DERIVATIVE CALCULUS

Simple equations for the electroklnetlc phenomena discussed in sec. 4.2 can be derived under a number of more or less restrictive conditions, using elementary calculus. Deriving such expressions serves a number of purposes. Including ... 

In this case, the calculus derivation already described leads to the integrated zero-order rate equation... 

In calculus, derivative and antiderivative relationships among the trigonometric functions are established. Of primary importance are the ones involving sine and cosine Cosine is the derivative function of sine, while the negative sine is the derivative function of cosine. 

A second type of snbtraction artifact are derivative-shaped peaks, as shown in Figure 3.6. These features like the calculus derivative of an absorbance band. Figure 3.6 shows a comparison of a sample and a reference spectrum, both of which contain liquid water. In theory these two spectra could be subtracted from each other, resulting in the removal of the water peak. However, note that the water peaks in Figure 3.6 are at slightly different wavenumbers. This wavenumber shift is a result... 

From basic calculus, it is known that a function of a single variable is analytic at a given interval if and only if it has well-defined derivatives, to any order, at any point in that interval. In the same way, a function of several variables is analytic in a region if at any point in this region, in addition to having well-defined derivatives for all variables to any order, the result of the differentiation with respect to any two different variables does not depend on the order of the differentiation. 

A somewhat similar problem arises in describing the viscosity of a suspension of spherical particles. This problem was analyzed by Einstein in 1906, with some corrections appearing in 1911. As we did with Stokes law, we shall only present qualitative arguments which give plausibility to the final form. The fact that it took Einstein 5 years to work out the bugs in this theory is an indication of the complexity of the formal analysis. Derivations of both the Stokes and Einstein equations which do not require vector calculus have been presented by Lauffer [Ref. 3]. The latter derivations are at about the same level of difficulty as most of the mathematics in this book. We shall only hint at the direction of Lauffer s derivation, however, since our interest in rigid spheres is marginal, at best. 

The varianee equation ean be solved direetly by using the Calculus of Partial Derivatives, or for more eomplex eases, using the Finite Difference Method. Another valuable method for solving the varianee equation is Monte Carlo Simulation. However, rather than solve the varianee equation direetly, it allows us to simulate the output of the varianee for a given funetion of many random variables. Appendix XI explains in detail eaeh of the methods to solve the varianee equation and provides worked examples. 

One of the pleasant aspects of the study of thermodynamics is to find that the mathematical operations leading to the derivation and manipulation of the equations relating the thermodynamic variables we have just described are relatively simple. In most instances basic operations from the calculus are all that are required. Appendix 1 reviews these relationships. 

At the temperature of the critical isotherm (71 = 304.19 K for C02), the coexistence region has collapsed to a single point and represents a point of inflection in the isotherm. From calculus we know that at an inflection point, the first and second derivatives are equal to zero so that... 

Thermodynamic derivations and applications are closely associated with changes in properties of systems. It should not be too surprising, then, that the mathematics of differential and integral calculus are essential tools in the study of this subject. The following topics summarize the important concepts and mathematical operations that we will use. 

Consider the bimolecular reaction of A and B. The concentration of B is depleted near the still-unreacted A by virtue of the very rapid reaction. This creates a concentration gradient. We shall assume that the reaction occurs at a critical distance tab- At distances r tab. [B] = 0. Beyond this distance, at r > rAB, [B] = [B]°, the bulk concentration of B at r = °°. We shall examine a simplified, two-dimensional derivation the solution in three dimensions must incorporate the mutual diffusion of A and B, requiring vector calculus, and is not presented here. 

Optional mathematical derivations. The How do we do that feature sets off derivations of key equations and encourages students to appreciate the power of mathematics by showing how it enables them to make progress and answer questions. All quantitative applications of calculus in the text are confined to this feature. The end-of-chapter exercises that make use of calculus are identified with a [cl... 

To derive an expression for the change in entropy when a system is heated, we first note that Eq. 1 applies only when the temperature remains constant as heat is supplied to a system. Except in special cases, that can be true only for infinitesimal transfers of heat so we have to break down the calculation into an infinite number of infinitesimal steps, with each step taking place at a constant but slightly different temperature, and then add together the infinitesimal entropy changes for all the steps. To do this is we use calculus. For an infinitesimal reversible transfer dgrev at the temperature T, the increase in entropy is also infinitesimal and, instead of Eq. 1, we write... 

This chapter makes extensive use of expressions derived from calculus. For a discussion of derivatives and related functions, see Appendix IF. 

Because an instantaneous rate is a derivative of concentration with respect to time, we can use the techniques of integral calculus to find the change in [A] as a function of time. First, we divide both sides by A and multiply through by — dt ... 

In differential calculus, the slope of the curve is found by letting the separation of the points become infinitesimally small. The first derivative of the function y with respect to x is then defined as... 

Integra] calculus provides a way to determine the original function, given its first derivative. Thus, if we know that the first derivative is lx, then the integral calculus allows us to deduce that the function itself is y = x2. Formally, we write... 

Some problems in functional optimization can be solved analytically. A topic known as the calculus of variations is included in most courses in advanced calculus. It provides ground rules for optimizing integral functionals. The ground rules are necessary conditions analogous to the derivative conditions (i.e., df jdx = 0) used in the optimization of ordinary functions. In principle, they allow an exact solution but the solution may only be implicit or not in a useful form. For problems involving Arrhenius temperature dependence, a numerical solution will be needed sooner or later. 

Some difference formulae. In the sequel, when dealing with various difference expressions, we shall need the formulae for difference differentiating of a product, for summation by parts and difference Green s formulae. In this section we derive these formulae within the framework similar to the appropriate apparatus of the differential calculus. Similar expressions were obtained in Section 2 of Chapter 1 in studying second-order difference operators, but there other notations have been used. It performs no difficulty to establish a relationship between formulae from Section 2 of Chapter 1 and those of the present section. 

There are also techniques to determine whether we are dealing with a maximum or a minimum, that is, by use of the second derivative. And there are techniques to determine whether we simply have a maximum (one of several local peaks) or the maximum. Such approaches are covered in elementary calculus texts and are well presented relative to optimization in a review by Cooper and Steinberg [2]. 

It was already assumed in Chapter 1 that readers are familiar with the methods for determining the derivatives of algebraic functions. The general rules, as proven in all basic calculus courses, can be summarized as follows. 

For optimization problems that are derived from (ordinary or partial) differential equation models, a number of advanced optimization strategies can be applied. Most of these problems are posed as NLPs, although recent work has also extended these models to MINLPs and global optimization formulations. For the optimization of profiles in time and space, indirect methods can be applied based on the optimality conditions of the infinite-dimensional problem using, for instance, the calculus of variations. However, these methods become difficult to apply if inequality constraints and discrete decisions are part of the optimization problem. Instead, current methods are based on NLP and MINLP formulations and can be divided into two classes ... 

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