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Authors = Roberto Pacciani ORCID = 0000-0002-7242-0480

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14 pages, 2724 KiB  
Article
Predicting the Impact of Compressor Flexibility Improvements on Heavy-Duty Gas Turbines for Minimum and Base Load Conditions
by Martina Ricci, Marcello Benvenuto, Stefano Gino Mosele, Roberto Pacciani and Michele Marconcini
Energies 2022, 15(20), 7546; https://doi.org/10.3390/en15207546 - 13 Oct 2022
Cited by 3 | Viewed by 2869
Abstract
The increasing importance of renewable energy capacity in the power generation scenario, together with the fluctuating consumer energy demand, forces conventional fossil fuel power generation systems to promptly respond to relevant and rapid load variations and to operate under off-design conditions during a [...] Read more.
The increasing importance of renewable energy capacity in the power generation scenario, together with the fluctuating consumer energy demand, forces conventional fossil fuel power generation systems to promptly respond to relevant and rapid load variations and to operate under off-design conditions during a major fraction of their lives. In order to improve existing power plants’ flexibility in facing energy surplus or deficit, retrofittable solutions for gas turbine compressors are proposed. In this paper, two different operation strategies, variable inlet guide vanes (IGVs) and blow-off extraction (BO), are considered for enabling partial load and minimum environmental load operation, and thus to identify implementation opportunities in existing thermal power plants. A typical 15-stage F-class gas turbine compressor is chosen as a test case and some energy demand scenarios are selected to validate the adopted solutions. The results of an extensive 3D, steady, CFD analysis are compared with the measurements coming from an experimental campaign carried out in the framework of the European Turbo-Reflex project. It will be shown how the combined strategies can reduce gas turbine mass flow rate and power plant output, without significantly penalizing efficiency, and how such off-design performance figures can be reliably predicted by employing state-of-the-art CFD models. Full article
(This article belongs to the Special Issue Computational Fluid Dynamics in Gas Turbines)
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11 pages, 1555 KiB  
Article
Retrofittable Solutions Capability for Gas Turbine Compressors
by Martina Ricci, Stefano Gino Mosele, Marcello Benvenuto, Pio Astrua, Roberto Pacciani and Michele Marconcini
Int. J. Turbomach. Propuls. Power 2022, 7(1), 3; https://doi.org/10.3390/ijtpp7010003 - 11 Jan 2022
Cited by 5 | Viewed by 4499
Abstract
The increasing introduction of renewable energy capacity has changed the perspective on the operation of conventional power plants, introducing the necessity of reaching extreme off-design conditions. There is a strong interest in the development and optimization of technologies that can be retrofitted to [...] Read more.
The increasing introduction of renewable energy capacity has changed the perspective on the operation of conventional power plants, introducing the necessity of reaching extreme off-design conditions. There is a strong interest in the development and optimization of technologies that can be retrofitted to an existing power plant to enhance flexibility as well as increase performance and lower emissions. Under the framework of the European project TURBO-REFLEX, a typical F-class gas turbine compressor designed and manufactured by Ansaldo Energia has been studied. Numerical analyses were performed using the TRAF code, which is a state-of-the-art 3D CFD RANS/URANS flow solver. In order to assess the feasibility of lower minimum environmental load operation, by utilizing a reduction in the compressor outlet mass-flow rate, with a safe stability margin, two different solutions have been analyzed: blow-off extractions and extra-closure of Variable Inlet Guide Vanes. The numerical steady-state results are compared and discussed in relation to an experimental campaign, which was performed by Ansaldo Energia. The purpose is to identify the feasibility of the technologies and implementation opportunity in the existing thermal power plant fleet. Full article
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17 pages, 1504 KiB  
Article
Assessment of Machine-Learned Turbulence Models Trained for Improved Wake-Mixing in Low-Pressure Turbine Flows
by Roberto Pacciani, Michele Marconcini, Francesco Bertini, Simone Rosa Taddei, Ennio Spano, Yaomin Zhao, Harshal D. Akolekar, Richard D. Sandberg and Andrea Arnone
Energies 2021, 14(24), 8327; https://doi.org/10.3390/en14248327 - 10 Dec 2021
Cited by 16 | Viewed by 3490
Abstract
This paper presents an assessment of machine-learned turbulence closures, trained for improving wake-mixing prediction, in the context of LPT flows. To this end, a three-dimensional cascade of industrial relevance, representative of modern LPT bladings, was analyzed, using a state-of-the-art RANS approach, over a [...] Read more.
This paper presents an assessment of machine-learned turbulence closures, trained for improving wake-mixing prediction, in the context of LPT flows. To this end, a three-dimensional cascade of industrial relevance, representative of modern LPT bladings, was analyzed, using a state-of-the-art RANS approach, over a wide range of Reynolds numbers. To ensure that the wake originates from correctly reproduced blade boundary-layers, preliminary analyses were carried out to check for the impact of transition closures, and the best-performing numerical setup was identified. Two different machine-learned closures were considered. They were applied in a prescribed region downstream of the blade trailing edge, excluding the endwall boundary layers. A sensitivity analysis to the distance from the trailing edge at which they are activated is presented in order to assess their applicability to the whole wake affected portion of the computational domain and outside the training region. It is shown how the best-performing closure can provide results in very good agreement with the experimental data in terms of wake loss profiles, with substantial improvements relative to traditional turbulence models. The discussed analysis also provides guidelines for defining an automated zonal application of turbulence closures trained for wake-mixing predictions. Full article
(This article belongs to the Special Issue Transition/Turbulence Models for Turbomachinery Applications)
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17 pages, 1512 KiB  
Article
Transition Modeling for Low Pressure Turbines Using Computational Fluid Dynamics Driven Machine Learning
by Harshal D. Akolekar, Fabian Waschkowski, Yaomin Zhao, Roberto Pacciani and Richard D. Sandberg
Energies 2021, 14(15), 4680; https://doi.org/10.3390/en14154680 - 1 Aug 2021
Cited by 34 | Viewed by 3346
Abstract
Existing Reynolds Averaged Navier–Stokes-based transition models do not accurately predict separation induced transition for low pressure turbines. Therefore, in this paper, a novel framework based on computational fluids dynamics (CFD) driven machine learning coupled with multi-expression and multi-objective optimization is explored to develop [...] Read more.
