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[Objective] This study aims to address critical issues in current safety training systems for university laboratories, including incomplete coverage of trainees, lack of hierarchical management, insufficient interdepartmental collaboration, and ineffective evaluation and follow-up mechanisms. Recognizing the vital role of comprehensive safety education in preventing laboratory accidents and promoting a proactive safety culture, the study proposes an innovative safety training framework grounded in the integration of the principles of product lifecycle management(PLM) and SMART goal-setting criteria. The study primarily aims to establish a systematic, dynamic, and effective safety training system that enhances safety awareness, emergency response capabilities, and prevention skills among faculty and students undertaking laboratory activities. [Methods] Methodologically, the study first deconstructs the core concepts of the PLM and SMART frameworks, emphasizing their applicability to safety training lifecycle management. Based on extensive empirical investigations and current deficiencies identified through field surveys, the study constructs a six-phase implementation strategy that comprises needs analysis, system design, deployment, monitoring and evaluation, ongoing maintenance, and reflective summarization. Each phase delineates specific tasks, targeted measures, and operational principles that aim to ensure the robustness and adaptability of the system. Needs analysis entails precise identification of target audiences, including different personnel categories and laboratory types, along with detailed segmentation based on risk and developmental stage. The design phase focuses on developing tailored curricula that incorporate diverse training modalities such as online modules, hands-on simulations, case-based discussions, and safety competitions to enhance engagement and efficacy. [Results] During implementation, the framework emphasizes cross-departmental coordination, resource sharing, and establishing standardized protocols to ensure consistency and scalability. The monitoring and evaluation phase integrates SMART principles to clearly define performance indicators; collect feedback through tests, questionnaires, and observational assessments; and establish correction mechanisms for continued improvement. Post-training maintenance includes regular updates on safety knowledge and reinforcement activities, thus fostering a safety-oriented culture. The summarization stage involves systematic documentation, success case analysis, and refining training strategies based on accumulated insights. [Conclusions] To validate the effectiveness of the developed framework, pilot programs were conducted across five faculties—namely, chemical engineering, mechanical engineering, medical sciences, energy technology, and physical education—over a one-year period. The results demonstrated significant improvements: passing rates in examinations increased from an average of 45% at pre-implementation to more than 95% after one year, indicating enhanced safety knowledge and practical skills. Satisfaction surveys highlighted more than 90% approval from participants regarding the relevance, clarity, and applicability of training content and methods. Furthermore, organized emergency drills obtained scores between 85 and 93 points across departments, reflecting substantial enhancement in emergency response abilities. These metrics collectively validate that the proposed safety training system based on PLM and SMART effectively improves safety awareness, behavioral compliance, and accident prevention capabilities among university laboratory personnel. [Conclusions] This study presents a comprehensive, structured approach to developing and implementing a safety training system for university laboratories; this approach overcomes existing limitations through systematic phases, innovative management principles, and practical validation. The findings suggest that integrating product lifecycle concepts with goal-oriented management significantly enhances the systematicity, effectiveness, and sustainability of safety education, thus providing valuable guidance for universities seeking to strengthen their laboratory safety management frameworks.
