A Multiscale Reliability-Based Design Optimization Method for Carbon-Fiber-Reinforced Composite Drive Shafts

Carbon fiber composites,characterized by their high specific strength and low weight,are becoming increasingly crucial in automotive lightweighting.However,current research primarily emphasizes layer count and orientation,often neglecting the potential of microstructural design,constraints in the layup process,and performance reliability.This study,therefore,introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic(CFRP)drive shafts.Initially,parametric modeling of the microscale cell was performed,and its elastic performance parameters were predicted using two homogenization methods,examining the impact of fluctuations in microscale cell parameters on composite material performance.A finite element model of the CFRP drive shaft was then constructed,achieving parameter transfer between microscale and macroscale through Python programming.This enabled an investigation into the influence of both micro and macro design parameters on the CFRP drive shaft’s performance.The Multi-Objective Particle Swarm Optimization(MOPSO)algorithm was enhanced for particle generation and updating strategies,facilitating the resolution of multi-objective reliability optimization problems,including composite material layup process constraints.Case studies demonstrated that this approach leads to over 30%weight reduction in CFRP drive shafts compared to metallic counterparts while satisfying reliability requirements and offering insights for the lightweight design of other vehicle components.

Force CT高级建模迭代重建算法对门静脉图像质量的影响

目的:探讨Force CT高级建模迭代重建算法(ADMIRE)对门静脉图像质量影响。方法:回顾性分析2022年1—4月于中山大学附属第八医院行上腹部CT平扫及增强的40例患者影像资料,在syngo.via后处理工作站重建,采用门脉期原始数据重建出滤波反投影算法(FBP)、ADMIRE1、ADMIRE3、ADMIRE5 4组不同重建算法的图像,在4组不同算法图像上测量门静脉干中心位置、肝实质及同层竖脊肌的CT值和噪声值,计算门静脉和肝实质的信噪比(SNR)和对比噪声比(CNR)。此外,由两位具有5年以上诊断经验的医生对图像进行主观评分。结果:随着迭代等级的增高,图像的CNR、SNR呈现上升的趋势,图像的噪声值呈现下降的趋势,其中ADMIRE5组图像中门静脉和肝脏具有最高的CNR和SNR且具有最低的噪声值,以及最高的主观评分,采用ADMIRE5重建算法的门静脉与周围组织对比非常好,门静脉5级分支显示良好。结论:高级建模迭代重建ADMIRE算法相比于FBP重建算法,降噪效果更好,门静脉的显示更加锐利,能提升门静脉的图像质量。

Self-assembly of perovskite nanocrystals:From driving forces to applications

Self-assembly of metal halide perovskite nanocrystals(NCs)into superlattices can exhibit unique collective properties,which have significant application values in the display,detector,and solar cell field.This review discusses the driving forces behind the self-assembly process of perovskite NCs,and the commonly used self-assembly methods and different self-assembly structures are detailed.Subsequently,we summarize the collective optoelectronic properties and application areas of perovskite superlattice structures.Finally,we conclude with an outlook on the potential issues and future challenges in developing perovskite NCs.

The Integration of Modern Electronic Technology and E-Commerce:the Driving Force of Innovation Development

In the 21st century,which is known as the age of information,the integration of electronic technology and e-commerce has become an irreversible trend in the field of business.This trend not only promotes the innovative development of e-commerce,but also brings unprecedented opportunities and challenges for enterprises.With the continuous development and popularization of Internet technology,more and more people choose to carry out shopping,payment and other consumption activities through e-commerce platforms,which also provides merchants with a broader market space and more sales channels.At the same time,e-commerce also brings more convenience and choice to consumers,making it easier for consumers to obtain the goods and services they need.However,the development of e-commerce has also brought some new challenges,such as how to ensure the quality of goods,how to protect consumer privacy and so on.Therefore,enterprises and government departments need to strengthen the supervision and management of e-commerce to ensure its healthy and orderly development.In general,the integration of electronic technology and e-commerce has become an important trend in today’s business field,which brings both opportunities and challenges to enterprises.

