Analytical Model Simulations Research Articles

Optimal dispatching of wind turbine-photovoltaic-pumped storage new energies and thermal generators combined distribution network

This paper mainly investigates the optimal dispatching problem of the combined distribution network consisting of wind turbine generators (WTGs), photovoltaic generators (PVGs), pumped storage generators (PSGs) and thermal generators (TGs). According to the load demand in the distribution network and the output conditions of different renewable energy generators, PSGs and TGs, a joint optimal dispatching model based on the operation cost of the distribution network is set up. Based on the power flow model of second-order cone relaxation (SOCR) technology, the nonlinear constraints on voltage and current in the distribution network are linearized, so as to solve the cost optimization scheduling problem more efficiently. Finally, an improved IEEE33-node distribution network is used as the basic grid model for simulation analysis, so as to verify the effectiveness of the proposed model.

Quantifying interactions in the water-energy-food nexus: data-driven analysis utilizing a causal inference method

Introduction: There is a pressing need for a holistic approach to optimize water-energy-food (WEF) resources management and to address their interlinkages with other resources due to population growth, socio-economic development, and climate change. However, the structural and spatial extent of the WEF system boundaries cause exponential growth in computational complexity, making exploratory data analysis crucial to obtain insight into the system’s characteristics and focus on critical components.Methods: This study conducts a multiscale investigation of the WEF nexus within the Canadian prairie provinces (Alberta, Saskatchewan, and Manitoba), utilizing causal-correlational analysis and the multispatial Convergence Cross Mapping (mCCM) method. Initially, we employed regression analysis to establish equations, along with their coefficients of determination (R2), to identify patterns among pairs of WEF sectors, gross domestic product (GDP), and greenhouse gas (GHG) emissions. Subsequently, we conducted a causal analysis between correlated pairs using the mCCM method to explore the cause-and-effect relationships between sector pairs within the Canadian prairie provinces; both individually and as a single unit over the period 1990-2020.Results and discussion: Results show that energy and water are the most influential sectors on GHG emissions and GDP in the prairies as a whole. Energy has a stronger influence on GHG compared to water and food sectors, while water has the strongest causal influence on the GDP of Alberta, and food and energy do so for Saskatchewan and Manitoba, respectively. The trade-offs for improving WEF nexus security strongly depend on the scale of the system under investigation, highlighting the need for careful deliberations around boundary judgment for decision-making. This study provides a better understanding of the WEF-GDP-GHG nexus in the Canadian prairies and existing interrelationships among the aforementioned sectors, helping to build more efficient WEF nexus models for further simulation and scenario analysis.

Research of simulation and experiment on arc characteristics of gas mechanical switch

AbstractAn arc is the high‐temperature discharge plasma produced in the opening process of mechanical switches, which directly affects the breaking capability of a hybrid DC circuit breaker. According to the physical mechanism of an electric arc, the construction of an arc model for simulation analysis is an important technical means in the electrical field. In this study, based on the theory of magneto hydrodynamics (MHD), a gas mechanical switch model of a natural commutation DC circuit breaker with a compound gap is established. The arc motion process under different conditions is simulated and calculated. The influence of different initial pressures, different opening speeds, and different striking currents on the arc voltage characteristics is analysed. The results show that the larger the gas pressure, the smaller the arc volume and the higher the arc voltage. The faster the opening speed, the longer the arc and the higher the arc voltage; with the increase of the current, the arc voltage increases rapidly at a low current, while the arc voltage increases slowly at a high current.

