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Typical Model Studies

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.

Design Example: Creating a Hydraulic Model of a Dam Spillway

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Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.

Modeling and Similitude

Modeling and Similitude

Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...

Dimensional Analysis

Dimensional Analysis

Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...

Laminar Flow

Laminar Flow

Laminar flow represents a smooth, orderly fluid motion where particles move along parallel paths, resulting in minimal mixing between layers. Streamlined particle paths characterize this flow regime and occur under conditions where viscous forces dominate over inertial forces. The distinction between laminar, transitional, and turbulent flow is primarily determined by the Reynolds number, a dimensionless quantity calculated as:

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Surrogate Model Development for Digital Experiments in Welding

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Computational Fluid Dynamics as a Digital Tool for Enhancing Safety Uptake in Advanced Manufacturing Environments

Dionysia Maria Voultsou¹, Stratos Saliakas¹, Spyridon Damilos¹

¹Innovation in Research & Engineering Solutions (IRES), 1000 Brussels, Belgium.

Materials (Basel, Switzerland)

|January 25, 2025

Summary

This study developed a computational fluid dynamic (CFD) model to map indoor 3D printing pollution. The model shows ventilation effectively reduces ultrafine particles, enhancing worker safety and air quality.

Keywords:

computational fluid dynamics manufacturing particle tracing safety simulation three-dimensional printing turbulent flow

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Area of Science:

Manufacturing Engineering
Environmental Science
Computational Fluid Dynamics

Background:

Pollution management is crucial in manufacturing due to health risks.
3D printing processes can release harmful ultrafine particles.

Purpose of the Study:

To develop and apply a two-stage CFD model for estimating indoor pollutant distribution.
To evaluate factors influencing ultrafine particle distribution in 3D printing environments.

Main Methods:

Utilized Reynolds-Averaged Navier-Stokes (RANS) for airflow and temperature simulation.
Employed the Lagrangian method for particle tracing.
Applied the model to a theoretical acrylonitrile butadiene styrene (ABS) filament 3D printing process.

Main Results:

Identified high flow velocities and turbulent kinetic energy near ventilation systems, aiding particulate removal.
Demonstrated that ventilation is key to reducing stagnant zones and pollutant buildup.
Found limited impact of cooling fans and thermal sources on particle removal.

Conclusions:

Effective ventilation strategies are critical for mitigating airborne pollutants in 3D printing.
Digital twins can improve worker safety and air quality assessments in manufacturing.
Understanding airflow dynamics is essential for pollution control in additive manufacturing.