Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties i...We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties in each construction phase.Specifically,the algorithm is developed for the Government Assisted Owner Driven(GAOD)reconstruction system to simulate long-term recovery trajectory.SDES,as a flexible modeling approach,can simulate any housing recovery scenario that follows phased reconstruction.The 2015 M 7.8 Gorkha earthquake sequence in Nepal is considered the extreme event,with 796,245 buildings requiring reconstruction.We present some recovery trajectories from severely hit,crisis hit,and earthquake hit parishes,comparing them with the actual reconstruction progress.We also assess quality and improvement of reconstructed buildings using seismic fragility functions,compared to pre-earthquake constructions.Housing recovery uncertainties are dissected in relation to reconstruction pace.We conclude that the vast majority of the reconstructed buildings followed the Build Back Better(BBB)approach and missed the opportunity to pursue the Build Back Resilient(BBR)approach due to multifaceted challenges ranging from unclear policies to economic constraints.We critically assess the GAOD vs Owner Driven(OD)recovery framework and conclude that insurance-supported and technically assisted OD approach could be the most suitable model for post extreme event housing recovery.展开更多
Traditional oilfields face increasing extraction challenges, primarily due to reservoir quality degradation and production decline, which are further exacerbated by volatile international crude oil prices—illustrated...Traditional oilfields face increasing extraction challenges, primarily due to reservoir quality degradation and production decline, which are further exacerbated by volatile international crude oil prices—illustrated by Brent Crude’s trajectory from pandemic-induced negative pricing to geopolitically driven surges exceeding USD 100 per barrel. This study addresses these complexities through an integrated methodological framework applied to medium-permeability sandstone reservoirs in the Xinjiang oilfield by combining advanced numerical simulations with multivariate regression analysis. The methodology employs Latin Hypercube Sampling (LHS) to stratify geological parameter distributions and constructs heterogeneous reservoir models using Petrel software, rigorously validated through historical production data matching. Production forecasting integrates numerical simulation and Decline Curve Analysis (DCA), while investment estimation utilizes Ordinary Least Squares (OLS) regression to correlate engineering parameters with drilling and completion costs. Economic evaluation incorporates Discounted Cash Flow (DCF) modeling and breakeven analysis, establishing techno-economic boundaries via oil price sensitivity analysis ranging from USD 40 to 90 per barrel. Visualization tools, including 3D heatmaps, delineate nonlinear interactions among engineering, geological, and investment datasets under economic constraints. Key findings demonstrate that for the target reservoirs, as oil prices increase from USD 40 to USD 90 per barrel, the minimum economic thickness threshold decreases from approximately 5.7 m to about 2.5 m, with model prediction errors consistently below 25% across validation datasets. This framework provides scientifically grounded decision support for optimizing capital allocation and offers actionable insights to enhance undeveloped hydrocarbon development planning amid market uncertainty. Ultimately, it supports national energy security through technically robust and economically viable resource exploitation strategies.展开更多
In deep coal mining,surrounding rock is subjected to both high in-situ stress and intense mining disturbances,leading to significant time-dependent behavior.Accurately capturing this behavior is essential for predicti...In deep coal mining,surrounding rock is subjected to both high in-situ stress and intense mining disturbances,leading to significant time-dependent behavior.Accurately capturing this behavior is essential for predicting long-term roadway stability,necessitating the development of a reliable constitutive creep model and numerical simulation approach.In this study,creep experiments were conducted on pre-damaged rock with varying initial damage levels to investigate the time-dependent mechanical properties.Based on the experimental results,an accelerated-creep criterion was proposed,and an elastic-viscoplastic creep damage model(EVPCD)was established that simultaneously considers the effects of time-dependent damage and instantaneous damage caused by stress disturbances on rock creep behavior.Subsequently,the effectiveness of the proposed creep model was verified using experimental data,and the secondary development of the EVPCD model was completed based on the FLAC3D platform.Following this,a long-term stability analysis method of deep surrounding rock that accounts for excavation-and mining-induced disturbances was proposed.Using the main roadway of Xutuan Coal Mine as a case study,numerical simulations were carried out to investigate the time-dependent deformation and failure characteristics of the surrounding rock following excavation and mining disturbance.Combined with on-site monitoring of the surrounding rock damage areas,the results indicate that the EVPCD outperforms the CVISC and Nishihara models in predicting the time-dependent behavior of deep surrounding rock.展开更多
The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-ti...The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.展开更多
With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyz...With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.展开更多
Objectives This study aimed to compare the effectiveness of the semi-virtual simulation and traditional simulation teaching models based on the Standards of Best Practice(SOBP)according to the International Nursing As...Objectives This study aimed to compare the effectiveness of the semi-virtual simulation and traditional simulation teaching models based on the Standards of Best Practice(SOBP)according to the International Nursing Association for Clinical Simulation and Learning(INACSL)in the Adult Nursing course.Methods This study used a quasi-experimental design.A total of 94 third-year nursing students from a university in Beijing between November and December 2022 were recruited as participants.An innovative semi-virtual simulation teaching model was designed based on the SOBP established by the INACSL.In the Adult Nursing course,both the semi-virtual and traditional simulation teaching models were implemented.At the end of the simulation sessions,participants completed the Chinese version of the Simulation Effectiveness Tool-Modified(SET-M)to assess the effectiveness of the two teaching models.Results All nursing students completed the simulation sessions.There was no difference(t=−0.93,P=0.353)in the total scores between the semi-virtual simulation teaching model(50.87±5.30)and the traditional simulation teaching model(50.37±5.16).However,there was a statistically significant difference(t=−2.65,P=0.010)in the prebriefing section(semi-virtual simulation:5.60±0.71;traditional simulation:5.33±0.78).In contrast,no statistically significant differences were found for the scenario and debriefing sections(P>0.05).At the individual item level,statistical differences(P<0.05)between the two models were identified for items 1 and 9,but not for the remaining items(P>0.05).By analyzing the open-ended question,it was found that both simulation models were effective,and students’comments were similar.Conclusions The study demonstrated equivalent effectiveness between the semi-virtual and traditional simulation teaching models.Semi-virtual simulation teaching model could offer a more flexible and feasible approach to simulation teaching.展开更多
