Grid Method Research Articles

Research on wheel–rail impact dynamics due to combined rail weld irregularities and polygonal wheel effects considering 3D contact geometry

The geometric irregularities of rail welds and polygonal wheels are common defects observed in high-speed railways, leading to the generation of high-frequency impact forces and vibrations in the wheel–rail contact system. This research establishes a novel vehicle-track coupled dynamic model that incorporates a 3D wheel–rail contact model using meshing grid and conjugate gradient methods to study the high-magnitude wheel–rail impact forces caused by rail weld irregularities and polygonal wheel combinations. The primary objective of this study is to develop a precise 3D contact model that incorporates the actual geometry of wheel and rail surface irregularities into the calculation of vehicle-track dynamic interactions. The study evaluates the effects of 3D rail weld irregularities and polygonal wheels on wheel–rail dynamic interaction by comparing results with those obtained from a conventional vehicle-track coupled model that considers a 2D contact model. The results show that the lengths and depths of polygonal wheels and rail weld irregularities, as well as vehicle speeds, significantly increase the wheel/rail dynamic impact forces. The results also indicate that the widening of irregularities not only significantly affects the wheel–rail contact force but also has an important influence on the contact stiffness.

NutriCare: Aplikasi Pemantau Gizi Ibu Hamil untuk Menghindari Stunting dengan Memenuhi Kebutuhan Kalori dan Zat Besi

Stunting in children under five, due to chronic malnutrition since in the womb, has an impact onchildren's health and cognitive development as well as the potential for long-term economic losses.In Indonesia, the prevalence of stunting will reach 21.6% in 2022. Iron and calorie deficiency inpregnant women is the main factor causing stunting, with 48.6% of pregnant women experiencinganemia. Many pregnant women lack easily accessible nutritional information. The Hilda AlnairaClinic in Koja, North Jakarta, faces challenges in providing manual nutritional recommendationsthat are inefficient and lack personalization. This research aims to develop the "NutriCare" mobileapplication to help pregnant women monitor calorie and iron intake. This Android-basedapplication was developed using a prototypemethod, easy-to-use interface, relevant features, testedusing the black box method, and optimized before full implementation. This application helpsincrease pregnant women's understanding of nutrition and supports maternal health and fetaldevelopment in efforts to prevent stunting.

Evaluating the IUCN conservation status of Tritaxis kurnoolensis (R.R.V.Raju & Pull.) R.Y.Yu. & Welzen (Euphorbiaceae), an endemic tree species found in the Eastern Ghats region of Andhra Pradesh, India

Tritaxis kurnoolensis, a small tree of the Euphorbiaceae family, is endemic to a valley within the Sullavai Sandstone plateau in close proximity to the Paleru Reservoir (Owk dam). The species is a narrow endemic. No documented sightings of this species have been recorded beyond the type locality since its description in 1994 by Venkataraju & Pullaiah as Dimorphocalyx kurnoolensis from the Nandyal District of Andhra Pradesh. In this study, the authors applied the grid method for quantification and subjected the species to a meticulous analysis aligning with IUCN Red List Criteria. The distribution was found to be restricted due to habitat (valley) fragmentation, reservoir which is arresting seed dispersal, and destruction caused by tunnel construction civil works. The area of occupancy (AOO) at 16 km² and the extent of occurrence (EOO) at 0.474 km², were systematically computed using GeoCAT. The species is assessed here using the Red List methodology for evaluating extinction risk. Based on its AOO, EOO, and population size, it has been classified as Critically Endangered.

Identification of Phospholipids Relevant to Cancer Tissue Using Differential Ion Mobility Spectrometry

