Search Results (101)

Precise time interval generation is a cornerstone of modern measurement, automation, and distributed control systems, particularly within Internet of Things (IoT) architectures. This paper presents the design, implementation, and evaluation of a low-cost and high-precision time interval generator based on Complementary Metal-Oxide Semiconductor (CMOS) logic counters (Integrated Circuit (IC) IC 7493 and IC 4017) and inverter-based crystal oscillators (IC 74LS04). The proposed system enables frequency division from 1 MHz down to 1 Hz through a cascade of binary and Johnson counters, enhanced with digitally controlled multiplexers for output signal selection. Unlike conventional timing systems relying on expensive Field-Programmable Gate Array (FPGA) or Global Navigation Satellite System (GNSS)-based synchronization, this approach offers a robust, locally controlled reference clock suitable for IoT nodes without network access. The hardware is integrated with Arduino and ESP32 microcontrollers via General-Purpose Input/Output (GPIO) level interfacing, supporting real-time timestamping, deterministic task execution, and microsecond-level synchronization. The system was validated through Python-based simulations incorporating Gaussian jitter models, as well as real-time experimental measurements using Arduino’s micros() function. Results demonstrated stable pulse generation with timing deviations consistently below ±3 µs across various frequency modes. A comparative analysis confirms the advantages of this CMOS-based timing solution over Real-Time Clock (RTC), Network Time Protocol (NTP), and Global Positioning System (GPS)-based methods in terms of local autonomy, cost, and integration simplicity. This work provides a practical and scalable time reference architecture for educational, industrial, and distributed applications, establishing a new bridge between classical digital circuit design and modern Internet of Things (IoT) timing requirements. Full article

Although through tied-arch bridges exhibit strong structural robustness, collapse incidents triggered by the progressive failure of hangers still occasionally occur. Given that such bridges are unlikely to collapse due to the damage of a single or multiple hangers under the serviceability limit state, this study focuses on the failure safety limit state. Using the Nanfang’ao Bridge with inclined hangers and the Liujiang Bridge with vertical hangers as case studies, this paper investigates the dynamic response and failure modes of the residual structures when single or multiple hangers fail and initiate progressive collapse of all hangers. The results demonstrate that the configuration of hangers significantly influences the distribution of structural importance coefficients and the load transmission paths. Under identical failure scenarios, the Nanfang’ao Bridge with inclined hangers remains stable after the failure of four hangers without experiencing progressive collapse, whereas the Liujiang Bridge with vertical hangers undergoes progressive failure following the loss of only three hangers, which indicates that inclined hanger configurations offer superior resistance to progressive collapse. Based on the aforementioned analysis, the LS-DYNA Simple–Johnson–Cook damage model was employed to simulate the collapse process. The extent of damage and ultimate failure modes of the two bridges differ significantly. In the case of the Nanfang’ao Bridge, following the progressive failure of the hangers, the bridge deck system lost lateral support, leading to excessive downward deflection. The deck subsequently fractured at the mid-span (1/2 position) and collapsed in an inverted “V” shape. This failure then propagated to the tie bar, inducing outward compression at the arch feet and tensile stress in the arch ribs. Stress concentration at the connection between the arch columns and arch rings ultimately triggered global collapse. For the Liujiang Bridge, failure initiated with localized concrete cracking, which propagated to reinforcing bar yielding, resulting in localized damage within the bridge deck system. These observations indicate that progressive stay cable failure serves as the common initial triggering mechanism for both bridges. However, differences in the structural configuration of the bridge deck systems, the geometry of the arch ribs, and the constraint effects of the tie bar result in distinct failure progression patterns and ultimate collapse behaviors between the two structures. Thereby, design recommendations are proposed for through tied-arch bridges, from the aspects of the hanger, arch rib, bridge deck system, and tie bar, to enhance the resistance to progressive collapse. Full article

