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Risk assessment of tunnel excavation beneath ancient buildings based on dynamic Bayesian networks for double-line tunnels
JIANG Chunhai;WANG Zhen;ZHENG Zhao;ZHAO Bo;FENG Wei;ZHANG Mingli;[Objective] Urban tunnel construction projects frequently involve large-scale excavation activities that can disturb the geological strata, posing potential hazards to ground stability and the safety of surrounding underground and surface structures. This concern is particularly pronounced when tunnels pass beneath clusters of ancient buildings, as these historical structures often possess unique architectural features and varying structural conditions that render them highly sensitive to ground movements. Accurately assessing and predicting the effects of tunnel excavation on such buildings is therefore critical for ensuring both construction safety and the preservation of cultural heritage. This study primarily aimed to develop a comprehensive, dynamic risk assessment framework that captures the interactions between tunnel excavation, soil deformation, and the structural behavior of ancient buildings. Using the Lanzhou Baita Mountain Double-Line Tunnel project as a representative engineering case in which the tunnel passes directly beneath a major historical building cluster, this research seeks to provide a scientifically grounded methodology for evaluating construction-induced risks and guiding effective mitigation strategies. [Methods] This study proposes a novel risk assessment approach that combines dynamic Bayesian networks(DBNs) with finite element analysis(FEA) to model the complex, time-dependent interactions between tunnels, soil, and building structures. A detailed finite element model was first developed to simulate the stress distribution, deformation, and displacement patterns induced by tunnel excavation at multiple construction stages. These simulations provided quantitative data on ground movements and structural responses, which were then incorporated into a DBN framework. The network models the probabilistic relationships among key variables, including tunnel construction parameters, soil mechanical properties, building structural characteristics, and historical deformation patterns. The DBN allows for real-time updating of risk probabilities as new monitoring data become available, thus enabling dynamic prediction of risk evolution throughout the tunnel construction process. This approach also facilitates the quantification of the relative contributions of various risk factors at different construction stages, thereby identifying critical phases during which ancient buildings are most vulnerable. Model validation was conducted by comparing Bayesian network predictions with finite element simulation results to evaluate predictive accuracy and reliability. [Results] The results demonstrate that after integrating finite element deformation data into the DBN model, the risk levels of overlying ancient buildings during tunnel excavation are predominantly classified as Grade II. The analysis identifies building structural characteristics and tunnel-related excavation factors as the primary contributors to the observed risk. Prediction error rates of 5.8% for the left-line tunnel and 10% for the right-line tunnel confirm the model's reliability and practical applicability. The model also provides a dynamic visualization of risk evolution over time, highlighting the stages during which the ancient buildings are most susceptible to damage. Based on these findings, targeted mitigation measures are proposed, including staged structural monitoring, reinforcement or optimization of supporting structures, and real-time adjustment of excavation parameters. These measures help ensure that risk levels remain effectively controlled while maintaining construction efficiency. [Conclusions] The integration of DBNs with FEA provides a robust and reliable methodology for dynamically assessing the risk of tunnel construction impacts on ancient buildings. The proposed framework effectively identifies critical risk factors, quantifies the evolving risk levels during construction, and supports proactive intervention strategies. By enabling continuous monitoring and predictive assessment, this method enhances safety management in urban tunneling projects while safeguarding historically significant structures. The findings provide a scientifically validated approach for decision-making in complex urban construction projects involving heritage conservation, offering theoretical insights and practical guidance for engineers, project managers, and policymakers.
