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    Interval Predictor Model for the Survival Signature Using Monotone Radial Basis Functions 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 003:;page 04024034-1
    Author(s): Jasper Behrensdorf; Matteo Broggi; Michael Beer
    Publisher: American Society of Civil Engineers
    Abstract: This research describes a novel method for approximating the survival signature for very large systems. In recent years, the survival signature has emerged as a capable tool for the reliability analysis of critical ...
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    Estimation of Response Expectation Bounds under Parametric P-Boxes by Combining Bayesian Global Optimization with Unscented Transform 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 002:;page 04024017-1
    Author(s): Chen Ding; Chao Dang; Matteo Broggi; Michael Beer
    Publisher: ASCE
    Abstract: In engineering analysis, propagating parametric probability boxes (p-boxes) remains a challenge because a computationally expensive nested solution scheme is involved. To tackle this challenge, this paper proposes a novel ...
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    Bayesian Model Updating in Time Domain with Metamodel-Based Reliability Method 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 007 ):;issue: 003:;page 04021030-1
    Author(s): Masaru Kitahara; Sifeng Bi; Matteo Broggi; Michael Beer
    Publisher: ASCE
    Abstract: In this study, a two-step approximate Bayesian computation (ABC) updating framework using dynamic response data is developed. In this framework, the Euclidian and Bhattacharyya distances are utilized as uncertainty ...
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    Interval Fields for Geotechnical Engineering Uncertainty Analysis under Limited Data 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2025:;Volume ( 011 ):;issue: 002:;page 04025004-1
    Author(s): Chengxin Feng; Matteo Broggi; Yue Hu; Matthias G. R. Faes; Michael Beer
    Publisher: American Society of Civil Engineers
    Abstract: Spatial uncertainty is a critical challenge in many engineering fields. To date, probabilistic methods have been applied to describe the uncertainty of engineering parameters with considerable achievements. However, they ...
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    DSpace software copyright © 2002-2015  DuraSpace
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