Differential Burst Pressure of Marine Pipelines as an Independent Layer of Protection

2011 ◽  
Author(s):  
Sirous F. Yasseri ◽  
R. B. Mahani
Keyword(s):  
Burst Pressure ◽  
Offshore Pipelines ◽  
First Order ◽  
Reliability Method ◽  
Structural Fuse ◽  
Environmentally Sensitive ◽  
Protection Layer ◽  
Pressure Surge ◽  
Pipeline Design

Offshore pipelines and risers are designed to different codes leading to different reliability targets, and different wall thicknesses. Pipeline design codes also differentiate between areas where people are present and those with no population or less environmentally sensitive. As a result, the offshore section of the pipeline (with “thinner walls”) could be considered to work as a structural fuse during an unforeseen pressure surge; if the pipeline bursts first, then the occupants of platform would be exposed to less risk than if the riser or pipeline in the vicinity of the platform were to fail. This implies that differential burst pressure could act as an Independent Protection Layer (IPL). This paper explores conditions that sections of a pipeline must satisfy in order to be considered as an IPL. A first order reliability method is outlined for determining the required target reliability. The application of this approach is described in a case study.

scholarly journals Reliability-Based Multidisciplinary Design Optimization under Correlated Uncertainties

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Huanwei Xu ◽  
Xin Wang ◽  
Wei Li ◽  
Mufeng Li ◽  
Suichuan Zhang ◽  
...  
Keyword(s):  
Design Optimization ◽  
Set Theory ◽  
Multidisciplinary Design Optimization ◽  
Reliability Assessment ◽  
Multidisciplinary Design ◽  
Sequential Optimization ◽  
Engineering System ◽  
First Order ◽  
Reliability Method

Complex mechanical system is usually composed of several subsystems, which are often coupled with each other. Reliability-based multidisciplinary design optimization (RBMDO) is an efficient method to design such complex system under uncertainties. However, the present RBMDO methods ignored the correlations between uncertainties. In this paper, through combining the ellipsoidal set theory and first-order reliability method (FORM) for multidisciplinary design optimization (MDO), characteristics of correlated uncertainties are investigated. Furthermore, to improve computational efficiency, the sequential optimization and reliability assessment (SORA) strategy is utilized to obtain the optimization result. Both a mathematical example and a case study of an engineering system are provided to illustrate the feasibility and validity of the proposed method.

A Probabilistic Model-Based Prognostics Using Meshfree Modeling: A Case Study on Fatigue Life of a Cantilever Beam

2016 ◽  
Author(s):  
Haileyesus B. Endeshaw ◽  
Fisseha M. Alemayehu ◽  
Stephen Ekwaro-Osire ◽  
João Paulo Dias
Keyword(s):  
Monte Carlo ◽  
Fatigue Life ◽  
Monte Carlo Method ◽  
Cantilever Beam ◽  
Research Question ◽  
Computational Framework ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method

Accurate prediction of remaining useful life (RUL) will improve reliability and reduce maintenance cost. Therefore, prognostics is essential to predict the RUL of systems and components. However, a big issue of uncertainty prevails in prognostics due to the fact that prognostics pertains to prediction of future state, which is affected by uncertainty. While various researches have been done in areas of prognostics and health management, they lack to perform RUL predictions efficiently. There is a need for an efficient comprehensive framework for quantifying uncertainty in prognostics. The research question to this study is: can meshfree modeling be used in probabilistic prognostics to efficiently predict RUL? The specific aims developed to answer the research question are (1) develop a computational framework for probabilistic prognostics of a fatigue life of a component using meshfree modeling, and (2) perform case study analyses on fatigue life of a cantilever beam. A probabilistic framework was developed that efficiently predicts the RUL of a component using a combination of the meshfree method known as local radial point interpolation method and a fatigue degradation model. Loading uncertainty is quantified and employed in the framework. The computational framework is easily customizable and computationally efficient and, hence, aids in decision making and fault mitigation. As a case study, the RUL of a cantilever beam under plane stress subjected to fatigue loadings was analyzed. Uncertainties in the RUL were quantified in terms of probability density functions, cumulative distribution functions, and 98% bounds of confidence interval. Sensitivity analysis was studied and computational efficiency of the framework was also investigated using first order reliability method and Monte Carlo method. When compared to the Monte Carlo method, first order reliability method provides reasonably good results and is found to be computationally more efficient.

