Stopping Position Research Articles

Imaging for ion beam therapy: current trends and future perspectives

PurposeSince the pioneering use of planar X-ray imaging in early experimental sites of proton and light ion cancer therapy, imaging has always been a cornerstone of ion beam therapy (IBT). This contribution highlights current trends and future perspectives of imaging in modern IBT.MethodsSeveral flavours of image guidance are under investigation to enhance IBT. A first class of in-room imaging techniques aims at providing insights on updated patient anatomy prior to or ideally during treatment. Owing to the unique characteristics of IBT, these methods do not only target a correct localization of the tumour and critical structures as in photon therapy, but also aim at extracting the tissue stopping properties for accurate (re)planning. A second class of techniques, predominantly performed during beam delivery, aims at capturing different secondary emissions induced by the irradiation to identify the beam stopping position and ideally reconstruct the dose delivery for inter- or intra-fractional treatment adaptation. Finally, a third class of imaging techniques is being explored to provide novel insights on the underlying biological mechanisms to open new opportunities for more effective and better tolerated treatments.Results and conclusions70 years after the worldwide first proton treatment, image guidance of IBT continues to be an evolving area which combines advanced instrumentation with progress in computational areas, including artificial intelligence, and beam delivery schemes. Especially on-site imaging opens new opportunities to innovate the IBT chain with daily treatment adaptation, real-time verification of in-vivo range and dose delivery along with biological guidance for treatment personalization.

A flexible train composition strategy with extra-long trains for high-speed railway corridors with time-varying demand

To accommodate the uneven spatio-temporal distribution of passenger demand and improve the maximum transportation capacity for high-speed railway (HSR) corridors, this study proposes a demand-oriented flexible train composition strategy. The proposed strategy allows flexibility in selecting the number of train composition units (e.g., train carriages) for each train to accommodate the demand variations, where extra-long trains (longer than the length of the train station platform) might be utilized. Under such a strategy, a seat allocation method coupled with a train stopping position control strategy is proposed to avoid the need for cross-carriage walking during passenger boarding or alighting (for those extra-long trains). The train stopping position control strategy specifies the carriages that dock at or extend beyond the station platform, while the seat allocation method allocates seats within each carriage to specific origin-destination pairs. The studied problem can be formulated as an integer nonlinear programming model, where the weighted sum of the HSR operating cost and passenger travel time cost is minimized. The proposed model is then reformulated into an integer linear programming model via a series of linearization techniques. A tailored heuristic algorithm based on the variable neighborhood search (VNS) and GUROBI solver is designed to produce high-quality solutions for large-scale problems. Two numerical examples, i.e., a small example and a real-world Shanghai-Hangzhou HSR line example, are presented to illustrate the effectiveness of the proposed approach. The computation results show that, in comparison to traditional fixed and flexible train composition strategies without extra-long trains, the proposed strategy can significantly reduce the total operating cost and total travel time cost.

Research on the Prediction Method of Braking Rotation Angle for Remote-Controlled Excavator.

To calculate, analyze, and predict the rotation angle during the deceleration and braking process of large remote-controlled excavators, this article established a spatial coordinate system based on a simplified model of a hydraulic excavator's upper structure. Using the D-H parameter method, a mathematical model of the working device's center of gravity and its rotational inertia was established. Based on the characteristics of the excavator's hydraulic system and the relationship between brake torque variations, a prediction model was developed to forecast the stopping position (brake rotary angle) of the excavator's bucket after braking. Subsequently, the predicted results were validated using simulation and compared with existing experimental data to assess the accuracy of the model. The findings demonstrate that the predictive model exhibited high precision with minimal error. The utilization of this model enabled effective forecasting of the excavator's braking position changes, providing a theoretical foundation for the intelligent remote control of excavators.

