ASHRAE IJHVAC 16-4-2010 HVAC&R Research《《HVAC&R研究》》.pdf

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1、 VOLUME 16, NUMBER 4 HVAC accepted February 25, 2010This paper will discuss the study of turbulent and mean airflow exiting air terminal devices and surrounding occupants seated in classroom desks for slightly warm environments equipped with personalized ventilation systems with upper and lower air

2、terminal devices. In the turbulent air-flow analysis the air root mean square, the air turbulence intensity, and the air velocity fluctua-tions frequencies are calculated, while in the mean airflow analysis the mean air velocity and temperature, the human body skin temperature, and the thermal comfo

3、rt indexes are evaluated using a multi-node thermal regulation model for two different airflow rates.In the experimental tests made in a wood chamber a manikin, a ventilated desk, and two interior climate analyzers are used. The fluctuations of air velocity and temperature are mea-sured in the air t

4、erminal devices and in 15 human body sections around the manikin, while the mean value of air relative humidity and mean radiant temperature are evaluated inside the experimental chamber.The mean air temperature in the air terminal devices is around 28C (82.4F), while the mean radiant temperature in

5、 the occupation area, the mean air temperature far from the occu-pation area, and the internal mean air relative humidity in the occupation area are around 28C (82.4F), 28C (82.4F), and 50%, respectively. The airflow rate in tests I and II are 25.75 m3/h (15.16 ft3/min) and 48.04 m3/h (28.27 ft3/min

6、), respectively. The mean air velocity, root mean square, and turbulence intensity for test I are 0.59 m/s (1.94 ft/s), 0.13 m/s (0.43 ft/s), and 22.4%, in the upper air terminal device, and 0.9 m/s (2.96 ft/s), 0.15 m/s (0.49 ft/s), and 16.7%, in the lower air terminal device; while, for test II th

7、ey are 1.72 m/s (5.64 ft/s), 0.16 m/s (0.52 ft/s), and 9.4%, in the upper air terminal device, and 1.06 m/s (3.48 ft/s), 0.16 m/s (0.52 ft/s), and 14.9%, in the lower air terminal device.In test I the mean air velocity and the airflow rate are higher in the lower exit air terminal device than in the

8、 upper exit air terminal device; while in test II, the opposite is true. It is also true that the skin temperature is slightly lower in test II than in test I, mainly in human body sec-tions near the air terminal devices, such as the chest, arms, and legs. The occupant in test I con-ditions is therm

9、ally uncomfortable; however, in test II conditions, the obtained results are near the comfort recommendations.Eusbio Z. E. Conceio is an assistant professor and Slvia P. Rosa, Ana L. V. Custdio, Renata L. Andrade, and Maria J. P. A. Meira are graduates of the University of Algarve, Campus de Bambela

10、s, Faro, Portugal. M Manuela J. R. Lcio is a teacher at the Vertical Grouping of Schools Professor Paula Nogueira, Olho, Portugal. 2010 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in HVAC never-theless, the air terminal device located a

11、bove the desk writing area, in front to the trunk area, was incident in the trunk area. Conceio et al. (2007) measured four values at 90 angles in different human body sections. In accordance with the obtained values the mean difference of the air velocity around each sec-tion is, in general, lower

12、than 0.2 m/s (0.66 ft/s), and the measurement made in front to the man-ikin surface is, in general, representative of each section. In similar studies, but only with measurements made in front of the manikin surface, Con-ceio et al. (2008a) verified that the design used with two air terminal devices

13、, installed in the classroom desk, guarantees a relatively uniform air velocity field around the manikin. The pres-ence of the small ventilators, located in the exit air terminal devices, increases the thermal com-fort levels; nevertheless, the airflow turbulence levels also increase. Conceio et al.

