System Dynamics Research Articles

Response analysis of asymmetric monostable energy harvester with an uncertain parameter

The nonlinear piezoelectric vibration energy harvesting system offers a solution to the power supply challenge for low-power sensors. However, In practical engineering, structural parameter uncertainties arise from manufacturing errors, environmental temperature fluctuations, and changes in material properties. Besides, due to inherent flaws in the structure and materials, asymmetry may occur in the potential well, which leads to the complexity of the dynamic behavior exhibited in energy harvesting system. In this paper, in order to investigate the dynamics of the asymmetric monostable piezoelectric energy harvesting system under an uncertain parameter, the orthogonal polynomial approximation method is applied to transform the stochastic system into an equivalent deterministic system. Then, the responses of the equivalent deterministic system are used to reveal the stochastic behavior of the uncertainty system. The results indicate that, when the uncertainty intensity of the cubic nonlinear coefficient is 0, an increase in the asymmetry level of the potential well leads to an increase in the output voltage. Increasing the other parameters, the output voltage is reduced. In addition, as the uncertainty intensity increases, the parameter intervals of chaotic response become wider and the energy harvesting efficiency decreases. Moreover, as the potential well asymmetry increases, the sensitivity of energy harvesting system to uncertain parameter increases.

The role of ice-sheet dynamics in the Miocene-Pliocene depositional systems of the Ross Sea, Antarctica

The dynamics of the Antarctic ice sheet (AIS) have profound implications for the evolution of the Antarctic continental margin, global ocean currents, and climate changes. Marine sediments from the Antarctic continental margins recorded the history of the advance and retreat of the AIS. In this study, we present an integrated analysis of the sedimentary characteristics of the Early Miocene to Late Miocene of the Ross Sea by using 2D seismic reflection data and cores from International Ocean Discovery Program (IODP) Expedition 374 Sites U1521, U1522, and U1524. The characteristics of the seismic facies and sediments show that the expansion and grounding of the ice sheets across the continental shelf significantly influenced the depositional processes, leading to increased glacial erosion, the formation of prograding wedges, mass transport deposits (MTDs), and mixed (turbidite-contourite) depositional systems since the Early Miocene. The seaward migration of the continental shelf edge and the steepening of the continental slope were mainly influenced by the glaciation of extreme expansion of the AIS. Marked increases in the prograding wedge and MTD are associated with extensive sediment reworking and deposition at the grounding zones and along the continental slope as a result of ice sheet expansion. The development of the mixed (turbidite-contourite) depositional systems was the result of extensive sediment reworking and deposition by gravity flows and bottom currents on the continental slope and the rise. This research provides new insights into the complexity of the ice sheet and the sensibility of marginal sediments in responding to the past climate changes in Antarctica.

New sustainable strategy for rehabilitating phosphate mining sites using phosphate industry by-products and sludge integrating Argan, Carob and Olive trees

In semi-arid context, the development of anthroposol from phosphate industry by-products and sewage sludge could be a new approach for sustainable phosphate mining soils. The objective of this 2 years field study carried out at Benguerir phosphate mine, was to evaluate nutrients and heavy metals dynamics in the soil-plant system of three species planted on anthroposol consisting of a mixture of 65% phosphogypsum (PG), 30% phosphate sludge (PS), and 5% sewage sludge (SS). The experimental layout was a randomized complete block design with six replicates and three species: argan, olive, and carob. No fertilizer was applied to the different plots. Heights and diameters of the different species were measured. Species were pruned, and leaves and stems were separated. The nutrients (N, P, K, Ca, and Mg) and heavy metals (Cd, Cu, Cr, Pb, Ni and Zn) contents in both soil and plant part were determined. The results of the Pearson correlation showed significant correlations between height and diameter of the different species. The strongest correlation was observed for the argan tree. Furthermore, nutrient contents in the rhizosphere of species were significantly reduced, excepted Ca. Also, nutrient contents in leaves were significantly higher than those in the stems. In addition, the concentration of heavy metals in argan, olive and carob leaves, were below international standards. In semi-arid contexts, argan tree could be the best candidate for revegetating mining sites and this anthroposol (65% PG – 30% PS – 5% SS) could be a new approach to rehabilitate mining site on large scale.

