Stress wave propagation in jointed rock masses is a fundamental issue for the dynamic stability evaluation of rock engineering structures. Traditional numerical methods rely heavily on predefined empirical constitutive models, while a priori constitutive selection and subjective parameter inversion inevitably introduce significant errors in wave propagation prediction. To address this critical limitation, this study proposes a model-free data-driven computational mechanics for dynamic response analysis of jointed rock masses, establishing a dual “rock-joint” discrete data-driven framework. In this framework, the rock matrix is discretized with solid elements, while discontinuous joint surfaces are explicitly characterized using Goodman joint elements. Computations are directly driven by the synergistic coupling of three discrete mechanical databases: the rock stress–strain database, joint normal stress-displacement database, and joint tangential stress-displacement database, completely eliminating the need for conventional constitutive equation formulation. Furthermore, the framework seamlessly integrates viscous dynamic artificial boundaries with an equivalent nodal force seismic input mechanism, and employs GPU parallel computing alongside hierarchical search strategies to accelerate the mapping of physically admissible states and the retrieval of material data states. Systematic validation through a series of cases, ranging from single joints to complex cross-joint networks, demonstrates that the data-driven solutions are in excellent agreement with classical analytical solutions and conventional Jointed Finite Element Method (JFEM) results, accurately capturing complex dynamic characteristics such as wave energy transmission and reflection, nonlinear repeated opening and closing of joints, and multi-wavefield interference. Computations utilizing measured data from natural joints, combined with database coverage verification, further confirm the reliability of this method in predicting dynamic responses directly from real discrete data. Finally, sensitivity and efficiency analyses verify parameter robustness and computational scalability. This work provides a novel, high-fidelity computational paradigm for wave propagation analysis in jointed rock masses directly utilizing discrete material data.

Interfacial micro-cracks can compromise the sealing and barrier performance of subsurface energy systems, yet their dielectric observability and electromagnetic wavefield expression remain insufficiently quantified under roughness, local contact, fluid infill, and background heterogeneity. Here, we establish an integrated experimental–numerical framework for cracked bilayer interfaces by combining waveguide-based microwave measurements, REV-scale dielectric homogenization, analytical mixing-law benchmarking, and 6-GHz FDTD wavefield simulations. Waveguide measurements over 5.35–8.17 GHz demonstrate that intact interfaces, air-filled cracks, and water-filled cracks can be distinguished through S-parameters, retrieved effective permittivity, and reflection–transmission–absorption energy partitioning. Numerical homogenization shows that crack inclination and volume fraction primarily control the real effective permittivity, roughness and spatial position modulate dielectric contrast through field redistribution, and salinity is more clearly expressed through effective conductivity. Benchmarking against BHS, CRIM, and LLCM indicates that phase-fraction-based mixing laws may substantially overestimate the contribution of high-permittivity crack fillings when rough-surface mismatch and local solid-to-solid contact are present, whereas a calibrated BHS model with c = 0.75 gives the closest approximation within the examined range. FDTD simulations further show that crack-induced dielectric contrasts generate observable reflection–diffraction characteristics in A-scan, B-scan, and spectral responses. Reference-based residual-wavefield descriptors reveal that crack state mainly reorganizes spatial and spectral energy distributions rather than producing simple monotonic amplitude enhancement. These findings provide a physically constrained basis for interpreting interfacial micro-crack states in high-frequency GPR-based nondestructive assessment of bilayer systems.

Underground hydrogen storage, involving periodic injection and extraction of hydrogen gas, serves as a crucial approach for achieving energy peak shaving and accommodating large-scale renewable energy. However, microorganisms residing underground may undergo metabolic reactions when stimulated by hydrogen, producing gases and altering rock surface properties. This could potentially influence hydrogen migration and storage behavior, yet the underlying mechanisms remain poorly understood. To address this, this study introduces microbial reactions within a microfluidic chip and combines hydrogen displacement experiments under varying pressure differentials to reveal two distinct phenomena by which microbial activity influences hydrogen flow pathways. It was observed that when microbially produced gas communicates with hydrogen, it triggers a readjustment of flow pathways and accelerates the advancement of the hydrogen front. In addition, when microbially produced gas forms stable gas mass downstream in the pore network, it induces shifts in dominant flow pathways. Contact angle measurements further confirm that microbial metabolism significantly reduces pore surface wettability, though this wettability change exhibits pronounced spatial heterogeneity. Displacement results under varying pressure differentials reveal that at low pressures, reduced capillary resistance facilitates sweep range and higher hydrogen saturation. Conversely, at high pressures, viscous flow dominates; weakened wettability accelerates breakthrough while inhibiting lateral branch development, ultimately reducing overall saturation. This study provides novel experimental evidence for understanding microbe-flow interactions during underground hydrogen storage.