Phospholipids are the main building components of cell membranes and are also used for cell signaling and as energy storages. Cancer cells alter their lipid metabolism, which ultimately leads to an increase in phospholipids in cancer tissue. Surgical energy instruments use electrical or vibrational energy to heat tissues, which causes intra- and extracellular water to expand rapidly and degrade cell structures, bursting the cells, which causes the formation of a tissue aerosol or smoke depending on the amount of energy used. This gas phase analyte can then be analyzed via gas analysis methods. Differential mobility spectrometry (DMS) is a method that can be used to differentiate malignant tissue from benign tissues in real time via the analysis of surgical smoke produced by energy instruments. Previously, the DMS identification of cancer tissue was based on a ‘black box method’ by differentiating the 2D dispersion plots of samples. This study sets out to find datapoints from the DMS dispersion plots that represent relevant target molecules. We studied the ability of DMS to differentiate three subclasses of phospholipids (phosphatidylcholine, phosphatidylinositol, and phosphatidylethanolamine) from a control sample using a bovine skeletal muscle matrix with a 5 mg addition of each phospholipid subclass to the sample matrix. We trained binary classifiers using linear discriminant analysis (LDA) and support vector machines (SVM) for sample classification. We were able to identify phosphatidylcholine, -inositol, and -ethanolamine with SVM binary classification accuracies of 91%, 73%, and 66% and with LDA binary classification accuracies of 82%, 74%, and 72%, respectively. Phosphatidylcholine was detected with a reliable classification accuracy, but ion separation setups should be adjusted in future studies to reliably detect other relevant phospholipids such as phosphatidylinositol and phosphatidylethanolamine and improve DMS as a microanalysis method and identify other phospholipids relevant to cancer tissue.

The Influence of Leadership Style and Cognitive Attitudes on Patient Safety Culture With Coordination as a Moderation Variable in Inpatient Nurses at Tzu Chi Hospital

This research is based on the results of initial observations which indicate that several safety incident problems will occur in the year 2022. The aim of this research is to reveal empirically the influence of leadership style and cognitive attitudes on patient safety culture with coordination as a moderator. This type of research is quantitative with a cross sectional study design. The population used is nurses who work in inpatient installations. The sampling technique is non-probability sampling, with perm = calculation of the number of samples using Slovin's formula with an error rate of 10%, so that a total sample of 64 respondents was found. The data collection technique uses a questionnaire, and the analysis method uses three box method analysis and PLS-SEM with the help of the Smart-PLS program. The results of the analysis prove that leadership style, cognitive attitude and coordination simultaneously and partially influence patient safety culture, and cognitive attitude is the most dominant variable capable of improving patient safety culture. Coordination cannot moderate the influence of leadership style on patient safety culture, but coordination can weaken the influence of cognitive attitudes on patient safety culture.

Can L-Methionine and S-Adenosyl-L-Methionine effectively mitigate scopolamine-induced cognitive and motor deficits in mice?

Motor balance deficits often coincide with cognitive deficits in older adults. Current medications provide temporary relief with several potential side effects. Essential amino acids and their derivatives, such as S-Adenosyl-L-Methionine (SAMe), can improve nerve function, mood regulation, and neuroprotection against neurodegenerative diseases. This study investigated the protective effects of SAMe in scopolamine-degraded memory, and motor balance in an animal model. To evaluate the possible effects of SAMe on cognitive and motor balance improvement, both Shuttle box and rotarod methods were performed in seven groups of animals (n=7). The mice groups received the saline (control), scopolamine, scopolamine+rivastigmine, scopolamine +methionine, and scopolamine+ three different doses of SAMe daily and separately for two weeks. Data were analyzed independently by one-way ANOVA and P<0.05 was considered significant. SAMe 150 mg/kg worsened scopolamine-induced memory impairment (P<0.001), while methionine (100 mg/kg) or SAMe (only 100 mg/kg) together with scopolamine could reduce the duration of the animal's presence in the dark chamber (P<0.05). Daily administration of methionine and SAMe at the rate of 100 mg/kg daily could significantly improve the decrease in motor balance caused by scopolamine (P<0.05). Rivastigmine improved memory and motor balance impairment caused by scopolamine (P<0.05). No difference between SAMe and L-methionine for memory, and balance. The results suggest that while L-methionine and SAMe may not be effective in improving memory impairments (Even SAMe high doses can aggravate the destruction of passive avoidance memory), they may be beneficial in enhancing motor balance.

