Cellular Automata Approach Research Articles

Cellular automata modelling to simulate patterns of urban growth for Nusantara: Indonesia’s new capital

This paper uses cellular automata (CA) modelling to simulate possible patterns of urban growth for Nusantara–Indonesia’s new capital. The modelling uses criteria such as projected population growth and planned development stages and a range of relevant factors that influence urban development. Further the study simulates the possible impact of future urban growth on key biodiversity areas (KBAs). Two scenarios were modelled to simulate urban growth patterns–(1) the nature sensitive city and (2) the Indonesian government’s current plan. Results of the scenario-based CA modelling demonstrate that scenario 1 offers a more sustainable and liveable approach to urban growth, despite its larger land footprint. This is achieved by preserving protected and key biodiversity areas, which are essential for the long-term well-being and resilience of the environment. While scenario 2 is more land-efficient, it presents a possible risk to the overall ecological integrity and liveability of the metropolis by impinging into key biodiversity areas. The study’s cellular automata approach and methodology can be employed for urban planning and biodiversity impact assessment in similar contexts of new city development.

New method for constructing phase diagrams in 2D centered tetragonal Ising nanoparticles using the cellular automata approach

In this study, both ferromagnetic and antiferromagnetic spin configurations of a 2D-centered tetragonal Ising nanoparticle with two types of exchange interactions (J and Jr) are considered. A newly introduced algorithm using Cellular Automata simulation method, which is relied on counting the states with a magnitude of magnetization per site exceeding a threshold value mt, is used to compute the value of the reduced critical temperature. The sensitivity of the critical temperature value to the lattice size and exchange interactions (The ratio of Jr/J denoted by r parameter) are examined. The results show that the value of the critical temperature increases with increasing lattice size with a decreasing slope. Moreover, the same behavior was observed in ferromagnetic and antiferromagnetic cases.

Study of Energy Dissipation and Satisfaction Rates in Mixed Traffic Flow with Lights: A Two-Lane Cellular Automaton Approach

Traffic lights in cities play a crucial role in regulating the complex dynamics of diverse vehicles, giving priority to certain users or vehicles on the road. However, the alternating stop-and-go patterns induced by these lights have an impact on desired speed of vehicles and energy dissipation. In this paper, we examine the impacts of traffic signals, focusing on a two-lane cellular automaton model. Our model accounts for traffic heterogeneity by differentiating vehicles based on speed (slow and fast) and size (large, slow vehicles and small, fast vehicles). In our study, we concentrated on a case in which the lane-changing rules were asymmetric., this regulation stipulates that slower-moving traffic should keep to the righthand lane (or the left-hand lane in countries where driving is on the left) to allow faster vehicles to pass. Although these vehicles occasionally change lanes, they revert to their preferred lane at the earliest opportunity. Hence, we examined two traffic light control strategies: the green wave and synchronized methods. Our findings indicate that both strategies exhibit comparable performance for vehicles in terms of traffic flow parameters. However, differences emerge when comparing the two lanes or vehicle types. Specifically, the slow lane demonstrates a higher traffic flow for slower vehicles and a reduced flow for faster vehicles. When examining satisfaction rates and energy dissipation, notable variations emerge, especially in extremely low densities. The green wave demonstrates marginally superior performance compared to the synchronized traffic light control. This investigation deepens our understanding of the impact of various control strategies on performance. The findings can serve as a foundation for exploring more intricate aspects of traffic management, enhancing the potential for creating efficient and adaptive urban transportation systems.

