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Design and implementation of an integrated cloud platform for intelligent and data-driven oilfield development
ZHANG Liming;ZHAO Xudong;JIANG Peiyin;QIN Guoyu;WANG Xiaopu;ALFARISI Omar;ZHANG Kai;[Objective] The rapid growth of the “Belt and Road” initiative has significantly boosted international oil and gas cooperation in resource-rich regions such as the Middle East, Central Asia, and Africa. However, these international projects often encounter challenges like complex geological environments, remote operation and maintenance needs, and varying technical standards. In this context, accelerating digital and intelligent transformation is crucial to help oilfields reduce costs, improve efficiency, and develop innovative industrial models. Traditional development methods struggle to handle the multi-source, high-dimensional data produced in modern oilfields. To promote the smart development of global oilfields, it is essential to build a digital-intelligent integrated cloud platform that combines data-driven decision-making, digital twin technology, and cross-disciplinary expertise. [Methods] We created a multi-module integrated cloud platform utilizing the interdisciplinary resources of the China–Saudi Petroleum Energy Belt and Road Joint Laboratory. The platform's architecture is based on a cloud-native framework, comprising a data layer, an AI algorithm layer, and a control service layer. It incorporates back-end microservices, an Oracle database for reliable data management, and a progressive front-end framework for interactive visualization. The core technology consists of four specialized modules that perform intelligent analysis of artificial-lift operating conditions, optimize artificial-lift design, assess oilfield production performance, and run virtual simulations. By integrating these modules, the platform forms a seamless intelligent workflow from real-time condition diagnosis to production optimization and comprehensive performance evaluation. [Results] The platform has been successfully implemented in several major international projects, most notably within the Ahdab Oilfield in Iraq. Using the first module, the platform demonstrated its ability to analyze block-wide conditions and identify specific issues, such as gas lock and supply shortages, with high accuracy. In the Ahdab field, which faces challenges like high water cut and production stability issues, the platform completed 156 well-cycle control measures. These optimizations led to a total oil increase of 110 700 tons, effectively achieving objectives related to boosting oil production, controlling water production, and reducing operational costs. Additionally, the evaluation module proved effective in identifying low-performing wells by ranking them based on standardized multidimensional scores, enabling engineers to implement targeted geological and technical interventions. Moreover, the platform has served as a key tool for international collaboration, supporting 27 national-level research projects and training over 1 000 petroleum professionals from partner countries such as Uganda.[ Conclusions]This study established a robust technological foundation for smart oilfield development. By integrating big data analytics, AI, and cloud computing, the platform bridges the gap between theoretical oilfield development and practical engineering applications. The successful deployment at the Ahdab Oilfield offers a replicable and scalable model for oilfields in Belt and Road partner countries. It enhances production management and decision-making efficiency and promotes international scientific cooperation. Future updates will aim to expand the platform's application across the entire oil and gas value chain and further explore the use of digital twins in global energy transformation.
Design of an experimental system and numerical simulation method for underground gas and energy storage
CHEN Fuzhen;YANG Yongfei;AlFARISI Omar;LI Lei;WANG Xiaopu;SUN Renyuan;GU Jianwei;[Objective] Underground gas and energy storage are emerging interdisciplinary fields that utilize subsurface geological space to store gaseous substances and, in some cases, surplus energy that is converted into gaseous carriers. The large-scale deployment of carbon, seasonal natural gas, geological hydrogen, and compressed air energy storage depends critically on a thorough understanding of multiphase flow mechanisms in porous media. However, accurately quantifying trace amounts of fluids under high-temperature and high-pressure conditions remains a major bottleneck in core-scale gas–liquid two-phase flow experiments. Conventional experimental approaches are largely limited to bulk statistical observations and fail to monitor the temporal and spatial evolution of fluid migration and distribution in real time. Furthermore, numerical simulation methods for accurate modeling through scale-up remain insufficiently developed. To address these challenges, this study conducts integrated experimental and numerical simulation investigations focused on underground gas and energy storage. [Methods] A comprehensive experimental platform was designed and constructed, consisting of three tightly coupled subsystems for displacement, nuclear magnetic resonance(NMR) measurement, and metering. Gas injection experiments into brine-saturated cores were conducted following standardized core-flooding procedures, employing stepwise injection and intermittent NMR scans. NMR measurements were performed using three complementary modalities: T2 relaxation spectra to quantify pore-scale fluid occupancy and movable pore space; SE-SPI maps to capture one-dimensional spatial distributions