Experimental Digital Twins with Socio-Economic Artificial Environments of Forecast and Analytical Simulation Models

The technological development of Russia in recent years has been moving at an active pace due to external challenges that dictate the need to search for internal resources and poses serious challenges to the scientific community in terms of developing research potential and creating software and technological sovereignty, especially emphasizing the importance of the IT industry and long-term forecasting. Nanotechnology, which incorporates the concepts of IT, is a supra-industry technology, that is, it is the basis for achieving progress in any area of human activity. Without the use of information technology, it will be extremely difficult to achieve outstanding achievements in a dynamically changing world. There is an emerging interest in new computer modeling methods that make it possible to create experimental digital twins in the form of simulation models and can partially compensate for the incompleteness of information. Having modeled the necessary processes, it is possible to make management decisions on the construction of facilities, simulate socio-economic processes, and formulate a 10-year forecast about the demographic situation of the country. The applied modeling tools discussed in the article demonstrate the usefulness of such management tools with developed functional elements in information and analytical management structures. Soon, this trend will increase and those countries that will take leading positions in this direction will be able to create ultra-effective forecasting and analytical scenarios with various levels of detail. By using all the functionality of simulation modeling, it is possible to create truly applied instrumental complexes with a potential basis for the implementation of such solutions in the structures of systems of distributed situational centers for the future development of technological sovereignty and the introduction of fundamentally new methods of strategic forecasting in the Russian Federation.

Research on the design of a novel composite solenoid model ship simulation magnetic source based on DTW

In order to study the simulation ability of a solenoid on a ship magnetic field, a new composite model based on a double row magnetic dipole array model with an ellipsoid was designed. The time-domain characteristics, such as magnetic field characteristics, magnetic inclination cosine, magnetic field scalar gradient, and magnetic field spatial distribution characteristics, were extracted. It was verified that the model can accurately simulate the magnetic field characteristics of ships through ship model experiments and simulation analysis. To further quantitatively and accurately analyze the simulation ability of the composite model for ship magnetic fields, a dynamic time wrapping measurement method based on one-dimensional time series was adopted to calculate the similarity of four characteristic quantities: magnetic field vector, magnetic field modulus, magnetic inclination cosine, and magnetic field scalar gradient. The results showed that the composite model has high simulation ability for ship magnetic fields.

Cost-effectiveness analysis of bevacizumab combined with lomustine in the treatment of progressive glioblastoma using a Markov model simulation analysis.

Progressive glioblastoma (GBM) is a malignancy with extremely poor prognosis. Chemotherapy is one of the approved systemic treatment modalities. The aim of this study is to assess the cost-effectiveness of using bevacizumab (BEV) in combination with lomustine (LOM) regimen for the treatment of progressive glioblastoma in China. The estimation results are derived from a multicenter randomized phase III trial, which demonstrated improved survival in GBM patients receiving BEV+LOM combination therapy. To calculate the incremental cost-effectiveness ratio (ICER) from the perspective of Chinese society, a Markov model was established. Univariate deterministic analysis and probabilistic sensitivity analysis were employed to address the uncertainties within the model. Compared to LOM monotherapy, the total treatment cost for BEV+LOM combination therapy increased from $2,646.70 to $23,650.98. The health-adjusted life years (QALYs) for BEV+LOM combination therapy increased from 0.26 QALYs to 0.51 QALYs, representing an increment of 0.25 QALYs. The incremental cost-effectiveness ratio (ICER) was $84,071.12. The cost-effectiveness curve indicates that within the willingness-to-pay (WTP) range of $35,906 per QALY, BEV+LOM combination therapy is not a cost-effective treatment option for unresectable malignant pleural mesothelioma patients. Taken as a whole, the findings of this study suggest that, from the perspective of payers in China, BEV+LOM combination therapy as a first-line treatment for GBM is not a cost-effective option. However, considering the survival advantages this regimen may offer for this rare disease, it may still be one of the clinical treatment options for this patient population.

Lightweight Computational Complexity Stepping Up the NTRU Post-Quantum Algorithm Using Parallel Computing

The Nth-degree Truncated polynomial Ring Unit (NTRU) is one of the famous post-quantum cryptographic algorithms. Researchers consider NTRU to be the most important parameterized family of lattice-based public key cryptosystems that has been established to the IEEE P1363 standards. Lattice-based protocols necessitate operations on large vectors, which makes parallel computing one of the appropriate solutions to speed it up. NTRUEncrypt operations contain a large amount of data that requires many repetitive arithmetic operations. These operations make it a strong candidate to take advantage of the high degree of parallelism. The main costly operation that is repeated in all NTRU algorithm steps is polynomial multiplication. In this work, a Parallel Post-Quantum NTRUEncrypt algorithm called PPQNTRUEncrypt is proposed. This algorithm exploits the capabilities of parallel computing to accelerate the NTRUEncrypt algorithm. Both analytical and Apache Spark simulation models are used. The proposed algorithm enhanced the NTRUEncrypt algorithm by approximately 49.5%, 74.5%, 87.6%, 92.5%, 93.4%, and 94.5%, assuming that the number of processing elements is 2, 4, 8, 12, 16, and 20 respectively.

