Mechanical Systems Modeling
Mechanical Systems Modeling - Related Videos
01:22
Mechanical Systems
0 Views •
2024
Mechanical systems are analogous to to electrical networks where springs and masses play similar roles to inductors and capacitors, respectively. A viscous damper in mechanical systems functions similarly to a resistor in electrical networks, dissipating energy. The forces acting on a mass in such systems include an applied force in the direction of motion, counteracted by forces from the spring, a viscous damper, and the mass's acceleration. This interplay of forces is mathematically described...
01:19
Electro-mechanical Systems
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2024
Electromechanical systems are intricate configurations that effectively combine electrical and mechanical elements to achieve a desired outcome. Central to many of these systems is the DC motor, a device that converts electrical energy into mechanical motion, enabling various applications ranging from simple fans to complex robotic mechanisms. A key component of the DC motor is the armature, a rotating circuit positioned within a magnetic field. As an electric current passes through the...
02:45
The Quantum-Mechanical Model of an Atom
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2020
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra. Schrödinger...
09:52
A Mouse Model for Pathogen-induced Chronic Inflammation at Local and Systemic Sites
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Cited by 15 •
2014
Animal models have proven to be invaluable tools in defining host and pathogen specific mechanisms that contribute to the development of chronic inflammation. Here we describe a mouse model of oral infection with the human pathogen Porphyromonas gingivalis and detail methodologies to assess the progression of inflammation at local and systemic sites.
18:57
Models and Methods to Evaluate Transport of Drug Delivery Systems Across Cellular Barriers
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Cited by 58 •
2013
Many therapeutic applications require safe and efficient transport of drug carriers and their cargoes across cellular barriers in the body. This article describes an adaptation of established methods to evaluate the rate and mechanism of transport of drug nanocarriers (NCs) across cellular barriers, such as the gastrointestinal (GI) epithelium.
FAQs
Measured responses can be used to estimate parameters that describe masses, springs, dampers, joints, or actuators. Statistical model fitting compares predicted behavior with observations and adjusts parameter values to represent the measured system more closely. This approach supports system identification, especially when component properties are not fully known before testing.
Residuals are the differences between observed measurements and model predictions. Examining them helps distinguish measurement noise from mechanical effects that the equations do not capture adequately. Patterns in residuals can indicate that the model requires revision, while comparatively unexplained residual variation supports the interpretation that the model describes the observed behavior reasonably well.
Uncertainty assessment quantifies how uncertain predictions are when measurements or fitted parameters are imperfect. Sensitivity assessment examines how strongly predicted behavior changes when model quantities vary. Together, these analyses show which inputs most influence results and help researchers judge prediction reliability, prioritize measurements, and evaluate whether a proposed design or modification is sufficiently understood.
Newtonian mechanics represents a system through relationships involving forces and motion, whereas energy principles describe behavior through quantities such as energy and constraints. Both provide routes for translating components and interactions into equations. Selecting a formulation helps organize the mechanical representation before statistical fitting, residual analysis, or uncertainty evaluation is applied to measured behavior.
A practical workflow begins by representing relevant components and constraints with equations, then collecting measurements of system behavior. Researchers fit model parameters to those observations, examine residuals for unexplained patterns, and assess sensitivity and uncertainty. The resulting model can then be used for simulation or to evaluate how well predicted behavior agrees with measured performance.
The approach supports simulation before a machine or structure is built or modified, reducing the need to rely solely on physical trials. It also contributes to system identification, control design, and fault detection by connecting measured behavior with mechanical equations. Statistical evaluation further assists experimental planning and helps assess reliability and performance.