1269 A Framework for Post-Disaster Facility Restoration Management: Needs and Requirements for the Use of Hybrid Simulation Moonseo PARK 1 ; SangHyun LEE 2 ; Hyun-Soo LEE 3 ; Minji CHOI 4 ; Sungjoo HWANG 5 ; MyungGi MOON 6 ; Seulbi LEE 7 ; and Jae-Ho PYEON 8 1 Prof., Dept. of Architecture and Architectural Engineering, Seoul National Univ., 1 Gwanak-ro, Seoul, Korea, email: mspark@snu.ac.kr 2 Assistant Prof., Dept. of Civil and Environmental Engineering, Univ. of Michigan, 2350 Hayward St., Ann Arbor, MI 48109, email: shdpm@umich.edu 3 Prof., Dept. of Architecture and Architectural Engineering, Seoul National Univ., 1 Gwanak-ro, Seoul, Korea, email: hyunslee@snu.ac.kr 4 PhD Student, Dept. of Architecture and Architectural Engineering, Seoul National Univ., 1 Gwanak-ro, Seoul, Korea, email: mjchoi7@hotmail.com 5 PhD Student, Dept. of Architecture and Architectural Engineering, Seoul National Univ., 1 Gwanak-ro, Seoul, Korea, email: nkkt14@snu.ac.kr 6 PhD Student, Dept. of Civil and Environmental Engineering, Univ. of Michigan, 2350 Hayward St., Ann Arbor, MI 48109, email: mgmoon@umich.edu 7 Master s Course Student, Dept. of Architecture and Architectural Engineering, Seoul National Univ., 1 Gwanak-ro, Seoul, Korea, email: lee130@snu.ac.kr 8 Associate Prof., Dept. of Civil and Environmental Engineering, San Jose State Univ., One Washington Square, San Jose, CA 95192, email: jae.pyeon@sjsu.edu ABSTRACT Catastrophic disasters can cause fatal damage to civil infrastructures and facilities that provide basic services to the region. The malfunctioning restoration conditions (e.g., resource supply system and work environment) and lifeline systems (e.g., electric power) in the region have a significant influence on an individual facility restoration operation. Therefore, it is necessary to analyze the impact of regional-level recovery conditions for an effective implementation of facility restoration operation. Since it is hard to analyze interactions among diverse recovery efforts with a single stand-alone simulation approach, this research introduces a hybrid simulation framework for post-disaster facility restoration management. This is based on data exchange between different simulation modules of regional-level restoration conditions, lifeline systems, and facility operation. The use of hybrid simulation enables users to fully utilize each advantage of different simulation methods. The simulation results of the prototype imply that external recovery conditions can have significant impacts on a facility restoration operation, which highlights the necessity of considering external conditions for project management after a disaster. A better understanding of the surrounding conditions (i.e., the effect of the resource supply system, work environment, and lifeline system) can thus support project managers in implementing appropriate restoration planning to avoid project delays.
1270 INTRODUCTION Catastrophic disasters generate a large and immediate functional loss of a built environment due to the fatal damage of structures (Olshansky et al. 2012). Since the interrupted function of facilities may cause tremendous inconveniences to residents, appropriate restoration plans need to be immediately employed to recover social and economic activities in communities within a limited amount of time. Due to the need for the rapid recovery of a facility s function, facility restoration project planners are required to initiate their projects with wellimplemented plans as soon as possible. However, a post-disaster recovery situation, where resource and time limitations are strongly imposed, may cause the following negative outcomes to facility restoration operations that may lead to unexpected delays and additional project costs: (a) resource availability (e.g., materials, equipment, and workforces) and lifeline services (e.g., water, electricity, and gas) become limited due to damaged production systems and the excessive demand for restoration at the same time (Orabi et al. 2010); (b) damage to existing buildings and infrastructure can cause delays in the overall restoration process by obstructing work spaces with debris and resource delivery capability (Olshansky et al. 2012); and (c) restoration resources are unevenly allocated due to interdependency and competition among various types of facilities/infrastructures (Shoji and Toyota 2009). These possible outcomes imply that restoration management should incorporate comprehensive investigations into various elements in terms of both external recovery conditions (e.g., resource supply systems, lifeline systems, and work environment) and facility restoration operations. For the purpose of comprehensively analyzing the diverse levels of recovery efforts i.e., both regionaland individual facility-level a hybrid simulation framework for post-disaster facility restorations is introduced. Hybrid simulation, the idea to combine different simulation paradigms, is currently in place in many research fields necessitated by the increasing need for comprehensive analysis of complex systems (Mosterman 1999). Due to its advantage in the analysis of large and complex systems that requires both strategic and operational point of view, hybrid simulation can offer a better understanding of external conditions for facility restoration, which are affected by an interdependent restoration process among a regional-level built environment and lifeline systems. As a result, an integrated model is developed as a prototype to display the hybrid simulation with data exchange requirements. Finally, the research outcome is expected to assist facility managers with appropriate restoration planning to minimize the waste of time, cost, and resources. PRELIMINARY STUDY The importance of efficient disaster recovery planning has been highlighted in the civil and construction research areas. In general, previous research on construction processes and operations considers resource logistics and schedule performance as the main interests (Peña-Mora et al. 2008). However, the most severely restricted aspects of the restoration activities were inefficient resource supply and unavailable required services for work. Numerous research efforts regarding regional-level planning thus included resource supply chain management (Orabi et al. 2010) and debris disposal management (Swan 2000). To address
