Turbine Disk Research Articles

Tool wear prediction in broaching based on tool geometry

Abstract The aircraft engine is a safety-critical part of an aircraft. Constructive modifications resulting in ecological and economic improvements of the engine lead to necessary changes in manufacturing processes. The turbine discs in the low-pressure section are made of temperature resistant nickel-based superalloys. For the connection of the turbine blades with the disc, fir-tree slots are machined by broaching. The broaching process achieves high geometrical accuracy as well as process reliable rim zone properties. Alternative manufacturing processes such as milling or wire electrical discharge machining are still the subject of research in many applications and do not yet achieve the required process reliability. Especially in finishing operations, tool geometry is complex. In previous research work, the local rake angle and, as a result, the acting cutting force were determined analytically and empirically. Based on these results, the relationship between tool geometry, cutting force, and tool wear will be investigated in this work to enable a cutting length dependent prediction of tool wear. The aim of this work is a model-based prediction of tool wear for a given cutting length and a previously unknown tool geometry. For this purpose, a method was developed to predict tool wear using empirical test data as well as internal machine data. With the results of this work, it is not only possible to identify critical points on newly developed broaching tools by maxima of the cutting force, but also to predict wear locally, depending on the cutting length.

Simulation method for dynamic characteristics of rotor-support system subjected to environmental loads

An improved finite element method was proposed to investigate the dynamic characteristics of rotor system with environmental loads (temperature and aerodynamic forces) in aeroengines. According to the axial temperature distribution within shaft elements, the polynomials were established for physical properties of material. The derivation for coefficient matrices under thermal loads, and the tensile stiffness matrix considering axial aerodynamic forces were completed, based on the Timoshenko beam theory. A high-pressure rotor was simulated with operating temperature 200∼600∘C, and the magnitude of aerodynamic force is 105N. Furthermore, a squeezed film damper (SFD) was adopted to this rotor-support system, its steady responses were solved by the equivalent coefficient method, and the Newmark-HHT method was utilized to solve the transient responses. The results indicate that the first two critical speeds are reduced by 1.85 % and 2.07 %, which is mainly caused by thermal loads. The rising temperature leads to lower elastic modulus, higher Poisson's ratio and expansion ratio. With the amount of a mass unbalance being 500 g·mm located at the 1st-stage compressor disk (CD1): the 1st resonance peaks at CD1 and turbine disk (TD) increase by 4.56 % and 4.98 %, respectively, and the 2nd resonance peaks at CD1 and TD rise 5.88 % and 5.00 %, separately. Owing to SFD damping, the first two resonance peaks at CD1 and TD decrease by 69 % and 51 %, respectively. Compared to 40 °C, the first two resonance peaks at CD1 increase by 88 % and 55 % at the oil temperature 100 °C. The oil-film damping deteriorates significantly due to the lower oil viscosity in higher temperature. When operating near the first-order critical speed, the transient responses of rotor perform as simple harmonics, circular precession trajectory, dominant rotational frequency, and periodic motions. Overall, the dynamic characteristics of rotor-SFD-support systems exposed to environmental loads can be predicted by the proposed simulation method.

Probabilistic risk assessment of civil aircraft associated failures under condition-based maintenance

Maintenance can improve an aircraft system's reliability over a long operation period or when a component has failed. However, inappropriate maintenance inspection intervals will cause latent failures to be covered or undetected, leading to a large number of unplanned flight disruptions for airlines. In this paper, we present a two-stage framework to assess the associated failure risk of civil aircraft under condition-based maintenance. In the first stage of the framework, the probability of primary functional failure across the lifecycles of the monitored component is determined by analyzing whether the current inspection interval prevents the component from progressing from latent failure to functional failure. In the second stage of the framework, the associated failure probability between components and related systems is formulated by the adjacency matrix. The structure and performance of the proposed model were tested on a case study by run-to-failure data associated with aircraft engines from a large airline. Focusing on the scenario of turbine disk cracking leading to fragment penetration of the fuel tank and causing fire as the consequential fault impact path, the results show that the risk of aircraft fire caused by turbine disk fragments falls within an acceptable range, necessitating the completion of inspections and subsequent monitoring within the stipulated timeframe. The method can be used to readjust the inspection interval, optimize the operation plan, improve the on-time performance of flights, and reduce the risk of aviation accidents.