Trapez Hız Profilinin Ayarlanması Yoluyla Hareketli Bir Kütle Altındaki Kirişin Titreşim Kontrolü

In this article, the residual vibration of a simply supported beam with a moving mass is studied. The mass moves from a starting point to an end point on the beam with a trapezoidal velocity profile having accelerating, constant velocity and decelerating time intervals. The residual vibration of the mid-point of the beam after the mass stops is analyzed. The mathematical model of the system is developed using the finite element (FE) theory. Newmark method is used for the solution of FE model having time dependent matrices because of the moving mass. The model is verified by comparing the solution results with the results given in the previous studies in the literature. It is seen that the relationship between the natural frequency of the system and the velocity profile of the moving mass has an effect on the residual vibration of the structure. If the natural frequency of the system and the inverse of the deceleration time interval of the moving mass are equal while the moving mass is at the stopping position, residual vibrations occur at a minimum level. It seen that with the right speed profile selection, the decrease in vibration levels approaches 70% during the movement and 80% after stopping.

Intelligent train stopping control for railways: A deep learning approach

AbstractStation parking accuracy is an important indicator for the automatic control of high‐speed trains; however, it is subject to many influencing factors, such as the characteristics of high nonlinearity and large time delays in the train control model, time‐variant humidity, and uncertain weather conditions, leading to unsatisfying performance with existing feedback control algorithms. This study first proposes an intelligent train stopping control approach based on deep learning for high‐speed railways. By collecting a large amount of historical train operation data from the Beijing–Shenyang high‐speed railway, three data‐driven models are developed for train stopping control. The first model is based on a deep‐layered feedforward neural network (DNN), which predicts the exact train stopping position with dynamic train running states (position, velocity etc.) as input. Taking advantage of the physical train control models used in practice, the DNN to a convolutional neural network (CNN) is then improved by customizing the convolutional layers of the CNN. To overcome the issues arising from the incompleteness of data samples, a few‐shot convolutional neural network (FSCNN) is further developed to enhance the prediction performance of the CNN. Compared with that of the current method used in practice, the simulation experiments show that the train station parking error can be decreased by 38.6%, 42.8%, and 49.2% by our developed DNN, CNN, and FSCNN, respectively.

On the robustness of multilateration of ionoacoustic signals for localization of the Bragg peak at pre-clinical proton beam energies in water

Objectives. The energy deposited in a medium by a pulsed proton beam results in the emission of thermoacoustic waves, also called ionoacoustics (IA). The proton beam stopping position (Bragg peak) can be retrieved from a time-of-flight analysis (ToF) of IA signals acquired at different sensor locations (multilateration). This work aimed to assess the robustness of multilateration methods in proton beams at pre-clinical energies for the development of a small animal irradiator. Approach. The accuracy of multilateration performed using different algorithms; namely, time of arrival and time difference of arrival, was investigated in-silico for ideal point sources in the presence of realistic uncertainties on the ToF estimation and ionoacoustic signals generated by a 20 MeV pulsed proton beam stopped in a homogeneous water phantom. The localisation accuracy was further investigated experimentally based on two different measurements with pulsed monoenergetic proton beams at energies of 20 and 22 MeV. Main results. It was found that the localisation accuracy mainly depends on the position of the acoustic detectors relative to the proton beam due to spatial variation of the error on the ToF estimation. By optimally positioning the sensors to reduce the ToF error, the Bragg peak could be located in-silico with an accuracy better than 90 μm (2% error). Localisation errors going up to 1 mm were observed experimentally due to inaccurate knowledge of the sensor positions and noisy ionoacoustic signals. Significance. This study gives a first overview of the implementation of different multilateration methods for ionoacoustics-based Bragg peak localisation in two- and three-dimensions at pre-clinical energies. Different sources of uncertainty were investigated, and their impact on the localisation accuracy was quantified in-silico and experimentally.

Study on Amplification Effect of Wind Turbine Blade Stopping Position on Vortex Induced Vibration of Tower

This project takes XX unit as the analysis object to study the first-order vibration wind speed of wind turbine under shutdown vibration. The vortex-induced vibration response is calculated and the displacement under resonant wind speed is calculated by fluid-solid coupling method. The above analysis techniques and methods are forward-looking and advanced in vibration characteristics of domestic wind turbines. On the basis of fluid dynamics analysis, the suppression measures are studied emphatically. Through the optimization and comparison of different inhibition schemes, the effect of inhibition measures was quantitatively analyzed. The analysis shows that the vibration characteristics of wind turbine with high flexible tower has its own particularity. The first order vibration probability and vibration displacement can be effectively reduced by pneumatic method and external measures.

