A flutter wind tunnel test model simulates a shape and vibration property of an aircraft part, for a flutter wind tunnel test of the aircraft part. The model at least partially has non-solid structure having branched clearances inside. A volume of a portion, other than the clearances, of the non-solid structure, per unit volume is defined by density. A method of producing a flutter wind tunnel test model simulating a shape and vibration property of an aircraft part, for a flutter wind tunnel test of the aircraft part, includes: shaping non-solid structure with a three-dimensional printer and composing at least a part of the flutter wind tunnel test model using the non-solid structure. The non-solid structure has branched clearances inside. A volume of a portion, other than the clearances, of the non-solid structure, per unit volume is defined by density.

Processor-implemented methods and systems for aerodynamically optimizing a design geometry of a vehicle body using a convolutional neural network (CNN) are provided. The method may include receiving a signed distance function (SDF) data file that represents the design geometry of the vehicle body. The method includes receiving a range of inflow boundary conditions. The processor processes the SDF over the range of boundary conditions, using the CNN, to generate therefrom drag and lift outputs for the design geometry. The drag and lift outputs may be displayed in the form of one or more intensity maps.

Processor-implemented methods and systems for aerodynamically optimizing a design geometry of a vehicle body using a convolutional neural network (CNN) are provided. The method may include receiving a signed distance function (SDF) data file that represents the design geometry of the vehicle body. The method includes receiving a range of inflow boundary conditions. The processor processes the SDF over the range of boundary conditions, using the CNN, to generate therefrom drag and lift outputs for the design geometry. The drag and lift outputs may be displayed in the form of one or more intensity maps.

Disclosed are devices and methods of detecting and mitigating oscillatory instabilities in systems with turbulent flow, such as thermoacoustic, aeroacoustic or aeroelastic equipment. The system includes a sensor array for measuring one or more parameters of an operating equipment S, and an analysis and prediction unit. The analysis and prediction unit is configured to estimate a state tensor to identify a state of the equipment indicating stable operation or impending oscillatory instability. The system further includes an actuator array configured to implement a control action to promote stable operation of the equipment. Methods for robust prediction of the state of stability are also disclosed. A neural ordinary differential equation (ODE) method of predicting stability or instability is disclosed, involving forming a neural network that incorporates an equation characteristic of the operational state. The invention further discloses a hybrid convolutional neural network based prediction method for stability.

A balance protection system for a wind tunnel test system that includes a balance component, a model component connected to the balance component and a sting component connected to the balance component is disclosed. The balance protection system includes a first set of features on the model component that mate with a second of features on to the sting component. The clearances between the first and second set of features determine an amount of allowed movement of the model with respect to the balance. Actuators can be used to actively adjust the amount of clearance and respective allowed movement of the model with respect to the balance. Limiting movement of the model with respect to the balance protects the balance from damage caused by excessive forces applied to the model.

An assembly quality detection device and a method for a wind screen cleaning system based on streamline pattern, includes a main body of a test bench and a detection system. The main body of the test bench includes a test bench rack and a cleaning centrifugal fan; the inside of the test bench rack is provided with a cleaning space. The detection system includes a smoke generation and transmission device, a two-degree-of-freedom smoke fixed-point release mechanism, a high-speed image acquisition system and a control system. A fixed base is installed on the upper end of the outlet of the cleaning centrifugal fan, a linear moving guide rail device is installed on the fixed base, the linear moving guide rail device is equipped with a moving slider, the moving slider is installed with a rotating mechanism, the rotating mechanism output end is provided with a smoke releasing duct, the smoke releasing duct is communicated with the smoke generation and transmission device. The detection device and method can test the manufacturing and assembly quality of the cleaning system of the combine harvester by combining the characteristics of wind tunnel streamline pattern with image processing and corresponding mathematical operation.

The present invention belongs to the field of ship engineering, and provides a ship real wind measuring device calibration method. In this method a ship sway simulator is build using a 2-axis ganged platform, natural wind is simulating generated using a wind tunnel flow field. Then the ship sway simulator is controlled to simulate the ship spatial motion under the disturbance of stormy waves. Furthermore, the data of the wind speed and direction is obtained under different sway angles and speeds. So that the database of wind direction and speed measurement, attitude measurement, actual wind direction and speed measurement is formed. Subsequently, a calibration model based on BP neural network is constructed using this database, a ship real wind direction and speed calibration algorithm is formed, which can calibrate a ship real wind measuring device.

Various techniques are provided for correcting error in static pressure data. In one example, a system includes an aircraft component. The aircraft component can include a port disposed within the aircraft component. A static pressure sensor is disposed within the port. The static pressure sensor is configured to provide primary pressure data in response to environmental air pressure. The data provided can include error due to acoustic disturbance. The system can also include an acoustic sensor configured to provide acoustic data in response to the acoustic disturbance. Data from the static pressure sensor and the acoustic sensor can be provided to a processor communicatively coupled to the static pressure sensor and the acoustic sensor. The processor can be configured to determine corrected static pressure data using the provided primary pressure data and the provided acoustic data. Additional systems and similar methods are also provided.

The invention discloses a coupled free vibration wind tunnel testing device with adjustable frequency ratio of torsional-vertical vibration, belonging to the technical field of bridge wind tunnel testing device. The device includes rigid testing model, lightweight rigid rods, lightweight rigid circular hubs, thin strings, linear tensile springs, carbon fiber ropes, and lightweight small hubs. The invention adjusts the torsional stiffness of the system by conveniently changing the diameter of the small hub, the diameter and length of the carbon fiber rope, etc. The device has the advantages of simple structure, convenient installation and avoiding the previous tedious work. It can achieve a variety of torsional-vertical vibration frequency ratio testing conditions by using only one diameter large hub. It can not only greatly save the time of replacing the large hub, but also facilitate the realization of higher torsional-vertical vibration frequency ratio testing conditions which are difficult to achieve by the previous methods.

A sensing mechanism of a two-dimensional airfoil model, which includes pressure sensor groups, multiple first tubes, the second tube, and a cavity. The pressure sensor groups are vertically fixed to mounting holes in the surface of the two-dimensional airfoil model. The pressure measurement surface of each pressure sensor is vertical to the surface of the two-dimensional airfoil model. Multiple mounting holes are opened in and vertical to the surface of the two-dimensional airfoil model. The cavity is fixed to the interior of the two-dimensional airfoil model. The reference pressure end of each pressure sensor is connected to the cavity through the first tube, the multiple pressure sensors of the pressure sensor groups are in one-to-one correspondence with the multiple first tubes. The cavity is connected with the first end of the second tube. The second end of the second tube is located in the air outside the two-dimensional airfoil model.