The present disclosure is related generally to computer-aided design systems and, more particularly, to using such systems to design for airborne contaminant flows.
This section introduces aspects that may help facilitate a better understanding of the invention. Accordingly, the statements of this section are to be read in this light and are not to be understood as admissions about what is prior art or what is not prior art.
Ideally, architectural structures are designed to prevent or to minimize the spread of airborne contaminants. Some such contaminants may be deliberately introduced by acts of terrorism as the anthrax attacks of 2001 illustrated. Even in peacetime, proper architectural design can decrease the spread of chemical or biological contaminants and thus reduce the effects of “sick building syndrome.”
To address the issue of airborne contaminant flows, a computer-aided design system incorporates a contaminant-flow calculator. In designing a new architectural structure, or modifying an existing one, the calculator informs the architect of the airflow ramifications of the design as the design is created or modified. The calculator uses a closed-form solution for calculating the airflow in order to present its results in a timely fashion.
While the appended claims set forth the features of the present techniques with particularity, these techniques, together with their objects and advantages, may be best understood from the following detailed description taken in conjunction with the accompanying drawings of which:
Detailed illustrative embodiments of the present invention are disclosed herein. However, specific structural and functional details disclosed herein are merely representative for purposes of describing example embodiments of the present invention. The present invention may be embodied in many alternate forms and should not be construed as limited to only the embodiments set forth herein. Further, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments of the invention.
As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It further will be understood that the terms “comprises,” “comprising,” “includes,” and “including” specify the presence of stated features, steps, or components but do not preclude the presence or addition of one or more other features, steps, or components. It also should be noted that in some alternative implementations, the functions and acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may in fact be executed substantially concurrently or may sometimes be executed in the reverse order, depending upon the functionality and acts involved.
Designing (or redesigning) architectural structures to protect their occupants from airborne contaminants is a known priority. Clearly, access to safe air is a life-safety issue, yet it has been difficult to achieve protection from airborne contaminants once those contaminants are drawn into a structure's heating, ventilation, and air-conditioning (“HVAC”) system. This difficulty arises from a combinatorial explosion of different technical problems.
One of these problems involves the calculating of exposure levels for the structure's occupants under various scenarios. The problem can be stated in terms of systems of ordinary differential equations which can be addressed by matrix-inversion methods. However, traditional methods for calculating a solution to those systems become slow and unwieldly as the structure increases in both number of rooms and in the number of HVAC zones. Unfortunately for the sake of quick calculations, typical buildings have many HVAC zones and many rooms per zone. Even structures as small as a mobile home require many minutes of computer simulation to analyze the first few minutes of a simulated exposure to biological or chemical contaminants.
Thus, meaningful feedback on exposure was not often provided to the structure's designer. Exposure levels were only calculated for situations where bio-protection was utterly imperative (e.g., military installations and some hospital operating rooms). Even then, the calculations would serve only as a single final check on the structural design and would not contribute much to the design process itself. Additionally, calculating exposure levels during a real-time response to a contamination incident was unheard of.
The techniques of the present disclosure address these and other issues. By incorporating a near real-time calculator of airborne contaminant flows, a novel computer-aided design (“CAD”) system provides designers with useful feedback during the architectural design (or re-design) process. The designer, or the CAD system itself, uses that feedback to improve a structure's response to contaminant flows. Because the calculator uses so few computer resources, it can be repeatedly invoked to test novel design features thus enabling a fuller expression of the designer's creativity.
Turning now to the figures,
When beginning to work on a new architectural structure, be that structure a building, a vehicle (boat, submarine, airplane, spaceship), a space station, or whatever, the designer uses the CAD system 100 to collect and organize his thinking about the developing design. The designer submits new elements and modifications via any of numerous input devices 104 supported by the CAD system 100 and receives feedback via any of numerous output devices 102. For example, the designer views the design-in-progress of a building layout on a computer screen 102, uses the computer pointing device 104 or a touchscreen 102/104 to change the layout by adding a door, and then views the resulting design on the screen 102. Other uses of the CAD system's input/output devices are called out below where appropriate.