Fatigue Failure Of Steam Turbine Discs - A Centenary Tribute To Wilfred Campbell

Abstract The year 2024 marks one hundred years since Wilfred Campbell published his landmark work on vibrational analysis of rotating disc following a series of disc failures in steam turbines. Despite the absence of advanced engineering analytical tools, Campbell came up with an elegant method to visually demonstrate and capture the mode shapes in rotating discs. The first part of this paper reviews Campbell?s life and analytical and experimental work in this area. Regardless of the current advanced engineering capabilities to predict nodal shapes in turbine discs, turbine discs still experience failures related to vibration. The second part of the paper discusses a recent case study where a turbine disc failure occurred as a result of vibration. The discussion includes metallurgical root cause failure analysis and engineering analysis to predict the vibrational characteristics. Metallurgical failure analysis confirmed that the primary mode of failure was fatigue and did not have any issues with the disc material or its mechanical properties. Finite element modeling and analysis were used for the engineering analysis to predict the natural frequencies of the bladed-disc. The engineering analysis showed the evidence of potential resonance, and the failure was related to nodal vibration issues.

Multi-Objective Optimization of the Pre-Swirl System in a Twin-Web Turbine Disc Cavity

Enhancing thermal efficiency and minimizing weight are prevailing issues in aero engines. Owing to its hollow structure, the twin-web turbine disc exhibits remarkable weight reduction properties, while its enhanced cooling constitutes a novel challenge. In this study, a twin-web turbine disc cavity system is numerically investigated. To enhance the cooling effect and minimize pressure loss, a multi-objective genetic algorithm and Kriging surrogate model are employed to optimize the radial height of the pre-swirl nozzle and receiver hole in the disc cavity system. The results indicate that the overall performance of Opt-3, derived from the Technique for Order Preference by Similarity to the Ideal Solution method within the Pareto frontier, is superior. This configuration achieves a uniform low distribution of rotor temperatures while maintaining moderate pressure losses. Notably, the maximum temperature is reduced by 21.1 K compared to the basic model, with pressure losses remaining largely unchanged. Additionally, an increase in the flow ratio leads to a reduction in both the maximum temperature and average temperature of the back web while simultaneously increasing the temperature of the front web and augmenting pressure losses. However, it is important to note that the degree of variation in these parameters diminishes with increasing flow ratios.

A modified cyclic elastoplastic constitutive model considering the variational dynamic recovery term of back stress for FGH95 under asymmetrical cyclic loading

The asymmetric cyclic loading process occurs in aero-engine turbine discs. A constitutive model that accurately describes the cyclic elastoplastic behaviour of the material is important for structural design and low cycle fatigue life prediction of turbine discs. In this paper, the low cycle fatigue test of FGH95 was carried out at 620℃ under 0.5%, 0.6%, 0.7%, 0.8%, 0.9%, 1.0% and 1.1% strain amplitude with strain ratio equal to 0. The material exhibited cyclic hardening followed by cyclic softening at high strain amplitudes and cyclic softening at low strain amplitudes. The mean stress relaxation rate was similar for each strain amplitude. In addition, the evolution of effective stress and back stress was obtained through the method of internal stress division. Then, the relationship between the change in stress amplitude and the change in internal stress was discussed. The results showed that with cyclic loading, cyclic hardening/softening of FGH95 was affected by the competition mechanism of back and effective stresses. Considering that slip deformation and crystal lattice rotation coexist in plastic deformation, the dynamic recovery term of the Abdel-Karim and Ohno model was used. In order to characterize the different magnitudes of back stress change in materials at different plastic strain intervals, a dynamic recovery term coefficient was introduced to the dynamic recovery term and the critical surface of the back stress. The modified model was used to compare with experimental results. Then, it gives a good description of the material’s mean stress relaxation and strain amplitude variation and gives good agreement on the hysteresis loop.

