Transport Experiment
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Author(s):  
Kouyou IWAKI ◽  
Ryousuke MORITA ◽  
Satoshi ITO
Keyword(s):  

2020 ◽  
Vol 79 (1) ◽  
pp. 15-25
Author(s):  
Masashi Watanabe ◽  
Takumi Yoshii ◽  
Volker Roeber ◽  
Kazuhisa Goto ◽  
Fumihiko Imamura

2020 ◽  
Vol 12 (19) ◽  
pp. 7930 ◽  
Author(s):  
Jung-Hun Woo ◽  
Younha Kim ◽  
Hyeon-Kook Kim ◽  
Ki-Chul Choi ◽  
Jeong-Hee Eum ◽  
...  

A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: (1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and (2) a base-year, natural emissions inventory for biogenic and biomass burning. For (1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO2, NOx, CO, non-methane volatile organic compounds (NMVOC), NH3, OC, BC, PM10, PM2.5, CO2, CH4, N2O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.


2020 ◽  
Vol 54 (18) ◽  
pp. 11249-11257
Author(s):  
Emily L. Tran ◽  
Paul Reimus ◽  
Ofra Klein-BenDavid ◽  
Nadya Teutsch ◽  
Mavrik Zavarin ◽  
...  

SPE Journal ◽  
2020 ◽  
pp. 1-19
Author(s):  
Jung Yong Kim ◽  
Lijun Zhou ◽  
Nobuo Morita

Summary Hydraulic fracturing with slickwater is a common practice in developing unconventional resources in North America. The proppant placement in the fractures largely determines the productivity of the well because it affects the conductivity of fractures. Despite the wide use of slickwater fracturing and the importance of proppant placement, the proppant transport is still not fully understood, and the efficiency of the proppant placement is mostly bound to the changes to proppant properties, friction reducers, and guar technology. Although the degradable fiber is currently used in some cases, it has not been well investigated. In this experimental study, we conducted a proppant transport experiment using different fluid compositions of fiber and guar gum in three types of proppant transport slot equipment. After the experiments, simulation was conducted with the commercial fracture software StimPlanTM (NSI Technologies 2020) to simulate and compare the fracture fluid performance with and without the fibers. The results indicate that using degradable fibers with or without the guar gum as a viscosifier can produce a fracture slurry applicable in both conventional and unconventional fracturing operations, helping proppant placement in the reservoir.


In the article, the application of modern MEMS accelerometers to evaluate driver training is discussed. Data from a transport experiment with Tatra 815 on a training polygon consisting of 4 types of surfaces were used, and the driver completed 4 individual laps. The tested parameters showed statistically significant differences between selected laps and surfaces (sections) depending on the driving style and the average speed. It is clear from the evaluation of the ride that the driver is gradually improving when driving on the polygon, as assumed. However, from a certain moment the magnitude of generated shocks exceeds normatively determined values. The design part determines specific requirements on driving characteristics of a driver during a driver training.


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