Dynamic Analysis Research Articles

Immobilization of arsenic wastes and retardation effect on cement hydration: Experimental and molecular dynamic analysis

AbstractThis work was designed to investigate the influence of arsenic dosage, variety on the mechanical properties, hydration, and solidification from the perspective of Portland cement (PC) performance evolution. The results demonstrate that using PC could solidify the arsenic wastes effectively, with arsenic leaching concentrations consistently below 5 mg/L. Arsenic wastes retard cement hydration, leading to a slower rate of hydrates formation, disrupting the calcium silicate hydrate (C–S–H) stacking structure, and thus detrimental to strength development especially at early age. The adverse effect is highly dependent on the arsenic variety. The insoluble calcium arsenate exhibits the least impact, while the arsenates show the largest challenging to immobilization due to the instability of hydrates. Molecular dynamic simulation indicates that arsenic can be chemically immobilized with Ca2+, and be physically adsorbed onto the positively charged C–S–H by forming As‐O···Ca···Si‐O units, accompanied by a significant reduction in adsorption energy by 46.5%. The arsenic solidification behavior provides a basis for the resource utilization of arsenic wastes in cementitious materials.

Robust seismic fragility curves for concrete gravity dams incorporating aleatory, epistemic, and fuzzy uncertainties

Concrete gravity dams are critical infrastructure assets, and their failure in seismically active regions poses significant risks. The primary problem addressed in this research is the need for a reliable assessment of the seismic fragility of these dams to ensure safety in such areas. The research aims to develop a comprehensive methodology for seismic fragility analysis that accounts for various uncertainties affecting dam performance, including uncertainties in material properties and seismic characteristics and the fuzziness of damage state thresholds through the Latin Hypercube Sampling method. The methodology involves a three-stage approach: first, a finite element model is created using Abaqus software, incorporating uncertainties in material properties and earthquake characteristics using the Latin Hypercube Sampling method (LHS). Second, incremental dynamic analysis (IDA) defines damage states based on concrete cracking severity and overall stability, utilizing four performance categories of limit states (minor, moderate, extensive, and heavy). Finally, a mathematical model is introduced to characterize the ambiguity in damage state thresholds, recognizing the gradual nature of damage evolution. The primary findings demonstrate that fuzziness substantially influences the probability of exceedance across all damage states, with varying effects on different damage indices because of their differing frequency distributions. This research enhances the reliability and accuracy of seismic fragility assessments, contributing to more robust design guidelines and effective risk mitigation strategies for concrete gravity dams.

Multi-temporal image analysis of wetland dynamics using machine learning algorithms

Wetlands play a crucial role in enhancing groundwater quality, mitigating natural hazards, controlling erosion, and providing essential habitats for unique flora and wildlife. Despite their significance, wetlands are facing decline in various global locations, underscoring the need for effective mapping, monitoring, and predictive modeling approaches. Recent advances in machine learning, time series earth observation data, and cloud computing have opened up new possibilities to address the challenges of large-scale wetlands mapping and dynamics forecasting. This research conducts a comprehensive analysis of wetland dynamics in the Thatta region, encompassing Haleji & Kinjhar Lake in Pakistan, and evaluates the efficacy of different classification systems. Leveraging Google Earth Engine, Landsat imagery, and various spectral indices, we assess four classification techniques to derive accurate wetland mapping results. Our findings demonstrate that Random Forest emerged as the most efficient and accurate method, achieving 87% accuracy across all time periods. Change detection analysis reveals a significant and alarming decline in Haleji & Kinjhar Lake wetlands over 1990–2020, primarily driven by agricultural expansion, urbanization, groundwater extraction, and climate change impacts like rising temperatures and reduced precipitation. If left unaddressed, this continued wetland loss could have severe implications for aquatic and terrestrial species, water and soil quality, wildlife populations, and local livelihoods. The study predicts future wetland dynamics under different scenarios - enhancing drainage for farmland conversion (10–20% increase), increasing urbanization (10–20% expansion), escalating groundwater extraction (7.2m annual decline), and climate change (up to 5 °C warming and 54% precipitation deficit by 2050). These scenarios forecast sustained long-term wetland deterioration driven by anthropogenic pressures and climate change. To guide conservation strategies, the research integrates satellite data analytics, machine learning algorithms, and spatial modeling to generate actionable insights into multifaceted wetland vulnerabilities. Findings provide a robust baseline to inform policies ensuring sustainable management and preservation of these vital ecosystems amidst escalating human and climate threats. Over 1990–2020, the Thatta region witnessed a 352.8 sq.km loss of wetlands, necessitating urgent restoration efforts to safeguard their invaluable ecosystem services.

