Dynamic Behavior Research Articles

Health-related quality of life dynamics: modeling insights from immunotherapy.

Understanding health-related quality of life (HRQoL) dynamics is essential for assessing and improving treatment experiences; however, clinical and observational studies struggle to capture their full complexity. We use simulation modeling and the case of Chimeric Antigen Receptor T-cell therapy-a type of cancer immunotherapy that can prolong survival, but carries life-threatening risks-to study HRQoL dynamics. We developed an exploratory system dynamics model with mathematical equations and parameter values informed by literature and expert insights.We refined its feedback structure and evaluated its dynamic behavior through iterative interviews. Model simulated HRQoL from treatment approval through six months post-infusion. Two strategies-reducing the delay to infusion and enhancing social support-were incorporated into the model. To dynamically evaluate the effect of these strategies, we developed four metrics: post-treatment HRQoL decline, recovery time to pre-treatment HRQoL, post-treatment HRQoL peak, and durability of the peak. Model captures key interactions within HRQoL, providing a nuanced analysis of its continuous temporal dynamics, particularly physical well-being, psychological well-being, tumor burden, receipt and efficacy of treatment, side effects, and their management. Model analysis shows reducing infusion delays enhanced HRQoL across all four metrics. While enhanced social support improved the first three metrics for patients who received treatment, it did not change durability of the peak. Simulation modeling can help explore the effects of strategies on HRQoL while also demonstrating the dynamic interactions between its key components, offering a powerful tool to investigate aspects of HRQoL that are difficult to assess in real-world settings.

Hopf Bifurcation Analysis of a Nose Landing Gear System of Aircraft

The Hopf bifurcation problem of a nose landing gear system is investigated. Taking the nearly smooth landing gear system with high-order nonlinear terms as the research object, the nose landing gear system is simplified to a plane dynamic system considering nonlinear factors by using the center manifold simplification method. The first Lyapunov coefficient of the landing gear system is derived by using the classical bifurcation theory, and the Hopf bifurcation type of the system is determined according to its sign. The bifurcation diagram is obtained by solving the differential equations of motion numerically. It is revealed that there is a stable limit cycle in the neighborhood of the supercritical Hopf bifurcation point. The influence of velocity and other factors on the shimmy oscillations of the landing gear system is analyzed. The dynamical behavior in the neighborhood of the Hopf bifurcation point is explored theoretically and numerically. The research results can provide a theoretical basis for the optimal design of aircraft landing gear systems.

Synthesis and Electrochemical Properties of Oleylamine as a Sour Saline Corrosion Inhibitor Under Laminar Flow at 40 °C.

In this study, the synthesis of a long-chain aliphatic amino compound and its sour corrosion inhibition properties were reported. Oleylamine was obtained through the reaction of 4-(Aminomethyl) pyridine with 1-chloro-octadecane. The identification and characterization of reaction products were carried out through Fourier transform infrared spectroscopy (FTIR) and gas chromatography/mass spectroscopy (GC-MS). Oleylamine was tested as a sour corrosion inhibitor for steels. Different concentrations of oleylamine (0, 5, 10, 25, and 100 ppm) in a sour saline electrolyte were analyzed. The dynamic anticorrosive behavior of oleylamine on carbon mild steel (AISI 1018) surfaces was evaluated using a laminar flow of 100 rpm and tested with potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) measurements. After electrochemical testing, the surface of the steel specimens that were used was characterized with Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The electrochemical results of the anticorrosive efficiency of oleylamine for steel showed an exponential behavior as a function of inhibitor concentration. At a concentration of 20 ppm of the inhibitor, the anticorrosive efficiency did not show any significant changes. However, at 100 ppm of the inhibitor, an efficiency of over 95% was achieved. After the electrochemical tests, the surface of the steel samples with the inhibitor revealed the formation of an inhibitor layer that prevented the corrosion of the steel.

Dynamic Mechanical Properties and Constitutive Modeling of Polyurethane Microporous Elastomers.