1271 restoration conditions in a more specific manner, particular attention was also paid to critical infrastructures of the region. O Rourke (2007) developed the concept of a lifeline system to describe the large and geographically distributed principal networks, including electric power, gas, and water supply. Lifeline systems play a primary role in securing the functionality for the entire region as well as individual facilities/infrastructures by providing basic requirements and services for everyday lives. The recovery of a lifeline system was thus treated as one of the most urgent priorities at an early recovery phase (Shoji and Toyota 2009). Despite the academic contributions toward alleviating the negative impacts of the regional environment on facility restoration operation, such challenges as the analysis of how and to what extent regional-level restoration conditions affect individual facility restoration still exist. This is because: (a) an analysis on various scope considering detail facility restoration operations and comprehensive regional-level recovery conditions is necessary; (b) interdependency among different facilities/infrastructures should be determined; and (c) interactions among regional- and facility-level restoration efforts need to be identified for effective operation management. NECESSITY OF HYBRID SIMULATION Since computer simulation techniques can articulate the complex behavior of an interest over time (Harrison et al. 2007), they have been widely applied in the construction engineering and management sectors. In particular, discrete event simulation (DES) is regarded as an effective tool for construction process analysis due to its advantages in describing process and operational details, including resources (Law and Kelton 2006). An event-based modeling technique can be helpful when dealing with the detailed restoration operation process of an individual facility where available resources are strictly limited and where the sequence of various activities is highly intricate. On the other hand, a system dynamics (SD) simulation provides an analytic solution for complex, nonlinear, and dynamic systems by focusing on interactions among variables and understanding their structures (Sterman 2000; Harrison et al. 2007). Based on the cause-and-effect relationship among variables, SD can be applied to model the behavior of a system as a whole. While existing operation analysis methods (e.g., DES) focus on the detailed description of process, SD modeling at the macro-level is stronger for analyzing surrounding resource supply systems and the work environment caused by feedback processes among the interdependent restoration operations of the overall built environment. In addition, the available functionality of lifeline systems should be taken into account by considering their networks and functional interdependencies within the local level. In this research, agent-based modeling (ABM) can be used to determine strong interdependency and connection among lifeline systems with its ability to formulate the actions and interactions of autonomous decision-making entities called agents (Bonabeau 2002). The utilization of ABM enables a representation of the different physical or functional state of each facility/infrastructure that is considered an individual agent that may compete for repair resources. The physical/functional state generates both direct and indirect interaction with other lifeline systems connected by pre-assigned network rules. Although three different simulation methods (i.e., DES, SD, ABM) can be helpful for experimenting with "what-if" scenarios to make effective recovery plans
1272 for both facility- and regional-level management in chaotic situations, interactions among diverse levels of recovery efforts are hard to analyze with a single stand-alone simulation approach. This difficulty is due to the gap of the goal, scope, and detail level of analysis between each simulation method. In this situation, there has been a growing interest in hybrid simulation because seamless integration of each simulation model supported capturing many complex problems in large systems (Mosterman 1999; Venkateswaran et al. 2004). Hybrid simulation approach was successfully used to analyze the impact of higher level decision on the lower level and vice versa (Venkateswaran et al. 2004). This research thus applies hybrid simulation to fully utilize the benefits of different simulators with specific purposes, as well as to conduct comprehensive analysis on restoration management. Similarly, Lee et al. (2009) applied a hybrid simulation in the construction field in order to facilitate a better understanding of complex interactions among various processes in large-scale construction. In this context, hybrid simulation provides analytic capabilities for understanding multi-dimensional aspects of disaster restoration situations, including the operation itself and the critical surroundings affecting the operation. Furthermore, it enables the investigation of each restoration management level (i.e., individual facility restoration, regional built environment, and lifeline systems) as well as its interaction from a detailed and comprehensive perspective. FRAMEWORK FOR RESTORATION MANAGEMENT USING HYBRID SIMULATION The interactions among regional restoration conditions, lifeline system recovery, and facility reconstruction operation are visualized in Fig. 1. Each simulation module produces