System Dynamics Simulation Model Research Articles

Trajectories of socio-ecological systems: A case study in the tropical Andes.

Scenario and policy assessments in socioeconomic and environmental studies face significant challenges in socio-ecological systems (SES). There are a limited number of studies that have looked at the impact of different scenarios within integrated approaches, and many have used a static approach with a single driver of change. The present work analyzes the SES dynamics for a strategic basin in the Colombian Andes when implementing and analyzing scenarios and policies related to land cover and land use change using a system dynamics simulation model. The model includes natural, ecosystem services, sociocultural, and economic components. Scenarios and policy options are analyzed both individually and jointly to identify synergies or trade-off effects between the different SES components. The results showed the different trajectories of the socio-ecological system according to the cases studied, and its impact on different variables in the analyzed components. Some counterintuitive effects were also identified, such as the importance of intrinsic motivations in decision-making processes, and determinants in land management and policy design.

Research on vibration characteristics of cone valve based on steady state hydrodynamics

The steady-state fluid dynamic force of the cone valve core reduces the stability of the cone valve, thereby affecting its vibration characteristics. This study first derived the formula for calculating the steady-state fluid dynamic force of the valve core using the momentum theorem. Then, the study used the Computational Fluid Dynamics (CFD) method to explore the variation of steady-state fluid dynamic force with the opening degree of the cone valve and the pressure difference at the inlet and outlet. The study also analyzed the steady-state fluid dynamic force of the improved structure cone valve. Combining the CFD calculation results with the established axial vibration and dynamic models of the valve core spring system, a system dynamics simulation model was developed. Innovatively, the study combined experimental and simulation methods to investigate the vibration characteristics of the cone valve and the impact of steady-state fluid dynamic force on these characteristics. The experimental results aligned well with the simulation results, showing that the influence of steady-state fluid dynamic force on vibration characteristics is similar to that of spring force. At a small opening degree, the compensation structure of steady-state fluid dynamic force can reduce axial vibration amplitude. Increasing the inlet pressure from 2.0 MPa to 2.5 MPa results in a decrease in axial amplitude and an increase in the numerical value of the vibration balance position. Increasing the outlet pressure from 0.5 MPa to 0.9 MPa initially decreases axial amplitude and axial waveform factor, followed by an increase. Increasing the spring preload from 9.4 mm to 13.4 mm leads to a decrease in the numerical value of the balance position, a reduction in amplitude, and a decrease in the waveform factor of the axial vibration of the valve core. The study reveals systematic effects of inlet pressure, outlet pressure, and spring preload on the vibration characteristics of the cone valve. The research results in this paper can provide theoretical support for the structural design of hydraulic valves, reduce the impact of fluid dynamics on vibration, and thereby improve the stability of hydraulic system operation.

Scenarios for offshore wind co-existence opportunities and trade-offs

This paper introduces the MARCO (MARine CO-existence scenario building) concept for using scenario exploration in stakeholder engagement processes in offshore wind. MARCO builds on spatial analyses using geographic information systems (GIS), and projections over time using system dynamics simulation models. We position the concept within the existing literature on tools for decision support and stakeholder participation, and provide a preliminary status on the spatial baselines, as well as example scenarios for area usage in offshore wind and implications, including risks and co-existence opportunities, on other sectors and nature.

The Impact of Climate Change and Urbanization on Groundwater Levels: A System Dynamics Model Analysis