Driving the CAD system 100 is an internal control module 106, typically one or more microprocessors working together. The internal control module 106 controls the output devices 102, receives information from the input devices 104, and stores the developing design in short-term and long-term memories (not shown but well known in the art).
The internal control module 106 also contains logic (not shown but well known in the art) to present aspects of the developing design in different ways to help the designer understand how all parts of a complicated structure work together. This is useful not only when developing a design for a new structure but for helping to understand an existing structure.
Other well known aspects of logic implemented by the internal control module 106 ensure that the design is a rational whole and check the developing design against applicable standards. Some of standards vary depending upon the purpose of the structure. As can be well imagined, air-filtration requirements differ for an industrial meat locker, a hospital operating room, and a hotel meeting room.
In some embodiments of the CAD system 100, various checks are performed automatically when a proposed modification may implicate an important aspect of the structure. For example, the CAD system 100 may automatically re-test structural integrity when a load-bearing wall is breached by a proposed modification. If the designer changes the anticipated number of occupants of a building, then the CAD system 100 may ensure that the modified design still meets all fire-code regulations by having an adequate sprinkler system and enough emergency-exit doors for the anticipated number of occupants.
In other situations, the standards-checking may involve calculations so onerous that instead of being invoked automatically, they are only invoked at the direction of the designer when the developing design reaches substantial progress points.
In some embodiments, the present disclosure adds two new aspects to a traditional CAD system 100. These are denoted in
The flowchart of
However the structural information was gathered in step 202, and however complete or sketchy that information is, that structural information is used by the airborne contaminant-flow calculator module 108 to create a model showing how air is expected to flow throughout the structure as the structure is currently designed (step 204).
As mentioned above, such airflow calculations were traditionally performed using extensive numerical modeling. Such modeling was both very expensive and very slow. An airflow model for a moderately-sized building would consume hours or even days of computer time. While the results are very useful and important, those methods were much too slow to provide near real-time feedback to a designer contemplating a modification to the structure's design. Thus, these airflow calculations were only invoked at the end of the design process to verify that the structure as completely designed met whatever applicable standards and design goals were set when the structure was first contemplated.
Another result of the extremely high costs (in terms of both time and dollars) of numerical methods is “over-specification” of HVAC system performance for critical facilities. Because it was so difficult to calculate the actual airflow requirements, it was safest to assume a worst case scenario and then specify the most capable HVAC filtration system available. As just one example, the United States federal government was justly concerned about terrorists intentionally introducing airflow contaminants, so it specified very expensive HEPA filtering for many of its installations, which led to costs in replaceable filters and electricity of hundreds of thousands of dollars per year per installation.
Now, however, recently developed closed-form solutions can be applied to many airborne contaminant scenarios. In many embodiments, the airborne contaminant-flow calculator 108 uses one or more closed-form solutions in step 204 and thus provides near real-time feedback to the designer.
Turn now to
For the moment considering only the curve labelled “Ideal Building,”
Note on the “Protection Factor:” This is one result of the contaminant-flow calculations, and it summarizes how good the structure under test will be at protecting its proposed occupants from airborne contaminants, whether those contaminants are intentionally introduced in an act of terrorism or unintentionally introduced (e.g., pollen or other allergens sucked into the building through the outdoor air filter at Top, or chemicals outgassed by a “sick building”). The exact interpretation of the Protection Factor depends upon the specifics of the methods used to calculate it other than the general observation that “higher numbers are better.” For exemplary details usable in some embodiments, see the Notes on a Closed-Form Solution for Airborne Contaminant Flows below and, especially, the article “Bioprotection of Facilities” cited therein where the Protection Factor is defined as “the asymptotic ratio of outdoor-to-indoor air concentration of particulate matter when the outdoor air is held at a fixed contaminant concentration.” The techniques disclosed herein are not tied to any particular method for calculating the airflow nor to any particular definition of the Protection Factor.
The charts of
Returning to the method 200 of
In some embodiments, the CAD system 100 analyzes the proposed modification and, if it seems appropriate, may decide to recalculate the airflow in step 210. (Step 208, skipped for now, is discussed below.) Only certain modifications would cause the CAD system 100 to take this action: Changing the color of an inside wall probably would not trigger the recalculation while changing the color of an outside wall or the roof may, as would adding a door or another room.
