scholarly journals Operational Life Estimation of Carbon Steel Heat Exchanger with Cooling Water based on Extreme Value Analysis

1994 ◽  
Vol 43 (11) ◽  
pp. 624-631 ◽  
Author(s):  
Masao Nakahara ◽  
Tetsuo Shoji
Keyword(s):  
Heat Exchanger ◽  
Carbon Steel ◽  
Cooling Water ◽  
Extreme Value ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Life Estimation ◽  
Operational Life ◽  
Water Based ◽  
Steel Heat

Extreme Value Analysis of Heat Exchanger Tube Inspection Data

2006 ◽  
Author(s):  
W. David Wang
Keyword(s):  
Heat Exchanger ◽  
Sample Size ◽  
Heat Exchangers ◽  
Extreme Value ◽  
American Petroleum Institute ◽  
Extreme Value Analysis ◽  
Test Cases ◽  
Petrochemical Plant ◽  
Value Analysis ◽  
Inspection Data

This paper presents a statistical extreme value analysis (EVA) method for assessment of the minimum remaining thickness of tubes in industrial heat exchangers, including air-cooled heat exchangers and shell-and-tube heat exchangers. Five test cases are used to evaluate the effectiveness of the EVA method developed in this work. In each case, real inspection data from heat exchangers in petroleum refinery and petrochemical plant are analyzed, and the results discussed. The effectiveness of the EVA method is then evaluated per the Inspection Effectiveness definition used by American Petroleum Institute (API) for Risk-Based Inspection (RBI), so that the EVA method and results can be easily incorporated in API RBI assessment. It is found through these test cases that the most ideal sample size seems to be 20–30 tubes, regardless of the number of tubes in the heat exchanger. At that sample size, A, B, C and D levels of API RBI inspection effectiveness can be achieved by using the lower bound value of the 99%, 95%, 90%, and 80% confidence intervals, respectively.

Modeling European hot spells using extreme value analysis

2014 ◽  
Vol 58 (3) ◽  
pp. 193-207 ◽  
Author(s):  
C Photiadou ◽  
MR Jones ◽  
D Keellings ◽  
CF Dewes
Keyword(s):  
Extreme Value ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Hot Spells

scholarly journals Threshold selection in univariate extreme value analysis

Extremes ◽  
2021 ◽  
Author(s):  
Laura Fee Schneider ◽  
Andrea Krajina ◽  
Tatyana Krivobokova
Keyword(s):  
Mean Squared Error ◽  
Extreme Value ◽  
Hill Estimator ◽  
Small Samples ◽  
Extreme Value Analysis ◽  
Threshold Selection ◽  
Value Analysis ◽  
Wide Range ◽  
Asymptotic Mean Squared Error ◽  
The Hill

AbstractThreshold selection plays a key role in various aspects of statistical inference of rare events. In this work, two new threshold selection methods are introduced. The first approach measures the fit of the exponential approximation above a threshold and achieves good performance in small samples. The second method smoothly estimates the asymptotic mean squared error of the Hill estimator and performs consistently well over a wide range of processes. Both methods are analyzed theoretically, compared to existing procedures in an extensive simulation study and applied to a dataset of financial losses, where the underlying extreme value index is assumed to vary over time.

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