bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of Autoignition Chemistry in Aeroderivative Premixers at Engine Conditions
Authors: Jella Sandeep , Bourque Gilles , Gauthier Pierre , Versailles Philippe , Bergthorson Jeffrey , Park Ji-Woong , Lu Tianfeng , Panigrahy Snehashish , Curran Henry 
Published: January 2021

Abstract
The minimization of autoignition risk is critical to the design of premixers of high power aeroderivative gas turbines as an increased use of highly reactive future fuels (for example, hydrogen or higher hydrocarbons) is anticipated. Safety factors based on ignition delays of homogeneous mixtures, are generally used to guide the choice of a residence time for a given premixer. However, autoignition chemistry at aeroderivative conditions is fast (0.5–2 milliseconds) and can be initiated within typical premixer residence times. The analysis of what takes place in this short period necessarily involves the study of low-temperature autoignition precursor chemistry, but precursors can change with fuel and local reactivity.
Chemical Explosive Modes are a natural alternative to study this as they can provide a measure of autoignition risk by considering the whole thermochemical state in the framework of an eigenvalue problem. When transport effects are included by coupling the evolution of the Chemical Explosive Modes to turbulence, it is possible to obtain a measure of spatial autoignition risk where both chemical (e.g. ignition delay) and aerodynamic (e.g. local residence time) influences are unified.
In this article, we describe a method that couples Large Eddy Simulation to newly developed, reduced autoignition chemical kinetics to study autoignition precursors in an example pre-mixer representative of real life geometric complexity. A blend of pure methane and dimethyl ether (DME), a common fuel used for experimental autoignition studies, was transported using the reduced mechanism (38 species / 238 reactions) at engine conditions at increasing levels of DME concentration until exothermic autoignition kernels were formed. The resolution of species profiles was ensured by using a thickened flame model where dynamic thickening was carried out with a flame sensor modified to work with multi-stage heat release.
The paper is outlined as follows: First, a reduced mechanism is constructed and validated for modeling methane as well as di-methyl ether (DME) autoignition. Second, sensitivity analysis is used to show the need for Chemical Explosive Modes. Third, the thickened flame model modifications are described and then applied to an example premixer at 25 bar / 890K preheat. The Chemical Explosive Mode analysis closely follows the large thermochemical changes in the premixer as a function of DME concentration and identifies where the premixer is sensitive and flame anchoring is likely to occur.
Cyclostationary Approach for Instabilities Detection and Condition Monitoring of Centrifugal Compressor
Authors: Stajuda Mateusz , Garcia Cava David , Liśkiewicz Grzegorz 
Published: January 2021

Abstract
This study intends to explore the capabilities of the cyclostationary approach for instabilities detection and operating conditions monitoring of centrifugal compressors.
Cyclostationary approach offers powerful signal analysis methods, applicable to different processes. It was proven useful for analysis of vibration, acoustic and pressure data for systems exhibiting periodicity. Cyclostationarity has been used for extracting subtle changes between cycles of the periodic signal which could be used for condition monitoring. Recent research focuses on employing this method for fault indication. Cyclostationary approach has not been extensively used in the field of turbomachinery, except for a few cases when it was proven to give a better insight into flow structure than standard signal processing techniques and allow for the detection of instabilities in flow systems. Thus, the cyclostationary approach may be suitable for instabilities detection and condition monitoring in centrifugal compressors.
This paper exploits various techniques employing a cyclostationary framework for instabilities detection and operating conditions monitoring with the use of pressure signals from the low-speed centrifugal compressor. The most prospective cyclostationarity-based indicators are applied for the detection of instabilities. Due to a lack of second-order cyclostationarity, the study confines to the analysis of first-order cyclostationarity strongly exhibited in the compressor pressure signal. First-order cyclostationarity analysis provides an indication of instabilities and working conditions differentiation, but due to time-domain sampling, it is not fully robust and reliable. The highest potential is perceived in the cyclostationary approach use to extract changes between cycles. Different measures of change in variability could serve as a valuable indicator of instabilities.
Experimental Investigation of Innovative Cooling Schemes on an Additively Manufactured Engine Scale Turbine Nozzle Guide Vane
Authors: Hossain Mohammad A. , Ameri Ali , Gregory James W. , Bons Jeffrey P. 
Published: January 2021