[Objective] Heavy metal(HM) pollution has posed an increasingly serious threat to the environment and human health. Therefore, accurately assessing the bioavailability of HMs is crucial for their environmental risk assessment(ERA). Traditional detection methods employed for ERA, such as chemical extraction, cannot reflect the actual interactions between HMs and organisms. However, plant-and animal-based biological detection methods suffer from several limitations, including time-consuming procedures and complex operational requirements. Therefore, developing a rapid, efficient, and operationally simple ERA technique for HMs is of great significance. This laboratory course aimed to utilize the whole-cell bioreporter “zntA” for designing and implementing a novel, experimental, teaching method for the quantitative detection of lead(Pb) bioavailability in water and soil, providing a case for innovative environmental science education. [Methods] This experiment employed a Type I whole-cell bioreporter, zntA, to detect Pb bioavailability through a specific response mechanism. The experimental design included strain isolation and cultivation, HM exposure assays, and bioluminescence detection. The bacterial strain was cultured in a lysogeny broth medium, harvested via centrifugation, and subsequently resuspended in an optimized minimal medium to obtain the bacterial suspension. A standard curve was plotted using standard Pb solutions with a 0–0.4 mg·L~(-1) gradient. Water samples were filtered through a 0.45 μm membrane, while soil samples were prepared as slurries at 0.78–25 mg·mL~(-1). These samples were then mixed with the bacterial suspension, and the bioluminescence kinetics were recorded for 7 h with a microplate reader. To address the issue of optical signal interference caused by soil particles, a light-blocking calibration model was established to compensate for signal attenuation induced by soil particulates, thereby enhancing the detection accuracy of the bioreporter for soils. [Results] Per the results, zntA exhibited a dose-dependent response to Pb, with bioluminescence peaking at 140 min. The limit of detection was 4 μg·L~(-1), much lower than the drinking water guideline of 10 μg·L~(-1) set by the WHO. An analysis of the samples from natural water bodies revealed Pb bioavailability of 0.21(W1) and 0.18 mg·L~(-1)(W2). For soil samples, the optical interference caused by soil particles was corrected by measuring light transmittance and optical density. A mathematical model correlating slurry concentration with optical signal obstruction was established, offering a calibration method for complex matrices. After calibration, the bioavailable Pb concentration in the soil was detected to be 0.69 mg·kg~(-1). These results show that excessive soil slurry concentrations caused signal suppression due to toxic effects. [Conclusions] This experiment successfully applied whole-cell bioreporter technology to environmental biology teaching, demonstrating its advantages of speed and sensitivity over conventional methods. By optimizing the experimental procedures and introducing a light-blocking calibration model, interference from soil matrices was effectively addressed, providing a reliable solution for detecting HM bioavailability. The experimental design not only enhanced the practical and research skills of students but also served as a model for disseminating environmental monitoring technology-related.
[Objective] The homogenization of civil engineering experimental courses in agricultural and forestry universities impedes discipline-specific development. This study addresses this gap by constructing an innovative teaching system centered on planting concrete, an eco-functional material integrating agricultural and civil engineering principles. [Methods] This research established a tripartite pedagogical framework: project selection targeting agricultural applications(e.g., slope restoration and pollution control), scheme design emphasizing material–plant synergy, and analytical methods quantifying ecological–mechanical performance. Methodologically, low-alkali sulphoaluminate cement(LAC) was replaced with Portland cement to regulate pore pH(9.5–10.5 vs. 12.5–13.5) while enhancing early strength(54.5 MPa at 3 d, a +38% improvement). Recycled brick aggregate(RBA, 16–20 mm) with high porosity(23.6%) and water absorption(15.8% vs. natural aggregate's 2.65%) was systematically compared with natural gravel. Using skeleton density theory, an absolute volume method(Equations 1–7) optimized the mix parameters: target porosity(20%–30%), water–cement ratio(W/C: 0.30–0.36), and RBA substitution rate(0%–100%). Critical tests included compressive strength(ISO 679), porosity via hydrostatic weighing(error ≤2.3%), and pore pH measurement through solid–liquid extraction using a PHS-25 pH meter. [Results] Results revealed coupled mechanical–ecological behaviors: compressive strength peaked at W/C = 0.34(6.05 MPa) but declined by 2.64% at W/C = 0.36 due to slurry segregation. RBA substitution of >40% reduced strength by 17.4% per 20% increment, owing to its high crushing value(23.25% vs. natural aggregate's 5.7%). Porosity increased by 4.6% per 0.02 W/C rise and by 4.1% for RBA >40%, directly influencing plant root development. Pore p H decreased with higher W/C(9.6→9.1) but increased with RBA substitution(up to 3.9%) through enhanced ion migration, enabling customized plant adaptability. Educational outcomes demonstrated significant interdisciplinary competency. Students established quantitative models linking porosity(25%–30%) to root growth, undergraduates published four SCI-indexed papers and filed two patents, and 87.3% of learners showed enhanced problem-solving skills for agricultural–civil engineering challenges. [Conclusions] The course integrated ideological education by correlating material choices(e.g., RBA recycling) with national strategies like “Loess Plateau soil conservation,” resulting in 92% student endorsement of strengthened commitment to rural development. This system's three-layer architecture—foundation(conventional tests enhanced by LAC/RBA), specialization(agriculture-oriented porosity/pH modules), and extension(real-world cases like “slope restoration using RBA”)—effectively cultivates agrarian-minded engineers. Future work aims to develop virtual simulations for parameter optimization and standardize curricula across agricultural universities.
