Changes In Dynamic Behavior Research Articles

Simultaneous tuning of multiple PID controllers for multivariable systems using deep reinforcement learning

Traditionally, tuning of PID controllers is based on linear approximation of the dynamics between the manipulated input and the controlled output. The tuning is performed one loop at a time and interaction effects between the multiple single-input-single-output (SISO) feedback control loops is ignored. It is also well-known that if the plant operates over a wide operating range, the dynamic behaviour changes thereby rendering the performance of an initially tuned PID controller unacceptable. The design of PID controllers, in general, is based on linear models that are obtained by linearizing a nonlinear system around a steady state operating point. For example, in peak seeking control, the sign of the process gain changes around the peak value, thereby invalidating the linear model obtained at the other side of the peak. Similarly, at other operating points, the multivariable plant may exhibit new dynamic features such as inverse response. This work proposes to use deep reinforcement learning (DRL) strategies to simultaneously tune multiple SISO PID controllers using a single DRL agent while enforcing interval constraints on the tuning parameter values. This ensures that interaction effects between the loops are directly factored in the tuning. Interval constraints also ensure safety of the plant during training by ensuring that the tuning parameter values are bounded in a stable region. Moreover, a trained agent when deployed, provides operating condition based PID parameters on the fly ensuring nonlinear compensation in the PID design. The methodology is demonstrated on a quadruple tank benchmark system via simulations by simultaneously tuning two PI level controllers. The same methodology is then adopted to tune PI controllers for the operating condition under which the plant exhibits a right half plane multivariable direction zero. Comparisons with PI controllers tuned with standard methods suggest that the proposed method is a viable approach, particularly when simulators are available for the plant dynamics.

Characterization of wave propagation in complex composite structures (CCS) using a robust inverse analysis method

This paper presents the application of wave propagation characterization for complex composite structures through the Algebraic K-space Identification technique in the Cartesian coordinate system (AKSI-C). The proposed method is a novel development since the developed methodology uses adequate partial differential algebraic operations to provide a robust and low-cost framework for identifying wave propagation parameters of the structures with multidimensional signals for the first time. Additionally, the proposed method has been experimentally applied to identify the complex wave propagation phenomenon of different complex composite structures: (i) honeycomb sandwich composite structure: variability of orthotropic behavior and damping properties with frequency and direction is identified by wavenumber space, 3D dispersion curves, and damping loss factor surface. Then, the contribution of individual layer properties on the changes in dynamic behavior is studied by estimating transition frequency; (ii) locally resonant meta-structure: the effect of the local resonator-induced band gap on the wave attenuation is investigated; (iii) periodic rib-stiffened composite plates: the inner resonance phenomena and their remarkable elastic wave manipulation ability are explored by designing 3D-printed resonators and identifying the mixed-resonance-induced band gap. The proposed method has been compared with other inverse methods to assess its reliability under complex conditions.

Delving into Earth Dam Dynamics: Exploring the Impact of Inner Impervious Core and Toe Drain Arrangement on Seepage and Factor of Safety during Rapid Drawdown Scenarios

The study examined the intricate relationships between embankment slope configurations, toe drain designs, and drawdown scenarios. It utilized a unique combination of numerical, physical, and mathematical models. The investigation involved 16 numerical models and 8 physical models with distinct characteristics. The research explored the correlations of key parameters: matric suction, horizontal water conductivity, time, and factor of safety. The factor of safety values varied from 0.62 to 1.03 as a result of the different investigated combinations. For instance, a 1:2 embankment slope without a toe drain under instantaneous drawdown led to the factor of safety values ranging from 1.22 to 1.57. Additionally, incorporating elements like a 30 m toe drain and a 1 m per day drawdown rate influenced these values, with extremes recorded from 1.337 to 2.21, shedding light on embankment stability under diverse conditions and configurations. When subjected to a 1 m per day drawdown, water flow rates decreased significantly at the upstream face and increased downstream, accompanied by an increase in water mass flux at the upstream face and a decrease at the downstream toe, suggesting dynamic changes in water behavior in response to drawdown. Moreover, the findings unveiled significant correlations between matric suction and time (correlation coefficient of 0.950) and factor of safety and water conductivity (correlation coefficient of 0.750). Conversely, a distinct negative correlation emerged between matric suction and factor of safety (correlation coefficient of −0.864). The study’s distinctive insights contribute to our understanding of seepage behavior and dam stability across varied scenarios, offering valuable input for resilient dam construction approaches that will ensure the longevity and effectiveness of these essential structures.