Cherry Tomato Detection for Harvesting Using Multimodal Perception and an Improved YOLOv7-Tiny Neural Network

Robotic fruit harvesting has great potential to revolutionize agriculture, but detecting cherry tomatoes in farming environments still faces challenges in accuracy and efficiency. To overcome the shortcomings of existing cherry tomato detection methods for harvesting, this study introduces a deep-learning-based cherry tomato detection scheme for robotic harvesting in greenhouses using multimodal RGB-D perception and an improved YOLOv7-tiny Cherry Tomato Detection (YOLOv7-tiny-CTD) network, which has been modified from the original YOLOv7-tiny by eliminating the “Objectness” output layer, introducing a new “Classness” method for the prediction box, and incorporating a new hybrid non-maximum suppression. Acquired RGB-D images undergo preprocessing such as color space transformation, point cloud normal vector angle computation, and multimodal regions of interest segmentation before being fed into the YOLOv7-tiny-CTD. The proposed method was tested using an AGV-based robot in a greenhouse cherry tomato farming facility. The results indicate that the multimodal perception and deep learning method improves detection precision and accuracy over existing methods while running in real time, and the robot achieved over 80% successful picking rates in two-trial mode in the greenhouse farm, showing promising potential for practical harvesting applications.

Unsteady numerical simulations of aircraft icing based on the dynamic grid method

In this study, an unsteady numerical simulation method based on dynamic grids was established to solve unsteady aircraft icing processes. The dual-time step method was used to achieve the time advancement of the transient airflow and droplets fields. The droplets trajectory was calculated using the Euler method, which incorporates a supercooled large droplets model. The transient evolution of the water film and ice layer on the substrate surface was considered in the icing thermodynamic model. The accuracy of the unsteady method for ice-shape prediction was verified via comparison and analysis of numerical examples. Additionally, the rime and glaze ice formation processes were explored, and the coupling effects of ice horn growth and the air convective heat transfer coefficient, water collection coefficient, and water film flow on the substrate surface were studied. The ice shapes calculated by unsteady and quasi-steady methods were compared. The results indicated that the latter predicts a larger icing range than the former. Moreover, there may be more obvious distinctions between these two methods in predicting glaze ice.

Fisher Information-Based Optimization of Mapped Fourier Grid Methods

The mapped Fourier grid method (mapped-FGM) is a simple and efficient discrete variable representation (DVR) numerical technique for solving atomic radial Schrödinger differential equations. It is set up on equidistant grid points, and the mapping, a suitable coordinate transformation to the radial variable, deals with the potential energy peculiarities that are incompatible with constant step grids. For a given constrained number of grid points, classical phase space and semiclassical arguments help in selecting the mapping function and the maximum radial extension, while the energy does not generally exhibit a variational extremization trend. In this work, optimal computational parameters and mapping quality are alternatively assessed using the extremization of (coordinate and momentum) Fisher information. A benchmark system (hydrogen atom) is employed, where energy eigenvalues and Fisher information are traced in a standard convergence procedure. High-precision energy eigenvalues exhibit a correlation with the extrema of Fisher information measures. Highly efficient mapping schemes (sometimes classically counterintuitive) also stand out with these measures. Same trends are evidenced in the solution of Dalgarno–Lewis equations, i.e., inhomogeneous counterparts of the radial Schrödinger equation occurring in perturbation theory. A detailed analysis of the results, implications on more complex single valence electron Hamiltonians, and future extensions are also included.

Particle tracking-aided digital volume correlation for clay–sand soil mixtures

In this study, a novel, interdisciplinary method is introduced that merges fundamental geomechanics with computer vision to develop an advanced hybrid feature-aided digital volume correlation (DVC) technique. This technique is specifically engineered to measure and compute the full-field strain distribution in fine-grained soil mixtures. A clay–sand mixture specimen composed of quartz sand particles and kaolinite was created. Its mechanical properties and deformation behaviour were then tested using a mini-triaxial apparatus, combined with micro-focus X-ray computed tomography (μCT). The CT slices underwent image processing for denoising, segmentation of distinct phases, reconstruction of sand particles and feature extraction within the soil specimen. The proposed approach incorporated a two-step particle tracking method, which initially uses particle volume and surface area features to establish a preliminary matching list for a reference particle and then use the iterative closest point method for precise target particle matching. The soil specimen's initial displacement field was then mapped onto the DVC method's grid, and further refined through sub-voxel registration by way of a three-dimensional inverse compositional Gauss–Newton algorithm. The proposed method's effectiveness and efficiency were validated by accurately calculating the displacement and strain fields of the soil mixture sample, and comparing the results with those from a traditional DVC method. Given the soil's compositional and microstructural characteristics, these image-matching techniques can be integrated to create a versatile, efficient, and robust DVC system, suitable for a variety of soil mixture types.