War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient an...War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient and inflexible,with particularly pronounced limitations in command and decision-making.The overwhelming volume of information and high decision complexity hinder the realization of autonomous and agile command and control.To address this challenge,an intelligent warfare simulation framework named Command-Agent is proposed,which deeply integrates large language models(LLMs)with digital twin battlefields.By constructing a highly realistic battlefield environment through real-time simulation and multi-source data fusion,the natural language interaction capabilities of LLMs are leveraged to lower the command threshold and to enable autonomous command through the Observe-Orient-Decide-Act(OODA)feedback loop.Within the Command-Agent framework,a multimodel collaborative architecture is further adopted to decouple the decision-generation and command-execution functions of LLMs.By combining specialized models such as Deep Seek-R1 and MCTool,the limitations of single-model capabilities are overcome.MCTool is a lightweight execution model fine-tuned for military Function Calling tasks.The framework also introduces a Vector Knowledge Base to mitigate hallucinations commonly exhibited by LLMs.Experimental results demonstrate that Command-Agent not only enables natural language-driven simulation and control but also deeply understands commander intent.Leveraging the multi-model collaborative architecture,during red-blue UAV confrontations involving 2 to 8 UAVs,the integrated score is improved by an average of 41.8%compared to the single-agent system(MCTool),accompanied by a 161.8%optimization in the battle loss ratio.Furthermore,when compared with multi-agent systems lacking the knowledge base,the inclusion of the Vector Knowledge Base further improves overall performance by 16.8%.In comparison with the general model(Qwen2.5-7B),the fine-tuned MCTool leads by 5%in execution efficiency.Therefore,the proposed Command-Agent introduces a novel perspective to the military command system and offers a feasible solution for intelligent battlefield decision-making.展开更多
The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Ni??o-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the origi...The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Ni??o-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the original ZC model exhibits certain biases in reproducing the ENSO–related sea surface temperature anomalies and heating anomalies, limiting its broader applicability. To improve the accuracy of ENSO simulation, we propose a modified ZC model based on Xie et al.(2015), named the MZC_XJH model, through refining the heating parameterization scheme. The performance in simulating the nonlinear SST–precipitation relationship in the MZC_XJH model is firstly elaborated. Then, we investigate the impacts of three key atmospheric parameters on ENSO simulation by conducting experiments with the MZC_XJH model. Through assessing the performance in simulating five fundamental ENSO metrics(amplitude, periodicity,seasonality, diversity, and skewness), we uncover that the sensitivities of simulated ENSO behaviors to different parameters are distinct. Moreover, we explain why a particular parameter greatly affects some simulated ENSO behaviors while others exert minor influence. We also reveal that the nonlinear effect due to the covariation of multi-parameters on ENSO simulation warrants careful consideration when tuning multi-parameters synchronously. Lastly, we present an updated version of the MZC_XJH model, in which some biases have been mitigated but some remain obvious. Although there are no universally optimal parameters that would ensure flawless performance in simulating every aspect of ENSO, this study provides a valuable reference for tuning atmospheric parameters in the MZC_XJH model, rendering the MZC_XJH model applicable to some research objectives.展开更多
Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphys...Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphysical processes such as raindrop evaporation and cloud water accretion in a double-moment six-class cloud microphysics scheme were revised to enhance the simulation of low clouds using the Global-Regional Integrated Forecast System(GRIST)model. The validation of the revised scheme using a single-column version of the GRIST demonstrated a reasonable reduction in liquid water biases. The revised parameterization simulated medium-and low-level cloud fractions that were in better agreement with the observations than the original scheme. Long-term global simulations indicate the mitigation of the originally overestimated low-level cloud fraction and cloud-water mixing ratio in mid-to high-latitude regions,primarily owing to enhanced accretion processes and weakened raindrop evaporation. The reduced low clouds with the revised scheme showed better consistency with satellite observations, particularly at mid-and high-latitudes. Further improvements can be observed in the simulated cloud shortwave radiative forcing and vertical distribution of total cloud cover. Annual precipitation in mid-latitude regions has also improved, particularly over the oceans, with significantly increased large-scale and decreased convective precipitation.展开更多
This work investigates the effects of deformation mechanisms on the mechanical properties and anisotropy of rolled AZ31B magnesium alloy under uniaxial tension,combining experimental characterization with Visco-Plasti...This work investigates the effects of deformation mechanisms on the mechanical properties and anisotropy of rolled AZ31B magnesium alloy under uniaxial tension,combining experimental characterization with Visco-Plastic Self Consistent(VPSC)modeling.The research focuses particularly on anisotropic mechanical responses along transverse direction(TD)and rolling direction(RD).Experimental measurements and computational simulations consistently demonstrate that prismaticslip activation significantly reduces the strain hardening rate during the initial stage of tensile deformation.By suppressing the activation of specific deformation mechanisms along RD and TD,the tensile mechanical behavior of the magnesium alloy was further investigated.The results show that basalslip has the greatest impact during the initial deformation stage and basalslip activation substantially affects the deformation behavior of AZ31B alloy,causing marked decreases in both yield and tensile strength along RD.Under tensile loading along TD,prismaticslip not only exhibits a synergistic effect on yield strength,but also dominants work hardening during the initial plastic deformation.展开更多
It is well known that aluminum and copper exhibit structural phase transformations in quasi-static and dynamic measurements,including shock wave loading.However,the dependence of phase transformations in a wide range ...It is well known that aluminum and copper exhibit structural phase transformations in quasi-static and dynamic measurements,including shock wave loading.However,the dependence of phase transformations in a wide range of crystallographic directions of shock loading has not been revealed.In this work,we calculated the shock Hugoniot for aluminum and copper in different crystallographic directions([100],[110],[111],[112],[102],[114],[123],[134],[221]and[401])of shock compression using molecular dynamics(MD)simulations.The results showed a high pressure(>160 GPa for Cu and>40 GPa for Al)of the FCC-to-BCC transition.In copper,different characteristics of the phase transition are observed depending on the loading direction with the[100]compression direction being the weakest.The FCC-to-BCC transition for copper is in the range of 150–220 GPa,which is consistent with the existing experimental data.Due to the high transition pressure,the BCC phase transition in copper competes with melting.In aluminum,the FCC-to-BCC transition is observed for all studied directions at pressures between 40 and 50 GPa far beyond the melting.In all considered cases we observe the coexistence of HCP and BCC phases during the FCC-to-BCC transition,which is consistent with the experimental data and atomistic calculations;this HCP phase forms in the course of accompanying plastic deformation with dislocation activity in the parent FCC phase.The plasticity incipience is also anisotropic in bothmetals,which is due to the difference in the projections of stress on the slip plane for different orientations of the FCC crystal.MD modeling results demonstrate a strong dependence of the FCC-to-BCC transition on the crystallographic direction,in which the material is loaded in the copper crystals.However,MD simulations data can only be obtained for specific points in the stereographic direction space;therefore,for more comprehensive understanding of the phase transition process,a feed-forward neural network was trained using MD modeling data.The trained machine learning model allowed us to construct continuous stereographic maps of phase transitions as a function of stress in the shock-compressed state of metal.Due to appearance and growth of multiple centers of new phase,the FCC-to-BCC transition leads to formation of a polycrystalline structure from the parent single crystal.展开更多