The present study fabricated samples of polyurethane elastomers (PUEs) with three distinct densities and assessed their mechanical responses using split Hopkinson pressure bar (SHPB) tests. The findings reveal a significant increase in PUE stress with increasing strain rate and density. To further investigate the influence of strain rate sensitivity on PUEs, a strain rate sensitivity coefficient was employed to quantify the impact of strain rate on the mechanical properties of PUEs. Separate quantifications were performed for collapse stress, plateau stress, and densification strain as indicators of the strain rate sensitivity coefficient. The results demonstrate that the collapse stress sensitivity coefficient was notably affected by the applied strain rate. Additionally, both collapse and plateau stresses exhibited an increase with increasing density, which could be described by a power function relationship. Based on the theory of strain energy function, a constitutive model considering density and strain rate effects was developed to describe the stress-strain behavior of PUEs under various densities and strain rates. A comparison between this constitutive relationship and experimental results showed good agreement, highlighting its potential in describing dynamic mechanical behavior.

Comparative Analysis of Soil-Piles Structure Interaction of Framed Structure

This study presents a comparative analysis of a 15-story building with two foundational approaches: a fixed- base foundation and a pile foundation incorporating soil- structure interaction (SSI) in sandy soil conditions. The research investigates the dynamic behavior of each foundation type under varying conditions, specifically examining the effects of different pile spacings and relative densities of sandy soil on the building’s fundamental frequency, time period, lateral displacement, and overall structural stability. The SAP2000 software is used for numerical study. Key Words: Soil-Structure Interaction (SSI), frequency, time period, displacement, Lateral Displacement, Seismic Analysis, G+14, SAP2000, sandy soil

On the study of solitary wave dynamics and interaction phenomena in the ultrasound imaging modelled by the fractional nonlinear system

This research work focuses on investigating the propagation of ultrasonic waves, which propagate mechanical vibrations of molecules or particles inside materials. Ultrasound imaging is extensively used and deeply rooted in the medical field. The key technologies that form the basis for many different uses in the area include transducers, contrast agents, pulse compression, beam shaping, tissue harmonic imaging, techniques for measuring blood flow and tissue motion, and three-dimensional imaging. The third-order non-linear β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta$$\\end{document}-fractional Westervelt model has been used as a governing model in the imaging process for securing the different wave structures. The exact solutions of different types, including mixed, dark, singular, bright-dark, bright, complex and combined solitons are extracted. These solutions are obtained by using two newly introduced techniques, namely modified generalized Riccati equation mapping method and modified generalized exponential rational function method. Moreover, breather, lump and other waves are extracted by the assistance of logarithmic transformation and different test functions. The used methodologies are extremely effective and possess substantial computing capacity to effectively address the different solutions with a high level of accuracy in these systems. The techniques used are well-known for being effective, simple, and flexible enough to integrate multiple soliton systems into a unified framework. In addition, we provide 2D and 3D graphs that explain the behavior of the solution at various parameter values, under the influence of β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta$$\\end{document}-fractional derivatives. The results offered in this study may improve the comprehension of the nonlinear dynamic behavior of the specific system and confirm the efficacy of the approaches used. We expect that our approaches will be beneficial for a wide range of nonlinear models and other problems in the related fields.

224-fs soliton pulses generation at 1μm from ytterbium-doped fiber laser with CoTe2 nanosheets as an ultrafast modulator

