bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Hybrid, Runtime Coupled Incompressible CFD/CAA Method for Analysis of Thermoacoustic Instabilities
Authors: Reinhardt Hanna , Alanyalıoğlu Çetin , Fischer André , Lahiri Claus , Hasse Christian 
Published: October 2022

Abstract
Thermoacoustic instabilities in gas turbine engines are of increasing interest for design of future low-emission technology combustors. Numerical methods used to predict thermo-acoustic instabilities often employ either fully compressible resource-intense Computational Fluid Dynamics (CFD) simulations, or two-step approaches where source terms extracted from CFD simulations are supplied to subsequent Computational Aero Acoustics (CAA) simulations. The present work demonstrates an analysis of self-excited thermoacoustic instabilities using a hybrid method based on runtime coupling of incompressible CFD and CAA simulations. A prior implementation for the computation of combustion noise through one-way coupling of CFD and CAA solvers has been extended to a two-way coupling that allows acoustics to influence the flow field. The resulting hybrid method couples acoustic and convective physical phenomena by using mean flow field quantities and the thermoacoustic energy source term obtained from the solution of the Navier-Stokes equations in the low Mach number limit as an input for the Acoustic Perturbation Equations (APE). The fluctuating acoustic quantities pressure and velocity obtained from the solution of the APE are in turn included in the solution of the low Mach number Navier-Stokes equations, influencing the convective dynamics of the flow field. The suitability of the present implementation to capture thermoacoustic feedback is demonstrated through analysis of the well-known self-excited instability observed in a Rijke Tube. The results are presented and discussed in comparison with a fully compressible reference solution.
Thermal Management for Electrification in Aircraft Engines: Optimization of Coolant System
Authors: Raske N. , Ausin Gonzalez O. , Furino S. , Pietropaoli M. , Shahpar S. , Montomoli F. 
Published: October 2022

Abstract
This work shows the application of fluid Topology Optimization for the thermal management of electric parts in aircraft engines. There is a growing trend in electrification of current engines, but this requires higher power to be dissipated. Standard coolant systems based on serpentines are not effective enough to remove the heat produced by these systems. In this work a new solution is shown which has a higher heat dissipation, lower pressure loss and a reduction in the mass of the heat exchanger. The optimization is carried out with the commercial solver TOffee. Manufacturing constraints allow the part to be manufacturable using two different methods: additive manufacturing and milling with diffusion bonding.
Overall, the optimized geometry, a nearly 2D coldplate with extruded channels, shows higher heat dissipation and a reduction of weight of 38.5% if compared with the baseline heat exchanger. The overall pressure drop has been also reduced by 65%.
Study on Unsteady Flow Characteristic in a Transonic Axial Compressor Rotor at Near Stall Condition
Authors: Zhang Ziyun , Wu Yanhui , Li Ziliang 
Published: October 2022

Abstract
In this paper, the three dimensional single-channel numerical simulation has been undertaken to analyze unsteady flow characteristic and fluctuation mechanism at near stall condition in a transonic compressor rotor. It has been found that at near stall condition, strong unsteady fluctuations appeared at the region near the downstream of shock wave and leading edge to 80% axial chord of blade pressure side in rotor tip. Then, detailed analysis of the tip flow field showed that the interaction between tip leakage vortex (TLV) and shock waves causes the spiral type breakdown of TLV, and caused reverse flow periodic shedding in the recirculation region, both of the effects given rise to the large fluctuation of the rotor tip field. Periodic shedding of the reverse flow affected the pressure distribution of blade pressure side so that the blade tip was unloaded and the tip leakage vortex breakdown was thus suppressed, thereby forming a self-sustaining unsteadiness. The TLV breakdown was the decisive factor leading to the flow unsteadiness.
Solution-Based Mesh Adaption Criteria Development for Accelerating Flame Tracking Simulations
Authors: Shrivastava Sourabh , Verma Ishan , Yadav Rakesh , Nakod Pravin 
Published: October 2022