Existing Reynolds Averaged Navier–Stokes-based transition models do not accurately predict separation induced transition for low pressure turbines. Therefore, in this paper, a novel framework based on computational fluids dynamics (CFD) driven machine learning coupled with multi-expression and multi-objective optimization is explored to develop models which can improve the transition prediction for the T106A low pressure turbine at an isentropic exit Reynolds number of Re2is=100,000. Model formulations are proposed for the transfer and laminar eddy viscosity terms of the laminar kinetic energy transition model using seven non-dimensional pi groups. The multi-objective optimization approach makes use of cost functions based on the suction-side wall-shear stress and the pressure coefficient. A family of solutions is thus developed, whose performance is assessed using Pareto analysis and in terms of physical characteristics of separated-flow transition. Two models are found which bring the wall-shear stress profile in the separated region at least two times closer to the reference high-fidelity data than the baseline transition model. As these models are able to accurately predict the flow coming off the blade trailing edge, they are also able to significantly enhance the wake-mixing prediction over the baseline model. This is the first known study which makes use of ‘CFD-driven’ machine learning to enhance the transition prediction for a non-canonical flow. Full article
(This article belongs to the Special Issue Transition/Turbulence Models for Turbomachinery Applications)
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21 pages, 5296 KiB  
Article
Validation of a Modal Work Approach for Forced Response Analysis of Bladed Disks
by Lorenzo Pinelli, Francesco Lori, Michele Marconcini, Roberto Pacciani and Andrea Arnone
Appl. Sci. 2021, 11(12), 5437; https://doi.org/10.3390/app11125437 - 11 Jun 2021
Cited by 19 | Viewed by 4970
Abstract
The paper describes a numerical method based on a modal work approach to evaluate the forced response of bladed disks and its validation against numerical results obtained by a commercial FEM code. Forcing functions caused by rotor–stator interactions are extracted from CFD unsteady [...] Read more.
The paper describes a numerical method based on a modal work approach to evaluate the forced response of bladed disks and its validation against numerical results obtained by a commercial FEM code. Forcing functions caused by rotor–stator interactions are extracted from CFD unsteady solutions properly decomposed in time and space to separate the spinning perturbation acting on the bladed disk in a cyclic environment. The method was firstly applied on a dummy test case with cyclic symmetry where the forcing function distributions were arbitrarily selected: comparisons for resonance and out of resonance conditions revealed an excellent agreement between the two numerical methods. Finally, the validation was extended to a more realistic test case representative of a low-pressure turbine bladed rotor subjected to the wakes of two upstream rows: an IGV with low blade count and a stator row. The results show a good agreement and suggest computing the forced response problem on the finer CFD blade surface grid to achieve a better accuracy. The successful validation of the method, closely linked to the CFD environment, creates the opportunity to include the tool in an integrated multi-objective procedure able to account for aeromechanical aspects. Full article
(This article belongs to the Special Issue Bladed Disks Structural Dynamics)
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12 pages, 1718 KiB  
Article
A CFD-Based Throughflow Method with Three-Dimensional Flow Features Modelling
by Roberto Pacciani, Michele Marconcini and Andrea Arnone
Int. J. Turbomach. Propuls. Power 2017, 2(3), 11; https://doi.org/10.3390/ijtpp2030011 - 24 Jun 2017
Cited by 15 | Viewed by 6188
Abstract
The paper describes the development and validation of a novel computational fluid dynamics (CFD)-based throughflow model. It is based on the axisymmetric Euler equations with tangential blockage and body forces and inherits its numerical scheme from a state-of-the-art CFD solver (TRAF code). Secondary [...] Read more.
The paper describes the development and validation of a novel computational fluid dynamics (CFD)-based throughflow model. It is based on the axisymmetric Euler equations with tangential blockage and body forces and inherits its numerical scheme from a state-of-the-art CFD solver (TRAF code). Secondary and tip leakage flow features are modelled in terms of Lamb–Oseen vortices and a body force field. Source and sink terms in the governing equations are employed to model tip leakage flow effects. A realistic distribution of entropy in the meridional and spanwise directions is proposed in order to compute dissipative forces on the basis of a distributed loss model. The applications are mainly focused on turbine configurations. First, a validation of the secondary flow modelling is carried out by analyzing a linear cascade based on the T106 blade section. Then, the throughflow procedure is used to analyze the transonic CT3 turbine stage studied in the framework of the TATEF2 (Turbine Aero-Thermal External Flows) European program. The performance of the method is evaluated by comparing predicted operating characteristics and spanwise distributions of flow quantities with experimental data. Full article
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