Agent-based model for assessment of multiple circular economy strategies: Quantifying product-service diffusion, circularity, and sustainability

Despite the increasing need for tools to support a circular economy, methods for assessing circularity and environmental consequences in a way that considers dynamic changes in heterogeneous consumer behavior are lacking. Here we propose an agent-based model for assessing seven explicitly-defined product-level circular economy strategies. The model endogenizes bounded rational consumer behavior and interactions related to product acquisition, obsolescence, repair, hibernation, and discharge. Simulation experiments with numerical examples were used to quantify the diffusion of product service systems (e.g., leasing of refurbished products and sharing/rental services), product circularity, and lifecycle greenhouse gas emissions over 30 years. As a result, synergies arising from promotion measures (e.g., pricing, advertisements, and service levels), bottlenecks (e.g., lack of collected products), and rebound effects (e.g., due to new production and transport) were identified. By employing “what-if” analyses, this model provides a means to identify effective interventions in the transition to a net-zero circular economy.

Menggapai Keunggulan Promosi di Era Digital: Kolaborasi Canva untuk Peningkatan Ekonomi Lokal

This research analyzes the potential for collaboration with graphic design platform Canva to generate promotional advantages for local businesses in the digital era and their impact on local economic growth. Amidst dynamic changes in consumer behavior and marketing trends, promotion is the key to local business success. Canva offers a solution for creating visually appealing content with minimal design skills, making it relevant for users of all backgrounds. This research deepens the understanding of the effectiveness of promotional campaigns, increased brand visibility, and higher audience engagement through the use of Canva. However, this research also considers the limitations in using this platform, including the risk of uniform content that is less unique. The practical implications of this research are to guide local businesses in designing more effective promotions through the Canva platform, increasing interaction with consumers, and contributing to local economic growth. With a focus on the Canva collaboration, this research provides insight into how this graphic design platform can become a strategic tool in achieving business promotion and development goals in the digital age.

Express packaging waste recycling: Stakeholders’ dynamic behavioral changes based on a computational evolutionary game theoretic approach

Identifying stakeholder behaviors is crucial in managing municipal express packaging waste. Prior studies have neglected the impacts of the advertising effect and environmental preference and thus fail to detect stakeholders’ behavioral changes under different policies. To address this limitation, we build a computational evolutionary game model that integrates the advertising effect, environmental preference benefits, and economic and information policies. A numerical simulation is then conducted via a differential equation solver embedded in MATLAB software to identify the behavioral changes of the government, express delivery enterprises, and consumers. The results indicate that subsidies induce enterprises and consumers to reach their stability strategy more quickly, with maximum behavioral change rates of 0.82% and 0.64%, respectively. The marginal impacts of information policy and environmental preference benefits are greatest for consumers, whose behavioral change rates can reach 1.33% and 1.52%, respectively. For enterprises, a 1.71% behavioral change rate can be achieved by increasing the government’s effort level. An increase in enterprises’ effort level causes both enterprises and consumers to reach a stability strategy more quickly and achieves behavioral change rates of 4.21% and 1.51%, respectively. Our model can be used to predict stakeholders’ behavioral changes in the waste disposal industry, and the findings of this study provide novel ideas for waste management practitioners to use in encouraging recycling behaviors.

