Distributed Simulation Platforms and Data Passing Tools for Natural Hazards Engineering: Reviews, Limitations,and Recommendations

here 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.

Bayesian method for system reliability assessment of overlapping pass/fail data

For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve the precision of the system reliability assessment. If the multi-level pass/fail data are overlapping,one challenging problem for the Bayesian analysis is to develop a likelihood function. Since the computation burden of the existing methods makes them infeasible for multi-component systems, this paper proposes an improved Bayesian approach for the system reliability assessment in light of overlapping data. This approach includes three steps： fristly searching for feasible paths based on the binary decision diagram, then screening feasible points based on space partition and constraint decomposition, and finally simplifying the likelihood function. An example of a satellite rolling control system demonstrates the feasibility and the efficiency of the proposed approach.

An efficient parallel algorithm for ocean circulation numerical model based on irregular rectangle decomposition scheme

A parallel algorithm of circulation numerical model based on message passing interface（MPI） is developed using serialization and an irregular rectangle decomposition scheme. Neighboring point exchange strategy（NPES） is adopted to further enhance the computational efficiency. Two experiments are conducted on HP C7000 Blade System, the numerical results show that the parallel version with NPES（PVN） produces higher efficiency than the original parallel version（PV）. The PVN achieves parallel efficiency in excess of 0.9 in the second experiment when the number of processors increases to 100, while the efficiency of PV decreases to 0.39 rapidly. The PVN of ocean circulation model is used in a fine-resolution regional simulation, which produces better results. The capability of universal implementation of this algorithm makes it applicable in many other ocean models potentially.