System Dynamics Research Articles

Concave Gold Nanocubes Exhibit Growth-Etching Behavior: Unexpected Morphological Transformations.

Chemical equilibrium stands as a fundamental principle governing the dynamics of chemical systems. However, it may become intricate when it refers to nanomaterials because of their unique properties. Here, we invesitigated concave gold nanocubes (CGNs) subjected to an akaline Au3+/H2O2 solution, which exhibit both etching and growth in a monotonic solution. When CGNs were subjected to an increasingly alkaline Au3+/H2O2 solution, their dimensions increased from 107 to 199 nm and then decreased to 125 nm. Transmission electron microscopy (TEM) demonstrated that their morphology undergoes intricate alternations from concave to mutibranch and finally to concave again. Real-time ultraviolet-visible spectroscopy and time-dependent TEM also demonstrated reduction first and then oxidation in one solution. Among the nanomaterials, the obtained carpenterworm-like gold nanoparticles revealed the best catalytic performance in p-nitrophenol reduction by NaBH4, with a chemical rate that continues to increase until the reaction reaches completion. Growth leading to atomic dislocation, distortion, and exposure on nanoparticles and the redox of H2O2 plausibly account for the further etching due to the Ostwald ripening effect. Our study may spur more interest in the tuning of the properties, engineering, investigation, and design of new kinds of nanomaterials.

Composite‐observer‐based asynchronous control for hidden Markov nonlinear systems with disturbances

SummaryIn this article, an asynchronous adaptive tracking control approach is presented for a type of hidden Markov jump nonlinear systems with external disturbances. In this joint jump process model, hidden Markov model signifies the dynamics of the actual system, whereas the signal emits from the detector symbolizes the transmitted information. This leads to the phenomenon of asynchronization between the modes of the system and that of the controller. Accordingly, an asynchronous observer is developed by using the mode information from the detector to develop an asynchronous control approach. The observer contains a disturbance estimation part, to compensate the unknown external inputs. Utilizing the backstepping scheme, a strict‐feedback asynchronous tracking controller is formulated, guaranteeing that all signals within the closed‐loop system are semi‐globally uniformly ultimately bounded in probability. Finally, the validity of the presented methodology is illustrated by means of a simulation example.

Dynamics of the epidemiological Predator-Prey system in advective environments.

This paper aims to establish the existence of traveling wave solutions connecting different equilibria for a spatial eco-epidemiological predator-prey system in advective environments. After applying the traveling wave coordinates, these solutions correspond to heteroclinic orbits in phase space. We investigate the existence of the traveling wave solution connecting from a boundary equilibrium to a co-existence equilibrium by using a shooting method. Different from the techniques introduced by Huang, we directly prove the convergence of the solution to a co-existence equilibrium by constructing a special bounded set. Furthermore, the Lyapunov-type function we constructed does not need the condition of bounded below. Our approach provides a different way to study the existence of traveling wave solutions about the co-existence equilibrium. The existence of traveling wave solutions between co-existence equilibria are proved by utilizing the qualitative theory and the geometric singular perturbation theory. Some other open questions of interest are also discussed in the paper.

Early Predictor for the Onset of Critical Transitions in Networked Dynamical Systems

Numerous natural and human-made systems exhibit critical transitions whereby slow changes in environmental conditions spark abrupt shifts to a qualitatively distinct state. These shifts very often entail severe consequences; therefore, it is imperative to devise robust and informative approaches for anticipating the onset of critical transitions. Real-world complex systems can comprise hundreds or thousands of interacting entities, and implementing prevention or management strategies for critical transitions requires knowledge of the exact condition in which they will manifest. However, most research so far has focused on low-dimensional systems and small networks containing fewer than ten nodes or has not provided an estimate of the location where the transition will occur. We address these weaknesses by developing a deep-learning framework which can predict the specific location where critical transitions happen in networked systems with size up to hundreds of nodes. These predictions do not rely on the network topology, the edge weights, or the knowledge of system dynamics. We validate the effectiveness of our machine-learning-based framework by considering a diverse selection of systems representing both smooth (second-order) and explosive (first-order) transitions: the synchronization transition in coupled Kuramoto oscillators; the sharp decline in the resource biomass present in an ecosystem; and the abrupt collapse of a Wilson-Cowan neuronal system. We show that our method provides accurate predictions for the onset of critical transitions well in advance of their occurrences, is robust to noise and transient data, and relies only on observations of a small fraction of nodes. Finally, we demonstrate the applicability of our approach to real-world systems by considering empirical vegetated ecosystems in Africa. Published by the American Physical Society 2024