To accurately assess the effect of different plate thicknesses on the residual stress field of laser shock peened GH3039 superalloy, residual stress measurements were performed on GH3039 alloy plates with thicknesses of 2 mm and 5 mm after laser shock peening (LSP) treatment. Both quasi-static and high strain rate mechanical tests of GH3039 were conducted, and the Johnson-Cook (J-C) constitutive equation for GH3039 alloy at specific strain rates was fitted based on the experimental results. To obtain the parameter C in the J-C constitutive equation of GH3039 alloy under ultra-high strain rates, a modified method was proposed based on LSP experiment and finite element simulation results. Using the modified GH3039 alloy J-C constitutive equation, numerical simulations and comparative analyses of the residual stress field of GH3039 alloy plates of different thicknesses under LSP were carried out using ABAQUS software. The simulated residual stress fields of laser-shocked GH3039 alloy plates of different thicknesses were in good agreement with the experimental measurements, indicating that the modified GH3039 alloy J-C constitutive equation can accurately predict the mechanical behavior of GH3039 alloy under ultra-high strain rates. Based on the modified GH3039 alloy J-C constitutive equation, the effect of different plate thicknesses on the residual stress distribution of laser-shocked GH3039 alloy was studied, along with the underlying mechanisms. The unique distribution characteristics of residual stresses in laser-shocked GH3039 plates with varying thicknesses are primarily attributed to differences in plate bending stiffness and the detrimental coupling effects of reflected tensile waves. Full article

The constitutive model is widely employed to characterize the rheological properties of metallic materials under high-temperature conditions. It is typically derived from a series of high-temperature tests conducted at varying deformation temperatures, strain rates, and strains, including hot stretching, hot compression, separated Hopkinson pressure bar testing, and hot torsion. The original experimental data used for establishing the constitutive model serves as the foundation for developing phenomenological models such as Arrhenius and Johnson–Cook models, as well as physical-based models like Zerilli–Armstrong or machine learning-based constitutive models. The resulting constitutive equations are integrated into finite element analysis software such as Abaqus, Ansys, and Deform to create custom programs that predict the distributions of stress, strain rate, and temperature in materials during processes such as cutting, stamping, forging, and others. By adhering to these methodologies, we can optimize parameters related to metal processing technology; this helps to prevent forming defects while minimizing the waste of consumables and reducing costs. This study provides a comprehensive overview of commonly utilized experimental equipment and methods for developing constitutive models. It discusses various types of constitutive models along with their modifications and applications. Additionally, it reviews recent research advancements in this field while anticipating future trends concerning the development of constitutive models for high-temperature deformation processes involving metallic materials. Full article

This study investigates the long-term performance of flexible anti-collision rings after 12 years of service on the Xiangshan Port Highway Bridge. Stepwise loading–unloading tests at multiple loading rates (0.8–80 mm/s) were performed on the anti-collision rings, with full-field strain measurement via digital image correlation (DIC) technology. The results show that: The mechanical response of the anti-collision ring shows significant asymmetric tension–compression, with the tensile peak force being 6.8 times that of compression. A modified Johnson–Cook model was developed to accurately characterize the tension–compression force–displacement behavior across varying strain rates (0.001–0.1 s⁻¹). The DIC full-field strain analysis reveals that the clamping fixture significantly influences the tensile deformation mode of the anti-collision ring by constraining its inner wall movement, thereby altering strain distribution patterns. Despite exhibiting a corrosion gradient from severe underwater degradation to minimal surface weathering, all tested rings demonstrated consistent mechanical performance, verifying the robust protective capability of the rubber coating in marine service conditions. Full article

This paper, based on the Johnson–Cook damage model, investigates the damage mechanism of high-strength steel tailor welded blanks (TWBs) (Usibor1500P and Ductibor500) during the forming process. Initially, specimens with varying notch sizes were designed and fabricated to perform uniaxial tensile tests to determine their mechanical properties. Then, the deformation process of the notched specimens was simulated using finite element software, revealing the distribution and variation of stress triaxiality at the fracture surface. By combining both experimental and simulation data, the parameters of the Johnson–Cook (J–C) damage model were calibrated, and the effects of temperature, strain rate, and stress triaxiality on material fracture behavior were further analyzed. Based on finite element analysis, the relevant coefficients for stress triaxiality, strain rate, and temperature were systematically calibrated, successfully establishing a J–C fracture criterion for TWB welds, Usibor1500P, and Ductibor500 high-strength steels. Finally, the calibrated damage model was further validated through the Nakajima-type bulge test, and the simulated Forming Limit Diagram (FLD) closely matched the experimental data. The results show that the analysis based on the J–C damage model can effectively predict the fracture behavior of tailor welded blanks (TWB) during the forming process. This study provides reliable numerical predictions for the damage behavior of high-strength steel laser-customized welded sheets and offers a theoretical basis for engineering design and material performance optimization. Full article