Research on the Relationship between Dynamic Characteristics and Friction Torque Fluctuation of CMGB under the Condition of Time-Varying Moment

In this paper, a dynamic simulation analysis model was established for CMGB (control moment gyroscope bearing) under the conditions of time-varying moment. The influences of the moment’s response time, axial preload, and working temperature on the dynamic characteristics and friction torque of CMGB were analyzed, and the relevant verification tests were conducted. The results show that the friction torque fluctuation of CMGB directly corresponds to the dynamic characteristics. The faster the response time of the time-varying moment, the larger the friction torque fluctuation of CMGB. The larger preload minimizes the difference in the ball’s loading state, which is the actual reason for reducing the friction torque fluctuation. Moreover, as the working temperature increases, the friction torque fluctuation of CMGB decreases.

Optimal Design of Thermal Cycling Reliability for Plastic Ball Grid Array Assembly Via Finite Element Method and Taguchi Method

Abstract A finite element simulation analysis model was developed for a plastic ball grid array (PBGA) assembly to analyze its behavior under thermal cyclic loading conditions. The stress distribution in the SAC305 solder joints at different locations within the array was investigated by using ANAND constitutive equations. Subsequently, the thermal fatigue life of the key solder joints was quantified. The study also examined the influence of the solder joint diameter, substrate thickness, solder joint height, printed circuit board (PCB) thickness, and mold compound height on solder joint stress. Optimization of assembly parameters was achieved through the application of the Taguchi method. An extensive analysis was conducted using different assembly parameter combinations, employing the L9(34) orthogonal array design to explore the thermal cycling effects. The computed average Von Mises stress Δσ for the critical thin-layer elements of solder joints located in hazardous positions within the assembly was notably affected by variations in the solder joint height, substrate thickness, solder joint diameter, and mold compound height. This impact ranked in descending order of significance as solder joint height, substrate thickness, solder joint diameter, and mold compound height. The optimal parameter combination determined was a solder joint height of 0.70 mm, a solder joint diameter of 0.85 mm, a substrate thickness of 0.51 mm, and a mold compound height of 1.12 mm. Implementing this optimized configuration led to a significant 4.07% reduction in average stress Δσ for the critical thin-layer elements within hazardous solder joints. Moreover, the extension of the thermal fatigue life was notably improved, achieving an impressive 51.72% increase.

Assessment of extreme rainfall events over the Indian subcontinent during the historical and future projection periods based on CMIP6 simulations

AbstractThe impact of climatic change on the summer monsoon season is studied to understand the rainfall pattern towards the end of the century utilizing the Coupled Model Intercomparison Project, Phase 6 (CMIP6) released by the World Climate Research Programme (WCRP). The analysis of model simulations from CMIP6 was carried out using 64 years of the historical period (1951–2014) and future projections till the end of the century (2015–2100). The models are compared with observed daily rainfall data from the APHRODITE (Asian Precipitation‐Highly‐Resolved Observational Data Integration Towards Evaluation). The analysis revealed that most of the models show an overestimation in the annual cycle of rainfall in the historical period; however, a few of them underestimate the values. The majority of them capture the onset signal of the summer monsoon in early June, along with a good seasonality in the daily rainfall climatology. The simulations that are coherent with the observational data sets are selected on the basis of the Taylor diagram for future projections in four scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5). The projections of the aforementioned scenarios are taken from the model outputs of EC‐Earth3‐Veg‐LR, INM‐CM4‐8, INM‐CM5‐0, MIROC‐ES2L and MPI‐ESM1‐2‐HR. The selected models exhibit far greater agreement among the 30 models when it comes to the features of rainfall during the summer monsoon. We have given more emphasis on summer monsoon rainfall in the historical and future projection periods since the trends are becoming more chaotic, as reported in observational studies. Over the Indian subcontinent, all of the chosen scenarios show an increased frequency of intense rainfall events with varying decadal and multidecadal features. Central India and west coastal belts are showing positive trends in extreme rainfall events towards the end of the century. At the turn of the century, the southern peninsular region experienced a decline in monsoon precipitation, whereas central India experienced an increase. The severity of rainfall variations during the monsoon season and trends in extremes are increasing as we move from the low‐emission scenario to the high‐emission scenario.

