Configurable Inspection Platform

Abstract

Various embodiments described herein relate to a test chamber device, associated methods, and non-transitory machine-readable media, including a test chamber, a system builder configured to build and apply an equipment load to the test chamber, a load creator configured to build and apply a predetermined load to the test chamber, and a tester that measures behavior of the equipment load and the predetermined load within the test chamber and generates test states.

Description

[Technical Field]

[0001] (1) This disclosure relates to test equipment, and more particularly, but not exclusively, to a configurable test platform that allows control sequences to be easily reconfigured to test various equipment layouts.

[0002] (2) Today, testing equipment for HVAC and other uses involves testing each piece of equipment, consulting load tables in a book, and calculating whether the equipment is sized correctly. In some cases, energy simulation software is used to determine the required load. However, these results are theoretical and do not take into account the actual equipment, nor the actual physical loads that the equipment requires to interact with. Summary of the Invention [Means for solving the problem]

[0003] (3) This Summary is provided to introduce in a simplified form a selection of concepts further described below in the Detailed Description section. This Summary does not identify essential features or essential features of the claimed subject matter. The innovation is defined by the claims, and to the extent this Summary is inconsistent with the claims, the claims shall control.

[0004] (4) Various embodiments described herein provide a system for testing an equipment system using a test chamber. For example, in one embodiment, the test chamber is paired with a system builder, which is configured to build an equipment load and apply it to the test chamber. A load maker is also configured to build a predetermined load and apply it to the test chamber. A tester is also included that measures the behavior of the equipment load and the predetermined load in the test chamber and generates test conditions. In one embodiment, the system builder includes system builder equipment and a system configuration matrix, which attaches the system builder equipment to each other and to the test chamber. In one embodiment, the system builder equipment includes at least two of a heating and cooling section, a pumping section, a storage section, a heat exchange section, and a mixing section. Various embodiments described herein relate to a test chamber. The test chamber includes a chamber and a test chamber instrument, the test chamber instrument providing a test condition distribution, the test condition distribution including a radiation condition distribution, an air condition distribution, or a convection condition distribution.

[0005] (5) In various described embodiments, the test chamber equipment includes an air handler, a variable air chamber box, a radiant floor, or a radiator for applying a predetermined load. In various described embodiments, the test chamber is substantially enclosed by a hydronic shroud. In various described embodiments, the equipment load is a dynamic load, and the predetermined load is a dynamic load. In various described embodiments, the test chamber equipment further includes a hot water tank and a cold water tank, the hot water tank and the cold water tank configured to provide dynamic heating and cooling to the hydronic shroud. In various described embodiments, the system builder equipment includes at least two of a heating and cooling section, a pumping section, a storage section, a heat exchange section, and a mixing section. Additionally, various embodiments include a system configuration matrix including a plurality of two-way valves, which operatively couples at least two of the system builder equipment to create the equipment load. In various described embodiments, the load former uses a buffer tank to create a zone mass.

[0006] (6) Various embodiments described herein relate to a method for determining test chamber behavior including a test chamber, a system builder, and a weathermaker system, the weathermaker system being included in a system having a processor and memory, the method including configuring the system builder to create a system builder configuration, creating a first dynamic load in the test chamber using the system builder configuration, determining a second dynamic load using the processor and memory, generating the determined second dynamic load, configuring the weathermaker system to create the determined second dynamic load in the test chamber, and using the interaction of the first dynamic load and the second dynamic load in the test chamber to determine test chamber behavior.

[0007] (7) In various described embodiments, configuring the system builder includes configuring equipment associated with the system builder using a bidirectional valve matrix. In various described embodiments, the test chamber behavior includes a state within the test chamber when a first dynamic load and a second dynamic load are simultaneously present within the test chamber for a determined amount of time. In various described embodiments, the test chamber enables a state distribution, whereby the state distribution includes a radial state distribution, an air state distribution, or a convective state distribution. In various described embodiments, determining a state within the test chamber includes determining when the second dynamic load balances with the first dynamic load. In various described embodiments, determining when the second dynamic load balances with the first dynamic load includes determining when a state of the second dynamic load equals a state of the first dynamic load. In various described embodiments, the state of the first dynamic load is temperature.

[0008] (8) Various embodiments described herein relate to a non-transitory machine-readable storage medium having data and instructions configured thereon. When executed by at least one processor, the instructions cause one or more devices to perform a method for determining test chamber behavior, including a test chamber, a system builder, and a weathermaker system. The weathermaker system is included in a system having a processor and a memory. The method includes configuring the system builder to create a system builder configuration, creating a first dynamic load in the test chamber using the system builder configuration, determining a second dynamic load using the processor and memory and generating the determined second dynamic load, configuring the weathermaker system to create the determined second dynamic load in the test chamber, and using the interaction of the first dynamic load and the second dynamic load in the test chamber to determine test chamber behavior. Various embodiments described herein include determining the second dynamic load using additional machine learning.

[0009] (9) For a better understanding of various example embodiments, reference is made to the accompanying drawings, in which: [Brief explanation of the drawings]

[0010] [Figure 1] (10) A generalized example of a suitable computing environment in which the described embodiments may be implemented. [Figure 2] (11) An example flow diagram illustrating a high level configurable testing platform is shown. [Figure 3] (12) An example block diagram illustrating a configurable testing platform in further detail is shown. [Figure 4] (13) Examples of specific types of loads that can be used herein are provided. [Figure 5] (14) Examples of equipment that can be used within the test chamber to apply the test load are provided. [Figure 6a] (15) An example of a weathermaker system is shown. [Figure 6b1] (16) An example of a system builder schematic diagram is shown below. [Figure 6b2] An example of a system builder schematic diagram is shown below. [Figure 6c] (17) An example of a system builder and a schematic diagram of a wall broken down into sections. [Figure 6d] (18) An example of a configuration matrix setup that can be used within System Builder is shown below. [Figure 6e] (19) An example of a partial device configuration that can be used within the system builder is shown below. [Figure 6f] (20) An example of a bidirectional valve configuration that can be used within a system builder is shown. [Figure 6g] (21) shows an example of a configuration matrix configured to present variable primary system builder configurations. [Figure 6h](22) An example of a configuration matrix configured to present primary / secondary system builder configurations is shown. [Figure 6i] (23) An example of a configuration matrix configured to present complex system builder configurations is shown. [Figure 6j] (24) An example of a configuration matrix configured to present complex system builder configurations is shown. [Figure 7] (25) is a flowchart illustration illustrating an embodiment of a configurable testing platform. [Figure 8] (26) is an example flow chart illustrating another embodiment of a configurable testing platform. [Figure 9] (27) An example of a user interface screen that can be used to enter build information is shown. [Figure 10] (28) Another example embodiment provides a control path for running test wall equipment. [Figure 11] (29) Suitable equipment that can be used on the test wall is shown. [Figure 12] (30) An example of a flowchart describing the determination of test chamber behavior is shown. DETAILED DESCRIPTION OF THE INVENTION

[0011] (31) Disclosed below are exemplary embodiments of methods, machine-readable media, and systems that are particularly applicable to systems and methods for warming up a simulation. The described embodiments implement one or more of the described techniques.

