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  • MDPI AG  (6)
  • 1
    Online Resource
    Online Resource
    A Lumped Mass Model for Circular Micro-Resonators in Coriolis Vibratory Gyroscopes
    MDPI AG ; 2019
    In:  Micromachines Vol. 10, No. 6 ( 2019-06-06), p. 378-
    Details
    In: Micromachines, MDPI AG, Vol. 10, No. 6 ( 2019-06-06), p. 378-
    Abstract: Coriolis vibratory gyroscopes (CVGs) with circular micro-resonators, such as hemispherical, ring, and disk resonators, exhibit excellent performances and have extraordinary potential. This paper discusses a generalized lumped mass model for both 3D and planar circular micro-resonators, establishing the relationship between the modal effective mass, the modal equivalent force, and the point displacement of the resonator. The point displacement description of a continuous circular resonator’s motion is defined from the view of capacitance measurement. The modal effective mass is, consequently, determined by the kinetic and the potential energy of the structure and is computed with numerical simulations. Moreover, the modal equivalent force, which can be theoretically calculated for any configuration of discrete electrodes, is deduced by using the concept of force density and the force distribution function. By utilizing the lumped mass model in this paper, the stiffness softening, the mode tuning, and the quadrature correction of the micro-resonators are investigated in detail. The theoretical model is verified by both the finite element method (FEM) and the experiments.
    Type of Medium: Online Resource
    ISSN: 2072-666X
    URL: Article
    DOI: 10.3390/mi10060378
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2620864-7
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    Online Resource
  • 2
    Online Resource
    Online Resource
    A Privacy-Preserving Consensus Mechanism for ADMM-Based Peer-to-Peer Energy Trading
    MDPI AG ; 2023
    In:  Symmetry Vol. 15, No. 8 ( 2023-08-10), p. 1561-
    Details
    In: Symmetry, MDPI AG, Vol. 15, No. 8 ( 2023-08-10), p. 1561-
    Abstract: In the electricity market, prosumers are becoming more and more prevalent due to the fast development of distributed energy resources and demand response management, which also promote the appearance of peer-to-peer (P2P) trading mechanisms for energy. Optimization-based methods are efficient tools to design the P2P energy trading negotiation mechanism. However, the main drawback for market mechanisms based on optimization methods is that the incentive compatibility cannot be satisfied, which means participants can obtain more profit by providing untruthful biddings. To overcome this challenge, a novel consensus mechanism based on Proof of Solution (PoSo) is proposed for P2P energy trading. The optimization results will be verified by neighboring agents according to the KKT conditions in a fully decentralized and symmetric manner, which means agents will check each other’s solutions. However, the verification process may leak the private information of agents, and a privacy-preserving consensus mechanism is designed using Shamir’s secret sharing method. After that, we explore a method to realize that trusted agents can recover the right information even under the misbehavior of malicious agents by inheriting the philosophy of Practical Byzantine Fault Tolerance (PBFT). The numerical results demonstrate the effectiveness and efficiency of our proposed consensus mechanisms. In more detail, (1) when the message delivery success rate is not lower than 0.7, the consensus mechanisms almost guarantee success; (2) if the proportion of untrusted agents satisfies 4f+1≤Nωn, the proposed method guarantees the correctness of the consensus verification results; (3) the communication times among agents can be highly reduced by more than 60% by only verifying the optimality of the received results for the first three and last few iterations.
