There has been a strong need for simulation environments that are capable of modeling deep interdependencies between complex systems encountered during natural hazards, such as the interactions and coupled effects between civil infrastructure systems response, human behavior, and social policies, for improved community resilience. Coupling such complex components with an integrated simulation requires continuous data exchange between different simulators simulating separate models during the entire simulation process. This can be implemented by means of distributed simulation platforms or data passing tools. In order to provide a systematic reference for simulation tool choice and facilitating the development of compatible distributed simulators for deep interdependent study in the context of natural hazards, this article focuses on generic tools suitable for integration of simulators from different fields but not the platforms that are mainly used in some specific fields. With this aim, the article provides a comprehensive review of the most commonly used generic distributed simulation platforms (Distributed Interactive Simulation (DIS), High Level Architecture (HLA), Test and Training Enabling Architecture (TENA), and Distributed Data Services (DDS)) and data passing tools (Robot Operation System (ROS) and Lightweight Communication and Marshalling (LCM)) and compares their advantages and disadvantages. Three specific limitations in existing platforms are identified from the perspective of natural hazard simulation. For mitigating the identified limitations, two platform design recommendations are provided, namely message exchange wrappers and hybrid communication, to help improve data passing capabilities in existing solutions and provide some guidance for the design of a new domain-specific distributed simulation framework.

迫切需要能够模拟自然灾害期间遇到的复杂系统之间的深度相互依赖关系的模拟环境，例如民用基础设施系统响应、人类行为和社会政策之间的相互作用和耦合效应，以提高社区弹性。将此类复杂组件与集成仿真耦合需要在整个仿真过程中模拟不同模型的不同仿真器之间进行持续的数据交换。这可以通过分布式仿真平台或数据传递工具来实现。为了为仿真工具选择提供系统参考，促进兼容分布式仿真器的开发，以便在自然灾害背景下进行深度相互依赖的研究，本文重点介绍适用于不同领域模拟器集成的通用工具，而不是主要用于某些特定领域的平台。为此，本文全面回顾了最常用的通用分布式仿真平台（分布式交互仿真 (DIS)、高级架构 (HLA)、测试和培训支持架构 (TENA) 以及分布式数据服务 (DDS)） ) 和数据传递工具（机器人操作系统 (ROS) 和轻量级通信和编组 (LCM)）并比较它们的优缺点。从自然灾害模拟的角度确定了现有平台的三个具体限制。为了减轻已确定的限制，提供了两个平台设计建议，