Thermal Environmental Conditions for Human Occupancy
01 Jan 1992-Vol. 5
About: The article was published on 1992-01-01 and is currently open access. It has received 5855 citations till now. The article focuses on the topics: Occupancy.
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TL;DR: In this paper, the authors tried to contribute to the understanding of the role of the occupant related to the energy consumption of residential buildings by means of simulations and experimental data obtained by an extensive measurement campaign.
Abstract: Residential buildings account for a significant amount of the national energy consumption of all OECD countries and consequently the EU and the Netherlands. Therefore, the national targets for CO2 reduction should include provisions for a more energy efficient building stock for all EU member states. National and European level policies the past decades have improved the quality of the building stock by setting stricter standards on the external envelope of newly made buildings, the efficiency of the mechanical and heating components, the renovation practices and by establishing an energy labelling system. Energy related occupancy behavior is a significant part, and relatively unchartered, of buildings’ energy consumption. This thesis tried to contribute to the understanding of the role of the occupant related to the energy consumption of residential buildings by means of simulations and experimental data obtained by an extensive measurement campaign.
10 Dec 2018
TL;DR: Aijazi et al. as mentioned in this paper combined future weather files with whole building energy simulations to assess the sensitivity and feasibility of natural ventilation in providing thermal comfort in three locations, representing different climate types.
Abstract: Author(s): Aijazi, Arfa; Brager, Gail | Abstract: Observed global warming trends undermine the conventional practice of using historic weather files, such as Typical Meteorological Year (TMY), to predict building performance during the design process. In order to limit adverse impacts such as improperly sized mechanical equipment or thermal discomfort, it is important to consider how the building will perform in the future. Like all passive design strategies, natural ventilation, relies on local climate to be effective in improving building performance. This paper combines future weather files with whole building energy simulations to assess the sensitivity and feasibility of natural ventilation in providing thermal comfort in three locations, representing different climate types. The results show how building performance, as measured by thermal comfort metrics, changes over time. Natural ventilation can provide a buffer against warming climate, but only to a certain extent. Future weather files are useful for identifying where and when there is a risk that an exclusively passive design is no longer possible.
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01 Jan 2021
TL;DR: In this paper, Younis et al. presented the results of a study at the Prince Sattam Bin Abdulaziz University, College of Engineering at Wadi Addwaser, Department of Mechanical Engineering, Saudi Arabia.
Abstract: Obai Younis1,2 *, Reem Ahmed3, Ali Mohammed Hamdan4, Dania Ahmed2 1Prince Sattam Bin Abdulaziz University, College of Engineering at Wadi Addwaser, Department of Mechanical Engineering, Wadi Addwaser, Saudi Arabia 2University of Khartoum, Faculty of Engineering, Department of Mechanical Engineering, Khartoum, Sudan 3Elgerafsharg Technical College, Department of Mechanical Engineering, Sudan 4University of Bahri, Department of Mechanical Engineering, Alkadroo, Sudan
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TL;DR: In this article, the authors propose to use a finite-horizon oracle controller with perfect knowledge of all system parameters as a reference for optimal control actions for learning-based control of nonlinear control systems.
Abstract: The exploration/exploitation trade-off is an inherent challenge in data-driven and adaptive control. Though this trade-off has been studied for multi-armed bandits, reinforcement learning (RL) for finite Markov chains, and RL for linear control systems; it is less well-studied for learning-based control of nonlinear control systems. A significant theoretical challenge in the nonlinear setting is that, unlike the linear case, there is no explicit characterization of an optimal controller for a given set of cost and system parameters. We propose in this paper the use of a finite-horizon oracle controller with perfect knowledge of all system parameters as a reference for optimal control actions. First, this allows us to propose a new regret notion with respect to this oracle finite-horizon controller. Second, this allows us to develop learning-based policies that we prove achieve low regret (i.e., square-root regret up to a log-squared factor) with respect to this oracle finite-horizon controller. This policy is developed in the context of learning-based model predictive control (LBMPC). We conduct a statistical analysis to prove finite sample concentration bounds for the estimation step of our policy, and then we perform a control-theoretic analysis using techniques from MPC- and optimization-theory to show this policy ensures closed-loop stability and achieves low regret. We conclude with numerical experiments on a model of heating, ventilation, and air-conditioning (HVAC) systems that show the low regret of our policy in a setting where the cost function is partially-unknown to the controller.
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01 Aug 2013TL;DR: The results of the performance characteristics of the HCR indicate the encouraging enhancement of the automotive air conditioning system compared to Hydrofluorocarbon refrigerant (HFC-R134a) as discussed by the authors.
Abstract: The HFC-R134a and hydrocarbon refrigerant (HCR) will be evaluated on the automotive air conditioning (AAC) experimental test rig which completed with the AAC system including the blower, evaporator, condenser, radiator, electric motor, compressor, alternator and equipped with the simulation room acting (equipped with internal heat load) as the passenger compartment. The electric motor operated as a car’s engine and will drive the compressor simultaneously to the alternator to recharge the battery. The tests have been performed by varying the motor speed; 1000, 2000 and 3000 rpm, temperature set-point; 21 and 230C, and internal heat loads; 0, 500, 700 and 1000 W. The results of the performance characteristics of the HCR indicate the encouraging enhancement of the AAC system compared to Hydrofluorocarbon refrigerant (HFC-R134a).