along the core axis via virtual slicing; and NMR imaging to obtain a two-dimensional visualization of dynamic displacement patterns and gravity segregation. To translate the laboratory findings to field scales, a hierarchical numerical simulation workflow was established. A core-scale model was constructed, enabling mechanistic interpretation of observed NMR patterns. Further, a two-dimensional plane radial flow model was developed to examine cyclic injection–production behavior and gas–water transition-zone evolution. Finally, a three-dimensional field-scale model was constructed to replicate the complex structures and heterogeneity of real formations and provide fully visualized multiphase–multicomponent dynamics for production forecasting and optimization. [Results] The NMR-based experimental system enabled multidimensional, real-time quantification of gas–water processes, which are difficult to resolve using conventional methods. T2 spectra enabled accurate quantification of hydrogen-bearing fluids in porous media and revealed that evaporation is an additional transport pathway that can reduce residual water saturation, indicating a coupled “displacement–evaporation” mechanism. The SE-SPI maps revealed pronounced spatial non-uniformity in fluid distributions, indicating that injected gas preferentially concentrated in the upper part of the formation. NMR imaging indicated that the evaporation of residual water into the gas phase could mobilize water mass transport without requiring bulk liquid flow. Numerical simulations provided consistent mechanistic explanations and enabled reliable scale-up insights, and core-scale simulations successfully replicated key features observed in the experiments, including upward gas accumulation driven by gravity. The two-dimensional single-well model demonstrated a clear zonal storage pattern, comprising gas, gas–water transition, and outer water zones, and clarified the aquifer's role in stabilizing reservoir pressure while driving water invasion during production. The three-dimensional field-scale model enabled visualization of convective behavior and heterogeneity-induced fingering and identified leakage-prone areas that require operational constraints and continuous monitoring. [Conclusions] This study proposes and validates an integrated experimental–numerical framework for underground gas and energy storage research. It combines an NMR-based laboratory system with multiscale, multiphase, multicomponent simulations spanning from core to field scale. This platform addresses longstanding limitations in trace fluid measurement and spatiotemporal visualization, enabling a systematic interpretation of storage mechanisms, migration behaviors, and distribution patterns under realistic formation conditions. By bridging laboratory measurements with well-and field-scale modeling, the framework establishes a practical basis for evaluating storage sites, designing injection and production processes, and optimizing underground gas storage in a risk-informed manner. Leveraging the China–Saudi “Belt and Road” joint laboratory, this methodology provides a scalable pathway for international collaboration and technology transfer in underground gas and energy storage, particularly in Middle Eastern regions with a number of depleted reservoirs and in China, which possesses extensive aquifer resources. This approach thus supports the development of cleaner and more diversified energy systems.
A machine learning-based optimization design method for fracturing fluid flow rate targeting equilibrium proppant bank height
LIU Huajie;LI Zhaopeng;CHERNYSHOV Sergey;ZHANG Liming;LIN Wenxiang;DING Fuquan;SOLLING Theis Ivan;[Objective] The Middle East is a key region for oil and gas within the Belt and Road Initiative, but it faces challenges because most oil fields lack optimized fracturing designs. To achieve the desired stimulation results, high-displacement fracturing fluid operations are often used, which can lead to significant groundwater contamination from broken gel fluid. Visual plate experiments are commonly employed to optimize fracturing parameters; however, they are time-consuming and require substantial material, which hinders the development of green and intelligent oilfields. Therefore, this study aimed to develop an efficient machine learning model to predict the equilibrium proppant bank height within primary fractures and to use the output to inversely optimize the fracturing fluid displacement rate. [Methods] After a comprehensive review of existing literature, a dataset was established, and data standardization was carried out. By evaluating predictive performance using five-fold cross-validation and a test set, four machine learning algorithms were compared, and the best predictive model was selected. A method leveraging this optimal model to improve both the plate experiment process and the fracturing fluid displacement rate was then proposed. [Results] The random forest model showed the best predictive performance, achieving a coefficient of determination of 0.947, a root mean square error of 3.62, and a mean absolute error of 2.27 on the test set. For the validation set with 21 samples, the absolute error was within 1.50 cm, with a fitted curve slope of 1.07 and an intercept of-0.81. The inversely designed, optimized fracturing fluid displacement rate was significantly lower than the empirical rate, saving at least 106.2 m3 of fracturing fluid per hour while still ensuring effective fracture filling. [Conclusions] This study not only addresses current limitations of plate experiments but also offers guidance for designing fracturing fluid displacement rates in field operations within the Middle East.