Abstract
This study includes the design, validation, and fabrication via Direct Metal Laser Sintering (DMLS) of a gas turbine nozzle guide vanes (NGV) that incorporates three innovative cooling schemes specifically enabled by additive manufacturing. The novel NGV design is the culmination of an extensive research and development effort over a period of four years that included low and high speed cascade testing coupled with unsteady CFD for numerous candidate innovative cooling architectures. The final vane design (SJ-vane) consists of sweeping jet (SJ) film cooling holes on the suction surface, sweeping jet impingement holes at the leading edge and double-wall partial length triangular pin-fin with impinging jet at the trailing edge. For comparison purposes, a second DMLS enabled vane (777-vane) was designed and fabricated with prototypical cooling circuits to serve as a baseline. This vane consists of a shaped film cooling holes on the suction surface, circular impingement holes at the leading edge and full length cylindrical pin-fins at the trailing edge. Experiments with the two DMLS enabled vanes were performed at the Ohio State University Turbine Reacting Flow Rig (TuRFR) at engine relevant temperature (1375K) and Mach number conditions. Infrared (IR) thermography was utilized to measure the wall temperature of the pressure and suction surface at several coolant mass flow rates to estimate the overall cooling effectiveness (ϕ). Results showed improved cooling performance for the advanced cooling schemes (sweeping jet film cooling, impingement cooling and triangular pin-fin cooling) compared to the baseline cooling schemes.
An Integrated Principal Component Analysis, Artificial Neural Network and Gas Path Analysis Approach for Multi-Component Fault Diagnostics of Gas Turbine Engines
Authors: Alozie Ogechukwu , Li Yi-Guang , Pilidis Pericles , Liu Yang , Wu Xin , Shong Xingchao , Ren Wencheng , Korakianitis Theodosios 
Published: January 2021

Abstract
Gas path diagnostics is a key aspect of the engine health monitoring (EHM) process that aims to detect, identify and predict engine component faults, using information from installed sensors, in order to guide maintenance action, maintain engine efficiency and prevent catastrophic failures. To achieve high prediction accuracies, current data-derived diagnostic models tend to be engine specific while the model-based methods are known to be time-consuming, especially for complex engine configurations. This paper proposes an integrated approach for accurate and accelerated isolation and prediction of multiple-degraded gas turbine component faults that comprises 3 steps — feature extraction using the Principal Component Analysis (PCA), machine learning classification with a multi-layer perceptron, artificial neural network (MLP-ANN) and model-based fault prediction via the non-linear Gas Path Analysis (GPA) technique. In this hybrid approach, the PCA first transforms the measurement fault signature into a fault-feature domain, which becomes an input to the multi-label ANN classifier used to isolate the potential faulty components. The non-linear GPA finally quantifies the magnitude of degradation that produced the recorded fault signature. Once trained and validated, the PCA-ANN model is deployed as part of the data processing mechanism prior to the actual GPA calculation. This method was assessed and validated using the thermodynamic performance model of a 2-shaft, high-bypass ratio, turbofan engine. For training and testing the PCA-ANN classifier, a total of 28,000 final samples for 14 measurement parameters, each averaged from 10 data points with Gaussian noise of zero mean and unit standard deviation, and implanted with single-, double- and triple-component fault cases of various magnitude, were generated by steady-state performance simulation of the engine model at its reference operating condition. Correlation analysis of this data set revealed the optimum sensor subset to be used for multi-component diagnostics. A quantitative analysis of the PCA-ANN fault isolation on the test set produced a classification accuracy of 96.6% and performed better on all metrics, compared to other multi-label classification algorithms. Finally, the proposed integrated approach achieved an average of 94.35% reduction in processing time, when compared to the conventional non-linear GPA by component-fault-cases (CFCs), while predicting implanted faults to the same accuracy.
Impingement Heat Transfer From a Jet-Array With In-Between Return Holes for the Crossflow
Authors: Tang Chen , Acharya Sumanta 
Published: January 2021