Effects of Moisture Content and Heat Treatment on the Viscoelasticity and Gelation of Polyacrylonitrile/Dimethylsulfoxide Solutions

Polyacrylonitrile (PAN) gels create significant obstacles in industrial fiber spinning by forming insoluble networks that compromise solution stability and uniformity. This study investigates the rheological properties of PAN/dimethyl sulfoxide (DMSO) solutions, examining how aging time, moisture content, and polymer concentration affect gelation behavior. Dynamic rheological analysis revealed that both physical and chemical crosslinks play crucial roles in gel formation, with gelation accelerating markedly when moisture content exceeds 3% and aging progresses. Under heat treatment at 80 °C, samples with increased moisture content demonstrated rapid transitions to solid-like states, indicating a critical moisture threshold for enhanced gelation kinetics. Additionally, reductions in polymer concentration disrupted physical crosslink density, thereby mitigating gel formation. These results underscore the importance of precisely controlling moisture and concentration parameters in PAN solutions to stabilize solution properties and minimize gel formation, thus enhancing process efficiency and quality in PAN-based carbon fiber production.

Numerical Study on Combustion Characteristics of a 600 MW Boiler Under Low-Load Conditions

Under the background of achieving carbon dioxide peaking and carbon neutrality, the rapid development of renewable energy power generation poses new challenges to the flexible adjustment capabilities of traditional power plants. To explore the furnace combustion stability and optimal operation modes during deep peak shaving, a simulation of the combustion process under low-load conditions for a 600 MW wall-fired boiler is performed utilizing computational fluid dynamics (CFD) analysis. The impact of burner combination modes on the combustion process within the furnace is explored at 25% and 35% boiler maximum continuous ratings (BMCRs). This study investigates two configurations of burner combinations. One mode operates burners in layers A, B, and C, which include the lower layers of burners on the front and rear walls of the boiler, as well as the middle-layer burners on the rear wall, referred to as OM1. The other mode operates burners in layers A and C, which include the lower layers of burners on the front and rear walls of the boiler, referred to as OM2. The results indicate that OM2 exhibits superior capabilities in orchestrating the distribution of the airflow velocity field and temperature field under the premise of ensuring no more than a 1% decrease in the pulverized coal burnout rate. When OM1 is employed, the airflow ejected from the middle-level burners hinders the upward movement of pulverized coal sprayed from the lower-level burners, causing a larger proportion of pulverized coal to enter the ash hopper for combustion. Consequently, the ash hopper attains a peak mole fraction of CO2 at 0.163. OM2 delays the blending of pulverized coal with air by enhancing the injection quantity of pulverized coal per burner. As a result, the generation of CO in the ash hopper reaches a notable mole fraction of up to 0.108. The decreased furnace temperature promotes the formation of fuel-based NOx during low-load operation. Taking the 25% BMCR as an example, the NOx emissions measured at the furnace outlet are 743 and 1083 ppm for OM1 and OM2, respectively. This study focuses on the impact of combustion combinations on the combustion stability when the boiler is operating at low loads. The findings could enrich previous research on combustion stability and contribute to the optimization of combustion schemes for power plant boilers operating at low loads.

