Test Encoding for Extreme Response Compaction

2009 ◽  
Author(s):  
Michael A. Kochte ◽  
Stefan Holst ◽  
Melanie Elm ◽  
Hans-Joachim Wunderlich
Keyword(s):  
Extreme Response

New Evidence on the Construct Validity of the ASI-3 and the Dimensional Conceptualization of Trait Anxiety Sensitivity From IRT Modeling

2017 ◽  
Vol 33 (3) ◽  
pp. 181-189 ◽  
Author(s):  
Christoph J. Kemper ◽  
Michael Hock
Keyword(s):  
Construct Validity ◽  
Anxiety Sensitivity ◽  
Latent Class ◽  
Dimensional Structure ◽  
Sensitivity Index ◽  
Response Scale ◽  
Established Risk Factor ◽  
Irt Models ◽  
Level Data ◽  
Extreme Response

Abstract. Anxiety Sensitivity (AS) denotes the tendency to fear anxiety-related sensations. Trait AS is an established risk factor for anxiety pathology. The Anxiety Sensitivity Index-3 (ASI-3) is a widely used measure of AS and its three most robust dimensions with well-established construct validity. At present, the dimensional conceptualization of AS, and thus, the construct validity of the ASI-3 is challenged. A latent class structure with two distinct and qualitatively different forms, an adaptive form (normative AS) and a maladaptive form (AS taxon, predisposing for anxiety pathology) was postulated. Item Response Theory (IRT) models were applied to item-level data of the ASI-3 in an attempt to replicate previous findings in a large nonclinical sample (N = 2,603) and to examine possible interpretations for the latent discontinuity observed. Two latent classes with a pattern of distinct responses to ASI-3 items were found. However, classes were indicative of participant’s differential use of the response scale (midpoint and extreme response style) rather than differing in AS content (adaptive and maladaptive AS forms). A dimensional structure of AS and the construct validity of the ASI-3 was supported.

Efficient Analysis of a Catenary Riser

2006 ◽  
Author(s):  
Elizabeth Passano ◽  
Carl M. Larsen
Keyword(s):  
Operating Conditions ◽  
Stochastic Simulations ◽  
Worst Case ◽  
Nonlinear Structure ◽  
Tension Response ◽  
Extreme Response ◽  
Analysis Strategies ◽  
Low Tension ◽  
Term Response

The paper deals with the challenge of predicting the extreme response of catenary risers, a topic of both industry and academic interest. Large heave motions introduced at the upper end of a catenary riser can lead to compression and large bending moments in the region immediately above the touch down area. In the worst case, dynamic beam buckling may occur. The focus of the paper will be on understanding the riser behaviour in extreme, low-tension response and in establishing suitable analysis strategies to predict the extreme response. Results from long nonlinear stochastic simulations of many sea states with varying environmental and operating conditions may be combined to describe the long-term response of a nonlinear structure such as a catenary riser. However, this theoretically straight-forward approach is very demanding computationally and ways to limit the extent of nonlinear stochastic simulations are therefore sought. The usefulness of simpler methods such as regular wave analysis to improve understanding of the physical behaviour and to aid in concentrating the nonlinear simulations to where they are most useful, will be demonstrated.

Extreme Response Prediction for Fixed Offshore Structures by Monte Carlo Time Simulation Technique

2016 ◽  
Author(s):  
M. K. Abu Husain ◽  
N. I. Mohd Zaki ◽  
M. B. Johari ◽  
G. Najafian
Keyword(s):  
Monte Carlo ◽  
Statistical Properties ◽  
Simulation Technique ◽  
Random Wave ◽  
Wave Loading ◽  
Offshore Structure ◽  
Sampling Variability ◽  
Time Simulation ◽  
Wide Range ◽  
Extreme Response

For an offshore structure, wind, wave, current, tide, ice and gravitational forces are all important sources of loading which exhibit a high degree of statistical uncertainty. The capability to predict the probability distribution of the response extreme values during the service life of the structure is essential for safe and economical design of these structures. Many different techniques have been introduced for evaluation of statistical properties of response. In each case, sea-states are characterised by an appropriate water surface elevation spectrum, covering a wide range of frequencies. In reality, the most versatile and reliable technique for predicting the statistical properties of the response of an offshore structure to random wave loading is the time domain simulation technique. To this end, conventional time simulation (CTS) procedure or commonly called Monte Carlo time simulation method is the best known technique for predicting the short-term and long-term statistical properties of the response of an offshore structure to random wave loading due to its capability of accounting for various nonlinearities. However, this technique requires very long simulations in order to reduce the sampling variability to acceptable levels. In this paper, the effect of sampling variability of a Monte Carlo technique is investigated.

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