Thermal Comfort Study Based on PMV-PPD in the Building of a Screening Center for COVID-19

Background: One way to achieve a standard heating, ventilating, and air conditioning system with maximum satisfaction is to use a thermal index to identify and determine the thermal comfort of people. In this study we intend to evaluate thermal comfort based on PMV-PPD (Predicted Mean Vote/Predicted Percentage Dissatisfied) model in workers of screening center for COVID-19. Methods: The study period was from March 1 to October 31, 2020. In this study, we used the ISO 7730 model to determinate PMV-PPD index. PMV index was used to determine thermal comfort at different scales in Birjand city with arid and hot climate. All data were analyzed using R software (version 3.3.0) and IBM SPSS statistics softwares. Results: The maximum and minimum recorded physical PMV values in the study period were observed in June as (2.09 ± 0.03) and March as (-1.27 ± 0.14), respectively. The amplitude of the thermal sense in the study period was varied between slightly cool (-1.5) and warm (+2.5). The PPD in spring was 40% which indicated slightly warm to hot condition. Conclusions: The October was the only month during the study in which thermal stress was in comfort or neutral thermal condition. Our results suggest that thermal comfort has dimensions and indices which are helpful in managing energy consumption.

Thermo Condition Determines the Uptake of Autumn and Winter Applied Nitrogen and Subsequent Utilization in Spring Tea (Camellia sinensis L.)

The effect of thermal condition on the uptake of autumn and winter applied N and its subsequent utilization in spring tea (Camellia sinensis) was investigated by applying 15N enriched urea as single or split applications between October and February in two commercial plantations at Xingyang of Henan province and Yongchuan of Chongqing with different thermal conditions. The proportion of N derived from 15N-labeled urea (Ndff%) in fibrous root and mature leaves 15 days after application at Xingyang and the Ndff% of mature leaves on the day of the first spring tea harvest at both sites were the highest in the single October application. The Ndff% of the following spring tea was also the highest in the single October application at both sites. The results showed that application of N fertilizer in October relative to other later months most significantly improves the accumulation of plant N reserves and consequently contributes more significantly to the early spring tea. Such timing effect was related to the thermal condition, i.e., the growing degree days (°C•d, T > 8 °C) between the dates of fertilization and harvest of young shoots, which represents the combining effect of the temperature and the residence time of N fertilizer in the soil.

Subglacial discharge controls seasonal variations in the thermal structure of a glacial lake in Patagonia

Water temperature in glacial lakes affects underwater melting and calving of glaciers terminating in lakes. Despite its importance, seasonal lake temperature variations are poorly understood because taking long-term measurements near the front of calving glaciers is challenging. To investigate the thermal structure and its seasonal variations, we performed year-around temperature and current measurement at depths of 58–392 m in Lago Grey, a 410-m-deep glacial lake in Patagonia. The measurement revealed critical impacts of subglacial discharge on the lake thermal condition. Water below a depth of ~100 m showed the coldest temperature in mid-summer, under the influence of glacial discharge, whereas temperature in the upper layer followed a seasonal variation of air temperature. The boundary of the lower and upper layers was controlled by the depth of a sill which blocks outflow of dense and cold glacial meltwater. Our data implies that subglacial discharge and bathymetry dictate mass loss and the retreat of lake-terminating glaciers. The cold lakewater hinders underwater melting and facilitates formation of a floating terminus.

Experimental study on ventilation using earth-to-air heat exchanger in Surabaya

The main problem related to thermal condition in Surabaya as a second-largest city in Indonesia is humid and hot. It is a typical condition of tropical climate. Ventilation in the hot day will bring warm and humid outdoor air into a room. It will increase the temperature of air in the room. One of some efforts to reduce the outdoor air temperature is using an earth to air heat exchanger (EAHE) to transfer heat from the air to the earth or ground. This paper will discuss about research done to study the effect of EAHE to a room temperature. The study used two model rooms which are similar and a model EAHE. One room called condition room will receive air flowing from the EAHE pipe and the other room is called the referent room. From the research, it is found that the air in condition room with EAHE is cooler in the daytime compared to the referent room. The temperature of the condition room with EAHE is more stable.

Research on Recognition and Location Method of Insulator in Infrared Image Based on Deep Learning

Infrared thermography technology is widely used in the thermal condition detection of insulators due to its advantages of non-contact, sensitive, online detection. To realize the automatic detection of the operating condition of insulators in complex environments, this paper proposes a method for the recognition and location of the insulator based on Region-based Fully Convolutional Networks (R-FCN). The model was trained and tested on the constructed insulator infrared data set, compared with the SSD model. The results showed that the R-FCN detecting insulators can not only accurately locate insulators, but have an AP (average precision) value as high as 89.2%. Therefore, the findings in this paper have verified that R-FCN has great advantages in the recognition and location of infrared images of insulators and has practical application value.