Mixed Conditions Research Articles

Identifying the role of route choice behavior of motorcycle riders in microscopic simulation modeling under mixed traffic conditions

Microscopic simulation models are pivotal in transportation planning for their ability to intricately capture complex traffic patterns. This study specifically explores the role of dynamic route choice behavior within micro-simulation frameworks, emphasizing its application in the context of motorcycle-dominated traffic in Ninh Kiều District, Cần Thơ, Vietnam. By integrating discrete choice models for route selection with rigorous calibration and validation in AIMSUN, the study developed a comprehensive traffic simulation model for large-scale networks. Findings reveal that motorcycles dynamically adjust routes based on current traffic conditions rather than adhering strictly to shortest path strategies. However, the availability of roadside traffic information systems accessible to motorcycles in developing countries is limited, hindering optimal route choices. To address this gap and encourage the enhancement of route choice behavior, the study evaluates the impact of real-time traffic information provision using Macroscopic Fundamental Diagrams within the micro-simulation model. The results demonstrate significant improvements in network efficiency when informed route selection behaviors are facilitated, particularly with comprehensive coverage across all road types. Higher compliance rates notably improved network capacity by up to 84%. Overall, this study contributes methodologically by increasing model precision and practical insights into managing heterogeneous traffic environments, highlighting the transformative potential of traffic information systems and advocating for broader implementation in similar motorcycle-centric regions, which currently still rarely extend beyond toll roads. Future research should extend these methodologies to diverse urban contexts for broader validation and application.

Analysis of the three‐dimensional elasticity theory problem for a radially inhomogeneous cylinder

AbstractIn this paper an axisymmetric problem of elasticity theory for a radially inhomogeneous cylinder of small thickness is studied. It is assumed that homogeneous mixed boundary conditions are specified on lateral surfaces of the cylinder, and boundary conditions that leave the cylinder in equilibrium are specified on the ends of the cylinder. It is considered that elastic moduli are arbitrary continuous functions of a variable along the radius of the cylinder. The formulated boundary value problem is reduced to a spectral problem containing a small parameter characterizing the thinness of the cylinder walls. To determine its solution, the method of asymptotic integration is used, based on three iteration processes. All solutions of the equilibrium equation are constructed, satisfying the specified homogeneous boundary conditions on lateral surfaces. It is obtained that the solution of the problem consists of a penetrating solution and a solution of the nature of the boundary layer. An analysis of stress‐strain states corresponding to different types of solutions is carried out. Based on the constructed asymptotic solutions, a connection is found between the solutions obtained by the equation of elasticity theory and by the applied theory of shells. It is shown that the penetrating solution determines the internal stress‐strain state of a radially inhomogeneous cylinder. The stress state determined by the penetrating solution is equivalent to the principal vector of stress acting in a cross section perpendicular to the axis of the cylinder.The first terms of asymptotic expansions of the penetrating solution in a small parameter coincide with solutions in the applied theory of shells. New classes of solutions are defined as the character of a boundary layer, which are localized at the ends of the cylinder and decrease exponentially with distance from the ends. These solutions are absent in the applied theories of shells. The first terms of the asymptotic expansion of the solution, having the nature of a boundary layer, are equivalent to the Saint‐Venant edge effect in the theory of heterogeneous plates. Asymptotic formulas for displacement and stresses are constructed, allowing one to calculate the three‐dimensional stress‐strain state of a radially heterogeneous cylinder of small thickness with any predetermined accuracy. Based on the obtained asymptotic expansions, one can estimate the applicability areas of applied theories and construct a refined applied theory for radially heterogeneous cylindrical shells.