Land cover change analysis of buffer areas in New Capital City of Nusantara, Indonesia: A cellular automata approach on satellite imageries data

The proposed plan to move Indonesia's capital city to the New Capital City of Nusantara in East Kalimantan Province undoubtedly requires careful efforts to ensure food supply for the population. Population migration to the new capital may pose a food security challenge. To address this fundamental issue, one of the most crucial approaches is to establish buffer areas that can support the food needs of the new capital. The currently existing official Area Sampling Frame survey conducted by the government to assess food vulnerability faced several limitations, including weather conditions, field terrain variations, and high cost. In this study, we propose the utilization of remote sensing satellite imagery data in buffer areas to analyze changes and predict future land cover, which can provide valuable data for assessing food availability. We investigate the integration of a Cellular Automata method with the two most popular analytical methods of classical Logistic Regression and data-driven Artificial Neural Networks, known as CA-LR and CA-ANN, to identify and map land cover changes in the new capital buffer zones. Our findings reveal that both combined methods, CA-LR and CA-ANN, yield fairly promising results, with correctness and kappa statistic values exceeding 80%. Prediction results indicate that buffer areas are predominantly covered by trees, while built-up areas are still limited. The flooded vegetation cover, including rice fields, is predicted to decrease by 2024. This should be a matter of concern for stakeholders, considering the construction of the new capital city is still ongoing and the number of migrants is expected to keep rising.

A new approach to simulate watershed sediment graphs

Soil loss management requires reliable data for assessing the conditions prevailing in a watershed. Suspended sediment concentration (SSC) is one of the indicators of soil loss, and its data and associated properties are essential for integrated watershed management. However, until now, practical methods for estimating the temporal variation of SSC at the watershed scale, i.e., a sediment graph (SG), using measured data have been given less attention. Therefore, the current study was planned to simulate the SG through conceptual modeling of the soil erosion process and sediment yield. The Galazchai Watershed in West Azerbaijan Province, Iran, was selected as a case study. In this regard, the isochrone histograms were initially prepared using two methods of the longitudinal channel profile and spatially distributed travel time. Soil erosion was calculated in each isochrone segment using the Revised Universal Soil Loss Equation (RUSLE), applying the lumped and cellular automata approach. The soil erosion between isochrones was subsequently routed using the Hadley, WaTEM/SEDEM, and newly modified U.S. Forest Service methods. The last method was developed based on seven standardized variables for the current research. Synthetic SGs were ultimately derived from 12 different combinations of the study methods. The modeling performance was assessed using 38 storm events collected over several years. The base time, time to peak, peak value, and total sediment load of the simulated and observed SGs were evaluated using relative error. Comparison based on the evaluation indicators indicated better performance of the combination of the spatially distributed travel time method, cellular automata, and modified U.S. Forest Service method with the coefficient of efficiency and the normalized coefficient of efficiency varying from −1.16 to 0.99 and from 0.32 to 0.99 for the calibration and validation stages, respectively. However, none of the models were simulating satisfactorily the entire sediment graphs.

Effects of process parameters on the microstructure of Inconel 718 during powder bed fusion based on cellular automata approach

ABSTRACT Using numerical simulation methods in additive manufacturing (AM) processes can effectively reduce the cost of process exploration. This study presents a multi-scale simulation study based on the powder bed model for grain growth in the laser powder bed fusion (L-PBF) process of the Inconel 718 material. The finite volume method (FVM) and cellular automaton (CA) model were used to reproduce the process. The simulation results were consistent with the experimental results in terms of melt pool morphology, grain structure, and average grain size. The processes of the competitive and epitaxial growth of grains were discussed. The effects of laser power, scanning speed, hatch distance, and scanning strategy on microstructure were further analyzed through pole figure, grain area distribution, CA nucleation and capture event. The results demonstrated the feasibility of this method in predicting the evolution of microstructures in the L-PBF process and provide a reference for future research.

Multilayer dripping handrail: Modeling accretion disk dynamics with cellular automaton leaky faucet model

We study the behavior of a Multilayer Dripping Handrail model of the accretion disk, which is based upon a cellular automaton approach inspired by Yonehara et al. (1997). In combination with the Mass–Spring model of a leaky faucet system first proposed by Shaw (1984) and later modified by Kiyono and Fuchikami (1999). Mass–Spring model serves the purpose of critical condition for the dripping mechanism redistributing accreting mass into lower disk annuli. As falling matter loses energy, we model the accretion disk’s temperature distribution and radiative output. Our primary focus is on modeling the temperature distribution changes, of which the main manifestation is the flickering in extracted synthetic light curves.

