by
Conor J. Walsh
An Engineering Project Submitted to the Graduate
Faculty of Rensselaer Polytechnic Institute in Partial Fulfillment of the
Requirements for the degree of
MASTER OF ENGINEERING
Major Subject: MECHANICAL ENGINEERING
Approved:
_________________________________________
Ernesto Gutierrez-Miravete, Project Adviser
Rensselaer Polytechnic Institute
Hartford, Connecticut
December, 2013 i

© Copyright 2013 by
Conor J. Walsh
All Rights Reserved i i

LIST OF FIGURES .......................................................................................................... iv
LIST OF TABLES ............................................................................................................. v
LIST OF KEYWORDS .................................................................................................... vi
ABSTRACT .................................................................................................................... vii
INTRODUCTION/BACKGROUND ................................................................................ 1
THEORY/METHODOLOGY ......................................................................................... 10
RESULTS AND DISCUSSION ...................................................................................... 22
REFERENCES ................................................................................................................ 37
APPENDIX A: HISTOGRAM PERCENTAGES........................................................... 39
APPENDIX B: COMSOL REPORTS............................................................................. 41
APPENDIX C: SPECIAL RESULTS SECTION ......................................................... 100 i i i

Error! No table of figures entries found.
i v

Table 1.1: Maximum Yield for Various Homebrewing Malts .......................................... 6
Table 3.1: Mash Tun Parameters Evaluated Through x-y Plane Models ........................ 26
Table 3.2: COMSOL Results from Varying Number of Manifold Legs ......................... 27
Table 3.3: Mash Tun Parameters Evaluated Through y-z Plane Models ........................ 29
Table 3.4: List of Mash Tun Parameters Considered and Impact on Performance ......... 32 v

body , 2 channeling , 28 hydrometer , 4 mash tun , vii mashing , vii mouthfeel , 2 oversparged , 20 sparging , 2 batch sparging, 3 continuous sparging, 3 no sparge, 3 s pecific gravity , 4 undersparged , 20 wort , 1
v i

A mash tun is the device used when brewing beer that allows fermentable sugars to be extracted from malted grains (called mashing ). The grain is crushed, then allowed to soak in hot water in the tun for a proscribed period of time in order to activate enzymes in the malt, which in turn convert starches in the malt into sugars. The water is drained from the grains, and then more hot water is used to rinse the grains in order to extract further sugars. The mash tun must include a filter of some kind to allow for hot water to run through the grain and carry the sugar out while leaving the grain husks. For homebrewers, a popular design for filtering is the pipe manifold: a series of pipes with small slots that allow water to enter, then exit the mash tun. This style of mash tun will be modeled in COMSOL and optimized for maximum sugar extraction and wort quality, given some parameters common to the average homebrewer.
The advantages and disadvantages of various design modifications are not obvious or readily available to the average homebrewer and home mash tun designer.
There are a number of parameters that can be varied during the mash tun build, and it is not at all clear how each factor affects the final device. When designing a set up that maximizes extract efficiency and wort quality, a homebrewer would be well served to have an ideal design on which to base their own mash tun.
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On May 9, 2013, Alabama's Governor Robert Bently signed into law House Bill 9, making his state the 50th to pass legislation legalizing the production of beer within the home. This event was considered by many to be long overdue, as Federal restrictions on homebrewing were repealed with H.R. 1337, passed in October of 1978. This final legal step also coincides with a recent increase in public interest in the United States in the homebrewing hobby, and contributes to the passage of homebrewing from the underground out into mainstream culture. This marks an ideal time for the homebrewing community to take advantage of these developments and bolster the beer-making craft with science and technology. This is not to say that no one in the community has yet pursued the scientific side of brewing; obviously, commercial breweries in the U.S. have been advancing in technical prowess since the end of Prohibition, and books such as
Charlie Papazian's The Complete Joy of Homebrewing (1984) are testament to the existence of a technical approach to homebrewing for decades. To some extent, however, homebrewing is very much still an art. This project aims to move in the technical direction by utilizing the simulation capabilities of COMSOL Multiphysics, an easily accessible and highly capable modeling program. In particular, this project will evaluate a mash tun, and will attempt to produce reliable technical results that can be used by any homebrewer.
At a high level, the recipe for beer is a simple one: water, malted grains, hops, and yeast. Other ingredients can be and often are added, but only four ingredients are required to make beer. The major steps in the beer process can also be outlined simply.
First, grain (usually barley) is wetted and allowed to partially germinate before dried in a kiln. This is the malting process, and is done in order to convert starch reserves within the grain into more easily fermentable sugars. Next, the malted grains are soaked in hot water in order to extraction those fermentable sugars, and then rinsed to ensure as much sugar is removed as possible. This step is the called “mashing,” and the device in which it is conducted is called a “mash tun.” The water/sugar mixture (which is now referred to as wort ) that exits the mash tun is then boiled, at which point hops are added. It is this step that determines the bitterness of the beer. Finally, the wort is cooled and filtered to remove hop material, and then combined with beer yeast in a fermenter vessel.
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In the fermenter the yeast will eat the sugars and produce alcohol and carbon dioxide, forming beer.
The mashing process is critical to the final taste, aroma, color, and body of the beer, and provides an excellent opportunity to use science and technology to improve the homebrewing experience. The alcohol content in a beer is contributed by the yeast, and the strain of yeast chosen by the brewer will often determine how much of the fermentable sugar available in the wort will be converted and how much will remain.
However, the mash step determines exactly how much of the fermentable sugar is available, and thus provides the upper limit for alcohol content. Further, most malts also provide some level of nonfermentable sugars (highly caramelized and long-chain sugars known as dextrins) and proteins to the wort. These compounds cannot be broken down by the yeast, and will be present in the final beer. It is these compounds that contribute most to the mouthfeel and body of the final product, which are both beer tasting terms used to qualitatively assess the beer’s viscosity and density: literally, how the beer
“feels” in the mouth. Finally, the nonfermentable sugars also help to determine the beer’s sweetness.
Mashing can be further broken down into the initial steeping step (where the grains simply sit in hot water) and the subsequent rinsing step (called sparging ). After the malted grains are crushed in a mill in order to facilitate complete hydration and expose the inner grain material, it is added to hot water (usually at a temperature of 160 to 165°F) in the mash tun and allowed to sit there for some period of time, usually
around 1 hour (see Figure 1.0.2). The mash temperature should settle at a temperature
between 150 and 155°F, and kept there for the entire steeping time. This is why plastic coolers are the mash tun structure of choice for homebrewers: they make relatively cheap and easily available options for creating moderate thermal insulation. Any offthe-shelf plastic cooler will provide the thermal insulation sufficient for the precision required of a beginner to intermediate homebrewer.
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Figure 1.0.1: Mashing Process
After steeping, the newly-formed wort (water-sugar mixture) is then drained from the mash, and the sparging process is initiated. At this point, there is still a considerable amount of fermentable sugar left in the malted grains, and the goal of sparging is to extraction as much of the sugar as possible without extracting other undesirable compounds, particularly tannins. Tannins are astringent, bitter polyphenol compounds that are produce some of the most common off-flavors in beer. The astringency of tannins creates a dry, mouth-puckering sensation that is much more common and desirable in wine. The bitterness of tannins can also throw off a recipe’s ratio of bitterness to sweetness, causing the sweet malt notes to be muted more than intended. Other undesirable compounds can also be extracted from over-sparged grain husks, and for this reason sparging requires a delicate balance.
Different sparging techniques exist, but generally fall into three categories: no sparge , batch sparging , and continuous sparging . The no sparge method is exactly as it sounds: no further water is added to the grains, and whatever wort was drained off from the initial steeping step. This method is highly inefficient, but is simple and often used by beginners. It also has the added benefit of low risk of tannin extraction. Batch sparging is akin to a more rapid version of the steeping step: water is added, the mash is stirred and allowed to settle, and the wort is drained off. Continuous sparging is a more advanced process where sparge water is slowly added while wort is slowly drained off
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such that the overall level of water in the mash tun is not changing. This process can take some time, anywhere between 30 minutes and 2 hours. Continuous sparging is significantly more efficient than batch sparging and as a result is used by all commercial breweries. Additionally, continuous sparging prevents possible oxidation damage that occurs by exposing the grain periodically to oxygen as in batch sparging. This is done by maintaining a small amount of water above the grain bed at all times, usually about
1” high, that is kept constant by regulating flow into and out of the mash tun. In fact, commercial breweries take the process one step further, using closed piping systems to transport the hot wort after it leaves the tun. Oxidized phenolic compounds can contribute to a darker wort color, harsher flavor, reduced protein coagulation and reduced flavor stability in the packaged beer [1]. Wort quality and flavor consistency is much more of a scientific process in commercial breweries, and damage due to oxidation is unlikely to be a major problem for beginner and intermediate homebrewers, if at all.
However, the increase in efficiency through continuous sparging is attainable for homebrewers, and can be done with a simple setup. Using a container with the heated sparge water elevated above the mash tun (which is in turn elevated above wherever the wort will be collecting), the flow of sparge water can be gravity-driven into and wort out of the tun and regulated with valves to ensure that the flow is slow and equal. However, with this increased efficiency there is an increased risk of over-extraction of certain areas of the grain bed when using the continuous sparging process, potentially causing extraction of unwanted compounds from the grain and leading to the development of offflavors. For this reason, one must also make sure to consider wort quality factors along with extraction efficiency.
When calculating the extraction efficiency of a beer, the concept of specific gravity must first be addressed. Specific gravity is the ratio of the density of any liquid to the density of water, such that the specific gravity of pure water would equal exactly
1. Specific gravity is a direct measurement made by homebrewers using a hydrometer , which is simply a device that is floated in a small amount of liquid and calibrated to
show the specific gravity based on the density of the fluid (see Figure 1.0.3). Specific
gravity of beer generally varies between 1.005 and 1.150, and as such is usually
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expressed in “points,” where the leading 1 is dropped and the remainder is multiplied by
1000. For example, a specific gravity reading of 1.040 would be 40 “points.”
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Figure 1.0.2: Hydrometer Reading
Using the specific gravity measurement, the volume of wort, and the amount of malt added to the mash tun, the efficiency of extraction can be easily determined. First, the concentration of sugar in the wort is calculated in ppg (specific gravity points per pound per gallon), called c wort
: c wort
=
V wort