Displacement-potential analysis of ply-stresses in a partially guided non-uniform short-column of hybrid laminated composites

Reliable and accurate analysis of local stresses in structural problems of fiber-reinforced laminated composites involving nonuniform geometry is of utmost practical importance, especially when they are subjected to local loads and supports. In this research, a new study of ply stresses in a partially guided, nonuniform, short composite column of hybrid laminates, subjected to an eccentrically distributed loading is conducted using an efficient computational scheme. The analytical modeling of the present mixed-boundary-value problem of laminated structure is realized in terms of a single scalar function of space variables (called as displacement-potential function), which is defined by the displacement components of plane elasticity, and is governed by a single fourth-order partial-differential equation of equilibrium. In this modeling approach, the original three-dimensional symmetric laminated column is reduced to a plane-stress scalar-field problem of an equivalent imaginary lamina in an attempt to obtain the corresponding strain field (global laminate strain), which is then used to determine the stress fields of individual plies through the respective transformed reduced stiffness matrices. A finite-difference based computational scheme is developed to solve the representative nonuniform equivalent lamina in terms of the displacement-potential function, which is however well capable of dealing with different ply materials as well as fiber orientations, together with the associated mixed and changeable physical conditions along the boundaries of the column. A 28-ply balanced hybrid laminate composed of boron-epoxy and glass-epoxy plies with various fiber orientation is considered as the structural material for the present column. The stress fields obtained for individual plies as well as the overall laminate are analyzed in the perspective of a number of practical issues of structural design, which include material hybridization, eccentricity of loading and attachment of partial guides to the column. The design stresses of the nonuniform laminated column are identified to be affected significantly by the material and orientation of fibers as well as the laminate hybridization. An attempt is also made to verify the soundness and accuracy of the present computational scheme through the comparison of the present potential-function solutions with those obtained by the conventional computational method.

Determination of steady-state for continuous powder mixing: Analysis of mixture properties and signal processing

Continuous powder mixing offers many advantages over batch processes, but its industrial implementation requires control of transient phases due to startup or variations in operating conditions. Detecting the steady-state by observing the mixture properties, obtained through in-line analysis of the mixture composition, is challenging due to the significant fluctuations in these properties. However, there is no quantitative method for identifying the steady-state for continuous powder mixing. We therefore propose in this work a methodology for steady-state detection by comparing several methods of mixture property analysis and signal processing. We show that conventional methods of mixture property analysis cannot reliably and accurately detect steady-state. We conclude that the best methodology is to perform signal processing on the content of the key component in the mixture. To do this, the signal of the content of the key component is first smoothed by the Savitzky-Golay filter. Then, the standard deviation of the filtered signal is compared with a tuning parameter to detect the beginning of steady-state. This method could be used to determine the mixing conditions leading to the smallest startup time, hence avoiding costly waste.

Mechanism of Wheel-Rail Adhesion Recovery during Large Sliding processes under Water Lubrication condition

The challenge of low adhesion between the wheel and rail constrains the advancement of train braking technologies, resulting in sliding during braking, increased braking distances, and even operational safety incidents. Low adhesion arises from the contamination of the rail surface by a third body, such as water or oil, significantly reducing adhesion. However, experimental studies have found that wheel-rail adhesion coefficient under water lubrication conditions possesses a recovery capability: In scenarios characterized by low adhesion in water lubrication conditions, a secondary rise in adhesion occurs when substantial wheel-rail sliding is present. This paper focuses on numerically modeling the unique phenomenon of adhesion recovery during large-sliding processes under water lubrication conditions. Considering the notable differences in frictional heating during wheel sliding, as opposed to pure rolling conditions, we construct a wheel-rail contact model under mixed lubrication conditions that incorporates the solid-liquid coupled heat transfer effect. This model achieves stable solutions for the wheel-rail contact relationship and the temperature at the wheel-rail interface. The impacts of velocity, axle load, water temperature, and slide ratio on the adhesion recovery phenomenon are discussed, revealing the underlying mechanism of adhesion recovery during large sliding processes. Finally, brake adhesion tests under water lubrication conditions are conducted on a scaled test rig to validate the proposed theoretical model.