[Objective] With the rapid advancement of intelligent sensing technology, mechanoluminescence(ML) materials—which emit light under mechanical stress—have garnered significant interest in stress sensing and biomechanical applications. Among them, ZnS:Cu stands out given its high luminescence efficiency, superior force–light conversion properties, and excellent reusability, making it highly suitable for biomedical sensing. However, the integration of ML materials into engineering education remains underexplored. To bridge this gap, this study designs an interdisciplinary and open-ended teaching experiment introducing ML materials into experimental education. By incorporating elements of material science, biomechanics, optical sensing, and computational analysis, this experiment aims to enhance students' interdisciplinary problem-solving abilities and hands-on engineering skills, aligning with the evolving demands of modern engineering education. [Methods] The experiment follows a structured framework simulating real-world research and development processes and integrating multiple aspects of material science, biomechanics, and computational analysis. It first characterizes commercial ZnS:Cu materials, where students conduct optical and structural analyses to fundamentally understand material properties. This is followed by sensor fabrication, where a composite thin-film preparation method is employed to optimize sensor composition(with a ZnS:Cu to PDMS base to PDMS curing agent ratio of 0.6:1:0.1), ensuring an optimal balance between force–light conversion efficiency and mechanical flexibility. After fabrication, students develop a Python-based image processing algorithm to reconstruct spatiotemporal ML signal maps. This enables the quantitative visualization of force distribution in dental occlusion and dynamic knee joint stress responses. Throughout the experiment, a research-driven, problem-oriented, and innovation-focused teaching model is implemented, engaging students in literature review, experimental design, data analysis, and system integration. This approach simulates real-world engineering workflows, fostering interdisciplinary collaboration and critical thinking. [Results] Through this experiment, students acquire hands-on experience in ML sensor fabrication, optical signal acquisition, and computational analysis. Experimental results confirm that the optimized ZnS:Cu/PDMS composite exhibits significant ML emission, with the highest force–light conversion efficiency achieved at a ZnS:Cu doping ratio of 0.6:1.0:0.1. Using high-resolution imaging and Python-based data processing, students successfully visualize stress distribution in biomechanical applications. Compared with conventional methods, such as occlusion paper and wax, the ML sensor demonstrates superior sensitivity, repeatability, and real-time force mapping capabilities, highlighting its potential for biomedical sensing. Furthermore, student feedback indicates notable improvements in interdisciplinary problem-solving skills, experimental proficiency, and teamwork, underscoring the pedagogical value of this teaching experiment. [Conclusions] The comprehensive teaching experiment introduced in this study establishes an effective educational framework integrating cutting-edge material science with digital signal processing in engineering curricula. By combining theoretical instruction with practical applications, it enhances students' experimental research capabilities, interdisciplinary collaboration skills, and innovation-driven thinking. This approach bridges the gap between fundamental scientific principles and real-world engineering applications, equipping students with the necessary competencies to address contemporary engineering challenges. Future iterations of this experiment will incorporate artificial intelligence and data analytics to further expand ML-based sensing applications and continuously refine teaching methodologies to cultivate the next generation of engineers.