Perancangan Model Spasial Kawasan Permukiman Perkotaan Berbasis Cellular Automata Di Kabupaten Minahasa Selatan

The purpose of this research is to design a spatial model of urban settlement areas using the Cellular Automata approach in South Minahasa Regency. The research location is located in a sub-district in South Minahasa Regency which has a delineation of urban settlement areas namely Tumpaan, Tareran, Amurang Timur, Amurang, Amurang Barat, Tenga and Sinonsayang Districts, covering an area of ​​656.6 Km2. Primary data collection methods are: Field observation and distribution of questionnaires to academics, government and local communities. Secondary data collection methods, namely: literature review and data request survey. The method of analysis is quantitative analysis using AHP and spatial analysis based on Cellular Automata. The results of the research show that the direction of modeling starts towards the east and south of the research location. Urban residential land in the research location experienced a growth of 4.19% from the previous year in 2014 covering an area of ​​11.96 Km2 increasing by 15.26 Km2 to 27.22 Km2 in 2034. The modeling results also show that in the 2014-2019 range is the range in which growth the highest settlement that occurred was 5.7%. The development of settlements resulted in the conversion of several land uses, namely alang-alang land and mixed gardens. Urban settlements in Tareran District are settlements that experience greater growth among settlements in other districts with a percentage reaching 9.1%.

Land Use Prediction Using Markov – Cellular Automata in the Peusangan Watershed, Aceh

The population growth rate is a factor that causes changes in land use that impact land ecology due to increased population activities related to social, economic, and cultural aspects. Land use change aims to develop facilities and infrastructure to meet the population's needs. This research seeks to interpret land-use changes in 1999, 2008, and 2019 and predict land use in the Peusangan watershed in 2030. The map overlay method analyzes land use change in 1999-2008, 2008-2019, and 2019-2030. In predicting land use, this study uses the Cellular Automata approach. The results of the analysis specifically show that the trend of land use change until 2030 is a decrease in the area of forest land use covering an area of 11,014 ha (4.27%), open land covering an area of 31 ha (0.01%), shrubs 6,083 ha (2.36%), and water bodies covering an area of 459 ha (0.18%). On the other hand, it is predicted that in 2030 the Peusangan watershed will see the most significant increase in land use for plantations of 14,225 ha (5.52%), followed by land use of 1,664 ha (0.65%), 817 ha (0.32%), settlements covering 710 ha (0.28%), 132 ha of rice fields (0.05%), and 28 ha of pond land use (0.01%). The results of this study are expected to be input for policymakers regarding land use planning in the Peusangan watershed in the future

The Cellular Automata Approach in Dynamic Modelling of Land Use Change Detection and Future Simulations Based on Remote Sensing Data in Lahore Pakistan

