The Electrical Resistivity Tomography (ERT) method is a powerful tool for inferring subsurface structures in landslide investigations. However, its effectiveness is often limited by the inherent non-uniqueness of inversion and the severe smearing artifacts caused by conventional regularization, particularly for delineating thin structures like slip zones. To address these challenges, this paper proposes a unified and application-oriented constrained inversion framework for ERT that flexibly integrates multi-source prior geological information. Building on established constrained inversion concepts, the framework combines structurally guided directional constraints, borehole resistivity constraints, differentiated regional constraints, and localized borehole-derived interface and dip constraints within a consistent Gauss–Newton inversion workflow. The framework integrates different types of constraints into the inversion process, including structural orientations, known resistivity points from boreholes, and pre-determined interface positions. We first demonstrate the efficacy of each constraint type through numerical simulations on a theoretical landslide model. The method was then validated with a comprehensive field study at the Huangtupo landslide in the Three Gorges Reservoir area of China. In-situ resistivity tests within a tunnel system provided characteristic resistivity values for key structural elements (slip zone, slip mass, and bedrock), forming the basis for the reference model. Constrained inversions were performed on four ERT survey lines by incorporating interfaces from seismic ambient noise tomography and orientations from multiple boreholes and tunnels. The results show that, compared with unconstrained inversion, the proposed constrained strategy reduces inversion ambiguity associated with equivalence and suppresses the smearing effects, enabling a clearer identification of multi-level landslide structures that are typically obscured in standard ERT images. Finally, a detailed and reliable 3D model of the landslide was constructed by integrating the interpreted 2D profiles. The proposed constrained inversion approach mitigates the common pitfalls of standard ERT and provides a practical methodological basis for landslide characterization and stability analysis.

Accurate evaluation of the water-bearing capacity of weathered bedrock aquifers is essential for water hazard prevention in shallow coal seam mining in northern Shaanxi.To address the limitations of conventional smoothness-con-strained inversion in Magnetic Resonance Sounding(MRS),including insufficient resolution of aquifer boundaries,inac-curate estimation of volumetric water content(w)and mean relaxation time(T*2),and the consequent large deviations in hydraulic conductivity estimation,a full-envelope signal focusing inversion method based on Minimum Gradient Support(MGS)regularization is proposed.Within the framework of Iteratively Reweighted Least Squares(IRLS),MGS regulariz-ation is introduced to impose focusing constraints on w and T*2,forming a hybrid objective function with optional prior weighting.A dynamic weight updating mechanism is employed,in which a focusing weight matrix is constructed from the gradient information of model parameters at each iteration to control the layering capability of w and T*2.Linear subprob-lems are efficiently solved using the preconditioned conjugate gradient method,and a projection operator is applied to im-pose physically feasible bounds.The focusing factor β governs the degree of stratification.A smaller β enhances interface focusing,while a larger β reduces to smoothness constraints.The optimal β is determined by comparing the results of MGS inversion with those of smoothness-constrained inversion.Numerical simulations demonstrate that MGS inversion significantly improves the stratigraphic characterization of w and T*2.For the weathered bedrock aquifer model,the relat-ive error of w is approximately 6%compared with about 20%for smoothness constraints,and the upper and lower aquifer boundaries can be clearly resolved.Field data from the Hongliulin coal mine indicate that,when aquifer boundaries are de-termined by water content gradients,the positioning error of MGS is about 14.1%,much lower than 43.6%for smooth-ness constraints and 34.4%for the commercial Samovar software.Based on the Seevers model,the hydraulic conductivity calculated from MGS inversion results deviates by about 31.35%from pumping test values,representing improvements of approximately 15%and 47%compared with smoothness-constrained inversion and Samovar,respectively.MGS-based focusing inversion markedly enhances the resolution of aquifer boundaries and improves the inversion accuracy of w and T*2,thereby indirectly increasing the reliability of hydraulic conductivity estimation using the Seevers model.The focusing factor β is a key parameter controlling the balance between stratification capability and smoothness,and more in-telligent and robust strategies for selecting β will be the focus of future research.At present,the application of MRS in coal mines remains relatively limited.This study presents measured MRS data and inversion results for the weathered bed-rock aquifer of the Hongliulin coal mine.The measured signals clearly capture the decay characteristics of NMR re-sponses generated by groundwater,and the inversion results show good consistency with pumping test data from the same location,suggesting that the application potential of MRS in coal mine water hazard investigation warrants further devel-opment.

