# Vector calculus gradient divergence curl pdf

This article is about the gradient of a multivariate function. In the above two images, the values of the function are represented in black and white, black representing vector calculus gradient divergence curl pdf values, and its corresponding gradient is represented by blue arrows. Assume that the temperature does not change over time.

The magnitude of the gradient will determine how fast the temperature rises in that direction. The steepness of the slope at that point is given by the magnitude of the gradient vector. If, instead, the road goes around the hill at an angle, then it will have a shallower slope. This observation can be mathematically stated as follows. There are two forms of the chain rule applying to the gradient. At a non-singular point, it is a nonzero normal vector. The gradient of a function is called a gradient field.

This page was last edited on 6 February 2018, at 11:38. This article is about divergence in vector calculus. As an example, consider air as it is heated or cooled. While air is heated in a region, it expands in all directions, and thus the velocity field points outward from that region. The divergence of the velocity field in that region would thus have a positive value. While the air is cooled and thus contracting, the divergence of the velocity has a negative value. In physical terms, the divergence of a three-dimensional vector field is the extent to which the vector field flow behaves like a source at a given point.

If the divergence is nonzero at some point then there must be a source or sink at that position. The use of local coordinates is vital for the validity of the expression. Some conventions expect all local basis elements to be normalized to unit length, as was done in the previous sections. The divergence of a vector field can be defined in any number of dimensions.

This means that the divergence measures the rate of expansion of a volume element as we let it flow with the vector field. This page was last edited on 9 January 2018, at 22:00. Please forward this error screen to 216. Vector calculus is an extremely interesting and important branch of math with very relevant applications in physics.

So what does this all mean? Let’s break it down, arduously and tediously, from the nitty-gritty of the vector calculus requisite for understanding the elegance of these equations. Note: I presume basic knowledge of calculus in this post. Obviously, this is not meant to be a substitute for a more rigorous foundation with more computational practice. First, let’s talk about vectors. Specifically, let’s handle them in an intuitive sense. Both of these concepts just represent functions.

Recall that a function is roughly an object that takes in an input and returns an output. Such functions are the subject of much discussion in early math classes, but this idea can be generalized. When a function takes in multiple inputs, it is often regarded as taking as input a vector. It is called a scalar field because it outputs a scalar. This can be thought of as an assignment of a number to every point in space.