Design and experimental validation of path planning for fire rescue robots in long traffic tunnels
HU Qingsong;LIANG Huayu;[Objective] China has an increasing number of long traffic tunnels exceeding 10 km, which face severe fire risks owing to enclosed spaces and limited evacuation paths. Fires in such tunnels are characterized by dynamic fire spread and real-time fluctuations in environmental parameters such as temperature and visibility. Traditional path planning algorithms, however, fail to dynamically incorporate environmental factors into global planning or adapt to fire evolution during local planning, leading to suboptimal paths for rescue robots. This study aims to propose an improved hybrid algorithm, called improved ant colony optimization-improved artificial potential field(IACO-IAPF), to achieve efficient and safe path planning for fire rescue robots under dynamic tunnel fire scenarios and to verify its performance through simulation experiments to provide technical support for practical tunnel fire rescue operations. [Methods] A two-stage IACO-IAPF algorithm following a framework of global guidance and local correction was designed. First, a 500 m × 30 m scaled tunnel model was constructed using PyroSim, discretized into 1.0 m × 1.0 m × 1.0 m grids, and instrumented with 500 temperature sensors and 500 smoke sensors to collect real-time environmental data, forming a dynamic grid map based on NFPA 72-2025 risk grading standards. For global planning(IACO), an equivalent length heuristic function integrating temperature and visibility factors was proposed to replace geometric distance and an adaptive pheromone evaporation factor update strategy based on the environmental change index was designed to enhance convergence and scenario adaptability. For local planning(IAPF), a backtracking direction-finding strategy with escape force was adopted to resolve the local minimum problem; a dynamic repulsion field with decreasing repulsion at the target point addressed the target inaccessibility issue; and a Gaussian-distributed dynamic virtual fire source repulsion field was established to accommodate fire spread. Four dynamic fire scenarios with different fire spread ranges(20 m × 30 m/30 m × 50 m) and obstacle distributions were set up, and IACO-IAPF was compared with traditional algorithms(ACO, GA, PSO, and ACO-APF) in terms of path length, running time, path safety, and path effectiveness. [Results] Experimental results demonstrated the superior performance of IACO-IAPF over the traditional algorithms. In global planning, IACO generated the shortest path(65.18 m) with the highest safety score(0.94) and only a marginally longer running time(20.71 s) compared with ACO, whereas GA failed to converge. In full path planning across four scenarios, IACO-IAPF reduced path length by 8.2%–15.7% and running time by 11.3%–29.3% compared with ACO-APF. Notably, IACO-IAPF maintained path safety consistently above 0.90 in all scenarios, markedly higher than that of ACO-APF in complex scenarios. The paths planned by IACO-IAPF were smoother with fewer turning points, responded to fire evolution in real time, and achieved targeted avoidance of high-risk areas, with optimal path effectiveness in all tests. [Conclusions] The proposed IACO-IAPF algorithm effectively addresses the limitations of traditional path planning algorithms under dynamic tunnel fire conditions. The improved heuristic function and adaptive pheromone evaporation factor in IACO enhance global planning ability, enabling paths that are more responsive to dynamic fire environments while avoiding local optima. The optimized strategies in IAPF successfully resolve the local minimum and target inaccessibility problems inherent in the traditional artificial potential field method, enabling precise real-time avoidance of fire sources and obstacles. The PyroSim simulation results confirm that IACO-IAPF delivers strong performance in path optimization, operational efficiency, and safety assurance, with strong practicality and scenario adaptability for long traffic tunnel fire rescue operations.
Road performance of basalt fiber-reinforced asphalt mixture by experimental tests and discrete element simulation
WU Kun;HE Wanping;XIONG Liwei;MA Jie;CHEN Yu;HUANG Xin;LI Changhui;QI Lin;SUN Bowei;Erwin Oh;[Objective] Asphalt mixture is a widely used pavement material in road and airport engineering. The incorporation of fibers has been demonstrated to substantially enhance the performance of asphalt mixtures in road applications. Nevertheless, research on the uniaxial compressive performance of fiber-reinforced asphalt mixtures and the microscopic enhancement mechanism of fibers remains limited. [Methods] The basalt fiber-reinforced asphalt mixture is selected as the research object. Material tests on basalt fiber-reinforced asphalt mixtures, including the Marshall test and uniaxial compressive tests, are conducted to study the effect of basalt fiber content on the physical and mechanical properties of asphalt mixtures, such as bulk density, stability, flow value, and compressive strength. Based on discrete element simulation, a numerical model for basalt fiber-reinforced asphalt mixture is established, in which the fibers are modeled as clumps, aggregates with diameters larger than 2.36 mm are represented as balls, and the asphalt mortar, composed of aggregates smaller than 2.36 mm and base asphalt, is simulated using a contact model. The discrete element model is verified with the test results, and the contact parameters are calibrated. An investigation is conducted into the process of crack formation, development, and failure of the asphalt mixture under uniaxial compression. [Results] The results show that(1) with an increase in fiber content, there is a gradual decrease in bulk density and voids filled with asphalt, while the void content of the asphalt mixture, optimum asphalt binder content, and mineral aggregate voidage of the asphalt mixture increase.