useful data output based on its specific purposes. The restoration conditions constitute the resource supply system and work environment (affected by work space and resource delivery system) that determine resource availability and the work effectiveness of the restoration process. They eventually influence the progress of both lifeline system recovery and facility reconstruction operations with its ability to provide available resources and effective work conditions. The recovered lifeline system provides required services to facility reconstruction operation; this may include gas, water, power supply, and so forth. These basic services are indispensable requirements for commencing the operation smoothly, and for significantly changing the quality of the recovery environment. After regaining the functionality of the lifeline system, an intensive reconstruction or full restoration is initiated with the reconstruction of the individual facility/infrastructure. While the restoration process of the individual facility is affected by regional recovery conditions, a restored individual facility can also improve overall restoration conditions. For instance, the early restoration of an industrial facility that produces construction materials can be helpful in recovering overall resource supply capability. To effectively analyze the diverse restoration processes, both at the regional and facility level, ABM can be helpful to model lifeline system networks and interconnection among nodes. SD can provide a comprehensive solution to analyze overall restoration efforts and restoration conditions at the regional level with a consideration of policy factors. With a detailed event-oriented view, in addition, DES can create a model of a detailed reconstruction operation.
1273 Figure 1. Interactions among Different Post-Disaster Restoration Phases PROTOTYPE OF THE HYBRID SIMULATION Prototype Overview Fig. 2 visualizes an overview of a hybrid simulation prototype that can be applied to the recovery phase after a catastrophic earthquake. Each section of the diagram represents a lifeline system recovery focusing on power supply (A in Fig. 2), resource supply and work environment (B in Fig. 2), and the restoration operation for a residential/commercial complex building (C in Fig. 2). The simulation methods of agent-based modeling, system dynamics, and discrete event simulation are applied respectively to analyze the behavior at each level. In a lifeline system, developed by ABM, the agents are assigned to the major supply system and connection nodes of the power supply station at a local level. Based on each agent s damage state and interdependency with others, repair resources are given to the agent to carry out the functional recovery process. As a result, the simulation module generates a lifeline service (i.e., electric power) supply ratio to other modules to deliver information on the availability of the service. While the lifeline system module focuses on assessing interdependency and the damage states of corresponding agents, resource supply and the work environment simulation module using SD comprehensively deal with various facilities/infrastructures in an overall region. The restoration work rate of a damaged facility/infrastructure depends on resource allocation; this is an outcome of both governmental recovery plans and resource competitions among various types of facilities/infrastructures (loops B1 and B2) and resource availability from production ability (loop R1). In addition, a functional interdependency among different facilities/infrastructures also determines the work delay ratio, influencing the restoration work rate (loops R2 and R3).
1274 Lastly, the DES module for the facility reconstruction operation simulates a four-day cycle of core work operations in a 70-story high-rise residential/commercial complex building as an example. This simulation incorporates the information of lifeline service supply, resource supply, and construction work delay ratio from previous modules. The operation module aims to examine the changes in restoration operation according to changes in regional-level recovery conditions. Figure 2. An Overview of Hybrid Simulation Prototype
1275 Behavior Test of Simulation and Analysis Based on the developed prototype presented in Fig. 2, this research conducts simulation for the comprehensive understanding of facility restoration to inspect the impact of post-disaster damage patterns on restoration. This is implemented by four different scenarios: (a) a normal situation that only the DES module is simulated (graph line 1 in Fig. 3); (b) an interrupted situation with the effects of the damaged lifeline system that ABM and DES modules are interacted (graph line 2 in Fig. 3); (c) an interrupted situation with the effects of damaged built environment that SD and DES modules are interacted (graph line 3 in Fig. 3); and (d) an interrupted situation with the effects of complex damage to both lifeline system and built environment that ABM, SD, and DES modules are all interacted (graph 4 in Fig. 3). For instance, information of unavailable lifeline services and inefficient resources are analyzed by ABM and SD simulation modules and then relayed to DES modules as external conditions for construction operations during the simulation in the fourth scenario. Simulation results can be validated by conducting a comparative analysis between the actual construction operation and the recovery patterns from past earthquakes. Figure 3. The Effects of Damaged Lifeline System and Restoration Conditions on Construction Work Delay As a result of the hybrid simulation prototype, Fig. 3 illustrates the effects of a lifeline system and built environment restoration on construction work delay after disaster. The general assumptions are set for four cases: as the disaster event takes place, at week 10, and when the restoration project starts at week 20. Graph line 1 displays construction work progress completed in 56 weeks in the pre-disaster situation where the functionality of the lifeline system and recovery environment is assumed to be normal. In actuality, the core work process of this building took 60 weeks, including 3 to 4 weeks of break in the winter season, which shows the