Abstract
Accurate flame tracking plays a vital role in predicting the combustion characteristics of a system. This is even more critical for systems that evolve over time. Predicting relight performance of an aero combustor, predicting flame propagation due to gas leakage from a storage tank or during the thermal runaway of batteries, are some examples of such dynamic systems. Predicting accurate flame position also plays an important role in deriving the correct pollutant formation rate from a combustion system.
The challenge with flame tracking through a 3D computational fluid dynamics (CFD) simulation comes from the requirement to have a good resolution of gradients along the flame front. This requirement can push the overall mesh count of any industrial cases to a very large value (several million-mesh count). Further, the global drive towards using hydrogen or hydrogen blended fuels for different combustion applications pushes the limits on having even finer cells since hydrogen is a fast-burning fuel and has a much thinner flame front compared to hydrocarbons.
Solution-based mesh adaption approaches have been widely studied and tested by different research groups to generate the required finer meshes in the critical regions on the fly while keeping the overall mesh count to a manageable level. However, these approaches are typically applicable for a set of problems, and therefore, there is a need for a generic approach suitable for a broader range of problems. This work explores various parameters and specific weightage factors to predict correct flame-tracking outcomes for different types of flames. The selections of flow quantities (flow-variables, their gradients, curvatures) are performed using simple flames and flow configurations. The functions based on selected flow-quantities derived from these studies are then tested to predict the results for the more complex set of published flames like the Engine Combustion Network (ECN) spray flame and Knowledge for Ignition, Acoustics and Instabilities (KIAI) five-burner configuration (liquid and gas fuel). Derived adaption criteria are found to predict the correct flame tracking behavior in terms of transient evolution of flame front, flame propagation, and ignition timing of burners. The parameters used for the study are identified keeping genericity as the key point, and thus making sure that the derived adaption functions can be applied across different types of fuel blends, combustion systems (gaseous or liquid fuel-based systems) and combustion models, for example species transport or mixture fraction-based models.
Condition Monitoring of Wind Turbines Based on Anomaly Detection Using Deep Support Vector Data Description
Authors: Peng Dandan , Liu Chenyu , Desmet Wim , Gryllias Konstantinos 
Published: October 2022

Abstract
Wind turbine condition monitoring is considered as a key task in wind power industry. A plethora of methodologies based on machine learning have been proposed but the absence of faulty data, at the amount and the variety needed, still set limitations. Therefore Anomaly Detection methodologies are proposed as alternatives for fault detection. Deep learning tools have been introduced in the research field of wind turbines’ monitoring for the purpose of higher detection accuracy. In this work, a deep learning-based anomaly detection method, the Deep Support Vector Data Description (Deep SVDD), is proposed for the monitoring of wind turbines. Compared to the classic SVDD anomaly detection approach, this method combines a deep network, more specifically a Convolutional Neural Network (CNN), with the SVDD detector in order to automatically extract effective features. To test and validate the effectiveness of the proposed method, the Deep SVDD method is applied on SCADA data from a real wind turbine use case, targeting to the ice detection on wind turbine blades. The experimental results show that the method can effectively detect the generation of ice on wind turbines’ blades with a successful detection rate of 91.45%.
Characterizing Flow Instabilities During Transient Events in the Turbine Rim Seal Cavity
Authors: Rozman Maria , DeShong Eric T. , Berdanier Reid A. , Thole Karen A. , Robak Christopher 
Published: October 2022