Effect of pH shifting and temperature on the functional properties of a commercial pea protein isolate

AbstractBackground and ObjectivesIn the present study, the effect of a pH‐shifting method in combination with heat was investigated for its effects on the resulting surface and functional properties of a commercial pea protein isolate. The pH shifting process was performed at both acidic (pH 2) and alkaline (pH 10) pH and then adjusted back to neutrality. The heat‐treated samples were further subjected to heating and later neutralized at pH 7.FindingsThe results of these treatments indicated that an alkaline pH shifting, as well as its combination with heat, resulted in a significant increase in the solubility of the proteins, whereas an acidic pH shifting, and in combination with heat, reduced the stability of the proteins in solution. Additionally, some functional properties were enhanced by pH shifting, such as foaming capacity or emulsion stability, while other properties showed no alteration or were negatively impacted, such as foaming stability. Furthermore, analysis of the bubble structure of foams using a dynamic foam analyzer revealed that bubble sizes for samples shifted at pH 2 in combination with heat presented the biggest increase in bubble growth over time, creating a less stable foam.ConclusionsThe application of pH shifting and the use of heat can aid in the improvement of pea protein functionality and allow tailoring of these proteins for specific applications.Significance and NoveltyThis study utilized a simple method to achieve modifications in the protein structures, providing insights into the application of pea proteins into food products as emulsifying and foaming agents.

Analysis of Land Use and Land Cover Dynamics in the Highlands of Northern Ethiopia

In the highlands of northern Ethiopia, many land use and land cover changes (LULCC) have occurred during different activities of the populations. Despite its coverage and unwise use of natural resources, these land uses and land covers are facing increasing or decreasing their area coverage. Information derived from land use and land cover change detection is important to land conservation, sustainable development, and management of Natural resources. This purpose of this study is therefore concerned with identifying the change in land use and land cover detection of the Wejic watershed. To identify land cover changes detection; remote sensing data, satellite imagery and image processing techniques had done within two dates of 1998 and 2017 using Land sat TM 30 m resolution images using Arc GIS 10.1. Hence, a field survey was carried out in 2017 to identify the major land cover types in the watershed. Detection Analysis of land use and land cover dynamics were calculated from the selected watershed in Southern Tigray, Northern Ethiopia. These land use types were cultivated, forest, bush, shrub, and homestead lands. Furthermore, a normalized difference vegetation index (NDVI) was developed for both years. The land use and land cover change results indicated that forest, cultivated land, and bush land decreased by 4.4%, 2.2%, and 2.4%, respectively. However, shrub land and homestead increased by 5.5% and 3.6%, respectively. Therefore The change detection analysis using GIS and remote sensing could deliver useful information to understand the seasonal patterns of land use dynamics for planners and decision makers; consequently, sustainable land management planning is possible.

Dynamic Analysis and Vibration Control of Additively Manufactured Thin-Walled Polylactic Acid Polymer (PLAP) and PLAP Composite Beam Structures: Numerical Investigation and Experimental Validation

This study primarily presents a numerical investigation of the dynamic behavior and vibration control in thin-walled, additively manufactured (AM) beam structures, validated through experimental results. Vibration control in thin-walled structures has gained significant attention recently because vibrations can severely affect structural integrity. Therefore, it is necessary to minimize these vibrations or keep them within acceptable limits to ensure the structure’s integrity. In this study, the AM beam structures were made of polylactic acid polymer (PLAP), short carbon fiber reinforced in PLAP (SCFR|PLAP), and continuous carbon fiber reinforced in PLAP (CCFR|PLAP), with 0°|0° layer orientations. The finite element modeling (FEM) of the AM beam structures integrated with macro fiber composite (MFC) was carried out in Abaqus. The initial four modal frequencies of bending modes (BMs) and their respective modal shapes were acquired through numerical simulation. It is crucial to highlight the numerical findings that reveal discrepancies in the 1st modal frequencies of the beams, ranging up to 1.5% compared to their respective experimental values. For the 2nd, 3rd, and 4th modal frequencies, the discrepancies are within 10%. Subsequently, frequency response analysis (FRA) was carried out to observe the frequency-dependent vibration amplitude spectrum at the initial four BM frequencies. Despite discrepancy in the amplitude values between the numerical and experimental datasets, there was consistency in the overall amplitude behavior as frequency varied. THz spectroscopy was performed to identify voids or misalignment errors in the actual beam models. Finally, vibration amplitude control using MFC (M8507-P2) was examined in each kinematically excited numerical beam structure. After applying a counterforce with the MFC, the controlled vibration amplitudes for the PLAP, SCFR|PLAP, and CCFR|PLAP configurations were approximately ±19 µm, ±16 µm, and ±13 µm, respectively. The trend in the controlled amplitudes observed in the numerical findings was consistent with the experimental results. The numerical findings of the study reveal valuable insights for estimating trends related to vibration control in AM beam structures.