Climate change and population growth have placed increasing stress on groundwater resources. Effective management of groundwater resources is crucial for promoting sustainable development, especially in areas heavily reliant on groundwater supply. However, sustainable groundwater management is more complex due to various factors affecting key drivers and their feedback interactions. In this regard, this study aims to examine the key driving forces and their interplay concerning fluctuations in groundwater levels within a study area in Illinois, United States, which heavily relies on groundwater for water supply. To achieve this objective, a system dynamics (SD) simulation model was developed, utilizing hydrology, climate, and urbanization data spanning from 2010 to 2020. Through calibration and validation of the SD model with historical data, the model demonstrated reliable simulation capabilities for groundwater levels. Additionally, sensitivity analysis and exploration of water resource scenarios were conducted to evaluate the critical factors influencing groundwater levels. Results revealed that population dynamics, agricultural land, and groundwater recharge were analyzed as key drivers influencing the change in groundwater level for the study area, among the climate and urbanization factors that had different contributions to the groundwater dynamics. A 10% increase in population, agricultural land, and groundwater recharge led to a decrease of approximately 5.5% and increases of 4.5% and 4.27% in groundwater levels, respectively. The results of the four-scenario analysis indicated that both climate change and urbanization exerted significant and adverse impacts on the groundwater level in the study area. These scenarios represented prominent and worst-case situations, highlighting the potential challenges and risks associated with the combination of these factors, which resulted in about a 77 mm decrease in groundwater levels by 2030. Overall, given limited data availability for SD model parameterization, the study emphasizes the need to consider the effects of both urbanization and climate change on groundwater supplies in decision-making for sustainable groundwater management, as well as the need for adequate management measures to maintain the long-term usage of groundwater resources.

Novel synergy mechanism for carbon emissions abatement in shipping decarbonization

Greenhouse gas emissions lead to climate change, subjecting the maritime environment to severe threats. In response, globally, states and organizations are taking actions to decarbonize. In this context, this paper builds an evolutionary game analysis involving the government and shipping company under a governance framework with IMO, from a perspective of economic regulations, and explores how to establish a proper shipping decarbonization mechanism and implementation plans in the process of dynamic evolution. Based on a system dynamics simulation model, we analyzed how the cap-and-trade policy system, tax-and-subsidy policy system, and cooperative policy system perform in terms of shipping decarbonization and the role of IMO in shipping decarbonization. Our research proves that the cooperative system is more efficient and stable in decarbonization than singular economic regulations; static and dynamic implementation plans should be coordinated in different stages; and finally, IMO plays an active role in multi-agent coordinated controls.

System dynamics simulation model for efficient on-farm carrot cultivation

The article describes the development of a simulation model of processes related to carrot cultivation. The obtained digital twin can be used as a model, which is the basis of a comprehensive software solution for control and management of the full life cycle of the specified crop. The use of structural analysis and synthesis methods allowed to establish all objects and parameters of the processes related to the cultivation of carrots. The use of the system dynamics method based on the Forrester model allowed us to develop a parametric model with a detailed description of the resources and characteristics affecting the processes of transformation. The application of the graphical method to the obtained results allowed creating a graphical interpretation of the parametric model for clarity and the possibility of creating scenarios of changes in indicators in order to develop scenarios of effective response to changes in external conditions in the real environment to maintain and increase carrot yields.

Digitally enabled food sharing platforms towards effective waste management in a circular economy: A system dynamics simulation model

As a solution to tackle the food waste (FW) challenge, digitally enabled food sharing platforms (FSPs) are emerging as FW warriors and anti-waste social movements. Despite the rapidly growing number of users, the amount of FW prevented per user in these platforms is relatively low. Hence, the real contribution of FSPs to the circular economy (CE) by preventing FW is still blurred. To fill this gap, a System Dynamics simulation model is developed in this research to unfold how people adopt such platforms over time, and how such platforms contribute to the CE through FW prevention. The model is used to simulate the adoption and performance of Italy's Too Good To Go (TGTG) platform spanning 2015-2060 as a reference case. The results show that although TGTG is a successful FSP in terms of adoption, it can still significantly improve in terms of performance. Besides, while the current TGTG's marketing strategy is effective, knowledge-enhancing activities should be strengthened to improve performance. Hence, this research recommends a winning policy, which can reduce approximately 3% of the total FW generated at the country level (Italy) in 2060, a significant contribution to the CE transition.

