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  1. Article ; Online: Experimental and simulation studies on heat pump integration two stage desalination and cooling system

    Tangellapalli Srinivas / Akash Saxena / Shaik Vajeer Baba / Rajeev Kukreja

    Energy Nexus, Vol 11, Iss , Pp 100221- (2023)

    2023  

    Abstract: The coefficient of performance (COP) of a heat pump is higher than a refrigerator. The simultaneous utilisation of cooling effects and heat rejection improves the COP better than heat pump operation. In the proposed system, the cooling and heating ... ...

    Abstract The coefficient of performance (COP) of a heat pump is higher than a refrigerator. The simultaneous utilisation of cooling effects and heat rejection improves the COP better than heat pump operation. In the proposed system, the cooling and heating functions of heat pump have been utilised for the simultaneous benefits of freshwater production and cooling. The Humidification-dehumidification and vapour compression refrigeration (HDH-VCR) cycle has been developed and studied for the production of freshwater, cooling, and hot water. The integrated refrigerator and heat pump's cooling and heating energies were used for freshwater production, cooling, and self-heat generation for system operation. As the heat pump rejects more quantities of heat than the requirements, the additional hot water is a byproduct of the process. The plant also has the ability to generate cool air or hot air depending on the season. Theoretical work (post design analysis) and experimental analysis have been conducted with the aim of theoretical model development and maximising the energy performance ratio (EPR) of the system. The developed coefficients can be used by the researchers in the further developments without repeating the experiment. The identified process variations are evaporator temperature, hot water supply temperature, atmospheric air temperature, and atmospheric air relative humidity (RH). The system resulted in 5 LPH of freshwater, 6.5 kW of cooling, and 3.8 EPR at airflow of 1000 m3/h.
    Keywords Air conditioning ; Freshwater ; Heat pump ; Humidification-dehumidification ; Solar desalination ; Renewable energy sources ; TJ807-830 ; Agriculture (General) ; S1-972
    Subject code 690
    Language English
    Publishing date 2023-09-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Performance Evaluation of Ingenious Crow Search Optimization Algorithm for Protein Structure Prediction

    Ahmad M. Alshamrani / Akash Saxena / Shalini Shekhawat / Hossam M. Zawbaa / Ali Wagdy Mohamed

    Processes, Vol 11, Iss 1655, p

    2023  Volume 1655

    Abstract: Protein structure prediction is one of the important aspects while dealing with critical diseases. An early prediction of protein folding helps in clinical diagnosis. In recent years, applications of metaheuristic algorithms have been substantially ... ...

    Abstract Protein structure prediction is one of the important aspects while dealing with critical diseases. An early prediction of protein folding helps in clinical diagnosis. In recent years, applications of metaheuristic algorithms have been substantially increased due to the fact that this problem is computationally complex and time-consuming. Metaheuristics are proven to be an adequate tool for dealing with complex problems with higher computational efficiency than conventional tools. The work presented in this paper is the development and testing of the Ingenious Crow Search Algorithm (ICSA). First, the algorithm is tested on standard mathematical functions with known properties. Then, the application of newly developed ICSA is explored on protein structure prediction. The efficacy of this algorithm is tested on a bench of artificial proteins and real proteins of medium length. The comparative analysis of the optimization performance is carried out with some of the leading variants of the crow search algorithm (CSA). The statistical comparison of the results shows the supremacy of the ICSA for almost all protein sequences.
    Keywords protein structure ; prediction ; swarm intelligence ; crow search algorithm ; numerical optimization ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
    Subject code 006
    Language English
    Publishing date 2023-05-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Process Optimization of Biodiesel Production Using the Laplacian Harris Hawk Optimization (LHHO) Algorithm

    Ashutosh Sharma / Akash Saxena / Shail Kumar Dinkar / Rajesh Kumar / Ameena Saad Al-Sumaiti

    Modelling and Simulation in Engineering, Vol

    2022  Volume 2022

    Abstract: Continuous power consumption from standard fuel resources is responsible for producing large-scale environmental greenhouse gases. Production of biodiesel fuels from the vegetable oils can be considered an alternative source. Effect of greenhouse gases ... ...

    Abstract Continuous power consumption from standard fuel resources is responsible for producing large-scale environmental greenhouse gases. Production of biodiesel fuels from the vegetable oils can be considered an alternative source. Effect of greenhouse gases can also be diminished. The production of biodiesel is done by a chemical process namely transesterification and usually maximized by using the Response Surface Methodology (RSM) tool. This paper presents a new approach to optimize the production of biodiesel by introducing a new variant of recently published metaheuristic Harris Hawk Optimization (HHO). The developed variant is based on the replacement of random numbers of normal distribution at the initialization phase by the random numbers generated from the Laplacian distribution. The proposed variant is named as the Laplacian Harris Hawk Optimization (LHHO) algorithm. The contribution of this paper is in twofold: firstly the performance of the proposed algorithm is verified over a well-known set of benchmark functions, and then, we applied the LHHO to maximize biodiesel production. Comparison of LHHO is carried out with five other recent metaheuristic algorithms. An optimization routine is formulated in the form of a single-objective function with a temperature, methanol to oil ratio, and catalyst concentration as the optimization variables. These parameters are optimized to maximize the production of biodiesel. The results obtained using the proposed LHHO show significant improvement as compared to other algorithms.
    Keywords Electronic computers. Computer science ; QA75.5-76.95
    Subject code 660
    Language English
    Publishing date 2022-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Ambient Air Quality Classification by Grey Wolf Optimizer Based Support Vector Machine

    Akash Saxena / Shalini Shekhawat

    Journal of Environmental and Public Health, Vol

    2017  Volume 2017

    Abstract: With the development of society along with an escalating population, the concerns regarding public health have cropped up. The quality of air becomes primary concern regarding constant increase in the number of vehicles and industrial development. With ... ...

