System Dynamics Research Articles

Exploiting automatic differentiation for quantum optimal control of driven dissipative two-level systems

Abstract In principle one can use the Pontryagin’s minimum principle to treat an optimal control problem and derive the gradient for the cost functional. However, for the driven spin-boson model studied here, the response of the system to the variation of the control is determined by the master equation and the equation of motion for the propagator of the coherent system dynamics. As a result, the application of the Pontryagin’s minimum principle is less straightforward.
An alternative to this approach is the technique of automatic differentiation which in principle amounts to doing calculus on the fully discretized form of the optimal control problem. Automatic differentiation tools can be viewed as black boxes taking as input a program computing the cost functional and giving as output another program computing its gradient. First we drive for the polaron transformed Hamiltonian a Born‒Markov master equation using the Bloch‒Redfield formalism. By combining the latter with automatic differentiation we are able to implement Z‒gate and coherent destruction of tunnelling with high fidelity. Optimization of a dissipative quantum gate poses a more complex numerical problem. Since it should occur independent of the input state. To overcome this difficulty, we apply optimal control to the concept of resolvent of the master equation which is the generalisation of quantum unitary evolution operator in case of dissipative dynamics.

Modelling connected and autonomous bus on dynamics of mixed traffic in partially connected and automated traffic environment

Since connected and autonomous buses (CABs) have great potential of being operated in partially connected environment and raise great impact on mixed traffic flow, this study develops an analytical model for modeling system dynamics of mixing connected and autonomous vehicles (CAV), human-driven vehicles (HV), and CABs in both cases of dedicated bus lane and non-dedicated bus lane, in which the impact of CABs is specifically quantified under varied levels of connected vehicle penetration. A Vissim-Matlab simulation evaluation is also developed for validating the model’s effectiveness. The results demonstrate that the proposed model performs well with an accuracy of over 85%, and it can be up to 95% in case of non-dedicated bus lane when the inflow rate is higher than 2000veh/h. Besides, the impacts of CABs’ volume, bus dwelling time, and bus stop location on the performance of mixed traffic flow are verified in two CAB operating environments. The obtained results can be used as the basis for planning and operating CABs in partially connected environment.

Cluster consensus for nonlinear multi‐agent systems restricted with input saturation by event triggered control

AbstractThis article studies the cluster consensus problem for the nonlinear multi‐agent systems subject to input saturation under the context of event triggered control. Taking ordinary consensus object as a special case, this article considers the problem of cluster consensus. The event triggered mechanism is designed and the Zeno phenomenon is ruled out. The sufficient conditions of control protocol and range estimation of domain of attraction are formulated by the linear matrix inequalities for the constraints of input saturation and nonlinear terms existed in the system dynamics. Finally, the proposed results are validated by one example in the background of spring damping system.

Temporal wave dynamics, phase portrait and qualitative analysis of the time-dependent (2+1)-dimensional Zakharov-Kuznetsov equation

In this article, we analyze the effect of time-dependent coefficients and the complex wave dynamics of the (2+1)-dimensional Zakharov-Kuznetsov (ZK) equation. This equation provides a detailed, insightful, and realistic description of space physics, plasma physics, controlled fusion, and nonlinear sciences. The wave solutions are established using the generalized Kudryashov, modified simple equation, and modified sine-Gordon expansion techniques and are illustrated by graphical depictions, which provide valuable insight into understanding the complex dynamics of waves across different physical systems. Exact solitary wave solutions offer a dependable approach to investigating the behavior of a system under particular conditions and facilitating a comprehensive understanding of its dynamics. We also conduct a stability analysis and present the phase portrait of the solutions, which are useful in various fields, including physics, plasma physics, chemistry, biology, economics, and sociology. We ascertain that the profiles of 3D and 2D soliton-shaped waves are significantly affected by dynamic changes in coefficients, wave velocity, and associated model parameters. This research could help clarify the dynamics of intricate systems, paving to a better understanding and analysis of the temporal aspects of various phenomena.

Greedy identification of latent dynamics from parametric flow data

Projection-based reduced-order models (ROMs) play a crucial role in simplifying the complex dynamics of fluid systems. Such models are achieved by projecting the Navier-Stokes equations onto a lower-dimensional subspace while preserving essential dynamics. However, this approach requires prior knowledge of the underlying high-fidelity model, limiting its effectiveness when applied to black-box data. This article introduces a novel, non-intrusive, data-driven method–Greedy Identification of Latent Dynamics (GILD)–for constructing parametric fluid ROMs. Unlike traditional methods, GILD constructs models directly from data, without relying on specific high-fidelity model information. It also employs interpolation within the manifold R∗N×q/Oq to accommodate parameter variability. Numerical experiments on various fluid dynamics scenarios, including lid-driven cavity flow, flow past a cylinder with varying Reynolds number, and Ahmed body flow with variable geometry, demonstrate GILD’s robust performance across both training and unseen parameter values. GILD’s ability to accurately capture system dynamics and its adaptability to diverse data sources highlight its potential as a powerful tool for constructing parametric reduced-order models in an easy and general way for complex fluid dynamics and beyond.

Community-Based Participatory Research and System Dynamics Modeling for Improving Retention in Hypertension Care

The high prevalence of hypertension calls for broad, multisector responses that foster prevention and care services, with the goal of leveraging high-quality treatment as a means of reducing hypertension incidence. Health care system improvements require stakeholder input from across the care continuum to identify gaps and inform interventions that improve hypertension care service, delivery, and retention; system dynamics modeling offers a participatory research approach through which stakeholders learn about system complexity and ways to model sustainable system-level improvements. To assess the association of simulated interventions with hypertension care retention rates in the Nigerian primary health care system using system dynamics modeling. This decision analytical model used a participatory research approach involving stakeholder workshops conducted in July and October 2022 to gather insights and inform the development of a system dynamics model designed to simulate the association of various interventions with retention in hypertension care. The study focused on the primary health care system in Nigeria, engaging stakeholders from various sectors involved in hypertension care, including patients, community health extension workers, nurses, pharmacists, researchers, administrators, policymakers, and physicians. Simulated intervention packages. Retention rate in hypertension care at 12, 24, and 36 months, modeled to estimate the effectiveness of the interventions. A total of 16 stakeholders participated in the workshops (mean [SD] age, 46.5 [8.6] years; 9 [56.3%] male). Training of health care workers was estimated to be the most effective single implementation strategy for improving retention in hypertension care in Nigeria, with estimated retention rates of 29.7% (95% CI, 27.8%-31.2%) at 12 months and 27.1% (95% CI, 26.0%-28.3%) at 24 months. Integrated intervention packages were associated with the greatest improvements in hypertension care retention overall, with modeled retention rates of 72.4% (95% CI, 68.4%-76.4%), 68.1% (95% CI, 64.5%-71.7%), and 67.1% (95% CI, 64.5%-71.1%) at 12, 24, and 36 months, respectively. This decision analytical model study showed that community-based participatory research could be used to estimate the potential effectiveness of interventions for improving retention in hypertension care. Integrated intervention packages may be the most promising strategies.

Virtual track irregularity establishment for load prediction of heterogeneous bogie frames for virtually coupled trainsets

In this paper, we establish the virtual track irregularity (VTI) considering suspension system dynamics for load prediction of heterogeneous bogie frames for virtual coupled train sets (VCTS). At first, the dynamic characteristics of axlebox spring set and primary suspension vertical damper of A/B-type high-speed trains are analyzed and compared for establishment of frequency-varying parameter simplified vehicle dynamic models (FVP-SVDMs). Then, a frequency-segmented time-domain inversion (FSTIM) of VTI suitable for FVP-SVDMs is conducted, and a quantitative evaluation method for VTI consistency is established. Finally, the consistency of VTIs based on measured loads of A/B-type high-speed train bogie frames is quantitatively assessed, and the agreement between the measured and predicted load spectra based on VTI is evaluated. Based on the FVP-SVDM and the corresponding VTI, the equivalent load amplitude error between the predicted and measured bouncing load is 7%. The VTI technology provides the possibility for VCTS to eliminate the need for conducting the main test before applying the new vehicles on the line. In addition, for the fleet is running on the same track through the VCTS communication, the VTI will provide the theoretical support for implementing active control across the entire fleet.

Policy design for renewable energy development based on government support: A system dynamics model

Energy's centrality to life, work, and progress underscores its indispensable role in modern society. However, burgeoning energy consumption and finite resources have prompted concerns regarding resource sustainability. Consequently, renewable energy sources have gained prominence as alternatives, integral to societal advancement. Therefore, with the increase in the price of fossil fuels and its limitations and the attention to renewable energies, in this research, we decided to study the implementation processes of the development of this type of energy about possible future scenarios and possible implementation policies at the time of each scenario. Let's pay Considering the dynamic complexities of this issue over time and the involvement of government sectors in policy discussions and private sectors in the implementation and participation of these two groups simultaneously, using dynamic system modeling to design a dynamic model that economic aspects, technical, political and environmental aspects should be evaluated simultaneously in a causal-disability manner. To implement this model, two scenarios of government support and non-support for this industry were taken into consideration, and in each scenario two policies of workforce training and technology import for the use of private sector managers and in the best scenario two policies of tax exemption and reduction of technology import tariff for Government decision-making was reviewed. The results showed that when this industry enjoys government support, the speed of development of renewable energy projects can be greatly increased by importing equipment. Without governmental backing, expedited progress is achievable through skilled labor training and employment. Tax exemptions are the most effective policy tool for stimulating renewable energy project processes, production, and sales. The findings underscore the pivotal role of strategic governmental intervention in facilitating renewable energy development, which is essential for meeting energy demands while mitigating environmental impact.

Investigating new solutions for a general form of q$$ \mathfrak{q} $$‐deformed equation: An analytical and numerical study

SummaryThis paper contributes to the study of a new model called the ‐deformed equation or the ‐deformed tanh‐Gordon model. To understand physical systems with violated symmetries. We utilize the ‐expansion approach to solve the ‐deformed equation for specific parameter values. This method generates solutions that provide valuable insights into the system's dynamics and behavior. To verify the accuracy of our solutions, we also apply the finite difference technique to obtain numerical solutions to the ‐deformed equation. This dual approach ensures the reliability of our results. We present our findings using tables and graphics to enhance clarity and facilitate comparison between the analytical and numerical solutions. These visual aids help readers better understand the similarities and differences between the two approaches. The ‐deformation is significant as it models physical systems with nonstandard symmetry features, like extensivity, offering a more accurate representation of real‐world phenomena. The growing significance of this equation across various disciplines highlights its potential in advancing our understanding of complex physical systems. This paper contributes valuable knowledge about the ‐deformed equation, demonstrating its potential for accurately modeling physical systems with violated symmetries. Through both analytical and numerical techniques, we offer comprehensive solutions and validate their accuracy, with graphical representations enhancing the clarity and understanding of our results. This exploration of ‐deformation advances modeling techniques, providing a more precise depiction of real‐world processes with nonstandard symmetry features.

The effect of carbon quota allocation methods on maritime supply chain emission reduction

In September 2020, the European Parliament decided to include the CO2 emitted on the all intra-European and 50% of extra-European voyages in the European Union Emission Trading System (EU-ETS) starting from 2022, in order to reduce the CO2 emission. With the implementation of EU-ETS, the maritime supply chain will inevitably be significantly affected. Different carbon quota allocations in ETS have different impact on the CO2 emission reduction, which motivates us to investigate the effect of different carbon quota allocations on maritime CO2 emission reduction. Therefore, this paper considers two carbon quota allocations: the historical total quantity method and the historical intensity method, and develops a game model for each method. Then, the equilibrium solutions of each game model are analyzed. With the help of the system dynamics and the software Vensim, numerical experiments are conducted to verify the properties obtained in the analysis of the equilibrium solutions. The experimental results indicate that 1) Green technology (GT) can effectively reduce carbon emissions. Based on long-term simulation results, the GT investments will be gradually offset by profiting from carbon quota trading. 2) Profits may vary with price, but the Historical Intensity method consistently achieves better carbon reduction effects or relatively higher profits. 3) The marginal profits of companies with similar historical intensity baselines are almost the same. This gives an advantage to companies who implement green technologies earlier, as they can quickly gain returns from GT.

Coupled analysis of floating offshore wind turbines with new mooring systems by CFD method

This paper presents a fully coupled aero-hydro-mooring numerical model of the National Renewable Energy Laboratory's (NREL) 5 MW OC4 semi-submersible Floating Offshore Wind Turbine (FOWT). The model's accuracy was validated through comparisons with existing experimental and numerical data, utilizing OpenFOAM, a Computational Fluid Dynamics (CFD) software. The key contributions of this study include demonstrating the model's precision in predicting aerodynamic performance, motion responses, and mooring system dynamics under wind and wave conditions. Additionally, a comparative analysis is conducted between a Conventional mooring system (CMS) and a New mooring system (NMS). The results show that the NMS offers improved stability in surge and heave motions, crucial for operational effectiveness and resilience. Furthermore, the NMS demonstrates a more efficient stress distribution and also reduced tensions in the mooring lines, contributing to the long-term durability and safety of the structure. In terms of aerodynamic performance, the differences between the two mooring systems are limited due to the combined surge and pitch motion phase difference. Future research will focus on optimizing these phase differences to enhance performance and refine the cost-efficiency of the mooring system.

Adaptive neural optimal tracking control for uncertain unmanned surface vehicle

This article proposes a novel adaptive neural optimal control scheme for the uncertain unmanned surface vehicle (USV) system. The proposed adaptive neural optimal control scheme is composed of a neural feedforward controller and a neural optimal feedback controller. The neural feedforward controller is designed by using neural networks (NNs) and the backstepping control design technique to make the unknown nonlinear dynamics of USV system to be stabilized. The neural optimal feedback controller is designed based on adaptive dynamic programming (ADP) theory. It is proved that the formulated adaptive neural optimal control scheme can achieve all signals in USV system are uniformly ultimately bounded (UUB) and the cost function is minimized. The simulation and comparison results demonstrate the effectiveness of the proposed optimal control scheme.

Towards sustainable urban logistics: Exploring the implementation of city hubs through system dynamics

The urban logistics system causes negative externalities, such as pollution, noise and congestion. This study focuses on city hubs as a concept to reduce these externalities by improving consolidation and adopting zero-emission vehicles. Our research employs system dynamics as a method to uncover the dynamics and mechanisms related to the barriers and potentials of city hub implementation in Stockholm from the perspectives of the Logistic Service Providers (LSPs), the receivers and the public sector. Moreover, a mixed method approach is used for data collection, allowing us to extract the knowledge from the real implementation case, co-create a qualitative model as a Causal Loop Diagram (CLD) with the stakeholders involved in the system, and generalise the model. The mixed method approach includes a group model-building workshop, literature review, existing city hub analysis and stakeholder interviews. The main result is a CLD, visualising the dynamics of the introduction of city hubs. The CLD explores three potential incentives and policies: (i) the receivers change address; (ii) shippers oblige LSPs to use the hubs; (iii) the public sector gives monetary incentives to LSPs. The CLD presented in this paper establishes a validated system structure for the urban logistic system and facilitates the policymakers’ understanding of the barriers to implementing city hubs and what policies could help their implementation.

Intramolecular charge transfer dynamics of anthraquinone derivatives in the confined environments of reverse micelles

Reverse micelles (RMs) are considered important model systems for molecular dynamics and chemical reactions, where the nanopools of aqueous and nonaqueous polar cores are separated from the surrounding organic phase via a monolayer of surfactant molecules. Here, we report the intramolecular charge transfer (ICT) dynamics of anthraquinone derivatives in the methanol-in-oil RMs composed of nonionic surfactants Igepal by femtosecond transient absorption and fluorescence upconversion spectroscopy. The ICT dynamics slow down inside the RMs due to abnormally diminished solvent motions and restricted internal rotations of the (methyl)amino group during the ICT in the excited states. The micelle size-dependent dynamics of anthraquinone derivatives inside the RMs were compared with the results in bulk aliphatic alcohols and understood as the changes in the microenvironment properties such as microviscosity.

Evaluation of driving effects of carbon storage change in the source of the Yellow River: A perspective with CMIP6 future development scenarios

Understanding how future climate scenarios impact land use/cover (LUC) and carbon storage (CS) is crucial for achieving carbon neutrality. However, research often overlooks the spatiotemporal impacts of future climate and socioeconomic changes on CS. This study integrates system dynamic (SD), patch-generating land use simulation (PLUS), the integrated valuation of ecosystem services and tradeoffs (InVEST) model, and the geographical detector to assess the LUC and CS evolution in the source of the Yellow River (SYR) from 2020 to 2060. Utilizing carbon density and LUC data, we explored the influence of natural and socioeconomic factors on CS under five shared socioeconomic pathways and representative concentration pathways (SSP-RCPs) scenarios. Our findings demonstrate that: (1) Ecological land, including woodland, grassland, and wetland, expanded more under SSP126 compared to SSP245, with SSP345, SSP460, and SSP585 showing a trend of degradation tied to deeper economic contribution. (2) By 2060, CS in terrestrial ecosystem under SSP126, SSP245, SSP345, SSP460, and SSP585 were 702.33 × 106 t, 700.33 × 106 t, 697.22 × 106 t, 696.03 × 106 t, and 691.21 × 106 t, respectively. This represents changes of 3.69 × 106 t, 1.69 × 106 t, −1.49 × 106 t, −2.68 × 106 t, and −7.43 × 106 t compared to 2020. (3) Soil type predominantly influenced the spatial differentiation of CS, with significant interactions with precipitation. This research provides new insights into land redistribution, economic strategies, and achieving carbon neutrality.

Lean manufacturing tools as drivers of social sustainability in the Mexican maquiladora industry

Social Sustainability (SOS) is crucial to an industry’s success and depends on various factors. This study presents a structural equation model (SEM) that examines how three lean manufacturing tools, focused on continuous improvement, Kaizen, Gemba, and 5Whys, can enhance SOS. Six hypotheses were proposed and validated using information from 411 responses to a survey on the Mexican maquiladora industry, and the partial least squares approach was used to test them. Subsequently, the system dynamics technique was applied to simulate different scenarios and determine the optimum SOS level based on lean manufacturing tools. The findings indicate that only Kaizen can achieve 100 % implementation within less than five years, whereas the other variables require a more extended period. Specifically, the SOS reached 100 % after 10.25 years, and this period is considered too long. Companies should periodically investigate the new needs of employees to improve their SOS. This study is the first to combine SEM and SD to assess the impact of Kaizen, Gemba, and 5Whys as LM Social Sustainability tools, offering a new perspective to achieve sustainable industrial practices. Companies should periodically investigate new employees’ needs to improve their SOS.

Modeling for sustainable groundwater management: Interdependence and potential complementarity of process-based, data-driven and system dynamics approaches

Groundwater systems are vast natural water reservoirs used to support human water demands and ecosystem services. Various modeling approaches have been developed to help manage these complex highly-dynamic systems. This paper discusses the strengths and limitations of three modeling approaches, namely: process-based, data-driven and system dynamics modeling. For demonstration purposes, the three modeling approaches are applied to the Konya Closed Basin, a large agricultural region with semi-dry climate located in central Turkey. Process-based modeling is grounded in the theory-based representation of the governing processes but is somewhat limited by the computational effort and the difficulty of defining the required input parameters that characterize the heterogeneous aquifer system. Process-based models are shown to be powerful tools for resource management purposes provided climatic and water demand scenarios are accurately defined. Data-driven models are efficient tools for the management of groundwater resources but are highly dependent on the availability of large training data sets encompassing the spectrum of possible system responses. The high efficiency of surrogate modeling approaches makes them ideal tools for incorporation into applications such as real-time decision support systems and digital twin platforms. System dynamics modeling examines the groundwater exploitation problem within a socio-economic context that involves multiple stakeholders and their decision making. It combines groundwater flow models with socio-economics and endogenous decision rules to conduct scenario analysis and support policy development. The analyses and model demonstrations presented in this paper underscore the interconnectedness and complementarity of these three modeling approaches and the need for more integrated use of these modeling approaches for enhanced multi-sectoral management of groundwater systems.

Design and analysis of discrete fractional-order chaotic map with offset-boosting behavior

Fractional calculus, as a more accurate tool for depicting the dynamics of complex systems, has been introduced into discrete chaotic maps. To further describe the offset-boosting behavior in discrete systems, a discrete fractional-order chaotic map (DFOCM) based on the Caputo difference operator is constructed. The mapping order of this fractional-order model controls the stability of the fixed point, thereby affecting the dynamic behavior of the map. The dynamics of DFOCM is studied using numerical simulation methods such as bifurcation diagrams and maximum Lyapunov exponents, revealing the presence of multistability. By comparing with integer-order map, it is found that DFOCM exhibit a larger chaotic region. Based on this, the difference between fractional order and integer order offset-boosting behavior is theoretically derived. Specifically, the offset-boosting behavior of fractional-order maps concerning mapping parameters is related to the initial state, which was further demonstrated through numerical simulations. SE complexity proves that the chaotic sequences generated by DFOCM have high unpredictability and pseudo-randomness. Finally, the proposed DFOCM is implemented on the DSP hardware platform, and the physical feasibility of numerical simulation is verified.

Seeking a pathway towards a more sustainable human-water relationship by coupled model – From a perspective of socio-hydrology

It is essential to systematically consider social, economic, and natural endowments in managing and allocating water resources. However, few studies have comprehensively quantitatively evaluated the allocation of regional water resources from a socio-hydrology perspective and provided recommendations. To explore this research gap, we have constructed a tightly coupled framework that integrates system dynamics models and optimization algorithms to carry out an innovative redistribution of water resources in Shaanxi Province. The system dynamics model simulation results showed that the error was almost always within 10% over the research period, indicating robust simulation capability and laying a solid foundation for subsequent model coupling. The coupled model achieves convergence in approximately 30 generations by formulating the optimization problem with four individual objectives. Optimizing four objectives concurrently results in convergence around the 150th generation. The optimized Pareto solution sets visually demonstrate the trade-offs between different objectives. In the optimized water allocation schedule, the water consumption in Yulin exhibits a change of 1.22 ×108m3, reflecting the most significant optimization effects on agricultural and domestic water allocation. The results indicated that the comprehensive Gini coefficient typically ranged between 0.2 and 0.3. Over the period from the year 2010–2021, the Gini coefficient exhibited a declining trend, signifying a positive trajectory in water resource allocation throughout the research period and a high level of fairness. The annual total green WF of grain in Weinan was the highest at 14.26 ×108m3, followed by Xianyang at 9.52 ×108m3, and the lowest in Tongchuan at 0.54 ×108m3. The annual average amount of blue WF of grain is the highest in Hanzhong, at 11.33 ×108m3, followed by Weinan at 9.60 ×108m3, and the lowest in Tongchuan at 0.14 ×108m3. The coupled framework proposed in this study exhibits significant innovation, scalability, and practical efficiency. It can inspire future research and decision-making and holds the potential for application in other regions.

ACL Injury Etiology in Its Context: A Systems Thinking, Group Model Building Approach.

Background/Objectives: Given the complex nature of Anterior Cruciate Ligament (ACL) injury, it is important to analyze its etiology with suitable approaches in order to formulate intervention strategies for effective prevention. The present study employs system thinking techniques to develop a Causal Loop Diagram (CLD) Model for investigating the risk factors for ACL Injury (CLD-ACLI), through a Group Model Building approach. Methods: A two-stage procedure was applied involving a comprehensive literature review followed by several systems thinking group-modeling co-creation workshops with stakeholders. Results: Based on input from experts and stakeholders, combined with the latest scientific findings, the derived CLD-ACLI model revealed a series of interesting complex nonlinear interrelationships causal loops between the likelihood of ACL injury and the number of risk factors. Particularly, the interaction among institutional, psychological, neurocognitive, neuromuscular, malalignment factors, and trauma history seem to affect neuromuscular control, which subsequently may alter the biomechanics of landing, predisposing the ACL to injury. Further, according to the proposed CLD-ACLI model, the risk for injury may increase further if specific environmental and anatomical factors affect the shear forces imposed on the ACL. Conclusions: The proposed CLD-ACLI model constitutes a rigorous useful conceptual presentation agreed upon among experts on the dynamic interactions among potential intrinsic and extrinsic risk factors for ACL injury. The presented causal loop model constitutes a vital step for developing a validated quantitative system dynamics simulation model for evaluating ACL injury-prevention strategies prior to implementation.