226 results about "Drag coefficient" patented technology

The invention provides an airfoil flow field prediction method based on multi-task learning, and the method comprises the steps: firstly building an airfoil flow field prediction model based on multi-task learning, which comprises an encoder, a backbone network and a multi-head decoder; then training the established model by using an airfoil flow field data set and adopting an optimization strategy based on multi-task learning; and finally, performing geometric parameterization and grid generation processing on an airfoil which actually needs flow field prediction to obtain standardized airfoil flow field data, and inputting the airfoil flow field data into the trained airfoil flow field prediction model for prediction to obtain full flow field physical quantity distribution and lift-drag coefficient information. According to the method, a multi-task loss optimization strategy is used in the prediction model training process, so that the problem of conflict between airfoil profile surface loss and volume loss optimization can be effectively solved, and then the construction of an airfoil profile proxy model and the accurate prediction of flow field information and aerodynamic parameters are realized.

The invention provides an aircraft aerodynamic configuration design method and device based on simulation, and relates to the technical field of aircraft aerodynamic configuration design, and the method comprises the steps: obtaining aerodynamic characteristic parameters of aircrafts of different airfoils to construct a multi-source aerodynamic database; a neural network model is established based on the database, airfoil geometric parameters serve as input, the lift coefficient, the resistance coefficient and the lift-drag ratio serve as labels for training, and an aerodynamic performance prediction model is obtained; candidate combinations are generated in an airfoil geometric parameter design space, aerodynamic characteristics of the candidate combinations are predicted through a model, a fitness function is optimized by utilizing dynamic weights, and the combination with the highest fitness is selected as an optimized airfoil parameter by adopting a genetic algorithm; and performing simulation verification on the optimization parameters, extracting a simulation result, comparing the simulation result with the output of the prediction model, judging that the optimization combination is effective when an error meets a preset requirement, and completing aerodynamic configuration design accordingly. The method improves the prediction accuracy and design efficiency of aerodynamic performance.

The invention relates to the technical field of ship design optimization, and discloses a hull shape optimization method based on neural network modeling. In the data acquisition stage of the method, initial appearance parameters and hydrodynamic performance data of a ship body are obtained, the appearance parameters comprise geometric dimensions and shape features, and the performance data comprise resistance coefficients and wave-making resistance values. In the neural network construction stage, a neural network model with a multi-layer perceptron structure is trained by using collected data, weights are updated through a back propagation algorithm, and a nonlinear mapping relation between appearance parameters and hydrodynamic performance indexes is established. In the shape optimization stage, the trained neural network model is used for carrying out iterative adjustment on the shape of the ship body, fluid dynamic performance indexes are recalculated through the model after each adjustment until preset convergence conditions are met, and finally optimized ship body shape data are output. According to the method, partial complex calculation is replaced by the neural network, and intelligent optimization of the hull appearance is realized.

The invention provides a joint prediction method and system for a wind resistance coefficient and a surface pressure field of an automobile, and relates to the technical field of automobile aerodynamics. According to the joint prediction method, the pressure field and the wind resistance coefficient are predicted in the same network in parallel, and the wind resistance coefficient obtained by pressure field integration and derived from the pressure field and the wind resistance coefficient obtained by network direct regression are calibrated by physical consistency constraint. The model has physical confidence and interpretability while ensuring numerical precision, so that a key stress area can be positioned and serves an automobile modeling iteration process.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

The invention discloses a design method for a propeller of a hydrogen energy power logistics unmanned aerial vehicle. The design method comprises the steps that overall design parameters of the unmanned aerial vehicle and basic parameters of blades of the propeller are determined; selecting a basic airfoil based on the overall design parameters, and constructing a proxy model for airfoil optimization by taking a target lift coefficient as a design point, keeping the maximum thickness of the airfoil unchanged to a constraint and taking a minimum resistance coefficient as targets; based on the blade design objective function and the design variable, blade appearance design optimization is carried out, and chord length distribution parameters and torsion angle distribution parameters of airfoils of all station positions of the blade are determined according to the minimum energy loss principle; performing three-dimensional modeling on the propeller based on the chord length distribution parameters and the torsion angle distribution parameters of the airfoils of all the station positions of the blades to obtain a propeller three-dimensional model; performing performance calculation on the propeller three-dimensional model to obtain propeller tension and power at different rotating speeds and wind speeds; and comparing the pulling force and power of the propeller at different rotating speeds and wind speeds with design parameters, and determining the initial shape of the propeller.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

