An In Situ Experimental Method for the Development and Validation of Slat-Type Blind Models in Cooling Load Calculations

2005 ◽  
Vol 128 (2) ◽  
pp. 189-198 ◽  
Author(s):  
Chanvit Chantrasrisalai ◽  
Daniel E. Fisher
Keyword(s):  
Measured Data ◽  
Energy Calculation ◽  
Cooling Load ◽  
Experimental Uncertainty ◽  
Experimental Facility ◽  
Experimental Procedure ◽  
Load Calculation ◽  
Building Cooling ◽  
Development And Validation

An in situ experimental procedure suitable for the development and validation of slat-type blind models used in building cooling load calculations is presented. Unique requirements of the experimental facility are presented, and measured data from the facility are compared with existing experimentally validated models. The experimental uncertainty associated with the measured solar transmittance is shown to be less than ±0.05, well within the range of accuracy required for the development of cooling load calculation procedures. The new procedure was used to validate the fenestration model in EnergyPlus, a heat balance based cooling load and energy calculation program.

A Simplified Method for Building Cooling Load Calculation

ICSDEC 2012 ◽  
2012 ◽  
Author(s):  
Siyue Gong ◽  
Guangcai Gong ◽  
Tianhe Han ◽  
Rong Wu
Keyword(s):  
Cooling Load ◽  
Simplified Method ◽  
Load Calculation ◽  
Building Cooling

scholarly journals ANALYTICAL METHOD TO CALCULATE ROOM COOLING LOAD

2020 ◽  
Vol 7 (8) ◽  
pp. 56-64
Author(s):  
Gedlu Solomon ◽  
Yeshurun Alemayehu Adde
Keyword(s):  
Sea Level ◽  
Latent Heat ◽  
Analytical Method ◽  
Heat Load ◽  
Total Heat ◽  
Cooling Load ◽  
Heat Gain ◽  
Load Calculation ◽  
Building Cooling ◽  
North Latitude

This paper focus on cooling load calculation of the meeting hall [4m*15m*7m] in the location of 8.55 north latitude, East longitude 39.27 and Altitude 1726 m elevation above sea level. The total building cooling load consists of inside design condition of building, outside design condition of building, consider building mater and wall facing to sun and etc.by categorized in to sensible and latent heat gain from ventilation, infiltration and occupants. From different Room heat gain component, the total heat load 21,301.66 w.

New design-day method for building cooling load calculation in China

2019 ◽  
Vol 47 (8) ◽  
pp. 901-911
Author(s):  
Xia Wu ◽  
Zhe Tian ◽  
Chengzhi Tian ◽  
Yuanyuan Wang ◽  
Jiaqing Li
Keyword(s):  
Cooling Load ◽  
Load Calculation ◽  
Building Cooling

ANALISIS BEBAN PENDINGINAN PADA COLD STORAGE UNTUK PENYIMPANAN DAGING

2019 ◽  
Vol 7 (1) ◽  
pp. 12-22
Author(s):  
Ratu Mutia Fajarani ◽  
Yopi Handoyo ◽  
Raden Hengki Rahmanto
Keyword(s):  
Experimental Method ◽  
Cold Storage ◽  
Freezing Point ◽  
Cooling Load ◽  
Internal Factors ◽  
External Cooling ◽  
Preservation Method ◽  
Load Calculation ◽  
Selection Of

Cooling is the best preservation method than others because the food that has been cooled will remain fresh and will not experience a change in taste, color and aroma, besides all the activities that cause decay will stop so that the cooled food will last longer. (Hartanto, 1984). With the proper cooling engine planning, it can help with spatial adjustments, adjustments to loading, estimation of the power to be used, and budget plans. That is what is commonly called the cooling load calculation. Calculation of cooling load needs to be carried out before planning. This is necessary because the magnitude of the pending load is very influential on the selection of the cooling engine so that the freezing point for preserving food can be accurate. Pendiginan burden is influenced by external and internal factors. With the experimental method, it is obtained the results of the external cooling load as the external cooling load is 11.6 kW, the inner cooling load is 138.8 kW and the performance work coefficient (COP) is 2.