[Objective] To enhance the cutting-edge nature of experimental teaching in civil engineering materials and its integration with engineering practice, this study incorporates the mechanical property testing of ultra-high performance concrete(UHPC) under high-temperature extreme working conditions into a teaching system. A multidimensional teaching module is developed, integrating conventional tests with research on high-temperature mechanical properties. This approach promotes the transformation of experimental teaching from “phenomenon observation” to “mechanism exploration,” helping students cope with challenges in complex engineering environments and addressing the development needs of new engineering disciplines. [Methods] This paper combines the standard temperature-rise fire test with traditional concrete mechanics experiments to comparatively analyze differences in the compressive performance of UHPC cubes following high-temperature exposure. According to the temperature threshold for building fires specified in the ISO-834 standard, three typical exposure temperatures—200 ℃, 400 ℃, and 600 ℃—were selected. Each specimen was held at the target temperature for a constant duration of 60 min. Before compressive testing, physical phenomena in the UHPC specimens after high-temperature exposure were observed, and the mass loss rate was analyzed. The UHPC cube compression test utilized 100-mm× 100-mm×100-mm cube specimens. During testing, the load was applied continuously and uniformly at a rate of 1.4 MPa/s. This research achieved two objectives:(1) the introduction of new instruments and technologies to establish correlations and understanding between the conventional properties of civil engineering materials and their performance in extreme environments;(2) the explanation of the experimental results through a multiscale damage mechanism. [Results] The experimental results show the following. 1) At 400 ℃, the UHPC color deepened to brownish gray. At this point, polypropylene fibers completely melted and decomposed, leaving distinct evaporation traces. 2) At exposure temperatures up to 200 ℃, the mass loss rate of the UHPC specimens was relatively low. However, when the temperature exceeded 400 ℃, the specimen mass loss increased significantly. 3) Following exposure to 200 ℃, the axial compressive failure mode of the UHPC specimens resembled that observed at room temperature. The primary manifestation was the formation of several fine, longitudinal cracks propagating along the specimen sides, connecting the upper and lower surfaces. At this stage, the cracks were relatively fine and few. 4) At an exposure temperature of 200 ℃, the compressive strength of the UHPC cube increased by 2.30% compared with that at room temperature. At 400 ℃, the strength increased by 6.34% compared with that at room temperature. 5) Although the cubic compressive strength of the specimens exposed to 600 ℃ decreased compared with those exposed to 400 ℃, it remained slightly higher than the strength at room temperature. [Conclusions] The coupled experimental design, simulating fire effects and testing compressive performance post-high-temperature exposure, systematically elucidated the intrinsic correlation mechanism between material microstructure evolution and macroscopic mechanical response. The results indicated that the nonlinear attenuation characteristics of UHPC compressive strength with increasing temperature correlated significantly with the reconstruction process of its microscopic phase composition. At 600 ℃, the compressive performance of UHPC diminished significantly compared with that at 400 ℃. Although microstructural damage occurred at 600 ℃, the combined effects of water evaporation and structural optimization enabled the material to retain compressive strength marginally higher than under normal temperature conditions. Furthermore, the high density and low waterbinder ratio of UHPC endowed it with excellent high-temperature damage resistance, contributing to the maintenance of its relatively high compressive strength. Teaching practice demonstrated that this reform, through standardized high-temperature experimental procedures, effectively promoted students' systematic understanding of material property evolution in extreme environments while enhancing their theoretical analysis capabilities and engineering problem diagnosis skills.
