Conventional simulation methods relying on single models or empirical formulas fail to support intelligent, full-lifecycle simulation and verification for complex systems such as marine power systems. Multi-domain modeling languages like Modelica, while powerful, remain at the tool level and cannot resolve bottlenecks in data fusion, high-confidence simulation, or closed-loop verification. To overcome these limitations, this paper proposes a system simulation methodology based on data, models, and mock-ups. The methodology integrates fulllifecycle multi-source data into simulation, employs simulation models to construct a digital mock-up, and achieves tight integration and closed-loop iteration among data, models, and the physical mock-up among data, models, and the physical mock-up, thereby establishing high-confidence system-level simulation across design, testing, service, and maintenance. A digital twin of a marine power system is developed using Modelica with real-time multi-dimensional data interaction. Experimental validation under four typical operating conditions (shutdown, 0kW, 30kW, 60kW) shows that simulated key parameters (steam pressure, turbine speed, output power) agree closely with measured values, with all relative errors controlled within 8%. These results demonstrate the feasibility, practicality, and engineering applicability of the proposed methodology, confirming that integrating data, models, and mock-ups effectively supports intelligent full-lifecycle operation and maintenance of complex systems and provides an implementable pathway for the intelligent transformation of systems engineering.

The Xu’s Modeling Method, originating from foundational research for the HyPneu software at Oklahoma State University in the 1980s, provides an intuitive framework for hydraulic system modeling. Its core premise is to align the modeling process with engineers’ cognitive paradigms. A key breakthrough was its algorithmic solution to Differential-Algebraic Equation (DAE) problems, validated through the PERSIM software developed under China’s “Seventh Five-Year Plan” national project. The method enables model construction directly from hydraulic schematics by applying Kirchhoff’s law at junctions, reducing all components to two fundamental sub-models: hydraulic resistance (throttle) and hydraulic capacitance (cylinder). This yields an implicit state equation (a DAE). The Xu’s Algorithm solves this via a unified dynamic-static simulation approach, using the Newton-Raphson method iteratively to compute static states and dynamic derivatives over time steps. In the Digital Twin era, the method finds new relevance. Its implicit state equation serves as a potential mechanism model for digital twins, contingent on solving the inverse problem—a current research focus that may incorporate Artificial Intelligence. Additionally, the method offers a theoretical basis for creating “Hydraulic Intelligent Components,” guiding the design of simpler, more efficient constructions from first principles. This positions it as an advancement over the classic Hydraulic Resistance Systematic Theory. Practically, the method is being applied to develop dedicated simulation and digital twin software for a hydraulic robot system manufactured in Shenzhen, demonstrating its ongoing industrial applicability.