Indeed, turn to
Returning to
In general, by reviewing all of these graphs, the designer compares the newly calculated airflow against that made in step 204 for the base case “Ideal Building.” The designer immediately sees the consequence of adding the new door and may decide whether or not the convenience of the new door is worth the decrease in the Protection Factor that it causes.
In some embodiments, the CAD system 100 itself compares the new vs. the old airflow calculations and, if the Protection Factor is too adversely affected by a modification, may alert the designer to that fact. Fully informed by all of the airflow calculations, the designer then decides on an appropriate course of action.
As a final stage of this example, the designer adds a vestibule (design stage 404,
This procedure of modifying the design and automatically recalculating the airflow and the Protection Factor continues until the final design stage is reached. At that point, the final design is stored in conjunction with the final airflow calculations (step 212) and the structure may be build according to the design (step 214).
In the above scenario, it was the CAD system 100 that decides to recalculate the airflow in step 210. In many embodiments, the designer has the option of deciding to call for a recalculation at any time.
Some embodiments of the CAD system 100 provide another intriguing feature. In the discussion so far, the airflow calculations, whether invoked by the designer or by the CAD system 100 itself, are presented to the designer and stored in conjunction with the developing design. The next feature, embodied in the “Suggestion Module” 110 of
The suggestion module 110 bases its suggestions in part on the quick production of calculations provided by the airborne contaminant-flow calculator 108. In an advanced embodiment, the suggestion module 110 automatically introduces follow-on modifications (or alerts the designer that such follow-on modifications may be necessary) whenever the designer modifies the design. As a simple example, if the designer increases the number of occupants anticipated in the building, then the suggestion module 110 may automatically increase the air-conditioning capacity of the HVAC system. It may also alert the designer that more bathrooms may be needed and may provide suggestions as to good locations for those additional bathrooms.
The flowchart of
Also, existing structures may impose significant constraints that do not exist for new structures. As just one instance, there may be limits to how the appearance of a historically significant building can be changed, even for changes that improve the quality of the internal air.
By bringing airflow calculations into the heart of the design process, the above procedures make a great advance over traditional techniques that treat airflow calculations as an added validation made only at the end of the design process. The designer can now experiment with various airflow scenarios and then specify an HVAC system appropriately scaled for the structure being designed. Presenting the designer with timely, accurate airflow analysis can save substantial initial and ongoing costs over the traditional step of wildly over-specifying the HVAC system to ensure safe operation.
As mentioned above, airborne contaminant-flow problems are often stated in terms of systems of ordinary differential equations which can be addressed by matrix-inversion methods.
Traditionally, many problems requiring matrix inversion are addressed using either computer algebra systems or numerical approximations and simulations. Numerical solutions usually require that all algebraic variables lee substituted with specific numbers, so that an individual program run yields a single specific numerical result. Understanding how this numerical answer varies with a change in system variables requires many program runs. Moreover, numerical methods use floating-point numbers which are subject to errors when a computer attempts to handle both very large and very small numbers simultaneously.
Computer algebra systems, although avoiding the vagaries associated with floating-point representation, are exceptionally complex as they need to handle a large variety of functions: linear, trigonometric, transcendental, etc, They also require a large rule-base of algebraic manipulations.
Fortunately, recent advances in the field have begun to yield closed-form solutions for many airborne contaminant scenarios. This note details a few such solutions. For another, complementary, analysis, see the article by M. D. Ginsberg & A. T. Bui entitled “Bioprotection of Facilities,” Defense & Security Analysis (2015), available at http://dx.doi.org/10.1080/14751798.2014.995335, which is incorporated herein in its entirety by reference.
Consider the general formulation of an ordinary differential equation used to describe a dynamical system. In the time domain, this problem description is to study the time evolution of a signal y(t) as a function of the time-varying signal u(t). As a convention, the bold typeface means vector or matrix (depending on context). In the time domain, let x be a column vector of time-varying signals x(t)=[x1(t), x2(t), . . . , xn(t)]T. Let y(t) and u(t) be the time-varying scalar output and input (respectively) of the system. Let F be a square, constant, state-matrix of n×n.