[Objective] To address critical energy supply challenges for power-specific sensors and pedagogical limitations exposed during power grid digitalization, this study presents a holistic simulation and experimental platform for piezoelectric vibration energy harvesting, targeting transformer vibrations. [Methods] Designed to bridge theoretical knowledge and practical engineering applications, the proposed platform comprehensively integrates four synergistic modules spanning the entire energy flow pathway.(1) The electromagnetic– mechanical vibration coupling module employs COMSOL Multiphysics for the finite element modeling of power transformer dynamics, simulating core vibrations governed by magnetostriction principles(where acceleration scales proportionally with voltage squared) and winding vibrations(where acceleration correlates with current squared), predicting dominant frequencies at 100 and 200 Hz. These results are experimentally validated using CT1010 LF piezoelectric accelerometers mounted magnetically on transformer surfaces, capturing realworld vibrations such as the measured 0.42 g acceleration amplitude at a 200-Hz frequency from a 240-kVA/220-kV SFSZ10-240000/220 transformer under operational conditions.(2) The force–electric coupling module focuses on series–parallel piezoelectric arrays utilizing Sm-doped lead magnesium niobate–lead titanate bimorph cantilevers. It incorporates detailed simulations to analyze resonance shifts when adjusting tungsten mass block positions along the cantilever axis and establishing Multisim-compatible equivalent circuit models parameterized through laser displacement testing. It shows a free-end vibration displacement U_d of 0.021 65 mm and derived sinusoidal current sources I_p = I_M sin(ωt) with clamped capacitance C_p values of 27.32 nF. Experimental validation under 1g acceleration excitation demonstrates optimized configurations, such as nine parallel arrays delivering maximum power outputs of 2.341 mW at a load resistance of 150 kΩ.(3) The energy management module simulates, designs, and implements power conditioning circuits exemplified by the synchronous electric charge extraction topology. Multisim simulations guide printed circuit board layouts fabricated using Altium Designer to achieve efficient AC–DC conversion and voltage regulation.(4) The energy storage and delivery module evaluates charging–discharging cycles for capacitors powering sensors. It documents 16 daily operational cycles for a 5-V vibration monitoring sensor, consuming 0.6 V per measurement event with systematic charging time metrics quantifying energy autonomy performance. [Results] Extensive case studies centered on the SFSZ10 transformer validate platform efficacy: electromagnetic simulations predict vibration hotspots, whereas experimental measurements confirm spatial variations in surface acceleration. Meanwhile, piezoelectric array simulations reveal that parallel configurations boost current summation and power transfer to lower resistance loads, whereas experiments identify optimal 150 kΩ matching points. SECE circuit comparisons demonstrate enhanced efficiency over basic rectifiers. Moreover, sensor charging tests verify sustainable operation under realistic duty cycles. Pedagogically, this integrated framework enables problem-based learning where students execute vibration spectral analysis using Fourier transforms, design cantilever structures by tuning mass positions to match 100–300 Hz vibration spectra, construct electrical models from laser-measured displacement and voltage data, compare array topologies through output power curves, and evaluate circuit efficiency using capacitor charging rates. These cultivate competencies in multiphysics simulation, experimental instrumentation, and energy system optimization. For research, the platform's modular architecture facilitates parametric studies on piezoelectric material selection, array scalability, circuit topologies, and storage integration—directly advancing solutions for autonomous sensor networks in digitalized power equipment. Quantitative outcomes include achieving 4.354 mW simulated power at 21 kΩ for nine parallel piezoelectric patches versus 2.341 mW experimentally at 150 kΩ, identifying material and impedance matching challenges; transformer vibration mapping showing 71.43% of measurement points exhibiting 200-Hz center frequencies; and capacitor charging sequences enabling multicycle sensor operation without external power. [Conclusions] By unifying high-fidelity simulations with hands-on experiments across the electromagnetic, mechanical, electrical, and energy domains, this platform not only revolutionizes engineering education for electrical and smart grid disciplines but also establishes an extensible research testbed for developing self-powered systems critical to grid digitalization under China's dual carbon strategy. This effectively closes the gap between academic concepts and field-deployable energy harvesting technologies for next-generation power infrastructure.
