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Lehar Asip Khan

Researcher at Capital University

Publications -  10
Citations -  213

Lehar Asip Khan is an academic researcher from Capital University. The author has contributed to research in topics: Phase-change material & Heat transfer. The author has an hindex of 3, co-authored 4 publications receiving 34 citations. Previous affiliations of Lehar Asip Khan include Dublin City University.

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Melting performance enhancement of PCM based thermal energy storage system using multiple tubes and modified shell designs

TL;DR: In this article, experimental and numerical investigations are performed for heat transfer enhancement in a horizontal Latent Thermal Energy Storage System using multiple heat transfer tubes and modified shell designs, where Stearic acid is used as phase change material and it is placed in the annulus of steel shell and copper tubes carrying water as the heat transfer fluid.
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Melting performance enhancement of a phase change material using branched fins and nanoparticles for energy storage applications

TL;DR: In this article, the application of branched fins and nanoparticles to enhance the melting of phase change material (PCM) placed in a horizontally configured latent heat thermal energy storage (LHTES) unit was presented.
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Role of orientation of fins in performance enhancement of a latent thermal energy storage unit

TL;DR: In this article, the role of orientation of fins in performance enhancement of a horizontal Latent Thermal Energy Storage Unit (LTESU) is investigated, and two important correlations are proposed which can accurately predict the melting and heat transfer performance of LTESU for a large range of HTF temperatures.
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Dominant roles of eccentricity, fin design, and nanoparticles in performance enhancement of latent thermal energy storage unit

TL;DR: In this paper, numerical and experimental investigations of thermal performance enhancement of horizontal longitudinal shell and tube latent heat thermal energy storage unit (LHTESU) via eccentricity (e), fin design optimization, and nanoparticles in the phase change material (PCM) of stearic acid are presented.
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Anomaly detection in laser powder bed fusion using machine learning: A review

TL;DR: In this article , the authors provide an overview of L-PBF and outline the ML methods used for anomaly detection in LPBF, and explain how ML methods are being used as a step forward toward enabling the real-time process control of MAM and the process can be optimized for higher accuracy, lower production time, and less material waste.