D
D. Yogi Goswami
Researcher at University of South Florida
Publications - 208
Citations - 11365
D. Yogi Goswami is an academic researcher from University of South Florida. The author has contributed to research in topics: Organic Rankine cycle & Thermal energy storage. The author has an hindex of 46, co-authored 187 publications receiving 9957 citations. Previous affiliations of D. Yogi Goswami include University of Florida & Glenn Research Center.
Papers
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Phase Change and Heat Transfer Numerical Analysis during Solidification on an Encapsulated Phase Change Material
Antonio Ramos Archibold,Antonio Ramos Archibold,Muhammad M. Rahman,José Gonzalez-Aguilar,D. Yogi Goswami,Elias K. Stefanakos,Manuel Romero +6 more
TL;DR: In this article, the coupled phase change and heat transfer in a spherical capsule partially filled with sodium nitrate is numerically investigated during the solidification process, where the finite volume method is used to compute energy and linear momentum equations along with the enthalpy-porosity method to track the melting front.
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Comparison of Numerical and Experimental Assessment of a Latent Heat Energy Storage Module for a High-Temperature Phase-Change Material
Antonio Ramos Archibold,Antonio Ramos Archibold,Abhinav Bhardwaj,Muhammad M. Rahman,D. Yogi Goswami,Elias K. Stefanakos +5 more
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Characterization of 10,12-pentacosadiynoic acid Langmuir-Blodgett monolayers and their use in metal-insulator-metal tunnel devices.
TL;DR: The precise control of the thickness of the insulating monolayers proved critical for electron tunneling to take place in the MIM structure, and the current–voltage characteristics of the M IM diode revealed tunneling behavior in the fabricated Ni–PDA LB film–Ni structures.
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Generalized distributed state space model of a CSP plant for simulation and control applications: Single-phase flow validation
Marcus V. Americano da Costa,Arun Kumar Narasimhan,Diego Guillen,Babu Joseph,D. Yogi Goswami +4 more
TL;DR: In this paper, a distributed state space model is proposed to ensure computational flexibility and facilitate industrial applications, such as optimization, control and automation, which can be easily extended to direct steam generation (DSG) plants.