[0012] (32) In the following description, numerous specific details are set forth to provide a thorough understanding of the present embodiments. However, it will be apparent to one skilled in the art that these specific details are not necessarily required to practice the present embodiments. On the other hand, well-known materials or methods are not described in detail to avoid obscuring the present embodiments. The use of "one embodiment," "an embodiment," "one example," or "an example" means that at least one embodiment of the present embodiments includes the particular feature, structure, or characteristic described in connection with the embodiment or example. In other words, the appearances of the phrases "in one embodiment," "in an embodiment," "one example," or "an example" in various places throughout this specification do not necessarily all refer to the same embodiment or example. The systems, devices, and methods described herein may be modified, added, or omitted without departing from the scope of the present disclosure. For example, system and device components may be integrated or separated. Furthermore, the operations of the systems and devices disclosed herein may be performed by more, fewer, or other components, and the methods described may include more, fewer, or other steps. In addition, steps may be performed in any suitable order.

[0013] (33) For convenience, the present disclosure may be described using relative terms, including, for example, left, right, top, bottom, front, back, upper, lower, up, and down, and the like, with the understanding that these terms are used for illustrative purposes only and are not intended to be limiting in any way.

[0014] (34) The present embodiments may be embodied as an apparatus, a method, or a computer program product. Accordingly, the present embodiments may take the form of entirely hardware embodiments, entirely software embodiments (including firmware, resident software, microcode, etc.), or embodiments combining software and hardware aspects. An embodiment combining software and hardware aspects may also be referred to as a "system." Furthermore, the present embodiments may take the form of a computer program product embodied in any tangible medium having machine-usable program code embodied in the medium.

[0015] (35) Any combination of one or more non-transitory machine-usable or machine-readable media may also be utilized. For example, the machine-readable medium may include one or more of a portable computer diskette, a hard disk, a random access memory (RAM) device, a read-only memory (ROM) device, an erasable programmable read-only memory (EPROM or flash memory) device, a portable compact disk read-only memory (CDROM), an optical storage device, and a magnetic storage device. The computer program code for carrying out operations of the present embodiments may be written in any combination of one or more programming languages.

[0016] (36) The block diagrams in the flowcharts and flow diagrams illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of code constituting one or more executable instructions for implementing the specified logical function(s). It should also be noted that each block in the block diagrams and / or flowchart diagrams, and combinations of blocks in the block diagrams and / or flowchart diagrams, may also be implemented by a special-purpose hardware-based system or a combination of special-purpose hardware and computer instructions that performs the specified functions or acts. These computer program instructions may also be stored on a machine-readable medium, and the instructions stored on the machine-readable medium may direct a computer or other programmable data processing apparatus to function in a specific manner to produce an article of manufacture including instruction means that implement the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0017] (37) For convenience of presentation, some operations of the disclosed methods are described in a specific order; however, it will be understood that this description encompasses rearrangements unless a specific order is required by specific language set forth below. For example, operations described sequentially can be rearranged or performed simultaneously. Moreover, for simplicity, the accompanying figures may not show the various ways in which the disclosed methods, apparatus, and systems can be used in conjunction with other methods, apparatus, and systems. Additionally, the description sometimes uses terms such as "determine," "build," and "identify" to describe the disclosed technology. These terms are high-level abstractions of the actual operations that are performed. The actual operations that correspond to these terms will vary depending on the particular implementation, but will be readily discernible by those skilled in the art.

[0018] (38) As used herein, the terms "comprises," "comprising," "includes," "including," "has," "having," or any other variation thereof, are intended to cover non-exclusive inclusion. For example, a process, article, or apparatus that includes a list of elements is not necessarily limited to those elements and may include other elements not expressly listed or inherent in such process, article, or apparatus.

[0019] (39) Furthermore, unless expressly stated to the contrary, "or" refers to an inclusive or, not an exclusive or. For example, condition A or B is satisfied by any one of the following: A is true (or exists) and B is false (or does not exist); A is false (or does not exist) and B is true (or exists); or A and B are both true (or exist). "Program" is used broadly herein to include applications, kernels, drivers, interrupt handlers, firmware, state machines, libraries, and other code written by programmers (also called developers) and / or automatically generated. "Optimize" means to improve, but not necessarily to perfection. For example, an optimized program or algorithm may be capable of further improvement. "Determine" means to understand well, not necessarily to arrive at a precise value. For example, an already determined value or algorithm may be capable of further improvement.

[0020] (40) Additionally, any examples or illustrations provided herein should not be construed as limiting, restricting, or expressly defining any of the term(s) used in conjunction with them. To the contrary, these examples or illustrations are described with respect to one particular embodiment and should be considered illustrative only. Those skilled in the art will recognize that any term(s) used in conjunction with these examples or illustrations encompasses other embodiments that may or may not be shown therewith, or that may or may not be shown elsewhere in this specification, and that all such embodiments are intended to be included within the scope of the term(s). Phrases indicating such non-limiting examples and illustrations include, but are not limited to, "for example," "for instance," "eg," and "in one embodiment."

[0021] (41) The technical features of the embodiments described herein will be apparent to those skilled in the art and will become apparent in various ways to the broader attentive reader. Some embodiments address technical activities rooted in computing techniques, such as determining a specific control sequence for a particular piece of equipment to handle a given load while conserving the most energy. The disclosures and embodiments presented herein provide a rapid method for providing a wide range of physical systems with different characteristics and topologies. Such disclosures also accommodate performing a wide range of physical experiments, such as sensor calibration timing, equipment specification validation, and measurement and verification techniques. Other advantages based on the technical features of the present teachings will be apparent to those skilled in the art from the following description.

[0022] 1.Big picture (42) Disclosed herein are systems and methods for creating and using a configurable testing platform. A testing platform that generates real loads and uses real equipment that must work against those loads would be extremely useful in determining actual energy performance and behavior in a real-world context.