The invention provides a vehicle point cloud wind resistance coefficient integrated prediction method and system based on feature recognition, and relates to the technical field of wind resistance coefficient prediction, and the method specifically comprises the steps: obtaining the point cloud data of a vehicle model, and carrying out the preprocessing of the point cloud data; constructing a classification network model, inputting the preprocessed point cloud data into the classification network model for vehicle type classification, and outputting vehicle type categories and probability values corresponding to the vehicle type categories; constructing a plurality of specific models in one-to-one correspondence with the vehicle type categories and a generalization model; whether the maximum probability value in the vehicle type classification labels is higher than a preset threshold value or not is judged, if yes, a specific model corresponding to the vehicle type category is selected to conduct wind resistance coefficient prediction, and if not, a generalization model is selected to conduct wind resistance coefficient prediction; according to the method, the vehicle types are classified and matched with the proper wind resistance coefficient prediction model, so that the prediction speed and the accuracy of a prediction result are greatly improved.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

The invention discloses an aerodynamic airfoil profile generation method based on a de-noising diffusion probability model and a variational auto-encoder in the technical field of deep learning and aerodynamic design, which comprises the following steps of: 1, acquiring airfoil profile set data from a public database, re-dividing airfoil profile coordinate points, and calculating a lift coefficient and a resistance coefficient of the airfoil profile set data; 2, preprocessing the airfoil profile data; 3, constructing a joint model based on a variational auto-encoder and a de-noising diffusion probability model, and generating airfoil profile potential representation meeting design conditions by learning potential space representation and combining the de-noising diffusion probability model; 4, inputting the re-divided airfoil profile coordinate point data set into the potential spatial diffusion model for training; and step 5, based on the trained potential spatial diffusion model, inputting different design conditions, and generating an airfoil profile sample conforming to specified geometric characteristics, and according to the method, a high-quality airfoil profile can be generated under different aerodynamic constraint conditions, so that the feasibility and reliability of aerodynamic configuration optimization are improved.

A deformable wing with variable camber of front and rear edges is composed of a driving device, a middle-section fixed wing, a movable rear edge and a movable front edge. Through the combined movement of the wings, the smooth and continuous deformation of the wings can be realized, and the resistance caused by discontinuous deformation and gaps of the traditional wings is eliminated. The deformable wing capable of changing the camber of the front edge and the rear edge has the advantages of being simple in structure, low in cost, light and firm in structure and large in variable angle, the lift-drag coefficient of the wing can be changed under the control of an airborne computer according to different flight tasks and environments through smooth and continuous deformation on the premise of low resistance and low noise, and the wing can be applied to the aircraft. The wing can be used as a flap to improve cruising speed and shorten takeoff and landing taxiing distance, and can also be used as an aileron to ensure that resistance coefficients of a left wing and a right wing are the same when lift coefficients change, a rolling-yawing coupling effect is reduced, and flight quality is remarkably improved.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

The invention discloses a wind turbine airfoil full-attack-angle pneumatic measurement and prediction method for a wind tunnel experiment in the field of wind tunnel experiments, and the method comprises the steps: 1) carrying out the modeling of a wind turbine airfoil, designing a wind turbine airfoil model of the wind tunnel experiment, and building a test platform; (2) checking the safety of equipment and an experimental environment; 3) opening a wind tunnel to obtain a set wind speed; 4) sequentially changing the attack angle, obtaining the pressure data of the wind turbine airfoil at the expected attack angle moment, and closing the wind tunnel after the measurement is finished; 5) adjusting the pitot tube to be right in front of the wind turbine airfoil, repeating the step 3), and collecting incoming flow pressure right in front of the wind turbine airfoil when the attack angles are 90 degrees and 270 degrees; (6) data processing is conducted, and correction coefficients related to the incoming flow wind speed are obtained; and 7) calculating a lift coefficient and a resistance coefficient, obtaining a resistance coefficient shrinkage ratio, and predicting the lift coefficient and the resistance coefficient of the wind turbine airfoil under the full-attack-angle working condition. The method can quickly predict the aerodynamic change condition of the wind turbine airfoil under the expected working condition.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle wind speed estimation method, which comprises the following steps: acquiring the relationship between the windward area and the body resistance coefficient of an unmanned aerial vehicle and the horizontal attitude angle of the unmanned aerial vehicle; the unmanned aerial vehicle is controlled to be automatically braked and stopped at different speeds, and induced resistance parameters are identified according to the acceleration in the braking and stopping process; according to the induced resistance parameters and the obtained relation, a wind speed model for calculating the wind speed is obtained; controlling the flight of the unmanned aerial vehicle, and collecting flight parameters of the unmanned aerial vehicle in the flight process in real time; and calculating the wind speed in the flight process of the unmanned aerial vehicle by combining the obtained wind speed model and the flight parameters. According to the method, induced resistance parameters are calculated off line through a parameter identification method, so that the method can be more effectively close to a real flight state and has better accuracy.

