Mixed Conditions Research Articles

Comparison of E-Scooter and Bike Users’ Behavior in Mixed Traffic

This study aims to investigate the different behaviors with respect to safety measures related to the interaction of e-scooters and bikes with cars in mixed traffic. E-scooters are relatively new vulnerable road users, and their behavior is still not fully understood. For this purpose, an observational study was carried out at an unsignalized at-grade intersection in the city of Catania, Italy. A total of 128 interactions between cars and e-scooters and 89 interactions between cars and bikes were detected. Specifically, two surrogate measures of safety were used, the time to collision (TTC) and post encroachment time (PET), which relate to the “crossing” and the “following” interactions between cars and bikes/e-scooters. The results show that 50% of the “crossings” involving bikes were close interactions with low TTCs representing high risk (TTC < 1.5); meanwhile, for the “crossing” interactions between cars and e-scooters, the same threshold of TTC relates to percentiles of more than 80%. In addition, more than 60% of interactions between cars and e-scooters were characterized by PET values representing a potentially high risk (PET < 1.0 s). The results provide a useful starting point for the elaboration and adaptation of new regulations for mixed traffic conditions including e-scooters that are currently being introduced in several countries with different rules. It should be noted that e-scooters are an intrinsically different transport mode from a bicycle, mainly because their interactions in mixed traffic show that they are prone to a higher risk of closer interactions.

Study on the mixed lubrication of rough planar extrusion considering surface texture

Surface texture plays a crucial role in fluid dynamic lubrication. The non-Newtonian thermal elastohydrodynamic lubrication problem involving rough surfaces with texture has not been investigated to date. In this paper, a model for non-Newtonian thermal elastohydrodynamic lubrication incorporating rough surfaces and texture morphology is developed, focusing on the problem of mixed lubrication in planar extrusion with texture. The model builds upon the Reynolds equation with flow factor introduced. It considers the effects of rough surface texture, thermal effects, and non-Newtonian effects. The Reynolds equation is numerically solved using the Semi-System method to calculate the oil film pressure in full film region and contact pressure in dry contact area. The DC-FFT algorithm is employed to calculate surface elastic deformation. Comparing the calculated friction coefficient of the present model with the measured values in literature experiments, the average error is only 6.94%. Furthermore, the study investigates the effects of texture, temperature, and non-Newtonian on interfacial lubrication performance under mixed lubrication conditions. It’s found that compared to untextured surface, the average film thickness of textured surface increased by a maximum of 10.8%, and the friction coefficient decreased by a maximum of 67.4%; Compared to Newtonian fluids, shear thinning fluids reduce temperature by 0.18%, and shear thickening fluids are more conducive to improving mixed lubrication performance. A stepped pit texture is designed based on the dynamic pressure mechanism of the texture, indicating that the circular stepped pit texture has the best load-bearing capacity improvement.

Upcycling rice husk ash and coal-fired fly ash as si/al sources into hierarchical ZSM-5 for efficient mercury capture from industrial flue gas

Limiting gaseous Hg0 emission is pressing due to the high toxicity in the ecosystem. Zeolites can be regarded as a promising alternative to carbon-based Hg0 adsorbents. However, the mass transfer limitations of conventional singe-sized zeolites constrain the industrial application of zeolites. This study explores the synthesis of hierarchical ZSM-5 zeolites using rice husk ash (RHA) and coal-fired fly ash (FA) as sustainable sources of silicon and aluminum, aimed at enhancing Hg0 removal from industrial flue gases. By adopting a one-step hydrothermal method, we introduced hierarchical porosity into the ZSM-5 framework, enhancing mass transfer and adsorption efficiencies. Iron (III) chloride (FeCl3) was utilized as an active species for modifying the hierarchical ZSM-5, significantly boosting its Hg0 adsorption capabilities. Fe/6RF-hZ demonstrating more than 92% mercury removal efficiency in 60 min under mixed flue gas condition. The structural and chemical attributes of the synthesized ZSM-5 were detailedly characterized, revealing notable differences in surface chemistry and porosity that correlate with varying calcination temperatures of RHA. TEA analysis reveals that hierarchical ZSM-5 zeolites outperform traditional sorbents in demercuration (DeHg) applications, with exceptional DeHg efficiency, energy efficiency (12 kWh), synthesis cost (860 $/ton), and carbon content (non-carbon). This study not only sheds light on the upcycling of solid wastes in synthesizing novel adsorbents but also contributes to the broader application of zeolitic materials in environmental remediation.