Development and performance evaluation of phase change microcapsule-based inhibitors for controlling gas hydrate dissociation in marine reservoirs
WANG Jintang;GUO Jianxun;HUANG Xianbin;WANG Xiaopu;LIAO Bo;LI Meichun;WANG Ren;LYU Kaihe;SUN Jinsheng;[Objective] Natural gas hydrates are a key resource for enhancing energy security and supporting the low-carbon transition in countries along the Maritime Silk Road. During drilling in hydrate-bearing formations, heat transfer from the drilling fluid to the formation is the main factor driving reservoir hydrate dissociation and borehole wall instability. To maintain stability in hydrate-bearing formations during drilling, a treatment agent was developed to regulate the temperature of the drilling fluid in the wellbore and reduce heat transfer from the fluid to the hydrate reservoir. To meet current engineering requirements for natural gas hydrate drilling and production, a high phase-change latent heat n-alkane was chosen as the core material, while environmentally friendly sodium alginate and carboxymethyl cellulose served as shell materials. Using a physical cross-linking mechanism, microencapsulated phase-change cold-storage materials with a core–shell structure(phase-change microcapsules(PCMCs)) were produced via an electrostatic spraying technique. [Methods] This method allowed precise control of droplet formation and solidification, facilitating accurate adjustment of microcapsule size distribution. The microstructure and surface morphology of the PCMCs were analyzed by scanning electron microscopy and a focused beam reflectance measurement system, while laser particle-size analysis determined their particle-size distribution. Differential scanning calorimetry was employed to study the phase-change behavior, latent heat properties, and thermal cycling stability of the PCMCs. Additionally, a thermal conductivity analyzer and a high-pressure natural gas hydrate evaluation system—capable of simulating hydrate reservoir pressure– temperature conditions—were used to systematically assess the thermal insulation capabilities of the PCMCs and their inhibitory effect on hydrate decomposition. [Results]Results demonstrated that the PCMCs maintained an intact spherical capsule shape with a clear core–shell interface, and had a particle size distribution ranging from 5.7 to 50.09 μm, with a median diameter of 21.26 μm, meeting the operational demands of offshore drilling. Moreover, the phase-change melting temperature was 13.88 ℃ with a latent heat of 171.51 J/g and an encapsulation efficiency of 89.5%. After 30 heating–cooling cycles, the PCMCs retained 90.6% of their initial latent heat, indicating excellent thermal reliability and suitability for repeated use during drilling, which helps lower operational costs. When added to drilling fluid, the PCMCs reduced the system's bulk thermal conductivity by approximately 13%, extended the time to reach the target temperature by 26.3%, and decreased hydrate decomposition rates by 12.57% compared with the control fluid. Ultimately, these PCMCs effectively inhibit reservoir hydrate dissociation by lowering the thermal conductivity, slowing heat transfer from wellbore fluid to the formation, and absorbing heat during phase change to mitigate temperature increases. [Conclusions] This research has been applied in China's third offshore natural gas hydrate trial production campaign, providing a theoretical basis and technical support for future development and utilization in hydrate-rich countries like Pakistan and Indonesia. It is also expected to promote further technical exchange and cooperation in gas hydrate exploration, development, and wellbore integrity among countries participating in the Belt and Road Initiative.
Analysis of the seepage mechanism of brine-CO2 oil displacement and storage in heterogeneous porous media with carbonate coating
WANG Xiaopu;MA Kefan;WANG Qingxuan;ZHANG Liming;ZHANG Kai;ALFARISI Omar;LI Zhaomin;LI Binfei;[Objective] Carbonate reservoirs have become strategic targets for reserve expansion in China and the Middle East, driven by the dual goals of reducing carbon emissions and ensuring energy security. However, their significant heterogeneity, complex pore structures, and wettability changes present considerable challenges to the efficiency of CO2-based enhanced oil recovery(EOR). At the pore level, the interaction of capillary forces, viscous forces, and the evolution of multiphase interfaces causes unstable displacement fronts and severely limits sweep efficiency in low-permeability areas. [Methods] To tackle these issues, this study aims to reveal the pore-scale multiphase seepage mechanisms of brine–CO2 displacement in carbonate-coated heterogeneous porous media. This provides a microscopic foundation for optimizing CO2 flooding parameters and enhancing sweep performance in actual carbonate reservoirs. A heterogeneous pore network was constructed using a microfluidic chip, and calcium carbonate was coated in situ to simulate authentic carbonate reservoir surfaces and wettability. A series of visualization experiments were conducted at a controlled temperature(40 ℃). CO2 foam flooding and brine flooding at different injection rates were compared. A CCD imaging system was used to capture pore-scale evolution of oil, water, and gas phases, and gas saturation and residual oil distributions were quantified through image processing. To improve the accuracy of residual oil characterization, the ResNet152 deep neural network was trained on 2 885 labeled microfluidic sub-images from CO2 flooding, CO2–water alternating flooding, and brine flooding. Using weighted cross-entropy loss, AdamW optimization, and learning rate scheduling, the model achieved high classification accuracy for dispersed, mixed, and heterogeneous residual oil. [Results] Results showed that flooding performance was