[0023] (43) Buildings and the spaces within them are unique and have their own idiosyncrasies, and a mere listing of building characteristics, no matter how detailed, cannot fully reflect these characteristics. Buildings are slow to change state, and state changes often depend on external factors such as weather, the number of people in the building during the day, etc. Therefore, determining whether a state-changing system within a building is behaving correctly can be a long and tedious process. Because everything in a building is thermodynamically connected, it can be very difficult to say whether the building is functioning as designed. For example, if a thermostat is placed in a zone adjacent to where it should be, it will not only heat the incorrect zone but also provide heat to the correct zone, making this error very difficult to detect. When creating systems for new buildings or adding new equipment to existing buildings, it would be beneficial to be able to actually test such systems under real-world conditions, rather than just simulated conditions, prior to installation to avoid making costly errors. It would also be beneficial to be able to test proposed equipment control sequences in a real-world test environment where the control sequences can be run on equipment and introduced into a space with known state loads and acted upon these state loads. This can be used to verify that the equipment for which the control sequences are programmed can actually handle the expected loads over a period of time, including the weather that may be encountered.

[0024] (44) One example includes a test wall and a configuration matrix connected to a test chamber. The test wall can house a collection of equipment, such as heating and cooling sources, pumps, heat exchangers, valves, tanks, etc. The configuration matrix allows for the inclusion of equipment so that almost any type of state system can be built within minutes. This allows for great flexibility when testing a wide range of system topologies and configurations. The test chamber is connected to the configured equipment and a load shaper. The equipment transfers loads into the test chamber. For example, the equipment can dynamically transfer conditions, such as heat, into the test chamber. Ideally, both the equipment and the load shaper inject conditions into the test chamber simultaneously. In an example, this can be thought of as modeling a building's HVAC system using weather effects. Measurements in the test chamber then inform the tester of how the equipment coped with the weather-like conditions in the test chamber (represented by conditions generated by the weathermaker). In another exemplary embodiment, conditions representing the thermodynamic properties of a structure are inserted into the test chamber through the WeatherMaker, and configured equipment then transfers the conditions into the test chamber to see if they can, for example, offset the structure conditions.

[0025] II. Example Computing Environment (45) Figure 1 illustrates a generalized example of a suitable computing environment 100 in which portions of the described embodiments may be implemented. The computing environment 100 is not intended to suggest any limitation as to the scope of use or functionality of the present disclosure, as the present disclosure can be implemented in a variety of general-purpose or special-purpose computing environments.

[0026] (46) Referring to FIG. 1, computing environment 100 may include processor 130. This processor 130 may include at least one central processing unit 110 and memory 120. Central processing unit 110 executes machine-executable instructions and may be a real or virtual processor. It may also include vector processor 112. In a multiprocessing system, multiple processing units execute machine-executable instructions to increase processing power, and thus vector processor 112, GPU 115, and CPU 110 may execute simultaneously. However, in various embodiments, elements belonging to processor 130 need not be physically co-located. For example, CPU 110 and GPU 115 may be mounted on boards that are physically separate from one another.

[0027] (47) Memory 120 may be volatile memory (e.g., registers, cache, RAM), non-volatile memory (e.g., ROM, EEPROM, flash memory, etc.), or some combination of the two. Memory 120 stores software 185 that implements the described methods and systems for aligning and correcting inaccurate polygons, as needed.

[0028] (48) A computing environment may also have other features. For example, computing environment 100 includes storage 140, one or more input devices 150, one or more output devices 155, one or more network connections (e.g., wired, wireless, etc.) 160, and other communication connections 170. An interconnection mechanism (not shown), such as a bus, controller, or network, interconnects the components of computing environment 100. Typically, operating system software (not shown) provides an operating environment for other software executing in computing environment 100 and coordinates the activities of the components of computing environment 100.

[0029] (49) Storage 140 may be removable or non-removable and includes magnetic disks, magnetic tapes or cassettes, CD-ROMs, CD-RWs, DVDs, flash drives, or any other media that can be used to store information and that can be accessed within computing environment 100. Storage 140 stores software instructions, such as software 185 that implements the systems and methods used to configure the testing platform.

[0030] (50) Input device(s) 150 may be devices that enable a user or other devices to communicate with computing environment 100, such as a touch input device like a keyboard, a video camera, a microphone, a mouse, a pen, a trackball, a digital camera, a LiDAR device, a scanning device like a digital camera with a scanner, a touchscreen joystick controller, a Wii remote, or other devices that provide input to computing environment 100. For audio, input device(s) 150 may be a sound card or similar device that accepts audio input in analog or digital form, or a CD-ROM reader that provides audio samples to the computing environment. Output device(s) 155 may be a display, a hardcopy generating output device like a printer or plotter, a text-to-speech reader, a speaker, a CD writer, or other device that provides output from computing environment 100.

[0031] (51) Communication connection(s) 170 enable communication to other computing entities over a communication medium. The communication medium conveys information such as machine-executable instructions, compressed graphics information, or other data in a modulated data signal. Communication connection(s) 170 may include input device(s) 150, output device(s) 155, and input / output devices that enable the client device to communicate with other devices over network 160. Communication devices may include one or more wireless transceivers for wireless communication and / or one or more communication ports for wired communication. These connections may include network connections, which may be wired or wireless networks such as the Internet, an intranet, a LAN, a WAN, a cellular network, or other types of networks. It should be understood that network 160 may be a combination of multiple different types of wired or wireless networks. Network 160 may also be a distributed network including multiple computers, which may work together to form a controller. The communication connection 170 may be a portable communication device, such as a wireless handheld device, a personal electronic device, or the like.

[0032] (52) A machine-readable medium is any available, non-transitory, tangible medium that can be accessed within a computing environment. By way of example, and not limitation, in computing environment 100, non-transitory machine-readable media can include memory 120, storage 140, communication media, and any combination thereof. To aid in understanding, FIG. 1 illustrates non-transitory machine-readable storage medium 165 and associated content. It will be appreciated that non-transitory machine-readable storage medium 165 may correspond to memory 120, storage 140, or a similar device (not shown) accessible via communication connection 170. As used herein, the term “non-transitory” is understood to exclude transitory signals, but to include all forms of memory and storage, including both volatile and non-volatile memory. This non-transitory machine-readable storage medium 165 can store instructions 175 and data 180. The data source can be a computing device, such as a general-purpose hardware platform server, configured to receive and transmit information via communications connection 170. Computing environment 100 can also be an electrical controller directly connected to various resources, such as HVAC resources, with the electrical controller having CPU 110, GPU 115, memory 120, input devices 150, communications connection 170, and / or other features shown in computing environment 100. Computing environment 100 can also be a series of distributed computers, which can comprise a series of connected electrical controllers.

[0033] (53) Furthermore, data generated from any of the disclosed methods can be created, updated, or stored on tangible machine-readable media (e.g., one or more CDs, volatile memory components (such as DRAM or SRAM), or non-volatile memory components (such as hard drives) using a variety of different data structures or formats. Such data can be created or updated locally on a computer or over a network (e.g., by a server computer), or can be stored and accessed in a cloud computing environment.

