Special Issue "Advancements in Multiphase Fluid Dynamics in Energy and Propulsion Systems"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: 30 November 2021.

Special Issue Editors

Prof. Dr. Luis Bravo
E-Mail Website
Guest Editor
U.S. Army Research Laboratory, 6340 Rodman Road, Aberdeen Proving Groud, MD, USA
Interests: spray breakup; chemically reacting flows; particle-laden turbulence; high performance computing
Dr. Anindya Ghoshal
E-Mail Website
Guest Editor
U.S. Army Research Laboratory, 6340 Rodman Road, Aberdeen Proving Groud, MD, USA
Interests: Turbomachinery Sciences; Propulsion Materials; Material State Awareness; Prognostics and Diagnostics; Sensors.
Dr. Michael J. Walock
E-Mail Website
Guest Editor
U.S. Army Research Laboratory, 6340 Rodman Road, Aberdeen Proving Groud, MD, USA
Interests: molecular dynamics; tribo-corrosion; thin films/coatings growth; materials characterization

Special Issue Information

Dear Colleagues,

Multiphase turbulence plays a fundamental role in a remarkably broad range of both engineering and basic science applications. Notable examples range from fuel spray modeling to particulate (sand/salt/ash) entrainment in gas turbine engines, to adhesion and tribocorrosion in materials, to name a few. One of the most important features is the presence of a very wide spectrum of length scales and timescales associated with the phase–interphase, smallest (particle) motions, as well as the anisotropic turbulence structures in confined environments. Despite the significant increase in the body of research in multiphase flows, the understanding of the underlying physics remains incomplete and poses one of the grand challenges in fluid dynamics.

Establishing a predictive understanding in multiphase turbulence requires an integrated computational, theoretical, and experimental approach able to provide validated models and useful insights of the governing physics. Recent advancements in supercomputing power and algorithms now provide the ability to investigate a wide range of high dimensional unsteady multiscale problems that have historically remained inaccessible to laboratory experiments. These have set the stage for the emergence of high-fidelity computational tools, which open the possibility for first-principle modeling of multiphase turbulence and will be crucial towards the design of future very powerful, high-efficiency, and cleaner propulsion systems. 

This Special Issue seeks multidisciplinary scientific contributions in areas encompassing computational, experimental, or theoretical research that advance the understanding of multiphase turbulence. Topics of interest include (but are not limited to) spray breakup, dispersed flows, shocked flows, fluid structure interactions, cluster-induced turbulence, particle–wall interactions, deposition, and chemically reacting flows. We therefore invite original papers on basic scientific research, innovative technical developments, state-of-the-art reviews, and analytical studies, which are relevant to aerospace and propulsion sciences.

Prof. Dr. Luis Bravo

Dr. Anindya Ghoshal

Dr. Michael J. Walock
Guest Editor

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 papers will be 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 2000 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

  • Computational fluid dynamics
  • multiphase flows
  • turbulence
  • shocks
  • deposition
  • particle-wall interactions

Published Papers (6 papers)

