January 2022
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Quantum Part 3: The Tools of Autonomy
How PassiveLogic’s Quantum Creator and Autonomy Studio software works



Troy Harvey

Troy Harvey,
CEO
PassiveLogic

Joseph Riddle - Marketing
joseph@passivelogic.com
385.743.9121



Control Solutions, Inc



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In Part 1, we introduced the concept of Digital Twins and the Quantum Digital Twin standard for buildings.

 In Part 2, we dove into semantic labeling systems as they compare to ontology systems. A comprehensive, physics-based ontology is a baseline requirement for full autonomy in buildings.

 In Part 3, we’re going to get into practical real-world applications for Quantum Digital Twins, and finally answer the question of “why does all of this matter?” by explaining how PassiveLogic’s Quantum Creator and Autonomy Studio software works, and some of the cool things you can do with those solutions.

 First, it’s worth answering “Why does Quantum matter to you”? Quantum addresses a number of challenges in industry and fills several gaps in today’s workflow. Fundamentally, Quantum is the industry's first and only description language for autonomous systems. Not only that, Quantum provides a single unified language for industry — end-to-end.  It enables manufacturers to define equipment at the factory, embedding profiles right into equipment. It enables the real-time control and operation of a system. And finally Quantum provides the industry's first high-level API for buildings, enabling plug-and-play services for analytics, analysis, energy monitoring, building management, maintenance and smart grid interactivity.

 We also need to take one more dive into concepts that span building science and physics. We began with some conceptual ideas around how to make controls technology autonomous: the role of quanta (packets of information relayed within a system) and actors (the defined roles on each piece of equipment: to store, transport, etc). Next we explain how these concepts become real.

 Quantum Digital Twins

Where we previously described the abstract underpinnings of the Quantum Standard, these ideas become tangible once we explore additional concepts: Quantum’s behaviors, components, equipment and assemblies. In systems theory, one can think of these as the foundational building blocks of any complex system. An equipment digital twin defines a real world counterpart, like a valve. Equipment is made up of components. For instance, a valve is made of a valve body, an actuator, and a control interface. Behaviors define what components physically do, at the deepest layer. Behaviors are composed into compute graphs that act upon quanta, and they define the same meaning regardless of their context. For example, resistance —whether from a pipe, wire or duct — is a measurable behavior.

2

Finally, equipment can be composed into assemblies, just like an actuator can be coupled to a mechanical damper into a single assembly.

 

Left Image: Quantum digital twin of a valve

 

For the vast majority of people’s day-to-day work, it’s only necessary to understand equipment. To define a controllable system, all you need to do is compose equipment into a complete system. But, if you are an engineer, manufacturer, or researcher, you might take any one of those layers and edit the finer grain constituents.

 

Because physics is the universal language that describes the function and “purpose” of every element in the physical world, it forms the foundation of how we can describe anything. When used as a definitional standard, it allows for progressive disclosure, and for easy access and management by ordinary users.

 Comparing Digital Twin Approaches

There are a few emerging technologies defining themselves as digital twins. Most of these are better defined as “CAD in the cloud.” These cloud-based semantic tools enable the tagging or data mapping of CAD components, but they lack a true understanding of the fundamental physics or operational behavior of things. Quantum Standard, in contrast, meets this physics-based criterion.

 We talked about semantic systems (knowing what a thing is called) and ontology systems (knowing what a thing is meant to do) in Part 2, so I won’t go too far into it here, but perhaps a simple analogy will help.

 Most of us are familiar with robots that vacuum our homes. Some of these are smarter than others, using a laser scanner to ensure that they don’t bump blindly into objects around the house. That’s a level of sophistication that we call protocol semantics. The robot is given a basic instruction, “move around the house without bumping into things,” and is given a tool to do it.

 You can program that robot with more sophisticated conceptual semantics by mounting a camera and giving labels to these obstacles: door, chair, couch. A conceptual semantic system offers another layer beyond protocol semantics, but it’s not a Quantum digital twin. The robot still doesn’t know what a chair is.

 To give that robot an ontology, and something like a Quantum-digital-twin view of your home, you’d have to arm the robot with knowledge about what these obstacles are. A door is now a router. If it’s open, the robot can move from one space to the next, and if it’s closed it can’t. A couch is a fixed obstacle, while a chair is an obstacle that moves — residing in one place on one encounter, but moving a few inches before the next encounter.

 Knowing what “door" and “chair” do is the starting point for a Quantum digital twin view of your home, enabling something approaching autonomy.

 In the building industry, many semantic-based systems that call themselves digital twins are really just robots who’ve been given a camera and some tagging. They encounter something they call “door,” without knowledge of what a door is. Most building information models (BIMs) only get to the level of semantic definition: labels and tags might have been applied, but the system lacks knowledge of the meaning behind those tags and labels.

 Quantum Creator (pre-Design)

The challenge facing Quantum digital twins and ontology standards is that these ideas are abstract pursuits even among scientists and engineers. The complexity itself is a hurdle to adoption. And that’s a problem! If you need a room full of PhD’s to understand digital twins, or to interface to semantic standards, how will it ever be possible to scale?