[0034] (54) While computing environment 100 is shown as including one of each described component, various embodiments may duplicate various components. For example, CPU 110 may include multiple microprocessors, configured to independently perform the methods described herein, or configured to cooperate to perform method steps or subroutines described herein to achieve the functionality described herein. Furthermore, when computing environment 100 is implemented within a cloud computing system or swarm computing system, various hardware components may reside in separate physical systems. For example, processor 130 may include a first processor located within a first cloud server and a second processor located within a second cloud server.

[0035] III. DISCLOSURE OF AN EXEMPLARY CONFIGURABLE INSPECTION PLATFORM (55) FIG. 2 shows an example of a high-level flow diagram of a configurable testing platform at 200. The illustrated system 200 shows various functional components and some of the interactions between them. The configurable testing platform 200 includes a first load determiner 203. This load determiner 203 can be virtually any system capable of determining state loads for a controlled space. This "controlled space" should be loosely defined. It can refer to a building, a collection of related buildings, a collection of related buildings and their surrounding spaces, a collection of unrelated related buildings, a collection of unrelated buildings and their surrounding spaces, an exterior space such as a garden with an irrigation system, a floor, a zone, a room, various rooms, multiple zones in a room, a portion of a building such as multiple zones across several rooms, multiple zones across several buildings, etc. Many different conditions 210 can be used within the configurable testing platform 200, such as humidity, atmospheric pressure, sound pressure, occupancy, indoor air quality, CO2 concentration, light intensity, or any other condition that can be measured or controlled. A first load determiner 203 determines the amount of state needed to maintain the controlled space at a desired state over time. Building-controlled-space-conditions are dynamic by their nature. For example, using heat as a typical state, a building has many ways to both gain and lose heat over time. Some of these ways are solar heat gain (heat gain from absorbing solar energy), heat generated by people in the building, and heat generated by equipment such as lighting. Heat can also be lost from the building itself, such as through vents, windows, and leakage from the building itself. Weather also affects the temperature of a building. Other conditions can be considered, such as humidity, atmospheric pressure, sound pressure, occupancy, indoor air quality, CO2 concentration, and light intensity. 2 Conditions such as concentration, light intensity, or any other condition that can be measured or controlled can all be used within the configurable testing platform.

[0036] (56) A load is a state quantity that must be added to or removed from a space to maintain the state within a desired range. If the state under consideration is temperature, the load is the amount of heat (e.g., state) that must be added or removed by the HVAC system to reach the desired temperature over time, taking into account the heat sources acting on the space, as discussed above. If the state is humidity, the load is the amount of humidity that must be supplied or removed by the humidity control device to reach the desired humidity over time. As previously mentioned, these states are dynamic, and therefore the loads are dynamic as well. These loads are often measured over time; that is, they describe how the desired load is expected to vary over time.

[0037] (57) The first load determiner 203 determines how many states must be created to meet the system requirements. This will be discussed with reference to FIG. 10 and the surrounding text. The system builder 205 creates the states 210 determined by the load determiner 203 and then transfers the created states 210 to the test chamber 215. The second load determiner 235 determines how many states must be created to meet the test chamber requirements. This second state can be conceptually thought of as a state designed to balance the states created by the system builder. In one embodiment, the first load determiner 203 and the second load determiner 235 are the same load determiner. The weather maker 225 creates the states already determined by the second load determiner 235 and transfers these states to the test chamber. The sensor 230 measures the conditions inside the test chamber. In some embodiments, indoor air quality may be the condition 210, and test chamber 215 includes filtration equipment, and weathermaker 225 adds particulate matter from wildfires, pollution, etc. The weathermaker may also add particles, etc., that are closely associated with illness. In some embodiments, the condition is sound, and test chamber 225 includes sound-attenuating equipment, white noise, different sources of different types of sound, etc. In some embodiments, multiple conditions are tested at once.

[0038] (58) Figure 3 shows an example block diagram at 300 that further details a configurable inspection platform. The first load determiner 303 can use a digital twin model to determine the load curve. This digital twin model can include constructing a copy of the controlled space in question. This may involve describing the space's components and their thermal properties. For example, a wall may include brick, insulation, drywall, etc. These components can be encoded into a simulation, such as a physics-based simulation. In such a simulation, a wall can be modeled as one or more nodes that describe the properties of the wall's building layers. There is a brick node, followed by an insulation load, followed by a drywall node, and so on, throughout the building. The exterior nodes have their state values ​​changed by weather nodes, and this state change flows throughout the building. Interior nodes representing the inside of a room can apply other functions, such as those representing lighting and people in the zone (hot air). The state information continues to propagate until it reaches other outer layers, and the individual node parameter values ​​are updated at time T. n represents the conditions that exist within a building. In some embodiments, each exterior surface has its own time-temperature curve. In some embodiments, the building is decomposed into smaller subsystems (or zones), so that only parts of the structure are affected by a given input, rather than propagating temperatures throughout the entire structure.

[0039] (59) In one embodiment, the digital twin model is built on a controller associated with the controlled building. This controller may be the first load determiner 303, the second load determiner 335, both load determiners, etc. In one example, the controller is embedded within the controlled building and used to automate the building. The controller may include a simulation engine that itself constructs a model of the controlled system in which the controller is embedded, a model of the equipment in the controlled system in which the controller is embedded, or both. This model may also be referred to as a "physical model." The physical model may itself be trained. Training may include past regressions and cost functions. Past regressions are past instances of these models run and their results. The controlled system has at least one sensor, and the sensor values ​​may be used to calibrate the physical model(s) by checking how close the model values ​​at the sensor locations are to the simulated equivalent sensor values ​​in the physical model. The cost function may be used to determine the distance between the sensor values ​​and the simulated equivalent sensor values. This information can then be used to make refinements to the physics model. This controller-controlled system loop can also be implemented without the use of an external network, such as the cloud and / or colloquially known as the "Internet." The controller can control and / or run a local area network (LAN) through which it communicates to sensors and other resources. The controller can also be hardwired to and embedded with sensors and other resources. There can also be a combined system where some resources are hardwired and others connect to the LAN. The system builder 305 is configured to build the equipment state loads 330 and apply the loads 330 to the test chambers.

