Comparative Probabilistic Initial Bridge Load Rating Model

A model that applies to initial bridge load ratings based on allowable stress, load factor, and load and resistance factor design is presented. The prognostic component calculates bridge load ratings probabilistically considering random variables representative of load and resistance effects. The diagnostic component helps to point out the sensitivity rankings of these input parameters. Monte Carlo simulation and Bayesian networks are the tools employed in this bidirectional model. The model is applied to a beam in a prestressed concrete bridge at the beginning of its service life to demonstrate conclusions related to its applicability as a tool in areas related to bridge design and load rating.

[1]  Brian S. G. E. Sahely,et al.  Diagnosing Upsets in Anaerobic Wastewater Treatment Using Bayesian Belief Networks , 2001 .

[2]  Dan M. Frangopol,et al.  BRIDGE RATING AND RELIABILITY CORRELATION: COMPREHENSIVE STUDY FOR DIFFERENT BRIDGE TYPES , 2004 .

[3]  Christopher G. Gilbertson,et al.  A PROBABILISTIC COMPARISON OF PRESTRESS LOSS METHODS IN PRESTRESSED CONCRETE BEAMS , 2004 .

[4]  Michael P. Wellman,et al.  Real-world applications of Bayesian networks , 1995, CACM.

[5]  Ayman M. Okeil,et al.  LRFD FLEXURAL PROVISIONS FOR PRESTRESSED CONCRETE BRIDGE GIRDERS STRENGTHENED WITH CARBON FIBER-REINFORCED POLYMER LAMINATES , 2002 .

[6]  Richard N. Palmer,et al.  Expert System for Prioritizing the Inspection of Sewers: Knowledge Base Formulation and Evaluation , 2002 .

[7]  Antoine E. Naaman,et al.  RELIABILITY OF PARTIALLY PRESTRESSED BEAMS AT SERVICEABILITY LIMIT STATES , 1982 .

[8]  Michael J. Chajes,et al.  Reliability-Based Load and Resistance Factor Rating Using In-Service Data , 2005 .

[9]  David V. Jáuregui,et al.  Load rating of prestressed concrete girder bridges : Comparative analysis of load factor rating and load and resistance factor rating , 2005 .

[10]  J. G. MacGregor Statistical Analysis of Resistance of Reinforced and Prestressed Concrete Members , 1983 .

[11]  Hojjat Adeli,et al.  Case-Based Reasoning for Converting Working Stress Design-Based Bridge Ratings to Load Factor Design-Based Ratings , 2005 .

[12]  Eric P. Steinberg Probabilistic assessment of prestress loss in pretensioned prestressed concrete , 1995 .

[13]  J. G. Macgregor,et al.  Statistical Descriptions of Strength of Concrete , 1979 .

[14]  Simaan M. AbouRizk,et al.  BELIEF NETWORKS FOR CONSTRUCTION PERFORMANCE DIAGNOSTICS , 1998 .

[15]  Eugene Charniak,et al.  Bayesian Networks without Tears , 1991, AI Mag..

[16]  Andrzej S. Nowak,et al.  CALIBRATION OF LRFD BRIDGE DESIGN CODE , 1999 .

[17]  Mark E. Borsuk,et al.  Integrated approach to total maximum daily load development for Neuse River Estuary using bayesian probability network model (Neu-BERN) , 2003 .