Bifurcation analysis, quasi-periodic and chaotic behavior of generalized Pochhammer-Chree equation

We take into account the bifurcation analysis of the generalized Pochhammer-Chree (PC) equation that describes the dynamics of several systems in science and engineering. The considered model is changed into a planar dynamical system by applying the Galilean transformation. The phase portraits are plotted by considering suitable values of the bifurcation parameters. The considered model is solved using the RK method to compute the supernonlinear and nonlinear wave solutions. All phase portraits and wave solutions are depicted in the phase plane by simply fixing the relevant parameters values. The equilibrium points are obtained, and the same are classified. Moreover, sensitive analysis for different initial value problems is applied to analyze the quasiperiodic, chaotic behavior and time series after introducing an extrinsic periodic perturbation term. In addition, the Lyapunov characteristic exponents, Poincare section and bifurcation diagrams are also discussed to examine the chaotic pattern of the model. Numerical simulation results show that changing the frequencies and amplitude values impacts the dynamical features of the considered model.

Fractional view analysis of coupled Whitham- Broer-Kaup and Jaulent-Miodek equations

In this study, I systematically investigate the fractional Whitham-Broer-Kaup (WBK) system and the fractional Coupled Jaulent-Miodek (CJM) equation under the Caputo fractional calculus. The nonlinear fractional differential equation systems are investigated via the Aboodh transform iteration method and the Aboodh residual power series method, thus offering a thorough analytical investigation. The dynamics of the fractional WBK system are accomplished using the Aboodh transform iteration method, and the Aboodh residual power series method is employed to study the behavior of the fractional CJM equation. Using established solutions, we completely analyze their dynamics employing both symbolic computations and numerical simulations. Consequently, novel solutions are identified, and the behavior of these fractional systems in the Caputo operator sense are clarified. The results obtained show good agreement of convergence of the numerical and analytical solutions, highlighting the effectiveness of the schemes adopted for unraveling the complex dynamics of fractional nonlinear systems.

Correlation between structure and dynamics of liquid GeO2 under compression

Correlation between structure and dynamics of GeO2 system under compression is investigated by molecular dynamics and Monte-Carlo methods. Results show that structural phase transition occurs at the range of oxygen packing factor from 0.55 to 0.60. Self-diffusion coefficient of Ge and O exhibits anomalous and depends on percentage of GeOx polyhedrons (x = 4,5,6) and packing factor/ free volume of model. The self-diffusion coefficient can be determined via percentage of GeOx units and free volume fraction. The data mining technique is applied to clarify the polyamorphism, structure and dynamics heterogeneities. The cause of anomalous diffusion has been elucidated.

Ultrafast state-selective tunneling in two-dimensional semiconductors with a phase- and amplitude-controlled THz-scanning tunneling microscope

THz-pulse driven scanning tunneling microscopy (THz-STM) enables access to the ultrafast quantum dynamics of low-dimensional material systems at simultaneous ultrafast temporal and atomic spatial resolution. State-selective tunneling requires precise amplitude and phase control of the THz pulses combined with quantitative near-field waveform characterization. Here, we employ our state-of-the-art THz-STM with multi-MHz repetition rates, efficient THz generation, and precisely tunable THz waveforms to investigate a single sulfur vacancy in monolayer MoS2. We demonstrate that 2D transition metal dichalcogenides (TMDs) are an ideal platform for near-field waveform sampling by THz cross-correlation. Furthermore, we determine the THz voltage via QEV scans, which measure the THz rectified charge Q as a function of THz field amplitude E and dc bias Vdc. Mapping the complex energy landscape of localized states with a resolution down to 0.01 electrons per pulse facilitates state-selective tunneling to the HOMO and LUMO orbitals of a charged sulfur vacancy.

