A strategy for the robust forecasting of gas turbine health subjected to fouling

Fouling represents a major problem for Gas Turbines (GTs) in both heavy-duty and aeropropulsion applications. Solid particles entering the engine can stick to the internal surfaces and form deposits. Components' lifetime and performance can dramatically vary as a consequence of this phenomenon. These effects impact the whole engine in terms of residual life, operating stability, and maintenance costs. In the High-Pressure Turbine (HPT), in particular, the high temperatures soft the particles and promote their adhesion, especially in the short term. Unfortunately, predicting the GT response to this detrimental issue is still an open problem for scientists. Furthermore, the stochastic variations of the components operating conditions increase the uncertainty of the forecasting results. In this work, a strategy to predict the effects of turbine fouling on the whole engine is proposed. A stationary Gas Path Analysis (GPA) has been performed for this scope to predict the GT health parameters. Their alteration as a consequence of fouling has been evaluated by scaling the turbine map. The scaling factor has been found by performing Computational Fluid Dynamic (CFD) simulations of a HPT nozzle with particle injection. Being its operating conditions strongly uncertain, a stochastic analysis has been conducted. The uncertainty sources considered are the circumferential hot core location and the turbulence level at the inlet. The study enables to build of confidence intervals on the GT health parameters predictions and represents a step forward towards a robust forecasting tool

Assessment of Parathyroid Function in Clinical Practice: Which Parathyroid Hormone Assay Is Better?

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Off-line washing effectiveness on a multistage axial compressor

The interaction between gas turbines and airborne particles determines detrimental effects on the performance, efficiency, and reliability of the power unit. When it is possible, the interaction is reduced by the use of inlet separators and filtration systems. In an aero engine, these barriers are difficult to implement, and only bigger particles (usually greater than 10 µm) are separated from the airflow. Small units, especially those equips helicopters, are usually affected by fouling issues, especially when the aircraft is employed in harsh environments such as firefighting and rescue activities. To recover this contamination, the unit is washed after the mission by ground operations to restore the unit performance by removing the deposits. This operation occurs during a sub-idle unit operation, and the washing process has to be effective when the engine operates in this off-design condition. In this paper, the evaluation of the washing performance during a sub-idle unit operation is carried out. The compressor unit is a multistage axial compressor that equips the Allison 250-C18 engine. The washing operation was performed by water, and a sensitivity analysis is carried out to discover the capability of water droplets to remove the contaminants. The experimental analysis involves the contamination of the unit by micro-sized soot particles and a washing operation by micro-sized water droplets. These experimental results are compared to numerical simulations to discover the effects of the washing operation on a small power unit during sub-idle operating conditions. The off-design regime imposes a specific evaluation of the proper setup of the washing strategy: flow separations involve wider regions in the compressor unit, and the removal capability is strongly related to the droplet path through the stages. The results show how in the off-design washing operation, the droplet diameter has greater importance than the water flow rate for reducing the deposits over the compressor stages. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/

Experimental Assessment of Fouling Effects in a Multistage Axial Compressor

The study of the adhesion of micro sized particles to gas turbine internal surfaces, commonly known as gas turbine fouling, has gained increasing attention in the last years due to its dramatic effect on machine performance and reliability. On-field fouling analysis is mostly related to visual inspections during overhaul and/or programmed stops, which are performed, in particular, when gas turbine performance degradation falls under predetermined thresholds. However, these analyses, even if performed in the most complete as possible way, are rarely (or never) related to the conditions under which the gas turbine contamination takes place since the affecting parameters are difficult or even impossible to be adequately monitored. In the present work, a small scale multistage axial compressor is used to experimentally simulate the fouling phenomenon. The test rig allows the accurate control of the most relevant operating parameters which influence the fouling phenomenon. The compressor performance loss due to particle contamination has been quantitatively assessed. Soot particles appear stickier, especially in the presence of high humidity, and represent the most harmful operating conditions for the compressor unit. The deposits on the stator vanes and the rotor blades have been detected and post-processed, highlighting the most affected regions of each compressor stage employing an image analysis package tool

Numerical Investigation of a Wood-Chip Downdraft Gasifier

Biomass gasification is regarded as one of the most promising technology in the renewable energy field. The outcome of such operation, i.e. the synfuel, can be exploited in several ways, for example powering engines and turbines, and is considered more flexible than the biomass itself. For this reason, a careful analysis of the gasification performance is of paramount importance for the optimization of the process. One of the techniques that can be used for such a purpose, is the numerical analysis. CFD is indeed a tool that can be of great help in the design and study of the operation of the gasifier, allowing for an accurate prediction of the operating parameters. In this work, a downdraft gasifier is considered, and the biomass is made of wood chip. The present analysis is devoted to build the numerical model and simulate all the reactions that happen inside an actual gasifier, considering the drying of the wood chip, heating, pyrolysis, and combustion. Good match with experimental results is found, making the numerical model here presented a reliable virtual test bench where investigating the effects of variation in the working parameter

Dust ingestion in a rotorcraft engine compressor: Experimental and numerical study of the fouling rate