Analyzing the impact of convective boundary conditions on fluid–particle mixture flow in a ciliated walled horizontal tube filled with Rabinowitsch fluid

This study investigates the impact of convective boundary conditions, thermal radiation, and viscous dissipation on the flow of fluid–particle mixture in a ciliated walled horizontal tube filled with Rabinowitsch fluid. A mathematical model is developed using partial differential equations of continuity, motion, and energy, which are solved using the symbolic software MATHEMATICA 12.0 with convective boundary conditions. Exact solutions for velocity, temperature distribution, pressure gradient, pressure rise, stream function, and heat transfer rate are obtained and analyzed for dilatant, Newtonian, and pseudoplastic fluids. Computational results reveal that the velocity and temperature profiles are highest at the center of the tube for pseudoplastic and Newtonian fluids compared to dilatant fluid. Additionally, pressure gradient fluctuates near the tube walls. The study also explores special cases where the Rabinowitsch fluid model is reduced to dilatant, Newtonian, and pseudoplastic fluids. The findings have potential applications in medical treatments for respiratory system tumors, airway cleaning, physiological fluids, and manufacturing processes involving peristaltic flow. This original research contributes to the understanding of fluid dynamics in complex systems and has implications for various practical applications.

Fast event-driven simulations for soft spheres: from dynamics to Laves phase nucleation.

Conventional molecular dynamics (MD) simulations struggle when simulating particles with steeply varying interaction potentials due to the need to use a very short time step. Here, we demonstrate that an event-driven Monte Carlo (EDMC) approach was first introduced by Peters and de With [Phys. Rev. E 85, 026703 (2012)] and represents an excellent substitute for MD in the canonical ensemble. In addition to correctly reproducing the static thermodynamic properties of the system, the EDMC method closely mimics the dynamics of systems of particles interacting via the steeply repulsive Weeks-Chandler-Andersen (WCA) potential. In comparison to time-driven MD simulations, EDMC runs faster by over an order of magnitude at sufficiently low temperatures. Moreover, the lack of a finite time step in EDMC circumvents the need to trade accuracy against the simulation speed associated with the choice of time step in MD. We showcase the usefulness of this model to explore the phase behavior of the WCA model at extremely low temperatures and to demonstrate that spontaneous nucleation and growth of the Laves phases are possible at temperatures significantly lower than previously reported.

Predicting Land Use Changes under Shared Socioeconomic Pathway–Representative Concentration Pathway Scenarios to Support Sustainable Planning in High-Density Urban Areas: A Case Study of Hangzhou, Southeastern China

Amidst the challenges posed by global climate change and accelerated urbanization, the structure and distribution of land use are shifting dramatically, exacerbating ecological and land-use conflicts, particularly in China. Effective land resource management requires accurate forecasts of land use and cover change (LUCC). However, the future trajectory of LUCC, influenced by climate change and urbanization, remains uncertain. This study developed an integrated multi-scenario framework by combining system dynamics and patch-generating land use simulation models to predict future LUCC in high-density urban regions under various Shared Socioeconomic Pathway (SSP)–Representative Concentration Pathway (RCP) scenarios. The results showed the following: (1) From 2020 to 2050, cultivated land, unused land, and water are projected to decrease, while construction land is expected to increase. (2) Future land use patterns exhibit significant spatial heterogeneity across three scenarios. Construction land will expand in all districts of Hangzhou, particularly in the main urban areas. Under the SSP585 scenario, the expansion of construction land is most significant, while it is the least under the SSP126 scenario. (3) Distinct factors drive the expansion of different land use types. The digital elevation model is the predominant factor for the expansion of forest and grassland, contributing 19.25% and 30.76%, respectively. Night light contributes the most to cultivated land and construction land, at 13.94% and 20.35%, respectively. (4) The average land use intensity (LUI) in central urban districts markedly surpasses that in the surrounding suburban areas, with Xiacheng having the highest LUI and Chun’an the lowest. Under the SSP126 scenario, the area with increased LUI is significantly smaller than under the SSP245 and SSP585 scenarios. These findings offer valuable guidance for sustainable planning and built environment management in Hangzhou and similarly situated urban centers worldwide.

