船用HVAC风管减隔振工艺措施试验及分析

某船典型环境下,HVAC风管在管内风速风量的激励下,产生明显振动。采用安装橡胶减振元件及消音装置等措施后,HVAC风管振动下降最大达10%以上。本试验研究风管安装相关措施对管路振动的影响,发现橡胶垫的厚度、硬度等材料参数对风管路振动传递影响呈复杂关系。其中,橡胶垫的减隔振效果随着厚度的增加不断提升,最终趋于稳定效果,并且软管径向安装偏差对管路各方向振动亦有较大影响,为该型船减隔振措施提供一定参考。

HVAC(Heating,Ventilation and Air Conditioning,空气调节系统)现场设备——市场份额分析、行业趋势与统计

2024年HVAC(Heating,Ventilation and Air Conditioning,空气调节系统)现场设备市场规模预计为211.3亿美元,预计到2029年将达到287.2亿美元,在预测期内(2024-2029年)复合年增长率为6.3%。新冠肺炎疫情对暖通空调行业产生了重大影响,由于封锁限制和企业避免投资新设备,全球许多建设项目被迫暂停。

Entropy Assessment on Environmental Influence of Condense Heat in Recovery System in Air-Conditioning Refrigerating Machine

This paper presented an entropy evaluation method for the influences of condense heat recovery system on the environment.Aiming at the damage of the condense heat to the environment,an entropy of resource loss and an emission entropy from the condense heat recovery system in the air conditioning refrigerating machine were introduced.For the evaluation of the entropies,we developed a new algorithm for the parameter identification,called the composite influence coefficient,based on the Least Squares Support Vector Machine method.By simulation,the numerical experiments shows that the Least Squares Support Vector Machine method is one of the powerful methods for the parameter identification to compute the damage entropy of the condense heat,with the largest training error being-0.025(the relative error being-3.56%),and the biggest test error being 0.015(the relative error being 2.5%).

Impact of summer office set air-conditioning temperature on energy consumption and thermal comfort

To explore the relationship between summer office set air-conditioning temperature and energy consumption related to air conditioning use to provide human thermal comfort,a comparison experiment was conducted in three similar offices at temperatures of 24,26 and 28 ℃ respectively. A thermal comfort questionnaire survey was conducted. It is demonstrated that air-conditioner energy consumption at the set temperature of 28 ℃ is 113% and 271% lower than at 26 ℃ and 24 ℃,respectively. A linear relationship exists between air-conditioner energy consumption and the indoor and outdoor temperature difference. When comfortably dressed,over 80% of research participants accept the set temperature of 28 ℃. The regression analysis leads to a neutral temperature of 26.2 ℃ and an acceptable temperature of 28.2 ℃ for over 80% of the research participants subjects,indicating that the current 26 ℃ set temperature for offices in summer,required by Chinese General Office of the State Council,can be increased to 28 ℃. Moreover,analysis of predicted mean vote(PMV) index shows that a set temperature of 27 ℃,not 26 ℃,is sufficiently comfortable for office staff wearing long-sleeve shirts,long pants and leather shoes.

Selection of Weather Parameters for Air-Conditioning System Design for Buildings with Long Thermal Lag

Two building factors-a longer thermal lag of more than one hour for building envelops and a lag of indoor radiation to convert into cooling load-have impact on the instantaneous heat input and instantaneous cooling load.So the two factors should be taken into account when selecting the weather parameters for air-conditioning system design.This paper developed a new statistic method for the rational selection of coincident solar irradiance,dry-bulb and wet-bulb temperatures.The method was applied to historic weather records of 25 years in Hong Kong to generate coincident design weather data.And the results show that traditional design solar irradiance,dry-bulb and wet-bulb temperatures may be significantly overestimated in many conditions,and the design weather data for the three different constructions is not kept constant.