Implementation of lean principles in the yarn manufacturing industry: a system dynamics approach

PurposeThe textile industry contributes 2 and 3% to the global and Indian Gross Domestic Product (GDP), respectively. India supplies a quarter of global cotton yarn. Yet, most yarn manufacturing companies use outdated methods and lack organisational skills and strategies. Improvement in processes in India could significantly help the industry worldwide.Design/methodology/approachThe variables that influence the performance of the system were identified. Their interrelationships and impact were identified from the employees in the chosen case study, a yarn manufacturing industry. A System Dynamics (SD) approach was employed to study the benefits of implementing 5S lean strategies. The impact of each variable on various performance measures such as throughput, Work In Progress, processing time, waiting time, idle time, over-processing and scraps was analysed.FindingsImprovement in outcomes reflected an enhanced adoption of leanness in the industry. The decision-makers can utilise this study to optimise the necessary parameters in the system and attain the desired productivity levels. Better resource management and reduced processing time helped increase the despatch rate by 9.735% and decrease the WIP by 23.01%. Time management helped to reduce the inventory, idle time and waiting time. Over-processing, defects and scraps were minimised, indicating a shift towards lean.Research limitations/implicationsThis study pioneers the use of SD simulation models for optimising yarn manufacturing using lean strategies. Improvement in performance measures by integrating these strategies opens avenues for future research using multiple approaches to address a problem.Practical implicationsImplementing 5S lean principles and simulations enhances productivity, reduces waste and optimises resource management for the yarn manufacturing industry. Decision-makers can employ simulation to witness the outcomes of their changes without investing cost and time and without associated implementation risks.Originality/valueThe use of a simulation model to witness the benefits of incorporating lean strategies in yarn production has not been explored. This approach could help the managers and policymakers understand their existing system's shortcomings and critical areas that require improvement.

How to promote the trading in China's green electricity market? Based on environmental perceptions, renewable portfolio standard and subsidies

The behavior evolution of market players is crucial to promoting green electricity trading. This paper develops an evolutionary game model of China's green electricity market to analyze the strategic interactions among players. The model incorporates key variables such as renewable energy subsidies, renewable energy quotas, and environmental perceptions. Then, a system dynamics simulation model is constructed, and simulation experiments are designed to reveal the influence of key factors on the evolutionary path. The results indicate that: (1) Players exhibit varying sensitivities to green electricity prices under different trading modes. (2) Renewable energy projects with high subsidy intensity have no willingness to enter the market if the benefits of participating in the green electricity market cannot surpass subsidies. (3) The evolutionary stabilization trend depends on users' environmental perceptions, and the environmental perception effect exhibits a diminishing marginal trend. (4) The implementation of renewable portfolio standard is an effective way to promote green electricity trading, especially when there is a high green electricity premium. (5) There is a trade-off between low incentive participation and high incentive coefficients in the system. These findings provide valuable policy recommendations for effectively promoting green electricity trading in China.

The impact of non-pharmaceutical interventions on the spread of COVID-19 in Saudi Arabia: Simulation approach

ObjectivesThis paper aims to measure the impact of the implemented nonpharmaceutical interventions (NPIs) in the Kingdom of Saudi Arabia (KSA) during the pandemic using simulation modeling. MethodsTo measure the impact of NPI, a hybrid agent-based and system dynamics simulation model was built and validated. Data were collected prospectively on a weekly basis. The core epidemiological model is based on a complex Susceptible-Exposed-Infectious-Recovered and Dead model of epidemic dynamics. Reverse engineering was performed on a weekly basis throughout the study period as a mean for model validation which reported on four outcomes: total cases, active cases, ICU cases, and deaths cases. To measure the impact of each NPI, the observed values of active and total cases were captured and compared to the projected values of active and total cases from the simulation. To measure the impact of each NPI, the study period was divided into rounds of incubation periods (cycles of 14 days each). The behavioral change of the spread of the disease was interpreted as the impact of NPIs that occurred at the beginning of the cycle. The behavioral change was measured by the change in the initial reproduction rate (R0). ResultsAfter 18 weeks of the reverse engineering process, the model achieved a 0.4 % difference in total cases for prediction at the end of the study period. The results estimated that NPIs led to 64 % change in The R0. Our breakdown analysis of the impact of each NPI indicates that banning going to schools had the greatest impact on the infection reproduction rate (24 %). ConclusionWe used hybrid simulation modeling to measure the impact of NPIs taken by the KSA government. The finding further supports the notion that early NPIs adoption can effectively limit the spread of COVID-19. It also supports using simulation for building mathematical modeling for epidemiological scenarios.

