Dataset of Numerical assessment on the combined effects of non-thermal plasma and water addition in hydrogen combustion

• This dataset offers a comprehensive numerical insight into the synergistic effects of nanosecond repetitively pulsed discharge (NRPD) plasma and water vapor addition on hydrogen combustion and NOₓ formation. • The data can help researchers and engineers design and optimize plasma-assisted hydrogen engines and low-emission combustion systems by understanding ignition delay, radical formation, and emission behavior under different plasma–water conditions. • It supports the development and validation of chemical kinetic models and machine-learning-based combustion optimization frameworks using well-defined simulation parameters and responses. • The dataset offers a valuable benchmark for comparing experimental or computational studies on plasma-assisted combustion, non-equilibrium plasma chemistry, and water–fuel interactions. • The structured Design of Experiments (DoE) and Response Surface Methodology (RSM) data can be reused to explore sensitivity analyses, optimize operating ranges, or develop surrogate models for practical hydrogen combustion systems.• 本数据集全面呈现了纳秒重复脉冲放电（nanosecond repetitively pulsed discharge, NRPD）等离子体与水蒸气添加对氢气燃烧及氮氧化物（NOₓ）生成的协同效应的数值研究结果。 • 该数据集可帮助研究人员与工程师通过厘清不同等离子体-水工况下的点火延迟、自由基生成及排放行为，设计并优化等离子体辅助氢气发动机与低排放燃烧系统。 • 本数据集可借助明确界定的仿真参数与响应结果，支撑化学动力学模型以及基于机器学习的燃烧优化框架的开发与验证。 • 本数据集可为等离子体辅助燃烧、非平衡等离子体化学以及水-燃料相互作用领域的实验或计算研究对比提供极具价值的基准参照。 • 本数据集采用结构化的实验设计（Design of Experiments, DoE）与响应面法（Response Surface Methodology, RSM）生成的数据，可被重复用于开展敏感性分析、优化运行范围，或为实用型氢气燃烧系统开发替代模型。