bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Experimental and Modelling Strategy for Obtaining Complete Characteristic Maps of Dual-Volute Radial Inflow Turbines
Authors: Serrano José Ramón , Arnau Martínez Francisco José , García-Cuevas Luis Miguel , Samala Vishnu , Guilain Stephane , Batard Samuel 
Published: January 2021

Abstract
Despite the importance of turbocharged engines with radial inflow dual-volute turbines, their characteristic maps and fully predictive modelling using 1D gas dynamic codes are not well established yet. The complexity of the unsteady flow and the unequal admission of these turbines, when operating with pulses of engine exhaust gas, makes them a challenging system. This is mainly due to the unequal flow admission, which generates an additional degree of freedom with respect to well-known single entry vanned or vaneless turbines. This paper has as a main novelty a simple procedure for characterizing experimentally and elaborating characteristic maps of these turbines with unequal flow conditions. This method of analysis allows for easy interpolation within the proposed characteristic maps or conceiving simple models for calculating and extrapolating full performance parameters of dual-volute turbines.
Here, also described are two innovative 0D mean-line models that require a minimum quantity of experimental data for calibrating both: the mass flow parameter model and the isentropic efficiency model. Both models are predictive either in partial or unequal flow admission conditions using as inputs: the mass flow ratio between branches; the total temperature ratio between branches; the blade to jet speed ratio in each branch and the pressure ratio in each branch. These six inputs are generally instantaneously provided by 1D gas-dynamics codes. Therefore, the novelty of the model is its ability to be used in a quasi-steady way for dual-volute turbines performance prediction. This can be done instantaneously when turbines are calculated operating at turbocharged engines under pulsating and unequal flow conditions.
Reynolds Stress Field and Turbulent Kinetic Energy Budget in a Repeating Compressor Stage
Authors: Nawab Ahmad , Wang Feng , di Mare Luca , Adamczyk John J. 
Published: January 2021

Abstract
Turbulence modelling in compressor passages continues to be a challenging problem. In order to better understand the shortcomings of turbulence modelling, a LES and a RANS computation were performed of a repeating compressor stage. The computation was carried out near the aerodynamic design point of the compressor stage, in order to minimise the challenge posed to the turbulence model.
The use of a repeating stage configuration removes the need to specify the statistics of the incoming turbulent field; the statistics become an output of the simulation and not an input. This is a critical fact that greatly increases the credibility of the current LES compressor simulation over many previous simulations. As the computations are performed at mid-span, radial gradients can safely be assumed to be small, thus removing issues associated with capturing flow features attributed to 3D geometry. The flow field is assumed to be incompressible, which is required in order to achieve a true repeating stage environment.
The RANS computation is based on a state-of-the-art turbulence model. At the same flow coefficient, the RANS simulation yielded a total pressure rise very near that of the LES simulation. However, there are nontrivial differences in the flow details. The mean flow and Reynolds shear stress boundary layer profiles are in good agreement in regions of favourable pressure gradient, but significant differences exist in the presence of adverse pressure-gradients. The turbulent kinetic energy profiles however are in poor agreement throughout the flow.
The mean flow production rates predicted by the RANS computation are largely similar to those of the LES simulation forward of mid-chord where the pressure gradient is favourable. A notable exception is the leading-edge region where the LES predicts negative production i.e. a net transfer of energy to the time-mean flow, and the region aft of mid-chord where the pressure gradient is adverse.
Outside of the viscous sub-layer, the dissipation rates are also predicted correctly by the RANS simulation forward of midchord where the pressure gradient is favourable. Aft of mid-chord however, there are significant differences in the dissipation rates.
Evaluation of a Machine Learning Turbulence Model in a Square Transverse Jet in Crossflow
Authors: Costa Fabíola Paula , Díaz Rubén Bruno , Milani Pedro M. , Takachi Tomita Jesuíno , Bringhenti Cleverson 
Published: January 2021

