Configurable test platform

Abstract

Various embodiments described herein relate to test chamber devices, related methods, and non-transitory machine-readable media, including: a test chamber; a system builder configured to build a device load and apply the device load to the test chamber; a load generator configured to construct a predefined load and apply the predefined load to the test chamber; and a tester that measures the action of the device load and the predefined load within the test chamber to produce a test state.

Description

Technical Field

[0001] The present disclosure relates to testing equipment and, more particularly, but not exclusively, to a configurable test platform that allows control sequences to be easily configured and tested for a variety of equipment layouts. Background Art

[0002] Today, testing equipment for HVAC and other uses is done by testing individual pieces of equipment, consulting load tables in books, and calculating whether the equipment is sized correctly. In some cases, energy simulation software is used to determine the amount of load required. However, these results are theoretical and do not take into account the actual equipment and the actual physical loads that the equipment needs to interact with. Summary of the invention

[0003] This summary is provided to introduce some concepts in a simplified form, which are further described in the "Detailed Description" section below. This summary does not identify necessary or essential features of the claimed subject matter. The innovative solutions are defined by the claims, and if this "Summary" conflicts with the claims, the claims shall control.

[0004] Various embodiments described herein provide a system for testing a device system using a test chamber. For example, in some embodiments, the test chamber is paired with a system builder, which is configured to build a device load and apply it to the test chamber. The load generator is also configured to build a predefined load and apply it to the test chamber; and also includes a tester that measures the action of the device load and the predefined load in the test chamber to generate a test state. In some embodiments, the system builder includes a system builder device and a system configuration matrix, which connects the system builder devices to each other and connects the system builder device to the test chamber. In some embodiments, the system builder device 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, which includes a chamber and a test chamber device, and the test chamber device provides a test state distribution, which includes a radiation state distribution, an air state distribution, or a convection state distribution.

[0005] Various embodiments are described in which the test room equipment includes an air handler, a variable air plenum box, a radiant floor, or a radiator to apply a predefined load. Various embodiments are described in which the test room is substantially covered by a hydraulic hood. Various embodiments are described in which the equipment load is a dynamic load, and wherein the predefined load is a dynamic load. Various embodiments are described in which the test room equipment also includes a hot water tank and a cold water tank, and wherein the hot water tank and the cold water tank are configured to provide dynamic heating and cooling to the hydraulic hood. Various embodiments are described in which the system builder equipment includes at least two of a heating and cooling portion, a pumping portion, a storage portion, a heat exchange portion, and a mixing portion. Various embodiments additionally include a system configuration matrix including a plurality of bidirectional valves, the system configuration matrix being operably capable of coupling at least two of the system building equipment to generate the equipment load. Various embodiments are described in which the load generator uses a buffer tank to generate a zone mass.

[0006] Various embodiments described herein relate to a method for determining test room behavior, comprising a test room, a system builder, and a weather generator system, the weather generator system being included in a system comprising a processor and a memory, the method comprising: configuring the system builder to create a system builder configuration; using the system builder configuration to create a first dynamic load in the test room; determining a second dynamic load using the processor and the memory to produce a determined second dynamic load, configuring the weather generator system to create the determined second dynamic load in the test room; and using the interaction of the first dynamic load and the second dynamic load in the test room to determine the test room behavior.

[0007] Various embodiments are described in which configuring a system builder includes configuring a device associated with the system builder using a bidirectional valve matrix. Various embodiments are described in which a test chamber behavior includes a state in the test chamber when a first dynamic load and a second dynamic load are simultaneously present in the test chamber for a determined amount of time. Various embodiments are described in which the test chamber allows for a state distribution, and thus the state distribution includes a radiation state distribution, an air state distribution, or a convection state distribution. Various embodiments are described in which determining a state in the test chamber includes determining when the second dynamic load is balanced with the first dynamic load. Various embodiments are described in which determining when the second dynamic load is balanced with the first dynamic load includes determining when the state of the second dynamic load is equal to the state of the first dynamic load. Various embodiments are described in which the state of the first dynamic load is a temperature.

[0008] Various embodiments described herein relate to a non-transitory machine-readable storage medium configured with data and instructions that, when executed by at least one processor, cause one or more devices to perform a method of determining test room behavior, including a test room, a system builder, and a weather generator system, the weather generator system being included in a system including a processor and a memory, the method comprising: configuring the system builder to create a system builder configuration; using the system builder configuration to create a first dynamic load in the test room; determining a second dynamic load using the processor and the memory to produce a determined second dynamic load; configuring the weather generator system to create the determined second dynamic load in the test room; and using the interaction of the first dynamic load and the second dynamic load in the test room to determine the test room behavior. Various embodiments described herein include using additional machine learning to determine the second dynamic load. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] For a better understanding of various example embodiments, reference may be made to the accompanying drawings, in which:

[0010] Figure 1 A general example of a suitable computing environment in which the described embodiments may be implemented is shown;

[0011] Figure 2 An example of a flow chart describing a configurable testbench at a high level is shown;

[0012] Figure 3 An example of a block diagram describing a configurable test platform in more detail is shown;

[0013] Figure 4 Examples of some types of loads that may be used herein are shown;

[0014] Figure 5 An example of equipment that can be used in a test chamber to provide a test load is shown;

[0015] Figure 6a An example of a weather generator system is shown;

[0016] Figure 6b1 and 6b2 An example schematic diagram of a system builder is shown;

[0017] Figure 6c An example schematic diagram of a system builder is shown, wherein a wall is divided into sections;

[0018] Figure 6d shows an example of a configuration matrix setup that can be used in the system builder;

[0019] Figure 6eshows an example of a partial device configuration that can be used in the system builder;

[0020] Figure 6f shows an example of a bidirectional valve configuration that can be used in the system builder;

[0021] Figure 6g An example of a configuration matrix configured to provide variable master system builder configurations is shown;

[0022] Figure 6h An example of a configuration matrix configured to provide a primary-secondary system builder configuration is shown;

[0023] Figure 6i An example of a configuration matrix configured to provide a complex system builder configuration is shown;

[0024] Figure 6j An example of a configuration matrix configured to provide a complex system builder configuration is shown;

[0025] Figure 7 is an illustration of a flow chart describing an embodiment of a configurable test platform;

[0026] Figure 8 is an illustration of a flow chart describing another embodiment of a configurable test platform;

[0027] Fig. 9 shows an example of a user interface screen that can be used to enter build information;

[0028] Fig.10 An example of another embodiment of developing a control path to operate a test wall device is shown;

[0029] Fig.11 A feasible device that can be used on a test wall is shown;

[0030] Fig.12 An example of a flow chart for determining test chamber behavior is shown. DETAILED DESCRIPTION

[0031] Representative embodiments of methods, machine-readable media, and systems are disclosed below, particularly systems and methods suitable for warmth simulation. The embodiments implement one or more of the described techniques.