Groundwater within rock fractures is a major contributing factor to water-induced geohazards. Accurate detection of water-bearing fracture zones is essential for identifying potential water-induced geohazard risks. The Surface Nuclear Magnetic Resonance (SNMR) method is a geophysical technique that detects groundwater by measuring differences in precession frequencies between underground medias. It uses differences in NMR signal relaxation times to identify high-conductivity structures, such as fracture zones, in porous aquifers. Currently, SNMR data inversion primarily depends on Q-Time (QT) inversion, which often encounters challenges in yielding reliable results in practice. This study introduces a deep learning approach for SNMR QT inversion to enhance the imaging accuracy of water-bearing fracture zones. We propose two key parameters to characterize water-bearing fracture zones: fracture zone water content and relaxation time; furthermore, we develop a comprehensive model based on geostatistics and stochastic modeling. Using the SegNet architecture, we designed a deep convolutional neural network for water-bearing fracture zone inversion. Through network training, we established a nonlinear mapping between NMR signals and model parameters. Numerical simulations show that the proposed inversion method effectively distinguishes porous aquifers from water-bearing fracture zones. Related field test successfully imaged water in weathered fracture zones, which is further verified by pumping tests. This study presents a novel method for imaging geological structures, such as water-bearing fracture zones, by combining SNMR with deep learning, offering improved solutions for groundwater-related issues.

Proton exchange membrane fuel cells (PEMFCs) are promising energy conversion devices, and the gas diffusion layer (GDL) plays an important role in reactant transport and water management. Polytetrafluoroethylene (PTFE) is commonly applied to GDL as a hydrophobic treatment to regulate the water management capability. To investigate the relationship between GDL microstructure and surface hydrophobicity, this study developed a boundary-aware deep learning network for phase segmentation of scanning electron microscope (SEM) images, with enhanced capability for both feature extraction and boundary delineation. The model was first used to identify the main structural phases of the GDL and was then further extended to resolve the PTFE phase that is directly related to surface hydrophobicity. Based on the segmented PTFE masks, several microstructural descriptors were extracted to characterize PTFE coverage, continuity, and morphology. The segmented PTFE distribution was further interpreted in the framework of classical wetting theory to elucidate the microstructural basis of apparent hydrophobicity. The proposed framework achieved mean Dice coefficient (mDice) of 0.921 for fiber and binder segmentation. For the segmentation of PTFE phase, the Dice score reached 0.796, respectively. Overall, these results provide a useful route for relating GDL microstructure to hydrophobic behavior, and offer guidance for the microstructure design and hydrophobicity optimization of GDL in PEMFCs.

Proton exchange membrane fuel cells (PEMFCs) are promising clean energy technologies, where multiphysical coupling governs overall performance. The hydrophobicity is crucial for the water management of the gas diffusion layer (GDL). However, the mechanism by which hydrophobicity and structural changes affect the multi-physical performance of GDL remains unclear. In this study, the quantitative relationship between mesoscopic PTFE volume fraction and hydrophobicity was established, and three-dimensional models with different hydrophobicity were reconstructed. The two-phase transport behavior was studied using Lattice Boltzmann method (LBM), while the mechanical response under 30% compression was evaluated through the elastoplastic finite element method (FEM). The effective electrical and thermal conductivity variation with compression ratio and wettability was obtained. Based on the experimental and numerical analyses, the influence of the hydrophobic modification is systematically investigated at multiple scales. When the contact angle exceeds 133 degrees, further increasing hydrophobicity will significantly reduce the porosity and increase tortuosity. Liquid water saturation is primarily governed by hydrophobicity. The gas diffusivity is highest with a contact angle of 122 degrees, and the drainage capacity of GDL is strongest at 135 degrees. Excessive PTFE reduces the stiffness of GDL, whereas GDL with contact angles between 122 degrees and 135 degrees exhibits superior through-plane (TP) conductivity. The study deepens the understanding of the structure-function relationship in the GDL and provides a theoretical and computational framework for the optimization of GDL.