Numerical Analysis of the Projection Dynamics and Their Associated Mean Field Control

Numerical Analysis of the Projection Dynamics and Their Associated Mean Field Control

Dynamic Mechanisms of R&D Innovation in Chinese Multinational Corporations: The Impact of Government Support, Market Competition and Entrepreneurial Spirit

This study focuses on the R&D innovation drive mechanism of Chinese multinational companies. Using a grounded theory, five driving factors were identified: government support, entrepreneurial spirit, market competition, company profits, and the innovation environment of the host country. Dynamic Qualitative Comparative Analysis was then employed to assess the validity of these driving factors and determine their pathways of influence, leading to the establishment of a driving mechanism. Finally, structural equation modeling was used to explore the magnitude of the effects of these driving factors. Based on data analysis from Chinese A-share listed multinational companies from 2007 to 2022, it was found that entrepreneurial spirit serves as the core driving force, while government support and market competition act as mediating variables that significantly promote R&D innovation among Chinese multinational companies. However, company profits were found to have a negative impact. Additionally, the innovation environment of the host country plays a moderating role, enhancing the positive effects of government support and market competition on innovation. These findings emphasize the importance of the synergy between the internal and external resources for Chinese multinational companies, providing important insights for integrating global resources to enhance international competitiveness and innovation capabilities.

High-Strength, Self-Healing Copolymers of Acrylamide and Acrylic Acid with Co(II), Ni(II), and Cu(II) Complexes of 4′-Phenyl-2,2′:6′,2″-terpyridine: Preparation, Structure, Properties, and Autonomous and pH-Triggered Healing

The utilization of self-healing polymers is a promising way of solving problems associated with the wear and tear of polymer products, such as those caused by mechanical stress or environmental factors. In this study, a series of novel self-healing, high-strength copolymers of acrylamide, acrylic acid, and novel acrylic complexes of 4′-phenyl-2,2′:6′,2″-terpyridine [Co(II), Ni(II), and Cu(II)] was prepared. A systematic study of the composition and properties of the obtained polymers was carried out using a variety of physicochemical techniques (elemental analysis, gel permeation chromatography (GPC), attenuated total reflectance Fourier transform infrared spectroscopy (ATR/FT-IR), ultraviolet-visible spectroscopy (UV-vis), small-angle X-ray scattering (SAXS), wide-angle X-ray scattering (WAXS), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA), confocal laser scanning microscopy (CLSM), and tensile testing). All metallopolymer samples exhibit autonomous intrinsic healing along with maintaining high tensile strength values (for some samples, the initial tensile strength exceeded 100 MPa). The best values of healing efficiency are possessed by metallopolymers with a nickel complex (up to 83%), which is most likely due to the highest lability of the metal–heteroatom coordination bonds. The example of this system shows the ability to re-heal with negligible deterioration of the mechanical properties. The possibility of tuning the mechanical properties of self-healing films through the use of different metal ions has been demonstrated.

Impact of ethanol on the flotation efficiency of imidazolium ionic liquids as collectors: Insights from dynamic surface tension and solvation analysis

Impact of ethanol on the flotation efficiency of imidazolium ionic liquids as collectors: Insights from dynamic surface tension and solvation analysis

Preparation of multiaxial glass fiber/epoxy prepreg and its mechanical properties in composites

AbstractThis study investigates the mechanical properties of composites made from biaxial warp‐knitted glass fiber/epoxy prepregs (BW‐GF/EP) in comparison to plain woven glass fiber/epoxy prepregs (PW‐GF/EP). The BW‐GF/EP composites demonstrated superior tensile strength, with an increase of 9.5%, and bending strength, with an increase of 12.2%, compared to the PW‐GF/EP composites. Despite having a lower tensile modulus, the BW‐GF/EP composites exhibited 8.7% higher interlaminar shear strength. Dynamic mechanical analysis showed that both materials had similar storage and loss moduli at lower temperatures, with PW‐GF/EP performing better at higher temperatures. Microscopy revealed that failure in PW‐GF/EP occurred at weave intersections, while BW‐GF/EP composites showed fiber rupture and delamination. The findings highlight the advantages of using biaxial warp‐knitted fabrics for improved composite performance.Highlights Developed biaxial warp‐knitted fabric prepregs to replace liquid molding techniques. Improved interlaminar shear strength, reducing delamination risks in composites. Achieved higher tensile and bending strength compared to plain weave composites. Enhanced resin impregnation and molding efficiency with biaxial warp‐knitted fabrics. Reduced environmental impact and costs by avoiding VOCs and minimizing waste.

