Curve Research Articles

Developing an effective approach to assess pavement condition for high friction surface treatment (HFST) installation

For more than two decades, High Friction Surfacing Treatments (HFST) have been used worldwide to improve road safety at critical locations, such as sharp curves and intersections. However, the costs associated with HFST installation and the rapid deterioration observed on pavements with poor structural conditions cannot be overlooked. To address these concerns, this research study sought a reliable and accurate method for assessing the suitability of applying HFST to pavements. The main focus was on using machine learning techniques and incorporating International Roughness Index (IRI) and Pavement Condition Index (PCI) data to predict and provide informed recommendations for HFST application. To achieve this, ensemble models were employed, of which the decision tree and extreme gradient boosting showed robust performance, achieving an impressive R-squared value of 0.90, indicating a high level of accuracy in predicting PCI. These models were further assessed for HFST application using the LTPP dataset, with sections classified as suitable and categorised them as good, fair, or poor. The suggestions from these models were particularly reliable in determining the appropriate area for HFST application. The research results clearly demonstrated the efficacy of the ensemble models in accurately predicting PCI and providing informed recommendations for HFST application.

An Improved Multi-point Chord Reference Measurement Device and Error Correction Method for Corrugation Measuring in Sharp Curves

Background: The traditional chord reference method and its device have faced challenges matching the sharp curve track. Thus, it is of utmost importance to research and develop a measurement device and method that can obtain accurate and comprehensive information regarding rail running band corrugation. Aims: It provides a solution for the measurement of the multi-point chord reference method on sharply curved rails and, at the same time, meets the demand for data richness and accuracy in theoretical studies on the causes of rail corrugation and wheel-rail contact relationships. Objective: This paper aims to research and design a measurement device based on the multi-point chord reference method for the rail running band corrugation. Meanwhile, the error in measuring the sharp curve rail is corrected and verified by simulation. Methods: The lateral information of rail running band is obtained by using a line laser profile sensor; the rail corrugation measurement model and error correction model of the rail running band area are established based on multi-point reference system; the simulation of the system model is carried out using Matlab; and the mechanical structure is built for static testing. Results: The measurement model based on the profile sensor and multi-point chord reference system can accurately obtain the rail corrugation waveform of any longitudinal measurement line in the running band area. The measurement results can be accurately corrected for a radius of 200m- 400m, the error parameters can be effectively improved, and the mechanical mechanism of the measurement system runs stably. Conclusion: The results show that the measurement model can accurately measure the rail corrugation of the sharp curve section, and the multi-waveform in the rail running band area has good measurement performance, but the mechanical structure can be optimized and improved in the light weight.

Investment Market Trend Forecasting and Strategy Optimization based on Big Data Analytics

The financial market is an important part of the global economy, and there exists a certain special internal regularity in its changes. With the rapid development of big data technology, the huge amount of data in the financial market provides new opportunities for the prediction of investment trends and strategy optimization. Based on big data analytics technology, combined with machine learning models, the study explores how to construct investment market trend prediction models through effective data preprocessing and feature engineering, and evaluates and compares the performance of different prediction models. How to accurately predict the direction of the financial market will be an important reference value for relevant practitioners as well as researchers. Traditional financial time series research mainly focuses on linear trend fitting based on statistical knowledge, however, the trend of the financial market is not limited to pure mathematical and rational function curves, the financial market is affected by a combination of various factors from all walks of life. Big data analytics has significant application potential in the investment market, providing investors with more scientific and accurate decision support.

Effect of Propeller Face Camber Ratio on the Reduction of Fuel Consumption

This paper presents the effect of the face camber ratio (FCR) on propeller performance, cavitation, and fuel consumption of a bulk carrier in calm water. First, using a developed propeller optimization model coupling a ship performance prediction tool (NavCad) and a nonlinear optimizer in MATLAB, an optimized propeller design at the optimal engine operating point with minimum fuel consumption is selected. This optimized propeller demonstrates superior fuel efficiency compared to the one selected by using the traditional selection methods that prioritize only higher propeller efficiency. Afterward, the FCR is applied to the propeller geometry to evaluate the effect on propeller performance. The open water curves of propellers with different FCRs ranging from 0% to 1.5% are computed based on empirical formulas and computational fluid dynamics (CFD) simulations. Between the two techniques, a good agreement is noted in verifying the predictions. Then, the open water curves from CFD models are implemented into NavCad to evaluate the overall hydrodynamic performance of the propeller at the design point in terms of efficiency, quantify reductions in fuel consumption, and analyze changes in cavitation and noise criteria. The computed results show a reduction in fuel consumption by 3% with a higher FCR. This work offers a preliminary evaluation of propeller performance-based FCR and shows its benefits. This technique offers a promising solution for improving the energy efficiency of the ship and lowering the level of fuel consumption and exhaust emissions.