Sustainable development of Depok Beach, Yogyakarta: System dynamics approach to waste management and maritime economy enhancement

<p dir="ltr"><span>Depok Beach is a tourist destination in Yogyakarta which has experienced significant development as part of the South Coast National Tourism Strategic Area of Yogyakarta. However, waste management is still the main challenge faced. The objectives of this study is to build a sustainable model for Depok Beach, to estimate the behaviour of the management system, and develop a strategy to promote the maritime economy in the. System dynamics was used for modelling the management strategy. Data were collected through observation and in-depth interviews with related stakeholders. The results showed that Depok Beach will continue to attract more tourists until 2030, but a decrease in visitor numbers is expected to occur after that. It is due to a decrease in the attractiveness value of the beach. Meanwhile, a comprehensive and integrated approach of policy implementation scenarios is needed to yield significant results. The development of Depok Beach required a comprehensive, integrated policy approach.</span></p>

Robust error-state Kalman-type filters for attitude estimation

State estimation techniques appear in a plethora of engineering fields, in particular for the attitude estimation application of interest in this contribution. A number of filters have been devised for this problem, in particular Kalman-type ones, but in their standard form they are known to be fragile against outliers. In this work, we focus on error-state filters, designed for states living on a manifold, here unit-norm quaternions. We propose extensions based on robust statistics, leading to two robust M-type filters able to tackle outliers either in the measurements, in the system dynamics or in both cases. The performance and robustness of these filters is explored in a numerical experiment. We first assess the outlier ratio that they manage to mitigate, and second the type of dynamics outliers that they can detect, showing that the filter performance depends on the measurements’ properties.

On the Dynamics of a Three-dimensional Differential System Related to the Normalized Ricci Flow on Generalized Wallach Spaces

On the Dynamics of a Three-dimensional Differential System Related to the Normalized Ricci Flow on Generalized Wallach Spaces

Different patterns of coupled predator-prey dynamics when the same species interact in different locations.

Individual predator and prey species exhibit coupled population dynamics in simple laboratory systems and simple natural communities. It is unclear how often such pairwise coupling occurs in more complex communities, in which an individual predator species might feed on several prey species and an individual prey species might be attacked by several predators. To examine this problem, we applied multivariate autoregressive state-space (MARSS) models to 5-year time-series of monthly surveys of a predatory fish, the eastern mosquitofish (Gambusia holbrooki), and its littoral zone prey species, the least killifish (Heterandria formosa), in three locations in north Florida. The MARSS models were consistent with coupled predator-prey dynamics at two of the three locations. In one of these two locations, the estimated densities of the two species displayed classic predator-prey oscillations. In the third location, there was a positive effect of killifish density on mosquitofish density but no detectable effect of mosquitofish density on killifish density. In all three locations, increased submergent vegetation cover was associated with increased prey density but not increased predator density. Eigenvalues analyses for the joint predator-prey dynamics indicated that one of the cyclic locations had more stable dynamics than the other locations. The three different patterns demonstrate that the dynamics of a pairwise predator-prey interaction emerge not only from the characteristics of the prey and the predator, but also those of the habitat and trophic web in which the predator and prey are embedded.

Proposing a Novel System for Measuring the Effectiveness of Validating Customers of the Banking System based on the System Dynamics

Proposing a Novel System for Measuring the Effectiveness of Validating Customers of the Banking System based on the System Dynamics

Signal enhancement method for gearboxes fault diagnosis in robotic flexible joint

Abstract Motor Current Signal Analysis (MCSA) provides a non-intrusive approach to fault diagnosis. However, the fault impact reacting in the current is reduced due to the presence of flexible structures in the transmission path from the fault source to the motor. Therefore, this paper proposes a method to enhance the frequency domain of the current signal of a single mechanical fault through a transfer model between motor torque and link vibration. First, the joint system dynamics model was developed based on a three-inertia simplified model. The transfer model of motor torque and link vibration was defined based on the system dynamics. The link vibration is then estimated based on the transfer model and electromagnetic torque. Link vibration signal is considered as an enhancement of the torque signal. Finally, the link vibration signature analysis is performed instead of MCSA. The experimental results show that the method is effective in enhancing the features of individual mechanical faults and improving the fault diagnosis performance.

