A method for determining mechanical performance of the road includes the following: acquiring an initial subgrade reaction modulus k.sub.s of a subgrade of a target road section by using a field plate-bearing test process; acquiring a preset load p of the subgrade and geocell parameters of a preset geocell of the subgrade; calculating a composite subgrade reaction modulus k.sub.r of the subgrade on condition that the roadbed is under a reinforced working condition by a composite modulus calculation formula; calculating an equivalent thickness RP of the roadbed under the reinforced working condition by a depth adjustment calculation formula; and outputting the composite subgrade reaction modulus k.sub.r and the equivalent thickness RP.

A method of designing a morphable aerodynamic surface includes discretizing and parameterizing a model of a morphable surface to create a function to optimize; utilizing finite element analysis to solve for displacements and associated errors at an initialization point; and iteratively calculating a gradient cost function, define step size and search direction, step according to defined step size and search direction, and recalculate displacements and associated errors to converge on final thickness vector.

The road simulation device includes a frame structure and a transmission structure. The transmission structure includes a first test bench, a second test bench, a third test bench and a fourth test bench. A first sliding plate structure of the first test bench slides in a first direction and a second direction, a second sliding plate structure of the second test bench slides in the first direction, and a third sliding plate structure of the third test bench slides in the second direction. The first sliding plate structure and the first base structure, the second sliding plate structure and the second base structure, the third sliding plate structure and the third base structure, as well as the fourth baffle plate structure and the fourth base structure are connected by spherical hinges. Damages to the frame structure caused by huge acting force generated by rigid connection during testing can be avoided.

An optimization analysis method of an adhesive position in an automotive body includes: imposing a predetermined vibration condition on an automotive body model, performing frequency response analysis, and obtaining a vibration mode generated in the automotive body model, and a deformation form in the vibration mode; determining a load condition to be imposed on the automotive body model; generating an optimization analysis model obtained by setting an adhesive candidate in the automotive body model; setting an optimization analysis condition used to perform optimization analysis by using the adhesive candidate set in the generated optimization analysis model; and imposing the load condition determined in the load condition determination step on the optimization analysis model, performing the optimization analysis, and obtaining the adhesive candidate that satisfies the optimization analysis condition, as an optimized adhesive portion where each parts assembly is adhesively bonded.

Provided is a configuration construction and attitude control method for a pyramid deorbit sail. By taking into consideration environmental perturbation like atmospheric resistance perturbation and non-spherical earth perturbation, a dynamics model featuring three-dimensional orbit-and-attitude coupling based on position vectors and quaternion descriptions, the deorbit sail is taken as a rigid body, a spacecraft body is taken as a mass point, airflow obstruction is considered in the windward area, thereby improving the precision of the dynamics model; based on this model, the law of influence of the configuration parameters in the deorbit sail, such as a cone angle and a strut length, on the attitude stability and deorbiting efficiency of the spacecraft in different cases is analyzed, the configuration parameters of the pyramid deorbit sail system are analyzed and optimized according to the derived law, so as to obtain a pyramid deorbit sail achieving high attitude stability and high deorbiting efficiency.

A method for controlling a deformable mirror surface shape based on a radial primary function processes samples of a neural network training set, obtains elements of the neural network training set, characterizes the complex surface shape of the deformable mirror in each sample by using a radial primary function, takes characterization parameters of the surface shape in the each sample as an input of a neural network, and trains the neural network by taking a voltage of each piezoelectric ceramic corresponding to the complex surface shape as a corresponding output of the neural network. Training times of the neural network are consistent with a number of the samples. Finally, the trained neural network is obtained to verify the training effect of the neural network. According to the characterization parameters of the required surface, the neural network is used to control the deformable mirror to generate the required surface.

A simulation test system and method for vehicle road noise cancellation (RNC) are provided in one or more embodiments of the present disclosure. The simulation test system may include a vehicle RNC simulation system and a power amplifier. The vehicle RNC simulation system is configured to simulate an RNC system in a vehicle environment. The power amplifier is configured to execute an RNC algorithm and may perform data communication with the vehicle RNC simulation system. The vehicle RNC simulation system transmits acceleration data representing an acceleration signal and microphone data representing a microphone signal to the power amplifier as inputs to the RNC algorithm in the power amplifier. Moreover, the vehicle RNC simulation system may receive speaker data representing a speaker signal from the power amplifier. The vehicle RNC simulation system includes a secondary path simulation model and a signal flow simulation model.

A system and method for simulating activity of a fluid in a volume that represents a physical space, the activity of the fluid in the volume being simulated so as to model movement of elements within the volume. The method includes at a first time, identifying a first set of vortices in a transient and turbulent flow. The method includes at a second time that is subsequent to the first time, identifying a second set of vortices. The method includes tracking changes in the vortices by comparing the first set and the second set of discrete vortices. The method includes identifying one or more noise sources based on the tracking. The method includes determining the contribution of one or more noise sources at a receiver. The method also includes outputting data indicating one or more modifications to one or more geometric features of a device or an entity.

A machine learning model is trained by defining a scenario including models of vehicles and a typical driving environment. A model of a subject vehicle is added to the scenario and sensor locations are defined on the subject vehicle. A perception of the scenario by sensors at the sensor locations is simulated. The scenario further includes a model of a parked vehicle with its engine running. The location of the parked vehicle and the simulated outputs of the sensors perceiving the scenario are input to a machine learning algorithm that trains a model to detect the location of the parked vehicle based on the sensor outputs. A vehicle controller then incorporates the machine learning model and estimates the presence and/or location of a parked vehicle with its engine running based on actual sensor outputs input to the machine learning model.

A simulation system and method for simulating a noise environment of a vehicle includes a memory configured to store a reference sample signal and a noise sample signal, a control unit electrically connected to the memory and configured to generate a reference signal based on the reference sample signal, generate a noise signal based on the noise sample signal, and transmit the reference signal to a noise control system, and a speaker electrically connected to the control unit and configured to convert the noise signal into a sound wave and output the sound wave.