Constitutive model of high-temperature rapid fracture of Si3N4 ceramics for engine turbine discs and their pore insensitivity parameters

ABSTRACT The metallic materials used to manufacture turbine components can potentially be replaced with ceramics such as Si3N4, but the stress on turbine discs is difficult to determine experimentally, which hinders the development and optimization of ceramics. The finite element method solves this problem, but it requires an accurate constitutive model and parameters. Existing methods for determining model parameters lack versatility and do not consider the internal pores of ceramics. This work proposes a method for determining the parameters of the high-temperature rapid fracture constitutive model of ceramics with internal pores based on the results of industrial computed tomography (CT) and high-temperature fracture toughness experiments. The constitutive model for a ceramic with internal pores was selected based on the typical service conditions of turbine discs. Industrial CT was used to measure pore information. A finite element preprocessor was developed to create simulated specimens with pores. The high-temperature fracture toughness of the ceramics was measured. Pore insensitivity was the parameter obtained from the high-temperature constitutive model of ceramics with pores using this method. The maximum relative error between the predicted and experimental flexural strengths was 6.8%. It provides a new idea for determining the parameters of constitutive models for materials with pores.

Topology Optimization of 3D Turbine Disk Considering Thermal Load Based on BESO Method

Topology Optimization of 3D Turbine Disk Considering Thermal Load Based on BESO Method

Genetic Optimization of Twin-Web Turbine Disc Cavities in Aeroengines

Genetic Optimization of Twin-Web Turbine Disc Cavities in Aeroengines

The diminishing positive effect of phosphorus on the creep behavior with the decrease of applied stress in a Ni-Fe-based alloy

Phosphorus can increase the creep and stress-rupture properties of the turbine disk materials served in high stress with short life. However, the effect of P on the creep of boiler tube in advanced ultra-supercritical power plants served in low stress with long life is still unknown. Combining the formula derivation and experimental analysis, the varying effects of P on the creep with the decrease of stress were clarified. The positive effect of P on prolonging the creep rupture life reduces with the decrease of creep stress, even vanishes when the creep stress decreases to 93 MPa, 133 MPa and 140 MPa in the alloy doping 100 ppm, 200 ppm and 400 ppm P, respectively. The degeneration of M23C6 and the dynamic segregation of P at grain boundary during long-term creep under low stress can decrease the deformation coordination between the adjacent grains and the grain boundary binding force, which makes the positive effect of phosphorus on the creep diminish.

An improved adaptive Kriging method for the possibility-based design optimization and its application to aeroengine turbine disk

Possibility-based design optimization (PBDO) can provide theoretical basis for the structural optimal design of fuzzy uncertainty model in engineering, so as to obtain the optimal design variables. The genetic algorithm (GA) based on adaptive Kriging method for PBDO requires high precision in the whole design space, while the region far from the limit state surface (LSS) of the constraint function has little effect on PBDO, thus greatly affects the computational efficiency. In order to improve the efficiency of PBDO, an improved adaptive Kriging method combined with active possibility constraint (I-AK-AC) is proposed in this paper. In I-AK-AC, the enhanced expected improvement learning function is first put forward to promote the convergence efficiency of Kriging model by reducing the accuracy of the region far from the LSS of the constraint function. Whereafter, the active possibility constraint is identified, and only the boundaries of active possibility constraint need to be approximated precisely by Kriging model. By these ways, the convergence speed of Kriging model is further ameliorated without affecting the computational accuracy, and the efficiency of PBDO is significantly improved. Three test examples and an engineering application of aeroengine turbine disk illustrate the validity and accuracy of the proposed I-AK-AC.

A weakest link theory‐based probabilistic fatigue life prediction method for the turbine disc considering the influence of the number of critical sections

A weakest link theory‐based probabilistic fatigue life prediction method for the turbine disc considering the influence of the number of critical sections

Nonlinear dynamics analysis of hydraulic turbochargers in reverse osmosis desalination plants

The hydraulic turbocharger plays a vital role in harnessing the energy stored in brine within reverse osmosis desalination plants. To optimize the efficiency and durability of this equipment, it is crucial to develop accurate dynamic models of the turbocharger rotor. An improved understanding of rotor dynamics enables the integration of innovative technologies such as Hydraulic Energy Management Integration, effectively enhancing efficiencies in systems characterized by small capacities and high rotational speeds. This study presents a dynamic modeling methodology for the hydraulic turbocharger. The analysis involves approximating the turbocharger rotor with an equivalent finite element shaft line model. Verification of the model’s natural frequency is conducted using three-dimensional finite element analysis, employing the ANSYS modal analysis module. Computational fluid dynamics is employed to evaluate the fluid forces, while the Reynolds equation is utilized to assess the journal bearing forces. The resulting model is employed to investigate the nonlinear dynamics of the rotor, examining the impact of various system parameters, including rotational speed, unbalance forces, and shaft geometrical parameters. The results highlight the significance of balancing the turbine and pump disks for optimal performance. Furthermore, the research demonstrates that increasing the shaft length reduces the rotor’s threshold speed, while increasing the shaft diameter initially raises the threshold speed until it reaches a critical value. Beyond this critical value, further increases in shaft diameter lead to a decrease in the threshold speed.

