A Novel Aircraft Air Conditioning System with a Sterilization Unit by Ultra-High-Temperature Air Stream

An aircraft cabin is a narrow,closed-space environment.To keep the air quality in cabin healthy for passengers,especially during an epidemic such as SARS-CoV-2(or 2019-nCoV)in 2020,a novel aircraft air conditioning system,called the ultra-high-temperature instantaneous sterilization air conditioning system(UHTACS),is proposed.Based on the proposed system,a simulation of the UHT-ACS is analysed in various flight states.In the UHT-ACS,the mixing air temperature of return and bleed air can reach temperature up to 148.8°C,which is high enough to kill bacilli and viruses in 2一8 s.The supply air temperature of the UHT-ACS in a mixing cavity is about 12 C in cooling mode both on the ground and in the air.The supply air temperature is about 42 C in heating mode.Compared with the air conditioning systems(ACS)of traditional aircraft the supply air temperatures of the UHT-ACS in the mixing cavity are in good agreement with those of a traditional ACS with 60%fresh air and 40%return air.Furthermore the air temperature at the turbine outlet of the UHT-ACS is higher than that of a traditional ACS which will help to reduce the risk of icing at the outlet.Therefore the UHT-ACS can operate normally in various flight states.

Analyses of an air conditioning system with entropy generation minimization and entransy theory

In this paper,based on the generalized heat transfer law,an air conditioning system is analyzed with the entropy generation minimization and the entransy theory.Taking the coefficient of performance（denoted as COP） and heat flow rate Qout which is released into the room as the optimization objectives,we discuss the applicabilities of the entropy generation minimization and entransy theory to the optimizations.Five numerical cases are presented.Combining the numerical results and theoretical analyses,we can conclude that the optimization applicabilities of the two theories are conditional.If Qout is the optimization objective,larger entransy increase rate always leads to larger Qout,while smaller entropy generation rate does not.If we take COP as the optimization objective,neither the entropy generation minimization nor the concept of entransy increase is always applicable.Furthermore,we find that the concept of entransy dissipation is not applicable for the discussed cases.

Effect of Two Kinds of Similarity Factors on Principal Component Analysis Fault Detection in Air Conditioning Systems

Screening similar historical fault-free candidate data would greatly affect the effectiveness of fault detection results based on principal component analysis(PCA).In order to find out the candidate data,this study compares unweighted and weighted similarity factors(SFs),which measure the similarity of the principal component subspace corresponding to the first k main components of two datasets.The fault detection employs the principal component subspace corresponding to the current measured data and the historical fault-free data.From the historical fault-free database,the load parameters are employed to locate the candidate data similar to the current operating data.Fault detection method for air conditioning systems is based on principal component.The results show that the weighted principal component SF can improve the effects of the fault-free detection and the fault detection.Compared with the unweighted SF,the average fault-free detection rate of the weighted SF is 17.33%higher than that of the unweighted,and the average fault detection rate is 7.51%higher than unweighted.

Influence of Three Sizes of Sliding Windows on Principle Component Analysis Fault Detection of Air Conditioning Systems

Principal component analysis(PCA)has been already employed for fault detection of air conditioning systems.The sliding window,which is composed of some parameters satisfying with thermal load balance,can select the target historical fault-free reference data as the template which is similar to the current snapshot data.The size of sliding window is usually given according to empirical values,while the influence of different sizes of sliding windows on fault detection of an air conditioning system is not further studied.The air conditioning system is a dynamic response process,and the operating parameters change with the change of the load,while the response of the controller is delayed.In a variable air volume(VAV)air conditioning system controlled by the total air volume method,in order to ensure sufficient response time,30 data points are selected first,and then their multiples are selected.Three different sizes of sliding windows with 30,60 and 90 data points are applied to compare the fault detection effect in this paper.The results show that if the size of the sliding window is 60 data points,the average fault-free detection ratio is 80.17%in fault-free testing days,and the average fault detection ratio is 88.47%in faulty testing days.

