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Recent advancements in computer technology have allowed for designers to have direct control over the production process through the help of computer-based tools, creating the possibility of a completely integrated design and manufacturing process. Over the last few decades, "artificial intelligence" (AI) techniques, such as machine learing and deep learning, have been topics of interest in computer-based design and manufacturing research fields. However, efforts to develop computer-based AI to handle big data in design and manufacturing have not yet been successful. This Special Issue aims to collect novel articles covering artificial intelligence-based design, manufacturing, and data-driven design. It will comprise academics, researchers, mechanical, manufacturing, production and industrial engineers and professionals related to engineering design and manufacturing.

History of engineering & technology --- product service system (PSS) --- availability --- field repair kit --- gradient-based algorithm --- robust genetic algorithm --- warpage --- design of experiments --- fringe pattern --- birefringence --- automatic design --- intelligent optimization method --- CFD --- fluid machinery --- pumps --- multi-function console --- data-driven design --- mismatch equation --- anthropometric measures --- algorithmic approach --- optimal design --- stretchable antenna-based strain sensor --- structural optimization --- structural health monitoring --- dimension reduction --- entropy-based correlation coefficient --- multidisciplinary design and analysis --- uncertainty-integrated and machine learning-based surrogate modeling --- additive manufacturing --- complexity --- modular design --- part consolidation --- product recovery --- product image design --- Kansei Engineering --- integrated decision system --- qualitative decision model --- quantitative decision model --- train seats --- measurement-assisted assembly --- coordination space --- assemblability --- small displacement torsor --- Kriging --- lower confidence bounding --- entropy theory --- product design --- simulation-based design optimization --- convolutional neural network --- object detection --- piping and instrument diagram --- unsupervised learning --- n/a

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Recent advancements in computer technology have allowed for designers to have direct control over the production process through the help of computer-based tools, creating the possibility of a completely integrated design and manufacturing process. Over the last few decades, "artificial intelligence" (AI) techniques, such as machine learing and deep learning, have been topics of interest in computer-based design and manufacturing research fields. However, efforts to develop computer-based AI to handle big data in design and manufacturing have not yet been successful. This Special Issue aims to collect novel articles covering artificial intelligence-based design, manufacturing, and data-driven design. It will comprise academics, researchers, mechanical, manufacturing, production and industrial engineers and professionals related to engineering design and manufacturing.

History of engineering & technology --- product service system (PSS) --- availability --- field repair kit --- gradient-based algorithm --- robust genetic algorithm --- warpage --- design of experiments --- fringe pattern --- birefringence --- automatic design --- intelligent optimization method --- CFD --- fluid machinery --- pumps --- multi-function console --- data-driven design --- mismatch equation --- anthropometric measures --- algorithmic approach --- optimal design --- stretchable antenna-based strain sensor --- structural optimization --- structural health monitoring --- dimension reduction --- entropy-based correlation coefficient --- multidisciplinary design and analysis --- uncertainty-integrated and machine learning-based surrogate modeling --- additive manufacturing --- complexity --- modular design --- part consolidation --- product recovery --- product image design --- Kansei Engineering --- integrated decision system --- qualitative decision model --- quantitative decision model --- train seats --- measurement-assisted assembly --- coordination space --- assemblability --- small displacement torsor --- Kriging --- lower confidence bounding --- entropy theory --- product design --- simulation-based design optimization --- convolutional neural network --- object detection --- piping and instrument diagram --- unsupervised learning --- product service system (PSS) --- availability --- field repair kit --- gradient-based algorithm --- robust genetic algorithm --- warpage --- design of experiments --- fringe pattern --- birefringence --- automatic design --- intelligent optimization method --- CFD --- fluid machinery --- pumps --- multi-function console --- data-driven design --- mismatch equation --- anthropometric measures --- algorithmic approach --- optimal design --- stretchable antenna-based strain sensor --- structural optimization --- structural health monitoring --- dimension reduction --- entropy-based correlation coefficient --- multidisciplinary design and analysis --- uncertainty-integrated and machine learning-based surrogate modeling --- additive manufacturing --- complexity --- modular design --- part consolidation --- product recovery --- product image design --- Kansei Engineering --- integrated decision system --- qualitative decision model --- quantitative decision model --- train seats --- measurement-assisted assembly --- coordination space --- assemblability --- small displacement torsor --- Kriging --- lower confidence bounding --- entropy theory --- product design --- simulation-based design optimization --- convolutional neural network --- object detection --- piping and instrument diagram --- unsupervised learning

