Surrogate modeling of the aeroacoustics of an NM80 wind turbine

Wind turbines play a major role in the European Green Deal for clean energy transition. Noise is a critical aspect among open technological issues, as it determines the possibility of onshore installations near inhabited places and the possible detrimental effects on wildlife when offshore. This paper assesses the accuracy of different approaches to predicting the sound pressure level (SPL) of a wind turbine. The 2.75 MW Neg Micon NM80 horizontal axis wind turbine (HWAT) was simulated in OpenFOAM, modeling the turbine with the actuator line method (ALM) implemented in the turbinesFoam library. Two different inflow conditions were considered: a stationary inflow with a typical atmospheric boundary layer profile and a time-dependent inflow derived from a precursor channel with fully turbulent conditions. The surrogate model for noise prediction used for this work is based on the synthetic/surrogate acoustics models (SAMs) of Amiet and Brooks-Pope-Marcolini (BPM). This approach allows for blade motion modeling and the prediction of the SPL of the URANS postprocessing results. The SPL spectrum obtained was then compared to the results from the other aeroacoustic solvers of IEA Task 39 participants, showing the best performance in the fully turbulent case. The results demonstrate that coupling between the ALM and surrogate acoustics provides more accurate results than the blade element momentum (BEM) approach

A fluid structure interaction framework for digital twins in turbomachinery

Fluid Structure Interaction (FSI) is a class of multiphysics problems that couple the analysis of fluid dynamics of flows around solid objects and the structural dynamics of the same solid that interacts with the flow around it. By solving an FSI problem, is possible to obtain information about both the fluid and solid phases, as a function of their complex interactions, exchanges of forces, changes in shape, induced dynamics. This class of problem can be recognized in a large number of phenomena in nature, and also in the human technologies. Recently, following the constant effort to push forward the performances of the existing energy conversion technologies, FSI has been applied to several classes of rotating fluid machines: wind turbines, tidal turbines, air turbines, fans can all be observed from the FSI perspective when the designer is interested into the optimization and improvement of a device that, for different reasons (extremely large rotor radius, flexible blades, passive adaptive appendices or blades, thin structures) is expressing a non negligible interaction between the structure and the fluid flow. So far, the FSI problem for complex geometries and flows such the ones characterizing internal and external flows in turbomachinery, was solved numerically using computational FSI models and algorithms, that are designed to couple the approximate solution of the Navier-Stokes (NS) equations with the elastodynamics equations. At the same time, the growing interest in Cyber-Physical Systems (CPS) and Digital Twin (DT) technologies from the turbomachinery producers is explained by the numerous benefits that would occur adopting those technologies: prediction capabilities, design, testing and monitoring, in a real time digital environment would cut by a significative amount costs and time consumption at multiple stages of the products lifetime. The attempt to build a DT (or in general, a CPS) able to describe some of the FSI phenomena in turbomachinery represents a challenging task, yet extremely interesting and promising. Among the several technical obstacles that a DT (or a CPS in general) would face when demanded to describe the FSI of a rotating fluid machinery there's the evident mismatch of the time scales of the time consuming FSI numerical simulations, and the real time functioning required by the DT to process the input signals and to give an adequate output with the least possible delay. This obstacle can be possibly overcome by decoupling the slow but high fidelity simulations and the data usage from the DT: to achieve this, a database that collects FSI data can be built for a specific set of problems, and a Machine Learning (ML) algorithm might be used to build a Reduced Order Model (ROM) that would constitute the virtual core of the DT. A DT built on top of a ROM should be able to obtain results comparable to the ones from a canonical numerical simulation in a fraction of the time required by the simulation (orders of magnitudes). The shortcoming of this approach, aside of the complexity of the entire system, and the technical difficulties to build a suitable database and a reliable ROM, would obviously be the lack of generalization: such ROM (and DT) would be appplicable only to the specific subset of conditions that built the original database, possibly accepting only minor deviations. In spite of this shortcoming, from a manifacturer perspective this issue would be minor: the lack of generalization can still be compensated for by the production in series of the device, and the technology could still fit the scale economy. In an attempt to follow the research path that would eventually lead to a DT with FSI capabilities in turbomachinery, in this dissertation is introduced the first fundamental block of this roadmap, on top of which the subsequent components will be built: FEMpar, a in-house developed software for FSI analysis using Finite Elements Method (FEM), is presented together with a description of the numerical models implemented to solve the NS equations, the nonlinear structural dynamics equations and the moving mesh problem. Along with the presentation of the software tool and its main components, several applications of FEMpar to CFD-FSI analysis in turbomachinery are showcased as well, to highlight the potential and relevance of FSI analysis in those devices. The proposed cases were selected to highlight different features and benefits to adopt FSI at the design and testing stage of a rotating fluid machinery: the flow around fans with large diameters, extreme aspect ratio, or made with flexible materials is simulated to observe the interaction of thin structures immersed in an unsteady flow; the possible adoption of low stiffness materials to design passive adaptive blade, and the design of specific constraints that would allow the passive morphing of the blades up to the desired configurations, are explored for a reversible axial fan and a Wells turbine (both devices characterized by quick and impulsive changes in the flow direction)