Research on the Spatio-Temporal Evolution and Driving Forces of Green Spaces in the Central Urban Area of Zunyi City

Green space,as a medium for carrying out urban functions and guiding urban development,is becoming a scarce resource along with the urbanization process and the intensification of environmental problems.In the face of the spatial mismatch between high demand and low supply,it is of great significance to clarify the evolution mechanism of green space to undertake national spatial planning,protect the natural strategic resources in the urban fringe area,and promote the sustainable development of the“three living spaces.”The study focuses on the Zunyi City Center,selecting the 20 years of rapid development following its establishment as a city as the study period.It explores the dynamic evolution of green space and the main driving forces during different periods using remote-sensing image data.The study shows that from 2003 to 2023,the total scale of green space has an obvious decreasing trend along with the expansion of the urban built-up area.A large amount of arable land is being converted to construction land,resulting in a sudden decrease in arable land area.In the past 10 years,the comprehensive land use dynamics have accelerated.Still,the spatial difference has gradually narrowed,indicating that the overall development intensity of Zunyi City’s central urban area has increased.There is a gradual spread of the trend to the hilly areas.The limiting effect of the mountainous natural environment on the city’s development has gradually diminished under the superposition of external factors,such as economic development,industrial technological upgrading,and policy orientation so the importance of the effective protection and rational utilization of urban green space has become more prominent.

Comparisons of Wave Force Model Effects on the Structural Responses and Fatigue Loads of a Semi-Submersible Floating Wind Turbine

The selection of wave force models will significantly impact the structural responses of floating wind turbines.In this study,comparisons of wave force model effects on the structural responses and fatigue loads of a semi-submersible floating wind turbine(SFWT)were conducted.Simulations were performed by employing the Morison equation(ME)with linear or second-order wave kinematics and potential flow theory(PFT)with first-or second-order wave forces.A comparison of regular waves,irregular waves,and coupled wind/waves analyses with the experimental data showed that many of the simulation results and experimental data are relatively consistent.However,notable discrepancies are found in the response amplitude operators for platform heave,tower base bending moment,and tension in mooring lines.PFT models give more satisfactory results of heave but more significant discrepan-cies in tower base bending moment than the ME models.In irregular wave analyses,low-frequency resonances were captured by PFT models with second-order difference-frequency terms,and high-frequency resonances were captured by the ME models or PFT models with second-order sum-frequency terms.These force models capture the response frequencies but do not reasonably predict the response amplitudes.The coupled wind/waves analyses showed more satisfactory results than the wave-only analyses.However,an important detail to note is that this satisfactory result is based on the overprediction of wind-induced responses.

Culturally competent care across borders: Implementing culturally responsive teaching for nurses in diverse workforces

The migration of healthcare professionals,including nurses,is a global phenomenon.It is driven by various factors,including the pursuit of better opportunities,living conditions,and professional development,as well as political instability or conflict in their home countries.The World Health Organization(WHO)has noted that high-income countries often rely on foreign-trained nurses to fill gaps in their healthcare systems[1].For instance,as of 2021,over 40%(52 million)of all nurses in the United States(US)were expatriates[2].In the United Kingdom(UK),the percentage of expatriate nurses was even higher,reaching approximately 18%in 2021[3].Owing to globalization and migration,healthcare providers must possess cultural competence to deliver improved care[4,5].Culturally responsive teaching(CRT)is rooted in the idea that culture plays a vital role in shaping people’s behaviors,beliefs,values,and communication styles[6].Furthermore,these cultural factors influence patients’perspectives on health,illness,healing,and their preferences for care and communication[7].By recognizing and embracing these cultural differences,nurses can provide more effective and compassionate care to their diverse patient population[8].

Effects of drive imbalance on the particle emission from a Bose-Einstein condensate in a one-dimensional lattice

Time-periodic driving has been an effective tool in the field of nonequilibrium quantum dynamics,which enables precise control of the particle interactions.We investigate the collective emission of particles from a Bose-Einstein condensate in a one-dimensional lattice with periodic drives that are separate in modulation amplitudes and relative phases.In addition to the enhancement of particle emission,we find that amplitude imbalances lead to energy shift and band broadening,while typical relative phases may give rise to similar gaps.These results offer insights into the specific manipulations of nonequilibrium quantum systems with tone-varying drives.

