Simulation Model System Research Articles

Research on Fuzzy PID Compliant Grinding Control Based on DBO Algorithm Optimization

In order to achieve the requirements of high precision, fast response and low overshoot in the robot grinding process. An active compliant actuator at the end of the robot is designed, and a fuzzy PID constant force control method based on dung beetle optimizer (DBO) optimization is proposed. The force and gas flow model of the compliant actuator are analyzed, and the mathematical model of the actuator is established. On the basis of fuzzy PID algorithm, the fuzzy PID parameters optimized by DBO algorithm are adopted. The simulation system model is established by MATLAB, and the performance of PID control, fuzzy PID control and fuzzy PID control method optimized by DBO algorithm is compared. The simulation results show that the fuzzy PID control based on DBO algorithm has faster response speed, reaches stability in 0.5s, no overshoot, and the system is more stable.

Asymmetric ENSO teleconnections in a symmetric CO2 concentration pathway

Abstract El Niño-Southern Oscillation (ENSO) is the strongest interannual phenomenon occurring in the tropical Pacific, significantly affecting the entire world. The ENSO response to increasing CO2 concentrations have been extensively studied, but the reverse scenario is still not well understood. Here, we investigate the hysteresis of ENSO teleconnections in a CO2 removal simulation of an earth system model. During the ramp-up period of CO2 concentrations, Pacific-North American and Pacific-South American patterns are intensified, with the eastward shift of their poles, which are even further intensified during the ramp-down period. This ENSO teleconnection hysteresis is closely linked to the tropical-origin hysteresis, in which, during the ramp-down periods, the prevalence of the eastern-Pacific type El Niño leads to the hysteresis in the eastern Hemispheric ENSO teleconnections and the enhanced ENSO skewness and the eastward shift of ENSO-induced tropical atmospheric convection do to that in the western Hemispheric ENSO teleconnection. The alterations by the tropical origin are predominantly associated with intensified southward migration of the Intertropical Convergence Zone, along with a stronger El Niño-like warming trend. We also demonstrate that the hysteretic change in the mid-latitude mean state over the North Pacific region could lead to hysteresis of the ENSO teleconnection without invoking a tropical origin.

A Method for Simulating an Information System with Life Cycle Simulation

Given the rapid growth of digital technologies, the use of information systems (ISs) is increasingly important for businesses positioned within the circular economy (CE). When designing an IS for such businesses, it is essential to simulate how the IS affects the life cycle (LC). However, existing research has not yet addressed this issue. For example, life cycle simulation (LCS) mods an LC and evaluates the economic profit and environmental impact of a product across its entire LC but does not explicitly model the IS and the effect from IS on LC is not simulated clearly. In this study, we propose a modeling method (E-DFD) and a simulation system (ISS) for modeling and simulating the IS. In the E-DFD and the ISS, we model and simulate an IS as a set of functions. Additionally, we propose a method that facilitates cooperation between IS simulations and LC simulations, allowing the effect of IS functions on LC to be evaluated. To validate the effectiveness of the ISS and the simulation method, we describe a case study that targets a new servitized business model with refrigerators. In the case study, we considered three patterns of LCs and two IS patterns with different functions for comparing the entire LCs and how the economic profit and environmental impact are changed depending on the difference in IS functions. In this case study, the IS and LC simulations identify how differences in IS functions affect the economic service provider’s profit, as well as the CO2 emission from the entire LC. Although our simulation method covers the entire LC, the functions of the IS focused on the use process in the case study. Therefore, further case studies targeting the LC processes, except the use process, are important for future work. In addition, developing methods for modeling and simulating the economic and environmental aspects of an IS is required.

