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Ship’s Digital Twin—A Review of Modelling Challenges and Applications. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12126039] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
The Ship’s Digital Twin (SDT) is a digital record of a ship’s behaviour or a software clone, which can be used to simulate scenarios that are expensive or hardly feasible to perform on a real object and especially in real time. The purpose of the SDT is to achieve cost reduction, obtain timely warnings of irregularities, and optimise individual ship system performances or the operation of the whole ship and to assist ship management. The aim of this paper is to describe the concept of the SDT and clarify some perplexities that may occur from initial introduction to concept. To that end, the paper identifies the steps in the SDT formulation process and methods used in each step of the process. Furthermore, a four-step iterative procedure for the SDT development is proposed. The applications of the concept are numerous, and some of them are presented in a review analysis in this paper. The presented analysis leads to a conclusion that should give some direction to future research in this area.
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A Two-Stage Decision-Making Method Based on WebGIS for Bulk Material Transportation of Hydropower Construction. ENERGIES 2022. [DOI: 10.3390/en15051726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Bulk materials are necessary for hydropower construction. The bulk materials transportation (BMT) scheme is a guiding document for material supply, and its selection has a significant influence on hydropower construction. Since the BMT problem includes transportation planning and scheme selection issues simultaneously, only a small number of studies have focused on it. This paper presents a theoretical two-stage decision-making method (TDM), which innovatively combines the path optimization method and the multi-criteria decision-making (MCDM) method to solve the BMT problem. In the first stage, a multi-source path optimization model is established to optimize the transportation network and obtain a set of alternatives from each supply point to the construction site. In the second stage, considering the factors of economy, risk and construction progress, the MCDM method is adopted to select the optimal scheme from the alternatives. In addition, web crawler technology is used to obtain the transportation network data from the public WebGIS automatically. Case results show that the TDM can effectively solve this problem, and its result keeps consistent with engineering practice; with the help of the web crawler, it can reduce the design task time from months to days. Therefore, the TDM based on WebGIS can benefit hydropower construction design efficiency.
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Time Optimization of Unmanned Aerial Vehicles Using an Augmented Path. FUTURE INTERNET 2021. [DOI: 10.3390/fi13120308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
With the pandemic gripping the entire humanity and with uncertainty hovering like a black cloud over all our future sustainability and growth, it became almost apparent that though the development and advancement are at their peak, we are still not ready for the worst. New and better solutions need to be applied so that we will be capable of fighting these conditions. One such prospect is delivery, where everything has to be changed, and each parcel, which was passed people to people, department to department, has to be made contactless throughout with as little error as possible. Thus, the prospect of drone delivery and its importance came around with optimization of the existing system for making it useful in the prospects of delivery of important items like medicines, vaccines, etc. These modular AI-guided drones are faster, efficient, less expensive, and less power-consuming than the actual delivery.
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