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本文(ASHRAE NA-04-2-6-2004 Recalibration of the Complaint Prediction Model《RP-1129模型对投诉的预测的重新调整》.pdf)为本站会员(fatcommittee260)主动上传,麦多课文库仅提供信息存储空间,仅对用户上传内容的表现方式做保护处理,对上载内容本身不做任何修改或编辑。 若此文所含内容侵犯了您的版权或隐私,请立即通知麦多课文库(发送邮件至master@mydoc123.com或直接QQ联系客服),我们立即给予删除!

ASHRAE NA-04-2-6-2004 Recalibration of the Complaint Prediction Model《RP-1129模型对投诉的预测的重新调整》.pdf

1、NA-04-2-6 (RP-1129) Recalibration of the Complaint Prediction Model Clifford C. Federspiel, Ph.D. Associate Member ASHRAE Rodney A. Martin Student Member ASHRAE Hannah Yan Associate Member ASHRAE ABSTRACT This paper describes the evaluation and recalibration of the complaint prediction model develop

2、ed by Federspiel (2000). We collected temperature time-series data and complaint dataj-om six buildings ranging in size from 60,000 fi to 800,000 f? from three different geographical locations. Using these data, we found a low correlation between the observed number of complaint events and the Predi

3、cted Average Complaint Events (PACE) for the monitoring intervals and systematic underpre- diction ofhot complaints. We recalibrated the model, increasing the correlation coeficient between obsewednumber of complaint events and PACE to r = 0.49. This degree of correlation, though still not high, is

4、statistically sign$cant (p = 0,044). The reca- librated modelpredicts that the temperature corresponding to the minimum number of complaints is lower than that of the original model. The recalibrated model also predicts that the minimum number of complaints is greater than that of the original model

5、. Finally, the recalibrated model is not symmetrical. The recalibrated model predicts that hot complaints will increase faster as the average temperature rises than will cold complaints as the average temperature decreases. We used complaint temperatures and an observed setup in building-wide mean t

6、emperature to validate the recalibration. From observed complaint temperatures, we constructedsix hypothesis tests on predicted values ofthe mean and standard deviation of complaint temperatures. The difer- ences between the predicted and computed complaint temperature statistics were not statistica

7、lly signiJicant in all six cases. We comparedthe observedeffect ofraising the mean temperature 3Fwith thepredictedeffect. The observed hot complaint rateduring the high-temperature period was 2.4 times higher than during the low-temperature period. The predicted ratio was 5.3 times. The diflerence w

8、as explained by underreporting observed by the chief engineer. We expected a dependence of the mean complaint levels on mean outdoor temperature because correlations between mean outdoor temperature, clothing insulation, and indoor air velocity have been established. However, we did notjhdsuch an in

9、fluence. The complaint modelpredicts that the mean temper- ature for minimizing complaint rate on arrival is lower than for minimizing complaint rate during the occupiedperiod of the day. This can be explained by a higher metabolic rate on arrival. *The full text of this paper can be found in the In

10、ternational Journal of Heating, Ventilating, Air-conditioning and Refrigerating Research, Volume 10, Number 2, April 2004, pp. 179-200. Responses to questions/comments to this paper will be published in the Research Journal. Clifford C. Federspiel is a research specialist at the Center for the Built Environment and Rodney A. Martin is a Ph.D. candidate in mechan- ical engineering, University of California, Berkeley, Calif. Hannah Yan is a rncchanical engineer at Flack + Kurtz, San Francisco, Calif. , 594 02004 ASHRAE.

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