Development of an improved three-dimensional rough discrete fracture network model: Method and application

Structure plane is one of the important factors affecting the stability and failure mode of rock mass engineering. Rock mass structure characterization is the basic work of rock mechanics research and the important content of numerical simulation. A new 3-dimensional rough discrete fracture network (RDFN3D) model and its modeling method based on the Weierstrass-Mandelbrot (W-M) function were presented in this paper. The RDFN3D model, which improves and unifies the modelling methods for the complex structural planes, has been realized. The influence of fractal dimension, amplitude, and surface precision on the modeling parameters of RDFN3D was discussed. The reasonable W-M parameters suitable for the roughness coefficient of JRC were proposed, and the relationship between the mathematical model and the joint characterization was established. The RDFN3D together with the smooth 3-dimensional discrete fracture network (DFN3D) models were successfully exported to the drawing exchange format, which will provide a wide application in numerous numerical simulation codes including both the continuous and discontinuous methods. The numerical models were discussed using the COMSOL Multiphysics code and the 3-dimensional particle flow code, respectively. The reliability of the RDFN3D model was preliminarily discussed and analyzed. The roughness and spatial connectivity of the fracture networks have a dominant effect on the fluid flow patterns. The research results can provide a new geological model and analysis model for numerical simulation and engineering analysis of jointed rock mass.

Numerical analysis of the effect of trench on indoor vibration adjacent to railway ground line

By establishing a 3D finite element numerical simulation analysis model of railway-soil-trench-building, the accuracy of the simulation analysis model is verified using on-site measured data of surface vibration attenuation law. Install vibration isolation trenches with different depths at different locations between the building and the railway, and analyze and compare the impact of indoor vibration in different situations. The results indicate that; The surface vibration caused by railways attenuates rapidly around 30m~76m from the line, and then shows a slight amplification trend around 120m. The surface vibration near the railway is mainly concentrated in the range of 15-90Hz; The vibration reduction effect of trench on different indoor rooms in buildings varies greatly. By optimizing the parameters of trench, the average indoor vibration reduction effect can be close to 5dB, and the vibration reduction effect of trench at different positions varies greatly. The increase in trench from 6m to 12m increases the indoor vibration isolation effect.

Analysis of Teachers’ Discourse in the Digital Platform Mode of College English Teaching Based on the Information Diffusion Model

Abstract This paper utilizes the information diffusion mechanism of the information extension model, which can act on the influence of students in the process of university English teaching to the information extension model to the diffusion ability that English information has. It examines the level of student activity and English information coverage in university English teaching and discusses the use of the information extension model in English teaching. According to the objectives of university English teaching, the functional requirements of the university English teaching platform are analyzed, the university English teaching platform based on the information diffusion model is designed through big data technology, and the English teaching platform combined with the information extension model is analyzed in an example study. The results show that on the model simulation analysis, the performance of this paper’s model is better than the User Rank model and UI-LR model when mining less than 30 information extensions. In the analysis of teachers’ discourse, the speech rate of teachers in the university English teaching platform is mainly concentrated in the range of 140-149 syllables/minute and 150-159 syllables/minute, and only one teacher’s speech rate exceeds 170-179 syllables/minute. This study has the potential to enhance students’ understanding of teachers’ discourse and establish a solid platform for communication between teachers and learners.

