## Abstract

In this chapter, mixing problems are considered since they always lead to linear ordinary differential equation (ODE) systems, and the corresponding associated matrices have different structures that deserve to be studied deeply. This structure depends on whether or not there is recirculation of fluids and if the system is open or closed, among other characteristics such as the number of tanks and their internal connections. Several statements about the matrix eigenvalues are analyzed for different structures, and also some questions and conjectures are posed. Finally, qualitative remarks about the differential equation system solutions and their stability or asymptotical stability are included.

### Keywords

- eigenvalues
- Gershgorin circle theorem
- mixing problems
- linear ODE systems
- associated matrices

## 1. Introduction

Mixing problems (MPs), also known as “compartment analysis” [1], in chemistry involve creating a mixture of two or more substances and then determining some quantity (usually concentration) of the resulting mixture. For instance, a typical mixing problem deals with the amount of salt in a mixing tank. Salt and water enter to the tank at a certain rate, they are mixed with what is already in the tank, and the mixture leaves at a certain rate. This process is modeled by an ordinary differential equation (ODE), as Groestch affirms: “The direct problem for one-compartment mixing models is treated in almost all elementary differential equations texts” [2].

Instead of only one tank, there is a group, as it was stated by Groestch: “The multicompartment model is more challenging and requires the use of techniques of linear algebra” [2]. In particular, the ODE system-associated matrix deserves to be studied since it determines the qualitative behavior of the solutions.

In several previous papers and book chapters [3, 4, 5, 6], MPs were studied from different points of view. In the first paper [3], a particular MP with three compartments was proposed, and after applying Laplace transform, this example was connected with important concepts in reactor design, like the transference function. 2 years later, another work [4] analyzed more general MPs in order to obtain characterization results independent of the internal geometry of the tank system. In the third paper [5], the educative potential of MPs was studied, focusing on inverse modeling problems. Finally, in a recent book chapter [6], results for MPs with and without recirculation of fluids were analyzed, and other general results were obtained.

In all these works, a given MP is modeled through an ODE linear system, in which qualitative properties (like stability and asymptotic stability) depend on the eigenvalues and eigenvectors of the associated matrices, so-called MP-matrix.

Taking into account previous results about MP-matrices, and the new ones presented here, two main conjectures can be proposed:

All the solutions of a given MP are stable.

If the MP corresponds to an open system, then the solutions are asymptotically stable.

In order to investigate if these conjectures—among others, introduced in the following sections—are true or not, MP-matrices (i.e., square matrices associated to the ODE linear system that models a given MP) should be deeply analyzed.

## 2. Nomenclature

In this section we introduce a specific terminology useful to allow understanding of the terms properly.

In order to analyze MPs and MP-matrices, we begin by studying a problem already considered in a previous book chapter [6], which involves a tank with five compartments, shown in Figure 1.

In this scheme, _{0} is the initial concentration (e.g., salt concentration in water at the entrance of the tank system), * C* is the concentration in the ith compartment (

_{i}

*= 1,…,5), and*i

For instance, if
* k* = 2, 3, 4) and

The ODEs associated with the central compartments (* i* = 2, 3, 4) are simpler, since in each case, there is only one incoming flux

*= 2, 3, 4) and a unique outgoing flux*k

*= 2, 3, 4). Once again, if*k

Finally, for the right (fifth) container, we have:

If all these equations are put together, the following ODE system is obtained:

After some algebraic manipulations, the corresponding mathematical model can be written as

The system-associated matrix (MP-matrix) is

Hereafter, we will call MP-matrix to any ODE system-associated matrix related to a given MP, like matrix

In the previous example, the MP-matrix obviously depends on the numbers given to the different containers. In that example it was possible to enumerate the compartments such that the flux always goes from the ith compartment to the jth one, where

In general, if in a given MP it is possible to enumerate the containers such that the flux always goes from the ith compartment to the jth one, with

Now, let us analyze a different problem, where a couple of tanks are linked by all possible connections between them, including recirculation from the second tank back to the first one, as in Figure 2. This problem represents an interesting variation of an MP analyzed by Zill [7] in his textbook, where the main difference is that this new MP has no incoming and/or outgoing flux, i.e., it is a closed system.

If in a given MP we have that

Taking into account the abovementioned nomenclature, the example considered in Figure 2 corresponds to an MP-CS, while the MP analyzed in Zill’s textbook [7] is an MP-OS, and both are systems with recirculation.

Finally, it is important to observe that in both examples (Figures 1 and 2), we have

In that case all the compartment volumes remain constant, and so if in an MP the following equation

Taking into account all these terms, several previous results can be reformulated, as shown in the next section.

## 3. Previous results revisited

In order to give some general results, it is convenient to consider two different situations: MP without recirculation and MP with recirculation.

Considering again the example in Figure 1, it is possible to enumerate the compartments, such that the flux always goes from the ith container to the jth one, being

Analyzing the system (Eq. (4)), it is easy to observe that for the jth container, the ODE right hand side is a linear combination of a subset of

being

As a consequence, under the previous conditions, the corresponding ODE system has an associated upper matrix.

