Rishabh Mishra’s Post

We are pleased to inform you that we have lots of new published contents online: Enjoy reading through the newest article.   This week we have the following article online:   1. Field-data-based validation of an aero-servo-elastic solver for high-fidelity large-eddy simulations of industrial wind turbines 2. Nonlinear vibration characteristics of virtual mass systems for wind turbine blade fatigue testing 3. Towards real-time optimal control of wind farms using large-eddy simulations 4. Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 1: Large-eddy-simulation study 5. Breakdown of the velocity and turbulence in the wake of a wind turbine – Part 2: Analytical modelling 6. Drivers for optimum sizing of wind turbines for offshore wind farms 7. Sensitivity of cross-sectional compliance to manufacturing tolerances for wind turbine blades 8. Active trailing edge flap system fault detection via machine learning 9. Influence of rotor blade flexibility on the near-wake behavior of the NREL 5 MW wind turbine Here the corresponding links to read the full article: 1.   https://lnkd.in/gHRrbecQ 2.  https://lnkd.in/gBPdrQgH 3.  https://lnkd.in/gzXYWwdf 4.   https://lnkd.in/giEW6GeE 5.  https://lnkd.in/gSBQYHpU 6.   https://lnkd.in/gmEJaGa3 7.  https://lnkd.in/gAQkAWMG 8.  https://lnkd.in/gq_t7gN4   9.   https://lnkd.in/gw55-5Ww A big thanks to all the authors and reviewers for their great effort and support. For more information, and to submit your new manuscript, visit us at the WES Journal website: https://lnkd.in/dfDVqGv7 #windenergy #windenergyresearch #research #journal #windenergysciencejournal #futurewind #papers #publications #wind #EAWE #sustainableenergy #renewableenergy #openaccessjournal #impactfactor

🔗 **Harnessing Advanced Simulations to Optimize Wind Turbine Design** Wind energy plays a crucial role in reducing greenhouse gas emissions, yet challenges like noise regulations often limit turbine operations and increase costs. LM Wind Power and Dassault Systèmes have joined forces to tackle these issues using cutting-edge simulations. By leveraging the advanced capabilities of the SIMULIA PowerFLOW solver, they are developing a methodology to accurately predict and reduce aerodynamic noise from wind turbines. This innovative approach uses both low- and high-fidelity simulations to create cost-effective and precise designs, eliminating the need for expensive wind tunnel and field tests. This collaboration marks a new era in virtual prototyping and digital twin design, paving the way for digital noise certification of wind turbines. The results promise optimized blade shapes, efficient design iterations, and significant cost reductions in energy production, all while ensuring compliance with stringent noise regulations. Discover how this pioneering effort is shaping the future of wind energy: [link to full article] #WindEnergy #Sustainability #Simulation #DigitalTwin #Innovation #RenewableEnergy #LMWindPower #DassaultSystèmes

🔔 Photovoltaic Tracker | CFD Model for RWIND 2 🔹 Renewable energy is the future! This model is a photovoltaic tracker in the wind simulation (a wind tunnel) in RWIND 2. Download it for free! ❗By the way❗ RWIND 2 is at your side as a stand-alone application. You can also use it interoperably with RFEM and RSTAB. Thus, structural and dynamic analysis becomes child's play: https://bit.ly/3WCIeVi Are you looking for more examples? No problem! 👉 On the "Structural Analysis Models to Download" page, you can find many other example files. No matter whether you are looking for an inspiration or an introduction to the Dlubal programs – take a look around: https://bit.ly/3qbdbnq ℹ Download the structural analysis model and get started: https://lnkd.in/eEPCxWXp #WindSimulation #WindTunnel #WindLoad #WindFlow #Dlubal #DlubalSoftware #RWIND #CFD #StructuralEngineering #StructuralDesign #StructuralAnalysis #StructuralAnalysisSoftware #BIM

Our latest work on #tidal #turbine modelling is on "Efficient prediction of tidal turbine fatigue loading using turbulent onset flow from Large Eddy Simulations" (https://lnkd.in/dWY_srz5) led by Hannah Mullings, MEng PhD CEng MIMechE FHEA in collaboration with Orbital Marine Power Ltd. Current IEC/DNV standards (and software) assume idealised conditions for evaluating turbine loading. However, higher fidelity data, e.g. from specific flow conditions or sites, can be generated with #LES (we used our code #DOFAS) to improve confidence in design. It is a relatively "cheap" approach to generate realistic inflow conditions. For turbine #arrays, we show the prediction of loading by LES with actuator line and BEM (in-house code and TidalBladed). TB predicts higher thrust for downstream rows. We hope this approach can be taken up in future design campaings by the whole industry and perhaps expanding to wind turbines too. The University of Manchester Supergen Offshore Renewable Energy (ORE) Hub EMEC: European Marine Energy Centre Offshore Renewable Energy Catapult Tim Stallard Calum Miller . This was funded by the Interreg #TIGER project.