Research on Hybrid Heating System in Cold Oilfield Regions

Efficient and clean treatment of wastewater and energy recovery and utilization are important links to realize low-carbon development of oilfields. Therefore, this paper innovatively proposes a multi-energy complementary co-production heating system which fully and efficiently utilizes solar energy resources, oilfield waste heat resources, and biomass resources. At the same time, a typical dormitory building in the oil region was selected as the research object, the system equipment selection was calculated according to the relevant design specifications. On this basis, the simulation system model is established, and the evaluation index and operation control strategy suitable for the system are proposed. The energy utilization rate of the system and the economic, energy-saving, and environmental benefits of the system are simulated. The results show that, under the simulated conditions of two typical days and a heating season, the main heat load of the system is borne by the sewage source heat pump, the energy efficiency is relatively low in the cold period, and the energy-saving characteristics are not obvious. With the increase in heating temperature and anaerobic reactor volume, the energy consumption of the system also increases, and the energy efficiency ratio of each subsystem and the comprehensive energy efficiency ratio of the system gradually decrease. In addition, although the initial investment in cogeneration heating systems is high, the operating costs and environmental benefits are huge. Under the condition of maintaining 35 °C, the anaerobic reactor in the system can reduce carbon emissions by 12.15 t per year, reduce sulfur dioxide emissions by 98.4 kg, reduce dust emissions by 49.2 kg, and treat up to 2700 t of sewage per year, which has broad application prospects.

Predicting weight dispersion in seabass aquaculture using Discrete Event System simulation and Machine Learning modeling

Marine aquaculture, particularly in the Mediterranean region, faces the challenge of minimizing growth dispersion, which has a direct impact on the production cycle, market value and sustainability of the sector. Conventional grading methods are resource intensive and potentially detrimental to fish health. The current study presented an innovative approach in predicting fish weight dispersion in European seabass (Dicentrarchus labrax) aquaculture. Seabass is one of the two major fish species cultivated on the Mediterranean coast, with a fattening cycle of 18–24 months. During this period, several grading operations are carried out to minimize growth dispersion. The intricate feed-fish-water system, characterized by complex interactions among feeding regimes, fish behavior, individual metabolism and environmental factors, is the focus of the study. The comprehensive, five-step methodology addresses this complexity. The process begins with a Discrete Event System (DES) model that simulates the feed-fish-water dynamics, taking into account individual fish metabolism. This is followed by the development of a surrogate machine learning (ML) regressor model, which is trained on DES simulation data to efficiently predict growth distribution. The model is then calibrated and customized for specific fish stocks and production tanks. The preliminary results from 21 tanks in two trials with European seabass (D. labrax) showed the effectiveness of the method. The results from the simulation models achieved a R2 of 99.9 % and a Mean Absolute Percentage Error (MAPE) of 1.1 % for the prediction of mean final weight and a R2 of 90.3 % with a MAPE of 8.1 % for the standard deviation of final weight. In summary, this study represents a significant advance in the planning and management of seabass aquaculture. Given the lack of effective prediction tools in the aquaculture industry, the proposed methodology has the potential to reduce risks and inefficiencies, thus possibly optimizing aquaculture practices by increasing sustainability and profitability.

China's future forest carbon sequestration potential under different management scenarios

Enhancing forest carbon storage and carbon sequestration capacity is crucial for achieving carbon neutrality. Scientific forest management can maintain a high level of carbon sequestration capacity in forests, and considering the carbon pool of wood products can extend the time of carbon fixation. However, current predictions of large-scale forest carbon storage and carbon sequestration capacity have overlooked changes in forest carbon absorption with forest age and the buffering effect of wood product carbon pools in the carbon release process. In this paper, we used the Forest Simulation and Optimization System model (FSOS) to analyze the wood supply and carbon sequestration capacities of different management scenarios based on data from the Forest Resources Inventory (2014–2018). The results showed that China's forests could export significant amounts of timber in the future; According to the 9th forest survey report, China's forests produce only 88 million m3 yr-1. Among them, the harvested objects were mainly planted forests, and if all forests (planted forests and natural forests) are involved in forest management planning, the maximum sustainable annual wood supply will reach 286 million m3 yr-1. Moreover, due to the current large proportion of younger forests in China, 358 million m3 of annual wood supply will be achievable in the future (as of the year 2039). Forest management can increase the carbon sequestration capacities in forest ecosystems as well as the wood supply compared to the no management options. In summary, the carbon sequestration potential of unmanaged forests is limited. Appropriate forest management can increase the carbon sequestration potential of forests. The substitution of carbon emission reduction of wood products and bioenergy can also greatly reduce the pressure to achieve carbon neutral strategies.

