Environmental Simulation Models Research Articles

Environmental Simulation Model for Rapid Prediction of Tea Seedling Growth

Accurate and effective monitoring of environmental parameters in tea seedling greenhouses is an important basis for regulating the seedling environment, which is crucial for improving the seedling growth quality. This study proposes a tea seedling growth simulation (TSGS) model based on deep learning. The Internet of Things system was used to measure environmental change during the whole seedling process. The correlation between the environmental parameters and the biomass growth of tea seedlings in various varieties was analyzed. A CNN-LSTM network was proposed to build the TSGS model of light, temperature, water, gas, mineral nutrition, and growth biomass. The results showed that: (1) the average correlation coefficients of air temperature, soil temperature, and soil moisture with the biomass growth of tea seedlings were 0.78, 0.84, and −0.63, respectively, which were three important parameters for establishing the TSGS model. (2) For evaluating the TSGS model of a single variety, the accuracy of ZM’s TSGS based on the CNN-LSTM network was the highest (Rp2 = 0.98, RMSEP = 0.14). (3) For evaluating the TSGS model of multiple varieties, the accuracy of TSGS based on the CNN-LSTM network was the highest (Rp2 = 0.96, RMSEP = 0.17). This study provided effective technical parameters for intelligent control of tea-cutting growth and a new method for rapid breeding.

Deep Learning in Security of Internet of Things

Internet-of-Things (IoT) technology is increasingly prominent in the current stage of social development. All walks of life have begun to implement the IoT integration technology, so as to strive to promote industrial modernization, intelligence, and digitalization. In this case, how to link high-risk network activities with entities has become the primary issue for promoting industrial development. However, at this stage, the security issues in the development of the IoT technology have contradictions that are difficult to resolve. According to this situation, how to make system defense intelligent and replace manual monitoring has become the future of the development of security architecture. This article combines existing security research to explore the possibility of deep learning (DL) in upgrading the IoT security architecture, discusses how the IoT can identify and respond to cyber attacks, and how to encrypt edge data transmission. Moreover, this article discusses security research in application fields, such as Industrial IoT, Internet of Vehicles, smart grid, smart home, and smart medical. Then, we summarized the areas that can be improved in future technological development, including sharing computing power through the edge network processing unit (NPU) central device and closely combining the environmental simulation model with the actual environment, as well as malicious code detection, intrusion detection, production safety, vulnerability detection, fault diagnosis, and blockchain technology.

Optimization of Parameters for Pedestrian Simulation Software: A Case Study of Emergency Evacuation Experiments

This research study provides a new framework to optimize pedestrian simulation parameters required to replicate emergency evacuation conditions specifically observed in high rise buildings, passenger vehicles and transport terminals. The simulation experiments are performed with generalised social force model in VISWALK simulation environment. The data required for optimization are obtained by conducting several evacuation experiments. The results indicate that pedestrian behavioural aspects, such as the relaxation time, distance from the other pedestrian and force exerted by closest pedestrians, have a significant impact on total evacuation time. The outcomes are in consistence with field observations and the calibrated parameters would help in simulating future scenarios including building level simulations and further simulating emergency evacuation of passengers from transport terminals and vehicles.

A novel asymmetric compound parabolic collector under experimental and numerical investigation

In this study a novel compound parabolic collector (CPC) with an asymmetric reflector and an evacuated U-pipe tubular receiver was examined numerically and experimentally. The thermal operation of the system was tested in a range of 22–70 °C inlet temperature in the city of Athens in Greece, using water as the working fluid. The collector was oriented towards the sun in each case, while the measurements where conducted for 10 min regarding each operating point. The data acquisition as regards the solar irradiation intensity, the inlet, the outlet and the ambient temperature was conducted every 30 s. The experimental results were also validated by developing a numerical model in SolidWorks Flow Simulation environment. Particularly, it was found that the numerical results diverge from the experimental one by 3% on average, with the maximum declination to take the value of 5.17%. By this simulation it was possible to estimate the temperature of the receiver and the convection regime at the interior of the U-pipe. The convective coefficient at the interior of the flow tube was also validated through a theoretical model. Last but not least, the collector was compared with three other designs taken from literature as regards the optical performance.