Novel Approach to Analyzing Friction Losses by Modeling the Microflow of Lubricating Oil between the Piston Rings and Cylinder in Internal Combustion Engines

This work focuses on the evolution of lubrication wedge shaping in internal combustion piston engines, taking into account liquid microflows on curved surfaces and coating microgeometries. It introduces a new approach to the analysis of friction losses by simulating the microflow of lubricating oil between the surfaces of piston rings cooperating with the cylinder surface. The models used take into account three types of microgeometry and material expansion. Key results indicate that microirregularities with a stereometry of 0.1–0.2 µm significantly influence the distribution of oil film thickness in the phase of maximum working pressure, which is critical for the functioning of the seal ring. The innovation of the work consists of demonstrating that, despite small changes in the friction force and power in the piston rings, changes in the minimum values of the oil film thickness are significant. The work highlights the failure to take into account microgeometry parameters in friction models, which leads to significant errors in the simulation results, especially in terms of oil film continuity and the contribution of mixed friction. The simulations also indicate that advanced geometric models with high mesh resolution are necessary only for the assessment of changes in oil film thickness during the highest pressure increase in the combustion chamber and taking into account various mixed friction conditions. The results suggest significant progress in engine design and performance, confirming the importance of advanced fluid and mixed friction models in piston engine lubrication research.

New synchronization results for fractional neural networks with parameter uncertainty and reaction–diffusion terms

New synchronizations of fractional neural networks (FNNs) with uncertain parameters and reaction diffusion terms are investigated in this paper. Firstly, considering a system with mixed boundary conditions, a mixed boundary controller is designed. Sufficient criteria for the global exponential synchronization of the designed FNNs are given through Lyapunov function, inequality techniques and Razumikhin theorem. Furthermore, the exponential synchronization of the system can be explored under Neumann boundary conditions. An example is provided to verify the theoretical part and present the synchronization results for different fractional orders and diffusion coefficients.

Effect of autonomous vehicle-related eWOM on (fe)males’ attitude and perceived risk as passengers and pedestrians

PurposeThis study investigates how autonomous vehicle (AV)-related electronic word-of-mouth (eWOM) of different polarities affects attitude and perceived risk from the perspectives of both passengers and pedestrians and whether any gender differences exist. It also seeks to identify AV-adoption user archetypes.Design/methodology/approachAn online experiment was conducted, manipulating eWOM polarity (positive, negative or mixed) as a between-participants factor.FindingsWhile eWOM polarity did not affect attitude, perceived risk was the highest in the mixed eWOM condition. Males and females differed from each other in terms of attitude toward AVs from a passenger perspective, attitude toward AVs from a pedestrian perspective and perceived risk for passengers in AVs. Four AV-adoption user archetypes were identified: AV watchfuls, AV optimists, AV nonchalants and AV skeptics.Originality/valueThe paper contributes to the AV adoption literature by adding the effects of eWOM. It not only sheds light on how AV-related eWOM polarity affects attitude and perceived risk but also teases out nuances from the perspectives of passengers and pedestrians as a function of gender.

Solving Fractional Boundary Value Problems with Nonlocal Mixed Boundary Conditions Using Covariant JS-Contractions

This paper investigates the existence, uniqueness, and symmetry of solutions for Φ–Atangana–Baleanu fractional differential equations of order μ∈(1,2] under mixed nonlocal boundary conditions. This is achieved through the use of covariant and contravariant JS-contractions within a generalized framework of a sequential extended bipolar parametric metric space. As a consequence, we obtain the results on covariant and contravariant Ćirić, Chatterjea, Kannan, and Reich contractions as corollaries. Additionally, we substantiate our fixed-point findings with specific examples and derive similar results in the setting of sequential extended fuzzy bipolar metric space.

