Battery Train Fire Risk on a Steel Warehouse Structure

Lithium ion battery fire hazard has been well-documented in a variety of applications.Recently,battery train technology has been introduced as a clean energy concept for railway.In the case of heavy locomotives such as trains,the massive collection of battery stacks required to meet energy demands may pose a significant hazard.The objective of this paper is to review the risk evaluation processes for train fires and investigate the propagation of lithium ion battery fire to a neighboring steel warehouse structure at a rail repair shop through a case study.The methodology of the analyses conducted include a Monte Carlo-based dynamic modeling of fire propagation potentials,an expert-based fire impact analysis,and a finite element(FE)nonlinear fire analysis on the structural frame.The case study is presented as a demonstration of a holistic fire risk analysis for the lithium ion battery fire and results indicate that significant battery fire mitigations strategies should be considered.

Virtual reality for immersive multi-user firefighter-training scenarios

Background Virtual reality(VR)applications can be used to provide comprehensive training scenarios that are difficult or impossible to represent in physical configurations.This includes team training for emergency services such as firefighting.Creating a high level of immersion is essential for achieving effective virtual training.In this respect,motion-capture systems offer the possibility of creating highly immersive multi-user training experiences,including full-body avatars.Methods This study presents a preliminary prototype that helps extin-guish a virtual fire on a container ship as a VR training scenario.The prototype provides a full-body and multi-user VR experience based on the synthesis of position data provided by the motion-capture system and orientation data from the VR headsets.Moreover,the prototype facilitates an initial evaluation of the results.Results The results confirm the value of using VR for training procedures that are difficult to implement in the real world.Furthermore,the results show that motion-capture-based VR technologies are particularly useful for firefighting training,in which participants can collaborate in difficult-to-access environments.However,this study also indicates that increasing the immersion in such training remains a challenge.Conclusions This study presents a prototypical VR application that enables the multi-user training of maritime firefighters.Future research should evaluate the initial results,provide more extensive training scenarios,and measure the training progress.

Smoke movement in a tunnel of a running metro train on fire

Research on the distribution of smoke in tunnels is significant for the fire emergency rescue after an operating metro train catches fire. A dynamic grid technique was adopted to research the law of smoke flow diffusion inside the tunnel when the bottom of a metro train was on fire and to compare the effect of longitudinal ventilation modes on the smoke motion when the burning train stopped. Research results show that the slipstream curves around the train obtained by numerical simulation are consistent with experimental data. When the train decelerates, the smoke flow first extends to the tail of the train. With the decrease of the train's speed, the smoke flow diffuses to the head of the train. After the train stops, the slipstream around the train formed in the process of train operation plays a leading role in the smoke diffusion in the tunnel. The smoke flow quickly diffuses to the domain in front of the train. After forward mechanical ventilation is provided, the smoke flow inside the tunnel continues to diffuse downstream. When reverse mechanical ventilation operates, the smoke in front of the train flows back rapidly and diffuses to the rear of the train.

The influence of resistance exercise training prescription variables on skeletal muscle mass,strength,and physical function in healthy adults:An umbrella review

Purpose:The aim of this umbrella review was to determine the impact of resistance training(RT)and individual RT prescription variables on muscle mass,strength,and physical function in healthy adults.Methods:Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines,we systematically searched and screened eligible systematic reviews reporting the effects of differing RT prescription variables on muscle mass(or its proxies),strength,and/or physical function in healthy adults aged>18 years.Results:We identified 44 systematic reviews that met our inclusion criteria.The methodological quality of these reviews was assessed using A Measurement Tool to Assess Systematic Reviews;standardized effectiveness statements were generated.We found that RT was consistently a potent stimulus for increasing skeletal muscle mass(4/4 reviews provide some or sufficient evidence),strength(4/6 reviews provided some or sufficient evidence),and physical function(1/1 review provided some evidence).RT load(6/8 reviews provided some or sufficient evidence),weekly frequency(2/4 reviews provided some or sufficient evidence),volume(3/7 reviews provided some or sufficient evidence),and exercise order(1/1 review provided some evidence)impacted RT-induced increases in muscular strength.We discovered that 2/3 reviews provided some or sufficient evidence that RT volume and contraction velocity influenced skeletal muscle mass,while 4/7 reviews provided insufficient evidence in favor of RT load impacting skeletal muscle mass.There was insufficient evidence to conclude that time of day,periodization,inter-set rest,set configuration,set end point,contraction velocity/time under tension,or exercise order(only pertaining to hypertrophy)influenced skeletal muscle adaptations.A paucity of data limited insights into the impact of RT prescription variables on physical function.Conclusion:Overall,RT increased muscle mass,strength,and physical function compared to no exercise.RT intensity(load)and weekly frequency impacted RT-induced increases in muscular strength but not muscle hypertrophy.RT volume(number of sets)influenced muscular strength and hypertrophy.