Комплексный алгоритм процессов контроля и управления телекоммуникационной сетью Carrier Ethernet с применением механизмов ОАМ

Purpose: Analysis, classification of a variety of mechanisms in OAM (Operations, Administration and Management) methodology, development of an algorithmic model of the proposed classification taking into account the features of managing telecommunication network, which functions with Carrier Ethernet technology, that will allow to improve software-technology complex of subsystems and axrise the efficiency of telecommunication network management. Methods: System/control theory provisions, simulation modeling and algorithmic structure design methods. Results: Classification of a variety of OAM mechanisms has been obtained which will enable adequately upon goals and tasks of telecommunication network management the inclusion of unique processes and mechanisms of OAM methodology into the control/management of devices of telecommunication network, based on Carrier Ethernet technology; comprehensive algorithm of OAM processes for managing Carrier Ethernet network devices has been developed that will allow to hold simulation modeling and evaluation of individual subprocesses and entire algorithm functioning. Practical significance: Expansion of the list of processes implemented in OAM telecommunication networks, that’re based on Carrier Ethernet technology, will allow achieving the required level of management efficiency as well as conducting a number of studies, in particular, simulation modeling of control systems with inclusion into a model of being controlled object, functioning in accordance with standardized OAM mechanisms. Possibility to obtain results in AnyLogic simulation modeling environment will allow to use them as an independent program for remote setting at technological level, accordingly telecommunication network management systems, of network devices.

Aircraft-Type-Specific Impact of Speed Brakes on Lift and Drag

The increasing influence of current research in air traffic management on daily flight operations leads to a stronger consideration of individually optimized aircraft trajectories. However, in the dichotomy between ecological, economic, and safety-based optimization goals, four-dimensionally optimized trajectories are subject to severe constraints in terms of position and speed. To fully assess the performance envelope of these trajectories, precise modelling of the influence of secondary control surfaces on flight performance is necessary. In particular, the use of speed brakes can significantly influence the descent and speed profile and allows the implementation of different cost indices. In this study, we present a modelling approach of the influence of extended speed brakes on flight performance and apply this method in a simulation environment for trajectory modelling of twelve different aircraft types. In doing so, we can determine an almost linear influence of the additional fuel requirement from the effective area of the speed brakes. The results can be implemented in any flight performance model and enable more precise modelling of future aircraft trajectories. Specifically, optimization targets regarding the required time of arrival, or the cost index and the consideration of the dynamic impact of atmospheric conditions in the trajectory optimization, only becomes possible through the calculation of the influence of the speed brake on lift and drag.

Optimization of differentiated regional land development patterns based on urban expansion simulation—A case in China

AbstractThe advancing global urbanization puts great pressure on the society and ecosystem, especially in developing countries. Reasonable land‐use policies adapted to local conditions are the key issues to prevent disordered urban expansion. Multi‐scenario simulation provides a new perspective for differentiated policy formulation based on regional heterogeneity. Regarding the Shaanxi Province, a rapid urbanized area with high spatial heterogeneity in western China, as the study case, we tracked its past land‐use changes and predicted the characteristics of urban expansion using the Future Urban‐Regional Environment Simulation model. We found that (1) during the past 35 years, built‐up land evidently increased accompanied by the loss of cropland, grassland, and unused land. (2) The urban expansion mainly will occur in the areas with flat terrain under three scenarios. (3) The urban expansion will transit into the “requiring land from mountains” pattern in the future, which means that it will gradually spread to areas with higher slopes. (4) Differentiated and optimal development patterns are proposed for different subregions by accounting the loss of ecosystem service in the procedure of urban expansion. This research can help local governments formulate differentiated future macro control of territorial spatial planning to optimize subregional land development.

Smart Computing Techniques for Predicting Soil Compaction Criteria under Realistic Field Conditions

The primary objective of this paper was to develop an artificial neural network (ANN) simulation environment and mathematical models for predicting with high accuracy soil compression parameters. The experiments were conducted at the College of Agriculture - University of Basra, located at Garmat Ali, the soil was silty clay loam. The factors that were investigated are moisture content (14 and 24%), tillage depths (0, 15, 30, 45, and 50 cm) forward speeds (0.57, 0.94, and 1.34 m.s-1) and tire pressures (50, 100, and 150 kPa). ANN environment was developed with the back propagation algorithm using MATLAB software with various structures and training algorithms. Design Expert software utilized to evaluate the studied parameters and produce mathematical models. The results showed that all studied parameters had a significant effect on soil physical properties including bulk density and cone index. The effects of the studied factors on bulk density were depth > moisture content > forward speed, > tire pressure (6% 4%, 2.4%, 2%, respectively). Whereas, the order of the investigated factors based on their effects on cone index were depth > moisture content > tire pressure > forward speed (6%, 4%, 2.4% and 2%, respectively). The best model for predicting the bulk density under different field conditions was the 4-8-1 architecture. Levenberg-Marquardt (Trainlm) produced outstanding performance with an MSE of 0.00226 and R2 of 0.986. Moreover, this performance was occurring at an epoch of 100. For predicting cone index, the best performance was achieved by Levenberg-Marquardt (trainlm) in 85 epochs, giving minimum MSE equal to 0.005112 and greater (R2) equal to 0.967 during the training process. Thus, the optimal structure for predicting cone index was 4-7-1.