Revisiting the ODE system (Eq. (4)), corresponding to Figure 1, it can be rewritten as

It follows that for the jth compartment, the coefficient corresponding to

However, not all of these results can be extended to MPs with recirculation as will be analyzed in the following subsection.

In previous works [4, 5], a “black box” system was analyzed (see Figure 3), in order to obtain a necessary condition to be satisfied by any MP-matrix with any number of compartments and unknown internal geometry. In Figure 3

If all volumes

Then, Eq. (9) is obtained without any consideration of the internal geometry of the tank system and can be easily verified in the previous example (see Figure 1). In fact, by adding the equations of the ODE system (Eq. (4)), it follows straightforward that the condition given in Eq. (9) is satisfied. The same conclusion can be drawn from other possible examples, corresponding to open or closed MPs, with or without recirculation. For instance, in the case schematized in Figure 2, the ODE system can be written as follows:

Operating with these equations, it can be proved that

The previous result can be generalized as follows: in a given MP—with or without recirculation—with input and output concentrations

An analogous condition may be used to know if a given matrix may or may not be an MP-matrix. For this purpose, let us consider the MP-matrix

It is easy to observe that

This equation can be written as

If there exists an incoming (and outgoing) flux

It can be noted that Eq. (12) and Eq. (13) are particular cases of the following result: in a given MP—with or without recirculation—with an incoming and outgoing flux

Then, independently of the internal geometry of the system, the following condition is satisfied:

Now, let us consider again the MP-matrix

If

It is easy to observe that this new matrix will not satisfy the condition given by Eq. (14). Moreover, there is no MP associated to this matrix

As a first consequence, not every square matrix is an MP-matrix. A second observation is that if a given MP-matrix is slightly changed, the result is not necessarily a new MP-matrix.

Furthermore, if volumes

After interpreting the previous results, we note that when working with MP-matrices, existence, uniqueness, and stability questions for the inverse-modeling problem have negative answers.

The same situation can be observed in many other inverse problems [2], and it is not an exclusive property of compartment analysis.

## 4. Some considerations about terminology

We start this section explaining three simple and intuitive terms.

Firstly, we will consider that an input tank is a tank with one or more incoming fluxes. Secondly, a tank with one or more outgoing fluxes will be called output tank. Finally, we will say that an internal tank is a tank without incoming and/or outgoing fluxes to or from outside the system.

Taking into account the previous nomenclature, if

Input and output tanks are not mutually exclusive. For instance, in Figure 4, the first tank is an input tank, and at same time, it is an output tank, since it has an incoming flux

Another interesting example was proposed by Boelkins et al. [8]. The authors considered a three-tank system connected such that each tank contains an independent inflow that drops salt solution to it, each individual tank has a separated outflow, and each one is connected to the rest of them with inflow and outflow pipes. In this case, all tanks are input and output ones, and there is no internal tank.

It is important to mention that those types of tanks or compartments play different roles in the ODE-associated system and also—as a consequence—in the corresponding MP-matrix. In order to show this fact, let us examine a three-tank system with all the possible connections among them, as in Figure 5.

As a first remark, Figure 5 system has recirculation—unless

In the mass balance for the first tank—which is an input one—a term

Once again, the ODE system can be written as

In the previous ODE system, the independent vector is:

It is easy to observe that the outgoing flux

## 5. The Gershgorin circle theorem

The Gershgorin circle theorem first version was published by S. A. Gershgorin in 1931 [9]. This theorem may be used to bind the spectrum of a complex

If

This theorem was widely used in previous book chapters [6, 10, 11] in order to obtain new results about matrices corresponding to chemical problems.

Here, the main purpose is to apply this theorem to MP-matrices as a method to bind their eigenvalues, depending on the characteristics of the MP ODE system, and, even more, the compartment considered.

For instance, if we consider the MP corresponding to Figure 5, the first ODE of Eq. (17) can be expressed as

This equation—which obviously corresponds to an input tank—gives the first row of the MP-matrix (Eq. (18)) that can be written as

The Gershgorin disk corresponding to this row is centered at

Now, if a flux balance is performed in this input tank, we have this equation:

Now, if the second ODE of Eq. (17) is considered, this equation can be written as

This internal tank equation corresponds to the second row of the MP-matrix (Eq. (18)):

The Gershgorin disk corresponding to this row is centered at

Now, if a flux balance is performed in this internal tank, we have this equation:

Finally, if the third ODE of Eq. (17) is considered, this equation can be written as

This output tank equation corresponds to the third row of the MP-matrix Eq. (18):

The Gershgorin disk corresponding to this row is centered at the point

The flux balance in this case gives

Taking into account all these results, the Gershgorin circles for the MP of Figure 5 are shown in Figure 8.

Since every eigenvalue lies within at least one of the Gershgorin disks, it follows that

In the following section, these results—among others—will be generalized.

