Resistance of full-scale beams against close-in explosions.Numerical modeling and field tests

This paper explores the performances of a finite element simulation including four concrete models applied to a full-scale reinforced concrete beam subjected to blast loading. Field test data has been used to compare model results for each case. The numerical modelling has been, carried out using the suitable code LS-DYNA. This code integrates blast load routine(CONWEP) for the explosive description and four different material models for the concrete including: Karagozian & Case Concrete, Winfrith, Continuous Surface Cap Model and Riedel-Hiermaier-Thoma models, with concrete meshing based on 10, 15, and 20 mm. Six full-scale beams were tested: four of them used for the initial calibration of the numerical model and two more tests at lower scaled distances. For calibration, field data obtained employing pressure and accelerometers transducers were compared with the results derived from the numerical simulation. Damage surfaces and the shape of rupture in the beams have been used as references for comparison. Influence of the meshing on accelerations has been put in evidence and for some models the shape and size of the damage in the beams produced maximum differences around 15%. In all cases, the variations between material and mesh models are shown and discussed.

Numerical analysis of high‑speed railway slab tracks using calibrated and validated 3D time‑domain modelling

Concrete slabs are widely used in modern railways to increase the inherent resilient quality of the tracks,provide safe and smooth rides,and reduce the maintenance frequency.In this paper,the elastic performance of a novel slab trackform for high-speed railways is investigated using three-dimensional finite element modelling in Abaqus.It is then compared to the performance of a ballasted track.First,slab and ballasted track models are developed to replicate the full-scale testing of track sections.Once the models are calibrated with the experimental results,the novel slab model is developed and compared against the calibrated slab track results.The slab and ballasted track models are then extended to create linear dynamic models,considering the track geodynamics,and simulating train passages at various speeds,for which the Ledsgard documented case was used to validate the models.Trains travelling at low and high speeds are analysed to investigate the track deflections and the wave propagation in the soil,considering the issues associated with critical speeds.Various train loading methods are discussed,and the most practical approach is retained and described.Moreover,correlations are made between the geotechnical parameters of modern high-speed rail and conventional standards.It is found that considering the same ground condition,the slab track deflections are considerably smaller than those of the ballasted track at high speeds,while they show similar behaviour at low speeds.

A framework for dynamic modelling of railway track switches considering the switch blades,actuators and control systems

The main contribution of this paper is the development and demonstration of a novel methodology that can be followed to develop a simulation twin of a railway track switch system to test the functionality in a digital environment.This is important because,globally,railway track switches are used to allow trains to change routes;they are a key part of all railway networks.However,because track switches are single points of failure and safety-critical,their inability to operate correctly can cause significant delays and concomitant costs.In order to better understand the dynamic behaviour of switches during operation,this paper has developed a full simulation twin of a complete track switch system.The approach fuses finite element for the rail bending and motion,with physics-based models of the electromechanical actuator system and the control system.Hence,it provides researchers and engineers the opportunity to explore and understand the design space around the dynamic operation of new switches and switch machines before they are built.This is useful for looking at the modification or monitoring of existing switches,and it becomes even more important when new switch concepts are being considered and evaluated.The simulation is capable of running in real time or faster meaning designs can be iterated and checked interactively.The paper describes the modelling approach,demonstrates the methodology by developing the system model for a novel“REPOINT”switch system,and evaluates the system level performance against the dynamic performance requirements for the switch.In the context of that case study,it is found that the proposed new actuation system as designed can meet(and exceed)the system performance requirements,and that the fault tolerance built into the actuation ensures continued operation after a single actuator failure.

Multiple model PHD filter for tracking sharply maneuvering targets using recursive RANSAC based adaptive birth estimation

An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.

Research on Track Fastener Service Status Detection Based on Improved Yolov4 Model

As an important part of railway lines, the healthy service status of track fasteners was very important to ensure the safety of trains. The application of deep learning algorithms was becoming an important method to realize its state detection. However, there was often a deficiency that the detection accuracy and calculation speed of model were difficult to balance, when the traditional deep learning model is used to detect the service state of track fasteners. Targeting this issue, an improved Yolov4 model for detecting the service status of track fasteners was proposed. Firstly, the Mixup data augmentation technology was introduced into Yolov4 model to enhance the generalization ability of model. Secondly, the MobileNet-V2 lightweight network was employed in lieu of the CSPDarknet53 network as the backbone, thereby reducing the number of algorithm parameters and improving the model’s computational efficiency. Finally, the SE attention mechanism was incorporated to boost the importance of rail fastener identification by emphasizing relevant image features, ensuring that the network’s focus was primarily on the fasteners being inspected. The algorithm achieved both high precision and high speed operation of the rail fastener service state detection, while realizing the lightweight of model. The experimental results revealed that, the MAP value of the rail fastener service state detection algorithm based on the improved Yolov4 model reaches 83.2%, which is 2.83% higher than that of the traditional Yolov4 model, and the calculation speed was improved by 67.39%. Compared with the traditional Yolov4 model, the proposed method achieved the collaborative optimization of detection accuracy and calculation speed.