Emerging smallholder cattle farming from a One Health perspective: A system dynamics model of the highveld region of South Africa

BackgroundOne Health is built on the concept that "human health and animal health are interdependent and bound to the health of the ecosystems in which they exist" (OIE, 2021). The zoonotic origins of the COVID-19 pandemic elevated the importance of the One Health concept while highlighting the complexities of human-animal-environmental interfaces in public health management. The definition and purpose of One Health includes an applicability to cattle farming systems. One Health-awareness in livestock rearing is essential in ensuring animal, human, and environmental health and in limiting the spread and emergence of diseases that threaten the health of the three domains. OriginalityThis article identified a gap in One Health research in South Africa and its emerging smallholder cattle production systems. It presents the research problem of the impact of low on-farm productivity on One Health outputs in the emerging smallholder cattle farming sector, and addresses a gap in the academic literature to adopt modelling approaches as a comprehensive means of representing the dynamics of One Health with Systems Dynamic Modelling. MethodologyWe adopt a One Health approach in presenting a system dynamics simulation model of the weaner-rearing production system and the effect of nutrition and disease management on One Health production outputs. ResultsThe model is applied to the highveld region of South Africa and aims to identify the interventions that would most benefit the three One Health parameters of human, animal, and environmental health. The results suggest that increasing farmers' access to disease management training and on-farm infrastructure that aids in disease prevention activities (such as crushing pens) can improve One Health farming outputs (such as improving herd numbers, increasing income from weaner sales, and reducing the disease burden). However, these interventions do not have the desired significant positive impacts on cattle nutrition or feed density. Therefore, some well-intended interventions also have undesirable effects on One Health farming outputs. The results suggest One Health trade-offs within the production system and emphasizes that decision-makers across all levels must clearly define their individual and collective goals when adopting a One Health strategy.

Capturing the science behind the craft: a reporting framework to improve quality and confidence in nonsimulated models

AbstractQualitative nonsimulated models (causal loop diagrams, stock‐flow diagrams, or hybrids of both) have been used since within a decade after the inception of system dynamics (SD). In this article, we assert that the well‐known weaknesses of nonsimulated models need to be balanced against the contexts, purposes, and strengths that nonsimulated models provide. We propose a framework consisting of a set of best practices for model reporting and documentation that would improve the quality, consistency, and transparency of nonsimulated models. Several high‐quality examples are described and referenced in the framework to illustrate support of each criterion. The framework's purpose is help improve the transparency around the creation and evaluation of nonsimulated models, thereby enhancing their confidence and legitimate use in SD practice. Ultimately, high‐quality nonsimulated models can offer broader access to the powerful body of SD knowledge to audiences likely never to have access to formal SD simulation models. © 2023 System Dynamics Society.

A decision support methodology to support military asset and resource planning

ABSTRACT This paper presents a decision-support methodology to support the development and assessment of military asset and resource strategies. The methodology is built around a system dynamics model that allows users to examine the performance of a strategy over time. The novelty of the model lies in its flexibility and ability to address questions about asset planning from both holistic and lifecycle viewpoints. From the user perspective, the decision-support methodology is structured around three phases: (1) Design an asset management strategy, (2) Evaluate strategy using system dynamics simulation model, and (3) Generate performance indicators and analyse results. The methodology is developed and used in a real case study to support the modernisation of the Australian Defence Force. This paper demonstrates that system dynamics offers useful methods to study the dynamics of supply-demand, and support the development of systemic asset and resource management strategies.

Effects of government policies reform on environmental sustainability: An integrated approach of PMP and system dynamics simulation model