System design and analysis of the trans-critical carbon-dioxide automotive air-conditioning system

As an environmentally harmless and feasible alternate refrigerant, CO 2 has attracted worldwide attention, especially in the area of automobile air conditioning (AAC). The thermal property of CO 2 and its trans critical refrigeration cycle is very different from that of the traditional CFC or HCFC system. The detailed process of CO 2 system thermal cycle design and optimization is described in this paper. System prototype and performance test bench were developed to analyze the performance of the CO 2 AAC system.

Energy Efficient Air Conditioning System Using Geothermal Cooling-Solar Heating in Gujarat, India

It is well known that one unit of electrical energy saved is equal to more than two units produced. One way of economizing the power is utilization of energy efficient systems at all locations. In the present study, the air conditioning system is analysed and an innovative way is suggested. We use natural low temperature of shallow sub surface (1 - 3 m) of the earth—geothermal cooling system. It is known that majority of the households and the apartment complexes in India have two tanks for water storage. One is the underground water sump and the other is the overhead water tank. In our study, we use these two water storage systems for space cooling during summer and also for heating during winter. The main aim of our paper is air-conditioning of the space in an economic way to save electricity. It is based on a simple idea of transferring the low temperature from underground water sump to the room in the house using water as a mode of transport. Since India is a tropical country located at low latitude, most of the year, the air temperature is high and demands space cooling. However, for a couple of months during severe winter months (Dec.-Jan.) at Ahmedabad, heating of the space is required. For heating the space, we suggest to use the well-known solar water heater. Effective use of heat exchanger is shown through computation, modelling schemes and lab experiment. We recommend geothermal cooling for 10 months in a year and solar hot water system during 2 months of winter. It is observed that the ambient air temperature of 35°C - 40°C in the room can be brought down to 26°C without much consumption of electricity. In a similar manner, the room temperature at night (13°C) during winter in Ahmedabad can be increased to 27°C through circulation of water from solar water heater in the heat exchanger.

Method for acquiring part load distribution coefficient of air conditioning system

This paper presents a method to acquire runtime distribution ratio of building air conditioning system under part load condition (part load coefficient of system) through practical energy consumption data. By utilizing monthly energy consumption data of the entire year as the analysis object,this paper identifies data distribution,verifies distribution characteristics and analyzes distribution probability density for the issue of running time distribution ratio of air conditioning system in part load zones in the whole operation period,thus providing a basic calculation basis for an overall analysis of energy efficiency of air conditioning system. In view of the general survey of public building energy consumption carried by the government of Chongqing,this paper takes the governmental office building as an example,the part load ratio coefficient corresponding to practical running of air conditioning system of governmental office building in Chongqing is obtained by utilizing the above probability analysis and the solving method of probability density function. By utilizing the ratio coefficient obtained using this method,the part load coefficient with any running ratio of air conditioning system can be obtained according to the requirement of analysis,which can be used in any load ratio for analyzing running energy efficiency of air conditioning system.

Applicability of sewage heat pump air-conditioning system

A sewage heat pump system and its application based on a project in Chongqing,China,were discussed. Based on the sewage conditions,a feasibility analysis of the sewage heat pump air conditioning system was conducted. The theoretical and quantitative calculations indicate that sewage flux in the city sewage main pipe in the project can satisfy heat exchange requirements,and taking water from the pipes has relatively small influence on the pipe net in summer and winter. The sewage heat pump air-conditioning system can save 21.5% operating cost in one year,which is energy efficient and environmentally friendly.

