As a new energy harvesting technology, triboelectric nanogenerators are widely used for vibration mechanical energy harvesting. However, the current schemes ignore the composite characteristics of vibration, with problems such as utilization and low collection efficiency. In this paper, a random resonance cantilever beam triboelectric nanogenerator (RCB-TENG) with dual-mode coupled is presented, the working mode is a coupling form of in-plane sliding and vertical contact-separation that can effectively collect complex vibration energy in transverse and longitudinal directions. The influences of the structural parameters of the RCB-TENG and different dielectric materials on the output performance are systematically investigated. The single vibration module achieved a power density of 463.56 mW/m 2 and a transfer charge of 10.7 μC at a vibration frequency of 46 Hz, an increase in power density, and a transfer charge of 4.94 and 3.82 times, respectively, compared to the conventional contact-separation mode. Finally, the RCB-TENG was tested in practice, and it was observed that nine 1 W commercial LED bulbs and 500 5 mm diameter LED lamps were successfully lit. This work offers new ideas for distributed energy harvesting technologies and holds broad promise in the field of energy harvesting from wind, water, wave, and random vibrations caused by mechanical energy.
In modern manufacturing industry, the impact of tolerance cost is increasing fast, and reasonable tolerance design plays an important role. Product manufacturing cost was taken as the research object in this paper, the appropriate cost tolerance model was selected, and the tolerance optimization model was established by combining genetic algorithm. Taking antenna window installation as an example, the closed loop dimension chain analysis was carried out first. Then the power exponential tolerance model was used to obtain the cost parameters through the empirical method. Finally, the tolerance optimization problem was transformed into a multi-objective optimization mathematical model. The tolerance values were obtained by genetic algorithm and compared with the equal tolerance method. The results were shown that the manufacturing cost can be effectively reduced by the minimum cost method.
A civil aircraft scaled demonstrator is an unmanned aerial vehicle (UAV) obtained by reducing the geometry of a civil aircraft by an equal scale and simplifying the airframe and airborne subsystems. Due to the low development cost and flight risk of scaled demonstrators, flight tests with demonstrators are an attractive way to assess the reliability and effectiveness of new configurations and/or technologies available for civil aircraft. Nevertheless, engineers still hope to reduce the development cycles and costs of demonstrators to evaluate their multiple civil aircraft design solutions through flight tests in a short period of time. Model-based systems engineering (MBSE) is a formalized requirement and architecture modeling method which is a useful tool in aircraft design. However, no existing MBSE framework has been found suitable for the development of demonstrators due to their unique features. In this paper, an MBSE approach for civil aircraft scaled demonstrator is proposed based on the MagicGrid methodology and the existing technical process for the demonstrator. This approach formalizes the requirement analysis and architecting for demonstrators via system modeling language (SysML). Meanwhile, the stakeholders of civil aircraft scaled demonstrators are identified, and a requirement ontology and modeling standard are established according to existing demonstrator development practice. Then, a case study is performed through a hybrid power demonstrator which carries a hydrogen fuel cell as the main power supply, a set of solar cells, and two lithium cells. The requirement traceability and verifiability are examined, and a logic simulation is executed for architecture, which shows the feasibility of applying the MBSE approach for the development of civil aircraft scaled demonstrators.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.