The Role of Mechanical Mixing and Biologically Active Additives in Enhancing Cutlet Quality

The research relevance is determined by the need to understand the effect of mechanical mixing and the use of biologically active additives on the quality of cutlet mass, which will optimize food technologies and create products with improved texture and nutritional value. This need stems from the fact that the quality and characteristics of culinary products are important criteria for consumers. The research aims to investigate the relationship between mechanical mixing parameters and the use of biologically active additives with structural and mechanical quality parameters of cutlet mass, to improve production processes and develop higher quality food products. Analytical methods, classification methods, functional methods, statistical methods, and synthesis methods were used to determine the quality of the cutlet mass. In the course of the study, a comprehensive analysis of the effect of various parameters of mechanical mixing and the use of various biologically active additives on the structural and mechanical characteristics of the cutlet mass was carried out. It was found that optimal mixing conditions and types of additional components can significantly improve the textural properties of the product. It was found that the use of certain biologically active additives helps to increase the resistance of the mass to mechanical stress and preserve its juiciness. These conclusions allow us to develop more effective strategies for the production of cutlet mass with improved quality and nutritional value. The practical significance of this study is to provide scientifically based recommendations for optimizing food production processes aimed at improving the quality and nutritional value of cutlet mass by studying the effect of mechanical mixing and biologically active additives on its structural and mechanical properties.

Environmental dependency of ectomycorrhizal fungi as soil organic matter oxidizers.

Forest soils play a pivotal role as global carbon (C) sinks, where the dynamics of soil organic matter (SOM) are significantly influenced by ectomycorrhizal (ECM) fungi. While correlations between ECM fungal community composition and soil C storage have been documented, the underlying mechanisms behind this remain unclear. Here, we conducted controlled experiments using pure cultures growing on naturally complex SOM extracts to test how ECM fungi regulate soil C and nitrogen (N) dynamics in response to varying inorganic N availability, in both monoculture and mixed culture conditions. ECM species dominant in N-poor soils exhibited superior SOM decay capabilities compared with those prevalent in N-rich soils. Inorganic N addition alleviated N limitation for ECM species but exacerbated their C limitation, reflected by reduced N compound decomposition and increased C compound decomposition. In mixed cultures without inorganic N supplementation, ECM species with greater SOM decomposition potential facilitated the persistence of less proficient SOM decomposers. Regardless of inorganic N availability, ECM species in mixed cultures demonstrated a preference for C over N, intensifying relatively labile C compound decomposition. This study highlights the complex interactions between ECM species, their nutritional requirements, the nutritional environment of their habitat, and their role in modifying SOM.

A fusion algorithm of multidimensional element space mapping architecture for SOC estimation of lithium-ion batteries under dynamic operating conditions

Accurate estimation of the state of charge (SOC) is pivotal for ensuring the reliable operation of lithium-ion batteries in electric vehicles, particularly under complex real-world conditions. This paper introduces a novel SOC estimation method named Multidimensional Elemental Space Mapping Architecture (MESMA), which integrates the battery equivalent circuit model with a data-driven approach to tackle adaptability under intricate conditions and high-dimensional input data correlation. Initially, a least squares method incorporating a forgetting factor is employed to identify the battery circuit model parameters and analyze their correlation with SOC. Subsequently, a feature fusion algorithm is introduced to discern spatial variables highly correlated with SOC by leveraging both original voltage and current data and circuit model parameters as inputs to a Convolutional Neural Network (CNN) model, and an eight-input and one-output spatially mapped feature CNN model is established. Finally, the XGBoost model is harnessed for battery SOC estimation. The effectiveness and adaptability of MESMA are validated using experimental data from both public single condition and mixed condition datasets, including FUDS, Mixed-1, etc. The results unequivocally demonstrate that MESMA accurately estimates the SOC of lithium-ion batteries under varying operating conditions. Furthermore, it exhibits remarkable adaptability and stability across different temperatures, effectively capturing SOC trends.

Seasonal variability of epipelic microphytobenthos community in two subtidal areas of the Northern Adriatic Sea

We investigated the biodiversity and seasonality of subtidal benthic diatoms at two sites of the Northern Adriatic Sea differently affected by anthropogenic inputs. Sediment samples were collected seasonally, and diatom cells were then separated from the sediment using the density gradient centrifugation method. The total abundance of benthic diatoms ranged between 4,409 ± 1,638 and 77,663 ± 30,415 cells cm-2 and the biomass between 0.41 ± 0.22 and 3.66 ± 2.01 μg C cm-2. At both stations, the benthic diatoms showed a marked seasonal pattern, with maximum abundance, biomass and biodiversity in spring and minimum in summer. Motile life forms, such as Navicula, Nitzschia, Fallacia, and Psammodictyon, dominated in terms of abundance at both stations throughout the study period, while plocon (centric diatoms mainly belonging to Biddulphiaceae) increased under mixing conditions, when they represented the largest contributor to biomass. At both stations and in all seasons, the Si:N:P ratio highlighted the strong P limitation, typical of the Adriatic Sea. The ammonium concentration was the highest component of DIN in spring and summer when we observed the highest and lowest MPB abundance respectively. The preference of diatoms for ammonia, coupled with the increased daylight period, may have enhanced the spring growth, whereas in summer the hypoxic conditions may have caused a decrease. Despite the different environmental conditions, the two stations exhibited similar species compositions and seasonal trends, highlighting relative stability against anthropogenic pressures of a different nature.

