Steep Downhill Research Articles

Analysis of the influence of brake pipe pressure gradient on heavy haul combined train and optimisation of operation strategy

In this paper, based on the theory of gas flow, the action logic of the control valve, and the principle of multi-rigid-body dynamics, a simulation model of the 20,000 t heavy haul combined train is established to investigate the influence of brake pipe pressure gradient on the braking performance, longitudinal dynamics, braking and release characteristics of trains. Utilizing real railway line conditions, locomotive and vehicle parameters, and train operation monitoring equipment (LKJ) record data of Shuozhou-Huanghua Railway, the cyclic braking condition of the train on the long and steep downhill is simulated, and the control strategy of reducing the coupler force during the cyclic braking is proposed. The results indicate that a larger brake pipe pressure gradient before braking leads to weaker braking capability, and higher coupler forces during braking, but smaller coupler forces during release. As the brake pipe pressure gradient before braking increases, braking synchronicity decreases, while release synchronicity slightly improves. By adjusting the locomotive’s electric braking force during the cyclic braking, it is possible to appropriately increase the brake pipe pressure gradient before braking, effectively reducing coupler forces during release and reducing the number of braking cycles, thus lowering the operational difficulty of the train.

Train wheel-rail force collaborative calibration based on GNN-LSTM

Accurate wheel-rail force data serves as the cornerstone for analyzing the wheel-rail relationship. However, achieving continuous and precise measurement of this force remains a significant challenge in the field. This article introduces a calibration algorithm for the wheel-rail force that leverages graph neural networks and long short-term memory networks. Initially, a comprehensive wheel-rail force detection system for trains was constructed, encompassing two key components: an instrumented wheelset and a ground wheel-rail force measuring system. Subsequently, utilizing this system, two distinct datasets were acquired from the track inspection vehicle: instrumented wheelset data and ground wheel-rail force data, a feedforward neural network was employed to calibrate the instrumented wheelset data, referencing the ground wheel-rail force data. Furthermore, ground wheel-rail force data for the locomotive was obtained for the corresponding road section. This data was then integrated with the calibrated instrumented wheelset data from the track inspection vehicle. Leveraging the GNN-LSTM network, the article establishes a mapping relationship model between the wheel-rail force of the track inspection vehicle and the locomotive wheel-rail force. This model facilitates continuous measurement of locomotive wheel-rail forces across three typical scenarios: straight sections, long and steep downhill sections, and small curve radius sections.

Deep Q-Network Algorithm-Based Cyclic Air Braking Strategy for Heavy-Haul Trains

Cyclic air braking is a key element for ensuring safe train operation when running on a long and steep downhill railway section. In reality, the cyclic braking performance of a train is affected by its operating environment, speed and air-refilling time. Existing optimization algorithms have the problem of low learning efficiency. To solve this problem, an intelligent control method based on the deep Q-network (DQN) algorithm for heavy-haul trains running on long and steep downhill railway sections is proposed. Firstly, the environment of heavy-haul train operation is designed by considering the line characteristics, speed limits and constraints of the train pipe’s air-refilling time. Secondly, the control process of heavy-haul trains running on long and steep downhill sections is described as the reinforcement learning (RL) of a Markov decision process. By designing the critical elements of RL, a cyclic braking strategy for heavy-haul trains is established based on the reinforcement learning algorithm. Thirdly, the deep neural network and Q-learning are combined to design a neural network for approximating the action value function so that the algorithm can achieve the optimal action value function faster. Finally, simulation experiments are conducted on the actual track data pertaining to the Shuozhou–Huanghua line in China to compare the performance of the Q-learning algorithm against the DQN algorithm. Our findings revealed that the DQN-based intelligent control strategy decreased the air braking distance by 2.1% and enhanced the overall average speed by more than 7%. These experiments unequivocally demonstrate the efficacy and superiority of the DQN-based intelligent control strategy.

The contribution of lower-limb joint quasi-stiffness to theoretical leg stiffness during level, uphill and downhill running at different speeds.