Mechanical characterization and microstructural evolution of Inconel 718 and SS316L TIG weldments at high temperatures

This study examines the impact of both constant and pulsed current on the tensile characteristics, micro-hardness of weld surface, and metallurgical properties of the Inconel 718 and SS316L weldments. The Tungsten Inert Gas (TIG) welding process utilized two distinct arc modes to combine incompatible metals. The pulse frequency was systematically adjusted within the range of 2 Hz–6 Hz in order to investigate its impact on the welding parameters. A tensile test was performed using a universal testing equipment under various temperature conditions, including room temperature and an elevated temperature of 350 °C. When the samples were welded at a frequency of 4 Hz, both the Ultimate Tensile Strength (UTS) and Yield Strength (YS) were greater compared to when the samples were welded at 2 Hz, 6 Hz, or a continuous arc mode. Furthermore, it was noted that the YS-to-UTS ratio was higher for the weldments produced at 4 Hz pulse frequency. The UTS of current and pulsed (4 Hz) modes at a temperature of 350 °C were determined to be 505 and 524 MPa, respectively. Pulse welding demonstrated a higher hardness number compared to steady welding due to the regulated rate of heat. The TIG weldments of Inconel 718 and SS316L demonstrated superior mechanical and metallurgical qualities when exposed to elevated temperatures. The practical implications of these findings are relevant to the fabrication of turbine discs and shafts.

Chebyshev-Homotopy Perturbation Method for Studying the Flow and Heat Transfer of a Non-Newtonian Fluid Flow on the Turbine Disk

Chebyshev-Homotopy Perturbation Method for Studying the Flow and Heat Transfer of a Non-Newtonian Fluid Flow on the Turbine Disk

Quantitative Microstructure Prediction of Powder High-Temperature Alloy during Solution Heat Treatment and Its Validation

Heat treatment, particularly solution heat treatment, is a critical process in the preparation of powder metallurgy superalloys, where the cooling process significantly impacts the microstructure. This study, based on thermodynamic and kinetic databases as well as the precipitation mechanism of strengthening phases, delves into the influence of cooling process, especially the cooling path, on the material’s microstructure. The results indicate that under slow cooling rates, the precipitated phases are more likely to exhibit a multimodal size distribution, while under rapid cooling rates, a unimodal distribution may form. The average cooling rate does not consistently accurately reflect the growth of the precipitated phases; even with the same average cooling rate, different cooling paths can lead to significant differences in the size of the precipitates. To accurately predict the size of the precipitates, it is necessary to consider the specific cooling process. Constant cooling rate experiments designed for the study and the dissection testing of full-size turbine discs produced in manufacturing validated the calculated results of the precipitates. Therefore, optimizing cooling through simulation calculations can effectively and accurately control the precipitates, thereby obtaining a microstructure that can meet performance requirements.

Difference in hot deformation behavior of a Ni–Fe based superalloy through cast-wrought and additive manufactured processes

Traditional cast-wrought superalloys have been challenging in cogging due to element segregation. However, additive manufacturing technology is anticipated as a novel method for producing low-segregation superalloys. A set of isothermal compression tests were conducted on a Ni–Fe based superalloy GH4169 in various processing conditions, including as-cast and as-homogenized alloy produced by triple melting (Alloy TMC and TMH), as well as additive manufactured alloy (Alloy AM). Flow stresses were examined to develop activation energy maps and processing maps. Additionally, microstructure evolutions were observed to investigate the mechanisms of recrystallization nucleation and grains refinement during hot deformation. Under specific deformation conditions, three alloys have developed to varying refinement stages. As Zener-Hollomon parameter Z decreases, the nucleation mechanism shifts from continuous to discontinuous dynamic recrystallization. Alloy TMH exhibits enhanced hot workability compared to TMC, which is attributed to its lower activation energy Q and more limited instability region. Q value of Alloy AM is slightly higher than that of TMH; however, it demonstrates a wider processing window. Utilizing AMed superalloys for hot deformation not only provides advantages in low segregation and fine grains, but also simplifies the process sequences. This is expected to break through the current technical bottleneck associated with higher performance superalloy turbine disks.