The government's supportive policies in the agricultural sector may provide some goals intended by policymakers; however, they may have environmental, social, and sometimes economic inefficiencies. Therefore, policy analysis not only needs to examine the effectiveness of these policies from the point of view of economic components but also, in a more comprehensive view, should assess the impact of these policies on other aspects like sustainability. In this study, an integrated Positive Mathematical Programming (PMP) and System Dynamics (SD) model was developed to investigate the effects of the agricultural policy reform on the cultivation pattern and water resources sustainability in the Doroodzan Dam basin in Fars Province, southern Iran, where managing water resources is a seriously challenging due to population growth and periodic drought. The initial investigation involved analyzing how price policies (guaranteed price and world price of crops) and non-price policies (removal of subsidy payments to agricultural inputs and improvement of irrigation efficiency) impacted the cropping pattern. The results of the study showed that the most significant decrease in cropland area occurs due to the removal of agricultural input subsidies. Although this crop pattern can lead to environmental sustainability, it is not considered from the point of view of food self-sufficiency. Based on the results, applying world prices increase cropping area for crops like rice, which is a water-intensive crop. Another point was the high priority of onions, fodder corn, and beans while they are not subjected to governmental pricing intervention. This may indicate the extent of public policies' impact on agriculture. Although under some policy scenarios changes in the gross margin or cropping area do not sound significant, the water-saving nature of these policies is more compelling. Finally, the impact of altering cropping patterns along with climate change and population growth on water indices was assessed using SD modeling. Thus, reforming the government's policies in the agricultural sector may help reduce the water shortage index in the basin. The policy of removing subsidies for the agricultural inputs led to the attainment of the lowest water shortage index.

Down the drain: The dynamic interplay of governance adjustments addressing setbacks in large public–private projects

AbstractLarge government projects involving public–private collaborations inherently suffer from setbacks such as delays, cost overruns, or failure to meet contracted performance. Such setbacks may effectively be addressed through adjustments to contractual and relational governance; yet to date, the dynamics of governance adjustments and their interplay in addressing setbacks is not well understood. This research presents a dynamic theory of how parties can effectively address project setbacks through adjustments to contractual and relational governance. The dynamic theory was generated using longitudinal case data from two large public–private projects in the Netherlands that faced comparable project setbacks but deployed opposing governance adjustments, leading to drastically different project outcomes (i.e., collapse vs. recovery). This theory was then elaborated through two more cases and evidence from the literature. A system dynamics simulation model was then built that reproduces the different governance adjustments and outcomes observed in the four projects and serves to extend theory building. The refined theory not only shows under what conditions adjustments to contractual or relational governance are most effective, but also that governance adjustment interplay may trigger unintended side effects. As such, the theory explains why the careful balancing of governance adjustments is critical to project outcomes.

A bi-objective decision support tool based on system dynamics and discrete event modelling for sustainable supply chain

Based on the development trend of sustainable concepts and the implement ability of composites combined with Agave Bagasse Fibre (ABF) and Polyethylene Terephthalate (PET). The purpose of this paper is to design a bi-objective decision support tool for supply chain of composite material which combined with ABF and PET. Through the production, processing, recycling, and reprocessing of composite materials, the sustainable supply chain model of four different schemes is designed, and the data results of each scheme model are calculated and analysed. The tool can support supply chain modelling solutions that seek best practices for sustainable supply chains and optimize resource efficiency through cost and carbon dioxide emissions. The sustainable supply chain model was designed, created, and optimized in AnyLogic software using System Dynamics and Discrete Event Simulation modelling methods based on the supply chain model established by previous researchers. According to the analysis results of the model data, the reasonable design of the whole process can effectively reduce the cost and carbon dioxide emissions and achieve the effectiveness and implementation of the sustainable supply chain. The results of this study will provide reference for more sustainable supply chain models in the future. Further research on composite materials can be carried out by combining with practice.

A system dynamics model for effective management strategies of High-Speed Railway (HSR) projects involving private sector participation

Policymakers increasingly seek recommendations to maximize ridership and public welfare for High-Speed Railway (HSR) projects implemented through private sector participation. Conventionally, such literature on Public-Private-Partnerships (PPPs) overlooks the complexity of HSR operations in achieving theoretical policy recommendations. Public policy recommendations based on a comprehensive understanding of HSR operations are rarely found in the literature. The current study develops a System Dynamics (SD) simulation model that formally structures the complex non-linear interactions between HSR stakeholders' management decisions and their impact on passenger ridership. The SD model is calibrated with actual operational data from the Taiwanese HSR. Simulations are implemented to observe how endogenous linkages between pricing, seat availability, maintenance, and service quality impact HSR ridership across lifecycle phases. The results provide a basis for considering important implications for relevant HSR stakeholders by revealing how simplistic strategies for managing HSR projects, not based on a complex system perspective, can lead to suboptimal results for long-term system performance. In particular, the study illustrates a mechanism for efficient HSR management through a balance between Market Saturation and Word-of-Mouth effects, with the need to increase the number of passengers willing to adopt HSR. As HSR operators alone are constrained in affecting many strategies generated by the model, the study also highlights the need for flexible but targeted coordination between public and private HSR stakeholders throughout different lifecycle phases of HSR operations. Such coordination should focus on promotional activities during the early operation stages and implementing pricing and service availability adjustments to respond differently to market penetration and demand expansion phases.