On non parametric kernel estimation of the mode of the regression function in the strong mixing random design model with censored data

. This study delves into the conditional mode estimation of a randomly censored scalar response variable operating within the framework of strong mixing conditions. We introduce a kernel-based estimator for the conditional mode function. The principal contribution of this investigation lies in the derivation of the asymptotic distribution and the strong rate of convergence of the newly proposed estimators. These findings are established under a set of fairly comprehensive structural assumptions governing the underlying models. Additionally, we conduct a series of simulation studies to showcase the finite sample performance characteristics of the proposed estimator.

Study on the mechanical behavior of microcapsules during the mixing process of asphalt mixture

To enhance the survival rate of microcapsules during the mixing process of asphalt mixture, the mechanical behavior of microcapsules during this process was investigated through simulation. Initially, the asphalt mixture containing microcapsules was divided into mesoscopic and microscopic scales. Utilizing composite material models, the stepwise inclusion method and high-temperature tensile tests, the equivalent mechanical parameters for the microcapsules, asphalt mastic and asphalt mortar at mixing temperature were estimated. Following this, the mixing process of the asphalt mixture incorporating microcapsules was simulated employing the discrete element method (DEM) coupled with multi-body dynamics (MBD). This simulation was instrumental in identifying optimal mixing parameters and enabled the analysis of force chain transmission across the multi-scale model. Furthermore, the finite element method (FEM) was employed to develop a monomer model of the microcapsules, facilitating the assessment of their mechanical behavior under optimal mixing conditions. Finally, a detailed sensitivity analysis was performed to investigate the influence of various parameters on the mechanical behavior of microcapsules. The results indicated that, at the mixing temperature, the equivalent Young’s modulus and Poisson's ratio for urea-formaldehyde (UF) resin microcapsules, asphalt mastic, and asphalt mortar were determined to be 0.22 GPa and 0.478, 19.87 GPa and 0.4986, and 88.77 GPa and 0.468, respectively. The optimal mixing parameters for AC-16 asphalt mixture including mixing speed, filling rate and mixing duration were identified as 49 rpm, 50 % and 53 s, under which the most adverse load on the microcapsule is 80 mN. Under the most adverse load, microcapsules might rupture from the inside out, and their survival rate was not less than 68.9 %. Increasing the particle size of microcapsules and reducing the relative radius of the microcapsule core could potentially enhance the crack resistance of microcapsules during mixing.

Enhancing practicality of deep learning for crop disease identification under field conditions: insights from model evaluation and crop-specific approaches.

Crop diseases can lead to significant yield losses and food shortages if not promptly identified and managed by farmers. With the advancements in convolutional neural networks (CNN) and the widespread availability of smartphones, automated and accurate identification of crop diseases has become feasible. However, although previous studies have achieved high accuracy (>95%) under laboratory conditions (Lab) using mixed data sets of multiple crops, these models often falter when deployed under field conditions (Field). In this study, we aimed to evaluate disease identification accuracy under Lab, Field, and Mixed (Lab and Field) conditions using an assembled data set encompassing 14 diseases of apple (Malus × domestica Borkh.), potato (Solanum tuberosum L.), and tomato (Solanum lycopersicum L.). In addition, we investigated the impact of model architectures, parameter sizes, and crop-specific models (CSMs) on accuracy, using DenseNets, ResNets, MobileNetV3, EfficientNet, and VGG Nets. Our results revealed a decrease in accuracy across all models from Lab (98.22%) to Mixed (91.76%) to Field (71.55%) conditions. Interestingly, disease classification accuracy showed minimal variation across model architectures and parameter sizes: Lab (97.61-98.76%), Mixed (90.76-92.31%), and Field (68.56-73.81%). Although CSMs were found to reduce inter-crop disease misclassifications, they also led to a slight increase in intra-crop misclassifications. Our findings underscore the importance of enriching data representation and volumes over employing new model architectures. Furthermore, the need for more field-specific images was highlighted. Ultimately, these insights contribute to the advancement of crop disease identification applications, facilitating their practical implementation in farmer's fields. © 2024 Society of Chemical Industry.