FSI analysis and simulation of flexible blades in a Wells turbine for wave energy conversion

In this paper a preliminary design and a 2D computational fluidstructure interaction (FSI) simulation of a flexible blade for a Wells turbine is presented, by means of stabilized finite elements and a strongly coupled approaches for the multi-physics analysis. The main objective is to observe the behaviour of the flexible blades, and to evaluate the eventual occurrence of aeroelastic effects and unstable feedbacks in the coupled dynamics. A series of configurations for the same blade geometry, each one characterized by a different material and mechanical properties distribution will be compared. Results will be given in terms of total pressure difference, supported by a flow survey. The analysis is performed using an in-house build software, featured of parallel scalability and structured to easy implement coupled multiphysical systems. The adopted models for the FSI simulation are the Residual Based Variational MultiScale method for the Navier-Stokes equations, the Total Lagrangian formulation for the nonlinear elasticity problem, and the Solid Extension Mesh Moving technique for the moving mesh algorithm

Condition-Based Maintenance of Gensets in District Heating Using Unsupervised Normal Behavior Models Applied on SCADA Data

Increasing interest in natural gas-fired gensets is motivated by District Heating (DH) network applications, especially in urban areas. Even if they represent customary solutions, when used in DH, duty regimes are driven by network thermal energy demands resulting in discontinuous operation, which affects their remaining useful life. As such, the attention on effective condition-based maintenance has gained momentum. In this paper, a novel unsupervised anomaly detection framework is proposed for gensets in DH networks based on Supervisory Control And Data Acquisition (SCADA) data. The framework relies on multivariate Machine-Learning (ML) regression models trained with a Leave-One-Out Cross-Validation method. Model residuals generated during the testing phase are then post-processed with a sliding threshold approach based on a rolling average. This methodology is tested against nine major failures that occurred on the gas genset installed in the Aosta DH plant in Italy. The results show that the proposed framework successfully detects anomalies and anticipates SCADA alarms related to unscheduled downtime

Unsteady flow simulation of an axial fan for dry cooling in a CSP plant using the variational multiscale method

We present an unsteady simulation of an axial fan with low pressure and high flow rate, developed during the MinWaterCSP EU project, specifically designed and optimized for Concentrating Solar Power (CSP) plants with the aim of reducing water consumption at the condenser stage. An earlier version of the fan, referred as M-fan, was initially developed to serve the hybrid cooling system, to boost the overall heat transfer performance with dry cooling. In this work, we will performing a Computational Fluid Dynamics (CFD) analysis of the unsteady flow on a redesigned and scaled version of the M-fan, referred as T-fan, by The T-fan was designed and optimized to reduce noise emissions and improve efficiency with respect to the M-fan. We perform the simulation using an in-house built C++ parallel code for CFD analysis using Finite Elements (FE). We model the flow dynamics using the Residual Based Variational MultiScale method (RBVMS) to obtain a stabilized solution of the Navier-Stokes equation using FE discretization. We will discuss the simulation results of the RBVMS model by comparing our simulation of the T-fan with experimental results on the same fan