[0040] (60) The equipment load curve measures conditions over time and therefore may be dynamic, as discussed above. To create it, the system builder 305 further includes equipment 340 and a configuration matrix 310, which allows for different configurations of the equipment 340. The system builder is further described in FIGS. 6b1, 6b2, and 6c-6h. The weathermaker 225 also operates to move conditions into the test chamber and may include a load shaper "in" located inside the test chamber and / or a load shaper "out" 325 located outside the test chamber and directing its conditions 330 into the test chamber. The weathermaker is further described in FIG. 6a. The condition loads 330 from the system builder 305 may be moved into the test chamber 315 and balanced against the condition loads generated by the load shaper input 320 and load shaper output 325. In some embodiments, testing can also measure how states from the system builder behave against states generated from a load shaper (320, 325) in the test chamber. In some embodiments, testing can also measure how states from the system builder behave against states, additional loads, or synthetic zones generated from a load shaper (320, 325) in the test chamber.

[0041] (61) As an illustrative example of operation, a test chamber load shaper can simulate a snowstorm zone where the (simulated) outside temperature is between 10 degrees above freezing and 25 degrees above freezing for an eight-hour period. The system builder determines how much heat can be pumped into the test chamber over the eight hours to maintain the temperature at a desired high temperature. This desired high temperature may vary. This desired high temperature is transformed into a control sequence to operate the equipment. The equipment 340 then operates for eight hours, using the control sequence to pump conditions into the test chamber. For example, if the test chamber 315 is equipped with a hot water radiator (not shown), the equipment 340 controls the delivery of hot water to the radiator to raise the temperature of the test chamber to the current desired heat level, countering the effects of the load shapers 320, 325, which typically lower the temperature of the test chamber 315 when simulating a snowstorm. How well the temperature matches the desired temperature over the length of the test (test chamber behavior) will determine how well the control sequence works.

[0042] (62) FIG. 4 illustrates various types of loads that can be used in 400. Weathermaker 225 loads can be thought of as falling into three types: test chamber loads 410, synthetic zones 415, and tanks of zone loads 420. The test chamber loads 410 can be applied to a test chamber (in one example embodiment, the test chamber may be 10' x 10' x 12', but can be smaller or larger depending on application, system, space, and / or pricing requirements). Heating, cooling, and other loads can be applied to the chamber by a hydronic shroud (an example of which is described in more detail below) around the chamber, or by one or more in-room emitters for additional loads. The synthetic zones 415 can be created using heat exchangers that use hot and cold water to generate specific dynamic loads. In some embodiments, a building includes at least one controlled space. This controlled space can be an entire building, part of a building, a single room, a portion of a room, an exterior area such as a garden, etc. It can be a space that currently exists or a space that only exists as a design. Buildings are often divided into zones. These zones often represent separate areas with distinct sensors, such as rooms or other such controlled spaces, but can also represent different areas within a larger space, such as a warehouse. Loads can be controlled by modulating flow rates with energy / control valves. Within a zone, energy is consumed and energy is added, both of which change the state of the zone. Thus, a composite zone 415 can be modeled using contraptions that consume energy and can supply it with energy. The composite load can dump state into a state exchanger and does not store energy. Hot or chilled water is pumped throughout the space to provide heating and cooling for the actual hydronic controlled zones.In synthesis zone 415, the same process is used, except there is no void, e.g., hot water can be produced to provide heat to the synthesis zone and cold water to provide cooling, but rather, it is simulated by a heat exchanger that essentially releases energy to nowhere.

[0043] (63) Tanks 420 as zone loads may be buffer tanks of water, fluid, or other material capable of simulating the mass of a zone. Loads can then be applied to the tanks to simulate conditions in these "real" zones (either constructed or designed). For example, the mass of a 25-gallon aquarium can be considered equivalent to a room of a particular size. Larger tanks may represent larger rooms, and so on. One or more gas-to-water heat pumps can be used to apply dynamic loads. Tanks 420 as zone loads behave similarly to synthetic zones 415, except that rather than releasing load energy, the tank can store the load energy and store it for later use. Synthetic zones 415 provide the ability to have zones of various sizes and loads can be applied to them (by the weathermaker). In some embodiments, control and test walls can treat these synthetic zones as real spaces. The weathermaker system 225 can monitor the test chamber load 415, the synthetic zone 415, the tank 420 as a zone load, etc., with one or more temperature sensors and one or more flow sensors.

[0044] (64) FIG. 5 shows, at 500, an example of equipment that can be used in the test chamber to apply the test load 220, such as a weathermaker 225. It may include one or more air handlers 505, which may be variable-speed air handlers with heating and test cells, or different types of air handlers. It may also include one or more variable air volume (VAV) boxes 510. These VAV boxes can be reheated and used to maintain a more precise temperature (or other condition) within the chamber, thereby helping to create and maintain a dynamic load. Additional loads 515 may also be included to drive loads beyond those that the rest of the equipment can apply. A radiator 520, which may be a hydronic radiator, may be used to provide radiant heat. A radiant floor 525 may also be used to provide additional heat. A hydronic shroud 530 may be provided. This shroud 530 may substantially enclose the test chamber and further direct heating and cooling loads within the space. In some embodiments, the hydronic shroud 530 can have a heat circulation loop of plastic piping for heat transfer. Aluminum transfer plates can be inserted in multiple locations inside the shroud to spread the heat provided by the water flowing through the piping. The hydronic shroud 530 can be covered with insulation 535, which can be a rigid insulation. This insulation can be used to ensure that the temperature provided by the liquid is pumped into the testing chamber and not lost to the outside, and can also provide rigidity to the shroud. Different loads can be applied to different sides of the shroud, allowing for the testing of different types of building walls (e.g., interior, exterior, etc.). In some embodiments, the hydronic shroud can cover all six sides. In some embodiments, specific sides can have separate temperature sources. For example, convective heat 525 can be provided. This convective heat can be provided to the floor or to different sides.In some embodiments, convective heat may be provided on multiple sides. In some embodiments, the hydronic shroud 530 covers fewer than six sides, covers all sides, or only partially covers one or more sides.

[0045] (65) Figure 6a shows an example 600a of a weathermaker system 225. The system can utilize an air-to-water heat pump 605a, which can be used as a geothermal heat source. The system can also utilize a ground maker circular pump 610a, a ground grading buffer tank 615a (or a buffer tank used for a different reason, such as tank-as-zone load 420), one or more test chamber shroud linkers / manifolds 620a that supply heated or cooled water to the hydronic shroud 530, one or more hydronic shroud control valves 635a, one or more tank-as-zone loads 625a, and one or more synthesis zones 630a with heat exchangers, e.g., 645a. Some embodiments of the system include one or more hot water tanks and / or one or more cold water tanks. These tanks are used to supply hot or cold water to the linker / manifold(s) 620a or directly to the hydronic shroud. These hot and cold water tanks can also be configured to supply dynamic loads to the hydronic shroud 539, and thus to the test chamber 315. Control valves, e.g., 635a, 640a, can be positioned so that different parts of the system builder 205 can be switched on and off by a user configuring the system builder, by an automation system, by a controller, etc. Controller 650a can be used to control flow to downstream devices, etc. By opening and closing valves and varying the controller behavior, many different scenarios can be addressed. The controller behavior can be controlled by some combination of the control sequence determination software 720 and the controller 740. The control sequence determination software-controller combo can use machine learning techniques to determine the controller behavior. The controller itself can use machine learning techniques to determine near-optimal behavior for a given expected event.