Rapid urbanization has become an immense problem in Lahore city, causing various socio-economic and environmental problems. Therefore, it is noteworthy to monitor land use/land cover (LULC) change detection and future LULC patterns in Lahore. The present study focuses on evaluating the current extent and modeling the future LULC developments in Lahore, Pakistan. Therefore, the semi-automatic classification model has been applied for the classification of Landsat satellite imagery from 2000 to 2020. And the Modules of Land Use Change Evaluation (MOLUSCE) cellular automata (CA-ANN) model was implemented to simulate future land use trends for the years 2030 and 2040. This study project made use of Landsat, Shuttle Radar Topography Mission Digital Elevation Model, and vector data. The research methodology includes three main steps: (i) semi-automatic land use classification using Landsat data from 2000 to 2020; (ii) future land use prediction using the CA-ANN (MOLUSCE) model; and (iii) monitoring change detection and interpretation of results. The research findings indicated that there was a rise in urban areas and a decline in vegetation, barren land, and water bodies for both the past and future projections. The results also revealed that about 27.41% of the urban area has been increased from 2000 to 2020 with a decrease of 42.13% in vegetation, 2.3% in barren land, and 6.51% in water bodies, respectively. The urban area is also expected to grow by 23.15% between 2020 and 2040, whereas vegetation, barren land, and water bodies will all decline by 28.05%, 1.8%, and 12.31%, respectively. Results can also aid in the long-term, sustainable planning of the city. It was also observed that the majority of the city's urban area expansion was found to have occurred in the city's eastern and southern regions. This research also suggests that decision-makers and municipal Government should reconsider city expansion strategies. Moreover, the future city master plans of 2050 must emphasize the relevance of rooftop urban planting and natural resource conservation.

Spatial and Temporal Modeling of Land use/Land cover Change at the Ca River Basin (North Central Viet Nam) Using Markov Chain and Cellular Automata Approach

Spatial and Temporal Modeling of Land use/Land cover Change at the Ca River Basin (North Central Viet Nam) Using Markov Chain and Cellular Automata Approach

On-Street Cruising for Parking Model in Consideration with Gaming Elements and Its Impact Analysis

On-street cruising by drivers impedes the effectiveness of road traffic conditions and increases energy consumption and environmental impact. Existing models of on-street cruising for parking mainly embody those intrinsic on-street parking factors and disregard the extrinsic impacts from off-street parking gaming factors. This research focused on both the intrinsic and extrinsic elements, especially gaming factors, of off-street parking, i.e., the price of off-street parking, the waiting time of off-street parking, and the difference in walking time between their parking lots to their destinations. On-street cruising for a parking model is reconstructed in this paper in consideration with the equilibrium cruising time, i.e., the maximum tolerable cruise time after evaluating the cost of on-street and off-street parking. Correlation analysis showed that the off-street parking gaming factors were all positively related with the maximum tolerable cruise time. A simulation model was further presented for on-street cruising for the parking model by the cellular automata approach with real-world data. Simulation experiments demonstrated that the average speed of vehicles on the street increases by 9.858 km/h, the average delay decreases by 44.934 s, and the price of on-street parking increases by 4.5 CNY/h. The proposed on-street cruising for parking model proved effective by decreasing the maximum tolerable cruising time to bring significant improvements in average speed, average delay, and on-street cruising vehicles in road traffic flow.

Modeling fall armyworm resistance in Bt-maize areas during crop and off-seasons

Entomologists have often used computational modeling to study the dynamics of insects in agricultural landscapes. Recently, important issues such as the movement of adults and immatures associated with insect resistance to GMO (genetically modified organism) crops have been addressed using computational models. We developed an individual-based model using the cellular automata approach (CA) to investigate how an intercropping system composed of maize engineered with Bacillus thuringiensis (Bt) gene, refuge areas (non-Bt maize), and grasses combined with off-season periods might influence the evolution of resistance in Spodoptera frugiperda (Lepidoptera: Noctuidae), one of the leading agricultural pests targeted by GMOs. We designed the Bt and non-Bt plants in two different arrangements: (a) a seed mixture and (b) strips rows, adding grasses in areas adjacent to the field. We added the seasonal planting dynamics (crop season and off-season), to evaluate a total of six agricultural scenarios. We followed a crop calendar from the United States to create simulations close to agricultural practice. The results showed that the frequency of the resistance allele was strongly related to the landscape arrangements and their dynamics. Since the adult insects are mobile, the seed-mixture scenario increased the frequency of the resistance the most (95.86%), followed by strips (82.10%), without grass fields. The maize harvest made it possible to reduce the frequency of resistance allele below 1%. Based on our results, we can expect that the maintenance of pasture areas, for instance next to the corn crops, will act as a reservoir of susceptible insects during off-season periods.

