ChemicalEngineeringScience, 1960, Vol. 12, pp. 24s to 252. Pergamon Press Ltd., London. Printed in Great Britain
Studies in optimizationI The optimum
design of adiabatic R.
Department
of Chemical Engineering,
reactors with several beds
ARIS
University
of Minnesota,
Minneapolis
14, Minnesota
(Received 1 December 1959) AbstractThe optimum design of an adiabatic reactor involves the choice of the size of each bed and the amount of interstage cooling between beds. These decisions can be made in an orderly way by applying the notion of dynamic programming, and in the case of a single reaction allow of a simple graphical presentation. The principal subject of this paper is case of a single reaction with costs proportional to the bed volume and the amount of heat removed. It is shown that this simple model suffices to solve a number of more general problems. ResumeLe projet optimum d’un r6acteur adiabatique met en jeu le choix de la dimension de chaque lit et la valeur, a des stades intermediaires, de la refrigeration entre les lits. Ces conclusions peuvent etre times methodiquement par l’application de la programmation dynamique et dans le cas oh une reaction unique permet une representation graphique simple. Le sujet principal de ce memoire traite le cas d’une reaction simple dont le cotit est proportionnel au volume du lit et a la quantite de chaleur Climinte. On voit que ce simple modele suffit pour r&oudre un certain nombre de problemes les plus generaux. ZusammenfassungDie opthnale Gestatlung eines adiabatischen Reaktors Iauft hinaus auf die Wahl der Abmessungen jeder Kontaktschicht und den Umfang der Kiihlung zwischen den Kontaktschichten. Diese Entscheidungen konnen durch Anwendung der dynamischen Programmierung getroffen werden. Im Falle einer einfachen Reaktion ist eine einfache graphische Darstellung moglich. Hauptgegenstand dieser Arbeit ist der Fall einer einfachen Reaktion, bei dem die Kosten proportional dem Kontaktvolumen und der abgefiihrten Reaktionswiirme sind. Es tird gezeigt, dass dieses einfache Model1 geniigt, urn eine Reihe allgemeiner Probleme au Ibsen. 1.
TIDETYPE
to be considered
one or more adiabatic single reaction
the composition
INTB~BuCTI~N
of reactor
beds of catalyst
is taking
place.
the first bed and between
consists
of
in which a
Before
cooling
from equilibrium
stages
is needed
conditions
for,
and temperature
if the
of reaction reaction
composition,
each bed the reaction
obtained
by
reaction
is entirely
variations
are
is exothermic,
the
used in heating
up
mixture.
For a fixed reference from which the reaction mixture is letting
the
reaction
proceed
to
a
certain point, the composition at all times can be specified in terms of the concentration of one
example, in the oxidation of sulphur or the production of methanol. The between
heat the
entering
mixture is heated or cooled to the most suitable temperature. Such a reactor is commonly used, as, for dioxide
related,
reactant. composition
to keep away
and is accomplished
either by an interchanger or by adding a cold shot of reactants to the reaction mixture ; in this paper we shall be concerned only with interchanger cooling. When a single reaction is considered the design of such a reactor is susceptible to a simple graphical procedure. Since the beds are adiabatic 243
Thus, of
for the
example, reacting
if the
reference
mixture
were
0, : SO, : SO, = 34 : 65 : 1 (per cent volume mole fraction) then when the concentration
or of
SO, is c, the stoicheiometry of the reaction gives concentrations of (0.345  0.33 c)/l.O05 and (0.66  0.67c)/l.O05 for 0, and SO, respectively. We shall use the concentration c of the product to define the composition of the mixture so that, if T is its temperature, the state of the reactants
R. ARM
at any instant can be represented by a point in a cT diagram such as is shown in Fig. 1. Let the rate of reaction be a function of composition and temperature R (c, T), then if z, is the linear velocity of flow and x the distance along the bed, a mass balance gives v$=R(c,T)
(1)
reactants at the inlet to a bed (the point A in Fig. 1) the composition and temperature at any other point are related by T = T, + h (c 
c,,)
(4)
It follows that at any point in the bed the rate of reaction is a function of c only, namely R (c, T,, + h (c  q,)) = rj (c ; c,,, T,). Equation (1) can now be integrated immediately, for, setting 2 = x/v, the variables separate to give t&)=
s= dc
(5)
Fi3
where (t  t,) is the holding time of a bed that suffices to raise the concentration of the product from cO to c. The adiabatic paths can thus be graduated in the variable t and the bed size required to get from a state A (c,,, TO) to another state B (cl, T,) is the difference of the graduations (4  to). The reactions for which this type of reactor is used are generally limited by equilibrium and at a given temperature T the reaction cannot yield a greater concentration than ce (T). If this function is plotted in the cT diagram it gives a curve, C,, along which R E R (c, (T), T) = 0, and we are limited to the left hand side of this curve. Since the reaction velocity is small for low temperatures and vanishes on the equilibrium curve, C,, there must be a point on each adiabatic line at which R is greatest. Let such a point be (c,, T,), at which
Temperature
FIQ. 1. The adiabatic paths in the concentration
temperature plane.