[0032] In the following description, many specific details are set forth to provide a comprehensive understanding of the current embodiment. However, it is obvious to those of ordinary skill in the art that it is not necessary to adopt the specific details to implement the current embodiment. In other cases, well-known materials or methods are not described in detail to avoid making the current embodiment unclear. "One embodiment", "embodiment", "one example" or "example" means that the specific features, structures or characteristics described in connection with the embodiment or example are included in at least one embodiment of the current embodiment. Therefore, the phrases "in one embodiment", "in an embodiment", "one example" or "example" appearing throughout this specification do not necessarily 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, the components of the system and the device may be integrated or separated. In addition, the operation of the system and the device disclosed herein may be performed by more, less or other components, and the method may include more, less or other steps. In addition, the steps may be performed in any suitable order.

[0033] For convenience, the present disclosure may be described using relative terms, for example, left, right, top, bottom, front, back, over, under, up, down, etc. It is to be understood that these terms are used for descriptive purposes only and are not intended to be limiting in any way.

[0034] Embodiments according to the present embodiment may be implemented as devices, methods or computer program products. Thus, the present embodiment may take the form of a complete hardware embodiment or a complete software embodiment (including firmware, resident software, microcode, etc.), or a combination of software and hardware embodiments (which may be referred to as a "system"). In addition, the present embodiment may take the form of a computer program product implemented as any tangible medium of expression in which a machine-usable program code is implemented.

[0035] Any combination of one or more non-transitory machine-usable or machine-readable media may be used. For example, the machine-readable medium may include one or more of a portable computer disk, 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 performing the operations of the current embodiment may be written in any combination of one or more programming languages.

[0036] The flowcharts and block diagrams in the flowchart diagrams illustrate the architecture, functions and operations of possible implementations of the systems, methods and computer program products according to various embodiments of the present embodiments. In this regard, each box in the flowchart or block diagram may represent a module, segment or code portion, which includes one or more executable instructions for implementing one or more specified logical functions. It should also be noted that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can be implemented by a dedicated hardware-based system or a combination of dedicated hardware and computer instructions that performs the specified function or action. These computer program instructions can also be stored in a machine-readable medium, which can instruct a computer or other programmable data processing device to operate in a specific manner so that the instructions stored in the machine-readable medium produce a manufactured article including an instruction device, which implements the function / action specified in one or more boxes of the flowchart and / or block diagram.

[0037] Although the operations of some disclosed methods are described in a particular order for ease of presentation, it is understood that this description includes rearrangement unless the specific language set forth below requires a particular order. For example, operations described in order can be rearranged or performed simultaneously. In addition, for simplicity, the accompanying drawings may not show the various ways in which the methods, devices, and systems disclosed therein can be used in combination with other methods, devices, and systems. In addition, the description sometimes uses terms such as "determine," "construct," and "identify" to describe the disclosed technology. These terms are superordinate concepts of the actual operations performed. The actual operations corresponding to these terms will vary depending on the specific implementation and are easily discernible by those of ordinary skill in the art.

[0038] As used herein, the terms "comprises," "including," "comprising," "containing," "having," "having" or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, article, or apparatus.

[0039] In addition, unless otherwise expressly stated, "or" refers to an inclusive "or" rather than an exclusive "or". For example, condition A or B is satisfied by any of the following conditions: 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), and both A and B are true (or exist). "Program" is used broadly in this article to include applications, kernels, drivers, interrupt handlers, firmware, state machines, libraries, and other code written and / or automatically generated by programmers (who are also called developers). "Optimize" means to improve, but not necessarily to perfect. For example, it may be possible to make further improvements to an already optimized program or algorithm. "Determine" means to have a good understanding of a value, but not necessarily to reach an exact value. For example, it may be possible to make further improvements to an already determined value or algorithm.

[0040] In addition, any examples or descriptions given herein should not be considered in any way as limitations, restrictions or express definitions of any one or more terms used therein. On the contrary, these examples or descriptions should be considered as being described for a specific embodiment and are merely illustrative. It will be understood by those of ordinary skill in the art that any one or more terms used with these examples or descriptions will cover other embodiments that may or may not be given together with these examples or descriptions or elsewhere in the specification, and all such embodiments are intended to be included within the scope of the one or more terms. Languages ​​representing such non-limiting examples and descriptions include, but are not limited to: "for example," "such as," "as," and "in one embodiment."

[0041] The technical features of the embodiments described herein will be readily apparent to those of ordinary skill in the art, and will also be readily apparent to many careful readers in a variety of ways. Some embodiments involve technical activities rooted in computing technology, such as determining a specific control sequence for a particular device to process a given load in the most energy-efficient manner. The disclosures and embodiments presented herein provide a rapid method to provide an extremely wide range of physical systems with different features and topologies. Such disclosures also provide for conducting a variety of physical experiments, such as sensor calibration timing, device specification verification, measurement and verification methods. From the description provided, other advantages of the technical features based on the present teachings will also be readily apparent to the technician.

[0042] I. Overview

[0043] Systems and methods for creating and using a configurable test platform are disclosed herein. If there is a test platform that can generate realistic loads and use real devices that must work against these loads, it would be very helpful to determine actual energy performance and behavior in real world environments.

