Indoor Thermal Environment and Energy Characteristics with Varying Cooling System Capacity and Restart Time

Office cooling systems are controlled with on/off control according to typical occupancy patterns. During unoccupancy, the cooling systems remain switched off to reduce unnecessary energy consumption. During occupancy, however, the cooling systems are in operation to decrease the indoor air temperature, which is increased during unoccupancy, to the cooling set-point temperature. The time required to decrease the indoor air temperature to the cooling set-point temperature is defined as the “recovery time”. According to the recovery time, the indoor thermal comfort at the occupancy start time may worsen, and unnecessary energy may be consumed. Moreover, a cooling system capacity affects the recovery time and the energy consumption because the amount of heat that the cooling system can remove varies according to its size. Therefore, it is necessary to analyze the indoor thermal environment and the energy consumption according to the capacity and the restart time of the cooling system. This study implemented a building system energy simulation using EnergyPlus to evaluate the indoor air temperature, recovery time, and energy consumption of the cooling system while varying the capacity and restart time. As a result, the recovery time was between 49 and 425 min. and energy consumption varied between 419.0 and 521.4 kWh for various capacities. The recovery time was between 26 and 153 min. and energy consumption was between 426.0 and 439.0 kWh for various restart times

Indoor Thermal Environment and Energy Characteristics with Varying Cooling System Capacity and Restart Time

Office cooling systems are controlled with on/off control according to typical occupancy patterns. During unoccupancy, the cooling systems remain switched off to reduce unnecessary energy consumption. During occupancy, however, the cooling systems are in operation to decrease the indoor air temperature, which is increased during unoccupancy, to the cooling set-point temperature. The time required to decrease the indoor air temperature to the cooling set-point temperature is defined as the “recovery time”. According to the recovery time, the indoor thermal comfort at the occupancy start time may worsen, and unnecessary energy may be consumed. Moreover, a cooling system capacity affects the recovery time and the energy consumption because the amount of heat that the cooling system can remove varies according to its size. Therefore, it is necessary to analyze the indoor thermal environment and the energy consumption according to the capacity and the restart time of the cooling system. This study implemented a building system energy simulation using EnergyPlus to evaluate the indoor air temperature, recovery time, and energy consumption of the cooling system while varying the capacity and restart time. As a result, the recovery time was between 49 and 425 min. and energy consumption varied between 419.0 and 521.4 kWh for various capacities. The recovery time was between 26 and 153 min. and energy consumption was between 426.0 and 439.0 kWh for various restart times

An Analytical Study of the Latest Trends of Free-Form Molds

With the development of technology, the number of free-form structures—as well as their value—is increasing. In order to construct such free-form structures, a number of studies are being conducted on free-form molds from multifaceted perspectives. However, it is difficult to identify the progress of studies related to free-form molds, as the scope of the studies is redundant or similar in many cases. Therefore, the current study focused on the identification of the trends of preceding studies on free-form molds using the PRISMA technique. The study classified the studies into three topics in order to identify the trends: ‘free-form curve fabrication technology’, ‘free-form mold fabrication technology’, and the ‘analysis of free-form panel forms.’ Each topic was further categorized into two tiers for more in-depth analysis. The whole process was adopted in order to suggest the trends of studies on free-form molds. The findings are expected to be used to provide fundamental data for future studies on free-form molds, and to set the directions for new studies

Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends

Buildings use up to 40% of the global primary energy and 30% of global greenhouse gas emissions, which may significantly impact climate change. Heating, ventilation, and air-conditioning (HVAC) systems are among the most significant contributors to global primary energy consumption and carbon gas emissions. Furthermore, HVAC energy demand is expected to rise in the future. Therefore, advancements in HVAC systems’ performance and design would be critical for mitigating worldwide energy and environmental concerns. To make such advancements, energy modeling and model predictive control (MPC) play an imperative role in designing and operating HVAC systems effectively. Building energy simulations and analysis techniques effectively implement HVAC control schemes in the building system design and operation phases, and thus provide quantitative insights into the behaviors of the HVAC energy flow for architects and engineers. Extensive research and advanced HVAC modeling/control techniques have emerged to provide better solutions in response to the issues. This study reviews building energy modeling techniques and state-of-the-art updates of MPC in HVAC applications based on the most recent research articles (e.g., from MDPI’s and Elsevier’s databases). For the review process, the investigation of relevant keywords and context-based collected data is first carried out to overview their frequency and distribution comprehensively. Then, this review study narrows the topic selection and search scopes to focus on relevant research papers and extract relevant information and outcomes. Finally, a systematic review approach is adopted based on the collected review and research papers to overview the advancements in building system modeling and MPC technologies. This study reveals that advanced building energy modeling is crucial in implementing the MPC-based control and operation design to reduce building energy consumption and cost. This paper presents the details of major modeling techniques, including white-box, grey-box, and black-box modeling approaches. This paper also provides future insights into the advanced HVAC control and operation design for researchers in relevant research and practical fields

Development of Free-Form Assembly-Type Mold Production Technology Using 3D Printing Technology

Free-form molds are used for one-time curve configuration, and because they are produced through manpower, they have issues with reduced precision and the occurrence of errors. In this study, 3D printing technologies were used to ensure precision, and polylactic acid and reusable eco-friendly materials to develop free-form assembly-type side-mold production technologies. In verifying the side mold, a free-form concrete panel was produced to check whether deformation occurs due to lateral pressure. Therefore, in this study, to verify this, a free-form concrete panel was produced and 3D-scanned to analyze the error at the side mold and the cause of the error to confirm the performance of the mold. The results showed that the error at each part was small, with a standard deviation of 1.627 mm, and there was little error at the panel joint part, around 1°. Such research is expected to be used in studies related to mold production technologies using 3D printers and on the production of free-form side molds

Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends

Buildings use up to 40% of the global primary energy and 30% of global greenhouse gas emissions, which may significantly impact climate change. Heating, ventilation, and air-conditioning (HVAC) systems are among the most significant contributors to global primary energy consumption and carbon gas emissions. Furthermore, HVAC energy demand is expected to rise in the future. Therefore, advancements in HVAC systems’ performance and design would be critical for mitigating worldwide energy and environmental concerns. To make such advancements, energy modeling and model predictive control (MPC) play an imperative role in designing and operating HVAC systems effectively. Building energy simulations and analysis techniques effectively implement HVAC control schemes in the building system design and operation phases, and thus provide quantitative insights into the behaviors of the HVAC energy flow for architects and engineers. Extensive research and advanced HVAC modeling/control techniques have emerged to provide better solutions in response to the issues. This study reviews building energy modeling techniques and state-of-the-art updates of MPC in HVAC applications based on the most recent research articles (e.g., from MDPI’s and Elsevier’s databases). For the review process, the investigation of relevant keywords and context-based collected data is first carried out to overview their frequency and distribution comprehensively. Then, this review study narrows the topic selection and search scopes to focus on relevant research papers and extract relevant information and outcomes. Finally, a systematic review approach is adopted based on the collected review and research papers to overview the advancements in building system modeling and MPC technologies. This study reveals that advanced building energy modeling is crucial in implementing the MPC-based control and operation design to reduce building energy consumption and cost. This paper presents the details of major modeling techniques, including white-box, grey-box, and black-box modeling approaches. This paper also provides future insights into the advanced HVAC control and operation design for researchers in relevant research and practical fields