Since there is no heat loss a heat balance over an element of the bed gives ocpp~=HR(c,
T)
(2)
where cP is the specific heat and p the density of the reaction mixture and H is the heat of reaction. Writing H/c, p = h and dividing (2) by (1) we have
dT dc
T=.
h
h will generally be a function of c and T so that (3) is a first order differential equation which has to be solved for the relation between c and T in any adiabatic bed. For simplicity we will assume h is constant (though the analysis is equally valid for varying h) and the adiabatic paths are then straight lines with slope l/h, as shown on Fig. 1. Thus if c,,, T, is the state of the 244
g
+,hg = 0,
(6)
and denote the locus of these points by Then the intersection of this curve with adiabatic line gives us a suitable origin for integration in (5), and we can graduate adiabatic lines with
R [c, T,
+ h (c 
cm)]
C,. an the the
(7)
=m
Fig. 2 shows some typical curves for the reversible reaction A _‘B first order in the concentrations of A and B. The curves C,, C, and some of the
Studies
in optimizationI taken in seeking the optimum policy for an original state 0 are thus connected with the points A, B, C etc. and we might expect that in a good design the line segments AB, CD, etc. would lie over the curve of maximum reaction velocity. To formulate the optimum problem precisely we must first construct a suitable profit function. 2.
c
0
lh.
THE PROFIT FUNCTION AND METHOD OF MAXIMIZING IT
550
600
%. Concentrationtemperature plane order reversible reaction.
The beds of an Nstage adiabatic reactor will be numbered backwards, N being the first bed the reactants enter and 1 the last. Primed quantities will denote exit values and unprimed inlet values. Thus c’r is the exit concentration from the last bed (and T’, the corresponding temperature) ; cl is the inlet concentration to the last bed and equals c’~, the exit concentration at the penultimate. We may consistently write the feed condition as c’~.+~, T’,, and c’,+~ = c,, N. Thus the total increase in n=l,2,... concentration is
650
for
first
cI1  C’N+r= _? (c’,  c,). contours of constant t and R are shown ; Cm is by definition the curve t = 0, whilst C, is R = 0 ort= co. The interstage cooling that is required to bring the reactants away from equilibrium can also be represented on the cT diagram. Supposing the reaction mixture enters the first bed in a state corresponding to the point A (Fig. 1) and the bed is of such a length that it leaves it in state B. In the interchanger it is cooled down to a lower temperature but does not change in composition. This is represented by a horizontal line BC, where the abcissa of C is the temperature to which the reactants are cooled. In the next bed the reaction will follow the adiabatic path through C, reaching the state D, for example. Finally we may observe that as originally available to the reactor the reaction mixture will be of a certain composition but probably not at the best temperature ; the point 0 represents such a state. It is therefore necessary to heat, or cool, the reactants to the inlet temperature most suitable for the first bed. The decisions that have to be
1
If q is the flow rate and a the value of a unit quantity of the product, the rate of increase in value of the product stream is a Q (c’~  c’~+J. This is the simplest expression for the rate at which money is made by the reaction process ; more sophisticated profit functions will be discussed in the last section. The cost associated with the process are those of providing and maintaining the catalyst beds and heat interchanges. We will again consider these as simple proportionalities, reserving generalizations until later. The cost associated with the bed will be taken to be proportional to the total volume p 5 tn. This includes the cost 1
of the catalyst, of maintainance and of construction amortized in the conventional way. The cost of heating or cooling will be taken to be proportional to the total heat added or removed, namelypc,p
;IT, 1
two
245

T:+,l.