Abstract
Gas turbine engine design requires considerations not only for long-term steady operation, but also for critical transient events. Aircraft engines undergo significant stress during takeoff and landing while power generation turbines must be flexible for hot restarts as renewable energy sources come on and offline. During these transient cycles, engines sustain wear and degradation that can lead to a reduction in the lifespan of their components and more frequent, costly maintenance. Cooling flows are often used to mitigate these effects, but can lead to complex and problematic flow interactions. This study uses high frequency response pressure probes and heat flux gauges in the rim seal cavity of a one-stage research turbine to characterize the properties of large-scale flow structures during transient operation. A continuous-duration turbine testing facility provides the ability to assess the importance of these transients by first reaching steady state operation prior to imposing transient behaviors. Although previous studies have conducted similar measurements for steady purge flows and wheel speeds, varying these parameters to simulate transient effects revealed several unique phenomena not identifiable with discrete steady measurements. The measurement approach connects the varied transient parameter to the behavior of the flow structures to enable a better understanding of the type of instability observed and the root cause of its formation. In particular, a relationship between instability cell formation and rim sealing effectiveness was identified using experimental data and was supported through computational simulations.
Mean-Line Design and Optimization of Axial-Flow Turbines Based on Mixed Integer Nonlinear Programming
Authors: Dipierro Vincenzo , Martinelli Matteo , Persico Giacomo , Martelli Emanuele 
Published: October 2022

Abstract
This work proposes a novel equation-oriented approach for the mean-line design optimization of axial-flow turbines, in which turbine constitutive equations and design specifications are included as constraints of the optimization problem. The problem is formulated as a MINLP (Mixed Integer Nonlinear Programming), including either Soderberg or Traupel loss models. This model formulation allows the use of the gradient/Hessian information of both constraints and objective function, speeding-up the optimization process. Moreover, it allows using “Spatial Branch-and-Bound” optimization algorithms (e.g., BARON) which have guaranteed global optimality. After an exhaustive validation, the model is applied to the optimization of two case studies (air and sCO2 as working fluids), resulting in certified optimal solutions and computational time lower than the black-box approach.
Using Engineering Enhanced AI to Forecast Combined Cycle Power Plant Performance in the Presence of Uncertain Weather Conditions
Authors: Perullo Christopher A. , Boche Lea , Redling Alex , Lim Jamie , Choi Woosung , Lieuwen Timothy C. , Noble David 
Published: October 2022

Abstract
Characterizing the performance of gas fired combined cycle power plants is critical to economic dispatch decisions. Dispatch models rely on an accurate prediction of Gas Turbine and combined cycle power output and heat rate. Approaches for generating performance characteristics range from correction curves to detailed thermodynamic performance models. Unfortunately, most techniques are either too simplified, require significant expertise, or are manually labor intensive. Furthermore, these performance estimation techniques do not intrinsically capture uncertainty due to the inherent variability of the weather and state of the asset. This paper proposes a physics-enhanced Artificial Intelligence technique for automatically characterizing power plant performance including uncertainty due to weather effects. The model uses a layered sub-model approach to rapidly learn power plant performance without the need for extensive data preparation. The proposed technique is used to evaluate for accuracy, ease of use, and level of automation. The new technique is accurate to within 1% and provides a power and efficiency forecast one week out. The technique is also applicable to other power generation assets and scaling techniques, and challenges will be discussed. An overview of the automation framework is provided including discussion on modeling approaches, AI approaches used, modeling techniques, and use cases.
Formaldehyde Emissions from Dry Low Emissions Industrial Gas Turbines
Authors: Carlos Ivan , Witherspoon Leslie , Cowell Luke , Saxena Priyank 
Published: October 2022