Stiffness Degradation Modeling for Composite Wind Turbine Blades Based on Full-Scale Fatigue Testing

In order to provide more insights into the damage propagation composite wind turbine blades(blade)under cyclic fatigue loading,a stiffness degradation model for blade is proposed based on the full-scale fatigue testing of a blade.A novel non-linear fatigue damage accumulation model is proposed using the damage assessment theories of composite laminates for the first time.Then,a stiffness degradation model is established based on the correlation of fatigue damage and residual stiffness of the composite laminates.Finally,a stiffness degradation model for the blade is presented based on the full-scale fatigue testing.The scientific rationale of the proposed stiffness model of blade is verified by using full-scale fatigue test data of blade with a total length of 52.5 m.The results indicate that the proposed stiffness degradation model of the blade agrees well with the fatigue testing results of this blade.This work provides a basis for evaluating the fatigue damage and lifetime of blade under cyclic fatigue loading.

Experimental investigations on small-and full-scale ship models with polyurea coatings subjected to underwater explosion

Nowadays, the mitigation of damage to a ship caused by the underwater explosion attracts more and more attention from the modern ship designers. In this study, two kinds of scale tests were conducted to investigate the effects of polyurea coatings on the blast resistance of hulls subjected to underwater explosion. Firstly, small-scale model tests with different polyurea coatings were carried out. Results indicate that polyurea has a better blast resistance performance when coated on the front face, which can effectively reduce the maximum deflection of the steel plate by more than 20% and reduce the deformation energy by 35.7%-45.4%. Next, a full-scale ship(approximately 50 m × 9 m) under loadings produced by the detonation of 33 kg of spherical TNT charges was tested, where a part of the ship was coated with polyurea on the front face(8 mm + 24 mm) and not on the contrast area. Damage characteristics on the bottom were statistically analyzed based on a 3D scanning technology, indicating that polyurea contributes to enhancing the blast protection of the ship. However, damage results of this test were different from those of the small-scale tests. Moreover, the deformation area of the bottom with polyurea was greatly increased by 40.1% to disperse explosion energy, a conclusion that cannot be drown from the small-scale tests.

Full-scale multi-functional test platform for investigating mechanical performance of track–subgrade systems of high-speed railways

Motivated by the huge practical engineering demand for the fundamental understanding of mechanical characteristics of high-speed railway infrastructure,a fullscale multi-functional test platform for high-speed railway track–subgrade system is developed in this paper,and its main functions for investigating the mechanical performance of track–subgrade systems are elaborated with three typical experimental examples.Comprising the full-scale subgrade structure and all the five types of track structures adopted in Chinese high-speed railways,namely the CRTS I,the CRTS II and the CRTS III ballastless tracks,the double-block ballastless track and the ballasted track,the test platform is established strictly according to the construction standard of Chinese high-speed railways.Three kinds of effective loading methods are employed,including the real bogie loading,multi-point loading and the impact loading.Various types of sensors are adopted in different components of the five types of track–subgrade systems to measure the displacement,acceleration,pressure,structural strain and deformation,etc.Utilizing this test platform,both dynamic characteristics and long-term performance evolution of high-speed railway track–subgrade systems can be investigated,being able to satisfy the actual demand for large-scale operation of Chinese high-speed railways.As examples,three typical experimental studies are presented to elucidate the comprehensive functionalities of the full-scale multi-functional test platform for exploring the dynamic performance and its long-term evolution of ballastless track systems and for studying the long-term accumulative settlement of the ballasted track–subgrade system in high-speed railways.Some interesting phenomena and meaningful results are captured by the developed test platform,which provide a useful guidance for the scientific operation and maintenance of high-speed railway infrastructure.

