Variable Thermal Comfort Index for Indoor Work Space in Office Buildings: A Study in Germany

Kuchen, Ernesto

doi:10.4236/ojce.2016.64054

Cited by 6 publications

(3 citation statements)

References 10 publications

(13 reference statements)

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“…Adaptive thermal comfort is based on three main things: Thermal Comfort Vote (CV), Preference vote (PV), and Thermal Acceptance and Neutrality. Adaptive thermal comfort can also predict thermal comfort through statistic tests [1]. Occupants' adaptation is a factor influencing the building's thermal comfort.…”

Section: Introductionmentioning

confidence: 99%

Thermal evaluation for exposed stone house with quantitative and qualitative approach in mountainous area, Wonosobo, Indonesia

Hermawan

Prianto

2017

IOP Conf. Ser.: Earth Environ. Sci.

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Section: Introductionmentioning

confidence: 99%

Thermal evaluation for exposed stone house with quantitative and qualitative approach in mountainous area, Wonosobo, Indonesia

Hermawan

Prianto

2017

IOP Conf. Ser.: Earth Environ. Sci.

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“…Mann-Whitney analyses (after correction for climatic variables) showed that subjects with higher job satisfaction had thermal sensations closer to "neutral". The combination of objective and subjective evaluation of thermal comfort conditions has been studied by Eide et al, Kuchen [7][8][9][10][11]. From the perspective of objective evaluation of thermal comfort of monitored subjects is, in the article from Lu et al [12], described interesting way to apply infrared thermography to develop individual human thermal models to predict thermal sensations.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree

Andrejiová

Piňosová

Kralikova

et al. 2019

IJERPH

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During the process of designing and implementing a working environment, there is a need to guarantee adequate conditions for future workers' health and well-being. This article addresses the classification of employees characterized by several basic input variables (gender, age, class of work). The investigated variable was the health of employees. This article aims to create a prediction classification model using the classification tree, which can be used to classify new cases into appropriate classes as accurately as possible. Objective measurements of microclimatic parameters were performed by the Testo 435 instrument. The subjective evaluation was performed by a questionnaire survey formed from the training group of 80 respondents and independently verified by the test group of 80 more respondents. The result confusion matrix shows that the number of correctly classified respondents was 69 from a total of 80 respondents. The overall accuracy was A C = 0.863, which means that the likelihood that respondents are properly classified in the correct health class is 86.3%. Based on the model obtained using the classification tree, we can classify respondents into the relevant class for their state of health. The respondent is classified into the class of work for which particular health and working conditions are most likely.

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“…The differential value influences both of human thermal comfort and energy saving (1,2). Too big the differential value makes a conditioned room comfort less (3)(4)(5).Whereas, too small the differential causes inefficient system (6)(7)(8)(9) and also A/C be on and off frequent (2,10). In addition, the action also requires high restarting current that equals to 4 to 10 times bigger than running current (11).…”

Section: Introductionmentioning

confidence: 99%

Design of a new on-off controller based on Arduino UNO R3 with application to Window A/C

Erham¹,

Markus²,

Sopianti³

2018

IJPS

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Window Air Conditioner (A/C) is air conditioning which services need of thermal comfort inside a small or medium room. To maintain the desired temperature, then A/C employs the thermostat that functions as an on-off controller. In general, it works based on the set point and the control differential; however the differential is not available to set. In fact, the differential has a quite important role. In this paper was proposed a new optional controller based on an Arduino UNO R3 so that the differential can be also set. In addition, it is aimed to anticipate if the thermostat has a problem. Based on these purposes, then it was designed an on-off controller and the thermostat was replaced by using the Arduino in which was uploaded the algorithm of controller. However, the excellence of device can be tested in A/C without uninstalling the existing thermostat. The response of control system obtained is appropriate with design objectives. Although, it at crucial time points still has a response error with range from 0.02 0 C to 0.38 o C.Thus, it is more accurate than a conventional system whose error from 0.5°C to 0.95°C. Moreover, the designed controller can reduce the energy consumption of about 66% compared to the thermostat.

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Variable Thermal Comfort Index for Indoor Work Space in Office Buildings: A Study in Germany

Cited by 6 publications

References 10 publications

Thermal evaluation for exposed stone house with quantitative and qualitative approach in mountainous area, Wonosobo, Indonesia

Thermal evaluation for exposed stone house with quantitative and qualitative approach in mountainous area, Wonosobo, Indonesia

Analysis of the Impact of Selected Physical Environmental Factors on the Health of Employees: Creating a Classification Model Using a Decision Tree

Design of a new on-off controller based on Arduino UNO R3 with application to Window A/C

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