SDG-based Model Validation in Chemical Process Simulation

Signed direct graph (SDG) theory provides algorithms and methods that can be applied directly to chemical process modeling and analysis to validate simulation models, and is a basis for the development of a software environment that can automate the validation activity. This paper is concentrated on the pretreatment of the model validation. We use the validation scenarios and standard sequences generated by well-established SDG model to validate the trends fitted from the simulation model. The results are helpful to find potential problems, assess possible bugs in the simulation model and solve the problem effectively. A case study on a simulation model of boiler is presented to demonstrate the effectiveness of this method.

基于定性趋势与符号有向图的模型校核方法

模型校核的首要目标是建立一个完备的测试剧情集。针对现有模型校核方法存在的问题,提出了基于定性趋势与符号有向图的模型校核方法。首先,在总结前人多种SDG建模方法的基础上,提出了SDG校核模型的建模方法。其次,提出了基于定性趋势与符号有向图的模型校核方法,包括建立SDG校核模型、产生测试剧情、推理标准趋势序列、仿真模型数据趋势提取与识别和趋势对比分析5部分。最后,以TE模型为例进行分析,证明该方法的有效性。

符号有向图与定性趋势的半定量验证方法

针对传统仿真模型验证方法存在的完备性不足、过于依赖人经验等问题,提出一种基于符号有向图(Signed Directed Graph, SDG)与定性趋势的仿真模型半定量验证方法。该方法首先建立过程对象的SDG验证模型,并将定性趋势加入到模型中,然后通过正向推理产生完备的验证测试案例,同时在多个尺度分析比较测试案例与仿真模型输出的相似程度,实现了对仿真模型的半定量验证。最后采用一个反应器仿真模型进行案例研究,证明了方法的有效性。