[0046] (66) Figures 6b1 and 6b2 show, at 600b1 and 600b2, respectively, a system builder 205 that can be used within the configurable testing platform 200. This system builder 205 is the basis for Figures 6c, 6d, and 6g-6j, although other system builders are contemplated. The figures are drawn using common mechanical design symbols and combinations. For example, 605b discloses a gate valve. The system is designed to allow thousands of configurations of the condition testing system and targets a virtual building that allows these configurations to be tested against both the conditions provided by the testing chamber 215 and other loads applied within the weathermaker 225. Different condition testing configurations are created by switching valves on and off.

[0047] (67) Figure 6c shows at least some portions of an exemplary system builder divided into multiple sections, at 600c. Other system builders may have different configurations. In some system builders, certain types of functional equipment are physically located close to each other. In the illustrated system 600c, heating and cooling sources are located together (605c), pumping elements are located together (610c), routing elements are located together (615c), storage elements are located together (620c), heat exchange elements are located together (625c), pumping elements are located together (630c), mixing elements are located together (635c), and load elements are located together (640c). The test configuration may use one or more elements from each section, if desired.

[0048] (68) Figures 6d and 6e show an example of a system builder constructed along both sides of a single wall, with the majority of the two-way valves on one side 600d. In this example, the two-way valves are installed within a matrix tower. Referring to Figure 6f, the matrix tower is shown in more detail at 600f. The main body of the equipment used to create the conditions is constructed on the other side 600e of the wall shown in 600d. Many other embodiments are possible, including constructing all the equipment and valves on one side, constructing the system builder on multiple walls, or constructing multiple parts of the system builder as a single piece of equipment.

[0049] (69) Figure 6f illustrates at 600f potential valve setups possible for system builder 205. In this exemplary embodiment, the bidirectional valves are built in a tower that houses 28 bidirectional valves. Other sizes of towers and other non-tower configurations are also contemplated. In this exemplary embodiment, opening and closing these bidirectional valves configures different possible system builder configurations.

[0050] (70) FIG. 6g illustrates at 600g how an example system builder 205 can be used to create a variable primary HVAC system and then test the system builder 205 using the test chamber 215. FIG. 6h illustrates at 600h how an example system builder 205 can be used to create a primary / secondary system. FIG. 6i at 600i and FIG. 6j at 600j are examples of how to recreate a composite system that integrates components and subsystems that accommodate multiple heating and cooling sources, multiple storage options, and different load sources.

[0051] (71) Figure 7 is an example flowchart 700 illustrating one embodiment of a configurable testing platform. The testing platform has two tracks. One is a weather track, which determines the external loads generated on a space by weather (load curve). The other is a test track, which assumes weather and determines the amount of thermal heating / cooling required to maintain the space in a desired state for a certain period of time. Once these are known, the weather track uses a weathermaker 225 to generate the desired amount of conditions (loads) to act on the test chamber. The test track uses the determined loads to determine how to operate the equipment on the structure being tested (test wall equipment 750 is configured to simulate numerous equipment settings). The equipment on the test wall 750 is then operated according to the load specifications to see how the test wall's equipment handles the weathermaker's weather loads. This allows the test to be performed. The WeatherMaker completes its tests by physically heating and cooling the zones, rooms, liquid tanks that model the zones, etc., while the test truck controls the actual equipment to handle the loads generated by the WeatherMaker.

[0052] (72) Weather Track acquires weather data in operation 705. This weather data may be in the form of time / condition curves, such as time / temperature curves, time / humidity curves, etc. This condition data may be in the form of historical weather patterns, collected data, weather forecasts, etc. "Weather data" may be any type of condition data and need not literally be weather data. In operation 710, building data is collected. Once collected, this building data is used to determine the flow of conditions throughout the building. In some embodiments, the building data may be defined by a predefined CAD drawing, by scanning the building with a 3-D floorplan capture system, by constructing an interface that includes predefined but modifiable building materials that can be drawn, or a combination thereof.

[0053] (73) This building and weather data is then provided to program 715, which determines a load curve 725 based on the building's construction and weather loads. One such program is the ENERGYPLUS™ Building Energy Simulation Program, developed and operated by the U.S. Department of Energy. A load curve is the amount of energy that should be supplied to a zone (or other defined location) to achieve a particular condition. The load curve may be in Kbtu / hr (thousands of British thermal units per hour) or a different unit. These load curves are then provided to WeatherMaker 735, which then uses the load curves to generate the "desired weather" using a load shaper (see, for example, Figure 4). The thermal units generated by the WeatherMaker (if temperature is a condition) are then provided to Test Configuration 755. This includes the inspection chamber 500, the hydronic shroud 530, the synthesis zone 415, the tank 420 as a zero load, any additional loads, or any combination thereof.

[0054] (74) For inspection trucks, in one example environment, building data is collected in operation 710. In some embodiments, the building data can be determined by a predefined CAD drawing, or by scanning the building using a 3-D floor plan capture system or the like.

[0055] (75) A 3-D scanning program may be used to determine the size of one or more spaces. Previously developed blueprints may be used. Point-and-touch programs, etc., may be used to input space statistics. This building data can then be converted into a digital twin. The digital twin can be converted into a machine learning model, which utilizes deep learning neuron models to accurately determine the thermal properties of the modeled building. One way to do this is to use a neuron modeling system. This neuron modeling system may include neurons representing individual material layers of the building, each with different values, such as their resistance and capacitance. When the digital representation of the building is input into an automation system, component parts of the building with different thermodynamic qualities are comprehensively defined. These (in one embodiment) can be decomposed into buildings, floors, zones, surfaces, layers, and materials to reduce complexity. Layers are composed of materials, surfaces are composed of layers, etc. These neurons are formed into parallel, unbranched neural network strings through which heat (or other state values) propagate. Neurons can be considered heterogeneous in that their activation functions can represent the ways in which heat propagates. In such a neural network, each neuron representing a material with a different thermal (or other state) quality can have a different activation function. That is, rather than introducing nonlinearity into the neural network, the activation functions perform distinct functions that represent the flow of state through the neural network.

[0056] (76) Which specific component parts of a building are used depends on the implementation model. Some models may be at a very high level and thus have structural elements consisting of floors, for example. Other models may be at a very low level and thus use material-level structural elements, such as a kind of subfloor, a kind of underlayment, a kind of floor, etc. Other options are possible as well.