The Experiment and Simulation of Solid Desiccant Dehumidification for Air-Conditioning System in a Tropical Humid Climate

The aim of this research was to study and design a solid desiccant dehumidification system suitable for tropical climate to reduce the latent load of air-conditioning system and improve the thermal comfort. Different dehumidifiers such as desiccant column and desiccant wheel were investigated. The ANSYS and TRASYS software were used to predict the results of dehumidifiers and the desiccant cooling systems, respectively. The desiccant bed contained approximately 15 kg of silica-gel, with 3 mm average diameter. Results indicated that the pressure drop and the adsorption rate of desiccant column are usually higher than those of the desiccant wheel. The feasible and practical adsorption rate of desiccant wheel was 0.102 kgw/h at air flow rate 1.0 kg/min, regenerated air temperature of 55?C and at a wheel speed of 2.5 rpm. The humidity ratio of conditioning space and cooling load of split-type air conditioner was decreased to 0.002 kgw/kgda (14%) and 0.71 kWth (19.26%), respectively. Consequently, the thermal comfort was improved from 0.5 PMV (10.12% PPD) to 0.3 PMV (7.04% PPD).

An Energy-Saving Control Strategy on Central Air-Conditioning System

An energy-saving control strategy based on predictive control for central air-conditioning systems is proposed in this paper. The cold load model is developed to describe the dynamic characteristics of temperature control systems, and then parameters in the cold load model and in the central air-conditioning system model are estimated. Generalized predictive control (GPC) is used to establish an optimization model to minimize the consumption of energy and the control error of temperature. The simulated annealing (SA) algorithm, combined with quadratic programming, is adopted to solve the optimal problem. Contrasted with the simulation of traditional PID control, the results prove the effectiveness of this proposed strategy.

Application of Fuzzy Comprehensive Evaluation to Air-conditioning Competitive Power Analysis

As the conceptual design of air-conditioning is done using the theory of Quality Function Deployment (QFD),cus- tomer requirements should be understood and the product competitive power be analyzed as exactly as possible for new product de- signing.Lots of information in the process of this research is fuzzy and uncertain,but traditional QFD can not deal with it well. Fuzzy theory can solve the problem.So a fuzzy model for analyzing product competitive power is formulated in this paper to im- prove traditional QFD,after that it is applied to analyze air-conditioning competitive power.When air-conditioning competitive power is analyzed using this model,firstly the importance weight of the customer requirements o fair-conditioning is determined us- ing the Analytic Hierarchy Process (AHP) weighting process,then air-conditloning competitive power is evaluated using fuzzy comprehensive evaluation.It is proved that the model is feasible and has good applicability.

Application of Dual Throttling Air-Conditioning System to Explosion-Proof Frequency Converter

An explosion-proof dual throttling air-conditioning system was put forward to solve the heat dissipation and internal dewing problems of explosion-proof frequency converter in the underground coal mine. This study investigated the feasibility and benefits of explosion-proof dual throttling cooling and dehumidification air-conditioning system applied to the explosion-proof frequency converter. The physical model of dual throttling air-conditioning system was established and its performance parameter was described by mathematical method. The design calculation of the system has also been done. The experimental result showed that the system reached the steady state at the refrigeration mode after running 45 min, and the maximum internal temperature of the flame-proof cavity was 31.0 ℃. The system reached the steady state at the dehumidification mode after running 37 min. The maximum internal relative humidity and temperature of the flame-proof cavity were 33.4% and 36.3 ℃, respectively. Therefore, the proposed system had excellent ability of heat dissipation and avoided internal dewing. Compared with water cooling system, it was more energy-saving and economical. The airflow field of dual throttling air-conditioning system was also studied by CFD simulation. It was found that the result of CFD numerical simulation was highly consistent with the experimental data.

Simulation of Artificial Intelligence for Automotive Air-conditioning System

The artificial intelligence is applied to the simulation of the automotive air-conditioning system ( AACS )According to the system's characteristics a model of AACS, based on neural network, is developed. Different control methods of AACS are discussed through simulation based on this model. The result shows that the neural- fuzzy control is the best one compared with the on-off control and conventional fuzzy control method.It can make the compartment's temperature descend rapidly to the designed temperature and the fluctuation is small.

Research on the Arrangement of Dew Point Temperature Detectors of Capillary Plane Radiation Air-Conditioning

Based on analysis of the reason and process of condensation on ceiling radiant cooling panels, two kinds of arrangement of detectors are put forward. The physical model is established, the results show that detectors are arranged as the form of triangle is more suitable. It can not only satisfy the use requirement but also it is economical and practical. Finally we can conclude that the inlet water temperature 0.5°C higher than dew point temperature is safe and reliable.