Surgical intervention combined with weight-bearing walking training promotes recovery in patients with chronic spinal cord injury:a randomized controlled study

For patients with chronic spinal cord injury,the co nventional treatment is rehabilitation and treatment of spinal cord injury complications such as urinary tract infection,pressure sores,osteoporosis,and deep vein thrombosis.Surgery is rarely perfo rmed on spinal co rd injury in the chronic phase,and few treatments have been proven effective in chronic spinal cord injury patients.Development of effective therapies fo r chronic spinal co rd injury patients is needed.We conducted a randomized controlled clinical trial in patients with chronic complete thoracic spinal co rd injury to compare intensive rehabilitation(weight-bearing walking training)alone with surgical intervention plus intensive rehabilitation.This clinical trial was registered at ClinicalTrials.gov(NCT02663310).The goal of surgical intervention was spinal cord detethering,restoration of cerebrospinal fluid flow,and elimination of residual spinal cord compression.We found that surgical intervention plus weight-bearing walking training was associated with a higher incidence of American Spinal Injury Association Impairment Scale improvement,reduced spasticity,and more rapid bowel and bladder functional recovery than weight-bearing walking training alone.Overall,the surgical procedures and intensive rehabilitation were safe.American Spinal Injury Association Impairment Scale improvement was more common in T7-T11 injuries than in T2-T6 injuries.Surgery combined with rehabilitation appears to have a role in treatment of chronic spinal cord injury patients.

Numerical analysis of moving train induced vibrations on tunnel,surrounding ground and structure

This study is focused on the effect of vibration induced by moving trains in tunnels on the surrounding ground and structures.A three-dimensional finite element model is established for a one-track railway tunnel and an adjacent twelve-storey building frame by using commercial software Midas GTS-NX(2019)and Midas Gen.This study considered the moving load effect of a complete train,which varies with space as well as with time.The effect of factors such as train speed,overburden pressure on the tunnel and variation in soil properties are studied in the time domain.As a result,the variations in horizontal and vertical acceleration for two different sites,i.e.,the free ground surface(without structure)and the area containing the structure,are compared.Also,the displacement pattern of the raft foundation is plotted for different train velocities.At lower speeds,the heaving phenomenon is negligible,but as the speed increases,both the heaving and differential settlement increase in the foundation.This study demonstrates that the effect of moving train vibrations should be considered in the design of new nearby structures and proper ground improvement should be considered for existing structures.

Application value research of swallowing treatment device combined with swallowing rehabilitation training in the treatment of swallowing disorders after stroke

BACKGROUND Stroke is a common disabling disease,whether it is ischemic stroke or hemorrhagic stroke,both can result in neuronal damage,leading to various manifestations of neurological dysfunction.AIM To explore of the application value of swallowing treatment device combined with swallowing rehabilitation training in the treatment of swallowing disorders after stroke.METHODS This study selected 86 patients with swallowing disorders after stroke admitted to our rehabilitation department from February 2022 to December 2023 as research subjects.They were divided into a control group(n=43)and an observation group(n=43)according to the treatment.The control group received swallowing rehabilitation training,while the observation group received swallowing treatment device in addition to the training.Both groups underwent continuous intervention for two courses of treatment.RESULTS The total effective rate in the observation group(93.02%)was higher than that in the control group(76.74%)(P=0.035).After intervention,the oral transit time,swallowing response time,pharyngeal transit time,and laryngeal closure time decreased in both groups compared to before intervention.In the observation group,the oral transit time,swallowing response time,and pharyngeal transit time were shorter than those in the control group after intervention.However,the laryngeal closure time after intervention in the observation group was compared with that in the control group(P=0.142).After intervention,average amplitude value and duration of the genioglossus muscle group during empty swallowing and swallowing 5 mL of water are reduced compared to before intervention in both groups.After intervention,the scores of the chin-tuck swallowing exercise and the Standardized Swallowing Assessment are both reduced compared to pre-intervention levels in both groups.However,the observation group scores lower than the control group after intervention.Additionally,the Functional Oral Intake Scale scores of both groups are increased after intervention compared to pre-intervention levels,with the observation group scoring higher than the control group after intervention(P<0.001).The cumulative incidence of complications in the observation group is 9.30%,which is lower than the 27.91%in the control group(P=0.027).CONCLUSION The combination of swallowing therapy equipment with swallowing rehabilitation training can improve the muscle movement level of the genioglossus muscle group,enhance swallowing function,and prevent the occurrence of swallowing-related complications after stroke.