Existence of solutions for singular elliptic equations with mixed boundary conditions

In this article, we investigate generalized solutions for elliptic equations involving double-phase ( p ( x ) , q ( x ) ) -Laplacian operators with Hardy potential in variable exponent spaces. ( p ( x ) , q ( x ) ) -Laplacian operators include p-Laplacian, q-Laplacian, p ( x ) -Laplacian and q ( x ) -Laplacian operators. Additionally, ( p ( x ) , q ( x ) ) -Laplacian elliptic equations with singular coefficients under mixed boundary conditions are seldom mentioned in previous work. Some new theorems of the existence on the generalized solutions are reestablished for such equations via variational methods when the nonlinearity satisfies suitable hypotheses in variable exponent Lebesgue spaces.

Stochastic method based on copulas for predicting severe road traffic interactions

A major difficulty in assessing road traffic safety is the scarcity of historical accident data. xxThis is a common problem in contexts where a certain level of safety has been reached or where exposure is low, such as mixed traffic conditions with different levels of transport automation. Recent studies have demonstrated how severe interactions between road users and/or road users and infrastructure can be a direct measure of safety. However, limiting the investigation to only the most extreme events may lead to inconclusive results considering the lack of prediction robustness and the possible selection bias. In this context, extreme value theory (EVT) is commonly used to extrapolate crashes from road traffic interactions, even combining several indicators. The present work extends the EVT paradigm by proposing a method based on copula functions and EVT, which enables a more specific and continuous evaluation of interaction severity. Compared with pure EVT, this new approach extends the boundary to interactions of all severities while implicitly assuming that the relationship between safety-relevant events and road casualties is stochastic. This EVT-copula approach was also compared with bivariate peaks over threshold (BPOT). It was found that the two approaches yield similar prediction results for crash probabilities. Furthermore, the proposed approach applies to events not properly defined in BPOT and provides more accurate predictions for severe (and less severe) interactions compared with BPOT, when benchmarked against observations.

Preparation of Experiments on Growing Zinc–Cadmium Telluride Crystals in Microgravity

Cd1-xZnxTe crystals are necessary for the production of ionizing radiation detectors widely used in science, technology, medicine and other fields. Internal stresses during crystallization lead to generation of dislocations and low-angle boundaries. Typical problem of melt crystal growth of Cd-Zn-Te compounds are tellurium inclusions, which deteriorate detector performance. Microgravity conditions provide unique opportunities for growing high-quality crystals due to the absence of convection, more equilibrium conditions of melt mixing, and a decrease in internal stresses. Since the properties of such crystals strongly depend on the production conditions, seeds and a feed ingot with specified compositions and structure are required. Ampoules with two compositions of materials have been prepared for the space experiment. Crystals of different compositions Cd0.96Zn0.04Te and Cd0.9Zn0.1Te were produced for two charges. They consist of an oriented seed, solvent, and feeding ingot, which are single-phased, single crystalline, have certain crystallographic orientation, meet demands for growth of Cd–Zn–Te crystals in microgravity. Ampoules containing these materials were sent to International Space Station for crystal growth on equipment already assembled at “Nauka” station.

Solvability analysis for the Boussinesq model of heat transfer under the nonlinear Robin boundary condition for the temperature.

We consider the new boundary value problem for the generalized Boussinesq model of heat transfer under the inhomogeneous Dirichlet boundary condition for the velocity and under mixed boundary conditions for the temperature. It is assumed that the viscosity, thermal conductivity and buoyancy force in the model equations, as well as the heat exchange boundary coefficient, depend on the temperature. The mathematical apparatus for studying the inhomogeneous boundary value problem under study based on the variational method is being developed. Using this apparatus, we prove the main theorem on the global existence of a weak solution of the mentioned boundary value problem and establish sufficient conditions for the problem data ensuring the local uniqueness of the weak solution that has the additional property of smoothness with respect to temperature. This article is part of the theme issue 'Non-smooth variational problems with applications in mechanics'.