If fi and y are the
unit costs the net profit from the reaction is
the optimum policy for Nstages. this may be written fN
If we write h = /3/u, TV= y cr p/a total profit is q ccPN, where P,=
then
the
&I,== 1
&‘+l, Th+,)= Max{%
In our notation
(ck,Tk)} (10)
+fN1
where the maximum is over variations of t, and m 1 1, p~=&cN&t+kT;v+ll and C’N
tN=
s
(11)
dc
R [c, TN + h (c cN)] ’ cN = ‘IN+1
J
CN
The optimum problem may now be stated in precise terms : Given the initial state c;+~, Tk+, and the constants h and p, the bed sizes t,, t,, * * * t, and inlet temperatures T,, T,, . . . TN are to be chosen so that the greatest value of PN is attained. Although this may seem a somewhat restricted problem it will be shown later that it can be extended to cope with more When the choice of complicated situations. policy (t,, T,, n. = 1, 2, . . . N) has been made, the resulting maximum of PN will be a function only of c;+~ and Tk+l,
[email protected];+I,
Tk+,) = Max PN
(9)
It is thus necessary to make a choice of 2N variables and if these have to be found simultaneously the problem is formidable. However, by using the methods of dynamic programming the problem can be reduced to a sequence of problems each of which requires the simultaneous choice of only two variables. To show this we first observe that the Nstage process and the profit function can be broken into two parts, the first stage (labelled N) and an (N  I)stage process. The exit conditions ch, T& of the first stage are the feed conditions for the subsequent (N  1)stage process. The optimum from the Nstage process with respect to its feed cL+~, Tk+, will certainly not be achieved unless the (N  1)stage process is giving its best with respect to its feed CL, Tk. If we know the optimum (N  1)stage policy we can get the optimum Nstage policy by varying the operating conditions t,, TN of the first stage only, always using the optimum (N  1)stage policy for the subsequent stages. By selecting the tN, TN for which PN is greatest we shall have 246
Equation (10) gives a simple method of successively calculating fi, fi,...fN ; f. is, of course, zero. We are thus led to consider the optimum design of a onestage reactor first afterwards making it the second stage of a twostage reactor, and so on. The socalled principle of optimality, on which dynamic programming rests [l], has been invoked to establish the basic equation (10). 3. THE OPTIMUM PERFORMANCE SINGLE BED
OF A
For a single bed we have
fi(c'~, T’,)
= Max p1 =
Max{c’,

c1 
At, CL IT, 
T’sl}
(12)
where the maximization is by correct choice of t, and T,. Suppose that T, has already been chosen, then since c1 = c’, we are already committed to the adiabatic path through (cl, T,) and have to choose t, to maximize pi. However from (12) and (7). 3Pl _=Aat,
dc1’ dt,
h = R (c’~, T’,) 
h
the derivative being taken along the adiabatic path. If p1 is to be maximum the end point (c’i, T’,) must therefore lie on the curve R (c, T) LMoreover only the A, which we denote by r’l. part of the curve R = X which lies to the right of C,,, is of interest since otherwise bp&, would be negative during the reaction, which is uncounprofitable. Analytically the condition for the end point is R’, = R (dl, T’,) = R (~‘1, T, + h (cfl 
cl)) = h
(13)
Studies in optimkbtionI Consider now the choice of the best T,, that is the point A on the horizontal line c = cl2 = cl. Denote by I, the integral
For given c’s = c1 the optimum policy for the choice of T, and the resulting maximum profit fi is now seen to have a very simple structure. In Fig. 4 S, and S* are the points where the tangents at T,+ and T*, meet the axis I1 = 0. Then if:
where cfl is always chosen to satisfy the condition (Is), so that I1 is a function of T, only. If A is at C in Fig. 3 the intersection of c = cf2 and P1 then cI1 = c1 and I, = 0. As T, decreases (A moves to the left) I, will increase at first and then decrease for in the position A’ B’, where B’ is the intersection of c,,, and Pi, I, is certainly negative. It follows that I, as a function of T, must be a curve such as is shown in the lower part of Fig. 3. But
FIG. 4. ~Jc’~, T’J for a given c’,
0)
T’, < S,, p1 is always negative and it is unprofitable to react (i.e. the reactants are so cold that it is not worth heating them up at the cost of heating p).
(ii)
S, < T’, < T1*, p1 is maximum when T, = T,. (i.e. the reactants should be heated to T,+ before entering the reaction bed). fi= I1 (T,.)  /I (T,*  T’J.
(iii)
T,. < T’, < T*l, p, is maximum when T, = T’, (i.e. the reactants should be introduced into the reaction bed immeddiately). fi = I, (T’,).
