I have been wanting to do some multi-criteria optimization for a passive solar greenhouse design. I have experience with the same ML and AI techniques that Gagnon used in his work on multi-objective optimization[1] and his PhD dissertation[2]. In specific I am hoping to work with someone to develop an EnergyPlus model for one or more passive solar greenhouses initially based on UMN's Deep Winter Greenhouse (DWG)[3], and then add modular features like climate batteries, solar/ground heat-pumps, and active/passive venting. The reason that I wanted to start with the DWG is that UMN not only provides detailed plans, dozens of them have been built, and many of them have been well instrumented. In addition, one of my collaborators is willing to provide performance data from his first DWG greenhouse -- the data to be used for initial model calibration and validation. In his build, he also installed a climate battery, which he has turned on and off as part of his as-built performance tests. Once the models are "believable", I then want to apply the ML techniques to optimize the model for one or more fully instrumented greenhouses to be built on my small farm in Maryland. Please PM me if you are interested, and we can discuss details.
[1] https://corpus.ulaval.ca/jspui/bitstream/20.500.11794/68283/1/Performance%20of%20a%20sequential%20versus%20holistic.pdf
[2] https://corpus.ulaval.ca/jspui/bitstream/20.500.11794/32726/1/34660.pdf
[3] https://extension.umn.edu/growing-systems/deep-winter-greenhouses
[1] https://corpus.ulaval.ca/jspui/bitstream/20.500.11794/68283/1/Performance%20of%20a%20sequential%20versus%20holistic.pdf
[2] https://corpus.ulaval.ca/jspui/bitstream/20.500.11794/32726/1/34660.pdf
[3] https://extension.umn.edu/growing-systems/deep-winter-greenhouses
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