Abstract: A system for reducing vibrations in a rotating system uses a variable viscosity medium that is redistributed in a housing connected to the rotating system. Specifically, the medium is responsive to a control signal that is generated as a function of rotational speed of the rotational system. The control signal activates a triggering device that promotes a change in viscosity of the medium such that it is distributed within the housing in a manner that reduces vibratory loads.

Abstract: A multi-element rotor blade includes an individually controllable main element and fixed aerodynamic surface in an aerodynamically efficient location relative to the main element. The main element is controlled to locate the fixed aerodynamic surface in a position to increase lift and/or reduce drag upon the main element at various azimuthal positions during rotation.

Abstract: A method of predicting the cutting speed for machining of titanium alloy comprising the steps of obtaining a first transfer function for a tool system, obtaining a second transfer function for a workpiece system, selecting from the first transfer function a first flexible mode, selecting from the second transfer function a second flexible mode, defining a natural frequency of the first flexible mode and the second flexible mode, calculating a tooth passing frequency using the defined natural frequency, accepting the calculated tooth passing frequency if the calculated tooth passing frequency differs from a second harmonic of a combined system formed of the tool system and the workpiece system and from at least one natural frequency corresponding to the tool system and the workpiece system, calculating a stable spindle speed, defining a cut depth using the calculated spindle speed.

Abstract: A method of predicting the cutting speed for machining of titanium alloy comprising the steps of obtaining a first transfer function for a tool system, obtaining a second transfer function for a workpiece system, selecting from the first transfer function a first flexible mode, selecting from the second transfer function a second flexible mode, defining a natural frequency of the first flexible mode and the second flexible mode, calculating a tooth passing frequency using the defined natural frequency, accepting the calculated tooth passing frequency if the calculated tooth passing frequency differs from a second harmonic of a combined system formed of the tool system and the workpiece system and from at least one natural frequency corresponding to the tool system and the workpiece system, calculating a stable spindle speed, defining a cut depth using the calculated spindle speed.

Abstract: A multi-element rotor blade includes a main element and an active slat movable relative to the main element. The slat rotates and translates relative to the main element from a base position. The base position provides a compromise between minimum coefficient of drag CD and maximum coefficient of lift CLmax. In the advancing blade, since the airspeed thereof is significantly greater than the retreating blade, the slat is positively rotated from the base position to minimizes drag at low angles of attack. In the retreating blade, since the airspeed thereof is significantly lower than the advancing blade, the slat is negatively rotated and translated to maximize the coefficient of lift CLmax.

Abstract: Two neural networks are used to control adaptively a vibration and noise-producing plant. The first neural network, the emulator, models the complex, nonlinear output of the plant with respect to certain controls and stimuli applied to the plant. The second neural network, the controller, calculates a control signal which affects the vibration and noise producing characteristics of the plant. By using the emulator model to calculate the nonlinear plant gradient, the controller matrix coefficients can be adapted by backpropagation of the plant gradient to produce a control signal which results in the minimum vibration and noise possible, given the current operating characteristics of the plant.

Abstract: Two neural networks are used to control adaptively a vibration and noise-producing plant. The first neural network, the emulator, models the complex, nonlinear output of the plant with respect to certain controls and stimuli applied to the plant. The second neural network, the controller, calculates a control signal which affects the vibration and noise producing characteristics of the plant. By using the emulator model to calculate the nonlinear plant gradient, the controller matrix coefficients can be adapted by backpropagation of the plant gradient to produce a control signal which results in the minimum vibration and noise possible, given the current operating characteristics of the plant.

Abstract: An elastomeric coupler assembly having a helical elastomeric bearing movably supports an active slat relative to a main element. An inner elastomeric coupler assembly and an outer elastomeric coupler assembly support the slat therebetween. Centrifugal force operates to drive the slat to a first position and an actuator rod operates in tension to pull upon the inner elastomeric coupler assembly to drive the slat in opposition to the centrifugal force to a second position. The helical elastomeric bearing is layered such that it defines a section of a circular helix. The circular helix provides a coupling, which converts a linear input parallel to a virtual hinge axis into a rotary output to pitch the slat. In operation, centrifugal force operates to slide the slat outboard toward the blade tip such that the attached slat moves elastomerically along the helical arc of the helical elastomeric bearing to rotate the slat nose down.

Abstract: An elastomeric coupler assembly having a helical elastomeric bearing movably supports an active slat relative to a main element. An inner elastomeric coupler assembly and an outer elastomeric coupler assembly support the slat therebetween. Centrifugal force operates to drive the slat to a first position and an actuator rod operates in tension to pull upon the inner elastomeric coupler assembly to drive the slat in opposition to the centrifugal force to a second position. The helical elastomeric bearing is layered such that it defines a section of a circular helix. The circular helix provides a coupling, which converts a linear input parallel to a virtual hinge axis into a rotary output to pitch the slat. In operation, centrifugal force operates to slide the slat outboard toward the blade tip such that the attached slat moves elastomerically along the helical arc of the helical elastomeric bearing to rotate the slat nose down.

Abstract: A multi-element rotor blade includes a main element and an active slat movable relative to the main element. The slat rotates and translates relative to the main element from a base position. The base position provides a compromise between minimum coefficient of drag CD and maximum coefficient of lift CLmax. In the advancing blade, since the airspeed thereof is significantly greater than the retreating blade, the slat is positively rotated from the base position to minimizes drag at low angles of attack. In the retreating blade, since the airspeed thereof is significantly lower than the advancing blade, the slat is negatively rotated and translated to maximize the coefficient of lift CLmax.

Abstract: Two neural networks are used to control adaptively a vibration and noise-producing plant. The first neural network, the emulator, models the complex, nonlinear output of the plant with respect to certain controls and stimuli applied to the plant. The second neural network, the controller, calculates a control signal which affects the vibration and noise producing characteristics of the plant. By using the emulator model to calculate the nonlinear plant gradient, the controller matrix coefficients can be adapted by backpropagation of the plant gradient to produce a control signal which results in the minimum vibration and noise possible, given the current operating characteristics of the plant.

Abstract: Two neural networks are used to control adaptively a vibration and noise-producing plant. The first neural network, the emulator, models the complex, nonlinear output of the plant with respect to certain controls and stimuli applied to the plant. The second neural network, the controller, calculates a control signal which affects the vibration and noise producing characteristics of the plant. By using the emulator model to calculate the nonlinear plant gradient, the controller matrix coefficients can be adapted by backpropagation of the plant gradient to produce a control signal which results in the minimum vibration and noise possible, given the current operating characteristics of the plant.

Abstract: A hub mounted actuation system for providing control of a portion of a rotor blade, such as a flap, on a rotorcraft. The rotor blade is attached to a rotor shaft that rotates with respect to an airframe. The hub mounted actuation system includes a stationary support mounted to the airframe and a rotary support attached to the rotor shaft for concomitant rotation therewith. At least one hub actuator rotates in combination with the rotor blade and includes a piston which is slidable within a housing. The piston and housing define a pressure chamber within the actuator which contains a fluid to be pressurized. A displacement control device is disposed between the stationary support and the rotary support for controlling movement of the piston within the housing. A linkage connects the hub actuator to the portion of the blade to be controlled. The linkage is adapted to displace the blade portion as a function of the movement of the piston within the housing.