Automatic Deceleration and Braking Research for Driverless Vehicles in Rail Transit based on Internet of Vehicles

With the development of vehicle networking, driverless technology has also seen great progress. In this paper, we mainly study the automatic deceleration and braking method of driverless vehicles in rail transportation. Firstly, Radio Frequency Identification (RFID) technology was briefly introduced. Then, based on RFID, a graded deceleration and braking scheme was designed to position driverless trains through RFID and control the deceleration of vehicles when they reach different subintervals, so that the speed of the vehicles was 0 when they reached the stopping point. The experimental results showed that the reading distance of the system met the requirements of practical use even when the transmitting frequency was small. In the simulation experiment, the system operated stably and the errors of actual speed and the target speed between different sub-intervals were small, which ensured that the vehicle stopped precisely at the stopping position. The experimental results verify that the proposed method is effective. The method can be further promoted and applied in practice.

Study on Stability and Control of Surrounding Rock in the Stopping Space with Fully Mechanized Top Coal Caving under Goaf

Under the condition of fully mechanized top coal caving in close-distance coal seams, the surrounding rock of the stopping space easily loses stability during the withdrawal of mining equipment in the working face because the lower coal seam working face is located under the goaf and the overburden rock has a large range of complex interaction. Field investigation, theoretical analysis, laboratory experiment, similar simulation experiment, numerical simulation, and field industrial tests are used to carry out the research on the stability and control of the surrounding rock in the large section stopping space under the goaf in this paper. The research conclusions are as follows. (1) It is determined that the lower coal seam working face can only stop mining under the goaf, and the reasonable stopping position under the goaf should ensure that the key block fracture line of the main roof is behind the support. (2) The interaction law between the main roof’s key blocks of the upper and lower coal seams is analyzed, and the catastrophic conditions for sliding instability and rotary instability of the main roof’s key blocks of the upper and lower coal seams are obtained. (3) “Anchorage with push and pull equipment-Embedded anchorages and trays” integral anchoring technology is developed. The dimensions of the push and pull equipment are determined. (4) Through numerical simulation of the distribution characteristics of the anchor cable pre-stress field, the asymmetric control scheme of “Partition long and short anchor cables + Integral polyurethane mesh + Embedded anchorages and trays for roof protection” is determined. The rock pressure observation shows that the withdrawal of the working face equipment is implemented safely.

Robust treatment planning in scanned carbon-ion radiotherapy for pancreatic cancer: Clinical verification using in-room computed tomography images.

PurposeCarbon-ion beam (C-beam) has a sharp dose distribution called the Bragg peak. Carbon-ion radiation therapy, such as stereotactic body radiotherapy in photon radiotherapy, can be completed in a short period by concentrating the radiation dose on the tumor while minimizing the dose to organs at-risk. However, the stopping position of C-beam is sensitive to density variations along the beam path and such variations can lower the tumor dose as well as cause the delivery of an unexpectedly high dose to the organs at risk. We evaluated the clinical efficacy of a robust planning technique considering gastrointestinal gas (G-gas) to deliver accurate radiation doses in carbon-ion radiotherapy for pancreatic cancer.Materials and methodsWe focused on the computed tomography (CT) value replacement method. Replacement signifies the overwriting of CT values in the CT images. The most effective replacement method for robust treatment planning was determined by verifying the effects of the three replacement patterns. We selected 10 consecutive patients. Pattern 1 replaces the CT value of the G-gas contours with the value of the region without G-gas (P1). This condition indicates a no-gas state. Pattern 2 replaces each gastrointestinal contour using the mean CT value of each contour (P2). The effect of G-gas was included in the replacement value. Pattern 3 indicates no replacement (P3). We analyzed variations in the target coverage (TC) and homogeneity index (HI) from the initial plan using in-room CT images. We then performed correlation analysis on the variations in G-gas, TC, and HI to evaluate the robustness against G-gas.ResultsAnalysis of variations in TC and HI revealed a significant difference between P1 and P3 and between P2 and P3. Although no statistically significant difference was observed between P1 and P2, variations, including the median, tended to be fewer in P2. The correlation analyses for G-gas, TC, and HI showed that P2 was less likely to be affected by G-gas.ConclusionFor a treatment plan that is robust to G-gas, P2 mean replacement method should be used. This method does not necessitate any particular software or equipment, and is convenient to implement in clinical practice.