The integrity evolution of cement–caprock systems in CO2-rich environments is critical for assessing wellbore leakage risks in CO2 geological utilization and storage projects. While existing studies have provided valuable insights into this issue, limited attention has been given to shale—a common caprock—and especially to the role of pre-existing fractures in governing the reaction processes within cement-shale-brine-CO2 systems. Therefore, this study conducted a 35-day corrosion experiment on fracture-bearing cement-shale composites under typical CO2 geological storage conditions (50 °C, 10 MPa, 1 wt

Underground hydrogen storage in aquifers (UHSA) is a promising approach for large-scale, cyclical hydrogen storage. However, indigenous hydrogenotrophic microorganisms may utilize hydrogen for biochemical reactions, potentially causing issues such as pore clogging and hydrogen loss. These microbial activities are further influenced by multi-physical fields such as fluid flow and temperature. In this study, we developed a coupled thermo-hydro-bio-chemical model for UHSA. Numerical simulation of a base-case scenario was conducted to investigate the spatiotemporal distribution of microorganisms, evolution of reservoir porosity, and hydrogen recovery performance. In addition, we analyzed the impact of various hydrogen injection strategies on biochemical effects. Our results indicate that microbial populations generally exhibit a growth-then-decay trend, and convective flow during the production stage can reduce microbial concentrations. Injecting low-temperature hydrogen helps suppress the formation of high-density microbial communities. Microorganisms are accumulated in the low-temperature zone during the production stage, resulting in substantial microbial decay which is favorable for hydrogen storage. Porosity evolution during the hydrogen storage process is primarily governed by microbial adsorption in the early stage and by mineral dissolution and precipitation in the later stage, showing a slight increase followed by a decrease. Nonetheless, the overall variation in porosity is negligible, exerting minimal influence on the flow behavior. Biogeochemical reactions lead to a 9.53% hydrogen loss and a 5% reduction in recovery efficiency. Compared to other injection strategies, slow and pulsed hydrogen injection induces a weaker microbial response. These findings enhance understanding of the biochemical impacts in UHSA and provide technical insights for practical applications.

Interfacial debonding in bi-layer composites commonly manifests as millimeter-scale fractures that alter microwave scattering and attenuation, yet quantitative links between crack state and effective dielectric response remain insufficiently constrained. Here, we develop and validate a waveguide S-parameter–based characterization framework to retrieve the effective complex permittivity of bilayer structures containing interfacial fractures over 5.8 GHz to 8.2 GHz. The inversion workflow is verified against both full-wave numerical simulations and laboratory waveguide measurements, and is further employed to systematically elucidate the coupled effects of crack geometry, spatial distribution, and infilling media on reflection, transmission attenuation, and the partitioning of energy dissipation. Results show that dry interfacial cracks primarily affect the energy-storage response. The real part of the effective permittivity decreases monotonically as the crack volume fraction increases from 1 % to 10 %, producing deviations of 0.93 % to 8.72 % relative to the intact interface. When the crack filling transitions from air to distilled water, the response shifts from a permittivity-real-part offset to a loss-dominated regime, characterized by pronounced transmission suppression accompanied by enhanced absorption. Moreover, under identical constituent properties, changing the crack inclination leads to up to a 5.37 % variation in the real part of the effective permittivity, indicating that orientation-driven geometric anisotropy significantly modulates the dielectric response. This study presents a validated inversion route for retrieving effective complex dielectric properties, providing a non-destructive means to evaluate the interfacial integrity of bi-layer structures in subsurface energy engineering.

