AddedResistance (Windows/MAC OS), a computer program for the estimation of wave added resistance at preliminary ship design

These files contain the "AddedResistance" computer program binaries, which were developed utilising the algorithm presented in the article entitled 'The prediction of ship added resistance at the preliminary design stage by the use of an artificial neural network'. In order to create a reliable model, only experimental data determined through model tests measurements was used to train this neural network. The following model tests results of these vessels were used in the development of this software:
• Van der stel (Gerritsma and Beukelman , 1972; Journee 1976),
• S175 containership (Nakamura, 1976),
• Series 60 CB=0.6, CB=0.65, CB=0.7, CB=0.75, CB=0.8, Strøm-Tejsen (1973),
• WILS II containership (Söding et al., 2014), DTC containership (Sprenger et al. , 2015),
• Cruise ship (Ley et al., 2014), Bulk carrier (Kadomatsu, 1988),
• RoPax (Sprenger et al., 2015),
• KVLCC2 tanker (Guo & Steen, 2010; Sadat-Hosseini et al., 2013),
• KRISO containership (Simones et al. 2014).
AddedResistance program could have practical application at the preliminary design stage. But this computer program might have two limitations. Firstly, the program may be inaccurate in the design of an innovative ship. This results from the data used to train the network which was measured on standard ship hulls. Secondly, the neural network was developed using the model test data with limited parameter ranges. Therefore, AddedResistance might only be used to estimate added wave resistance for ships with the following design characteristic ranges:
• length between perpendiculars LBP from 90 m to 335 m,
• breadth B from 16.25 m to 58 m,
• draught d from 4.2 to 20.8 m,
• block coefficient CB from 0.503 to 0.829,
• Froude number Fn from 0.087 to 0.3,
• LBP/B ratio from 5 to 7.5,
• B/d ratio from 2.5 to 4.5.
The application of this computer software to calculate ship resistance with design characteristics outside these ranges might be associated with the risk of low accuracy estimations.
The total mean added resistance of sailing ship in irregular waves is calculated by the use of the wave energy spectrum. A common ITTC spectrum based on Bretschneider wave energy spectrum was used here to calculate the mean added resistance in irregular wave.
Lazarus IDE software (Lazarus 2.0.0, 2019) with a Free Pascal compiler was used to develop the AddedResistnace program.

本数据集包含"AddedResistance"计算机程序二进制文件，该程序基于发表于题为《利用人工神经网络（Artificial Neural Network）预测初步设计阶段船舶附加阻力》的文章中的算法开发。为构建可靠的预测模型，本程序仅采用模型试验（Model Test）实测数据对该人工神经网络进行训练。本软件开发过程中使用了下述船型的模型试验结果：
• 范德斯特尔船型（Gerritsma与Beukelman，1972；Journee，1976）
• S175型集装箱船（Nakamura，1976）
• 60系列船型（方形系数CB=0.6、0.65、0.7、0.75、0.8，Strøm-Tejsen，1973）
• WILS II型集装箱船（Söding等，2014）、DTC型集装箱船（Sprenger等，2015）
• 邮轮（Ley等，2014）、散货船（Kadomatsu，1988）
• 滚装客船（RoPax，Sprenger等，2015）
• KVLCC2型油轮（Guo与Steen，2010；Sadat-Hosseini等，2013）
• 韩国船舶与海洋工程研究所（KRISO）集装箱船（Simones等，2014）

AddedResistance程序可在船舶初步设计阶段发挥实际应用价值，但该程序存在两处局限。其一，针对创新型船型的设计场景，该程序可能存在估算精度不足的问题，这是由于训练网络所用数据均来自标准船型的实测结果。其二，本神经网络仅基于有限参数范围的模型试验数据开发，因此AddedResistance程序仅可用于估算符合下述设计参数范围的船舶的附加波浪阻力：
• 垂线间长（Length Between Perpendiculars, LBP）：90 m至335 m
• 船宽（Breadth, B）：16.25 m至58 m
• 吃水（Draught, d）：4.2至20.8 m
• 方形系数（Block Coefficient, CB）：0.503至0.829
• 弗劳德数（Froude Number, Fn）：0.087至0.3
• LBP/B比值：5至7.5
• B/d比值：2.5至4.5

若将本计算机软件用于设计参数超出上述范围的船舶阻力计算，可能会出现估算精度偏低的风险。

不规则波中航行船舶的总平均附加阻力，通过波浪能谱进行计算。本文采用基于Bretschneider波浪能谱（Bretschneider Wave Energy Spectrum）的国际拖曳水池会议（International Towing Tank Conference, ITTC）通用谱，来计算不规则波中的平均附加阻力。

本AddedResistance程序采用Lazarus IDE（Lazarus 2.0.0，2019）软件开发环境搭配Free Pascal编译器（Free Pascal Compiler）开发完成。