Modeling and Simulation of Unmanned Swarm System Based on Dynamic Structure DEVS

As a complex system with collaborative cooperation and capability emergence, the unmanned swarm system plays an important role in military, agriculture, aerospace and other fields. With the increasing complexity of unmanned swarm systems, traditional modeling methods cannot effectively describe the dynamics of swarm systems. In order to effectively design, use and evaluate unmanned swarm systems, this article conducts modeling and simulation of unmanned swarm systems based on DSDEVS(Dynamic Structure Discrete Event System Specification). Describe the unmanned swarm system from both behavioral and structural aspects. Based on component modeling, the microscopic behaviors of the unmanned platforms that constitute the unmanned swarm are described, and coupling relationships are established to describe the collaborative structure between unmanned platforms. According to the state transfer and event interaction characteristics of the unmanned swarm system, a synchronization mechanism is added to support changes in the swarm structure. This enables the unmanned swarm system to make adaptive structural adjustments according to environmental changes and its own goals during simulation operation, so as to achieve a state of enhanced capabilities and structural stability to complete the task. Finally, the effectiveness and feasibility of this method were verified through a simulation experiment of joint reconnaissance by a UAV swarm.

Simulation of CuO-water nanofluid flow for cooling of solar photovoltaic module

The importance of studying photovoltaic thermal (PVT) systems is underscored by their potential to harness both solar thermal and photovoltaic energy simultaneously, making them a promising avenue for sustainable power generation. The integration of a PVT system allows for enhanced energy conversion and utilization of available resources. In the context of the broader field of renewable energy, understanding and optimizing PVT systems contribute to the development of efficient and environmentally friendly power generation solutions. The introduction of CuO nanoparticles proves beneficial, contributing to an overall improvement in system performance. Throughout this exploration, the aim is to provide insights into the intricate dynamics of PVT systems under varying conditions, emphasizing the impact of key parameters on system efficiency and performance. Examining PVT systems, this study focuses on a rectangular duct equipped with a turbulator featuring rectangular cuts. The simulation considers the flow of CuO-H2O within the channel and accounts for pure conduction within the layers, employing the finite volume method with a validation test for accuracy. The mesh size has been optimized for computational efficiency. In this context, the study investigates variations in cell temperature (T PV) and efficiency components (electrical (η PV), thermal (η th), overall (η PVT)) concerning key variables: wind speed (V w (0.4, 1, 1.4 m/s)), incident irradiation (G (730, 830, 930 W/m2)), inlet velocity (0.08, 0.1, 0.12 m/s), volume fraction of CuO (ϕ = 0, 0.018). Introducing the turbulator improves T PV uniformity by about 20.43%. With increased incident irradiation in the presence of the turbulator, η PV, η th, and η PVT values enhance by approximately 1.02%, 8.18%, and 4.99%, respectively. Specifically, at G = 930 W/m2, the turbulator installation leads to a 4.35% increase in η PVT. However, certain variables demonstrate contrasting effects. Increased wind speed results in a 3.63% decrease in η PVT for tubes equipped with a turbulator. Conversely, intensifying the inlet velocity leads to an augmentation of η PVT by around 3.19%, coupled with a notable 16.34% improvement in the uniformity of T PV.

Implementation of a Fully Automatic Four-way Traffic Light Controller Using Verilog

The traffic control system is one of the challenging problems in metropolitan and developed cities. This is due to the large number of vehicles and the high dynamics of the traffic system. Impoverished traffic systems are the big reason for accidents and time losses. In this project, the Fully Automatic Four-way Traffic light controller is implemented by using Verilog and we have overcome some drawbacks i.e., we included the area detection parameter that improves the detection of vehicles compared to the design part in the base paper.

Epitaxial oxide ionotronics: Interfaces and oxygen vacancies

Epitaxial oxide ionotronics: Interfaces and oxygen vacancies

58. The Neural Systems and Real-World Mood Dynamics Underlying Dispositional Risk for Internalizing Illness

58. The Neural Systems and Real-World Mood Dynamics Underlying Dispositional Risk for Internalizing Illness

Modelling dynamics between free-living amoebae and bacteria.

