Handoff processes during civil infrastructure operations are transitions between sequential tasks. Typical handoffs constantly involve cognitive and communication activities among operations personnel, as well as traveling activities. Large civil infrastructures, such as nuclear power plants (NPPs), provide critical services to modern cities but require regular or unexpected shutdowns (i.e., outage) for maintenance. Handoffs during such an outage contain interwoven workflows and communication activities that pose challenges to the cognitive and communication skills of handoff participants and constantly result in delays. Traveling time and changing field conditions bring additional challenges to effective coordination among multiple groups of people. Historical NPP records studied in this research indicate that even meticulous planning that takes six months before each outage could hardly guarantee sufficient back-up plans for handling various unexpected events. Consequently, delays frequently occur in NPP outages and bring significant socioeconomic losses. A synthesis of previous studies on the delay analysis of accelerated maintenance schedules revealed the importance and challenges of handoff modeling. However, existing schedule representation methods could hardly represent the interwoven communication, cognitive, traveling, and working processes of multiple participants collaborating on completing scheduled tasks. Moreover, the lack of formal models that capture how cognitive, waiting, traveling, and communication issues affect outage workflows force managers to rely on personal experiences in diagnosing delays and coordinating multiple teams involved in outages. This study aims to establish formal models through agent-based simulation to support the analytical assessment of outage schedules with full consideration of cognitive and communication factors involved in handoffs within the NPP outage workflows. Simulation results indicate that the proposed handoff modeling can help predict the impact of cognitive and communication issues on delays propagating throughout outage schedules. Moreover, various activities are fully considered, including traveling between workspaces and waiting. Such delay prediction capability paves the path toward predictive and resilience outage control of NPPs.