The invention belongs to the technical field of launching platforms, and particularly relates to a same-projectile different-shot average trajectory difference evaluation method which comprises the following steps: step 1, establishing a trajectory simulation model; 2, carrying out an average ballistic performance difference check test; 3, identifying a zero resistance coefficient; 4, coincidence calculation is carried out; step 5, determining equivalent distributed source parameter distribution characteristics; 6, equivalent current-day error source parameter distribution characteristics are determined; 7, estimating a system error; 8, evaluating the average ballistic difference of the non-test supporting points; step 9, reconstructing a trajectory; and step 10, evaluating the average ballistic difference of the test supporting points. Compared with the prior art, the method has the advantages that test supporting point average ballistic difference evaluation with low consumption, low false risk and high credibility can be realized; and non-test supporting point average ballistic performance difference evaluation information can be given, and comprehensive evaluation is realized.

The present invention provides an online estimation method, device and medium for aircraft aerodynamic parameters based on thrust deviation correction, and relates to the technical field of online identification of aircraft parameters. The method comprises: using an extended Kalman filter to iteratively predict the augmented state of the aircraft system step by step; using a forgotten recursive least squares estimator to estimate the axial aerodynamic force and normal aerodynamic force coefficients and the thrust deviation proportional coefficient within a given time window, and then calculating the aerodynamic lift, drag coefficients and the corrected thrust estimation results; judging the convergence of the thrust deviation proportional coefficient estimation results; if it has not converged, aerodynamic derivative estimation is carried out based on the uncorrected thrust and lift and drag aerodynamic coefficients; if it has converged, the corrected thrust and the corrected lift and drag aerodynamic coefficients are brought into the general recursive least squares estimator to carry out aerodynamic derivative estimation. The online estimation method proposed by the present invention can effectively improve the accuracy of longitudinal aerodynamic derivative estimation under thrust measurement deviation.

The invention discloses a method and a system for rapidly evaluating aerodynamic performance of an automobile body appearance. The method specifically comprises the following steps: generating a geometric curved surface sample of an automobile body surface by adopting a parameterized design method; carrying out fluid numerical analysis on a vehicle body external flow field; an encoder for vehicle body appearance surface geometry is established, and the geometric structure of the vehicle body surface is recognized; establishing a prediction model based on a multi-scale map neural network, and performing geometric data memory, transmission and updating on the flow field of the vehicle body appearance surface; and outputting vehicle body aerodynamic characteristic parameters (a resistance coefficient, a lift coefficient and a lateral force coefficient) and an error level. Compared with the prior art, the neural network algorithm is ingeniously designed, rapid prediction of the aerodynamic characteristic parameters of the automobile body is achieved, the method can be used for rapid performance evaluation in the automobile body development process, the design efficiency is improved, and the development cost is reduced.

The present invention provides a golf ball in which dimples are formed on a ball surface, wherein when edge angles at points where depths are 10%, 20%, and 30% in a cross-section of one dimple are denoted as ED1, ED2, and ED3, respectively, dimples with a cross-sectional shape satisfying the following condition (1):ED⁢1<ED⁢2>ED⁢3(1)account for at least 10% of a total number of the dimples, and further a ratio A1 of a lift coefficient at a Reynolds number of 218,000 and a spin rate of 2,800 rpm to a drag coefficient, a ratio A2 of a lift coefficient at a Reynolds number of 184,000 and a spin rate of 2,900 rpm to a drag coefficient, and a ratio A3 of a lift coefficient at a Reynolds number of 158,000 and a spin rate of 3,100 rpm to a drag coefficient are optimized.