Segmentation Based Real Time Anomaly Detection and Tracking Model for Pedestrian Walkways

Presently,video surveillance is commonly employed to ensure security in public places such as traffic signals,malls,railway stations,etc.A major chal-lenge in video surveillance is the identification of anomalies that exist in it such as crimes,thefts,and so on.Besides,the anomaly detection in pedestrian walkways has gained significant attention among the computer vision communities to enhance pedestrian safety.The recent advances of Deep Learning(DL)models have received considerable attention in different processes such as object detec-tion,image classification,etc.In this aspect,this article designs a new Panoptic Feature Pyramid Network based Anomaly Detection and Tracking(PFPN-ADT)model for pedestrian walkways.The proposed model majorly aims to the recognition and classification of different anomalies present in the pedestrian walkway like vehicles,skaters,etc.The proposed model involves panoptic seg-mentation model,called Panoptic Feature Pyramid Network(PFPN)is employed for the object recognition process.For object classification,Compact Bat Algo-rithm(CBA)with Stacked Auto Encoder(SAE)is applied for the classification of recognized objects.For ensuring the enhanced results better anomaly detection performance of the PFPN-ADT technique,a comparison study is made using Uni-versity of California San Diego(UCSD)Anomaly data and other benchmark data-sets(such as Cityscapes,ADE20K,COCO),and the outcomes are compared with the Mask Recurrent Convolutional Neural Network(RCNN)and Faster Convolu-tional Neural Network(CNN)models.The simulation outcome demonstrated the enhanced performance of the PFPN-ADT technique over the other methods.

Behaviour of non-ballast pre-stressed and precast track structures in high speed railway based on multiscale finite element model

In order to make further study on the mechanical property of CRTSIII type slab non-ballast track structures,which was self-designed in China,based on the method of the multiscale finite element model(FEM),the traditional FEM of slab non-ballast track structures was improved.The multiscale FEM of CRTSII type slab nonballast track structures was established based on the general finite element program ABAQUs.Then the comparative calculation was made between various FEMs,showing that the high solution precision,fast modelling speed and high solution efficiency could be obtained.Therefore,the multiscale FEM was suitable for the parametric study on mechanical behaviour of CRTSII type slab non-ballast track structures,and then the key influence factor and constructions could be optimized.

A Non-geometrically Similar Model for Predicting the Wake Field of Full-scale Ships

The scale effect leads to large discrepancies between the wake fields of model-scale and actual ships, and causes differences in cavitation performance and exciting forces tests in predicting the performance of actual ships. Therefore, when test data from ship models are directly applied to predict the performance of actual ships, test results must be subjected to empirical corrections. This study proposes a method for the reverse design of the hull model. Compared to a geometrically similar hull model, the wake field generated by the modified model is closer to that of an actual ship. A non-geometrically similar model of a Korean Research Institute of Ship and Ocean Engineering （KRISO）’s container ship （KCS） was designed. Numerical simulations were performed using this model, and its results were compared with full-scale calculation results. The deformation method of getting the wake field of full-scale ships by the non-geometrically similar model is applied to the KCS successfully.

Numerical Prediction of Ride Comfort of Tracked Vehicle Equipped with Novel Flexible Road Wheels

Enhancing ride comfort has always constituted a crucial focus in the design and research of modern tracked vehicles,heavily reliant on the driving system's performance.While the road wheel is a key component of the driving system,traditional road wheels predominantly adopt a solid structure,exhibiting subpar adhesion performance and damping effects,thereby falling short of meeting the demands for high-speed,stable,and long-distance driving in tracked vehicles.Addressing this issue,this paper proposes a novel type of flexible road wheel(FRW)characterized by a catenary construction.The study investigates the ride comfort of tracked vehicles equipped with flexible road wheels by integrating finite element and vehicle dynamic.First,three-dimensional(3D)finite element(FE)models of both flexible and rigid road wheels are established,considering material and contact nonlinearities.These models are validated through a wheel radial loading test.Based on the validated FE model,the paper uncovers the relationship between load and radial deformation of the road wheel,forming the basis for a nonlinear mathematical model.Subsequently,a half-car model of a tracked vehicle with seven degrees of freedom is established using Newton's second law.A random road model,considering the track effect and employing white noise,is constructed.The study concludes by examining the ride comfort of tracked vehicles equipped with flexible and rigid road wheels under various speeds and road grades.The results demonstrate that,in comparison to the rigid road wheel(RRW),the flexible road wheel enhances the ride comfort of tracked vehicles on randomly uneven roads.This research provides a theoretical foundation for the implementation of flexible road wheels in tracked vehicles.

Path Tracking Controller Design of Automated Parking Systems via NMPC with an Instructible Solution

Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.

