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The purpose of this paper is to propose a new aerodynamic parameter estimation methodology based on neural network and output error method, while the output error method is improved based on particle swarm algorithm.

Firstly, the algorithm approximates the dynamic characteristics of aircraft based on feedforward neural network. Neural network is trained by extreme learning machine, and the trained network can predict the aircraft response at (k + 1)th instant given the measured flight data at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output error method to estimate aerodynamic derivatives.

Neither depending on the initial guess of the parameters to be estimated nor requiring numerical integration of the aircraft motion equation, the proposed algorithm can be used for unstable aircraft and is successfully applied to extract aerodynamic derivatives from both simulated and real flight data.

The proposed method requires iterative calculation and can only identify parameters offline.

The proposed method is successfully applied to estimate aircraft aerodynamic parameters and can also be used as a new algorithm for other optimization problems.

In this study, the output error method is improved to reduce the dependence on the initial value of parameters and expand its application scope. It is applied in aircraft aerodynamic parameter identification together with neural network.

This paper aims to describe a three-dimensional mathematical and numerical model based on finite volume method to simulate the fluid dynamics in weld pool, droplet transfer and keyhole behaviors in the laser-MIG hybrid welding process of Fe36Ni Invar alloy.

Double-ellipsoidal heat source model and adaptive Gauss rotary body heat source model were used to describe electric arc and laser beam heat source, respectively. Besides, recoil pressure, electromagnetic force, Marangoni force, buoyancy as well as liquid material flow through a porous medium and the heat, mass, momentum transfer because of droplets were taken into consideration in the computational model.

The results of computer simulation, including temperature field in welded plate and velocity field in the fusion zone were presented in this article on the basis of the solution of mass, momentum and energy conservation equations. The correctness of elaborated models was validated by experimental results and this proposed model exhibited close correspondence with the experimental results with respect to weld geometry.

It lays foundation for understanding the physical phenomena accompanying hybrid welding and optimizing the process parameters for laser-MIG hybrid welding of Invar alloy.

The conventional design method relies on a priori knowledge, which limits the rapid and efficient development of electronic packaging structures. The purpose of this study is to propose a hybrid method of data-driven inverse design, which couples adaptive surrogate model technology with optimization algorithm to to enable an efficient and accurate inverse design of electronic packaging structures.

The multisurrogate accumulative local error-based ensemble forward prediction model is proposed to predict the performance properties of the packaging structure. As the forward prediction model is adaptive, it can identify respond to sensitive regions of design space and sample more design points in those regions, getting the trade-off between accuracy and computation resources. In addition, the forward prediction model uses the average ensemble method to mitigate the accuracy degradation caused by poor individual surrogate performance. The Particle Swarm Optimization algorithm is then coupled with the forward prediction model for the inverse design of the electronic packaging structure.

Benchmark testing demonstrated the superior approximate performance of the proposed ensemble model. Two engineering cases have shown that using the proposed method for inverse design has significant computational savings while ensuring design accuracy. In addition, the proposed method is capable of outputting multiple structure parameters according to the expected performance and can design the packaging structure based on its extreme performance.

Because of its data-driven nature, the inverse design method proposed also has potential applications in other scientific fields related to optimization and inverse design.

Surface mount technology (SMT) is widely used and plays an important role in electronic equipment. The purpose of this paper is to reveal the effects of interface cracks on the fatigue life of SMT solder joint under service load and to provide some valuable reference information for improving service reliability of SMT packages.

A 3D geometric model of SMT package is established. The mechanical properties of SMT solder joint under thermal cycling load and random vibration load were solved by 3D finite element analysis. The fatigue life of SMT solder joint under different loads can be calculated by using the modified Coffin–Manson model and high-cycle fatigue model.

The results revealed that cracks at different locations and propagation directions have different effect on the fatigue life of the SMT solder joint. From the location of the cracks, Crack 1 has the most significant impact on the thermal fatigue life of the solder joint. Under the same thermal cycling conditions, its life has decreased by 46.98%, followed by Crack 2, Crack 4 and Crack 3. On the other hand, under the same random vibration load, Crack 4 has the most significant impact on the solder joint fatigue life, reducing its life by 81.39%, followed by Crack 1, Crack 3 and Crack 2. From the crack propagation direction, with the increase of crack depth, the thermal fatigue life of the SMT solder joint decreases sharply at first and then continues to decline almost linearly. The random vibration fatigue life of the solder joint decreases continuously with the increase of crack depth. From the crack depth of 0.01 mm to 0.05 mm, the random vibration fatigue life decreases by 86.75%. When the crack width increases, the thermal and random vibration fatigue life of the solder joint decreases almost linearly.

This paper investigates the effects of interface cracks on the fatigue life and provides useful information on the reliability of SMT packages.