Research on rheological behavior of fresh concrete single-cylinder pumping based on SPH-DEM

In contrast to traditional approaches to simulating fresh concrete, the model applied here allows issues such as liquid phase and the motion of sub-scale particles to be considered. The rheological behavior of fresh concrete materials was investigated, and the slump test and pumping process of fresh concrete were simulated by combining the smooth particle hydrodynamics coupled with discrete element method. Based on Bi-viscosity model and Bingham model, linear and nonlinear fitting of rheometer data and the derivation equations were educing. Bi-viscosity model and the Bingham model were compared in slump test. The results show that the Bi-viscosity model is more accurate in simulation, and the error percentage is less than 10%. The Bi-viscosity model was used to simulate and predict the results of slump experiment, and the influence of rheological parameters on the slump velocity and shape was obtained. The simulation analysis model of concrete single-cylinder pumping is established, and the experimental and simulation analysis models are compared. The results show that the SPH-DEM pumping pressure prediction is very close to the experimental results.

Nonlinear Dynamic Mechanical Characteristics of Air Springs Based on a Fluid–Solid Coupling Simulation Method

The use of air springs has become widespread in various industries due to their exceptional superelastic properties; however, their strong nonlinear characteristics have become a hindrance to numerical simulations of air springs and have garnered increasing attention. This paper examined the nonlinear dynamic mechanical characteristics of air springs from a fluid–structure interaction perspective and verified the accuracy of the simulation analysis model through quasistatic tension and compression experiments. The average relative errors for air spring load and gas pressure were found to be 8.1% and 7.7%, respectively, which supports the validity of the model. The impact of frequency and amplitude excitations on the axial load characteristics of air springs was investigated through tension and torsion testing. The results showed that increasing the excitation frequency improves the stability of the axial load, while increasing the excitation amplitude enhances the axial load value. The change in axial compression was found to be more significant than that in axial tension, as it was affected not only by the axial load but also by the radial load, which is a key factor affecting the dynamic characteristics of air springs. A radial load analysis model was established to study the influence of frequency and amplitude excitations on the axial load characteristics of air springs. The simulation results indicated that under different amplitudes, the radial load of air springs goes through four stages: a steady period, rising period, steady period, and falling period. Additionally, under the same amplitude, the radial load value increases with an increase in frequency. This research on the dynamic load characteristics of air springs under amplitude and frequency excitations is important for their application in low-frequency and low-amplitude vibration environments, and its findings can be utilized to improve the technical parameters of air springs for suspension damping.

Increasing heavy rainfall events and associated excessive soil water threaten a protein-source legume in dry environments of West Africa

The intensification of the hydrological cycle has increased heavy rainfall and drought events in a changing climate. However, compared to drought, the impacts of heavy rainfall on crop production are under-studied. Using field experimental data and a calibrated crop model CYGMA, we showed that excessive soil water associated with heavy rainfall events is having a detrimental effect on cowpea yields, even in the dry environments of West Africa where cowpea is an important, protein-rich cash crop. Cowpea yields are susceptible to heavy rainfall in areas with poorly drained soils, and to drought in soils that have a low water-retention capacity. The crop model captured of the main characteristics of the observed development, growth, and yield, as well as the characteristics of root-zone soil water contents and how they vary by soil type. The analysis of d4PDF factual and counterfactual climate model simulations revealed that heavy rainfall events associated with anthropogenic climate change have increased in recent decades, and that they are projected to increase in future. Further, changes in seasonal rainfall and the number of dry days would be largely absent from CMIP6 climate projections by mid-century. Reductions in cowpea yields due to excessive soil water is projected to become more frequent, and the potential damage in a 1-in-100 extremely wet year would be comparable to the damage currently experienced in droughts, irrespective of soil types. Simulations of the projected damage due to drought show that the situation will be similar to current levels, with drought remaining a major climate hazard. However, excessive soil water is projected to be a serious threat to food security in the region. Our findings indicate that, even in dry environments, cropping systems need to be implemented in order to reduce the susceptibility of soils to both drought and excessive soil water.

