Grid Method Research Articles

Development of an enhanced base unit generation framework for predicting demand in free‐floating micro‐mobility

AbstractAccurate demand forecasting has become increasingly necessary in the burgeoning field of free‐floating micro‐mobility systems. However, for model training, the service area must be divided into specific areal units, which often involves grid‐based methods. Although these methods are feasible and provide a uniform area division, they are highly susceptible to the Modifiable Areal Unit Problem (MAUP), which is a critical issue in spatial data analysis. Although MAUP can adversely affect predictive model learning, studies addressing this issue are scarce. Therefore, a novel base areal unit generation algorithm is proposed that employs a clustering approach to enhance the prediction accuracy in free‐floating micro‐mobility system demand. The method identifies suitable base areal units by merging smaller ones while considering the similarities in temporal usage patterns and distances between different areas, mitigating the impact of MAUP during model learning. The approach was evaluated using shared e‐scooter data from two cities, Kansas City and Minneapolis, and it was compared to the traditional grid method. The findings indicate that the proposed framework generally improves prediction performance within the newly defined areal units.

Effect of boron oxide and basicity on viscosity and crystallization onset temperature of СаО–SiO<sub>2</sub>–B<sub>2</sub>O<sub>3</sub>–12%Cr<sub>2</sub>O<sub>3</sub>–3%Аl<sub>2</sub>O<sub>3</sub>–8%МgO slag system

The rapid growth of demand for stainless steel and, accordingly, its production, which occurred in the second half of the 20th century and continues till today, makes it necessary to conduct studies of the properties of oxide systems that will contribute to the improvement of metallurgical production technologies for such steel. Therefore, in this paper, using the method of simplex grids for experimental planning and vibration viscometry, a study was conducted of the effect of basicity and boron oxide content on the viscosity and crystallization onset temperature of slags of the СаО–SiO2–B2O3–12%Cr2O3–3%Аl2O3–8%МgO oxide system formed during the reduction period of the production of low-carbon stainless steel by the argon-oxygen decarbonization (AOD) process, which is currently the main method for producing corrosion-resistant steel. The introduction of boron oxide into AOD-slags is a possible solution to the problem of instability of the physical properties of slags during smelting, caused by the volatility of fluorspar fluorides, traditionally used as a flux, and compliance with increasingly stringent environmental requirements by eliminating the formation of toxic fluorine compounds. Based on the results of experimental studies of the viscosity of slags of the studied oxide system depending on the chemical composition and temperature, approximating mathematical models in the form of a reduced third-degree polynomial are constructed. Graphically, the results of mathematical modeling are presented in the form of “composition – property” diagrams, which allow quantitatively determining the effect of temperature and chemical composition of the slags under study on viscosity and their composition on the crystallization onset temperature. It is noted that at 1600 and 1650°C, an increase in the boron oxide content in the slag from 3.0 to 6.0% has a favorable effect on the fluidity of the formed slags in the basicity range of 1.0-2.5. For example, an increase in the boron oxide concentration from 3.0 to 6.0% ensures a decrease in the viscosity of the slags from 2.0 to 0.5 Pa s at a temperature of 1600°C and from 0.4 to 0.3 Pa s at a temperature of 1650°C in the region of increased basicity up to 2.0-2.5.

Design and Construction of Infrastructure Asset Management Information Systems Using the Rapid Application Development (RAD) Method

The school administration system manages several things, such as the management, storage, and use of facilities and infrastructure items, which have been done traditionally. In contrast, the management must be well structured so that integration with information technology is needed. In previous studies, there were many areas for improvement in the asset information system, one of which was the use of traditional methods such as waterfall which had weaknesses in user flexibility and took a long time to process. Therefore, that a more relevant and accurate method is needed in its completion. SD Khaijah Surabaya built a facilities and infrastructure asset information system using the Rapid Application Development (RAD) method, which offers a more adaptive and interactive solution because it allows the development of rapid prototypes and continuous evaluation of the system. The results of this study show that building an asset management information system can simplify the process of managing infrastructure assets, improve data accuracy, and assist in making decisions related to asset management. The implementation of this system is expected to significantly improve organizational performance in terms of asset management, while system testing using the Black Box method shows accurate results and using the System Usability Scale (SUS) method manages to get a precise score of 80. The average person gives a score of 5 on the assessment of the questionnaire distributed to stakeholders.