The deformation and stress distribution of fractured rock masses under external loads remain key scientific challenges, primarily due to their inherent heterogeneity, discontinuity, and anisotropy. To address this, this study proposes a model-free data-driven computational mechanics for deformation analysis of fractured rock masses, which can more accurately capture their mechanical response under external loading. This method bypasses traditional constitutive modeling by directly incorporating experimental data, including rock stress-strain data, joint normal stress-displacement data, and tangential stress-tangential displacement data. Solutions are obtained by minimizing the distance between these data points and those satisfying the conservation equations (i.e. equilibrium and geometric equations). Specifically, the fractured rock mass is regarded as a binary system consisting of rocks and joints, with the rocks represented by solid elements and the joints simulated through Goodman elements to capture discontinuous deformation behavior accurately. The validity and computational accuracy of the model-free data-driven computational mechanics for deformation analysis of fractured rock masses are verified by comparing the data-driven solution with a reference solution based on the constitutive model through typical numerical calculations. Furthermore, validation with real experimental data confirms that the method offers significant advantages in analyzing the nonlinear mechanical behavior of fractured rock masses, providing a unified and practical numerical approach for studying the deformation response of fractured rock masses.

Debonding at the concrete–rubber interface, driven by air leakage, is recognized as a primary factor contributing to the failure of the rubber sealing layer in compressed air energy storage (CAES) caverns. However, the mechanism of air-driven debonding at the concrete–rubber interface in CAES caverns remains poorly understood. This study investigates the debonding mechanism using experimental testing and numerical simulation methods. The cohesive performance of the interface is evaluated through a three-point bending test. Based on the experimental results, the cohesive element parameters in ABAQUS software are used to accurately describe interface debonding behavior. Additionally, a three-dimensional numerical model is developed to simulate air-driven debonding using the coupled pore pressure cohesive zone method. The study analyzes the debonding process, seepage behavior, and structural stress distribution in the cavern structure. Furthermore, the effects of air temperature and pressure inside the CAES cavern on interface debonding are examined. The interface pressure at the leakage point fluctuates significantly during the debonding process, primarily influenced by the debonding area and height. As air leakage progresses, both the debonding range and debonding height at the interface continue to increase. In addition, air leakage significantly affects pore pressure and structural stress distribution in the cavern structural layer. Higher air pressure leads to an increase in both fracture breakdown pressure (FBP) and debonding range, whereas higher temperatures exhibit the opposite trend, reducing both FBP and debonding extent. Highlights

Pre-fracturing energy enhancement has shown promising potential to improve stimulation performance in low-permeability reservoirs, yet its influence on subsequent hydraulic fracturing remains unclear. This study develops a fully coupled hydro-mechanical model based on the XFEM to simulate this integrated process. Both displacement and pressure fields are discretized using XFEM with appropriate enrichment functions, enabling accurate representation of fracture-induced discontinuities. A unified computational framework is established to solve the coupled hydro-mechanical response during two sequential stages: energy-enhanced injection and hydraulic fracturing. The model accuracy is validated against the classical KGD problem in permeable media. Numerical analyses are conducted to investigate stress redistribution and pore pressure evolution during energy enhancement. Parametric studies are performed to quantify the influence of injection volume, injection rate, matrix permeability, shut-in time, and fracture initiation location on fracture propagation behavior. Results show that energy enhancement elevates pore pressure and total stress, thereby reducing fluid leak-off and enhancing fracturing efficiency, though at the cost of higher injection pressure. Specifically, in a 1 mD reservoir, 30-day energy enhancement via water injection at a rate of 2.61 m3/(m·day) raises fracture propagation pressure by over 5.63 MPa compared to the non-enhanced case, while fracturing efficiency improves from 51.09% to 80.5%, and fracture length increases from 24.7 m to 50.0 m under a stimulation time of 40 s. Fracture initiation location significantly influences fracture propagation path, aperture, and symmetry. Initiating a fracture 10 m away along the minimum stress direction results in a symmetric but deflected path, with a maximum tip deviation of 3.96 m at a 50 m fracture length. In contrast, initiation along the maximum stress direction results in severely asymmetric propagation. The growth of one wing is strongly suppressed, extending only about 5 m when the total fracture length is 50 m. These findings provide critical insights for optimizing energy-enhanced fracturing treatments in unconventional reservoirs.