A simple, effective and high-precision boundary meshfree method for solving 2D anisotropic heat conduction problems with complex boundaries

A simple, effective and high-precision boundary meshfree method called virtual boundary meshfree Galerkin method (VBMGM) is used to tackle 2D anisotropic heat conduction problems with complex boundaries. Temperature and heat flux are expressed by virtual boundary element method. The virtual source function is constructed through the utilization of radial basis function interpolation. Calculation model diagram and discrete model diagram of real boundaries, and schematic diagram of VBMGM are demonstrated. Using Galekin method and considering boundary conditions, the integral equation and the discrete formula of VBMGM are given in detail. The benefits of the Galerkin, meshfree, and boundary element methods are all presented in VBMGM. Seven numerical examples of general anisotropic heat conduction problems (including three numerical examples with complex boundaries and four numerical examples with mixed boundary conditions) are computed and contrasted with precise solutions and different numerical methods. The computation time of each example is given. The number of degrees of freedom used in many examples is half or less than that of the numerical method being compared. The suggested method has been demonstrated to be effective and high-precision for solving the 2D anisotropic heat conduction problems with complex boundaries.

Simple and efficient step detection algorithm for foot-mounted IMU

Abstract This paper presents a concise, efficient, and adaptive step detection algorithm based on foot-mounted inertial measurement unit sensors. The proposed method maps the temporal values of pedestrian motion and gait diversity into two variables: the distance between peaks and valleys, and the slope. Compared to traditional sliding window methods, this approach amplifies the differences between normal and abnormal steps, allowing it to adapt to various indoor activities such as fast walking, slow walking, running, jogging, standing still, and turning. By incorporating adaptive factors, it addresses the challenge of detecting steps while going up and down stairs. The proposed algorithm overcomes the limitations of traditional adaptive threshold methods that require different temporal and peak thresholds for various gait conditions. By utilizing the significant differences in distance and slope, it effectively resolves the issue of detecting steps during stationary periods. Unlike neural network-based gait classifiers, this algorithm does not need to account for multiple gait conditions, thereby simplifying the training process. Experimental results demonstrate that the algorithm achieves an average accuracy of over 99% under mixed indoor walking conditions and over 98% accuracy in long-term outdoor walking conditions.

Periodic dual-mixing method for fast and robust solving of ultra-thin fluid-structure interaction problems

This study proposes the periodic dual-mixing method (PDMM) that can rapidly and robustly solve ultra-thin fluid-structure interaction (UTFSI) problems, especially in severe mixed lubrication. The dual mixing denotes a two-step process: the first step is to mix the historical inputs and outputs separately according to optimal mixing weights; the obtained results are mixed with dynamic damping factors in the second step to predict the deformation of the next iteration. Meanwhile, the residual is injected into the predicted deformation periodically. The comparison study is carried out with the popular IQN-ILS method in general FSI, which shows the PDMM is 5.3 times faster and 5 times more robust. Furthermore, the advantages of the PDMM are more significant under harsh mixed lubrication conditions.