Abstract
Jet-impingement heat transfer is commonly used for vane leading edges and end-walls of turbine components for cooling the surfaces. One of the factors that limit high heat transfer rates is the effect of the crossflow which builds up downstream and adversely impacts the jet penetration and the impingement heat transfer rates. The present paper investigates the concept of introducing return holes (RH) for the crossflow to prevent its build-up and therefore reduce its deleterious effects. In the present experimental study, a 3 by 9 jet-array impinging on a target surface is considered with and without return holes. The return holes are located in an in-line pattern between the impingement holes. Experiments are conducted in an impingement channel with closed side walls and for jet-to-target distances (H/D) of 1D to 9D and a jet-Reynolds number of 20,000. Two different crossflow schemes combined with three return hole (RH) configurations are studied. The two crossflow arrangements are: (1) one radial exit and RH’s open for the spent air to exit and (2) all radial exits blocked with the spent air exiting through the RH’s only. Three different area-openings for the RH’s are considered and correspond to 33.3%, 66.7%, and 100% of the total return hole area open. In addition, a baseline case with no RH’s and one radial exit is studied. A transient liquid-crystal based study is conducted using a thin sheet of narrowband Thermochromic Liquid Crystal glued on an acrylic plate serving as the target surface. Local heat transfer coefficients are obtained based on the measured surface temperature and the solution of 1D transient heat conduction in the target acrylic plate. Return holes have significant influence on the crossflow-induced degradation effects at small jet-to-target spacing. The all-blocked crossflow scheme demonstrates good uniformity and axisymmetric Nusselt number distributions.
An Ensemble of Recurrent Neural Networks for Real Time Performance Modelling of Three-Spool Aero-Derivative Gas Turbine Engine
Authors: Ibrahem Ibrahem M. A. , Akhrif Ouassima , Moustapha Hany , Staniszewski Martin 
Published: January 2021

Abstract
Gas turbine is a complex system operating in non-stationary operation conditions for which traditional model-based modelling approaches have poor generalization capabilities. To address this, an investigation of a novel data driven neural networks based model approach for a three-spool aero-derivative gas turbine engine (ADGTE) for power generation during its loading and unloading conditions is reported in this paper. For this purpose, a non-linear autoregressive network with exogenous inputs (NARX) is used to develop this model in MATLAB environment using operational closed-loop data collected from Siemens (SGT-A65) ADGTE. Inspired by the way biological neural networks process information and by their structure which changes depending on their function, multiple-input single-output (MISO) NARX models with different configurations were used to represent each of the ADGTE output parameters with the same input parameters. First, data preprocessing and estimation of the order of these MISO models were performed. Next, a computer program code was developed to perform a comparative study and to select the best NARX model configuration, which can represent the system dynamics. Usage of a single neural network to represent each of the system output parameters may not be able to provide an accurate prediction for unseen data and as a consequence, provides poor generalization. To overcome this problem, an ensemble of MISO NARX models is used to represent each output parameter. The major challenge of the ensemble generation is to decide how to combine results produced by the ensemble’s components. In this paper, a novel hybrid dynamic weighting method (HDWM) is proposed. The verification of this method was performed by comparing its performance with three of the most popular basic methods for ensemble integration: basic ensemble method (BEM), median rule and dynamic weighting method (DWM). Finally, the generated ensembles of MISO NARX models for each output parameter were evaluated using unseen data (testing data). The simulation results based on datasets consisting for experimental data as well as data provided by Siemens high fidelity thermodynamic transient simulation program show improvement in accuracy and robustness by using the proposed modelling approach.
Fluctuation of Inducer Recirculation Stemming From Diffuser Stall in Centrifugal Turbomachinery Near Surge Condition
Authors: Tsukamoto Kazuhiro , Kato Chisachi 
Published: January 2021