    Type of Medium: Online Resource
    ISSN: 2073-8994
    URL: Article
    DOI: 10.3390/sym15081561
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2518382-5
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  • 3
    Online Resource
    Online Resource
    Anthrax Susceptibility: Human Genetic Polymorphisms Modulating ANTXR2 Expression
    MDPI AG ; 2015
    In:  Toxins Vol. 8, No. 1 ( 2015-12-22), p. 1-
    Details
    In: Toxins, MDPI AG, Vol. 8, No. 1 ( 2015-12-22), p. 1-
    Type of Medium: Online Resource
    ISSN: 2072-6651
    URL: Article
    DOI: 10.3390/toxins8010001
    Language: English
    Publisher: MDPI AG
    Publication Date: 2015
    detail.hit.zdb_id: 2518395-3
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  • 4
    Online Resource
    Online Resource
    A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
    MDPI AG ; 2022
    In:  Sensors Vol. 22, No. 22 ( 2022-11-21), p. 9020-
    Details
    In: Sensors, MDPI AG, Vol. 22, No. 22 ( 2022-11-21), p. 9020-
    Abstract: Consumers in electricity markets are becoming more proactive because of the rapid development of demand–response management and distributed energy resources, which boost the transformation of peer-to-peer (P2P) energy-trading mechanisms. However, in the P2P negotiation process, it is a challenging task to prevent private information from being attacked by malicious agents. In this paper, we propose a privacy-preserving, two-party, secure computation mechanism for consensus-based P2P energy trading. First, a novel P2P negotiation mechanism for energy trading is proposed based on the consensus + innovation (C + I) method and the power transfer distribution factor (PTDF), and this mechanism can simultaneously maximize social welfare and maintain physical network constraints. In addition, the C + I method only requires a minimum set of information to be exchanged. Then, we analyze the strategy of malicious neighboring agents colluding to attack in order to steal private information. To defend against this attack, we propose a two-party, secure computation mechanism in order to realize safe negotiation between each pair of prosumers based on Paillier homomorphic encryption (HE), a smart contract (SC), and zero-knowledge proof (ZKP). The energy price is updated in a safe way without leaking any private information. Finally, we simulate the functionality of the privacy-preserving mechanism in terms of convergence performance, computational efficiency, scalability, and SC operations.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s22229020
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2052857-7
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  • 5
    Online Resource
    Online Resource
    Bionic Design of a Winding Roller and Experiments for Cleaning Long Foreign Matter from Raw Cotton
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 19 ( 2022-10-05), p. 10003-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 19 ( 2022-10-05), p. 10003-
    Abstract: Natural cotton fibers are inevitably mixed with long foreign matter (LFM) from the planting and ginning processes, which greatly deteriorate the quality of textile products. Therefore, how to design automated equipment that can efficiently remove LFM is very important for the cotton industry supply chain. Inspired by the comb-like gill rake structure of the carp (cyprinus carpio), a structural bionic method is first proposed for the development of automatic equipment. A series of key parameters of the proposed bionic design are presented and further optimized based on the orthogonal experimental design algorithm and the designed experimental automatic equipment through a sensitivity analysis between the factors (key parameters) and response (LFM removal efficiency). The design results show that the tooth length of the winding roller is the most significant factor effecting the response. Experimental results demonstrate that the designed modular comb-like winding device has great potential for application in the industrial cotton supply chain. Moreover, the structural bionic method is an applicable and promising method to develop this equipment compared with traditional design ideas.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app121910003
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 6
    Online Resource
    Online Resource
    Improving the Wear and Corrosion Resistance of Aeronautical Component Material by Laser Shock Processing: A Review
    MDPI AG ; 2023
    In:  Materials Vol. 16, No. 11 ( 2023-06-01), p. 4124-
    Details
    In: Materials, MDPI AG, Vol. 16, No. 11 ( 2023-06-01), p. 4124-
    Abstract: Since the extreme service conditions, the serious failure problems caused by wear and corrosion are often encountered in the service process for aeronautical components. Laser shock processing (LSP) is a novel surface-strengthening technology to modify microstructures and induce beneficial compressive residual stress on the near-surface layer of metallic materials, thereby enhancing mechanical performances. In this work, the fundamental mechanism of LSP was summarized in detail. Several typical cases of applying LSP treatment to improve aeronautical components’ wear and corrosion resistance were introduced. Since the stress effect generated by laser-induced plasma shock waves will lead to the gradient distribution of compressive residual stress, microhardness, and microstruture evolution. Due to the enhancement of microhardness and the introduction of beneficial compressive residual stress by LSP treatment, the wear resistance of aeronautical component materials is evidently improved. In addition, LSP can lead to grain refinement and crystal defect formation, which can increase the hot corrosion resistance of aeronautical component materials. This work will provide significant reference value and guiding significance for researchers to further explore the fundamental mechanism of LSP and the aspects of the aeronautical components’ wear and corrosion resistance extension.
    Type of Medium: Online Resource
    ISSN: 1996-1944
    URL: Article
    DOI: 10.3390/ma16114124
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2487261-1
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