Air leakage in rubber-sealed compressed air energy storage (CAES) caverns is inevitable, making an accurate evaluation of cavern airtightness essential. However, air permeation through the rubber sealing layer is strongly influenced by temperature and pressure. Previous studies have often neglected these effects and instead adopted fixed parameter values to describe air permeation in rubber. Such simplifications have led to inaccurate assessments of cavern airtightness. In this study, the effects of temperature and pressure on the airtightness of a rubber-sealed cavern are considered, and the cavern airtightness during the operation of CAES is evaluated. Permeation pressure tests were conducted on rubber samples under varying temperature and pressure conditions using a dedicated experimental setup. Based on the experimental results, a modified model for the solution and diffusion coefficients was then developed to explicitly account for their coupled effects. To validate the accuracy of the solution–diffusion model and its associated parameters, a numerical model consistent with the experimental parameters and boundary conditions was established. Finally, an engineering-scale numerical model of a rubber-sealed cavern was developed to simulate air leakage during the CAES process. The results indicate that the predicted air leakage rate, when accounting for the temperature-pressure coupling effect, is higher than that predicted without this consideration. The maximum instantaneous leakage rate rises from 0.16 kg/s to 0.35 kg/s, and the 24-hour air loss rate of the cavern increases from 0.11% to 0.16%. Furthermore, the pore pressure of the lining and surrounding rock, as calculated by the modified model, exceeds that of the unmodified model. Following a long-term CAES cycle, the cavern pressure predicted by the modified model is lower than that from the unmodified model, with a calculated difference of 0.25 MPa at the 200th cycle.

Accurately evaluating the dynamic response of rock masses under seismic loading remains a critical challenge in geotechnical engineering. However, existing numerical methods generally rely on empirical constitutive models, whose selection and parameter calibration are highly sensitive to computational results, making it difficult to objectively and accurately capture the complex mechanical behavior of rock masses. To address this issue, this study proposes a model-free data-driven computational mechanics for seismic response analysis of rock masses, which directly employs experimental stress-strain data for dynamic computations, thereby fundamentally avoiding the empirical assumptions and uncertainties inherent in conventional constitutive modeling. Within the data-driven computational framework, five typical dynamic artificial boundaries-namely viscous boundary, viscous-spring boundary, free-field boundary, seismic input boundary, and static-dynamic unified boundary-are systematically incorporated to significantly enhance the physical consistency and accuracy of seismic wave propagation and dynamic response simulations. Furthermore, by integrating GPU parallel computing with a hierarchical data search algorithm, the method achieves efficient acceleration of both linear system solving and database retrieval. Validation through benchmark examples, including elastic bar, ground surface models, and slope models, demonstrates that the proposed approach can accurately and stably reproduce the seismic dynamic response of rock masses, exhibiting strong robustness and broad applicability.

The long-term deformation mechanisms of high-steep rock slopes excavated in stages remain insufficiently understood, particularly regarding the progressive degradation of rock mass properties induced by continuous excavation. In this study, a parameter inversion-based framework is proposed to investigate excavation-induced rock mass degradation and its role in controlling slope deformation evolution. A surrogate model mapping rock mass mechanical parameters to surface displacements was established by integrating numerical simulations with a backpropagation neural network (BPNN). Particle swarm optimization (PSO) was subsequently employed to invert the time-varying rock mass parameters by matching monitored and predicted displacement sequences at different deformation stages. The proposed framework was validated using a representative excavated rock slope. Multi-stage inversion results indicate that continuous excavation leads to progressive degradation of key rock mass parameters, particularly cohesion (c) and Young’s modulus (E), which decrease by approximately 50% and 30%, respectively, over the deformation process. Correspondingly, numerical simulations reveal a gradual expansion of plastic zones within the slope, followed by plastic zone coalescence after a critical excavation stage, marking the transition from stepwise deformation to accelerated displacement. The inverted parameters and simulated responses show good agreement with monitored displacement data, confirming the reliability of the proposed approach. The results demonstrate that continuous excavation alone can drive progressive rock mass degradation, plastic zone development, and the transition from stepwise to accelerated deformation in high-steep slopes. The proposed parameter inversion framework provides an effective tool for interpreting excavation-induced deformation mechanisms and assessing long-term slope stability.