EXTENDING THE BOX METHOD FOR POLYNOMIAL ARITHMETIC

The box method for performing polynomial multiplication is a popular form of demonstrating the process of multiplying polynomials. This method is graphical, but still lacks the inherent simplicity as well as the organization of like terms. It still requires that combining terms with x’s in the table itself. While this method is very well received and beneficial, we shall extend this further to work solely with numbers and let the table tell us how to combine the values. The purpose of this paper is to demonstrate polynomial arithmetic using tables similar to those constructed for synthetic division. Our focus will be on addition, subtraction and multiplication. Similar to how synthetic division focuses on the coefficients of the polynomials involved, the tables constructed below shall do the same. The advantage to this technique is that it reduces polynomial arithmetic to numerical arithmetic as the table organizes the terms into like terms. How to construct such tables in order to easily perform the arithmetic for students is our primary effort.

Abrupt changing aerodynamic loads resulting in diminished ride comfort when two high-speed trains intersect in a tunnel

The lateral force exerted when two trains pass each other can adversely affect train safety, and this adverse effect becomes more pronounced as the train speed increases. When trains cross paths in tunnels, the aerodynamics differ from those in open lines due to the restrictive nature of tunnel walls. Utilizing the Renormalization Group (RNG) k-ε turbulence model and the “Mosaic” grid method, this research examines changes in aerodynamic load of the train and ride comfort during a intersection at 400 km/h in a tunnel and contrasts this with conditions at 350 km/h. The results indicate that the change in aerodynamic load on each carriage is more pronounced when the head train of the oncoming train passes than when its tail train passes, with the largest variation observed during the passing of both the head and tail trains. This alteration in aerodynamic load is primarily attributed to the air being pushed in the locomotive area and the negative pressure from the vortex structure between trains. When the speed is increased from 350 km/h to 400 km/h, the aerodynamic load on the train increases by approximately 20 % to 40 %, and the acceleration of the head train grows by 20 % to 50 %. The most noticeable decrease in ride comfort is observed in the head train, with the highest increase in the head train’s Overall Vibration Total Value (OVTV), which rises by 30.1 %.

Steady-State Response Analysis of an Uncertain Rotor Based on Chebyshev Orthogonal Polynomials

The performance of a rotor system is influenced by various design parameters that are neither precise nor constant. Uncertainties in rotor operation arise from factors such as assembly errors, material defects, and wear. To obtain more reliable analytical results, it is essential to consider these uncertainties when evaluating rotor performance. In this paper, the Chebyshev interval method is employed to quantify the uncertainty in the steady-state response of the rotor system. To address the challenges of high-dimensional integration, an innovative sparse-grid integration method is introduced and demonstrated using a rotor tester. The effects of support stiffness, mass imbalance, and uncertainties in the installation phase angle on the steady-state response of the rotor system are analyzed individually, along with a comprehensive assessment of their combined effects. When compared to the Monte Carlo simulation (MCS) method and the full tensor product grid (FTG) method, the proposed method requires only 68% of the computational cost associated with MCS, while maintaining calculation accuracy. Additionally, sparse-grid integration reduces the computational cost by approximately 95.87% compared to the FTG method.

Optimization and sensitivity analysis of magnetic fields on nanofluid flow on a wedge with machine learning techniques with joule heating, radiation and viscous dissipation

PurposeIn this study, the flow of nanofluids (NFDs), consisting of water and copper nanoparticles over a wedge, is simulated. The analysis considers the effects of a magnetic field (MFD) and Joule heating (JOH). Variables such as nanoparticle volume fraction (NVF), Eckert number (EC), radiation, and wedge angle (BT) are also examined for their impacts on the Nu and Cf. Design/methodology/approachThe simulation utilizes the similarity method and the Keller box method, implemented through custom coding. Additionally, machine learning techniques are applied for sensitivity analysis and optimization of the results by varying the parameters. FindingsThe findings indicate that increasing the BT, NVF and MFD strength can elevate the average friction coefficient (Cf-m) by up to 42.8 %. Sensitivity analysis reveals that factors like BT and MFD significantly influence the Cf-m and Nu. An increase in MFD strength generally reduces the Nu-m. A larger BT substantially boosts the Nu-m; however, heightened JOH results in a sharp decline in the Nu. An increase in the EC leads to a decrease in the Nu-m. At low radiation parameter (RD) values, increasing this parameter reduces the Nu-m, whereas at higher values, it increases the Nu. Originality/valueThe key contribution of the article is the optimization and sensitivity analysis of NFD flow over a surface, considering the effects of a MFD, JOH, radiation, EC, and BT. This is done to achieve maximum heat transfer and minimum friction loss.