Microfeature Segmentation Algorithm for Biological Images Using Improved Density Peak Clustering.

To address the problem of low precision in feature segmentation of biological images with large noise, a microfeature segmentation algorithm for biological images using improved density peak clustering was proposed. First, the center pixel and edge information of a biological image were obtained to remove some redundant information. The three-dimensional space of the image is constructed, and the coordinate system is used to describe every superpixel of the biological image. Second, the image symmetry and reversibility are used to obtain the stopping position of pixels, other adjacent points are used to obtain the current color and shape information, and more vectors are used to express the density to complete the image pretreatment. Finally, the improved density peak clustering method is used to cluster the image, and the pixels completed by clustering and the remaining pixels are evenly distributed into the space to segment the image so as to complete the microfeature segmentation of the biological image based on the improved density peak clustering method. The results show that the proposed algorithm improves the segmentation efficiency, segmentation integrity rate, and segmentation accuracy. The time consumed by the proposed biological image microfeature segmentation algorithm is always less than 2 minutes, and the segmentation integrity rate can reach more than 90%. Furthermore, the proposed algorithm can reduce the missing condition and the noise of the segmented image and improve the image feature segmentation effect.

Stopping Position Matters: Drawing A Better Communication between Pedestrian and Driverless Automated Vehicles on Narrow Roads

Automated vehicles (AVs) are expected to be used as mobility services for improving the quality of life in aging rural areas. In this study, we investigated problematic cases of interaction between pedestrians and AVs in Japanese rural areas and observed cases that occurred on narrow roads. To explore a better communication method when pedestrians interact with vehicles, a virtual reality experiment examined the impacts of two communication methods (external human-machine interface and vehicle movement) regarding two types of vehicles (golf cart and bus). The results showed that pedestrians could decide on crossing the road quickly when the AV attempted to reduce speed early and stopped maintaining an appropriate distance from pedestrians. The stopping position is an important contributor to pedestrian decision-making in crossing and attitude toward AVs. The findings of this study have implications for the design of future automated service vehicles in rural areas.

Evaluation of displacement damage in solids induced by fast positrons: Modeling and effect on vacancy measurement

• The latest theoretical models of radiation damage in solid and numerical results of Mott differential cross section were used; • Displacement cross section by positrons for elements in most commonly used solids was calculated and the difference between positron and electron radiation was emphasized; • Displacement thresholds of kinetic energy for positrons in 30 elemental solids were presented; • Defects spatial distribution was obtained using Monte Carlo modeling. Positron Annihilation Technique is very sensitive to vacancy defects and small vacancy clusters and has been used as supplementary for TEM in radiation damage research. In this paper, we evaluated the displacement damage in solids induced by positrons and its effect on defects measurement, which has not been considered carefully in most PAT application. Displacement damage could only be produced when kinetic energy of positron exceeds a threshold determined by average displacement energy and the mass of atoms. Based on the latest models of displacement damage and numerical Mott elastic differential cross section of positrons interacting with atoms, displacement cross section for fast positron in solids was calculated and compared with that for electrons. In the energy range from 1 MeV to 100 MeV, electrons will produce more displacement defects than positrons do, especially in high-Z materials. Number of total defects depends on the primary displacement cross section and the size of damage cascades. To get distributions of defects and terminating position of positrons in materials, a Monte Carlo tool with full damage model was developed and validated. From the results of Monte Carlo modeling, the defects -generated by mono-energy positron beam have shallower distribution than the stopping position of positrons, indicating separation of defects and positrons and this fact benefits defects measurement because displacement damage produced by fast probing positron beam have little affection on the measurement. But for the positron beams from radioactive sources (such as 22 Na and 64 Cu) with continuous energy spectrum (from 0 to E max ), the depth profile of defects and terminated position of positrons overlap with each other and this fact indicated that defects measurement in materials will be affected by extra defects produced by positrons. The density of defects produced by positron beam is quite low with a typical value of about 0.01–0.1 cm −3 per positron in low-Z materials, which could be comparable with the defect density limitation if enough accumulated positrons are implanted into materials during measurement. For commonly used structural metals (such as Fe, Mn, Cu and metals with Z number higher than 40), using positron from 22 N and 64 Cu directly to measure defects density is quite safe because the energy is smaller than the displacement threshold.

