bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detailed Sliding-Mesh Computation of Turbulent Jet Ignition and Combustion in a Wave Rotor Combustor With Stationary Pre-Chamber
Authors: Yinusa Rasheed K. , Nalim Mohamed Razi 
Published: August 2024

Abstract
Computational fluid dynamic and chemical simulation is used to investigate the ignition and combustion processes in a pior experimental wave rotor combustor that used a stationary pre-combustion chamber to produce a traversing hot reactive jet or torch for rapid ignition in the wave rotor. The traversing jet delivers reactive hot gas into a premixed ethylene-air mixture in a constant volume combustor from a continuous-flow prechamber torch igniter positioned at a fixed location adjacent to one end of the wave rotor with a clearance gap. This finite-volume fluid dynamics and combustion simulation consider three channels of the wave rotor, with combustion simulated fully in one channel, to optimize computational cost while closely mimicking the traversing jet motion and subsequent ignition and combustion processes using a transient Reynolds Averaged Navier-Stokes two-equation eddy-viscosity turbulence model with detailed chemistry mechanism with 81 species and 573 reactions. The simulation begins at a point in the wave rotor cycle when the channel contains an unburnt uniform mixture with substantial and varied residual turbulence. The pressure rise, flame travel, and heat release rates predicted are compared with experimental data previously collected from a highly instrumented wave rotor constant volume combustor rig. Experimental conditions that had not been measured, but which may affect its combustion processes include turbulent kinetic energy and turbulence scales of the mixture prior to ignition, and the level of active radicals in the traversing hot jet. The pre-chamber combustion model is manipulated to understand how dosing of free radical species enhances localized ignition initiation and affects overall fuel burn. The initial turbulent properties were varied to understand the sensitivity of combustion to turbulence as the flame propagates away from the initial ignition jet zone. These findings advance the understanding of a demonstrated wave rotor combustor with potential to revolutionize gas turbine engine technology.
Effect of Transverse Acoustic Excitation Over a Partially-Premixed Swirling Flame
Authors: Gupta Ravi , Bohrey Aayushi , Panda Pratikash 
Published: August 2024

Abstract
In this work, we investigate the effect of transverse acoustic excitation on a partially premixed swirling flame. Azimuthal instabilities in annular gas turbine combustors are one of the major challenges. Thermoacoustic instabilities are driven by azimuthal acoustic modes. We have designed and fabricated a multi-nozzle linear array combustor to simulate the flow conditions of an annular combustor. The nozzle features an axial swirler with a centerbody acting as a fuel injector. Simultaneous high-speed chemiluminescence (OH*) and high-frequency pressure measurements are conducted to measure the time-averaged flame shape and the chamber acoustics respectively. These measurements are taken at multiple forcing frequencies and amplitude under in-phase (IP) and out-of-phase (OP) conditions. It is observed that, at one of the combustor modes (580Hz), during OP forcing, the flame transitions from a V-shape to an M-shape as the forcing amplitude is increased. However, with IP forcing the flame continues to remain in V-shape with the increase in forcing amplitude. Spectral proper orthogonal decomposition (SPOD) analysis of OH* images show that for OP forcing dominant mode shapes are present mostly at 0.5D away from the center-line, but for IP forcing the dominant mode shapes indicate combined axial and radial oscillations in the OH* intensity field. Furthermore, cross-wavelet transform (XWT) analysis shows a strong correlation between pressure fluctuations and OH* fluctuations around the forcing frequency for IP forcing, and a weak or intermittent correlation for OP forcing. Based on the acoustic simulation, instantaneous time snapshots of OH* chemiluminescence and existing literature, we hypothesize that the transition from V-shape to M-shape can be due to acoustically induced velocity and vortical fluctuations near burner lip during OP forcing. This causes the V-flame to stretch, roll outward, and stabilize in the outer recirculation zone (ORZ).
Rotor Design of Heavy-Duty Gas Turbines for Power Generation: A Comparative Analysis for Transition to Net Zero Emission Target
Authors: Ugel Diego , Olmes Sven , Cassinelli Claudio , Goerzer Michael , Ivkovic Sinisa , Winge Torsten , Bordo Luca 
Published: August 2024