Calculation Method Based on Flower Petal Area and Other Plant Leaf Spot Area

In order to calculate the area of irregular shapes such as plant leaves and diseased spots or flower petals, this paper presents a new method to calculate them by using flood fill algorithm, HSV color space, improved k-means algorithm and morphological operation. First, 501 butterfly petal images and pathological leaf images of Bauhinia and phyllotaxus were collected, and then flood was used Fill algorithm selects the disease-free area and records the selected pixel value. HSV color space conversion is applied to the image to facilitate the segmentation of leaves. Then, the improved k-means algorithm is used to extract the binary image of leaves and record the pixel value of the outer contour with morphological closed operation. Finally, the proportion and truth of the disease spots of plant leaves are obtained by calculating the pixel value and the real value of the rectangle in the sampling area Real area. Compared with the results of artificial labeling, the average accuracy of petal area and lesion area of Phalaenopsis was 96.3% and 96.61%, respectively. It can be seen that the program can calculate the area of irregular shape of plant surface accurately. In conclusion, this method can replace the artificial grid method to calculate the information of plant leaf area and disease proportion, and effectively reduce the work intensity of experimental personnel.

Development of a Prediction Model for Specific Fuel Consumption in Rotary Tillage Based on Actual Operation

Tractor fuel consumption has typically been predicted using indoor test results under specific conditions. This study analyzes the factors affecting fuel consumption during rotary tillage in actual fields and develops a prediction model. The test field was divided into sections using a grid method, and rotary tillage operations were performed to measure various parameters, including soil strength, tractor’s transmission and PTO gear stages, tillage pitch, travel speed, engine and PTO shaft torque and speed, and fuel consumption. Pearson correlation identified variables affecting specific fuel consumption, and regression analysis was used to develop a prediction model. The model’s accuracy was analyzed using the coefficient of determination (R2) and root mean square error (RMSE), and it was compared with the ASABE’s fuel consumption prediction model. The test results showed that higher transmission and PTO gear stages, and tillage pitch decreased specific fuel consumption, while soil strength had no significant effect. Thus, operating at higher gear and PTO stages within suitable conditions enhances energy efficiency in rotary tillage. Statistical analysis showed that specific fuel consumption significantly correlated with tractor travel speed, PTO shaft power, and PTO shaft speed. The prediction model, including these variables, had the highest accuracy with R2 of 0.91 and RMSE of 0.011 L/kW·h. The developed prediction model showed significantly improved accuracy compared to the ASABE model, indicating that it can predict specific fuel consumption based on key operational variables in actual rotary tillage operations.

Non-inertial computational framework for long-distance shock-driven object dynamics

In the realm of dynamic separation problems, the motion of a body triggered by shock interactions is a common phenomenon. This is particularly important in terms of the safe separation of two-stage-to-orbit vehicles, where the motion must remain stable despite long-distance disturbances from shock waves. The flow field in these cases is complex, marked by interactions between hypersonic shock waves and a moving boundary. This leads to significant unsteady effects due to the body's translation and rotation over extended distances. Existing simulation techniques fall short in rapidly and accurately predicting the aerodynamic force and thermal properties for these problems, largely due to the overwhelming computational demands that result from oversize computational domains and the necessity of grid deformation. This paper presents a novel non-deforming grid method to address these challenges. The central concept is to anchor the reference frame to the moving object itself and to approach the problem from a non-inertial frame perspective. This accounts for the motion of the object solely via the inertial source term, circumventing the complexities of mesh manipulation typically required to link flow and motion equations. The moving shock boundary is designed to be closely compatible with selected shock-captured schemes, which reduces non-physical oscillations compared to the traditional method of direct assembly with theoretical shock relations. Other boundary conditions and the solution process are also refined to specifically target the unsteady, shock-dominated flow. These modifications significantly alleviate the computational burden. The effectiveness of the proposed method is demonstrated through several test cases. To showcase the method's practical application, a scenario is simulated wherein an ellipse is dislodged from a wedge by an incident shock wave, covering a long distance. These tests confirm the method's feasibility in aerospace engineering problems.

The Impact of Longevity Annuity Provision on Retirement Income Planning for Canadians—A Modified General Endogenous Grid Method

This article examines the impact of longevity annuities on retirement income planning for Canadians across various socioeconomic classes, considering realistic tax rules, retirement systems, and the uncertainty of future mortality improvement. We employ a dynamic life cycle framework to analyze changes in saving and consumption patterns resulting from longevity annuities. A modified general endogenous grid method (G2EGM) is proposed to efficiently determine saving and consumption decisions while addressing non-differentiability issues arising from realistic government regulations. Additionally, we investigate factors influencing longevity annuity demand, including annuity price, risk attitude, mortality assumptions, and information asymmetry. Our methodological advancements and empirical findings provide valuable insights into the role of longevity annuities in retirement planning across diverse socioeconomic backgrounds in Canada.