A Case Study:Distribution of Bacterial and Fungal Aerosols in Air-Conditioning Systems in Shaanxi History Museum

In order to investigate the bacteria and fungi aerosol characteristic distribution in HVAC-system and its components at Shaanxi History Museum.Measurements were performed to probe the bacteria and fungi aerosol in HVAC systems,located at Xi'an city,China.The results showed that there was fungi growth inside the ventilation ducts,fungi contamination was worse than bacteria,and both of them were distributed into occupied space with the air supply ducts.The dominating genera of fungi was found to be Penicillium spp.and Aspergillus spp.,which was respectively 46.1% and 20.7% in settling fungi,and the dominating genera of fungi in dust were Cladosporium spp.and Penicillium spp.,which was 41.8% and 30.1% respectively.It suggests that available measures to improve and control the performance of HVAC-systems such as the maintenance,management and cleaning should be taken to prevent this pollution and to develop strategies to keep this pollution away.

Evaporative Condensers in Comfortable Air Conditioning System

The operating theory of an evaporative condenser was expatiated.The difference between an evaporative condensing refrigeration system and a general refrigeration system was analyzed.Compared with the air-cooled and the water-cooled,the virtues of energy-conservation and water-conservation of evaporative condensers were analyzed.Some questions existing in the application of evaporative condensers were pointed out,the corresponding solving methods were analyzed accordingly,and the development trend of evaporative condensing technique in mechanical refrigeration system field and the applied foreground of evaporative condensers in comfortable air conditioning were prospected.

Acoustic Conditioning System Development and Conditioning Experiments on Black Seabreams in the Xiangshan Bay Sea Ranch

Attracting released hatchery-reared fish to designated areas during the growth process is vital to realize the objectives of sea ranching. Based on the bottom artificial reefs and surface kelp culture facilities in the Xiangshan Bay sea ranch, we proposed systematic techniques related to acoustic conditioning of the black seabream(Sparus macrocephalus). Experiments conducted in 12 m × 10 m × 1.6 m ponds on Xixuan Island showed that black seabream was positively sensitive to 500–600 Hz periodic signals. Conditioned responses were apparent after 8 d. Two to three days were required for recovery of the memory of a conditioned response after a 20-day interval. According to the practical application requirements in the open sea, unattended acoustic conditioning equipment was developed. The ranching equipment was used in 12 m × 12 m × 2.5 m cages, and the behavior of black seabream juveniles was successfully guided after 7 days. Of the 16000 released fish, 82.5% of them were conditioned with a flexible grading net. To avoid inducing a stress response, the juveniles were released into the sea ranch in situ from the net cage. The acoustic conditioning equipments were moved into the open sea and the aggregation phenomenon of the released fish was observed when the sound was played. After 6 months of investigation and based on Sr+ marking, only one acoustically conditioned fish was found outside the 3.5-km^2 sea ranch area, thereby reached the goal of guiding activity. The practical effect in the Xiangshan Bay sea ranch showed the validity of the acoustic conditioning system, which may contribute to improve the operation of the sea ranches in the East China Sea.

Metal hydride work pair development and its application on automobile air conditioning systems

Aiming at developing exhaust gas driving automobile air conditioning systems, a hydride pair LaNi4.61Mn0.26A10.13/ La0.6Y0.4Ni4.8Mn0.2 was developed working at 393-473 K/293-323 K/263-273 K. Property tests showed that both alloys have flat plateau slopes and small hystereses; system theoretical coefficient of performance （COP） is 0.711. Based on this work pair, a function proving automobile metal hydride refrigeration system was constructed. The equivalent thermal conductivities of the activated reaction beds were merely 1.1-1.6 W/（m-K）, which had not met practical requirement. Intermittent refrigeration cycles were achieved and the average cooling power was 84.6 W at 423 K/303 K/273 K with COP being 0.26. By altering cycling parameters, experiment data showed that cooling power and system COP increase with the growth of heat source temperature as well as pre-heating and regeneration time while decrease with heat sink temperature increment. This study confirms the feasibility of automobile metal hydride refrigeration systems, while heat transfer properties of reaction beds still need to be improved for better performance.

