INDUSTRY-BASED THERMODYNAMICS CASE STUDY ON REFRIGERATION CYCLE

The case study learning methodology has been used for more than 20 years in teaching science and engineering. This methodology is known to be highly effective in promoting students' understanding of the concepts and improving their ability to make connections between the concepts. In 2020 and 2021, the limited access to laboratory equipment and facilities due to the COVID-19 pandemic encouraged instructors to implement alternative methods. One of the alternatives considered in the current institution is the use of case studies to enhance students' understanding of thermodynamics and fluid mechanics topics during the online and hybrid implementations of those courses. In this study, an industry-based air-conditioning (AC) unit is facilitated to prepare a case study to teach refrigeration cycles in the laboratory part of thermodynamics. All four components of the AC unit, which include a compressor, a condenser, an expansion valve, and an evaporator, are assembled on a single platform. In an actual application, the compressor and condenser are part of the outside unit while an evaporator and expansion valve would be located indoors. In the first phase of the case study, students analyze temperature and pressure data for the normal operation of the unit to understand the function of each component in the cycle. In addition, by using thermodynamics property tables, they determine enthalpy and entropy values at different stages of the process, generate a temperature versus entropy (T-s) diagram, and calculate the efficiency of the AC unit. In the second phase of the study, they are provided with temperature and pressure data collected for the cases corresponding to when there is a problem with the AC unit. They perform analysis of those cases. The examples of issues introduced include part of the condenser or evaporator coils being disabled or using a partially blocked air filter. The equipment used in the case study is modified by the manufacturer to simulate those issues. During data analysis, student teams are tasked with identifying the issue introduced by looking at the changes in temperature, pressure, and T-s diagram. This paper provides detailed information about the case study, data collection, and analysis. Copyright © 2022 by ASME.

Learning to Learn HVAC Failures: Layering ML Experiments in the Absence of Ground Truth

Passenger comfort systems such as Heating, Ventilation, and Air-Conditioning units (HVACs) usually lack the data monitoring quality enjoyed by mission-critical systems in trains. But climate change, in addition to the high ventilation standards enforced by authorities due to the COVID pandemic, have increased the importance of HVACs worldwide. We propose a machine learning (ML) approach to the challenge of failure detection from incomplete data, consisting of two steps: 1. human-annotation bootstrapping, on a fraction of temperature data, to detect ongoing functional loss and build an artificial ground truth (AGT);2. failure prediction from digital-data, using the AGT to train an ML model based on failure diagnose codes to foretell functional loss. We exercise our approach in trains of Dutch Railways, showing its implementation, ML-predictive capabilities (the ML model for the AGT can detect HVAC malfunctions online), limitations (we could not foretell failures from our digital data), and discussing its application to other assets. © 2022, Springer Nature Switzerland AG.

Design of an intelligent purification and disinfection apparatus for air conditioning units

With the sudden outbreak and rapid spread of COVID-19, global economic development and social stability have been seriously affected. The virus mainly spreads infection among people on a large scale through the air. People are gradually focusing on how to use HVAC system, so that it can play a more efficient and positive role in epidemic prevention and control. Consequently, we designed an intelligent purification and disinfection apparatus for air-conditioning units. The apparatus integrates rapid virus detection and high-efficiency disinfection functions. It uses a modular design and different operating modes for different levels of epidemic periods. This apparatus is not only suitable for daily life, but also can meet the prevention and control requirements during the epidemic period, which takes the economy, energy saving, and environmental protection into account. © 2021 Institute of Physics Publishing. All rights reserved.