This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high bl...This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high blood pressure in the pulmonary artery. To simulate the hemodynamic abnormalities in pulmonary hypertension under different causes and pathologies, we construct a localized parameter circuit model governed by nonlinear ordinary derivative equations of the human circulatory system. Thus, two special cases are considered, namely pulmonary the artery stenosis and the left ventricular diastolic dysfunction. For each case of pulmonary hypertension development, we determine the relationships between blood pressure and chamber and vessel pressure-volume. When the pulmonary hypertension is due to pulmonary artery stenosis, it appears that the right ventricular pressure increases up to 90 mm Hg, likewise the rise in pulmonary artery resistance induces direct increment in pulmonary artery pressure. However, when the pulmonary hypertension is due to left ventricular diastolic dysfunction, we note that the left atrial pressure and the pulmonary vein pressure augment, leading to the growth of the pulmonary artery blood pressure. The established results within this paper are useful for understanding the hemodynamic mechanism of particular pulmonary hypertension.展开更多
In this study,we simulated the thermal behavior of the mud-brick walls of a Nubian vault.We used EnergyPlus software for the simulation.The results obtained showed that the indoor temperature varies from 25.5℃ to 26....In this study,we simulated the thermal behavior of the mud-brick walls of a Nubian vault.We used EnergyPlus software for the simulation.The results obtained showed that the indoor temperature varies from 25.5℃ to 26.5℃ for the period of January 2018.It varies from 33.2℃ to 33.6℃ with an average value of 33.1℃ for the month of April 2018.For the period of July 2018,it varies from 30.3℃ to 32.2℃ with an average value of 31.2℃..Relative humidity for the period of July ranged from 62.3%to 73.5%,with an average value of 67.9%.The simulation enabled us to compare simulated and measured temperature and humidity values.We found that the level of thermal comfort in the Nubian vault is acceptable in both cool and hot periods.In view of these results,we can say that the Nubian vault is an architecture suited to our climate.The technical concept of the Nubian vault is adapted to the climatic conditions and traditional know-how of the Sahel.We also found that the use of raw earth,a locally available material,and the Nubian vault architectural process,contribute to thermal comfort and a reappropriation of local and adapted know-how.展开更多
A new three-dimensional multiphase numerical model was built.The volume of fluid and k-ε turbulence models were used to investigate the hot metal ladle pouring process.During the pouring process,issues such as iron s...A new three-dimensional multiphase numerical model was built.The volume of fluid and k-ε turbulence models were used to investigate the hot metal ladle pouring process.During the pouring process,issues such as iron splashing,overflow,and significant heat loss are prevalent.To realize efficient and stable pouring,the effects of ladle tilting velocity,flow rate,and converter tilting angle on the pouring process were examined.The model was verified by comparing the actual pouring time with the numerical results.It is shown that there is a nonlinear relationship between pouring velocity and hot metal flow rate at the ladle mouth.As the mass flow increased and the converter tilting angle decreased,the impact point of the hot metal into the converter pool shifted from the side wall to the bottom,and the impact force increased accordingly.The pouring velocity curve was optimized by the volume difference of the ladle at different angles,and an empirical formula was derived.After the optimization of pouring speed,the flow rate was stabilized between 4000 and 6000 kg/s,and the pouring time was reduced by approximately 30 s.After applying this model in actual production,the hot metal temperature inside the converter increased by approximately 5℃statistically.This model is potential to enhance the production efficiency,stability,and safety of the pouring process between open containers.展开更多
To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However...To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However,we prove that the spatial simulation error of the finite difference method is associated with the dot product of the spatial dispersion relation of the finite-difference weights and the spectrum of the seismic wavefield.Based on the dot product relation,we construct a L_(2) norm cost function to minimize spatial simulation error.For solving this optimization problem,the seismic wavefield infor-mation in wavenumber region is necessary.Nevertheless,the seismic wavefield is generally obtained by costly forward modeling techniques.To reduce the computational cost,we substitute the spectrum of the seismic wavelet for the spectrum of the seismic wavefield,as the seismic wavelet plays a key role in determining the seismic wavefield.In solving the optimization problem,we design an exhaustive search method to obtain the solution of the L_(2) norm optimization problem.After solving the optimization problem,we are able to achieve the finite-difference weights that minimize spatial simulation error.In theoretical error analyses,the finite-difference weights from the proposed method can output more accurate simulation results compared to those from previous optimization algorithms.Furthermore,we validate our method through numerical tests with synthetic models,which encompass homogenous/inhomogeneous media as well as isotropic and anisotropic media.展开更多
Process of dynamic recrystallization(DRX)plays a crucial role in altering the microstructure and enhancing the mechanical characteristics of CrNiMoVW steel.However,its initiation mechanism,deformation conditions,and p...Process of dynamic recrystallization(DRX)plays a crucial role in altering the microstructure and enhancing the mechanical characteristics of CrNiMoVW steel.However,its initiation mechanism,deformation conditions,and predictive models remain insufficiently understood,requiring further research to optimize the processing technology.In the present study,hot compression experiments were carried out on 30CrNiMoVW steel under deformation conditions with temperatures ranging from 950 to 1,250℃and strain rates from 0.001 to 1 s~(-1),during which true stress-strain curves were obtained.Based on friction and temperature corrections applied to these curves,a constitutive equation for 30CrNiMoVW steel was established,and its accuracy was verified through fitting analysis.Simultaneously,the study identified limitations in the initial volume fraction model,prompting the development of a modified recrystallization volume fraction model that was validated via correlation analysis between experimental data and model predictions.Furthermore,building upon the modified recrystallization volume fraction model,a novel recrystallization rate model was developed,and three characteristic strain points were determined.These points segmented the rate curve into three stages:a slow initiation stage(0,ε1),a rapid growth stage(1,ε3),and a slow equilibrium stage(e3,0.9).Notably,the value ofε3 was considered the most economical,ensuring the formation of fine and uniform grains during production while optimizing the process,reducing energy consumption and costs,and enhancing overall material performance.Finally,based on the physical constitutive relationships and kinetic models,a multiscale simulation approach combining the finite element method(FEM)and cellular automata(CA)was employed to predict the microstructural evolution of 30CrNiMoVW steel.The simulation results demonstrate that the FEM&CA approach can accurately reproduce the dynamic recrystallization behavior and microstructural evolution observed experimentally.This work provides critical guidance for the development of forging processes for 30CrNiMoVW steel.展开更多