Long-run analysis of a perturbed HIV/AIDS model with antiretroviral therapy and heavy-tailed increments performed by tempered stable Lévy jumps

The novelty of this article lies in providing a new framework for modeling the dynamics of HIV/AIDS infection under antiretroviral therapy (ART) which aims to reduce a person's viral load to an undetectable level. Since HIV/AIDS transmission can exhibit very tailed behavior (unpredictable jumps) due to the fact that the risk of spreading can vary greatly depending on the behavior and characteristics of individuals, we probe the effect of α-stable jumps on its asymptotic dynamics. Our proposed model is a compartmental step-wise formulation that takes the form of a system of Itô-Lévy differential equations with α-stable process. First, we check its well-posedness and we give the necessary assumptions needed for the analysis. Then, and based on a new approach, we prove two main asymptotic scenarios: extinction and stationary persistence of HIV/AIDS infection. The theoretical outcomes show that the kinetic behavior of our HIV/AIDS system is principally induced by certain underlying parameters, which are accurately correlated to the Lévy noise amplitudes. Finally, we reinforce our study with two numerical experiments to test the impact of the innovative mathematical techniques adopted to obtain the main results. Moreover, we numerically highlight the influence of α-stable jumps in epidemic state transition and dynamic behavior change.

Double‐sensor conductivity probe applied in a flotation system

AbstractThis study proposed a new approach for measuring bubble size distribution, bubble mean diameter, Sauter mean bubble diameter, and gas holdup using a double‐sensor conductivity probe in an air/water two‐phase system bubble column. The results for the two‐phase system were compared and calibrated using analyses from bubble images taken by a digital camera from the side of the column wall. Good agreement was observed between the two techniques. The same double‐sensor conductivity was used in an air/water/solids three‐phase system. The conductivity probe captured the change in bubble dynamic behaviour inside the pulp phase; however, the presence of the solids made it more challenging to measure. As a result, the VisioFroth commercial package, using images taken from the top of the froth layer, could be used in conjunction with the double‐sensor conductivity probe to show the dynamic evolution of mineralized bubbles from the pulp zone to the froth zone in a flotation process.

Evaluation of Electrocardiogram-Gated Computed Tomography Angiography to Quantify Changes in Geometry and Dynamic Behavior during the Cardiac Cycle of the Nellix Endovascular Sealing System.

The Nellix endovascular sealing system (EVAS) was a unique concept with regard to its sealing concept that failed, related to high migration rates. We investigated the changes in aortoiliac morphology during the cardiac cycle before and after EVAS using electrocardiography (ECG)-gated CT. Eight patients scheduled for EVAS were prospectively enrolled. ECG-gated CT scans were made pre- and postoperatively. Measurements were performed in the mid-systolic and mid-diastolic phases. Endpoints were changes in infrarenal aortoiliac morphology postoperatively compared to preoperatively and their changes in the cardiac cycle. Both pre- and postoperatively, there were no changes during the cardiac cycle. EVAS caused an increase in neck diameter and surface in both phases (p < 0.001). EVAS increased the luminal AAA volume (p < 0.001), with a decrease in thrombus volume (p < 0.001) in both phases and an increase in total volume (p < 0.001) in the systolic phase. During follow-up, one patient presented with >5 mm migration. There were no differences in the movements of this patient compared to the remaining patients. The cardiac cycle had a very limited effect on the aortoiliac dynamics before and after EVAS and, therefore, there is probably not a role for ECG-gated CT in enhanced surveillance programs. EVAS itself has a significant impact on anatomy, particularly the neck diameter, length, and volumes of the AAA.

Detecting and Estimation Change-point in Dynamic Systems using Segmentation Technique

There is no doubt that the sudden changes in dynamic behavior of the system greatly influences the choice of the appropriate model to represent this behavior, From here comes the importance of the discovery points that change in dynamic behavior of the system, Enabling the researcher of this behavior to segmentation it to groups or sectors in a manner cutting each line itself and this provides the Researcher the possibility of fitting appropriate model for each sector or department represents the best representation of the data. Discovery points of changing and estimation it is one of the critical issues, and in this research we use package of statistical and engineering criterion used in the discovery and estimation of the change points. The application by used simulation data.&#x0D;

Comparing structural dynamic properties of diseases causing mutations of KCNE3 with wild-type KCNE3 in a lipid bilayer membrane using molecular dynamics simulations.

