Estimates of EAST Operation Window with LHCD by Using a Core-SOL-Divertor Model

An experimental advanced superconducting tokamak （EAST） operation window with the lower hybrid current drive （LHCD） in H-mode is estimated by using a eore-SOL-divertor （C-S-D） model validated by the present EAST divertor experiments. The operation window consists of four limits including two usual limits, one of which is the maximum allowable heat load onto the divertor plate, and two additional limits associated with the LHCD. The predictive EAST operation window is not qualified to fulfill its mission for high input power. To extend the operation window, gas puffing and impurity seeding are presented as two effective methods. In addition, the effect of the LHCD current on the operation window is also discussed. Our numerical analysis results provide a reference for the safe operation of EAST experiments with LHCD in future.

Thermal Indices Influence on Occupants’ Window Opening Behaviours: A Case of Ibadan and Ogbomoso, Oyo State, Nigeria

Window opening operations are considered as one of the significant way of regulating indoor climate and maintaining thermal comfort in buildings,even when alternative active devices such as fans and air conditioners are available.This study investigates responses of occupants of the traditional core areas of Ibadan and Ogbomoso to thermal comfort conditions(thermal stress)through window opening behaviours.Climatic data of the two cities were subjected to Evans scale to predict their day and night thermal stress and questionnaires were administered to know how occupants respond to changing thermal conditions through window opening behaviours.Descriptive and inferential statistics were used in analysing the data.The study found the morning periods to be the most comfortable,the afternoon periods offer the most hot discomfort condition and cold discomfort is mostly experienced in the evening periods in both cities.Findings revealed that majority of occupants in both cities prefer to keep their windows opened in the morning and afternoon periods and an increase was observed in the numbers of occupants who prefer to keep their windows closed in the evening periods.This is an indication that building occupants in both cities actively respond to thermal stress using window opening operations.Results obtained from chi square analysis concluded that there is a significant relationship between occupants’window opening behaviour and thermal conditions at different periods of the day in both cities.Recommendations were given on how to improve on window opening systems in the future.

An action-based Markov chain modeling approach for predicting the window operating behavior in office spaces

Reliable energy and performance prediction for building design and planning is important for newly-designed or retrofitted buildings.Window operating behavior has an important influence on the ventilation and energy consumption of these buildings under different realistic scenarios.Therefore,quantitatively describing this behavior and constructing a prediction model are important.In this work,an action-based Markov chain modeling approach for predicting window operating behavior in office spaces was proposed.Two summer measurement data(2016 and 2018)were used to verify the accuracy and validity of the modeling approach.The opening rate,outdoor temperature,time distribution,and on-off curve were proposed as four inspection standards.This study also compared the prediction performance between the action-based Markov chain modeling approach with the state-based Markov chain modeling approach,which is the most popular modeling approach to model occupant window operating behavior.This study proved that the yearly variation of occupants’behavior performed a form of action that remained unchanged during a certain period.Meanwhile,the results also proved that the action-based Markov chain modeling approach can reflect the actual window operating behavior accurately within an open-plan office,which is a beneficial supplement for energy-consumption simulation software in a window-state prediction module.The state-based Markov chain modeling approach showed better stability and accuracy in terms of the opening rate,whereas the action-based Markov chain modeling approach showed good consistency with the measurement data in the on-off curves and in situations with little data.For the on-off curves,the accuracy of action-based modeling approach in the prediction of window open-state is 20%higher.

Comparative analysis of window operating behavior in three different open-plan offices in Nanjing

Research on the window operating behavior of offices is of great significance for reducing building energy con-sumption and improving indoor comfort.The open-plan office is a common office form that involves a large number of people and a complex staffcomposition.The window operating behaviors in open-plan offices are also random and various.This study took three open-plan offices with different situations(area,office type,staffcomposition,etc.)as an example,which provides a new perspective on how people behave differently when opening or closing windows.The window operating behaviors in two typical seasons(summer and transition seasons)were recorded and analyzed.The occupants’schedules and influencing factors of window operating behavior were investigated by questionnaire surveys.In addition,the indoor environmental parameters,occu-pancy situation,and on-offstatuses of windows and air conditioning were acquired through field measurements.Furthermore,the differences in window operating behaviors in the three open-plan offices were compared from the perspectives of influencing factors,duration of the window on-offstatuses,and cause of window control ac-tions,among others.In addition,Spearman Correlation Coefficient was used to analyze the ranks of the candidate motivations for window operating behaviors.The preliminary results show that influenced by the personnel com-position,type of air conditioner and adjustable degree of windows,the window operating behaviors of different office buildings have larger discrepancies than that in the same building.However,there were some common characteristics in the window regulation behaviors of the three open-plan offices:they were generally influenced by the coupling of environmental factors,schedule factors,and equipment factors.This study reveals that when expand the research object from a single building to multiple buildings,more difficulties and challenges would be involved into behavior research.