Int. J. Turbomach. Propuls. Power, Volume 10, Issue 3 (September 2025) – 11 articles

The present study reports the outcome of an experimental study of organic vapor trailing edge flows. As a working fluid, the organic vapor Novec 649 was used under representative pressure and temperature conditions for organic Rankine cycle (ORC) turbine applications characterized by values of the fundamental derivative of gas dynamics below unity. An idealized vane configuration was placed in the test section of a closed-loop organic vapor wind tunnel. The effect of the Reynolds number was assessed independently from the Mach number by charging the closed wind tunnel. The airfoil surface roughness and the trailing edge shape were evaluated by experimenting with different test blades. The flow and the loss behavior were obtained using Pitot probes, static wall pressure taps, and background-oriented schlieren (BOS) optics. Isentropic exit Mach numbers up to 1.5 were investigated. Features predicted via a simple flow model proposed by Denton and Xu in 1989 were observed for organic vapor flows. Still, roughness affected the downstream loss behavior significantly due to shockwave boundary-layer interactions and flow separation. The new experimental results obtained for this organic vapor are compared with correlations from the literature and available loss data. Full article

Non-synchronous vibration (NSV), flutter, or rotating stall can cause severe blade vibrations and limit the operating range of compressors and fans. To enhance the understanding of these phenomena, this study investigated the corresponding mechanisms in modern composite ultra-high-bypass-ratio (UHBR) fans based on the ECL5/CATANA test campaign. Extensive steady and unsteady instrumentation such as stereo-PIV, fast-response pressure probes, and rotor strain gauges were used to derive the aerodynamic and structural characteristics of the rotor at throttled operating conditions. The study focused on the analysis of the transition region from transonic to subsonic speeds where two distinct phenomena were observed. At transonic design speed, rotating stall was encountered, while NSV was observed at 90% speed. At the intermediate 95% speedline, a peculiar behavior involving a single stalled blade was observed. The results emphasize that rotating stall and NSV exhibit different wave characteristics: rotating stall comprises lower wave numbers and higher propagation speeds at around 78% rotor speed, while small-scale disturbances propagate at 57% rotor speed and lock-in with blade eigenmodes, causing NSV. Both phenomena were observed in a narrow range of operation and even simultaneously at specific conditions. The presented results contribute to the understanding of different types of operating range-limiting phenomena in modern UHBR fans and serve as a basis for the validation of numerical simulations. Full article

The development of compact high-speed low-pressure turbines with high efficiencies requires the characterization of the secondary flow structures and the interaction of cavity purge and leakage flows with the mainstream. During the SPLEEN project funded by the European Union’s Horizon 2020, the von Karman Institute and Safran Aircraft Engines performed detailed measurements of low-pressure turbines in engine-realistic conditions (i.e., low Reynolds and high exit Mach numbers considering background turbulence, wakes, row interactions, and leakages). The SPLEEN project is thus a fundamental contribution to the progress of high-speed low-pressure turbines by delivering unique experimental databases, essential to characterize the time-resolved 3D turbine flow, and new critical knowledge to mature the design of 3D technological effects. Being able to simulate the flow and associated losses in such a configuration is both challenging and of paramount importance to help the understanding of the flow physics complementing experimental measurements. This paper focuses on the high-fidelity numerical simulation of one of the SPLEEN configuration consisting of a linear blade cascade. The objective is to provide a validated numerical setup in terms of computational domain, boundary conditions, mesh resolution and numerical scheme to reproduce the experimental results. By mean of wall-resolved large-eddy simulations, the design point characterized by an exit Mach number of 0.9 and an exit Reynolds number of 70,000 with a turbulence level of 2.4% is investigated for the baseline configuration without purge and without wake generator. The results show that the considered computational domain and the associated inlet total pressure profile play a critical role on the development of secondary flows. The isentropic Mach number distribution around the blade is shown to be robust to the mesh and numerical scheme. The development of the wake and secondary flow fields are drastically influenced by the mesh resolution and numerical scheme, impacting the resulting losses. Full article

In gas–liquid two-phase flows, diverging channels such as diffusers often develop low-pressure separation zones where gas can accumulate, hindering pressure recovery and reducing system performance. This issue is particularly critical in centrifugal pumps, where it leads to efficiency losses. Unlike pumps, diffusers without rotating components allow for more precise experimental studies. This research investigates a passive control method using upstream cross-flow steps to reduce gas accumulation in a horizontal diverging channel. Thin metallic sheets with toothed geometries of 2 mm, 5 mm, and 8 mm heights were installed upstream to interact with the flow. These features aim to enhance turbulence, break up larger gas pockets, and promote vertical bubble dispersion, all while minimizing additional flow separation. The diffuser was intentionally designed with an expanding angle to encourage flow separation and gas accumulation. The experiments covered various two-phase flow conditions (liquid Reynolds number 59,530–78,330; gas Reynolds number 3–9.25), and high-speed imaging captured detailed phase interactions. The results show that the steps significantly reduce gas accumulation, especially at higher water flow rates. These findings support the development of more accurate computational models and offer insights for optimizing centrifugal pump designs by minimizing gas buildup in separated flow regions. Full article