Exploring cooperative hunting dynamics and PRCC analysis: insights from a spatio-temporal mathematical model

The proposed mathematical model explores the intricate dynamics of a predator-prey system involving prey infection and cooperative hunting of predators. The model incorporates habitat complexity, emphasizing its influence on ecological interactions. The well-posedness of the system has rigorously been examined in a temporal setting and also conducted stability analysis. The bifurcation analysis reveals the existence of several local bifurcations on the system, namely transcritical bifurcation, saddle-node bifurcation, and Hopf bifurcation. Furthermore, these investigations delineate the two-dimensional bifurcations including Bogdanov–Takens and cusp bifurcations for different parametric combinations. With suitable choices of parameter values, the proposed model exhibits diverse dynamic phenomena, including bistable and tri-stable behavior. Latin hypercube sampling is utilized to conduct uncertainty analysis on input parameters, aiming to observe their effects on population dynamics. Subsequently, Kendall’s tau and Spearman’s rank correlation coefficients are also computed to investigate the impact of these uncertainties on the population. In the later part, a spatio-temporal system is proposed with two-dimensional diffusion terms to obtain the conditions for Turing instability. Numerical simulations have been conducted to observe the emergence of spatial patterns and the impact of predator cooperation in these patterns. The study provides valuable insights into the dynamics of complex ecological systems, emphasizing the interplay of spatial and temporal factors in shaping population dynamics and predator-prey interactions.

Ecological and evolutionary dynamics of CRISPR-Cas systems in Clostridium botulinum: Insights from genome mining and comparative analysis

Understanding the prevalence and distribution of CRISPR-Cas systems across different strains can illuminate the ecological and evolutionary dynamics of Clostridium botulinum populations. In this study, we conducted genome mining to characterize the CRISPR-Cas systems of C. botulinum strains. Our analysis involved retrieving complete genome sequences of these strains and assessing the diversity, prevalence, and evolution of their CRISPR-Cas systems. Subsequently, we performed an analysis of homology in spacer sequences from identified CRISPR arrays to investigate and characterize the range of targeted phages and plasmids. Additionally, we investigated the evolutionary trajectory of C. botulinum strains under selective pressures from foreign invasive DNA. Our findings revealed that 306 strains possessed complete CRISPR-Cas structures, comprising 58% of the studied C. botulinum strains. Secondary structure prediction of consensus repeats indicated that subtype II-C, with longer stems compared to subtypes ID and IB, tended to form more stable RNA secondary structures. Moreover, protospacer motif analysis demonstrated that strains with subtype IB CRISPR-Cas systems exhibited 5′-CGG-3′, 5′-CC-3′, and 5′-CAT-3′ motifs in the 3′ flanking regions of protospacers. The diversity observed in CRISPR-Cas systems indicated their classification into subtypes IB, ID, II-C, III-B, and III-D. Furthermore, our results showed that systems with subtype ID and III-D frequently harbored similar spacer patterns. Moreover, analysis of spacer sequences homology with phage and prophage genomes highlighted the specific activities exhibited by subtype IB and III-B against phages and plasmids, providing valuable insights into the functional specialization within these systems.

Tracking and managing the water-food-environment-ecosystem (WFEE) nexus in groundwater irrigation districts using system dynamics modelling

Groundwater irrigation districts, which play a crucial role in the Earth's critical zone, are confronted with numerous challenges, including water scarcity, pollution, and ecological degradation. These issues come from multiple systems and are linked to a groundwater-dominated water-food-environment-ecosystem nexus problem related to agricultural activities (WFEE). There is a pressing need for the scientific characterization and evaluation of the WFEE nexus in groundwater irrigation districts to assure high-quality, sustainable development. Furthermore, it is critical to provide practical and efficient regulations at the farmer level to uphold the health of this nexus. This paper presents a mapping network that focuses on groundwater irrigation districts. The network aims to convert the restriction indicators utilized to maintain the health of the WFEE nexus (at the irrigation district scale) into the targets employed to manage farmers' living and agricultural activities (at the farmer scale). Additionally, a system dynamics model is created to track and manage the interacting relationships between the WFEE nexus and farmers' living and agricultural activities. This proposed model employs a structured parameter system comprising targets, state parameters, regulatory parameters, and evaluation parameters. This system can get insight into the status of the WFEE nexus at the farmer level using state parameters, induce tailored management and regulation measures using regulatory parameters, assess the effectiveness of various measures using the evaluation parameters, and finally provide decision support to enhance the health of the WFEE nexus. The findings from the research conducted in the Yong'an groundwater irrigation district demonstrated that the model accurately described the relationship between the WFEE nexus and farmers' activities in groundwater irrigation districts. Furthermore, the model responded strongly to a variety of improvement strategies, including adjustments in planting area, optimization of planting pattern, improvement of irrigation method, and implementation of agronomic measures. As a result, it provided farmers with decision support for applying agricultural management methods and addressing the WFEE nexus problem in groundwater irrigation areas.

ADP-Based Fault-Tolerant Control for Multiagent Systems With Semi-Markovian Jump Parameters.

This article analyzes and validates an approach of integration of adaptive dynamic programming (ADP) and adaptive fault-tolerant control (FTC) technique to address the consensus control problem for semi-Markovian jump multiagent systems having actuator bias faults. A semi-Markovian process, a more versatile stochastic process, is employed to characterize the parameter variations that arise from the intricacies of the environment. The reliance on accurate knowledge of system dynamics is overcome through the utilization of an actor-critic neural network structure within the ADP algorithm. A data-driven FTC scheme is introduced, which enables online adjustment and automatic compensation of actuator bias faults. It has been demonstrated that the signals generated by the controlled system exhibit uniform boundedness. Additionally, the followers' states can achieve and maintain consensus with that of the leader. Ultimately, the simulation results are given to demonstrate the efficacy of the designed theoretical findings.

Connecting Soft and Hard: An Integrating Role of Systems Dynamics in Tsunami Modeling and Simulation

Connecting Soft and Hard: An Integrating Role of Systems Dynamics in Tsunami Modeling and Simulation

Ultrafast Dynamics of Bloch Surface Wave Polaritons in Large-Area 2D Semiconductor Monolayers at Room Temperature.

The dynamics of strongly coupled polariton systems integrated with 2D transition metal dichalcogenides (TMDs) is key to enabling efficient coherent processes and achieving high-performance TMD-based polaritonic devices, such as ultralow-threshold polariton lasers and ultrafast optical switches. However, there has been a lack of a comprehensive understanding of the excited state dynamics in TMD-based polariton systems. In this work, ultrafast pump-probe optical spectroscopy is used to investigate the room temperature dynamics of the polariton systems consisting of TMD monolayer excitons strongly coupled with Bloch surface waves (BSWs) supported by all-dielectric photonic structures. The transient response is found for both above-exciton energy pumping and polariton-resonant pumping. The excited state population and ultrafast coherent coupling of the exciton reservoir and lower polariton (LP) branch are observed for resonant pumping. Moreover, it is found that the transient response of the LP first decays on a short-time scale of 0.15-0.25ps compared to the calculated intrinsic lifetime of 0.11-0.20ps, and is followed by a longer decay (>100ps) due to the dynamical evolution of the exciton reservoir. The results provide a fundamental understanding of the dynamics of TMD-based polariton systems while showing the potential for achieving efficient coherent optical processes for device applications.

A compensation method for PMSM sensorless control with parameter identification considering SMO observation error

AbstractSensorless control of permanent magnet synchronous motor (PMSM) can increase the reliability of electric actuators of more electrical aircraft. Numerical online parameter estimation method will enhance the performance for sensorless control methods based on sliding mode observer (SMO). However, numerical online parameter identification methods typically assume zero rotor position estimation error to ensure full rank of the identification equation set. This assumption actually leads to errors in parameter identification, resulting in steady‐state errors in rotor position estimation. This paper focuses on a compensation method for PMSM online parameter identification that takes into account rotor position estimation error. This method is used for sensorless control based on SMO, using model reference adaptive systems for online parameter identification, and no additional parameter adjustment required. Validation is conducted on a PMSM experimental platform with maximum load of 15kW. The experimental results of 1000 r/min steady state operation proved the effectiveness of the method, and the dynamic experiments with 5 and 15kW loads proved that the method has no significant adverse effect on the system dynamics.