[Objective] “Pavement engineering” is a comprehensive course where experiments play a vital role. To promote the progress of China's advancement of first-class undergraduate education, the course constantly explores innovative teaching approaches. Given the above considerations, this paper expands on the original dynamic modulus experiment, selecting different loading modes according to different loading conditions, and adds data analysis and processing. On the basis of the above practice, students can more deeply understand scientific research. [Methods] This paper first introduces that dynamic modulus tests require the selection of different loading modes on the basis of varying loading conditions, primarily including three modes: uniaxial compressive(UC), indirect tensile(IDT), and four-point bending(4 PB). The specific procedures and experimental parameter selections for dynamic modulus tests under these three loading modes are then elaborated. The tests involve five temperatures:-10, 4.4, 21.1, 37.8, and 54.4 ℃. At each temperature, six loading frequencies are applied—0.1, 0.5, 1, 5, 10, and 25 Hz—to capture stress-strain data across a wide temperature and frequency range. Taking the UC dynamic modulus test as an example, the detailed process of specimen preparation, experimental execution, and data processing and analysis is explained. Finally, a practical engineering case study is presented to illustrate the entire workflow of dynamic modulus testing, from material selection to data analysis. [Results] The results indicate that AC-13 mixtures with varying void ratios exhibit consistent trends in dynamic modulus: the modulus decreases significantly with rising temperature and increases with higher loading frequencies, reflecting the temperature-and frequency-dependent(viscoelastic) characteristics of asphalt mixtures. Similarly, the phase angle of different AC-13 mixtures follows the same patterns: at low and intermediate temperatures(-10 ℃, 4.4 ℃, and 21.1℃), the phase angle decreases with increasing loading frequency. At high temperatures(37.8 ℃), the phase angle initially rises and then declines with increasing frequency, with an inflection point at 1 Hz. Overall, the phase angle increases with temperature. In IDT dynamic modulus tests, mixtures with different void ratios show analogous phase angle behaviors: At 4.4 ℃ and 21.1 ℃, the phase angle decreases with higher frequencies. At 37.8 ℃, the phase angle first increases and then decreases, with inflection points at 1 or 5 Hz. For 4 PB dynamic modulus tests, the phase angle trends of the AC-13 mixtures align with those observed in UC and IDT tests: At 4.4 ℃ and 21.1 ℃, the phase angle decreases with rising frequency. At 37.8 ℃, the phase angle peaks and then declines, with inflection points at 1 or 5 Hz. The phase angle consistently increases with temperature across all tests. [Conclusions] The methods and results presented in this study support dynamic modulus testing and analysis under diverse loading conditions, advancing the field of pavement engineering. This framework also offers valuable guidance for students in designing experiments and interpreting results, enhancing both academic and practical applications in asphalt mixture performance evaluation. Dynamic modulus is also the basic input parameter of pavement mechanics analysis and structural design. Through dynamic modulus experiments, the complex characteristics of asphalt mixture modulus can be better understood. Therefore, the research results of this paper also contribute to the development and application of pavement materials.
[Objective] The transmission of information using wireless technology has simplified people's everyday lives; however, it has resulted in electromagnetic(EM) pollution, which endangers human health and equipment operation. Furthermore, the continuous progress in radar detection technology requires lightweight microwave absorbing materials coated on the surfaces of modern weapons and military equipment, especially aircraft; the objective is to reduce the enemy defense penetration and improve the battlefield survivability of military systems. [Methods] Microwave absorbing materials(MAMs) are highly important in protecting human health and ensuring the normal operation of electronic equipment, as well as improving the EM stealth capability of weapons and military equipment. MAMs absorb or attenuate the incident EM waves by converting their EM energy into thermal energy. Therefore, the development of MAMs that can cope with complex EM environments and exhibit broad bandwidth, light weight, small thickness, and strong absorption capability has become the research focus in related fields. In recent years, carbonaceous materials, such as carbon nanotubes(CNTs), carbon nanofibers, reduced graphene oxides, hollow carbon spheres, porous carbon, and onion-like carbon, have been extensively used as dielectric lossy fillers in MAMs because of their low density, good electrical conductivity, high dielectric loss, as well as excellent thermal stability and corrosion