A canonical example is given here in frequency space:
sX(s)=FX(s)+GU(s)
Y(s)=HX(s) (1)
where X(s) is Laplace transform of x(t) as given earlier. Analogously, U(s) is an exogenous input, and Y(s) is an output of interest. F is a state-matrix; G and H are vectors. For simplicity, F, G, and H contain constants. One can easily ask for the “transfer function” of the system (how the input, maps to the output). Using the notation I as the identity matrix, the formal solution is:
Notice this requires calculating the matrix inverse (sI−F)−1. As the number of states n increases, this matrix grows as n2. This can easily exhaust computational resources if carried out with numerical methods or with standard computer algebra methods (e.g., by using Cramer's rule or similar).
To continue fleshing out this idea, consider this equation worked out for a two-state system:
Note that this is equivalent to the “all integrator block diagram” shown in
To solve Equation (3) by hand, use Equation (2):
Using software, a simple gain evaluation by inspection produces:
Carefully comparing Equations (7) and (8) shows that this is the required result.
At first blush, the preceding calculations merely yielded the transfer function:
What happened to the promised inverse matrix (sI−F)−1? A key realization here is that the vectors G and H play no role in the inverse. Hence they could be assigned any value which might be helpful. For instance, the choice: G=[e,f]T=[1,0] and H=[g,h]=[1,0] picks off the first row and first column of (sI−F)−1. Carrying this idea further, G and H can be set to values that pick off the desired row and column of (sI−F)−1, respectively. Therefore the transfer function given by Equation (8) contains complete information about the inverse matrix (sI−F)−1. For clarity's sake, now carry this out both by hand calculation starting with F and then compare the result to substituting selected variables (namely e, f, g, and h) into the transfer function of Equation (8). Hence:
So, for example, substituting e=1, f=0, g=1, h=0 into Equation (8) yields the row 1, column 1 term in Equation (11) as stated earlier. The following equations can be seen by careful inspection of Equations (8) and (11) because the denominators are equal to one another and invariant with respect to the variables e, f, g, and h. Hence:
again proving the equivalence of information stored in Equation (8) by careful selection of the extra vectors G and H.
There are strategic ways in which the system can be made more complicated, yet yield enough additional information that the additional complexity is worth accepting.
As shown above, the free variables of the vectors G and H allowed the method to read the inverse matrix element-by-element after calculating a single transfer function. This process can be understood by imagining the vectors G and H as being like oscilloscope probes making contact with the system at two points, one being interpreted as an input node and the other as an output node. Thus, substitute the value “1” both where a probe touches the input node (in the vector G) and where a probe touches the output node (in the vector H). All other components of G and H are set to zero.
Although these extra variables make the system more complicated, and can quickly push the calculations beyond the capability of a human, they are easily handled by a computer and yield the complete inverse matrix.
A formal proof of this property would require an extra signal input, call it im(t) for “meta” input, and a meta output om(t). There would be two extra vectors, Gm and Hm each of which has connections to each node of the circuit, where node is defined as: input signal, output signal, summing output, integrator input, and integrator output. Any of these nodes may be redundant if connected to another node with no intervening transmittance or sum. In the example, this is six nodes: input, output, and either side of each integrator.
Some matrices do not have an inverse; they are said to be singular. Further, some matrices may represent a system diagram with unusual characteristics. As an example, the resulting diagram may represent two or more non-connected system diagrams. In general, any of these situations could cause the “gain evaluation by inspection” method to produce nonsense answers. However, the complexity of the matrix may be increased by adding new “conditioning” variables and connections that condition the matrix to have desirable properties. Elements of the resulting inverse matrix can be taken when these variables are driven to a specific limit that removes their effect from the final solution. As an example, one could add connections at a transmittance of t that assure a path from the input to the output. The inverse matrix can then be subject to taking a limit as t goes to zero, thus erasing the new connection from the problem altogether.
By strategic use of conditioning variables, connections are added to the system diagram in a manner that may increase the complexity of the system diagram beyond any hope of human analysis. However, any pathology exhibited by the original matrix does not appear until limits are taken of the individual terms of the resulting inverse matrix. This is an intrinsically much simpler method to manage than existing numerical approximations to taking a matrix inverse.
