Temperature Control Response Study of Data Centers Based on Gappy Pod DOI
Xin Wang,

Zhiyin Cao,

Yuhong Liu

и другие.

Опубликована: Янв. 1, 2023

As the size and load of data centers continue to grow, how ensure stable operation center equipment has become an important issue. Therefore, this study developed a “smart box” system for temperature prediction control response. A test bench is also constructed verify reliability system. The Results show that in six randomly selected working conditions, average errors predicted temperatures ranged from 1.17% 2.1%. Furthermore, able reduce time required lower safety threshold by 10% effectively fluctuation range compared with fixed air volume through dynamic ventilation control. result, it can improve stability equipment. In future, expected be widely used field centers.

Язык: Английский

Computer vision to advance the sensing and control of built environment towards occupant-centric sustainable development: A critical review DOI
Junqi Wang, Lanfei Jiang,

Hanhui Yu

и другие.

Renewable and Sustainable Energy Reviews, Год журнала: 2023, Номер 192, С. 114165 - 114165

Опубликована: Дек. 23, 2023

Язык: Английский

Процитировано

28

Zonal demand-controlled ventilation strategy to minimize infection probability and energy consumption: A coordinated control based on occupant detection DOI
Chen Ren,

Hanhui Yu,

Junqi Wang

и другие.

Environmental Pollution, Год журнала: 2024, Номер 345, С. 123550 - 123550

Опубликована: Фев. 12, 2024

Язык: Английский

Процитировано

9

Multi-objective ventilation optimization for indoor air quality, thermal comfort, and energy conservation in the post-pandemic era: A case study for a moving elevator DOI
Dan Mei, Xinwen Zhang, Chenxia Wang

и другие.

Physics of Fluids, Год журнала: 2024, Номер 36(6)

Опубликована: Июнь 1, 2024

Cases of respiratory disease transmission in enclosed elevators have been reported frequently. In the post-pandemic era, order to mitigate spread diseases moving elevators, a multi-objective genetic optimization method based on response surface model is used optimize elevator ventilation. The ventilation parameters were optimized for three objectives: reducing carbon dioxide concentration, maintaining human thermal comfort, and achieving energy conservation. First, established using computational fluid dynamics Kriging correlate design variables (air supply velocity x, y, z directions air temperature) with output function (CO2 average temperature, velocity). Subsequently, Pareto optimal solution set was obtained by employing algorithm. Finally, velocity, angle, temperature both peak periods traffic (13 passengers) other situations (4 when up down, which satisfy objectives health,

Язык: Английский

Процитировано

4

A Dynamic Cluster-Aware Modeling Approach for Distribution Networks Based on New Energy Intelligent Individuals DOI
Ling Liang,

Yuan Ji,

Jianwei Ma

и другие.

Lecture notes in electrical engineering, Год журнала: 2025, Номер unknown, С. 140 - 146

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Numerical investigation and dynamics of pollutant dispersion in underground restroom ventilation DOI

Xianzhou Dong,

Zhuoru Chen,

Yongqiang Luo

и другие.

Journal of Building Engineering, Год журнала: 2024, Номер 88, С. 109132 - 109132

Опубликована: Март 26, 2024

Язык: Английский

Процитировано

2

Application of Mixed-Mode Ventilation to Enhance Indoor Air Quality and Energy Efficiency in School Buildings DOI Creative Commons

Christopher Otoo,

Tao Lü, Xiaoshu Lü

и другие.

Energies, Год журнала: 2024, Номер 17(23), С. 6097 - 6097

Опубликована: Дек. 4, 2024

Indoor air quality and energy efficiency are instrumental aspects of school facility design construction, as they directly affect the physical well-being, comfort, academic output both pupils staff. The challenge balancing need for adequate ventilation to enhance indoor with goal reducing consumption has long been a topic debate. implementation mixed-mode systems automated controls presents promising solution address this issue. However, comprehensive literature review on subject is still missing. To gap, examines potential application attaining improved savings without compromising thermal comfort in educational environments. Mixed-mode systems, which combine natural mechanical ventilation, provide versatility alternate between or merge methods based real-time outdoor environmental conditions. By analyzing empirical studies, case theoretical models, investigates efficacy minimizing use enhancing quality. Essential elements such operable windows, sensors, sophisticated control technologies evaluated illustrate how dynamically optimize sustain comfortable healthy climates. This paper further addresses challenges linked including complexities necessity climate-adaptive strategies. findings suggest that can considerably lower heating, conditioning usage, ranging from 20% 60% across various climate zones, while also advanced data-driven In conclusion, offer approach buildings achieve effective sacrificing environment

Язык: Английский

Процитировано

1

Temperature Control Response Study of Data Centers Based on Gappy Pod DOI
Xin Wang,

Zhiyin Cao,

Yuhong Liu

и другие.

Опубликована: Янв. 1, 2023

As the size and load of data centers continue to grow, how ensure stable operation center equipment has become an important issue. Therefore, this study developed a “smart box” system for temperature prediction control response. A test bench is also constructed verify reliability system. The Results show that in six randomly selected working conditions, average errors predicted temperatures ranged from 1.17% 2.1%. Furthermore, able reduce time required lower safety threshold by 10% effectively fluctuation range compared with fixed air volume through dynamic ventilation control. result, it can improve stability equipment. In future, expected be widely used field centers.

Язык: Английский

Процитировано

0

Temperature Control Response Study of Data Centers Based on Gappy Pod DOI
Xin Wang,

Zhiyin Cao,

Yuhong Liu

и другие.

Опубликована: Янв. 1, 2023

As the size and load of data centers continue to grow, how ensure stable operation center equipment has become an important issue. Therefore, this study developed a “smart box” system for temperature prediction control response. A test bench is also constructed verify reliability system. The Results show that in six randomly selected working conditions, average errors predicted temperatures ranged from 1.17% 2.1%. Furthermore, able reduce time required lower safety threshold by 10% effectively fluctuation range compared with fixed air volume through dynamic ventilation control. result, it can improve stability equipment. In future, expected be widely used field centers.

Язык: Английский

Процитировано

0