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Simpson's rule is a widely used numerical integration technique that was originally documented by Thomas Simpson, an English weaver who self-taught himself mathematics in the 18th century (Schwartz, 2011). Since the basis of this method involves using parabolas to approximate the shape of a curve, to generate any parabola, three consecutive points are required. Thus, to correctly apply this method, three or more odd equally spaced consecutive data points are needed along a curve. To obtain an odd number of data points along a curve, an even number of subintervals, \(n\), must be used \((n≥2)\) – a subinterval is the space between two points. In fact, for every two subintervals, one parabolic segment is produced; hence, it is impossible for \(n\) to be odd or exceed the total number of data points. Incorporating additional points enhances the precision of the approximation since more parabolas can be generated to approximate different regions along the curve (Easa, 1988). We will run this method on the same problem used to illustrate the trapezoidal rule from the previous chapter (Example 2.1) to demonstrate the benefits that come from using Simpson's rule. Example 3.1
Solution
From the graph given in Example 3.1 (part (a)), it is evident that using more subintervals would reduce the instances of areas being either overestimated or underestimated. When you are provided with an illustration of the object for which you are calculating the area, there is virtually no restriction on the number of subintervals you can use when applying Simpson's rule, except for practical limitations such as time or resource constraints. In theory, you can divide the curve into as many subsegments as needed to achieve a highly precise estimation of the area. However, when applying Simpson's rule to a set of data points measured at a work site, it is important to note that interpolation (estimating values between consecutive observations) is not permitted. Unlike when we have an illustration of the object, where we can visually understand the shape and make informed decisions about subintervals, the lack of a visual representation restricts our ability to accurately interpolate data points in between the observed values, as demonstrated in Example 3.2. Example 3.2
Solution
There are several known variants of Simpson's rule, including one that uses third-degree polynomials rather parabolas and another that allows the use of unequal intervals (Easa, 1988). For most trade-related applications, however, the standard version of Simpson's rule presented here, utilizing parabolic segments and equally spaced intervals, offers a practical and reliable method for estimating areas of irregular shapes. Video DemonstrationThe two videos below illustrate how Simpson's rule can be applied to find the area. The video under Question 1 mentions the 'prismoidal formula' in the introduction, although it should not be mistaken with the Simpson's rule. The prismoidal formula is used to calculate the volume of irregularly shaped solids. In retrospect, mentioning the prismoidal formula was a mistake, but that should not detract from the overall message of the video. Furthermore, in both videos we see the formula written in function notation (e.g. we see \(f(x_n)\) rather than \(y_n\)). This does not change how the Simpson's rule is applied; as an exercise, try doing the problems using the notation outlined in this article. Question 1Question 2Question 3 (Advanced)https://www.youtube.com/watch?v=NShwzjTBOzY SourceEasa, S. (1988). Area of irregular region with unequal intervals. Journal of Surveying Engineering, 114(2), 50-58. Schwartz, R. (2011). Thomas Simpson, Weaver and Mathematician. The Right Angle, 18, 6. |
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