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Related Concept Videos

Design Consideration01:22

Design Consideration

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Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
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Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Constraints and Statical Determinacy01:26

Constraints and Statical Determinacy

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In structural engineering, the equilibrium of a system is not only determined by its equations of equilibrium but also with the help of constraints. Constraints refer to restrictions on the motion of a system. The proper combinations of constraints can minimize the total number of constraints needed to maintain a system in mechanical equilibrium. When this happens, the system is said to be statically determinate. For such systems, the unknown reaction supports can be estimated using equilibrium...
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Yield Criteria for Ductile Materials under Plane Stress01:25

Yield Criteria for Ductile Materials under Plane Stress

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In designing structural elements and machine parts using ductile materials, it is crucial to ensure that these components withstand applied stresses without yielding. Yielding is initially determined through a tensile test, which evaluates the material's response to uniaxial stress. However, tensile stress is insufficient when components face biaxial or plane stress conditions This condition requires advanced criteria to predict failure.
The Maximum Shearing Stress Criterion, also known as...
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Prismatic Beams: Problem Solving01:15

Prismatic Beams: Problem Solving

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In the design of a supported timber beam subjected to a distributed load, both the beam's physical dimensions and the timber's characteristics, such as its grade and species, are critical. These factors determine the allowable stress values, which are crucial for calculating the necessary beam depth to ensure structural integrity and safety.
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Multimachine Stability01:25

Multimachine Stability

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
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A simplified reliability-based design method for multiple design variables considering different limit states.

Yanbing Fang1, Jingxuan Zhang1, Kun Feng1

  • 1Key Laboratory of Transportation Tunnel Engineering, Ministry of Education, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China.

Heliyon
|June 7, 2024
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Summary
This summary is machine-generated.

This study introduces a generalized reliability model and a simplified method for reliability-based design (RBD) with multiple variables. Results highlight the importance of considering design variable variations and unexpected outcomes in RBD.

Keywords:
Coefficient of variationMultiple design variablesRandom variableReliability index approachReliability-based design

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Area of Science:

  • Engineering
  • Reliability Engineering
  • Structural Design

Background:

  • Traditional reliability-based design (RBD) methods may not fully capture complex engineering scenarios.
  • The influence of parameter properties and negative reliability indices requires further investigation.
  • Understanding the behavior of multiple design variables in reliability analysis is crucial.

Purpose of the Study:

  • To establish a generalized reliability model for the reliability index approach (RIA).
  • To develop a simplified method for solving multi-variable RBD problems.
  • To investigate the impact of design variable uncertainties and reliability requirements on RBD outcomes.

Main Methods:

  • Development of a generalized reliability model incorporating objective, constraint, and judgment functions.
  • Translation of RBD problems into nonlinear equations solvable by a simplified Newton iteration and finite difference method (FDM).
  • Numerical verification of the proposed reliability approach and determination of FDM incremental step size.

Main Results:

  • The proposed reliability approach is efficient for solving RBD problems.
  • Variations in design variables, including manufacturing and operational uncertainties, significantly impact RBD.
  • Design values may not intuitively correlate with coefficient of variation (CoV) or increasing reliability requirements in multi-variable problems.

Conclusions:

  • Design variable variations are critical and should not be overlooked in RBD.
  • The non-intuitive relationship between design values, CoV, and reliability requirements in multi-variable problems necessitates careful, problem-specific analysis.
  • Awareness of these systematic complexities is essential for accurate engineering design.