BG m malt
[1]
In this equation, V wort
is the total volume of wort in gallons, BG represents the original specific gravity of the boil (also the specific gravity of the wort after it leaves the mash tun), and m is the mass of the malt used in the mash tun in pounds. Once this value is malt determined, it can be compared to the maximum potential yield from the malt. The following equation defines the extraction efficiency of a beer: e extract
= c wort c max
[2]
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(where e extract
is the extraction efficiency and c max is the maximum yield for the given malt in ppg). The maximum yield can vary for different malts used, but approximate
values are readily available for most common homebrewing malts, as shown in Table 1.1
[2].
Table 1.1: Maximum Yield for Various Homebrewing Malts
Pale 2-row malt
Type of Malt
Pale 6-row malt
Munich malt (Belgian/German)
Munich malt (US)
Wheat malt
Crystal malt
Special "B"
Chocolate Malt
Black Patent
Roasted Barley
Amber/Brown malt
Cara-pils (US)
Cara-pils (Belgian)
Aromatic
Biscuit
Potential Extract (points per pound per gallon)
37
35
37
33
39
34
30
30
29
29
32
33
34
36
35
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Homebrewer extraction efficiency values average around 75%. As discussed above, using the continuous sparging method can greatly increase the efficiency of a given system. The methods for predicting extraction efficiency in this project using computer simulation will be discussed in the next section.
Highly efficient setups are desirable for a number of reasons. High mash extraction efficiency is an ideal goal of a homebrewer looking to save money or simply minimize waste, as a highly efficient mash produces a higher sugar output per grain input. For a specific beer recipe (for which the amount of sugar is a constant, this equates to less grain to buy and less wasted grain overall.
As mentioned briefly above, the highly efficient setups achievable through continuous sparging techniques bring with them an increased risk of over extraction and poor wort quality due to the presence of undesirable flavor compounds. As a result, wort quality should also be considered when optimizing a mash tun. For calculation purposes, wort quality has been found to relate to the overall uniformity of flow of water through the mash tun [3], which will be discussed further in the next section. The mechanism of this correlation is uneven flow throughout the mash tun while rinsing the grain bed, as this can result in over-extraction of certain areas of the grain bed and produce tannins and other compounds that negatively impact taste.
Homebrewers have a limited ability to affect wort quality compared to the commercial brewer: for example, they do not have much control over the quality of ingredients, and must select from those ingredients already available to them in their area or, more recently, through a small number of internet retail providers. Further, they have a limited range of heating and cooling techniques and equipment available to them.
Minimizing off-flavors during the mash is one of the few methods through which they can improve the quality of the wort, and thus the final beer.
The initial inspiration for this Masters Project came from work done by John
Palmer, a homebrewing expert, writer and personality. Palmer, a chemical engineer by education, often approaches homebrewing from a more technical angle than most when writing magazine articles and books. In particular, his book How to Brew and the article
“Fluid Dynamics -- A Simple Key to the Mastery of Efficient Lautering” in the
July/August 1995 edition of the magazine Brewing Techniques both address the concept
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of extraction efficiency and how fluid dynamic analysis can be used to determine the most efficient mash tun designs.
A mash tun must include a filter of some kind to allow for hot water to run through the grain and carry the sugar out while leaving the grain husks. The differences in how this filter is designed are the primary drivers of the efficiency of a mash tun. For homebrewers, a popular design for filtering is the pipe manifold: a series of copper pipes at the bottom of the tun with small slots cut into them, nearly halfway through the pipe
(Figure 1.0.4). The slots of a pipe manifold allow wort to enter while keeping grains in
the mash tun. The pipes are connected and run together to allow the wort to exit through a hole in the tun wall.
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Figure 1.0.3: Pipe Manifold
Palmer focuses on comparing different mash tun types than just the pipe
manifold, including the false bottom (Figure 1.0.5). He comes to the conclusion that the
false bottom is inherently more efficient than a manifold. This is due primarily to the uniformity of flow that occurs in a mash tun with a false bottom, which is essentially a perforated sheet filling the entire tun onto which the grain is placed. Small holes allow wort to pass through an outlet but keeps the entire grain bed within the tun. This design was not pursued in this Masters Project for several reasons. First, while false bottoms are available commercially they are exceedingly difficult to make oneself, particularly with the holes spaced uniformly enough to realize their inherent efficiency advantage over other filtering styles. Additionally, false bottoms available commercially are
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designed only for round coolers or buckets. False bottoms also have few parameters that can be modified and optimized, and do not present a very interesting design opportunity.
Pipe manifolds provided a much more attractive topic for this project for these reasons.
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Figure 1.0.4: False Bottom
In this project, a pipe manifold-type of mash tun will be examined and analyzed using a fluid dynamic computer simulation. Design parameters will be optimized for extraction efficiency, while also evaluating the impacts to wort quality. Above all, the feasibility of a real-world mash tun build will be considered, and the final result of the project will be a practical recommendation directed towards the average homebrewer.
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In order to analyze the extraction efficiency and wort quality of a mash tun, fluid dynamics computer simulations were performed using the COMSOL Multiphysics software. This program was used extensively to model fluid flow through the grain bed and pipe manifold. Ideally a single, accurate 3-dimensional model including all relevant
features would be used to evaluate different mash tun configurations (see Figure 2.0.1),
but due to computation limitations this was not feasible. In place of a single model were substituted two types of 2-dimensional models, by taking various x-y plane or y-z plane
cuts (see Figure 2.0.1) and modifying individual features. These different planar cuts
were evaluated separately, but amount to 3-dimensional parameter modification when all results are viewed in aggregate. In this way, no model considered all of the applicable factors at once, but the results can be combined from the various models to develop an ideal mash tun design.
In 3D, the geometry was contained within a rectangular impermeable boundary, to represent the mash tun, with the dimensions of an average rectangular cooler often used by homebrewers. This geometry (12” x 12” x 21”) was carried over into the 2dimensional models.
Figure 2.0.1: 3-Dimensional COMSOL Geometry Compared to Actual Cooler
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Figure 2.0.2: Planar Cuts of 3D Geometry for 2D Models (Left: x-y plane, Right: y-z plane)
Figure 2.0.3: 2D COMSOL Model (x-y plane type)
As can be seen above in Figure 2.0.3, the x-y plane type of 2D model was made
such that the lower extents of the model end at the level of the pipe manifold. This was done in order to make each leg of the manifold into an outlet for the fluid dynamic
analysis in COMSOL (shown in blue in Figure 2.0.3). The x-y planar cuts that make up
this type of model are intended to represent a plane of the manifold coincident with a slot cut into the pipes, and thus modeling the pipes as outlets in this way is considered
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reasonable. Unfortunately, the 3-dimensional nature of the flow could not be captured, as there is no capacity in the COMSOL module used for flow into and out of the 2D plane. However, the relative improvements of wort quality and extraction efficiency for different mash tun configurations can still be quite easily and reliably compared using this type of model. In fact, the first parameter to be varied (as will be discussed further in the next section of the report) was the number of pipes, which was as simple as
modifying the geometry as shown below in Figure 2.0.4.
Figure 2.0.4: Example Mash Tun Parameter Variation - Number of Pipes
In order to model the specific details (such as slot size and spacing) for the actual filtering features of the pipe manifold and thus be able to determine the effects of their variation, another type of 2-dimensional model was required. Cuts of the y-z planes
were used as shown in Figure 2.0.5 below.
Figure 2.0.5: 2D COMSOL Model (y-z plane type)
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As can be seen from Figure 2.0.5, the y-z planar cuts allow examination of the
slots cut into the copper pipe manifold that actually performing the filtering, in practice keeping the grain bed from flowing out through the manifold but allowing wort to pass through. Additional benefits of the y-z plane models include the ability to examine the area below the manifold, which is unfortunately not possible for the x-y plane models.
In a well-settled (stable) grain bed, the grain will be packed on all sides of the manifold, including this area beneath the pipes, and as such this is also modeled in COMSOL as a part of the porous medium. Understandably, there is a large region of low flow underneath the manifold, and this predictably leads to lower calculated efficiencies for the y-z model runs in comparison to the x-y model. A further benefit of this y-z planar cut is that flow within the manifold can be calculated. This provides further precision and confidence in the calculated interactions around the manifold openings, and allows calculation of the Reynolds number within the manifold itself (which will be discussed further later).
Some critical assumptions were made for the fluid dynamic computer simulation performed in COMSOL, and are outlined as follows. First, it was assumed that the flow rate into and out of the mash tun will be constant and equal, as if it were regulated with valves as described in the previous section of this report. This allows the analysis to be done in a steady state, without the overall volume of fluid within the mash tun changing with time, and also provides the inlet boundary condition necessary for solving the model. This assumption is considered reasonable as the valve-regulated system is a common setup for homebrewers, and is ideal in that it requires the least attention (since the flow is regulated and there is no need to periodically add water or prevent overflowing).
A further assumption is that the ideal sparge velocity is 0.18 [gal/min/ft^2]. This is a value Ludwig Narziss of Weihenstephan Brewery recommended for optimal starch conversion based on empirical results [1] that is now used nearly universally by homebrewers [3] [4]. However, the value is often simplified to the well-known 1
[qt/min] flow rate into the top of a standard cylindrical cooler with a diameter of approximately 16 inches. The methodology used to determine extraction efficiency and wort quality for this project does not allow for reliable calculation of the effects of
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varying this velocity. However, besides the widespread acceptance of this value in the homebrewing community, it also has the added benefit of ensuring laminar flow throughout the mash tun (as will be examined later in the report). In practice, 1 [qt/min] is a flow rate easily achievable and manageable with a standard homebrewing setup.
One final important assumption is that the filter mechanism is assumed to be perfect, which allows the porous media region to stop exactly at the filter features. This is also reasonable, as most filtering setups are successful in keeping any major particles from passing through with the wort. The smaller particles that do make it through are often important components that factor in to the final beer taste and mouthfeel, such as proteins and dextrins discussed in the previous section, and are accounted for in the higher density and viscosity of the wort region as modeled in COMSOL. Additionally, there is another common homebrewing step between steeping and rinsing the grains, commonly called recirculating. This step involves draining wort from the mash tun and adding it again carefully to the top of the mash tun, until there are no visible particles making it through the filter. Recirculating allows the grain bed to compact further, ensuring that large particles are pressed up against the filter features and minimizing the amount of grain particles that pass through during the sparging process.
The intent of this project is that both wort quality and extraction efficiency can be accurately predicted using fluid dynamics. This will be done as follows: first, flow through the grain bed can be analyzed using Darcy’s law for flow through porous media: q =