[0044] Buildings and the spaces within them are all unique and have their own characteristics that cannot be fully captured by a bare description of the building’s features, no matter how detailed. Building states change slowly and often depend on external factors such as weather, the number of people in the building over the course of a day, etc. Therefore, determining whether a state-changing system within a building is operating properly can be a long and tedious process. Since everything within a building is thermodynamically connected, it can be very difficult to tell if a building is operating as designed, for example, if a thermostat is placed in a zone next to the zone it should be in, it will heat not only that wrong zone, but also the correct zone, making errors very difficult to detect. When creating systems for new buildings or when adding new equipment to existing buildings, it would be beneficial to be able to actually test such systems under real conditions (not just in simulation) before installation to avoid making costly mistakes. It would also be beneficial to be able to test proposed equipment control sequences in a real test environment where the control sequences are run on the equipment and input into a space with known state loads to work against them. This can be used to ensure that equipment programmed with a control sequence can actually handle the expected load over a period of time, including the weather that may be encountered.

[0045] An illustrative example includes a test wall and a configuration matrix connected to the test chamber. The test wall can contain a set of devices, such as heating and cooling sources, pumps, heat exchangers, valves, tanks, etc. The configuration matrix allows the devices to be connected in such a way that almost any type of state system can be built in a few minutes by using the configuration matrix. This provides an extremely high degree of flexibility for testing a wide variety of system topologies and configurations. The test chamber is connected to the configured devices and load generators. The devices transmit loads into the test chamber. For example, the devices can dynamically transmit states (such as heat) into the test chamber.

[0046] In an ideal case, both the device and the load generator pump states into the test chamber simultaneously. In one illustrative example, this can be thought of as modeling a building HVAC subject to weather. The measurements in the test chamber then give the tester an idea of ​​how well the implemented device can withstand the conditions, such as weather, in the test chamber (represented by the conditions produced by the weather generator). In another illustrative embodiment, the conditions are inserted into the test chamber by a weather generator representing the thermodynamic properties of the building. The configured device then transmits the conditions into the test chamber to, for example, observe whether it can withstand the building conditions.

[0047] II. Example Computing Environment

[0048] Figure 1A general example of a suitable computing environment 100 is shown in which some 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 may be implemented in various general-purpose or special-purpose computing environments.

[0049] refer to Figure 1 , the computing environment 100 may include a processor 130. The processor 130 may include at least one central processing unit 110 and a memory 120. The central processing unit 110 executes machine executable instructions and may be a real or virtual processor. It may also include a vector processor 112. In a multi-processing system, multiple processing units execute machine executable instructions to increase processing power, and thus the vector processor 112, GPU 115, and CPU 110 may run simultaneously. However, it should be apparent that in various embodiments, the elements belonging to the processor 130 may not be physically co-existing. For example, the CPU 110 and the GPU 115 may be connected to boards that are physically separate from each other.

[0050] 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 for implementing the described method and system, wherein inaccurate polygons are aligned and modified when necessary.

[0051] The computing environment may have additional functionality. For example, the computing environment 100 includes a storage device 140, one or more input devices 150, one or more output devices 155, one or more network connections (e.g., wired, wireless network connections, etc.) 160, and other communication connections 170. An interconnection mechanism (not shown) such as a bus, controller, or network interconnects the components of the computing environment 100. Typically, operating system software (not shown) provides an operating environment for other software executed in the computing environment 100 and coordinates the activities of the components of the computing environment 100.

[0052] Storage device 140 may be removable or non-removable and include disks, tapes or cartridges, CD-ROMs, CD-RWs, DVDs, flash drives, or any other medium that can be used to store information and accessed within computing environment 100. Storage device 140 stores instructions for the software (e.g., software 185) to implement systems and methods for configuring a test platform.

[0053] One or more input devices 150 may be devices that allow a user or another device to communicate with the computing environment 100, such as a touch input device (e.g., a keyboard, camera, microphone, mouse, pen, or trackball), a digital camera, a lidar device, a scanning device (e.g., a digital camera with a scanner), a touch screen, a joystick controller, a wii remote, or another device that provides input to the computing environment 100. For audio, one or more input devices 150 may be a sound card or similar device (which accepts audio input in analog or digital form), or a CD-ROM reader that provides audio samples to the computing environment. One or more output devices 155 may be a display, a hard copy generating output device (e.g., a printer or plotter), a text-to-speech sound reader, a speaker, a CD burner, or another device that provides output from the computing environment 100.

[0054] One or more communication connections 170 allow communication with another computing entity through a communication medium. The communication medium transmits information, such as machine executable instructions, compressed graphics information, or other data in a modulated data signal. The communication connection 170 may include an input device 150, an output device 155, and an input / output device that allows the client device to communicate with another device through a network 160. The communication device may include one or more wireless transceivers for performing wireless communications and / or one or more communication ports for performing wired communications. These connections may include a network connection, which may be a wired or wireless network, such as the Internet, an intranet, a LAN, a WAN, a cellular network, or other types of networks. It is understood that the network 160 may be a combination of multiple different types of wired or wireless networks. The network 160 may be a distributed network in which multiple computers (which may be building controllers) operate in series. The communication connection 170 may be a portable communication device, such as a wireless handheld device, a personal electronic device, etc.

[0055] Machine-readable media is any available non-transitory tangible media that can be accessed in a computing environment. By way of example, but not limitation, with respect to computing environment 100, non-transitory machine-readable media may include memory 120, storage device 140, communication media, and any combination of the foregoing. To aid understanding, Figure 1A non-transitory machine-readable storage medium 165 and related contents are shown; it is understood that the non-transitory machine-readable storage medium 165 may correspond to memory 120, storage device 140, or a similar device (not shown) accessible via communication connection 170. As used herein, the term "non-transitory" should be understood to exclude temporary signals, but include all forms of memory and storage devices, including both volatile memory and non-volatile memory. The 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 communication connection 170. The computing environment 100 can be an electrical controller directly connected to various resources (e.g., HVAC resources), and it has a CPU 110, a GPU 115, a memory 120, an input device 150, a communication connection 170, and / or other features shown in the computing environment 100. The computing environment 100 can be a series of distributed computers. These distributed computers can include a series of connected electrical controllers.

[0056] In addition, data generated by any disclosed method may be created, updated, or stored on a tangible machine-readable medium (e.g., a tangible machine-readable medium such as one or more CDs, volatile memory components (e.g., DRAM or SRAM), or non-volatile memory components (e.g., a hard drive)) using a variety of different data structures or formats. Such data may be created or updated at a local computer or over a network (e.g., via a server computer), or stored and accessed in a cloud computing environment.

