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"Configuration design"
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Synergistic‐engineered van der Waals photodiodes with high efficiency
Van der Waals (vdW) heterostructures based on two‐dimensional transition‐metal dichalcogenides have provided unprecedented opportunities for photovoltaic detectors owing to their strong light‐matter interaction and ultrafast interfacial charge transfer. Despite continued advancement, insufficient control of photocarrier behaviors still limits the external quantum efficiency (EQE) and operation speed of such detectors. Here, we propose a synergistic strategy of contact‐configuration design and thickness‐modulation to construct high‐performance vdW photodiodes based on the typical type II heterostructure (MoS2/WSe2). Through integrating three contact architectures into one device to exclude other factors, we solid the superiority of designed 1L‐MoS2/WSe2/graphene heterostructures incorporating efficient photocarrier collection and gate modulation. Together with leveraging the layer‐number‐dependent properties of WSe2, we observe the critical thickness of WSe2 (11 layers) for the highest EQE, which verifies the thickness‐dependent competition between photocarrier generation, dissociation, and collection. Finally, we demonstrate the synergistic‐engineered vdW heterostructure can trigger record‐high EQE (61%) and manifest ultrafast photoresponse (4.1 μs) at the atomically thin limit (8 nm). The proposed strategy enables architecture‐design and thickness‐engineering to unlock the potential to realize high‐performance optoelectronic devices. Van der Waals heterostructures have great potential in next‐generation optoelectronic devices. Here we present a synergistic‐strategy of configuration‐design and thickness‐modulation to fabricate high‐performance photodiodes based on monolayer MoS2/multilayer WSe2/graphene. The synergistic‐engineered photodetector exhibits high external quantum efficiency (61%) and ultrafast photoresponse (4.1 μs) in self‐powered mode, which advances the prospects of photovoltaic applications.
Journal Article
Design and test of robotic harvesting system for cherry tomato
Harvesting of fresh-eating cherry tomato was highly costly on labor and time. In order to achieve mechanical harvesting for the fresh-eating tomato, a new harvesting robot was designed, which consisted of a stereo visual unit, an end-effector, manipulator, a fruit collector, and a railed vehicle. The robot configuration and workflow design focused on the special cultivating condition. Three key parts were introduced in detail: a railroad vehicle capably moving on both ground and rail was adopted as the robot's carrier, a visual servo unit was used to identify and locate the mature fruits bunch, and the end-effector to hold and separate the fruit bunch was designed based on the stalk's mechanical features. The field test of the new developed robot was conducted and the results were analyzed. The successful harvest rate of the robot was 83%, however, each successful harvest averagely needed 1.4 times attempt, and a single successful harvesting cycle cost 8 s excluding the time cost on moving.
Journal Article
MANAGING FUNCTIONAL TRADE-OFFS IN THE MECHANICAL DESIGN OF INTEGRATED PRODUCTS USING MULTIOBJECTIVE MONOTONICITY ANALYSIS
With the continuously increasing integration of (mechanical) products, the identification and management of trade-offs becomes a major task in product synthesis, with substantial effect on optimality and robustness of the final solution. At the same time, a rigorous and comprehensive study of trade-offs through mathematical design optimisation is often impractical in design, as efforts spent on modeling and optimizing are likely wasted if a chosen design is changed. Extending research on configuration redesign based on a multiobjective monotonicty analysis (MOMA), this paper presents three levels of evaluation for early design or redesign: (I) informal evaluation, (II) opportunistic evaluation, and (III) exhaustive evaluation. The chosen level depends on what knowledge the designer wants to gain, and the higher the level, the larger the analysis effort, the lesser the re-use of the information gained from the initial MOMA analysis respectively. The approach is illustrated using a novel drug delivery device, the Self-Orienting Millimeter-Scale Applicator (SOMA), for the oral delivery of protein compounds such as insulin.
