Difference in parameters among three estimating methods when the extreme value statistical analysis was applied to corrosion problems in chemical process plants.

Abstract. A previous application of extreme-value statistics to the first, second and third largest geomagnetic storms per solar cycle for nine solar cycles is extended to fourteen solar cycles (1844–1993). The intensity of a geomagnetic storm is measured by the magnitude of the daily aa index, rather than the half-daily aa index used previously. Values of the conventional aa index (1868–1993), supplemented by the Helsinki Ak index (1844–1880), provide an almost continuous, and largely homogeneous, daily measure of geomagnetic activity over an interval of 150 years. As in the earlier investigation, analytic expressions giving the probabilities of the three greatest storms (extreme values) per solar cycle, as continuous functions of storm magnitude (aa), are obtained by least-squares fitting of the observations to the appropriate theoretical extreme-value probability functions. These expressions are used to obtain the statistical characteristics of the extreme values; namely, the mode, median, mean, standard deviation and relative dispersion. Since the Ak index may not provide an entirely homogeneous extension of the aa index, the statistical analysis is performed separately for twelve solar cycles (1868–1993), as well as nine solar cycles (1868–1967). The results are utilized to determine the expected ranges of the extreme values as a function of the number of solar cycles. For fourteen solar cycles, the expected ranges of the daily aa index for the first, second and third largest geomagnetic storms per solar cycle decrease monotonically in magnitude, contrary to the situation for the half-daily aa index over nine solar cycles. The observed range of the first extreme daily aa index for fourteen solar cycles is 159–352 nT and for twelve solar cycles is 215–352 nT. In a group of 100 solar cycles the expected ranges are expanded to 137–539 and 177–511 nT, which represent increases of 108% and 144% in the respective ranges. Thus there is at least a 99% probability that the daily aa index will satisfy the condition aa < 550 for the largest geomagnetic storm in the next 100 solar cycles. The statistical analysis is used to infer that remarkable conjugate auroral observations on the night of 16 September 1770, which were recorded during the first voyage of Captain Cook to Australia, occurred during an intense geomagnetic storm.

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Application of Extreme Value Statistical Analysis to Distribution of Peening Marks Obtained by Water Jet Peening

Proceedings of the 1992 Annual Meeting of JSME/MMD ◽

10.1299/jsmezairiki.2002.0_485 ◽

2002 ◽

Vol 2002 (0) ◽

pp. 485-486

Author(s):

Inami KAZUNORI ◽

Toshihiko YOSHIMURA ◽

Ren MORINAKA ◽

Noboru SAITO

Keyword(s):

Statistical Analysis ◽

Extreme Value ◽

Water Jet

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Application of Extreme Value Statistical Analysis to Estimation of Corrosion Rate of Aluminum Alloys

Corrosion engineering digest ◽

10.3323/jcorr1974.32.1_47 ◽

1983 ◽

Vol 32 (1) ◽

pp. 47-52

Author(s):

Zen-ichi Tanabe

Keyword(s):

Statistical Analysis ◽

Aluminum Alloys ◽

Corrosion Rate ◽

Extreme Value

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Factory Manufactured Modular Construction of Process Plants

10.3233/atde210039 ◽

2021 ◽

Author(s):

Paul Wrigley ◽

Paul Wood ◽

Sam O’Neill ◽

Richard Hall ◽

Daniel Robertson

Keyword(s):

Literature Review ◽

Design Process ◽

Chemical Process ◽

Research Area ◽

Small Scale ◽

Plant Design ◽

Modular Construction ◽

Assembly Design ◽

Process Plant ◽

Process Plants

Off-Site Modular Construction (OSMC) research has been a growing research area over the past two decades because of low productivity in construction. Tools are superior in factories and productivity is much higher compared to a stick built site. This has spawned the development small, factory built, rapidly deployable and flexible process plants to take advantage of the gains in OSMC productivity. Chemical process plant research is studying fast, automated design and configuration. In this paper, a literature review was performed on modular factory manufactured process plants. The literature review found that moving to small scale OSMC plant systems could enable cost and schedule savings and months of design time compared to the previous on-site assembly design. It was also found that while automation has been applied in earlier stages of the plant design process, a layout optimisation methodology has not been applied to small OSMC process plants. The paper then proposes to utilise a mathematical layout optimisation model to help design and construct modular process plants and considers how this may fit into the process plant design process, as well as considering the transport requirements for modules.

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Seismic Fragility Analysis of a Coupled Tank-Piping System based on Artificial Ground Motions and Surrogate Modeling

10.31224/osf.io/qf9ep ◽

2020 ◽

Author(s):

Giuseppe Abbiati ◽

Marco Broccardo ◽

Rocco di Filippo ◽

Bozidar Stojadinovic ◽

Oreste S. Bursi

Keyword(s):

Risk Assessment ◽

Earthquake Engineering ◽

Chemical Process ◽

Computational Cost ◽

System Level ◽

Process Equipment ◽

Piping System ◽

Component Level ◽

Process Plants ◽

Level Model

The catastrophic consequences of recent NaTech events triggered by earthquakes highlighted the inadequacy of standard approaches to seismic risk assessment of chemical process plants. To date, the risk assessment of such facilities mainly relies on historical data and focuses on uncoupled process components. As a consequence, the dynamic interaction between process equipment is neglected. In response to this gap, researchers started a progressive integration of the Pacific Earthquake Engineering Research Center (PEER) Performance-Based Earthquake Engineering (PBEE) risk assessment framework. However, a few limitations still prevent a systematic implementation of this framework to chemical process plants. The most significant are: i) the computational cost of system-level simulations accounting for coupling between process equipment; ii) the experimental cost for component-level model validation; iii) a reduced number of hazard-consistent site-specific ground motion records for time history analyses.In response to these challenges, this paper proposes a recently developed uncertainty quantification-based framework to perform seismic fragility assessments of chemical process plants. The framework employs three key elements: i) a stochastic ground-motion model to supplement scarcity of real records; ii) surrogate modeling to reduce the computational cost of system-level simulations; iii) a component-level model validation based on cost-effective hybrid simulation tests. In order to demonstrate the potential of the framework, two fragility functions are computed for a pipe elbow of a coupled tank-piping system.

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