(iv)
T,* < T’, < S*, p1 T, = T*, (i.e. the cooled to T*, before bed). fi= I, (T*,) 
Fra. 3. The construction of the integral 1,
difference between the humped curve of I, just constructed and the Vshaped curve The maximum difference will P IT,  T’,I. occur when T, has a value of either T,+ or T*, the point at which 31&T, = + ~1or  p.
is
maximum
when
reactants should be entering the reaction p (T’, 
T*,).
the
I, (c’w T,,) fi
@a’,T’,) =

(v)
p (T,.
S* < T12, p1 is always negative (i.e. the reactants are too hot to be worth cooling).
Moreover the maximum profit function 
T’s),
T,e < T’, < T,*
I, (c’s, T’s), I1 (c’z, T,*) 
S. < T’, < T,.
/a(T’*247
T*,),
T*, < T’, < S* !
(15)
is precisely the curve I, (c’~, T’,) bevelled off with its two tangents of slope f p. In the last paragraph cl2 = c1 has been held constant and the values of T*, and T,+ determined. If this is done for various cl2 we obtain T*, and T,+ as functions of cIz. These may be plotted in the C, T plane as a curve I’, having The optimum two branches, r*l and I’,,. policy for a single bed is completely given by the If the feed curves r, and r1 as in Fig. 5. point c’~, T’, lies to the left of r,, (as A in Fig. 5)
The foregoing construction has been given to show the structure of the policy but to calculate the curve r, it is best to proceed analytically. Thus (14) is actually C'l
II (c’mT’,)
=
1 
so
dc
+,T,+:(c~,)]
S( c*a
(16)
I
In both the integrals I, and J, the upper limit lies on the curve Pi so that on any adiabatic path J, can be calculated as a function of the lower limit by integrating back from the upper limit. Now hi01 __=
&
JTI
(4 
P
IT1 T’aO=
h J, F p according as T, >< T’,.
WIG. 5. Typical optimum policies with one bed.
the policy is to heat the reactants to T,* (c’& (point B) and then react until R (c’~, T’,) = h (point C). If the feed point lies between the two branches of r, the policy is just to react (the line DE). If the feed point lies to the right of r*i the reactants are cooled to T,* (c’~) and reacted (the line FGH). Since the single bed will next be regarded as the second of two stages it is the last situation that is important. The surface .f, (c’~, T’,) is shown in Fig. 6.
Then on any adiabatic path we can find the points at which J, = f p/A and these are the intersections of the curves r,, and Pi with the adiabatic path. For the next step it is necessary to have the partial derivatives of Jr. These will only be stated here ; the proof of them is given in the appendix. In these formulae it is understood that J, is calculated using the optimum policy for its end’ points and R, = R (cl, T,), Tl being chosen optimally. Then
bf1_
(18)
3c’a
e&&J
(19)
1
ZIT’,
$+h$,=2
c;
(20) 2
If c’~, T’, lies outside the branches of the curve r, then h J, = p or  II. In the important case T’, > T*, (c’,) X J, =  p. 4.
THE OPTIMUM PERFORMANCE OF SEVERAL BEDS
In
the
conditions
FIG. 6. The optimum yield surface. 248
case
of two
cP3, T’,
adiabatic
we have
beds
with
feed
Studies in optimizationI
f2(c’~,T’d = Max (p2+ fI FzT y2)}
(21)
where
p2~~a(l;)
It is evident that r’, must lie between C, and rrl. This is shown in Fig. 7. Analytically we find T’, as a function of cf2 by solving
/.&IT,_‘,I
R
% =I,,ulT,
T’,I
(22)
[c’z,
T’,
(c’,,]
=
R
[~‘a,
T*,
(c’,,].
To find the best value of the inlet temperature T, we proceed as before. The quantity
We again assume T, the inlet temperature to 12 +fi (~‘29 T’2) the first bed to have been fixed and ask at what as a function of T, for fixed c2 gives a humped concentration cl2 the reaction in the first bed distortion of the curve of Fig. 4 to which we can be stopped to give the greatest value of p, + fi. draw the tangents with slope & p and obtain T’, is linearly related to c’% by f2 precisely as before. This will yield two temT’, = T, + h (c’~  cJ peratures T,, and T*, to which the reactants should be heated or cooled according as T’, is so differentiating along the adiabatic path less than T*, or greater than T*,. Again a curve r2 with two branches can be drawn in the c, T plane and the policy for a twostage reactor is found immediately in the same way as before. Setting this derivative equal to zero for the maximum and using (20) and (22) we have (l&)((1&o
where R’, = R (c’~, T’,).
