scholarly journals Utilization of Thermally Activated Building System with Horizontal Ground Heat Exchanger Considering the Weather Conditions

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7927
Author(s):  
Woong June Chung ◽  
Sang Hoon Park

The thermally activated building system (TABS) can reduce the peak load by integrating with the ground heat exchangers. When integrated, the cost of groundwork and stability of the ground temperature would counteract because the weather conditions would influence the ground temperature in shallow depth. However, previous studies on TABS assumed constant ground temperatures such as average outdoor air temperature. In this study, ground temperatures in different depths are simulated for their detailed investigations, and simulated results of ground temperature were applied to building energy simulations for observing the load-handled ratio (LHR), representing the peak load reduction by TABS evaluated in various weather conditions. Simulation results of ground temperatures from 1 m to 39 m depths show that the temperature stabilized at 2 m to 11 m depths depending on the characteristics of the outdoor air temperature. LHR increased as the ground depth increased because the ground temperature at shallow depths increased during peak hours. Ground depths of 8 m were found ideal for maintaining consistent LHR for all weather conditions. Detailed observation of ground temperature and its effect on LHR in various weather conditions can help system engineers design and operate the TABS with the ground system.

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 860
Author(s):  
Piotr Michalak

Modern buildings with new heating, ventilation and air conditioning (HVAC) systems offer possibility to fit parameters of the indoor environment to the occupants’ requirements. The present paper describes the results of measurements performed in an office room in the first Polish passive commercial office building during four months of normal operation. They were used to calculate parameters describing thermal comfort: vertical air temperature profile, floor surface temperature, predicted mean vote (PMV) and predicted percent of dissatisfied (PPD). Obtained results confirmed good thermal conditions in the analysed room. The average temperature of the floor’s surface varied from 20.6 °C to 26.2 °C. The average vertical air temperature, calculated for working days, was from 22.5 °C to 23.1 °C. The temperature difference between the floor and 5 cm below the ceiling was from −0.9 °C to 6.3 °C. The PMV index varied from 0.52 to 1.50 indicating ‘slightly warm’ sensation, in spite of ‘neutral’ reported by employees. Also measured cooling and heating energy consumption was presented. The performed measurements confirmed the ability of thermally activated building system (TABS) to keep good thermal conditions.


2021 ◽  
Author(s):  
Giuliano Andrea Pagani ◽  
Marcel Molendijk ◽  
Jan Willem Noteboom

<p>Modern automobiles are becoming more and more “computers on the wheels” having lots of digital equipment on board. Such equipment is both for the comfort and entertainment of the passengers and for their safety. Sensors play a key role in measuring several parameters of the car performance (e.g., traction control, anti-lock breaking system) and also environmental  parameters are observed directly (e.g., air temperature) or can be somehow inferred (e.g., precipitation via windscreen wipers activity/speed).</p><p>KNMI has been provided air temperature recorded every 10 minutes by thousands of vehicles driving in the Netherlands for the period January-October 2020. We have performed an initial exploratory temporal and spatial analysis to understand the most promising periods of the day and areas where sufficient data is available to perform a more thorough data analysis in the future. Furthermore, we have performed a correlation analysis between the outside temperature measured by cars and air and ground temperature observed by official weather station sensors placed at one location on the Dutch highways. The correlation results for three randomly selected days (with different weather conditions) show a good positive correlation coefficient ranging from 0.93 to 0.76 for car and station air temperature and from 0.91 to 0.67 for car temperature and station ground temperature.</p><p>This initial exploration paves the way to the use of (OEM) car data as (mobile) weather stations. We foresee in the future to use a combination of sensed variables from cars such as air temperature, traction control, windscreen wipers activity for example to improve observations of road slipperiness and related warning systems that are not restricted to Dutch highways only.</p>


2016 ◽  
Vol 29 (2) ◽  
pp. 173-182 ◽  
Author(s):  
Kelly R. Wilhelm ◽  
James G. Bockheim

AbstractVariations in atmospheric conditions can be important factors influencing temperature dynamics within the active layer of a soil. Solar radiation and air temperature can directly alter ground surface temperatures, while variations in wind and precipitation can control how quickly heat is carried through soil pores. The presence of seasonal snow cover can also create a thermal barrier between the atmosphere and ground surface. This study examines the relation between atmospheric conditions and ground temperature variations on a deglaciated island along the Western Antarctic Peninsula. Ground temperatures were most significantly influenced by incoming solar radiation, followed by air temperature variations. When winter months were included in the comparison, the influence of air temperature increased while solar radiation became less influential, indicating that snow cover reflected solar radiation inputs, but was not thick enough to insulate the ground. When ground temperatures were compared to atmospheric conditions of preceding weeks, seasonal temperature peaks 1.6 m below ground were best related to seasonal air temperature peaks from the previous two weeks. The same ground temperature peaks were best related to seasonal solar radiation peaks of seven weeks prior. This difference was a result of temperature lags within the atmosphere.


