Numerical modeling is converting a physical problem into mathematical statements that can be solved. It involves simplifications and assumptions but is generally helpful in reproducing the behavior and mechanisms of physical processes.
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Accuracy
The accuracy of numerical modelling is essential. The governing equations of the model must capture the actual geological scenario quantitatively. This is done through mathematical algorithms that approximate these governing equations and are subsequently solved by computers. The model results can then be interpreted.
The engineer must understand these concepts well to build the model with accurate assumptions and input data. This will also help the engineers to interpret the model results correctly.
Thorough reviews and iterative revisions are key to the accuracy of engineering drawings. It is also very important that the engineers attend professional development programs to ensure they have a strong working knowledge of current technology and design standards.
Efficiency
Many engineering projects are unique or need more historical data, making it difficult to rely on experience in cost estimation. It is vital to use advanced methods that leverage data analytics and artificial intelligence to reduce the time and effort spent on manual calculations.
Numerical models can be used to determine how the geomechanical properties of a site will behave, especially in complex conditions such as those encountered in deep excavations or on slope stability. These models help avoid expensive and risky physical experiments and provide the same information at a fraction of the time and cost.
However, it is essential to remember that the computer can unquestioningly process wrong data and produce undesired incorrect output. Therefore, the results should always be interpreted in conjunction with engineering judgment.
Predictability
Predictability is developing and delivering project plans to meet delivery timelines confidently. It’s an important metric for capital projects but often difficult to measure accurately. Unlike productivity, which is a function of team member’s individual skills and overall team cohesion, predictability is mostly influenced by external factors that are impossible to account for upfront. For example, when software engineering teams are behind schedule, it might not be because of technical issues or design flaws that could have been easily spotted and corrected during the planning phase but because the business side delayed release cycles to avoid risking negative performance appraisals. To increase predictability, organizations must adopt out-of-the-box best practices, automate processes, and implement incentivization programs encouraging teams to report progress honestly.
Flexibility
Numerical modeling is the use of sophisticated computer software to model the fundamental physics of a system. This process helps to determine its behavior and provides information that may be difficult or impossible to obtain from expensive experiments. While numerous factors can affect a geological system, it is often impractical to consider them all when building a mathematical model. In such cases, the model will usually be simplified by omitting some less significant factors. A study has shown that a flexible design of building structures is much better for the future accommodation of users. A mathematical formula has been prepared to compare the extra cost incurred for flexibility during the initial stage of construction to the discount that can be earned by investing in this premium.