Thus
R’, = R (d2, T’,) = R (cl, T,) = R,
(23)
and the reaction in the first bed should continue to such a point that on cooling to the optimum inlet temperature for the second bed the reaction will continue at the same rate. This is a remarkably simple criterion and allows a curve P2 to be drawn on which the exit conditions of the first bed must lie. To construct P2 we have only to take a point cl, T, on the curve r*l and draw through it the line of constant reaction rate R until it again meets the horizontal line c = cl.
FIG. 7. Exit conditions for
the first of two beds.
FIG. 8.
Typical
optimum
policies with two beds.
Fig, 8 shows the three different kinds of reaction path given by a reaction mixture initially too at a suitable temperature cold (ABCDE), (FGHK) and initially too hot (LMNPQ). This process will generate an optimum policy surface f2 (c’~, T’J lying wholly above the surface fi and therefore extends to some degree the limits S,, S*, without which it is unprofitable to operate. Analytically the condition for the optimum T, simplifies in a remarkable way and if T’, > T, 249
Aaxs
R.
the same derivative is whilst if T, < T’, h J,  2~. Thus Fe2 and r,, can be determined by integrating back from r2 along the adiabatic until J, = 0 to give r*2 and on until J, = 2h/h to give r*p The detailed manipulations are given in the Appendix. Even more remarkable is the fact that the partial derivatives offs (c’s, T’,) have the same structure as before and in particular the derivative in an adiabatic direction is
$+I++$) a
3
a
where R, is the reaction rate at the optimum inlet conditions (cz, T,) for the feed (c’s, T’,). Because of this we can proceed to the three bed optimum with equal ease. I”* the curve on which exit conditions of the first of three beds should lie is constructed from l”*a in the same way as p2 was constructed from r*r (see Fig. 7). When I”s is known, r*3 and I’,, can be found as the curves for which J, = 0 and 2p./h respectively. 5.
GENERALIZATIONS
Although the profit function PN may appear to be too simple to be realistic it can be adapted to meet a variety of practical problems. Until now the parameters h and p have been regarded as constants, but it is clear that the optimum policy is a function of X and CL. The maximum profit function is thus fN (&+,,Tk+, ; A, p). In particular if p is fixed the total bed volume V, = q $t,,
will depend upon h.
By repeating
the calcilation for various h the function V, (X) may be found ; it is a monotonic decreasing one for X is the relative cost of bed volume and the higher this is the smaller will be the optimum volume. If then a design were asked for to give a certain total volume V it would be the solution of the optimum problem outlined above with X = X, so chosen that V, (A,) = V. This might be a consideration of overriding importance as, for example, when the reactor is required to fit into some existing high pressure forging, which is too valuable to waste. Programmed for a
modern computer such a problem as this would be very rapidly solved. If the interchangers between stages had also to be accommodated within a given volume it would be necessary to vary both h and p and to use data on the volume required by an interchanger removing a given amount of heat according to best design practice. In this case for each p there would be a value of X = (1 (p) satisfying the volume requirement and the final choice of p would be the one that made fN&+,, Tk+l; ~h.4, P)thegreatest. Again supposing h and p are known we might ask for a design with a given output Q = q(c'l  &+I). Here we may take into account the cost of pumping the reactants at a rate q. For any q the exit concentration cfl = c’~+~ + Q/q. We can design the last bed first for its exit conditions must he on rll. Taking the adiabatic back from the point c = c’~ on p1 to r*l we have the inlet conditions to the last bed cl, T,. Moving to the right along the line c = c1 to the curve rla gives the exit conditions of the penultimate bed. Again moving down an adiabatic we find cs, T, on r*2 and so on. Some adiabatic line will cross the horizontal line through the feed c = cF and this intersection will give the feed conditions to the first bed. Thus the number of beds to give the required output has been found and the volume of each may be calculated. Using the accepted design practice the pressure drop through the reactor may be found and hence the cost g (q) of pumping the reactants through at a rate q is found. Finally q is chosen to maximize fN (ch+,, Tk+,)  g(q). If the value of the product is not proportional to C’l but is a more [complicated function, say
9(z (c’r)  2)(&+J> = q 5 (v (c’,)  v (c,))
precisely the same technique may be applied as above save that we redefine the integral I as tin I,, = v (c’,)  v (c,)  h
2
s =n
d?l =
s 53
{v’ (c)  A/R}&
if v (c) is differentiable. The curve r/1 is now given by v’ (c) R (c, T) = A. A specification restriction could be included in v (c), for in case c must lie between c* and c* we could set
250
Studies in optimizationI v (c) E o outside this interval. More interestingly v (c) might take account of subsequent operations on the product stream such as the separation of the valuable product. If the optimum policy of operating the separating unit is studied so that v (c) is maximized with respect to this operation then the principle of optimality shows that we would find the optimum overall policy for both reactor and separating unit. If the cost of bed volume and heat interchange is not proportional to the volume or the heat removed the optimum problem can still be solved by solving the sequence of equations (lo), using the appropriate nonlinear expressions in p,. In this case, however, the simple structure of the policy will be lost and it will no longer be possible to draw the sequence of curves rln and r,* The solution, however, is still within the powers of a modern digital computer. It thus appears that the method of dynamic programming is well suited to a number of significant problems in the design of adiabatic reactors. It may be extended to the design of coldshot reactors and to the case of more than one reaction, as will be shown in later publications.
