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Transport Phenomena Studies for Renewable Energy Development
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Transport Phenomena Studies for Renewable Energy Development

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (15 March 2023) | Viewed by 12687
The paper submitted to the Special Issue will be processed and published immediately if it's accepted after peer-review.
Please contact the guest editor or the journal editor ([email protected]) for any queries.

Special Issue Editors

Dr. Yubiao Sun

E-Mail Website
Guest Editor
Department of Engineering, University of Cambridge, Trumpington St, Cambridge CB2 1PZ, UK
Interests: multiphase flows; aerodynamics; spray cooling; droplet dynamics; thermal management; CFD flow modelling; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Kan Qin

E-Mail Website
Guest Editor
School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710060, China
Interests: computational fluid dynamics; energy system; heat transfer and turbomachinery

Special Issue Information

Dear Colleagues,

We are pleased to invite you to submit your high-quality manuscripts to our forthcoming Special Issue on “Transport Phenomena Studies for Renewable Energy Development” in the journal Energies. The theme of the paper may relate to theoretical, experimental, or numerical studies investigating phenomena related to heat and mass transfer in renewable energy development, including but not limited to wind and wave energy resources, fuel cells, geothermal energy, and solar and hydrogen energy. This Special Issue is open to researchers and authors who work in renewable and sustainable energy development to submit their original research and review articles in applied energy conversion and management, single-phase and multiphase flows, heat and mass transfer in energy generation systems, fluid modelling and state-of-art machine learning techniques. CFD work with commercial software should include deep analysis of the results, and studies using open-source codes are encouraged. Energies covers a wide range of topics related to energy generation, energy storage and transmission, energy management and conversion, fossil fuels, nuclear and renewable resources, waste utilisation, and sustainability. All other works that examine phenomena in renewable energy systems using new techniques such as artificial neural networks, genetic algorithms, and dynamic programming are also strongly encouraged.

Manuscripts may be review papers or regular papers based on applied or fundamental studies. Physical and mathematical modelling including machine learning is of interest, as well as field case studies. For example, a fundamental study may be about understanding the mechanisms of boundary layer interaction with a functional surface. Instances of applied research may concern the optimisation of a pipeline for heavy oil transport or the design of novel channels which have important environmental applications.

The Special Issue will explore the technical challenges related to important heat and mass transfer problems and will serve as an excellent opportunity to rapidly share your research in an open-access journal for the widest reach and impact.

We look forward to receiving your manuscripts for this Special Issue.

Dr. Yubiao Sun
Dr. Kan Qin
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • heat and mass transfer
  • energy conversion and storage
  • multiphase flows
  • computational fluid dynamics
  • power generation
  • machine learning
  • thermal management technologies
  • renewable energy technologies
  • power cycle analysis

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Published Papers (4 papers)

