Jan Drgona on Solving Problems with Energy Sustainability in Buildings Using Scientific Machine Learning and Engineering

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Our guest today is Jan Drgona, who joins us today from Johns Hopkins University. Jan is an associate professor in the department of civil and systems engineering, and is also at the Ralph S O’Connor Sustainable Energy Institute.

In this full-length interview, Jan talks with us about the challenges in sustainably heating and cooling buildings, and how physics and scientific machine learning can help.

Highlights of the episode:

*Susan introduces the Science Fare podcast and frames the idea that a building’s materials play a role in the ubiquitous challenge of fighting the second law of thermodynamics [0:01]; *Susan introduces guest Jan Drgona, an engineering professor at Johns Hopkins University who is studying sustainable energy use in buildings [1:30]; *Jan shares his “winding” path to becoming a scientist, from wide-ranging interests in science as a kid to knowing he wanted to be a scientist due to a great high school chemistry experience and interests in math and computers [2:29]; *A lucky encounter conversing with another Ph.D. student during the coffee break at a scientific workshop who was working in modeling physical processes in buildings and was looking to collaborate with someone with Jan’s background and skills [5:12]; *Susan reflects on the power of in-person scientist meetings leading to multi-decade collaborations [7:28]; *Jan talks about the fascinating and important interdisciplinary research going on at the Ralph S O’Connor Sustainable Energy Institute [8:30]; *Susan sets up the problem Jan is working on — the difficulty in sustainably heating and cooling buildings — and Jan explains why building energy use is often inefficient and what the problem-solving opportunities are [9:20]; *The hundreds or thousands degrees of freedom in building HVAC — far higher than in driving a car (more like 12 degrees of freedom)! And how one human can’t really manage this in a static rules-based way [12:23]; *Why we often need to wear sweaters in buildings in summer and other problems with the current, more conservative approach to HVAC [14:30]; *Let’s talk about these problems in terms of something high school students are learning — the second law of thermodynamics [15:30]; *Combining thermal mass and thermal resistance of building materials can help make operation more efficient [19:00]; *HVAC type — electrification and coefficient of performance [19:31]; *Susan introduces Next Generation High School Science Standard PS 3-4, which states that students should be able to plan and conduct an investigation to provide evidence that when two components of different temperature are combined within a closed system, transfer of thermal energy results in a more uniform energy distribution among the components in the system — buildings can be a great setting for this kind of investigation! [21:49]; *Jan describes scientific machine learning and how it’s different from regular machine learning and illustrates with a concrete example of a building he worked on [23:30]; *Jan explains that scientific machine learning combines the guarantees of the physics with the adaptability of machine learning [30:16]; *Susan asks what would be the most complicated building to deal with in terms HVAC? One kind, Jan explains, are data centers [31:55]; *Jan’s hopes for the near future [34:27]; *Susan asks, what do you enjoy most about working in science? Jan says the people and the community, and the chance to live in many different places and countries and meet many different kinds of people. [39:39]; *Jan’s advice for high school students interested in science — follow your passion — your path is important! [43:20]; *Closing remarks, listener feedback information, and acknowledgment of the Science Fare team [45:47]

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