14、 (2008a) suggested to put other grids in the exit air terminal devices area, so as not to use small ventilators placed in the exit air terminal devices and to change slightly the upper air terminal devices exit direction.In Conceio et al. (2009), in order to evaluate all of the chambers internal air

15、flow, a devel-oped computational fluid dynamic numerical model was also applied. This kind of study, that analyzes in detail the airflow around the occupants, was also used to evaluate the airflow topol-ogy inside the experimental chamber.Different philosophies of personalized ventilation systems, u

16、sing experimental, numerical, or combinations of numerical and experimental means, were studied in the past few years. Person-alized ventilation systems with only one air terminal device present the highest number of stud-ies; nevertheless, recently, more than one air terminal device placed in the d

17、esk has been introduced. Cermak et al. (2002), Kaczmarczyk et al. (2004), Zeng and Zhao (2005), Sekhar et al. (2005), Pan et al. (2005), Muhic and Butala (2006), and Sun et al. (2007), are some examples.The influence between the environmental variables around the body and the human thermal response

18、can be evaluated through the multi-node thermal regulation model. This kind of numerical methodology was developed in the last years, as an example, by Stolwijk (1970), Thellier et al. (1994), Huizenga et al. (1999), Fiala et al. (1999), Farrington et al. (2001), Fiala et al. (2001), Tanabe et al. (

19、2002), Ozeki et al. (2004), and Gao et al. (2006). These methodologies, and others, were used in the analysis of cold, moderate, or warm environments. In slightly warm 2010 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in HVAC ISO 2005).

20、This philosophy considers four environmental variables (air temperature, air velocity, air relative humidity, and mean radiant temperature) and two personal parameters (activity and clothing levels). For acceptable thermal comfort conditions, the ISO 7730 (2005) defines three comfort categories: A (

21、6% of unsatisfied people), B (10% of unsatis-fied people), and C (15% of unsatisfied people).The aim of this study is to investigate turbulent and mean airflow in the exit air terminal devices and around an occupant seated in classroom desks equipped with personalized ventila-tion systems with upper

22、 and lower air terminal devices, for slightly warm environments. In the study, a desk is equipped with one air terminal device located above the desk writing area, in front of the trunk area, and incident in the trunk area, while another air terminal device is located below the desk writing area, in

23、 front to the legs area, and incident in the knees area. The airflow in the upper and lower exit air terminal devices is obtained using only one ventilator placed before the personalized ventilation system, depending on the ventilator airflow rate and the duct geometry.NUMERICAL MODELThe multi-nodal

24、 human thermal comfort numerical model is used to evaluate the thermal comfort level, to which the occupant is subjected, using experimental data obtained around the manikin. In the multi-nodal human thermal comfort model (Conceio et al. 2006) that works in transient and steady-state conditions and

25、simultaneously simulates a group of persons, the three-dimensional body is divided into 24 cylindrical and 1 spherical elements. Each element is divided into 4 parts (core, muscle, fat, and skin), sub-divided into several layers, and could still be protected from the external environment through som

26、e clothing layers. This numerical model is divided into four parts (Conceio et al. 2006): human body thermal system, clothing thermal system, thermo-regulatory system, and thermal comfort.The human body thermal response is based on energy balance integral equations for the human tissue layers and ar

27、terial and venous blood, as well as mass balance integral equations for the blood and transpired water in the skin surface for each element (Conceio et al. 2006). The clothing thermal response is based on energy balance integral equations for the clothing layers, as well as water mass balance integr

28、al equations in the clothing layers in each element. In the resolution of these equations systems, the Runge-Kutta-Fehlberg method with error control is used (Conceio et al. 2006). The thermal-regulatory system, used to control the human body temperature, is based on the Stolwijk (1970) numerical mo

29、del. To evaluate the thermal comfort level in steady-state conditions, the PMV and the PPD indexes (Fanger 1970) are used. In these calculations, based on the heat exchanged between the human body elements and the environ-ment (by convection, conduction, evaporation, radiation, and respiration), a m

30、odified Fanger model (Miyanaga and Nakamo 1998) is used.In order to validate the numerical model, the experimental data and the numerical values of the convective and radiative coefficients, heat and mass fluxes, temperature field, and comfort indexes were all compared. More details about these vali

31、dation results can be seen in Conceio et al. (2006).In this numerical work, the virtual manikin was 1.70 m (5.58 ft) tall, weighed 70 Kg (154.3 lb), measured 1.2 Met of activity level, and wore 0.3 Clo of clothing (short-sleeved shirt, shorts, shoes, 2010 American Society of Heating, Refrigerating a

32、nd Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in HVAC for the horizontal sections the measurements are made above, while the vertical sec-tions, the measurement are made in front.The indoor climate analyzer (BABUC-A from LSI), multi-data logger with 11 inputs with sensors from LSI,

33、 is used to measure the mean environmental variables inside the experimental chamber, namely, the air relative humidity, the air mean temperature far from the occupation area, and the radiant mean temperature in the occupation area.The mean air temperature in the exit air terminal devices is around