The invention discloses an excavator heat balance performance prediction method, system and device and a storage medium. The method comprises the steps that a heat balance performance test of a standard excavation working condition is conducted; respectively establishing an engine heat dissipating capacity Qw calculation model and an engine air inflow mair calculation model; obtaining Qw and mair under the standard excavation working condition; building a one-dimensional cooling system model; cabin resistance coefficient calibration is completed; setting the heat dissipation power of the hydraulic system, calculating the real-time oil temperature of the hydraulic oil tank based on the one-dimensional cooling system model, adjusting the heat dissipation power of the hydraulic system to enable the difference value between the real-time oil temperature of the hydraulic oil tank and the oil temperature of the hydraulic oil tank to be smaller than a set value, and calculating the ratio b of the heat dissipation power of the hydraulic system to the engine power; and on the basis of a calculation model of Qw and mair, b and the calibrated cabin resistance coefficient, predicting the heat balance performance of the excavator under the target working condition. According to the method, the design accuracy and economy can be improved, the prediction of the full-working-condition heat balance performance is realized, and the high-temperature fault solving efficiency is accelerated.

A multi-piece solid golf ball includes a core, a surrounding layer, an intermediate layer, and a cover, in which a large number of dimples are formed on an outside surface of the cover, a relationship of surface hardnesses of each sphere is specified, an initial velocity of the ball is set to 75.0 to 77.724 m / s, and a relationship of a ratio to a lift coefficient / drag coefficient at a Reynolds number of 218,000 and a spin rate of 2,800 rpm, a lift coefficient / drag coefficient at a Reynolds number of 184,000 and a spin rate of 2,900 rpm, and a lift coefficient / drag coefficient at a Reynolds number of 158,000 and a spin rate of 3,100 rpm is specified.

The invention discloses a ship air sail navigation aiding energy efficiency dynamic optimization method and system and a ship, and relates to the technical field of ship energy conservation. Dynamic parameters in the ship navigation process are collected in real time; establishing a dynamic coupling model; the coupling model is utilized to quantify the dynamic interference of the hull attitude parameters on the air sail state parameters into attack angle offset; a reinforcement learning algorithm is adopted to simulate the attack angle offset, and the optimal attack angle of the air sail is obtained; according to the optimal attack angle and the environmental parameters, target adjustment parameters of the air sail are calculated; and driving the air sail to adjust the sail body rotation angle and the sail surface inclination angle in real time according to the target adjustment parameters. According to the method, the air sails always work in the efficient interval with the maximum lift coefficient and the minimum resistance coefficient, the pneumatic interference model is introduced, the total auxiliary thrust of the multiple sails is improved, the problem that the energy-saving effect is reduced due to dynamic deviation of the attack angle is effectively solved, and the situation that the fuel consumption of a main engine is reduced is stably achieved.

The invention provides a multi-vehicle-type wind resistance coefficient real-time prediction method and system based on vehicle characteristic parameters, and relates to the technical field of vehicle wind resistance coefficient prediction.The method comprises the steps that an original data set containing whole vehicle characteristic parameters and vehicle type labels is obtained, the original data set is processed, and a test set and a non-test set are obtained through division; performing hyper-parameter tuning on the XGBoost model by adopting a Bayesian optimization method and utilizing the non-test set, and determining an approximate optimal hyper-parameter of the XGBoost model; performing optimization again by using a sparrow search algorithm to obtain an optimal hyper-parameter; and carrying out multiple times of training and verification on the optimized XGBoost model, and determining an optimal model so as to carry out wind resistance coefficient prediction. According to the method, high prediction precision can be ensured when wind resistance prediction of different vehicle types is coped, meanwhile, good calculation efficiency is achieved, and the requirements of rapid iteration and real-time prediction are met.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.

The invention discloses a ship resistance reduction optimization design method and system based on CFD-GA, and the method comprises the steps: carrying out the CFD numerical simulation of a ship without a fairing, and calculating a ship resistance coefficient; initial design parameters of the fairing are determined, parametric modeling of the fairing is carried out, and a fairing model is generated; cFD numerical simulation is carried out on the multiple sets of ships with the fairings, and the resistance coefficient and the drag reduction rate are calculated; an RBF-GA ship resistance reduction optimization model is constructed, the fairing initial design parameters and the CFD calculation resistance coefficient are input into the RBF-GA ship resistance reduction optimization model, and optimized fairing design parameters are obtained; according to the optimized fairing design parameters, generating a new fairing model, and performing CFD numerical simulation to calculate a ship resistance coefficient; and the steps are repeated until the drag reduction target is achieved, and the optimized design ship fairing appearance is obtained. According to the method, the shape optimization design of the ship fairing can be efficiently carried out, wind resistance is effectively reduced, ship energy consumption is reduced, and the requirements of ship transportation for energy conservation and emission reduction are met.

A golf ball is disclosed herein that has at least one modified aerodynamic characteristic or performance trait. More specifically, the golf ball disclosed herein can include a dimple pattern having a specific drag coefficient and / or specific integrated drag area.