Free-living amoebae (FLA) serve as hosts for a variety of endosymbionts, which are microorganisms that reside and multiply within the FLA. Some of these endosymbionts pose a pathogenic threat to humans, animals, or both. The symbiotic relationship with FLA not only offers these microorganisms protection but also enhances their survival outside their hosts and assists in their dispersal across diverse habitats, thereby escalating disease transmission. This review is intended to offer an exhaustive overview of the existing mathematical models that have been applied to understand the dynamics of FLA, especially concerning their interactions with bacteria. An extensive literature review was conducted across Google Scholar, PubMed, and Scopus databases to identify mathematical models that describe the dynamics of interactions between FLA and bacteria, as published in peer-reviewed scientific journals. The literature search revealed several FLA-bacteria model systems, including Pseudomonas aeruginosa, Pasteurella multocida, and Legionella spp. Although the published mathematical models account for significant system dynamics such as predator-prey relationships and non-linear growth rates, they generally overlook spatial and temporal heterogeneity in environmental conditions, such as temperature, and population diversity. Future mathematical models will need to incorporate these factors to enhance our understanding of FLA-bacteria dynamics and to provide valuable insights for future risk assessment and disease control measures.

Exploring scale-free networks: Survey on autonomous system dynamics and connectivity analysis

The global Internet is continuously developing; however, it is becoming more complex with time owing to the introduction of new nodes and links among autonomous systems (ASes). The network links among ASes appear and disappear, especially when the shortest path is required or a low-cost upstream Internet service provider (ISP) is a prerequisite. Understanding the Internet dynamics is critical for improving Internet characteristic analysis. In this work, we reviewed the existing studies from the last two decades on AS network topology as well as relations and routing among ASes. Similarly, we measured the link value differences within Russia and Central Asian ASes using the Barabasi–Albert (BA) model. Our analysis results show that in the last two years, the number of newly added links among 5377 ASes is 65,782. Further, the results show that the ASes with a high network degree in terms of high connectivity or preferential attachment approach are those used by the largest telecom companies in Russia and Central Asian regions. This survey paper aimed to determine whether the Internet AS graphs in these regions adhere to scale-free network properties, and we further examined the growth patterns of node connectivity within these regions.

Modified Tilt-integral Active Disturbance Rejection Controller with Inertia Emulated Direct Current Link for Frequency Control of Marine Microgrid

The increasing integration of intermittent renewable sources (RSs) poses a dynamic frequency stability challenge for modern marine vessel microgrids. To address this issue, this paper proposes a novel control approach, specifically targeting frequency and tie-line power stabilization in a diverse source marine microgrid (MμG) with two intertied areas featuring renewable (wind-wave) sources. The suggested approach introduces a modified tilt-integral active disturbance rejection (TI-ADRC) controller designed to ensure effective damping of power frequency oscillations. As the control scheme depends on the optimal setting of the proposed controller, a recently developed marine predator technique (MPT) has been adopted. The performance of the proposed controller is compared with other recent controllers viz. PID, tilt-integral derivative (TID), two-degree-of-freedom (2DOF)-PID, fuzzy-PI, and ADRC to validate its superiority. To further enhance the system dynamics, a precise modeling of inertia emulated direct current (IEPDC) tie link is incorporated in microgrid system. The impact assessments, considering time delays with pre/post IEPDC link, demonstrate a substantial 57.79% and 81.53% reduction in peak frequency overshoot compared to DC link (conventional model) and AC link, respectively. The analysis of the eigen plot confirms the stability of the control system. Sensitivity assessments of the controller against ±30% parametric variations and load fluctuations are conducted, affirming its robustness. Finally, the result from OPAL-RT confirm the practicality of the proposed method. It is asserted that the suggested controller is reliable and functions well in n the presence of diverse disruptions and parametric variations.

Distillation of quantum non-Markovianity

Non-Markovianty of open quantum systems dynamics is a physically relevant property which is usually associated with the backflow of (quantum) information. Using this paradigmatic marker, we develop an operational framework to investigate how non-Markovianity for qubit dynamics can be distilled when many copies of the channels are used, possibly allowing for a stronger effect on the backflow of information.

A simplified system dynamics model to investigate the effects of urban transportation management policies on reducing CO2 and greenhouse gas emissions