Assessing the Impact of Contact Tracing, Quarantine and Red Zone on the Dynamical Evolution of the Covid-19 Pandemic using the Cellular Automata Approach and the Resulting Mean Field System: A Case study in Mauritius

A cellular automaton (CA) depicting the dynamics of the Covid-19 pandemic, is set up. Unlike the classic CA models, the present CA is an enhanced version, embodied with contact tracing, quarantine and red zones to model the spread of the Covid-19 pandemic. The incubation and illness periods are assimilated in the CA system. An algorithm is provided to showcase the rules governing the CA, with and without the enactment of red zones. By means of mean field approximation, a nonlinear system of delay differential equations (DDE) illustrating the dynamics of the CA is emanated. The concept of red zones is incorporated in the resulting DDE system, forming a DDE model with red zone. The stability analysis of both systems are performed and their respective reproduction numbers are derived. The effect of contact tracing and vaccination on both reproduction numbers is also investigated. Numerical simulations of both systems are conducted and real time Covid-19 data in Mauritius for the period ranged from 5 March 2021 to 2 September 2021, is employed to validate the model. Our findings reveal that a combination of both contact tracing and vaccination is indispensable to attenuate the reproductive ratio to less than 1. Effective contact tracing, quarantine and red zones have been the key strategies to contain the Covid-19 virus in Mauritius. The present study furnishes valuable perspectives to assist the health authorities in addressing the unprecedented rise of Covid-19 cases.

Modeling microalgae biofilms morphology using a 2-D cellular automaton approach to reveal the combined effect of substrate and light

The microalgal biofilm morphology can influence the bulk transport of nutrients and subsequently affect the growth process of the microalgal biofilm and its final biomass. Light is the energy base for microalgae and profoundly affects their growth, but how light intensity affects the morphology of microalgae biofilms has not been well studied. Here, we have confirmed experimentally and by a 2-D cellular automata model that light and nutrient concentrations together determine the morphology of microalgal biofilms. From the experiments conducted, at a NO3-N concentration of 2 mg/L, the biofilm morphology produced at high light intensities was very rough and granular, whereas at low light intensities, the biofilm was flat and smooth. Meanwhile, at sufficiently high concentrations of NO3-N, a flatter, smoother biofilm was produced regardless of the light intensity. This conclusion was also confirmed using the 2-D cellular automata model. Using the model, we established that the effect of light intensity on biofilm morphology is mainly twofold: the effect on the maximum growth rate of the microalgae and the depth of light penetration into the biofilm. The significance of these two effects changes as the bulk concentration varies, which in turn, leads to the biofilm morphology responding differently to changes in light intensity at different bulk concentrations. Based on the effects of light intensity and bulk concentration, a redefined Thiele module (Th) is proposed for microalgal biofilms. We demonstrate that the compactness of the biofilm decreased logarithmically while roughness increased logarithmically as the Th number increased when Th > 3.

Cellular automaton approach for carrier degeneracy effects on the electron mobility of high electron mobility transistors

GaN-based high electron mobility transistors (HEMTs) are expected to have high performance in base station applications. Recently, it was reported that the combination of the Poisson–Schrödinger method and cellular automaton method is effective for predicting the mobility of channel two-dimensional electron gas of GaN HEMTs. In the operation condition of HEMT, the surface electron density of the channel is on the order of 1013 cm−2, and the effect of degeneracy cannot be ignored in calculating the mobility. Since the electron distribution function is always stably obtained by the cellular automaton method, the degeneracy effect can be considered stably. In this paper, through the comparison of different degeneracy evaluation methods, the anisotropy of the electron distribution function under the electric field acceleration is clarified to affect the HEMT mobility prediction significantly.

