用CH3COONa溶液处理合成多级孔ZSM-5分子筛,对处理前后的样品采用XRD、XRF、BET、SEM进行表征,并分别负载Fe,进行高浓度有机胺废水的催化氧化降解。结果表明,采用CH3COONa溶液处理ZSM-5分子筛,具有碱改性的作用,且显著提高了催化氧化降...用CH3COONa溶液处理合成多级孔ZSM-5分子筛,对处理前后的样品采用XRD、XRF、BET、SEM进行表征,并分别负载Fe,进行高浓度有机胺废水的催化氧化降解。结果表明,采用CH3COONa溶液处理ZSM-5分子筛,具有碱改性的作用,且显著提高了催化氧化降解有机胺废水性能。在此基础上,运用正交试验对催化氧化降解有机胺废水条件进行优化,确定出试验范围内的最佳评价条件:反应时间为90 min,反应温度为95℃,催化剂用量为30g/L,溶液初始pH为4,氧化剂H2O2用量为45 m L/L,经过3次验证试验证明,该反应条件具有高度的可靠性和重现性,在此条件下,COD去除率高达98.73%。展开更多
In elastic-wave reverse-time migration(ERTM),the reverse-time reconstruction of source wavefield takes advantage of the computing power of GPU,avoids its disadvantages in disk-access efficiency and reading and writing...In elastic-wave reverse-time migration(ERTM),the reverse-time reconstruction of source wavefield takes advantage of the computing power of GPU,avoids its disadvantages in disk-access efficiency and reading and writing of temporary files,and realizes the synchronous extrapolation of source and receiver wavefields.Among the existing source wavefield reverse-time reconstruction algorithms,the random boundary algorithm has been widely used in three-dimensional(3D)ERTM because it requires the least storage of temporary files and low-frequency disk access during reverse-time migration.However,the existing random boundary algorithm cannot completely destroy the coherence of the artificial boundary reflected wavefield.This random boundary reflected wavefield with a strong coherence would be enhanced in the cross-correlation image processing of reverse-time migration,resulting in noise and fictitious image in the migration results,which will reduce the signal-to-noise ratio and resolution of the migration section near the boundary.To overcome the above issues,we present an ERTM random boundary-noise suppression method based on generative adversarial networks.First,we use the Resnet network to construct the generator of CycleGAN,and the discriminator is constructed by using the PatchGAN network.Then,we use the gradient descent methods to train the network.We fix some parameters,update the other parameters,and iterate,alternate,and continuously optimize the generator and discriminator to achieve the Nash equilibrium state and obtain the best network structure.Finally,we apply this network to the process of reverse-time migration.The snapshot of noisy wavefield is regarded as a 2D matrix data picture,which is used for training,testing,noise suppression,and imaging.This method can identify the reflected signal in the wavefield,suppress the noise generated by the random boundary,and achieve denoising.Numerical examples show that the proposed method can significantly improve the imaging quality of ERTM.展开更多
文摘用CH3COONa溶液处理合成多级孔ZSM-5分子筛,对处理前后的样品采用XRD、XRF、BET、SEM进行表征,并分别负载Fe,进行高浓度有机胺废水的催化氧化降解。结果表明,采用CH3COONa溶液处理ZSM-5分子筛,具有碱改性的作用,且显著提高了催化氧化降解有机胺废水性能。在此基础上,运用正交试验对催化氧化降解有机胺废水条件进行优化,确定出试验范围内的最佳评价条件:反应时间为90 min,反应温度为95℃,催化剂用量为30g/L,溶液初始pH为4,氧化剂H2O2用量为45 m L/L,经过3次验证试验证明,该反应条件具有高度的可靠性和重现性,在此条件下,COD去除率高达98.73%。
基金The study is supported by the National Natural Science Foundation of China(No.41674118)the Fundamental Research Funds for the Central Universities of China(No.201964017).
文摘In elastic-wave reverse-time migration(ERTM),the reverse-time reconstruction of source wavefield takes advantage of the computing power of GPU,avoids its disadvantages in disk-access efficiency and reading and writing of temporary files,and realizes the synchronous extrapolation of source and receiver wavefields.Among the existing source wavefield reverse-time reconstruction algorithms,the random boundary algorithm has been widely used in three-dimensional(3D)ERTM because it requires the least storage of temporary files and low-frequency disk access during reverse-time migration.However,the existing random boundary algorithm cannot completely destroy the coherence of the artificial boundary reflected wavefield.This random boundary reflected wavefield with a strong coherence would be enhanced in the cross-correlation image processing of reverse-time migration,resulting in noise and fictitious image in the migration results,which will reduce the signal-to-noise ratio and resolution of the migration section near the boundary.To overcome the above issues,we present an ERTM random boundary-noise suppression method based on generative adversarial networks.First,we use the Resnet network to construct the generator of CycleGAN,and the discriminator is constructed by using the PatchGAN network.Then,we use the gradient descent methods to train the network.We fix some parameters,update the other parameters,and iterate,alternate,and continuously optimize the generator and discriminator to achieve the Nash equilibrium state and obtain the best network structure.Finally,we apply this network to the process of reverse-time migration.The snapshot of noisy wavefield is regarded as a 2D matrix data picture,which is used for training,testing,noise suppression,and imaging.This method can identify the reflected signal in the wavefield,suppress the noise generated by the random boundary,and achieve denoising.Numerical examples show that the proposed method can significantly improve the imaging quality of ERTM.
