Design-Space Dimensionality Reduction Benchmark Dataset - Ship Propeller

This dataset provides a benchmark database for the evaluation and comparison of design-space dimensionality reduction methods in hydrodynamic shape optimization problems. The dataset consists of 16,385 configurations of a six-blade, right-handed marine propeller for a cruise ship, generated through Sobol sampling of a B-Spline-based parametric model describing radial and chordwise blade features. Each configuration is described by 74 propeller parametrization parameters. Among them, 38 parameters are active design variables, while the remaining parameters are fixed and retained to preserve the complete propeller parametrization structure. The skew distribution is kept unchanged with respect to the reference propeller. The propeller blade geometry is discretized using 1,326 grid nodes, stored as flattened coordinate vectors. Each configuration includes: discretized propeller blade geometry coordinates (1,326 × x, y, z points) propeller parametrization parameters defining the B-Spline model pressure coefficient distribution (Cp) at the nominal equivalent condition, evaluated at 1,250 panel centers pressure coefficient distribution (Cp) at the loaded equivalent condition, evaluated at 1,250 panel centers pressure coefficient distribution (Cp) at the unloaded equivalent condition, evaluated at 1,250 panel centers integrated hydrodynamic quantities at the nominal condition: thrust coefficient (KT) efficiency (eta) tip-vortex intensity (Gamma) Hydrodynamic quantities are computed using a low-fidelity Boundary Element Method (BEM) solver. Simulation conditions: nominal equivalent condition loaded equivalent condition, representative of the blade passing through the 90° position in the non-uniform wake unloaded equivalent condition, representative of the blade passing through the 270° position in the non-uniform wake The dataset matrix has size 7,805 × 16,385 and includes: geometry coordinates propeller parametrization parameters distributed pressure coefficients integrated hydrodynamic quantities Dataset statistics: total configurations: 16385 baseline configuration: 1 sampled configurations: 16384 valid simulations: 16306 invalid simulations: 79 Invalid simulations correspond to cases where the BEM simulation or the post-processing of hydrodynamic quantities did not provide valid physical outputs. NaN values are also used when non-physical negative values occur in scalar quantities, including efficiency, thrust coefficient, or tip-vortex intensity. Samples with invalid or partially invalid physical quantities may still be useful for geometry-based dimensionality reduction studies. This dataset is part of a benchmark collection aimed at providing standardized databases for evaluating dimensionality reduction techniques in engineering design spaces. The dataset follows a physics-informed representation of the design space, where geometric, parametric, and physical information are combined consistently within a unified framework. The parametrization and solver used are described in: Serani, A., Palma, G., Wackers, J., Quagliarella, D., Gaggero, S., & Diez, M. (2025). Extending parametric model embedding with physical information for design-space dimensionality reduction in shape optimization. Engineering with Computers. Gaggero, S., & Serani, A. (2026). Physics-informed dimensionality reduction for propeller shape optimization. Applied Ocean Research, 166, 104932.本数据集为流体力学形状优化问题中的设计空间降维方法的评估与对比提供基准数据库。 本数据集包含16385个邮轮用右旋六叶船用螺旋桨构型，这些构型通过对描述桨叶径向与弦向特征的基于B样条（B-Spline）的参数化模型进行索博尔采样生成。 每个构型由74个螺旋桨参数化参数描述，其中38个为主动设计变量，其余参数保持固定以保留完整的螺旋桨参数化结构。桨叶的侧斜分布与参考螺旋桨保持一致。 螺旋桨桨叶几何通过1326个网格节点进行离散化，数据以扁平化坐标向量的形式存储。 每个构型包含以下内容： - 离散化螺旋桨桨叶几何坐标（1326组x、y、z坐标点） - 定义B样条模型的螺旋桨参数化参数 - 额定当量工况下的压力系数（Cp）分布，于1250个面板中心处计算得到 - 加载当量工况下的压力系数（Cp）分布，于1250个面板中心处计算得到 - 非加载当量工况下的压力系数（Cp）分布，于1250个面板中心处计算得到 - 额定工况下的集成流体力学量： - 推力系数（KT） - 效率（η） - 梢涡强度（Γ） 流体力学量通过低保真度边界元法（Boundary Element Method, BEM）求解器计算得到。 仿真工况包括： - 额定当量工况 - 加载当量工况，对应桨叶在非均匀尾流中经过90°位置的状态 - 非加载当量工况，对应桨叶在非均匀尾流中经过270°位置的状态 本数据集矩阵尺寸为7805×16385，包含几何坐标、螺旋桨参数化参数、分布式压力系数以及集成流体力学量。 数据集统计信息如下： - 总构型数：16385 - 基准构型：1 - 采样构型：16384 - 有效仿真数：16306 - 无效仿真数：79 无效仿真指边界元法仿真或流体力学量后处理无法得到有效物理输出的情况。当标量物理量（包括效率、推力系数或梢涡强度）出现非物理的负值时，也会使用NaN（非数字）值填充。 物理量无效或部分无效的样本仍可用于基于几何的降维研究。 本数据集属于基准数据集集合的一部分，该集合旨在为工程设计空间中的降维技术评估提供标准化数据库。 本数据集采用物理感知的设计空间表示方式，将几何、参数化与物理信息在统一框架内进行一致整合。 本数据集采用的参数化方法与求解器详见以下文献： 1. Serani, A., Palma, G., Wackers, J., Quagliarella, D., Gaggero, S., & Diez, M. (2025). Extending parametric model embedding with physical information for design-space dimensionality reduction in shape optimization. *Engineering with Computers*. 2. Gaggero, S., & Serani, A. (2026). Physics-informed dimensionality reduction for propeller shape optimization. *Applied Ocean Research*, 166, 104932.