strongly affected by injection rate and pore-structure heterogeneity. At moderate flow rates(0.5–3 μL·min–1), CO2 foam greatly improved sweep efficiency, nearly eliminating residual oil saturation. Foam viscosity and the Jamin effect effectively suppressed viscous fingering and prevented preferential flow through high-permeability channels, forcing the displacing phase into low-permeability areas. Conversely, at very low injection rates(0.1 μL·min–1), foam instability caused large dispersed gas bubbles, limiting gas saturation to 25%, and hindered oil droplet mobilization, resulting in a high residual oil saturation of 42%. Gas saturation displayed a parabolic relationship with flow rate, with the maximum(93%) at 1 μL·min–1, where bubble size was smallest, and foam stability was optimal. Deep-learning-based oil classification also showed that brine flooding and CO2–water alternating flooding primarily produced dispersed residual oil, whereas surfactant-assisted CO2 flooding created a mixture of dispersed(49%), mixed(36%), and heterogeneous(14%) oil, reflecting foam instability and uneven sweep in highly heterogeneous zones. The model achieved a validation accuracy of 93%, confirming its effectiveness in pore-scale residual oil identification. [Conclusions] This study clarifies the mechanisms underlying brine–CO2 displacement in carbonate-coated heterogeneous media. Calcium carbonate coating increases hydrophobicity, delays breakthrough in high-permeability pathways, and significantly enhances sweep in low-permeability zones, reducing residual oil by up to 28%. CO2 foam flooding is highly sensitive to injection rate, with moderate flow rates producing stable foam, high gas saturation, and efficient oil mobilization, whereas very low or high rates reduce displacement stability. By combining microfluidic visualization and deep-learning image analysis, this research offers microscopic insights for optimizing CO2 flooding conditions and provides technical guidance for deploying CO2-based EOR in Middle Eastern carbonate reservoirs. The findings also support international cooperation under the Belt and Road Initiative and contribute to global efforts in the low-carbon, efficient development of carbonate oilfields.
Study and experimental validation of the magnetic and thermal performance of UHV transformers under DC bias
HAO Liang;DU Zhenbin;WANG Youhua;WANG Jianmin;ZHAO Zhigang;[Objective] As a key component of ultrahigh-voltage (UHV) transmission systems， the operational reliability of UHV transformers directly affects power grid security， stability， and power quality. With China’s rapid development of hybrid UHV AC/DC power grids and the increasing occurrence of geomagnetic disturbances， the issue of DC bias has become highly important. The resulting surge in core and structural component losses， along with increased local temperature rises， poses a serious threat to grid safety. Therefore， an in-depth investigation into the magneto–thermal behavior of UHV transformers under DC bias conditions is essential. [Methods] This study focuses on a 1000 kV UHV main transformer. A three-dimensional magneto–thermal coupling model is developed based on actual product parameters， including structural components such as the tank， belly plates， tie plates， support plates， footings， and magnetic shields， along with a segmented-frame core. First， the magnetic characteristic curves of the ferromagnetic core material under different DC bias currents are obtained through single-sheet measurements， then corrected and extrapolated for accuracy. Second， under high to medium operating conditions， different levels of DC excitation are applied to the high-voltage side to calculate excitation currents for various DC bias conditions， followed by a comparative analysis of magnetic flux density and loss characteristics of the core and structural components at maximum excitation. Third， the calculated losses under various DC bias levels are directly coupled to the thermal field—ignoring oil flow effects—to perform magneto–thermal simulations and assess temperature distribution and hotspot formation. Finally， to verify the accuracy and reliability of the proposed model and method， experiments are conducted on a 10 kV transformer model to examine excitation currents and loss behavior under different DC bias conditions. [Results] The findings indicate that (1) without DC bias， the excitation current exhibits a symmetric peaked waveform with mainly odd harmonic components; as the DC component increases， the waveform becomes distorted， the amplitude increases significantly， and harmonic components emerge. (2) Introducing a 4 A DC bias current causes a 49.1% increase in core loss compared to the unbiased state. At the same time， the longitudinal leakage flux in the main channel between the high- and medium-voltage windings increases by 27.4%， significantly intensifying eddy current losses in structural parts， especially near winding ends. (3) Magneto–thermal coupling simulations show that with a 4 A DC bias， the overall core temperature rises notably， with the middle core limb experiencing the most significant increase， reaching 66.28 K. Distinct local hotspots appear in structural components， particularly near winding ends. (4) Experimental validation confirms consistent trends in excitation current and a gradual rise in no-load loss， with the growth rate decreasing over time. Although some numerical deviations occur， they remain within acceptable limits， validating the accuracy of the proposed approach. [Conclusions] Simulation and experimental results demonstrate that DC bias causes significant increases in losses and temperature， worsens local overheating， and accelerates insulation aging risks. Therefore， the negative effects of DC bias must be considered in the design， evaluation， and long-term operation of UHV transformers.