The variable exponent compound boundary value problem for Liapunov open curve

In this paper, we study the compound boundary value problem for a class of Cauchy-type integrals with density in variable exponent space. Based on the Smirnov theorem for multi-connected domains and the elimination method, we transform the compound boundary value problem of open curve into that of closed curve. The solvable condition and the explicit solution are obtained by the elimination method.

Curve squeal of modern tramcars: comparison between independently rotating wheels and solid axles

ABSTRACT Curve squeal noise is still one of the most serious problems related to the operation of trams in urban networks. Several mitigation solutions have been proposed in past research, usually dealing with friction modifiers or damping elements installed on the wheels or on the rails. In this paper, the role of the bogie architecture on curve squeal occurrence is investigated. Vehicle dynamics simulations and a wheel/rail coupled model in the frequency domain are used to compare curve squeal predictions in case of Independently Rotating Wheels (IRW) and Solid Axles (SA). The SA configuration results in higher longitudinal creepage compared to IRW. This modifies the transverse creep curve, making this design solution less susceptible to curve squeal induced by falling friction. Despite the well-known improved curving behaviour in sharp curves, the IRW architecture has been found to be more prone to curve squeal compared to the SA tramcar.

Novel Deposition Technique for Fabricating Films with Customized Thickness Profiles.

This study introduces a novel deposition technique capable of depositing thin films with any arbitrary thickness profile. The apparatus consists of a fixed shadow mask and a rotating sample carrier plate. The shadow mask features a specifically designed opening curve that corresponds to the particular thickness profile of the deposited film. We successfully designed two shadow masks and used them to deposit films with linear thickness gradients of 49.3 and 86.8 Å/mm and films with sinusoidal thickness profiles with a period of 40 mm. Furthermore, a linear variable filter was designed on the basis of a quarter-wavelength stack of Si3N4 and SiO2, combined with a TiO2 cavity layer with a linearly varying thickness. By coaxially rotating the sample carrier plate relative to the shadow mask, films with the desired thickness profiles could be fabricated in a single deposition step without the need for additional rotational or translational devices inside the deposition chamber. By rotating the carrier plate, the chips attached at different circumferential positions can achieve consistent thickness profiles, making this method well-suited for mass production.

Sharp Curve Trajectory Tracking of a Universal Omni-Wheeled Mobile Robot Using a Sliding Mode Controller

Abstract In our previous works, Amarasiri et al. (2022, “Robust Dynamic Modeling and Trajectory Tracking Controller of a Universal Omni-Wheeled Mobile Robot,” ASME Lett. Dyn. Sys. Control 2(4), p. 040902) and Amarasiri et al. (2024, “Investigating Suitable Combinations of Dynamic Models and Control Techniques for Offline Reinforcement Learning Based Navigation: Application of Universal Omni-Wheeled Robots,” ASME Lett. Dyn. Sys. Control 4(2), p. 021007), two dynamic models of a universal omni-wheeled mobile robot (UOWMR), and trajectory-tracking controllers (three linear and one nonlinear) were developed and presented. The purpose of that work was to identify suitable combinations of dynamic models and trajectory-tracking controllers, choosing the combination with the highest tracking accuracy and the lowest solver execution time. The ultimate purpose is to utilize these physics-based tools in a reinforcement learning (RL) agent developed for path planning and navigation in an unstructured environment. Three trajectories were investigated including a smooth path, a sharp curved path, and a smooth path with disturbance forces. The sliding mode controller (SMC) following a trajectory with sharp (right-angled) curves was not investigated in that work. The sharp corners caused indeterminacy in the path derivatives required for the SMC algorithm. In this short article, we complete our studies of the SMC on sharp corner paths utilizing slight trajectory corner smoothing.

A resident’s sharp learning curve: Post-needle stick injury arteriovenous fistula of the finger

Iatrogenic vascular injuries can be encountered during diagnostic or therapeutic interventions. Traumatic arteriovenous fistulas (AVFs) occur due to penetrating injury involving contiguous arteries and veins. We report a case of a 27-year-old postgraduate trainee who presented with swelling over her left middle finger for 5 months following a needle prick injury at the same site 1 year back, which was diagnosed with ultrasound and dynamic magnetic resonance imaging angiography. Endovascular embolization is avoided in AVFs of the hand due to the risk of distal ischemia, and surgical excision with reconstruction is the preferred treatment.

