Simultaneous dual pyrolysis synthesis of heterostructured FeCo/C porous hollow microspheres for high efficient microwave absorption

Due to their multiple dissipation mechanisms, low density and easy tailored impedance matching, heterogeneous hollow structures are promising candidates for microwave absorbents towards wideband absorption and lightweight design. In this...

A Shadow Capture Deep Neural Network for Underwater Forward-Looking Sonar Image Detection

Image sonar is a widely used wireless communication technology for detecting underwater objects, but the detection process often leads to increased difficulty in object identification due to the lack of equipment resolution. In view of the remarkable results achieved by artificial intelligence techniques in the field of underwater wireless communication research, we propose an object detection method based on convolutional neural network (CNN) and shadow information capture to improve the object recognition and localization effect of underwater sonar images by making full use of the shadow information of the object. We design a Shadow Capture Module (SCM) that can capture the shadow information in the feature map and utilize them. SCM is compatible with CNN models that have a small increase in parameters and a certain degree of portability, and it can effectively alleviate the recognition difficulties caused by the lack of device resolution through referencing shadow features. Through extensive experiments on the underwater sonar data set provided by Pengcheng Lab, the proposed method can effectively improve the feature representation of the CNN model and enhance the difference between class and class features. Under the main evaluation standard of PASCAL VOC 2012, the proposed method improved from an average accuracy (mAP) of 69.61% to 75.73% at an IOU threshold of 0.7, which exceeds many existing conventional deep learning models, while the lightweight design of our proposed module is more helpful for the implementation of artificial intelligence technology in the field of underwater wireless communication.

Experimental analysis on mechanical properties of BF/PLA composites and its lightweight design on power battery box

In response to the concept of energy conservation and environmental protection, a novel composite battery box with BF/PLA composite is proposed. Firstly, the mechanical properties of BF/PLA composite are tested, and it is concluded that the property parameters of BF/PLA composite with 50% BF mass fraction is selected as the material property parameter of subsequent finite element simulation. Subsequently, the statics analysis and constraint modal analysis of the traditional metal battery box are carried out under the typical working conditions of rapid turning and braking under vertical bumping. Based on this, the upper and lower box materials of the battery box except the bracket are replaced by BF/PLA composite. The morphology optimization, topology optimization and free size optimization are carried out with the constraint that the first-order modal vibration frequency is no less than 30 Hz. Compared with the traditional metal battery box, the stiffness and strength of the optimized BF/PLA composite battery box are significantly enhanced. Moreover, the first-order constraint modal frequency increases by 15.5%, and the comprehensive weight reduction ratio reaches 40.88%. Finally, the optimized BF/PLA composite battery box is verified under random vibration, mechanical shock analysis, collision analysis, extrusion and falling ball analysis and drop analysis conditions. Meanwhile, compared with the traditional metal battery box under the same working conditions, the excellent reliability of the composite battery box is highlighted. The proposed BF/PLA composite battery box satisfies the requirements of stiffness and strength performances under various working conditions, which provides theoretical and data support for the application of composite materials in battery box and other automotive components.

Multi-objective optimization of tensile properties of the corrugated composite sheet

Corrugated sheets with optimized mechanical properties are crucial for lightweight design in industrial applications. This study considered and optimized a corrugated sheet with a sinusoidal profile to enhance elastic modulus, tensile-bending coupling, and weight reduction. For this aim, first, flat specimens consisting of E-glass woven fiber and epoxy resin were made by hand lay-up method, following ASTM D3039. The tensile test determined young’s modulus of flat samples. Afterward, two molds with supports were fabricated. The corrugated specimens were constructed and exposed to a standard tensile test. The finite element analysis was used to simulate the tensile test of corrugated samples. The numerical force-displacement curve is derived from numerical analysis and verified by experimental results. After that, two multi-objective optimization problems, mass-constraint and global optimization, were implemented. Analytical formulations were verified by numerical and experimental results and utilized for optimization purposes. The genetic algorithm was used to examine and confirm trade-off behavior between objective functions. The Pareto fronts diagrams for mentioned two multi-objective optimization problem were obtained. Finally, the optimum parameters are calculated by using the LINMAP (Linear Programming Technique for Multi-dimensional Analysis of Preference) method.

Design and Implementation of Highly Integrated Electronic System for Small-Size Spacecraft

Due to the tight installation space, strict weight requirements, numerous functional units and dense wireless equipments of small-size spacecraft, the traditional electronic system design of aircraft cannot meet the requirements of miniaturization and lightweight for small-size spacecraft. In this paper, a highly integrated electronic system suitable for small-size spacecraft is designed, in which many key technologies such as miniaturization and lightweight design technology, multi frequency wireless electromagnetic compatibility design technology, small aircraft low delay cooperative networking and high-precision differential positioning are adopted. The proposed highly integrated electronic system makes timing control, attitude and orbit control, wireless telemetry, networking communication, satellite navigation, power distribution and other functions integrated. The total weight of the system is about 7.62kg, which is much lighter than existing electronic system. The experiment results that the highly integrated electronic system achieves good effect. This technology has broad application prospects in small-size aircraft with strict weight and space requirements.