GeoNER:Geological Named Entity Recognition with Enriched Domain Pre-Training Model and Adversarial Training

As important geological data,a geological report contains rich expert and geological knowledge,but the challenge facing current research into geological knowledge extraction and mining is how to render accurate understanding of geological reports guided by domain knowledge.While generic named entity recognition models/tools can be utilized for the processing of geoscience reports/documents,their effectiveness is hampered by a dearth of domain-specific knowledge,which in turn leads to a pronounced decline in recognition accuracy.This study summarizes six types of typical geological entities,with reference to the ontological system of geological domains and builds a high quality corpus for the task of geological named entity recognition(GNER).In addition,Geo Wo BERT-adv BGP(Geological Word-base BERTadversarial training Bi-directional Long Short-Term Memory Global Pointer)is proposed to address the issues of ambiguity,diversity and nested entities for the geological entities.The model first uses the fine-tuned word granularitybased pre-training model Geo Wo BERT(Geological Word-base BERT)and combines the text features that are extracted using the Bi LSTM(Bi-directional Long Short-Term Memory),followed by an adversarial training algorithm to improve the robustness of the model and enhance its resistance to interference,the decoding finally being performed using a global association pointer algorithm.The experimental results show that the proposed model for the constructed dataset achieves high performance and is capable of mining the rich geological information.

NeTrainSim:a network-level simulator for modeling freight train longitudinal motion and energy consumption

Although train modeling research is vast, most available simulation tools are confined to city-or trip-scale analysis, primarily offering micro-level simulations of network segments. This paper addresses this void by developing the Ne Train Sim simulator for heavy long-haul freight trains on a network of multiple intersecting tracks. The main objective of this simulator is to enable a comprehensive analysis of energy consumption and the associated carbon footprint for the entire train system. Four case studies were conducted to demonstrate the simulator's performance. The first case study validates the model by comparing Ne Train Sim output to empirical trajectory data. The results demonstrate that the simulated trajectory is precise enough to estimate the train energy consumption and carbon dioxide emissions. The second application demonstrates the train-following model considering six trains following each other. The results showcase the model ability to maintain safefollowing distances between successive trains. The next study highlights the simulator's ability to resolve train conflicts for different scenarios. Finally, the suitability of the Ne Train Sim for modeling realistic railroad networks is verified through the modeling of the entire US network and comparing alternative powertrains on the fleet energy consumption.

Evaluating the feasibility and preliminary effects of an online compassion training program for nursing students:A pilot randomized controlled trial

Objectives:This study aimed to assess the feasibility of an online compassion training program for nursing students and preliminarily investigate its effects on mindfulness,self-compassion,and stress reduction.Methods:This study employed a randomized controlled trial design.Second-year students from a nursing college in Guangzhou,China,were recruited as research participants in August 2023.The intervention group participated in an 8-week online compassion training program via the WeChat platform,comprising three stages:mindfulness(weeks 1e2),self-compassion(weeks 3e5),and compassion for others(weeks 6 e8).Each stage included four activities:psychoeducation,mindfulness practice,weekly diary,and emotional support.Program feasibility was assessed through recruitment and retention rates,program engagement,and participant acceptability.Program effectiveness was measured with the Mindful Attention Awareness Scale,Self-Compassion Scale-Short Form,and Perceived Stress Scale.Results:A total of 28 students completed the study(13 in the intervention group,15 in the control group).The recruitment rate was 36.46%,with a high retention rate of 93.3%.Participants demonstrated high engagement:69.2%accessed learning materials every 1e2 days,93.3%practiced mindfulness at least weekly,with an average of 4.69 diary entries submitted per person and 23.30 WeChat interactions with instructors.Regarding acceptability,all participants expressed satisfaction with the program,with 92.4%finding it“very helpful”or“extremely helpful.”In terms of intervention effects,the intervention group showed a significant increase in mindfulness levels from pre-intervention(51.54±10.93)to postintervention(62.46±13.58)(P<0.05),while no significant change was observed in the control group.Although there were no statistically significant differences between the two groups in post-intervention self-compassion and perceived stress levels,the intervention group showed positive trends:selfcompassion levels increased(35.85±8.60 vs.40.85±5.54),and perceived stress levels slightly decreased(44.77±8.65 vs.42.00±5.77).Conclusions:This pilot study demonstrated the feasibility of an online compassion training program for nursing students and suggested its potential effectiveness in enhancing mindfulness,self-compassion,and stress reduction.Despite limitations such as small sample size and lack of long-term follow-up,preliminary evidence indicates promising prospects for integrating such training into nursing education.Further research is warranted to confirm thesefindings and assess the sustained impact of this approach on nursing education and practice.