Transition metal ditellurides (TMDTs) have numerous attractive properties, making them suitable for a wide range of applications. In this study, cobalt ditelluride (CoTe2) nanosheets, a promising TMDT for photonic applications, were prepared using an ultrasound-enhanced liquid phase exfoliation (LPE) method. A novel saturable absorber (SA) employing CoTe2 nanosheets was then fabricated by optically depositing them on microfiber. The nonlinear optical modulation properties of the CoTe2 SA were investigated. A high-performance 1 μm ultrafast fiber laser was demonstrated by incorporating newly developed CoTe2 nanosheets-based SA in a ring cavity ytterbium-doped fiber laser (YDFL). The dynamical behaviour of the proposed passively mode-locked YDFL in response to variations in pump optical power was investigated. The findings reveal that the device achieved a modulation depth of 2.5 %, and saturation light intensity of 30.6 MW/cm2. Moreover, a stable and robust mode-locked soliton optical pulse sequence with a fundamental repetition frequency of 3.089 MHz, and a pulse duration of 224 fs was generated at 1032 nm. The proposed YDFL, being all-fiber, compact, and cost-effective, is set to find extensive applications in various domains, including optical fiber communication, sensing, and biomedical imaging.

An Experimental Study on the Effect of GFRP and CFRP Strengthening on the Static and Dynamic Behavior of R/C Beams Under Progressive Damage

This paper aims to investigate the effect of glass fiber-reinforced polymer (GFRP) and carbon fiber-reinforced polymer (CFRP) strengthening materials on the static and dynamic behavior of reinforced concrete (R/C) beams subjected to progressive damage. Four identical beams, each strengthened with either GFRP or CFRP, are tested under a cyclic quasi-static loading pattern. Impact hammer tests are performed for undamaged states and various damage levels of the beams. The dynamic test data are analyzed using the Enhanced Frequency Domain Decomposition (EFDD) method to estimate the dynamic characteristics of the beams. In this context, the first three vibration modes in both vertical and horizontal directions are considered. Strengthening is applied to both pre-damaged and undamaged beams, enabling a comparison of their performance before and after the strengthening procedure. Beams strengthened with CFRP exhibit a higher load-bearing capacity and stiffness but also fail at lower displacement levels compared to those strengthened with GFRP, which demonstrate more ductile behavior. Furthermore, the modal frequency ratios indicate that the first vibration mode is more sensitive to damage than the second and third modes. This study highlights the effectiveness of both strengthening materials in enhancing the structural performance of both undamaged and damaged beams.

Fractional-Order Modeling and Stochastic Dynamics Analysis of a Nonlinear Rubbing Overhung Rotor System

To study the nonlinear dynamic behavior and system stability of a rubbing overhung rotor with viscoelastic and memory-effect damping and random uncertain parameters, this paper introduces a fractional-order modeling and stochastic dynamic analysis method for the nonlinear overhung rotor system with frictional impact faults. Firstly, the dynamic equations of the overhung rotor considering friction effect and fractional damping effect are established based on the transfer matrix method and fractional order derivative. Then, the time-domain response of the fractional-order dynamic equations is solved by combining the Runge–Kutta method and the continuous fractional expansion, and the steady-state response characteristics of different fractional damping are analyzed in the deterministic case. Finally, to analyze the response of the system under the effect of stochastic parameters, the sparse grid-based PCE metamodel of the system response is developed. Statistical moments, probability distributions, and sensitivity indices of the response of stochastic systems are revealed. The results of this paper provide a theoretical basis for efficient and accurate prediction of the stochastic response of nonlinear rubbing overhung rotor systems.

Toward tailored light absorption manipulation by Kerr nonlinear nanoslits within a grating Fabry-Perot cavity coupled with reconfigurable GST225 material

In this paper, we investigate the absorption tunability of a silver plasmonic grating incorporating Kerr-type nonlinear graphene-oxide (GO) nanoslits and Ge2Sb2Te5 (GST225) phase-change material at telecom wavelengths. The linear absorption spectra reveal that the amorphous GST225 grating exhibits two distinct absorption peaks, while half-crystallization leads to a single pronounced peak, and full crystallization results in a redshifted peak with a slightly decreased value. These findings confirm that the crystalline degree of GST225 significantly modulates the absorption characteristics. Upon exposure to a nanosecond Gaussian pulse laser irradiation with appropriate fluences, the electric field confinement within the nanoslits intensifies, particularly at the center of the pulse, leading to a pronounced absorption adjustment due to Kerr nonlinearity. Temporal examination at the L-band wavelength of 1591.5 nm reveals a U-shaped absorption response for both amorphous and crystalline GST225, with a pronounced dip at the pulse’s peak. In the half-crystallized state, the weak linear absorption can be substantially enhanced at both the leading and trailing edges of the pulse, with a dip at the center, illustrating the Kerr nonlinearity within the GO nanoslits. The dynamic behavior of absorption under different laser fluences underscores the potential of this system for high-contrast optical switching. Our results offer insights into the development of reconfigurable optical switches utilizing nonlinear Kerr effects, paving the way for advancements in tunable optical communication technologies.