Journal Article
Advanced UAV Design Optimization Through Deep Learning-Based Surrogate Models
The conceptual design of unmanned aerial vehicles (UAVs) presents significant multidisciplinary challenges requiring the optimization of aerodynamic and structural performance, stealth, and propulsion efficiency. This work addresses these challenges by integrating deep neural networks with a multiobjective genetic algorithm to optimize UAV configurations. The proposed framework enables a comprehensive evaluation of design alternatives by estimating key performance metrics required for different operational requirements. The design process resulted in a significant improvement in computational time over traditional methods by more than three orders of magnitude. The findings illustrate the framework’s capability to optimize UAV designs for a variety of mission scenarios, including specialized tasks such as intelligence, surveillance, and reconnaissance (ISR), combat air patrol (CAP), and Suppression of Enemy Air Defenses (SEAD). This flexibility and adaptability was demonstrated through a case study, showcasing the method’s effectiveness in tailoring UAV configurations to meet specific operational requirements while balancing trade-offs between aerodynamic efficiency, stealth, and structural weight. Additionally, these results underscore the transformative impact of integrating AI into the early stages of the design process, facilitating rapid prototyping and innovation in aerospace engineering. Consequently, the current work demonstrates the potential of AI-driven optimization to revolutionize UAV design by providing a robust and effective tool for solving complex engineering problems.
Journal Article
Mobile welding robots under special working conditions: a review
The mobile welding robot (MWR) embodies remarkable versatility, distinguished by its agile manoeuvrability and robust environmental adaptability. It excels in executing automated welding tasks under special conditions, including intricate spatial surfaces, unconventional cross-sections, confined spaces, and even underwater and nuclear environments. However, the current research landscape of MWRs, both domestically and internationally, is characterized by disorganization, irregularity, and a lack of systematicity, resulting in a failure to provide comprehensive and insightful references for studying MWRs across diverse scenarios. This paper conducts a thorough review of the existing research on MWRs within diverse specialized industrial operating contexts, both locally and globally. This underscores the urgent need to establish a modular standard for MWRs and develop a robust configuration design system, which can serve as a valuable reference. On the basis of this foundation, this paper meticulously examines the critical technical challenges encountered in the application of MWRs. Ultimately, it offers an outline for the future development trajectories of MWR technology, aiming to serve as a valuable resource and guide researchers embarking on investigations into MWRs under exceptional operating conditions.
Journal Article
Configuration Design of a Cruise Ship Lifesaving System Based on a Genetic Algorithm
Zhang, T.; Cai, W., and Hu, M., 2023. Configuration design of a cruise ship lifesaving system based on a genetic algorithm. Journal of Coastal Research, 39(3), 569–581. Charlotte (North Carolina), ISSN 0749-0208. To improve the configuration design of cruise ship lifesaving systems, this study proposes a system configuration design method based on a genetic algorithm. The configuration design of the lifesaving system of a cruise ship is a combinatorial optimisation problem, with various performance constraints. This study analyses the rules of the configuration design through regression analysis and establishes a mathematical model on this basis. Subsequently, aiming at the discrete problem of the selection and configuration of lifesaving equipment on cruise ships, combined with the characteristics of genetic programming, the lifesaving system required by cruise ships is analysed, classified, and described as a coding structure form of genetic programming. From the perspective of safety, a genetic programming solution strategy for equipment configuration is proposed. The results show that the system configuration design method of cruise ship lifesaving equipment proposed in this study is effective and practical, and a reasonable configuration design scheme can be obtained accurately and efficiently.
Journal Article
A bilevel optimisation model for the joint configuration of new and remanufactured products considering specification upgrading of used products
The joint optimisation of product design configuration (PDC) for new and remanufactured products involves specification upgrading for parts recovered from used product returns. Reversely, the specification upgrading decision for used parts/modules is also affected by the original specifications selected for parts/modules during the new product design process. Hence, the joint optimisation of PDC for both new and remanufactured products entails a hierarchical decision framework, of which scarcely any study involves the specification upgrading concerns. To fill this gap, this paper proposes a bilevel optimisation model that involves two-level decision-making. The upper level handles the configuration of new product variants to maximise the shared surplus of new product offerings. Meanwhile, the lower-level deals with the configuration and specification upgrading of remanufactured product variants to maximise the shared surplus of remanufactured product offerings. A non-linear integer bilevel programming is further presented to model the hierarchical optimisation problem, to solve which a nested bilevel genetic algorithm is also proposed. Furthermore, a case study involving configuration design for new and remanufactured mobile phone variants is conducted to validate the proposed model. Four scenarios are investigated to examine the effects of model parameters on the optimal solutions with the simulation result given at last.
Journal Article
Combinatorial Maps
This book gathers important ideas related to combinatorial maps and explains how the maps are applied in geometric modeling and image processing. It focuses on two subclasses of combinatorial maps: n-Gmaps and n-maps. The book presents the data structures, operations, and algorithms that are useful in handling subdivided geometric objects. It shows how to study data structures for the explicit representation of subdivided geometric objects and describes operations for handling the structures. The book also illustrates results of the design of data structures and operations.
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