resistance. Notably, CNTs with a one-dimensional hollow nanostructure and tunable permittivity have attracted significant attention in the field of EM functional materials. Despite the recent progress in the development of CNT-based MAMs, designing and manufacturing lightweight and highly efficient CNT-based microwave absorbers remains a challenge. The performance of a microwave absorber mainly depends on its relative complex permittivity and complex permeability. Loading a microwave absorber with dielectric fillers has been widely regarded as a simple and effective technique to control its EM properties. Herein, commercial multiwalled carbon nanotubes(MWCNTs) are directly employed as fillers to develop lightweight and highly efficient microwave absorbers by simply adjusting their filling content. [Results] Using an MWCNT filling ratio of only 3 wt% in the paraffin matrix, an excellent absorption performance can be achieved; this is attributed to the improved balance between impedance matching and EM attenuation. For example, an absorber with a 2.5-mm thickness achieves a minimum return loss(RL) of-58.6 dB at 14.3 GHz, and an absorber with a 2.6 mm thickness achieves a maximum effective absorption bandwidth of 6.8 GHz with RL <-10 dB, thus covering the entire Ku band. This absorption performance is significantly better than that achieved in many previously reported carbon-based microwave absorbers with a much higher filling ratio. The simulation results of a radar cross-section(RCS) showed that an absorber with a 3 wt% MWCNT filling ratio achieves a maximum RCS reduction of-38.94 dB·m~2 and sufficient radar stealth capability, effectively decreasing the possibility of target detection by a radar. [Conclusions] Overall, commercial MWCNTs with excellent microwave absorption and radar stealth performance could be used in the field of EM functional materials, covering a wide range of applications, from EM interference shielding for civilian electronics to radar stealth for advanced military equipment and systems.
[Objective] The shift toward higher pressures has become a consensus in the development of modern civil aircraft hydraulic systems. However, increasing hydraulic system pressures from 3000 to 5000 psi introduces potential risks, such as elevated pressure surges, faster fluid flow rates, and rapid oil temperature rise. These challenges impose new demands on thermal and pressure control in hydraulic systems, necessitating theoretical and experimental analyses for their mitigation. Moreover, aircraft hydraulic systems operate in extreme low-temperature environments(-20 ℃ to-60 ℃), challenging the performance of seals, pipelines, pumps, and valves. Therefore, investigating the low-temperature characteristics of 5 000-psi high-pressure hydraulic systems is a critical step in advancing civil aircraft hydraulic technology. The reliability of low-temperature testing directly impacts aircraft system development. Conducting preliminary studies on low-temperature characteristics during early design stages to explore underlying mechanisms can help proactively mitigate risks. Currently, research on low-temperature testing for aviation hydraulic systems in China is in a gradual development and refinement phase, with some progress already achieved. However, there remains a lack of data and experience in laboratory-based extreme cold testing for 5000-psi hydraulic systems at the civil aircraft system level. Challenges such as complex control, high costs, and low efficiency persist, and related test rigs and methodologies still require continuous improvement. [Methods] System-level–low-temperature laboratory experiments at-40 ℃ were conducted to investigate the low-temperature behavior of civil aircraft 5,000-psi high-pressure hydraulic systems. By comprehensively reviewing the testing process, design solutions, and test data, this study identified typical failure risks in both testing systems(e.g., pressure, temperature, and flow sensor drift under cryogenic conditions) and mechanical systems(e.g., oil leakage in seals and abnormal output pressure fluctuations in constant-pressure variable-displacement pumps). Theoretical analyses were conducted from the perspectives of accuracy(e.g., low-temperature environment simulation, soaking time, and system reliability), efficiency(e.g., test conditions, sequence, procedure, and simulation), and safety(e.g., risks from increased oil viscosity, hydraulic water hammer, oil leakage, and component failure prevention). Corresponding mitigation measures were proposed, along with an optimized testing approach. [Results] During the low-temperature testing of the 5,000-psi hydraulic system for civil aircraft, the typical failure risks in the test system primarily involved faults in pressure, temperature, and flow sensors. The low-pressure circuit was susceptible to water hammer risks, requiring sensors with appropriate ranges based on specific needs. Additionally, the impact of water hammer effects on the pipeline system could not be overlooked. The uneven temperature distribution in the system required