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Virtual Work01:20

Virtual Work

1.4K
The principle of virtual work states that if a body is in static and dynamic equilibrium, then the sum of all the virtual work done by all external forces and couple moments for any given virtual displacement must be zero.
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
1.4K
Principle of Virtual Work: Problem Solving01:13

Principle of Virtual Work: Problem Solving

1.7K
The principle of virtual work is an essential concept in the field of mechanics and engineering. This is used to solve problems related to the equilibrium of a structure or system. It is based on the assumption that if a system is in equilibrium, the work done by all the forces during a virtual displacement is zero. This principle is applied by considering virtual displacements of the system and the corresponding work done by internal and external forces.
To apply the principle of virtual work,...
1.7K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

430
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
430
Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

773
Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
773
Multi-Step Reactions02:31

Multi-Step Reactions

8.9K
Chemical reactions often occur in a stepwise fashion involving two or more distinct reactions taking place in a sequence. A balanced equation indicates the reacting species and the product species, but it reveals no details about how the reaction occurs at the molecular level. The reaction mechanism (or reaction path) provides details regarding the precise, step-by-step process by which a reaction occurs. Each of the steps in a reaction mechanism is called an elementary reaction. These...
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Molecular Models02:00

Molecular Models

43.9K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Related Experiment Video

Updated: Feb 15, 2026

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
07:49

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization

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Modelling multi-rotor UAVs swarm deployment using virtual pheromones.

Fidel Aznar1, Mar Pujol1, Ramón Rizo1

  • 1Department of Computer Science and Artificial Intelligence, University of Alicante, San Vicente del Raspeig, Alicante, Spain.

Plos One
|January 26, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a novel swarm behavior for multi-rotor Unmanned Aerial Vehicles (UAVs) using virtual stigmergy for adaptable deployment in complex environments, ideal for emergency communication networks.

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Area of Science:

  • Robotics and Autonomous Systems
  • Swarm Intelligence
  • Network Engineering

Background:

  • Deploying Unmanned Aerial Vehicles (UAVs) for tasks like ad-hoc network creation faces challenges due to sensory, processing, and endurance limitations.
  • Existing UAV deployment behaviors often assume specific environmental features, limiting their real-world applicability.

Purpose of the Study:

  • To present a new swarm behavior for multi-rotor UAVs.
  • To enable adaptable and robust deployment in complex environments without prior information or external signals.
  • To facilitate the creation of ad-hoc communication networks for emergency response.

Main Methods:

  • Development of a virtual device for quantitative sematectonic stigmergy.
  • Microscopic model for UAV deployment and ad-hoc network creation incorporating stigmergy.
  • Macroscopic model to predict agent numbers and deployment time.
  • Simulation-based experimental analysis to validate models and assess environmental complexity and stigmergy influence.

Main Results:

  • The proposed swarm behavior demonstrates high robustness and fault tolerance.
  • The models accurately predict the number of UAVs and time required for area coverage.
  • Environmental complexity and the stigmergy system significantly influence deployment effectiveness.

Conclusions:

  • The virtual stigmergy approach enhances UAV adaptability in complex, unknown environments.
  • The developed models provide a reliable framework for planning UAV swarm deployments for emergency tasks.
  • This research contributes to the practical application of UAV swarms in creating essential communication infrastructure.