Helicopters often operate in dusty sites, ingesting huge amounts of contaminants during landing, take-off, hover-taxi, and ground operations. In specific locations, the downwash of the rotor may spread soil particles from the ground into the environment and, once ingested by the engine, may stick to the compressor airfoils. In the present work, the Allison 250 C18 engine’s multistage axial-flow compressor is employed to study the fouling rate on rotor blades and stator vanes from both numerical and experimental standpoints. The compressor is operated in a typical ground-idle operation, in terms of the rotational regime and contaminant concentration, in laboratory-controlled conditions. The mass of deposits is collected from the airfoil surfaces at the end of the test and compared to that estimated through the numerical model. The experimental test shows that the airfoils collect almost 1.6% of the engine’s total mass ingested during a ground-idle operation. The capability of numerical methods to predict the fouling rate on the rotating and stationary airfoils of a multistage compressor is tested through the implementation of literature based deposition models. Sticking models show a good agreement in terms of the relative results; nevertheless, an overestimation of the deposited mass predicted is observed

A quantitative approach for the estimation of the fouling rate on the stationary parts of a multistage test compressor

Gas turbine particle ingestion may lead to the deposition of contaminants in the compressor section, inducing the performance losses of the whole engine. The economic losses derived from this issue push great interest in the investigation of such a phenomenon from a numerical and experimental standpoint. This paper describes a quantitative approach to predict particle deposition on the vanes of an axial compressor starting from the flow field obtained employing CFD simulations. The results are then compared to the experiments performed on the Allison 250 C18 compressor unit subject to particle ingestion under controlled conditions. The results derived from the experimental and numerical investigations are presented, providing insight into the mass deposited on the vanes and the corresponding zones most affected by the particle deposition issue. The numerical model showed good agreement in the estimation of the predicted values of the deposited mass and the corresponding patterns through the compressor stages. The low-complexity approach proposed here, helps the designer to predict the contamination of the stationary rows starting from a simple set of single-phase numerical results. Furthermore, with the implementation of this approach into the design path, the designer could reduce the impact of fouling, looking at the effects of their solutions under the foulingreduction light

Performance losses and washing recovery of a helicopter engine compressor operating in ground-idle conditions

Helicopters operate often in dusty environments. During landings and takeoffs the engine ingests huge amounts of contaminants that might deposit inside the compressor. In this paper, the ground-idle operation of a helicopter engine compressor has been reproduced on a compressor test unit. The Allison 250 C18 compressor has been subjected to multiple runs under severe conditions of dust ingestion. At the end of each run, the performance curve was recorded while the performance loss has been measured during the operations. Finally, the compressor washing has been carried out and the performance curve has been recorded again. The characteristic curve are representative of the level of contamination of the machine, while the exposure time directly affects the performance loss. The results show the modification and the downward shift of the characteristic curves that lead to a gradual loss of the compressor performance. A detailed photographic report of the first compressor stages has been included in this work. The pictures show the deposition patterns on the blades and the compressor surfaces. The comparison of the pictures of the internal surfaces, before and after the removal of the deposits by the droplet action, highlights the parts that are more critical to clean

Outstretching population growth theory towards surface contamination

Nanoparticle surface interaction is a common phenomenon, even if a general explanation of nanoparticle deposit growth is still unknown. For several applications, the adhesion of such nanoparticles is detrimental, generating safety and performance issues. The present work shows an interpretation of deposit growth due to nanoparticle deposition, capable of predicting particle adhesion and layer accretion. The nanoparticle deposits grow analogously to a typical autonomous population settlement in a virgin area following statistical rule, which includes the initial growth, the successive stable condition (development), and catastrophic events able to destroy the deposited layer. This statistical population model allows the generalization of the nanoparticle adhesion/deposition behavior, and it could be used for improving the prediction capability of nanoparticle deposition to common engineering applications

A stochastic model for nanoparticle deposits growth

Natural events and human activities are responsible for the generation and transport of large amounts of micro-sized particles, which could contaminate several engineering devices like solar panels, wind turbines, and aero-engines. In industrial processes, systems as heat exchangers, fans, and dust collectors are continuously affected by nanoparticles' interaction. For several applications, the adhesion of such nanoparticles is detrimental, generating safety and performance issues. Particleto-particle and particle-To-surface interactions are well known, even if a general explanation of nanoparticle deposit growth is still unknown. In the present paper, an interpretation of deposit growth due to nanoparticle deposition can predict particle adhesion, and layer accretion is proposed. A statistical model and a set of coefficients are used to generalize nanoparticle deposits' growth by an S-shaped function. In particular, the nanoparticle deposits grow analogously to a typical autonomous population settlement in a virgin area following statistical rule, which includes the initial growth, the successive stable condition (development), and catastrophic events able to destroy the layer. This approach generalizes nanoparticle adhesion/deposition behavior, overpassing the constraints reported in common deposition models, mainly focused on the mechanical aspect of the nanoparticle impact event. The catastrophic events, such as layer detachment, are modeled with a Poisson s distribution, related to material characteristics and impact conditions. This innovative approach, analogies, and coefficients applied to common engineering applications may be the starting point for improving the prediction capability of nanoparticle deposition