Kuwait suffers from severe air pollution levels making it on the top ten list worldwide pollution wise based on the records of Air Quality Index (AQI). The transport and energy sectors represent the major players in contributing to the current unprecedent pollution situation Kuwait is suffering from. The unique harsh arid weather associated with high levels of humidity, high temperatures and frequent sandstorms in the region intensifies the extent of the pollution crisis. There is almost no single study in the literature that focused on testing different scenarios on transport and energy sectors effects into the reduction of prevailing pollution levels in this region of the world. This work comes to fill this gap in the literature. A simplified system dynamics model (covering the years from 2004 to 2040) was developed for Kuwait to simulate the effects of different urban transportation management policies on reducing CO2 and greenhouse gas emissions levels. Two policies were tested: a gasoline tax with low, medium, and high rates, as well as a free bus service. Combined policies resulting from merging the gasoline tax at different levels with the free bus service were also tested, which outperformed the two separate plans being implemented alone. The best combined strategy achieved was to encourage citizens to use public transportation by utilizing the free bus service rather than using private vehicles in addition to impose a high fuel tax. This action was anticipated to reduce CO2 emissions by 14 million metric tons and the number of private vehicles by 3 million vehicles by the end of 2040. Such approach proved to be helpful in reducing the pollution levels and in turn decrease the severity of global warming phenomenon in the Arabian desertic peninsula.

Simulating the corrective actions affecting system availability: a system dynamics approach

Purpose This paper aims to simulate vital corrective actions (CAs) affecting system availability through a system dynamics approach based on the results obtained by analyzing the causal relationships among failure modes and effects analysis elements. Design/methodology/approach A stock and flow diagram has been developed to simulate system behaviors during a timeframe. Some improvement scenarios regarding the most necessary CAs according to their strategic priority and the possibility of eliminating root causes of critical failure modes in a roller-transmission system have been simulated and analyzed to choose the most effective one(s) for the system availability. The proposed approach has been examined in a steel-manufacturing company. Findings Results indicated the most effective CAs to remove or diminish critical failure causes that led to the less reliability of the system. It illustrated the impacts of the selected CAs on eliminating or decreasing root causes of the critical failure modes, lessening the system’s failure rate and increasing the system availability more effectively. Research limitations/implications Results allow managers and decision-makers to consider different maintenance scenarios without wasting time and more cost, choosing the most appropriate option according to system conditions. Originality/value This study innovation would be the dynamic analysis of interactions among failure modes, effects and causes over time to predict the system behavior and improve availability by choosing the most effective CAs through improvement scenario simulation via VENSIM software.

An Evolutionary Game-Theoretic Approach to Analysis the Green Innovation Chain Dynamics under Government Policies

Continuous improvement of the green innovation chain is essential for promoting sustainable entrepreneurship and addressing environmental issues. In this paper, we developed a tripartite evolutionary game model involving tech firms, startups, and accelerators. Our goal is to examine the impact of both static and dynamic government interventions on the evolution of the green innovation chain. After determining the evolutionary stable strategies, we examine government interventions through a system dynamics simulation using three different scenarios: (1) Government support downstream of the innovation chain, (2) government support upstream of the innovation chain, and (3) government support throughout the chain. In the first scenario, it is observed that although it promotes green technological innovation (GTI), the necessary support for startups and accelerators to scale up green innovations is lacking. Consequently, the overall level of GTI is limited. Conversely, in the second scenario, there is a lack of incentives for tech firms to invest in GTI, resulting in a stagnation in the innovation chain. Nevertheless, with government support extended throughout the chain, a synergistic effect emerges between all players, leading to a higher level of collaboration and resulting in a more efficient and effective green innovation chain.

Temporal Fusion Transformers for streamflow Prediction: Value of combining attention with recurrence

Over the past few decades, the hydrology community has witnessed notable advancements in streamflow prediction, particularly with the introduction of cutting-edge machine-learning algorithms. Recurrent neural networks, especially Long Short-Term Memory (LSTM) networks, have become popular due to their capacity to create precise forecasts and realistically mimic the system dynamics. Attention-based models, such as Transformers, can learn from the entire data sequence concurrently, a feature that LSTM does not have. This work tests the hypothesis that combining recurrence with attention can improve streamflow prediction. We set up the Temporal Fusion Transformer (TFT) architecture, a model that combines both of these aspects and has never been applied in hydrology before. We compare the performance of LSTM, Transformers, and TFT over 2,610 globally distributed catchments from the recently available Caravan dataset. Our results demonstrate that TFT indeed exceeds the performance benchmark set by the LSTM and Transformers for streamflow prediction, when models are trained individually for each basin. Additionally, being an explainable AI method, TFT helps in gaining insights into the streamflow generation processes.