Abstract
Film cooling is an important technique to ensure safe operation and performance fulfillment of turbines. Its ultimate goal is to protect the axial turbine blades from high gas temperatures. An appropriate study is necessary in order to obtain a reliable representation of the flow characteristics involved in such phenomena. Because of the high computational cost of high-fidelity simulations, the low-fidelity simulation method Reynolds Averaged Navier Stokes (RANS) is commonly used in practical configurations. However, the majority of the current turbulent heat flux models fail to accurately predict heat transfer in film cooling flows. Recent work suggests the use of machine learning models to improve turbulent closure in these flows. In the present work, a machine learning model for spatially varying turbulent Prandtl number previously described in the literature is applied to a transverse film cooling flow consisting of a jet square channel. The results obtained in the present work were compared to adiabatic effectiveness experimental data available in the literature to assess the performance of the machine learning model. The results shown that for low blowing ratios (BR = 0.2 and BR = 0.4) the proposed machine learning model has poor performance. However, for the case with the highest blowing ratio (BR = 0.8), the proposed model presented better results. These results are then explained in terms of the resulting turbulent Prandtl number field and suggest that the training set is not appropriate for capturing the turbulent heat flux in fully attached jets in crossflow.
Stress and Modal Analysis of a Rotating Blade and the Effects of Nonlocality
Authors: Tufekci M. , Rendu Q. , Yuan J. , Dear J. P. , Salles L. , Cherednichenko A. V. 
Published: January 2021

Abstract
This study focuses on the quasi-static stress and modal analyses of a rotor blade by using classical and nonlocal elasticity approaches. The finite element method with an additional numerical integration process is used to evaluate the integral equation of nonlocal contionuum mechanics. The blade is assumed to be made of a linear elastic material of weak nonlocal characteristic. Such materials can be composites, metallic foams, nanophased alloys etc. A full-scale fan blade model is chosen as the test case to represent the rotor blade for a modern high bypass ratio turbofan engine. The boundary conditions and loads are chosen based on the steady-state cruising operating conditions of such blades. The nonlocal stresses are calculated by processing the calculated local stresses. To calculate the nonlocal stresses, the integral form of nonlocal elasticity is employed in the discretised domain. The results of the two cases are compared and discussed.
Data-Driven Combustion Modeling for a Turbulent Flame Simulated With a Computationally Efficient Solver
Authors: Talei Mohsen , Ma Man-Ching , Sandberg Richard 
Published: January 2021

Abstract
The use of machine learning (ML) for modeling is on the rise. In the age of big data, this technique has shown great potential to describe complex physical phenomena in the form of models. More recently, ML has frequently been used for turbulence modeling while the use of this technique for combustion modeling is still emerging. Gene expression programming (GEP) is one class of ML that can be used as a tool for symbolic regression and thus improve existing algebraic models using high-fidelity data. Direct numerical simulation (DNS) is a powerful candidate for producing the required data for training GEP models and validation. This paper therefore presents a highly efficient DNS solver known as HiPSTAR, originally developed for simulating non-reacting flows in particular in the context of turbo-machinery. This solver has been extended to simulate reacting flows. DNSs of two turbulent premixed jet flames with different Karlovitz numbers are performed to produce the required data for training. GEP is then used to develop algebraic flame surface density models in the context of large-eddy simulation (LES). The result of this work introduces new models which show excellent performance in prediction of the flame surface density for premixed flames featuring different Karlovitz numbers.
Large Eddy Simulation of Film Cooling for the Real Additive Manufactured Fan-Shaped Holes
Authors: Shi Wei , Li Xueying , Wang Lang , Ren Jing , Jiang Hongde 
Published: January 2021

Abstract
Additive Manufacturing (AM) is a process for making complex parts that were once difficult to machine using traditional manufacturing processes such as forging, casting, and welding. As a new and promising processing technology, AM is being increasingly applied to the manufacturing of high temperature turbine parts. However, before the widespread application of AM can become feasible, the influence of such processes on the performance of turbine hot ends — especially during the film cooling flow heat transfer — requires further study.
This paper focuses a large eddy simulation study done in order to understand the physical phenomena involved in the random roughness caused by the AM of fan-shaped film holes. This paper proposes a set of workflows to connect the AM, CFD simulation, Computed Tomography (CT) and reverse modeling, so that the effect of AM on the flow and heat transfer of film cooling can be studied.
The results of this preliminary workflow reveal several observations. First, that the film cooling effectiveness (η) of AM fan-shaped holes decreases. The area averaged η of the ideal hole is 0.32, while the area averaged cooling effectiveness of the AM hole is 0.29. As such, the η of the AM fan-shaped hole has a significant bifurcation phenomenon. This is because the separation bubble in-tube moves forward, and blocks the flow channel, which bifrucates the flow in-tube. Second, a pressure gradient towards the trailing edge generated at a random rough surface near the leading edge squeezes the fluid. The combined effect of these two mechanisms causes the fluid to flow out of the air film pores mainly from the leading edge with a smaller lateral expansion.
LES Study of the Effects of Oscillations in the Main Flow on Film Cooling
Authors: Baek Seung Il , Ahn Joon 
Published: January 2021

