The invention relates to a rotor for a fluid pump, in particular for use in the medical sphere, the rotor being compressible for bringing to the place of use and thereafter being expandable. The compressibility is assisted by the provision of cavities, in particular also production of the rotor at least partially from a foam.

A fluid dynamic body having a trailing edge with a pattern formed thereon, the pattern can include a plurality of smoothly surfaced adjacent members with respective interstices therebetween, wherein at least one of the interstices completely contains a porous barrier. In some embodiments, the porous barrier can obstruct fluid flow through the respective interstice between a first surface of the fluid dynamic body on a first side of the trailing edge and a second surface of the fluid dynamic body on a second side of the trailing edge. This helps to reduce noise produced at the trailing edge. In some embodiments, the fluid dynamic body is a wind turbine blade or an air-engine blade.

A method for manufacturing an outer skin of a rotor blade includes forming an outer skin layer of the outer skin from a first combination of at least one of one or more resins or fiber materials. The method also includes forming an inner skin layer of the outer skin from a second combination of at least one of one or more resins or fiber materials. More specifically, the first and second combinations are different. Further, the method includes arranging the outer and inner skin layers together in a stacked configuration. In addition, the method includes joining the outer and inner skin layers together to form the outer skin.

Rotor blade panels, along with methods of their formation, are provided. The rotor blade panel may include one or more fiber-reinforced outer skins having an inner surface; and, a plurality of reinforcement structures on the inner surface of the one or more fiber-reinforced outer skins, where the reinforcement structure bonds to the one or more fiber-reinforced outer skins as the reinforcement structure is being deposited. The reinforcement structure includes, at least, a first composition and a second composition, with the first composition being different than the second composition.

A vertical axis wind turbine is supported by a durable and lightweight composite mast comprising a foam material and a support material, wherein the foam material is either (i) layered within or (ii) distributed among the support material. The foam material may be selected from polyethylene, cross-linked polyethylene, ethafoam, polyester, polyether, ether-like-ester, expanded polystyrene, and/or polyurethane. The support material may be selected from steel, metal, carbon nanotubes, and/or plastics such as polyethylene terephthalate, polyethylene, polyvinyl chloride, polypropylene, polystyrene, polylactic acid, polycarbonate, acrylic, acetal and/or nylon. A mixture ratio between the foam material and the support material may be at least 15:1. The mast may comprise a central core layer of foam and a peripheral layer of the support material. In an embodiment, adjacent layers of the central core layer and the peripheral layers alternate between the core and support materials.

Rotor blade panels, along with methods of their formation, are provided. The rotor blade panel may include one or more fiber-reinforced outer skins having an inner surface; and, a plurality of reinforcement structures on the inner surface of the one or more fiber-reinforced outer skins, where the reinforcement structure bonds to the one or more fiber-reinforced outer skins as the reinforcement structure is being deposited. The reinforcement structure includes, at least, a first composition and a second composition, with the first composition being different than the second composition.

A rotor blade for a wind turbine comprising: an internal blade cavity defined by two opposing internal surfaces of two shells of the rotor blade; a receptor block forming part of a lightning protection system and disposed within the internal blade cavity; and a centralising device that spaces the receptor block from the two opposing internal surfaces of the shells such that the receptor block lies centrally within the internal blade cavity. The receptor block is therefore in a desired position for installing receptors for lightning discharge.

Provided is a composite material for a wind turbine blade, the composite material including a plurality of rigid elements and plurality of flexible elements, wherein each flexible element is arranged between two rigid elements and is connected thereto such that the rigid elements are flexibly connected to each other by the flexible elements. The flexibility of the composite material can be achieved by using the interspaces between the rigid elements. Therefore, when the composite material is placed on a curved surface, hollow spaces between the rigid elements may be reduced or avoided.

A rotor blade for a wind turbine is provided. The rotor blade includes a pressure side, a suction side, a leading edge section with a leading edge, and a trailing edge section with a trailing edge. An airflow flows along the surface of the rotor blade from the leading edge section to the trailing edge section and builds up a boundary layer in close proximity to the surface of the rotor blade. The rotor blade includes a noise reduction device for reducing noise which is generated by interaction of the airflow and the rotor blade. The noise reduction device is located within the boundary layer of the rotor blade. The noise reduction device includes a cover and connection device for connecting the cover to the surface of the rotor blade. The cover spans at least over a part of the surface of the rotor blade.

A method using machine learned, scenario based control heuristics including: providing a simulation model for predicting a system state vector of the dynamical system in time based on a current scenario parameter vector and a control vector; using a Model Predictive Control, MPC, algorithm to provide the control vector during a simulation of the dynamical system using the simulation model for different scenario parameter vectors and initial system state vectors; calculating a scenario parameter vector and initial system state vector a resulting optimal control value by the MPC algorithm; generating machine learned control heuristics approximating the relationship between the corresponding scenario parameter vector and the initial system state vector for the resulting optimal control value using a machine learning algorithm; and using the generated machine learned control heuristics to control the complex dynamical system modelled by the simulation model.