(2) The incorporation of basalt fibers significantly enhances the mechanical properties of asphalt mixtures, including Marshall stability, flow value, and compressive strength. In comparison with asphalt mixtures devoid of fiber, the uniaxial compressive strength increased by 13.2%, 43.3%, and 8.3% at fiber content levels of 0.2%, 0.3%, and 0.4% by weight, respectively.(3) Fiber content exerts a substantial influence on the axial compressive performance of asphalt mixtures. The maximum compressive strength value is observed at 0.3% fiber content for the asphalt mixtures examined in this study. When the basalt fiber content is below 0.6%, the compressive strength initially increases and then decreases with rising fiber content; however, it remains higher than that of mixtures devoid of fiber. In contrast, when the fiber content exceeds 0.6%, the compressive strength decreases below that of mixtures devoid of fibers.(4) The discrete element model of basalt fiber-reinforced asphalt mixtures accurately simulates the uniaxial compression process. [Conclusions] Microstructural analysis reveals that increasing basalt fiber content significantly reduces edge fragmentation and crack propagation in asphalt mixture specimens, while the number of interparticle contacts increases markedly. Analysis indicates that the discrete element model of asphalt mixtures developed using discrete element modeling software can accurately simulate the internal microscopic mechanisms during uniaxial compression, revealing the influence of basalt fibers on contact evolution and crack propagation within the mixture. The addition of an appropriate amount of basalt fibers enhances the physical and mechanical properties of asphalt mixtures. However, excessive fiber content may lead to fiber aggregation phenomena, resulting in performance degradation. Therefore, for practical engineering applications, the optimal fiber dosage should be determined through experimental testing and theoretical analysis based on specific conditions. The findings of this study have significant reference value for the design of fiber–asphalt mixture pavements and airport runways.
Tunnel monitoring data prediction for mixed periods
YANG Liu;LI Minghui;WANG Guo;WEN Yumin;LIU Heng;[Objective] A significant number of tunnels are equipped with health monitoring systems that generate multi-source monitoring series. These series exhibit pronounced mixed periodicity, containing both long-term and short-term patterns. In such circumstances, conventional methodologies, such as autoregressive models and Gaussian processes, may prove ineffective in capturing the intricate temporal dependencies. This paper presents an enhancement to the LSTNet model and introduces BiLSTNet-MHA, a data prediction model designed for the extraction of mixed-period features in tunnel monitoring data. The model facilitates a more comprehensive extraction of mixed-period features and reduces computational complexity. [Methods] Bi LSTNet-MHA is an extension of the LSTNet architecture. Convolutional layers with a one-dimensional CNN can capture short-term local dependencies in multivariate series. A bidirectional long short-term memory network, in conjunction with an LSTM-skip layer, extracts bidirectional long-term dependencies and periodic patterns in the series. A multi-head attention mechanism is introduced as a self-attention layer to capture non-periodic temporal patterns. A conventional autoregressive model constitutes the linear component, compensating for the limitations of neural networks in processing scale variations. Singular value decomposition is employed to perform low-rank approximation and dimensionality reduction for spatially correlated multivariate series. The training process utilizes quantile loss at 0.25, 0.5, and 0.75. The model is applied to spatially correlated structural-response monitoring series and factor-correlated environmental load series from a domestic tunnel. The structural responses include crown settlement, surrounding rock pressure, and concrete stress. The environmental loads include temperature, humidity, and wind speed. The monitoring period extends from January 1, 2020, to December 31, 2020. The records are resampled to 30-minute intervals, and the dataset is organized by quarter for analysis, with 80% of the data allocated for training and 20% for testing. The implementation utilizes PyTorch in conjunction with Python 3.7.11. The mean absolute error, root mean squared error, and the coefficient of determination are used to evaluate the forecasting performance of each model. Ablation variants omit recurrent skipping, multi-head attention, the autoregressive layer, or singular value decomposition. [Results] The experimental results indicate the following: 1) BiLSTNet-MHA demonstrates enhanced tracking of crown settlement sensor WY-03-01 in quarters exhibiting pronounced seasonal mixed periodicity, while the surrounding rock pressure sensor SL-S1-01 exhibits greater variability in the second quarter of 2020 due to its distinct trend compared to other quarters; 2) Examining the fourth-quarter data, BiLSTNet-MHA, based on the fourth-quarter 2020 metrics averaged across sensors of the same structural-response type, achieves the smallest errors among the compared models. In comparison to LSTNet, the mean absolute error and root mean squared error for surrounding rock pressure decrease by 43.15% and 48.79%, respectively, and the R2 score is also higher than that of LSTNet; 3) Removing the recurrent-skip layer increases MAE from 3.406 to 5.048, and the removal of the self-attention layer increases MAE to 4.471, indicating that the removal of recurrent skipping, multi-head attention, or the autoregressive layer degrades forecasting performance; 4) The removal of singular value decomposition slightly improves the average ablation accuracy but greatly increases training time. [Conclusions] BiLSTNet-MHA is capable of more comprehensively capturing longand short-term periodic patterns as well as non-periodic variations in tunnel monitoring series, while reducing computational complexity and improving sensitivity to outliers. This makes it a valuable tool for real-world, practical tunnel health monitoring.