[0057] Although computing environment 100 is illustrated as including one of each of the components, in various embodiments, the individual components may be repeated. For example, CPU 110 may include multiple microprocessors that are configured to independently execute the methods described herein, or are configured to execute the steps or subroutines of the methods described herein, so that multiple processors collaborate to implement the functions described herein. In addition, when computing environment 100 is implemented in a cloud computing system or a group computing system, the individual hardware components may belong to separate physical systems. For example, processor 130 may include a first processor in a first cloud server and a second processor in a second cloud server.

[0058] III. Disclosure of Example Configurable Test Bench

[0059] Figure 2An example of a flow chart is shown at 200 in the configurable test platform, which describes the configurable test platform at a high level. The system 200 shown shows various functional components and some interactions between them. The configurable test platform 200 includes a first load determiner 203. The load determiner 203 can be almost any system that can determine the state load of a controlled space. The "controlled space" should be defined broadly. It can refer to a single 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 part of a building, such as a floor, an area, a room, multiple rooms, multiple areas in a single room, multiple areas in multiple rooms, multiple areas across multiple buildings, etc. Many different states 210 can be used in the configurable test platform 200, such as humidity, atmospheric pressure, sound pressure, occupancy, indoor air quality, carbon dioxide concentration, light intensity, or other states that can be measured or controlled. The first load determiner 203 determines the amount of state required to keep the controlled space in a desired state over time. Buildings - controlled spaces - states are dynamic in their nature. For example, using heat as an exemplary state, buildings have many ways of gaining and losing heat over time. Some of these ways are solar heat gain (adding heat by absorbing solar energy), heat generated by people in the building, and heat generated by equipment such as lighting. The building itself also loses heat, for example due to ventilation, windows, and leaks in the building itself. Weather also has an effect on building temperature. Other states can also be considered. For example, states such as humidity, barometric pressure, sound pressure, occupancy, indoor air quality, carbon dioxide concentration, light intensity, or other states that can be measured or controlled can all be used in a configurable test platform.

[0060] The load is the amount of state that needs to be added or removed from the space to keep the state within the required range. If the state in question is temperature, the load is the amount of heat (e.g., state) that needs to be added or removed by the HVAC system to achieve the desired temperature over time, taking into account the sources that will act on the space, such as those mentioned above. If the state is humidity, the load is the amount of humidity that needs to be provided or removed by the humidity control equipment to achieve the desired humidity over time. As mentioned earlier, these states are dynamic, and so are the loads. These loads are typically measured in time series; that is, they describe how the expected load is expected to change over time.

[0061] The first load determiner 203 determines how many states to create to meet the system requirements. This will refer to Fig.10and corresponding content. The system builder 205 creates the state 210 determined by the load determiner 203, and then transmits the created state 210 to the test room 215. The second load determiner 235 determines how many states to create to meet the requirements of the test room. The second state quantity can be conceptually considered as a state quantity designed to balance the state generated by the system builder. In some embodiments, the first load determiner 203 and the second load determiner 235 are the same load determiner. The weather generator 225 creates the state previously determined by the second load determiner 235. It also transmits the state to the test room. The sensor 230 measures the state in the test room. In some embodiments, indoor air quality can be state 210, where the test room 215 includes a filtering device and the weather generator 225 adds particulate matter from wildfires, pollution, etc.; the weather generator can add particles consistent with diseases, etc. In some embodiments, the state is sound; the test room has a sound-absorbing device, white noise, different sources of different types of sounds, etc. In some embodiments, multiple states are tested at once.

[0062] Figure 3 An example of a block diagram describing a configurable test platform in more detail is shown at 300 in FIG. A first load determiner 303 may use a digital twin model to determine a load profile. The digital twin model may include building a replica of the controlled space in question. This may require describing the components of the space and their thermal properties. For example, a wall may include bricks, insulation, drywall, etc. These parts may be encoded into a simulation, such as a physics-based simulation. In such a simulation, a wall may be modeled as one or more nodes that describe the properties of that building layer—a brick node, then an insulation load, then a drywall node, and so on throughout the building. The state values ​​of the external nodes are modified by the weather nodes, and the state modifications flow throughout the building. At the internal nodes representing the interior of the room, other functions may be applied, such as functions representing lighting and people (warmth) within the area. The state information continues to propagate until it reaches another outer layer, where the individual node parameter values ​​represent the state of the room at time T. n In some embodiments, each exterior surface has its own time temperature profile. In some embodiments, a building is broken down into smaller subsystems (or zones) so that instead of propagating the temperature through the entire structure, only a portion of the structure is affected by a given input.

[0063] In some embodiments, the digital twin model is built on a controller associated with the controlled building. The controller can be a first load determiner 303, a second load determiner 335, two load determiners, etc. In some cases, the controller is embedded in the controlled building and used to automate the building. The controller may include a simulation engine, which itself includes a model of the controlled system in which the controller is located, or a model of the device in the controlled system in which the controller is located, or both. This model may be called a "physical model". This physical model itself may be trained. Training may include past regression and cost functions. Past regression is the instance and result of these models running in the past. The controlled system has at least one sensor, whose value can be used to calibrate one or more physical models by checking the proximity of the model value at the sensor location to the equivalent value of the sensor value in the simulation in the physical model. The cost function can be used to determine the distance between the equivalent value of the sensor value and the simulated sensor value. This information can then be used to improve the physical model. The system loop controlled by the controller can be implemented without using a cloud and / or an external network (e.g., the so-called "Internet"). The controller may control and / or operate a local area network (LAN) over which it talks to sensors and other resources. The controller may be hardwired into the sensors and other resources, or there may be a combined system where some resources are hardwired and others are connected to the LAN. The system builder 305 is configured to build the device state load 330 and apply it to the test chamber.

