{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/129630"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/129630","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A static modeling framework for evaluating the flood resilience of real-world electric vehicle charging networks","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","abstract_has_math":false,"creators":["Jagtap, Sumeet"],"institution":"University of Illinois Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Industrial Engineering","degree_department":null,"school":null,"contributors":["Wang, Pingfeng"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-05-09","date_published":"2025-05-09","updated_at":"2026-07-22T22:25:05Z","subjects":["Electric Vehicle Infrastructure","Flood Resilience","Charging Networks","Network Modeling","Static Simulation","Resilience Metrics","Graph Modeling"],"languages":["en","eng"],"rights":["Copyright 2025 Sumeet Jagtap"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/129630","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Wang, Pingfeng"]},{"key":"dc:creator","label":"Author","values":["Jagtap, Sumeet"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-05-09","2025-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electric Vehicle Infrastructure","Flood Resilience","Charging Networks","Network Modeling","Static Simulation","Resilience Metrics","Graph Modeling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Sumeet Jagtap"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/129630"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","The student, Sumeet Jagtap, accepted the attached license on 2025-05-05 at 15:24.","The student, Sumeet Jagtap, submitted this Thesis for approval on 2025-05-05 at 15:56.","This Thesis was approved for publication on 2025-05-09 at 09:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22217 on 2025-10-19 at 19:17:03","As electric vehicles (EVs) become increasingly central to modern transportation, the resilience of the supporting EV charging infrastructure has emerged as a critical concern, particularly in the face of climate-related disruptions such as flooding. This thesis presents a static, simulation-based framework to evaluate the flood resilience of real-world EV charging networks (EVCNs). Instead of generating synthetic or hypothetical networks, the study constructs a data-driven graph model using publicly available datasets, where EV charging stations serve as nodes and geographic proximity defines the edges. Flood scenarios are simulated by removing nodes and their associated edges based on the geographic flood vulnerability of each station. Network resilience is then quantified using adapted metrics from the resilience framework proposed by Wu and Wang (2022) and others, including connectivity retention, redundancy, accessibility loss, and systemic degradation. A resilience curve is developed to capture the overall performance decline of the network across disruption levels, with the area under the curve serving as a proxy for systemic resilience. The selected case study of Miami-Dade County demonstrates how a real-world EVCN responds under increasing levels of disruption and reveals critical thresholds in its network performance. By grounding the analysis in real-world empirical data and emphasizing static evaluation, this methodology offers a diagnostic tool for assessing the vulnerability of existing EVCNs. It provides a practical foundation for resilience benchmarking as well as comparative resilience studies across regions where EV infrastructure is emerging, and aims to support the design of more robust EV infrastructure systems in flood-prone regions."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A static modeling framework for evaluating the flood resilience of real-world electric vehicle charging networks"]}]}],"canonical_facts":{"dc:contributor":["Wang, Pingfeng"],"dc:creator":["Jagtap, Sumeet"],"dc:date":["2025-05-09","2025-05"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01","The student, Sumeet Jagtap, accepted the attached license on 2025-05-05 at 15:24.","The student, Sumeet Jagtap, submitted this Thesis for approval on 2025-05-05 at 15:56.","This Thesis was approved for publication on 2025-05-09 at 09:40.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22217 on 2025-10-19 at 19:17:03","As electric vehicles (EVs) become increasingly central to modern transportation, the resilience of the supporting EV charging infrastructure has emerged as a critical concern, particularly in the face of climate-related disruptions such as flooding. This thesis presents a static, simulation-based framework to evaluate the flood resilience of real-world EV charging networks (EVCNs). Instead of generating synthetic or hypothetical networks, the study constructs a data-driven graph model using publicly available datasets, where EV charging stations serve as nodes and geographic proximity defines the edges. Flood scenarios are simulated by removing nodes and their associated edges based on the geographic flood vulnerability of each station. Network resilience is then quantified using adapted metrics from the resilience framework proposed by Wu and Wang (2022) and others, including connectivity retention, redundancy, accessibility loss, and systemic degradation. A resilience curve is developed to capture the overall performance decline of the network across disruption levels, with the area under the curve serving as a proxy for systemic resilience. The selected case study of Miami-Dade County demonstrates how a real-world EVCN responds under increasing levels of disruption and reveals critical thresholds in its network performance. By grounding the analysis in real-world empirical data and emphasizing static evaluation, this methodology offers a diagnostic tool for assessing the vulnerability of existing EVCNs. It provides a practical foundation for resilience benchmarking as well as comparative resilience studies across regions where EV infrastructure is emerging, and aims to support the design of more robust EV infrastructure systems in flood-prone regions."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/129630"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Sumeet Jagtap"],"dc:subject":["Electric Vehicle Infrastructure","Flood Resilience","Charging Networks","Network Modeling","Static Simulation","Resilience Metrics","Graph Modeling"],"dc:title":["A static modeling framework for evaluating the flood resilience of real-world electric vehicle charging networks"],"dc:type":["text"],"thesis:degree_discipline":["Industrial Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:05Z"}