Modeling and Simulation of Thermal Effects on Electrical Behavior in Lithium-Ion Cells

Thermal effects exert a crucial influence on the electrical behavior of lithium-ion batteries, significantly impacting key parameters such as the open circuit voltage curve, internal impedance, and cell degradation rate. Furthermore, these effects may give rise to electrolyte loss, resulting in a reduction in capacity. The cycling of batteries inherently generates internal heat, establishing a direct relationship between cell temperature and power demand. This article aims to provide a methodology to model electrothermal relations and temperature influence on electrical behavior in lithium-ion cells, as well as a simulation of extended cell operation under arbitrary power loads, presenting a novel approach not previously explored. It does this by considering three models: the Bernardi model for heat generation within the cell, a thermal lumped model for the cell’s temperature, and the Vogel-Fulcher-Tammann model for the capacity change as a function of temperature. These models are then connected to a state-of-the-art open circuit voltage model of a cell, providing a connection from the thermal world back into the electrical world. Experiments with different power demands occur on the simulation, including estimation of thermal parameters with relative errors under 1%, visualizing the effects of the integrated models and potential for real-cell applications.

The generalized soliton wave structures and propagation visualization for Akbota equation

Abstract This paper explores in detail the integrable Akbota equation, a Heisenberg ferromagnet-type problem that is essential to the study of surface and curve geometry. A variety of soliton families are represented by the generalized solitonic wave profiles that are produced using the improved modified Sardar sub-equation technique, which is renowned for its accuracy and dependability. There has never been a study that used this technique before the current one. As a result, the solitonic wave structures have kink, dark, brilliant, king-singular, dark-singular, dark-bright, exponential, trigonometric, and rational solitonic structures, among other characteristics. In order to check the energy conservation, the Hamiltonian function is created and energy level demonstrated. The sensitivity analysis is also presented at various initial conditions. The graphical representation is also depicted along with the appropriate parametric values.

Predicting Lightweight Powders with Useful Sound Absorption Characteristics from Their Specifications

Powders that absorb sound by longitudinal vibration have either a gentle or sharp sound absorption curve at the first absorption peak frequency. Experiments were performed to investigate the conditions under which longitudinal vibration occurs in powders of various grain sizes and bulk densities. The sound absorption characteristics of the powders were then classified according to their specifications, and the sound absorption coefficients predicted by derived empirical equations were compared with the measured sound absorption coefficients. A threshold value for the areal density per grain layer was identified where lightweight powders at 0.0006 g/cm2 or less demonstrated useful sound absorption characteristics via longitudinal vibration. Powders with smooth (i.e., useful) and sharp (i.e., not useful) sound absorption curves could be further identified by the half-width value at 0.0974 < log f2 − log f1 < 0.119 decade. The bulk density can also be used to identify powders with useful sound absorption characteristics at 0.0868 < ρ < 0.124 g/cm3. A regression analysis was performed to obtain empirical equations expressing the relationship between the areal density per grain layer and first sound absorption peak frequency normalized by the layer thickness.

Exploring the potential of triticale lines for bioethanol production

Aim: Triticale is a well adaptable crop, tolerant of disease and abiotic stresses, and able to grow with good yields even in poor soil, thus representing a good choice to develop a new industrial agri-chain in Italy in a sustainability contest, to cope with its soil problems due to incoming desertification. Methods: Two triticale elite lines were grown in marginal lands in controlled field experiments. The lines were harvested at two different development stages, namely green mass and seeds, and suitable standard protocols were applied to test their potential to produce bioethanol in line with the emerging bioenergy processes. Results: The protocols applied were able to obtain bioethanol with a good yield from both feedstocks. In particular, very efficient fermentation kinetics was observed using seed feedstock, with a sharp curve between 15 h and 24 h, reaching 84% of the total alcohol obtained (final time 72 h). Conclusions: Therefore, the results of this research point to new sustainable potential for industrial applications of triticale crops in Italy. Furthermore, the high activity of the endogenous amylolytic enzymes, mainly α-amylase, and the high starch content suggest the potential use of triticale in other industrial applications, like the brewing industry.