Navigating the blame game: Investigating automated vehicle fault in collisions under mixed traffic conditions

Vehicle being at fault in a crash has extensively been associated with its driver's behaviors and other human errors for human-driven vehicles (HDV). The introduction of automated vehicles (AVs) is expected to eliminate such human errors due to the ability of AVs to communicate with the external environment. However, various reports have documented AVs being at fault in collisions. This study applied text mining and mixed-effects logistic regression (MELR) on crash data involving AVs collected between 2017 and 2022 in California to explore the likelihood of an AV being at fault during a collision. It was found that among 497 crashes, a relatively small percentage (14.29 %) involved AVs being at fault. The text network results revealed patterns of keywords associated with the AVs being at fault. Such patterns include conventional mode of operation, area of impact, and resulting injuries. Furthermore, with about a 93 % prediction accuracy and an 83 % sensitivity score, the MELR results revealed that the likelihood of AVs being at fault increases when they are operated in conventional mode or when disengagement is involved. Moreover, turning, merging, or changing lane movements, unclear weather conditions, and operating on roadways with four or more lanes significantly increased the odds of an AV being at fault during a crash. Conversely, AVs were less likely to be at fault in commercial land use than residential land use, at intersection locations, and when the crash involved a truck. The practical implications of the findings are presented to improve AV operations.

Failure Prediction of an Airfoil-Type Crack in Thermoelectric Coupling Materials

Airfoil-type cracks with curved surfaces and sharp tips are frequently encountered in modern engineering applications and the aerospace industry. However, such cracks significantly threaten structures due to stress concentration and further cause damage. This study investigates the theoretical analysis and failure prediction of airfoil-type cracks within thermoelectric coupling materials under the interaction of remote mechanical loads, heat flux and electric current density. By employing complex variable theory, conformal mapping methods, and the analytic continuation theorem, the full-field stress and stress intensity factors of an airfoil-type crack were determined under three different loading conditions. The results indicate that when the airfoil-shaped crack tip is subjected to horizontal compression, vertical tensile mechanical load, and both heat flux and current density parallel to the crack, the crack tip would reach a dangerous state. Additionally, the full-field stress distribution reveals stress concentration around the crack tip, which explains variations in SIFs under different external forces and shape factors. Four critical situations suppressing crack propagation under mixed loading conditions are proposed. Furthermore, using an acrylic plate and bismuth telluride alloy as examples, the critical values of external loading for the mixed-mode fracture are determined based on the strain energy density criterion. These critical values can be used to predict failure initiation, thus reducing the risk of structural failure due to airfoil cracks within thermoelectric coupling materials.

Nonideal mixing effect on the input multiplicity and controller performance of CSTR based on Cholette’s model – a simulation study

ABSTRACT The transfer function of the lead-lag process in a CSTR based on Cholette’s model is used to facilitate the input multiplicity analysis. Ideal and nonideal mixing are introduced to investigate the mixing condition effect on the CSTR dynamic behavior. It is verified that the input multiplicity origins include the output multiplicity and the nonideal mixing bypass effect. The former leads to instability in the first-order process, while the latter transforms the first-order process into a lead-lag process and introduces a positive zero transfer function. The start-up diagrams established with both ideal and nonideal mixings are of critical importance to identify the unique and multiple operating regions. We also analyzed the stability conditions based on the pole and the zero of the lead-lag process, which is determined by the nonideal mixing and dominates the behaviors of a real isothermal CSTR with control. The linear and nonlinear integral controller regulatory response simulation results demonstrate that the controller performance could be deteriorated by nonideal mixing.

A novel feature screening algorithm for low-resolution LIBS spectrum elemental quantification

This study presents an innovative approach that integrates Laser-Induced Breakdown Spectroscopy (LIBS) with chemometrics for the quantitative analysis of Si, Ca, Al, and Mg in geological samples. Given the spectral redundancy in low-resolution LIBS devices, the study employs pre-processing techniques, such as AirPLS, Wavelet Transform (WT), and normalization to mitigate spectral noise. Enhanced feature threshold searching is achieved by incorporating SHapley Additive exPlanations (SHAP) and LightGBM into the Boruta algorithm, substantially improving quantitative analysis models based on Support Vector Regression (SVR) and Partial Least Squares Regression (PLSR). The modified Boruta-SVR model demonstrated remarkable robustness, with R2 values of 0.9862, 0.9873, 0.9882, and 0.9916, and RMSE values of 0.8099, 0.324, 0.1378, and 0.2382, respectively, for Si, Ca, Al, and Mg. The results confirm that the Boruta-based feature selection method, when applied to low-resolution LIBS spectra, outperforms traditional methods, capturing unique sample features under mixed spectral peak conditions, thereby enhancing the robustness of quantitative analysis models.

