| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000435861 |
| 005 | | 20200228110201 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781392418857 |
| 035 | |
▼a (MiAaPQ)AAI27712083 |
| 035 | |
▼a (MiAaPQ)OhioLINKosu1556988737709233 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 624 |
| 100 | 1 |
▼a Sirca, Gene F. |
| 245 | 10 |
▼a Analysis of Full-Scale in-Service Civil Engineering Structures. |
| 260 | |
▼a [S.l.]:
▼b The Ohio State University.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 212 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-05, Section: B. |
| 500 | |
▼a Advisor: Butalia, Tarunjit. |
| 502 | 1 |
▼a Thesis (Ph.D.)--The Ohio State University, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 520 | |
▼a This dissertation focuses on the analysis of full-scale in-service civil engineering structures such as bridges and dams. Four aspects of these types of structures are considered: suspension bridges, prestressed concrete bridges, concrete dams, and soil-filled sheet pile dams. The structures are evaluated using a Wavelet Neural Network (WNN) model for system identification, a neural dynamics model for cost optimization, an Infrared Thermography (IRT) model to detect near-surface defects in concrete, and a permeation grout test method to determine groutability of soils subject to surcharge loading.A new WNN model was developed for system identification of suspension bridge structures and its use in health monitoring systems for damage detection and applied to an in-service bridge structure. The model was formed by combining wavelet decomposition with neural networks by replacing the traditional sigmoid function with a wavelet function, to take advantage of their universal approximation property. A method is presented for the total cost optimization of large prestressed concrete structures, by taking into account the costs of the prestressed concrete, deck concrete, prestressed I-beam steel, deck reinforcing steel, and formwork. The problem is formulated as a mixed integer-discrete nonlinear programming problem. and solved using a robust neural dynamics model. An example is presented to demonstrate the practical application of the methodology presented. Typical network convergence curves using three different network starting points demonstrate the excellent convergence and the robustness of the optimization model.A new IRT method was developed to detect near-surface defects in large in-service concrete structures and was successful in detecting the defects. Although it is possible for a trained eye to examine an IRT image and find the defects in the image, the new method is significantly faster and more accurate. The method was able to detect all the known defects from time-lapsed images by taking advantage of the concrete emissivity where defective concrete temperatures change at different rates than non-defective concrete. An innovative permeation grout test is developed for determining groutability of soils under surcharge load where a soil sample is placed in a rigid container, a surcharge is placed on the soil, and pressurized grout is injected into the soil. After the grout has cured and the surcharge removed, the diameter of the grout column is measured and recorded. Then the test results are evaluated to determine whether the soil is groutable or not. The procedure is repeated at various surcharge loads and grout pressures to establish a relationship between grout pressure and permeation for a given soil overburden. The soils used in the test apparatus during the initial development of the test procedure are those with known and somewhat uniform grain size in order to validate the procedure. Once validated, the test apparatus may be used on soils obtained from the field. |
| 590 | |
▼a School code: 0168. |
| 650 | 4 |
▼a Civil engineering. |
| 690 | |
▼a 0543 |
| 710 | 20 |
▼a The Ohio State University.
▼b Civil Engineering. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-05B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0168 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15494732
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |