System Dynamics Research Articles

Research on carbon emission accounting and low carbon operation methods for urban water supply systems

Under the environment of global warming, how to promote the innovative and efficient development of water supply system is the key to sustainable urban development. There is still room for improvement in the study of carbon emissions in urban water supply systems and there is a lack of appropriate rationale for low-carbon operation and management of waterworks. A water-energy-carbon (WEC) framework is established in Fuzhou to account for the carbon emissions from 2013 to 2022 and the level of coupling and coordination development is evaluated in this study. A multi-objective optimization model and a system dynamics (SD) model were developed to optimize the low-carbon operation of the water supply system and predict future climate impacts. We also provide a quantitative and qualitative evaluation method for low-carbon operation. The results show that carbon emissions generated by electricity consumption and chemical use in the water supply system contribute greatly, and the coupling coordination level is high. Under different scenarios, the optimal solutions of carbon emissions, carcinogenic risk factors and unit energy economy range from 1.63 to 3.82 kt CO2-eq, 4.4 × 10−5 to 2.7 × 10−4, and 0.26 to 0.73 RMB/MJ. In the SD model, the water supply system can achieve 17 % and 20 % carbon reduction in 2025 and 2030. Its carbon reduction direction is mainly reflected in public service water use. This study provides a reference for optimizing the operation of water supply systems.

Vermicomposting organic waste with Eisenia fetida using a continuous flow-through reactor: Investigating five distinct waste mixtures

In this study, the vermicomposting of source-separated organic solid waste was investigated using Eisenia fetida in a continuous flow-through reactor. This novel approach is capable of simulating the complex interactions and dynamics of a full-scale vermicomposting system, offering valuable insights into the optimization of organic waste management. The primary objective of the research was to evaluate the quality of vermicompost produced in the reactor and determine its compliance with regulatory standards. For this purpose, food waste, yard waste, and pruning waste were mixed in different proportions to create five waste mixtures, which were then subjected to an 8-week pre-composting process. Subsequently, vermicompost was produced from the pre-composted waste mixtures using a continuous flow-through reactor that allows for long-term operation without disturbing the worms. While the total Kjeldahl nitrogen (TKN) content of the vermicomposts ranged from 2.04% to 2.48%, the total organic carbon (TOC) content of the vermicomposts was between 25.68% and 32.64%. Therefore, the carbon/nitrogen (C/N) ratio was calculated to be between 12.60 and 13.66. The quality of the final compost product showed that it met the limitations suggested in the European Fertilizer Regulation for the main physico-chemical parameters and heavy metals. It is concluded that vermicomposting in a continuous flow-through system reactor would be applicable to different organic waste streams.

MINN: Learning the Dynamics of Differential-Algebraic Equations and Application to Battery Modeling.

The concept of integrating physics-based and data-driven approaches has become popular for modeling sustainable energy systems. However, the existing literature mainly focuses on the data-driven surrogates generated to replace physics-based models. These models often trade accuracy for speed but lack the generalizability, adaptability, and interpretability inherent in physics-based models, which are often indispensable in modeling real-world dynamic systems for optimization and control purposes. We propose a novel machine learning architecture, termed model-integrated neural networks (MINN), that can learn the physics-based dynamics of general autonomous or non-autonomous systems consisting of partial differential-algebraic equations (PDAEs). The obtained architecture systematically solves an unsettled research problem in control-oriented modeling, i.e., how to obtain optimally simplified models that are physically insightful, numerically accurate, and computationally tractable simultaneously. We apply the proposed neural network architecture to model the electrochemical dynamics of lithium-ion batteries and show that MINN is extremely data-efficient to train while being sufficiently generalizable to previously unseen input data, owing to its underlying physical invariants. The MINN battery model has an accuracy comparable to the first principle-based model in predicting both the system outputs and any locally distributed electrochemical behaviors but achieves two orders of magnitude reduction in the solution time.

VOF-based modeling study of surface oscillation behavior and gas–liquid stirring dynamics in the bottom-blown reactors

Gas bottom-blown reactors are widely employed in the chemical, metallurgical, and biochemical industries due to their superior mixing capabilities. This study numerically investigates the gas–liquid flow hydrodynamics and bubble dynamics in a bottom-blown system with a circular boundary using the volume of fluid approach. Following the experimental validation of the mathematical model, the study evaluates the effects of gas flow rates, liquid heights, and fluid medium properties on both the dynamics of the bubble swarm and the mixing characteristics of the flow field. The results indicate that: (1) Rising bubbles disturb the fluid, generating numerous vortices that facilitate momentum transfer for effective gas stirring; (2) The height of the liquid surface oscillation during the bottom-blown process exhibits significant temporal variation, with the peak showing clear lateral swings; (3) Due to the nonlinear interactions involving bubble coalescence and breakup during their ascent, along with constructive and destructive interference between liquid surface waves, the liquid surface can exhibit violent fluctuations at certain moments; (4) Bubble size and aspect ratio significantly influence liquid surface oscillations; (5) The bubble rising path displays instability due to vortex shedding, with some vortices forming at locations where the bubble shape changes abruptly. A bubble velocity prediction equation is proposed: uc=σ5.2737Lcρc4.2737/16156μl9.5475.

An analytical investigation of the Van Der Waals gas system: Dynamics insights into bifurcation, optical pattern along with sensitivity and chaotic analysis

This paper focuses on obtaining exact solutions for the nonlinear Van der Waals gas system using the modified Khater method. Renowned as one of the latest and most precise analytical schemes for nonlinear evolution equations, this method has proven its efficacy by generating diverse solutions for the model under consideration. The governing equation is transformed into an ordinary differential equation through a well-suited wave transformation. This analytical simplification makes it possible to use the provided methods to derive trigonometric, rational, and hyperbolic solutions. To illuminate the physical behavior of the model, graphical plots of selected solutions are presented. By selecting appropriate values for arbitrary factors, this visual representation enhances comprehension of the dynamical system. Furthermore, the system undergoes a certain transformation to become a planar dynamical system, and the bifurcation analysis is examined. Additionally, the sensitivity analysis of the dynamical system is conducted using the Runge–Kutta method to confirm that slight alterations in the initial conditions have minimal impact on the stability of the solution. The presence of chaotic dynamics in the Van der Waals gas system is explored by introducing a perturbed term in the dynamical system. Two and three-dimensional phase profiles are used to illustrate these chaotic behaviors.

Study on Household Investment Decision of Household Photovoltaic Project Promotion -- Based on Inclusive Finance Perspective

Considering the lack of research on households' investment decisions in promoting photovoltaic projects in existing studies, this study constructs a four-party evolutionary game model based on local governments, financing institutions, photovoltaic enterprises and households from the perspective of inclusive finance. In addition, according to the influence of irrational psychological factors on the decision-making outcome of each interested party in decision-making, this study innovatively introduces regret theory to improve the evolutionary game model. Then, each subject' evolutionary stabilisation strategies and system equilibrium points are analysed explicitly using the perceived benefit function and the replicated dynamic differential equation. Finally, combined with the system dynamics method, the theoretical derivation results are verified by parameter assignment, and the sensitivity of each subject to multiple influencing factors is explored. The results show that: (1) under the current market condition, the system is stabilised in the strategy combination of Case I (subsidy, conventional finance, non-promotion, loan to build), but the ideal state can be achieved through the refinement and adjustment of policies. And there is a mutual influence between the subjects. (2) The regret-elation perception psychology of each subject has a non-negligible influence on their decision-making behaviour. The combination of strategies in Case I is a conservative decision by the subjects. (3) A variety of factors influences the behavioural decisions of each subject, and the amount of rent that photovoltaic enterprises can provide is a crucial factor affecting households' investment decisions. (4) Local governments incentives and penalties play a key incentive role in promoting the active participation of financing institutions and photovoltaic enterprises in the promotion endeavour. This study provides practical guidance and policy insights for promoting the diffuse use of renewable energy and the promotion of household photovoltaic projects while enriching the applied research by combining regret theory and evolutionary game theory.

Priority Order of Rural Infrastructure Investment Options: System Dynamics Analysis

Priority Order of Rural Infrastructure Investment Options: System Dynamics Analysis

Is net zero net positive? – Opportunities and challenges for pursuing a socio-economically sensitive net-zero transition for India

ABSTRACT At COP26 in Glasgow, India announced a long-term ambition to achieve net-zero greenhouse gas emissions by 2070. Existing emissions-economy modelling studies highlight that India’s emissions show no sign of peaking before mid-century and will not reach net zero by 2070 in a business-as-usual scenario with current policies. Using a mixed methodology of expert elicitation and system dynamics modelling, this article examines the policy gap that needs to be bridged for India to realize its net zero by 2070 commitment. The study discusses a socio-economically sensitive policy mix that could set India on a trajectory to peak its emissions in a decade and zero out its carbon dioxide (CO2) emissions by mid-century, leaving about one gigaton of other greenhouse gases to be decarbonized by 2070 to meet India’s net-zero goal. The policy mix realizes this goal while maintaining the government’s fiscal stability, and increasing employment and GDP beyond business-as-usual. The trajectory reported here is one of many possible low-carbon development pathways that could potentially be a net socio-economic positive for India. However, barriers such as the country’s lack of clean energy innovation and industrial policies, the gap between its domestic manufacturing capacity and deployment requirements, individual sector readiness for decarbonization, and the distributional implications of government revenue shifts through the energy transition remain significant challenges that need to be addressed to realize these potential socio-economic benefits of decarbonization.

A systematic method to integrate co‐produced causal loop diagrams based on feedback stories

AbstractWithin participatory systems dynamics, more practitioners are compiling co‐produced causal loop diagrams (CLDs) to analyse and report workshop outputs. Though not formalized, existing documented techniques have been limited to analyses of representations in single‐group diagrams predicated on, at times, untraceable subjective judgements. This paper addresses the need for a systematic method to guide and justify the subjective decisions made in the integration process. We propose a multistep, three‐stage process that synthesizes feedback stories from representations in diagrams (i.e. what is represented) and transcripts of the participatory process (i.e. what is said). This approach enables practitioners to report the interpretive scheme through which qualitative data are analysed and, thus, support the subjective decisions they made during the integration process. Using a case study, we demonstrate the application of this method and its potential for narrowing the semantic distance between participants, practitioners and external audience for interpreting and analysing an integrated diagram. © 2024 The Author(s). System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.

Towards resilience in Industry 5.0: application of system dynamics in matrix-structured manufacturing system

In the face of increasing global disruptions, resilient manufacturing systems are critical to ensuring operational stability, a concept central to the Industry 5.0 vision. The Matrix-Structured Manufacturing System (MMS) is a key example of such resilience, designed to maintain functionality and recover quickly under major disruptions. This paper introduces a novel System Dynamics (SD)-based modelling and simulation framework to quantitively assess the performance indicators and resilience of MMS. By simulating key disruption scenarios, including partial equipment failures and order fluctuations with resource constraints, this study evaluates the system’s response and recovery capabilities using a Comprehensive Resilience Index (CRI). Unlike conventional approaches, the proposed SD model captures the dynamic interactions across various production configurations and simulates the operational logic governing them, which can also be applied to other production systems. The simulation results demonstrate the potential of SD to support decision-making by providing insights into the effectiveness of reconfiguration strategies and resource management. This work aims at offering robust methods for quantitative resilience assessment and strategic planning towards the practical implementation of resilient manufacturing in Industry 5.0 envisions.

Integrating Self-Initialized Local Thermalizing Lindblad Operators for Variational Quantum Algorithm with Quantum Jump: Implementation and Performance.

Quantum computing holds great potential for simulating quantum systems, such as molecular systems, due to its inherent ability to represent and manipulate quantum states. However, simulating nonunitary dynamics of open quantum systems on a quantum computer is still challenging. Here, we present a scheme denoted as VQS-QJ-LTLME, which adopts the trajectory average of quantum jump Monte Carlo wave function variational evolution to evolve the system's density matrix and local thermalizing Lindblad operators to describe the system-environment interactions. This combination allows the quantum circuit to be initialized after a period of evolution, thereby eliminating the accumulation of errors. The VQS-QJ-LTLME algorithm requires only log2(n) qubits for system size n and holds a time complexity of , making it particularly suitable for operation on noisy intermediate-scale quantum devices. To accelerate the Monte Carlo sampling process in VQS-QJ-LTLME, we introduce an efficient sampling method, named No-evolution sampling (NES). The VQS-QJ-LTLME aided by NES requires simulating only n3 + 1 trajectories on quantum computers, and then makes 106 to 107 samplings on classical computers in a few seconds. To demonstrate the performance of the VQS-QJ-LTLME algorithm, we simulate the dynamics of a two-level spin-boson model and a four-level reduced Fenna-Matthews-Olson system with real superconducting quantum computers and classical simulators. It is shown that the simulations produced by VQS-QJ-LTLME algorithm align closely with those obtained from the purely classical methods.

Solving coupled non-linear schrödinger equations via quantum imaginary time evolution

AbstractCoupled non-linear Schrödinger equations are crucial in describing dynamics of many-particle systems. We present a quantum imaginary time evolution (ITE) algorithm as a solution to such equations in the case of nuclear Hartree-Fock approach. Under a simplified Skyrme interaction model, we calculate the ground state energy of an oxygen-16 nucleus and demonstrate that the result is in agreement with the classical ITE algorithm. We examine bottlenecks and deficiencies in the quantum algorithm and suggest possible improvements.

Towards systemic transformation in the construction industry: a complex adaptive systems perspective

PurposeThis study aims to investigate the strategies that successful companies in the construction industry use to achieve systemic transformation within their value chains and broader ecosystems. This study focuses on understanding how these companies navigate the challenges of a mature and slow-changing industry through innovative approaches.Design/methodology/approachA multiple case study design is used to analyze the systemic innovation dynamics across construction subsystems, through the lens of Complex Adaptive Systems theory. This research involves an empirical examination of nine case companies, selected based on their innovations in at least two construction subsystem areas and markers of success such as growth, profitability or invested capital. This methodology facilitates a detailed understanding of the company-level transformation.FindingsThis study identifies four distinct development paths toward systemic transformation within the construction industry: product-driven, product platform-driven, process integration-driven and business model-driven. These paths are characterized by unique strategies integrating technology, optimizing processes and innovating business models, demonstrating how companies can effectively adapt to and evolve within the construction ecosystem.Originality/valueThis research contributes original insights into company strategies and how they achieve systemic transformation. This study expands existing knowledge on systemic transformation in the construction industry by integrating empirical evidence with theoretical frameworks, offering a novel perspective on how successful companies innovate within a traditionally slow-changing sector.

Zero Plastic Drive: A Comprehensive Review on Unveiling Innovative Sustainable Solutions for a Circular Plastics Economy

Living in a society where plastic has become a necessity, the over-reliance on these materials is quite disturbing as they have social and economic effects, especially in waste disposal and resource management. Such issues have introduced the circular plastics economy (CPE), which aims to eliminate plastic waste by focusing on reducing, recycling, and reusing (3R) and designing biodegradable plastic products. Owing to these facts, a systematic literature review (SLR) was conducted to analyze the existing literature on circular economy principles and plastic waste management systems in terms of 3R initiatives. Also, this study showcases the CPE by investigating how it is possible to manage plastic within a circular economy instead of a linear system. Additionally, system dynamics modeling (SDM) was applied to examine the inter-relationships between key elements such as plastic production, waste generation, recycling rates, and regulatory actions, along with the cognizance phase of waste diversion and advanced sorting technology to minimize landfill dependency and environmental pollution initiatives, including producer responsibility programs and zero-landfill targets. This study accumulated that zero waste strategies, such as plastic circularity, national waste management, and high-quality recycling, have achieved recycling rates ranging from 30% to 81% across various countries, significantly reducing plastic waste and enhancing resource efficiency. However, the added strategies in countries that are related to policy-driven initiatives can prospectively be useful for increasing recycling capacity to eliminate plastic waste in landfills, promoting a circular economy and sustainable waste management practices. This study also involved the critical stakeholders of the CPE who will make the utilization of plastic waste a reality. Ultimately, this research contributes to the fast-growing knowledge base on plastic waste management by presenting an interdisciplinary framework based on model synthesis and mathematical modeling, which is crucial for decision-makers, industries, and researchers.

The Enrichment Economy: Market Dynamics, Brand Strategy, and Ethics

Rare watches, fine wines and spirits, sports cars, designer sneakers, and many other luxury goods create massive enrichment opportunities for consumers if they resell them on secondary markets. This trend is part of the enrichment economy, a novel form of market arrangement wherein consumers use iconic goods to increase their capital. However, it creates challenges for brands, such as preserving their primary market desirability and avoiding cannibalization. To understand how brands can navigate the enrichment economy, the authors conducted an ethnographic study of the luxury watch industry. They draw on market system dynamics to theorize market processes that sustain a market within the enrichment economy, and they explain the shared discourses, norms, and practices that make the enrichment economy function. This research makes four contributions. First, the authors theorize primary–secondary market dynamics as a novel class of market dynamics. Second, they theorize the new role of luxury brands as enrichment curators. Third, they discuss the ethics of enrichment by highlighting inequalities and risks it creates. Fourth, this research introduces the enrichment strategy as a novel brand strategy that capitalizes on the market dynamics of enrichment. The authors offer recommendations for luxury and nonluxury brands on product portfolio management, customer relationship management, and ethical innovation.

Exceptional swallowtail degeneracies in driven-dissipative quadrature squeezing

We show that swallowtail catastrophe consisting of various-order non-Hermitian and Hermitian degeneracies naturally exists in the dynamics of two-mode driven-dissipative quadrature squeezing systems that break pseudo-Hermiciticy by judiciously engineered losses. We reveal that the swallowtail degeneracy structure enables nontrivial braiding of complex eigenvalues by looping around an exceptional line in the parameter space. Our findings provide a comprehensive understanding of the degeneracy geometry in two-mode driven-dissipative bosonic quadratic systems, opening pathways toward topologically nontrivial control of Gaussian states. Published by the American Physical Society 2024

A global binary asteroid system model with irregularly shaped components via iterated surface integral

Abstract The dynamics of binary asteroid systems are referred to as the full two-body problem (F2BP), which is one of the principal problems in astrodynamics. The gravitational interactions, including the mutual potential, force, and torque, are necessary quantities to acquire the solution of F2BP. However, it is usually difficult to balance accuracy with efficiency of the evaluations, due to the highly irregular shapes of the asteroids and the close distance between the two components. In this paper, a global model is proposed for evaluating the interactions between two polyhedral asteroids with arbitrary separating distances. First, the interactions are represented as the double surface integrals through the iterated divergence theorem, which is lossless. The integrals over the complex boundaries of bodies are then converted to the sum of subdomain integrals over triangular facets which are compatible with the polyhedron model. Finally, these integrals are conveniently approximated through the numerical quadrature. This work provides a general solution that avoids the divergence problem of most traditional models. The benchmarking tests against the exact solution between two ellipsoids verify its high precision even if the bodies are almost touching. Considering asteroids with irregular shapes, we investigate the evolution of the Moshup-Squannit system and compare the results with the traditional series-based model. The developed model makes a reasonable balance between accuracy and efficiency with different quadrature strategies. The simulations show that the developed model achieves a comparable precision with the 4th-order series solution and a relatively fast computation speed with an appropriate quadrature strategy.

Enhancing production system resilience with digital twin-driven management

ABSTRACT In the last decade, significant advancements in digital technologies have revolutionized production systems, leading to the development of Cyber-Physical Systems (CPS) and Digital Twins (DT). This paper proposes a design of a production management system that leverages a Digital Twin associated with the shop floor. The objective is to enhance the resilience of production systems by providing real-time monitoring and enabling cloud-based outsourcing during production line failures. The methodology involves creating a Digital Twin model of the CPS, which is used to monitor the production process and visualize key performance indicators through a business intelligence tool. The contribution of this study lies in addressing the growing need for resilient production systems capable of withstanding disruptions and unexpected events. The DT provides accurate information useful for making informed decisions during disruptions. This research contributes to improving management practices by integrating production and enterprise data, facilitating decision-making processes aligned with company objectives, and enhancing the overall resilience of production systems. These findings illustrate the potential of cloud production services to maintain service levels. Among the academic contributions of this paper, is the use of System Dynamics as a suitable approach to modeling the behavior of a digital twin.

Insights into rare earth element speciation: unraveling sulfate and hydrolysis complexes through DFT calculations.

Rare earth elements (REE) are indispensable in numerous green technologies owing to their exceptional physical and chemical attributes. Separating REE is a pivotal process to meet the increasing demands of the high-tech industry. Understanding the hydrolysis of REE in aqueous environments marks the initial stride in comprehending their separation mechanisms. Sulfate commonly coexists in high-concentration solutions alongside REE, stemming from mineral processing. We analyzed the hydrolysis of REE and their complexes with sulfate using DFT methods. We present and discuss on the structural characteristics of hydrolysis species and sulfate complexes in alignment with existing experimental data. Estimates of Gibbs free energies for hydrolysis and sulfate complex formation were compared against literature values. REE pose challenges owing to the labile nature of aqua complexes and the pivotal role of system dynamics. We showed that hydrolysis reactions could be suitably modeled, yielding an error margin of approximately 5kcalmol-1 concerning experimental values, employing the M06 exchange-correlation functional with the SMD implicit solvation model. However, sulfate chemical species proved to be more challenging, exhibiting larger error margins with substantial variations across the REE series. The Raman spectrum analysis of lanthanum sulfate complexes demonstrated excellent agreement with experimental values. We applied the M06, PBE, and PBE0 exchange-correlation functionals combined with def2-TZVP basis sets and SMD to obtain the Gibbs free energies of hydrolysis and sulfate complexation with lanthanides in aqueous solution. The calculations were performed using the ORCA program.

OpenBF: an open-source finite volume 1D blood flow solver.

Computational simulations are widely adopted in cardiovascular biomechanics because of their capability of producing physiological data otherwise impossible to measure with non-invasive modalities. 
Objective
This study presents openBF, a computational library for simulating the blood dynamics in the cardiovascular system. 
Approach
openBF adopts a 1-D viscoelastic representation of the arterial system, and is coupled with 0-D windkessel models at the outlets. Equations are solved by means of the finite-volume method and the code is written in Julia. We assess its predictions by performing a multiscale validation study on several domains available from the literature. 
Main results
At all scales, which range from individual arteries to a population of virtual subjects, openBF's solution show excellent agreement with the solutions from existing software. For reported simulations, openBF requires low computational times. 
Significance
openBF is easy to install, use, and deploy on multiple platforms and architectures, and gives accurate prediction of blood dynamics in short time-frames. It is actively maintained and available open-source on GitHub, which favours contributions from the biomechanical community.