Humans change joint quasi-stiffness (k joint) and leg stiffness (kleg) when running at different speeds on level ground and during uphill and downhill running. These mechanical properties can inform device designs for running such as footwear, exoskeletons and prostheses. We measured kinetics and kinematics from 17 runners (10 M; 7 F) at three speeds on 0°, ±2°, ±4° and ±6° slopes. We calculated ankle and knee k joint, the quotient of change in joint moment and angular displacement, and theoretical leg stiffness (klegT) based on the joint external moment arms and k joint. Runners increased k ankle at faster speeds (p < 0.01). Runners increased and decreased the ankle and knee contributions to klegT, respectively, by 2.89% per 1° steeper uphill slope (p < 0.01) during the first half of stance. Runners decreased and increased ankle and knee joint contributions to klegT, respectively, by 3.68% during the first half and 0.86% during the second half of stance per 1° steeper downhill slope (p < 0.01). Thus, biomimetic devices require stiffer k ankle for faster speeds, and greater ankle contributions and greater knee contributions to klegT during the first half of stance for steeper uphill and downhill slopes, respectively.

An improved energy‐efficient driving strategy for routes with various gradients and speed limits

AbstractWith the increasing concerns about railway energy efficiency, two typical driving strategies have been used in actual train operation. One includes a sequence of full power traction, cruising, coasting, and full braking (CC). The other uses coasting–remotoring (CR) to replace cruising in CC. However, energy‐saving performance by CC and CR, which can be affected by route parameters of gradients and speed limits, has not been fully compared and studied. This paper analyses the energy distribution of CC and CR considering various route parameters and proposes an improved strategy for different gradients and speed limits. The detailed energy flow of CC and CR is analysed by Cauchy–Bunyakovsky–Schwarz inequality and the generalised Hölder's inequality, and then, a novel driving strategy CC_CR is designed. To verify the theoretical results and the effectiveness of the proposed strategy, three simulators with CC, CR, and CC_CR driving modes have been developed and implemented into case studies of four scenarios as well as a real‐world metro line. Simulation results demonstrate that CR can only outperform CC on routes with steep downhill and CC_CR is always the best strategy. The energy savings of CC_CR can be as much as 15% more than CR and 42% greater than CC.

Abnormal gait pattern in downhill hiking is related to muscular deficits of the knee flexors and extensors in active patients with total knee arthroplasty

BackgroundTo assess the in-field walking mechanics during downhill hiking of patients with total knee arthroplasty five to 14 months after surgery and an age-matched healthy control group and relate them to the knee flexor and extensor muscle strength. MethodsParticipants walked on a predetermined hiking trail at a self-selected, comfortable pace wearing an inertial sensor system for recording the whole-body 3D kinematics. Sagittal plane hip, knee, and ankle joint angles were evaluated over the gait cycle at level walking and two different negative slopes. The concentric and eccentric lower extremity muscle strength of the knee flexors and extensors isokinetically at 50 and 120°/s were measured. FindingsLess knee flexion angles during stance have been measured in patients in the operated limb compared to healthy controls in all conditions (level walking, moderate downhill, steep downhill). The differences increased with steepness. Muscle strength was lower in patients for both muscle groups and all measured conditions. The functional hamstrings to quadriceps ratio at 120°/sec correlated with knee angle during level and downhill walking at the moderate slope in patients, showing higher ratios with lower peak knee flexion angles. InterpretationThe study shows that even if rehabilitation has been completed successfully and complication-free, five to 14 months after surgery, the muscular condition was still insufficient to display a normal gait pattern during downhill hiking. The muscle balance between quadriceps and hamstring muscles seems related to the persistence of a stiff knee gait pattern after knee arthroplasty. LoE: III.

Real-Time Predictive Energy-Saving Control for Electric Vehicle Based on Road Slope Prediction

Predictive energy-saving control (PEC) is aimed at reducing energy consumption by designing the vehicle speed while considering future road and traffic information. In particular, the slope of the road ahead is necessary and critical for PEC. This paper proposes a road slope prediction method for production vehicles that uses the nonlinear autoregressive (NAR) neural network model based on road slope sensors. To adaptively balance the energy savings and trip time, this paper proposed a real-time variable weight PEC method for a four-wheel-drive (4WD) intelligent electric vehicle. The weight coefficients are automatically changed according to the characteristics of the road slope, where the vehicle energy-saving rate on the steep downhill road can be maximized. The results of real-time simulation on the dSPACE platform indicated that the road slope predictive model can be run in real time and adapted to changes in road slope and speed. The root mean square error (RMSE) of the predictive results is 0.3063. On a steep downhill road, the energy-saving rate of the proposed PEC method can reach 30.87% at a small expense of time of 3.75%. On uphill and flat roads, energy can be saved by 6.35% at a time cost of 3.0%. Compared with the PEC with constant weight factors, the two control objectives of energy savings and traveling time can be better balanced on various types of roads.

