F. Xavier Malcata - Mathematics for Enzyme Reaction Kinetics and Reactor Performance

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Mathematics for Enzyme Reaction Kinetics and Reactor Performance
Enzyme Reactor Engineering
The second volume begins with an introduction to basic concepts in calculus, i.e. limits, derivatives, integrals and differential equations; limits, along with continuity, are further expanded afterwards, covering uni- and multivariate cases, as well as classical theorems. After recovering the concept of differential and applying it to generate (regular and partial) derivatives, the most important rules of differentiation of functions, in explicit, implicit and parametric form, are retrieved – together with the nuclear theorems supporting simpler manipulation thereof. The book then tackles strategies to optimize uni- and multivariate functions, before addressing integrals in both indefinite and definite forms. Next, the book touches on the methods of solution of differential equations for practical applications, followed by analytical geometry and vector calculus. Brief coverage of statistics–including continuous probability functions, statistical descriptors and statistical hypothesis testing, brings the second volume to a close.

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and

(5.11) respectively so Eqs 33 35are particular cases of Eqs 53 57 - фото 1123

respectively – so Eqs. (3.3)– (3.5)are particular cases of Eqs. (5.3), (5.7), and (5.11).

In view of the (3 × 3) matrix representation of a tensor, one may retrieve all operations presented before to some length – as they are applicable also to tensors; this includes addition of matrices as per Eq. (4.4), multiplication of scalar by matrix as per Eq. (4.20), and multiplication of matrices as per Eq. (4.47). A number of operations specifically dealing with, or leading to tensors are, in addition, worth mentioning on their own – all of the multiplicative type, in view of the underlying portfolio of applications thereof.

One such multiplicative operation is the dyadic product of two vectors, uand v– also known as matrix product of the said vectors, since the first vector is multiplied by the transpose of the second via the algorithm labeled as Eq. (4.47); it is accordingly represented by

(5.12) as opposed to Eq 352 and readily degenerates to 513 which abides to - фото 1124

as opposed to Eq. (3.52)– and readily degenerates to

(5.13) which abides to the definition of tensor conveyed by Eq 51 The said - фото 1125

which abides to the definition of tensor conveyed by Eq. (5.1). The said representation is equivalent to

(5.14) where the js denote the unit vectors oriented along one of the Cartesian axes - фото 1126

where the j’s denote the unit vectors oriented along one of the Cartesian axes, previously labeled as Eqs. (3.3)– (3.5); comparative inspection of Eqs. (5.1)and (5.13)and of Eqs. (5.2)and (5.14)indicates that the double products of j 's can be seen as matrix products of the corresponding unit vectors, according to

(5.15) картинка 1127

(5.16) картинка 1128

(5.17) картинка 1129

(5.18) картинка 1130

(5.19) картинка 1131

(5.20) картинка 1132

(5.21) картинка 1133

(5.22) картинка 1134

and

(5.23) In view of Eqs 515 523 one may rewrite Eq 514as 524 or in - фото 1135

In view of Eqs. (5.15)– (5.23), one may rewrite Eq. (5.14)as

(5.24) or in a more condensed fashion 525 provided that i and j denote x i - фото 1136

– or, in a more condensed fashion,

(5.25) provided that i and j denote x i 1 or j 1 y i 2 or j 2 or z i - фото 1137

provided that i and j denote x ( i = 1 or j = 1), y ( i = 2 or j = 2), or z ( i = 3 or j = 3).

One may now briefly refer to the multiplication of scalar α by tensor τ– represented by

(5.26) which may be rewritten as 527 in view of Eq 52 the distributive and - фото 1138

which may be rewritten as

(5.27) in view of Eq 52 the distributive and commutative properties of - фото 1139

in view of Eq. (5.2); the distributive and commutative properties of multiplication of scalar by matrix as per Eq. (4.34)produces

(5.28) or in condensed form 529 which is equivalent to writing 530 - фото 1140

or, in condensed form,

(5.29) which is equivalent to writing 530 in parallel to Eq 420 The scalar - фото 1141

– which is equivalent to writing

(5.30) in parallel to Eq 420 The scalar or dot product of a vector uby a tensor - фото 1142

in parallel to Eq. (4.20).

The scalar (or dot) product of a vector uby a tensor τis a vector defined by

(5.31) inspired by Eq 352and taking advantage of Eq 447 or in condensed - фото 1143

inspired by Eq. (3.52)and taking advantage of Eq. (4.47)– or, in condensed form,

(5.32) if the order of multiplication is reversed one obtains 533 that may be - фото 1144

if the order of multiplication is reversed, one obtains

(5.33) that may be rephrased as 534 so inspection of Eq 534 visàvis with - фото 1145

that may be rephrased as

(5.34) Mathematics for Enzyme Reaction Kinetics and Reactor Performance - изображение 1146

– so inspection of Eq. (5.34) vis‐à‐vis with Eq. (5.32)indicates that

(5.35) Mathematics for Enzyme Reaction Kinetics and Reactor Performance - изображение 1147

except if τis symmetric (as τ ji = τ ijunder such circumstances).

The scalar product of two tensors, σand τ(also known as double dot product, :), is a scalar defined as

(5.36) where straightforward algebraic rearrangement was used to advantage or in - фото 1148

where straightforward algebraic rearrangement was used to advantage – or, in condensed form,

(5.37) Here tensor σabides to 538 while 1 3 row vectors σ x σ y and σ - фото 1149

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