Experimental and 3D mesoscopic numerical simulation study of kinetic projectile penetrating into concrete

Concrete is a multiphase composite material composed of mortar, aggregate, and interface transition zone (ITZ). The mesoscopic components of concrete have an important influence on its anti-penetration performance. In this study, a series of penetration experiments with large-caliber ogive-nosed projectiles penetrating concrete targets are carried out. The test results show that the damage to the concrete target consists of crater and tunnel zones and increases with increasing impact velocity. Then, a local background grid method is proposed to establish a 3D mesoscopic model of concrete, based on the arrangement characteristics of the sequence number of the finite elements. Compared with the traditional 3D mesoscopic concrete modeling method, the proposed method can effectively improve the modeling efficiency. Subsequently, numerical simulations are performed based on the 3D mesoscopic model, with the simulation and experimental results in good agreement, verifying the effectiveness of the model. Finally, the verified 3D mesoscopic model is employed to investigate the effects of shape, volume fraction, size interval, and strength of the concrete aggregates on the depth of penetration (DOP) and deflection of the projectile. The simulation results indicate that the shape of the aggregate has a negligible effect on both uniaxial compressive strength and DOP. Therefore, spherical aggregates are used to improve modeling efficiency. Increasing the volume fraction and strength of the aggregates can significantly enhance the anti-penetration performance of concrete. The influence of aggregate size interval on DOP is slight, but it has a significant impact on projectile and trajectory deflection at the same aggregate volume fraction. The uneven lateral resistance on both sides of the projectile, caused by the random distribution of aggregates, is a major factor in deflection.

Active fault-tolerant control with prescribed performance and reachability judgement for the altitude ground test facility

This research proposes an active fault-tolerant control (AFTC) method based on reachability judgement with asymmetric appointed-time prescribed performance to ensure the safety of altitude ground test facility (AGTF) under potential valve actuator and sensor faults. Firstly, a long short-term memory (LSTM) neural network is employed for fault diagnosis. Given the unique characteristics of AGTF, the equivalent multiplicative fault is introduced to ensure the successful fitting of the fault diagnosis network. Then, a reachability judgement network based on the distance field on grids (DFOG) method is designed to assess the impact of faults on subsequent tasks of the system, thereby ensuring the safety of the AGTF. Subsequently, this study proposes an error transformation function of prescribed performance control (PPC) that ensures error convergence even in cases of asymmetric performance function. This enables the performance boundaries to be further reduced to improve the control performance of the system. Finally, experiments validate the effectiveness of the methods proposed in this manuscript.

Preliminary comparison of soundscape preferences in community public spaces between the individuals with visual impairment and with normal vision

Hearing is an important way for the visually impaired to perceive the environment, and the visually impaired have a different preference for urban soundscape than those with normal vision. Therefore, understanding the differences in the preference of the visually impaired and the normal vision to the urban soundscape will help to create a sound environment that is suitable for both of them, so as to enhance the inclusiveness of the urban environment. This study took the community public spaces as the typical urban environment research object, and used the Evaluation Grid Method (EGM) to conduct semi-structured in-depth interviews on soundscape preferences of 20 visually impaired individuals and 25 individuals with normal vision. By sorting out the interview results, 18 soundscape attributes preferred by the visually impaired and 12 soundscape attributes preferred by the normal vision individuals were extracted. Through comparison, it was found that visually impaired individuals have richer descriptions and preferences of soundscape compared to those with normal vision, and the particularity of their preference is mainly reflected in its semantics and its promotion of spatial cognition of the visually impaired.