Research on Driver’s Fatigue Detection Based on Information Fusion

Driving fatigue is a physiological phenomenon that often occurs during driving.After the driver enters a fatigued state,the attentionis lax,the response is slow,and the ability todeal with emergencies is significantly reduced,which can easily cause traffic accidents.Therefore,studying driver fatigue detectionmethods is significant in ensuring safe driving.However,the fatigue state of actual drivers is easily interfered with by the external environment(glasses and light),which leads to many problems,such as weak reliability of fatigue driving detection.Moreover,fatigue is a slow process,first manifested in physiological signals and then reflected in human face images.To improve the accuracy and stability of fatigue detection,this paper proposed a driver fatigue detection method based on image information and physiological information,designed a fatigue driving detection device,built a simulation driving experiment platform,and collected facial as well as physiological information of drivers during driving.Finally,the effectiveness of the fatigue detection method was evaluated.Eye movement feature parameters and physiological signal features of drivers’fatigue levels were extracted.The driver fatigue detection model was trained to classify fatigue and non-fatigue states based on the extracted features.Accuracy rates of the image,electroencephalogram(EEG),and blood oxygen signals were 86%,82%,and 71%,separately.Information fusion theory was presented to facilitate the fatigue detection effect;the fatigue features were fused using multiple kernel learning and typical correlation analysis methods to increase the detection accuracy to 94%.It can be seen that the fatigue driving detectionmethod based onmulti-source feature fusion effectively detected driver fatigue state,and the accuracy rate was higher than that of a single information source.In summary,fatigue drivingmonitoring has broad development prospects and can be used in traffic accident prevention and wearable driver fatigue recognition.

Controlled thermally-driven mass transport in carbon nanotubes using carbon hoops

Controlling mass transportation using intrinsic mechanisms is a challenging topic in nanotechnology.Herein,we employ molecular dynamics simulations to investigate the mass transport inside carbon nanotubes(CNT)with temperature gradients,specifically the effects of adding a static carbon hoop to the outside of a CNT on the transport of a nanomotor inside the CNT.We reveal that the underlying mechanism is the uneven potential energy created by the hoops,i.e.,the hoop outside the CNT forms potential energy barriers or wells that affect mass transport inside the CNT.This fundamental control of directional mass transportation may lead to promising routes for nanoscale actuation and energy conversion.

Electric field and force characteristic of dust aerosol particles on the surface of high-voltage transmission line

High-voltage transmission lines play a crucial role in facilitating the utilization of renewable energy in regions prone to desertification. The accumulation of atmospheric particles on the surface of these lines can significantly impact corona discharge and wind-induced conductor displacement. Accurately quantifying the force exerted by particles adhering to conductor surfaces is essential for evaluating fouling conditions and making informed decisions. Therefore, this study investigates the changes in electric field intensity along branched conductors caused by various fouling layers and their resulting influence on the adhesion of dust particles. The findings indicate that as individual particle size increases, the field strength at the top of the particle gradually decreases and eventually stabilizes at approximately 49.22 k V/cm, which corresponds to a field strength approximately 1.96 times higher than that of an unpolluted transmission line. Furthermore,when particle spacing exceeds 15 times the particle size, the field strength around the transmission line gradually decreases and approaches the level observed on non-adhering surface. The electric field remains relatively stable. In a triangular arrangement of three particles, the maximum field strength at the tip of the fouling layer is approximately 1.44 times higher than that of double particles and 1.5 times higher compared to single particles. These results suggest that particles adhering to the transmission line have a greater affinity for adsorbing charged particles. Additionally, relevant numerical calculations demonstrate that in dry environments, the primary adhesion forces between particles and transmission lines follow an order of electrostatic force and van der Waals force. Specifically, at the minimum field strength, these forces are approximately74.73 times and 19.43 times stronger than the gravitational force acting on the particles.

Experimental and numerical simulation study on forced ventilation and dust removal of coal mine heading surface

In order to study the problems of unreasonable airflow distribution and serious dust pollution in a heading surface,an experimental platform for forced ventilation and dust removal was built based on the similar principles.Through the similar experiment and numerical simulation,the distribution of airflow field in the roadway and the spatial and temporal evolution of dust pollution under the conditions of forced ventilation were determined.The airflow field in the roadway can be divided into three zones:jet zone,vortex zone and reflux zone.The dust concentration gradually decreases from the head to the rear of the roadway.Under the forced ventilation conditions,there is a unilateral accumulation of dust,with higher dust concentrations away from the ducts.The position of the equipment has an interception effect on the dust.The maximum error between the test value and the simulation result is 12.9%,which verifies the accuracy of the experimental results.The research results can provide theoretical guidance for the application of dust removal technology in coal mine.