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Article
Massively Parallel Large Eddy Simulation of Rotating Turbomachinery for Variable Speed Gas Turbine Engine Operation
Energies 2020, 13(3), 703; https://doi.org/10.3390/en13030703 - 06 Feb 2020
Cited by 3 | Viewed by 791
Abstract
Gas turbine engines are required to operate at both design and off-design conditions that can lead to strongly unsteady flow-fields and aerodynamic losses severely impacting performance. Addressing this problem requires effective use of computational fluid dynamics tools and emerging models that resolve the [...] Read more.
Gas turbine engines are required to operate at both design and off-design conditions that can lead to strongly unsteady flow-fields and aerodynamic losses severely impacting performance. Addressing this problem requires effective use of computational fluid dynamics tools and emerging models that resolve the large scale fields in detail while accurately modeling the under-resolved scale dynamics. The objective of the current study is to conduct massively parallel large eddy simulations (LES) of rotating turbomachinery that handle the near-wall dynamics using accurate wall models at relevant operating conditions. The finite volume compressible CharLES solver was employed to conduct the simulations over moving grids generated through Voronoi-based unstructured cells. A grid sensitivity analysis was carried out first to establish reliable parameters and assess the quality of the results. LES simulations were then conducted to understand the impact of blade tip clearance and operating conditions on the stage performance. Variations in tip clearance of 3% and 16% chord were considered in the analysis. Other design points included operation at 100% rotor speed and off-design conditions at 75% and 50% of the rotor speed. The simulation results showed that the adiabatic efficiency improves dramatically with reduction in tip gap due to the decrease in tip leakage flow and the resulting flow structures. The analysis also showed that the internal flow becomes highly unsteady, undergoing massive separation, as the rotor speed deviates from the design point. This study demonstrates the capability of the framework to simulate highly turbulent unsteady flows in a rotating turbomachinery environment. The results provide much needed insight and massive data to investigate novel design concepts for the US Army Future Vertical Lift program. Full article
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Article
Smoothed Particle Hydrodynamics Simulation of High Velocity Impact Dynamics of Molten Sand Particles
Energies 2020, 13(19), 5134; https://doi.org/10.3390/en13195134 - 02 Oct 2020
Cited by 3 | Viewed by 550
Abstract
Sand ingestion is highly detrimental for gas turbines because it leads to erosion and corrosion of engine components, accelerating material fatigue and contributing to global engine failure. In this paper the high velocity impact of a molten sand particle onto a solid wall [...] Read more.
Sand ingestion is highly detrimental for gas turbines because it leads to erosion and corrosion of engine components, accelerating material fatigue and contributing to global engine failure. In this paper the high velocity impact of a molten sand particle onto a solid wall is investigated by means of the Smoothed Particles Hydrodynamics method where the three phases are taken into account. Nominal conditions are a 25 μm particle composed of molten sand (dynamic viscosity μl=11 Pa·s) impacting the wall at a velocity of 250 m/s. The influence of different parameters are explored such as the mechanical properties of the molten sand particle (density, viscosity, surface tension), the impact conditions (velocity magnitude, particle size and angle of impact) as well as the particle shape (sphere or cube with different geometrical features impacting the wall). It is found that the particles do not form a lamella during the impact but mostly conserve its initial shape. It is also confirmed that sharp features such as edges lead to a larger normal pressure at the impact location. Correlations to quantify (i) the spread factor, (ii) the maximum and mean impact force and impact pressure and (iii) the slip distance are derived for the first time based on the investigated parameters. The importance of these correlations is that they provide information needed to implement low-order models for studying impact and deposition of molten sand in engineering simulations. Full article
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Article
Embedded Temperature Sensor Evaluations for Turbomachinery Component Health Monitoring
Energies 2021, 14(4), 852; https://doi.org/10.3390/en14040852 - 06 Feb 2021
Viewed by 459
Abstract
Current rotorcraft gas turbine engines typically use titanium alloys and steel for the compressor section and single-crystal nickel superalloys for the hot-section turbine stator vanes and rotor blades. However, these material selections are rapidly changing due to increased requirements of power-density and efficiency. [...] Read more.
Current rotorcraft gas turbine engines typically use titanium alloys and steel for the compressor section and single-crystal nickel superalloys for the hot-section turbine stator vanes and rotor blades. However, these material selections are rapidly changing due to increased requirements of power-density and efficiency. Future U.S. Army gas turbine engines will be using ceramic matrix composites for many high temperature engine components due to their low density and improved durability in high temperature environments. The gas turbine industry is also actively developing adaptive concept technologies for production and assembly of modular gas turbine engine components with integrated sensing. In order to actively monitor engine components for extended seamless operation and improved reliability, it is essential to have intelligent embedded sensing to monitor the health of critical components in engines. Under this U.S. Army Foreign Technology Assessment Support (FTAS) program funded research project, embedded fiber-optic temperature sensors from U.K.-based company, Epsilon Optics Ltd (Fordingbridge, UK)., were experimentally evaluated to measure temperature responses on typical turbomachinery component material coupons. The temperature responses from this foreign technology sensor were assessed using a thermomechanical fatigue tester with a built-in furnace to conduct thermal cycling durability experiments. The experimental results obtained from the durability performance of this embedded fiber Bragg sensor are reported in this paper. This sensor technology, upon maturation to higher TRL (technology readiness level), can greatly reduce the lifecycle cost of future U.S. Army gas turbine engines. Full article
