Multidisciplinary design optimisation (MDO) is nowadays widely employed to obtain advanced turbomachines design. The aim of this work is to provide a complete tool for the aeromechanical design of a radial inflow gas turbine. The high rotational speed of such machines, especially if used for micro cogenerative power plants, coupled with high exhaust gas temperature, exposes blades to really high centrifugal and thermal stresses; thus the aerodynamics optimisation has to be necessarily coupled with the mechanical one. Such an approach involves two different computational tools: a fully 3D Reynolds Averaged Navier-Stokes (RANS) solver is used for the aerodynamic optimisation, while an open source Finite Element Analysis (FEA) solver is employed for the mechanical integrity assessment. The geometry parameterization is handled with a commercial tool that employs b-spline advanced curve for blades and vanes definition. The aerodynamic mesh generation is managed via dedicated tools provided by the CFD software and it is a fully structured hexahedral multi-block grid. The FEA mesh is built by means of a harmonic map approach, which is able to provide high quality second order unstructured grid preserving geometrical features starting from boundary surfaces of the fluid domain. The finite element calculation provides stresses, displacements and eigenmodes that are used for mechanical integrity assessments while the CFD solver provides performance parameters and local thermodynamic quantities. Due to the high computational cost of both these two solvers, a metamodel, such as an artificial neural network, is employed to speed up the process. The interaction between two codes, the mesh generation and the post processing of the results is obtained via in-house developed scripting modules. Results obtained are presented and discussed.
The recent coming in force of MARPOL 2020 restrictions on shipping pollutant emissions highlights a growing interest in current times towards cleaner means of transport. One way to achieve more sustainable vessels is represented by updating onboard engines to suit current regulations and needs: Gas Turbines are not a novelty in the field and, despite the few applications in commercial shipping so far, this technology is again under evaluation for different reasons. Indeed, it is still a preferred choice in navy, where swift maneuvering is a key factor; it is employed by fast ferries and hydrofoils for its high power/weight ratio; it has been recently applied to LNG carriers to burn boil-off gas in a more efficient way and several studies in literature suggest its possible introduction on large Cruise Ships. Since there seems to be a lack of research concerning small size units, the present work attempts to evaluate the possible usages of Mini Gas Turbine Cycles in the range of 1 to 10 MW of electric output for heat and power generation onboard commercial vessels dedicated to passenger transport. For this purpose, a statistical analysis on existing operating vessels up to 2020 was made, to eplore main engine sizes; a literature review was carried out to find representative onboard heat demands. Once the main vessel electrical and thermal requirements were evaluated, Mini Cogenerative plants based on Gas Turbines were designed within the identified boundaries and compared with state-of-the-art Marine Diesel Engines and Gas Turbines on estimated global performance, dimensions and weights.
In the present paper, an optimized design procedure capable of providing the geometry of a high efficiency compact hydraulic propeller turbine for low head is proposed and developed. The turbine preliminary design is based on fundamental turbomachinery mean-line equations and on the employment of statistical correlations, which relate the main geometrical parameters to the fundamental design parameters. The first obtained geometry represents the starting point of an automated aerodynamic single point optimization procedure based on a genetic algorithm generating and updating a wide database of turbine geometries. The approach employs a three-dimensional (3D) Reynolds averaged Navier–Stokes (RANS) solver for the construction of the corresponding database of performance. A meta-model, such as an artificial neural network (ANN), is used to speed up the design optimization process. The procedure has been applied on the practical case of a novel simplified hydraulic propeller turbine prototype for very low heads. The adopted design optimization procedure is able to modify the turbine blade and vane geometries in order to achieve automatically the targeted net head and the maximum for the total to total internal efficiency once diameter, mass flow rate, and rotational speed are assigned.
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