The Mao open-pit coal mine waste dump in Hequ, Shanxi, is a loose, anthropogenic mass accumulated over the original topography. Following a recent sliding and significant settlement event, this dump became the subject of intense stability concerns. Due to the high moisture sensitivity of its interlayered soil and coal gangue structure, rainfall infiltration can reduce internal effective stress, triggering slope instability. Although conventional geological surveys have mapped surface fractures, implementing precise, targeted drainage control requires characterizing the internal geometric structure and preferred seepage directions. To address this, this study integrates electrical resistivity tomography (ERT), surface nuclear magnetic resonance (SNMR), and spontaneous potential (SP) methods. Multiple ERT profiles (270–600 m long) were deployed across several benches at varying elevations, supplemented by fixed-point SNMR sounding over typical low-resistivity anomalies and dense SP grid scanning. The integrated results successfully delineate the internal architecture and seepage characteristics of the dump. Specifically, ERT imaging resolves the primary geoelectrical interface (tentatively inferred as the potential sliding surface) separating the overlying loose mass from the stable underlying strata while mapping the spatial extent of the inferred water accumulation zone (IWAZ). SNMR sounding quantitatively reveals a two-layer water-bearing structure at the specific sounding site, with a deep primary water-bearing zone at 45–80 m depth. Furthermore, SP inversions illuminate the seepage process, demonstrating that meteoric water deflects along the geoelectrical interface to converge laterally toward the central axis at approximately 42°, before transitioning into a high-angle vertical deep infiltration zone (61.7°) within the axial region. These findings suggest a potential engineering direction for remediating surficial fractures and designing subsurface drainage along this 1040 m bench axis, which would mitigate future landslide risks by reducing internal pore water pressure.

Proton exchange membrane fuel cells (PEMFC) are efficient clean energy devices that convert chemical energy into electrical energy through electrochemical reactions. The gas diffusion layer (GDL) is a critical component for energy transfer, mass transport, and mechanical support to the membrane electrode assembly. The anisotropic properties of GDL show obvious structural differences, and the compression effect also significantly affects the pore structure. However, the influence of the coupling effect of the native structure and the compression on the electrical and thermal conductivity of the GDL has not been systematically studied. This study employs the finite element method to examine the effects of various porosity, thickness, carbon fiber diameter, and fiber inclination angles. The maximum fiber inclination angle phi max is defined to reflect the manufacturing process. The heat exchange coefficient between carbon fibers and air is proposed. All structures exhibit nonlinear mechanical behavior, with porosity exerting significant influence on mechanical and conductive properties. The stiffness of GDL increases proportionally with phi max. The GDL with a fiber diameter of 10 mu m exhibits the lowest stiffness under 20 % compression. The electrical and thermal conductivity in the through-plane (TP) direction before and after compression is also proportional to phi max. A phi max of 7.5 degrees benefits in-plane (IP) electrical conductivity under compression but does not enhance thermal conductivity. Compared to an approximate 30 % increase in the effective thermal and electrical conductivity in the IP direction, the effective conductivity in the TP direction is significantly enhanced by several multiples. The findings presented in this work contribute to a deeper understanding of the structural, mechanical, and conductive properties of GDL. And the pore-scale simulation methodology employed can serve as a valuable reference for analogous investigations.

