The rules on energy consumption and pollutant emissions impose increasingly restrictive limitations in today's industrial sectors. The glass production sector is one of the highest sources of energy consumption in Europe, but also in Italy. For this reason it is very important to develop strategies for consumption reduction in a glass production plant. A glass furnace is in fact conceived with systems to recover heat from the combustion gases through regenerative and recuperative systems in order to increase the efficiency of the plant. Several systems to reduce nitrogen oxides emissions have been also developed and designed. A further method to exploit the residual heat from the exhausted gases is to pre-heat the recycled glass raw material to be introduced into the furnace so as to require a smaller amount of energy for its melting. This paper shows various numerical strategies for the design of a pre-heating system for the recycled glass raw material through CFD techniques. In this regard, numerical models have been developed for systems with direct (hot gases come directly into contact with the raw material) and indirect heat exchange (the raw material is heated through the diffusion of heat from a tube bundle).

The limitation of nitrogen oxides emissions is nowadays a challenge in several engineering fields. Recent European regulations have reduced the maximum NOx emissions and therefore forced the glass production sector to develop emission reduction strategies. Two different systems have been developed within the framework of the European LIFE project and are currently applied to glass regenerative furnaces: the Waste Gas Recirculation (WGR) and the Hybrid Air Staging (HyAS). The above systems are primary NOx reduction strategies because they both operate to control the combustion evolution. Both WGR and HyAS systems have been conceived with the extensive use of Computational Fluid Dynamics (CFD) models: design strategies for both systems have been developed based on the use of CFD and are currently under use by glass furnace designers. In the present work, the CFD procedures routinely used for the design of the above systems are described. The systems effectiveness, due to the harsh conditions in the industrial installation, can be tested with oxygen concentration measurements inside the regenerators. The oxygen concentration is correlated to the flame evolution and therefore to the nitrogen oxides formation. For the above reason, the models have been validated with experimental data from pilot furnaces using measured values of O2 mole fraction. The CFD procedures are described in the paper together with their application to different configurations.

One of the main issues addressed in any engineering design problem is to predict the performance of the component or system as accurately and realistically as possible, taking into account the variability of operating conditions or the uncertainty on input data (boundary conditions or geometry tolerance). In this paper, the propagation of uncertainty on boundary conditions through a numerical model of supersonic nozzle is investigated. The evaluation of the statistics of the problem response functions is performed following ‘Surrogate-Based Uncertainty Quantification’. The approach involves: (a) the generation of a response surface starting from a DoE in order to approximate the convergent–divergent ‘physical’ model (expensive to simulate), (b) the application of the UQ technique based on the LHS to the meta-model. Probability Density Functions are introduced for the inlet boundary conditions in order to quantify their effects on the output nozzle performance. The physical problem considered is very relevant for the experimental tests on the UQ approach because of its high non-linearity. A small perturbation to the input data can drive the solution to a completely different output condition. The CFD simulations and the Uncertainty Quantification were performed by coupling the open source Dakota platform with the ANSYS Fluent® CFD commercial software: the process is automated through scripting. The procedure adopted in this work demonstrate the applicability of advanced simulation techniques (such as UQ analysis) to industrial technical problems. Moreover, the analysis highlights the practical use of the uncertainty quantification techniques in predicting the performance of a nozzle design affected by off-design conditions with fluid-dynamic complexity due to strong nonlinearity.

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 NOx. 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 NOx 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.

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.