KCNE3 is a potassium channel accessory transmembrane protein that regulates the function of various voltage-gated potassium channels such as KCNQ1 and KCNQ4. KCNE3 plays an important role in the recycling of potassium ion by binding with KCNQ1. KCNE3 can be found in the small intestine, colon, and in the human heart. Its malfunction has been proven to lead to disorders such as cardiac arrhythmia, long QT syndrome, tinnitus, cystic fibrosis, and Menière's disease. Despite of its biological significance, little is known about its structural and dynamic properties. Molecular dynamics (MD) simulation serves as a computational tool to study structural and dynamic properties of membrane proteins at an atomic level. Previously, we have studied structural and dynamic properties of wild-type KCNE3 in various lipid bilayer membranes. In this study, we have utilized all atom molecular dynamics simulation to investigate the structural dynamics of various disease causing mutations of KCNE3 in POPC/POPG lipid bilayers. The root mean square deviation (RMSD) of the different section of various diseases causing mutations of KCNE3 is compared to the wild-type KCNE3 to determine the changes in dynamic behavior. Our simulation results are consistent with electron paramagnetic resonance (EPR) experimental results.

Sustainable Combustion Technologies Need Acoustics Research

This paper outlines the challenges of developing hydrogen-fueled combustion systems, which are safe from combustion instabilities. Combustion instabilities can occur in any configuration where a continuously burning flame is housed in an acoustic resonator, such as gas turbine engines, boilers and furnaces. They manifest themselves by large-amplitude oscillations of one or more resonator modes and can cause major damage to the combustion system. Their underlying cause is the following feedback loop: the flow carrying the combustible mixture is perturbed → the flame becomes unsteady and its heat release fluctuates → the fluctuating heat release generates sound → the sound perturbs the flow of the mixture, and the feedback cycle is closed. Various strategies exist to prevent instabilities in conventional combustion systems, which burn hydrocarbon fuels. However, if hydrogen or a hydrogen-blend is used as fuel, the flame's dynamic behaviour changes, and as a consequence, combustion instabilities occur under new and unexpected conditions. In order to give some explicit physical insight, a generic combustion system will be presented and described by an analytical model. Predictions will be made about the impact of hydrogen fuel and other parameters.

Analyzing global features of magnetic resonance images in widespread neurodegenerative diseases: new hope to understand brain mechanism and robust neurodegenerative disease diagnosis.

Neurodegenerative diseases are caused by progressive degeneration of the central nervous system (CNS)'s neuronal structure. Well-known diseases in this category include Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS), which are also addressed in this study. The CNS appears to be a complex dynamic system, whose parameters change during the disease due to neuronal damage, resulting in various symptoms. Since the change in dynamic behavior is due to the neurons' death and change in neurons' connectivity, brain images of the affected areas appear to provide a good understanding of this change. This work attempts to focus on brain magnetic resonance images (MRI) and examine the effect of neuronal loss on the images. To this end, the complex features of these images, including 2D and Higuchi's fractal dimensions (HFD), correlation dimension (CD), largest Lyapunov exponent (LLE), and approximate entropy (ApEn) were calculated. Despite small differences in numerical values (0.01-0.35), these values differ significantly. This shows that the brain dynamic system behaves and functions differently in the disease state, which is clear in the behavior of global features. These three diseases have the same functional pattern, and this study seems to have captured the roots of these seemingly variant diseases.

Concept Drift Analysis and Malware Attack Detection System Using Secure Adaptive Windowing

Concept drift is a main security issue that has to be resolved since it presents a significant barrier to the deployment of machine learning (ML) models. Due to attackers’ (and/or benign equivalents’) dynamic behavior changes, testing data distribution frequently diverges from original training data over time, resulting in substantial model failures. Due to their dispersed and dynamic nature, distributed denial-of-service attacks pose a danger to cybersecurity, resulting in attacks with serious consequences for users and businesses. This paper proposes a novel design for concept drift analysis and detection of malware attacks like Distributed Denial of Service (DDOS) in the network. The goal of this architecture combination is to accurately represent data and create an effective cyber security prediction agent. The intrusion detection system and concept drift of the network has been analyzed using secure adaptive windowing with website data authentication protocol (SAW_WDA). The network has been analyzed by authentication protocol to avoid malware attacks. The data of network users will be collected and classified using multilayer perceptron gradient decision tree (MLPGDT) classifiers. Based on the classification output, the decision for the detection of attackers and authorized users will be identified. The experimental results show output based on intrusion detection and concept drift analysis systems in terms of throughput, end-end delay, network security, network concept drift, and results based on classification with regard to accuracy, memory, and precision and F-1 score.