Design and evaluation of integrated energy system combining solar energy and compressed-air energy storage

A new integrated energy system (IES) has been proposed by combining the cooling, heating, and power generation (CCHP) system coupled with PV/T and compressed air energy storage (CAES). Based on the developed control operation strategy, rigorous system modeling and dynamic simulation are carried out by TRNSYS to determine the integrated operation effect of each subsystem. Energy utilization efficiency and annual value of costs were adopted to assess the benefits of the system. A building in Gansu Longnan area is selected as a study case. The study results show that the proposed system can meet the building load demand well. The PV efficiency and thermal efficiency are 0.17 and 0.19, respectively. The gas ratio of CAES storage tank is 0.94, which is safe and stable. In addition, the energy utilization is maximum when the internal combustion engine proportioning capacity is 30 % of the maximum heat load, which is 89.13 %. The annual value of the cost is 2.49 × 107 RMB during 40 years of operation.

Vehicle vibration test platform structure design and control strategy optimization

AbstractFor the needs of vehicle vibration test platform with high precision, large load capacity and fast response, the three‐dimensional model design and analysis of vehicle vibration test platform are carried out; in order to improve the motion performance of the platform, a vibration test plat‐form control strategy combining hybrid heuristic algorithm and PID control is proposed. Based on the designed 3D model parameters, the single‐channel mathematical model of the servo‐electric cylinder is derived and a hybrid heuristic algorithm PID optimization model is established to compare and analyze the control performance of the platform with the Ziegler‐Nichols method PID. The results show that the step system overshoot is 3.80% and the dynamic performance of the system is significantly improved when the hybrid heuristic algorithm PID control is used. The simulation system model of vehicle vibration test platform control is established, and the operation results show that the platform is closer to the input signal in the spatial position change curve when the hybrid heuristic algorithm PID control is used. Its maximum displacement error is 0.09 mm, and the motion accuracy of the system is improved by 61% compared with the Ziegler‐Nichols method PID control.

Dynamic Modeling of a Concentrating Solar Thermal Plant With a Packed Bed Energy Storage

The Air-packed bed system is a cost-competitive concentrating solar thermal system that employs air as the heat transfer fluid and a solid packed bed as the thermal energy storage medium. The thermocline behavior of the packed bed plays an important role in the performance and operation of the system, so a dynamic model of the TES is needed to evaluate the design and performance of the system. A high-fidelity first-principle TES model is often too computationally expensive to incorporate into a larger system model for simulation and optimization at an annual time scale. Here, we develop in Modelica a system model for a CST concept plant with a reduced order TES model to ensure the necessary thermocline fidelity while maintaining suitable computational performance. The validity of the reduced order model is quantified both against simulation results from a first-principle finite-difference model and against real-world test data taken at the Heliogen Test Facility in Lancaster, CA. The thermocline fidelity and computational performance of the system model are then demonstrated with an annual simulation run of the concept air-packed bed plant.

Simulink Model for LMV and Conceptualization of 2 Speed E-Axle

Heavy-duty trucks are the primary contributor to the global emissions of greenhouse gases. Because of this, electric haulage has seen significant growth in popularity. Electric heavy-duty trucks aren't widely adopted because of their limited range, payload capacity, and high prices. Electric axle systems, sometimes known as "E-Axles," are capable of electrifying heavy-duty vehicles effectively. The motor, power electronics, and gearbox are all combined into one unit in an E-axle. E-axles that are devoid of motors and gearboxes have the potential to boost performance while also reducing weight and fuel consumption. Heavy-duty automobiles are similar to them. E-axles have the potential to increase the fuel efficiency, flexibility, and emissions of heavy-load trucks. The e-axles are being inspected. E-axles for heavy-duty trucks bring both issues and opportunities concerning finances, infrastructure, and costs. Examine the performance standards as well as the technology behind batteries. This paper provides an introduction to MATLAB Simulink, which focuses on engineering and science. Simulink facilitates the design, simulation, and evaluation of systems. This article demonstrates the fundamental principles, features, and benefits of Simulink through the application of system modeling, control design, and dynamic simulation. It presents Simulink methodologies, libraries, and blocks, as well as interactive simulations.
 Keywords: MATLAB, Simulink, EV Control systems, EV simulation, EV powertrain modeling, EV test and validation Simulink, WLTP drive cycle