Incorporating numerical method for analyzing the conduction heat transfer during solidification loading nanoparticles

This study examines the freezing within a tank with a curved cold surface, integrating an innovative use of fins. The addition of fins and the careful introduction of nanomaterial knowingly enhance solidification efficiency, with potential applications in areas such as cryopreservation and thermal energy storage. To further optimize the solidification process, various types and concentrations of nano-powders were dispersed into the water, serving as heat transfer enhancers. The mathematical model was refined through specific assumptions, leading to the derivation of two principal equations. These equations were then effectively solved using the Galerkin method, offering a novel optimization approach for solidification. The enhancement in conductivity due to the modifications plays a key role in improving the productivity of the system. Furthermore, the addition of nanoparticles resulted in a notable extension of freezing time around 26.71 %. The use of an adaptive grid method during grid generation, coupled with the successful verification of the final model, strengthens the reliability of the research. By increasing the parameter "m" (shape factor) from 4.8 to 8.6, the solidification time was reduced by approximately 6.96 %, demonstrating a significant improvement in the system's efficiency.

Trajectory reconstruction method for spacecraft formation considering collision probability constraints

Abstract This paper introduces a trajectory reconstruction algorithm for spacecraft formation, combining collision probability and sequential convex programming algorithms. When reconstructing the trajectory of spacecraft formation, external collision avoidance constraint is added to avoid collision threats from space objects. The constraint accuracy of the external collision avoidance constraints of the BOX method and the collision probability method is analyzed. The simulation results indicate that the collision probability method has higher accuracy compared to the BOX method. It addresses the issue of inaccurate division of collision avoidance zones in the BOX method, which tends to be aggressive in the velocity direction and conservative in other directions. A reference is provided for trajectory reconstruction when formation satellites encounter non-cooperative targets.

Numerical simulation of jet interaction flow field of complex configuration based on hybrid grid method

Abstract The supersonic/hypersonic jet interaction flow field includes many fluid phenomena such as shock waves, separation and reattachment of the boundary layer, expansion wave, Mach disk, shear layer, and so on. The complexity of the jet interaction flow field makes it difficult to simulate accurately, and the structured grid method is generally used in engineering applications. However, the structured grid has many shortcomings when dealing with complex configurations, and the traditional hybrid grid method has the problem of insufficient accuracy. In the paper, a structured/unstructured grid algorithmic coupling numerical simulation method is developed. Firstly, the feasibility and accuracy of this method are verified by numerical simulation of the jet interference flow field of cone-cylinder-skirt shape, along with a comparison with the results of the experiment and structural method. Then, the jet interference flow fields of the rudders and the grid fins configuration are simulated to show the efficiency of the method, and the accuracy is further verified. The results show that the hybrid numerical simulation method can save grid generation time and grid quantity to a certain extent when compared with the structural, showing higher accuracy, which provides an accurate and efficient solution to jet interaction problems with complex configurations.

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.

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 1 s, 2 s, and 3 s 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.

Extreme rainfall and soil water consumption differences increase yield shedding at lower fruiting branches, reducing cotton water productivity under different sowing dates

Improvement of cultivated cotton adaptability to extreme climate events under climate change promotes sustainable cotton production. Extreme rainfall leads to a significant decrease in cotton yield, which may be related to changes in soil water consumption (SWC) and the vertical distribution of yield, but relevant research is still scarce. Here, a two-year cotton sowing date experiment was conducted in which geostatistics, sensor technology, the spatial grid method, and principal component analysis were combined to analyze cotton utilization of soil water during extreme rainfall (2021) and normal (2022) years. The reasons for cotton yield reduction under extreme rainfall and strategies to improve cotton production adaptability to extreme rainfall were discussed. Under extreme rainfall, the morphogenesis and reproductive organ development of cotton were inhibited. The accumulation of SWC and its relationship with the biomass accumulation of cotton on different sowing dates under extreme rainfall exhibited nearly opposite characteristics to those in a normal year. Simultaneously, the two-year yield showed the opposite trend with the change in sowing date. There existed a trade-off strategy for the vertical distribution (i.e., on the upper, middle and lower fruiting branches) of cotton yield. Extreme rainfall reduced the yield at lower fruiting branches and increased the boll-forming rate of the upper fruiting branches, which was closely related to seed cotton yield, lint yield and water productivity (WP). Optimizing the cotton sowing date (early sowing should be appropriate in this study) may improve the adaptability of cotton production under extreme rainfall, but further long-term studies are needed. This study highlights the critical practice of climate-smart agriculture and has reference value for the sustainable development of cotton production.

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 ≤ ξ ≤ 2.0, 0.0 ≤ n ≤ 1.2, 0.1 ≤ Ec ≤ 2.0, 0.07 ≤ Pr ≤ 7.0, 0.01 ≤ Nt ≤ 0.8, 0.01 ≤ Nb ≤ 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.