The automatic feeding device is crucial in grassland livestock farming, enhancing feeding efficiency, ensuring regular and accurate feed delivery, minimizing waste, and reducing costs. The shape and size of pellet feed render it particularly suitable for the delivery mechanism of automated feeding troughs. The uniformity of pellet flow is a critical factor in the study of automatic feeding troughs, and optimizing the movement characteristics of the pellets contributes to enhanced operational efficiency of the equipment. However, existing research often lacks a systematic analysis of the pellet size characteristics (such as diameter and length) and flow behavior differences in pellet feed, which limits the practical application of feed troughs. This study optimized the angle of repose and structural parameters of the feeding trough using Matlab simulations and discrete element modeling. It explored how the stock bin slope and baffle opening height influence pellet feed flow characteristics. A programmable logic controller (PLC) and human–machine interface (HMI) were used for precise timing and quantitative feeding, validating the design’s practicality. The results indicated that the Matlab method could calibrate the Johnson–Kendall–Roberts (JKR) model’s surface energy. The optimal slope was found to be 63°, with optimal baffle heights of 28 mm for fine and medium pellets and 30 mm for coarse pellets. The experimental metrics showed relative errors of 3.5%, 2.8%, and 4.2% (for average feed rate) and 8.2%, 7.3%, and 1.2% (for flow time). The automatic feeding trough showed a feeding error of 0.3% with PLC-HMI. This study’s optimization of the automatic feeding trough offers a strong foundation and guidance for efficient, accurate pellet feed distribution. Full article

Background/Objectives: The combination drug sulfamethoxazole/trimethoprim (ST) is a broad-spectrum antibiotic used against various infections; however, it is associated with several serious adverse events. The ST package inserts contain warnings about these adverse events. However, warnings vary internationally, and specific measures to address ST-related adverse events are unclear. Therefore, we aimed to comprehensively evaluate ST-related adverse events using the Japanese Adverse Drug Event Report (JADER) database and analyze the onset time for each event. Methods: Adverse events due to ST were analyzed using the JADER database between April 2004 and June 2023. The reported odds ratio and 95% confidence interval (95% confidence interval [CI]) were calculated, with a signal detected if the 95% CI lower limit exceeded 1. The Weibull distribution was used to characterize the onset time of adverse events with detected signals. Results: The total number of cases in the JADER database during the study period was 862,952, and the number of adverse events involving ST as a suspected drug was 4203. Adverse events associated with ST include hyperkalemia, syndrome of inappropriate antidiuretic hormone secretion, hematopoietic cytopenia, acute renal failure, hypoglycemia, disseminated intravascular coagulation syndrome, hepatic disorder, and the Stevens–Johnson syndrome/toxic epidermal necrolysis. Conclusions: Weibull analysis indicated an early failure-type onset time for all adverse events, suggesting the need for intensive adverse event monitoring of ST, especially in the first month of use. These findings may support revising drug package inserts in Japan to better reflect the identified risks. Full article

The distribution of Amaryllidaceae alkaloids, with a focus on their chemodiversity, has been reported previously, but not at a genera-wide diversity level. This review provides a comprehensive survey of the occurrence of Amaryllidaceae alkaloids across the genera of the Amaryllidaceae family. This survey is taxonomically guided by the National Center for Biotechnology Information (NCBI) Taxonomy Browser, with targeted keyword searches conducted in the Chemical Abstracts Service (CAS) SciFinder-n and PubMed. The family Amaryllidaceae comprises over 1214 species across three subfamilies: Agapanthoideae (1 genus, 5 species), Allioideae (3 genera plus 11 subgenera, 617 species), and Amaryllidoideae (58 genera plus 13 subgenera, 592 species). Amaryllidaceae alkaloids have been identified exclusively in 36 of the 58 genera and 6 of the 13 subgenera within the Amaryllidoideae subfamily. To date, more than 600 Amaryllidaceae alkaloids have been isolated, predominantly from this subfamily—hence the designation “Amaryllidaceae alkaloids”. These alkaloids display a wide spectrum of biological activities, including acetylcholinesterase inhibition, anti-inflammatory, antioxidant, antimicrobial, antidiabetic, and anticancer effects. A notable example is galanthamine (also known as galantamine), an FDA-approved drug marketed under the brand names Reminyl™ (Janssen Research Foundation, Beerse, Belgium, 2001) and Razadyne™ (Johnson & Johnson Pharmaceutical Research, New Brunswick, NJ, USA, 2004) for the treatment of mild to moderate Alzheimer’s disease, due to its potent acetylcholinesterase-inhibitory activity. Galanthamine has been isolated from species belonging to the genera Cyrtanthus, Galanthus, Leucojum, Lycoris, Narcissus, Ungernia, Chlidanthus, Crinum, Eucharis, Eustephia, Pancratium, and Phaedranassa. Lycorine is another widely distributed alkaloid found across multiple genera, and it has been extensively studied for its diverse bioactivities. Given the remarkable chemical diversity and bioactivity of Amaryllidaceae alkaloids, along with the many underexplored genera and species, further research into Amaryllidaceae species and their alkaloids is strongly warranted to support the discovery and development of novel therapeutic agents. Full article

This study investigates the effects of Laser Shock Peening (LSP) on residual stress distribution and surface deformation using a Finite Element Method (FEM) model. LSP is a surface treatment process that generates compressive residual stress by applying high-energy laser pulses over nanosecond timescales. The study aims to analyze the impact of key parameters, specifically laser spot overlap rate and power density, on the induced residual stress and surface deformation. A Design of Experiment (DOE) approach was used to systematically vary these parameters. These simulations were performed using the ANSYS Explicit Dynamics FEM with a Johnson–Cook material model to capture the nonlinear constitutive behavior. The research analyzes the distribution of residual stress and surface deformation caused by LSP. Increasing laser spot overlap and power density leads to higher compressive residual stress and surface deformation, revealing two distinct behavioral outcomes: either deep compressive stress with minimal deformation or a transition from compressive to tensile stress followed by significant surface deformation and a subsequent return to compressive stress. The results demonstrate strong agreement with existing experimental data presented in the literature. This study contributes novel insights into the interaction between LSP parameters and their effects on material properties, with implications for understanding LSP techniques in practical applications. The triangular pulse model and dual-overlap analysis offer a novel simulation strategy for optimizing LSP parameters in stainless steel. Full article

Boron steel welded tubes show strong potential as blanks in the integrated hot gas forming–quenching process for fabricating complex thin-walled automotive parts. Nonetheless, the non-uniform characteristics of the base metal and the weld in the high-heat welded tube can result in uneven deformation during the bulging process. This inconsistency hampers precise predictions of the deformation behavior of the welded tubes at high temperatures. Accordingly, this research explored the flow characteristics and mechanical properties of PHS1500 boron steel welded tubes. This research was conducted at 850 °C and 900 °C, with strain rates of 0.01 s⁻¹–1 s⁻¹. The Johnson–Cook model was modified for both the base metal and the weld using experimental stress–strain data. Meanwhile, to assess the model precisions, the correlation coefficient r and the average absolute relative error (AARE) were employed. Finally, hot gas forming of PHS1500 boron steel welded tubular parts with complex shapes was predicted through a finite element analysis. This research showed a positive correlation of the strain rate with both the yield and tensile strengths in the base metal and the weld. The average yield strength and tensile strength of the weld were 12.8% and 3.9% higher than those of the base metal, respectively. The r and AARE of the modified Johnson–Cook constitutive model for the base metal’s and the weld’s flow stress were 0.99 and 2.23% and 0.982 and 5.31%, respectively. The maximum deviation in the predictions of the distribution of the wall thickness of a typical cross-section of the formed complex-shaped tubular parts was less than 8%. Full article