Multiphase Biopolymers Enriched with Suberin Extraction Waste: Impact on Properties and Sustainable Development

This manuscript explores the development of sustainable biopolymer composites using suberin extraction waste, specifically suberinic acid residues (SAR), as a 10% (w/w) reinforcing additive in polylactide (PLA) and thermoplastic starch–polylactide blends (M30). The materials were subjected to a detailed analysis using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA) to assess their thermal, mechanical, and structural properties. The study confirmed the amorphous nature of the biopolymers and highlighted how SAR significantly influences their degradation behavior and thermal stability. M30 exhibited a multi-step degradation process with an initial decomposition temperature (T5%) of 207.2 °C, while PLA showed a higher thermal resistance with decomposition starting at 263.1 °C. Mechanical performance was assessed through storage modulus (E′) measurements, showing reductions with increasing temperature for both materials. The research provides insights into the potential application of SAR-enriched biopolymers in sustainable material development, aligning with circular economy principles. These findings not only suggest that SAR incorporation could enhance the mechanical and thermal properties of biopolymers, but also confirm the effectiveness of the research in reassurance of the audience.

Design and Computational Modelling of AUV Tunnel Thruster Covers for Efficient Operation

Autonomous underwater vehicles have seen widespread adoption across industrial, scientific, and defence applications. They are typically utilized to perform oceanic mapping, surveillance, and inspection-type missions. Hovering AUVs, used for inspection applications, are over-actuated vehicles incorporating multiple thrusters to enable multiple degrees of freedom control at a low velocity. These vehicles, however, are extremely energy-limited, owing to their restrictive structural design that prohibits large batteries. This necessitates careful hydrodynamic design to best utilize this limited energy storage. Of particular importance are the hydrodynamic propulsion efficiencies of these vehicles. Whilst the external structure of AUV platforms is relatively well-defined and hydrodynamically optimized, one area has seen limited focus and optimization. This is the immediate surroundings of the propulsion geometry and housing. In this body of work, we propose an adaptation to the traditional through-body tunnel thruster geometry of an over-actuated AUV platform. The modification is the inclusion of a retractable internal thruster cover. Subsequently, a comparison is provided between a clean-hull AUV configuration, one with open through-body thrusters, and one fitted with the designed cover geometry. A comprehensive computational fluid dynamics analysis is then converged and assessed using the Reynolds-Averaged Navier–Stokes equations. The drag and local flow fields are determined, where the covers are found to reduce the drag coefficient and total drag of the AUV by 9.51%, primarily due to a reduction of 9.91% in the pressure drag. These findings highlight the increased operational efficiency of the cover geometry and support the adoption of such covers for energy-constrained AUVs.

Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning

ABSTRACT BACE1 has been regarded as an essential drug design target for treating Alzheimer’s disease (AD). Multiple independent Gaussian accelerated molecular dynamics simulations (GaMD), deep learning (DL), and molecular mechanics general Born surface area (MM-GBSA) method are integrated to elucidate the molecular mechanism underlying the effect of D93 and D289 protonation on binding of inhibitors OV6 and 4B2 to BACE1. The GaMD trajectory-based DL successfully identifies significant function domains. Dynamic analysis shows that the protonation of D93 and D289 strongly affects the structural flexibility and dynamic behaviour of BACE1. Free energy landscapes indicate that inhibitor-bound BACE1s have more conformational states in the protonated states than the wild-type (WT) BACE1, and show more binding poses of inhibitors. Binding affinities calculated using the MM-GBSA method indicate that the protonation of D93 and D289 highly disturbs the binding ability of inhibitors to BACE1. In addition, the protonation of two residues significantly affects the hydrogen bonding interactions (HBIs) of OV6 and 4B2 with BACE1, altering their binding activity to BACE1. The binding hot spots of BACE1 recognized by residue-based free energy estimations provide rational targeting sites for drug design towards BACE1. This study is anticipated to provide theoretical aids for drug development towards treatment of AD.