Evaluating carbon emissions of construction and demolition waste in building energy retrofit projects

Building energy retrofit (BER) is one of the priority tasks of China's ‘14th Five-Year Building Energy Efficiency and Green Building Development Plan’. The number of BER projects has dramatically increased in recent years in China, studies related to the management of construction and demolition waste (CDW) from BER projects have not kept pace. There is a need for more related studies, particularly for evaluating and mitigating the environmental impact of CDW from BER projects. This study aims to evaluate and mitigate carbon emissions from CDW of BER projects using a system dynamics (SD) approach through a case study BER project in the urban area of China. The SD model developed for this study includes sub-models for evaluating carbon emissions from the dismantlement of old components and the retrofit construction. Three scenarios were developed and the scenario analysis results reveal that the carbon emissions of CDW from the dismantlement of the old components account for higher carbon emissions than retrofit construction. Improving the inert waste recycling rate from 50% to 90% could save 2034.43 kg CO2 eq carbon emissions. Reducing 50% of CDW in BER construction could save 7673.06 kg CO2 eq carbon emissions. Improving WTE incineration rate from 50% to 100% could save another 50.53% of carbon emissions from the combustible waste. The SD simulation model provides a dynamic and non-linear scenario analysis platform for decision-makers to analyze the carbon emissions for managing CDW from BER projects.

Design and Development of an Optimal Control Model in System Dynamics through State-Space Representation

Control engineering and state-space representation are valuable tools in the analysis and design of dynamic systems. In this research, a methodology is proposed that uses these approaches to transform a system-dynamics simulation model into a mathematical model. This is achieved by expressing input, output and state variables as input, output and state vectors, respectively, allowing the representation of the model in matrix form. The resulting model is linear and time-invariant, facilitating its analysis and design. Through the use of this methodology, the system transfer matrix is obtained, which allows the analysis and design of the optimal control of the simulation model. The Ackermann gain-control technique is used to determine the optimal control of the system, which results in a shorter settlement time. This research proposal seeks to mathematically strengthen simulation models and provide an analytical alternative through modern control engineering in SD simulation models. This would allow more informed and effective decisions in the implementation of dynamic systems.

Dynamic Resilience Quantification of Hydropower Infrastructure in Multihazard Environments

Ensuring the continued functionality of hydropower infrastructure is of the greatest importance, considering the devastating socioeconomic and environmental impacts of dam operation failures. Among the different approaches currently adopted in hydropower dam operational safety, those that are resilience-based are at the leading edge because they focus on assessing the dynamic system performance pre-, during-, and post-hazard exposures. However, the main challenge for such assessment pertains to the complexity associated with the dynamic operation simulation of hydropower dam systems that consist of several components with nonlinear interdependencies. Moreover, the infrastructure’s exposure to a multihazard environment, which may impact one or more hydropower critical system components, poses further challenges to understanding possible subsequent dam operation failure scenarios. This study develops a resilience-centric system dynamics simulation model that provides a holistic representation of hydropower dam system components to estimate the system’s dynamic resilience in multihazard environments. The study also discusses a combinatorial procedure to generate multihazard scenarios, where a primary hazard can trigger one or more subsequent hazards. Finally, an actual hydropower dam is employed to demonstrate the developed model utility in assessing the resilience of complex infrastructure under a wide range of multihazard scenarios. The proposed model provides valuable decision support tools for infrastructure systemic risk mitigation in multihazard environments—facilitating the development of effective resilience planning strategies.