Growth potential, biochemical properties and nutrient removal efficiency of some freshwater microalgae and their consortia from wastewater

Impact of varying nitrate (NO3-N) and phosphate (PO4-P) concentrations and sewage water (SW) on the growth, nutrient removal, lipid accumulation, enzymatic antioxidant activity and phytochemical contents of the microalgae Scenedesmus dimorphus, Coelastrella tenuitheca, Chroococcus turgidus and Parachlorella kessleri under monoculture and their consortia have been investigated. High growth rates were observed for all the four algae in both mono and mixed culture conditions at enhanced concentrations of N (1500 mg/L NO3-N) and P (40 mg/L PO4-P). The species Scenedesmus dimorphus outperformed other microalgae growing in SW in efficiently removing nitrogen. The algal consortia of mixed species was found to be more effective in phosphorus removal. The carbohydrate and protein contents were highest in Parachlorella kessleri, about 37% and 44%, respectively, in SW cultivation. The algal consortia demonstrated highest starch content (4%) in nitrogen deprived growth medium. Highest lipid production (43%) was observed in the SW culture. The species Coelastrella tenuitheca, Chroococcus turgidus and Scenedesmus dimorphus irrespective of the growth media indicated significant accumulation of phenol, flavonoid and tannin. The DPPH, catalase and ascorbic peroxidase assay showed pronounced antioxidant activity. Nutrient (N and P) enrichment exhibited enhanced antioxidant enzymatic activity and accumulation of cell storage products.

Characterization of the dynamic viscosity of cell cultures and its effect on mixing performance in a spinner flask bioreactor

Computational fluid dynamics (CFD) models have been developed to simulate cell culturing bioreactors but assume water-like viscosity properties due to significant data gaps. This study characterized the dynamic viscosity of HEK-293 cell cultures and evaluated its effect on mixing performance in a spinner flask bioreactor. Viscosity measurements indicated that the cell culture media, media with microcarriers, and cell cultures presented shear thinning behaviors within the measured shear rate range of 1–100 s−1. The viscosity also increased with the microcarrier concentrations and growth of cell culture. The CFD model, incorporating dynamic viscosity data, showed that shear stress and Kolmogorov length profiles are significantly influenced by microcarrier concentrations and cell culture growth. Higher microcarrier concentrations led to higher average shear stress and Kolmogorov values. The cultured HEK-293 cells after seven days of growth also had higher average shear stress and Kolmogorov values than at the day of seeding, indicating an impact caused by the cells’ metabolism and biomass. Overall, the results indicated that assuming water-like properties underestimates shear stress and Kolmogorov length scales, especially at zones of lower shear rates due to the observed shear thinning behavior. Thus, careful monitoring of dynamic viscosity of cell cultures and proper control of mixing parameters are critical to deliver the desired mixing conditions for optimized cell growth especially during scale-up production operations.

Steady-State Shape Factor for a Slug Test in an Unconfined Aquifer

A new solution is presented for the steady-state shape factor of a partially penetrating well in an unconfined aquifer. The problem is solved by taking into account mixed boundary conditions at the well, i.e., zero flux at the well casing and constant head at the well screen equal to the head in the well so that the flow through the well screen is non-uniform. The new method is compared with established methods, such as those of Bouwer and Rice and Zlotnik et al., demonstrating that the new approach provides more accurate results under certain conditions. The comparison highlights that the new method is particularly effective in scenarios where the assumptions of uniform flow through the well screen do not hold. This study assumes idealized conditions, such as homogeneity, isotropy, and negligible storativity in the aquifer, which may limit the method’s applicability in more complex environments. The computational demands of the iterative solution process may pose challenges for practical use, especially in resource-constrained settings.

First mixed Laplace eigenfunctions with no hot spots

The hot spots conjecture of J. Rauch states that the second Neumann eigenfunction of the Laplace operator on a bounded Lipschitz domain in R n \mathbb {R}^n attains its extrema only on the boundary of the domain. We present an analogous problem for domains with mixed Dirichlet-Neumann boundary conditions. We then solve this problem for Euclidean triangles and a class of planar domains bounded by the graphs of certain piecewise smooth functions.