Dynamic Behavior of Pt Multimetallic Alloys for Active and Stable Propane Dehydrogenation Catalysts.

Improving the use of platinum in propane dehydrogenation catalysts is a crucial aspect to increasing the efficiency and sustainability of propylene production. A known and practiced strategy involves incorporating more abundant metals in supported platinum catalysts, increasing its activity and stability while decreasing the overall loading. Here, using colloidal techniques to control the size and composition of the active phase, we show that Pt/Cu alloy nanoparticles supported on alumina (Pt/Cu/Al2O3) displayed elevated rates for propane dehydrogenation at low temperature compared to a monometallic Pt/Al2O3 catalyst. We demonstrate that the enhanced catalytic activity is correlated with a higher surface Cu content and formation of a Pt-rich core and Cu-rich shell that isolates Pt sites and increases their intrinsic activity. However, rates declined on stream because of dynamic metal diffusion processes that led to a more uniform alloy structure. This transformation was only partially inhibited by adding excess hydrogen to the feed stream. Instead, cobalt was introduced to provide trimetallic Pt/Cu/Co catalysts with stabilized surface structure and stable activity and higher rates than the original Pt/Cu system. The structure-activity relationship insights in this work offer improved knowledge of propane dehydrogenation catalyst development featuring reduced Pt loadings and notable thermal stability for propylene production.

Coexistence of hidden attractors in memristive chaotic system

In this paper, a charge controlled memristor model is introduced into the Sprott-A system equation to construct a new memristor chaotic system and the calculation of this new system satisfies the characteristics of no equilibrium points. The periodic function is added to the new constructed memristor chaotic system, and the coexistence of attractors in memristor chaotic system without equilibrium points is obtained by adjusting the control parameters. Through different analytical methods to explore the characteristics of the new system. The dynamic behaviors of the system before and after the periodic transformation are compared and analyzed. In the end, DSP simulation is used to verify the feasibility of the theoretical model. The coexistence of attractors in memristor chaotic systems can improve the flexibility and security of chaotic encryption systems. Further research on this kind of phenomena can meet the needs of higher encryption.

Multi-perspective API call sequence behavior analysis and fusion for malware classification

The growing variety of malicious software, i.e., malware, has caused great damage and economic loss to computer systems. The API call sequence of malware reflects its dynamic behavior during execution, which is difficult to disguise. Therefore, API call sequence can serve as a robust feature for the detection and classification of malware. The statistical analysis presented in this paper reveals two distinct characteristics within the API call sequences of different malware: (1) the API existence feature caused by frequent calls to the APIs with some special functions, and (2) the API transition feature caused by frequent calls to some special API subsequence patterns. Based on these two characteristics, this paper proposes MINES, a Multi-perspective apI call sequeNce bEhavior fuSion malware classification Method. Specifically, the API existence features from different perspectives are described by two graphs that model diverse rich and complex existence relationships between APIs, and we adopt the graph contrastive learning framework to extract the consistent shared API existence feature from two graphs. Similarly, the API transition features of different hops are described by the multi-order transition probability matrices. By treat each order as a channel, a CNN-based contrastive learning framework is adopted to extract the API transition feature. Finally, the two kinds of extracted features are fused to classify malware. Experiments on five datasets demonstrate the superiority of MINES over various state-of-the-arts by a large margin.