[0064] The device load profile measures the state over time and can therefore be dynamic, as described above. To create it, the system builder 305 also includes devices 340 and a configuration matrix 310 that allows different configurations of the devices 340. The system builder Figure 6b1 , 6b2 , 6c-6h. Weather generator 225 - which also moves state into the test room, can include an "internal" load generator located within the test room, and / or an "external" load generator 325 located outside the test room and directing its state 330 to the test room. The weather generator is in Figure 6a The state load 330 from the system builder 305 that moves into the test room 315 can be balanced against the state loads generated by the internal load generators 320 and the external load generators 325. In some embodiments, the test can measure how the state from the system builder holds up against the state generated by the load generators (320, 325) in the test room. In some embodiments, the test can measure how the state from the system builder holds up against the state generated by the load generators (320, 325) in the test room, additional loads, or synthetic areas.

[0065] As an illustration of an operational example, a test chamber load generator may simulate an area in a snowstorm, with a temperature outside (simulated) between 10 degrees above zero and 25 degrees above zero over an eight hour period. The system builder will determine how much heat can be pumped into the test chamber over eight hours to keep the temperature at the desired heat. The desired heat may change. The desired heat will be converted into a control sequence to run the device. The device 340 will then run for eight hours, pumping the conditions into the test chamber using the control sequence. For example, when the test chamber 315 is equipped with a hot water radiator (not shown), the device 340 will control the delivery of hot water to the radiator to raise the temperature of the test chamber to the current desired heat level, resisting the influence of the load generators 320, 325, which would normally lower the temperature of the test chamber 315 when simulating a snowstorm. The matching of the temperature to the desired temperature (test chamber behavior) over the entire length of the test indicates how well the control sequence works.

[0066] Figure 4400, various example types of loads that can be used are shown. The loads of the weather generator 225 can be considered to be divided into three types: test room loads 410, synthetic zones 415, and tank as zone loads 420. The test room load 410 can be applied to the test room (in an example embodiment, the test room can be 10'x 10x 12', but it can be smaller or larger depending on usage requirements, system requirements, space requirements, and / or pricing). Heating, cooling and other loads can be applied to the room through a hydraulic cover surrounding the room (an example of which will be described in more detail below) and one or more indoor transmitters for additional loads. The synthetic zone 415 can be created using a heat exchanger that uses hot and cold water to generate a specified dynamic load. In some embodiments, a building includes at least one controlled space. The controlled space can be an entire building, a portion of a building, a room, a portion of a room, an outdoor area (such as a garden), etc. This may be a space that currently exists, or it may be a space that exists only as a design. Buildings are typically divided into multiple zones. These zones typically represent different areas with separate sensors, such as rooms or other such controlled spaces, but may also represent different areas within a large space (such as a warehouse). The load can be controlled by adjusting the flow rate through an energy valve control valve. Within the zone, energy is consumed and energy is applied, both of which change the state of the zone. Therefore, a new device that consumes energy and can apply energy to it can be used to model the synthetic zone 415. The synthetic load can dump the state into the state exchanger instead of saving energy. In an actual hydraulically controlled zone, hot water or cold water is pumped through the space to provide heating and cooling. In the synthetic zone 415, using the same process, for example, hot water can be generated to provide heat for the synthetic zone, or cold water can be generated to provide cooling, but the space does not exist, but is simulated by a heat exchanger, and basically no energy is released anywhere. The energy load is dumped.

[0067] The tank area load 420 can be a buffer tank of water, fluid, or other substances that can simulate the quality of the area. The load can then be applied to the tank to simulate the state of these "real" areas (whether built or designed areas). For example, in a 25-gallon water tank, the mass can be considered to be equivalent to a room of a certain size. Larger water tanks can allow larger rooms to be represented, etc. One or more air-water heat pumps can be used to apply dynamic loads. The behavior of the tank area load 420 is similar to the synthetic area 415, except that it is not a dump load energy, but the load energy is saved by the tank, which can be stored for later use. The synthetic area 415 provides the ability to have areas of various sizes, which can be loaded (through the weather generator). In some embodiments, the controller and the test wall can treat these synthetic areas as actual spaces. The weather generator system 225 can monitor the test room load 415, the synthetic area 415, the tank area load 420, etc. through one or more temperature sensors and one or more flow sensors.

[0068] Figure 5An example of equipment that can be used in the test room to provide the test load 220 is shown at 500, such as a weather generator 225. One or more air handlers 505 may be included. It may be a variable speed AHU with a heating and test unit, or a different type of air handler. One or more variable air volume (VAV) boxes 510 may be included. These VAV boxes (which may have reheating) may be used to maintain a more precise temperature (or other state) in the room, which can help create and maintain dynamic loads. Additional loads 515 may also be included to drive loads beyond what the remaining equipment can provide. Radiators 520 (which may be water heating radiators) may be used to provide radiant heat. Radiant floors 525 may be used to provide more heat. A hydraulic hood 530 may be provided. The hood 530 may substantially enclose the test room and may drive heating and cooling loads into the space. In some embodiments, the hydraulic hood 530 may have a hydraulic circuit of plastic pipes that transfer heat. Aluminum transfer plates may be inserted at locations within the hood to diffuse the heat provided by the water flowing through the pipes. The hydraulic hood 530 may be covered by an insulating material 535. The insulation material can be a rigid insulation material. The insulation material can be used to ensure that the temperature provided by the liquid is driven into the test chamber, not lost to external diffusion, and can also provide rigidity to the cover. Different loads can be provided on different sides of the cover to allow testing of different types of building walls (e.g., interior, exterior, etc.). In some embodiments, the hydraulic cover can cover all six sides. In some embodiments, a specific side can have a separate temperature source. For example, convection heat 525 can also be provided. This convection heat can be provided on the floor side or on different sides. In some embodiments, convection heat can be provided on multiple sides. In some embodiments, the hydraulic cover 530 covers less than six sides, covers all sides, but only covers a portion of one or more sides, and the like.