This paper aims to propose a stable and precise recognition and pose estimation method to deal with the difficulties that industrial parts often present, such as incomplete point cloud data due to surface reflections, lack of color texture features and limited availability of effective three-dimensional geometric information. These challenges lead to less-than-ideal performance of existing object recognition and pose estimation methods based on two-dimensional images or three-dimensional point cloud features.

In this paper, an image-guided depth map completion method is proposed to improve the algorithm's adaptability to noise and incomplete point cloud scenes. Furthermore, this paper also proposes a pose estimation method based on contour feature matching.

Through experimental testing on real-world and virtual scene dataset, it has been verified that the image-guided depth map completion method exhibits higher accuracy in estimating depth values for depth map hole pixels. The pose estimation method proposed in this paper was applied to conduct pose estimation experiments on various parts. The average recognition accuracy in real-world scenes was 88.17%, whereas in virtual scenes, the average recognition accuracy reached 95%.

The proposed recognition and pose estimation method can stably and precisely deal with the difficulties that industrial parts present and improve the algorithm's adaptability to noise and incomplete point cloud scenes.

It is imperative to achieve sustainable growth in farmers' earnings to sustain poverty alleviation efforts and achieve rural revitalization goals. The authors investigated the nature of the non-linear relationship between farmers' e-commerce participation and income growth, analyzed the rationale behind this correlation and examined the moderating effect of digital finance on this relationship.

The authors conducted an empirical investigation using rural household data from the China Household Finance Survey and the regional digital finance index compiled by Peking University. The authors employed a fixed-effect model and a moderating effect model to identify the non-linear influences of e-commerce participation on farmers' income and to analyze the positive synergies of digital finance. The authors used identification and estimation techniques to mitigate the endogeneity problem, specifically employing heteroscedasticity-based instruments.

There is an inverted U-shaped relationship between e-commerce participation and farmers' income. Digital finance reduces the declining trend in the marginal effects of e-commerce and increases marginal values. Furthermore, the synergistic effect can promote the quality and efficiency of business activities by easing credit constraints, reducing risk aversion and stimulating innovative activities, which in turn can lead to sustained revenue growth.

Few studies have focused on the non-linear relationship between e-commerce and farmers' income. This implies that achieving sustained income growth using e-commerce alone is difficult. The synergy between e-commerce and digital finance is a feasible path for achieving this goal.

With the development of e-commerce and mobile payment, platform sales become unstoppable, and many manufacturers also encroach on online market by establishing direct selling channels. Channel conflict intensifies in online market and quality differentiation and is widely used in business practice as an effective way to alleviate such a competition. The authors study a retail platform's sales strategy and interactions with an upstream manufacturer's encroachment strategy in this paper. Unlike most online marketplace and encroachment research, product quality selection is also engaged in the present research to capture the motivation above.

The authors analyze a game-theoretical model that the platform as the first/second mover participates in strategic decision-making, and then jointly decides the product quality level with manufacturer.

The authors find that encroachment always profits the manufacturer and almost hurts the platform. Interestingly, the first-mover advantage can help the platform guide the manufacturer encroachment and promote a “win–win” situation when product quality level is relatively slight or obvious. Nevertheless, the second-mover advantage can help the platform alleviate the profit loss caused by encroachment when product quality level is moderate. Furthermore, suffered from encroachment loss, the platform can make a credible threat by sales termination to restrain manufacturer encroachment.

This paper innovatively explores the strategic interaction between manufacturer encroachment and quality differentiation in a platform supply chain, and further analyzes the first-mover advantage in this interaction, which fills the gaps of previous platform research and has great significances to enterprise production and operational decision in business practice.

This work aims to evaluate the influence of rheological properties of building materials on the bonding quality and ultimate tensile strength in the fused deposition modeling (FDM) process, through the investigation of parts printed by semi-crystalline and amorphous resins. Little information is currently available about the influence of the crystalline nature on FDM-printed part quality.

Semi-crystalline polyamide 12 and amorphous acrylonitrile butadiene styrene (ABS) were used to assess the influence of rheological properties on bonding quality and the tensile strength, by varying three important process parameters: materials, liquefier temperature and raster orientation. A fractography of both tensile and freeze-fractured samples was also investigated.

The rheological properties, mainly the melt viscosity, were found to have a significant influence on the bonding quality of fused filaments. Better bonding quality and higher tensile strength of FDM parts printed with semi-crystalline PA12, as compared with amorphous ABS, are suggested to be a result of higher initial sintering rates owing to the lower melt viscosity of PA12 at low shear rates. Near-full dense PA12 parts were obtained by FDM.

This project provides a variety of data and insight regarding the effect of materials properties on the mechanical performance of FDM-printed parts. The results showed that FDM technique allows the production of PA12 parts with adequate mechanical performance, overcoming the greatest limitation of a dependence on amorphous thermoplastics as a feedstock for the production of prototypes.