As a common fault of the aero-engine,the blade-casing rubbing(BCR)has the potential to cause catastrophic accidents.In this paper,to investigate the dynamic responses and wear characteristics of the system,the laminat...As a common fault of the aero-engine,the blade-casing rubbing(BCR)has the potential to cause catastrophic accidents.In this paper,to investigate the dynamic responses and wear characteristics of the system,the laminated shell element is used to establish the finite element model(FEM)of a flexibly coated casing system.Using the shell element,the blade is modeled,and the surface stress of the blade is calculated.The stress-solving method of the blade is validated through comparisons with the measured time-domain waveform of the stress.Then,a dynamic model of a blade-flexibly coated casing system with rubbing is proposed,accounting for the time-varying mass and stiffness of the casing caused by coating wear.The effects of the proposed flexible casing model are compared with those of a rigid casing model,and the stress changes induced by rubbing are investigated.The results show that the natural characteristics of the coated casing decrease due to the coating wear.The flexibly coated casing model is found to be more suitable for studying casing vibration.Additionally,the stress changes caused by rubbing are slight,and the change in the stress maximum is approximately 5%under the influence of the abrasive coating.展开更多
The numerical approximation of stochastic partial differential equations(SPDEs),particularly those including q-diffusion,poses considerable challenges due to the requirements for high-order precision,stability amongst...The numerical approximation of stochastic partial differential equations(SPDEs),particularly those including q-diffusion,poses considerable challenges due to the requirements for high-order precision,stability amongst random perturbations,and processing efficiency.Because of their simplicity,conventional numerical techniques like the Euler-Maruyama method are frequently employed to solve stochastic differential equations;nonetheless,they may have low-order accuracy and lower stability in stiff or high-resolution situations.This study proposes a novel computational scheme for solving SPDEs arising from a stochastic SEIR model with q-diffusion and a general incidence rate function.A proposed computational scheme can be used to solve stochastic partial differential equations.For spatial discretization,a compact scheme is chosen.The compact scheme can provide a sixth-order accurate solution.The proposed scheme can be considered an extension of the Euler Maruyama method.Stability and consistency in the mean square sense are also provided.For application purposes,the stochastic SEIR model is considered using q-diffusion effects.The scheme is used to solve the stochastic model and compared with the Euler-Maruyama method.The scheme is also compared with nonstandard finite difference method for solving deterministic models.In both cases,it performs better than existing schemes.Incorporating q-diffusion further enhanced the model’s ability to represent realistic spatial-temporal disease dynamics,especially in scenarios where classical diffusion is insufficient.展开更多
Structure-type rockbursts frequently occur in deep tunnels,with structural planes and stress conditions being critical factors in their formation.In this study,we utilized specially developed analogous materials that ...Structure-type rockbursts frequently occur in deep tunnels,with structural planes and stress conditions being critical factors in their formation.In this study,we utilized specially developed analogous materials that exhibit the high brittleness and strength characteristics of deep hard rock to construct physical models representing different types of structural planes,including composite,exposed,non-exposed,and throughgoing structural planes.Physical simulation experiments were conducted on structuretype rockbursts in deep horseshoe-shaped tunnels,focusing on strain differentiation characteristics,critical triggering conditions,critical crack opening displacement,the incubation process,the reduction effects of structural planes on failure intensity,and formation mechanisms.These experiments were complemented by acoustic and optical monitoring,as well as discrete element numerical simulations,to provide a comprehensive analysis.The results revealed that the most significant strain heterogeneity in the surrounding rock occurs at the tip of the structural plane along the tunnel's minimum principal stress direction,driven by the combined effects of tensile and shear forces.We quantitatively determined the critical stress and strain conditions for structure-type rockbursts and evaluated the intensity of rockbursts induced by different structural planes using critical crack opening displacement(COD)values,the uniformity coefficient,and the curvature coefficient.Analysis of acoustic emission events,including frequency,amplitude,and b-value,indicated that the macro-fracture process is governed by both the principal stress differential and the characteristics of the structural plane.Furthermore,using the bearing capacity reduction coefficient,we found that exposed structural planes have the most significant weakening effect on rock mass strength,followed by non-exposed and throughgoing structural planes.The analysis of average frequency(AF)and rise angle(RA)parameters revealed a close correlation between the failure modes of structure-type rockbursts,the rock mass structure,and the stress levels.These findings provide critical theoretical support for the prediction and prevention of structure-type rockburst disasters.展开更多
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
文摘We develop and implement a Stochastic Discrete Event Simulation(SDES)algorithm to model the housing re-covery trajectory after an extreme event.The algorithm models discrete events and their underlying uncertainties in each construction phase.Specifically,the algorithm is developed for the Government Assisted Owner Driven(GAOD)reconstruction system to simulate long-term recovery trajectory.SDES,as a flexible modeling approach,can simulate any housing recovery scenario that follows phased reconstruction.The 2015 M 7.8 Gorkha earthquake sequence in Nepal is considered the extreme event,with 796,245 buildings requiring reconstruction.We present some recovery trajectories from severely hit,crisis hit,and earthquake hit parishes,comparing them with the actual reconstruction progress.We also assess quality and improvement of reconstructed buildings using seismic fragility functions,compared to pre-earthquake constructions.Housing recovery uncertainties are dissected in relation to reconstruction pace.We conclude that the vast majority of the reconstructed buildings followed the Build Back Better(BBB)approach and missed the opportunity to pursue the Build Back Resilient(BBR)approach due to multifaceted challenges ranging from unclear policies to economic constraints.We critically assess the GAOD vs Owner Driven(OD)recovery framework and conclude that insurance-supported and technically assisted OD approach could be the most suitable model for post extreme event housing recovery.