Abstract
Current scenarios towards net zero emission assume an increasing demand for peaking operation of installed and new heavy-duty gas turbines for power generation, resulting in raising targets for transient behaviors of gas turbine rotors.
During the design development process cyclic damaging mechanisms related to centrifugal and thermal loads, as well as rotordynamic effects leading to high vibration and associated high-cycle fatigue mechanisms are mandatorily considered, accounting for potential aging effects taking place during the engine life. Additionally, rotor deformation due centrifugal and thermal loads are analyzed in detail to achieve the best rotor-casing clearance conditions, aiming to maximize engine performance and availability.
To satisfy the same set of functions and requirements different OEMs offer since decades alternative architectural layouts, stemming from both identified technical solutions and historical heritage. These existing layouts are compared in some publications, mostly focusing on baseload steady-state stress and idealized warm-up and cool-down considerations.
In this paper the two main families of existing rotor designs, namely bolted and welded, are analyzed and compared, on the basis of two F-Class engines in the portfolio of Ansaldo Energia. With a specific attention to transient effects from real operating cycles relevant for flexibility demand, the paper shows insights about design, clearance, lifetime management and extension.
The performed analysis highlights the key differentiators of the two fundamental rotor architectures that Ansaldo Energia is maintaining in its technology portfolio.
Numerical vs Experimental Investigation on Fuel Gas Leak Dispersion in a Real Scale GT Enclosure
Authors: Lucherini Gabriele , De Leo Elena , Minotti Stefano , Presotto Valentina , Singh Rajnish Kumar , Raju Susila Jegan Vishnu 
Published: August 2024

Abstract
Fuel gas leak is a possible scenario that could occur inside a gas turbine (GT) enclosure due to the large number of connections in the fuel gas supply line. Forced ventilation and gas detection systems are used as main mitigations to guarantee an acceptable level of safety. While the ventilation air promotes the dilution below the flammable range of any fuel gas release, the gas detectors monitor the concentrations levels and trigger corrective actions anticipating hazard scenarios. The combined design of these two systems is based on the use of CFD analyses as predictive tool according to guidelines given by ISO 21789.
The introduction of hydrogen as fuel for gas turbines makes this design more critical for all its characteristics such as reactiveness and large range of flammability. This leads to an intrinsic higher risk of ignition in case of leakage respect to other conventional fuels like natural gas.
In this context, it is fundamental to build reliable and robust computational models for the prediction of fuel gas dispersion inside a complex geometry with forced ventilation flow like a gas turbine package. For this purpose, experimental data of a fuel gas leakage inside a real scale GT enclosure would be needed to tune and validate such numerical models. Since up to now this kind of data is not available in literature, an experimental campaign on NovaLT16 100% H2 package was executed to create a real reference for CFD simulations. Hydrogen is rarely utilized in full scale tests for obvious safety concerns, thus methane was chosen to be released reproducing a real operating scenario. The same set up was replicated with CFD analyses and the results were finally compared.
SCADA-Based Long-Term Wind Turbine Performance Degradation Analysis Based on Deep Learning Techniques
Authors: Peng Dandan , Terzi Ludovico , Desmet Wim , Gryllias Konstantinos 
Published: August 2024

Abstract
In the context of the rapid development of wind energy as a renewable resource, ensuring effective monitoring and maintenance of wind turbines is increasingly important. Despite the large volume of data collected by Supervisory Control and Data Acquisition (SCADA) systems, extracting key feature information to construct successful condition monitoring models remains a complex and challenging task. This study introduces a deep learning approach, called Convolutional Neural Network-based Support Vector Data Description (CNN-SVDD), aiming at effectively monitoring the long-term health status of wind turbines and providing timely warning for potential faults. The method employs Convolutional Neural Network (CNN) to deeply analyze time-series features and the correlations between sensors from SCADA data, capable of overcoming the challenges posed by environmental noise and changes in operational conditions. Subsequently, within the deep feature space learned by CNN, the SVDD classifier constructs a soft-boundary hypersphere. It allows for some samples to reside outside the hypersphere, thereby enhancing robustness against potential outliers in the SCADA data. Notably, the optimization processes of CNN and SVDD are linked, forming together an end-to-end process. The anomaly score generated by SVDD may act as an intelligent health indicator for assessing long-term performance degradation in wind turbines. Additionally, the radius of the hypersphere serves as a threshold for potential fault warnings. Extensive experiments on SCADA data acquired from multiple wind turbines over an 11-year period demonstrate the effectiveness of this method in early fault warning and long-term wind turbine performance degradation monitoring.
Optimization of Low-Pressure Turbine Blade by Means of Fine Inspection of Loss Production Mechanisms
Authors: Russo Matteo , Carlucci Andrea , Dellacasagrande Matteo , Petronio Daniele , Lengani Davide , Simoni Daniele , Bellucci Juri , Giovannini Matteo , Granata Angelo Alberto , Gily Monica , Manca Carlotta 
Published: August 2024