Dual systems for all: Higher-order, role-based relational reasoning as a uniquely derived feature of human cognition

2019 ◽  
Vol 42 ◽  
Author(s):  
Daniel J. Povinelli ◽  
Gabrielle C. Glorioso ◽  
Shannon L. Kuznar ◽  
Mateja Pavlic
Keyword(s):  
Temporal Reasoning ◽  
Higher Order ◽  
Important Case ◽  
Human Cognition ◽  
Relational Reasoning ◽  
Dual Systems ◽  
First Order ◽  
Reasoning System ◽  
Role Based

Abstract Hoerl and McCormack demonstrate that although animals possess a sophisticated temporal updating system, there is no evidence that they also possess a temporal reasoning system. This important case study is directly related to the broader claim that although animals are manifestly capable of first-order (perceptually-based) relational reasoning, they lack the capacity for higher-order, role-based relational reasoning. We argue this distinction applies to all domains of cognition.

scholarly journals Nucleation is more than critical: A case study of the electroweak phase transition in the NMSSM

2021 ◽  
Vol 2021 (3) ◽  
Author(s):  
Sebastian Baum ◽  
Marcela Carena ◽  
Nausheen R. Shah ◽  
Carlos E. M. Wagner ◽  
Yikun Wang
Keyword(s):  
Phase Transition ◽  
Parameter Space ◽  
Local Minima ◽  
Critical Temperatures ◽  
Electroweak Phase Transition ◽  
First Order ◽  
Vacuum Structure ◽  
The Universe ◽  
Scalar Sector

Abstract Electroweak baryogenesis is an attractive mechanism to generate the baryon asymmetry of the Universe via a strong first order electroweak phase transition. We compare the phase transition patterns suggested by the vacuum structure at the critical temperatures, at which local minima are degenerate, with those obtained from computing the probability for nucleation via tunneling through the barrier separating local minima. Heuristically, nucleation becomes difficult if the barrier between the local minima is too high, or if the distance (in field space) between the minima is too large. As an example of a model exhibiting such behavior, we study the Next-to-Minimal Supersymmetric Standard Model, whose scalar sector contains two SU(2) doublets and one gauge singlet. We find that the calculation of the nucleation probabilities prefers different regions of parameter space for a strong first order electroweak phase transition than the calculation based solely on the critical temperatures. Our results demonstrate that analyzing only the vacuum structure via the critical temperatures can provide a misleading picture of the phase transition patterns, and, in turn, of the parameter space suitable for electroweak baryogenesis.

Some Important Issues on First-Order Reliability Analysis With Nonprobabilistic Convex Models

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
C. Jiang ◽  
G. Y. Lu ◽  
X. Han ◽  
R. G. Bi
Keyword(s):  
Reliability Analysis ◽  
Reliability Index ◽  
Probability Model ◽  
Mean Value ◽  
Convex Model ◽  
First Order ◽  
Reliability Method ◽  
Complex Engineering ◽  
Mean Value Method ◽  
Form Type

Compared with the probability model, the convex model approach only requires the bound information on the uncertainty, and can make it possible to conduct the reliability analysis for many complex engineering problems with limited samples. Presently, by introducing the well-established techniques in probability-based reliability analysis, some methods have been successfully developed for convex model reliability. This paper aims to reveal some different phenomena and furthermore some severe paradoxes when extending the widely used first-order reliability method (FORM) into the convex model problems, and whereby provide some useful suggestions and guidelines for convex-model-based reliability analysis. Two FORM-type approximations, namely, the mean-value method and the design-point method, are formulated to efficiently compute the nonprobabilistic reliability index. A comparison is then conducted between these two methods, and some important phenomena different from the traditional FORMs are summarized. The nonprobabilistic reliability index is also extended to treat the system reliability, and some unexpected paradoxes are found through two numerical examples.

scholarly journals Macroscopic and Multi-Scale Models for Multi-Class Vehicular Dynamics with Uneven Space Occupancy: A Case Study

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 102
Author(s):  
Maya Briani ◽  
Emiliano Cristiani ◽  
Paolo Ranut
Keyword(s):  
Road Network ◽  
Real Data ◽  
Second Order ◽  
Heavy Vehicles ◽  
First Order ◽  
Multi Scale ◽  
Stop And Go ◽  
Scale Models ◽  
Road Space

In this paper, we propose two models describing the dynamics of heavy and light vehicles on a road network, taking into account the interactions between the two classes. The models are tailored for two-lane highways where heavy vehicles cannot overtake. This means that heavy vehicles cannot saturate the whole road space, while light vehicles can. In these conditions, the creeping phenomenon can appear, i.e., one class of vehicles can proceed even if the other class has reached the maximal density. The first model we propose couples two first-order macroscopic LWR models, while the second model couples a second-order microscopic follow-the-leader model with a first-order macroscopic LWR model. Numerical results show that both models are able to catch some second-order (inertial) phenomena such as stop and go waves. Models are calibrated by means of real data measured by fixed sensors placed along the A4 Italian highway Trieste–Venice and its branches, provided by Autovie Venete S.p.A.

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