[RF] Behavioral Model

 Behavioral models capture the mathematical description of the physical and informational behavior of a component. For the scope of this research, we consider these models to consist of either differential-algebraic equations (DAEs) for continuous time phenomena, or discrete event systems specifications (DEVS). Behavioral models can also be composed out of other behavioral models through the port-based modeling paradigm.
  A component object can contain multiple behavioral models with different levels of detail. For example, a DC motor component can contain a family of mechanical behavioral models. One model could only capture the kinematic constraints between the rotor and the stator, while another could include non-linear friction models.
  All of these behavioral models are stored in a behavioral model container. The container is separated into three parts: a family of interfaces, a family of implementations of particular models and a set of 2-tuples that enumerate the correspondences between the interfaces and implementations. One of these 2-tuples is the default map, and determines the default interface and implementation for the behavioral model. The implementation is typically a mathematical description of the DAEs and DEVS that make up the behavior of the component. Behavioral models in our framework are represented using the Modelica simulation language.
  In addition to describing the internal component dynamics, behavioral models also describe the physical phenomena that act between components – the component interactions.
- Reference : Behavioral Model Composition in Simulation-Based Design

  Sinha, R.;   Paredis, C.J.J.;   Khosla,P.K.;

  Inst. for Complex Engineered Syst., Carnegie Mellon Univ., Pittsburgh, PA, USA 

  Behavioral model은 system theory와 dynamic system modeling과 같은 행동과학 분야에서 사용되는 modeling 방법으로 현재와 과거의 행동을 알고 있다면 미래의 행동을 예측할 수 있는 방법이다. 

 접근 방법은 기본적인 물리학으로부터 적절한 수학적 개념을 설정하고 시스템 분석을 위한 프레임 워크를 얻는다. 핵심은 현재의 사건으로부터 미래의 사건을 유추할 수 있는지 여부이다. 즉, A로부터  행동 모델 추출한 B를 특성을 분석하여 C를 예측할 수 있다.