[0069] Figure 6aAn example 600a of a weather generator system 225 is shown. The system can utilize an air-to-water heat pump 605a, which can be used as a ground heat source. The system can also utilize a ground generator circulation pump 610a, a buffer tank 615a for the ground generator (or a buffer tank for a different reason, such as for use as a tank farm load 420), one or more test chamber hood connections / manifolds 620a that provide heated or cooled water to the hydraulic hood 530, one or more hydraulic hood control valves 635a, one or more tank farm loads 625a, and one or more synthetic areas 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 for providing hot or cold water to one or more connections / manifolds 620a or directly to the hydraulic hood. These hot water tanks and cold water tanks can be configured to provide dynamic loads to the hydraulic hood 530, and thereby to the test chamber 315. The control valves (e.g., 635a, 640a) can be positioned so that different parts of the system builder 205 can be opened and closed by a user building configuration for the system builder, by an automation system, by a controller, etc. The controller 650a can be used to control flow into downstream devices, etc. Opening and closing valves and changing controller behavior can allow many different scenarios to be created. The controller behavior can be controlled by some combination of control sequence determination software 720 and controller 740. The control sequence determination software-controller combination can use machine learning techniques to determine the behavior of the controller. The controller itself can use machine learning techniques to determine the near-optimal behavior for a given scenario.

[0070] Figure 6b1 At 600b1 and Figure 6b2 At 600b2, a system builder 205 that can be used in the configurable test platform 200 is shown. The system builder 205 is Figure 6c , Figure 6d and Figure 6g-6j , although other system builders are contemplated. The diagram is drawn using common mechanical engineering symbols and combinations. For example, 605b discloses a gate valve. The system is intended to enable thousands of state test system configurations for both the virtual building and other loads provided within the weather generator 225, which can allow the configuration to be tested for the conditions provided by the test chamber 215. Different state test configurations are created by opening and closing valves.

[0071] Figure 6cAt 600c, at least some portions of the illustrated system builder are shown to be divided into multiple parts. Other system builders may have other configurations. In some system builders, certain types of functional devices are physically close to each other. In the system 600c shown, heating and cooling sources 605c are placed together, pumping elements 610c are placed together, routing elements 615c are placed together, storage elements 620c are placed together, and heat exchange elements 625c, pumping elements 630c, mixing elements 635c, and load elements 640c are each placed together. The test configuration may be able to use one or more elements from each part as needed.

[0072] Figure 6d and Figure 6e An example of a system builder built along two sides of a single wall is shown, where the majority of the two-way valves are located on a single side 600d. In this example, the two-way valves are arranged in a matrix tower, reference Figure 6f This is shown in more detail at 600f. Most of the equipment used to create the state is built on the other side 600e of the wall shown at 600d. Many other embodiments are contemplated, such as all equipment and valves built on a single wall, the system builder built on multiple walls, some parts of the system builder built as independent equipment, etc.

[0073] Figure 6f At 600f, potential valve configurations for the system builder 205 are shown. In this illustrative embodiment, two-way valves are built into a tower containing 28 two-way valves. Other sized towers and other non-tower configurations are also contemplated. In this illustrative embodiment, opening and closing these two-way valves configures different possible system builder configurations.

[0074] Figure 6g A method of using an example of the system builder 205 to create a variable primary HVAC system is shown at 600g, which can then be tested using the test chamber 215. Figure 6h A method of creating a primary / secondary system using an example of the system builder 205 is shown at 600h. Figure 6i At 600i and Figure 6j At 600j a method of recreating a complex system integrating components and subsystems including multiple heating and cooling sources, multiple storage options, and different load sources is shown.

[0075] Figure 7700 is a flow chart describing an embodiment of a configurable test platform. The test platform has two tracks; one is a weather track, which determines how much external load (load curve) the weather will produce on the space; and the other is a test track, which determines the amount of heat heating / cooling necessary to keep the space in the desired state for a period of time given the weather. Once this is known, the weather track uses the weather generator 225 to generate the required amount of state (load) to act on the test room. The test track uses the determined load to determine how to run the equipment in the building under test (the test wall equipment 750 is set to simulate many equipment settings). It then runs the equipment on the test wall 750 with the load specifications to see how well the test wall equipment handles the weather generator weather load. This produces a test. The weather generator performs the test by physically heating and cooling various areas, rooms, liquid tank modeling areas, etc., while the test track controls the actual equipment to handle the load generated by the weather generator.

[0076] For the weather track, weather data is acquired at operation 705. The weather data may be in the form of a time / state curve, such as a time / temperature curve, a time / humidity curve, etc. The state data may be in the form of historical weather patterns, may be collected data, may be a weather forecast, etc. "Weather data" may be any kind of state data; it is not necessarily literal weather data. In operation 710, building data is collected. Once the building data is collected, it is used to determine the state flow of the entire building. In some embodiments, the building data may be defined by predefined CAD drawings, may be defined by scanning the building using a 3-D floor plan capture system, may be constructed using an interface that includes drawable predefined but modifiable building materials, combinations of the above, and the like.

[0077] These building data and weather data are then provided to a program 715 which finds a load curve 725 based on the building structure and weather loads. One such program is ENERGYPLUS TM Building Energy Simulator, a program developed and operated by the U.S. Department of Energy. A load curve is the amount of energy applied to a zone (or other defined location) to achieve a specific state. A load curve can be in Kbtu / hr (1000 British Thermal Units per hour) or a different unit. These load curves are then provided to the weather generator 735, which then uses the load curves to generate "desired weather" using the load generator. (See, e.g., Figure 4 . ) The heat units generated by the weather generator (if temperature is the state) are then applied to the test configuration 755. This includes the test chamber 500, the hydro shield 530, the synthetic area 415, the tank farm load 420, any additional loads, or any combination thereof.

[0078] For the test track, in the example environment, building data is collected at operation 710. In some embodiments, the building data may be defined by predefined CAD drawings, may be defined by scanning the building using a 3-D floor plan capture system, and so on.

[0079] A 3-D scanning program can be used to determine the dimensions of one or more spaces; a previously developed blueprint can be used, a point-and-click program can be used to enter spatial statistics, and so on. The building data can then be converted into a digital twin. The digital twin can be converted into a machine learning model that uses a deep learning neuron model to accurately determine the thermal properties of the modeled building. One way to achieve this is to use a neuron model system. The neuron model system can include neurons representing the various material layers of the building, and these neurons have various values ​​of these material layers, such as their impedance and capacitance. When the digital representation of the building is input into the automation system, the components of the building with different thermodynamic properties are generally defined. These (for one embodiment) can be decomposed into buildings, floors, areas, surfaces, layers, and materials in a way that reduces complexity. Each layer is composed of materials, each surface is composed of layers, and so on. These neurons can be formed into parallel and branchless neural network strings that propagate heat (or other state values) through them. Neurons can be heterogeneous because the activation function of a neuron can represent the way heat propagates through it. In such a neural network, each neuron used to represent a material with different thermal properties (or other states) can have a different activation function. That is, the activation function performs a unique function for representing the flow of states through the neural network, rather than introducing nonlinearity into the neural network.