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Article
Design Space Exploration of Turbulent Multiphase Flows Using Machine Learning-Based Surrogate Model
Energies 2020, 13(17), 4565; https://doi.org/10.3390/en13174565 - 03 Sep 2020
Cited by 2 | Viewed by 775
Abstract
This study focuses on establishing a surrogate model based on machine learning techniques to predict the time-averaged spatially distributed behaviors of vaporizing liquid jets in turbulent air crossflow for momentum flux ratios between 5 and 120. This surrogate model extends a previously developed [...] Read more.
This study focuses on establishing a surrogate model based on machine learning techniques to predict the time-averaged spatially distributed behaviors of vaporizing liquid jets in turbulent air crossflow for momentum flux ratios between 5 and 120. This surrogate model extends a previously developed Gaussian-process-based framework applicable to laminar flows to accommodate turbulent flows and demonstrates that in addition to detailed fields of primitive variables, second-order turbulence statistics can also be predicted using machine learning techniques. The framework proceeds in 3 steps—(1) design of experiment studies to identify training points and conducting high-fidelity calculations to build the training dataset; (2) Gaussian process regression (supervised training) for the range of operating conditions under consideration for gaseous and dispersed phase quantities; and (3) error quantification of the surrogate model by comparing the machine learning predictions with the truth model for test conditions (i.e., conditions not used for training). The framework was trained using data generated by high-fidelity large eddy simulation (LES)-based calculations (also referred to as the truth model), which solves the complete set of conservation equations for mass, momentum, energy, and species in an Eulerian reference frame, coupled with a Lagrangian solver that tracks the dispersed phase. Simulations were conducted for the range of momentum flux ratios between 5 and 120 for liquid water injected into crossflowing air at a pressure of 1 atm and temperature of 600 K. Results from the machine-learned surrogate model, also called emulations, were compared with the truth model under testing conditions identified by momentum flux ratios of 7 and 40. L1 errors for time-averaged field quantities, including velocity magnitudes, pressure, temperature, vapor fraction of the evaporated liquid, and turbulent kinetic energy in the gas phase, and spray penetration and Sauter mean diameters in the dispersed phase are reported. Speedup of 65 was achieved with this emulator when compared against LES simulation of the same test conditions with errors for all quantities below 14%, thus demonstrating the potential benefits of using machine learning techniques for design space exploration of devices that are based on turbulent multiphase fluid flows. This is the first effort of its kind in the literature that demonstrates the application of machine learning techniques on turbulent multiphase flows. Full article
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Article
Optimizing Gas Turbine Performance Using the Surrogate Management Framework and High-Fidelity Flow Modeling
Energies 2020, 13(17), 4283; https://doi.org/10.3390/en13174283 - 19 Aug 2020
Cited by 3 | Viewed by 910
Abstract
This work couples high-fidelity moving-domain finite element compressible flow modeling with a Surrogate Management Framework (SMF) for optimization to effectively design a variable speed gas turbine stage. The superior accuracy of high-fidelity modeling, however, comes with relatively high computational costs, which are further [...] Read more.
This work couples high-fidelity moving-domain finite element compressible flow modeling with a Surrogate Management Framework (SMF) for optimization to effectively design a variable speed gas turbine stage. The superior accuracy of high-fidelity modeling, however, comes with relatively high computational costs, which are further amplified in the iterative design process that relies on parametric sweeps. An innovative approach is developed to reduce the number of iterations needed for optimal design, leading to a significant reduction in the computational cost without sacrificing the high fidelity of the analysis. The proposed design optimization approach is applied to a novel incidence-tolerant turbomachinery blade technology that articulates the stator- and rotor-blade positions of an annular single-stage high pressure turbine to achieve peak performance. This work also extends our understanding of rotor–stator interactions by simulating complex internal flows occurring during multi-speed turbine operation. Potential variable-speed gas turbine stage designs and the proposed optimization approach are presented to provide valuable insight into this new turbomachinery technology that can positively impact future propulsion systems. Full article
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Article
Experimental Investigations on the Inner Flow Behavior of Centrifugal Pumps under Inlet Air-Water Two-Phase Conditions
Energies 2019, 12(22), 4377; https://doi.org/10.3390/en12224377 - 17 Nov 2019
Cited by 7 | Viewed by 844
Abstract
Centrifugal pumps are widely used and are known to be sensitive to inlet air-water two-phase flow conditions. The pump performance degradation mainly depends on the changes in the two-phase flow behavior inside the pump. In the present paper, experimental overall pump performance tests [...] Read more.
Centrifugal pumps are widely used and are known to be sensitive to inlet air-water two-phase flow conditions. The pump performance degradation mainly depends on the changes in the two-phase flow behavior inside the pump. In the present paper, experimental overall pump performance tests were performed for two different rotational speeds and several inlet air void fractions (αi) up to pump shut-off condition. Visualizations were also performed on the flow patterns of a whole impeller passage and the volute tongue area to physically understand pump performance degradation. The results showed that liquid flow modification does not follow head modification as described by affinity laws, which are only valid for homogeneous bubbly flow regimes. Three-dimensional effects were more pronounced when inlet void fraction increased up to 3%. Bubbly flow with low mean velocities were observed close to the volute tongue for all αi, and returned back to the impeller blade passages. The starting point of pump break down was related to a strong inward reverse flow that occurred in the vicinity of the shroud gap between the impeller and volute tongue area. Full article
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