(27) In the region S, < T’, Q T,, C'l
UC’,, T’,)
S(’ 
h
R
[c,Tl,
(c’~) + h (c  c’~)]
c’a
+ P(T’,  T1*)
Here
but R’, = X and AJ, = p ao
that
Clearly 3jr/3T’.r = p = AJ,, so that the same formulae apply, it being understood that the path for J, is chosen optimally. A similar calculation for the region Tr* < T’, < S* gives the same formulae. To establish the formula (24), let T’, > Ts2 and h
F2 = ’ 
R [c, T, + h (c  c2)]
% B
APPENDIX To calculate the partial derivatives of jr we consider the three regions defined by (15). Take 6rst the region Tr, < T’, < T*, in which
dl fl (C’P’T’,) =
Sl’ 
h
R[c, T', + h (c  cl)]
c
df+
I
(T’,  T,) +fi
@‘$‘g)
and observe that c’~ and T’, are both functions of T,: However since T’, = T, + h (c’,  cz) we have
JT’a_ I++. 35
Then
de
de
8
(28)
and R’, = R [c’~, T’, + h (c;  c’~)] = X and c1 = c’* In the expression on the right side of c’r ia a function of c’, and T’,. Thus differentiating the limita and under the integral
+XJ,+p+AJ,
?+$$(Li$)AhJ,
ad,
= AJ,;
But since RI’ = X the Arst term vaniahea and
&J,
(25)
Similarly
(26)
(29)
to get the second line we use (25), (26) and (28) and the fmal reduction depends on the fact that Rr = R’, and AJ, = p. In case T, > T’g the sign of the term p(T’,,TT,)inFgmustbechanged,thisglvesa pin the penultimate line of (29) and 80 aF,/dT, = AJn  2~. To show how the derivative of la simplifle8 eo dramatically we will consider the case T; > T*a (c;). Here
fs (c’~,
and
251
T’*) = I4 
p (T’, 
T+*) + fi (~‘8, T’B)
(80)
R. AEIS and the R in I, is R [c, T,*(c’,) + h (c T’, both depend on c’s and T’s but since T;
= T*2 CC’~)+ h (c’* 
in this region this formula Finally
c’~)]. c’* and
can again be extended.
c’~)
(34)
we have is everywhere valid, so that the derivative along an adiabatic path of the optimum fa is related to R, just as the derivative of fl was related to RI
NOTATION c = concentration of product cp = specific heat of reactants %I = concentration for maximum reaction fN = maximumprofit from N beds H = heat of reaction h = H&p I = integral defined by equation (16) J = integral defined by equation (17) N = number of beds PN = total profit from N beds p, = profit from nth bed q = flow rate of reactants R = R (c, T), reaction rate T = temperature t = holding time, B/V V, = total volume of N beds u = linear velocity of reactants u (c) = value function of product z = distance from inlet of bed c( = unit value of product p = unit cost of bed volume y = unit cost of heat interchange x = j3/a
in which the frrst line is the derivative ef Is. Making use of (31), (25) and (26) and collecting terms together

hh(J,
+J,)
+
since the square brackets vanish. Of course the second term is really hp. However a little shows that in the form (32) the expression is T’, < TeP, it being understood that J, is on path.
J, = 0 so more work valid when an optimal
range
p=ycpplu p = density of reactants
Clearly =V!4 3T’,
~=((xJ,d
Suffix n denotes value in the rat” bed from the exit. A prime denotes conditions at exit of any bed.
(33)
REFERENCE [l]
BELLMAPI R. Q.paam~cProgramming.
Princeton
252
University
Press.
Princeton
1957.