Transurethral resection of bladder tumor: A systematic review of simulator-based training courses and curricula

Objective:Transurethral resection of bladder tumor is one of the most common everyday urological procedures.This kind of surgery demands a set of skills that need training and experience.In this review,we aimed to investigate the current literature to find out if simulators,phantoms,and other training models could be used as a tool for teaching urologists.Methods:A systematic review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement and the recommendations of the European Association of Urology guidelines for conducting systematic reviews.Fifteen out of 932 studies met our inclusion criteria and are presented in the current review.Results:The UroTrainer(Karl Storz GmbH,Tuttlingen,Germany),a virtual reality training simulator,achieved positive feedback and an excellent face and construct validity by the participants.The inspection of bladder mucosa,blood loss,tumor resection,and procedural time was improved after the training,especially for inexperienced urologists and medical students.The construct validity of UroSim®(VirtaMed,Zurich,Switzerland)was established.SIMBLA simulator(Samed GmbH,Dresden,Germany)was found to be a realistic and useful tool by experts and urologists with intermediate experience.The test objective competency model based on SIMBLA simulator could be used for evaluating urologists.The porcine model of the Asian Urological Surgery Training and Education Group also received positive feedback by the participants that tried it.The Simulation and Technology Enhanced Learning Initiative Project had an extraordinary face and content validity,and 60%of participants would like to use the simulators in the future.The 5-day multimodal training curriculum“Boot Camp”in the United Kingdom achieved an increase of the level of confidence of the participants that lasted months after the project.Conclusion:Simulators and courses or curricula based on a simulator training could be a valuable learning tool for any surgeon,and there is no doubt that they should be a part of every urologist's technical education.

Attack-Resilient Distributed Cooperative Control of Virtually Coupled High-Speed Trains via Topology Reconfiguration

Dear Editor,This letter addresses the resilient distributed cooperative control problem of a virtually coupled train convoy under stochastic disturbances and cyber attacks.The main purpose is to achieve distributed coordination of virtually coupled high-speed trains with the prescribed inter-train distance and same cruise velocity.

Effect of resistance training volume on body adiposity,metabolic risk,and inflammation in postmenopausal and older females:Systematic review and meta-analysis of randomized controlled trials

Purpose:This meta-analytical study aimed to explore the effects of resistance training(RT) volume on body adiposity,metabolic risk,and inflammation in postmenopausal and older females.Methods:A systematic search was performed for randomized controlled trials in PubMed,Scopus,Web of Science,and SciELO.Randomized controlled trials with postmenopausal and older females that compared RT effects on body adiposity,metabolic risk,and inflammation with a control group(CG) were included.Independent reviewers selected the studies,extracted the data,and performed the risk of bias and certainty of the evidence(Grading of Recommendations,Assessment,Development,and Evaluation(GRADE)) evaluations.Total body and abdominal adiposity,blood lipids,glucose,and C-reactive protein were included for meta-analysis.A random-effects model,standardized mean difference(Hedges’ g),and 95% confidence interval(95%CI) were used for meta-analysis.Results:Twenty randomized controlled trials(overall risk of bias:some concerns;GRADE:low to very low) with overweight/obese postmenopausal and older females were included.RT groups were divided into low-volume RT(LVRT,~44 sets/week) and high-volume RT(HVRT,~77 sets/week).Both RT groups presented improved body adiposity,metabolic risk,and inflammation when compared to CG.However,HVRT demonstrated higher effect sizes than LVRT for glucose(HVRT=-1.19;95%CI:-1.63 to-0.74;LVRT=-0.78;95%CI:-1.15 to-0.41) and C-reactive protein(HVRT=-1.00;95%CI:-1.32 to-0.67;LVRT=-0.34;95%CI,-0.63 to-0.04)) when compared to CG.Conclusion:Compared to CG,HVRT protocols elicit greater improvements in metabolic risk and inflammation outcomes than LVRT in overweight/obese postmenopausal and older females.