This article establishes a three-dimensional numerical model of shrinkage cracking of cementitious materials using the coupled Peridynamics (PD)-Finite Element Method (FEM). The dry shrinkage cracking mechanism in concrete are investigated through numerical simulations. The obtained results indicate that crack propagation mainly occurs in early stages of drying when pore pressure gradients are high in cementitious materials. While stiffness difference between aggregate and cement matrix promotes crack initiation, it is not a necessary condition for shrinkage cracking. The effects of aggregate properties-stiffness, particle size, and volume fraction-on shrinkage cracking exhibits non-monotonic behavior. Increased aggregate stiffness and volume fraction promote tensile tensile stress zones between aggregates, inducing crack propagation. Concurrently, these factors enhance the overall material stiffness and strength, limit deformation and failure. Consequently, crack area increases only with increasing aggregate stiffness and volume fraction. This study contributes to the understanding of concrete shrinkage behavior and provides insights for optimizing concrete mix designs to mitigate shrinkage-induced cracking.

As CO2 geological utilization and storage becomes a promising strategy for reducing excess CO2, the interactions among host rock, groundwater, and CO2 become an inevitable process that demands careful consideration. Despite considerable research on this process, few studies have monitored the in-situ pH evolution of the rockCO2-water system under high pressure and temperature and integrated these findings with numerical models to deduce the underlying mechanisms. In this study, four different rock-CO2-water interaction experiments under conditions of 15 MPa and 50 degrees C, equipped with spectroscopic in-situ pH measurement, are carried out, and the water chemistry and mineral compositions are also determined. Validated geochemical models are then established to investigate the long-term interaction characteristics and identify the controlling reactions in different systems. The results show that pH variations of the sandstone and granite-contained system are mainly controlled by the dissolution of carbonate minerals, while the dissolution of diopside dominates pH in the basalt-contained system. Consequently, pH stabilization occurs significantly ahead of the system's interaction equilibrium. Moreover, the long-term interactions within these systems exhibit obvious stage characteristics, driven by the varying reactivities of the minerals involved. The carbon mineralization potentials of different rock samples are assessed afterwards, with basalt demonstrating superior performance, followed by sandstones, whereas granite exhibits no capacity for carbon fixation. This work provides new experimental data and offers insights into the mechanisms governing rock-CO2-water interactions. It is hoped that these findings will provide new perspectives on the experimental and simulation approaches, as well as deepen the mechanistic understanding of rock-CO2-H2O interactions in the context of CO2 geological utilization and storage.

The growth of pre-existing bedrock fractures in running water plays an important role in landscape evolution. How fractures, formed by other geological processes, can be extended further by moderate water pressure to create blocks that can then be plucked by the flowing water is an open question. In this paper, the effect of hydrodynamic forcing on fracture growth that results in bedrock erosion is studied quantitatively to address this question. The fracturing process depends on the pre-existing fracture geometry, bedrock surface topology, local stresses, water flow rates and rock properties. A fracture-mechanics model coupling rock deformation and fluid flow is used to investigate the hydraulic conditions for propagation of a single pre-existing bedrock fracture. The numerical results show that fracture growth can occur and create fragments under the pressure levels for flow velocity of a few meters per second, which are comparable to those predicted by an empirical formula generated from the experiments of turbulent flow along a rough surface. The non-planar eroded blocks can be generated in the bedforms that have a reduced rock stiffness from weathering and are of an undulating morphology. The eroded block shapes are insensitive to slope angle, but depend on pre-existing fracture length and orientation, and rock fracture toughness. Under some conditions, the model predicts the fracture paths that extend deeply into massive rock. The fracture behaviors presented are useful for quantitative estimates of water-driven bedrock erosion rates.

Integrating horizontal wells with multi-cluster fracturing techniques has effectively enhanced the contact area between hydraulic fractures (HFs) and the reservoir formation. However, field observations often reveal that fractures do not propagate uniformly, leading to resource wastage and potential interference between wells. This paper introduces a fully coupled XFEM model to investigate the influence of natural fractures (NFs) on the simultaneous propagation of multi-cluster fractures. By incorporating wellbore and perforation elements into the XFEM framework and reformulating pressure drop equations using Darcy’s law, the model accurately represents fluid flow along both the wellbore and perforations. The XFEM approximates the displacement field, while the FEM handles the pressure field, with the resulting coupled equations solved using the Newton-Raphson iteration method. The validity and efficiency of the proposed model are demonstrated through comparisons with a four-fracture propagation problem. Sensitivity analysis indicates that NFs can disrupt uniform fracture propagation, with factors such as larger intersection angles, lower friction coefficients, and smaller NF apertures intensifying this effect. However, if the stress difference or intersection angle is relatively low, the impact of NFs may be temporary, allowing fluid partitioning to eventually become uniform. This study enhances the understanding of fracture propagation in the presence of NFs and provides valuable insights for optimizing hydraulic fracturing operations in fractured reservoirs.