Transition characteristics of the dynamic behavior of a vehicle wheel-rail vibro-impact system

&lt;abstract&gt; &lt;p&gt;A two-degree-of-freedom vehicle wheel-rail impact vibration system model is developed, and the equivalent impact stiffness and damping of the rail are fitted applying ABAQUS, taking into account the high and low irregularity generated by the welded joints of the rail. A wheel-rail periodic interface with fixed impact was selected as the Poincaré map, and the fourth-order Runge-Kutta numerical method with variable step size was used to solve the system response. The dynamic characteristics of the system are investigated using a combination of the Bifurcation diagram, Phase plane diagram, the Poincaré map, the Time-domain diagram and the Frequency-domain diagram. It is verified that the vehicle wheel-rail impact vibration system has Hopf bifurcation, Neimark-Sacker bifurcation, Period-doubling bifurcation and Boundary crisis, and there are rich and complex nonlinear dynamic behavior changes. The research on the bifurcation and chaos characteristics of vehicle wheel-rail impact vibration systems can provide a reference for improving the stability of vehicle operation in engineering practice as well as the prediction and control of chaos in vehicle vibration reduction design.&lt;/p&gt; &lt;/abstract&gt;

Pulse respiration quotient as a measure sensitive to changes in dynamic behavior of cardiorespiratory coupling such as body posture and breathing regime.

Objective: In this research we explored the (homeo)dynamic character of cardiorespiratory coupling (CRC) under the influence of different body posture and breathing regimes. Our tool for it was the pulse respiration quotient (PRQ), representing the number of heartbeat intervals per breathing cycle. We obtained non-integer PRQ values using our advanced Matlab® algorithm and applied it on the signals of 20 healthy subjects in four conditions: supine position with spontaneous breathing (Supin), standing with spontaneous breathing (Stand), supine position with slow (0.1Hz) breathing (Supin01) and standing with slow (0.1Hz) breathing (Stand01). Main results: Linear features of CRC (in PRQ signals) were dynamically very sensitive to posture and breathing rhythm perturbations. There are obvious increases in PRQ mean level and variability under the separated and joined influence of orthostasis and slow (0.1Hz) breathing. This increase was most pronounced in Stand01 as the state of joint influences. Importantly, PRQ dynamic modification showed greater sensitivity to body posture and breathing regime changes than mean value and standard deviation of heart rhythm and breathing rhythm. In addition, as a consequence of prolonged supine position, we noticed the tendency to integer quantization of PRQ (especially after 14min), in which the most common quantization number was 4:1 (demonstrated in other research reports as well). In orthostasis and slow breathing, quantization can also be observed, but shifted to other values. We postulate that these results manifest resonance effects induced by coupling patterns from sympathetic and parasympathetic adjustments (with the second as dominant factor). Significance: Our research confirms that cardiorespiratory coupling adaptability could be profoundly explored by precisely calculated PRQ parameter since cardiorespiratory regulation in healthy subjects is characterized by a high level of autonomic adaptability (responsiveness) to posture and breathing regime, although comparisons with pathological states has yet to be performed. We found Stand01 to be the most provoking state for the dynamic modification of PRQ (cardiorespiratory inducement). As such, Stand01 has the potential of using for PRQ tuning by conditioning the cardiorespiratory autonomic neural networks, e.g., in the cases where PRQ is disturbed by environmental (i.e., microgravity) or pathologic conditions.

Testing a simple and frugal model of health protective behaviour in epidemic times

The COVID-19 epidemic highlighted the necessity to integrate dynamic human behaviour change into infectious disease transmission models. The adoption of health protective behaviour, such as handwashing or staying at home, depends on both epidemiological and personal variables. However, only a few models have been proposed in the recent literature to account for behavioural change in response to the health threat over time. This study aims to estimate the relevance of TELL ME, a simple and frugal agent-based model developed following the 2009 H1N1 outbreak to explain individual engagement in health protective behaviours in epidemic times and how communication can influence this. Basically, TELL ME includes a behavioural rule to simulate individual decisions to adopt health protective behaviours. To test this rule, we used behavioural data from a series of 12 cross-sectional surveys in France over a 6-month period (May to November 2020). Samples were representative of the French population (N = 24,003). We found the TELL ME behavioural rule to be associated with a moderate to high error rate in representing the adoption of behaviours, indicating that parameter values are not constant over time and that other key variables influence individual decisions. These results highlight the crucial need for longitudinal behavioural data to better calibrate epidemiological models accounting for public responses to infectious disease threats.