2021 ◽  
Author(s):  
Cameron Ross ◽  
Ryley Beddoe ◽  
Greg Siemens

<p>Initialization (spin-up) of a numerical ground temperature model is a critical but often neglected step for solving heat transfer problems in permafrost. Improper initialization can lead to significant underlying model drift in subsequent transient simulations, distorting the effects on ground temperature from future climate change or applied infrastructure.  In a typical spin-up simulation, a year or more of climate data are applied at the surface and cycled repeatedly until ground temperatures are declared to be at equilibrium with the imposed boundary conditions, and independent of the starting conditions.</p><p>Spin-up equilibrium is often simply declared after a specified number of spin-up cycles. In few studies, equilibrium is visually confirmed by plotting ground temperatures vs spin-up cycles until temperatures stabilize; or is declared when a certain inter-cycle-temperature-change threshold is met simultaneously at all depths, such as ∆T ≤ 0.01<sup>o</sup>C per cycle. In this study, we investigate the effectiveness of these methods for determining an equilibrium state in a variety of permafrost models, including shallow and deep (10 – 200 m), high and low saturation soils (S = 100 and S = 20), and cold and warm permafrost (MAGT = ~-10 <sup>o</sup>C and >-1 <sup>o</sup>C). The efficacy of equilibrium criteria 0.01<sup>o</sup>C/cycle and 0.0001<sup>o</sup>C/cycle are compared. Both methods are shown to prematurely indicate equilibrium in multiple model scenarios.  Results show that no single criterion can programmatically detect equilibrium in all tested models, and in some scenarios can result in up to 10<sup>o</sup>C temperature error or 80% less permafrost than at true equilibrium.  A combination of equilibrium criteria and visual confirmation plots is recommended for evaluating and declaring equilibrium in a spin-up simulation.</p><p>Long-duration spin-up is particularly important for deep (10+ m) ground models where thermal inertia of underlying permafrost slows the ground temperature response to surface forcing, often requiring hundreds or even thousands of spin-up cycles to establish equilibrium. Subsequent transient analyses also show that use of a properly initialized 100 m permafrost model can reduce the effect of climate change on mean annual ground temperature of cold permafrost by more than 1 <sup>o</sup>C and 3 <sup>o</sup>C under RCP2.6 and RCP8.5 climate projections, respectively, when compared to an identical 25 m model. These results have important implications for scientists, engineers and policy makers that rely on model projections of long-term permafrost conditions.</p>


2004 ◽  
Vol 31 (2) ◽  
pp. 369-378 ◽  
Author(s):  
Aly Sherif ◽  
Yasser Hassan

Road and highway maintenance is vital for the safety of citizens and for enabling emergency and security services to perform their essential functions. Accumulation of snow and (or) ice on the pavement surface during the wintertime substantially increases the risk of road crashes and can have negative impact on the economy of the region. Recently, road maintenance engineers have used pavement surface temperature as a guide to the application of deicers. Stations for road weather information systems (RWIS) have been installed across Europe and North America to collect data that can be used to predict weather conditions such as air temperature. Modelling pavement surface temperature as a function of such weather conditions (air temperature, dew point, relative humidity, and wind speed) can provide an additional component that is essential for winter maintenance operations. This paper uses data collected by RWIS stations at the City of Ottawa to device a procedure that maximizes the use of a data batch containing complete, partially complete, and unusable data and to study the relationship between the pavement surface temperature and weather variables. Statistical models were developed, where stepwise regression was first applied to eliminate those variables whose estimated coefficients are not statistically significant. The remaining variables were further examined according to their contribution to the criterion of best fit and their physical relationships to each other to eliminate multicollinearities. The models were further corrected for the autocorrelation in their error structures. The final version of the developed models may then be used as a part of the decision-making process for winter maintenance operations.Key words: winter maintenance, pavement temperature, statistical modelling, RWIS.