A novel efficient method to evaluate time-periodic flows is applied to turbomachinery configurations in this paper (PSpTM). The technique reduces the overall computational cost of unsteady CFD calculations relative to conventional implicit approaches. The method is based on a pseudo-spectral definition of the time derivative rearranged in a time-marching fashion. The key advantage of this novel formulation compared with classical harmonic methods is that it requires minor modifications in the CFD solver structure. The method was implemented into an existing unstructured edge-based, second-order, compressible RANS solver. To benchmark the method, a well-established implicit time scheme based on a second-order backward implicit approach (BDF2) is used. Sample unsteady turbomachinery configurations are used to determine the accuracy and efficiency of the method. The accuracy of the solution is highly linked to the number of harmonics prescribed for the solution. An adequate level of accuracy was obtained while retaining a reduced number of harmonics, with approximately twice the number of harmonics of the unsteady perturbation. Notable savings in computational cost were observed when the PSpTM method was used with speed-up factors of between 2 and 10 with respect to the BDF2, depending on the case. However, the PSpTM method exhibits a poor periodic convergence rate, leaving room for further improvements in efficiency. However, even in its current form and with the current understanding, the method has a remarkable performance. Full article

Secondary flow phenomena have a significant influence on the generation of losses and the propagation of coolant on the turbine end walls. The majority of film cooling studies are carried out on linear rather than annular cascades due to the structural simplicity and ease of measurement integration of the former. This approach neglects the effects of the radial pressure gradient that is naturally imposed on the vortex flow in annular cascades. The first part of this paper numerically investigates the effect of the radial pressure gradient on the secondary flow under periodic flow conditions by comparing a linear and an annular case. It is shown that the radial pressure gradient has a significant influence on the propagation of the secondary flow induced vortices in the wake of the nozzle guide vanes (NGV). In the second part of the paper, a novel approach of a five-passage annular sector cascade is presented, which avoids the hub boundary layer separation, as is typical for this type of test rig. To increase the periodicity, a benchmark approach is introduced that includes multiple pointwise and integral flow quantities at different axial positions. Based on the optimized best-case design, general design guidelines are derived that allow a straightforward design process for annular sector cascades. Full article

With the advancement of modern fan architectures, dedicated experimental benchmarks are becoming fundamental to improving the knowledge of flow physics, validating novel CFD methods, and fine-tuning existing methods. In this context the open test case ECL5/CATANA, representative of a modern Ultra High Bypass Ratio (UHBR) architecture, has been designed and experimentally investigated at École Centrale de Lyon (ECL) in a novel test facility with multi-physical instrumentation, providing a large database of high-quality aerodynamic and aeromechanic measurements. In this paper, a thorough numerical study of the fan stage aerodynamics was performed using the CFD TRAF code developed at the University of Florence. Fan stage performance was studied at design speed over the entire operating range. The results were discussed and compared with datasets provided by ECL. Detailed sensitivity on numerical schemes and state-of-the-art turbulence/transition models allowed for the selection of the best numerical setup to perform UHBR fan simulations. Moreover, to have a deeper understanding of the fan stall margin, unsteady simulations were also carried out. The results showed the appearance of blade tip instability, precursor of a rotating stall condition, which may generate non-synchronous blade vibrations. Full article

A standard approach to design begins with scaling up state-of-the-art machines to new target dimensions, moving towards larger rotors with lower specific energy to maximize revenue and enable power production in lower wind speed areas. This trend is particularly crucial in floating offshore wind in the Mediterranean Sea, where the high levelized cost of energy poses significant risks to the sustainability of investments in new projects. In this context, the conventional approach of scaling up machines designed for fixed foundations and strong offshore winds may not be optimal. Additionally, modern large-scale wind turbines for offshore applications face challenges in achieving high aerodynamic performance in thick root regions. This study proposes a holistic optimization framework that combines multi-fidelity analyses and tools to address the new challenges in wind turbine rotor design, accounting for the novel demands of this application. The method is based on a modular optimization framework for the aerodynamic design of a new wind turbine rotor, where the cost function block is defined with the aid of a model reduction strategy. The link between the full-order model required to evaluate the target rotor’s performance, the physical aspects of blade aerodynamics, and the optimization algorithm that needs several evaluations of the cost function is provided by the definition of a surrogate model (SM). An intelligent SM definition strategy is adopted to minimize the computational effort required to build a reliable model of the cost function. The strategy is based on the construction of a self-adaptive, automatic refinement of the training space, while the particular SM is defined by the use of stochastic radial basis functions. The goal of this paper is to describe the new aerodynamic design strategy, its performance, and results, presenting a case study of a 15 MW wind turbine blades optimized for specific deepwater sites in the Mediterranean Sea. Full article

