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Related papers: Buffered environmental contours

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Classical environmental contours are used in structural design in order to obtain upper bounds on the failure probabilities of a large class of designs. Buffered environmental contours serve the same purpose, but with respect to the…

Optimization and Control · Mathematics 2020-09-09 Kristina Rognlien Dahl , Arne Bang Huseby

Environmental contours are tools frequently used in the early design of marine structures. They provide a description of critical design conditions and serve as a means for simplifying expensive long-term response calculations. Here, we…

Probability · Mathematics 2023-09-04 Åsmund Hausken Sande

Environmental contours are used in structural reliability analysis of marine and coastal structures as an approximate means to locate the boundary of the distribution of environmental variables, and hence sets of environmental conditions…

An offshore wind turbine needs to withstand the environmental loads, which can be expected during its life time. Consequently, designers must define loads based on extreme environmental conditions to verify structural integrity. The…

Methodology · Statistics 2017-10-20 Andreas F. Haselsteiner , Jan-Hendrik Ohlendorf , Klaus-Dieter Thoben

We propose two structural models for stochastic losses given default which allow to model the credit losses of a portfolio of defaultable financial instruments. The credit losses are integrated into a structural model of default events…

Risk Management · Quantitative Finance 2015-03-20 Simone Farinelli , Mykhaylo Shkolnikov

Design and operation of complex engineering systems rely on reliability optimization. Such optimization requires us to account for uncertainties expressed in terms of compli-cated, high-dimensional probability distributions, for which only…

Optimization and Control · Mathematics 2021-09-22 Ji-Eun Byun , Johannes O. Royset

The probabilistic design of offshore wind turbines aims to ensure structural safety in a cost-effective way. This involves conducting structural reliability assessments for different design options and considering different structural…

Applications · Statistics 2024-08-06 Hong Wang , Odin Gramstad , Styfen Schär , Stefano Marelli , Erik Vanem

Fault tree analysis is a technique widely used in risk and reliability analysis of complex engineering systems given its deductive nature and relatively simple interpretation. In a fault tree, events are usually represented by a binary…

Other Computer Science · Computer Science 2022-04-26 Gabriel San Martin Silva , Tarannom Parhizkar , Enrique Lopez Droguett

Environmental contours are an established method in probabilistic engineering design, especially in ocean engineering. The contours help engineers to select the environmental states which are appropriate for structural design calculations.…

Gradients and subgradients are central to optimization and sensitivity analysis of buffered failure probabilities. We furnish a characterization of subgradients based on subdifferential calculus in the case of finite probability…

Optimization and Control · Mathematics 2021-10-26 Johannes O. Royset , Ji-Eun Byun

Coastal flooding drives considerable risks to many communities, but projections of future flood risks are deeply uncertain. The paucity of observations of extreme events often motivates the use of statistical approaches to model the…

Applications · Statistics 2018-08-01 Tony E. Wong , Alexandra Klufas , Vivek Srikrishnan , Klaus Keller

We consider a multivariate default system where random environmental information is available. We study the dynamics of the system in a general setting and adopt the point of view of change of probability measures. We also make a link with…

Risk Management · Quantitative Finance 2016-11-21 Nicole El Karoui , Monique Jeanblanc , Ying Jiao

Fluvial floods drive severe risk to riverine communities. There is a strong evidence of increasing flood hazards in many regions around the world. The choice of methods and assumptions used in flood hazard estimates can impact the design of…

Flooding is one of the most destructive and costly natural disasters, and climate changes would further increase risks globally. This work presents a novel multimodal machine learning approach for multi-year global flood risk prediction,…

Machine Learning · Computer Science 2023-01-31 Cynthia Zeng , Dimitris Bertsimas

A new concept called multilevel contours is introduced through this article by the author. Theorems on contours constructed on a bundle of complex planes are stated and proved. Multilevel contours can transport information from one complex…

Complex Variables · Mathematics 2021-07-23 Arni S. R. Srinivasa Rao

Current approaches to design flood-sensitive infrastructure typically assume a stationary rainfall distribution and neglect many uncertainties. These assumptions are inconsistent with observations that suggest intensifying extreme…

Applications · Statistics 2022-01-11 Sanjib Sharma , Ben Seiyon Lee , Robert E. Nicholas , Klaus Keller

Structured prediction problems are one of the fundamental tools in machine learning. In order to facilitate algorithm development for their numerical solution, we collect in one place a large number of datasets in easy to read formats for a…

The dynamics of flooding are primarily influenced by the shape, height, and roughness (friction) of the underlying topography. For this reason, mechanisms to mitigate floods frequently employ structural measures that either modify…

Optimization and Control · Mathematics 2019-04-04 Byron Tasseff , Russell Bent , Pascal Van Hentenryck

Modern software systems provide many configuration options which significantly influence their non-functional properties. To understand and predict the effect of configuration options, several sampling and learning strategies have been…

Machine Learning · Statistics 2017-09-08 Pooyan Jamshidi , Norbert Siegmund , Miguel Velez , Christian Kästner , Akshay Patel , Yuvraj Agarwal

The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions…

Machine Learning · Computer Science 2010-06-29 Shankar Vembu
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