The Integration of ANN and FEA and Its Application to Property Prediction of Dual-Performance Turbine Disks.

Regulating the microstructure of powder metallurgy (P/M) nickel-based superalloys to achieve superior mechanical properties through heat treatment is a prevalent method in turbine disk design. However, in the case of dual-performance turbine disks, the complexity and non-uniformity of the heat treatment process present substantial challenges. The prediction of yield strength is typically derived from the analysis of microstructures under various heat treatment regimes. This method is time-consuming, expensive, and the accuracy often depends on the precision of microstructural characterization. This study successfully employed a coupled method of Artificial Neural Network (ANN) and finite element analysis (FEA) to reveal the relationship between the heat treatment process and yield strength. The coupled method accurately predicted the location specified and temperature-dependent yield strength based on the heat treatment parameters such as holding temperatures and cooling rates. The root mean square error (RMSE) and mean absolute percentage deviation (MAPD) for the training set are 50.37 and 3.77, respectively, while, for the testing set, they are 50.13 and 3.71, respectively. Furthermore, an integrated model of FEA and ANN is established using a Abaqus user subroutine. The integrated model can predict the yield strength based on temperature calculation results and automatically update material properties of the FEA model during the loading process simulation. This allows for an accurate calculation of the stress-strain state of the turbine disk during actual working conditions, aiding in locating areas of stress concentration, plastic deformation, and other critical regions, and provides a novel reliable reference for the rapid design of the turbine disk.

Robust Bayesian target vector optimization for multi-stage manufacturing processes

This research focuses on optimizing multi-stage manufacturing processes using Bayesian optimization (BO) with a robust Expected Improvement (EI) acquisition function. The aim is to optimize towards pre-selected target vectors, not to just minimize or maximize a function. To achieve this, we minimize the Euclidean distance between the actual and target output vectors, which requires transforming the Gaussian surrogate model posterior distribution into a non-central χ2(NCχ2) distribution. Furthermore, the distance measure additionally uses aleatoric uncertainty estimates of the actual output vectors to achieve robustness. We use a cascaded method that also considers the optimization results of intermediate stages, whereby optimization results are propagated from the last stage towards the first stage in each optimization iteration. By considering intermediate process outputs and aleatoric effects, our approach provides a robust optimization method for multi-stage manufacturing processes. To validate our method and to evaluate its properties, we use two artificial use cases. Moreover, we evaluate our approach in an industrial multi-stage forging process for the manufacturing of a nickel basis superalloy turbine disk, where involved stages are represented by corresponding 2D finite element method (FEM) DEFORM simulations. Evaluation suggests that our approach is superior in optimizing multi-stage manufacturing processes by considering all stage outcomes, robust distance measures, and the use of appropriate uncertainty distributions.

Dynamic Modeling and Experimental Modal Analysis for the Central Rod-Fastened Rotor With Hirth Couplings Based on Fractal Contact Theory

Abstract The central rod-fastened rotor of gas turbine exhibits pronounced noncontinuous characteristics due to the large number of contact interfaces between the compressor and turbine disks. It is necessary to establish an accurate dynamic modeling method for the central rod-fastened rotor that fully considers the contact surface effect. In this work, the contact behavior of the rough surface is characterized by the fractal theory. The normal and tangential contact stiffness models are developed, and the influence of fractal parameters is discussed. Besides, the finite element model for the central rod-fastened rotor is established by developing an improved contact element considering the equivalent stiffness segment of Hirth couplings. Finally, the proposed model is verified by conducting the modal testing and measuring the first four modes of natural frequencies and modal shapes of the central rod-fastened rotor. The results show that the numerical results are in good agreement with the experimental ones, and the fractal contact model can effectively predict the connection stiffness of Hirth couplings, which in turn improves the simulation accuracy for the modal characteristics of the central rod-fastened rotor and provides a dynamic modeling approach with high efficiency and less computational complexity.