On the other hand, 3D visualization software is also making an impact in advancing technology. Sure, Moore’s law plays a large part in the advancement of technology, but without the software-driven applications, technology would be very limited. People around the world are using computer programs daily to keep the world functioning. However, when it comes to software engineers are using, 3D visualization is a large part of what is progressing innovation.
3D software is currently used for many tasks, including modeling a figure to help visualize a final product or modeling a piece to be 3D printed. Additionally, 3D software is also helping us model things we may not be able to see in the real world. Technically, rolling a 3D model around in virtual space shows more data than a series of isometric 2D representations. 3D modeling, or 3D visualization, is not limited to building a virtual solid model, but can show a multitude of different types of data.
Like Microsoft’s GeoFlow, seeing the data move in virtual space can give new insights. Typical engineering test data can include things such as air or water flow, pressure, electric fields, current, or even radiation patterns. One specific application, which is commonly used for these functions, is MATLAB.
MATLAB can be an extremely helpful tool for an engineer. It is typically used to graph functions, implement algorithms, make user interfaces, make a connection to programs in other languages, and, more specifically, plot data.
Let’s consider antenna design and theory. Antennas work in three dimensions, and knowing how their radiation pattern works and what it looks like can be critical for a successful antenna design. Modeling an antennas’ radiation pattern can give helpful insight and help determine parameters such as beamwidth, directivity, and polarization. This can all be modeled with MATLAB, and even antenna array systems are included.
Since the release of version 2013a, MATLAB now offers a Phased Array System Toolbox. With this toolbox common array patterns such as a uniform linear array, uniform rectangular array, and conformal array can now be modeled and analyzed. It works by defining each element’s position in three-dimensional space, how many elements exist, and the spacing between them. Then, using a predefined ideal function or user-defined measurements, a three-dimensional pattern can be created.
In fact, many companies and researchers collect data from sensors in a very similar manner. Logging data over time from a sensor can provide lots of information and knowledge in many scenarios. This is a case where 3D data graphs can be extremely useful. For example, let's think of a system trying to collect data from a light source. To find the optimal position, many people may increment the sensor’s position, do a read from the light sensor, and then continue on by incrementing and collecting more data until a sufficient amount is harvested. Therefore, the user would have position data from the light intensity along with x-y plane, and intensity of light in the z plane. As a result, the data can all be displayed on one graph, rather than having two position graphs versus intensity of light.
As we can see, 3D software can be very beneficial in many applications. From stocks and business data, to engineering and modeling, 3D visualization is helping us express information in a way that’s more informative and easier to decipher.