K
  p [3]
In this equation, q is the Darcy flux, K is the permeability of the porous medium (in units of “darcy”, or square meters),  is the dynamic viscosity of the fluid, and p is the pressure [5] [6]. The negative sign is used to indicate that the Darcy flux will be in the direction opposite the pressure gradient; i.e. that the fluid will flow from high pressure to low pressure. Further, the flux is related to the actual fluid velocity by the porosity of the porous medium, as shown in the following equation: v = q n
[4]
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(here, v is the fluid velocity and n is a unitless (percentage) measure of the porosity of the porous medium). At a high level, it can be seen that the velocity is proportional to the permeability of the grain bed and the pressure, and inversely proportional to the porosity of the grain and the viscosity of the fluid. If there is no pressure gradient within the tun, there is no flow.
In an attempt to incorporate the potentially significant effects of sugar concentration within the wort and subsequent density and viscosity increase, two separate materials were used for the fluid regions in the COMSOL models. The small
fluid region sitting on top of the grain bed, shown in blue in Figure 2.0.3 and Figure
2.0.4, was given properties of pure water, using the built-in Water option from the
COMSOL material database. For the fluid through the remainder of the model, a custom material called Wort was created and given average fluid property values for wort: specifically, a viscosity of 1.5 mPa*s [7] and density of 1050 kg/m^3 (equal to a specific gravity of approximately 1.050, which is an average pre-boil gravity). As a result, there are two liquid material regions in the model, labeled “Water” and “Wort,” as
shown in the screenshots of Figure 2.0.6
.
All fluid regions of the model were held at
155 degrees Fahrenheit, a common sparging temperature. While this temperature may decrease slightly over the course of the continuous sparging procedure, modeling would require use of a time-dependent solver and considerably increased complexity. The mash tun is relatively well insulated (being made from a cooler) and the small drop in temperature is not expected to significantly affect the flow through the tun.
As explained earlier, for each model a region of copper pipe was also created in
COMSOL. This region used the built-in copper material properties from the COMSOL material database. However, no physics module was applied to this region, as the goals of the project focused on fluid flow and there would be no flow through these boundaries. Neither was a heat module used to couple the fluid and solid regions, for the same reasons described in the previous paragraph.
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Figure 2.0.6: Material Properties for Liquid Regions
Flow anywhere outside of the grain bed (in the pipe manifold, as well as in the water level above the grain bed) will be considered laminar flow and will be evaluated using the Navier-Stokes equation. The validity of this assumption will be confirmed later. The Navier-Stokes equation is as follows:

