Usage Of Heating Research Articles

Monitoring of indoor radon and assessment of lung cancer risk to population of Beit Ummar city, Palestine

Radon concentrations were measured using CR-39 passive dosimeters in Beit Ummar city. 150 dosimeters were distributed over the study area dwellings according to the fraction of the population. The exposure started from October 2014 and lasted for 90 days. The city was divided into five sectors with six categories for each; corridor, kitchen, living room, saloon, bedroom and store. The influence of floor number and building type was introduced. Obtained results have recorded relatively high radon concentration in 73% of the studied houses. This is explained due to several factors such as poor ventilation, construction materials, and continuous usage of heating during this period and age of the building. Different parameters were calculated based on the measurements of track density of the distributed dosimeters in order to estimate the risk of radiation exposure; those parameters are: radon concentration (CRn), exposure to radon progeny (EP), indoor annual effective dose (AED) and number of lung cancer cases per year per million persons (LCC). The results showed that the radon concentrations and the resulting doses in the monitored chambers exceed the safe limits recommended by the WHO and EPA in some aspects. Therefore, health risk due to radon is possible.

A METHOD OF OPTIMIZING FENESTRATION DESIGN FOR DAYLIGHTING TO REDUCE HEATING AND COOLING LOADS IN OFFICES

Modern office building designs tend to increase the window share per facade to make the building more impressive with extensive visibility and well daylit rooms. In general, an increased window share results in higher energy usage and higher costs of heating and cooling, but these disadvantages can be reduced with a more careful design. The aim of this paper is to show the influence of window design and room layout on heating and cooling demand and daylight availability in office buildings in northern Europe. The results in the paper are based on design calculations for two different room types and daylight measurements on two room scale models in a daylight laboratory. The calculations show the influence of window design parameters on the cooling and heating demand. The daylight measurements show the influence of window design parameters on the availability of daylight. The results have then been combined to show a feasible window design regarding daylight availability and the resulting cooling and heating demands for different window orientations. The results show that in most cases it is possible to find a combination of window share and window solar factor that is feasible with regard to daylight as well as cooling and heating. The main finding is that there is a smaller or wider range of feasible designs for different window orientations.

Composition and atomic structure of the [formula omitted] surface

Surface composition (In coverage and top Si atom density) and plausible adsorption sites of In atoms have been determined for the Si(111) 31 × 31 -In surface phase using scanning tunneling microscopy. The usage of indirect heating for the In–Si(111) interface formation has been shown to be a crucial requirement for composition determination, since it allows one to avoid the undesirable effects associated with surface atom electromigration. On the basis of the data obtained, a model of the atomic arrangement of the surface has been proposed. The model incorporates 17 In atoms in the 31 × 31 unit cell residing above the reconstructed Si layer containing 28 atoms. According to the model, the Si(111) 31 × 31 -In surface is free of dangling bonds and Si atoms in this structure preserve their basic tetrahedral bonding geometry.

下水熱利用地域冷暖房と空気熱利用地域冷暖の投入エネルギー解析

The efficiency of energy usage of a district heating and cooling plant using sewage water as heat source and sink, was evaluated by investigating the data of the district heat demand and energy supply to the plant, which were collected at the Koraku -1 Chome plant in Tokyo central region.Through analyzing these data, it was clarified that the overall COPs of the plant were 3.17 for cooling and 2.65 for heating.COP was then compared with that of another plant using air as heat source and sink. The overall COPs of this plant which were calculated according to the atmospheric temperature, were 2.54 for cooling in summer and 2.28 for heating in winter.The differences in COPs were due to the temperature differences between sewage water and air.As a result for COP differences, the district heating and cooling plant using sewage water could be more energy saving, up to 20% for cooling in summer and 14% for heating in winter, compared with the counterpart plant that uses air as heat source and sink.

Multivariate Regression Modeling

An empirical or regression modeling approach is simple to develop and easy to use compared to detailed hourly simulations of energy use in commercial buildings. Therefore, regression models developed from measured energy data are becoming an increasingly popular method for determining retrofit savings or identifying operational and maintenance (O&M) problems. Because energy consumption in large commercial buildings is a complex function of climatic conditions, building characteristics, building usage, system characteristics and type of heating, ventilation, and air conditioning (HVAC) equipment used, a multiple linear regression (MLR) model provides better accuracy than a single-variable model for modeling energy consumption. Also, when hourly monitored data are available, an issue which arises is what time resolution to adopt for regression models to be most accurate. This paper addresses both these topics. This paper reviews the literature on MLR models of building energy use, describes the methodology to develop MLR models, and highlights the usefulness of MLR models as baseline models and in detecting deviations in energy consumption resulting from major operational changes. The paper first develops the functional basis of cooling energy use for two commonly used HVAC systems: dual-duct constant volume (DDCV) and dual-duct variable air volume (DDVAV). Using these functional forms, the cooling energy consumption in five large commercial buildings located in central Texas were modeled at monthly, daily, hourly, and hour-of-day (HOD) time scales. Compared to the single-variable model (two-parameter model with outdoor dry-bulb as the only variable), MLR models showed a decrease in coefficient of variation (CV) between 10 percent to 60 percent, with an average decrease of about 33 percent, thus clearly indicating the superiority of MLR models. Although the models at the monthly time scale had higher coefficient of determination (R2) and lower CV than daily, hourly, and HOD models, the daily and HOD models proved more accurate at predicting cooling energy use.