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Wind turbine aerodynamics is one of the central subjects of wind turbine technology. To reduce the levelized cost of energy (LCOE), the size of a single wind turbine has been increased to 12 MW at present, with further increases expected in the near future. Big wind turbines and their associated wind farms have many advantages but also challenges. The typical effects are mainly related to the increase in Reynolds number and blade flexibility. This Special Issue is a collection of 21 important research works addressing the aerodynamic challenges appearing in such developments. The 21 research papers cover a wide range of problems related to wind turbine aerodynamics, which includes atmospheric turbulent flow modeling, wind turbine flow modeling, wind turbine design, wind turbine control, wind farm flow modeling in complex terrain, wind turbine noise modeling, vertical axis wind turbine, and offshore wind energy. Readers from all over the globe are expected to greatly benefit from this Special Issue collection regarding their own work and the goal of enabling the technological development of new environmentally friendly and cost-effective wind energy systems in order to reach the target of 100% energy use from renewable sources, worldwide, by 2050

simplified free vortex wake --- n/a --- H-type VAWT --- variable pitch --- wind tunnel experiment --- rotor blade optimization --- Non-dominated Sorting Genetic Algorithm (NSGA-II) --- wake effect --- wind turbine noise propagation --- RANS --- axial steady condition --- wind turbine blades --- optimization --- computational fluid dynamic --- straight blade --- typhoon --- gradient-based --- image processing --- actuator line method --- piezo-electric flow sensor --- stall --- turbulence --- airfoil design --- vortex ring --- defects --- DMST model --- wind turbine design --- S809 airfoil --- dynamic fluid body interaction --- Computational Fluid Dynamics --- ABL stability --- semi-submersible platform --- random search --- floating offshore wind turbine --- blade length --- adjoint approach --- Fatigue Loads --- wind turbine optimization --- wind turbine airfoil --- particle swarm optimization --- rotational augmentation --- NREL Phase VI --- mechanical performance --- coupling of aerodynamics and hydrodynamics --- tip speed ratio --- aerodynamics --- oscillating freestream --- super-statistics --- blade element momentum theory --- wind turbine --- wind energy --- boundary layer separation --- wind turbine blade optimization --- actuator disc --- dynamic stall --- complex terrain --- laminar-turbulent transition --- SCADA --- OpenFOAM --- atmospheric stability --- computational fluid dynamics --- economic analysis --- OC5 DeepCWind --- wind tunnel --- actuator disk --- meso/microscale --- cost of energy --- power coefficient --- pitch oscillation --- condition monitoring --- aerodynamic characteristics --- blade parametrization --- wind turbine wakes --- truss Spar floating foundation --- wind resource assessment --- wind shear --- wind turbine noise source --- design --- low wind speed areas --- aerodynamic --- wind farm --- met mast measurements --- turbulent inflow --- VAWTs (Vertical axis wind turbines) --- thermography --- wind speed extrapolation --- MEXICO --- wind turbine wake --- aerodynamic force --- layout optimization --- H-type floating VAWT --- LES --- NACA0012

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Advanced experimental and computational biomechanics have become essential components to better understand the physiological and pathological conditions of biological tissues in the human body. Recent advances in medical imaging modalities, image segmentation, tissue characterization experiments, and predictive computer simulations have made major contributions to transforming current therapeutic paradigms, towards the facilitation of patient-specific diagnostics and individualized surgery planning. This Special Issue of Bioengineering on Advances in Biological Tissue Biomechanics, therefore, focuses on research dealing with cutting-edge experimental and computational methodologies for biomechanical investigations of tissues in the human body system across multiple spatial and temporal scales.

computational fluid dynamics --- bileaflet mechanical heart valve --- adverse hemodynamics --- transvalvular pressure gradients --- turbulent shear stresses --- blood damage --- platelet activation --- aortic valve --- calcification --- elastin degradation --- leaflet --- curvature --- biomarker --- early detection --- porcine brain --- mechanical behavior --- hydration effects --- Split-Hopkinson pressure bar --- micromechanics --- finite element analysis --- collagen crimp --- elastin --- microstructures --- force-controlled mechanical testing --- the tricuspid valve --- functional tricuspid regurgitation --- cardiovascular imaging --- mechanical characterization --- in-vitro experiments --- constitutive modeling --- geometrical modeling --- finite element modeling --- isogeometric analysis (IGA) --- biaxial mechanical characterization --- fluid-structure interactions --- material anisotropy --- sub-valvular components --- soft tissue --- liver --- high-rate compression --- polymeric split-Hopkinson pressure bar --- pentagalloyl glucose --- aneurysm --- enzyme --- biomechanics --- aorta --- biaxial mechanical testing --- cardiac valves --- osmotic swelling --- parameter estimation --- nonlinear preconditioning --- gradient-based minimization --- cirrus --- myocardium --- stiffness --- viscoelastic property --- anisotropy --- fibrosis --- the mitral valve --- collagen fiber architecture --- glycosaminoglycan --- uniaxial mechanical testing --- in-vitro flow loops --- polarized spatial frequency domain imaging --- tricuspid regurgitation --- spatial alignment --- collagen fiber reorientation --- in vivo stress/strain quantification --- constitutive models --- soft tissues --- growth and remodeling (G & R) --- multiscale biomechanics --- patient-specific modeling