文摘Traditional oilfields face increasing extraction challenges, primarily due to reservoir quality degradation and production decline, which are further exacerbated by volatile international crude oil prices—illustrated by Brent Crude’s trajectory from pandemic-induced negative pricing to geopolitically driven surges exceeding USD 100 per barrel. This study addresses these complexities through an integrated methodological framework applied to medium-permeability sandstone reservoirs in the Xinjiang oilfield by combining advanced numerical simulations with multivariate regression analysis. The methodology employs Latin Hypercube Sampling (LHS) to stratify geological parameter distributions and constructs heterogeneous reservoir models using Petrel software, rigorously validated through historical production data matching. Production forecasting integrates numerical simulation and Decline Curve Analysis (DCA), while investment estimation utilizes Ordinary Least Squares (OLS) regression to correlate engineering parameters with drilling and completion costs. Economic evaluation incorporates Discounted Cash Flow (DCF) modeling and breakeven analysis, establishing techno-economic boundaries via oil price sensitivity analysis ranging from USD 40 to 90 per barrel. Visualization tools, including 3D heatmaps, delineate nonlinear interactions among engineering, geological, and investment datasets under economic constraints. Key findings demonstrate that for the target reservoirs, as oil prices increase from USD 40 to USD 90 per barrel, the minimum economic thickness threshold decreases from approximately 5.7 m to about 2.5 m, with model prediction errors consistently below 25% across validation datasets. This framework provides scientifically grounded decision support for optimizing capital allocation and offers actionable insights to enhance undeveloped hydrocarbon development planning amid market uncertainty. Ultimately, it supports national energy security through technically robust and economically viable resource exploitation strategies.
基金funded by the National Natural Science Foundation of China(Nos.52004098,U24B2041,and 52274079)the Key Research and Development Program of Henan Province(No.251111320400)+1 种基金the Key Research Project Plan for Higher Education Institutions in Henan Province(Nos.24A570006 and 25A570002)the Scientific and Technological Research Project in Henan Province(No.242102320061).
文摘In deep coal mining,surrounding rock is subjected to both high in-situ stress and intense mining disturbances,leading to significant time-dependent behavior.Accurately capturing this behavior is essential for predicting long-term roadway stability,necessitating the development of a reliable constitutive creep model and numerical simulation approach.In this study,creep experiments were conducted on pre-damaged rock with varying initial damage levels to investigate the time-dependent mechanical properties.Based on the experimental results,an accelerated-creep criterion was proposed,and an elastic-viscoplastic creep damage model(EVPCD)was established that simultaneously considers the effects of time-dependent damage and instantaneous damage caused by stress disturbances on rock creep behavior.Subsequently,the effectiveness of the proposed creep model was verified using experimental data,and the secondary development of the EVPCD model was completed based on the FLAC3D platform.Following this,a long-term stability analysis method of deep surrounding rock that accounts for excavation-and mining-induced disturbances was proposed.Using the main roadway of Xutuan Coal Mine as a case study,numerical simulations were carried out to investigate the time-dependent deformation and failure characteristics of the surrounding rock following excavation and mining disturbance.Combined with on-site monitoring of the surrounding rock damage areas,the results indicate that the EVPCD outperforms the CVISC and Nishihara models in predicting the time-dependent behavior of deep surrounding rock.
基金supported by the Advanced Materials-National Science and Technology Major Project(Grant No.2025ZD0618401)the National Natural Science Foundation of China(Grant No.12504285)+1 种基金the Natural Science Foundation of Jiangsu Province(Grant No.BK20250472)NFSG grant from BITS-Pilani,Dubai campus。
文摘The rapid advancement of machine learning based tight-binding Hamiltonian(MLTB)methods has opened new avenues for efficient and accurate electronic structure simulations,particularly in large-scale systems and long-time scenarios.This review begins with a concise overview of traditional tight-binding(TB)models,including both(semi-)empirical and first-principles approaches,establishing the foundation for understanding MLTB developments.We then present a systematic classification of existing MLTB methodologies,grouped into two major categories:direct prediction of TB Hamiltonian elements and inference of empirical parameters.A comparative analysis with other ML-based electronic structure models is also provided,highlighting the advancement of MLTB approaches.Finally,we explore the emerging MLTB application ecosystem,highlighting how the integration of MLTB models with a diverse suite of post-processing tools from linear-scaling solvers to quantum transport frameworks and molecular dynamics interfaces is essential for tackling complex scientific problems across different domains.The continued advancement of this integrated paradigm promises to accelerate materials discovery and open new frontiers in the predictive simulation of complex quantum phenomena.
基金funded by Humanities and Social Sciences of Ministry of Education Planning Fund of China,grant number 21YJA790009National Natural Science Foundation of China,grant number 72140001.
文摘With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.
文摘Objectives This study aimed to compare the effectiveness of the semi-virtual simulation and traditional simulation teaching models based on the Standards of Best Practice(SOBP)according to the International Nursing Association for Clinical Simulation and Learning(INACSL)in the Adult Nursing course.Methods This study used a quasi-experimental design.A total of 94 third-year nursing students from a university in Beijing between November and December 2022 were recruited as participants.An innovative semi-virtual simulation teaching model was designed based on the SOBP established by the INACSL.In the Adult Nursing course,both the semi-virtual and traditional simulation teaching models were implemented.At the end of the simulation sessions,participants completed the Chinese version of the Simulation Effectiveness Tool-Modified(SET-M)to assess the effectiveness of the two teaching models.Results All nursing students completed the simulation sessions.There was no difference(t=−0.93,P=0.353)in the total scores between the semi-virtual simulation teaching model(50.87±5.30)and the traditional simulation teaching model(50.37±5.16).However,there was a statistically significant difference(t=−2.65,P=0.010)in the prebriefing section(semi-virtual simulation:5.60±0.71;traditional simulation:5.33±0.78).In contrast,no statistically significant differences were found for the scenario and debriefing sections(P>0.05).At the individual item level,statistical differences(P<0.05)between the two models were identified for items 1 and 9,but not for the remaining items(P>0.05).By analyzing the open-ended question,it was found that both simulation models were effective,and students’comments were similar.Conclusions The study demonstrated equivalent effectiveness between the semi-virtual and traditional simulation teaching models.Semi-virtual simulation teaching model could offer a more flexible and feasible approach to simulation teaching.