Turbine yawing and downregulation can be used as control inputs to effectively decelerate the overall degradation of wind turbines within a wind farm.   The topic is addressed in the following collaborative paper involving the Norwegian University of Science and Technology, Sintef Energi in Norway, and Shanghai Jiao Tong University in China. This paper presents findings from the CONWIND project which focuses on investigating smart operational control technologies for offshore wind farms, funded by the Norwegian Research Council https://lnkd.in/d4Fkgzzb where the focus is on the fatigue damage of the powertrain (drivetrain + generator) system, but the methodology may be extended to other systems.    This paper has been published in the special issue "Online Monitoring of Wind Power Plants using Digital Twin Models" in the Journal of Frontiers in Energy Research. To access more relevant papers or to submit your research contribution please visit https://lnkd.in/dS82M26m

We are pleased to inform that we have new published contents online: Enjoy reading through the latest articles:   1. Experimental validation of a short-term damping estimation method for wind turbines in nonstationary operating conditions 2. OC6 project Phase IV: validation of numerical models for novel floating offshore wind support structures 3. Control co-design optimization of floating offshore wind turbines with tuned liquid multi-column dampers Here the corresponding links to read the full article: 1. https://lnkd.in/gREzpdJm 2. https://lnkd.in/gSW2rbfn   3. https://lnkd.in/gcPdbg7W A big thanks to all the authors and reviewers for their great effort and support. For more information, and to submit your new manuscript, visit us at the WES Journal website: https://lnkd.in/dfDVqGv7 #windenergy #windenergyresearch #research #journal #windenergysciencejournal #futurewind #papers #publications #wind #EAWE #sustainableenergy #renewableenergy #openaccessjournal #impactfactor

Thank you, Manuel Pusch and Po Wen Cheng, for the invitation to the ISES Institut für Nachhaltige Energiesysteme workshop on Wind Turbine Control. It was a pleasure reconnecting with the wind energy community. The presentations on various aspects of wind turbine control were highly insightful. In my talk, I focused on workflows for advanced wind turbine control, discussing the standard V-Cycle, its integration with W-Cycle for AI model incorporation, and multidomain multidisciplinary workflow. The latter is becoming increasingly important for holistic turbine control design and meeting stringent grid/load requirements. DM me for the slides! #wind #energy #mbd #control #vcycle #wcycle #design #tuning #grid #loads #AI #ML #MATLAB #Simulink #MathWorks

[Wind Power] – Helping you optimize the locations of wind turbines according to acoustic and spatial constraints.  Alexis Bigot, R&D manager in our acoustic team, has been working on the development of an innovative solution called Oppio.   This solution is based on the simultaneous optimization of operating modes and positions of wind turbines, in order to limit the loss of electricity production while taking regulatory constraints into account.      👉 How does our Oppio method work?   In the upstream phase, for wind farm developers, we model the project taking into account various data: the location of wind turbines as well as their acoustic and electrical power characteristics.    The aim of the method is to find the optimum layout to minimize production losses, while taking account of regulatory acoustic constraints🔊      Numerical simulations are carried out to compare with the acoustic baseline (initial noise before the wind turbines are installed) and enable the calculation of a curtailment plan of the wind farm.      The Oppio method is an #algorithm that seeks to optimize several factors: the wind farm's operating modes and the position of the machines. For projects where acoustic losses are initially high, Oppio can save up to 3% in night-time productivity and 1% in cumulative day/night productivity.      With Oppio we help you:   ✅ Search for optimum operating modes of the wind farm in compliance with acoustic regulations  ✅ Find the optimum wind turbine locations using our algorithm.      david SLAVIERO Marwen Bejaoui   

🍃An omni-directional wind turbine🎐 operates in any direction, as opposed to standard wind turbines, which must face the wind in order to function properly. These turbines can produce power regardless of the direction of the wind because of their inventive blade designs or multiple rotor systems. An omni-directional wind turbine's salient characteristics could be: 🟢 Multiple Rotors or Blades: Arranged such that wind can be captured from any direction. 🟢 Omni-directional turbines typically have a vertical axis arrangement, as demonstrated by the Darrieus or Savonius turbines. 🟢 These turbines revolve around a central axis and function effectively in all wind directions. 🟢 Self-Orientation Mechanism: A few models might have mechanisms that modify the turbine's orientation in order to optimise performance. When there are unpredictable or turbulent wind patterns and frequent changes in the direction of the wind, these turbines are especially helpful. 📌Unshared knowledge will vanish! 🎗 Share, like, and comment for others to see. Thank you for your support! 👉Follow me and 👉 Activate Bell 🛎️ for all posts as well as additional technical and educational content!💪🏆 #innovation #creativity #technology #letsconnect #future #education #knowledge #topvoice #amazing #engineering #research #science #design  #energy #greenenrgy #hydropower #electricity #powergeneration #renewableenergy #wind #turbines

🌬️How can we simulate tomorrow’s wind farms with confidence? 🌬️     As wind farms grow larger, with hundreds of turbines clustering together, they exert a substantial influence on the atmospheric boundary layer. This complicates flow dynamics and results in reduced available energy through wake and blockage losses.   DNV has since 2020 used CFD.ML as an interpolator of the high-fidelity CFD model, allowing us to simulate a reduced number of wind directions and yet fully capture the wake effect variation by wind direction for a project. Now, with more experience and training we can start using CFD.ML as a stand-alone model.     Read more about how artificial intelligence can provide fast and reliable turbine interaction modelling in the article written by our very own wind modelling expert Tom Levick here: https://lnkd.in/dae3KVGD #windfarmer #cfdml #windmodelling #windographer #windfarm