1276 similarity with simulation results of normal construction operation. However, significant delays are shown in graph lines 2, 3, and 4 as 80, 105, and 116 weeks, respectively. In particular, lifeline restoration after a disaster in the real world is expected to require 3 to 6 months (RA 2013). Lifeline restoration from the 2011 Japanese earthquake was completed almost 25 weeks after the event, which led to delays in commencing the full restoration (RA 2011). These past recovery patterns can explain the cause of delays in graph lines 2, 3, and 4 of Fig. 3. In addition, two years later the overall restoration of residential and commercial buildings was only about 40% completed due to the excessive need for reconstruction, while other core facilities were 80 90% done within the same time (RA 2011). From this actual recovery tendency, it is expected that limited resources may cause delays in facility restoration operation, as shown in Graph lines 3 and 4 of Fig. 3. The differences in simulation results imply the significant impact of external recovery conditions on the progress of facility restoration operation, and highlight the necessity of considering external conditions for project management after a disaster. In addition, it could be inferred from comparing graph lines 2 and 3 in Fig. 3 that damaged built environment restoration reacts more sensitively in regard to construction work delay than lifeline systems do. In other words, problems in resource availability caused by resource competition and availability have greater influences on project delays (i.e., 25 weeks of delay) than lifeline system problems do. This is because the recovery of lifeline systems normally takes place in the first emergency response phase after disaster, which is before or at the beginning of project initiation. However, resource availability is severely limited due to excessive needs for resources as a huge number of facilities/infrastructures are being repaired at the same time after the recovery of prioritized systems in the region is completed. Figure 4. The Effect of Project Initiation on Construction Work Progress
1277 On the other hand, Fig. 4 demonstrates what kinds of information can assist the project manager s decision-making planning phase (in particular, determining project initiation). When there are complex effects on a damaged lifeline system and built environment restoration simultaneously, significant delays can be generated after project initiation. Graph lines 1, 2, and 3 in Fig. 4 imply that reconstruction duration can vary according to project start time after a disaster event accompanying a malfunctioning lifeline system and recovery environment. If a project is initiated shortly after the occurrence of the disaster, entire project duration would inevitably be prolonged until basic requirements from lifeline and resources are available. However, graph lines 2 and 3 show a more effective reconstruction work process as the project initiation is postponed to week 70 and 120. In terms of both time and cost management, the latter displays more efficient behavior by reducing both wasted time and the indirect cost of running the unproductive site. By suggesting the effects of different project initiation times on reconstruction work progress, this result can be utilized to assist project managers during the project planning phase when encountering difficulties in resource and lifeline service supply. EXPECTED OUTCOME & FUTURE DEVELOPMENT This research aims to apply a hybrid simulation to incorporate the impact of regional-level damaged built environment and lifeline systems into facility restoration operation management at the post-disaster level. A comprehensive analysis of various levels of recovery effort is performed while determining interactions between regional levels and individual facility levels. The interactions are realized by a data exchange among each simulation module of DES, SD, and ABM. The research outcome implies that damaged built environment restoration reacts more sensitively on construction work delay than lifeline systems, and that the time of the project initiation at the post-disaster stage is likely to influence the reconstruction s duration. The use of a hybrid simulation approach is expected to offer a better understanding of the surrounding conditions (i.e., the effect of resource supply system, work environment, and lifeline systems) of individual facility restoration. It can also support project managers in implementing appropriate restoration planning to improve the recovery process of a damaged facility after a disaster, which may enable the reduction of the project time/cost, and the swift recovery of functionality of the facilities for public convenience in a chaotic situation. However, further development is required to enhance the applicability of the proposed research outcome. For instance, disaster simulators (e.g., earthquake) and spatial information of a facility/infrastructure can be supplemented. The interoperability within the integrated sub-simulators and modeling can potentially provide the simulation with extendibility to future types of disaster and to the all-time management of post-disaster restoration management. ACKNOWLEDGMENT This research was supported by both a grant (12TRPI-C064106-01) from the R&D Program and by a grant (13AUDP-C067809-0) from the Architecture & Urban Development Research Program, which are funded by the Ministry of Land, Infrastructure, and Transport Affairs of the Korean government.
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