Soft Computing 11 (2011), pp. 2356–2366. 4. Elvekrok D.R.: Concurrent Engineering in Ship Design . Journal of Ship Production, (1997) Vol. 13, No. 4, pp. 258–269. 5. Sea-web Ships (2018) [Online]. Available from: https://maritime.ihs.com [Accessed: 10. Feb. 2018] 6. Kristensen H.O.: Determination of Regression Formulas for Main Dimensions of Tankers and BulkCarriers based on IHS Fairplay data . Project no. 2010–56, Emissionsbeslutningsstøttesystem. Work Package 2, Report No. 02. (2012), Technical University of Denmark. 7. Lin C., Shaw H.: Feature
The paper presents mathematical relationships that allow us to forecast the newbuilding price of new bulk carriers, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the price based on a gross tonnage capacity and a main engine power The approximations were developed using linear regression and the theory of artificial neural networks. The presented relations have practical application for estimation of bulk carrier newbuilding price needed in preliminary parametric design of the ship. It follows from the above that the use of artificial neural networks to predict the price of a bulk carrier brings more accurate solutions than linear regression.
The paper presents the methodology for determining the components which are related to heel of bulk carrier with one component excluded — the heel of vessel due to waves. The described method was applied to the system, which is dedicated to use in determination of UKC of vessels at the approach to the Port of Swinoujscie. The method includes determination of heel caused by: draught reading errors, wind, current, tugboats and heel related to vessel maneuvers. To determine heel related to vessel maneuver 2-stage method was carried out. The first stage simulation was used to identify the parameters of ship movement. At the second stage, the maximum heel of Bulk Carrier were calculated by using analytical methods. Presented method was implemented to the item rating under keel clearance at the approach to the Port of Swinoujscie
The article presents the mathematical function to calculate the added wave resistance transfer function for bulk carriers. Based on this function, the statistical mean added wave resistance generated by an irregular head wave with arbitrary statistical parameters can be forecasted. The input parameters are: waterplane area, waterplane coefficient, ship speed, and frequency of the regular wave. The model has been developed based on the theory of artificial neural networks. The presented function can be used in design analyses, and for planning shipping routes in situations when basic geometrical parameters of the hull are only available and not the full technical documentation. The article presents sample cases of use of this function to calculate the added wave resistance transfer function and the statistical mean added wave resistance. Another presented application refers to waterplane coefficient optimisation taking into account the added wave resistance at the stage of preliminary bulk carrier design.
Extremely high price of oil and consequently fuel used by sea going bulk carriers combined with very low freight rates - BDI (Baltic Dry Index), the main index of the freight market dropped from almost 12,000 to about 700 during the last four years - forced ship owners and operators to re-calculate speed and consumption parameters of their fleet. On the basis of speed/consumption parameters taken directly from ships, the average cost of marine fuel IFO and the freight market reported by The Baltic Exchange the author calculated the profitability of the reduction of speed for typical bulk carriers from about 26,000 to 80,000 DWT. Despite the extremely low freight market and very high price of fuel the savings due to the reduction of fuel consumption are generally consumed by time loss. The speed reduction may be profitable only for the group of the largest of the analyzed ships but every time ship operators have to take into consideration such consequences as the weather risk, positioning for the next employment, charter party obligations etc.
Application of artificial neural networks to approximation and identification of sea-keeping performance of a bulk carrier in ballast loading condition
This paper presents an application of artificial neural networks to approximation and identification of additional wave-generated resistance, slamming and internal forces depending on ship motion and wave parameters. The analysis was performed for a typical bulk carrier in ballast loading conditions. The investigations were carried out on the basis of ship response data calculated by means of exact numerical methods. Analytical functions presented in the form of artificial neural networks were analyzed with a view of their accuracy against standard values. Possible ways of application of the artificial neural networks were examined from the point of view of accuracy of approximation and identification of the assumed ship response parameters.
BulkCarrier, Trans. SNAME , Vol. 98, 1990 Bjarrne E.: Systematic Studies of contra-rotating Propellers for Merchant Ship , Proc. IMAS'73, 1973, pp.49-59 Ghassemi H., Allievi A.: "A Computational Method for the Analysis of Fluid Flow and Hydrodynamic Performance of Conventional and Podded Propulsion Systems", Journal of Oceanic Engineering International , Vol. 3, No. 2, 1999 Koronowicz T., Tuszkowska T., Waberska G.: Computer software system for determining the pressure field resulting from hull flow and operation of the marine propeller. Polish Maritime Research
.H., et al., Flexible CFD meshing strategy for prediction of ship resistance and propulsion performance. International Journal of Naval Architecture and Ocean Engineering, 2010. 2(3): p. 139–145. 8. Gokce, M.K., O.K. Kinaci, and A.D. Alkan, Self-propulsion estimations for a bulkcarrier. Ships and Offshore Structures, 2018: p. 1–8. 9. Tran Ngoc Tu, N.M.C., Comparison Of Different Approaches For Calculation Of Propeller Open Water Characteristic Using RANSE Method . Naval Engineers Journal, 2018. Volume 130, Number 1, 1 March 2018, pp. 105–111(7). 10. http
Antimony is a promising material for the fabrication of photodetectors. This study deals with the growth of a photosensitive thin film by the physical vapor deposition (PVD) of antimony onto mica surface in a furnace tube. The geometry of the grown structures was studied via scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX) and elemental diffraction analysis. XRD peaks of the antimony film grown on mica mostly matched with JCPDF Card. The formation of rhombohedral crystal structures in the film was further confirmed by SEM micrographs and chemical composition analysis. The Hall measurements revealed good electrical conductivity of the film with bulk carrier concentration of the order of 1022 Ω·cm-3 and mobility of 9.034 cm2/Vs. The grown film was successfully tested for radiation detection. The photoresponse of the film was evaluated using its current-voltage characteristics. These investigations revealed that the photosensitivity of the antimony film was 20 times higher than that of crystalline germanium.