This paper proposes a data-driven method for the deformation analysis of layered rocks, which consists of generating a stress-strain database and using a data-driven computational solution. The method does not require defining the material's constitutive relationship to conduct analysis of layered rock deformation under loading of the same material. First, the data-driven identification (DDI) algorithm infers and builds a stress-strain database of the material based on the strain field and loading force. Then, this database is used to calculate the response of the same material structure with arbitrary geometry and boundary conditions using data-driven computational mechanics (DDCM). The specific workflow of the method is demonstrated, and the computational accuracy and reliability are verified through an experimental application example. The method naturally combines the DDI algorithm and the DDCM solver, providing a new concept for analysing the deformation of layered rocks. Through this method, it is possible to conduct more accurate deformation analysis of layered rocks without defining their constitutive relationships. This has significant engineering application value in the design of excavations for layered rock slopes, foundations, and underground caverns.

Determining the freezing fronts and evaluating the development of freezing walls can be crucial for ensuring the construction safety. Ground penetrating-radar (GPR) regarded as a rapid non-destructive detection method has been proved its potential capacity for identifying the freezing fronts. However, accurately locating the position of freezing fronts and defects remains significant challenges. Here we developed the theoretical and numerical models for GPR detecting freezing fronts using the correlation back-projection (CBP) method. These models were validated through an indoor GPR test using a 600 MHz radar. The results indicate that the quality of GPR images can be significantly improved using the CBP method, enhancing the resolution in detecting and determining the frozen fronts and defects behind shield segments. It thus provides direct evidence that the CBP method can effectively reconstruct the electromagnetic (EM) waves responses and achieve high-resolution identification of freezing states. These findings highlight the potential of GPR in tunnel freezing engineering and suggest a new strategy for cooperative monitoring of freezing walls.

Polymer rubber are considered viable sealing materials for lined rock caverns (LRC) in compressed air energy storage (CAES) systems. However, the mechanical stability and long-term durability of the rubber sealing layer are substantially impacted by the air temperature and pressure within the cavern. In this study, a hyperelastic damage constitutive model was proposed to characterize the mechanical behavior of the rubber sealing layer. Aging and mechanical experiments were conducted to investigate the uniaxial tensile and cyclic loading characteristics of aged and unaged rubber samples, along with the microscopic damage behavior. Based on the stress-strain curve from uniaxial tensile tests and load-displacement curve obtained from cyclic loading tests, the parameters of the rubber constitutive model for damaged and undamaged rubber were determined using the inverse analysis method. Additionally, temperature and pressure within the cavern, along with stress on the structural layers, were compared and analyzed via numerical simulation when using steel and rubber as sealing layers for the LRC. The long-term evolution of stress, strain, displacement, and damage state in the rubber sealing layer was evaluated under three conditions: no damage, pressure-induced damage, and coupled pressure-temperature damage. The results indicate that the rubber sealing layer reduces energy waste and mitigates stress induced by temperature and pressure within each structural layer compared to the steel sealing layer. However, the mechanical properties of the rubber sealing layer gradually deteriorate due to temperature and pressure, while displacement increases and stress decreases as operational cycles accumulate during CAES operation.

Classical peridynamics (PD) models exhibit significant inaccuracies, when applied to irregular grid distributions, limiting their practical engineering applicability. This study begins with the evaluation of existing improved PD formations on numerical specimens with irregular grids and pinpoints a critical source of errors: although bond stretch, overall support domain deformation, and individual bond forces are accurately computed, the resultant bond forces are not. To address this issue, we propose a gradient field computation method within a nonlocal framework tailored for irregular grids, resulting in a novel virtual-bond PD model that eliminates bond force calculations, where bonds are solely used to characterize material fracture and evaluate deformation. A series of numerical experiments demonstrate that the proposed model accurately simulates material deformation, fracture, and failure under irregular grid conditions. This research deepens the understanding of errors mechanisms in PD models under irregular grids and offers a promising pathway toward enhancing the applicability of nonlocal methods.