Search

The present study aimed to investigate the feasibility of blended amine absorbents in improving the CO2 alkanolamine-based absorption of multicycle integrated absorption–mineralization (multicycle IAM) under standard operating conditions (20–25 °C and 1 atm). Multicycle IAM is a promising approach that transforms CO2 emissions into valuable products such as carbonates using amine solvents and waste brine. Previously, the use of monoethanolamine (MEA) as an absorbent had limitations in terms of CO2 conversion and absorbent degradation, which led to the exploration of blended alkanolamine absorbents, such as diethanolamine, triethanolamine, and aminomethyl propanol (AMP) combined with MEA. The blended absorbent was evaluated in terms of the absorption performance and carbonate production in continuous cycles of absorption, precipitation/regeneration, and preparation. The results showed that the fourth cycle of the blend of 15 wt.% AMP and 5 wt.% MEA achieved high CO2 absorption and conversion efficiency, with approximately 87% of the absorbed CO2 being converted into precipitated carbonates in 43 min and a slight degradation efficiency of approximately 45%. This blended absorbent can improve the efficiency of capturing and converting CO2 when compared to the use of a single MEA, which is one of the alternative options for the development of CO2 capture and utilization in the future. [ABSTRACT FROM AUTHOR]

Making accurate prediction of methanol price is great important for intelligent coking plant production scheduling, and it is essentially a time-series prediction problem. Efficient extraction of temporal and spatial features of methanol price data is conducive to improve the prediction accuracy of the future methanol price, and there are cyclical influences in methanol price prediction. Considering the advantages of convolutional neural networks (CNN) and gated recurrent unit (GRU) in extracting temporal and spatial features, a novel methanol price prediction method based on multicycle CNN-GRU and attention mechanism is proposed, abbreviated MCGAT. In the model construction, a parallel hybrid network architecture is designed. First, CNN is used for extracting static spatial features of methanol price data, and GRU is employed to mine its dynamic temporal features; then, the attention mechanism is utilized to fuse the static spatial and dynamic temporal features attained by CNN and GRU; finally, the methanol price prediction model-based multicycle CNN-GRU is constructed to probe into the cyclical influences. Experimental results on two real methanol price datasets in the past six years manifest the proposed MCGAT outperforms other state-of-the-art methods, and it provides a useful prediction tool of future methanol price for intelligent coking plant. [ABSTRACT FROM AUTHOR]

This study elucidates the geological and physical factors that produce polymodal grain size distributions in two dunes systems in southeastern Oaxaca, Mexico. The dune systems are characterized by (1) small embryo vegetated, transverse and undeveloped dunes; and (2) tall types identified as barchanoid, parabolic, climbing and falling dunes. We performed a best-fit statistical Weibull distribution model with data obtained by laser granulometry to determine the polymodal trends of the coastal dune sands distribution. Polymodal distributions in small dunes arise from coarse and fine-grained sands mainly derived from the erosion of alluvial deposits composed of granitic and metasedimentary rock fragments (e.g., schists, orthogneiss and paragneiss). The medium- to fine-grained sands result from wind deflation, producing a heavy mineral lag. Conversely, the polymodal grain size distributions in the tall dunes are mainly derived from the physical weathering of granites, andesitic-tuff-lava flow marine sandstones (ATLMS), alluvial deposits, and metasedimentary rock fragments (e.g., schists, orthogneiss and paragneiss) due to the frequent storms and intense winds. We constructed binary plots of grain size parameters to compare the dune sand systems in Oaxaca with some others in Mexico. Based on the sedimentary results and the Weibull distributions, we conclude that the grain sizes of the coastal dune sands from Oaxaca, Mexico, are controlled by the sand composition, wind patterns, hydrodynamic conditions, weathering effects, and physical characteristics, regardless of the dune geomorphology. Evidence of multicycle aeolian transport of sand particles in the Oaxaca coastal dunes is supported by the compositional framework of the sands and the roundness of sand grains. [Display omitted] • Oaxaca's coastal dunes in Mexico develop under complex geological and physical conditions. • The Weibull analysis supports the polymodal distributions in the Oaxaca's coastal dune sands. • Dune morphology seems not to control the diversity in grain sizes of the coastal dune sands. [ABSTRACT FROM AUTHOR]

The sealing capacity of the caprock of a gas-reservoir-type underground gas storage (UGS) directly affects the safe storage and efficient utilization of natural gas, especially during a high rate of multicycle injection-withdrawal under different pressure ranges. In order to determine the safety threshold, we propose an in-situ stress-fluid coupling simulation and evaluation method to analyze the dynamic breakthrough pressure of caprock, and use the caprock samples from three UGSs to explore the evolution of the sealing capacity at alternating stress and the critical sealing capacity. We find that the fatigue effect caused by multicycle injection-withdrawal can change the pore-throat structure and enhance the in-situ sealing capacity of the caprock. Increasing gas injection pressure leads to the decline of breakthrough pressure, and the failure of capillary sealing occurs before mechanical failure. Our results show that the sealing capacity of caprock changes dynamically under in-situ effective stress during injection-withdrawal periods, and the dynamic sealing mechanism reveals the risk timing of the caprock, and guides to release the full potential of an UGS. • A novel method to evaluate dynamic sealing capacity of UGS caprock is proposed. • Safe threshold of caprock is found under in-situ stress-fluid coupling condition. • Sealing capacity of caprock changes dynamically during injection-withdrawal. • Capillary sealing failure is more likely to cause leakage than mechanical failure. [ABSTRACT FROM AUTHOR]