Hydrodynamically driven facet kinetics in crystal growth

In this paper we show that the presence of liquid flow around a crystal growing from melt can induce dissymmetry in growth similar to that described by anisotropic interfacial kinetic coefficients. A front tracking interface model based on a cellular automaton approach was applied to the growth of a Fe2Al5 crystal (also known as top dross particle) in a saturated Zn melt at constant temperature. The growth rate was found to be influenced by the intensity of the melt flow and by the direction of the flow with respect to the crystal orientation. The magnitude and the direction of flow modify the diffusion boundary layer, changing the conditions (temperature and concentration) at the facet interface, therefore the mass transfer. We have shown that despite the isotropy of interfacial kinetics, hydrodynamics was able to introduce an anisotropy in the crystal growth similar to the natural anisotropy in interfacial kinetics of the facets. The facets grow rate was found to be strongly dependant on the Reynolds number as well as on the orientation of the crystalline orientation with respect to the flow direction.

Simulation of crowd dynamics in pedestrian evacuation concerning panic contagion: A cellular automaton approach

The study of the panic evacuation process is of great significance to emergency management. Panic not only causes negative emotions such as irritability and anxiety, but also affects the pedestrians decision-making process, thereby inducing the abnormal crowd behavior. Prompted by the epidemiological SIR model, an extended floor field cellular automaton model was proposed to investigate the pedestrian dynamics under the threat of hazard resulting from the panic contagion. In the model, the conception of panic transmission status (PTS) was put forward to describe pedestrians’ behavior who could transmit panic emotions to others. The model also indicated the pedestrian movement was governed by the static and hazard threat floor field. Then rules that panic could influence decision-making process were set up based on the floor field theory. The simulation results show that the stronger the pedestrian panic, the more sensitive pedestrians are to hazards, and the less able to rationally find safe exits. However, when the crowd density is high, the panic contagion has a less impact on the evacuation process of pedestrians. It is also found that when the hazard position is closer to the exit, the panic will propagate for a longer time and have a greater impact on the evacuation. The results also suggest that as the extent of pedestrian’s familiarity with the environment increases, pedestrians spend less time to escape from the room and are less sensitive to the hazard. In addition, it is essential to point out that, compared with the impact of panic contagion, the pedestrian’s familiarity with environment has a more significant influence on the evacuation.

Prediction of grain-size transition during solidification of hypoeutectic Al-Si alloys by an improved three-dimensional sharp-interface model

Control of grain size during solidification is an important issue according to the desired usage properties. In this study, both microstructure characterizations and numerical simulations are performed for as-cast hypoeutectic Al-Si alloys to understand the mechanism of grain-size transition with initial Si contents. An improved three-dimensional (3D) sharp-interface model is developed that couples cellular automaton (CA) approach with a deterministic mesh-anisotropy reduction (DMAR) algorithm. The improved sharp-interface model is able to accurately calculate interface curvature and reproduce reasonable dendrite morphology within a wide range of cooling rates. It is found that grain size first decreases with increasing the initial Si content to 3 wt% and then increases with further Si additions. The nucleation undercooling significantly increases with increasing the Si content from 3 wt% to 10 wt% due to a Si-poisoning effect. The grain-size transition is mainly determined by the variations in the nucleation undercooling. Analysis using the Interdependence model also supports that a wide nucleation-free-zone is formed during solidification of Al-10 wt% Si alloy induced by a large nucleation barrier and a decreased growth velocity.

Empirical dependence of the probability of blocks rotations on the diffusion coefficient in a cellular automaton with a Margolus neighbourhood

The paper considers a cellular automaton approach to modeling physical processes, in particular, the diffusion of pulsed periodic gas discharges in plasma. An attempt to determine the dependence of the probability of the block rotation on the diffusion coefficient for a cellular automaton diffusion model with a Margolus neighborhood is describe. Some features of the tensor approach to the implementation of random block cellular automata are described. The results of computer experiments are presented. The analysis of this results indicates that the data from the literature sources differ from the data obtained during the experiment.