Abstract
This work investigates the unsteady fluctuation of inducer recirculation stemming from the diffuser stall that occurs near the surge condition. Experiments and unsteady numerical simulation were utilized for the investigation.
Inducer recirculation is known to occur near the surge occurrence flow rate, where the flow rate has a positive slope of the performance curve and the recirculation extends to the upstream of the impeller inlet when decreasing the flow rate more. However, few papers have investigated the unsteady phenomenon of the recirculation, even though the surge is what causes it. Clarifying the recirculation phenomenon is essential in terms of expanding the operation range to the lower flow rate for centrifugal turbomachinery. This was our motivation for investigating the unsteady oscillation phenomenon of the inducer recirculation.
We investigated a single-stage centrifugal blower with the maximum pressure rise ratio of 1.2 and focused on the flow rates near surge occurrence. The blower was equipped with an open type centrifugal impeller, a vane-less diffuser, and a scroll casing. The blower performance and pressure time-history data were obtained by experiments. Unsteady simulations using large eddy simulation (LES) were conducted to investigate the flow field in the blower for each flow rate.
The obtained performance curve showed that the positive slope of the pressure rise at the lower flow rate was due to the impeller stall and that the inducer recirculation extending upstream of the suction pipe near the slope of the curve was flat. LES analysis revealed that this inducer recirculation had two typical fluctuation peaks, one at 20% of the rotation frequency and the other at 95%. We also found that the stall cell at the impeller inlet propagated in the circumferential direction and swirled at almost the same frequency as the impeller rotation. In addition, the fluctuation at the diffuser derived from the diffuser rotating stall propagated to the suction pipe.
Theoretical and Experimental Investigation of a 34 Watt Radial-Inflow Steam Turbine With Partial-Admission
Authors: Wagner Patrick H. , Van herle Jan , Schiffmann Jürg 
Published: January 2021

Abstract
A micro steam turbine with a tip diameter of 15 mm was designed and experimentally characterized. At the nominal mass flow rate and total-to-total pressure ratio of 2.3 kg h−1 and 2, respectively, the turbine yields a power of 34 W and a total-to-static isentropic efficiency of 37%. The steam turbine is conceived as a radial-inflow, low-reaction (15%), and partial admission (21%) machine. Since the steam mass flow rate is limited by the heat provided of the system (solid oxide fuel cell), a low-reaction and high-power-density design is preferred. The partial-admission design allows for reduced losses: The turbine rotor and stator blades are prismatic, have a radial chord length of 1 mm and a height of 0.59 mm. Since the relative rotor blade tip clearance (0.24) is high, the blade tip leakage losses are significant. Considering a fixed steam supply, this design allows to increase the blade height, and thus reducing the losses. The steam turbine drives a fan, which operates at low Mach numbers. The rotor is supported on dynamic steam-lubricated bearings; the nominal rotational speed is 175 krpm. A numerical simulation of the steam turbine is in good agreement with the experimental results. Furthermore, a novel test rig setup, featuring extremely-thin thermocouples (ϕ0.15 mm) is investigated for an operation with ambient and hot air at 220 °C. Conventional zero and one-dimensional pre-design models correlate well to the experimental results, despite the small size of the turbine blades.
Influence of Shunt Injection on Predicted Rotordynamic Coefficients of a Labyrinth Seal Using Transient CFD
Authors: Thorat Manish R. , Jin Hanxiang , Pettinato Brian 
Published: January 2021