Abstract
In the present work, Proper Orthogonal Decomposition (POD) has been applied to Large Eddy Simulations (LES) of two high-loaded low-pressure turbine cascade operating under unsteady inflow for the detailed investigation of the entropy production in the different part of the blade passage. To this end, the Turbulent Kinetic Energy (TKE) production, diffusion and dissipation terms appearing into the stagnation pressure transport equation have been integrated all over the computational domain. The POD-based procedure allows splitting the contribution due to different coherent flow dynamics to the turbulent kinetic energy production and dissipation, due to the migration, bowing, tilting and reorientation of the incoming wake filaments, as well as to the breakup of streaky structures into the blade boundary layer and/or to the formation of Von Karman vortices into the wake of the blade. This enables a designer to identify the dominant POD modes (i.e., turbulent flow structures) responsible for loss generation mechanisms, their dynamics and the spatial locations where they mainly act, thus providing a deep view on the physical phenomena to be controlled. Following this optimization strategy, a new low pressure turbine profile has been designed. After running a LES calculation on the new optimized geometry, POD results showed that it is possible to design a higher-loaded profile which operate with a lower global loss coefficient. Thanks to stronger acceleration imposed to the bulk flow in the former part of the blade passage, the new loading distribution is shown to be responsible for lower upstream wake migration losses, as well as for a smaller amount of TKE production in the trailing edge wake zone, as a result of the early suction side boundary layer transition.
Modeling and Predicting Deflagration Phenomena in Hydrogen-Enriched Gas Turbine Exhausts: A CFD Approach
Authors: Lemmi Gianmarco , Nassini Pier Carlo , Cerutti Matteo , Andreini Antonio 
Published: August 2024

Abstract
The adoption of hydrogen-enriched fuels in gas turbine power plants is gaining prominence as an effective strategy for decarbonization. However, this transition presents unique challenges, particularly in relation to hydrogen’s wider flammability range compared to natural gas when mixed with air. Under certain operating conditions, this can lead to the undesired formation of flammable mixtures within the gas turbine exhaust channel, which, if ignited, can result in structural damage due to pressure increases caused by the deflagration process. An effective and robust way of assessing the related safety risk is to rely on high-fidelity Computational Fluid Dynamics (CFD) models, capable of accurately predicting the overpressure generated by the ignition of flammable mixtures.
In this study, a CFD model has been developed to perform three-dimensional and unsteady simulations of the deflagration of hydrogen-air mixtures within large partially confined volumes, representative of an industrial gas turbine exhaust. A high-fidelity Large Eddy Simulation (LES) approach coupled with the Renormalization Group Theory (RNG) subgrid-scale model was employed for turbulence modelling, while the Flamelet Generated Manifold (FGM) tabulated chemistry approach with the Turbulent Flame Speed Closure (TFSC) was adopted as the combustion model. Computational results have then been compared to experimental data from the literature to validate the presented model in terms of numerical domain discretization, turbulence modelling, and combustion modelling. The analysis is aimed at replicating the main overpressure peaks as measured by the British Gas Midlands Research Station. While exhibiting a satisfactory alignment with the experimental pressure distribution in the test case, the proposed setup was able to capture the primary dynamics of the deflagration process, demonstrating its readiness for application to real gas turbine exhaust geometries.
The setup has been then used to simulate the deflagration process of a hydrogen-air mixture at the exhaust of an industrial gas turbine manufactured by Baker Hughes. A discussion on this latter case has been reported as well in this paper.
Image-Based Flashback Detection in a Hydrogen-Fired Gas Turbine Using a Convolutional Autoencoder
Authors: Porath Paul , Yadav Vikas , Panek Lukasz , Ghani Abdulla 
Published: August 2024

