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Purpose: Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis. Design/methodology/approach: A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN. Findings: The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R2) is 0.93 for the validation set, and the R2 for the test set A and test set B are 0.93 and 0.94, respectively. Originality/value: This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications. [ABSTRACT FROM AUTHOR]

The application of novel injection strategies (high-pressure injection, early injection, retarded injection, etc.) in combustion engines has made the wall-wetting problem severer. As the splashed fuel dilutes the lubricating oil, the tribological performance of the cylinder liner–piston ring pair will be affected. In this research, the viscosity and wettability tests were conducted firstly by mixing diesel into lubrication oil. It was found that the dynamic viscosity of the mixture drops with more fuel diluting the oil, and a small quantity of diesel mixed will cause a remarkable decline in lubricant viscosity; also, the contact angle shows a downward trend with the increasing diluting ratio. Then based on several typical diluting ratios, the reciprocating friction tests were carried out to measure the instantaneous friction force of the production ring/liner pair. The experimental results showed that under a mixed lubrication state, the peak friction force of the ring/liner pair occurs around the dead centers, while the minimum force occurs at the middle position of the reciprocating stroke; with more fuel diluting the oil, the bearing capacity of oil film degrades, resulting in the increase of friction force. In addition, the average friction coefficient of the ring/liner pair shows an upward trend with the increasing diluting ratio, and the Stribeck curve moves toward the upper-left, which means the lubrication condition of this pair tends to transit from mixed lubrication to boundary lubrication, causing negative effects on the frictional property of the cylinder liner–piston ring pair. Therefore, the diluting ratio should be controlled under 20%.

To analyze quasi‐periodic signals (with time‐varying complex amplitudes/frequencies) typically contained in geophysical observables is a quest that has seen continual advances in numerical techniques over the decades. In this study, based on transient z‐pole estimation (in Hankel matrices), a state‐space analysis referred to as Hankel Spectral Analysis (HSA) was developed. Based on the Hankel total least squares and incorporating truncated singular value decomposition and its shift‐invariant property, the HSA aims to decompose the closely spaced sinusoids robustly and orthogonally. Upon using a sliding windows process, the HSA can be used for decomposing and analyzing quasi‐periodic signals, in the support of consecutive parameter spectra {Ai, fi, θi}. Based on a series of experiments, we first confirmed the superiority of the HSA for decomposing different signal constituents (e.g., amplitude‐frequency modulation, mutation, and episodic signals). In real applications, as examples, we use HSA to analyze the polar motion (PM) and Earth's dynamic oblateness (ΔJ2). For the PM, we obtained the time‐varying Chandler wobble (CW) and Annual wobble, and first confirmed that there are four phase jumps in the CW since the 1900s; we find that all of those phase jumps are synchronized by the sharp decrease of Chandler intensity and period, and their random excitation mechanism was discussed. For the ΔJ2, the 18.6 and 10.5 years signals were re‐extracted, and we found that its interannual‐to‐decadal oscillations contribute to multiple global gravity anomalies. These results indicate the great potential of the HSA in decomposing and extracting the recorded periodic/quasi‐periodic signals from geophysical observations. In signal analysis, the refined extracting of the periodic and quasi‐periodic signals remains a considerable challenge. In this study, we propose a powerful time‐series separator, the Hankel Spectral Analysis (HSA), which supports instant structured detection that traditional methods cannot afford. We have designed multiple sets of simulations to show the HSA's well‐restored ability for various and complex quasi‐periodic signals. Although the HSA has some significant advantages, it has two fundamental limitations: (a) it is applicable only to data series which are physically constituted by a sum of harmonic components; (b) the number of harmonic components needs to know beforehand. In the real application, we focus on the study of polar motion (PM) and the Earth's dynamic oblateness (ΔJ2). Here, we mainly attempted to resolve their recent disputes about the Chandler wobbles (CW) phase jumps in PM and the long periodic signal in ΔJ2. Subsequently, the origins of CW phase jumps are re‐examined; and our results show that there is a particular consistency between the four‐phase jump events and the valleys of amplitude and period. In addition, we re‐extracted the ∼18.6 and 10.5 years signals in ΔJ2and found that the famous “1998 anomaly” related to the fluctuations on interannual‐decadal timescales. Hankel Spectrum Analysis is proposed for more exactly decomposing and parameterizing signals with time‐varying amplitudes/frequenciesMultiple phase jumps of the Chandler wobble accompanied by sudden drops in instantaneous amplitude and period are detectedWe access the Earth's oblateness ΔJ2of the residual ∼18.6 years tidal signal, ∼10.5 years signal, and multiple global gravity anomaly peaks Hankel Spectrum Analysis is proposed for more exactly decomposing and parameterizing signals with time‐varying amplitudes/frequencies Multiple phase jumps of the Chandler wobble accompanied by sudden drops in instantaneous amplitude and period are detected We access the Earth's oblateness ΔJ2of the residual ∼18.6 years tidal signal, ∼10.5 years signal, and multiple global gravity anomaly peaks

Selective separation of molybdenum(Mo) and vanadium(V) from hazardous secondary resources containing Mo and V has become a technical bottleneck of its resource utilization. In this work, the selective separation of Mo and efficient recovery of V from simulated leaching solutions of spent hydrodesulfurization (HDS) catalysts were investigated via solvent extraction and chemical precipitation. The result indicates that the D2EHPA(P204) exhibits higher selectivity for Mo in strongly acidic conditions. Under optimum experimental conditions of hydrochloric acid of 1 mol/L, extractant concentration of 20 % (v/v), O/A ratio of 1:3 and contact time of 50 min, the single-stage extraction ratio of Mo reached 98.63 %, meanwhile, the co-extraction ratio of vanadium was less than 5 %. Additionally, over 97 % of Mo could be stripped from loaded organic phase at O/A ratio of 1 with 50 g/L NH4HCO3. The mechanism analysis revealed that selective extraction of Mo was mainly through the cation exchange mechanism. Moreover, the enthalpy changes in the molybdenum extraction were 44.1 kJ mol−1, which demonstrated that was an endothermic reaction. Furthermore, the Fe(III) was adopted to fabricate FeVO4by precipitating vanadium from raffinate, and the precipitation efficiency of vanadium reached 97.71 % at a Fe/V molar ratio of 5/2, meanwhile, the precipitation product was further confirmed by XRD, XPS and SEM-EDS. Ultimately, a conceptual flowsheet for recovering completely Mo and V from simulated leaching solutions of spent HDS catalysts was proposed, which provides theoretical guidance for the resource utilization of containing molybdenum and vanadium secondary resources.