different consistency measures to identify the rationality of judgments. This article summarises the consistency measures which have been proposed so far in the literature. Moreover, this paper describes briefly the functional relationships established in the literature among the well-known consistency indices. At last, some thoughtful research directions that can be helpful in further research to develop and improve the performance of AHP are provided as well.
Anuj Kumar, Sangeeta Pant, Mangey Ram, and Ganga Negi
IEEE
In this study, two conflicting objectives related to the system cost and system reliability of a complex bridge network (CBN) have been taken into consideration. A novel multi-objective evolutionary algorithm (MOEA) named Particle swarm optimization incorporating crowding distance (MOPSO-CD) has been applied to get the Reliability-Cost Fronts (RCFs) of this complex multi-objective reliability optimization problem. The simulation results obtained by MOPSO-CD give wide varieties of RCFs corresponding to different parameter settings from which the decision maker (DM) could select the RCF of his/her choice.
Mangey Ram, Ganga Negi, Nupur Goyal, and Anuj Kumar
River Publishers
The demand in the present global industrial system, requires the challenge to meet the growing consumer capabilities and requirements constantly. So, there is always a need to improve different parameters, one of them being different types of failures involved in the working of different engineering systems related to communication systems, manufacturing goods, nuclear and hydro power plants, automobiles and many others. Human error occurring in the working of various systems has always been the challenge to the researchers and is being constantly worked upon by the researchers in the analysis and improvement of reliability and availability of different complex and multistate systems. In the present paper, there is a three-unit system consisting of the unit A with two subunits in parallel and other units B and C are connected in series with A. The authors have investigated and analysed different reliability measures like availability, MTTF and sensitivity taking into account the human failure and carrying out rework system. This research work aims at the study of reliability and availability measures of a multi-state system incorporating human error so as to increase the efficiency of industrial systems by taking maintenance and rework measures to enhance the availability factors. This would help to understand and estimate the reliability measures of any such systems in the field of telecommunication, any electronic devices like that in small power plants, robot systems and such others. Also, a comparison has been made between the availability and reliability estimates in the presence and in the absence of human error. The techniques used are Markov process, Laplace transformation and supplementary variable technique.
Fatemah Mofarreh, S. K. Srivastava, Anuj Kumar, and Akram Ali
American Institute of Mathematical Sciences (AIMS)
<abstract><p>The main purpose of this paper is to study the properties of $ \\mathcal{PR} $-semi-invariant submanifold of para-Kenmotsu manifold. We obtain the integrability conditions for the invariant distribution and anti-invariant distribution. We obtain some existence and non-existence results of $ \\mathcal{PR} $-semi-invariant warped product submanifolds. We provide some necessary and sufficient conditions for $ \\mathcal{PR} $-semi-invariant submanifold to be a $ \\mathcal{PR} $-semi-invariant warped product submanifold in para-Kenmotsu manifold. We also derive some sharp inequalities for $ \\mathcal{PR} $-semi-invariant warped product submanifold in para-Kenmotsu manifolds.</p></abstract>
Ganga Negi, Anuj Kumar, Sangeeta Pant, and Mangey Ram
Springer Science and Business Media LLC
From the solitudinarian era to the present, the human race has been striving towards the betterment of his life by trying to find out the hidden secrets of our nature. Some time back one would hardly think that colonies of ant, pack of grey wolves, and elephants would be used to design an optimization algorithm. One of the optimization techniques called Grey Wolf Optimization (GWO) algorithm is motivated by the socio-hierarchical behaviour of the animal named Canis Lupus (Grey Wolf). In this paper, the detailed description of GWO is presented along with different development in standard GWO and its applications. Precisely, this article presents a state of the art review of the GWO algorithm, its progress, and applications in more complex real-world problem-solving.