## 6. The general form of MP-matrices and new results

As stated in Section 3, if there is no recirculation, then the ODE system has only negative eigenvalues of the form

In a previous work [6], it was proved that in an open MP, with three or less compartments, with or without recirculation, all the corresponding ODE system solutions are asymptotically stable.

It is important to analyze if this result can be generalized or not, when closed systems and/or tanks with more than three compartments are considered. For this purpose, we will start with the following theorem.

In an open system, if the ith tank is an input one, then the diagonal entry of the ith row is

If

This equation gives.

Eq. (20) implies that the ith row of the MP-matrix has entries:

A flux balance gives

In an open system, being the ith tank an input one, the Gershgorin circle corresponding to the ith row looks like the disk in Figure 6.

If in an open system, all are input tanks, all the eigenvalues satisfy the condition

In an open system, if the ith tank is not an input one, then the diagonal entry of the ith row is

If

This equation gives:

Eq. (22) implies that the ith row of the MP-matrix has entries

In this case a flux balance gives the following equation

In an open system, if the ith tank is not an input one, the Gershgorin circle corresponding to the ith row looks like the disk in Figure 7.

In an open system, the Gershgorin disks look like those of Figure 8.

As a consequence of the previous results, the following corollary can be stated.

In an open system with input and non-input tanks, all the eigenvalues satisfy the condition

Independently of the previous results, it is easy to observe that all the solutions corresponding to the eigenvalues with

For this purpose, when analyzing eigenvalues with

In the first case, the corresponding ODE solutions are a linear combination of the functions

In the second case—which really happens, as it will be observed later—we have

According to the position of the Gershgorin disks for an MP-matrix (see Figure 8), the ODE solutions corresponding to an eigenvalue

For this purpose it is important to observe that if an eigenvalue

In this case the ODE solutions are a linear combination of the following functions:

Considering all these results, it is obvious that the stability of the ODE system solutions will depend exclusively on

## 7. Several questions and a conjecture

In the previous section, some particular cases with

Other questions are not so simple like the previous one. The next two examples propose challenging problems that deserve to be studied:

Question 1:

Is it possible to find an MP-matrix with an eigenvalue

Question 2:

Is it possible to find an MP-matrix such that

Question 3:

Is it possible to find an MP-matrix with complex eigenvalues in an open system?

Finally, it is interesting to observe that all cases analyzed here with

## 8. Conclusions

Mixing problems are interesting sources for applied research in mathematical modeling, ODE, and linear algebra, and—as it was shown—their behavior depends on how they are connected. It has been proved that null eigenvalues are not expected in open systems with three or less components, and

As a final remark, all the MP differential equation systems considered in this chapter have stable or asymptotically stable solutions. Nevertheless, this situation may change depending on the answers to the questions and the conjecture presented in the last section, giving a challenging proposal for further research on this topic.

## Acknowledgments

The author wishes to thank Marjorie Chaves for her assistance and support in this work.

## References

- 1.
Braun M. Differential Equations and their Applications. 3rd ed. New York: Springer; 2013. 546 p. DOI: 10.1007/978-1-4684-9229-3 - 2.
Groestch C. Inverse Problems: Activities for Undergraduates. Washington D.C.: Mathematical Association of America; 1999. 222 p - 3.
Martinez-Luaces V. Engaging secondary school and university teachers in modelling: Some experiences in South American countries. International Journal of Mathematical Education in Science and Technology. 2005; 36 (2–3):193-205 - 4.
Martinez-Luaces V. Inverse-modelling problems in chemical engineering courses. In: Proceedings of the Southern Hemisphere Conference on Undergraduate Mathematics and Statistics Teaching and Learning. (Delta ´07); 26–30 November 2007; Calafate: Argentina. pp. 111-118 - 5.
Martinez-Luaces V. Modelling and inverse-modelling: Experiences with O.D.E. Linear systems in engineering courses. International Journal of Mathematical Education in Science and Technology. 2009; 40 (2):259-268 - 6.
Martinez-Luaces V. Matrices in chemical problems: Characterization, properties and consequences about the stability of ODE Systems. In: Baswell A, editor. Advances in Mathematics Research. New York: Nova Publishers; 2017. pp. 1-33 - 7.
Zill D. Differential Equations with Boundary-Value Problems. 9th ed. Boston: Cengage Learning; 2016. 630 p - 8.
Boelkins M, Goldberg J, Potter M. Differential Equations with Linear Algebra. New York: Oxford University Press; 2009. 576 p - 9.
Varga R. Geršgorin and His Circles. Berlin, Germany: Springer-Verlag; 2004 - 10.
Martinez-Luaces V. First order chemical kinetics matrices and stability of O.D.E. systems. In: Kyrchei I, editor. Advances in Linear Algebra Research. New York: Nova Publishers; 2015. pp. 325-343 - 11.
Martinez-Luaces V. Qualitative behavior of concentration curves in first order chemical kinetics mechanisms. In: Taylor J, editor. Advances in Chemistry Research. New York: Nova Publishers; 2017. pp. 139-169