A typical numerical approximation to taking an inverse can lead to the computer having to handle numerical quantities, some of which may be huge where others are tiny, or can lead to other pathological conditions that do not translate well to a computer's method of interpreting real numbers. The method described above, by keeping all results strictly algebraic, neatly skips over any of these problems until the end of the calculation. Once that point is reached, all of the resulting matrix entries are far easier to handle as individual expressions.
In some situations, better performance may be achieved by swapping Mason's Gain Formula for another standard method. Two likely candidates are the Samuelson-Berkowitz Method (a.k.a. “Berkowitz's algorithm”) and the Bereiss' Method.
The motivation to use these two methods is straightforward. Brute-force methods of matrix inversion (the most ubiquitous of which is Cramer's Rule) have a huge drawback. Although they arrive at the correct algebraic expression, the numerator and denominator generated can have a large number of canceling terms. This defeats the purpose of being free from an underlying computer algebra system. Indeed finding such cancelling terms adds needless computing time.
The need to invert a matrix and then avoid cancelling dividing terms has been looked at previously under another guise: when the matrix elements yield “characteristic polynomials over any commutative ring.” Luckily, the algorithms by Bereiss and Berkowitz are considered computationally efficient, and further, they are easily implemented for parallel computers. Hence, some implementations may use one or the other of these methods when inventing the (sI−F) matrix.
Unless explicitly stated otherwise, each numerical value and range should be interpreted as being approximate as if the word “about” or “approximately” preceded the value or range.
Unless otherwise indicated, all numbers expressing quantities of ingredients, properties such as molecular weight, percent, ratio, reaction conditions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term “about,” whether or not the term “about” is present. Accordingly, unless indicated to the contrary, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by the present disclosure. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the disclosure are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in the testing measurements.
It will be further understood that various changes in the details, materials, and arrangements of the parts which have been described and illustrated in order to explain embodiments of this invention may be made by those skilled in the art without departing from embodiments of the invention encompassed by the following claims.
In this specification including any claims, the term “each” may be used to refer to one or more specified characteristics of a plurality of previously recited elements or steps. When used with the open-ended term “comprising,” the recitation of the term “each” does not exclude additional, unrecited elements or steps. Thus, it will be understood that an apparatus may have additional, unrecited elements and a method may have additional, unrecited steps, where the additional, unrecited elements or steps do not have the one or more specified characteristics.
It should be understood that the steps of the exemplary methods set forth herein are not necessarily required to be performed in the order described, and the order of the steps of such methods should be understood to be merely exemplary. Likewise, additional steps may be included in such methods, and certain steps may be omitted or combined, in methods consistent with various embodiments of the invention.
Although the elements in the following method claims, if any, are recited in a particular sequence with corresponding labeling, unless the claim recitations otherwise imply a particular sequence for implementing some or all of those elements, those elements are not necessarily intended to be limited to being implemented in that particular sequence.
All documents mentioned herein are hereby incorporated by reference in their entireties or alternatively to provide the disclosure for which they were specifically relied upon.
Reference herein to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments necessarily mutually exclusive of other embodiments. The same applies to the term “implementation.”
The embodiments covered by the claims in this application are limited to embodiments that (1) are enabled by this specification and (2) correspond to statutory subject matter. Non-enabled embodiments and embodiments that correspond to non-statutory subject matter are explicitly disclaimed even if they fall within the scope of the claims.
In view of the many possible embodiments to which the principles of the present discussion may be applied, it should be recognized that the embodiments described herein with respect to the drawing figures are meant to be illustrative only and should not be taken as limiting the scope of the claims. Therefore, the techniques as described herein contemplate all such embodiments as may come within the scope of the following claims and equivalents thereof.
The present application is related to U.S. patent application Ser. No. ______ (Attorney Docket Number COE-768B), which is incorporated herein in its entirety by reference.
Under paragraph 1(a) of Executive Order 10096, the conditions under which this invention was made entitle the Government of the United States, as represented by the Secretary of the Army, to an undivided interest therein on any patent granted thereon by the United States. This and related patents are available for licensing to qualified licensees.
Number | Date | Country | |
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Parent | 16146941 | Sep 2018 | US |
Child | 18373215 | US |