 v
 t
+ v
  v =
 p +
 
T + f [5] where v is the flow velocity,

is the fluid density, p is the pressure, T is the stress deviator tensor, and f is a body force acting on the fluid. In this particular case, no body force was applied in the COMSOL model. Because the inlet velocity is regulated, this would have no impact on the flow through the tun.
COMSOL conveniently includes a module called “Free and Porous Flow” that easily combines these two flow regions, coupling Darcy’s Law with the Navier-Stokes equation. The Free and Porous Flow module naturally requires properties of the porous
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medium as inputs in order to evaluate Darcy's law. Values for permeability (k) of the grain bed vary significantly, and the estimated value of k = 9.87 e-11 m^2 [8], equal to about 100 darcys was used in the model. For porosity (n) a value of 0.30 (30%) was used, which is an average value used in soil analysis for a mix of gravel and sand particles [9]. This seemed to reasonably approximate the grain after milling, which will often consist of some large particles interspersed with fine, flour-like ground bits.
For porous media composed of loose material (like the grain bed), porosity depends on several factors such as grain packing, shape, arrangement, and size distribution [10]. Media made up of poorly sorted particles (meaning that the grain size varies) will have a lower porosity than well-sorted particles, all else equal. There is some change in porosity with depth, as compacting forces increase with depth. Athy
[11] demonstrated that the change in porosity with depth could be calculated with the following equation: n = n
0
 e
 alpha
 d
[6] where d is depth below the surface of the porous medium and alpha is a coefficient dependent on the factors identified above. The largest value for alpha given in Bear’s data [10] was for shale, where alpha = 3.84 e-4 [1/ft]. This example indicates that any change in porosity through a height of less than 2 feet would be negligible.
In order to ensure that Darcy’s law is appropriate for this problem, it must be shown that the flow is clearly laminar. For this reason the Reynolds number was calculated throughout the model in order to ensure that this is the case for each variation of the mash tun parameters. Any Reynolds number less than one is sufficient to show that the flow is slow and viscous enough to apply Darcy’s law, although empirical data has indicated that flow categorized by Reynolds numbers up to 10 may still be considered Darcian [12]. The equation for Reynolds number in porous media is as follows:
Re =
  v

 d g
[7] where
ρ
is the density of pure water, v is the outlet velocity,
μ
is the viscosity of the fluid, and d g
is a representative grain diameter for the porous media. The Reynolds
number was computed for every model, to ensure flow remained laminar (see Figure
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2.0.7). The largest Reynolds number within the grain bed was below 1 for all models,
and even within the pipe manifold was never found to exceed 3. These values confirmed the decision to assume flow throughout the model was laminar.
Figure 2.0.7: Example Reynolds Number for x-y Type Model (top) and y-z Type Model (bottom)
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In order to provide the boundary conditions for the Free and Porous Flow
module, inlet and outlets were identified for each model (marked by blue lines in Figure
2.0.8). As discussed above, the inlet condition was to prescribe a normal velocity of
0.18 [gal/min/ft^2] into the top of the water region. This converts to approximately
1.2224 e-4 [m/s]. The outlet was given a pressure condition of 0 Pa, with no viscous stress.
Figure 2.0.8: Inlets and Outlets for Both Types of 2D Models
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The method through which extract efficiency and wort quality will be estimated is fairly simple. When using a continuous sparging technique as discussed earlier, with constant flow at the inlet and outlet, flow through the grain bed will be distributed about the ideal velocity recommended by Narziss, about 1.224 e-4 [m/s]. After running a simulation, a histogram plot can created showing frequency of velocities through the grain bed. These results will be explained further in the next section.
Extraction efficiency is a measure of the efficiency of converting grain into fermentable sugars, and is commonly measured while homebrewing using specific gravity as discussed in the previous section. However, this value can also be calculated using COMSOL analysis, by making the assumption that the ideal Narziss velocity provides 100% extraction of sugars from the grain and into the wort. It follows that any velocity in the grain bed that exceeds this value will also provide 100% extraction.
Further, any velocity below this value provides less than 100% extraction, and the ratio of velocities will be used to determine the percent extraction. For example, if an area of the grain bed sees a velocity of 0.5 e-4 [m/s], the percent extraction will be:
% extraction =
0.5
e