PENGEMBANGAN FASILITAS PARKIR PANTAI BARON – PANTAI POK TUNGGAL BERBASIS PREFERENSI WISATAWAN

Baron – Pok Tunggal Beach area is the most popular tourist destination in Gunungkidul, and the number of visitors who come to this beach also continues to increase yearly. This tourist area has been supported with parking facilities on every beach so that tourists can bring their vehicles to the beach area. However, the conditions of existing parking facilities can potentially cause air and noise pollution. Also, an accident between tourists and vehicles potentially happen. Access to this beach area is also quite difficult because of many steep uphill and downhill roads, sharp turns, and narrow roads with ravines and cliffs. According to that condition, traffic accidents potentially happen if the drivers and the vehicles are not in good condition. To resolve the problems is by developing the parking facilities into centralized parking facilities outside the beach area. The purpose of this study is to determine parking facility development according to the preferences of its user (tourists). 348 respondents represented the tourists' preferences by distributing a stated preference questionnaire. The analytical method used is crosstabs, helped by SPSS 16.0 app. The result of this study is that most respondents, or equivalent to 47% of respondents, chose the park-and-ride parking facility development.

Blessings on a Cart: Ramadan and Street Vendors in Dhaka

Ramadan not only has a religious value to the community but also adds value to the economy through both formal, structured as well as informal unstructured employment. As during Ramadan, food consumption patterns change as well as people's tendency to buy religious items also heightens, it is an important month for the street vendors and impacts their socio-economic position for the year. This paper deals with gaining insight on social orientation, business modality, perception on the effect of festivals and the real effect of Ramadan and pandemic on the revenue and cost. The evidence suggests that despite the presence of other religious and non-religious festivals, Ramadan remains the most critical time for street vendors to generate additional revenue. However, the effect is greater for carts selling processed foods and religious items. The selling of religious items usually face a steep downhill during non-Ramadan times which makes it unsustainable throughout the year. However, although the pandemic hit the regular review of the street vendor, during Ramadan times they didn’t have to lower the prices of items being sold due to the persistent demand.

EFFECT OF BRAKING DISTANCE AND ROAD CONDITIONS ON BRAKE PAD TEMPERATURE ON 150 CC MOTORCYCLE

Road safety is the right of all road users. However, the reality is that the high number of deaths is still caused by accidents while driving on the road. One of the contributing factors to these accidents is the lack of warning signs when the braking system malfunctions. This study aims to monitor the temperature during braking and provide an early warning safety system for motorcycle riders based on the ESP32 microcontroller and the MAX6675 thermocouple type-K temperature sensor module. The method in this study, employed a quantitative experimental approach by conducting experiments on three types of road terrains: flat road, gentle downhill road, and steep downhill road. Braking was performed at intervals of 30 meters, with a final braking distance of 300 meters. The findings of this study indicate that the distance and road conditions have an impact on the increase in brake pad temperature. The experiments showed a significant temperature increase at a braking distance of 300 meters, with values of 99.75°C on flat roads, 115.50°C on gentle downhill roads, and 129.00°C on steep downhill roads.&#x0D; &#x0D; Keywords: early warning sign; ESP32 microcontroller; temperature monitoring; temperature sensor; road safety.

Study on longitudinal dynamics of heavy haul trains running on long and steep downhills

This paper investigates the longitudinal dynamics performance of the combined heavy haul trains, especially for the cyclic air braking strategy on the long and steep downhill segments. Firstly, the mathematical models for calculating the longitudinal forces in the longitudinal train dynamics simulations are formulated. The brake delay time between neighbouring cars and the pressure variation of the brake cylinders in the braking and releasing processes are considered in the air braking force model. Besides, the nonlinear hysteresis characteristic of the coupler-draft gear system is taken into account in the coupler force model. The Newmark-β method is introduced as a numerical solver in this paper. Finally, the simulations based on the real-word infrastructure and vehicle data of the Shuozhou-Huanghua Line are carried out to study the longitudinal dynamics of the combined heavy haul trains with two distributed locomotives.

Runners Adapt Different Lower-Limb Movement Patterns With Respect to Different Speeds and Downhill Slopes.