Development of lateral acceleration prediction models and consistency evaluation criteria for horizontal curves with gradient on two lane rural highways

Objectives The challenge of combined horizontal and vertical highway alignments continues to be a concern in transportation design, particularly regarding truck stability. This study analyses the stability of trucks on horizontal curves combined with ascending or descending gradients using center of gravity (CoG) height and curve geometry as parameters. It also develops models that predict lateral stability of trucks and criteria for evaluating geometric design consistency based on vehicle stability. Method A smartphone application was used to collect real-time data on lateral acceleration experienced by two-axle trucks on curves with gradient. Results Findings show a lower safety margin against rollover on curves with descending gradient compared to ascending ones. Key factors affecting stability are identified as radius and length of horizontal curve, suggesting improvements in rollover stability by increasing these parameters. Geometric design consistency evaluation criteria were developed based on lateral acceleration, categorizing curves with gradient as good, fair, or poor. Predictive models were developed to quantify the impact of CoG height of truck and curve geometry on lateral acceleration, aiding in consistency assessment. Conclusion Outcomes of research will be useful for the design of safer horizontal curves with gradient by prioritizing vehicle stability

Out-of-Plane Equilibrium Points in the Photogravitational Hill Three-Body Problem

This paper investigates the movement of a negligible mass body (third body) in the vicinity of the out-of-plane equilibrium points of the Hill three-body problem under the effect of radiation pressure of the primaries. We study the effect of the radiation parameters through the factors qi,i=1,2 on the existence, position, zero-velocity curves and stability of the out-of-plane equilibrium points. These equilibrium positions are derived analytically under the action of radiation pressure exerted by the radiating primary bodies. We determined that these points emerge in symmetrical pairs, and based on the values of the radiation parameters, there may be two along the Oz axis and either none or two on the Oxz plane (outside the axes). A thorough numerical investigation found that both radiation factors have a strong influence on the position of the out-of-plane equilibrium points. Our results also reveal that the parameters have impact on the geometry of the zero-velocity curves. Furthermore, the stability of these points is examined in the linear sense. To do so, the spatial distribution of the eigenvalues on the complex plane of the linearized system is visualized for a wide range of radiation parameter combinations. By a numerical investigation, it is found that all equilibrium points are unstable in general.

Comparative Evaluation of Methane Yield from Continuous and Batch Fermentative Processing of Selected Agrowaste

This study investigated the influence of different agrowaste compositions on methane yield in batch and continuous operational modes, highlighting the significance of substrate characteristics in determining the efficiency of methane production. It comparatively assessed the methane yield derived from continuous and batch fermentative processing of the following agrowaste; Cassava peels (A), Maize husks (B), Pig Slurry (C), and composite (D) that represents the co-digestion of the aforementioned A, B & C. Eight digesters were used in all, two anaerobic systems for each substrate, [I.e one operating in a batch mode (1) and the other in a continuous mode (2)]. The proximate properties of the substrates were determined and gas production rates were monitored over the experimental period of 45 days. Gas analysis of the generated gas revealed mainly methane and CO2, with concomitant organic compounds like; Ethanol, Methanol, Acetic Acid, Acetone, etc. Minute quantities of Phenol and Lactic Acid were mainly found in the gas generated from Cassava peels. The average percentage value of Co-digested substrates (D) yielded higher gas volume of 78.263±4.54, followed by C (74.263±4.65), B (70.240±4.38), and A (56.090±3.50). The results also revealed that the continuous fermentative process demonstrated a more stable and consistent methane production rate compared to the batch system, attributed to its steady-state operational mode and continuous substrate feed input. However, modeled graphical results showed that batch fermentation system produced higher gas yield (for all the substrates) between days 29-39 before it recorded a sharp decline curve, attributed to the reduction in substrate availability.

Study on the effect of mitigation strategies for rail corrugation in metro lines

Rail corrugation appears as a periodic irregularity on the rail running surface that causes severe dynamic loads at the wheel-rail interface. These dynamic forces may generate ground-borne vibrations that propagate from the line to the surrounding buildings causing discomfort to residents. Rail grinding is the most used countermeasure for the mitigation of corrugation. However, this maintenance operation determines high operative costs if frequently performed and must be carefully scheduled. To this end, it is important to assess the effectiveness of other mitigation solutions that may prevent or slow down its growth. The main objective of this study is to investigate the formation of rail corrugation on a sharp curve of the Cityringen underground line in Copenhagen. A wheel-rail interaction model is developed in the frequency domain to identify the root causes of the problem on the specific curve and predict the corrugation wavelength. Once the accuracy of the model is tested against experimental observations on the reference curve, it is used to explore the effectiveness of different mitigation actions, such as the use of friction modifiers, the variation of the speed, track design and track gauge. The results indicate that friction modifiers and speed variation are the most effective measures.