文摘War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient and inflexible,with particularly pronounced limitations in command and decision-making.The overwhelming volume of information and high decision complexity hinder the realization of autonomous and agile command and control.To address this challenge,an intelligent warfare simulation framework named Command-Agent is proposed,which deeply integrates large language models(LLMs)with digital twin battlefields.By constructing a highly realistic battlefield environment through real-time simulation and multi-source data fusion,the natural language interaction capabilities of LLMs are leveraged to lower the command threshold and to enable autonomous command through the Observe-Orient-Decide-Act(OODA)feedback loop.Within the Command-Agent framework,a multimodel collaborative architecture is further adopted to decouple the decision-generation and command-execution functions of LLMs.By combining specialized models such as Deep Seek-R1 and MCTool,the limitations of single-model capabilities are overcome.MCTool is a lightweight execution model fine-tuned for military Function Calling tasks.The framework also introduces a Vector Knowledge Base to mitigate hallucinations commonly exhibited by LLMs.Experimental results demonstrate that Command-Agent not only enables natural language-driven simulation and control but also deeply understands commander intent.Leveraging the multi-model collaborative architecture,during red-blue UAV confrontations involving 2 to 8 UAVs,the integrated score is improved by an average of 41.8%compared to the single-agent system(MCTool),accompanied by a 161.8%optimization in the battle loss ratio.Furthermore,when compared with multi-agent systems lacking the knowledge base,the inclusion of the Vector Knowledge Base further improves overall performance by 16.8%.In comparison with the general model(Qwen2.5-7B),the fine-tuned MCTool leads by 5%in execution efficiency.Therefore,the proposed Command-Agent introduces a novel perspective to the military command system and offers a feasible solution for intelligent battlefield decision-making.
基金supported by the National Key Research and Development Program of China (Grant No.2022YFF0802004)the Excellent Youth Natural Science Foundation of Jiangsu Province (BK20230061)+1 种基金the Joint Open Project of KLME&CIC-FEMD (Grant No.KLME202501)Jiangsu Innovation Research Group (Grant No.JSSCTD 202346)。
文摘The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Ni??o-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the original ZC model exhibits certain biases in reproducing the ENSO–related sea surface temperature anomalies and heating anomalies, limiting its broader applicability. To improve the accuracy of ENSO simulation, we propose a modified ZC model based on Xie et al.(2015), named the MZC_XJH model, through refining the heating parameterization scheme. The performance in simulating the nonlinear SST–precipitation relationship in the MZC_XJH model is firstly elaborated. Then, we investigate the impacts of three key atmospheric parameters on ENSO simulation by conducting experiments with the MZC_XJH model. Through assessing the performance in simulating five fundamental ENSO metrics(amplitude, periodicity,seasonality, diversity, and skewness), we uncover that the sensitivities of simulated ENSO behaviors to different parameters are distinct. Moreover, we explain why a particular parameter greatly affects some simulated ENSO behaviors while others exert minor influence. We also reveal that the nonlinear effect due to the covariation of multi-parameters on ENSO simulation warrants careful consideration when tuning multi-parameters synchronously. Lastly, we present an updated version of the MZC_XJH model, in which some biases have been mitigated but some remain obvious. Although there are no universally optimal parameters that would ensure flawless performance in simulating every aspect of ENSO, this study provides a valuable reference for tuning atmospheric parameters in the MZC_XJH model, rendering the MZC_XJH model applicable to some research objectives.
基金National Natural Science Foundation of China(42375153,42105153,42205157)Development of Science and Technology at Chinese Academy of Meteorological Sciences(2023KJ038)。
文摘Clouds play an important role in global atmospheric energy and water vapor budgets, and the low cloud simulations suffer from large biases in many atmospheric general circulation models. In this study, cloud microphysical processes such as raindrop evaporation and cloud water accretion in a double-moment six-class cloud microphysics scheme were revised to enhance the simulation of low clouds using the Global-Regional Integrated Forecast System(GRIST)model. The validation of the revised scheme using a single-column version of the GRIST demonstrated a reasonable reduction in liquid water biases. The revised parameterization simulated medium-and low-level cloud fractions that were in better agreement with the observations than the original scheme. Long-term global simulations indicate the mitigation of the originally overestimated low-level cloud fraction and cloud-water mixing ratio in mid-to high-latitude regions,primarily owing to enhanced accretion processes and weakened raindrop evaporation. The reduced low clouds with the revised scheme showed better consistency with satellite observations, particularly at mid-and high-latitudes. Further improvements can be observed in the simulated cloud shortwave radiative forcing and vertical distribution of total cloud cover. Annual precipitation in mid-latitude regions has also improved, particularly over the oceans, with significantly increased large-scale and decreased convective precipitation.
基金supported by the National Nature Science Foundation of China(52275356).
文摘This work investigates the effects of deformation mechanisms on the mechanical properties and anisotropy of rolled AZ31B magnesium alloy under uniaxial tension,combining experimental characterization with Visco-Plastic Self Consistent(VPSC)modeling.The research focuses particularly on anisotropic mechanical responses along transverse direction(TD)and rolling direction(RD).Experimental measurements and computational simulations consistently demonstrate that prismaticslip activation significantly reduces the strain hardening rate during the initial stage of tensile deformation.By suppressing the activation of specific deformation mechanisms along RD and TD,the tensile mechanical behavior of the magnesium alloy was further investigated.The results show that basalslip has the greatest impact during the initial deformation stage and basalslip activation substantially affects the deformation behavior of AZ31B alloy,causing marked decreases in both yield and tensile strength along RD.Under tensile loading along TD,prismaticslip not only exhibits a synergistic effect on yield strength,but also dominants work hardening during the initial plastic deformation.
基金founded by the Ministry of Science and Higher Education of the Russian Federation,State assignments for research,registration No.1024032600084-8-1.3.2Study of the grain growth and the formation of polycrystalline structure as a result of phase transition(Section 6)was founded by the Russian Science Foundation,Project No.24-71-00078+3 种基金https://rscf.ru/en/project/24-71-00078/(accessed on 01 December 2025).Study of the orientation dependence of the phase transition of aluminum in Section 3 was founded by the Russian Science Foundation,Project No.24-19-00684https://rscf.ru/en/project/24-19-00684/(accessed on 01 December 2025).