[0057] (77) A structure may have multiple zones (such as rooms or specific areas monitored by sensors). Each distinct zone can be modeled by its own neural model. This neural model may be a single neuron or multiple neurons connected in some way. A collection of neuron models can constitute a thermodynamic model of the structure. In such a multi-zone model, when multiple zones share a surface, such as a wall, floor, or ceiling (in a building implementation), the outer neurons of one neural model can be used as the inner neurons of the next neural model. Some zones may overlap with other zones, while others do not. The entire structure may be covered by zones, but some parts of the structure may not have explicit zones. A controlled space can be defined into multiple subsystems. Any of these partitioned controlled spaces can be used as subsystems.

[0058] (78) These zones can be modeled as neuron-model systems, with neurons representing the individual material layers of the building and their various values, such as resistance and capacitance. These neurons are organized into parallel, unbranched neuron network strings through which heat (or other state values) propagate. When a digital representation of the building is input into an automation system, component parts of the building with different thermodynamic qualities are comprehensively defined. These (for one embodiment) can be decomposed into buildings, floors, zones, surfaces, layers, and materials to reduce complexity. Layers are composed of materials, surfaces are composed of layers, and so on.

[0059] (79) In operation 720, in one embodiment, a control path creator system inputs building data 710 and weather data 705 and then outputs control path 730. An example of such a system is described in U.S. Patent Application No. 17 / 228,119, filed April 12, 2021, the disclosure of which is incorporated herein by reference in its entirety. Using such a method can reduce programming by 95%, or 60%, of the overall effort, and require only 40% of the time. This method can also include a guided graphical process (which may involve using a touchscreen, a browser on a laptop, or a different method). This method can include a 3D LiDAR scanning application and be integrated into the process for determining building data. A library of equipment and systems can be used to quickly build accurate models of the equipment within the building. Building floor plans, equipment, and sensor locations can all be created using a drawing program integrated into the system. For example, sensors and IoT devices can be dragged and dropped into a floor plan, and a WYSIWYG interface can be used to draw a schematic of the equipment. A program (e.g., Control Path Generator or other program) can then generate the control system design, determine how the equipment should be connected to the controller (automatic point mapping), etc.

[0060] (80) When it is time to run, weather 705 or other state data can be provided to a control path creator program 720. This program can use information about the structure and the provided state data 705 to generate control paths 730. The control paths 730 provide equipment setpoints for controlling conditions in the modeled structure over time. At 740, these control paths are provided to a controller, which then uses these control paths to operate test wall equipment 750. In one embodiment, the test wall equipment 750 operates simultaneously with the weathermaker, which, among other things, checks the control paths provided to the equipment to see if it can handle the weathermaker load, for example, and maintain the test chambers, synthesis zones, and / or other test loads in their desired states.

[0061] (81) FIG. 8 is an example flowchart 800 illustrating another embodiment of a configurable testing platform. Weather data 805 is interpreted or converted as a temperature curve 825 or a different type of state curve. A weathermaker 835 takes the temperature curve as input and uses it to output sufficient conditions (in the form of controlling testing equipment 340 to model the weather for testing chamber 755). The weathermaker can impose physical loads on testing chamber 855 using a hydronic shroud (and other equipment as shown with reference to FIG. 5). The physical loads can be used to test the control sequences generated as output of the control path creation-controller process.

[0062] (82) Figure 9 shows an example user interface screen 900 that can be used to enter building information. Other screens can be used to draw buildings, determine building material properties used, etc. The screen shown in Figure 9 can be used to enter sensor data locations. Other screens allow for the entry of equipment, such as HVAC equipment and other equipment that can be used to control building conditions.

[0063] (83) FIG. 10 illustrates, at 1000, an example of another embodiment for creating a control path for running test wall equipment (e.g., steps 720-740 of FIG. 7). Each of the steps in FIG. 10 can be performed by a control path creator, a load curve maker, either alone or both. The system requirements for the controlled space can be determined. To do this, in one embodiment, a digital twin of the building can be created, as discussed above. This digital twin representation of the building can include digital twin representations of the equipment used to run or be used in the space in question. The digital twin representation can also include a digital twin representation of the controlled space itself, as discussed above. One or more controllers with one or more processors can be used for the required computing. These controller(s) can be edge computing machines, working together and not using external internet connectivity. Conversely, if there are multiple controllers, they can run using a local network. It is also possible to use a pre-trained machine learning model that uses a digital twin model of the space to be inspected and run it on the controller, or on multiple controllers that are networked together.

[0064] (84) One or more temperature / time curves 1005 can be collected that model the weather experienced or will be experienced by the controlled space. These collected temperatures can be used 1015 as inputs to a machine learning building model program. There can also be one or more interior temperature curves 1010 that the space itself or one or more zones within the space are predicted to encounter. For example, the temperature within the space may ideally be 65 degrees from 8 PM to 6 AM, then change to 72 degrees from 6 AM to 8 PM. The machine learning model can then output 1020 a load time / state curve that provides the amount of state to inject into various zones over time to achieve the desired interior temperature, given the external temperature and the characteristics of the building itself. Using 1025 the time / state curves and knowledge of the equipment in the building, another trained machine learning model can determine 1030 the optimal control sequence to achieve the desired interior temperature, given the external temperature. This control sequence can then be executed 1035 on the test wall using test wall equipment 750. The output from the test wall equipment is then used in a test procedure 755. This test procedure can use weathermaker 225 to generate conditions that balance the generated test wall equipment conditions. The test results can be determined from how balanced the loads are, how unbalanced the loads are, or other results. The weathermaker can use the test chamber load 410, the synthetic zone 415, the tank 420 as a zone load, an additional load (e.g., 515), or any combination thereof.

[0065] (85) Figure 11 shows possible equipment 1100 that can be used on a test wall. This equipment can include any combination of heating and cooling equipment 1105, pumping equipment 1110, induction equipment 1115, storage equipment 1120, heat exchange equipment 1125, mixing equipment 1130, or loads 1135.

