bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determination of the Vibration Within a Squeeze-Film Damper Under Rotational Unbalance Conditions From Externally Mounted Sensors
Authors: Al-Ghazal Ghaith Ghanim , Bonello Philip , Torres Cedillo Sergio G. 
Published: November 2019

Abstract
Recently, there has been a focus on the use of inverse problem techniques in order to monitor rotor unbalance, and obtain a balancing solution, from vibration measurements on the casing and prior knowledge of the rotor-casing structure. In certain practical configurations that use nonlinear bearings like the squeeze-film damper (SFD) bearing, an inverse model of the bearing is an important part of the unbalance identification process. The inverse bearing model is used to estimate the journal vibration from casing vibration measurements, thus acting as a substitute for internal instrumentation in applications where the rotor is not accessible under operational conditions. Previous research has shown that an inverse bearing model can be identified using a trained Recurrent Neural Network (RNN) from experimental input/output data. However, the RNN was both trained and validated under simulated rotational conditions, wherein the motion was driven by two orthogonally-phased perpendicular shakers.
In this paper, a RNN of an inverse bearing model that is identified from experimental data generated under simulated rotational conditions is validated under actual rotational (i.e. unbalance-driven) vibration conditions. The necessary modifications to the test rig are presented, together with the identification/training procedure. The results of the validation tests show that the RNN is capable of predicting the frequency spectrum of the dynamic nonlinear response of the journal with reasonable accuracy. This inverse SFD bearing model can be thus used in a future work to identify rotor unbalance.
Validation of an Advanced Diagnostic Methodology for the Identification and Classification of Gas Turbine Sensor Faults by Means of Field Data
Authors: Manservigi Lucrezia , Venturini Mauro , Ceschini Giuseppe Fabio , Bechini Giovanni , Losi Enzo 
Published: November 2019

Abstract
Sensor fault detection is a crucial aspect for raw data cleaning in gas turbine industry. To this purpose, a comprehensive approach for Improved Detection, Classification and Integrated Diagnostics of Gas Turbine Sensors (named I-DCIDS) was developed by the authors to detect and classify several classes of fault. For single-sensors or redundant/correlated sensors, the I-DCIDS methodology can identify seven classes of fault, i.e. Out of Range, Stuck Signal, Dithering, Standard Deviation, Trend Coherence, Spike and Bias.
Since the considered faults are detected by means of a methodology which relies on basic mathematical laws and user-defined parameters, sensitivity analyses are carried out in this paper on I-DCIDS parameters to derive some rules of thumbs about their optimal setting. The sensitivity analyses are carried out on four heterogeneous and challenging datasets with redundant sensors installed on Siemens gas turbines.
Thermomechanical Fatigue of Ceramic Matrix Composites
Authors: Longbiao Li 
Published: November 2019

Abstract
In this paper, the thermomechanical fatigue (TMF) of fiber-reinforced ceramic-matrix composites (CMCs) is investigated using the hysteresis-based damage parameter. The micro stress field of the damaged CMCs of matrix cracking and fiber/matrix interface debonding is obtained considering the temperature-dependent fiber/matrix interface shear stress. The fiber/matrix interface debonded length and unloading/reloading slip length are determined using the fracture mechanics approach. Based on the damage mechanisms of fiber sliding relative to the matrix in the interface debonded region, the TMF hysteresis loops models and hysteresis-based damage parameters are developed for the partially and completely debonding to analyze the damage evolution inside of fiber-reinforced CMCs. The effects of temperature, phase angle and loading sequences on the damage development of SiC/SiC composite are discussed. When TMF temperature range increases, the fatigue hysteresis loops area, residual strain increase, and the hysteresis modulus decreases, due to the increase of the fiber/matrix interface slip length. Under TMF loading, the phase angle affects the interface debonding and sliding range, and the hysteresis loops shape, location and area of the fiber-reinforced CMCs. The experimental TMF damage evolution of 2D SiC/SiC and cross-ply SiC/MAS composites are predicted.
A Numerical Investigation of Air/Mist Cooling Through a Conjugate, Rotating 3-D Gas Turbine Blade With Internal, External, and Tip Cooling
Authors: Abdelmaksoud Ramy , Wang Ting 
Published: November 2019