Analysis of Solar Direct-Driven Organic Rankine Cycle Powered Vapor Compression Cooling System Combined with Electric Motor for Office Building Air-Conditioning

Solar energy powered organic Rankine cycle vapor compression cycle(ORC-VCC)is a good alternative to convert solar heat into a cooling effect.In this study,an ORC-VCC system driven by solar energy combined with electric motor is proposed to ensure smooth operation under the conditions that solar radiation is unstable and discontinuous,and an office building located in Guangzhou,China is selected as a case study.The results show that beam solar radiation and generation temperature have considerable effects on the system performance.There is an optimal generation temperature at which the system achieves optimum performance.Also,as a key indicator,the cooling power per square meter collector should be considered in the hybrid solar cooling system in design process.Compared to the vapor compression cooling system,the hybrid cooling system can save almost 68.23%of electricity consumption.

HVAC Optimal Control Based on the Sensitivity Analysis:An Improved SA Combination Method Based on a Neural Network

Aiming at optimizing the energy consumption of HVAC,an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis(SA),named the sensitivity analysis combination method(SAC).Based on the SA,neural network and the related settings about energy conservation of HVAC systems,such as cooling water temperature,chilled water temperature and supply air temperature,were optimized.Moreover,based on the data of the existing HVAC system,various optimal control methods ofHVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS.The results show that the proposed SA combination method can reduce significant computational load while maintaining an equivalent energy performance compared with traditional optimal control methods.

MAQMC:Multi-Agent Deep Q-Network for Multi-Zone Residential HVAC Control

The optimization of multi-zone residential heating,ventilation,and air conditioning(HVAC)control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads.Deep reinforcement learning(DRL)methods have recently been proposed to address the HVAC control problem.However,the application of single-agent DRL formulti-zone residential HVAC controlmay lead to non-convergence or slow convergence.In this paper,we propose MAQMC(Multi-Agent deep Q-network for multi-zone residential HVAC Control)to address this challenge with the goal of minimizing energy consumption while maintaining occupants’thermal comfort.MAQMC is divided into MAQMC2(MAQMC with two agents:one agent controls the temperature of each zone,and the other agent controls the humidity of each zone)and MAQMC3(MAQMC with three agents:three agents control the temperature and humidity of three zones,respectively).The experimental results showthatMAQMC3 can reduce energy consumption by 6.27%andMAQMC2 by 3.73%compared with the fixed point;compared with the rule-based,MAQMC3 andMAQMC2 respectively can reduce 61.89%and 59.07%comfort violation.In addition,experiments with different regional weather data demonstrate that the well-trained MAQMC RL agents have the robustness and adaptability to unknown environments.

Development of a Bias Compensating Q-Learning Controller for a Multi-Zone HVAC Facility

We present the development of a bias compensating reinforcement learning(RL)algorithm that optimizes thermal comfort(by minimizing tracking error)and control utilization(by penalizing setpoint deviations)in a multi-zone heating,ventilation,and air-conditioning(HVAC)lab facility subject to unmeasurable disturbances and unknown dynamics.It is shown that the presence of unmeasurable disturbance results in an inconsistent learning equation in traditional RL controllers leading to parameter estimation bias(even with integral action support),and in the extreme case,the divergence of the learning algorithm.We demonstrate this issue by applying the popular Q-learning algorithm to linear quadratic regulation(LQR)of a multi-zone HVAC environment and showing that,even with integral support,the algorithm exhibits bias issue during the learning phase when the HVAC disturbance is unmeasurable due to unknown heat gains,occupancy variations,light sources,and outside weather changes.To address this difficulty,we present a bias compensating learning equation that learns a lumped bias term as a result of disturbances(and possibly other sources)in conjunction with the optimal control parameters.Experimental results show that the proposed scheme not only recovers the bias-free optimal control parameters but it does so without explicitly learning the dynamic model or estimating the disturbances,demonstrating the effectiveness of the algorithm in addressing the above challenges.