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Teaching experimental design of magnetic anomaly detection based on a rotor UAV platform
WANG Chao;CHENG Linhan;WANG Yanzhang;WAN Yunxia;[Objective] In the talent training system for geophysical exploration and instrumentation majors， the integration of professional theory and engineering practice is a core requirement. The magnetic anomaly detection experiment serves as an important link between theory and practice， laying a solid foundation for subsequent professional learning and engineering applications. This paper presents the design of a full-process teaching experiment scheme for magnetic anomaly detection， covering “instrument system integration— instrument performance testing—target information acquisition—data preprocessing—result demonstration.” [Methods] Using a uniformly magnetized sphere as the research object， this study simulates the spatial distribution of magnetic anomalies. An experimental teaching system capable of synchronously acquiring magnetic field and spatial position data was designed and integrated， comprising an optically pumped magnetometer， a positioning module， a multichannel data acquisition instrument， and a UAV. Field experiments， including sensor performance testing， sensor placement testing， dynamic flight consistency testing， and regional magnetic anomaly surveys， were conducted to collect magnetic anomaly data. [Results] Due to differences between the field experimental environment and ideal working conditions， and because manually placed small vehicles cannot fully replicate standard uniformly magnetized spheres， certain numerical deviations exist between the measured data and the simulation results. However， both exhibit overall variation trends in the spatial distribution of the magnetic field that are highly consistent， thereby verifying the reliability and trend accuracy of the detected data. [Conclusions] The teaching demonstration and practical training mode designed in this paper， which combines “modular” instrument system integration， “process-based” instrument performance testing， and “scenario-based” field magnetic anomaly detection， effectively improves the cognitive level of students majoring in instrumentation on the design concept of advanced specialized instrument systems. It also deepens the understanding of students majoring in geophysical exploration-related disciplines regarding the fundamental principles of magnetic anomaly detection， and comprehensively tempers students’ comprehensive application capabilities in real-world engineering scenarios.
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Construction of a virtual simulation experiment for meteorological observation lidar
WANG Meng;WANG Yufeng;YAN Qing;WANG Li;LIU Jingjing;[Objective] In response to the strategic demands of national ecological civilization， meteorological observation lidar， as a key technology for atmospheric environmental monitoring， has become a core support for promoting the high-quality development of the meteorological industry. To address the challenges of high cost， high risk， and difficulty in reproducing experimental phenomena in traditional practical teaching， this study aims to develop a virtual simulation experimental system for meteorological observation lidar， thereby compensating for the shortcomings of existing virtual simulation systems in meteorological remote sensing. The system is developed based on a national first-class course and the Lidar Remote Sensing Research Center at the Xi’an University of Technology. It is designed to enhance students’ comprehensive design and innovation capabilities and to provide core teaching support for cultivating high-level interdisciplinary meteorological talents in the new era. [Methods] This study adopts an experimental approach based on “modular design and progressive training” and constructs a three-tiered experimental framework comprising “cognition， design， and exploration，” corresponding to three core modules: lidar system cognition， multispectral spectroscopic system design， and detection and data processing. (1) At the cognitive level， students master the structure and principles of lidar systems via immersive navigation and interactive model demonstrations. (2) At the design level， a task-driven mode is adopted to enable students to independently select detection targets and complete the design of a multispectral spectroscopic system. (3) At the exploration level， students assemble a functional lidar system and undergo a comprehensive training in data acquisition， inversion， and systematic error analysis. Throughout the experiment， scientific methods—including observation， modeling， comparison， and induction—are seamlessly integrated， with theoretical knowledge embedded into interactive tasks， thereby effectively enhancing the students’ capabilities from basic cognition to comprehensive innovation. [Results] This study has achieved substantial teaching effectiveness through an innovative design that integrates science and education， virtual reality， and learning with assessment. The system employs high-fidelity modeling to authentically reproduce lidar structures and detection processes， effectively addressing the challenges of high cost， safety risks， and limited repeatability in traditional experimental teaching. Within the simulated environment， students engage in a complete workflow， including system cognition， optical design， data acquisition， and inversion analysis. Their operational behaviors are recorded in real time and automatically evaluated， generating comprehensive multidimensional assessment reports. The experiment thus achieves a deep integration of theoretical knowledge acquisition， practical skill training， and process-oriented evaluation. [Conclusion] The implementation of this study has not only advanced the systematization and practical application of virtual simulation experiments for meteorological observation lidar， but has also explored an innovative talent development pathway characterized by “virtual augmentation of real practice and the integration of science and education.” This experimental framework significantly enhances students’ capabilities in system design， data processing， and scientific inquiry in complex meteorological detection scenarios. It provides robust support for cultivating high-quality talents in emerging engineering majors such as instrumentation， optoelectronics， and meteorology， thereby offering an important teaching and practical platform for the independent development of meteorological detection equipment and technologies in China.
