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Related Concept Videos

Factors Affecting Creep01:28

Factors Affecting Creep

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In normal-weight aggregate concrete, the hardened cement paste is the primary contributor to creep, whereas the aggregates, being stiffer than the cement paste, are more resilient to stress-induced deformation. The stiffness of the aggregates is defined by their modulus of elasticity, and the more voluminous they are in the concrete, the less it will creep.
Further, the water/cement ratio is critical, as a lower ratio increases concrete strength, thus reducing creep. The strength of the...
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Effects of Creep01:25

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Creep in concrete, the gradual deformation under prolonged stress, significantly impacts the integrity of structures. For reinforced concrete beams, it can be a vital design consideration, as it increases deflection, sometimes necessitating additional design measures. In columns, especially slender ones under eccentric loads, creep can cause buckling, compromising their stability. However, creep can be beneficial in indeterminate structures by mitigating stresses that arise from shrinkage,...
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Creep in Concrete01:22

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Creep refers to the time-dependent increase in strain under a sustained load, excluding other time-dependent deformations associated with shrinkage, swelling, and thermal expansion in concrete. The primary mechanism behind creep involves the loss of physically adsorbed water from the calcium silicate hydrate within the hydrated cement paste. This process is further exacerbated by concrete's non-linear stress-strain relationship, microcrack development in the interfacial transition zone, and...
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Dynamic Modulus of Elasticity of Concrete01:16

Dynamic Modulus of Elasticity of Concrete

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The dynamic modulus of elasticity assesses how a concrete structure deforms under impact or dynamic loads. It is typically higher than the static modulus of elasticity, measured under slow, steady loading conditions.
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Biasing of Metal-Semiconductor Junctions01:27

Biasing of Metal-Semiconductor Junctions

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Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
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Bending of Material: Problem Solving01:09

Bending of Material: Problem Solving

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In this lesson, determine the ratio of the maximum bending moments applied to two metal pipes, given that both pipes can withstand a maximum stress of 100 MPa. Both pipes have an outer radius of 1.8 cm. Pipe A has an inner radius of 1.5 cm, and Pipe B has an inner radius of 1 cm. The ratio of the maximum bending moment applied to two metallic pipes, each with a different inner and outer radius, is determined by considering their dimensions. The inner radius of the first pipe is 1.5 cm, and for...
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Updated: Aug 13, 2025

A Coupled Experiment-finite Element Modeling Methodology for Assessing High Strain Rate Mechanical Response of Soft Biomaterials
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Modeling and Optimization of Sensitivity and Creep for Multi-Component Sensing Materials.

Gangping Bi1,2,3, Bowen Xiao1,3,4, Yuanchang Lin1,3

  • 1Chongqing Institute of Green Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.

Nanomaterials (Basel, Switzerland)
|January 21, 2023
PubMed
Summary

This study optimized pressure sensor materials using advanced modeling techniques. The results show significantly improved sensitivity and reduced creep, paving the way for better sensor performance.

Keywords:
MLGMWCNTsNSGA-IINiRSMSVRcreepmagnetic fieldsensitivity

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Area of Science:

  • Materials Science
  • Sensor Technology
  • Computational Modeling

Background:

  • High-performance pressure sensors require advanced sensing materials.
  • Sensitivity and creep are critical metrics for sensor performance evaluation.
  • Accurate prediction of material parameter impacts is essential for sensor optimization.

Purpose of the Study:

  • To predict and optimize the sensitivity and creep of pressure sensing materials.
  • To evaluate the impact of nickel (Ni) particle concentration, multiwalled carbon nanotubes (MWCNTs), multilayer graphene (MLG), and magnetic field intensity (B).

Main Methods:

  • Response Surface Methodology (RSM) for sensitivity prediction.
  • Support Vector Regression (SVR) for creep prediction.
  • Non-dominated Sorting Genetic-II Algorithm (NSGA-II) for multi-objective optimization.

Main Results:

  • The SVR model demonstrated superior predictability and accuracy.
  • Optimized conditions yielded an average sensitivity of 0.059 kPa⁻¹ (0-16 kPa) and a creep of 0.0325.
  • Achieved improved sensitivity over a wider pressure range compared to previous studies.

Conclusions:

  • The developed methodology effectively optimizes pressure sensing materials.
  • Simulation and experimental verification showed minimal deviations (0.317% sensitivity, 0.307% creep).
  • The approach is representative for future transducer performance optimization.