Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanical Characteristics of Steel01:18

Mechanical Characteristics of Steel

369
The mechanical characteristics of steel are assessed through various tests that evaluate its strength, toughness, and flexibility. These tests include tension, torsion, impact, bending, and hardness assessments, each providing crucial information about steel's suitability for specific applications.
The tension test is fundamental for determining tensile strength. In this test, a steel specimen is stretched using a gripping device until it breaks. The data collected during this test are used...
369
Yield Criteria for Ductile Materials under Plane Stress01:25

Yield Criteria for Ductile Materials under Plane Stress

126
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...
126
Stress-Strain Diagram01:10

Stress-Strain Diagram

532
A stress-strain diagram is a crucial tool that graphically displays a material's mechanical characteristics. This diagram is derived from a tensile test performed on a carefully prepared cylindrical specimen. The specimen has two gauge marks inscribed on its central part, and the distance between these marks is known as the gauge length. The cylindrical specimen is placed in a testing machine, which applies an increasing centric load. As this load grows, so does the gauge length. This...
532
Measurements of Strain01:27

Measurements of Strain

153
Strain quantifies the deformation of a material under force, typically measured as normal strain, which represents the change in length when compared with the original length. Electrical strain gauges are used for enhanced accuracy. These devices consist of a conductive wire mounted on a paper backing that adheres to the material's surface. These gauges operate on the piezoresistive effect, where the wire's electrical resistance changes in response to mechanical deformation. The strain...
153
Bending of Members Made of Several Materials01:08

Bending of Members Made of Several Materials

132
In analyzing a structural member composed of two different materials with identical cross-sectional areas, it is crucial to understand how their distinct elastic properties affect the member's response under load. The analysis involves assessing stress and strain distributions using the transformed section concept, which accounts for variations in material properties.
Hooke's Law determines stress in each material, stating that stress is proportional to strain but varies due to each...
132

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A‑type potassium channels mediate the inhibitory effect of β‑hydroxybutyrate on CA1 pyramidal neurons in an immature mouse model of kainic acid‑induced status epilepticus.

Epilepsy research·2026
Same author

Regional homogeneity and interhemispheric connectivity alterations in major depressive disorder.

Asian journal of psychiatry·2026
Same author

The effects of rTMS over orbitofrontal cortex on cognitive functions in first-episode schizophrenia.

Psychological medicine·2026
Same author

DrugGPS: Attention-guided multimodal fusion for intelligent exploration of drug-target and drug-disease interactions.

British journal of pharmacology·2026
Same author

Hyper-scanning and hyper-pursuit define eye movement biomarkers of anxiety disorders.

The British journal of psychiatry : the journal of mental science·2026
Same author

Enhanced reactive oxygen species generation via a full-spectrum dual-shell photocatalyst towards effective degradation of emerging contaminants.

Journal of colloid and interface science·2026

Related Experiment Video

Updated: May 15, 2025

Ultrasonic Welding of Thermoplastic Composite Coupons for Mechanical Characterization of Welded Joints through Single Lap Shear Testing
08:40

Ultrasonic Welding of Thermoplastic Composite Coupons for Mechanical Characterization of Welded Joints through Single Lap Shear Testing

Published on: February 11, 2016

11.5K

A Multivariate Linear Regression-Based Ultrasonic Non-Destructive Evaluating Method for Characterizing Weld Tensile

Dazhao Chi1, Ziming Wang1, Haichun Liu2

  • 1State Key Laboratory of Precision Welding & Joining of Materials and Structures, Harbin Institute of Technology, Harbin 150001, China.

Materials (Basel, Switzerland)
|May 14, 2025
PubMed
Summary

This study introduces an ultrasonic method to assess weld tensile strength non-destructively. The developed model achieved 76.3% accuracy, offering a promising alternative to destructive testing for in-service structures.

Keywords:
non-destructive testingtensile strengthultrasonic testingweld

More Related Videos

Ultrasonic Fatigue Testing in the Tension-Compression Mode
06:54

Ultrasonic Fatigue Testing in the Tension-Compression Mode

Published on: March 7, 2018

10.6K
Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

588

Related Experiment Videos

Last Updated: May 15, 2025

Ultrasonic Welding of Thermoplastic Composite Coupons for Mechanical Characterization of Welded Joints through Single Lap Shear Testing
08:40

Ultrasonic Welding of Thermoplastic Composite Coupons for Mechanical Characterization of Welded Joints through Single Lap Shear Testing

Published on: February 11, 2016

11.5K
Ultrasonic Fatigue Testing in the Tension-Compression Mode
06:54

Ultrasonic Fatigue Testing in the Tension-Compression Mode

Published on: March 7, 2018

10.6K
Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

588

Area of Science:

  • Materials Science
  • Mechanical Engineering
  • Non-Destructive Testing and Evaluation (NDT&E)

Background:

  • Destructive testing is standard for weld tensile strength but impractical for in-service structures.
  • Non-destructive testing and evaluation (NDT&E) offers a solution for in-situ weld characterization.
  • Existing NDT&E methods require improvement for accurate weld property assessment.

Purpose of the Study:

  • To propose and validate an ultrasonic-based non-destructive method for evaluating weld tensile strength in X80 steel pipes.
  • To establish a predictive model for weld tensile strength using acoustic signal characteristics.
  • To introduce a grading evaluation model for rapid weld characterization.

Main Methods:

  • Collected acoustic signals from 240 measurement points on welded X80 steel pipes.
  • Processed signals to extract ultrasonic characteristic parameters.
  • Developed a multivariate regression-based (MLR) model using ultrasonic and destructive test data to predict tensile strength.
  • Implemented a grading evaluation model for weld characterization.

Main Results:

  • A multivariate regression model was established to predict weld tensile strength.
  • The grading evaluation model achieved an accuracy of 76.3% across 240 measurement points.
  • The proposed ultrasonic method demonstrates potential for non-destructive weld tensile strength assessment.

Conclusions:

  • The ultrasonic-based NDT&E method provides a viable alternative to destructive testing for weld tensile strength.
  • The current MLR model shows promising accuracy but can be improved.
  • Future work should explore deep learning methods to enhance prediction accuracy for weld tensile strength.