Multi-task unscented Kalman inversion (MUKI): a derivative-free joint inversion framework and its application to joint inversion of geophysical data

In the geophysical joint inversion, the gradient and Bayesian Markov Chain Monte Carlo (MCMC) sampling-based methods are widely used owing to their fast convergences or global optimality. However, these methods either require the computation of gradients and easily fall into local optimal solutions, or cost much time to carry out the millions of forward calculations in a huge sampling space. Different from these two methods, taking advantage of the recently developed unscented Kalman method in computational mathematics, we extend an iterative gradient-free Bayesian joint inversion framework, i.e., Multi-task unscented Kalman inversion (MUKI). In this new framework, information from various observations is incorporated, the model is iteratively updated in a derivative-free way, and a Gaussian approximation to the posterior distribution of the model parameters is obtained. We apply the MUKI to the joint inversion of receiver functions and surface wave dispersion, which is well-established and widely used to construct the crustal and upper mantle structure of the earth. Based on synthesized and real data, the tests demonstrate that MUKI can recover the model more efficiently than the gradient-based method and the Markov Chain Monte Carlo method, and it would be a promising approach to resolve the geophysical joint inversion problems.Comment: 13 pages, 4 figure

Hydrocarbon generation and expulsion modeling of different lithological combination source rocks from the Funing Formation in the Subei Basin

The oil expulsion efficiency and retention efficiency of shale affect the enrichment and preservation of shale oil. Two series of semi-closed hydrous pyrolysis experiments were performed under in situ geological conditions on a Paleogene shale sample as a comparable analog to evaluate the generation and preservation potential of shale oil in the Funing Formation shale in the Subei Basin. The results show that 1) the oil-generation capacity evolution of different lithological combination source rocks in the Funing Formation of the Subei Basin can be roughly divided into four stages: a) relatively slow oil-generating and slow gas-generating, b) relatively fast oil-generating and slow gas-generating, c) oil cracking into gas, and d) kerogen cracking into gas; 2) different lithological combinations have different hydrocarbon generation, expulsion, and retention efficiencies. The total oil generation rate and gas generation rate of pure shale are higher than those of shale with a silty interlayer, and the exchange point between the oil expulsion rate and retention rate of pure shale is earlier than that of shale with the silty interlayer, which indicates that the pure shale experienced the expulsion and retention process earlier. Oil retention mainly occurs at an EqVRo of 0.84%–1.12%, while oil is mainly discharged to the adjacent siltstone at an EqVRo of 1.12%–1.28%. Based on the simulation under geological conditions, it is recognized that for shale oil exploration in the Subei Basin, the favorable thermal maturity is at an EqVRo of 0.84%–1.12%, and the favorable lithology is the shale with the silty interlayer. On one hand, the siltstone interlayer can provide pore space for the early generated oil, and the concentration difference of hydrocarbons between the shale and the interlayer can be formed so that the generated shale can continuously enter the interlayer. On the other hand, the shale above the interlayer can be used as a cap rock to preserve shale oil. The favorable area for shale oil exploration in the Subei Basin is the area with relatively high maturity (at a VR value of about 1.1%

Simultaneously enhancing the strength and ductility in titanium matrix composites via discontinuous network structure

In this study, titanium matrix composites reinforced with graphene nanoplates (GNPs) were successfully prepared via an in-situ processing strategy. Both TiC nanoparticles and TiC@GNPs strips are in-situ formed at the grain boundaries, and enhance interfacial bonding strength between GNPs and Ti matrix by acting as rivets in the microstructure. The GNPs can be retained in the center of TiC layer, which provides a shielding protection effect for the GNPs. These in-situ formed TiC nanoparticles are linked together to form a discontinuous and three-dimensional (3D) network structure. Due to the formation of 3D network architecture and improved interfacial bonding, the composites show both high strength and good ductility. The significant strengthening effect reinforced by the GNPs can be attributed to a homogeneous distribution of in-situ formed TiC nanoparticles and TiC@GNPs strips, resulting in TiC interface/particle strengthening and excellent interfacial load transfer capability

Charge transport through dicarboxylic-acid-terminated alkanes bound to graphene-gold nanogap electrodes