The aim of this study was to investigate the influence of slope and speed on lower-limb kinematics and energy cost of running. Six well-trained runners (VO2max 72 ± 6 mL·kg−1·min−1) were recruited for the study and performed (1) VO2max and energy cost tests and (2) an experimental running protocol at two speeds, 12 km·h−1 and a speed corresponding to 80% of VO2max (V80, 15.8 ± 1.3 km·h−1) on three different slopes (0°, −5°, and −10°), totaling six 5-min workload conditions. The workload conditions were randomly ordered and performed continuously. The tests lasted 30 min in total. All testing was performed on a large treadmill (3 × 5 m) that offered control over both speed and slope. Three-dimensional kinematic data of the right lower limb were captured during the experimental running protocol using eight infrared cameras with a sampling frequency of 150 Hz. Running kinematics were calculated using a lower body model and inverse kinematics approach. The generic model contained three, one, and two degrees of freedom at the hip, knee, and ankle joints, respectively. Oxygen uptake was measured throughout the experimental protocol. Maximum hip extension and flexion during the stance phase increased due to higher speed (p < 0.01 and p < 0.01, respectively). Knee extension at the touchdown and maximal knee flexion in the stance phase both increased on steeper downhill slopes (both p < 0.05). Ground contact time (GCT) decreased as the speed increased (p < 0.01) but was unaffected by slope (p = 0.73). Runners modified their hip movement pattern in the sagittal plane in response to changes in speed, whereas they altered their knee movement pattern during the touchdown and stance phases in response to changes in slope. While energy cost of running was unaffected by speed alone (p = 0.379), a shift in energy cost was observed for different speeds as the downhill gradient increased (p < 0.001). Energy cost was lower at V80 than 12 km·h−1 on a −5° slope but worse on a −10° slope. This indicates that higher speeds are more efficient on moderate downhill slopes (−5°), while lower speeds are more efficient on steeper downhill slopes (−10°).

A DQN-based intelligent control method for heavy haul trains on long steep downhill section

The cyclic air braking strategy on the long and steep downhill section is one of the biggest challenges for heavy haul railway lines in China. To deal with this problem, this paper presents an intelligent control method based on the Deep-Q-Network (DQN) algorithm for the heavy haul train running on the long and steep downhill section. The aim of the optimal train control problem in the paper is to enhance the train operation performance in regard to the operational safety, maintenance costs and running efficiency. In the train control model, the characteristics of the heavy haul train, the speed limits and constraints on the air-refilling time of the train pipe are taken into consideration. Then the train control process on the long and steep downhill section is described as a Markov decision process for the application of the reinforcement learning (RL) technique. Further, the critical elements of RL are designed and an intelligent control method on the basis of the DQN algorithm is developed to address the optimal train control problem in this paper. Finally, experimental simulations are carried out with the actual data of the Shuozhou-Huanghua Line such that the effectiveness and robustness of the proposed DQN-based control method are verified.

Research on Freight Train Operation Control Simulation on Long Steep Downhill Lines

AbstractSteep ramps are often unavoidable in route design, leading to adverse effects on freight transportation organization. For operators, how to safely and effectively run trains on steep downhi...

Investigation on the impact of walkways slope and pedestrians physical characteristics on pedestrians normal walking and jogging speeds

Pedestrian’s speed is an important parameter for modelling and simulating pedestrians’ crowd movement under normal and emergency conditions. Limited studies have examined the effect of the slope of walkways on pedestrian’s speed. This study investigates the pedestrian’s normal walking and jogging speed on inclined and level walkways. Specifically, it evaluates the impact of various slopes and pedestrian’s physical characteristics (age, gender, body mass index) on pedestrian’s normal and jogging speed. A total of 1615 controlled experiments with 220 participants were conducted on three different slopes in two directions: level (0%), gentle downhill and uphill (±6%), and steep downhill and uphill (±12%) under normal walking and jogging speed conditions. The age, gender, and body mass index (BMI) of the participants were recorded. It was found that contrary to the normal walking speed, the pedestrian’s jogging speed on the steep downhill significantly decreased relative to level terrain. Under the jogging condition, the speed difference among males and females is higher as compared to the speed difference under normal walking. Likewise, the speed difference among elder and young pedestrians under jogging is almost twice the difference in speed under normal walking. The BMI significantly effects walking or jogging speed and the pedestrian’s jogging speed decreases at a faster rate than the pedestrian’s normal walking speed with an increase in BMI.Our findings suggest that due consideration needs to be given to the pedestrians’ physical characteristics, walkways slope, and selection of appropriate speed when simulating the pedestrians' crowd flow under normal and emergency conditions.