Abstract
Shunt injection is one of the methods used to improve rotordynamic stability of centrifugal compressors. It involves eliminating swirl by injecting fluid in an intermediate cavity of a seal. The fluid injection is usually directed from the discharge volute or diffuser section of the compressor. In this paper, shunt injection is modeled for a center seal in a back-to-back compressor arrangement. The test case is from an actual machine which was shown to be unstable during a factory loaded mechanical test (as per API standard 617) without shunt injection and stable with shunt injection. The center seal is a tooth-on-rotor type of labyrinth seal. Impeller back-face cavity passages at the entrance and exit of the seal are also modeled. To investigate the influence on shunt injection, models with and without shunt injection geometry are considered.
Steady state Computational Fluid Dynamics (CFD) is used to study the influence on steady state characteristics such as leakage rate and swirl ratio. The CFD analysis shows a significant swirl reduction with shunt injection at the injection location. The estimated swirl ratio is 0.55 at the injection location without shunt injection and approximately 0 with shunt injection. Frequency dependent seal rotordynamic coefficients are evaluated using transient CFD. Both translational and moment coefficients are evaluated for the seal and impeller passages. For the case without shunt injection, CFD results show negative (destabilizing) effective damping from the seal at the rotor first damped natural frequency. Shunt injection case shows a positive (stabilizing) estimated effective damping at the frequency of interest. The CFD results are shown to be consistent with the factory test case observations.
Investigation of Recirculating Casing Treatment for Low-Pressure Ratio Mixed-Flow Micro-Compressor
Authors: Xu Kewei , Zha Gecheng 
Published: January 2021

Abstract
This paper investigates the recirculating casing treatment (RCT) of a low total pressure ratio micro-compressor to achieve stall margin enhancement while minimizing the design point efficiency penalty. Three RCT injection and extraction configurations are studied, including combined slot-duct, ducts only, and slot only. The numerical approach is validated with a tested micro-compressor using RCT. A very good agreement is achieved between the predicted speedlines and the measured results. To minimize the design point efficiency loss, it is observed that the optimal location of extraction and injection is where the recirculated flow rate can be minimized at the design point. To maximize stall margin, extraction location should favor minimizing the tip blockage such as at the location where the tip flow separation of the baseline blade is fully developed. In addition, the slot configuration that generates pre-swirl to the upstream flow is beneficial to improve stall margin due to reduced incidence. The highest stall margin enhancement achieved is 9.49% with the slot geometry that has the extraction at the 62%C chordwise location, but has a design point efficiency loss of 1.9%. Overall, a small efficiency penalty of 0.6% at the design point is achieved for the final design with the stall margin increased by 6.2%.
Ignition Studies of C1–C7 Natural Gas Blends at Gas-Turbine Relevant Conditions
Authors: Sahu Amrit Bikram , Mohamed A. Abd El-Sabor , Panigrahy Snehasish , Bourque Gilles , Curran Henry 
Published: January 2021

Abstract
New ignition delay time measurements of natural gas mixtures enriched with small amounts of n-hexane and n-heptane were performed in a rapid compression machine to interpret the sensitization effect of heavier hydrocarbons on auto-ignition at gas-turbine relevant conditions. The experimental data of natural gas mixtures containing alkanes from methane to n-heptane were carried out over a wide range of temperatures (840–1050 K), pressures (20–30 bar), and equivalence ratios (φ = 0.5 and 1.5). The experiments were complimented with numerical simulations using a detailed kinetic model developed to investigate the effect of n-hexane and n-heptane additions. Model predictions show that the addition of even small amounts (1–2%) of n-hexane and n-heptane can lead to increase in reactivity by ∼40–60 ms at compressed temperature (TC) = 700 K. The ignition delay time (IDT) of these mixtures decrease rapidly with an increase in concentration of up to 7.5% but becomes almost independent of the C6/C7 concentration beyond 10%. This sensitization effect of C6 and C7 is also found to be more pronounced in the temperature range 700–900 K compared to that at higher temperatures (&gt; 900 K). The reason is attributed to the dependence of IDT primarily on H2O2(+M) ↔ 2ȮH(+M) at higher temperatures while the fuel dependent reactions such as H-atom abstraction, RȮ2 dissociation or Q.OOH + O2 reactions are less important compared to 700–900 K, where they are very important.