Research of Design Technology of Printed Circuit Board

This paper delves into various methodologies for enhancing the quality, design, and optimization of Printed Circuit Boards (PCBs). With the development of the technology, the importance of Printed Circuit Board(PCB) is recently mentioned by more and more people who is trying to make progress of human technology. The classification of PCB defects, a crucial step in ensuring product reliability, is discussed on several categories of defects in PCB, highlighting recent advancements such as fuzzy c-means segmentation, which significantly improves defect detection accuracy. When producing, the layout is quite significant. In a conference, a group of scientists used a thermal layout modelling and optimization routine to make the board having more space to put circuit on it. Methods to ensure PCB quality during production are examined, focusing on optical and electrical testing. The PCB design process is also explored, emphasizing the importance of those considerations before production. Finally, the paper reviews innovative approaches to PCB layout optimization, particularly in managing heat dissipation and dynamic behavior through advanced simulation techniques.

Advanced finite element modeling methods for tensile and bending analysis of arresting gear cables

This study addresses the gap in understanding the dynamic bending behavior of multi-layer twisted steel cable, pivotal in various industrial applications such as naval aircraft arresting systems. Utilizing advanced finite element modeling, the research explores the mechanical responses of these cables under macroscopic bending scenarios. By integrating beam elements and connectors within the finite element framework, the study simulates complex inter-strand interactions under various loading conditions. Results indicate that this method significantly enhances the prediction accuracy of the cables’ mechanical properties, thus offering substantial improvements in design and performance analysis of arresting gear systems. This study’s value lies in its potential to refine mechanical modeling of complex cable systems, thereby optimizing operational efficiency and safety in engineering applications.

Key feature identification of internal kink mode using machine learning

The internal kink mode is one of the crucial factors affecting the stability of magnetically confined fusion devices. This paper explores the key features influencing the growth rate of internal kink modes using machine learning techniques such as Random Forest, Extreme Gradient Boosting (XGboost), Permutation, and SHapley Additive exPlanations (SHAP). We conduct an in-depth analysis of the significant physical mechanisms by which these key features impact the growth rate of internal kink modes. Numerical simulation data were used to train high-precision machine learning models, namely Random Forest and XGBoost, which achieved coefficients of determination values of 95.07% and 94.57%, respectively, demonstrating their capability to accurately predict the growth rate of internal kink modes. Based on these models, key feature analysis was systematically performed with Permutation and SHAP methods. The results indicate that resistance, pressure at the magnetic axis, viscosity, and plasma rotation are the primary features influencing the growth rate of internal kink modes. Specifically, resistance affects the evolution of internal kink modes by altering current distribution and magnetic field structure; pressure at the magnetic axis impacts the driving force of internal kink modes through the pressure gradient directly related to plasma stability; viscosity modifies the dynamic behavior of internal kink modes by regulating plasma flow; and plasma rotation introduces additional shear forces, affecting the stability and growth rate of internal kink modes. This paper describes the mechanisms by which these four key features influence the growth rate of internal kink modes, providing essential theoretical insights into the behavior of internal kink modes in magnetically confined fusion devices.

Investigation of the Inhibition Mechanism of Process Porosity in Laser-MIG Hybrid-Welded Joints for an Aluminum Alloy

In this paper, 4 mm thick 7075 aluminum alloy was utilized for conducting laser-MIG hybrid welding tests to investigate the correlation between the dynamic behavior of keyholes and process-induced porosity. Additionally, the generation and inhibition mechanisms of process porosity were elucidated. Utilizing a high-speed camera test system of our own design, the formation position and movement characteristics of keyholes in the molten pool under different welding parameters were captured using a “sandwich” method. The dynamic behavior of keyholes during the hybrid welding process was analyzed, and the porosity of each welded joint was quantified, revealing an intrinsic relationship between keyhole dynamics and aluminum alloy laser-MIG hybrid welding porosity. The findings indicate that variations in the defocusing amount can influence both the morphology and stability of keyholes in the molten pool, consequently impacting welding porosity. The dynamic behavior of keyholes under different defocusing amounts can be categorized into five types: no keyhole formation, collapse of the keyhole root, complete instability of the keyhole, instability of the keyhole root, and stability of the keyhole. At a defocus of +12 mm, stable keyholes were observed, and no defects in the welded joints were identified.