[0080] Which specific components of a building are used depends in part on the model being implemented. For example, some models may be at a very high level and therefore may have structural elements consisting of floors. Other models may be at a very low level and therefore may use structural elements at a material level, such as type of subfloor, type of sub-material, type of floor, etc. Other options are also possible.

[0081] Some structures include multiple areas (such as rooms or specific areas monitored by sensors). Each individual area can be modeled by its own neural model. The neural model can be a single neuron or multiple neurons connected in some form. A collection of neural models can constitute a thermodynamic model of the structure. In such a multi-area model, when the areas share a surface, such as a wall, floor or ceiling (in a building embodiment), the external neurons of one neural model may be used as internal neurons of the next neural model. Some areas may overlap with other areas, while some areas do not overlap. The entire structure may be covered by the areas, or there may be no clear areas in certain locations within the structure. The controlled space can be defined as multiple subsystems. Any of these partial controlled spaces can be used as a subsystem.

[0082] These areas can be modeled as a neuron model system. The neuron model system includes neurons representing the various material layers of the building and various values, such as their impedance and capacitance. These neurons form parallel and branchless neural network strings that propagate heat (or other state values) through them. When the digital representation of the building is input into the automation system, the components of the building with different thermodynamic properties are usually defined. These (for one embodiment) can be decomposed into buildings, floors, areas, surfaces, layers and materials in a way that reduces complexity. Each layer is composed of materials, each surface is composed of layers, and so on.

[0083] At operation 720, in some embodiments, the control path creator system inputs building data 710 and weather data 705, and then outputs a control path 730. An example of such a system is described in U.S. Patent Application No. 17 / 228,119 filed on April 12, 2021, the entire disclosure of which is hereby incorporated by reference herein for all purposes. Using this method can save 95% of programming or 60% of the overall workload and save 40% of time. The method may also include a guided graphical process (which may require the use of a touch screen, a browser in a laptop, or other methods). The method may include a 3D LiDAR scanning application integrated into the process to determine the building data, and there may be a library of equipment and systems that can be used to quickly build an accurate model of the equipment in the building. In addition, building floor plans, equipment, sensor locations, etc. can all be created by 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 schematic diagram of the equipment can be drawn using the WISYWIG interface. A program (e.g., Control Path Creator or another program) can then generate the control system design, determining how to connect the devices to the controller (automatic point mapping), etc.

[0084] At run time, the weather 705 or other state data can be fed into the control path creator program 720. The program can use the information about the building and the given state data 705 to generate a control path 730 that provides device settings to control the state of the modeled building over time. At 740, the control path is provided to the controller, which then uses the control path to operate the test wall device 750. In some embodiments, the test wall device 750 is operated simultaneously with the weather generator. Among other things, this tests the control path provided to the device to see, for example, whether it can handle the weather generator load and keep the test room, synthesis area and / or other test loads in their desired state.

[0085] Figure 8 800 is an illustration of a flow chart describing another embodiment of a configurable test platform. Weather data 805 is interpreted or converted into a temperature profile 825 or another type of state profile. A weather generator 835 takes the temperature profile as input and uses that input to output sufficient states (in the form of controlling the test equipment 340) to model the weather for the test chamber 755. The weather generator may use a hydraulic hood (and other parameters such as reference Figure 5 other devices shown) provide a physical load to the test chamber 855 that can be used to test control sequences that are generated as output of the control path creator-controller process.

[0086] Fig. 9 An example of a user interface screen that can be used to enter building information is shown 900. Other screens can be used to draw a building, determine the properties of building materials used, and so on. Fig. 9 The screen shown may be used to input locations for sensor data. Other screens may allow input of equipment, such as HVAC equipment and other equipment that may be used to control the state of the building.

[0087] Fig.10 At 1000, an example of another embodiment for developing a control path to operate the test wall device is shown (e.g., Figure 7 720-740 in FIG. Fig.10Each of the steps in can be performed by a control path creator, a load profile generator, or both, or neither. System requirements for the controlled space can be determined. To this end, in some embodiments, a digital twin of a building can be developed, as described previously. This digital twin representation of a building can include a digital twin representation of equipment that will be used or is being used to operate the associated space. The digital twin representation can also include a digital twin representation of the controlled space itself, as described previously. One or more controllers with one or more processors can be used to perform the required calculations. One or more controllers can be edge computers that work together and do not use an external Internet connection. Instead, when there are multiple controllers, they can run using a local network. A previously trained machine learning model (which uses a digital twin model of the space to be tested) can be used and can be run on the controller. The machine learning model can run on multiple controllers that are networked together.

[0088] One or more temperature / time curves 1005 may be collected that model the weather that the controlled space has experienced or will experience. These collected temperatures can be used as input to the machine learning building model 1015 program. There may also be one or more internal temperature curves 1010 that the space itself or one or more areas within the implementation space are expected to meet. For example, the temperature within the implementation space may ideally be 65 degrees from 8 pm to 6 am, and then change to 72 degrees from 6 am to 8 pm. The machine learning model can then output a load time / state curve 1020 that gives the amount of state injected into each area over time to achieve the desired internal temperature given the external temperature and the characteristics of the building itself. Using the time / state curve and knowledge about the equipment within the building, another trained machine learning model 1025 can determine the optimal control sequence 1030 to achieve the desired internal temperature given the external temperature. The control sequence can then be run on the test wall 1035 using the test wall device 750. The output of the test wall device is then used to test the program 755. The test program may use the weather generator 225 to generate conditions to counter the generated test wall equipment conditions. The degree to which the loads are balanced, the degree to which the loads are unbalanced, or other results may determine the test results. The weather generator may use the test room load 410, the synthetic area 415, the tank area load 420, additional loads (e.g., 515), or any combination thereof.

