Resilience simply means to rebound when exposed to a disruptive event. Damage to bridges in transportation networks usually result in long detours and increased travel time hence have massive cost implications. Transportation networks composed of major bridge infrastructures frequently depend on the bridges to carry high traffic volumes. Transportation network resilience explains the ability of transportation networks to contain and recover from disruptions. Transportation network resilience entails the transportation network’s capability to continue functioning in spite of hazard-induced breakdown to network segments and how quickly those sections can be restored for the network to return to pre-disaster performance levels. Most resilience-related research in this area have primarily focused on physical bridge resilience without necessarily considering the resilience impact of bridge damage on the overall or regional network. This thesis is focused on filling this research gap by considering the resilience of transportation networks subject to bridge damage and road closures. This research further proposes the use of regional travel demand models and Geographic Information Systems (GIS) visualization techniques for network level impact visualization and accessibility analyses. The socio-technical approach associated with transportation system resilience is broad and multidisciplinary, focusing on the network’s ability to sustain functionality and recover speedily when faced with disruptions or shocks. Academic works in this area are generally viewed in terms of having qualitative or quantitative frameworks. There is also significantly less literature evaluating response and recovery phases of resilience. Developed resilience indexes have sparsely touched on many salient aspects of resilience; hence they are only applicable to very specific scenarios. Further investigative efforts are therefore necessary for post-disaster phases of resilience, evaluating the applicability of resilience indexes on multiple hazard events for transportation networks, and developing resilience indexes based on regional road network models while considering all network links and not just alternative routes. Temporary, long-term, and partial closures to bridges can result in enormous cost implications. However, bridge closures are inevitable not only due to the likelihood of hazard-induced damages, but routine maintenance, repair, and rehabilitation (MR&R) activities may also warrant closures. It is a current practice that vehicles are rerouted to the shortest alternative route (detour approach) during bridge closures. In an initial study, a scenario-based network approach for evaluating the impact of bridge closures on transportation user cost is proposed. Both the detour-based and network-based approaches were applied to the Tampa Bay regional network model while considering five bridge closure scenarios. User costs were computed in terms of delay and vehicle operating costs. Findings indicated that for closures to I-275, Gandy, Highway 580 and W.C.C Causeway bridges, there were increases of about 42%, 18%, 61%, and 45% respectively, in total user costs for the network-based approach when compared with the current detour-only approach, indicating a significant network impact captured by the network-based approach. The proposed methodology captures the effects of bridge closures on all road segments within the regional network jurisdiction, provides a more rigid framework for analysis by ensuring user costs are computed efficiently while avoiding overestimation, takes into account the fact that road users may have advance knowledge of roadway conditions prior to trips hence significantly influencing route choices, and provides sufficient information for agencies to implement preemptive measures to cater for network-level disruptions due to bridge closures. Also, regional network resilience was assessed, first through a schematic framework developed for selecting at-risk bridges during hurricane events by: (i) computing exposure probabilities for hurricane events at bridge locations; (ii) developing bridge damage state functions and damage state rating assignments using historical data from the National Bridge Inventory (NBI) database; (iii) identification of bridges at risk to hurricane-induced damage; and (iv) computing aging accessibility to hospitals from which resilience was measured. Results indicated an increase from about 1200 minutes to 2100 minutes and from about 900 to 1100 minutes, for the congested travel time (CTT) and free flow travel time (FFTT), respectively, representing about 75% and 15% for CTT and FFTT, respectively. Furthermore, an additional total travel distance of 52.85 miles was observed for CTT and FFTT. The mean travel times after bridge closures increased from 8.43 to 15.1 minutes and from 6.6 to 7.76 minutes for CTT and FFTT, respectively. The resulting resilience index scaled from 0 to 1 was computed with 1 representing a network which can recover immediately after a disruption (or a network without any performance loss) and zero for one that may never recover to its pre-disaster form. Restoration to moderately damaged bridge led to functionality improvement from 0.87 to 0.94 considering FFTT, and from 0.57 to 0.83 considering the CTT. Reinstating extensively-damaged bridges resulted in functionality increase from 0.94 to 0.96, and 0.83 to 0.85, respectively, for FFTT and CTT. The resilience index for this study was computed as 0.94 and 0.81 for FFTT and CTT respectively, implying a significant loss in senior mobility hence the need for mitigation measures A framework for assessing the regional network resilience was developed by leveraging scenario-based traffic modeling and Geographic Information System (GIS) techniques. High impact zones location identification metrics were developed and implemented in preliminarily identifying areas affected by bridge closures. Resilience index measures were developed by utilizing practical functionality metrics based on vehicle distance and hours traveled. These are illustrated for the Tampa Bay area. Findings for ten bridge closure scenarios and recovery schemas indicate substantial regional network functionality losses during closures. I-275 bridge closure yielded the highest functional loss to the regional network: the aggregated resilience index below 0.5 reflects severe network performance deficit and mobility limitations. Closure to the WCC Causeway bridge results in a network level resilience index value of 0.87, while the indexes for the other scenarios range between 0.76 and 0.97. These results reflect the high dependency of the network on the I-275 bridge. Damage to this bridge is foreseen to have a massive impact on the network in terms of travel cost. Lower resilience index values imply either significant functionality losses or lengthy closure durations or both. To demonstrate the proposed methodology, a hypothetical network illustration indicated that: (i) Single bridge closure scenarios recorded significant performance losses for bridges which directly connected to the destination zone; (ii) Resilience indexes echoed the need to compare predicted recovery times to scheduled restoration times since index measures are either compensated or penalized the speed of predicted recovery with respect to scheduled recovery durations; (iii) Sensitivity analyses reinforced the previous assertion by accounting for both performance loss and restoration or recovery times; (iv) Multiple closures had a significant impact on network performance hence rapidity is vital in improving network resilience. Like any study, there are some limitations identified in this research. While it was clearly identified that variation in response and recovery times may have a significant impact on explaining and formulating resilience measures, there is insufficient data on the road closure and bridge closure durations after hazard events. Such databases will help researchers in evaluating resilience more accurately. Furthermore, even though case studies in this thesis took into account large networks, the utilized models were based on static traffic assignment which suffices for long-term transportation planning. However, it is recommended that use of dynamic traffic assignment models should be explored since they are known to reflect more accurate travel times. This is especially important for equity-based case study applications with respect to post-disaster accessibility. The use of user equilibrium assignment which accounts for each road user minimizing his or her travel time was used for this study, it is recommended that the system optimal solution which minimizes the overall network travel time should be considered since it may be of specific interest to agencies. Solution-based resilience studies are encouraged, especially efforts which incorporate the influx of connected and autonomous vehicles and other shared mobility solutions. This study also recognized the need for collaborative efforts between management authorities and researchers to facilitate the development and implementation of necessary policies and systems for the enhancement of transportation systems’ resilience. / A Dissertation submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 19, 2018. / Bridges, Hazards, Infrastructure, Network Performance, Resilience, Transportation Networks / Includes bibliographical references. / John O. Sobanjo, Professor Directing Dissertation; Eric Chicken, University Representative; Ren Moses, Committee Member; Eren E. Ozguven, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_650753 |
| Contributors | Twumasi-Boakye, Richard (author), Sobanjo, John Olusegun, 1958- (professor directing dissertation), Chicken, Eric, 1963- (university representative), Moses, Ren (committee member), Ozguven, Eren Erman (committee member), Florida State University (degree granting institution), College of Engineering (degree granting college), Department of Civil and Environmental Engineering (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, doctoral thesis |
| Format | 1 online resource (248 pages), computer, application/pdf |
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