基于先验知识的HVAC系统深度Q网络控制方法

强化学习方法在近年来被逐渐尝试应用于工程控制之中,并且展示出其强大的控制能力和潜力。强化学习算法虽然具有较好的控制性能,但是其控制策略的收敛需要建立在一段时间后的训练上,而这段时间在工程应用上可能会造成一些浪费。为了解决这一问题,提出了基于先验知识的DQN对暖通空调(HVAC)系统中的冷却水系统进行控制,将先验知识引入DQN算法的前期训练中,以减少训练时间,加速收敛,节约成本。基于先验知识的DQN算法不仅能够对系统进行有效的控制,并且能够比DQN更早地实现节能。

极地LNG模块E-House HVAC系统设计

暖通空调(Heating,Ventilation and Air Conditioning,HVAC)系统是液化天然气(Liquefied Natural Gas,LNG)模块E-house的重要支持系统,也是维持LNG模块持续运行的关键。位于北极圈内的俄罗斯LNG开采、处理、运输模块,需要承受超低温极端恶劣工况,满足严格的防火防爆,及诸多俄罗斯本地法规要求。因此,通常的HVAC系统设计已无法满足其使用要求,亟待设计一套适用于极地LNG模块的HVAC系统:在系统计算上充分考虑极端运行环境因素,对比传统传热与逐时分析程序(Hourly Analysis Program,HAP)计算方法,介绍散热量选择和风量计算方法。此外,解析俄罗斯本地法规的特殊要求并提供相应的解决方案。研究成果可为极地LNG模块E-house的HVAC系统设计提供一定参考。

An Approach to Optimize Multi-family Residence HVAC Systems Using Digitalization

As mentioned by National Geographic(2017),70%of world’s population is expected to live in large apartment buildings by 2050.Today,buildings in cities generate 30%of world’s greenhouse gas emission or GHG(National Geographic,2017).Major urban centers are committed to reducing greenhouse gases by 80%by 2050(IEA,2021).However,achieving such goals in rental properties is not easy.Landlords are hesitant to use high-efficiency technologies because,typically,tenants pay the utilities bill.However,that situation is rapidly changing.For example,New York City like other US cities,is considering a carbon cap on all large buildings(Local Law 97,2019).That means landlords will pay a carbon penalty if the building’s carbon footprint exceeds certain threshold no matter who uses that carbon.The Pacific Northwest National Laboratory(PNNL)has received funds from DOE(US Department of Energy)with the collaboration of a commercial partner to address emerging energy efficiency market opportunity in multi-family or rental housing as discussed above.It has partnered with a large national real estate owner in order to test a novel energy optimization method at a rental property in Tempe,Arizona.By using a seamless-integrated method of acquiring building’s operating data,the optimization approach essentially resets setpoints of different energy consuming equipment such as chillers,boilers,pumps,and fans.Data-driven optimization approach is pragmatic and easily transferrable to other buildings.The authors shall share the problem background,technical approach,and preliminary results.

浅谈HVAC系统对住院患者健康的影响

论述了医院建筑供暖、通风和空调系统(HVAC)相关的室内环境参数对住院患者的影响。医院作为综合性的大型医疗场所,存在多种疾病源并存的风险,同时易感人群高度集中。对于空气暴露下患者的治疗及预后情况,感染源的风险防范,以及气候条件对于患者的不利影响都是医院建筑功能使用过程中面临的十分严峻的问题。综合工程项目经验,建筑HVAC系统的应用是一种对医疗环境很有效的适应措施,可以减轻环境风险以及气候变化对卫生医疗保健系统的不利影响。

Preliminary Research on Water Supply,Drainage,and HVAC Equipment in Shanghai Historic Buildings During the Northern Warlord Period

During the Northern Warlord Period(1912–1928),the construction industry in Shanghai underwent robust development.As an integral element of buildings,equipment served both functional purposes and stood witness to the evolution of the economy and society,thus earning its place as part of the architectural heritage.However,due to various reasons,there are many loopholes in the protection of these building equipment.This paper examines the development of building equipment in Shanghai during the Northern Warlord Period,using water supply,drainage,and heating,ventilation,and air conditioning(HVAC)systems as examples.Through historical context analysis,it summarizes this development from a social-spatial perspective,infers the reasons behind it,and analyzes the importance of preserving such equipment,considering both past and present viewpoints.In this research,the importance of protecting historical building equipment is emphasized,which aims to give people a deeper understanding of their cultural value,and suggests that scholars conduct more practical research on their protection.