[0089] Fig.11Possible equipment 1100 that may be used on a test wall is shown. The equipment may include some combination of heating and cooling equipment 1105, pumping equipment 1110, routing equipment 1115, storage equipment 1120, heat exchange equipment 1125, mixing equipment 1130, or loads 1135.

[0090] Fig.12 An example of a flow chart describing a method for determining test chamber behavior is shown at 1200. At step 1205, a system builder is configured. In some embodiments, configuring the system builder includes determining a control path of a system builder device, such as reference Figure 7 710, 720, 730, 740 and 750 and Fig.10 At step 1210, a first dynamic load is generated. In some embodiments, the dynamic load is created by using the control path configured at 1205 to operate the device 340 controlled by the configuration matrix 310. At 1215, a second dynamic load is created. In some embodiments, the second dynamic load may be as follows: Figure 7 In other embodiments, the second dynamic load may be created as shown in 705, 715, 725 and corresponding contents. Figure 8 805 and 825 and corresponding contents in . The second dynamic load can be determined by a system different from the system used to determine the first dynamic load determiner. The second dynamic load can be in the form of a temperature curve (temperature / time) that will simulate weather, as described with reference to weather data 705, 805. This can also be described with reference to test room load 410, synthetic area 415 and tank area load 420. At step 1220, the first dynamic load and the second dynamic load interact in the test room. As Figure 2 and Figure 3 As can be seen in FIG. 12 , the state 330 from the system builder (the first dynamic load) and the state from the weather generator 225 (e.g., the state from the internal load generator 320 and / or the state from the external load generator 325) meet in the test chamber 315. The states interact with each other, thereby changing the state within the test chamber. At step 1225, the results are collected. In some embodiments, when the measured state is the temperature, the result will be the temperature. The temperature in the test chamber can be measured. If the temperature is the expected temperature, or within a certain percentage, the test result can be positive. In some embodiments, determining the result includes balancing the second dynamic load with the first dynamic load. In some embodiments, the test result is positive when the second dynamic load is equal to the state of the first dynamic load (or within a certain percentage).

[0091] It should be apparent from the above description that various example embodiments of the present invention can be implemented in hardware or firmware. In addition, various example embodiments can be implemented as instructions stored on a machine-readable storage medium, which can be read and executed by at least one processor to perform each operation described in detail herein. The machine-readable storage medium may include any mechanism for storing information in a machine-readable form, such as a personal or laptop computer, a server or other computing device. Therefore, the machine-readable storage medium may include a read-only memory (ROM), a random access memory (RAM), a disk storage medium, an optical storage medium, a flash memory device, and similar storage media.

[0092] Those skilled in the art will appreciate that any block diagram herein represents a conceptual view of an illustrative circuit for embodying the principles of the present invention. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudocodes, etc. represent various processes that can be substantially represented in a machine-readable medium and executed by a computer or processor, whether or not such a computer or processor is explicitly displayed.

[0093] Although various exemplary embodiments have been described in detail, particularly with reference to certain exemplary aspects thereof, it will be appreciated that the invention is capable of other embodiments and that its details are capable of modification in various obvious respects. It will be readily appreciated by those skilled in the art that changes and modifications may be made while remaining within the spirit and scope of the invention. Therefore, the foregoing disclosure, description and drawings are for illustrative purposes only and do not in any way limit the invention, which is limited only by the claims.

Claims

1. A system for testing an equipment system, comprising: Testing room; a system builder configured to build a device load and apply the device load to the test chamber; a load generator configured to construct a predefined load and apply the predefined load to the test chamber; as well as A tester measures the motion of the device load and the predefined load within the test chamber to generate a test state.

2. The system according to claim 1, wherein: The system builder includes system builder devices and a system configuration matrix that connects the system builder devices to each other and to the test chamber.

3. The system of claim 2, wherein the system builder device 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. The system of claim 1, 2 or 3, wherein the test chamber comprises a chamber and a test chamber device, and wherein the test chamber device provides a test state distribution, the test state distribution comprising a radiation state distribution, an air state distribution, or a convection state distribution.

5. The system according to claim 4, wherein: The test room equipment includes an air handler, a variable air chamber box, a radiant floor, or a radiator to apply the predefined load.

6. The system of claim 1, 2, 3, 4 or 5, wherein the test chamber is substantially covered by a hydraulic shield.

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

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

9. The system of claim 2, 3, 4, 5, 6, 7 or 8, wherein the system builder device 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. The system of claim 2, 3, 4, 5, 6, 7, 8 or 9, wherein the system configuration matrix comprises a plurality of bi-directional valves, the system configuration matrix being capable of operatively coupling at least two system building devices to generate the device load.

11. The system of claim 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10, wherein the load generator uses a buffer tank to create regional mass.

12. A method of determining test chamber behavior, comprising a test chamber, a system builder, and a weather generator system, the weather generator system being included in a system comprising a processor and a 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 using the processor and the memory to produce a determined second dynamic load; configuring the weather generator system to create the determined second dynamic load in the test chamber; as well as The test chamber behavior is determined using an interaction of the first dynamic load and the second dynamic load in the test chamber.

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

14. The method according to claim 12 or 13, wherein: The test chamber behavior includes states in the test chamber when the first dynamic load and the second dynamic load are simultaneously located in the test chamber for a determined period of time.

15. The method of claim 12, 13 or 14, wherein the test chamber allows for a state distribution, and whereby the state distribution comprises a radiation state distribution, an air state distribution, or a convection state distribution.

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

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

19. A non-transitory machine-readable storage medium configured with data and instructions that, when executed by at least one processor, cause one or more devices to perform a method for determining test chamber behavior, comprising a test chamber, a system builder, and a weather generator system, the weather generator system being included in a system including a processor and a 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 using the processor and the memory to produce a determined second dynamic load; configuring the weather generator system to create the determined second dynamic load in the test chamber; as well as The test chamber behavior is determined using an interaction of the first dynamic load and the second dynamic load in the test chamber.

20. The non-transitory machine-readable storage medium of claim 19, comprising: The second dynamic load is determined using machine learning.

Images