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Experimental platform for enhancing resilience of distribution network under flood disasters based on power-transportation coupling
LIAN Xianglong;CHEN Jie;FU Weifeng;LIU Lijun;[Objective] With the increasing frequency and intensity of flood disasters， distribution networks are exposed to complex cascading failures caused by the strong coupling between power and transportation systems. However， conventional experimental pedagogy in electrical engineering focuses primarily on deterministic operation and single-system analysis， which limits students’ understanding of disaster-induced risks， recovery processes， and resilience-oriented decision-making. This study aims to design an experimental teaching platform for enhancing the resilience of distribution networks in flood-disaster scenarios by explicitly considering power–transportation coordination. The goal is to support interdisciplinary learning and improve students’ ability to analyze and manage complex coupled systems under extreme conditions. [Methods] An integrated experimental platform is developed by coupling distribution and transportation networks with emergency resource systems within a unified modeling framework. The evolution of flood disasters is first described using a grid-based hydrological model， which captures the spatial and temporal accumulation of surface water. The simulated flooding depth is then mapped to the probability of failure of distribution nodes and degradation of road traffic， enabling the construction of a coupled power–transportation failure model. Emergency resources， including repair crews and mobile energy storage systems (MESS)， are incorporated to represent both structural repair and temporary power supply capabilities. To reflect uncertainty in the impact of disasters， Monte Carlo simulation is employed to generate multiple failure scenarios. By implementing scenario clustering， the computational burden is reduced while preserving representative and high-risk characteristics. Based on these scenarios， a two-stage emergency scheduling framework is established， in which pre-disaster resource allocation and post-disaster dynamic dispatch decisions are jointly optimized. A risk-aware strategy based on conditional value-at-risk (CVaR) is introduced to emphasize low-probability but high-impact scenarios. The platform enables comparative experimental analysis by varying key dimensions， including the consideration of road flooding effects and the number of MESS units and repair crews deployed. [Results] The simulation results under different flood disaster scenarios demonstrate that the proposed platform effectively captures the influence of cross-system coupling on the resilience of the distribution network. When road flooding and traffic degradation are considered， the arrival of emergency resources is delayed， and the power restoration process is significantly slowed， leading to larger resilience loss. Increasing the number of MESS units improves early-stage power supply by providing temporary support to critical loads， which helps mitigate initial service interruptions. In contrast， increasing the number of repair crews mainly accelerates mid- and late-stage structural recovery， enabling the system to reach full restoration earlier. The best overall performance is achieved through the coordinated deployment of repair crews and MESS， combining early power support with faster recovery. Moreover， the CVaR-based scheduling strategy provides enhanced robustness by prioritizing high-impact disaster scenarios， resulting in more stable recovery trajectories across different scenarios. These results clearly illustrate the complementary roles of transportation conditions， emergency resources， and risk-aware decision-making in resilience enhancement. [Conclusions] The proposed experimental teaching platform integrates flood-disaster modeling， coupled power–transportation failure analysis， and risk-aware emergency scheduling into a coherent framework. It transforms abstract concepts of system resilience into observable experimental phenomena， enabling students to intuitively understand how disaster evolution， transportation accessibility， and resource coordination jointly affect the recovery of distribution networks. The platform effectively supports comparative experiments and decision analysis in uncertainty， fostering interdisciplinary thinking and resilience-oriented engineering skills. This study provides a practical reference for advancing experimental teaching reform in electrical engineering and cultivating students’ ability to analyze and manage complex coupled energy systems in the event of extreme events.
