Carlo Cravero

In the automotive industry, the increasing stringent standards to reduce fuel consumption and pollutant emissions has driven significant advancements in turbocharging systems. The centrifugal compressor, as the most widely used power-absorbing machinery, plays a crucial role but remains one of the most complex components to study and design. While most numerical studies rely on adiabatic models, this work analyses several Computational Fluid Dynamics (CFD) models with conjugate heat transfer (CHT) of varying complexity, incorporating real solid components. This approach allowed a sensitivity analysis of the performance obtained from the different models compared to the adiabatic case, highlighting the effects of internal heat exchange losses. Moreover, an analysis of the temperature distribution of the wheel was conducted, along with a thermal assessment of the various heat flux contributions across the different components, to gain a deeper understanding of the performance differences. The impact of including the seal plate has been evaluated and different boundary conditions on the seal plate have been tested to assess the uncertainty in the results. Finally, the influence of heat exchange between the shroud and the external environment is also examined to further refine the model’s accuracy. One of the objectives of this work is to obtain a correct temperature profile of the rotor for a subsequent thermo-mechanical analysis.

Modern radial compressors are designed to operate with high performance and a wide range of applications while minimizing their environmental impact. It is necessary to study the machine near the stability limit and gain a comprehensive understanding of the fluid dynamic mechanisms that trigger the instability in the system to extend the operating range at high efficiency. Machine learning aids in developing pattern identification models for detecting compressor instability. In a prior study, a two-stage radial compressor for refrigerant gas underwent extensive simulation, capturing unsteady RANS conditions and generating a substantial dataset of pressure signals from multiple probes. Selected signals, coupled with detailed computational fluid dynamics (CFD) post-processing, revealed fluid dynamic structures near surge conditions. This study utilizes all pressure signals to assess the stage's operational state (stable, transient, or unstable/surge). An additional goal is to develop an algorithm predicting flow patterns in different stage sections with minimal pressure signals at the rotor inlet. This is a preliminary step toward the development of a smart monitoring and diagnostic model for the compressor installed in a plant. The developed model consists of three submodels, trained with CFD results obtained from unsteady Reynolds averaged Navier–Stokes (URANS) simulations. The three submodels are a regression submodule, a classification submodule, and a forecasting algorithm. The regression submodule predicts diffuser static pressure fields, the classification submodule categorizes whether the compressor is in a critical condition or not, and the forecasting algorithm predicts the inducer pressure signals in the future impeller rotations according to the actual operation history. These sub-modules work together to forecast whether the compressor, according to the operation strategy, is going into instability conditions.

Centrifugal compressors are widely used in different fields. Their design requires high performance and a wide operating range, where, at lower mass flow rates, unstable flow dynamic phenomena occur, which are extremely harmful and, at the same time, complex to fully understand. This review paper presents the main research from the last 40 years on the subject of instability in centrifugal compressors, aiming to clarify the main (sometimes contradictory) causes, classifying them according to the component in which they are triggered or the interaction between them. Importance is given to works that develop criteria for the identification of the stability limit with simplified models. The main techniques used to extend the stability limit are also presented by distinguishing between passive and active fixed-flow control methods; moreover, the main works on variable geometry techniques are reported, showing the advantages and disadvantages of their use. Finally, an overview of the innovative applications of centrifugal compressors, such as fuel cells, is presented. The aim of this review is to highlight the continued interest in this field of study and provide the tools to understand the different unstable mechanisms and techniques used to extend the operating limit.

Modern compressor design targets require high performance and a wide operating range in order to reduce the environmental impact. To understand the fluid dynamics mechanisms that trigger instability, studying the system at the stability limit is required. In this work, a two-stage back-to-back centrifugal compressor for refrigerant applications has been simulated with computational fluid dynamics (CFD) techniques using unsteady calculations in different operating points close to surge. These models have been validated by comparing numerical performance with experimental data. An in-depth fluid dynamics analysis combined with the monitoring of several pressure signals, postprocessed with FFT, identified different flow phenomena in the two stages toward the surge limit. The key role of the volute that induces a stronger upstream counterpressure in the first stage has been highlighted. This effect causes the formation of high entropy (low momentum) rotating cells in the diffuser that involve a higher channel portion with respect to the flow structure in the second diffuser. This phenomenon affects the upstream flow conditions at the impeller. In addition, the interaction between the inlet guide vane (IGV) and the inducer has been analyzed, observing that in the second stage, due to the flow nonuniformity after the intermediate compressor pipe, non-negligible separations occur. Starting from the peaks detected in the FFT analysis of the pressure signals, all the above flow mechanisms have been detected and discussed.