4 v ideal

0.5
e

4
1.224
e

4

40.8% [8]
 bed by calculating the percent area of the bed that sees various velocities. For simplicity, the histogram was broken up into quantized sections of 5% of ideal velocity
(see Figure 3.0.4
in the next section for an example). The percent occurrence of each of these sections is then multiplied by that velocity and summed to give a direct representation of the extraction efficiency.
Wort quality is more qualitative assessment. However, it has been documented that highly uniform flow is well correlated with improved wort quality [3]. This is due primarily to the fact that excessive flow through certain regions of the grain bed due to non-uniform flow patterns, which result in higher level of tannins and other undesirable grain products in the wort. For the purposes of this project , areas of the grain bed with velocities in excess of 100% are considered oversparged . These oversparged regions
20

are where the danger of poor wort quality lies. At high flow, these areas of grain will be subject to tannin extraction.
The histogram plots generated by COMSOL will also be used to determine the percent of the grain bed that is oversparged, and this will provide another performance indicator for evaluating the various mash tun configurations.
21

The COMSOL models developed for this project were first used to determine velocities and pressures through the grain bed, in order to ensure that the simulations were performing as intended, and to provide a level of reassurance in the results ultimately calculated. For each mash tun configuration a velocity plot was created,
including streamlines, for visual confirmation of flow through the mash tun (Figure
3.0.2). Pressures throughout the grain bed were also plotted for every model (Figure
3.0.3). The two example plots for velocity and pressure through the grain bed shown
here represent the x-y plane cut of the initial mash tun configuration. This initial configuration, while analyzed in two dimensions, is intended to represent a manifold made from a single pipe running through the mash tun as shown below in three
dimensions in Figure 3.0.1. The results from all of the configurations examined in this
Master’s Project are included in Appendix B.
Figure 3.0.1: Three-dimensional View of Initial Mash Tun Configuration
22

QuickTime™ and a
decompressor are needed to see this picture.
Figure 3.0.2: Velocity Plot for Initial Mash Tun Configuration
QuickTime™ and a
decompressor are needed to see this picture.
Figure 3.0.3: Pressure Plot for Initial Mash Tun Configuration
23

Once the COMSOL model was developed and confirmed to run successfully, different model parameters could be modified in order to determine their effect on extract efficiency and wort quality. As discussed in the previous section, histogram plots were used to evaluate these two performance measures. Using the 1D plot feature in
COMSOL, results from each new model were mapped to a histogram plot that quantified
the percentage of the grain bed experiencing specific velocity levels. Figure 3.0.4
below shows an example. In the histogram on the left (for the region of 0% – 100% of ideal velocity) the histogram sections are divided into regions of 1/20 (5%) of the ideal velocity in order to evaluate the extraction efficiency of this particular mash tun configuration. In the right-hand histogram, the percentage of the grain bed that is oversparged can be evaluated by simply plotting the percentage of the bed experiencing a velocity greater than the ideal velocity. It can be easily seen from the right-hand histogram that about 54% of the bed is oversparged, but the efficiency is harder to determine from a quick glance. Using the export data function in COMSOL and incorporating the fact that all areas of the bed with velocities in excess of the ideal value are considered to be 100% efficient, the efficiency for this particular configuration was found to be about 81%.
Figure 3.0.4: Example Histograms
24

It should be stated at this point that the values calculated for efficiency and oversparged percentage are not expected to be exact. These are not the values that one would calculate if a real-world test of the equivalent mash tun design. This is true for several reasons, not the least of them being the oversimplification of the mash tun design. Other reasons include the inherent variability in real-world ingredients and other measurements which needed to be estimated in order to minimize the scope of the
simulation. Additionally, for simplicity of calculation, the histogram shown in Figure
3.0.4 on the right does not include higher velocity values which represent a very small
portion of the grain bed (see Figure 3.0.5 below). On the whole, the results of the
simulation are an approximation. However, it is expected that this approximation can be very useful in determining trends of increased efficiency or wort quality. While the exact percentages found through the simulations will not directly correlate to real-world testing, predictions of significantly improved performance metrics due to certain design variations are expected to transfer well to real-world mash tun builds.
Figure 3.0.5: Example Histogram Showing Potential Higher Velocities
The COMSOL analysis used simplified 2-dimensional geometry in order to create a more easily solvable simulation, as discussed previously. The first type of
model, where x-y planar cuts (see Figure 2.0.3 of the previous section) were taken
through the mash tun, allowed for evaluation of a certain set of parameters (Table 3.1).
These models are intended to represent a plane cut perpendicular to the manifold legs
(parallel sections of pipe) coincident with the locations of slots in the manifold.
25

Table 3.1: Mash Tun Parameters Evaluated Through x-y Plane Models
Parameter
Number of manifold legs
Interpipe spacing
Pipe diameter
Grain bed depth
Height of top water layer
Given Value/Range
1 – 8 even, stretched, squeezed
~3/8 – 2”
8 – 16”
0.1 – 6”
The baseline x-y type model included average or common values for the various parameters to be evaluated. The initial model had a single copper pipe making up the manifold, running right through the center of the mashtun. The pipe diameter was ½”, a common size pipe used by homebrewers likely due to its wide availability. The grain bed depth used was 12”, and the water level on top of the grain was 1”. The interpipe spacing parameter has no meaning when there is only 1 manifold leg, but when the number of legs was increased, they were initially evaluated with even spacing, such that the legs divided the tun area into equal sections.
The first parameter to be evaluated was the number of manifold legs (shown in
three dimensions in Figure 3.0.7 below). Increasing the number of manifold legs adds
significant complexity to the mash tun build, but has a clear impact on performance.
The effects are shown in the data included in Table 3.2. Increasing the number of legs
was found to improve both extraction efficiency and wort quality. This follows, because as the number of outlets for the grain bed increases, the outlets come closer and closer to encompassing the entire lower area of the picture, which logically would be the most efficient setup. In fact, this is similar to what a false bottom mash tun configuration would look like. A more widely spread outlet minimizes the regions to either side of the
mash tun that are subject to low flow (see Figure 3.0.7). It is interesting to note that,
once there are enough legs to sufficiently cover the bottom of the tun, the flow through the bed also becomes more uniform as the number of legs increases. This is due to the fact that the flow rate through the outlets is constant, so as the number and area of outlets increase, the velocity at those outlets decreases. This in turn improves wort quality.
26