Anuj Kumar, Mridul Vohra, Sangeeta Pant, and Sanjeev Kumar Singh
Informa UK Limited
Jyoti Verma, Sangeeta Pant, Anuj Kumar, Bhupendra Kumar Jangir, Jasvir Dalal, and Mangey Ram
Elsevier BV
Abstract Power generation and its distribution are highly required to support the health-care, comfort, and transportation of next generation. Silicon-based power devices have reached their theoretical limit. Alternative solution is suggested by introduction of wide bandgap semiconductors, i.e., SiC, GaN, etc. Maturity in crystal quality and availability in the market makes SiC a promising candidate to adopt in fabrication of power devices. However, their full potential is inhibited by lack of efficient trench termination technique. This work reports trench terminated 4H-nSiC based Schottky barrier diode structure using Al2O3 as a dielctric material. ATLAS device simulator of Silvaco software is used to simulate the device structures. Various models like SRH and Auger recombination, Fermi Dirac, parallel and concentration field dependent mobility, incomplete ionization, Selberherr impact ionization, etc. have been included. Due to high potential and electric field crowding at edges of unterminated schottky barrier diodes, their is predicted as ~ 350 V. However, the potential and therefore the electric field at edges of SBD has been minimized by forming a trench at its edges. The trench in the designed structure is filled with SiO2, Polyimide and with Al2O3. The high permittivty of dielctric material filled in the trench leads to enhancement in breakdown voltage of the device to ~ 1875 V.
Ganga Negi, , Anuj Kumar, Sangeeta Pant, Mangey Ram, , , and
Regional Association for Security and Crisis Management
Reliability allocation to increase the total reliability has become a successful way to increase the efficiency of the complex industrial system designs. A lot of research in the past have tackled this problem to a great extent. This is evident from the different techniques developed so far to achieve the target. Stochastic metaheuristics like simulated annealing, Tabu search (TS), Particle Swarm Optimization (PSO), Cuckoo Search Optimization (CS), Genetic Algorithm (GA), Grey wolf optimization technique (GWO) etc. have been used in recent years. This paper proposes a framework for implementing a hybrid PSO-GWO algorithm for solving some reliability allocation and optimization problems. A comparison of the results obtained is done with the results of other well-known methods like PSO, GWO, etc. The supremacy/competitiveness of the proposed framework is demonstrated from the numerical experiments. These results with regard to the time taken for the computation and quality of solution outperform the previously obtained results by the other well-known optimization methods.
Nitin Uniyal, Sangeeta Pant, and Anuj Kumar
International Journal of Mathematical, Engineering and Management Sciences plus Mangey Ram
Optimization has been a hot topic due to its inevitably in the development of new algorithms in almost every applied branch of Mathematics. Despite the broadness of optimization techniques in research fields, there is always an open scope of further refinement. We present here an overview of nature-inspired optimization with a subtle background of fundamentals and classification and their reliability applications. An attempt has been made to exhibit the contrast nature of multi objective optimization as compared to single objective optimization. Though there are various techniques to achieve the optimality in optimization problems but nature inspired algorithms have proved to be very efficient and gained special attention in modern research problems. The purpose of this article is to furnish the foundation of few nature inspired optimization techniques and their reliability applications to an interested researcher.
Anuj Kumar, Sangeeta Pant, and Mangey Ram
Wiley
Sangeeta Pant, Anuj Kumar, and Mangey Ram
Ram Arti Publishers
A framework devoted to the solution of nonlinear systems of equations using grey wolf optimization algorithm (GWO) and a multi-objective particle swarm optimization algorithm (MOPSO) is presented in this work. Due to several numerical issues and very high computational complexity, it is hard to find the solution of such a complex nonlinear system of equations. It then explains that the problem of solution to a system of nonlinear equations can be simplified by viewing it as an optimization problem and solutions can be obtained by applying a nature inspired optimization technique. The results achieved are compared with classical as well as new techniques established in the literature. The proposed framework also seems to be very effective for the problems of system of non-linear equations arising in the various fields of science. For this purpose, the problem of neurophysiology application and the problem of combustion of hydrocarbons are considered for testing. Empirical results show that the presented framework is bright to deal with the high dimensional equations system.