Experimental study on the dynamic performance of tunnel damping measures considering initial support
QI Bing;XU Haibin;JIANG Chenchen;ZHANG Guangkui;WEI Hong;MA Zhigang;[Objective] Tunnels in high-intensity seismic regions are susceptible to severe damage from earthquakes, such as lining cracking, spalling, invert uplift, and progressive plastic deformation, which jeopardize structural safety and serviceability. Although seismic isolation layers have been widely applied to mitigate tunnel seismic responses, most studies have primarily focused on the interaction between the secondary lining and isolation layer, often overlooking the role of primary support, an essential component in tunnel construction. This study aims to elucidate the dynamic response characteristics and damage evolution of tunnel linings when seismic mitigation measures are implemented under realistic primary support conditions. By integrating primary support into the mitigation system, the study experimentally evaluates the effectiveness of a composite configuration comprising the secondary lining, seismic isolation layer, primary support, and surrounding rock, providing guidance for resilience-oriented tunnel seismic design. [Methods] The Jiedexiu No. 2 Tunnel on the Lhasa-Nyingchi Railway was selected as a representative case for a series of shaking-table model tests. A gravity-distorted similarity model was developed based on the Buckingham π theorem, featuring a geometric similarity ratio of 1:40, alongside appropriate scaling of elastic modulus, density, displacement, and acceleration. The surrounding rock and overburden were simulated using Grade V phyllite and gravelly-breccia soils, respectively. The secondary lining was modeled with gypsum to simulate C30 concrete, whereas sponge rubber material was used as the seismic isolation layer. Basalt fiber-reinforced polymer anchors were employed to simulate rock bolts in the primary support. Horizontal excitation was applied using the El Centro earthquake wave with peak ground accelerations of 0.1 g, 0.2 g, 0.3 g, and 0.4 g. Acceleration sensors and strain gauges were arranged symmetrically to compare a conventional section with a mitigated section that incorporated the isolation layer and primary support. Dynamic responses were analyzed in the time and frequency domains, which included acceleration time histories, Fourier spectra, and acceleration response spectra. To quantify cumulative damage, a plastic deformation index(PDI), defined as the ratio of residual strain to peak dynamic strain, was introduced to classify damage evolution into elastic, elasto-plastic, and plastic stages. [Results] Results show that the seismic isolation layer significantly reduces the peak amplitudes of acceleration response spectra and Fourier spectra without altering their overall shapes. Under low-intensity excitation(0.1 g), the response spectra exhibit multipeak characteristics with a predominant period of approximately 0.06 s. As ground-motion intensity increases, the spectra transition to a single-peak pattern, accompanied by a lengthening of the predominant period to approximately 0.08 s, indicating enhanced system nonlinearity and amplification of low-frequency components. Dynamic strain measurements reveal that the mitigated section consistently experiences lower strain peaks and slower strain accumulation, particularly at the crown and invert, whereas the haunch exhibits the weakest mitigation effect due to strong boundary constraints. PDI analysis indicates that the conventional section enters a plastic-dominated state when excitation exceeds 0.3 g, whereas the mitigated section remains primarily in the elasto-plastic stage with substantially lower PDI values. Post-test observations confirm that damage in the mitigated section is markedly reduced compared to the conventional section. [Conclusions] Experimental results demonstrate that a seismic mitigation configuration that explicitly considers primary support and incorporates a seismic isolation layer can effectively improve tunnel seismic performance under high-intensity earthquake loading. This composite system reduces spectral amplitudes and plastic deformation demand while preserving the fundamental spectral characteristics of the lining response. The mitigation effect is most pronounced at the invert and crown, indicating that the haunch remains a critical area requiring additional design attention. The proposed approach provides a practical experimental basis for energy-dissipation-oriented seismic design and retrofitting of tunnels in earthquake-prone regions.