Distributed Dynamic Load in Structural Dynamics by the Impulse-Based Force Estimation Algorithm

This paper proposes a novel approach for identifying distributed dynamic loads in the time domain.Using polynomial andmodal analysis,the load is transformed intomodal space for coefficient identification.This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force,thereby achieving dimensionality reduction.The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain.Firstly,the algorithm establishes a recursion scheme based on convolution integral,enabling it to identify loads with a long history and rapidly changing forms over time.Secondly,the algorithm introduces moving mean and polynomial fitting to detrend,enhancing its applicability in load estimation.The aforementioned methodology successfully accomplishes the reconstruction of distributed,instead of centralized,dynamic loads on the continuum in the time domain by utilizing acceleration response.To validate the effectiveness of the method,computational and experimental verification were conducted.

Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse Reinforcement Learning Theory

The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.

Post-Traumatic Stress Disorder among Defence and Security Forces in Northern Benin (2023)

Introduction: Post-traumatic stress disorder (PTSD) is defined as “actual exposure to death or the threat of death, serious injury or sexual violence”, either directly or indirectly, resulting in a symptomatic procession of repetition, avoidance, neurovegetative hyperactivity and individualized symptoms, with or without negative cognitive and mood changes. It therefore goes without saying that the defence and security forces constitute a high-risk population in need of attention. Objective: To study post-traumatic stress disorder in defence and security forces in the city of Parakou in 2023. Methods: Descriptive cross-sectional study conducted from December 2022 to July 2023. The study population consisted of active military, republican police and firefighters in the city of Parakou in 2023. Non-proportional stratified sampling was used, given the inaccessibility of the source population size for national security reasons. Post-traumatic stress disorder was assessed using the “post-traumatic stress disorder checklist-5 (PCLS-5) scale. Results: A total of 305 subjects participated in the survey. Males dominated 90.2%. The most represented corps was the Republican Police (41.6%), most of whom were non-commissioned officers (46.6%). The majority count between 11 and 20 years of service (48.9%), with 2 to 5 missions completed (67.5%). The calculated prevalence of post-traumatic stress disorder was 11.8%, based on the post-traumatic stress disorder checklist-5 (PCL-5). Of the 36 respondents with post-traumatic stress disorder, 20 (55.6%) had experienced an armed attack, 25 (69.4%) had witnessed a violent death, 18 (50.0%) had witnessed the agony of a colleague, 15 (41.7%) had been exposed to a fire or explosion, while 26 (72.2%) had been traumatized by physical and/or verbal aggression. 5 (13.9%) had consulted a specialist psychiatrist, while 6 (16.7%) were on medication and 26 (72.2%) used sport as a means of maintaining physical and mental health. Respectively 22 (61.1%) and 21 (58.3%) had definite symptoms of anxiety and depression. Multivariate analysis revealed a significant association between post-traumatic stress disorder and the following variables: total number of children ≤ 2 (p = 0.015), comorbidities such as arterial hypertension (p = 0.007), history of hepatitis (p = 0.017), work accidents (p = 0.016), alcohol dependence (p = 0.004), domestic violence (p = 0.004), psychological violence (p = 0.017) and anxiety disorders (p Conclusion: Defence and security personnel can also be prey to post-traumatic stress disorder (PTSD), which needs to be systematically taken into account when they are subjected to trauma in the course of their duties. Mental health should be an integral part of the periodic medical check-up objectives for defence and security forces throughout the country.

An extended social force model on unidirectional flow considering psychological and behavioral impacts of hazard source

An accurate assessment of the evacuation efficiency in case of disasters is of vital importance to the safety design of buildings and street blocks.Hazard sources not only physically but psychologically affect the pedestrians,which may further alter their behavioral patterns.This effect is especially significant in narrow spaces,such as corridors and alleys.This study aims to integrate a non-spreading hazard source into the social force model following the results from a previous experiment and simulation,and to simulate unidirectional pedestrian flows over various crowd densities and clarity–intensity properties of the hazard source.The integration include a virtual repulsion force from the hazard source and a decay on the social force term.The simulations reveal(i)that the hazard source creates virtual bottlenecks that suppress the flow,(ii)that the inter-pedestrian push forms a stabilisation phase on the flow-density curve within medium-to-high densities,and(iii)that the pedestrians are prone to a less orderly and stable pattern of movement in low clarity–intensity scenarios,possibly with lateral collisions passing the hazard source.

