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Intelligent Stowage Of Bulk Carrier

Posted on:2018-06-29Degree:DoctorType:Dissertation
Country:ChinaCandidate:C L LiuFull Text:PDF
GTID:1312330518454634Subject:Traffic Information Engineering & Control
Abstract/Summary:PDF Full Text Request
The purpose of this paper is to study the core algorithm,the intelligent stowage al-gorithm and the loading process optimization based on 3D model of bulk carrier's shell and all compartments.Developing a new generation of bulk carrier intelligent loading computer on this basis.Based on this goal,the following works were carried out:Based on the digital 3D model of the ship's shell and all compartments provided by ship design department,the ship's 3D section model database was established.The core algorithm of the loading computer was completed based on the 3D database.Firstly,the ship's 3D section model database was established based on the Sutherland-Hodgeman polygon clipping algorithm,polygon equidistant offset algorithm and Douglas-Peucker polygon simplification algorithm.Then,the ship's floating condition,longitudinal strength and damaged flooding analysis were calculated on the basis of this database.In the calculation of the ship's floating condition,a " simplified matrix method" was pro-posed,which is easy achieved and high reliability.When calculating the longitudinal strength,the buoyancy distribution curve was calculated based on the ship's 3D section model and the weight distribution curve was calculated based on the holds' "weight dis-tribution table".When doing ship's damaged state analysis,the "added weight method"was used to the damaged floating condition,and the "loss buoyancy method" was used to calculate the damaged strength base on the 3D section model of the shell and all compart-ments.Realization of intelligent stowage of bulk carrier was based on standard differential evolution algorithm.Considering ship's safety and economy,and taking the ship's float-ing condition control as the constraint,the multi-objective constraint optimization math-ematical model of bulk carrier was established.The model is versatile and can meet dif-ferent practical requirements by setting different parameters,such as optimal stowage under optimal trim,draft adjustment in any trim and loading condition optimization.When solving the model,the double-layer optimization method was used by changing multi-objective constraint optimization problem to double-layer single-objective optimization problem.The intelligent stowage of the bulk carrier uses computer's full computing abil-ity,which makes up the shortage of the traditional artificial stowage.The given stowage scheme improves the ship's longitudinal strength effectively.Based on the standard differential evolution algorithm and the discrete differential evolution algorithm,the loading process optimization of the bulk carrier was realized.The fundamental problem of the bulk cargo loading process was to determine the optimal sub-loading schedule.In this paper,"single head operation,two round loading" loading method was taken as an example,a hybrid differential evolution algorithm based on standard differential evolution algorithm and discrete differential evolution algorithm was used to perform real number and integer cod:ing for round loading weight and round load-ing order respectively.By establishing bulk cargo loading optimization mathematical model,and using two-tier optimization method,the program will automatically give the best loading scheme.The method can improve the loading efficiency effectively and en-sure the loading safety.Finally,a bulk carrier intelligent loading system was developed based on the pro-posed algorithm.The system is of great significance to ensure the safety of ships,improv-ing the efficiency of loading and realizing the energy efficiency.Although this paper is based on bulk carrier,the key technology is also applicable to other types of ships.Setting a foundation for loading computer of oil tankers,container ships,multi-purpose ships and other types of ship.
Keywords/Search Tags:Bulk carrier, Loading computer, Automatic stowage, Optimization of loading process, Differential evolution
PDF Full Text Request
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