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Recent Advances in Fluid Machinery, Energy Systems and Power Generation

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: Thermal Management".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 2854

Special Issue Editors


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Guest Editor
Department of Energy, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Interests: computational fluid dynamics; component interaction; gas turbine cooling; pumps and compressors; uncertainty quantification
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The goals set by the European Commission in terms of pollutant emission reduction by 2050 have led energy system designers to increase their efforts towards the deployment and adoption of greener technologies and innovative solutions. This is especially true for the power generation and propulsion fields, both of which highly contribute to NOx and CO2 emissions.

Within this context, the thermal management of energy systems plays a key role in increasing overall system efficiency and, conversely, decreasing pollutant emissions. Researchers’ efforts should hence be driven towards the accurate evaluation of metal temperatures by correctly estimating heat transfer and fluid flow. Newly designed experimental equipment and high-fidelity computational fluid dynamics represent fundamental tools to deal with such demanding outcomes. Furthermore, optimization methods based on artificial intelligence are now available to design complex components that can be realized by additive manufacturing and can guarantee high aero-thermal efficiency. It is also worth considering that the increasing usage of sustainable fuels and energy carriers (e.g., hydrogen) further complicates the situation due to the potential increase in NOx production.

For such reasons, the Guest Editors are inviting submissions to this Special Issue in Energies on the subject area of “Recent Advances in Fluid Machinery, Energy Systems and Power Generation”. Topics of interest for publication include, but are not limited to, the following:

  • Experimental analysis;
  • Computational fluid dynamics;
  • Thermal management;
  • Power generation;
  • Turbomachinery;
  • Hybrid engines;
  • Turbine cooling;
  • Hydrogen combustion;
  • Optimization methods.

Dr. Daniela Anna Misul
Dr. Simone Salvadori
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

  • experimental analysis
  • computational fluid dynamics
  • thermal management
  • power generation
  • turbomachinery
  • hybrid engines
  • turbine cooling
  • hydrogen combustion
  • optimization methods

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Published Papers (3 papers)

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Research

21 pages, 4270 KiB  
Article
Shape Optimization of a Diffusive High-Pressure Turbine Vane Using Machine Learning Tools
by Rosario Nastasi, Giovanni Labrini, Simone Salvadori and Daniela Anna Misul
Energies 2024, 17(22), 5642; https://doi.org/10.3390/en17225642 - 11 Nov 2024
Viewed by 780
Abstract
Machine learning tools represent a key methodology for the shape optimization of complex geometries in the turbomachinery field. One of the current challenges is to redesign High-Pressure Turbine (HPT) stages to couple them with innovative combustion technologies. In fact, recent developments in the [...] Read more.
Machine learning tools represent a key methodology for the shape optimization of complex geometries in the turbomachinery field. One of the current challenges is to redesign High-Pressure Turbine (HPT) stages to couple them with innovative combustion technologies. In fact, recent developments in the gas turbine field have led to the introduction of pioneering solutions such as Rotating Detonation Combustors (RDCs) aimed at improving the overall efficiency of the thermodynamic cycle at low overall pressure ratios. In this study, a HPT vane equipped with diffusive endwalls is optimized to allow for ingesting a high-subsonic flow (Ma=0.6) delivered by a RDC. The main purpose of this paper is to investigate the prediction ability of machine learning tools in case of multiple input parameters and different objective functions. Moreover, the model predictions are used to identify the optimal solutions in terms of vane efficiency and operating conditions. A new solution that combines optimal vane efficiency with target values for both the exit flow angle and the inlet Mach number is also presented. The impact of the newly designed geometrical features on the development of secondary flows is analyzed through numerical simulations. The optimized geometry achieved strong mitigation of the intensity of the secondary flows induced by the main flow separation from the diffusive endwalls. As a consequence, the overall vane aerodynamic efficiency increased with respect to the baseline design. Full article
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19 pages, 6987 KiB  
Article
On the Flow in the Gap between Corotating Disks of Tesla Turbine with Different Supply Configurations: A Numerical Study
by Mohammadsadegh Pahlavanzadeh, Włodzimierz Wróblewski and Krzysztof Rusin
Energies 2024, 17(17), 4472; https://doi.org/10.3390/en17174472 - 6 Sep 2024
Viewed by 588
Abstract
Momentum diffusion and kinetic energy transfer in turbomachinery have always been significant issues, with a considerable impact on the performance of the bladeless Tesla turbine. This radial turbine shows high potential for various energy applications, such as Organic Rankine Cycle or combined heat [...] Read more.
Momentum diffusion and kinetic energy transfer in turbomachinery have always been significant issues, with a considerable impact on the performance of the bladeless Tesla turbine. This radial turbine shows high potential for various energy applications, such as Organic Rankine Cycle or combined heat and power systems. Analyzing the flow inside the gap between the corotating disks of the Tesla turbine presents challenges due to several factors, including submillimeter length scales, variations in flow cross-section, interactions of body forces arising from rotation with turbulence, interactions between the turbine’s inlet nozzles and rotor, and moving walls. General design parameters, e.g., number of nozzles, also pose a challenge in order to achieve the full potential of this turbine. In this research, two different variants of the supply system are considered with six and forty nozzles. To minimize computational expenses, a portion of the entire domain is considered. The flow in each domain, consisting of one inlet nozzle and a segment of one gap between the disks, is examined to reveal the complexity of flow structures and their impact on the Tesla turbine performance. Large Eddy Simulation (LES) with the Smagorinsky subgrid-scale model is used to verify the results of the k-ω Shear-Stress Transport (SST) turbulence model in the first case study with six nozzles. Analyzing the results indicates that the k-ω SST model provides valuable insights with appropriate accuracy. The second case study, with forty nozzles, is simulated using the k-ω SST turbulence model. The research compares flow structure, flow parameters, and their impact on the system’s performance. From the comparison between the k-ω SST turbulence model and LES simulation, it was observed that although the k-ω SST model slightly overestimates the general parameters and damps fluctuations, it still provides valuable insights for assessing flow structures. Additionally, the mesh strategy is described, as the LES requirements make this simulation computationally expensive and time-consuming. The overall benefits of this method are discussed. Full article
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15 pages, 2755 KiB  
Article
Numerical Investigation and Simulation of Hydrogen Blending into Natural Gas Combustion
by Laura Jung, Alexander Mages and Alexander Sauer
Energies 2024, 17(15), 3819; https://doi.org/10.3390/en17153819 - 2 Aug 2024
Viewed by 1159
Abstract
This study reviews existing simulation models and describes a selected model for analysing combustion dynamics in hydrogen and natural gas mixtures, specifically within non-ferrous melting furnaces. The primary objectives are to compare the combustion characteristics of these two energy carriers and assess the [...] Read more.
This study reviews existing simulation models and describes a selected model for analysing combustion dynamics in hydrogen and natural gas mixtures, specifically within non-ferrous melting furnaces. The primary objectives are to compare the combustion characteristics of these two energy carriers and assess the impact of hydrogen integration on furnace operation and efficiency. Using computational fluid dynamics (CFD) simulations, incorporating actual furnace geometries and a detailed combustion and NOx emission prediction model, this research aims to accurately quantify the effects of hydrogen blending. Experimental tests on furnaces using only natural gas confirmed the validity of these simulations. By providing precise predictions for temperature distribution and NOx emissions, this approach reduces the need for extensive laboratory testing, facilitates broader exploration of design modifications, accelerates the design process, and ultimately lowers product development costs. Full article
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