Beam Training and Tracking in mmWave Communication:A Survey

Communicating on millimeter wave(mmWave)bands is ushering in a new epoch of mobile communication which provides the availability of 10 Gbps high data rate transmission.However,mmWave links are easily prone to short transmission range communication because of the serious free space path loss and the blockage by obstacles.To overcome these challenges,highly directional beams are exploited to achieve robust links by hybrid beamforming.Accurately aligning the transmitter and receiver beams,i.e.beam training,is vitally important to high data rate transmission.However,it may cause huge overhead which has negative effects on initial access,handover,and tracking.Besides,the mobility patterns of users are complicated and dynamic,which may cause tracking error and large tracking latency.An efficient beam tracking method has a positive effect on sustaining robust links.This article provides an overview of the beam training and tracking technologies on mmWave bands and reveals the insights for future research in the 6th Generation(6G)mobile network.Especially,some open research problems are proposed to realize fast,accurate,and robust beam training and tracking.We hope that this survey provides guidelines for the researchers in the area of mmWave communications.

Increasing realism in modelling energy losses in railway vehicles and their impact to energy-efficient train control

The reduction of energy consumption is an increasingly important topic of the railway system.Energy-efficient train control(EETC)is one solution,which refers to mathematically computing when to accelerate,which cruising speed to hold,how long one should coast over a suitable space,and when to brake.Most approaches in literature and industry greatly simplify a lot of nonlinear effects,such that they ignore mostly the losses due to energy conversion in traction components and auxiliaries.To fill this research gap,a series of increasingly detailed nonlinear losses is described and modelled.We categorize an increasing detail in this representation as four levels.We study the impact of those levels of detail on the energy optimal speed trajectory.To do this,a standard approach based on dynamic programming is used,given constraints on total travel time.This evaluation of multiple test cases highlights the influence of the dynamic losses and the power consumption of auxiliary components on railway trajectories,also compared to multiple benchmarks.The results show how the losses can make up 50%of the total energy consumption for an exemplary trip.Ignoring them would though result in consistent but limited errors in the optimal trajectory.Overall,more complex trajectories can result in less energy consumption when including the complexity of nonlinear losses than when a simpler model is considered.Those effects are stronger when the trajectory includes many acceleration and braking phases.

Optimized operation scheme of flash-memory-based neural network online training with ultra-high endurance

With the rapid development of machine learning,the demand for high-efficient computing becomes more and more urgent.To break the bottleneck of the traditional Von Neumann architecture,computing-in-memory(CIM)has attracted increasing attention in recent years.In this work,to provide a feasible CIM solution for the large-scale neural networks(NN)requiring continuous weight updating in online training,a flash-based computing-in-memory with high endurance(10^(9) cycles)and ultrafast programming speed is investigated.On the one hand,the proposed programming scheme of channel hot electron injection(CHEI)and hot hole injection(HHI)demonstrate high linearity,symmetric potentiation,and a depression process,which help to improve the training speed and accuracy.On the other hand,the low-damage programming scheme and memory window(MW)optimizations can suppress cell degradation effectively with improved computing accuracy.Even after 109 cycles,the leakage current(I_(off))of cells remains sub-10pA,ensuring the large-scale computing ability of memory.Further characterizations are done on read disturb to demonstrate its robust reliabilities.By processing CIFAR-10 tasks,it is evident that~90%accuracy can be achieved after 109 cycles in both ResNet50 and VGG16 NN.Our results suggest that flash-based CIM has great potential to overcome the limitations of traditional Von Neumann architectures and enable high-performance NN online training,which pave the way for further development of artificial intelligence(AI)accelerators.