Influence of relative humidity and air temperature on the stopping position of the automatic tool changer in a CNC machine when using a pneumatic cylinder

The automatic tool changer (ATC) in computerized numerical control (CNC) milling machine often uses pneumatic dynamic sources. Friction in the pneumatic cylinder affects the ATC’s stopping position; this friction depends on many factors, including the air environment’s relative humidity and temperature. This paper presents the results of research on the effects of relative humidity (RH) and air temperature (T) on the stopping position of an ATC using a pneumatic cylinder. Studies were conducted at temperatures of [Formula: see text]C, [Formula: see text]C and [Formula: see text]C and relative humidity values of 51%, 75% and 99% for different speeds of the pneumatic cylinder (30, 50 and 100 mm/s). The results show that when the humidity increases from 51% to 99% and the temperature increases from [Formula: see text]C to [Formula: see text]C, the friction force decreases. The friction force is related to the relative humidity and temperature of the air. Thus, the deviation of the ATC’s stopping position depends on the relative humidity and temperature of the area under investigation.

Slip Estimation and Compensation Control of Omnidirectional Wheeled Automated Guided Vehicle

To achieve Industry 4.0 solutions for the networking of mechatronic components in production plants, the use of Internet of Things (IoT) technology is the optimal way for goods transportation in the cyber-physical system (CPS). As a result, automated guided vehicles (AGVs) are networked to all other participants in the production system to accept and execute transport jobs. Accurately tracking the planned paths of AGVs is therefore essential. The omnidirectional mobile vehicle has shown its excellent characteristics in crowded environments and narrow aisle spaces. However, the slip problem of the omnidirectional mobile vehicle is more serious than that of the general wheeled mobile vehicle. This paper proposes a slip estimation and compensation control method for an omnidirectional Mecanum-wheeled automated guided vehicle (OMWAGV) and implements a control system. Based on the slip estimation and compensation control of the general wheeled mobile platform, a Microchip dsPIC30F6010A microcontroller-based system uses an MPU-9250 multi-axis accelerometer sensor to derive the longitudinal speed, transverse speed, and steering angle of the omnidirectional wheel platform. These data are then compared with those from the motor encoders. A linear regression with a recursive least squares (RLS) method is utilized to estimate real-time slip ratio variations of four driving wheels and conduct the corresponding compensation and control. As a result, the driving speeds of the four omnidirectional wheels are dynamically adjusted so that the OMWAGV can accurately follow the predetermined motion trajectory. The experimental results of diagonally moving and cross-walking motions without and with slip estimation and compensation control showed that, without calculating the errors occurred during travel, the distances between the original starting position to the stopping position are dramatically reduced from 1.52 m to 0.03 m and from 1.56 m to 0.03 m, respectively. The higher tracking accuracy of the proposed method verifies its effectiveness and validness.

Design and Position Control of Overhang-Type Rail Mover Using Dual BLAC Motor

This paper presents the design and position control scheme of an overhang-type rail mover system driven by a dual Brushless AC (BLAC) motor with a simple Hall position sensor inside each motor. The overhang-type roller is chosen to reduce the slip between the roller and rail surface due to gravity. The BLAC motors are used to provide smooth translation along the rail and effective turning. Imbalances on any part of the motor and the simplicity of the Hall position sensor can create additional disturbance load, unsteady movement, and position errors. To reduce the sudden moving position error between the two motors, a balancing compensator with a Proportional-Differential (PD) position controller, which is based on the instantaneous speed and position trajectories, is presented. Furthermore, speed and position reference models are designed to compensate for the low Hall sensor resolution in the low-speed range. Therefore, steady-state position errors can then be regulated simply by using the instantaneous speed and position information. Experiments were performed to verify the viability of the proposed system and control. The results show a significant improvement in roller translation along the rail and stopping position accuracy.