Graphene-based electrodes are attractive for single-molecule electronics due to their high stability and conductivity and reduced screening compared with metals. In this paper, we use the STM-based matrix isolation I(s) method to measure the performance of graphene in single-molecule junctions with one graphene electrode and one gold electrode. By measuring the length dependence of the electrical conductance of dicarboxylic-acid-terminated alkanes, we find that transport is consistent with phase-coherent tunneling, but with an attenuations factor βN = 0.69 per methyl unit, which is lower than the value measured for Au-molecule-Au junctions. Comparison with density-functional-theory calculations of electron transport through graphene-molecule-Au junctions and Au-molecule-Au junctions reveals that this difference is due to the difference in Fermi energies of the two types of junction, relative to the frontier orbitals of the molecules. For most molecules, their electrical conductance in graphene-molecule-Au junctions is higher than that in Au-molecule-Au junctions, which suggests that graphene offers superior electrode performance, when utilizing carboxylic acid anchor groups

Multi-task Unscented Kalman Inversion for joint inversion of receiver function and surface wave dispersion

Based on the recently developed theory of Unscented Kalman Inversion in computational mathematics, we proposed a Bayesian joint inversion framework, i.e., Multi-task Unscented Kalman Inversion (MTUKI), and apply it to the joint inversion of receiver function (RF) and surface wave dispersion (SWD). This method can share information between different observations in a derivative-free way and provide an efficient Gaussian approximation to the posterior distribution of model parameters (thickness and S-wave velocity in each layer of media). The theory and experiments show that our proposed framework demonstrates superior performance in terms of robustness, accuracy, and high efficiency.Comment: 5 pages, 3 figure

Influence of αs precipitates on electrochemical performance and mechanical degradation of Ti-1300 alloy

The influence of αs precipitates on electrochemical behavior and mechanical degradation of Ti-1300 alloy in artificial seawater have been studied. The results show that corrosion resistance and mechanical degradation have been significantly affected by the formation of acicular αs precipitates. The precipitated αs phase with an acicular shape around 40–60 nm in width are uniformly distributed inside β grain. Many αs precipitates are intersected each other and keep a well-defined Burgers orientation relationship with β matrix, which restricts the growth of other αs phases due to pinning effect. Within the electrolyte, the αs phases can form “microgalvanic cells” with their adjacent intergranular β phases, which dramatically deteriorate its corrosion resistance. The mechanical properties of the alloy are also degraded with the increase of immersion time due to the pitting reaction. The precipitated microstructure exhibits an inferior mechanical degradation behavior, and this is mainly because a lot of corrosion cavities are nucleate d and propagated at the interface between αs precipitates and prior β grains

Application of sparry grain limestone petrographic analysis combining image processing and deep learning

Traditional carbonate rock slice identification is based on manual observation and description, which is highly subjective, mainly qualitative and difficult to quantify. In this paper, an intelligent rock thin-section image information mining model covering the process and technology is designed. The mapping relationship between lithofacies characteristics and thin slice images is constructed through a petrographic analysis framework. A full-flow feature extraction algorithm is also designed by combing image processing and deep learning. Qualitative recognition of grain type in structural component features is obtained by convolutional neural network, that is, the classification of grains (intraclasts, bioclasts, envelopes, spherulites and agglomerates) based on the improved ResNet50 model. Quantitative recognition of grain content, size, shape and contact mode in structural component features are obtained by digital image processing, that is, grain content is calculated based on threshold segmentation, grain morphology parameters are calculated based on minimum peripheral circle/minimum peripheral rectangle and by combining with area ratio/aspect ratio, intersection ratio (IoU) and other algorithms. And the qualitative and quantitative identification of calcite and other minerals in mineral component features are obtained by HSV colour space processing of the stained images. A thin section example from Shun X well is given as an example, and the validity of each feature extraction algorithm is verified through the complete image recognition process and comparison with the manual identification report. The results show that the petrographic analysis framework is effective in representing meaningful information in sparry grain limestone. Through the model of combing petrographic analysis framework with image analysis algorithm, a standard and intelligent identification of this type of carbonate rocks has been achieved, which can provide effective method support for the study of intelligent identification of rock slice images

Carbon use efficiency of terrestrial ecosystems in desert/grassland biome transition zone: A case in Ningxia province, northwest China