Comparison of community response to road traffic noise by housing category

In 2023, a socio-acoustic survey on community response to road traffic noise was conducted in residential areas along several arterial roads in Kanagawa Prefecture as part of the Kanagawa University Cross-disciplinary Research Promotion Project. The survey targeted residents living in detached houses and apartment buildings. A questionnaire used for the survey was designed based on new findings from a survey conducted in 2021 using the Image Grid Method. Factors we focused were economic burden due to increased use of air conditioner, harmful impact of noise on family members, and importance of measures reducing noise. Regarding the noise exposure, we estimated Lden using noise maps, which were created for the survey. This paper presented the frequency distribution of the importance of measures reducing noise. In addition, applying multiple logistic regression analysis to individual data, we developed the exposure-response function for economic burden and harmful impact as well as listening disturbance and annoyance. Based on the results obtained, we discussed the importance of measures reducing noise and difference in exposure-response function between housing categories.

Simulation of creep of a rectangular wooden beam under prolonged static load

Objective. Depending on the stress level, the operation of wooden beams under prolonged load is characterized by both linear and nonlinear creep. This has been shown by numerous experimental studies of wood. The theoretical description of these processes is poorly studied or presented extremely rarely. One of the priority areas in the calculations of wooden structure elements is the derivation of resolving equations of linear or nonlinear creep for various types of stress-strain state. Method. The Maxwell-Thomson equations are used as relations establishing the relationship between stresses and deformations. The technique was tested by comparing the solution with the calculation of well-known researchers. An example of calculation is given for various boundary conditions for fixing a beam of rectangular crosssection loaded with a uniformly distributed load. The deflection value is determined by the grid method. Result. A program has been developed for calculating in the MATLAB package with the possibility of varying the initial data and displaying a graph of the dependence of displacement, bending moment on time. The comparison of the maximum deflection value with the analytical solution is given. It is noted that the stresses practically do not change during creep. Conclusion. The proposed approach can be applied to the analysis of the stress-strain state and bearing capacity of wooden beams of arbitrary cross-section. There are no restrictions on boundary conditions and loading type, and the beam material can be not only wood, but also fiberglass.

Global path planning of unmanned ship island region based on improved A* algorithm

Abstract To solve the path planning problem for unmanned boats in island and reef areas, this paper introduces an adaptive heuristic function specifically for island and reef areas based on the traditional A* algorithm, in order to effectively handle the obstacle avoidance problem. A new cost function is designed to balance the relationship between path length and safety. The sea chart is converted into a path planning map by using the grid method, and the path planning is carried out. The paper compares the performance of the new path-planning algorithm with other path-planning algorithms through experiments, and the improved A* algorithm for global path planning of unmanned boats in island and reef areas shows excellent performance in various complex environments, effectively improving the island and reef area navigation efficiency.

Accuracy and Computational Cost Comparison of Numerical Flight Dynamics Reduced-Order Models

This paper compares several approaches to model the unsteady and nonlinear longitudinal aerodynamics of a generic unmanned combat air vehicle configuration based on computational fluid dynamics (CFD). Three different reduced-order models (ROMs) are implemented through unsteady simulations to predict the evolution of forces and moments during prescribed trajectories carried out at M=0.15. The first model investigates a linear quasi-steady model based on a first-order Taylor series expansion of the aerodynamic coefficients. The second one picks up the mathematical formulation of the first model but adds a dynamic coefficient in order to take into account the unsteady effect of rotation rate variations. Finally, the third model is built on indicial functions computed from positive step changes in the angle of attack or pitch rate. The unknown parameters of the first two models and the unknown indicial functions of the third one are obtained, respectively, from the study of forced oscillations and step motions. These prescribed trajectories are performed using unsteady Reynolds-averaged Navier–Stokes simulations coupled with a grid displacement tool. Two different methods are tested and compared to carry out the CFD mesh motions: an overset method and a full moving grid (FMG) method. The indicial functions obtained using the FMG method give results equivalent to those found in the literature in half the time of the overset method. To reduce the computational costs to set up the ROMs, the FMG method is preferred to the overset method. ROMs are then applied, and their predictions are compared with CFD simulations for prescribed trajectories with different angular rates and angles of attack. A study of instantaneous and overall accuracy associated with the implementation cost of the ROMs has allowed to show their strengths and their weaknesses. Similar results are observed at low angles of attack for the ROMs studied, while a major modeling advantage of the indicial method has been identified for higher angles of attack in the nonlinear domain.