Abstract
Formaldehyde is listed as a Hazardous Air Pollutant (HAP) by various regulatory agencies around the world because of its role as a carcinogen. To address this impact, several countries have regulated formaldehyde emissions from land-based gas turbines. In the United States (U.S.), the federal regulatory level is 91 ppb and state level formaldehyde requirements vary significantly. In Germany, the formaldehyde limit is 5 mg/Nm3 (∼3.7 ppm) from 70–100% load. Formaldehyde emissions from gas turbines are formed due to incomplete combustion of natural gas and predictably track with carbon monoxide (CO) and unburned hydrocarbon (UHC) emissions trends. This paper presents results from a formaldehyde measurement campaign completed in test cells at Solar Turbines on Dry Low Emissions (DLE) turbine products including the Mars® 100, Titan™ 130 and Titan™ 250 operating on pipeline natural gas. Theoretical modeling of formaldehyde formation using a Chemical Reactor Network (CRN) model are also presented. Measurements have been taken in the engine test cells over a range of operating conditions from full load* to idle. The latest Fourier Transform Infrared (FTIR) technology has been used to meet the challenges of accurately measuring formaldehyde down to the 10-ppb detection level. Formaldehyde emissions were found to range from near the detection limit to 50 ppb at full load with a small increase as load is decreased within the typical DLE operating range and a sharper increase outside of DLE mode to idle. The variation is attributed to differences between gas turbine models based on pressure ratio and combustion system design. CRN modeling predictions were compared with the test data, and the modeling results were used to gain insight into the formaldehyde emissions formation mechanisms.
Design and Validation of an Improved Lower Emission Additively Manufactured Combustor Pilot Nozzle for F Class Industrial Gas Turbine
Authors: Kalb Bryan , Yaquinto Matthew , Vogel Gregory , Keshava Bhattu Ramesh 
Published: October 2022

Abstract
Emerging additive manufacturing technology offers many opportunities for improved design in gas turbine components by enabling optimization of parts that are not manufacturable with conventional methods. The combustion components, for example, require complex fuel and air circuits to achieve best possible mixing and oxidation process for the lowest emissions possible. Thanks to the additive manufacturing, new combustor parts are making a break thru for improved capabilities in fuel flexibility and operating conditions. Also, quick turn around and modularity makes additive manufacturing a key enabler for fast validation of design concepts.
This paper describes the application of additive manufacturing technology in an F class industrial gas turbine including design, development and validation steps of a combustor pilot nozzle. A systematic design approach was undertaken to examine all aspects of combustion operation and testing, down-selecting the appropriate design, material and to productionize. Experience gained from other additive manufactured production parts as well as testing coupons were leveraged to ensure a robust production process. Combustion atmospheric rig testing was conducted to validate emissions performance. Detailed thermal and structural analyses were performed and validated with testing experience.
The new design demonstrated a benefit of approximately 50% in start-up emissions as well as improved combustion stability. In addition to the operability benefits, a 50% reduction in cost of the production assembly was realized. A main cost advantage gained with the utilization of additive manufacturing was the reduction in part quantity from 7 individual components down to 1. Constraints typical of conventional manufacturing methods were avoided with the implementation of innovative geometries only achievable by additive manufacturing. In addition to combustor component reduction, the additive process was also leveraged to reduce the total number of fuel circuits in the combustion system, making the installation and control logic more straightforward.
Several sets were successfully installed in customer’s engines, benefiting from an improved combustor pilot nozzle. Detail of the design and development steps as well as the results of combustion tests are presented and discussed in this paper. It shows that with proper considerations of the additive manufacturing technology, very quick turn-around and implementation of improved combustions solutions can be achieved: less than a year from development to production.
The Cooling Effect of Combustor Exit Louver Scheme on a Transonic Nozzle Guide Vane Endwall
Authors: Mao Shuo , Van Hout Daniel , Zhang Kaiyuan , Ng Wing F. , Xu Hongzhou , Fox Michael 
Published: October 2022

Abstract
The ever-increasing combustor exit temperature in modern turbine engine designs raises challenges for the nozzle guide vane cooling. Due to the challenges of NGV cooling design, the cooling effect from the combustor cooling features can prove valuable. This study investigates, experimentally and numerically, the cooling effect of a louver cooling scheme near the combustor exit on the NGV endwall. The wind tunnel testing and CFD simulation are carried out with engine-representative conditions of Maexit = 0.85, Reexit = 1.5 × 106, Tu = 16%, and DR = 2.1. Various coolant mass flow rates from 1% to 4% are tested to demonstrate the effect of the coolant rate.
For the geometry studied, the results found a critical MFR between 1%∼2%. By exceeding this value, the coolant forms a uniform film which provides good coverage upstream of the NGV passage inlet. As for the cooling of the NGV passage, the MFR of the range investigated is not sufficient for desirable cooling performance. The pressure side endwall proves most difficult for the coolant to reach. In addition, the fishmouth cavity at the combustor-NGV passage causes a three-dimensional cavity vortex that transports the coolant in the pitch-wise direction. The coolant transport pattern is dependent on the coolant MFR. Based on the results, it is proposed to combine this louver scheme with the upstream jump cooling scheme for a desirable NGV cooling system.
Numerical Investigations on the Rotating Stall in an Axial Compressor and Its Control by Flow Injection at Casing
Authors: Marty Julien , Castillon Lionel , Joseph Pierric 
Published: October 2022

