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- 검색키워드
- 저자 : Jingjing Long (검색결과 3 건)
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( Changdong Li ),( Jingjing Long ),( Zhiyong Fu ),( Wenqiang Chen ) 대한지질공학회 2019 대한지질공학회 학술발표회논문집 Vol.2019 No.2
The Zigui basin is one of the most landslide-prone areas where thousands of landslides are distributed. Researches show that areas sharing the same conditions as identified landslides are clearly potential areas for future disasters. Performing the landslide susceptibility mapping is a heated issue in the area. Continued improvements in high-resolution satellite images, and the developments of unmanned aerial vehicles (UAVs) and site-investigation function well in constructing effective, high-quality landslide databases. GIS technology and machine learning algorithms have been widely applied in landslide susceptibility prediction. Whereas, whether the random and subjective selection of the landslides or non-landslides grid cells are reasonable in research of landslide susceptibility mapping is the existence problem. Based on the Two step cluster (TSC) algorithm and the Self-organizing mapping - Random forest (SOM-RF) model, a novel hybrid model is proposed to overcome the above drawbacks. SOM is used to produce a preliminary landslide susceptibility mapping. TSC algorithm is applied in telling apart the most reasonable True-Positive (TP) from recorded landslide grid cells in high-susceptibility zones and the False-Positive (FP) in low-susceptibility zones. Afterwards, the labeled datasets are imported into the RF model for training. And then the trained SOM-RF model is utilized to perform an improved landslide susceptibility mapping. Most areas with high or very high susceptibility are located within the hydro-fluctuation belt of the TGR. Compared with the susceptibility mapping produced by single RF model, the results of SOM-RF model demonstrate to have the superior prediction skill and higher reliability.
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Bio-base Metal Organic Frameworks as Potential CO2 Adsorbents
Zhang Jiawei,Ma Jingjing,Liu Chen,Wang Qi,Xu Yiling,Fang Long,Xia Kai,Sun Deshuai 한국화학공학회 2024 Korean Journal of Chemical Engineering Vol.41 No.7
Environmental friendliness and high adsorption capacity are important properties of CO 2 adsorbents. Bio-based metal– organic framework (bioMOFs) materials off er notable benefi ts for CO 2 capture. Amino acids like L -glutamic acid (Glu) and L-aspartate (Asp) are employed as ligands for the synthesis of bioMOFs, Asp-Cu and Glu-Cu. Characterization results confi rmed that Asp-Cu and Glu-Cu possessed tertiary amine and secondary amine structures, respectively. The adsorption capacities of Glu-Cu and Asp-Cu were up to 253 mg·g −1 and 277 mg·g −1 at 1 bar CO 2 pressure and 190 mg·g −1 and 223 mg·g −1 at 0.15 bar CO 2 pressure. The CO 2 adsorption properties of bioMOFs were comprehensively evaluated under various conditions, including temperature, water content, SO 2 concentration, and other compositions. Adsorption data were fi tted well with the pseudo-fi rst-order kinetics and Weber-Morris intraparticle diff usion model. The kinetic studies revealed that a small amount of water signifi cantly accelerated the pseudo-fi rst-order kinetic constants, whereas excess water vapor greatly hindered the intra-diff usion constants of CO 2 . The presence of SO 2 led to a decrease in the adsorption capacity of both MOFs due to rapid reactions occurring with active sites on the MOF surface. Furthermore, these bioMOFs were easily recovered and regenerated for at least 20 cycles. The primary CO 2 adsorption mechanism involved catalytic hydration reactions on Asp-Cu, while chemical adsorption occurred on Glu-Cu. Both mechanisms were accompanied by physical adsorption.
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Haikuan Zhang,Changdong Li,Wenmin Yao,Jingjing Long 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.9
It is reported that there are many colluvial landslides with multilayered sliding masses; however, previous studies of the pile spacing of stabilizing piles mainly focus on the single-layered sliding mass, which may lead to design errors for pile spacing. Consequently, the paper presents a novel method to determine the pile spacing with considering interactions of multilayered sliding masses in colluvial landslides. Based on a generalized landslide model, equations for calculating stability coefficients of multilayered sliding masses were improved by examining the interactions among sliding masses. An accordingly colluvial landslide model with double-layered sliding masses was established by the finite differential method. The distribution of vertical landslide driving force and horizontal loading between adjacent piles were studied based on the colluvial landslide. A novel method of calculating the maximum pile spacing and minimum pile spacing was deduced by considering the soil arching effect and the interactions among multilayered sliding masses. The reasonable pile spacing was obtained considering cost and performance of stabilizing piles. The calculational process, which determines optimal pile spacing in multilayered masses, were shown based on the Bazimen landslide. The variations in pile spacing affected by various soil-layer sequences was illustrated by employing the Bazimen landslide model. The calculation results indicate that the pile spacing is positively correlated with the depth of soil with the maximum resistance sliding force. Effectiveness and significance of the presented method were proved through verify the calculational results by using numerical modeling approaches.
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