Visual Interactive Computer Package for Air Conditioning System Design: Case of the International Conference Centre, University of Ibadan, Nigeria

Air conditioning design has become an interesting aspect of human life with the aim of seeking environmental comfort for indoor spaces. Analytical work involves in the design of air-conditioning system is often time consuming and laborious. This work therefore aims at developing a visual interactive computer package for the design of air conditioning system using the international conference centre, University of Ibadan, Nigeria as a case study. Procedures for calculating heat gain through various building components were discussed in detail. Cooling load analysis was carried out using standard cooling load equations obtained from the American Society of Heating, Refrigeration and Air conditioning Engineers (ASHRAE) handbook. A computer program was developed using java programming language to compute the total cooling load in the building. The result from the computer program was obtained within a very short period of time when compared with that of the manual one. The cooling load of the building obtained was 3,194,414 btu/hr;a visual interactive computer package for the design of air conditioning system has been developed and tested positively;hence can be used to design air conditioning system for any building.

Energy Efficient Hospitals Air Conditioning Systems

Energy Efficiency and Indoor Air Quality in the healthcare applications and particularly in surgical operating theatres are important features in modernized designs. The various reasons for deviation from obtaining optimum IAQ and energy efficient buildings are listed. The air conditioning systems serving the operating rooms require careful design to minimize the concentration of airborne organisms. Numerical approach is an appropriate tool to be utilized to adequately identify the airflow patterns temperatures and relative humidity distributions and hence energy efficient designs.

Performance of Solar-Powered Air Conditioning System under AlMadinah AlMunawwarah Climatic Conditions

Nowadays, solar-powered air conditioning has witnessed an increased progress because air conditioning system is almost a must in every building in Saudi Arabia where the outside temperature in summer is higher than 42&degC. AlMadinah AlMunawwarah is one of the important holy places in the world, and therefore, this paper investigates the design and performance of solar-powered air conditioning system integrated with photovoltaic (PV) system which consists of PV panels, solar charger, inverter and batteries. This air conditioning system can be used in non-electrified areas near AlMadinah where the cost of electricity for this area is very high. The first step in this project is the cooling load calculations for the selected space that will be cooled and it was found about 1 ton refrigeration (3.52 kW). Based on this cooling load, the photovoltaic (PV) system has been estimated and built with the necessary connections. Data logging system has been used to measure the temperatures at the main components in the cycle like compressor inlet and outlet as well as evaporator and condenser. The input powers for the system as well as the coefficient of performance (COP) for the system under AlMadinah climatic conditions were measured along the day. The coefficient of performance varies from 2.16 to 4.22 for the system and these results compared with the conventional system performance with a good agreement.

Modelling, Transient Simulation and Economic Analysis of Solar Thermal Based Air Conditioning System in Gujarat

Commercial building sector accounts for 8% of the total electricity consumption in India. Cooling activities (HVAC) in commercial buildings consume 55% of the total energy utilized. Consequently, CO2 emissions from conventional buildings in India were estimated to be 98 metric tonnes of CO2 per million ft2 in 2014. Solar thermal air conditioning can be the solution to these demands and can contribute to about 15% to 20% of India’s total oil consumption thereby reducing the dependence on fossil fuels. Hence, the main objective of the work is to model and simulate a solar absorption cooling system for GERMI office building located in Gandhinagar, Gujarat, India, using the transient simulation software ‘TRNSYS’. Cooling load estimation and comfort conditions required for the building were determined based on ASHRAE standards. Evacuated tube collectors were selected because of its market availability, ease of manufacturing and proven technology. Single effect absorption chiller was used because of its commercial availability. The effects of storage tank volume, collector area and collector slope were also investigated for parametric optimization. The results of the simulation and parametric analysis are analyzed and presented in the paper.