Abstract
This paper describes a numerical investigation to study the effect of injecting mist (tiny water droplets) into the cooling air used to cool down rotating gas turbine blades. In this study, the conjugate heat transfer method is employed which consists of the simulation of the air/mist fluid flow inside and outside the blades as well as the heat conduction through the blade body. The complete 3-D blade with internal cooling passages and external film cooling holes on the surface and blade tip is simulated in a rotating, periodic sector of the blade. The discrete phase model (DPM) is used to simulate and track the evaporation and movement of the tiny water droplets. The rotation effect of the turbine blade is included in the CFD simulation by using the moving reference frame method. The effects of different parameters such as the mist/air ratio (10–20%) and the mist droplets size (20–40μm) on mist cooling enhancement are investigated. The results show that the mist cooling enhancements are about 10% to 25% on the outer surface of the blade and reach 50% in some locations inside the blade on the internal cooling passages walls. Most of the liquid droplets completely evaporate inside the internal cooling passages; only a limited amount of mist is able to escape from the film cooling holes to enhance the blade outer surface and blade tip cooling. The effect of 10% mist on enhanced cooling is also converted to an equivalent of a 30% reduction in cooling air flow.
Fretting Induced Fatigue Failure in Steam Turbine Blades
Authors: Gowreesan Vamadevan , Grebinnyk Kyrylo 
Published: November 2019

Abstract
Fretting occurs when there is cyclic relative motion of extremely small amplitude between two tightly fit mating surfaces. In this process, the tight fitting load may lead to adhesion of mating surface. The subsequent relative movement breaks the adhesion and lead to local grooves and pits. The localized damage in conjunction with the stresses associated with the cyclic relative motion may lead to surface cracking. This crack subsequently may propagate by fatigue provided there is high enough cyclic stress at that location.
The paper discusses a blade failure induced by such fretting related fatigue. The metallurgical evaluation of the fracture surfaces of the blades showed evidence of classical fatigue failure. However, the crack initiation location did not coincide with high stress location identified by the finite element analysis. This discrepancy along with the evidence of fretting at the crack initiation sites confirms that failures were induced by fretting. Finally, some methods to eliminate or minimize fretting damage are discussed.
Comparison of a Liquid Annular Seal for Pump Applications With and Without a Swirl Brake
Authors: Balke Nathan E. , Childs Dara W. 
Published: November 2019

Abstract
An annular seal is an annular clearance between a rotor and a stator within a turbomachine that restricts leakage flow, arising due to the seal’s pressure differential. Annular seals are important for consideration in turbomachinery in that they affect the rotodynamics and stability of the turbomachine. Data were available for a smooth liquid annular seal that had been previously tested with no swirl brakes. The seal was modified by adding slots at the inlet to produce a swirl brake seal. Tests produced static and dynamic data for the swirl brake seal. The swirl brake and unmodified seal data are compared to demonstrate how swirl brakes impact the seal’s rotordynamic performance.
Adding a swirl brake to a liquid annular seal increases direct stiffness, decreases cross-coupled stiffness, modestly increases direct damping, reduces cross-coupled damping, and decreases both the direct and cross-coupled virtual mass terms. The measured drop in cross-coupled stiffness via the addition of swirl brakes shows why swirl brakes are effective in remedying rotordynamic instabilities. Results show that varying inlet pre-swirl, or fluid rotation, on a swirl brake seal has little effect on the seal’s dynamic performance characteristics.
A notable phenomenon was observed with the direct stiffness. At certain test points the direct stiffness would abruptly increase and decrease when increasing either pressure or running speed. The behavior could be largely explained by transitioning the laminar/transitional/turbulent boundaries.
Secondary Flow Measurements in a Compressor Cascade Using 3D LDA/PDA: Part A — Flow Topology and its Numerical Representation
Authors: Geist Silvio , Harbeck Janneck , Joos Franz 
Published: November 2019

Abstract
A three-dimensional flow in a high speed (Main = 0.7) linear compressor cascade’s end wall region is presented in this paper. The attached blade geometry is of medium curvature with a deflection angle Δβ = 15°. To intensify the secondary flow structure the profiles were stalled deliberately and oil flow visualization was used to prove the presence of that hub-corner stall. Together with streamlines derived from velocities, measured by a three-channel laser Doppler anemometer (LDA), that allowed the identification of the secondary flow region’s key features and their extents into the flow field. A therefrom-derived topology is then compared to existing concepts. Moreover, an associated URANS simulation is set up using the k–ε model to verify its capabilities to reproduce the measured flow field. To confirm the previous observations the stall indicator is computed from the simulation results. It is further shown that the hub-corner stall dissolves when removing the side wall boundary layer. In summary, this paper combines elaborate laser Doppler measurements at both high Reynolds and Mach numbers combined with verified simulations allowing a detailed description of the end wall behavior within the cascade and further introduces a new flow topology concept.
Performance Informed Prognostics and its Implications
Authors: Slottner Pontus , Johansson Per 
Published: November 2019