Abstract
Flame flashback is a major concern in hydrogen-fired gas turbines. In order to determine the flashback propensity of a hydrogen burner, several burner design tests at different operating points and fuel blends are performed at the test facility of Siemens Energy. A camera monitors the flame in the combustion chamber and the occurrence of flame flashback events in the image recordings becomes clearly visible. This anomalous behaviour clearly deviates from normal hydrogen operation. We develop a data-driven approach to detect flame flashback events based on the camera images at 100% hydrogen operation, where all images feature identical characteristics since the pure hydrogen flame is not visible for the camera. Simultaneously, the highest susceptibility to flashback is attained in this regime. We use both facts as well as the good suitability of image data to train a Convolutional Autoencoder (CAE) model to detect anomalies. Here, anomalies correspond to flashback events. Flashback is captured by the CAE using the reconstruction error associated with a dynamic threshold as a measure of anomaly. This newly developed dynamic threshold overcomes the difficulties in the generalization capability of the CAE. Regardless of the test campaign, burner design and camera settings, it reliably recognizes flashback events. Along with the CAE, the compressed representation, namely the latent space of the CAE, detects the position of flame flashback events. Our methodology is able to detect flame flashback using only flame images and provides a reliable tool even when unseen data are used.
Targeting Full-Hydrogen Operation on Industrial-Scale Gas Turbines: Impact of Unconventional Fuels on Turbine Module Performance and Aeromechanics
Authors: Bandini Alberto , Bettini Claudio , Peruzzi Lorenzo , Carretta Mauro , Canelli Claudio , Marconcini Michele , Pinelli Lorenzo , Arnone Andrea 
Published: August 2024

Abstract
With the trend to full decarbonization, a full hydrogen economy development is a key industrial objective. Gas turbines, currently one of the cleanest fossil fuel-based power generation solutions, provide reliable and on-demand power. The introduction of hydrogen into the fuel mix of existing gas turbines represents a solution with great potential to provide low-carbon or even carbon-free energy. High-hydrogen content fuels, however, challenge the efficient operation of the gas turbine expander, as crucial aspects such as increased flow rate, different gas properties and temperature operating range may affect performance and structural integrity. To evaluate the impact of this conversion, a numerical investigation of five cases with increasing percentages of hydrogen in the fuel was carried out for an industrial four stages gas turbine module. The variation of turbine inlet temperature distribution from combustion chamber was considered, to assess the impact of the unconventional fuel on the well-known aeromechanical behavior of the last stage blades. Variations in capacity, efficiency, power and potential limits due to aeroelasticity were evaluated, identifying the most relevant differences with respect to the full methane case. All these analyses confirm the possibility to employ high-hydrogen fuel operation in a current gas turbine without the need of a further redesign, while maintaining acceptable performance levels.
Air Cycle Machine Modeling Applied to Aeronautical Air Conditioning Unit
Authors: Merzvinskas Marcelo , Bringhenti Cleverson , Takachi Tomita Jesuino , Jefferds Dos Santos Silva Franco , Vitor Tozi Luiz , Lopes Salgado Mayara 
Published: August 2024

