Jove
Visualize
Contact Us

Related Concept Videos

Cable Subjected to a Distributed Load01:24

Cable Subjected to a Distributed Load

1.3K
The analysis of suspension bridges is a complex and critical process that involves multiple factors, including the shape and tension of the main cables. The main cables of suspension bridges are subjected to distributed loads, which result in changes in tensile forces and deformation of the cable. These loads must be carefully considered to ensure that the bridge is safe and capable of supporting the weight of different loads.
1.3K
Behavior of Concrete Under Compressive Load01:23

Behavior of Concrete Under Compressive Load

895
Concrete exhibits specific behaviors under different compressive loads. Understanding this is crucial for understanding its structural integrity. When concrete undergoes uniaxial compression, it tends to develop cracks that run parallel to the direction of the force. These parallel cracks stem from localized tensile stresses that occur perpendicular to the compression direction. Additionally, angled cracks may appear due to the formation of shear planes.
As the concrete specimen fractures under...
895
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

384
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
384
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.2K
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
1.2K
Shearing Stresses in a Beam: Problem Solving01:14

Shearing Stresses in a Beam: Problem Solving

838
A cantilever beam with a rectangular cross-section under distributed and point loads experiences shearing stresses. The analysis begins by identifying the loads acting on the beam. Then, the reactions at the beam's fixed end are calculated using equilibrium equations. The vertical reaction is a combination of the distributed and point loads, while the moment reaction is the sum of their moments. The shear force distribution along the beam, resulting from these loads, is established by creating...
838
Design Example: Strain Gauge Bridge or Wheatstone Bridge01:15

Design Example: Strain Gauge Bridge or Wheatstone Bridge

1.3K
The utilization of strain gauges as transducers for converting mechanical strain into electrical signals is a common practice in various engineering applications. These strain gauges are frequently integrated into Wheatstone bridge circuits to accurately measure parameters such as force or pressure. Within this context, each element within the circuit exhibits a resistance that undergoes subtle variations when subjected to mechanical strain. The primary objective is to convert minuscule...
1.3K

You might also read

Related Articles

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

Sort by
Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026
Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026
Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026
Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026
Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026
Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026
See all related articles
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 Experiment Videos

Data compression of Bridge Resilience Control: Algorithm and case analysis.

Ming Chen1

  • 1School of Architecture Engineering, Shanghai ZhongQiao Vocational and Technical University, Shanghai, China.

Plos One
|April 15, 2026
PubMed
Summary
This summary is machine-generated.

A new data compression method for bridge resilience control integrates domain knowledge and time-series analysis. This approach achieves over 92% compression with 95% data fidelity, reducing storage and transmission costs.

Related Experiment Videos

Area of Science:

  • Civil Engineering
  • Structural Health Monitoring
  • Data Science

Background:

  • Bridge inspection and structural health monitoring are crucial for managing bridge resilience.
  • Massive data volumes from monitoring pose significant storage, transmission, and processing challenges.
  • Existing general-purpose data compression algorithms neglect the physical relevance of bridge monitoring data.

Purpose of the Study:

  • To develop a novel data compression algorithm for bridge resilience control that preserves critical structural information.
  • To address the limitations of conventional algorithms by integrating domain knowledge and time-series characteristics.

Main Methods:

  • Integration of domain knowledge, time-series characteristics, and bridge deterioration models into a new compression algorithm.
  • Transformation of raw monitoring data into engineering attributes for targeted data reduction.
  • Extraction of dynamic structural characteristics using the steady-state variation law and sparse data supplementation for incomplete datasets.

Main Results:

  • The domain knowledge-based compression achieved a 75% compression ratio.
  • Synergistic processing with time-series feature extraction and sparse data supplementation yielded a comprehensive compression ratio exceeding 92%.
  • Data fidelity rate of 95% was maintained, satisfying engineering precision requirements.

Conclusions:

  • The proposed method significantly reduces data storage and transmission bandwidth consumption (75%-92%) for bridge resilience control.
  • It effectively balances data compression efficiency with structural evaluation accuracy.
  • The approach ensures data integrity and applicability to practical bridge resilience management.