Full-scale Water Modeling on Flow Field of Continuous Casting Mold

In the continuous casting process of aluminum killed steel grades,nozzle clogging is a common problem.Argon is usually injected into the casting channel through stoppers or nozzles to minimize clogs;however,complex two-phase flow regimes appear,and the flow in the mold might deteriorate.This could result in a higher defect rate in the cast product and should be avoided as much as possible.Therefore,it is important to understand the interaction between process conditions and the refractory products used and their impact on the flow pattern in the mold.In this study,a full-scale water model was established to simulate the slab casting process.Three nozzle shapes and three immersion depths were applied to investigate the flow behavior and liquid level fluctuations by the full-scale water model.The relationship between the flow behavior and continuous casting parameters was evaluated.The results provide guidance for the design and production of the refractory nozzle and the operation of the continuous casting plant.

Full-scale model tests and nonlinear analysis of prestressed concrete simply supported box girders

Full-scale model tests were carried out on a 30 m span prestressed concrete box girder and a 20 m span prestressed concrete hollow slab. Failure models were prestressed reinforcement tensile failure and crashing of roof concrete, respectively. The ductility indexes of the box girder and hollow slab were 1.99 and 1.23, respectively, according to the energy viewpoint. Based on the horizontal section hypothesis, the nonlinear computation procedure was established using the limited banding law, and it could carry out the entire performance analysis including the unloading, mainly focusing on the ways to achieve the unloading curves computation through stress-strain, moment-curvature and load-displacement curves. Through the procedure, parameters that influence on the bearing capacity, deformation performance and ductility of the structures were analyzed. Those parameters were quantity of prestressed reinforcement and tension coefficients of prestressed reinforcement. From the analysis, some useful conclusions can be obtained.

基于DF-Track的水下鱼体跟踪方法

鱼类跟踪是分析鱼类行为、评估其健康水平的关键步骤。然而,由于真实水下养殖鱼群具有运动非线性、高外观相似度、鱼体互相遮挡、特征信息损失严重等特点,多目标跟踪鱼类是一项非常具有挑战性的任务。针对水下鱼体反射产生的伪影以及鱼体运动非线性、相互遮挡导致跟踪轨迹碎片化的问题,提出一种水下多鱼跟踪模型DF-Track。该模型采用基于检测的跟踪(TBD)范式,首先在YOLOv8的C2f结构中引入聚合感知注意力机制(APFA),提高在前向过程中提取图像特征的能力;然后使用SDI多层次特征融合模块对YOLOv8中的feature fusion部分进行重设计,减少特征融合阶段不同层级特征信息的冲突问题;最后提出一种优化轨迹管理的跟踪模型DF-Track,并引入Focal-EIoU补偿匹配空间中的运动估计偏差,平衡几何一致性。实验结果表明:与原YOLOv8相比,所提算法的精确率提高了1.7%,平均精度均值提高了2.1%;DF-Track与其他MOT跟踪算法相比,HOTA达到70.9%,MOTA达到91.9%,IDF1达到80.4%。证明DF-Track模型在水下鱼类跟踪任务中具有较好的性能。

An Effective Multiple Model Least Squares Method in Tracking of a Maneuvering Target

A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.

Mean shift algorithm based on fusion model for head tracking

To solve the mismatch between the candidate model and the reference model caused by the time change of the tracked head, a novel mean shift algorithm based on a fusion model is provided. A fusion model is employed to describe the tracked head by sampling the models of the fore-head and the back-head under different situations. Thus the fusion head reference model is represented by the color distribution estimated from both the fore- head and the back-head. The proposed tracking system is efficient and it is easy to realize the goal of continual tracking of the head by using the fusion model. The results show that the new tracker is robust up to a 360°rotation of the head on a cluttered background and the tracking precision is improved.

Maneuvering target tracking using threshold interacting multiple model algorithm

To avoid missing track caused by the target maneuvers in automatic target tracking system, a new maneuvering target tracking technique called threshold interacting multiple model （TIMM） is proposed. This algorithm is based on the interacting multiple model （IMM） method and applies a threshold controller to improve tracking accuracy. It is also applicable to other advanced algorithms of IMM. In this research, we also compare the position and velocity root mean square （RMS） errors of TIMM and IMM algorithms with two different examples. Simulation results show that the TIMM algorithm is superior to the traditional IMM alzorithm in estimation accuracy.

Target Tracking Using the Interactive Multiple Model Method

Aim To develop a practical target tracking algorithm for different motion modes. Methods After creation of the new model, it was implemented by computer simulation to prove its performance and compared with the often-used current statistical model. Results The simulation results show that the new IMM (interactive multiple model) have low tracking error in both maneuVering segment and non^Inaneuwi segment while the current statistical model bas muCh higher tracking error in non-maneuvering segment. Conclusion In the point of trackintaccuracy, the new IMM method is much better than the current acceleration method. It can develop into a practical target hacking method.