Three-dimensional numerical simulation of multi-physical coupled environment during electromagnetic propulsion

Electromagnetic propulsion technology is a new propulsion technology which uses electromagnetic force to push objects into high or ultra-high speed. However, during propulsion, the armature and launch load are affected by harsh multi-physics environment. The coupled effect was often ignored or over idealized in previous numerical simulations, which leads to large errors between simulation and experiment. In this paper, a three-dimensional multi-physics coupling environment simulation model is established. The distribution of electromagnetic field, structure field and temperature field in armature from static to high speed are effectively calculated. Moreover, the coupled effect between physical fields and the influence of key parameters on the simulation results are revealed. In conclusion, this model can reproduce the physical field distribution of armature and rail during electromagnetic propulsion. The time-varying resistance and inductance and the velocity skin effect (VSE) are the key parameters affecting armature movement. This method reveals a feasible path for the simplification of multi-physical model and the mitigation of extreme environment.

Исследование характеристик бесконтактной машины постоянного тока при косвенном измерении момента нагрузки

Vector control of an induction motor with indirect torque measurement eliminates the need for a torque sensor. This approach is applicable to study the characteristics of BLDC machine loaded by an induction machine powered by a frequency converter. A mathematical model of a BL DC machine loaded by an induction electric drive and the implementation of this model in the SimInTech dynamic simulation environment are considered. As a result of mathematical modeling, transient processes in terms of speed and Speed-Torque curve are obtained. Comparison of the values of characteristic points with specification data confirms the correctness of the mathematical model and the possibility of using indirect measurement of the torque set by the frequency converter to study the characteristics of a BL DC machine.

Exploring the Added-Value of Integrating Real-Time Location Systems for Tracking Critical Maintenance Tools

Searching and optimally locating maintenance tools is an important undertaking that influences productivity. The efficiency lost can be high for intensive maintenance processes, particularly in instances where technicians share critical (and expensive) tooling. Real-Time Location Systems (RTLS) can serve as a feasible solution for minimizing travel and search times, by tagging tools, thereby dynamically tracking their spatial location real-time. Moreover, RTLS can be deployed alongside Automated Guided Vehicles (AGV’s) thereby supporting smart material handling.In this paper, we propose a model for exploring the added value of implementing RTLS with AGV to better support maintenance processes in high-demand manufacturing and maintenance shop floors. The NetLogo (multi-agent programmable environment) simulation model mimics interactions of maintenance technicians, tasks, and critical tooling within an aircraft maintenance facility. To evaluate the added value of tagging critical tooling to better enhance efficiency locating tools, we define three use-cases. The first case mimics a current scenario in which critical tools are untagged, hence assuming significant search and travel times are incurred by technicians. The second case explores scenarios where tools are tagged, and trackable within the spatial environment of the hangar. The third case integrates both RTLS and AGVs to support both locating tools, and minimising travel times by technicians. Initial simulations results show significant added value for the second and third experiments, verifying suitability of implementing RTLS for complex maintenance and manufacturing processes.

An Improved Cellular Automaton Traffic Model Based on STCA Model Considering Variable Direction Lanes in I-VICS

In this paper, we propose an improved cellular automaton model for the traffic operation characteristics of variable direction lanes in an Intelligent Vehicle Infrastructure Cooperation System (I-VICS). According to the proposed flow of variable oriented lane operation in the I-VICS environment, the idea for the improved model has been determined. According to an analysis of different signal states, an improved STCA model is proposed, in combination with the speed induction method of I-VICS and the variable direction lane switching strategy. In the assumed regular simulation environment, the STCA and STCA-V models are simulated under different vehicular densities. The results indicated that traffic parameters such as traffic flow and average speed of the variable direction lanes in the I-VICS environment are better than those in the conventional environment according to the operating rules of the proposed model. Moreover, lane utilization increased for the same density.