As designers push engine efficiency closer to thermodynamic limits, the analysis of flow instabilities developed in a high-pressure turbine (HPT) is crucial to minimizing aerodynamic losses and optimizing secondary air systems. Purge flow, while essential for protecting turbine components from thermal stress, significantly impacts the overall efficiency of the engine and is strictly connected to cavity modes and rim-seal instabilities. This paper presents an experimental investigation of these instabilities in an HPT stage, tested under engine-representative flow conditions in the short-duration turbine rig of the von Karman Institute. As operating conditions significantly influence instability behavior, this study provides valuable insight for future turbine design. Fast-response pressure measurements reveal asynchronous flow instabilities linked to ingress–egress mechanisms, with intensities modulated by the purge rate (PR). The maximum strength is reached at PR = 1.0%, with comparable intensities persisting for higher rates. For lower PRs, the instability diminishes as the cavity becomes unsealed. An analysis based on the cross-power spectral density is applied to quantify the characteristics of the rotating instabilities. The speed of the asynchronous structures exhibits minimal sensitivity to the PR, approximately 65% of the rotor speed. In contrast, the structures’ length scale shows considerable variation, ranging from 11–12 lobes at PR = 1.0% to 14 lobes for PR = 1.74%. The frequency domain analysis reveals a complex modulation of these instabilities and suggests a potential correlation with low-engine-order fluctuations. Full article

The increasing deployment of wind energy systems, particularly offshore wind farms, necessitates advanced monitoring and maintenance strategies to ensure optimal performance and minimize downtime. Supervisory Control And Data Acquisition (SCADA) systems have become indispensable tools for monitoring the operational health of wind turbines, generating vast quantities of time series data from various sensors. Anomaly detection techniques applied to this data offer the potential to proactively identify deviations from normal behavior, providing early warning signals of potential component failures. Traditional model-based approaches for fault detection often struggle to capture the complexity and non-linear dynamics of wind turbine systems. This has led to a growing interest in data-driven methods, particularly those leveraging machine learning and deep learning, to address anomaly detection in wind energy applications. This study focuses on the development and application of a semi-supervised, multivariate anomaly detection model for horizontal axis wind turbines. The core of this study lies in Bidirectional Long Short-Term Memory (BI-LSTM) networks, specifically a BI-LSTM autoencoder architecture, to analyze time series data from a SCADA system and automatically detect anomalous behavior that could indicate potential component failures. Moreover, the approach is reinforced by the integration of the Isolation Forest algorithm, which operates in an unsupervised manner to further refine normal behavior by identifying and excluding additional anomalous points in the training set, beyond those already labeled by the data provider. The research utilizes a real-world dataset provided by EDP Renewables, encompassing two years of comprehensive SCADA records collected from a single offshore wind turbine operating in the Gulf of Guinea. Furthermore, the dataset contains the logs of failure events and recorded alarms triggered by the SCADA system across a wide range of subsystems. The paper proposes a multi-modal anomaly detection framework orchestrating an unsupervised module (i.e., decision tree method) with a supervised one (i.e., BI-LSTM AE). The results highlight the efficacy of the BI-LSTM autoencoder in accurately identifying anomalies within the SCADA data that exhibit strong temporal correlation with logged warnings and the actual failure events. The model’s performance is rigorously evaluated using standard machine learning metrics, including precision, recall, F1 Score, and accuracy, all of which demonstrate favorable results. Further analysis is conducted using Cumulative Sum (CUSUM) control charts to gain a deeper understanding of the identified anomalies’ behavior, particularly their persistence and timing leading up to the failures. Full article

Direct numerical simulations (DNSs) of the T106A low-pressure turbine were conducted for various turbulence intensities and length scales to investigate their effects on flow behaviour and transition. A source-term formulation of the synthetic eddy method (SEM) was implemented in the Nektar++ spectral/hp element framework to introduce anisotropic turbulence into the flow field. A single sponge layer was imposed, which covers the inflow and outflow regions just downstream and upstream of the inflow and outflow boundaries, respectively, to avoid acoustic wave reflections on the boundary conditions. Additionally, in the T106A model, mixed polynomial orders were utilized, as Nektar++ allows different polynomial orders for adjacent elements. A lower polynomial order was employed in the outflow region to further assist the sponge layer by coarsening the mesh and diffusing the turbulence near the outflow boundary. Thus, this study contributes to the development of a more robust and efficient model for high-fidelity simulations of turbine blades by enhancing stability and producing a more accurate flow field. The main findings are compared with experimental and DNS data, showing good agreement and providing new insights into the influence of turbulence length scales on flow separation, transition, wake behaviour, and loss profiles. Full article