Reducing trainee mistakes. Better performance with changing to a high-fidelity simulation system?

Postpartum hemorrhage is a significant cause of both maternal morbidity and mortality worldwide and is increasing in incidence. This study aimed to assess improvement and identify shortcomings in trainee performance in different simulation systems in the management of postpartum hemorrhage. To perform a pilot study evaluating and comparing high- and low-fidelity simulation models, assessing improvement in repeated performance with high-fidelity mode and identifying mistakes made assessed using Objective Structured Assessment of Technical Skills and thereby exploring what aspects of emergency management of postpartum hemorrhage should be prioritized in teaching settings and assessing what simulation setup is most effective in achieving competence. This was a prospective randomized, single-blinded, single-institution trial in a population of 17 junior obstetrical trainees at the Charité University Hospital Obstetric Simulation Center in Berlin. Trainees were randomized into 2 groups, with either initial low-fidelity simulation or high-fidelity simulation, followed by repeated assessment of performance, using the high-fidelity model simulation system. Individual simulation sessions were video-recorded and transcribed, and the timing of interventions was documented. Strandardized Objective Structured Assessment of Technical Skills forms were used as a checklist for performance. There was a statistically significant general improvement in performance (P=.02; 24.7-27.2 of 31.0 points; average of 8.7%) in the second cycle of simulation assessment and a statistically significant training effect (P=.043; 24.4-28.4 of 31.0 points; average of 12.9%) in the group that underwent repeat simulation assessment from the initial low-fidelity system to the high-fidelity system compared with the group using the same high-fidelity setup (P=.276; 25.0-25.8 of 31.0; average of 2.4%). There was an improvement in the performance when trainees underwent a repeated cycle of simulation assessment changing from a low-fidelity system to a high-fidelity system. Simulation assessment can identify mistakes and learning gaps that are important for obstetrical trainees. This study found that trainees make the same mistakes, regardless of which simulation model was initially used.

Разработка программного комплекса для испытания цифровых измерительных трансформаторов на вибростенде

The presented work examines a software package for monitoring the condition of a hydraulic servo drive with hydrostatic guides as part of a diagnostic vibration stand for digital transformers. The service life of digital instrument transformers is 25 years, and the calibration interval is 8 years. To achieve such high performance characteristics, it is necessary to conduct a large number of tests for such products. One such test is the vibration test. The uniqueness of the hydraulic drive used in the diagnostic vibration stand lies in its long service life under operational loads (up to 100 million cycles). This reliability is achieved with special hydrostatic guides in the hydraulic drive design and requires special software. The architecture of the software complex for the vibration stand has been created. To test the functionality of the package, simulation modeling of the operation of the components of the software package was performed. Aim. Based on the analysis of the functioning of technological equipment and options for implementing control software, develop the architecture of a software package for implementing a system for condition monitoring of a servo hydraulic drive with hydrostatic guides as part of a diagnostic vibration stand for digital transformers. Materials and methods. The stated scientific problems were solved using methods of system analysis, computer, mathematical and simulation modeling of the interaction of the software complex with the components of the servo hydraulic drive with hydrostatic guides. Results. The main practical result of the research is the development of the architecture of a software package for testing digital instrument transformers on a vibration stand. It is proposed to use cross-platform solutions when implementing the complex software and rely on modern experience in using freely distributed software. Conclusion. The developed architecture of the software package is focused on ensuring the automated operation of servo hydraulic drives, allows you to configure all the necessary equipment parameters, monitor the condition of the equipment using digital data transfer protocols, centrally save and replicate hydraulic drive settings for specific operating conditions on the enterprises. Analysis of implementation options showed that the use of a SCADA system simplifies the process of developing standard projects for dispatch control and data collection and condition monitoring, but at the same time, it has increased complexity at the stage of deployment and operation. The functionality of none of the widespread and reliable SCADA systems covers all the requirements for this project. This particularly applies to USB connectivity and high frequency signal processing required by design requirements. In addition, when using universal SCADA systems, the end user must purchase a license for the RunTime SCADA component.