Abstract
The effects of sinusoidal oscillations in the main flow on film cooling in the gas turbine were investigated by Large Eddy Simulation (LES). The film cooling flow fields for the sinusoidal oscillation of 32 Hz in the mainstream from a cylindrical hole inclined by 35° to a flat plate at average blowing ratio of M = 0.5 were numerically simulated. The LES results were compared to the experimental data from Seo, Lee and Ligrani (1998), Jung, Lee and Ligrani (2001) and Reynolds-Averaged Navier-Stokes (RANS) results. The experimental results showed that if the oscillation frequency in the main flow was increased, the adiabatic film cooling effectiveness was decreased. The credibility of the LES results relative to the experimental data was demonstrated by the comparison of time-averaged adiabatic film cooling effectiveness, time and phase-averaged temperature contours, contours of Q-criterion, time-averaged velocity profiles, and time and phase-averaged Urms profiles with the RANS results. The adiabatic film cooling effectiveness by LES model showed a good match to the experimental data, while RANS results highly over-predict the centerline effectiveness. Also, the LES results showed more consistent with the experimental data for the time-averaged and phase-averaged temperature contours, time-averaged velocity profiles and time and phase-averaged Urms profiles than the RANS results. RANS did not predict the peak generated by the jet penetration exactly and Urms profiles obtained by RANS approach was much smaller compared to the experimental results. Paper will discuss these results in detail.
Bayesian Machine Learning for the Prognosis of Combustion Instabilities From Noise
Authors: Sengupta Ushnish , Rasmussen Carl E. , Juniper Matthew P. 
Published: January 2021

Abstract
Experiments are performed on a turbulent swirling flame placed inside a vertical tube whose fundamental acoustic mode becomes unstable at higher powers and equivalence ratios. The power, equivalence ratio, fuel composition and boundary condition of this tube are varied and, at each operating point, the combustion noise is recorded. In addition, short acoustic pulses at the fundamental frequency are supplied to the tube with a loudspeaker and the decay rates of subsequent acoustic oscillations are measured. This quantifies the linear stability of the system at every operating point. Using this data for training, we show that it is possible for a Bayesian ensemble of neural networks to predict the decay rate from a 300 millisecond sample of the (un-pulsed) combustion noise and therefore forecast impending thermoacoustic instabilities. We also show that it is possible to recover the equivalence ratio and power of the flame from these noise snippets, confirming our hypothesis that combustion noise indeed provides a fingerprint of the combustor’s internal state. Furthermore, the Bayesian nature of our algorithm enables principled estimates of uncertainty in our predictions, a reassuring feature that prevents it from making overconfident extrapolations. We use the techniques of permutation importance and integrated gradients to understand which features in the combustion noise spectra are crucial for accurate predictions and how they might influence the prediction. This study serves as a first step towards establishing interpretable and Bayesian machine learning techniques as tools to discover informative relationships in combustor data and thereby build trustworthy, robust and reliable combustion diagnostics.
A Joint Experimental and LES Characterization of the Liquid Fuel Spray in a Swirl Injector
Authors: Vignat Guillaume , Rajendram Soundararajan Preethi , Durox Daniel , Vié Aymeric , Renaud Antoine , Candel Sébastien 
Published: January 2021

Abstract
The quality of liquid fuel spray injection determines to a large extent the steady state performance and dynamics of gas turbine and aero-engine combustors. The present investigation is focused on the detailed characterization of the liquid fuel spray in a single sector test rig targeted at aero-engine applications. The liquid fuel (heptane) is injected in a hollow cone spray pattern by a simplex atomizer and the injector comprises a radial swirler. Two features of the droplet distribution that are less commonly found in the technical literature are identified. First, the distributions of mean droplet diameters exhibit non-axisymmetric patterns, a lack of symmetry that is investigated for three types of swirlers differing by their swirl number and/or head loss. Second, it is found that the size-conditioned velocity distributions feature a single wide peak for small droplets and become bimodal for the largest droplets, with a first peak at low velocities, and a second one at higher velocities. The spray behavior analysis is complemented by making use of Large Eddy Simulations with Lagrangian Particle Tracking. Droplet injection is achieved with a model in which the initial size and velocity distributions are specified from experimental data in the atomizer near field. The initial spray interacts with the lateral injector surface and requires a droplet-wall interaction model accounting for the existence of a liquid film. Simulations do not retrieve the lack of rotational symmetry that is found experimentally indicating that this is not linked to the nature of the swirling flow. This is also consistent with further experiments with a different atomizer confirming that this is due to imperfections in the initial atomizer geometry. Another result is that certain swirler designs appear to be more robust to these atomizer imperfections. Simulations accounting for the liquid film yield a bimodal distribution for the droplets’ axial velocity distribution which would not be obtained without this model indicating that it is important to represent the droplet-wall interaction, a feature that is not commonly found in the literature.
On a New Nonlinear Reduced-Order Model for Capturing Internal Resonances in Intentionally Mistuned Cyclic Structures
Authors: Quaegebeur Samuel , Chouvion Benjamin , Thouverez Fabrice , Berthe Loïc 
Published: January 2021

