State-of-the-Art for Assessing Earthquake Hazards in the United States. Report 18. Errors in Probabilistic Seismic Hazard Analysis.

Abstract

After a period of fast development, procedures for the probabilistic quantification of seismic hazard have reached a state of relative maturity. Standard methods usually differ only by secondary characteristics. In spite of this operational stability, estimates of seismic hazard that are produced by different algorithms depend on and are often very sensitive to the form of the mathematical model and the choice of some of the parameters. It is important to recognize this sensitivity in order to avoid placing excessive confidence in numerical estimates of hazard, especially in the case of rare events. Errors may originate from conscious simplification of the mathematical representation (e.g., from the use of a Poisson model of earthquake occurrences as opposed to a physically more attractive point process with spatial and temporal memory), from limited statistical information, or from faulty judgment (expert errors). The purpose of this report is to review different types and sources of errors and to assess their impact on calculated seismic hazard. In the available literature, no generally accepted procedure exists to systematically deal with uncertainty on seismic hazard and, most frequently in practice, elusive arguments of conservatism are used to avoid direct confrontation with the problem. Scientific studies are sparse and fragmentary; they typically focus on narrow aspects of the problem, use different statistical techniques, and report results in different formats. Accordingly, an effort is made here to coordinate these results and provide a unified picture.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1982
Accession Number
ADA110619

Entities

People

  • Daniele Veneziano

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Civil Engineering
  • Computational Science
  • Data Science
  • Earthquake Engineering
  • Engineers
  • Estimators
  • Information Science
  • Knowledge Management
  • Mathematical Models
  • Mechanics
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistical Algorithms
  • Surveys
  • United States

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