Application of reinforcement learning for the optimization of clinch joint characteristics

Due to increasing challenges in the area of lightweight design, the demand for time- and cost-effective joining technologies is steadily rising. For this, cold-forming processes provide a fast and environmentally friendly alternative to common joining methods, such as welding. However, to ensure a sufficient applicability in combination with a high reliability of the joint connection, not only the selection of a best-fitting process, but also the suitable dimensioning of the individual joint is crucial. Therefore, few studies already investigated the systematic analysis of clinched joints usually focusing on the optimization of particular tool geometries against shear and tensile loading. This mainly involved the application of a meta-model assisted genetic algorithm to define a solution space including Pareto optima with all efficient allocations. However, if the investigation of new process configurations (e. g. changing materials) is necessary, the earlier generated meta-models often reach their limits which can lead to a significantly loss of estimation quality. Thus, it is mainly required to repeat the time-consuming and resource-intensive data sampling process in combination with the following identification of best-fitting meta-modeling algorithms. As a solution to this problem, the combination of Deep and Reinforcement Learning provides high potentials for the determination of optimal solutions without taking labeled input data into consideration. Therefore, the training of an Agent aims not only to predict quality-relevant joint characteristics, but also at learning a policy of how to obtain them. As a result, the parameters of the deep neural networks are adapted to represent the effects of varying tool configurations on the target variables. This provides the definition of a novel approach to analyze and optimize clinch joint characteristics for certain use-case scenarios.

Lightweight Design and Dynamics Analysis of ZYL-15000D Directional Drill Reducer

Since the output torque of the rotary reducer of the ZYL-15000D-kilometer directional drill is proportional to the gear train transmission ratio, the output torque is large enough when the input speed and output speed meet the design goal. This paper selects the method of reducing the transmission ratio to optimize the size parameters of the reducer. MATLAB genetic algorithm is used in the optimization design, and the minimum volume of the rotary part reducer is taken as the objective of optimization design, while the design variables and constraints are determined. The optimal value of design variables was obtained through optimization, and the parameter values of each gear were determined accordingly. Through analysis, the total volume of the optimized gear reducer was reduced by 49.6%. Then, the 3D model of the optimized gear was created, and the analysis of the transient dynamics of the optimized gear was carried out with ANSYS Workbench software. According to the analysis results, the optimized gear met the strength requirements and provided a reference for the subsequent optimization design of other types of gear reducers.

Design and development af a lightweight low-cost sensor unit for the parallel measurement of particles, gaseous air pollutants, atmospheric pressure, temperature and humidity

<p>There are frequent measurement tasks, where lightweight low-cost sensor units are of interest for the parallel measurement of several environmental parameters. Moreover, often measurements of environmental parameters are necessary not only at one specific point, but distributed over a large area or at different altidudes. In this case it makes sense to utilize lightweight low-cost sensor units. Because of the low price the can be produced in many exemplares und used at several places in parallel.</p> <p>The Laboratory for Environmental Measurement Techniques (UMT) at the Duesseldorf University of Applied Sciences (HSD) has developed such electronic units with following features:</p> <ul> <li>They can measure particulate matter PM10, PM2.5, PM1, PNC and size distribution using particulate sensors of different brands, e.g. Alphasense sensors R2 or N3 or Sensirion SDS 30.</li> <li>Additionally they have analog interfaces so that they can be equipped with sensor units for gaseous pollutants, e.g, Alphasense sensors for SO<sub>2</sub>, NO<sub>2</sub>, Ozone and many other gases like CO<sub>2</sub> using Sensirion sensors.</li> <li>In parallel atmospheric pressure, temperature and humidity can be measured by additional dedicated sensors.</li> <li>The sensor units are equipped with a SD card memory and optionally with I<sup>2</sup>C or RS232 interface.</li> <li>Additionally the data can be transmitted in a wireless way to a server on 433 MHz, 868 MHz, 2.4 GHz ISM-band or via LTE or IRIDIUM.</li> <li>The main electronic unit is of lightweight design. Therefore the low-cost sensor units can be used easily on mobile platformes like drones or bicycles.</li> <li>The sensor unit has a low power consumption, so it can be operated independently for days or weeks, depending on the battery capacity.</li> <li>A GPS module enables a timestamp for the data and gives position and altitude.</li> </ul> <p>Several fully installed measurement units have been tested by UMT groundbased at industrial and heavily polluted urban sites in Germany. Moreover, such a unit has been operated on a measurement drone for taking vertical and horizontal pollutant profiles. It is planned to use these sensor units also at volcanic sites in a mobile and stationary way. The low-cost sensor units have been intercompared with certified air pollution measurement systems to assure the data quality.</p>