Review of Three-phase Soft Switching Inverters and Challenges for Motor Drives

For electric vehicles (EVs),it is necessary to improve endurance mileage by improving the efficiency.There exists a trend towards increasing the system voltage and switching frequency,contributing to improve charging speed and power density.However,this trend poses significant challenges for high-voltage and high-frequency motor controllers,which are plagued by increased switching losses and pronounced switching oscillations as consequences of hard switching.The deployment of soft switching technology presents a viable solution to mitigate these issues.This paper reviews the applications of soft switching technologies for three-phase inverters and classifies them based on distinct characteristics.For each type of inverter,the advantages and disadvantages are evaluated.Then,the paper introduces the research progress and control methods of soft switching inverters (SSIs).Moreover,it presents a comparative analysis among the conventional hard switching inverters (HSIs),an active clamping resonant DC link inverter (ACRDCLI) and an auxiliary resonant commuted pole inverter (ARCPI).Finally,the problems and prospects of soft switching technology applied to motor controllers for EVs are put forward.

Scheme of negative acoustic radiation force based on a multiple-layered spherical structure

Acoustic radiation force(ARF), as an important particle manipulation method, has been extensively studied in recent years. With the introduction of the concept of “acoustic tweezers”, negative acoustic radiation has become a research hotspot. In this paper, a scheme of realizing negative ARF based on the multiple-layered spherical structure design is proposed. The specific structure and design idea are presented. Detailed theoretical calculation analysis is carried out.Numerical simulations have been performed to verify the correctness of this prediction. The conjecture that the suppression of backscattering can achieve negative ARF is verified concretely, which greatly expands the application prospect and design ideas of the ARF. This work has laid a theoretical foundation for realizing precise control of the structure.

Dynamic-based model for calculating the boulder impact force in debris flow

The boulder impact force in debris flow is generally calculated by static methods such as the cantilever beam models.However,these methods cannot describe the dynamic scenario of boulder collision on structures,so the inertia and damping effects of the structures are not involved causing an overestimation on the boulder impact force.In order to address this issue,a dynamic-based model for calculating the boulder impact force of a debris flow was proposed in this study,and the dynamic characteristics of a cantilever beam with multiple degrees of freedom under boulder collision were investigated.By using the drop-weight method to simulate boulders within debris flow,seven experiments of drop-weight impacting the cantilever beam were used to calibrate the error of the dynamicbased model.Results indicate that the dynamic-based model is able to reconstruct the impact force history on the cantilever beam during impact time and the error of dynamic-based model is 15.3%in calculating boulder impact force,significantly outperforming the cantilever beam model’s error of 285%.Therefore,the dynamic-based model can overcome the drawbacks of the static-based models and provide a more reliable theoretical foundation for the engineering design of debris flow control structures.

Optimal Design of the Modular Joint Drive Train for Enhancing Cobot Load Capacity and Dynamic Performance

Automation advancements prompts the extensive integration of collaborative robot(cobot)across a range of industries.Compared to the commonly used design approach of increasing the payload-to-weight ratio of cobot to enhance load capacity,equal attention should be paid to the dynamic response characteristics of cobot during the design process to make the cobot more flexible.In this paper,a new method for designing the drive train parameters of cobot is proposed.Firstly,based on the analysis of factors influencing the load capacity and dynamic response characteristics,design criteria for both aspects are established for cobot with all optimization design criteria normalized within the design domain.Secondly,with the cobot in the horizontal pose,the motor design scheme is discretized and it takes the joint motor diameter and gearbox speed ratio as optimization design variables.Finally,all the discrete values of the optimization objectives are obtained through the enumeration method and the Pareto front is used to select the optimal solution through multi-objective optimization.Base on the cobot design method proposed in this paper,a six-axis cobot is designed and compared with the commercial cobot.The result shows that the load capacity of the designed cobot in this paper reaches 8.4 kg,surpassing the 5 kg load capacity commercial cobot which is used as a benchmark.The minimum resonance frequency of the joints is 42.70 Hz.