Proton exchange membrane fuel cells (PEMFCs) are one of the most promising technologies for addressing the energy crisis. However, the nonuniform distribution of reactant gases and generated water limits actual performance. In this study, a novel composite flow field was designed by combining serpentine and wavy flow fields. Experimental and simulation work were carried out to study the multiphysical field transport mechanism. Over a wide relative humidity range from 20% to 100%, the maximum power density of the cell clamped by the composite flow field reaches 1.01 W cm-2, representing an improvement ratio of 20.9% compared to the traditional flow field. Under both dry and high-humidity conditions, the charge transfer resistance and mass transfer resistance of the composite flow field decreased by more than 40%. This enhancement is attributed to the distribution uniformity of reactant gases and current density, avoiding a local gas deficiency. Additionally, it promotes the uniform dispersion of generated water through a rapid flow under the flow field ribs. This allows limited water to wet the membrane under dry conditions while preventing local water accumulation or flooding under high-current or high-humidity conditions. Therefore, this study provides valuable insights for developing PEMFCs with superior mass transfer efficiency and high-humidity adaptability.

Combustion metamorphic rocks (CMR) are one of the main concealed disaster-causing factors in coal mines. Magnetic detection is the main method for delineating the distribution range of combustion metamorphic rocks, but accurately identifying the boundaries is a problem that needs to be solved. In order to accurately determine the boundaries of metamorphic rocks in coal fields using magnetic anomaly data, theoretical analysis, model calculation and field experiments were employed to conduct identification studies on the boundaries of single-layer and double-layer metamorphic rocks. Four boundary identification algorithms were selected to process the positive evolution results of the single-layer model, and the boundary identification effects were compared and analyzed; the secondary processing results of various combinations were analyzed, and the combination identification algorithms with better identification effects were selected; the two preferred combination identification algorithms were applied to the double-layer model to determine the optimal combination identification algorithm; the reliability of the boundary identification algorithms was verified through field experiments. The results show that the total horizontal derivative (THDR), vertical derivative (VDR), analytical signal amplitude (ASM), and gradient tilt angle (Tilt) based on the Reduction to the Pole magnetic anomaly (RTP) data can all display the boundaries of the single-layer model to varying degrees. Among them, the total horizontal gradient modulus has higher clarity relying on using the maximum value for identification. The comparison of the results of multiple combinations of secondary processing shows that the result of RTP-THDR-Tilt can clearly identify the boundary of the single-layer and has good continuity of the recognition signal. Further tests on the double-layer model revealed that the results of various combinations of secondary treatment using RTP-THDR-Tilt could effectively determine the boundaries of the superimposed metamorphic rocks; the RTP-THDR-Tilt results obtained from the on-site test data of the coal mine showed that the distribution of the boundary strips was in line with the geological characteristics of the mining area, and the two-layer boundaries of the metamorphic rocks determined by this method were consistent with the drilling and exposure results.

Seepage accelerates the weathering and destruction of cultural heritage sites, posing a major preservation challenge, while the concealed nature of seepage channels complicates their detection due to noninvasive requirements. In this study, we applied a comprehensive geophysical approach, integrating electrical resistivity tomography (ERT) and self-potential (SP) techniques, to image seepage channels within the Leitai heritage site. These potential seepage channels have already caused a collapse pit measuring 3.1 m × 2.7 m on the site’s surface. We began with 2D ERT surveys, which were then combined for 3D inversion to reveal the resistivity structure of the site. Subsequently, SP data were extracted along typical survey lines using interpolation algorithms, and these were inverted to supplement and verify the resistivity structure. The results from both techniques were highly consistent, indicating the presence of internal channels within the site. This comprehensive geophysical approach provides critical insights and references for the subsequent restoration efforts of the Leitai heritage site, ensuring the protection and preservation of this culturally significant landmark. Moreover, the method proposed in this study can be easily applied to the preservation of similar cultural heritage sites elsewhere.