Simulation of a vessel sensor network of ZigBee standard

The subject of the paper is a vessel sensor network designed to collect data from wireless sensors for various purposes. The peculiarity of this network application is the presence of a large number of premises, wireless communication between which is complicated. One of the possible approaches to solving this problem is to use coordinators connected by a switch into a local network, and a large number of routers that provide data relaying along the chain. Studies of the proposed vessel wireless network in the OMNeT ++ simulation modeling environment using Castalia framework are carried out in the paper. The process of modeling both the network itself and its individual components, and various modes of their operation is shown. The interaction of network nodes through intermediate routers is considered. Estimation of losses during packet delivery along a chain of routers, the time spent on processing packets in routers and delays in packet delivery to the network coordinator from the sending node is based on the compiled model. It is concluded that with the increasing complexity of the network structure (growth in the number of routers), there is a proportional rise of the packets delivery delay over the wireless network to the vessel local network. However, all transmitted packets are delivered to the addressee.

Theoretical Study on the Relationship of Building Thermal Insulation with Indoor Thermal Comfort Based on APMV Index and Energy Consumption of Rural Residential Buildings

In the field investigation of rural dwellings, it was found that thermal feelings are significantly different with varied envelopes even under the same indoor air temperature, and this paper explores the phenomenon in simulation. Based on building thermal investigations in several villages of North China, a typical energy and environment simulation model for rural residences was developed using DeST, and the hourly parameters of temperature and humidity were used to calculate the adaptive thermal comfort (APMV) of the rooms. The results show that the main reason for the different thermal comfort at the same air temperature is the large difference in the inner surface temperature. By adjusting the insulation thickness of the envelope structure, the relationship between it and the APMV value is obtained. By adjusting the insulation thickness of the enclosure structure and getting the correlation between it and the APMV value, it is obtained that when the heat transfer coefficient of the enclosure structure meets 0.5 W/(m2·K), the indoors can be in thermal comfort. This paper considers that the indoor air temperature cannot represent the APMV to evaluate the indoor thermal comfort, and the APMV value should be used to evaluate the thermal comfort of the renovated building and calculate the corresponding energy saving rate.

Dynamic influencing mechanism of traditional settlements experiencing urbanization: A case study of Chengzi Village

With the rapid progress of urbanization around the world, more and more traditional settlements are destroyed and disappeared, and the ecological experience which can effectively improve many current urban problems in traditional settlements also have disappeared. In this context, this research aims to examine the renewal of traditional settlements from a dynamic perspective, using digital twins to simulate the changes in settlement spatial forms, underlying surface materials and building facade materials, and to explore the ecological wisdom of traditional settlements. Achieve the unity of traditional feature and functional requirements of settlements in the process of urbanization. Furthermore, the research results can provide enlightenment for the modern translation of traditional settlements and urban construction. The complete research methods can also provide reference for the study of traditional settlements around the world. Through a comprehensive research method combining field measurement, field investigation and ENVI-met (a building environment simulation model) simulation, the microclimate of Chengzi Village, a typical traditional settlement in China, was studied. The results obtained in the above method shown that: (1) in the microclimate inference mechanism, traditional settlements’ spaces are highly efficient; (2) microclimate regulation of traditional settlements benefits mostly from the surface material, spatial form and building facade material; and (3) through a comparative study, it is concluded that in the process of urbanization, it is better for the spatial form to remain unchanged, but the building façade material can be changed appropriately. Concluded this study, the research results can not only promote the sustainable development of Chengzi village, but also provide experience for the modern translation of traditional settlements under similar circumstances around the world, which has important practical significance. In addition, The synergistic dynamic influence mechanism of development -inheritance is particularly important for the sustainable development of traditional settlements.

Study on Shortwave Signal Coverage Based on ITU-R P.533 Model

In this paper, the short-wave signal propagation modeling, short-wave electromagnetic environment simulation modeling, short-wave electromagnetic environment level evaluation modeling, simulation modeling of receiving antenna commonly used in short wave and other contents are studied in depth, in terms of short-wave electromagnetic environment and antenna simulation simulation. A more complete propagation model of short-wave signal, simulation model of short-wave electromagnetic environment, evaluation model of short-wave electromagnetic environment level and simulation model of receiving antenna commonly used in short-wave are established. Finally, the effectiveness of each model is verified by repeated comparative tests and experiments.