Abstract
Gas turbine maintenance has historically been performed firstly to keep equipment safe and reliable to operate, and secondly to prevent performance loss. Component replacement plans have often been generic and therefore best suited for one set of ambient conditions and a few pre-defined operation profiles. Continuous development in materials and computerized analysis methods have resulted in much more well understood and robust designs than before, resulting in design induced failure rates dropping to levels where they can be considered as random and unexpected.
While gas turbine designs matured, market conditions changed. Deregulation, consumer energy efficiency improvements, emission reduction requirements and large-scale introduction of renewables have reduced both average electricity price and thus the average amount of gas turbine power needed, but has also increased the variability in demand, resulting in highly unit specific operation profiles. This requires operators to cut unnecessary costs wherever possible and optimize operation and maintenance strategy in a complex environment with a growing number of parameters to consider. Over the past years much focus has been put on cost reduction through extension of maintenance intervals. However, since less maintenance and longer intervals can mean lower reliability and higher degradation, it is not always cost efficient. This paper shows how costs of maintenance, operation, fuel and degradation can be analyzed together, resulting in improved decision support for choosing better operation and maintenance strategies.
Prediction of Premixed Flame Dynamics Using LES With Tabulated Chemistry and Eulerian Stochastic Fields
Authors: Avdonin Alexander , Javareshkian Alireza , Polifke Wolfgang 
Published: November 2019

Abstract
This paper demonstrates that a Large Eddy Simulation (LES) combustion model based on tabulated chemistry and Eulerian stochastic fields can successfully describe the flame dynamics of a premixed turbulent swirl flame. The combustion chemistry is tabulated from one-dimensional burner-stabilized flamelet computations in dependence of progress variable and enthalpy. The progress variable allows to efficiently include a detailed reaction scheme, while the dependence on enthalpy describes the effect of heat losses on the reaction rate. The turbulence-chemistry interaction is modeled by eight Eulerian stochastic fields. A LES of a premixed swirl burner with a broadband velocity excitation is performed to investigate the flame dynamics, i.e. the response of heat release rate to upstream velocity perturbations. In particular, the flame impulse response and flame transfer function are identified from LES time series data. Simulation results for a range of power ratings are in good agreement with experimental data.
Time-Volume Estimation of Velocity Fields From Non-Synchronous Planar Measurements Using Linear Stochastic Estimation
Authors: Butcher Daniel , Spencer Adrian 
Published: November 2019

Abstract
With increasing complexity of aerodynamic devices such as gas turbine fuel swirl nozzles (FSN) and combustors, the need for time-resolved full volume flow characterisation is becoming greater. Even with modern advancements in both numerical and experimental methods, this remains a challenging area.
The work presented in this paper combines multiple non-synchronous planar measurements to reconstruct an estimate of a synchronous, instantaneous flow field of the whole measurement set. Temporal information is retained through the linear stochastic estimation (LSE) technique. The technique is described, applied and validated with a simplified combustor and FSN geometry flow for which 3-component, 3-dimensional (3C3D) flow information is known from published tomographic PIV[1]. Using the tomographic PIV data set, multiple virtual ‘planes’ may be extracted to emulate single planar PIV measurements and produce the correlations required for LSE. In this example, multiple parallel planes are synchronised with a single perpendicular plane that intersects each of them. As the underlying data set is volumetric, the measured velocity is known a priori and therefore can be directly compared to the estimated velocity field for validation purposes. The work shows that when the input time-resolved planar velocity measurements are first POD (proper orthogonal decomposition) filtered, high correlation between the estimations and the validation velocity volumes are possible. This results in estimated full volume velocity distributions which are available at the same time instance as the input field — i.e. a time resolved velocity estimation at the frequency of the single input plane. While 3C3D information is used in the presented work, this is necessary only for validation; in true application planar technique would be used. The study concludes that provided the number of sensors used for input LSE exceeds the number of POD modes used for pre-filtering, it is possible to achieve correlation greater than 99%.
Radial Inflow Turbine Geometry Generation Method Using Third Order Bezier Curves for Blade Design
Authors: Caldiño-Herrera U. , García J. C. , Sierra-Espinosa F. , Dávalos J. O. , Lira M. A. 
Published: November 2019

Abstract
Radial inflow turbines offer larger efficiency performance for small power applications due to its geometric configuration in which flow varies its radial position along the flow path.
The geometry configuration of radial-inflow turbines demands a careful and adequate design of the flow path, since a 90° change of direction occurs from the radial inflow to the axial outflow. The blade camberline also requires attention since it defines the tangential flow direction along the meridional coordinate and any variation in its geometry affects the turbine performance.
In this paper, a method for meridional profile and camberline geometry generation is proposed and tested through CFD. The method consists in using fourth order Bezier curves for defining the hub, shroud and mid-height blade meridional profile and third order Bezier curves for defining the relative flow velocity angle along the meridional coordinate, which leads to the camberline angular position in the rotor considering radial fibered blades. The blade thickness is set to vary linearly along the meridional coordinate and along the blade height. Different configurations of blade geometry are proposed and analyzed. These configurations are fixed to satisfy the design parameters.
The code is programed in Python and adjusts the geometry data in files that are readable by meshing software. Thereby numerical calculations are performed to verify which configuration of camberline results in better performance. The calculations are done in models with the same boundary conditions and geometric data except for the variation of relative flow velocity angle along the meridional coordinate but setting the inlet and outlet angle to a fixed value. This way, the most suitable camberline geometry can be selected. The CDF model used for this analysis was validated with the experimental results reported by Kang et al. [1]
Assessment of an Innovative Technique for the Robust Optimization of Organic Rankine Cycles
Authors: Serafino Aldo , Obert Benoit , Hagi Hayato , Cinnella Paola 
Published: November 2019