scholarly journals Development of the Statistical Model for Monitoring Salinization in the Mekong Delta of Vietnam Using Remote Sensing Data and In-Situ Measurements

Proceedings ◽  
2018 ◽  
Vol 2 (10) ◽  
pp. 565
Author(s):  
Nguyen Nguyen Vu ◽  
Le Van Trung ◽  
Tran Thi Van
Keyword(s):  
Statistical Model ◽  
Mekong Delta ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Measured Data ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Spectral Bands ◽  
Component Band

This article presents the methodology for developing a statistical model for monitoring salinity intrusion in the Mekong Delta based on the integration of satellite imagery and in-situ measurements. We used Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat- 8 OLI and TIRS) satellite data to establish the relationship between the planetary reflectance and the ground measured data in the dry season during 2014. The three spectral bands (blue, green, red) and the principal component band were used to obtain the most suitable models. The selected model showed a good correlation with the exponential function of the principal component band and the ground measured data (R2 > 0.8). Simulation of the salinity distribution along the river shows the intrusion of a 4 g/L salt boundary from the estuary to the inner field of more than 50 km. The developed model will be an active contribution, providing managers with adaptation and response solutions suitable for intrusion in the estuary as well as the inner field of the Mekong Delta.

Managing Flow Induced Vibration in Subsea Jumpers

2021 ◽  
Author(s):  
Rakshith Naik ◽  
Yetzirah Urthaler ◽  
Scot McNeill ◽  
Rafik Boubenider
Keyword(s):  
Dynamic Properties ◽  
Fatigue Analysis ◽  
Management Program ◽  
Measured Data ◽  
Operating Conditions ◽  
Valuable Insight ◽  
Fe Model ◽  
Flow Induced Vibration ◽  
Vibration Measurements

Abstract Certain subsea jumper design features coupled with operating conditions can lead to Flow Induced Vibration (FIV) of subsea jumpers. Excessive FIV can result in accumulation of allowable fatigue damage prior to the end of jumper service life. For this reason, an extensive FIV management program was instated for a large development in the Gulf of Mexico (GOM) where FIV had been observed. The program consisted of in-situ measurement, modeling and analysis. Selected well and flowline jumpers were outfitted with subsea instrumentation for dedicated vibration testing. Finite Element (FE) models were developed for each jumper and refined to match the dynamic properties extracted from the measured data. Fatigue analysis was then carried out using the refined FE model and measured response data. If warranted by the analysis results, action was taken to mitigate the deleterious effects of FIV. Details on modeling and data analysis were published in [5]. Herein, we focus on the overall findings and lessons learned over the duration of the program. The following topics from the program are discussed in detail: 1. In-situ vibration measurement 2. Overall vibration trends with flow rate and lack of correlation of FIV to flow intensity (rho-v-squared); 3. Vibration and fatigue performance of flowline jumpers vs. well jumpers 4. Fatigue analysis conservatism Reliance on screening calculations or predictive FE analysis could lead to overly conservative operational limits or a high degree of fatigue life uncertainty in conditions vulnerable to FIV. It is proposed that in-situ vibration measurements followed by analysis of the measured data in alignment with operating conditions is the best practice to obtain a realistic understanding of subsea jumper integrity to ensure safe and reliable operation of the subsea system. The findings from the FIV management program provide valuable insight for the subsea industry, particularly in the areas of integrity management of in-service subsea jumpers; in-situ instrumentation and vibration measurements and limitations associated with predictive analysis of jumper FIV. If learnings, such as those discussed here, are fed back into design, analysis and monitoring guidelines for subsea equipment, the understanding and management of FIV could be dramatically enhanced compared to the current industry practice.

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