The Ningdong coalfield has played a pivotal role in advancing local economic development and meeting national energy. Nevertheless, mining operations have engendered ecological challenges encompassing subterranean water depletion, land desertification, and ground subsidence, primarily stemming from the disruption of coal seam roof strata. Consequently, the local ecosystem has incurred substantial harm. Water-preserved coal mining presently constitutes the pivotal technology in mitigating this problem. The primary challenge of this technique lies in identifying critical aquifer layers and understanding the heights of water-conducting fracture zones. To obtain a precise comprehension of the seepage patterns within the upper coal seam aquifer during mining, delineate the extent of water-conducting fracture zones, non-invasive geophysical techniques such as time-lapse electrical resistivity tomography (TL-ERT), magnetic resonance sounding (MRS), and spontaneous potential (SP) have been employed to monitor alterations within the shallow coalfield’s aquifer throughout the mining process in the Ningdong coalfield. By conducting meticulous examinations of fluctuations in resistivity, moisture content, and self-potential within the superjacent strata during coal seam extraction, the predominant underground water infiltration strata were ascertained, concurrently enabling the estimation of the development elevation of water-conducting fracture zones. This outcome furnishes a geophysical underpinning for endeavors concerning local water-preserved coal mining and ecological rehabilitation.

Within the lower Wumishan Formation at the eastern edge of the Tai-hang Mountains in North China, a 10 m stratigraphic interval contains alternately "bright and dark" laminites with enigmatic loop structures (2.5–27.5 cm in length and 0.6–12 cm in height), preserved in cross-sectional and named "loopites" in this study. The loopites are composed of cores and annulate laminations. Based on the different morphologies, they can be divided into three different types: type I, II and III. Although the loopites are similar to the loop beddings, the formation mechanisms are different. The former is possibly microbially induced sedimentary structures (MISS), while the loop beddings preserve evidence of soft-sediment deformation structures (SSDS) such as boudinage or chain structures, joints and small-scale tensional faults. All three types of loopites have cores. The type I core is made up of relicts of previous microbial mat and the microhighlands, while the type II and III loopites have cores defined by debris and rock fragments. The cores are completely wrapped by microbial mats of later generation. Thus, we can conclude that the formation of loopites is due to the growth, wrapping and deposition of microbial mats, while loop beddings are generated by external triggering mechanism such as earthquake. Furthermore, the discovery and possible formation of loopites may provide a new type of MISS and indicate a stable, anoxic and carbonate-supersaturated environment favorable for microbial mats to form annulate structures, which are controlled by illumination, microtopography and hydrodynamics.

To investigate the causes of the water seepage damage of the Golden Buddha in the Tongnan Great Buddha Temple, on the basis of engineering geological and hydrogeological investigation and engineering mapping, the seepage mechanism was analyzed by the combination of drilling and physical survey, and the rock structure and the development of rock fissures and weak interlayer near the cliff wall of the cliff Buddha statue, as well as the distribution of groundwater flow field in the mountain behind the cliff statue were identified, and in addition to this, the seepage source, seepage path and fissure seepage mechanism of the Great Buddha were analyzed, which provided technical support for the water damage management of the Great Buddha.