34、28C (82.4F), while the mean radiant temperature in the occupation area, the mean air temperature far from the occupa-tion area and the internal mean air relative humidity in the occupation area are around, respec-tively, 28C (82.4F), 28C (82.4F), and 50%. The airflow rate in tests I and II are, resp

35、ectively, 25.75 m3/h (15.16 ft3/min) (10.20 m3/h (6 ft3/min) in the upper, and 15.55 m3/h (9.16 ft3/min) in the lower air terminal device), and 48.04 m3/h (28.27 ft3/min) (29.72 m3/h (17.49 ft3/min) in the upper, and 18.32 m3/h (10.78 ft3/min) in the lower air terminal device). The air velocity and

36、temperature around the occupant are measured in 15 human body sections. 2010 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in HVAC while, for test II, are they 1.72 m/s (5.64 ft/s), 0.16 m/s (0.52 ft/s), and 9.4%, in the upper air termina

37、l device, and 1.06 m/s (3.48 ft/s), 0.16 m/s (0.52 ft/s), and 14.9%, in the lower air terminal device.Figure 2. Exit air velocity fluctuations in the lower and upper air terminal devices, for tests I and II. 2010 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.as

38、hrae.org). Published in HVAC nev-ertheless, it is more evident in the upper body section than in the lower body sections.The air velocity fluctuation frequencies, in general, are more energetic in test II than in test I. In test I, the air velocity fluctuation frequencies, in decreasing importance,

39、are verified in the left arm, left hand, chest, right shoulder, right leg, head, left shoulder, while in test I the air velocity fluctuation frequencies, in decreasing importance, are verified in the chest, left hand, left arm, left shoulder, left foot, and right shoulder. The air velocity fluctuati

40、on frequencies in the lower body sections are more energetic in test I than in test II, while the air velocity fluctuation fre-quencies in the upper body sections are more energetic in test II than in test I. Mean Airflow that the Occupant is SubjectedThe mean value of air velocity (Vm) and temperat

41、ure (Tm), measured in each body section, in tests I and test II are presented, respectively, in Figures 6 and 7. In general, the mean air velocity around the body, which changes between the 0.2 m/s (0.66 ft/s) and the 0.6 m/s (1.97 ft/s), are higher in test II than in test I, mainly in the chest, he

42、ad, and upper Figure 5. Power spectra of the air velocity frequencies, calculated in each human body section, for tests I (a) and II (b).(a) (b) 2010 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. (www.ashrae.org). Published in HVAC accepted March 5, 2010Fouling of s

43、urfaces within the heat exchangers of heating, ventilating, and air-conditioning (HVAC) systems of buildings is an equipment fault that wastes appreciable amounts of energy; however, it escapes detection under current building automation technology. A novel concept is introduced to automatically det

44、ect this fouling on water-side and air-side surfaces of water-cooled HVAC air coils. The concept incorporates a model-driven component contributing a table of human expert information and an embedded data-driven component assimilating real-time data sampled from HVAC plant instrumentation. Superviso

45、ry programming (the “agent”) conducts real-time surveillance for coil fouling using the data-driven component, which is a model replicating the current dynamic thermal behavior of the coil. The surveillance is a spe-cific characterizing transient (a “query”) exercised periodically on the data-driven

46、 dynamic coil model as a surrogate for exciting the real coil. When a query returns a suspect result, the agent determines if coil fouling or some other change caused that result by using the tabulated expert information. The concept makes use of all data sampled from the plant, reflecting transient

47、 and steady behavior. Fouling can be discerned from other developments, such as instrument drift, and the agent can distinguish air-side fouling from water-side fouling, estimate the severity of fouling, and estimate an uncertainty for its classification. The values tabulated describe three-dimensio

48、nal surfaces characterizing the varied impact fouling generically has on coil ther-mal effectiveness when considered over the state space of coil operation. Categorical use of that information by the concept is justified by analysis in the effectiveness-NTU state plane.A companion paper (Veronica 20

49、11) gives results of exercising a crucial task within the concept on simulated data by using one form of a dynamic data-driven model; a multilayer perceptron.INTRODUCTIONFouling of heat transfer surfaces reduces the thermal conductance and thus the thermal effec-tiveness of water-cooled air coils in HVAC systems. A coil fouled on its water side (e.g., by slime, scale, or corrosion products) or air side (e.g., by particulate or fibrous buildup on fins) requires more fl