Safe and Ecological Speed Control for Heavy-Duty Vehicles on Long–Steep Downhill and Sharp-Curved Roads

To contribute to the development of sustainable transport that is safe, eco-friendly, and efficient, this research proposed a safe and ecological speed control system for heavy-duty vehicles on long–steep downhill and sharp-curved roads under a partially connected vehicles environment consisting of connected heavy-duty vehicles (CHDVs) and conventional human-driven vehicles. This system prioritizes braking and lateral motion safety before improving fuel efficiency and ensuring traffic mobility at optimal status, and optimizes the speed trajectories of CHDVs to control the entire traffic. Speed optimization is modelled as an optimal control problem and solved by the iterative Pontryagin’s maximum principle algorithm. The simulation-based evaluation shows that the proposed system effectively reduces the peak temperature of the brake drums, the lateral slip angle of the vehicle wheels, and the lateral load transfer rate of the vehicle body; all these measurements of effectiveness are limited to safe ranges. A detailed investigation reveals that the proposed system reduces fuel consumption by up to 15.49% and inhibits the adverse effects on throughput. All benefits increase with the market penetration rate (MPR) of CHDVs and the traffic congestion level and reach significant levels under low MPRs of CHDVs. This indicates that the proposed system has good robustness for the impedance from conventional vehicles and could be implemented in the near future.

David Ben-Gurion and Golda Meir: from partnership to enmity

ABSTRACTRelations between David Ben-Gurion and Golda Meir were complex and saw many ups and downs over the years. Having enjoyed fruitful collaboration prior to and after Israel’s establishment, with Meir even appointed foreign minister at the height of her career, they were never close friends. The relationship took a steep downhill course in the early 1960s, culminating in Ben-Gurion’s secession from the ruling Mapai party and the establishment of his own rival Rafi party. This article describes and analyzes the complex relationship and the rift between these two central leaders of Mapai and its impact on the party and on the political map.

The optimal energy-efficient operation of metro train on long and steep downhill segment

The optimal energy-efficient operation of metro train on long and steep downhill segment

Geometric Design Issues and Safety Analysis of Two-way Rural Road Tunnels

Rural road tunnels may pose specific issues from several perspectives: mainly environmental, geotechnical/structural (excavation methods), economical. Geometric road design is then an often arduous task, which should be conducted by trying to make trade-offs between the different issues, and at the same time, it should be compliant to relevant standards and regulations. Nevertheless, the safety of road tunnels should be preserved, not only considering technological systems (e.g. ventilation systems, emergency exits and paths), but also regarding traditional road-safety issues related to road geometric features. In fact, the analysis of recent accident data related to two-way two-lane rural road tunnels has revealed that accident frequencies/rates in two-way two-lane rural road tunnels are comparable with those on the corresponding open sections, even with some differences concerning the accident types. Since road safety issues may be exacerbated by geometric design inaccuracies, some relevant road tunnel geometric issues are discussed in this study. These issues, scarcely treated in previous research and not addressed in detail in technical documents, emerge from the match between different design needs. In detail, those relate to: 1) the possible need for variable road tunnel cross-sections in case of lane/shoulder widenings for the sake of improving visibility or for other reasons, or in case of lay-bys, 2) the possible need for climbing/overtaking lanes in case of steep downhill or uphill slopes. An attempt at addressing the mentioned problems is provided, based on relevant existing research and technical documents. In particular, the preliminary design stages leading to a “WES” (Without Enlargement Solution) solution are described. Hence, besides enlarging the research body in this specific field, the study is also potentially deemed useful for practitioners who have to face similar design problems.

Energy-Efficient Train Driving Strategy with Considering the Steep Downhill Segment

Implementation of energy-efficient train driving strategy is an effective method to save train traction energy consumption, which has attracted much attention from both researchers and practitioners in recent years. Reducing the unnecessary braking during the journey and increasing the coasting distance are efficient to save energy in urban rail transit systems. In the steep downhill segment, the train speed will continue to increase without applying traction due to the ramp force. A high initial speed before stepping into the steep downhill segment will bring partial braking to prevent trains from overspeeding. Optimization of the driving strategy of urban rail trains can avoid the partial braking such that the potential energy is efficiently used and the traction energy is reduced. This paper presents an energy-efficient driving strategy optimization model for the segment with the steep downhill slopes. A numerical method is proposed to calculate the corresponding energy-efficient driving strategy of trains. Specifically, the steep downhill segment in the line is identified firstly for a given line and the solution space with different scenarios is analyzed. With the given cruising speed, a primary driving strategy is obtained, based on which the local driving strategy in the steep slope segment is optimized by replacing the cruising regime with coasting regime. Then, the adaptive gradient descent method is adopted to solve the optimal cruising speed corresponding to the minimum traction energy consumption of the train. Some case studies were conducted and the effectiveness of the algorithm was verified by comparing the energy-saving performance with the classical energy-efficient driving strategy of “Maximum traction–Cruising–Coasting–Maximum braking”.