The Baishuihe landslide, a typical large-scale deposit landslide in the Three Gorges Reservoir area, has attracted considerable societal and scholarly attention. Since 2003, 11 displacement monitoring points have been established on the landslide mass for monitoring displacement data. Displacement monitoring data from 14 years have been widely applied in landslide displacement prediction research. However, there is a lack of research involving interpretations of displacement data. To interpret landslide displacement from geological and hydrodynamic perspectives, we applied integrated geophysical methods, including electrical resistivity tomography (ERT), selfpotential (SP), and surface nuclear magnetic resonance (SNMR), to model the landslide structure and investigate groundwater activity. The results indicate that the landslide deposit is predominantly located at the foot of the landslide, with a total volume of approximately 7.7 x 106 cubic meters. The thickness gradually increases in the eastern direction of the landslide along the sliding direction, while in the western direction, it initially increases and then decreases. The SNMR results reveal that groundwater is primarily situated in the gravel soil layer, demonstrating a volumetric water content of approximately 2.8% per unit volume. The SP results suggest that below an elevation of 190 m, the groundwater flow field is turbulent and irregular. Above an elevation of 190 m, the general direction of the groundwater flow field tends to align roughly with the sliding direction. Through the integration of GPS displacement monitoring data and comprehensive geophysical analysis, we discerned that the thickness of the deposit layer, the morphology of the sliding surface, and the interaction with groundwater recharge collectively exert significant influences on the displacement of the Baishuihe landslide. Generally, the thickness of the deposit layer and the morphology of the sliding surface determine whether the landslide will exhibit significant displacement. At a more detailed level, the weight of the accumulated mass and the influence of groundwater play a significant role in determining the displacement velocity.

Proton exchange membrane fuel cell (PEMFC) has been widely recognized as promising applications of hydrogen energy in automobiles and stationary power generation. Water management in PEMFC is crucial at high current densities, where mass transfer polarization and ohmic losses are the primary factors that limit performance. Both the flow field and the microporous layer (MPL) have a significant impact on water management efficiency. In this study, the researchers investigated the synergistic interaction between the flow field and MPL. Two types of flow fields were carefully examined: a single serpentine flow field and a triple serpentine flow field, along with two different MPL loadings. The water retention and mass transfer properties of various flow fields and MPLs were investigated. The maximum power density of the best combination is 9.86% higher than that of the worst combination, reaching 1.47 W/cm2. It was found that the water management properties of the flow fields and the MPL need to be coordinated to achieve effective water management. The essence of synergistic interaction is to facilitate the balance between ohmic resistance and mass transfer resistance by matching the flow field and the MPL. It is indicated that there is no universal optimal MPL loading, and the optimal MPL loading needs to be determined according to the flow field conditions. This work provides a fundamental overview of the engineering development of electrode assemblies.

The gas diffusion layer (GDL) is one of the core components of the proton exchange membrane fuel cell. The complex internal structure of the GDL makes it challenging to accurately predict the mechanical response during clamping compression. In this study, the mechanical properties of the carbon paper-based GDL were investigated using a combination of experimental and numerical simulation. The explicit finite element method (FEM) was used to perform quasi-static compression simulations on the reconstructed GDL. The simulation accounted for the fiber dynamic contact, predicting the true deformation of the GDL. Validation between simulation and experiments was conducted, identifying the initiation point of fiber fracture failure during the compression. The effective range of the elastic constitutive model was determined. The changes in tortuosity, effective diffusivity, absolute permeability, and conductivity in different directions were examined. Reliable experimental results were obtained when the sample quantity was five. Initially, the stress-strain curve exhibited distinct nonlinear characteristics. The equivalent elastic modulus of the GDL continuously increased, stabilizing after a certain compression ratio. With a compression ratio of 27%, the elastic model could accurately reflect the mechanical properties of GDL. Beyond this range, the fiber began to fracture, at which point the stress was 0.064 MPa. Bending and frictional sliding were the main deformation modes of the carbon fibers. The gas diffusion capacity increased first and then decreased; for in-plane direction and through-plane direction, the maximum value appeared at 10 and 5% compression ratio, respectively. The permeability was reduced monotonously. The mass transfer capacity in the in-plane direction of the carbon paper was superior to that in the through-plane direction. The effective conductivity increases in through-plane and in-plane directions were 1354.8 and 57.9%, respectively, at a compression ratio of 35%. Combined with the macroscopic and microscopic levels, it provides a reference for an in-depth understanding of the compressive mechanical properties of fiber porous media and improving the performance of fuel cells.