A Survey of Artificial Intelligence Applications in Nuclear Power Plants

Nuclear power plants (NPPs) rely on critical, complex systems that require continuous monitoring to ensure safe operation under both normal and abnormal conditions. Despite the potential of artificial intelligence (AI) to enhance predictive capabilities in these systems, limited research has been conducted on the application of AI algorithms within NPPs. This presents a knowledge gap in the integration of AI for improving safety, reliability, and decision making in NPP. In this study, we explore the use of AI methods, including machine learning and real-time data analytics, applied to NPP components to address the nonlinearity and dynamic behavior inherent in reactor operations. Through the implementation of AI and Internet of Things (IoT) devices, we propose a system that enables early warning and real-time data transmission to regulatory authorities and decision-makers, ensuring better coordination during incidents. Lessons from past nuclear accidents, such as Chernobyl, emphasize the importance of timely information dissemination to mitigate risks. However, this integration also presents challenges, including cybersecurity risks and the need for updated regulations to address AI use in safety-critical environments. The results of this study highlight the urgent need for further research on the application of AI in NPPs, with a particular focus on addressing these challenges to ensure safe implementation.

A Mathematical Model for the Combination of Power Ultrasound and High-Pressure Processing in the Inactivation of Inoculated E. coli in Orange Juice.

The mathematical modeling of a combination of non-thermal technologies for E. coli inactivation is of great interest for describing the dynamic behavior of microorganisms in food, with the goal of process control, optimization, and prediction. This research focused on the design and implementation of a mathematical model to predict the effect of power ultrasound (US), high-pressure processing (HPP), and the combination of both non-thermal technologies on the inactivation kinetics of E. coli (DSM682) inoculated in orange juice. Samples were processed by US, HPP, and a combination of both technologies at varying process parameters, and a mathematical model for microbial inactivation was developed using a System Dynamics approach. The results showed that the combination of these technologies exhibited a synergistic effect, resulting in no detectable colony-forming units per mL of juice. The developed model accurately predicted the inactivation of E. coli following the combination of these technologies (R2 = 0.82) and can be used to predict microbial load reduction or optimize it based on process parameters. Additionally, combining both techniques offers a promising approach for extending the shelf life of fresh juices using non-thermal stabilization technology.

Dynamic instability and nonlinear response analysis of nanocomposite sandwich arches with viscoelastic cores

This paper presents a comprehensive study of the nonlinear dynamic behavior and snap-through phenomena in sandwich arch structures with viscoelastic cores and carbon nanotube-reinforced nanocomposite face sheets. Subjected to uniform time-dependent pressure shocks, these arches exhibit complex snap-through behavior critical for practical engineering applications. Utilizing third-order shear deformation theory, the study accurately captures nonlinear behaviors. The viscoelastic core, modeled with the Kelvin-Voigt law, enhances damping and reduces vibration amplitudes. Numerical solutions are obtained using a Chebyshev-based Ritz method, Newmark integration, and Newton-Raphson method. The Budiansky-Ruth criterion evaluates dynamic buckling loads. Key findings include significant instability near buckling loads, increased buckling loads and vibration damping due to viscoelastic effects, reduced buckling loads with foam cores, improved performance with CNTs, and more pronounced CNT effects with greater deflections. Additional conclusions highlight the sensitivity of dynamic snap-through to geometric parameters and the superior accuracy of the proposed approach compared to traditional models. This research advances the understanding and design strategies for nonlinear sandwich arch structures, enhancing predictive capabilities in complex structural systems.