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Research

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21 pages, 8365 KiB  
Article
Fluid-Thermal Interaction Simulation of a Hypersonic Aircraft Optical Dome
by Zhiqiang Wang, Anjing Zhang, Jia Pan, Weiguo Lu and Yubiao Sun
Energies 2022, 15(22), 8619; https://doi.org/10.3390/en15228619 - 17 Nov 2022
Cited by 1 | Viewed by 1872
Abstract
Hypersonic aircraft design is an enabling technology. However, many problems are encountered, including the design of the hood. The aircraft optical dome can become heated due to aerodynamic effects. Since the optical dome of a hypersonic aircraft should satisfy optical imaging requirements, a [...] Read more.
Hypersonic aircraft design is an enabling technology. However, many problems are encountered, including the design of the hood. The aircraft optical dome can become heated due to aerodynamic effects. Since the optical dome of a hypersonic aircraft should satisfy optical imaging requirements, a conventional ablative coating cannot be adopted. The aerodynamic heating characteristics during the whole flight must be studied. In this study, a numerical simulation method for the aerodynamic heat of hypersonic aircraft under long-term variable working conditions is proposed. In addition, the numerical simulation of the external flow field and structure coupling of the aerodynamic heat problem is performed. The dynamic parameters of temperature and pressure are obtained, and the thermal protection basis of the internal equipment is obtained. Numerical results indicate that the average temperature and maximum temperature of the optical dome for inner and outer walls exhibit an “M” shape with time, with two high-temperature cusps and one low-temperature cusp. The time of average temperature coincides with that of maximum wall temperature. During the flight, the wall pressure changes with time, exhibiting the characteristics of higher temperature at both ends of the flight and lower temperature in the middle. The structural temperature of the hypersonic aircraft is higher than that of the external flow behind the shock wave after 310 s. Therefore, this study provides a reliable reference for the preliminary design and parameter research of optical domes of hypersonic aircraft. Full article
(This article belongs to the Special Issue Transport Phenomena Studies for Renewable Energy Development)
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18 pages, 5940 KiB  
Article
Motion Characteristics of High-Speed Supercavitating Projectiles Including Structural Deformation
by Chuang Huang, Zhao Liu, Zixian Liu, Changle Hao, Daijin Li and Kai Luo
Energies 2022, 15(5), 1933; https://doi.org/10.3390/en15051933 - 7 Mar 2022
Cited by 12 | Viewed by 2596
Abstract
High-speed supercavitating projectiles receive tremendous hydrodynamic force when flying underwater in tail-slap mode, and have obvious structural deformation and structural vibration. To study the motion characteristics of high-speed supercavitating projectiles, a bidirectional fluid-structure interaction model was established, and validated by comparing with the [...] Read more.
High-speed supercavitating projectiles receive tremendous hydrodynamic force when flying underwater in tail-slap mode, and have obvious structural deformation and structural vibration. To study the motion characteristics of high-speed supercavitating projectiles, a bidirectional fluid-structure interaction model was established, and validated by comparing with the existing results. The motion, supercavitation flow field, and structural deformation response process of a supercavitating projectile were numerically investigated under the conditions of initial speed within 800–1600 m/s. It was found that the tail-slap motion of high-speed supercavitating projectiles is correlated with a high-frequency structural vibration. Further, the amplitude of the structural vibration increases with the initial speed. When flying with an initial speed higher than 1200 m/s, supercavitating projectiles encounter a great structural deformation under the action of the huge hydrodynamic load, which exerts a significant influence on the motion characteristic, and even destroys the trajectory stability. Thus, the supercavitating projectile cannot be regarded as a rigid body any more, and the structural response effect must be considered. Full article
(This article belongs to the Special Issue Transport Phenomena Studies for Renewable Energy Development)
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24 pages, 11369 KiB  
Article
Physics-Based Deep Learning for Flow Problems
by Yubiao Sun, Qiankun Sun and Kan Qin
Energies 2021, 14(22), 7760; https://doi.org/10.3390/en14227760 - 19 Nov 2021
Cited by 7 | Viewed by 4051
Abstract
It is the tradition for the fluid community to study fluid dynamics problems via numerical simulations such as finite-element, finite-difference and finite-volume methods. These approaches use various mesh techniques to discretize a complicated geometry and eventually convert governing equations into finite-dimensional algebraic systems. [...] Read more.
It is the tradition for the fluid community to study fluid dynamics problems via numerical simulations such as finite-element, finite-difference and finite-volume methods. These approaches use various mesh techniques to discretize a complicated geometry and eventually convert governing equations into finite-dimensional algebraic systems. To date, many attempts have been made by exploiting machine learning to solve flow problems. However, conventional data-driven machine learning algorithms require heavy inputs of large labeled data, which is computationally expensive for complex and multi-physics problems. In this paper, we proposed a data-free, physics-driven deep learning approach to solve various low-speed flow problems and demonstrated its robustness in generating reliable solutions. Instead of feeding neural networks large labeled data, we exploited the known physical laws and incorporated this physics into a neural network to relax the strict requirement of big data and improve prediction accuracy. The employed physics-informed neural networks (PINNs) provide a feasible and cheap alternative to approximate the solution of differential equations with specified initial and boundary conditions. Approximate solutions of physical equations can be obtained via the minimization of the customized objective function, which consists of residuals satisfying differential operators, the initial/boundary conditions as well as the mean-squared errors between predictions and target values. This new approach is data efficient and can greatly lower the computational cost for large and complex geometries. The capacity and generality of the proposed method have been assessed by solving various flow and transport problems, including the flow past cylinder, linear Poisson, heat conduction and the Taylor–Green vortex problem. Full article
(This article belongs to the Special Issue Transport Phenomena Studies for Renewable Energy Development)
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Review

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26 pages, 4496 KiB  
Review
Characterization of Wax Precipitation and Deposition Behavior of Condensate Oil in Wellbore: A Comprehensive Review of Modeling, Experiment, and Molecular Dynamics Simulation
by Yong Wang, Xiaoyu Liu, Zuonan Huang, Zhihua Wang and Yang Liu
Energies 2022, 15(11), 4018; https://doi.org/10.3390/en15114018 - 30 May 2022
Viewed by 3250
Abstract
Condensate oil is increasingly valued as the high-quality conventional hydrocarbon resources generally decline. The efficient development of condensate oil, however, has always been a world problem; massive condensate oil will be retained in reservoirs in case of improper exploitation process, resulting in a [...] Read more.
Condensate oil is increasingly valued as the high-quality conventional hydrocarbon resources generally decline. The efficient development of condensate oil, however, has always been a world problem; massive condensate oil will be retained in reservoirs in case of improper exploitation process, resulting in a significant resource waste and economic loss. One of the problems closely related to enhancing condensate oil recovery is wax precipitation and deposition in wellbore. Therefore, it is vital to investigate the characterization methods for the wax precipitation and deposition behavior in wellbores. The current status of research on modelling characterization methods, experimental characterization methods and molecular dynamics representation of wax precipitation and deposition behavior is reviewed in this paper; the applicability and limitation of modeling and experiment studies for characterizing wax precipitation and deposition of condensate oil in the wellbore are critically summarized and discussed. Moreover, the molecular dynamics simulation technique characterizes wax precipitation and deposition behavior from the micro scale, which makes up for the deficiencies of macroscopic experiment, enriches the investigation of wax precipitation and deposition, and provides important guidance and reference value for the development of unconventional hydrocarbon exploitation processes. Full article
(This article belongs to the Special Issue Transport Phenomena Studies for Renewable Energy Development)
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