Technical and economic analysis of multi-energy complementary systems for net-zero energy consumption combining wind, solar, hydrogen, geothermal, and storage energy

An integrated renewable energy supply system is designed and proposed to effectively address high building energy consumption in Zhengzhou, China. This system effectively provides cold, heat, and electricity by incorporating various clean energy sources such as wind, solar, hydrogen, and geothermal energy. Technical and economic analyses are conducted to optimize the integration of these renewable sources. Technical and economic analyses are conducted to optimize the integration of these renewable sources. Rigorous system modeling and dynamic simulation using TRNSYS software evaluate the seamless integration and optimal functioning of the PV/T subsystem within the CCHP system. The interaction between Photovoltaic/Thermal (PV/T) and borehole heat exchanger (BHE) coupling is investigated, analyzing their impact on individual system performance. Furthermore, key indicators, including overall electricity consumption (OEC), life cycle cost (LCC), heat pump coefficient of performance (COPHP), and system coefficient of performance (COPSYS) are analyzed. The robust response surface methodology (RSM) and Box-Behnken experimental design approach are employed to show remarkable agreement between predicted and simulated values, with a maximum deviation of only 1.45%. The optimal configuration consists of a PV/T area of 132 m2, 20 wind turbines, 12 alkaline fuel cells, and 17 borehole heat exchangers, resulting in highly favorable outcomes: an OEC of −35648.72 kW∙h/year, an LCC of $209113.85, a COPSYS of 2.91, and a COPHP of 3.82. Moreover, detailed assessments of each subsystem's performance enhances our understanding of the system's overall operation, affirming the feasibility of the proposed integrated energy supply system for buildings.

Analisis Tarif Air PDAM Untuk Kelayakan Penerapan Sistem Pemanenan Air Hujan pada Skala Rumah Tangga

The limited availability of clean water is a problem that often occurs lately. Water use continues to increase due to population growth and technological developments. The availability of abundant rainwater and the application of a rainwater harvesting system are alternatives for water fulfillment as water supplies are limited. Rainwater harvesting system performance simulation modeling is essential in deciding the suitability of rainwater harvesting systems. In this study, the rainwater harvesting system simulation modeling was carried out using the Yield Before Spillage (YBS) algorithm in 3 cities in Indonesia (Palembang City, Bogor City, and Mataram City). This assessment considers 5 combinations of demand, 5 combinations of catchment area, 5 tank capacities, and 3 applicable water rates, resulting in 1,875 different value configurations. The performance and potential assessment of the rainwater harvesting system are determined by Water Saving Efficiency and Timetric Reliability, while the financial assessment is determined using the payback period and benefit-cost ratio. Benefits are derived from the potential for water savings with a rainwater harvesting system which is converted into financial savings according to the prevailing water rates and costs are determined based on the initial installation costs of the rainwater harvesting system. The results of this study indicate that the city of Bogor with an average rainfall of 3805.95 mm/year has the highest WSE rate of 100% and the fastest payback period is 4 years. Palembang City with an average rainfall of 2551.57 mm has the highest WSE rate of 99,273% and the fastest payback period is 5.42 years. Mataram, with an average rainfall of 1661.79 mm, has the highest WSE rate of 91.752% and the fastest payback period is 8.17 years. Topographical conditions and rainfall greatly affect the performance of the rainwater harvesting system.