Abstract
The air conditioning system of executive, commercial, or military aircraft heavily relies on air cycle machines due to the availability of engine bleed air and their lightness and reliability compared to vapor cycle systems. The type of application, weight, refrigeration capacity, financial aspects, size, performance, and other specific design requirements drive the selection of suitable equipment for a particular aircraft. The motivation of this paper has been based on summarize the main concepts of the aeronautical environmental control system, as well as the mathematical aspects underlying the modeling of a simple/bootstrap air cycle unit in a software. The main aim is to develop software that can generate high level requirements that would be refined during the development phase of an aeronautical air conditioning system. It will be greatly benefit for engineers and students in the design of aeronautical air conditioning systems to better understand and to meet the design requirements. The results demonstrate the influence of the water-sprayer and chilled-recirculation system on air cycle performance and cabin inlet temperature, respectively. They also show changes in certain parameters of interest such as a function of altitude, power consumed by the secondary compressor, and air cycle machine fan. The computational model has proven to be a useful tool for performing parametric studies and evaluating critical points in designing and selecting an air conditioning unit based on a simple/bootstrap air cycle with humid air (any quantity of moist) as the working fluid.
Generative Model Based Parameterization for More Efficient Aerodynamic Optimization of Non-Axisymmetric Endwall
Authors: Li Cunxi , Song Liming , Guo Zhendong , Yang Zhao , Li Jun , Feng Zhenping 
Published: August 2024

Abstract
The Non-axisymmetric Endwall Contouring (NEC) technique has been proven effective in reducing the secondary losses of turbine cascades. However, the parameterization of NEC, especially for spline-based techniques, would face a tradeoff between issues such as the dimensionality of the design space, sample variability, and the proportion of abnormal shapes. To address the above issue and achieve a moreefficient NEC optimization, a generative model based parameterization method is proposed. Specifically, to build a comprehensive design space that contains sufficient variability of NEC shapes, the samples of a set of conventional classical NEC parameterization methods are collected, which are combined by representing them with scatter coordinates in a uniform format. Then, to reduce the number of variables to the minimum extent, the Variational Autoencoder (VAE) is used to learn the intrinsic dimensions of the parameterized NEC design space. To ensure the smoothness of the contours and avoid abnormal shapes, a layer of NURBS is incorporated into the neural network architecture of VAE. This proposed model was used for the NEC parameterization of a high-pressure turbine stage testcase with 9 variables. Additionally, the proposed VAE was used for aerodynamic optimization of the non-axisymmetric endwalls, compared to other NEC parameterization approaches. The results demonstrate that the generative model based parameterization method can optimize aerodynamic performance more effectively while maintaining a lower limit on the number of performance evaluations. The effectiveness of our proposed generative model based parameterization method is well demonstrated.
Evaluation of Current and Future Aviation Fuels at High-Pressure RQL-Type Combustor Conditions
Authors: Griebel Peter , Hampp Fabian , Lückerath Rainer , Lammel Oliver , Grein Tobias , Sallinen Reetu , Vilja Jesse , Sandberg Kati 
Published: August 2024

Abstract
De-carbonizing the aviation sector is one of the biggest challenges in order to minimize climate change effects associated with the emission of carbon dioxide. Sustainable aviation fuels (SAF) will play a major role in this context especially for long-distance flights where hydrogen or all-electric propulsion systems do not present a feasible alternative. In addition, aromatic-free aviation fuels offer a promising solution to lower soot emissions of aeroengines. Today, experience of SAF combustion under aeroengine-typical operation conditions is limited.
In this paper five fuels samples, Jet A-1 as reference fuel, 2 blends and two neat synthesized paraffinic kerosenes from hydro-processed esters and fatty acids (HEFA-SPK) supplied by Neste were tested to characterize the combustion behaviour of drop-in / near drop-in fuels. These experiments were performed for the first time in an optically accessible high-pressure rich-quench-lean (RQL)-type combustor at typical aeroengine conditions. Optical diagnostics (OH* chemiluminescence, Mie scattering) as well as exhaust gas and particle sampling measurements were performed to delineate the fuel effects on spray, flame and emission characteristics. Measurements were performed at pressures up to 10 bar, air preheating temperatures up to 773 K and at primary zone equivalence ratios up to 1.66.
The results showed that the liquid fuel distribution and fuel placement were sensitive to the fuel properties. By contrast, no pronounced influence of the fuel properties on flame position and shape were observed. As a consequence, NOx and CO emissions of the tested fuels differed only moderately. However, particulate matter measurements at the fuel richest operating condition showed a clear ranking of the five fuels with the lowest particle emissions evident for the two neat HEFA-SPK samples. Moreover, the particle volume concentration at the fuel richest condition followed the expected trend with fuel H-content.