Mathematical modeling of the enzymatic hydrolysis of lignocellulosic waste in membrane bioreactor considering transport phenomena

Enzymatic hydrolysis is a crucial step in processing lignocellulosic biomass into biofuels and other valuable products in biorefineries. Applying a membrane reactor to realize this process allows for continuous separation of inhibitory end-products, thus improving process efficiency. Developed so far models have generally been dedicated to describing the reaction kinetics without considering transport phenomena and flux decline prediction. In the present paper, a new mathematical model simulating the hydrolysis process course in membrane bioreactor was established. Compared to previous reports, our study presents a novel approach to modeling the process accounting for the reaction course and permeate flux decline depending on reaction hydrodynamics. A surface renewal theory and empirical reaction kinetic model were implemented to simulate the influences of the operating parameters on the permeate flux and the monosaccharide concentration in the permeate. A procedure to determine the model parameters with experimental data was also presented. The proposed model simulated experimental data with good accuracy (R2>0.97). The total mass of glucose and xylose produced during 10 h of the hydrolysis performed under mixing conditions equaled 2.37 g and 2.39 g for the pressure of 0.4 and 0.6 bar, respectively. They correspond to the high hydrolysis yield, equaled in average to 99.1 %.

Variational inequality for a Timoshenko plate contacting at the boundary with an inclined obstacle.

A class of variational inequalities describing the equilibrium of elastic Timoshenko plates whose boundary is in contact with the side surface of an inclined obstacle is considered. At the plate boundary, mixed conditions of Dirichlet type and a non-penetration condition of inequality type are imposed on displacements in the mid-plane. The novelty consists of modelling oblique interaction with the inclined obstacle which takes into account shear deformation and rotation of transverse cross-sections in the plate. For proposed problems of equilibrium of the plate contacting the inclined obstacle, the unique solvability of the corresponding variational inequality is proved. Under the assumption that the variational solution is smooth enough, optimality conditions are obtained in the form of equilibrium equations and relations revealing the mechanical properties of integrated stresses, moments and generalized displacements on the contact part of the boundary. Accounting for complementarity type conditions owing to the contact of the plate with the inclined obstacle, a primal-dual variational formulation of the obstacle problem is derived. A semi-smooth Newton method based on a generalized gradient is constructed and performed as a primal-dual active-set algorithm. It is advantageous for efficient numerical solution of the problem, provided by a super-linear estimate for the corresponding iterates in function spaces. This article is part of the theme issue 'Non-smooth variational problems with applications in mechanics'.

Application of fungal-based microbial fuel cells for biodegradation of pharmaceuticals: Comparative study of individual vs. mixed contaminant solutions

The present study focuses on the application of fungal-based microbial fuel cells (FMFC) for the degradation of organic pollutants including Acetaminophen (APAP), Para-aminophenol (PAP), Sulfanilamide (SFA), and finally Methylene Blue (MB). The objective is to investigate the patterns of degradation (both individually and as a mixture solution) of the four compounds in response to fungal metabolic processes, with an emphasis on evaluating the possibility of generating energy. Linear Sweep Voltammetry (LSV) has been used for electrochemical analysis of the targeted compounds on a Glassy Carbon Electrode (GCE). A dual chamber MFC has been applied wherein the cathodic compartment, the reduction reaction of oxygen was catalyzed by an elaborated biofilm of Trametes trogii, and the anodic chamber consists of a mixed solution of 200 mg L−1 APAP, PAP, MB, and SFA in 0.1 M PBS and an elaborated biofilm of Trichoderma harzianum. The obtained results showed that all the tested molecules were degraded over time by the Trichoderma harzianum. The biodegradation kinetics of all the tested molecules were found to be in the pseudo-first-order. The results of half-lives and the degradation rate reveal that APAP in its individual form degrades relatively slower (0.0213 h−1) and has a half-life of 33 h compared to its degradation in a mixed solution with a half-life of 20 h. SFA showed the longest half-life in the mixed condition (98 h) which is the opposite of its degradation as individual molecules (20 h) as the fastest molecule compared to other pollutants. The maximum power density of the developed MFC dropped from 0.65 mW m−2 to 0.32 mW m−2 after 45.5 h, showing that the decrease of the residual concentration of molecules in the anodic compartment leads to the decrease of the MFC performance.