2 – 4 – 8
Figure 3.0.6: Manifolds with Different Number of Legs
Table 3.2: COMSOL Results from Varying Number of Manifold Legs
Configuration Percent Efficiency
1 legs
2 legs
3 legs
4 legs
5 legs
8 legs
90.0%
92.7%
93.9%
94.5%
94.9%
95.5%
Percent of Grain
Bed Oversparged
46.9%
50.3%
50.8%
49.7%
48.3%
42.5%
Figure 3.0.7: Improved Flow with Increasing Number of Manifold Legs
27

These results indicate that the ideal mash tun design would include as many manifold legs as can possibly be fit into the mash tun. While this conclusion is not disputed, the difficult of constructing a manifold like this at home is significant. There are also diminishing returns to be had from continually increasing the number of legs, as
was seen in Table 3.2. There is also one further concern. In practice, when manifold
legs are placed to closely to the side walls of the mash tun, flow along these walls is often prone to occur, a result called channeling [3]. The interaction between the plastic walls of the cooler and the grain bed is not well modeled in COMSOL, and thus is not predicted by the simulation. Despite this, channeling is well known to lower efficiency due to an unexpectedly under-sparged grain bed. As a result, a 4-pipe manifold was chosen for this project, and this configuration was used for the remainder of the parameters varied in the x-y plane models (Figure below____). The results the other parameters had on the performance of the mash tun can be seen in Appendix B and are
summarized later in this section in Table 3.4.
Picture of 4-pipe manifold in 3D
The second type of model used y-z planar cuts as shown in Figure 2.0.5 of the
previous section. These cuts were taken along a single leg of the pipe manifold, and allowed for evaluation of a different set of parameters from the x-y planar cuts, primarily
the individual features that provide the filtering for the manifold (Table 3.3).
28

Table 3.3: Mash Tun Parameters Evaluated Through y-z Plane Models
Parameter
Spacing between slots
Size of slots
Manifold location
Given Value/Range
1/2 – 2”
1/32 – 1/4”
1 – 5” from non-outlet side wall
The baseline y-z type model included some of the baseline values from the y-x models, including a pipe diameter of ½”, a grain bed depth of 12”, and a water level on top of the grain of 1”. Average values were also chosen for the new parameters. The baseline spacing between the slots was chosen to be 1”, which is often used in homebrewer mash tun builds. The initial size of the slots was 1/16”, intended to represent the width of hacksaw blade that would be used to make these cuts. The initial manifold location was chosen to end 3” from the non-outlet side of the mash tun, but as with the other parameters will be varied in order to see what effect this measurement has on tun performance.
Example velocity and pressure plots for y-z plane type models are shown below
in Figure 3.0.8 and Figure 3.0.9. Histogram examples are included in Figure 3.0.10.
Figure 3.0.8: Velocity Plot for Baseline y-z Type Mash Tun Model
29

Figure 3.0.9: Pressure Plot for Baseline y-z Type Mash Tun Model
Figure 3.0.10: Histograms for Baseline y-z Type Mash Tun Model
At first glance, some significant differences are apparent between the two types of models. For one, the efficiency appears significantly lower than in an x-y type model.
In fact, there is a large percentage of very low-velocity regions in this baseline y-z type model: nearly 20%, in comparison to practically 0% in the x-y type models. This is due
30

to the fact that the y-z type model includes the region of the grain bed that is below the manifold. This region sees very low flow in the model as all of the wort traveling through the grain bed takes the path of least resistance directly to the slots of the manifold and through the outlet. This meshes with actual experiences of homebrewers.
In fact, one of the primary sources of water lost when brewing comes from the percentage of water that remains trapped in the mash tun below the manifold and cannot be drained, and is even accounted for in specialized homebrewing software such as
BeerSmith. This is an indication of the lack of flow through this area, and hence the lower efficiencies seen when this area is included in the model. Logically, in order to improve efficiency one could minimize this area and drop the manifold closer to the bottom of the mash tun. However, the height from the bottom of the tun is determined by the height of the existing spigot hole in the side of the rectangular cooler used to create the tun. For ease of manufacturability for the average homebrewer, creating a new hole in the cooler or alternatively installing a manifold that is not parallel to the bottom of the cooler is not considered in this project.
Table 3.4 shows the list of all parameters considered during analysis, and what
general effects they had on the mash tun performance. Some parameters were taken to be constants and not varied at all during the analysis. This was mainly due in order to keep the mash tun materials easily accessible. Any variation in these parameters would have forced prospective mash tun builders to look elsewhere than their local hardware store. For example, only one standard size cooler was considered for the mash tun. No significant variations were found in large rectangular coolers, except occasionally that they were available in taller sizes. Further, only standard and widely available copper piping sizes were used in the analysis: in particular, nominal diameters of 3/8”, 1/2”,
3/4", 1”, and 1 ½”. The exact dimensions for the diameters and thicknesses of these pipes were determined by M-type copper piping, which is a light, thin-walled pipe intended for above-ground residential and commercial uses. To reiterate the methodology explained in the last section, an increase in the percentage of the grain bed that was oversparged, or subjected to velocities that were too high, was considered to lead to a decrease in wort quality.
31

Table 3.4: List of Mash Tun Parameters Considered and Impact on Performance
Parameter Type Given Value/Range
Impact on Extraction
Efficiency
Impact on Wort Quality
Mash tun dimensions
Constant
L = 21”
W = 12”
H = 12” (modified with grain bed depth)
Constant
1” from bottom of tun
Height of outlet hole
Thickness of pipe
Number of manifold legs
Inter-pipe spacing
Constant
Variable
Variable
Dependent on pipe diameter
1, 2, 3, 4, 5, 8
Even, stretched, squeezed
-
-
-
Increased efficiency with more legs
-
-
-
Increased quality with more legs
Pipe diameter
Grain bed depth
Height of top water layer
Spacing between slots
Size of slots
Manifold location
Variable
Variable
Variable
Variable
Nominal pipe size of
3/8”, ½”, ¾”, 1”, 1 ½”
8”, 10”, 12”, 14”, 16”
0.1”, 1”, 2”, 6”
¼”, ½”, ¾”, 1”, 1½”, 2”
Squeezed spacing lowers efficiency
No significant effect
Slight increase in efficiency with bed depth
No significant effect
Increased efficiency with smaller spacing
Increased quality with increased spacing
Slight decrease in quality with increased diameter
Increased quality with deeper bed
Slight increase in quality with higher water level
Decreased wort quality with smaller spacing
Variable
1/32”, 1/16”, 1/8”, 1/4”
Variable
1”, 3”, 5” from nonoutlet side wall
No significant effect
Increased efficiency closer to wall
No significant effect
Decreased wort quality
The effects of all variables were isolated by varying those parameters in separate
COMSOL models. COMSOL reports are provided for every model in Appendix B. The exported results from the histograms are included in Appendix A. All side-by-side comparisons of the results contained in Appendix A should be done with the baseline model for each type, which are marked bold in the tables: all x-y plane models should be compared to the original 4-pipe model, and all y-z plane models should be compared to the baseline of that type.
32