Abstract
After the extraordinary diffusion that we have observed over the last ten years, Organic Rankine Cycles (ORCs) are nowadays widely recognized as “the unrivalled technical solution for generating electricity from low-medium temperature heat sources of limited capacity” [1]. Despite the high level of confidence and know-how reached about ORCs, they still remain a delicate technology, hiding a great amount of technical difficulties which sometimes still make them a risky investment. Most of these complexities are originated from manifold sources of uncertainty which impact on almost the whole life of the ORC project, from their design to the commissioning and operation steps, with heavy consequences in terms of performance and costs. In this work we present the proof of concept assessing and validating an innovative technique for the robust design optimization (RDO) of ORC under uncertainty. The approach allows to deal with both aleatory and epistemic uncertainty in order to avoid an over-optimization of the system that can result in a high sensitivity to small changes. Because of the large number of sources of uncertainty, the design problem must be solved in a highly multi-dimensional space, spanned by the uncertain and design variables. In such a situation, the “brute-force” Monte-carlo approach [2] is not a viable technique, since it is limited to cheap and excessively simplified models. Consequently, in the present work we consider a more efficient design methodology relying on two nested Bayesian Kriging surrogates.
Object-Oriented Approach to Determine Effectiveness of Potential Gas Turbine Power Augmentation Methods
Authors: Krouse Charles R. , Delimont Jacob M. 
Published: November 2019

Abstract
Ambient conditions have a significant impact on the performance of gas turbines. Higher ambient temperatures correlate with decreased power output and increased heat rate. These effects are undesirable for power generation plants, especially given that energy demand is highest during hot days. To replace some of the power lost on hot days, power augmentation methods, such as inlet fogging or inlet chilling, can be used. To determine the effectiveness and return on investment of potential power augmentation methods, economic impact studies are generally conducted. Among other things, these studies require theoretical models of the power augmentation systems. An object-oriented approach seems to be the most logical approach for modeling a gas turbine with potential power augmentation systems. This approach allows numerous power augmentation models to easily be added to, evaluated with, and removed from a gas turbine model. Existing literature focuses heavily on economic studies and complicated models, and there is a lack of fundamental information on how to simulate power augmentation methods. This paper will focus on the modeling and simulation of four primary gas turbine power augmentation techniques: inlet chilling, inlet fogging, air injection, and steam injection. The fundamental calculations associated with each object are discussed. Finally, the different techniques are modeling in a GE-7FA gas turbine to demonstrate a simple power augmentation case study.
A New Data-Driven Turbulence Model Framework for Unsteady Flows Applied to Wall-Jet and Wall-Wake Flows
Authors: Lav Chitrarth , Philip Jimmy , Sandberg Richard D. 
Published: November 2019

Abstract
The unsteady flow prediction for turbomachinery applications relies heavily on unsteady RANS (URANS). For flows that exhibit vortex shedding, such as the wall-jet/wake flows considered in this study, URANS is unable to predict the correct momentum mixing with sufficient accuracy. We suggest a novel framework to improve that prediction, whereby the deterministic scales associated with vortex shedding are resolved while the stochastic scales of pure turbulence are modelled. The framework first separates the stochastic from the deterministic length scales and then develops a bespoke turbulence closure for the stochastic scales using a data-driven machine-learning algorithm. The novelty of the method lies in the use of machine-learning to develop closures tailored to URANS calculations. For the walljet/wake flow, three different mass flow ratios (0.86, 1.07 and 1.26) have been considered and a high-fidelity dataset of the idealised geometry is utilised for the sake of model development. This study serves as an a priori analysis, where the closures obtained from the machine-learning algorithm are evaluated before their implementation in URANS. The analysis looks at the impact of using all length scales versus the stochastic scales for closure development, and the impact of the extent of the spatial domain for developing the closure. It is found that a two-layer approach, using bespoke trained models for the near wall and the jet/wake regions, produce the best results. Finally, the generalisability of the developed closures is also evaluated by applying a given closure developed using a particular mass flow ratio to the other cases.