Terrestrial ecosystems play a critical role in the global carbon cycle and the feedbacks of carbon cycle will significantly impact future climate change. It's worth noting that semi-arid biomes in the Southern Hemisphere have driven the global carbon sink anomaly over the past 30 years. However, how does the desert/grassland biome transition zone, a part of arid and semi-arid biomes, respond to climate change and anthropogenic activities in carbon use efficiency (CUE) is still unclear. Therefore, based on the CUE of terrestrial ecosystem estimated by the moderate resolution imaging spectroradiometer (MODIS) data from 2001 to 2017, the spatial and temporal characteristics of CUE in Ningxia province, a typical desert/grassland biome transition zone, were studied. The main driving factors in climate and ecosystem were also investigated by partial correlation analysis. Results showed that the CUE of terrestrial ecosystems in desert/grassland biome transition zone is higher than 0.5, a constant value of CUE defined in many ecological models. However, the CUE varies with the ecosystem types even when they are located in the same climatic zone. There is a decreasing trend of annual CUE in the period of 2001–2017 and most of them will persistently decrease in future at pixels scales, which could be mainly caused by the land use change. Comparing the habitat conditions, we found the lower canopy density and water stress could increase the CUE in the same ecosystem, which indicates the plant could increase their efficiency of transforming carbon from the atmosphere to terrestrial biomass in adverse environment. Finally, the CUE significantly correlated to net primary productivity (NPP) and autotrophic respiration (Ra) in ecosystem processes, meanwhile water stress (lower precipitation) and heat stress (higher temperature) could increase the CUE, but the temperature has variable impacts in different ecosystem

Hierarchical Amplitude-Aware Permutation Entropy-Based Fault Feature Extraction Method for Rolling Bearings

In order to detect the incipient fault of rolling bearings and to effectively identify fault characteristics, based on amplitude-aware permutation entropy (AAPE), an enhanced method named hierarchical amplitude-aware permutation entropy (HAAPE) is proposed in this paper to solve complex time series in a new dynamic change analysis. Firstly, hierarchical analysis and AAPE are combined to excavate multilevel fault information, both low-frequency and high-frequency components of the abnormal bearing vibration signal. Secondly, from the experimental analysis, it is found that HAAPE is sensitive to the early failure of rolling bearings, which makes it suitable to evaluate the performance degradation of a bearing in its run-to-failure life cycle. Finally, a fault feature selection strategy based on HAAPE is put forward to select the bearing fault characteristics after the application of the least common multiple in singular value decomposition (LCM-SVD) method to the fault vibration signal. Moreover, several other entropy-based methods are also introduced for a comparative analysis of the experimental data, and the results demonstrate that HAAPE can extract fault features more effectively and with a higher accuracy

Dynamic Characteristics Analysis and Experimental Verification of Long Span Suspension Bridge

The dynamic characteristics of long-span suspension bridges are complex. The natural vibration frequency is changed with different structural parameters, and the sensitivity to different parameters is different. In order to solve this problem, the spatial model of a long-span suspension bridge was established by using finite element software, and the first 20 natural vibration periods, natural vibration frequencies and vibration modes were analyzed and calculated. The accuracy of the obtained natural vibration frequency data was verified through field tests. Finally, based on the model, the stiffness of structural components is studied by one -factor-at-one-time, and the influence of various variables on the frequency and mode of a certain mode is studied by one-factor-at-one-time method. The results show that different structural parameters have different effects on the vibration frequency. When the stiffness of stiffening girder and main tower is changed, with the increase of stiffness, the variation of frequency mostly presents an upward trend, and the range is large. With the change of the secondary dead load, most of the frequencies decrease first and then tend to be stable. It can be seen from the field test results that the vibration shapes and frequencies measured by numerical simulation and test are close to each other, which can meet the requirements of engineering precision. The stiffness of the main cable and the main tower has a great influence on the modes and periods corresponding to them. The increase of the secondary dead load can reduce the natural vibration frequency of the suspension bridge, but it is not unlimited to increase the secondary dead load to reduce the frequency. The stiffness of the stiffening girder has a great influence on the frequency of the suspension bridge. When the bending stiffness of the stiffening girder increases to 3 times of the original one, the order of vibration modes of the structure will change. The research results can provide references for structural design and dynamic parameter adjustment of long-span suspension bridge