Abstract
The operating range of a compressor is limited by surge or rotating stall line, among others. Numerical simulations must accurately predict these phenomena. This study is based on the experimental compressor CME2, which is a low-subsonic axial compressor. This compressor is tip-critical as the rotor tip is responsible for the rotating stall. This paper shows that the rotating stall onset flow rate is well captured by CFD, compared to experiments. After ten revolutions, all cells are merged and only one cell remains, as in experiments.
Active flow control improves compressor performance and extends the stable operating range. In the present configuration, flow injection is performed at the casing. In the simulation, the insertion of the actuators is carried out through hybrid meshes: structured mesh for blade passages and unstructured mesh for each actuator. For the some stalled operating points of baseline configuration, there is no rotating cells in the controlled configuration. Thus, the rotating stall is delayed at lower flow rate, as expected by the use of active flow control and is in agreement with the experiments.
Measurement of Inertial and Acoustic Waves in a Turbine Chute Rim Seal Cavity
Authors: Bru Revert Anna , Beard Paul F. , Chew John W. 
Published: October 2022

Abstract
A chute rim seal cavity has been instrumented with time resolved and time-averaged pressure transducers as well as a gas concentration measurement system at the Oxford Rotor Facility. The unsteady pressure transducers were unevenly distributed along the circumference generating 15 combinations of angular spacing to conduct a phase analysis. The test operating conditions were modified through different configurations of mainstream flow, a range of rotational speeds and purge flows to obtain test data in the regimes of rotationally-driven, pressure-driven and combined ingestion. The rotating unsteady flow structures within the rim seal cavity were studied through a combination of phase analysis of dynamic pressure signals and inspection of the frequency domain. The introduction of mainstream flow (axial and swirled) increased the overall unsteadiness exciting an additional band of lower frequencies. The phase analysis revealed these were associated with acoustic waves, providing the first experimental evidence of the presence and coexistence of inertial and acoustic waves in the rim seal cavity. The interaction of the inertial and acoustic waves strongly depends on the operating conditions, and may be linked to changes in sealing effectiveness.
Establishment of a Baseline Integrated Energy System to Decarbonise Geographical Islands
Authors: Mansouri Mohammad , Madi Hossein , Breuhaus Peter 
Published: October 2022

Abstract
Achieving strict decarbonisation targets, while providing a safe, reliable, and affordable supply of energy on geographical islands is more complex than in mainland locations. Contrary to the mainland, where grid support and energy exchange with other regions are possible because of integration into large energy grids, the situation for geographical islands is different. Islands often have either no or limited connection to neighbouring ones or to the mainland resulting in a relatively costly energy supply and less opportunities for services such as balancing or backup to overcome the challenges that fluctuating renewables can cause. This can be tackled by development of highly flexible energy systems integrating various available renewable energy sources, multiple prime movers, and necessary energy storage and transportation infrastructure.
A currently ongoing ROBINSON project aims at contributing to decarbonise geographical islands by developing and installing a demonstrator of an integrated energy system on the island of Eigerøy in the southwest coast of Norway. As part of the ROBINSON project, this paper presents a brief overview of the project and its objectives, the baseline configuration of the integrated energy system and its energy fluxes that will be demonstrated on the island of Eigerøy in Norway. Even though the project is still in an early stage of implementation, this paper describes possible challenges and resulting requirements of different sub-systems including a gas turbine based combined heat and power unit within a highly integrated energy system.