Obviously, every parameter that goes in the design of a pipe manifold mash tun could not be considered in this project. However, an attempt was made to evaluate some of the most common and most easily modified parameters for the average homebrewer.
In this way, the recommendations of this project can be easily and dependably translated into a superior mash tun design. However, there is one major design modification that is often used that was not discussed in this project: flipping the manifold orientation such that the slots are on the bottom of the manifold. This is not universal, but has been occasionally observed in a review of mash tun builds online. The effects are potentially significant and interesting: this would lower the location of the drains from the grain bed, serving to slightly reduce the area of the tun that is subject to low flow conditions.
However, the resulting flow around the manifold and then up into the slots would produce a very unusual flow pattern that could also have ramifications for efficiency and oversparging concerns. Unfortunately, this configuration could not be considered due to the manner in which the x-y and y-z models were set up. An attempt was made using the y-z type models, and is included in Appendix C, but is not expected to be an accurate representation of flow around the manifold, as flow can only be simulated in the plane chosen. This model does provide limited insight into the manner in which the flow would travel around the manifold, however.
As discussed earlier, there was a clear improvement in both wort quality and extraction efficiency as the number of legs making up the manifold increased. However, for several reasons it was concluded that a 4-leg manifold would be sufficient for the purposes of this project, and would provide considerable benefits over 1, 2, or 3-leg manifolds, which have been observed to make up the majority of homebrewer mash tun builds.
Interpipe spacing was a parameter intended to examine the effects of keeping the same number of legs of the manifold and the same size of pipes, but shift their locations
around. Figure 3.0.11 gives an indication of how this was accomplished. The baseline
model included an even configuration, where the 4 legs of the manifold split the area of the tun into 5 equal sections. A stretched-spacing model was also simulated, where the manifold legs were moved away from the center. Finally, a squeezed-spacing model
33

was simulated that included all 4 legs of the manifold gathered together at the center of the tun. Comparing the stretched and squeezed models with the even spacing, no improvement was seen in terms of extraction efficiency. In fact, the squeezed model had a significant drop in efficiency. However, there was a massive improvement in wort quality through a reduction in oversparged areas and thus an increase in flow uniformity,
as can be seen from the velocity plots in Figure 3.0.11. Unfortunately, the same concern
with channeling expressed earlier also comes in to play, as the manifold legs get too close to the walls of the mash tun. However, this significant improvement in quality is considered valuable enough to take on the risk of channeling. It is recommended that the stretched spacing be used, with attention kept to whether channeling seems to occur through observation and comparison of actual specific gravity with expected.
Figure 3.0.11: Even, Stretched, and Squeezed Spacing Between Manifold Legs
The pipe diameter was varied significantly, but kept within the constraints of widely-available M-type copper piping. However, no significant impact was seen to either efficiency. A very slight decrease in wort quality was seen with larger diameter.
There have been some concerns expressed by homebrewing websites that smaller piping may not be able to withstand the weight of the grain bed pressing down on it, specifically anything less than ½” in diameter. For these reasons, it is recommended that that a nominal pipe size of ½” be used.
34

The depth of grain bed was the next parameter evaluated in COMSOL. There was some correlation between increased depth and higher efficiencies, and there was a significant increase in wort quality as the bed grew deeper and deeper. The issue here is that the bed can only be as deep as the mash tun allows for, and deeper coolers are not always readily available. However, given the COMSOL results it is recommended that a cooler of at least 12” tall be used, and deeper ones considered if possible.
The height of the water level on top of the grain bed is normally not considered critical to homebrewers. The requirement of at least 1” of water on top of the bed is intended to provide some margin so that if the outlet flow rate exceeds the inlet flow rate during continuous sparging, there is some time for the homebrewer to realize and correct before air starts getting trapped in the grain bed. However, the simulation results indicated that there may be a slight increase in wort quality with a higher water level.
The problem with increasing the water level is that it limits how much of the mash tun can be used for the grain bed. For this reason, it is recommended to use the standard 1” level of water on top of the grain bed. It is much more important to the sparging process that there always be some level of water above the grain than the actual amount of water.
The spacing between slots in the pipe manifold was considered next. The baseline configuration used a 1” spacing between successive slots. Larger spacing and smaller spacing was evaluated. As was to be expected, the extraction efficiency improved as the spacing decreased and the total number of slots increased. In this way, the manifold resembled more and more the “false bottom” design discussed earlier.
However, wort quality also decreased at a similar rate as the spacing between slots decreased. It should also be noted that cutting slots into the copper piping when producing the manifold can be quite an ordeal, and doubling the number of slots is extremely difficult. It is therefore recommended that 1” spacing be used, which is expected to provide a reasonably high efficiency and wort quality. A homebrewer looking to build a mash tun can choose to add more slots if so desired.
The impact of varying the width of the slots in the manifold was also evaluated.
This parameter may be a difficult one to modify as a homebrewer, as the size of the slots is usually dependent on the width of the hacksaw blade used to cut the slots in the copper
35

pipe. Interestingly, there does not appear to a significant effect on either wort quality or extraction efficiency with changing slot size, so a homebrewer should use whatever saw blade they have on hand. One final note is that the larger slot size does increase the possibility of grain pieces making it through the filtering mechanism, or simply increasing the amount of time it would take to recirculate and successfully compact the grain bed. With this in mind, if the homebrewer has multiple options when it comes to saw blade thickness, it is recommended that the smallest blade width be used.
The final parameter that was evaluated was the distance between the manifold and the non-outlet side wall of the mash tun. Initially, the manifold was kept 3” away from the wall in order to moderate concerns with channeling occurring due to the proximity of the pipe with the wall. However, the COMSOL analysis indicated that moving the manifold closer to the wall would increase the efficiency substantially, although this modification would also decrease the wort quality somewhat. It is recommended that the manifold be moved closer to the wall that 3”, but perhaps not closer that 1” to minimize concerns with channeling.
In summary, the ideal mash tun design for a homebrewer looking for high efficiency and wort quality should feature the following feasible characteristics:

4-pipe manifold

Manifold legs stretched out towards either side of the mash tun
 ½” copper pipe
 12” tall grain bed
 1” of water on top of grain
 1” spacing between slots cut into manifold, although more may be desired

Any size slot is acceptable
 Manifold should be roughly 1” from the non-outlet end of the mash tun
Any one of these design choices should help to keep high wort quality and extraction efficiency, and incorporating all of these into one mash tun build will produce the ideal mash tun design.
36

[1] Narziss, Ludwig. The Technology of Brewing Beer . Ferdinand Enke Verlag,
Stuttgart, Germany, 1992.
[2] Uchima, Mike. “Potential Extract Tables.”
Mike’s Brew Page.
<http://hbd.org/uchima/tech/extract.html>
[3] Palmer, John J. How to Brew.
3 rd
ed. Brewers Publications, 2006.
[4] Miller, David. Brew Like a Pro.
Storey Publishing, 2012.
[5] de Lemos, Marcelo J.S.. Turbulence in Porous Media: Modeling and Applications,
Second Edition.
Elsevier Science and Technology Books, Inc., © 2012. Books24x7.
Web. Sep. 17, 2013. <http://common.books24x7.com.colelibprxy.ewp.rpi.edu/toc.aspx?bookid=49256>
[6] Vafai, Kambiz. Handbook of Porous Media, Second Edition. CRC Press, 2005.
[7] Pahl, “Important Raw Materials Quality Parameters and Their Influence on Beer
Production,” Brewing Conference Bangkok 2011.
[8] Hirasaki, G. J. “Lecture Notes on Adsorption.” CENG 402, Chapter 3.
<http://www.owlnet.rice.edu/~ceng402/Hirasaki/CHAP3D.pdf>
[9] Fetter, C. W. Applied Hydrogeology , 3rd ed. Upper Saddle River, NJ: Prentice
Hall, Inc., 1994.
[10] Bear, Jacob. Dynamics of Fluids in Porous Media. Dover Publications, 1972.
<http://app.knovel.com/hotlink/toc/id:kpDFPM000I/dynamics-fluids-in-porous>
[11] Athy, L. F. Density, Porosity, and Compaction of Sedimentary Rocks . v. 14,
AAPG Bulletin, 1930.
[12] Wang, Herbert F. and Mary P. Anderson. Introduction to Groundwater Modeling:
Finite Difference and Finite Element Methods. Academic Press, Inc., 1982.
37

Additional References not Cited:
Fox, Robert W., Philip J. Pritchard, and Alan T. McDonald. Introduction to Fluid
Mechanics . 7 th
ed. John Wiley and Sons, Inc., 2009.
Spanos, T. J. T. The Thermophysics of Porous Media.
Chapman and Hall/CRC, 2001.
Xie, Liquan, ed. Modeling and Computation In Engineering II.
CRC Press, 2013.
38

Model Number
11.1.1
11.1.2
11.1.3
11.1.4
11.1.5
11.1.6
11.1.7
11.1.8
11.1.9
11.1.10
11.1.11
11.1.12
11.1.13
11.1.14
11.1.15
11.1.16
11.1.17
11.1.18
11.1.19
very large diameter small diameter short grain bed shorter grain bed deep grain bed deeper grain bed minimal water level high water level higher water level
1 pipe x-y Type Models
Configuration Percent Efficiency
90.0%
Percent of Grain Bed
Oversparged
46.9%
2 pipe 92.7% 50.3%
3 pipe
4 pipe
5 pipe many pipes
93.9%
94.5%
94.9%
95.5%
50.8%
49.7%
48.3%
42.5% stretched spacing squeezed spacing large diameter larger diameter
94.3%
91.9%
94.5%
94.6%
29.5%
50.0%
49.9%
50.0%
94.6%
94.5%
94.2%
93.5%
94.5%
94.5%
94.8%
94.5%
94.5%
50.1%
49.6%
53.6%
56.2%
40.8%
35.6%
54.0%
48.1%
48.2%
39

Model Number
11.2.1
11.2.2
11.2.3
y-z Type Models
Configuration Percent Efficiency
Percent of Grain
Bed Oversparged baseline yz 85.5% 62.7% large spaced slots larger spaced slots
83.6%
80.0%
60.2%
55.9%
11.2.4
11.2.5
11.2.6
11.2.7
11.2.8
11.2.9
11.2.10
11.2.11
11.2.12
slots on bottom small slot spacing smaller slot spacing very small slot spacing
1/8-inch wide slots
1/4-inch wide slots
1/32-inch wide slots manifold closer to wall manifold further from wall
*
86.0%
86.6%
87.3%
85.6%
85.3%
85.3%
88.1%
82.4%
*
63.5%
64.3%
65.3%
63.0%
63.4%
62.3%
63.3%
59.3%
40

1-Leg Manifold
41

42

2-Leg Manifold
43

44

3-Leg Manifold
45

46

4-Leg Manifold
47

48

5-Leg Manifold
49

50

8-Leg Manifold
51

52

Stretched Spacing Between Legs
53

54

Squeezed Spacing Between Legs
55

56

Large Diameter (3/4”)
57

58

Larger Diameter (1”)
59

60

Very Large Diameter (1 ½”)
61

62

Small Diameter (3/8”)
63

64

Short Grain Bed (10”)
65

66

Shorter Grain Bed (8”)
67

68

Deep Grain Bed (14”)
69

70

Deeper Grain Bed (16”)
71

72

Minimal Water Level (0.1”)
73

74

High Water Level (3”)
75

76

Higher Water Level (6”)
77

78

Baseline y-z
79

80

Large Spacing Between Slots (1 ½”)
81

Larger Spacing Between Slots (2”)
82

83

Small Spacing Between Slots (3/4”)
84

85

Smaller Spacing Between Slots (1/2”)
86

87

Very Small Spacing Between Slots (1/4”)
88

89

1/8-inch Wide Slots
90

91

1/32-inch Wide Slots
92

93

1/4-inch Wide Slots
94

95

Manifold closer to wall (3”)
96

97

Manifold further from wall (5”)
98

99

This appendix includes only the results from the manifold configuration with slots on the bottom of the manifold. These results were kept separate from the rest of the models as they were not used to develop the recommended ideal mash tun design.
However, they are included here for information as they may provide some indication to the flow patterns that would result from such a manifold configuration.
Model Number Configuration Percent Efficiency
Percent of Grain
Bed Oversparged
11.2.4
slots on bottom 61% 32%
100

101

102