Analysis of Rockfall Hazards Stopping position and Energy dissipation Based on Orthogonal experiment

Many factors affect the movement of rockfall. Thus, this study explored the influence of rockfall shape, slope angle, angular velocity, slope hardness, rockfall mass, and slope surface roughness on the stopping position and potential energy loss rate based on an orthogonal experiment. To study the key factors affecting the movement of rockfall, 2500 sets of orthogonal tests were carried out by using ROCFALL 8.0 (ROCSCIENCE) numerical simulation program. SPSS19.0 software was used to perform importance analysis and correlation analysis on the test results. The analysis results show that rockfall shape has the greatest influence on the stopping distance. There is a significant positive linear correlation between the number of rockfall edges and the stopping distance of rockfall on the asphalt road. The slope angle has the greatest influence on the potential energy loss rate, and there is a significant negative linear correlation between the slope angle and the potential energy loss rate. In the case of a low angle slope, the stopping position of rockfall is more concentrated. Therefore, in the process of mountain engineering construction, more attention should be paid to the influence of rockfall shape and slope angle on rockfall hazard protection.

Speed Profile Tracking by an Adaptive Controller for Subway Train Based on Neural Network and PID Algorithm

Train running performance largely depends on the controller. In order to improve the controller performance of speed profile tracking, an adaptive control method for subway trains is addressed in this paper. Considered time-varying parameters of train motion, the train model with dynamic parameters is constructed. The model free adaptive controller combined with neural network and proportional-integral-derivative (PID) algorithm is proposed to realize adaptive control. The control laws and parameter tuning laws of the proposed controller are both illustrated, and PID gain range and actuator saturation are taken into consideration. Compared with other controllers, numerical tests are provided to verify the effectiveness and stability of the proposed controller. The controller is also applied on a real line, and the results show that the proposed controller outperforms the currently used controller. More specifically, the proposed controller reduces average absolute running time error by 0.67 s, average absolute stopping position error by 0.09 m, average maximum absolute speed tracking error by 1.22 m/s, and total energy consumption by 2.73 kWh.

Optimal Terminal Iterative Learning Control for the Parking Control System of Maglev Train

This paper analyzes the parking process of maglev trains, establishes the corresponding mathematical model, based on the method of terminal iterative learning control(TILC), uses the stopping position error in the previous braking process to update the current control curve. In this paper, we select the initial braking position, initial speed or braking force or a combination thereof as the control input, and formulate the corresponding learning law. Finally, a line is simulated, and the traditional TILC method and the optimal TILC method are compared through simulation experiments, which verify that the latter has a faster convergence speed.

Influence of momentum acceptance on range monitoring of 11C and 15O ion beams using in-beam PET

In heavy-ion therapy, the stopping position of primary ions in tumours needs to be monitored for effective treatment and to prevent overdose exposure to normal tissues. Positron-emitting ion beams, such as 11C and 15O, have been suggested for range verification in heavy-ion therapy using in-beam positron emission tomography (PET) imaging, which offers the capability of visualizing the ion stopping position with a high signal-to-noise ratio. We have previously demonstrated the feasibility of in-beam PET imaging for the range verification of 11C and 15O ion beams and observed a slight shift between the beam stopping position and the dose peak position in simulations, depending on the initial beam energy spread. In this study, we focused on the experimental confirmation of the shift between the Bragg peak position and the position of the maximum detected positron-emitting fragments via a PET system for positron-emitting ion beams of 11C (210 MeV u−1) and 15O (312 MeV u−1) with momentum acceptances of 5% and 0.5%. For this purpose, we measured the depth doses and performed in-beam PET imaging using a polymethyl methacrylate (PMMA) phantom for both beams with different momentum acceptances. The shifts between the Bragg peak position and the PET peak position in an irradiated PMMA phantom for the 15O ion beams were 1.8 mm and 0.3 mm for momentum acceptances of 5% and 0.5%, respectively. The shifts between the positions of two peaks for the 11C ion beam were 2.1 mm and 0.1 mm for momentum acceptances of 5% and 0.5%, respectively. We observed larger shifts between the Bragg peak and the PET peak positions for a momentum acceptance of 5% for both beams, which is consistent with the simulation results reported in our previous study. The biological doses were also estimated from the calculated relative biological effectiveness (RBE) values using a modified microdosimetric kinetic model (mMKM) and Monte Carlo simulation. Beams with a momentum acceptance of 5% should be used with caution for therapeutic applications to avoid extra dose to normal tissues beyond the tumour when the dose distal fall-off is located beyond the treatment volume.