Exploration of intelligent full-chain reconstruction in university analytical testing: A case study of environmental solid waste
YE Wen;LIN Kun;CHEN Kaixuan;FENG Tao;GUO Lingling;LI Jie;[Objective] University analytical testing platforms are an important component of the national science and technology infrastructure. With the advancement of organized scientific research and the implementation of the national strategy of scientific and technological self-reliance， research demands have shifted from single， routine testing to complex analyses involving multiple technologies and interdisciplinary integration. A complete characterization task in materials， environmental， biological， or chemical sciences often requires simultaneous acquisition of multi-dimensional data including elemental composition， phase structure， molecular information， and morphological features—no single instrument can independently fulfill such requirements. However， the traditional "demand-plan-execution-report" process of most university testing platforms faces four major challenges: difficulty in demand communication， slow plan formulation， blind execution， and scattered report data. Its service efficiency has been unable to meet the higher requirements of the country for strengthening organized research and serving strategic demands. This study aims to address these challenges by proposing an intelligent full-chain reconfiguration path for university analytical testing， with the goal of achieving simultaneous enhancement of process operation efficiency and research support effectiveness. [Methods] This study proposes a "four-dimensional integration and dual-effect promotion" approach， supported by the DeepSeek large language model as the core technological engine. The four dimensions are: guided demand parsing， holistic plan formulation， visualized process tracking， and in-depth report generation. An integrated intelligent platform is constructed that combines functions such as testing application， plan matching， progress tracking， and report generation. The demand parsing module converts natural language descriptions into structured testing instructions through intelligent guidance， transforming multi-round manual communication into human-machine collaborative interaction. The plan formulation module identifies the core scientific question common to multiple testing tasks， performs temporal dependency judgment to warn of sample state damage from pretreatment steps， recommends parallel sample configurations， and conducts equipment compatibility verification. The process tracking module decomposes the workflow into standardized nodes， enables real-time progress monitoring， and provides automatic notifications and anomaly warnings. The report generation module aggregates multi-source data， performs cross-instrument correlation analysis， and generates comprehensive reports containing scientific judgments and follow-up recommendations. Taking the analysis of the occurrence states of harmful elements in environmental solid waste as a case study， this paper elaborates on how the traditional manual coordination model is reconstructed into a data-driven intelligent process through this path. [Results] The intelligent service system has been officially implemented on the analytical testing platform. Practical application demonstrates that the model significantly shortens the plan formulation cycle， reduces communication costs， and improves report timeliness. The demand parsing process is completed in approximately ten minutes under the new model， compared to several days of communication under the traditional approach. The system successfully identifies temporal conflicts in pretreatment steps and recommends appropriate parallel sample configurations， preventing sample failure and reducing material waste. The comprehensive report integrates results from multiple instruments， provides cross-instrument correlation analysis and scientific interpretation， and offers specific follow-up research recommendations. Users receive not only data reports but also integrated conclusions that combine multi-technology results with scientific judgments and research suggestions. [Conclusions] The traditional university analytical testing service faces process pain points including difficult demand communication， slow plan formulation， blind execution， and scattered report data， with the core problem being over-reliance on manual coordination and empirical judgment. This study， based on the DeepSeek large language model， has constructed an intelligent testing platform with four functional modules and validated the "four-dimensional integration and dual-effect promotion" intelligent full-chain reconfiguration path. Practical data demonstrate that this path significantly improves operational efficiency while effectively promoting the leap in research support effectiveness， driving the systematic transformation of platform functions from instrument management to in-depth research support. Through deep integration and comprehensive analysis of multi-source data， the model provides strong support for forming more forward-looking and insightful scientific research conclusions. This offers a replicable practical example for university analytical testing platforms to empower the transformation of scientific research services through artificial intelligence technology. Future work will extend this approach to more complex testing scenarios， providing an actionable practical path for universities to leverage artificial intelligence in enhancing research testing efficiency and serving organized research.