the careful placement and selection of temperature sensors. When choosing flow sensors, the influence of oil viscosity and flow instability must be considered. Meanwhile, the typical failure risks in the mechanical system mainly include the degradation of seal performance at low temperatures, leading to oil leakage, as well as increased friction in components due to higher oil viscosity at low temperatures. These factors might also affect the control of hydraulic components. The low-pressure circuit was susceptible to water hammer effects, which could not be overlooked. Nonuniform temperature distribution within the system necessitated the careful selection of temperature sensor placement. Fluid viscosity and instability had to be considered when selecting flow sensors. For the mechanical system, typical failure risks included seal failure at low temperatures, leading to fluid leakage. Moreover, increased oil viscosity affected hydraulic component control. [Conclusions] Optimizing low-temperature testing for 5,000-psi hydraulic systems requires integrating mechanistic analysis with experimental validation. This should be achieved through multidimensional approaches, including simulation testing, collaborative optimization, intelligent sensing technologies, innovative materials and processes, and standardized laboratory management. These measures are expected to enhance operational safety and system performance under extreme conditions while providing critical technical support for the independent development of hydraulic systems in China's civil aviation sector.
[Objective] Traditional transmission loss models for LoRa wireless communication systems operating in near-ground environments exhibit limited applicability. Another issue is the difficulty of effectively supporting the design of near-ground wireless transmission networks. Furthermore, most of the currently available test methods for LoRa communication systems are costly and exhibit limited flexibility. Based on the above, we propose a new wireless communication system for testing the transmission quality of LoRa wireless communication systems operating in near-ground environments. [Methods] The proposed test system consists of a communication and an analysis part. The communication part includes a chip integrating a wireless microcontroller and wireless communication functions, as well as a Micro SD storage unit. The communication functions and the storage unit are used for LoRa signal communication, as well as the storage of the communication signals and their parameters(i.e., signal-to-noise ratio and signal strength); the microcontroller is used to implement visualization data functions and a key menu function for adjusting the communication parameters at any time during testing. The analysis is performed using the upper computer software, which is designed to read the communication quality parameters of the LoRa signals stored in the memory card. The strength of the transmitted signal is determined according to the traditional, empirical, and improved empirical transmission loss models. Finally, the host computer outputs the results generated by the three models. These results are the values of the parameters to be fitted for different models, the sum of residuals, and the correlation coefficient. [Results] The parameter fitting values are the environmental impact constant and the attenuation coefficient; these are used to represent the signal transmission characteristics in certain environments. The sum of residuals and the correlation coefficient represent the degree the fitted model represents the actual signal. When the sum of residuals is small and the correlation coefficient is large, the degree the model fits the actual signal increases. During testing, the strength values of the LoRa modulated signals near the ground(i.e., 1 m above the ground) are collected assuming three ground scenarios: snow-covered, farmland, and cement-covered ground; then, the signals are processed and analyzed using the proposed computer software. The value of the environmental impact constant obtained from the software using the empirical model with a one-step fitting was negative. This erroneous result indicates overfitting of the empirical model. Therefore, we employed an improved empirical model. In this model, the data are gradually fitted, starting from three pieces and ending with all nine pieces of data. Then, all fitting results are summed, and their average values are calculated. These values replace the corresponding parameter values in the empirical model to obtain a rational model. The rationality, validity, and convergence of the improved empirical model were verified using the proposed computer software. [Conclusions] The experimental results showed that the improved empirical model constructed using multistep fitting can reasonably and accurately describe the transmission loss characteristics of LoRa modulated signals in near-ground environments, providing a useful reference for the construction of future LoRa near-ground wireless transmission networks.