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Simulation and optimization practice of electromagnetic force stroke characteristics of the pilot solenoid valve in an electronic controlled air suspension gas distribution valve
LIU Yuechao;ZHAO Leilei;YU Yuewei;DING Fan;JIN Mingqing;SHAN Xiyu;[Objective] The pilot solenoid valve is a critical component of the electronic controlled air suspension (ECAS) air distribution valve， governing the inflation and deflation processes and， consequently， the inflation and deflation rates. Its electromagnetic force–stroke profile directly determines the accuracy and stability of spool-position control， which in turn affects the rapid and precise regulation of ECAS ride height and air-spring stiffness. Owing to the limited load capacity of commercial vehicle electrical systems， the available drive current is constrained， resulting in insufficient electromagnetic force at the beginning of the armature stroke and excessive force near the final pull-in. During the initial motion， an inadequate electromagnetic driving force cannot effectively overcome resistance， thereby deteriorating the armature start-up behavior， manifested as a delayed response or even start-up failure. During final pull-in， the electromagnetic force increases rapidly as the air gap decreases， causing the armature to accumulate excessive kinetic energy and collide with the stationary core at high speed. This induces stop-pin impact and energy loss， thereby reducing the operational stability and reliability of the solenoid valve. Therefore， without increasing the drive current， this study aims to improve the electromagnetic force–stroke distribution and to conduct structural optimization of the pilot solenoid valve. [Methods] Based on equivalent magnetic-circuit theory， the magnetic-circuit characteristics of the pilot solenoid valve were systematically analyzed. A finite-element electromagnetic model was established， considering magnetic nonlinearity and variations in the working air gap， and its accuracy was validated through comparison with static electromagnetic force experiments. On this basis， evaluation indices for characterizing the electromagnetic force–stroke distribution were defined. Pearson correlation coefficients were employed to perform sensitivity analyses of key structural parameters， and parameters with high sensitivity were selected as optimization variables to clarify the relationships between structural parameters and electromagnetic force distribution. Considering the coupling effects among multiple structural parameters， a response-surface prediction model for the average electromagnetic force over typical working air-gap intervals was developed using a Box–Behnken design. To maximize the average electromagnetic force in the initial and mid-stroke air-gap intervals and minimize it in the final pull-in interval， the NSGA-II multiobjective optimization algorithm was adopted to search for Pareto-optimal combinations of design variables. Subsequently， electromagnetic force simulations were conducted for the optimal parameter combination， and the simulation results were compared with the corresponding response-surface predictions to verify the effectiveness of the proposed optimization method. [Results] The optimization results indicate that， under an unchanged drive current， the average electromagnetic force in the initial working air-gap segment increased by 31.83% compared with the pre-optimization design， while it increased by 25.72% in the mid-stroke working air-gap segment. In contrast， the average electromagnetic force in the final pull-in air-gap segment was reduced by 20.98%. The improved electromagnetic force–stroke distribution effectively alleviates the imbalance between insufficient driving force at the initial stage and excessive pull-in force at the final stage. Consequently， the start-up capability of the pilot solenoid valve under current-limited conditions is significantly enhanced， the responsiveness and stability of armature motion in the intermediate stroke are improved， and the end-stage impact and associated energy loss are effectively reduced. [Conclusions] This study addressed the suboptimal electromagnetic force–stroke distribution of a small-orifice pilot solenoid valve in an ECAS air distribution valve under current-limited conditions through modeling， experimental validation， simulation， and optimization. The proposed method significantly improved the force distribution across the full stroke， providing a valuable reference for the design， simulation， testing， and application of pilot solenoid valves. Additionally， it serves as a typical case for solenoid valve simulation experiment teaching， enhancing students’ engineering analysis skills and innovative thinking.
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Study on the design and analysis methods of orthogonal experiment
Liu Ruijiang,Zhang Yewang,Wen Chongwei,Tang Jian(School of Pharmaceutics,Jiangsu University,Zhenjiang 212013,China)The importance of orthogonal experimental design and analysis is introduced briefly.The principle and characteristic are expounded.The design methods of orthogonal experiment and analysis methods of orthogonal experimental results are analyzed in detail,which afford fully systemic methods for orthogonal experimental design and analysis.Problems in orthogonal experimental design and analysis and development of software for orthogonal experimental design and analysis are also pointed out in the end.
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Research on statistical analyses and countermeasures of 100 laboratory accidents
Li Zhihong;Training Department,Kunming Fire Command School;This paper summarizes 100typical cases of laboratory accidents from 2001and analyzes the cases in fields of accident type,accident link,accident cause,dangerous substance category,etc.The result shows as follows:the fire disasters and explosive accidents are the main types of laboratory accidents;the dangerous chemicals,instruments and equipment,and pressure vessels are main dangerous substances;the instruments and equipment and reagent application processes are the main links of accidents;the violation of rules,improper operation,carelessness,wire short circuit and aging are the main reasons of accidents.It also puts forward the countermeasures and suggestions for the prevention and control of laboratory accidents in the following aspects:establishing complete safety management system,actively promoting standard construction of laboratory safety,strengthening laboratory safety education and training,and formulating and improving emergency plans for laboratory accidents.
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Promotion of reform and innovation on integration of theory teaching and experimental teaching by virtual simulation experiment teaching
XIONG Hongqi;Based on the concept of experimental teaching and its importance, the connotation of virtual simulation experimental teaching is expounded upon. On this basis, this paper puts forward six balance principles that virtual simulation experimental teaching should follow to promote the upgrading and reconstruction of traditional experimental teaching and elaborates the reform idea of virtual simulation experiment teaching for the overall optimization and innovation of theory teaching. The brief analysis is carried out on that the introduction of virtual simulation experimental teaching is conducive to promoting innovation and entrepreneurship education into the whole process of professional education.