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Experimental design of three-point bending tests on circular magnesium alloy tubes with five shear–span ratios
HUI Cun;CHEN Xiang;LIU Mingliang;WANG Yuanqing;LI Jiale;[Objective] Against the backdrop of research and innovation integration， magnesium alloys， with advantages such as light weight， high specific strength， excellent damping performance， and recyclability， have good applicability in lightweight building structures. However， research on their mechanical properties remains insufficient， which limits their engineering applications. [Methods] To fill this gap and promote these applications， five circular magnesium alloy tube specimens with different shear–span ratios were designed and fabricated and subjected to three-point bending tests. The failure modes， load–displacement responses， and strain distribution patterns of each specimen were systematically investigated. Combined with an analysis of the measured peak bearing capacity and theoretically calculated values， the control effect of the shear–span ratio on the mechanical behavior of magnesium alloy tubes was revealed. [Results] The results show that 1) the transformation process of the failure mode was clarified. All specimens exhibited linear elastic deformation characteristics during the initial loading stage without obvious yield platforms. 2) The influence of the shear–span ratio was quantified. The shear–span ratio considerably affects the failure mode. When the shear–span ratio is less than 5.17， the specimens mainly undergo local buckling failure; as the shear–span ratio increases to 6.21–8.28， the failure mode transforms into typical mid-span overall bending failure. Meanwhile， as the shear–span ratio increases， the peak bearing capacity of the specimens decreases nonlinearly by up to 57.1%， while the mid-span displacement considerably increases by up to 69.9%. 3) The strain distribution and plastic deformation laws were revealed. During the bending process， the strains in the top compression zone and bottom tension zone at the mid-span are strictly symmetrical (with similar values but opposite signs)， and the strain in the former zone is larger， verifying the mechanical attribute of a greater tendency for local buckling; moreover， it was clarified that when the load exceeds 0.6 times the peak load， the strain growth rate sharply increases， which is a key feature of entering the plastic deformation stage. 4) The applicability of the calculation method was verified. A calculation method was proposed for the ultimate bearing capacity of circular magnesium alloy tubes based on existing metal structure design codes. For specimens with a shear–span ratio greater than 6.21， the measured values closely match the calculated values， with all errors less than 7.0%， and the error of specimen MG3-1800 is only 0.2%， providing a reliable basis for engineering design. [Conclusions] 1) The shear–span ratio is the core parameter for regulating the failure mode of circular magnesium alloy tubes under bending. Different shear–span ratios correspond to various failure modes， providing a basis for component selection and design. 2) As the shear–span ratio increases， the peak load shows a nonlinear attenuation trend， the mid-span displacement increases， and the ductility improves. For specimens with a low shear–span ratio， the load–displacement curve drops sharply after reaching the peak load， while for those with a high shear–span ratio， the curve declines slowly after reaching the peak load. This finding provides a reference for ductility control in disaster-resistant design. 3) The bending specimens have a symmetrical strain distribution， and local buckling tends to occur in the top compression zone. When the load exceeds 0.6 times the peak load， plastic deformation considerably increases. The calculation method based on existing standards applies to specimens with a high shear–span ratio and can be used in engineering design. 4) This application enables students to integrate the mechanical theories they have learned， understand the relationship between experimental design and loading mechanisms， master the evolution law of the force–displacement curve during the bending process， identify the failure characteristics and bearing capacity variation trends under different shear–span ratios， and thereby establish the correlation mechanism between component response and material constitutive behavior， providing a reliable basis for subsequent numerical simulation and theoretical analysis and effectively enhancing students’ practical ability and innovative thinking in the application of new metal structural materials.
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Experimental teaching design for the motion control system of an industrial robot end-effector
GUO Wanjin;YE Min;ZHU Wuwei;DING Kai;HUI Jizhuang;WANG Zhaoman;CHEN Ziguan;[Objective] In industrial robots， the end-effector， the tool that directly interacts with the workpiece， is crucial for determining the quality of manufacturing tasks such as grinding， polishing， and deburring. However， traditional industrial robot systems mostly focus on the motion control of the robot body， even though the control performance of the end-effector often becomes the key bottleneck restricting processing quality. Therefore， talent in Intelligent Manufacturing Engineering programs must be cultivated to master high-precision motion control and constant force control methods for industrial robot end-effectors. To bridge this gap and considerably enhance the practical skills of students， this paper designs and develops an experimental platform and a corresponding teaching method centered on the motion control system of an industrial robot end-effector. The core objective is to enable students to systematically understand and implement motion control and constant force control techniques， with particular emphasis on force–position hybrid control in realistic grinding scenarios. [Methods] A dedicated experimental platform was developed， comprising a six-degree-of-freedom serial industrial robot， a 2R1T end-effector driven by voice coil motors， a Beckhoff industrial PC， ELMO servo drives， incremental encoders， and a six-axis force sensor. TwinCAT3 software was used to implement the control system， which comprised four functional modules: motion control， logic operation control， adaptive constant force variable admittance control， and a human–machine interface. A hierarchical experimental teaching method incorporating three progressively integrated experiments—single-axis motion control， multi-axis coordinated motion control， and constant force grinding control， the core experiment—was proposed. In the constant force experiment， students implemented force–position hybrid control and compared the performance of a PID-optimized admittance controller with that of a neural network adaptive constant force variable admittance controller based on an RBF network. Students performed the grinding task with a target contact force of 15 N， guided through the complete engineering cycle of parameter initialization， system activation， experimental execution， data acquisition， and performance evaluation. [Results] Through the single-axis motion control experiment， students mastered three positioning modes and developed precision positioning skills. The multi-axis coordinated motion control experiment enabled students to achieve smooth trajectory tracking and synchronous multi-axis movement. In the constant force grinding control experiment， students implemented force–position hybrid control and compared two control strategies. The neural network adaptive controller achieved steady-state force fluctuation within ±1.5 N and an average force error of 0.16 N， considerably outperforming the PID-optimized admittance controller， whose fluctuation range and average error were ±3.2 N and 0.31 N， respectively， under identical conditions. These results clearly illustrate the superior adaptability and disturbance rejection capability of the neural network adaptive constant force variable admittance controller. Throughout the process， students gained hands-on experience in parameter tuning， real-time data monitoring， system debugging， and quantitative performance evaluation. [Conclusions] The developed experimental platform and proposed teaching method effectively guide students from foundational motion control skills to a comprehensive understanding of force–position hybrid control. By completing the full engineering cycle of parameter setting， experimentation， data analysis， and iterative optimization， students develop practical abilities in system debugging， performance evaluation， and controller comparison. The teaching method provides a replicable and effective approach for cultivating high-quality talent in intelligent manufacturing.
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Experimental teaching design for the preparation of warm-mix asphalt mixtures rejuvenated with waste oil and the evaluation of their pavement performance
SUN Jishu;CHENG Xiangyu;ZHANG Caili;LI Xia;GONG Fangyuan;[Objective] To enrich the experimental teaching and practical components of the Road Engineering Materials course and to address the industry’s green development needs for the resource utilization of reclaimed asphalt pavement (RAP) and the coordinated disposal of waste cooking oil and waste engine oil in asphalt pavement maintenance， this study developed a comprehensive experimental teaching case on the preparation and pavement performance analysis of warm-mix waste-oil-rejuvenated asphalt mixtures (WMAs). [Methods] A base oil was prepared by blending waste engine oil and waste cooking oil at a ratio of 5:6， together with dioctyl adipate as a plasticizer， C9 petroleum resin as a tackifying resin， and a DWMA-1 warm-mix additive to produce a warm-mix waste-oil rejuvenator. Test results showed that all performance indicators met the technical requirements for rejuvenators. Aged asphalt was prepared through laboratory accelerated aging， and the optimum rejuvenator dosage was determined to be 12% based on penetration， ductility， softening point， and other indices， thereby producing warm-mix waste-oil-rejuvenated asphalt. With AC-16C used as the target gradation， old aggregates were extracted from RAP by the ignition method， and new aggregates were added to compensate for the finer characteristics of RAP aggregates. WMA with RAP contents of 30%， 50%， and 70% were designed， and hot-mix recycled asphalt mixtures (HMA) with the same RAP contents were used as control groups. The Marshall mix design method was applied to determine the optimum asphalt content under different RAP dosages. Next， high-temperature stability (Marshall stability test and rutting test)， low-temperature cracking resistance (low-temperature bending test)， water stability (freeze–thaw splitting test and immersion Marshall test)， and fatigue performance (four-point bending fatigue test) were systematically evaluated. [Results] The results showed that the dynamic stability of the WMA increased by up to 6.2% compared with HMA at the same RAP content; the maximum flexural tensile strain increased by up to 57.3%; the freeze–thaw splitting strength ratio and residual stability were considerably improved; and the fatigue life increased by up to 106.5%. Overall， the WMA had better pavement performance than the HMA. As RAP content increased， high-temperature performance improved gradually， whereas low-temperature performance， water stability， and fatigue performance declined. Considering all performance indicators comprehensively， the optimum RAP content was determined to be 30%. Simultaneously， course practice was conducted based on a reconstruction project of old branch roads in Xiqing District， Tianjin， establishing an integrated teaching model combining theoretical instruction， laboratory operation， and field construction. After construction， pavement smoothness， compaction， and other indicators met specification requirements. Practical results showed that more than 95% of students significantly improved their practical and collaborative abilities， and more than 88% independently completed experimental testing related to WMA. [Conclusions] This study achieved the coordinated resource utilization of waste oil and RAP， consistent with the green development concept under the “dual-carbon” goals. Meanwhile， it transformed scientific research outcomes into experimental teaching resources， providing theoretical support， technical reference， and an innovative teaching model for the reform of the Road Engineering Materials course and the promotion of green recycling technology for asphalt pavements.