A Short-term Vehicle Speed Prediction Approach considering Dynamic Traffic Scene

Vehicle speed serves as a crucial indicator in traffic flow efficiency and safety evaluation. Previous researches typically utilize the time-series data of target vehicle speed or the relative speed and distance between the target and leading vehicles as speed prediction model input, which are suitable for stable and single-vehicle scenes. However, the surrounding traffic scenes dynamically changes during the vehicle’s driving process, the driver needs to allocate attention to the key scene vehicles in the surrounding traffic scenes and adjust the current speed based on these vehicles’ behavior. Therefore, this paper proposes a short-time vehicle speed prediction model considering the dynamic traffic scenes. A dynamic grid method is adopted to divide the target vehicle’s surrounding areas into left front, front, and right front regions. And key scene vehicles are identified based on each region’s state. Then the relative distance, speed, and acceleration data between the target vehicle and key scene vehicles are selected as model inputs. Vehicle trajectory data from the South-North No. 1 Expressway in Hefei and Ranger optimized Temporal Convolutional Network (TCN) are utilized to train the speed prediction model. Experiment results indicated that under 1s, 2s, and 3s prediction lengths, the model’s average Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were 0.430 and 0.271 respectively. Compared to the speed prediction model considering the static traffic scenes, the average RMSE and MAE for the three prediction lengths have been reduced by 49.15% and 56.02% respectively.

Dynamics of non-Newtonian fluid–fiber interactions and void formation mechanism based on fused filament fabrication

Due to the presence of internal defects such as voids in the composites manufactured by material extrusion additive manufacturing (MEX AM), the mechanical properties of the composites are significantly below the theoretical optimum. Under this circumstance, this paper is intended to investigate the effects of nozzle feeding angles and to analyze the void formation and evolution of multiphase flow, in which systematic computational fluid dynamics numerical simulations are conducted. The volume of fluid model and overset grid method are used to simulate the extrusion deposition process of carbon fiber-reinforced polymer composites, and the Carreau model is used to represent the shear-thinning behavior of molten polymer. The numerical method is validated against previously experimental and numerical simulation data. The numerical results show that the key factor leading to void formation is the vortices caused by fiber oscillation. The intense vortex at the front end of the fibers disrupts the interface between molten polymer and air, creating a beneficial condition for air to enter. Nozzle tilting can effectively reduce the probability of void formation by decreasing the fiber oscillation velocity. The results of the present study provide insights into the development and optimization of printer nozzles to enable the printing of longer fibers with less probability of potential void formation.

Entropy optimization of MHD second-grade nanofluid thermal transmission along stretched sheet with variable density and thermal-concentration slip effects

The goal of present investigation is to explore the influence of exponential variable density and entropy optimization on second-grade nanofluid heating efficiency and mass-concentration transmission along extended surface using external magnetic-field and temperature-concentration slip effects. To enhance the motion of nanoparticles and thermal efficiency, the influence of exponential form of temperature-based density on magnetically charged second-grade nanomaterial is main novelty of this research. For higher temperature difference, the entropy optimization is used. The defined formulation of stream functions and similarities are used to convert leading second-grade nanofluid model into ordinary differential form. The efficient Keller box method and Newton Raphson technique are applied to compute numerical results. The final algebraic equations are solved through global matrix for unknown physical quantities. The consequence of all physical constraints on velocity/U profile, temperature/θ field, concentration/ϕ shapes, skin friction coefficient, Nusselt and Sherwood number are analyzed pictorially and numerically. The following range of parameters 0.1 ≤ ≤ 2.0, 0.0 ≤ ≤ 1.2, 0.1 ≤ ≤ 2.0, 0.07 ≤ ≤ 7.0, 0.01 ≤ ≤ 0.8, 0.01 ≤ ≤ 0.9 is used. It is found that velocity field increases with maximum amplitude as variable density, magnetic force and temperature-slip constraint. It is noted that the slip behavior in temperature field and concentration field are increased with convective boundary conditions. It is depicted that local Nusselt quantity and local Sherwood quantity increases as buoyancy force and Prandtl coefficient increases.