Magnetized blood flow supported by tri‐nanoparticles between a peristaltic curved conduit and endoscope

In order to inspect the interior of hollow organs or cavities in the human body, endoscopes are frequently employed in medicine. Over time, they have undergone substantial evolution and are now able to offer invaluable diagnostic data. The non‐invasive identification of tissue abnormalities with subcellular resolution or real‐time biochemical information is made possible by novel endoscopic optical diagnostic methods. These methods provide benefits in terms of detection, characterization, and confirmation while challenging conventional histology. An investigation is conducted on a magnetized ternary nanofluid to analyze its heat production characteristics in a heated flow scenario between two curved conduits that are peristaltic and experience sinusoidal fluctuations. In this study, the use of a new peristaltic endoscope inside a curved conduit is examined, with a specific focus on evaluating the flowing behavior and heat transference attributes. The use of a versatile and innovative endoscope equipped with peristaltic locomotion proves to be a superior approach for conducting endoscopic procedures on intricate mechanical systems. Furthermore, this advanced endoscope offers enhanced comfort for patients undertaking endoscopy of various human parts. A detailed mathematical model has been constructed to fully assess the flowing and heat transference study of this innovative endoscope using the main unsteady regulating formulas like impetus, Maxwell, and heat in their general form, then transformed to a non‐dimensional system with the assumption of a low Reynold's number and wavelength. Mathematica software was used to conduct precise and methodical calculations, enabling the acquisition of both accurate mathematical results and graphical representations. According to certain findings, the conduit is more influenced by the magnetized force, and the pressure rate over the channel width changes from a linear relationship to a sharp curve that ends in a small peak. Additionally, when utilizing different kinds of nanoparticles, there is a noticeable increase in the pressure gradient's magnitude.

Assessing micromobility safety on horizontal curves of bike lanes: a video motion analysis methodology

This study introduces a novel surrogate safety indicator, the ‘effective radius’, and a dynamic tracking methodology for assessing the safety of micromobility (MM) users on isolated bike lane curves, with a focus on geometric characteristics. The methodology involves six main pillars, including site selection, geometric data collection, video recording, speed and position extraction, visualization, and analysis. Naturalistic video data of bike lane users are captured to observe user behavior, and specific points along the curve centerline are identified for monitoring lateral position and speed on a selected curve site in Valencia, Spain. The analysis centers on a bidirectional bike lane featuring a sharp horizontal curve, incorporating the effective radius criteria to evaluate MM users' responses to geometry and environmental conditions. Findings reveal significant variation in effective radius, especially during left turns, primarily due to the geometry factor and the lane's positioning outside the curve. Lateral displacement heat maps indicate that left-turn users often have higher tendencies to violate dedicated lanes, posing collision risks. The speed analysis underscores potential conflicts and reduced handling capabilities for users breaching lane boundaries. The imperative need for well-informed design and safety measures in micromobility infrastructure is emphasized, considering the impact of geometric factors on user behavior and safety.

From Radar Sensor to Floating Car Data: Evaluating Speed Distribution Heterogeneity on Rural Road Segments Using Non-Parametric Similarity Measures

Rural roads, often characterized by winding paths and nearby settlements, feature frequent curvature changes, junctions, and closely spaced private accesses that lead to significant speed variations. These variations are typically represented by average speed or v85 profiles. This paper examines complete speed distributions along rural two-lane roads using Floating Car Data (FCD). The Wasserstein distance, a non-parametric similarity measure, is employed to compare speed distributions recorded by a radar Control Unit (CU) and a selected FCD sample. Initially, FCD speeds were validated against CU speeds. Subsequently, differences in speed distributions between the CU location and specific sections identified by sharp curves, intersections, or accesses have been assessed. The Wasserstein Distance is proposed as the most effective synthetic indicator of speed distribution variability along roadways, attributed to its metric properties. This measure offers a more concise and immediate assessment compared to an extensive array of statistical metrics, such as mean, median, mode, variance, percentiles, v85, interquartile range, kurtosis, and symmetry, as well as qualitative assessments derived from box plot trends.