文摘It is well known that aluminum and copper exhibit structural phase transformations in quasi-static and dynamic measurements,including shock wave loading.However,the dependence of phase transformations in a wide range of crystallographic directions of shock loading has not been revealed.In this work,we calculated the shock Hugoniot for aluminum and copper in different crystallographic directions([100],[110],[111],[112],[102],[114],[123],[134],[221]and[401])of shock compression using molecular dynamics(MD)simulations.The results showed a high pressure(>160 GPa for Cu and>40 GPa for Al)of the FCC-to-BCC transition.In copper,different characteristics of the phase transition are observed depending on the loading direction with the[100]compression direction being the weakest.The FCC-to-BCC transition for copper is in the range of 150–220 GPa,which is consistent with the existing experimental data.Due to the high transition pressure,the BCC phase transition in copper competes with melting.In aluminum,the FCC-to-BCC transition is observed for all studied directions at pressures between 40 and 50 GPa far beyond the melting.In all considered cases we observe the coexistence of HCP and BCC phases during the FCC-to-BCC transition,which is consistent with the experimental data and atomistic calculations;this HCP phase forms in the course of accompanying plastic deformation with dislocation activity in the parent FCC phase.The plasticity incipience is also anisotropic in bothmetals,which is due to the difference in the projections of stress on the slip plane for different orientations of the FCC crystal.MD modeling results demonstrate a strong dependence of the FCC-to-BCC transition on the crystallographic direction,in which the material is loaded in the copper crystals.However,MD simulations data can only be obtained for specific points in the stereographic direction space;therefore,for more comprehensive understanding of the phase transition process,a feed-forward neural network was trained using MD modeling data.The trained machine learning model allowed us to construct continuous stereographic maps of phase transitions as a function of stress in the shock-compressed state of metal.Due to appearance and growth of multiple centers of new phase,the FCC-to-BCC transition leads to formation of a polycrystalline structure from the parent single crystal.
文摘This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high blood pressure in the pulmonary artery. To simulate the hemodynamic abnormalities in pulmonary hypertension under different causes and pathologies, we construct a localized parameter circuit model governed by nonlinear ordinary derivative equations of the human circulatory system. Thus, two special cases are considered, namely pulmonary the artery stenosis and the left ventricular diastolic dysfunction. For each case of pulmonary hypertension development, we determine the relationships between blood pressure and chamber and vessel pressure-volume. When the pulmonary hypertension is due to pulmonary artery stenosis, it appears that the right ventricular pressure increases up to 90 mm Hg, likewise the rise in pulmonary artery resistance induces direct increment in pulmonary artery pressure. However, when the pulmonary hypertension is due to left ventricular diastolic dysfunction, we note that the left atrial pressure and the pulmonary vein pressure augment, leading to the growth of the pulmonary artery blood pressure. The established results within this paper are useful for understanding the hemodynamic mechanism of particular pulmonary hypertension.
文摘In this study,we simulated the thermal behavior of the mud-brick walls of a Nubian vault.We used EnergyPlus software for the simulation.The results obtained showed that the indoor temperature varies from 25.5℃ to 26.5℃ for the period of January 2018.It varies from 33.2℃ to 33.6℃ with an average value of 33.1℃ for the month of April 2018.For the period of July 2018,it varies from 30.3℃ to 32.2℃ with an average value of 31.2℃..Relative humidity for the period of July ranged from 62.3%to 73.5%,with an average value of 67.9%.The simulation enabled us to compare simulated and measured temperature and humidity values.We found that the level of thermal comfort in the Nubian vault is acceptable in both cool and hot periods.In view of these results,we can say that the Nubian vault is an architecture suited to our climate.The technical concept of the Nubian vault is adapted to the climatic conditions and traditional know-how of the Sahel.We also found that the use of raw earth,a locally available material,and the Nubian vault architectural process,contribute to thermal comfort and a reappropriation of local and adapted know-how.
基金supported by the National Natural Science Foundation of China(Grant Nos.52104318 and 52374322).
文摘A new three-dimensional multiphase numerical model was built.The volume of fluid and k-ε turbulence models were used to investigate the hot metal ladle pouring process.During the pouring process,issues such as iron splashing,overflow,and significant heat loss are prevalent.To realize efficient and stable pouring,the effects of ladle tilting velocity,flow rate,and converter tilting angle on the pouring process were examined.The model was verified by comparing the actual pouring time with the numerical results.It is shown that there is a nonlinear relationship between pouring velocity and hot metal flow rate at the ladle mouth.As the mass flow increased and the converter tilting angle decreased,the impact point of the hot metal into the converter pool shifted from the side wall to the bottom,and the impact force increased accordingly.The pouring velocity curve was optimized by the volume difference of the ladle at different angles,and an empirical formula was derived.After the optimization of pouring speed,the flow rate was stabilized between 4000 and 6000 kg/s,and the pouring time was reduced by approximately 30 s.After applying this model in actual production,the hot metal temperature inside the converter increased by approximately 5℃statistically.This model is potential to enhance the production efficiency,stability,and safety of the pouring process between open containers.
基金supported by the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(No.2021QNLM020001)the Major Scientific and Technological Projects of Shandong Energy Group(No.SNKJ2022A06-R23)+1 种基金the Funds of Creative Research Groups of China(No.41821002)the Major Scientific and Technological Projects of CNPC(No.ZD2019-183-003).
文摘To reduce the spatial simulation error generated by the finite difference method,previous researchers compute the optimal finite-difference weights always by minimizing the error of spatial dispersion relation.However,we prove that the spatial simulation error of the finite difference method is associated with the dot product of the spatial dispersion relation of the finite-difference weights and the spectrum of the seismic wavefield.Based on the dot product relation,we construct a L_(2) norm cost function to minimize spatial simulation error.For solving this optimization problem,the seismic wavefield infor-mation in wavenumber region is necessary.Nevertheless,the seismic wavefield is generally obtained by costly forward modeling techniques.To reduce the computational cost,we substitute the spectrum of the seismic wavelet for the spectrum of the seismic wavefield,as the seismic wavelet plays a key role in determining the seismic wavefield.In solving the optimization problem,we design an exhaustive search method to obtain the solution of the L_(2) norm optimization problem.After solving the optimization problem,we are able to achieve the finite-difference weights that minimize spatial simulation error.In theoretical error analyses,the finite-difference weights from the proposed method can output more accurate simulation results compared to those from previous optimization algorithms.Furthermore,we validate our method through numerical tests with synthetic models,which encompass homogenous/inhomogeneous media as well as isotropic and anisotropic media.
