Doctoral Dissertations


Ying Huang


"In the process of a progressive failure of steel structures in a post-earthquake fire, real-time assessment and prediction of structural behaviors are of paramount significance to an emergency evacuation and rescue effort. However, existing measurement technologies cannot provide the needed critical data such as large strains at high temperature. To bridge this gap, a novel optical fiber sensor network and an adaptive multi-scale finite element model (FEM) are proposed and developed in this study. The sensor network consists of long period fiber gratings (LPFG) sensors and extrinsic Fabry-Perot interferometer (EFPI) sensors or their integration. Each sensor is designed with a three-tier structure for an accurate and reliable measurement of large strains and for ease of installation. To maintain a balance between the total cost of computation and instrumentation and the accuracy in numerical simulation, a structure is divided into representative/critical components instrumented densely and the remaining components simulated computationally. The critical components and the remaining were modeled in different scales with fiber elements and beam/plate elements, respectively, so that the material behavior and load information measured from the critical components are representative to the remaining components and can be used to update the temperature distribution of the structure in real time. Sensitivity studies on the number of sensors and the initial selection of an updating temperature parameter were conducted. Both the sensor network and the FEM were validated with laboratory tests of a single-bay, one-story steel frame under simulated post-earthquake fire conditions. The validated FEM was applied to a two-bay, four-story steel building under the 1995 Kobe earthquake excitations. Based on extensive tests and analyses, the proposed sensor can measure a strain of 12% at as high as 800⁰C (1472⁰F) in temperature. Within the application range, the LPFG wavelength and the EFPI gap change linearly with the applied strain and temperature. The proposed updating criterion and algorithm in the adaptive FEM are proven to be effective. The number of sensors is sufficient in engineering applications as long as the sensors can adequately represent the material behavior of the instrumented components. The predicted structural behavior is unaffected by any change in a low temperature range and thus insensitive to the initial selection of the updating parameter"--Abstract, page iii.


Xiao, Hai, Dr.
Chen, Genda

Committee Member(s)

Myers, John
Chandrashekhara, K.
Sneed, Lesley


Civil, Architectural and Environmental Engineering

Degree Name

Ph. D. in Civil Engineering


Mid-America Transportation Center
National Science Foundation (U.S.)


Missouri University of Science and Technology

Publication Date

Summer 2012

Journal article titles appearing in thesis/dissertation

  • EFPI-based large strain sensor with adjustable resolution
  • Simultaneous large strain and high temperature measurements with optical fiber sensors
  • Sensor networking and experimental validation in simulated post-earthquake fire environments
  • Temperature-dependent finite element model updating
  • Progressive collapse evaluation of steel buildings with adaptive multi-scale modeling


xiii, 150 pages

Note about bibliography

Includes bibliographical references (pages 137-149).


© 2012 Ying Huang, All rights reserved.

Document Type

Dissertation - Open Access

File Type




Subject Headings

Building failures -- Testing
Metals -- Effect of high temperatures on -- Analysis
Optical fiber detectors -- Design
Sensor networks
Steel, Structural -- Fatigue

Thesis Number

T 10030

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Electronic OCLC #