Industry specialisation of the Kemerovsk region – Kuzbass: trends and problems that affect economic growth and development of the region

The article is devoted to studying the influence of industry specialisation of the Kemerovo region – Kuzbass on the economic growth of the entity. The purpose of the study is to identify the most significant trends and problems of the industry specialisation that affect the development of the region. Using methods of scientific knowledge – description, synthesis and generalisation of the data obtained; literature review, graphical method – the following has been conducted: analysis of the dynamics of structural changes in the gross regional product (hereinafter referred to as GRP) of the Kemerovo region – Kuzbass; assessment of trends in the movement of main industry indicators and indicators of regional industry. The information base of the study consists of foreign and domestic publications devoted to the analysis of the GRP sectoral structure; statistical data from the Federal State Statistics Service and its territorial authority for the Kemerovo Region – Kuzbass. Based on the analysis of the structural changes dynamics, an increase in the contribution of the raw materials sector to the country’s gross domestic product and an increase in the share of mineral extraction in the industry structure of the GRP of the Kemerovo region – Kuzbass have been revealed. The trend of decrease in the industrial production index is analysed, it is shown that it has a trend similar to the dynamics of the decline in mining production, and the reasons for the decline are described. The strengthening trend of economic growth in the Kemerovo region – Kuzbass based on the raw model has been determined. East Asian models of economic growth are considered. The expediency of using international experience in the design of high-tech industries on the basis of private investment in the research and development sector, and its adaptation to the realities of the development of Russian regions is indicated. A conclusion is drawn about the need to support the technological sovereignty of the country and the transition of the development of the Kemerovo region – Kuzbass to a non-primary model.

The Effect of Network Delay and Contagion on Mobile Banking Users: A Dynamical Analysis

This paper analyses how network contagion affects the acceptance or rejection of mobile banking, emphasizing the risk of contagion that hinders the growth of users among bank clients. As a research method, a mathematical model based on the Susceptible, Infected, and Recovered framework is used within a nonlinear dynamic system with a distributed time delay and the optimal control strategy. The approach aims to find the behaviour dynamics of mobile banking users, non-users, and undecided ones. Our model adds value to the existing literature by employing a qualitative dynamic analysis, as opposed to other studies that study contagion empirically. The steady states and their conditions for stability are found, and the critical value for time delay causing oscillatory is determined. The optimal control strategies are identified to enlarge the number of mobile banking users and decrease the number of non-users. Numerical simulations support the theoretical findings. The research has practical implications given that the model predicts mobile banking user behaviour in assisting policy decision-making and addresses the possible policy measures that aim to increase the number of mobile banking users. The conclusions suggest that financial inclusion can contribute to the expansion of mobile banking users.

Dynamical analysis on symptom-based SEMIR compartmental model with age groups

Dynamical analysis on symptom-based SEMIR compartmental model with age groups

An Efficient Analysis of Amplitude and Phase Dynamics in Networked MEMS-Colpitts Oscillators

Abstract This paper explores the interactions of both phase and amplitude in a network of N MEMS-Colpitts oscillators that are resistively coupled. The numerical simulations of the extensive networks of oscillators, required for emerging applications such as clock synchronization and neuromorphic computing, become computationally prohibitive as the number of oscillators increases. This complicates the design and evaluation of such systems, as understanding the effects of changes in coupling and design parameters can require many simulations. This study employs the method of multiple scales (MS) in combination with the harmonic balance method to convert the coupled differential equations governing the system of oscillators into a set of nonlinear evolution equations for the amplitude and phase of the oscillators. The amplitude and phase evolve on a timescale that is slow, commensurate with the damping in the system, compared with the fast timescale of the oscillation frequencies. The approach used in this study to describe the amplitude and phase dynamics offers significant computational efficiency (gains of 10× to 50× are shown) compared to direct numerical integration while maintaining an accurate representation of the response. The results of the presented simulations demonstrate the effect of coupling strength on the dynamics of the network, accounting for both phase and amplitude dynamics.