Interpretable data-driven fault diagnosis method for data centers with composite air conditioning system

Fault detection and diagnosis are essential to the air conditioning system of the data center for elevating reliability and reducing energy consumption.This study proposed a convolutional neural network(CNN)based data-driven fault detection and diagnosis model considering temporal dependency for composite air conditioning system that is capable of cooling the high heat flux in data centers.The input of fault detection and diagnosis model was an unsteady dataset generated by the experimentally validated transient mathematical model.The dataset concerned three typical faults,including refrigerant leakage,evaporator fan breakdown,and condenser fouling.Then,the CNN model was trained to construct a map between the input and system operating conditions.Further,the performance of the CNN model was validated by comparing it with the support vector machine and the neural network.Finally,the score-weighted class mapping activation method was utilized to interpret model diagnosis mechanisms and to identify key input features in various operating modes.The results demonstrated in the pump-driven heat pipe mode,the accuracy of the CNN model was 99.14%,increasing by around 8.5%compared with the other two methods.In the vapor compression mode,the accuracy of the CNN model achieved 99.9%and declined the miss rate of refrigerant leakage by at least 61%comparatively.The score-weighted class mapping activation results indicated the ambient temperature and the actuator-related parameters,such as compressor frequency in vapor compression mode and condenser fan frequency in pump-driven heat pipe mode,were essential features in system fault detection and diagnosis.

Optimization and comparative performance analysis of conventional and desiccant air conditioning systems regenerated by two different modes for hot and humid climates:Experimental investigation

A desiccant air conditioning system is considered a capable alternative to a conventional air conditioning system because of its independent control of temperature,humidity and being eco-friendly.Also,to resolve the problem of more energy consumption for the restoration of a desiccant,structures comprising of desiccant can utilize thermal energy or complete waste heat to revive desiccant material.Therefore,this research work executes an experimental,optimization and comparative examination for conventional and desiccant air conditioning sys-tems regenerated by two different modes,i.e.firstly using(Mode-I)complete waste heat from condenser and secondly using(Mode-II)rod(electric heater)heat for regeneration at different process air inlet temperatures,i.e.(28,29.5,31,32.5,34,35.5 and 37°C),at different process air inlet velocities,i.e.(1.5,2.5,3.5 and 4.5 m/s)and a fix(2.5 m/s)regeneration air inlet velocity.Thus,optimization of performance parameters,i.e.VCOP,ECOP,dehumidification effectiveness,moisture removal capacity(kg/hr),DCOP,regeneration effectiveness and regeneration rate(kg/hr),is identified for achieving maximum efficiency of conventional and desiccant air con-ditioning systems under the above operating conditions.

Model predictive control of indoor thermal environment conditioned by a direct expansion air conditioning system

Temperature and humidity are two important factors that influence both indoor thermal comfort and air quality.Through varying compressor and supply fan speeds of a direct expansion(DX)air conditioning(A/C)unit,the air temperature and humidity in the conditioned space can be regulated simultaneously.However,most existing controllers are designed to minimize the tracking errors between the system outputs with their corresponding settings as quickly as possible.The energy consumption,which is directly influenced by the compressor and supply fan speeds,is not considered in the relevant controller formulations,and thus the system may not operate with the highest possible energy efficiency.To effectively control temperature and humidity while minimizing the system energy consumption,a model predictive control(MPC)strategy was developed for a DX A/C system,and the development results are presented in this paper.A physically-based dynamic model for the DX A/C system with both sensible and latent heat transfers being considered was established and validated by experiments.To facilitate the design of MPC,the physical model was further linearized.The MPC scheme was then developed by formulating the objective function which sought to minimize the tracking errors of temperature and moisture content while saving energy consumption.Based on the results of command following and disturbance rejection tests,the proposed MPC scheme was capable of controlling temperature and humidity with adequate control accuracy and sensitivity.In comparison to linear-quadratic-Gaussian(LQG)controller,better control accuracy and lower energy consumption could be realized when using the proposed MPC strategy to simultaneously control temperature and humidity.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.