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Research and application of BOPPPS teaching method in MOOC teaching design
WU Changdong;JIANG Hua;CHEN Yongqiang;School of Electrical Engineering and Electronic Information,Xihua University;School of Information Science and Technology,Southwest Jiaotong University;On the basis of introducing the connotation of BOPPPS(bridge-in,objective,pre-assessment,participatory learning,post-assessment and summary)model,this paper explores upon the guiding role of the BOPPPS teaching model in MOOC teaching design.Based on the BOPPPS model,MOOC teaching design of"Series feedback voltage stabilization circuit"is carried out.This provides some reference for improving the quality of MOOC teaching design,stimulating students' learning interest and motivation,and promoting teachers' reform of teaching content design.
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The application of studying fluorescence spectroscopy on protein
Yin Yanxia,Xiang Benqiong,Tong Li(College of Life Science,Beijing Normal University,Beijing 100875,China)Fluorescence spectroscopy is very important for studying protein structure and conformation changes.The concept and principle of fluorescence spectroscopy are introduced at first,then the application of studying fluorescence spectroscopy on protein is explained.
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The CNC machine tool with systematic work process and its application of teaching design
Li Yanxian(Department of Mechanical and Electronic Engineering,Nanjing Communications Institute of Technology,Nanjing 211188,China)According to professional training objectives and the main jobs of the structure of vocational skills and knowledge required to "CNC machine tools and spare parts" for the carrier,taking the CNC programming and operation of capacity-building as the center,this paper shows the design of the "knowledge of CNC machine tools,observation and analysis of CNC lathes,CNC milling machine to observe and analyze the processing center,programming and processing stepped shaft,threaded shaft of the programming and processing,hand wheel slot programming and processing,convex programming and processing of the template,the base of the programming and processing"of 9 items,25 learning environment,67 tasks,and one of the "convex template programming and processing" learning environment for the teaching unit design.
[Downloads: 383,527 ] [Citations: 7 ] [Reads: 156 ] HTML PDF Cite this article
Study on the design and analysis methods of orthogonal experiment
Liu Ruijiang,Zhang Yewang,Wen Chongwei,Tang Jian(School of Pharmaceutics,Jiangsu University,Zhenjiang 212013,China)The importance of orthogonal experimental design and analysis is introduced briefly.The principle and characteristic are expounded.The design methods of orthogonal experiment and analysis methods of orthogonal experimental results are analyzed in detail,which afford fully systemic methods for orthogonal experimental design and analysis.Problems in orthogonal experimental design and analysis and development of software for orthogonal experimental design and analysis are also pointed out in the end.
[Downloads: 55,909 ] [Citations: 3,450 ] [Reads: 1203 ] HTML PDF Cite this article
Construction and actualization of new experimental teaching system for chemical specialty
YANG Jin-tian(Institute of Life Science,Huzhou Normal College,Huzhou 313000,China)The new system of chemical experiment teaching is constructed,and the comprehensive experiments,open experiments and research-oriented experiments are set up to improve the degree of source sharing,the efficiency of using equipment and the quality of experimental teaching,hence efficiently optimizing the practical abilities and fostering innovative spirit for the undergraduates are achieved.
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Research on statistical analyses and countermeasures of 100 laboratory accidents
Li Zhihong;Training Department,Kunming Fire Command School;This paper summarizes 100typical cases of laboratory accidents from 2001and analyzes the cases in fields of accident type,accident link,accident cause,dangerous substance category,etc.The result shows as follows:the fire disasters and explosive accidents are the main types of laboratory accidents;the dangerous chemicals,instruments and equipment,and pressure vessels are main dangerous substances;the instruments and equipment and reagent application processes are the main links of accidents;the violation of rules,improper operation,carelessness,wire short circuit and aging are the main reasons of accidents.It also puts forward the countermeasures and suggestions for the prevention and control of laboratory accidents in the following aspects:establishing complete safety management system,actively promoting standard construction of laboratory safety,strengthening laboratory safety education and training,and formulating and improving emergency plans for laboratory accidents.
[Downloads: 10,675 ] [Citations: 569 ] [Reads: 145 ] HTML PDF Cite this article
Practice and thinking of education of“College Students' Innovative and Entrepreneurial Training Program”based on tutor system
Qian Xiaoming;Rong Huawei;Qian Jingzhu;Office of Academic Affairs,Nanjing University of Technology;The innovation and entrepreneurship education has been included in the teaching and education program of college schools."College Students' Innovative and Entrepreneurship Training Program "has become an"Excellent Program"as one of the most important reform tasks in Ministry of Education.The tutor system is an effective way of innovative education and pilot training for both college schools and students.Students learn the method of innovation researches and technique of entrepreneurial process through the program.In the meanwhile,teachers in college schools find a new stage to improve their teaching ability.This article focuses on the project,practice and feasibility of the"College Students' Innovative and Entrepreneurial Training Program "under the tutor system.
[Downloads: 10,111 ] [Citations: 225 ] [Reads: 1223 ] HTML PDF Cite this article