Adapting Colorado River Basin Depletions to Available Water to Live within Our Means

The Colorado River’s two largest reservoirs are drawing down because releases exceed inflows and releases adapt to reservoir elevations instead of to elevation and inflow triggers. To help slow reservoir drawdown and sustain target elevations, we introduce a new rule that adapts basin depletions to available water. We simulated inflow-based operations and validated existing operations in a new open-source exploratory model for the Colorado River Basin. We developed the exploratory model to more easily adapt Upper and Lower Basin depletions to available water, reduce run time, and lower costs to use compared with the proprietary RiverWare Colorado River Simulation System (CRSS) model. We simulated adaptive and existing operations for (1) the 2000–2018 period, and (2) scenarios of steady Lees Ferry natural inflow each year of 17.3–6.2 billion m3 (bcm) [14–5 million acre-ft (maf)] per year. We found the following: (1) the existing rules drew down Lake Powell and Lake Mead to their critical storages of 7.4 bcm (6.0 maf) in less than 5 years when Lees Ferry natural flow was less than 15.3 bcm/year (12.4 maf/year) (the 2000–2018 period average); and (2) the adaptive rule sustained both reservoirs above their critical levels for long periods by requiring Upper and Lower Basin users to conserve as much as 1.2 bcm (1.0 maf) per year more water than existing operations. The next steps should be testing the adaptive rule in CRSS and devising conservation programs that can adapt and scale to available water.

Information technology for creating intelligent computer programs for training in algorithmic tasks. Part 2: Research and implementation

Information technologies, particularly artificial intelligence methods, involve more and more deeply into all spheres of human activity: science, technology, art, and education. Ukraine also has sufficient potential and needs to develop educational support, which is the subject of this paper. The work aims to demonstrate the components of information technology for the creation of Intelligent Tutoring Systems (ITS), which are involved in studying various engineering disciplines. The work includes methods of system analysis, mathematical and simulation modeling, technical diagnostics, and artificial intelligence. The proposed models and methods are implemented in ITS prototypes for teaching mathematics, programming, and the automatic control theory. The Intelligent Tutoring Systems were implemented in the educational process of KhAI University and other institutions in Ukraine, Great Britain, Austria, and China. Experimental studies have shown increased student learning success rates using ITS compared to traditional methods. Improved and adapted for computer training methods of technical diagnostics, Bayesian networks, and developed models of algorithmic tasks, the learning process and the learner are valuable from a scientific point of view. In a practical sense, the obtained results can be used to create new specialized ITSs and build an expandable common learning platform integrating the basic disciplines of a specific educational field.

Long short-term memory deep learning model for predicting the dynamic performance of automotive PEMFC system

As a high efficiency hydrogen-to-power device, proton exchange membrane fuel cell (PEMFC) attracts much attention, especially for the automotive applications. Real-time prediction of output voltage and area specific resistance (ASR) via the on-board model is critical to monitor the health state of the automotive PEMFC stack. In this study, we use a transient PEMFC system model for dynamic process simulation of PEMFC to generate the dataset, and a long short-term memory (LSTM) deep learning model is developed to predict the dynamic performance of PEMFC. The results show that the developed LSTM deep learning model has much better performance than other models. A sensitivity analysis on the input features is performed, and three insensitive features are removed, that could slightly improve the prediction accuracy and significantly reduce the data volume. The neural structure, sequence duration, and sampling frequency are optimized. We find that the optimal sequence data duration for predicting ASR is 5 s or 20 s, and that for predicting output voltage is 40 s. The sampling frequency can be reduced from 10 Hz to 0.5 Hz and 0.25 Hz, which slightly affects the prediction accuracy, but obviously reduces the data volume and computation amount.