A real-time dynamic path planning method combining artificial potential field method and biased target RRT algorithm

In order to improve the efficiency and effectiveness of path planning for mobile robots in dynamic environment, based on the comprehensive analysis of multiple path planning algorithms, an improved algorithm based on fast-spreading random tree algorithm is proposed. The proposed algorithm effectively combines the artificial potential field(APF) method with the biased target RRT algorithm, and judges the local minimum point in the process of solving the APF method to complete the switching with the biased target RRT algorithm. The motion environment simulation model is established in the Python environment, and the path planning simulation case of the mobile robot in the dynamic environment is completed. The simulation results show that the combined algorithm can avoid the phenomenon that the APF method falls into the local minimum point while taking the global and real-time performance into account, reduce the planning time of the biased target RRT algorithm, and improve the quality of path generation.

An intelligent optimization method of E-commerce product marketing

In order to improve the marketing effect of e-commerce products, based on machine learning algorithms, this paper constructs an e-commerce product marketing model based on machine learning and SVM. Moreover, this paper studies the classic reinforcement learning algorithm Q-learning and proposes an improved Q-learning algorithm. In addition, this paper uses the method of mean standardization to reduce the noise impact of the reward signal caused by the unfixed time interval between decision points, further constructs a standardization factor for the deviation caused by the asynchronous update of the time interval in the iterative process of the Q value function and updates the standardization factor according to the update method of the value function, and proposes the Interval-Q algorithm. At the same time, in view of the fact that traditional reinforcement learning algorithms cannot effectively deal with the observable part of customer status in direct marketing scenarios, based on the deep reinforcement learning DQN model, this paper combines with the idea of hybrid model to propose a DQN model based on dual networks. Finally, this paper uses public data sets for model training and simulation environment construction and then evaluates the algorithm proposed in this paper from different angles and analyses model performance based on examples. From the research results, it can be seen that the precision marketing model constructed in this paper has a good effect and can be applied to practice.

Economic and environmental consequences of nitrogen application rates, timing and methods on corn in Ontario

Large scale adoption of nitrogen (N) management practices, including the 4Rs, could lead to beneficial environmental and economic outcomes, but only if they improve agricultural profit or are driven by policy and legislation. This study uses a spatial economic maximization and environmental simulation model to examine the economic and environmental tradeoffs of adopting three different 4R practices, specifically N rate reduction, timing (sidedress versus at-planting) and placement methods (broadcast versus injection) in Ontario corn production, under alternative annual weather conditions. The study shows that the use of optimized agronomic, based on meeting crop N requirements specific to each fertilizer management practice, rather than historic, N application increases annual average Ontario-wide farm profit from $124 million to $173 million (39.5%), decreases N application from 122 to 97 kt (20.5%), decreases nitrous oxide (N2O) emissions from 3.4 to 2.4 kt (29.4%), decreases ammonia (NH3) volatilization from 12.4 to 1.2 kt (90.3%) and decreases nitrate (NO3−) leaching from 47 to 13 kt (72.3%), over 30-years of weather data. Injection and sidedress appear to be more N use efficient than broadcast, with sidedress becoming increasingly important as N prices and constraints increase. N2O emissions appear to be more difficult to mitigate compared to NH3 emissions and NO3− leaching. Regarding the 4Rs, right placement and right timing play a role under specific spatial conditions, while right rate appears to be the most effective means to mitigate the environmental impacts of corn N application and may be mutually beneficial to farmers and society.

KiMoSys 2.0: an upgraded database for submitting, storing and accessing experimental data for kinetic modeling

The KiMoSys (https://kimosys.org), launched in 2014, is a public repository of published experimental data, which contains concentration data of metabolites, protein abundances and flux data. It offers a web-based interface and upload facility to share data, making it accessible in structured formats, while also integrating associated kinetic models related to the data. In addition, it also supplies tools to simplify the construction process of ODE (Ordinary Differential Equations)-based models of metabolic networks. In this release, we present an update of KiMoSys with new data and several new features, including (i) an improved web interface, (ii) a new multi-filter mechanism, (iii) introduction of data visualization tools, (iv) the addition of downloadable data in machine-readable formats, (v) an improved data submission tool, (vi) the integration of a kinetic model simulation environment and (vii) the introduction of a unique persistent identifier system. We believe that this new version will improve its role as a valuable resource for the systems biology community. Database URL: www.kimosys.org