    Abstract With the development of society along with an escalating population, the concerns regarding public health have cropped up. The quality of air becomes primary concern regarding constant increase in the number of vehicles and industrial development. With this concern, several indices have been proposed to indicate the pollutant concentrations. In this paper, we present a mathematical framework to formulate a Cumulative Index (CI) on the basis of an individual concentration of four major pollutants (SO2, NO2, PM2.5, and PM10). Further, a supervised learning algorithm based classifier is proposed. This classifier employs support vector machine (SVM) to classify air quality into two types, that is, good or harmful. The potential inputs for this classifier are the calculated values of CIs. The efficacy of the classifier is tested on the real data of three locations: Kolkata, Delhi, and Bhopal. It is observed that the classifier performs well to classify the quality of air.
    Keywords Public aspects of medicine ; RA1-1270
    Subject code 006
    Language English
    Publishing date 2017-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Application and Development of Enhanced Chaotic Grasshopper Optimization Algorithms

    Akash Saxena / Shalini Shekhawat / Rajesh Kumar

    Modelling and Simulation in Engineering, Vol

    2018  Volume 2018

    Abstract: In recent years, metaheuristic algorithms have revolutionized the world with their better problem solving capacity. Any metaheuristic algorithm has two phases: exploration and exploitation. The ability of the algorithm to solve a difficult optimization ... ...

    Abstract In recent years, metaheuristic algorithms have revolutionized the world with their better problem solving capacity. Any metaheuristic algorithm has two phases: exploration and exploitation. The ability of the algorithm to solve a difficult optimization problem depends upon the efficacy of these two phases. These two phases are tied with a bridging mechanism, which plays an important role. This paper presents an application of chaotic maps to improve the bridging mechanism of Grasshopper Optimisation Algorithm (GOA) by embedding 10 different maps. This experiment evolves 10 different chaotic variants of GOA, and they are named as Enhanced Chaotic Grasshopper Optimization Algorithms (ECGOAs). The performance of these variants is tested over ten shifted and biased unimodal and multimodal benchmark functions. Further, the applications of these variants have been evaluated on three-bar truss design problem and frequency-modulated sound synthesis parameter estimation problem. Results reveal that the chaotic mechanism enhances the performance of GOA. Further, the results of the Wilcoxon rank sum test also establish the efficacy of the proposed variants.
    Keywords Electronic computers. Computer science ; QA75.5-76.95
    Subject code 006
    Language English
    Publishing date 2018-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Assessment of Transient Stability through Coherent Machine Identification by Using Least-Square Support Vector Machine

    Bhanu Pratap Soni / Akash Saxena / Vikas Gupta / S. L. Surana

    Modelling and Simulation in Engineering, Vol

    2018  Volume 2018

    Abstract: Transient stability assessment (TSA) of the power system is a crucial issue with escalating demands and large operational constraints. Real-time TSA allows for deciding and monitoring of the relevant preventive/corrective control actions depending on the ...

    Abstract Transient stability assessment (TSA) of the power system is a crucial issue with escalating demands and large operational constraints. Real-time TSA allows for deciding and monitoring of the relevant preventive/corrective control actions depending on the dynamic behavior of the system components. To assess this, coherency of generating machines is to be found. After determination of the coherent machines, any corrective or preventive action can be initiated by the system operator to maintain stability of the system during occurrence of any severe contingency. The Transient Severity Index (TSI) introduced in this paper has proven to be an interesting alternative for determining generator coherency. Furthermore, the numerical values of this index are employed to construct a supervised learning-based classifier and the ranking method with the help of system load and generation as input features. This framework employs the support vector machine (SVM) to perform the ranking of the generators based on severity and classify them into vulnerable and nonvulnerable machines. The results are validated on the IEEE 10-generator, 39-bus test (New England) system. It is observed that the proposed index and the supervised learning engine give satisfactory results and both are aligned with the published approaches.
    Keywords Electronic computers. Computer science ; QA75.5-76.95
    Subject code 670
    Language English
    Publishing date 2018-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Structured Clanning-Based Ensemble Optimization Algorithm

    Avinash Sharma / Rajesh Kumar / Akash Saxena / B. K. Panigrahi

    Modelling and Simulation in Engineering, Vol

    A Novel Approach for Solving Complex Numerical Problems

    2018  Volume 2018

    Abstract: In this paper, a novel swarm intelligence-based ensemble metaheuristic optimization algorithm, called Structured Clanning-based Ensemble Optimization, is proposed for solving complex numerical optimization problems. The proposed algorithm is inspired by ... ...

    Abstract In this paper, a novel swarm intelligence-based ensemble metaheuristic optimization algorithm, called Structured Clanning-based Ensemble Optimization, is proposed for solving complex numerical optimization problems. The proposed algorithm is inspired by the complex and diversified behaviour present within the fission-fusion-based social structure of the elephant society. The population of elephants can consist of various groups with relationship between individuals ranging from mother-child bond, bond groups, independent males, and strangers. The algorithm tries to model this individualistic behaviour to formulate an ensemble-based optimization algorithm. To test the efficiency and utility of the proposed algorithm, various benchmark functions of different geometric properties are used. The algorithm performance on these test benchmarks is compared to various state-of-the-art optimization algorithms. Experiments clearly showcase the success of the proposed algorithm in optimizing the benchmark functions to better values.
    Keywords Electronic computers. Computer science ; QA75.5-76.95
    Subject code 006
    Language English
    Publishing date 2018-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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