Effect of fortnightly and seasonal changes in estuarine physical variables on phytoplankton distribution in a macrotidal monsoon estuary

Seasonal and neap-spring tidal changes in estuarine physical variables and their effect on the phytoplankton distribution in the macrotidal Tanintharyi River estuary (TRE), Myanmar were studied in 2019. During the dry season, the saltwater intrudes upstream while only until the mid-estuary during the wet season due to the hindering of saltwater by the strong river flow. The turbidity variations driven by enhanced mixing and neap-spring transition influenced the light required for phytoplankton growth during both seasons. The diversity index was higher (2.57–3.07) in the dry season with low evenness (0.64–0.79) compared to the low diversity index (2.16–2.73) with high evenness (0.75–0.90) in the wet season. The peak diatom density was observed under low turbidity (6 FTU) and a salinity of 25, and their distribution were correlated positively with salinity, mean light intensity in the mixed layer (Im) and euphotic depth (Ze) while negatively with light attenuation (K) and turbidity. Among diatoms species, Thalassionema frauenfeldii, Thalassionema nitzschioides and Pseudonitzschia seriata were found as dominant species (positively correlated with salinity and Im whereas negatively with turbidity and K) during the dry season whereas Thalassiosira eccentrica and Coscinodiscus granii were dominant with low salinity in the wet season. The dinoflagellates were more sensitive to strong mixing condition than diatoms and their distribution were positively influenced by Im and Ze. Therefore, the neap-spring tidal and seasonal variations in saltwater intrusion, mixing, turbidity, and light availability are the major factors that maintained the phytoplankton diversity in the tropical TRE.

Simultaneous tartrazine-tetracycline removal and hydrogen production in the hybrid electrocoagulation-photocatalytic process using g-C3N4/TiNTAs

This study aimed to investigate the removal of tartrazine dye & tetracycline antibiotic and hydrogen (H2) production simultaneously through the hybrid electrocoagulation-photocatalytic process using g-C3N4/TiO2 nanotube arrays (TiNTAs) nanocomposite. The g-C3N4/TiNTAs was used as the photocatalyst. The melamine as the precursor of g-C3N4 was varied to obtain the optimal loading on the removal of tartrazine dye & tetracycline antibiotic and hydrogen (H2) production simultaneously. The integrated acrylic photoreactor was equipped with two 250-W mercury lamps. The nanotubular morphology of TiNTAs and nanostructure features of g-C3N4/TiNTAs were examined using FESEM/EDX and HR-TEM/SAED. The XRD patterns indicated the composition of TiNTAs, confirming the presence of anatase and rutile crystalline phases. UV-Vis DRS also showed a redshift in the composite absorbance and a reduced bandgap with g-C3N4 introduction. The results showed that when tartrazine and tetracycline were treated simultaneously, tartrazine was more dominantly degraded compared to tetracycline. In mixed pollutant system condition, the H2 production increased by 17.0% and 41.1% compared to single pollutant system of tartrazine and tetracycline, respectively. The photocatalyst used in the hybrid process was the g-C3N4/TiNTAs (3 g) which provide the optimum H2 production.

Toward occupant-centric system: Multicriteria optimization of hybrid displacement–personalized ventilation system using computational fluid dynamics with computer-simulated person

Engineers have integrated general ventilation systems with personalized ventilation (PV) to achieve energy efficiency while providing good indoor air quality (IAQ) and thermal comfort. Previous studies conducted parametric analyses of PV by varying its flow rate and temperature, analyzing energy, IAQ, and thermal comfort while keeping main ventilation settings constant, even though the latter significantly affect the general flow field. Therefore, computational fluid dynamics simulation is performed to simultaneously optimize the above-mentioned three outputs in an office with displacement ventilation (DV) and PV by varying the DV supply flow rate and temperature, the fraction of outlet air being resupplied to inlet or DV recirculation, and PV supply flow rate and temperature. We utilize the Taguchi design to minimize the number of simulations as well as use the “technique for order preference by similarity to ideal solution” (TOPSIS) coupled with Taguchi's signal-to-noise ratio analysis for optimization. Four optimization cases are investigated by varying the thermal comfort and IAQ parameters from volume-averaged to occupant-centric values, such as the skin temperature and inhaled concentration. Results show that occupant-centric optimization presents low energy requirements with acceptable IAQ and thermal comfort compared with volume-averaged optimization, which can be attributed to imperfect mixing conditions. Furthermore, the DV settings and thermal plumes significantly affect the direction of jet released by the PV, which does not improve the IAQ. This underscores the importance of considering the aforementioned effects in maximizing the PV potential. Nevertheless, the PV system functions as intended under a flow rate of 6 L/s.