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Design of simulation experiments on interfacial fatigue damage evolution in multiphase composite material
BAI Tao;ZHOU Xiaolong;LIU Zhangjun;[Objective] A virtual simulation experiment teaching scheme centered on interface fatigue damage was designed for senior undergraduates in civil engineering. This scheme addresses the difficulty in understanding the fatigue damage evolution law of multiphase interfaces in grouted asphalt concrete (GAC) under cyclic loading and the inability of traditional experiments to observe the meso-damage process. It transforms cutting-edge research results into operable inquiry-based teaching content to cultivate students’ interdisciplinary thinking and innovation ability. [Methods] The experimental teaching follows a progressive logic of “theoretical foundation → parameter calibration → modeling and solution → law analysis → innovation and expansion.” It comprises five specific steps. First， the theoretical foundation is established by systematically teaching the basic theory of the bilinear cohesive zone model (CZM)， the fatigue damage evolution criteria under cyclic loading， and the development principles of the USDFLD user subroutine. This foundation provides students with the necessary mathematical and programming knowledge. Second， for parameter calibration， students are guided to acquire the material’s meso-structure through the GAC original section image collection. Key CZM parameters (strength， stiffness， and fracture energy) are obtained via interface pull-out tests. The generalized Maxwell model is used to characterize asphalt viscoelasticity， and the Prony series is fitted to obtain the relaxation parameters needed for ABAQUS. The CZM interface simulation parameters are finally determined using an inversion method. Third， in the modeling and solution phase， students build a meso-scale representative volume element (RVE) model of the multiphase material (including asphalt， aggregate， and geopolymer) in ABAQUS. Cohesive elements are embedded to represent the interfaces. The core task is to develop and integrate a USDFLD user material subroutine to embed the fatigue damage model numerically. After the subroutine is verified， cyclic loading is applied to the model to calculate the solution. Fourth， for law analysis， students extract the stress–strain responses and cumulative damage values of the cohesive elements from two interface types (asphalt–geopolymer and asphalt–aggregate) from the simulation results. Through data curve analysis， they reveal the three-stage law of damage accumulation under cyclic loading and compare the impact of different interfaces on the overall fatigue life of the material. Fifth， during the innovation and expansion phase， students are guided to independently design a meso-scale parameter sensitivity analysis scheme. They change key parameters like interface properties or aggregate/grout attributes to explore the influence mechanism of these parameters in the macroscale fatigue damage evolution process and final failure life of the composite material. [Results] On the basis of the inquiry practice in the virtual simulation experiment， students drew clear conclusions. The greatest improvement in the fatigue resistance of GAC is obtained by increasing the interface ITZ fracture energy， followed by the interface ITZ bond strength， while the geopolymer flexural strength has a relatively minor impact. Students also gained a deep understanding that the interface， as the transition zone between material phases， directly determines the macroscopic mechanical properties. Teaching practice data show that 94.3% of students independently completed the entire process of simulation modeling and subroutine integration， and 48.1% further proposed innovative suggestions such as interface modification and parameter optimization. [Conclusions] This experiment effectively transforms cutting-edge research results into inquiry-based teaching content. It considerably enhances students’ innovative competence in applying multidisciplinary knowledge to solve complex engineering problems. It provides a practical paradigm for conducting cutting-edge， inquiry-based experimental teaching in civil engineering materials courses.
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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.
[Downloads: 55,909 ] [Citations: 3,450 ] [Reads: 1419 ] HTML PDF Cite this article
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: 167 ] HTML PDF Cite this article
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.
[Downloads: 4,982 ] [Citations: 319 ] [Reads: 138 ] HTML PDF Cite this article
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.
[Downloads: 3,883 ] [Citations: 273 ] [Reads: 194 ] HTML PDF Cite this article
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: 175 ] 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: 1419 ] 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.
[Downloads: 24,314 ] [Citations: 11 ] [Reads: 1436 ] HTML PDF Cite this article
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: 167 ] 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: 1440 ] HTML PDF Cite this article