 We take a two-phased approach to make Quantum digital twins accessible to a wide audience. The first phase is defining the digital twin itself, using a tool called Quantum Creator. This is the first software in any industry that enables simple graphical definition of a digital twinning in an accessible way. This enables equipment manufacturers, designers, and engineers to easily define the fundamental physical properties of assemblies and their components. In this pre-design phase you can create a Quantum digital twin of literally any device, by measuring its fundamental behaviors. And yet, a small number of components define almost all equipment in the world. Rearranging components4 allows easy definition of other equipment.

 

Left Image: Quantum digital twin of a building

 

If this work is done ahead of time, then you won’t need an advanced degree to begin assembling your building’s design. A non-expert can wield a drag and drop interface and a catalog of existing components — the physics of which are encapsulated in the model — to begin their design.

 

At PassiveLogic, we are about technology inclusion: how can we ensure that the coolest advancements are accessible to the largest numbers of people? We do it with a true Quantum digital twin creating tool that enables novices to do more while making experts more expert.

 

Autonomy Studio (Design, Build, Operate, Maintain)

Once a Quantum digital twin of each component and device is generated, we’re in the design and build phase. This is where we have an opportunity to use the complexity of Quantum digital twins to make them viable for system controls.

 Autonomy Studio is the first tool that allows a non-scientist to create a true, physics-based digital twin of a complex system like an office building. Beginners can pick up the Autonomy Studio tool easily, while experienced architects and engineers will find greater depth and faster workflow compared to conventional tools. Our motto is “draw, don’t code”: instead of manually programming control systems, users drag and drop in an intuitive interface to create designs of their building’s floor plan and mechanical systems.

Users have the ability to fully define the parts of a building — from the envelope, floor plan, and mechanical systems, to the occupancy schedule, internal environment, and external weather patterns. That information is used to build a Quantum digital twin of the entire system and its components in a queryable format.

We call this generative design. From their drawings, users can automatically generate the needed controls and wiring layout for the building. A bill of materials is assembled, and project managers can get parts orders out the door right away instead of spending days in product requisition. Autonomy Studio acts as an electrical engineer, parts catalog, and blueprint for installers.

Because it generated its own wiring layout, Autonomy Studio knows exactly how everything is supposed to connect together. Installers get a real-time view of digital blueprints, which helps them turn virtual plans into physical implementations right at the point of install. If a wiring mistake is made, Autonomy Studio now knows immediately and can help technicians get it right.

Without the ontology protocol that the Quantum Standard enables, a building is correctly commissioned only once: the day of the install. After that, the manually programmed static sequences become irrelevant over time, as conditions and use cases change in and around a building.

Combining Quantum digital twins with a lightning fast simulation engine brings the necessary speed to model predictive control in a way that makes these techniques viable and scalable for ongoing use (and continuous commissioning). We have built an auto-differentiable AI control engine that simulates possible future scenarios millions of times per second — and then picks the most optimal controls sequences in real time to realize that future. When conditions change, the simulation runs again, re-optimizing the control sequences of the building while in operation without any manual tweaking and tuning.

Along with making the controls decisions for the building, Quantum digital twins can be leveraged to automate the process of maintenance and keep all systems running smoothly. With a physics-based understanding of the system, the goal shifts from emergency care to preventative maintenance. Deviations from expected behavior are detected much earlier because a whole-systems approach allows accurate inferences to be made even where sensors are not providing data. The end result is a fault detection system with wider coverage and earlier warnings — with automatic task delegation to facilities staff when repairs need to be done.

A New Era

We are entering the next phase of interconnected autonomous systems. Quantum is an organizing intelligence for this growing complexity, offering facility managers an effective way to wrangle complexity across an entire building portfolio. In Autonomy Studio, professionals gain a portfolio-wide view of all their buildings, complete with automated projections of their most important chosen metrics. They can hop into a single building view as needed, and quickly pick up additional insights at a finer level of detail.

Larger organizations also need to translate complex building data within their enterprise systems and infrastructure. The Quantum Standard is exposed as an open API data layer that allows it to be integrated with in-house or third-party applications — meaning that ERP systems finally have a full data window into the whole enterprise and all its functions.

 Partners to the Industry

PassiveLogic has developed Quantum Creator and Autonomy Studio to be a core toolset for building Quantum digital twins. This toolset is available to partners and industry players to extend the library of components, equipment, assemblies, and systems templates. The API for Quantum Standard is available to all to expand this toolkit to additional applications and use cases. When it comes to autonomous control, there are unlimited possibilities with Quantum.

We are partnering with third-party software and hardware companies who are interested in being part of the evolution of what’s possible for autonomous systems. We solve the integration challenges of getting into buildings and extracting the right data, while expanding the number of applications available to customers through the Autonomy Studio marketplace.

 

Conclusion

At PassiveLogic, we believe a building’s digital twin is as important as its roof or its walls — the building simply won’t function as intended without it. And through Quantum Creator and Autonomy Studio, we can design and interact with true Quantum digital twins throughout a building’s life span.

Creating next-generation Autonomous Buildings is a community effort! We are working with the most innovative and forward thinking people in the industry to usher in this reality. If you are interested in joining the revolution, please get in touch and build the future with us!
















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