eprintid: 37783 rev_number: 28 userid: 4396 dir: disk0/00/03/77/83 datestamp: 2020-07-30 19:57:10 lastmod: 2020-07-30 19:57:10 status_changed: 2020-07-30 19:57:10 type: thesis_degree metadata_visibility: show contact_email: jwd25@pitt.edu eprint_status: archive creators_name: DeSantis, John / W. creators_email: jwd25@pitt.edu creators_id: jwd25 creators_orcid: 0000-0002-3391-025X title: Modeling the Development of Joint Faulting for Bonded Concrete Overlays of Asphalt Pavements (BCOA) ispublished: unpub divisions: sch_eng_civilenvironmental full_text_status: restricted keywords: Bonded Concrete Overlays of Asphalt abstract: Bonded concrete overlays of asphalt pavements (BCOAs), also known as whitetopping, consist of a thin concrete overlay on distressed asphalt or composite pavements. They typically have smaller panel sizes than traditional jointed plain concrete pavements (JPCP) in order to reduce stress levels. A distress that can occur in BCOAs is transverse joint faulting, but to date there is no predictive faulting model available for these structures. To be able to develop a faulting prediction model, a better understanding of the joint performance and the pumping mechanism that leads to this distress is necessary. It was determined that pumping in BCOAs is dictated by the depth of joint activation and can develop either at the bottom of the overlay slab within the asphalt layer or at the bottom of the asphalt layer in the granular layer. To account for the conditions unique to BCOA, a computational model was developed to predict the response of these structures. The model was validated using falling weight deflectometer (FWD) data from existing field sections at the Minnesota Road Research Facility (MnROAD) as well as at the University of California Pavement Research Center (UCPRC). A fractional factorial analysis was performed using the field validated computational models to develop predictive models, in the form of artificial neural networks (ANNs). The ANNs are able to rapidly estimate the structural response at the joint in BCOAs to environmental and traffic loads. The structural response is then related to damage using the differential energy (DE) concept. The DE concept is commonly used in faulting prediction models in order to relate damage to faulting. The final steps include conducting a calibration as well as a sensitivity analysis on the prediction capabilities of the model. The overall framework for predicting faulting for BCOAs is presented and is based on the model in the Pavement Mechanistic-Empirical (ME) design software. Improvements were made to the previous framework to be able to better characterize BCOAs so the accuracy of the predicted faulting could be improved. Future work includes implementation of the BCOA faulting prediction model into the BCOA-ME design guide developed at the University of Pittsburgh. date: 2020-07-30 date_type: published pages: 312 institution: University of Pittsburgh refereed: TRUE etdcommittee_type: committee_chair etdcommittee_type: committee_member etdcommittee_type: committee_member etdcommittee_type: committee_member etdcommittee_name: Vandenbossche, Julie / M etdcommittee_name: Khazanovich, Lev etdcommittee_name: Khanna, Vikas etdcommittee_name: Harvey, John etdcommittee_email: jmv7@pitt.edu etdcommittee_email: Lev.K@pitt.edu etdcommittee_email: khannav@pitt.edu etdcommittee_email: jtharvey@ucdavis.edu etd_defense_date: 2019-12-06 etd_approval_date: 2020-07-30 etd_submission_date: 2019-11-13 etd_release_date: 2020-07-30 etd_access_restriction: 2_year etd_patent_pending: FALSE thesis_type: dissertation degree: PhD citation: DeSantis, John / W. (2020) Modeling the Development of Joint Faulting for Bonded Concrete Overlays of Asphalt Pavements (BCOA). Doctoral Dissertation, University of Pittsburgh. (Unpublished) document_url: http://d-scholarship-dev.library.pitt.edu/37783/1/JWDeSantis_ETDfinal_2020_FINAL_v4.pdf