A Sustainable Supply Chain Framework for Dairy Farming Operations: A System Dynamics Approach

The dairy industry plays a significant role in the global food system, providing essential nutrients for human consumption and creating rural employment. A small-scale dairy can assist a family in maintaining their livelihoods in Bangladesh. However, it is also associated with various environmental and social impacts, making it crucial for achieving sustainability. The triple bottom line of sustainability intends to achieve sustainability through improving productivity, implementing sustainable practices, and incorporating waste management. The dairy industry can continue to provide nutritious diets, ensuring sustainability practices. This research is a follow-up paper of Nasir et al. to find better sustainable results. It considers the triple bottom line of sustainability theory to improve the farm environment by reducing waste, managing resources efficiently, and promoting environmentally friendly practices. This paper is a case study on a dairy farm of 400 cattle in Bangladesh. The system dynamics method and simulation modeling were employed to draw dairy supply chain networks and examine the existing dataset to find better utilization of the dairy waste produced on the farm. Consequently, the simulation model incorporates waste management and value addition concepts to find better resource exploitation for gaining sustainable outcomes. Finally, this paper summarizes the simulation outcomes and articulates possible extensions for achieving further economic, social, and environmental benefits for the industry and surrounding community.

Variation of Spring Stiffness, Monomeric Friction, and Brownian Intensity in the Simulation System of Unentangled Melt under Steady Flow

Understanding the nonlinear dynamics of an unentangled polymer melt from the bead-spring chain model requires knowledge of the variation of spring stiffness, monomeric friction, and Brownian intensity. In this work, these nonequilibrium (NE) parameters are quantified in the model simulation systems of unentangled melt under steady-flow conditions. We focus on a particular version of the model with undefined NE parameters. Some expressions to relate the NE parameters with the rheological and structural properties are pointed out. The spring stiffening parameter rκ is proven to be easily accessible in the planar flows. The distribution of the stiffening effect along the polymer contour is identified. The alignment-induced reduction of monomeric friction is confirmed in the simulation systems, but the anisotropic feature of friction is also emphasized. The constraint on the cooperative variation of spring stiffness and friction is proven to be an important property of extensional flow. The variation of Brownian intensity is found to be decoupled with the variation of friction, which means the violation of the fluctuation–dissipation (FD) theorem. The NE parameters of the simulation systems are further compared with those from the experimental systems.

Evolution of the water–carbon relationship at basin scale under the background of a vegetation restoration program

AbstractVegetation restoration is an important means for regional climate change mitigation and terrestrial carbon sequestration. However, large‐scale vegetation restoration in arid and semiarid regions can excessively consume local water resources, thus threatening regional water supply safety. To explore the impact of vegetation restoration on the water–carbon relationship in the Loess Plateau in China before and after the implementation of the Grain‐for‐Green Program (GfGP), the regional hydro‐ecological simulation system (RHESSys) model was used to simulate the temporal and spatial evolution of key variables of the water cycle, including the actual evapotranspiration (ET) and the surface runoff (Rs), and that of the carbon cycle, including the net primary productivity (NPP) and the total carbon density (TC). In addition, statistical methods were applied to analyze the interaction between water and carbon cycles. Results show that the RHESSys model is capable of simulating the key ecohydrological elements. In the period of 1990–2019, ET and NPP both showed significant increasing trends at rates of 8.9 mm yr−1 and 6.9 g C m−2 yr−1, respectively. The TC also had a slightly increasing trend, with rates of 0.04 t C hm−2 yr−1 (land‐use in 1995), 0.07 t C hm−2 yr−1 (land‐use in 2005), and 0.08 t C hm−2 yr−1 (land‐use in 2015). In contrast, Rs decreased at the rate of 0.35 mm yr−1. As for spatial distribution, in the middle and southeastern parts of the Yanhe River basin with the vegetation well‐restored, ET, NPP, and TC showed significant increasing trends, while the Rs showed a decreasing trend. ET was also found to have a positive correlation with NPP and TC, while the Rs has a negative correlation with NPP and TC. Moreover, the correlation of Rs‐NPP and Rs‐TC was found to increase after the implementation of the GfGP, which indicates the reinforcing effect of vegetation restoration on the water–carbon trade‐off relationship. Therefore, it is critical to coordinate and regulate the interaction between water consumption and runoff in the context of vegetation restoration in the Yanhe River basin, as well as to promote the synergy between regional ecological restoration and social economic development for water security.