Feature selection based machine learning models for 5G network slicing approximation

The development of 5G networks is expected to introduce novel concepts and challenges in domains such as technology, security, and customer demands due to advancements in mobile internet and communication services. The three main services that the 5G network provides are enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low-latency communication (URLLC). Network slicing is the practice of dividing a single physical network into many virtual networks in order to facilitate the delivery of multiple services across that network. These slices improve the network’s reliability and make it possible to provide more customized services. This article provides an overview of 5G network slicing, discussing its layers and overall architecture. Additionally, the paper proposes a machine learning network slicing model based on feature selection, comprising three main components. Firstly, data collection involves gathering two different datasets from various sources. Secondly, feature selection algorithms are applied to choose the most relevant set of features, as the collected datasets may contain numerous unnecessary attributes and values. Lastly, various classification models are utilized on the selected features to predict the optimal network slice, thereby improving the efficiency of the 5G network. The analytical results and simulation models demonstrate that the proposed machine learning models with feature selection perform exceptionally well and accurately predict 5G network slices.

Position control of Stewart platform with electric linear actuator

In recent decades, several technological applications have depended on manipulators like Stewart platform due to its accuracy and precision. Based on actuation type, Stewart platforms could be rotary or linearly actuated. Electric linear actuators are devices commonly consist of DC or AC motors coupled with lead screw or mechanism of gears and spindle which are used to convert rotary motion into linear (push or pull) motion. To increase accuracy and precision and achieve the desired linear actuator response, controllers should be used. The main aspiration of this work is to investigate the feasibility of using PID controllers for position control of Stewart platform with linear actuators. The mathematical model has been derived and the model transfer function has been obtained. To meet the required response of performance characteristics, the PID controller has been designed based on analysis of root-locus. Model simulation analysis has been carried out on both MATLAB and Simulink. For the electric linear actuator, comparison between the obtained response and the results of Ziegler-Nichols tuning method has been discussed on basis of the specifications of the time response. The PID controller parameters for the electric linear actuator has been tested experimentally and compared with simulation results.

Conversion Control for Remote Sensing Stable Platforms for Transient and Continuous Disturbances

An airborne electro-optical stabilized platform is a device situated between the aircraft and the imaging components, which serves to isolate external disturbances and maintain imaging axis stability for the imaging components. In light of the impact of transient and continuous attitude changes of the aircraft on the axis-stabilized imaging in visible light unmanned aerial vehicle (UAV) remote sensing missions, a control method combining a proportional-integral (PI) controller and a backpropagation neural network (BPNN) PID conversion control was devised. The specific procedure involved the following steps: firstly, the transfer mechanism of external disturbances between platforms was derived using the state transition matrix through mechanistic modelling. Secondly, the multi-rigid body dynamics equations of the airborne electro-optical platform were established based on Newton’s laws of motion and Euler’s laws. Subsequently, the relationship between the stable platform rotation angle and external disturbances was obtained using Laplace transformation, and an analysis was conducted on the effects of different disturbances on the stable platform. Lastly, conversion control was incorporated into the system model for simulation analysis. The simulation results demonstrated that transient disturbances could be effectively and rapidly isolated by the PI controller, while continuous disturbances exhibited improved performance when handled by the neural network PID controller, thus validating the efficacy of the designed conversion control method.

Analysis of sealing performance of combined seal structure with metal C-ring with built-in spring

The built-in spring reinforced metal C-shaped sealing ring is a high-performance static sealing component. Its metal combination sealing structure is designed to meet the sealing requirements of all metal graded cementing tools. To analyze and study the sealing performance of this combination sealing structure under complex underground application conditions, a three-dimensional simulation analysis model of the metal C-shaped ring combination sealing structure was established using ANSYS finite element analysis software, Simulate and analyze the stress and deformation of the combined sealing structure under different working conditions (room temperature and high temperature), and discuss the influence of external load conditions, including underground working medium pressure, temperature, and pre compression amount, on the sealing performance of the combined sealing structure. Calculate the variation law of contact pressure and equivalent stress under specific external conditions, providing some reference basis for the design and application of sealing rings and combined sealing structures.