基金supported by the National Natural Science Foundation of China(52071012)the National Natural Science Foundation of China(Grant No.52101119)+5 种基金the Open Foundation of State Key Laboratory for Advanced Metals and Materials(2022-Z01)the Open Research Fund of National Key Laboratory of Advanced Casting Technologies(CAT2023-004)the Key Research and Development Program of Shandong Province(2022JMRH0209)Hebei Province Innovation Capability Enhancement Plan Project(No.244A7607D)the Beijing Municipal Natural Science Foundation(No.2214072)Young Elite Scientist Sponsorship Program by CAST(No.2021QNRC001)。
文摘Process of dynamic recrystallization(DRX)plays a crucial role in altering the microstructure and enhancing the mechanical characteristics of CrNiMoVW steel.However,its initiation mechanism,deformation conditions,and predictive models remain insufficiently understood,requiring further research to optimize the processing technology.In the present study,hot compression experiments were carried out on 30CrNiMoVW steel under deformation conditions with temperatures ranging from 950 to 1,250℃and strain rates from 0.001 to 1 s~(-1),during which true stress-strain curves were obtained.Based on friction and temperature corrections applied to these curves,a constitutive equation for 30CrNiMoVW steel was established,and its accuracy was verified through fitting analysis.Simultaneously,the study identified limitations in the initial volume fraction model,prompting the development of a modified recrystallization volume fraction model that was validated via correlation analysis between experimental data and model predictions.Furthermore,building upon the modified recrystallization volume fraction model,a novel recrystallization rate model was developed,and three characteristic strain points were determined.These points segmented the rate curve into three stages:a slow initiation stage(0,ε1),a rapid growth stage(1,ε3),and a slow equilibrium stage(e3,0.9).Notably,the value ofε3 was considered the most economical,ensuring the formation of fine and uniform grains during production while optimizing the process,reducing energy consumption and costs,and enhancing overall material performance.Finally,based on the physical constitutive relationships and kinetic models,a multiscale simulation approach combining the finite element method(FEM)and cellular automata(CA)was employed to predict the microstructural evolution of 30CrNiMoVW steel.The simulation results demonstrate that the FEM&CA approach can accurately reproduce the dynamic recrystallization behavior and microstructural evolution observed experimentally.This work provides critical guidance for the development of forging processes for 30CrNiMoVW steel.
基金Project supported by the National Science and Technology Major Project(No.J2022-IV-0005-0022)the Aero Science Foundation of China(No.20230015050001)the Shenyang Science and Technology Plan Project of China(No.24-202-6-01)。
文摘As a common fault of the aero-engine,the blade-casing rubbing(BCR)has the potential to cause catastrophic accidents.In this paper,to investigate the dynamic responses and wear characteristics of the system,the laminated shell element is used to establish the finite element model(FEM)of a flexibly coated casing system.Using the shell element,the blade is modeled,and the surface stress of the blade is calculated.The stress-solving method of the blade is validated through comparisons with the measured time-domain waveform of the stress.Then,a dynamic model of a blade-flexibly coated casing system with rubbing is proposed,accounting for the time-varying mass and stiffness of the casing caused by coating wear.The effects of the proposed flexible casing model are compared with those of a rigid casing model,and the stress changes induced by rubbing are investigated.The results show that the natural characteristics of the coated casing decrease due to the coating wear.The flexibly coated casing model is found to be more suitable for studying casing vibration.Additionally,the stress changes caused by rubbing are slight,and the change in the stress maximum is approximately 5%under the influence of the abrasive coating.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2501).
文摘The numerical approximation of stochastic partial differential equations(SPDEs),particularly those including q-diffusion,poses considerable challenges due to the requirements for high-order precision,stability amongst random perturbations,and processing efficiency.Because of their simplicity,conventional numerical techniques like the Euler-Maruyama method are frequently employed to solve stochastic differential equations;nonetheless,they may have low-order accuracy and lower stability in stiff or high-resolution situations.This study proposes a novel computational scheme for solving SPDEs arising from a stochastic SEIR model with q-diffusion and a general incidence rate function.A proposed computational scheme can be used to solve stochastic partial differential equations.For spatial discretization,a compact scheme is chosen.The compact scheme can provide a sixth-order accurate solution.The proposed scheme can be considered an extension of the Euler Maruyama method.Stability and consistency in the mean square sense are also provided.For application purposes,the stochastic SEIR model is considered using q-diffusion effects.The scheme is used to solve the stochastic model and compared with the Euler-Maruyama method.The scheme is also compared with nonstandard finite difference method for solving deterministic models.In both cases,it performs better than existing schemes.Incorporating q-diffusion further enhanced the model’s ability to represent realistic spatial-temporal disease dynamics,especially in scenarios where classical diffusion is insufficient.
基金supported by the National Natural Science Foundation of China(Grant Nos.42307241 and 42107211)the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project(Grant No.SKLGP2022Z008).
文摘Structure-type rockbursts frequently occur in deep tunnels,with structural planes and stress conditions being critical factors in their formation.In this study,we utilized specially developed analogous materials that exhibit the high brittleness and strength characteristics of deep hard rock to construct physical models representing different types of structural planes,including composite,exposed,non-exposed,and throughgoing structural planes.Physical simulation experiments were conducted on structuretype rockbursts in deep horseshoe-shaped tunnels,focusing on strain differentiation characteristics,critical triggering conditions,critical crack opening displacement,the incubation process,the reduction effects of structural planes on failure intensity,and formation mechanisms.These experiments were complemented by acoustic and optical monitoring,as well as discrete element numerical simulations,to provide a comprehensive analysis.The results revealed that the most significant strain heterogeneity in the surrounding rock occurs at the tip of the structural plane along the tunnel's minimum principal stress direction,driven by the combined effects of tensile and shear forces.We quantitatively determined the critical stress and strain conditions for structure-type rockbursts and evaluated the intensity of rockbursts induced by different structural planes using critical crack opening displacement(COD)values,the uniformity coefficient,and the curvature coefficient.Analysis of acoustic emission events,including frequency,amplitude,and b-value,indicated that the macro-fracture process is governed by both the principal stress differential and the characteristics of the structural plane.Furthermore,using the bearing capacity reduction coefficient,we found that exposed structural planes have the most significant weakening effect on rock mass strength,followed by non-exposed and throughgoing structural planes.The analysis of average frequency(AF)and rise angle(RA)parameters revealed a close correlation between the failure modes of structure-type rockbursts,the rock mass structure,and the stress levels.These findings provide critical theoretical support for the prediction and prevention of structure-type rockburst disasters.