Recently, growing environmental awareness has radically changed the way the problems and priorities of industry are dealt with. Energy issues have become an issue of primary importance, both in terms of consumption and polluting emissions. However, for the green transition to happen, the first step is to have a deeper knowledge of the phenomena involved in processes with a special focus on combustion. The glass industry is one of the most energy-intensive since a temperature of over 1400 °C is required to keep glass molten, with a large consumption of natural gas used for combustion. A fundamental element to control the process is the burner. In this study, the CFD (Computational Fluid Dynamics) prediction of the internal streams repartition and the velocity profile at the exit, at different geometrical setups and operating conditions, of an industrial burner for glass furnaces is presented, with the aim of developing a surrogate model to provide these two important quantities quickly. The study of the repartition of the mass flow inside a double impulse burner and the subsequential velocity profile outside the burner is a novelty in the glass industry. The CFD prediction of the operating conditions is a crucial aspect because it is an essential boundary condition for the simulation of the reactive process from the diffusive flame found in glass furnaces. Different operating and geometrical conditions of the burner have been tested using Ansys CFX code, and results (velocity profile and mass flow repartition) have been organized in surrogate models. Results showed that the repartition of the fuel streams is mainly influenced by the position of the barrel, while the total flow rate is strongly influenced by the total inlet pressure. The internal flow varies from 20% to 50% of the total mass flow inside the burner, while the velocity magnitude outside the burner varies from 80 to 300 m/s approximately. The reconstruction of velocity profiles at the exit of the burners with surrogate models showed an acceptable match with numerical simulations.

A glass production furnace requires a considerable amount of energy to allow the correct glass melting process. In this work, a CFD model has been developed in order to simulate the convective flow movements within the molten glass bath of the glass furnace. A heat flux profile has been assigned to the glass free surface to model the combustion process, and the glass has been modelled with thermophysical properties variable with temperature based on its chemical composition. The model has been validated by comparing the flow structure and temperature with a reference work. Subsequently, a flow analysis has been carried out by using different shapes for the heat flux profile and by varying its main parameters. The above heat release profiles are representative of different settings of the combustion operating points and can be useful to understand the effects of different flames (i.e., from different fuels also) on the glass flow structure. It has been demonstrated that only the thermal distribution with a maximum generates two convective macro-cells: the first is necessary for the glass melting, the second for its homogenization. It has also been observed that the length of these vortices is related to the flame length. However, a portion of the flow exits directly from the throat (furnace exit port) without entering into the second cell; a low-quality product will be generated in this case.

The design of naval exhaust funnels has to take into account the interaction between the hot gases and topside structures, which usually includes critical electronic devices. Being able to predict the propagation trajectory, shape and temperature distribution of an exhaust gas plume is highly strategic in different industrial sectors. The propagation of a stack plume can be affected by different uncertainty factors, such as those related to the wind flow and gas flow conditions at the funnel exit. The constant growth of computational resources has allowed simulations to gain a key role in the early design phase. However, it is still difficult to model all the aspects of real physical problems in actual applications and, therefore, to completely rely upon the quantitative results of numerical simulations. One of the most important aspects is related to input variable uncertainty, which can significantly affect the simulation result. With this aim, the discipline of Uncertainty Quantification provides several methods to evaluate uncertainty propagation in numerical simulations. In this paper, UQ procedures are applied to a CFD simulation of a single plume in a crossflow. The authors test the influence of the uncertainty propagation of the chimney exit velocity and the main flow angle on the plume flow development. Two different UQ methods are applied to the analysis: the surrogate-based approach and the polynomial chaos expansion method. A comparison of the two methods is performed in order to find their pros and cons, focusing on the different and detailed quantities of interest.

The reduction in energy consumption and the increasingly demanding emissions regulations have become strategic challenges for every industrial sector. In this context, the glass industry would be one of the most affected sectors due to its high energy demand and emissions productions, especially in terms of NO_x. For this reason, various emission abatement systems have been developed in this field and one of the most used is the air staging system. It consists in injecting air into the upper part of the regenerative chamber on the exhaust gases side in order to create the conditions for combustion that reduces NO_x emissions. In this work, the combined use of CFD with data analysis techniques offers a tool for the design and management of a hybrid air staging system. Surrogate models of the bypass mass flow rate and uniformity index in the regenerative chamber have been obtained starting from DoE based on different simulations by varying the air mass flow rate of the two injectors located in a bypass duct that connects the two regenerative chambers. This model allows a UQ analysis to verify how the uncertainty of the air injectors can affect the bypass mass flow rate. Finally, an optimization procedure has identified the optimal condition for the best bypass mass flow rates and uniformity of the oxygen concentration in the chamber. High values of the mass flow rate of the pros injector and medium-low values for the cons injectors are identified as operating parameters for best conditions.

Axial flow fans are usually characterized by blade sections with low solidity and high inlet flow angles. Two main approaches are followed in the preliminary design phase, to take into account blade interaction effects: the use of available airfoil cascades data (or related correlations) and that of isolated airfoil data together with interference coefficients. The working conditions of low solidity airfoil cascades with highly tangential inflow are not widely studied in the literature, leaving the designer the possibility to rely on limited cascade data or often on the use of isolated airfoil data, with the assumption of negligible interference effects. A systematic investigation of the above working conditions for airfoil cascades is performed with Reynolds-averaged Navier–Stokes simulations. Three different airfoils are used to evaluate the influence of the design lift coefficient and maximum blade thickness. The results provide a better insight into the aerodynamic behavior of airfoil sections in such operating conditions, showing that interactions cannot be neglected. The use of metamodeling coupled with computational fluid dynamics (CFD) simulations is presented as a suitable tool for treating interference effects within the fan design process. The main findings of the present work can be used as a support for design choices as well as for developing design strategies both for the fan blades and for the airfoil sections.