Abstract
Cyclic structures such as turbomachinery present material and geometrical variations between sectors. These discrepancies are called mistuning and break the cyclic symmetry of the structure. Computing the forced response of mistuned cyclic structures is thus a numerical challenge. The Component Nonlinear Complex Mode Synthesis (CNCMS) is one of the few nonlinear reduced-order model formulations that allow to compute the nonlinear response of tuned and mistuned structures. It has been validated successfully for friction problems. However, in the presence of geometric nonlinearities, internal resonances may arise and they cannot be captured correctly with the CNCMS method. The purpose of this work is therefore to present a new methodology for developing a nonlinear reduced-order model that can successfully capture internal resonances for tuned and mistuned structures. This method, called Component Mode Synthesis with Nonlinear Re-evaluation (CMSNR), is based on a variation of the CNCMS approach. The final modal synthesis uses a multi-harmonic procedure and a re-evaluation of the nonlinear forces on each sector independently. The performance and limitations of the proposed approach are assessed using a simplified example of a blisk subject to polynomial nonlinearities. Different internal resonances are exhibited and studied depending on the type of excitation force and on the level of mistuning.
Nonlinear Vibration Analysis of Turbine Bladed Disks With Mid-Span Dampers
Authors: Ferhatoglu Erhan , Zucca Stefano , Botto Daniele , Auciello Jury , Arcangeli Lorenzo 
Published: January 2021

Abstract
Friction dampers are one of the most common structures used to alleviate excessive vibration amplitudes in turbomachinery applications. There are very well-known types of contact elements exploited efficiently, such as underplatform dampers. However, different design approach is sometimes needed to maximize the effectiveness further. In this paper, computational forced response prediction of bladed disks with a configuration of the secondary structure commonly used by Baker Hughes design, the so-called mid-span dampers, is presented. Mid-span dampers are metal devices positioned at the middle section of the airfoil span and come into contact with the blade by the centrifugal force acting during rotation. Proposed damping mechanism is applied to a realistic steam turbine bladed disk under cyclic symmetric boundary conditions. Friction contact is modeled through a large number of contact nodes between the blade and the damper by using a 2D friction contact element with variable normal load. Harmonic Balance Method and Alternating Frequency/Time approach are utilized to obtain nonlinear algebraic equations in frequency domain and nonlinear forced response is computed by using Newton-Raphson method. The results obtained by numerical simulations show that mid-span dampers are an efficient configuration type of a damping mechanism to be used in the design of the bladed disks for nonlinear vibration analysis.
Micro-, Macromechanical and Aeroelastic Investigation of Glass-Fiber Based, Lightweight Turbomachinery Components
Authors: Iseni Senad , Prasad Mahesh Ramaswamy Guru , Hartmaier Alexander , Holeczek Klaudiusz , Modeler Niels , di Mare Francesca 
Published: January 2021

Abstract
A major technical challenge for modern aero engines is the development of designs which reduce noise and emission whilst increasing aerodynamic efficiency and ensuring aeroelastic stability of low-temperature engine components such as fans and low-pressure compressors. Composites are used in aviation due to their excellent stiffness and strength properties, which also enable additional flexibility in the design process. The weight reduction of the turbomachine components, due to composite materials and lighter engines, is especially relevant for the design and developments of hybrid-electric or distributed propulsion systems [1].
To accomplish this, a representative volume element (RVE) of a glass-fiber reinforced polymer is created, describing the geometrical arrangement of the textile reinforcement structure within the polymer matrix. For both phases, realistic linear elastic properties are assumed. This RVE will be investigated with the finite element method under various loading conditions to assess its anisotropic elastic properties and also its damping behaviour for elastic waves. To study the influence of delamination on the mechanical properties, small defects will be introduced into the model at the interface between reinforcement and matrix. Based on this micromechanical approach, a constitutive model for the composite will be formulated that describes the anisotropic properties as well as the damping behaviour. This constitutive model is then used to describe the material response in a macro-mechanical model, which serves as the basis for an aeroelastic analysis of a 1/3-scaled high-speed fan using a conventional (Ti-6Al-4V) and fiber composite material.