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    ASME ( American Society of Mechanical Engineers )

    Description: The American Society of Mechanical Engineers (ASME) is a professional association that, in its own words, "promotes the art, science, and practice of multidisciplinary engineering and allied sciences around the globe" via "continuing education, training and professional development, codes and standards, research, conferences and publications, government relations, and other forms of outreach." ASME is thus an engineering society, a standards organization, a research and development organization, a lobbying organization, a provider of training and education, and a nonprofit organization. Founded as an engineering society focused on mechanical engineering in North America, ASME is today multidisciplinary and global.

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    A Computational Framework for Human-Centric Vehicular Crashworthiness Design and Decision-Making Under Uncertainty 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 002:;page 21206-1
    Author(s): Nellippallil, Anand Balu; Berthelson, Parker R.; Peterson, Luke; Prabhu, Raj K.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Government agencies, globally, strive to minimize the likelihood and frequency of human death and severe injury on road transport systems. From an engineering design standpoint, the minimization of these road accident ...
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    Proposing an Uncertainty Management Framework to Implement the Evidence Theory for Vehicle Crash Applications 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 002:;page 21204-1
    Author(s): Jehle, Jonas Siegfried; Lange, Volker Andreas; Gerdts, Matthias
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The purpose of this work is to enable the use of the Dempster–Shafer evidence theory (ET) for uncertainty propagation on computationally expensive automotive crash simulations. This is necessary as the results of these ...
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    Calibration and Validation of Multiscale Model for Ultimate Strength Prediction of Composite Laminates Under Uncertainty 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 002:;page 21205-1
    Author(s): Bhattacharyya, Rudraprasad; Mahadevan, Sankaran
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A methodology to account for the effect of epistemic uncertainty (regarding model parameters) on the strength prediction of carbon fiber reinforced polymer (CFRP) composite laminates is presented. A three-dimensional ...
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    Survey Use to Validate Engineering Methodology and Enhance System Safety 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 002:;page 24501-1
    Author(s): Corrado, Jonathan K.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Surveys and the resulting data provide powerful insights to an item or concept being assessed. Not only do they garner feedback that can be used to enhance the item, but, in the instance of this article, they can enhance ...
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    Comparison of the HAZOP, FMEA, FRAM, and STPA Methods for the Hazard Analysis of Automatic Emergency Brake Systems 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2021:;volume( 008 ):;issue: 003:;page 31104-1
    Author(s): Sun, Liangliang; Li, Yan-Fu; Zio, Enrico
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As autonomous vehicle (AV) intelligence for controllability continues to develop, involving increasingly complex and interconnected systems, the maturity level of AV technology increasingly depends on the systems reliability ...
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    Systematical Collision Avoidance Reliability Analysis and Characterization of Reliable System Operation for Autonomous Navigation Using the Dynamic Window Approach 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 003:;page 31106-1
    Author(s): Torkamani, Elnaz Asghari; Xi, Zhimin
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Dynamic window approach (DWA) is one of the most widely used algorithms for local path planning and autonomous navigation. Although many successful examples have been shown under various operation conditions, to the authors' ...
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    Fatigue Life Prediction of Structures With Interval Uncertainty 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 003:;page 31201-1
    Author(s): Desch, Michael; Modares, Mehdi
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A new method for reliable fatigue life prediction in metal structural components is developed, which quantifies uncertainties using interval variables. Using this crack-initiation-based method, first, the uncertainties in ...
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    Bayesian Calibration of Multiple Coupled Simulation Models for Metal Additive Manufacturing: A Bayesian Network Approach 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2021:;volume( 008 ):;issue: 001:;page 11111-1
    Author(s): Ye, Jiahui; Mahmoudi, Mohamad; Karayagiz, Kubra; Johnson, Luke; Seede, Raiyan; Karaman, Ibrahim; Arroyave, Raymundo; Elwany, Alaa
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Modeling and simulation for additive manufacturing (AM) are critical enablers for understanding process physics, conducting process planning and optimization, and streamlining qualification and certification. It is often ...
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    Multi-Objective Optimization Under Uncertainty of Part Quality in Fused Filament Fabrication 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 001:;page 11112-1
    Author(s): Kapusuzoglu, Berkcan; Nath, Paromita; Sato, Matthew; Mahadevan, Sankaran; Witherell, Paul
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This work presents a data-driven methodology for multi-objective optimization under uncertainty of process parameters in the fused filament fabrication (FFF) process. The proposed approach optimizes the process parameters ...
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    Uncertainty Quantification for Additive Manufacturing Process Improvement: Recent Advances 

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2022:;volume( 008 ):;issue: 001:;page 10801-1
    Author(s): Mahadevan, Sankaran; Nath, Paromita; Hu, Zhen
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper reviews the state of the art in applying uncertainty quantification (UQ) methods to additive manufacturing (AM). Physics-based as well as data-driven models are increasingly being developed and refined in order ...
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