Concrete is one of the most widely used materials in the construction industry. It exists in almost every modern structure, from roads to bridges to buildings. There are different types of concrete. Each type has its own specific application. These different types derive from the different compositions and proportions of the elements. Each type is designed to support different weights, compress more or less, and move in different ways. The introduction of artificial intelligence (AI) into the concrete industry is relatively new. But the impact is already felt. Civil engineers have been looking for ways to apply machine learning. The goal is to reduce human error, detect damage and determine the correct proportion of concrete mixture.
Application in structural integrity
There are various successful and innovative applications of AI in concrete. SmartRock is a sensor that sits inside a reinforced concrete framework. When the concrete is poured, the sensor remains fixed to the structure. Collect a set of data points about conditions and temperature. This data is then sent to the wireless application.
The main use of this data is to understand the compressive strength of concrete. Over time, as the temperature and conditions change, the app can calculate new values. Engineers can use these values and adapt accordingly.
Another application used is called Roxi. Use SmartRock data to predict how concrete will behave in future projects. This means that another project can already have a timeline of predicted compressive strength. The computer uses previous datapoints from another project with similar conditions. As more projects use this data collection method, forecasts can become more accurate.
Damage detection application
One of the major problems in the construction industry is the potential damage that can occur to structures. There are more obvious cases of damage. These include earthquakes, strong storms, and vehicle collisions with buildings. Some are less noticeable. These internal damage cases are some of the most dangerous. Engineers often cannot see this damage visibly and are unaware of its existence.
Structural Health Monitoring (SHM) is an analytical method used on bridges. Use computer software to analyze potential damage, model its severity, and predict how it will occur.
In the tester project, five cracks were mapped to a structural beam model. The software was able to predict the location, depth and width of the crack over time.
This application still needs some time to become more accurate. However, at this time it serves as an estimate of bridge cracks and damage.
Application to concrete mixing
The strength and durability of concrete depends largely on the mixture in which it is made. Different combinations of elements produce concrete samples with different properties. Some concrete mixtures use the addition of fibers. This is to increase the load-bearing capacity of concrete. However, the addition of fibers affects the workability of concrete. The Concrete Research Council has funded a project to apply statistical learning to the production of reinforced concrete. The computer analyzed the data of about 2,000 cases of this fiber concrete and the characteristics of the result.
Using this data, computers can develop statistical models of which combination of concrete produces a particular quality. Having an average database makes the production of fiber reinforced concrete more mathematical.
Engineers can understand which mix produces which result. Then you can predict the type of concrete that is suitable for different projects. This database is also useful for predicting concrete volatility and sensitivity.
The future of AI in concrete
As technology continues to advance, AI applications in the concrete industry will continue to be developed and improved. They have the potential to dramatically reduce human error in structural projects. They can be used to detect damage as the concrete used becomes older and weathered. This reduces the chance of collapse and can save lives.
Machine learning can be used to analyze millions of data effectively and efficiently.
You can then make real forecasts based on trends and patterns. It can be used to assess potential performance and suggest a mixture of concrete to use. AI continues to move the industry forward in ways we never imagined. That application has the potential to revolutionize the industry in which we rely heavily.
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