Spatiotemporal and bifurcation characteristics of a nonlinear prey-predator model

The fragile plateau pastoral ecosystem is vulnerable to human grazing activities. Studying the prey-predator relationship between species in plateau pastoral area helps predict the population change law of prey and predator, which is of significant meaning to protecting the stability of the ecosystem and promote the stable growth of economic animal husbandry on the plateau. Given this, this paper establishes a two time-delays prey-predator model of plateau pastoral ecosystem based on considering the time-delay of predators from larval to forage feeding stage and the time-delay of the age of the controlled predator and its delay-dependent coefficient. Firstly, to analyze the influence of human grazing on the spatial distribution of prey, the spatiotemporal characteristics of the system with time-delays of 0 are studied, and Turing instability and Hopf bifurcation conditions are obtained. The results show that the increase in predator migration rate will lead to a pattern. In order to analyze the influence of time-delays on the dynamical behavior of the model, the crossing curves composed of thresholds of dynamic behavior change on the double time-delays plane when the time-delays are greater than 0 and the type of threshold forming the crossing curves are obtained by using the crossing curves method. The results show that when the corresponding values on the crossing curves are taken, there are many depressions and bulges in the limit cycles of the system. Their appearance has certain rules. At this time, the system will move periodically. This shape of the limit cycles is found for the first time, which is worthy of further study.

On-microscope staging of live cells reveals changes in the dynamics of transcriptional bursting during differentiation

Determining the mechanisms by which genes are switched on and off during development is a key aim of current biomedical research. Gene transcription has been widely observed to occur in a discontinuous fashion, with short bursts of activity interspersed with periods of inactivity. It is currently not known if or how this dynamic behaviour changes as mammalian cells differentiate. To investigate this, using an on-microscope analysis, we monitored mouse α-globin transcription in live cells throughout erythropoiesis. We find that changes in the overall levels of α-globin transcription are most closely associated with changes in the fraction of time a gene spends in the active transcriptional state. We identify differences in the patterns of transcriptional bursting throughout differentiation, with maximal transcriptional activity occurring in the mid-phase of differentiation. Early in differentiation, we observe increased fluctuation in transcriptional activity whereas at the peak of gene expression, in early erythroblasts, transcription is relatively stable. Later during differentiation as α-globin expression declines, we again observe more variability in transcription within individual cells. We propose that the observed changes in transcriptional behaviour may reflect changes in the stability of active transcriptional compartments as gene expression is regulated during differentiation.

On butterfly effect in the dynamics of Oskarshamn-2 instability event of 1999

The current research is a further investigation on the OECD/NEA benchmark on the Oskarshamn-2 stability event of cycle 24, occurred on 25th February 1999, in order to study the effect of minor core design changes on both steady state and dynamic behavior of the reactor core, using SIMULATE-3K. The analysis of steady state and transient have been performed along with a systematic comparison between results of the reference and modified core. Results are presented in terms of different parameters such as power/flow ratio, 2D core maps for power and flow for steady state; and channels’ power time series, 2D core maps for maximum power, decay ratio, and resonance frequency, for the transient. The results show that, the introduction of minor changes in the core through the reshuffling of the two hottest channels, and even less limiting channels, has small effects on the steady state core behavior. However, a significant change in the core dynamic behavior is observed through a drastic reduction of the power oscillation amplitude and the simulation demonstrates that, if such minor core design changes had been introduced in the beginning of cycle 24, the stability event of February 25, 1999 might have been potentially avoided. This drastic change in dynamical behavior is explained by carrying out a detailed stability and bifurcation analysis, which concluded that the reason behind such significant reduction in the power oscillation amplitudes is due to a shift in the stability boundary, making the core more stable and also due to the fact that the event took place very close to the stability boundary, region in which the system, unexpectedly, found very sensitive to small changes in the unstable region where the supercritical Hopf bifurcation is expected.