1999 ◽  
Vol 26 (5) ◽  
pp. 675 ◽  
Author(s):  
P. B. Whitaker ◽  
R. Shine

Encounters between humans and dangerously venomous snakes put both participants at serious risk, so the determinants of such encounters warrant attention. Pseudonaja textilis is a large fast-moving elapid snake responsible for most snakebite fatalities in Australia. As part of a broad ecological study of this species in agricultural land near Leeton, New South Wales, we set out to identify factors influencing the probability that a human walking in farmland would come into close proximity to a brownsnake. Over a three-year period, we walked regular transects to quantify the number and rate of snake encounters, and the proportion of snakes above ground that could be seen. The rate of encounters depended upon a series of factors, including season, time of day, habitat type, weather conditions (wind and air temperature) and shade (light v. dark) of the observers’ clothing. Interactions between factors were also important: for example, the effect of air temperature on encounter probability differed with season and snake gender, and the effect of the observers’ shade of clothing differed with cloud cover. Remarkably, even a highly-experienced observer actually saw <25% of the telemetrically monitored snakes that were known to be active (i.e. above ground) nearby. This result reflects the snakes’ ability to evade people and to escape detection, even in the flat and sparsely vegetated study area. The proportion of snakes that were visible was influenced by the same kinds of factors as described above. Most of the factors biasing encounter rates are readily interpretable from information on other facets of the species’ ecology, and knowledge of these factors may facilitate safer coexistence between snakes and people.


Formulation of the problem. Understanding that solar energy is the main source of the majority of biological, chemical and physical processes on Earth, investigation of its influence on different climatic fields allows us to define the features of its space and hour fluctuations. To define radiation and temperature regime of the territory it is necessary to determine climatic features of the spreading surface, which absorbs and will transform solar energy. Considering the fact that modern climatic changes and their consequences cover all components of the system, today there is a problem of their further study for comprehension of atmospheric processes, modeling weather conditions on different territories depending on the properties. The purpose of the article is to determine interrelations between indexes of solar radiation (the Wolf's number) and air temperature, atmospheric pressure on the territory of Ukraine during 1965-2015, their change in space and time. Methods. Correlative method is one of the main methods of a statistical analysis which allows us to receive correlation coefficients of solar radiation variability indexes, air temperature, atmospheric pressure on the territory of the research. This technique estimates the extent of solar radiation influence on temperature regime of the territory and distribution of atmospheric pressure. Results. Coefficients of correlation, which characterize variability of solar radiation indexes, air temperature and atmospheric pressure on the explored territory have been received by means of statistical correlation analysis method. This technique allows us to estimate the degree and nature of solar radiation influence on a temperature regime of the territory and distribution of atmospheric pressure. It has been defined that direct correlative connection between indexes of solar radiation is characteristic of air temperature and atmospheric pressure fields. Significant statistical dependence between incoming solar radiation on the territory of Ukraine and atmospheric pressure has been noted during the spring and autumn periods mainly at the majority of stations. Between indexes of solar radiation and air temperature the inverse correlative connection in winter will be transformed to a direct connection during the spring and summer periods. Scientific novelty and practical significance. Physical processes, which happen in the atmosphere, are characterized by complex interrelations. For further research it is important to define solar radiation value and the extent of influence on climatic conditions.


Baltica ◽  
2018 ◽  
Vol 30 (2) ◽  
pp. 75-85 ◽  
Author(s):  
Viktorija Rukšėnienė ◽  
Inga Dailidienė ◽  
Loreta Kelpšaitė-Rimkienė ◽  
Tarmo Soomere

This study focuses on time scales and spatial variations of interrelations between average weather conditions and sea surface temperature (SST), and long-term changes in the SST in south-eastern Baltic Sea. The analysis relies on SST samples measured in situ four times a year in up to 17 open sea monitoring stations in Lithuanian waters in 1960–2015. A joint application of non-metric multi-dimensional scaling and cluster analysis reveals four distinct SST regimes and associated sub-regions in the study area. The increase in SST has occurred during both winter and summer seasons in 1960–2015 whereas the switch from relatively warm summer to colder autumn temperatures has been shifted by 4–6 weeks over this time in all sub-regions. The annual average air temperature and SST have increased by 0.03°C yr–1 and 0.02°C yr–1, respectively, from 1960 till 2015. These data are compared with air temperatures measured in coastal meteorological stations and averaged over time intervals from 1 to 9 weeks. Statistically significant positive correlation exists between the SST and the average air temperature. This correlation is strongest for the averaging interval of 35 days.


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