Dynamic analysis of axle box bearings on the high-speed train caused by wheel-rail excitation

To explore the impact of wheel-rail excitation on the dynamic performance of axle box bearings,a dynamic model of the high-speed train including axle box bearings is developed.Subsequently,the dynamic response characteristics of the axle box bearing are examined.The investigation focuses on the acceleration characteristics of bearing vibration under excitation of track irregularities and wheel flats.In addition,experiments on both normal and faulty bearings are conducted separately,and the correctness of the model and some conclusions are verified.According to the research,track irregularity is unfavorable for bearing fault detection based on resonance demodulation.Under the same speed conditions,the acceleration peak of bearing is inversely proportional to the length of the wheel flat and directly proportional to its depth.The paper will contribute to a deeper understanding of the dynamic performance of axle box bearings.

Influences of the Fresh Air Volume on the Removal of Cough-Released Droplets in a Passenger Car of a High-Speed Train Using CFD

The spread and removal of pollution sources,namely,cough-released droplets in three different areas(front,middle,and rear areas)of a fully-loaded passenger car in a high-speed train under different fresh air flow volume were studied using computational fluid dynamics(CFD)method.In addition,the structure of indoor flow fields was also analysed.The results show that the large eddies are more stable and flow faster in the air supply under Mode 2(fresh air volume:2200m3/h)compared to Mode 1(fresh air volume:1100m3/h).By analysing the spreading process of droplets sprayed at different locations in the passenger car and with different particle sizes,the removal trends for droplets are found to be similar under the two air supply modes.However,when increasing the fresh air flow volume,the droplets in the middle and front areas of the passenger car are removed faster.When the droplets had dispersed for 60s,Mode 2 exhibited a removal rate approximately 1%–3%higher than Mode 1 for small and medium-sized droplets with diameters of 10 and 50μm.While those in the rear area,the situation is reversed,with Mode 1 slightly surpassing Mode 2 by 1%–3%.For large droplets with a diameter of 100μm,both modes achieved a removal rate of over 96%in all three regions at the 60 s.The results can provide guidance for air supply modes of passenger cars of high-speed trains,thus suppressing the spread of virus-carrying droplets and reducing the risk of viral infection among passengers.

Effect of cognitive training on brain dynamics

The human brain is highly plastic.Cognitive training is usually used to modify functional connectivity of brain networks.Moreover,the structures of brain networks may determine its dynamic behavior which is related to human cognitive abilities.To study the effect of functional connectivity on the brain dynamics,the dynamic model based on functional connections of the brain and the Hindmarsh–Rose model is utilized in this work.The resting-state fMRI data from the experimental group undergoing abacus-based mental calculation(AMC)training and from the control group are used to construct the functional brain networks.The dynamic behavior of brain at the resting and task states for the AMC group and the control group are simulated with the above-mentioned dynamic model.In the resting state,there are the differences of brain activation between the AMC group and the control group,and more brain regions are inspired in the AMC group.A stimulus with sinusoidal signals to brain networks is introduced to simulate the brain dynamics in the task states.The dynamic characteristics are extracted by the excitation rates,the response intensities and the state distributions.The change in the functional connectivity of brain networks with the AMC training would in turn improve the brain response to external stimulus,and make the brain more efficient in processing tasks.

Torque effect on vibration behavior of high-speed train gearbox under internal and external excitations

The high-speed train transmission system,experiencing both the internal excitation originating from gear meshing and the external excitation originating from the wheel-rail interaction,exhibits complex dynamic behavior in the actual service environment.This paper focuses on the gearbox in the high-speed train to carry out the bench test,in which various operat-ing conditions(torques and rotation speeds)were set up and the excitation condition covering both internal and external was created.Acceleration responses on multiple positions of the gearbox were acquired in the test and the vibration behavior of the gearbox was studied.Meanwhile,a stochastic excitation modal test was also carried out on the test bench under different torques,and the modal parameter of the gearbox was identified.Finally,the sweep frequency response of the gearbox under gear meshing excitation was analyzed through dynamic modeling.The results showed that the torque has an attenuating effect on the amplitude of gear meshing frequency on the gearbox,and the effect of external excitation on the gearbox vibration cannot be ignored,especially under the rated operating condition.It was also found that the torque affects the modal param-eter of the gearbox significantly.The torque has a great effect on both the gear meshing stiffness and the bearing stiffness in the transmission system,which is the inherent reason for the changed modal characteristics observed in the modal test and affects the vibration behavior of the gearbox consequently.