[0066] (86) FIG. 12 shows an example flowchart describing a process for determining test chamber behavior at 1200. At step 1205, a system builder is configured. In one embodiment, configuring the system builder includes determining control paths for the system builder's equipment, as discussed with reference to 710, 720, 730, 740, and 750 of FIG. 7 and FIG. 10. At step 1210, a first dynamic load is generated. In one embodiment, this dynamic load is created by operating equipment 340 controlled by configuration matrix 310 using the control paths configured at step 1205. At 1215, a second dynamic load is generated. In one embodiment, this second dynamic load can be generated as shown at 705, 715, 725 of FIG. 7 and surrounding text. In other embodiments, this second dynamic load can be determined as shown at 805 and 825 of FIG. 8 and surrounding text. This second dynamic load may be determined by a different system than that which determined the first dynamic load determiner. This second dynamic load may be in the form of a temperature curve (temperature / time) that simulates weather, as described with reference to weather data 705, 805. This may also be described with reference to test chamber load 410, synthetic zone 415, and tank 420 as a zone load. In step 1220, the first dynamic load and the second dynamic load interact in the test chamber. As can be seen in FIGS. 2 and 3, state 330 (first dynamic load) from the system builder and state from WeatherMaker 225 (e.g., state from load shaper input 320 in 320 and / or state from load shaper output 325) converge within test chamber 315. These states interact to change the state inside the test chamber. In step 1225, the results are collected. In one embodiment, when the state being measured is temperature, the result is temperature. The temperature within the test chamber can be measured, and if the temperature is as expected or within a certain percentage, the test may be positive.In some embodiments, determining the result includes the second dynamic load balancing the first dynamic load, hi some embodiments, the test is considered positive when the second dynamic load is equal to (or within a certain percentage of) the first dynamic load condition.

[0067] (87) From the foregoing description, it should be apparent that various exemplary embodiments of the present invention may be implemented in hardware or firmware. Moreover, various exemplary embodiments may be implemented as instructions stored on a machine-readable storage medium, which may be read and executed by at least one processor to perform the operations detailed herein. A machine-readable storage medium may include any mechanism for storing information in a form readable by a machine, such as a personal or laptop computer, a server, or other computing device. In other words, a machine-readable storage medium may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, and similar storage media.

[0068] (88) It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative circuitry embodying the principles of the present invention. Similarly, it should be appreciated that any flowcharts, flow diagrams, state diagrams, pseudocode, etc. represent various processes that may be substantially represented in a machine-readable medium and, therefore, executed by such a computer or processor, whether or not a computer or processor is explicitly depicted.

[0069] (89) While various example embodiments have been described in detail above, with particular reference to certain exemplary aspects, it should be understood that the invention is capable of other embodiments and that its details are susceptible to modifications in various obvious respects. As will be readily apparent to those skilled in the art, variations and modifications can be made while remaining within the spirit and scope of the invention. Accordingly, the foregoing disclosure, description, and figures are for illustrative purposes only and in no way limit the invention, which is defined solely by the claims.

Claims

1. 1. A system for inspecting an equipment system, comprising: an inspection chamber; a system builder configured to build and apply an instrument load to the test chamber; a load creator configured to create and apply a predetermined load to the test chamber; a tester that measures the behavior of the equipment load and the specified load within the test chamber and generates a test state; A system comprising:

2. 2. The system of claim 1, wherein the system builder comprises system builder instruments and a system configuration matrix, the system configuration matrix connecting the system builder instruments to each other and connecting the system builder instruments to the test chamber.

3. 3. The system of claim 2, wherein the system builder equipment comprises at least two of a heating and cooling section, a pumping section, a storage section, a heat exchange section, and a mixing section.

4. 4. The system of claim 1, 2, or 3, wherein the test chamber comprises a chamber and test chamber equipment, the test chamber equipment presenting a test condition distribution, the test condition distribution comprising a radiation condition distribution, an air condition distribution, or a convection condition distribution.

5. 5. The system of claim 4, wherein the test chamber equipment comprises an air handler, a variable air chamber box, a radiant floor, or a radiator that applies the predetermined load.

6. 6. The system of claim 1, 2, 3, 4, or 5, wherein the inspection chamber is substantially covered by a heated water circulating shroud.

7. 7. The system of claim 1, 2, 3, 4, 5, or 6, wherein the equipment load is a dynamic load and the predetermined load is a dynamic load.

8. 8. The system of claim 4, 5, 6, or 7, wherein the test chamber equipment further comprises a hot water tank and a cold water tank, the hot water tank and the cold water tank configured to provide dynamic heating and cooling to the hydronic shroud.

9. 9. The system of claim 2, 3, 4, 5, 6, 7, or 8, wherein the system builder equipment comprises at least two of a heating and cooling section, a pumping section, a storage section, a heat exchange section, and a mixing section.

10. 10. The system of claim 2, 3, 4, 5, 6, 7, 8, or 9, wherein the system configuration matrix comprises a plurality of two-way valves, and the system configuration matrix is ​​operable to couple at least two of the system configuration devices to create the device load.

11. 11. The system of claim 2, 3, 4, 5, 6, 7, 8, 9, or 10, wherein the load shaper uses a buffer tank to create zone mass.

12. 1. A method for determining test chamber behavior comprising a test chamber, a system builder, and a weathermaker system, wherein the weathermaker system is included in a system having a processor and memory, the method comprising: configuring the system builder to create a system builder configuration; creating a first dynamic load in the test chamber using the system builder configuration; determining a second dynamic load and generating the determined second dynamic load using the processor and memory; configuring the weathermaker system to create the determined second dynamic load in the test chamber; and determining test chamber behavior using the interaction of the first dynamic load and the second dynamic load in the test chamber.

13. 13. The method of claim 12, wherein configuring the system builder includes configuring equipment associated with the system builder using a bidirectional valve matrix.

14. 14. The method of claim 12 or 13, wherein the behavior of the test chamber comprises a condition within the test chamber when the first dynamic load and the second dynamic load are simultaneously present within the test chamber for a determined amount of time.

15. 15. The method of claim 12, 13, or 14, wherein the test chamber allows for a condition distribution, such that the condition distribution comprises a radial condition distribution, an air condition distribution, or a convective condition distribution.

16. 16. The method of claim 12, 13, 14, or 15, further comprising determining when the second dynamic load balances the first dynamic load.

17. 17. The method of claim 12, 13, 14, 15, or 16, wherein determining when the second dynamic load balances the first dynamic load comprises determining when a state of the second dynamic load is equal to a state of the first dynamic load.

18. 18. The method of claim 17, wherein the first dynamic load condition is temperature.

19. 1. A non-transitory machine-readable storage medium having data and instructions configured thereon that, when executed by at least one processor, cause one or more devices to perform a method for determining test chamber behavior, the method including a test chamber, a system builder, and a weathermaker system, the weathermaker system being included in a system having a processor and a memory, the method including the steps of configuring the system builder and creating a system builder configuration; creating a first dynamic load in the test chamber using the system builder configuration; determining a second dynamic load and generating the determined second dynamic load using the processor and memory; configuring the weathermaker system to create the determined second dynamic load in the test chamber; and determining test chamber behavior using the interaction of the first dynamic load and the second dynamic load in the test chamber.

20. 20. The non-transitory machine-readable storage medium of claim 19, further comprising using machine learning to determine the second dynamic load.

Images