Contributors: Kyle Gluesenkamp, Corey Blackman, Zhiyao Yang, Mini Malhotra
... calculation spreadsheet for paper results
Data for: Experimental and numerical research of heat transfer and phase change characteristics of cemented paste backfill with PCM
Contributors: LANG LIU, Yuhang Jia, Mei Wang, Shiqi Wang, xiaoyan Zhang, Chen Liu
Date for: Enhanced solar steam generation using carbon nanotube membrane distillation device with heat localizationvesting and heat localization
Contributors: Cheng-Long Guo, En-Dong Miao, Zhonghao Rao, lin liang, Meng-Qi Ye, Qi Liu
... This file contains all the raw data from this work.
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Data for: Chemiluminescence based operating point control of domestic gas boilers with variable natural gas composition
Contributors: Yi Ding, Thierry Schuller, Daniel Durox, Nasser Darabiha
... Tests results of the chemiluminescence-based equivalence ratio control loop
Data for: Experimental and numerical study on heat transfer and flow characteristics in shell side of helically coiled trilobal tube heat exchanger
Contributors: guanghui wang
... Simulation and experimental data in this paper
Data for: Thermal influences of stabilization on warm and ice-rich permafrost with cement: field observation and numerical simulation
Contributors: Yanhu Mu, Ma Wei, Hu Zhang, Mingtang Chai, jianming zhang, Zhenhua Yin
... This dataset is the original data in each figure in the manuscript.
Data for: Dynamic scenario simulation of dropwise condensation on a structured superhydrophobic surface with droplet jumping
Contributors: Hao Wang, Kaixin Meng
... The simulation has well reproduced the condensing process on a vertical surface. The droplets are growing and coalescing with neighbors. The coalescence and jumping are shown. Those jumping ones leave blank areas on the surface where new droplets then nucleate and grow up and then coalesce again. Some coalescence pairs don’t meet the criteria and cannot jump. Quite a few droplets are always more than 1.5 times larger than their small neighbors, therefore they keep “eating” their neighbors and grow up. The gravity removal of big droplets, as well as its sweeping to the downstream, is reproduced well as shown in Video 2.
Contributors: Jacob Hinze, Robert Braun, Logan Rapp, Mark Anderson, Evan Reznicek, Greg Nellis
... This file gives all of the temperature, pressure, and mass flow measurements averaged for one cycle under constant test conditions. Each of the runs is on a different tab of the document.
Data for: Experimental study of the effectiveness and exergetic efficiency of counter-rotating screw heat exchanger in a prebaked anode production plant
Contributors: CK TAN, Ahmed Abd Elrahman, s attalla, m mohamed, s Wahid, A Ahmed
... This Excel file records both the raw and processes experimental data.
Data for: Optimization model and application for the recondensation process of boil-off gas in a liquefied natural gas receiving terminal
Contributors: Dongxu Sun, Kai Tang, Junnan He, Ming Wu, Shizhang Tian, Benyuan Hu, Zuoliang Zhu
... The data uploaded this time consists of four parts: the HYSYS files, the data for figures, the initial data obtained by using HYSYS and the data for each month of a year. The HYSYS files include two operational models during the unloading stage in the LNG receiving terminal used primarily in this paper. The ambient temperature of the file named "November to March" was set to 5 degrees Celsius, and the operating cycle was set to 2 days. Meanwhile, the ambient temperature of the file named "April to October" was set to 25 degrees Celsius, and the operating cycle was set to 9 days. The two operational models can be used to obtain initial operating data which can be seen in the folder named "Initial data obtained by using HYSYS". The folder contains the data at the key nodes in the different phases for each month obtained using the HYSYS model. We can fit the data of each stage and get the flow rate of LNG and BOG at the key nodes of each stage. The operating cycle and ambient temperature vary depending on the month. We can calculate the operating power and the cost of each month. By optimizing the calculations described in the article, we can get the lowest operating power and the cost per month. We can compare the operating costs before and after optimization to see the optimization effect which can be seen in the folder named "Data for each month of a year". "Data for figures" shows the data for each figure in this paper.