Free-Space Optical (FSO) communication systems operating in arid regions, especially those envisioned for current and future 5G/6G networks, are significantly affected by dust storms, which cause signal attenuation and service disruptions. While previous studies have proposed deterministic models to characterize attenuation in both controlled and real environments, probabilistic modeling approaches remain largely unexplored, particularly for capturing the variability of FSO signal attenuation under dust conditions. This study proposes a probabilistic model for FSO signal attenuation developed from experiments conducted in a repeatable and well-characterized controlled dust chamber. The chamber-based setup allowed precise manipulation of dust visibility levels and consistent data collection, serving as a benchmark for statistical modeling. We analyzed the measurements to fit appropriate probability distributions for modeling the signal attenuation as a random variable. The empirical data were fitted to several candidate distributions, and the Johnson SB distribution consistently achieved superior performance with $R^2\ge 0.95$ and RMSE and MAE values close to zero across all dust conditions. The results offer a foundational framework for modeling dust-induced attenuation as a random process, providing statistical bounds for FSO link planning in desert environments. Full article

This study examines the impact that fat-tailed distributions of the spread residuals have on the optimal orders for pairs trading of stocks and cryptocurrencies. Using daily data from selected pairs, the spread dynamics has been modeled through a mean-reverting Ornstein–Uhlenbeck process and investigates how deviations from normality affect strategy design and profitability. Specifically, we compared four fat-tailed distributions—Lévy stable, generalized hyperbolic, Johnson’s S_U, and non-centered Student’s t—and showed how they modify optimal entry and exit thresholds, and performance metrics. The main findings reveal that the proposed pairs trading strategy correctly captures some key stylized facts of residual spreads such as large jumps, skewness, and excess Kurtosis. Interestingly, we considered regime-switching behaviors to account for structural changes in market dynamics, providing empirical evidence that optimal trading rules are regime-dependent and significantly influenced by the residual distribution’s tail behavior. Unlike conventional approaches, we optimized the entry signal and link heavy tails not only to volatility clustering but also to the nonlinearity in switching regimes. These findings suggest the need to account for distributional properties and dynamic regimes when designing robust pairs trading strategies, providing a more realistic and effective framework of these strategies in highly volatile and non-normal markets. Full article

Additive Manufacturing (AM) has become a revolutionary technology in manufacturing, attracting considerable attention in industrial applications recently. It allows for intricate fabrication, reduces material waste, offers design flexibility, and has economic implications. Nonetheless, the residual stresses generated during the AM process and their effects on microstructural evolution and material properties continue to pose significant challenges hindering its advancement. This paper investigates the evolution of microstructures, focusing on texture and grain size as influenced by processing parameters. It examines how these factors affect the performance of multi-phase materials, specifically in terms of elastic modulus, Poisson’s ratio, and yield strength, leading to variations in residual stress through analytical simulation. The authors developed a thermal model that considers heat transfer boundaries and the geometry of the molten pool. They simulated grain size by considering the heating and cooling processes, including thermal stress, the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, and grain refinement. The texture was simulated using the Columnar-to-Equiaxed Transition (CET) model, thermal dynamics, and Bunge calculations. The self-consistency model determines the properties based on the established texture distribution. Finally, both microstructure-affected and non-affected residual stresses were modeled and compared. Two gaps between microstructure-affected residual stress and non-affected analytical models appear at the depths of 0.02 mm and 0.078 mm. The results indicate that controlling process parameters and optimizing microstructures can effectively reduce residual stresses, significantly enhancing the overall performance of AM components. Hence, this work provides a more accurate analytical residual stress model and lays the foundation for better control of residual stress in the AM industry. Full article

Friction has a significant impact on chip formation, so modeling it accurately is crucial in numerical cutting simulations. However, there is still controversy regarding the application scope and effectiveness of various friction models. A two-dimensional orthogonal cutting thermomechanical coupled finite element model is established. Critical strain values, recrystallization temperature, and recrystallization flow stress are introduced, and a power-law-modified softening coefficient is used to modify the standard Johnson–Cook constitutive model to simulate material mechanical properties. Zorev’s friction model, velocity-dependent friction model, and temperature-dependent friction model are separately employed to describe the friction behavior between the tool and workpiece. The contact and friction characteristics between the workpiece and tool, material damage, and temperature field are evaluated. Predicted cutting forces are compared and analyzed with experimental values. The friction coefficient can adjust the contact length between the tool and chip, the high-temperature range on the tool surface, and the fluctuation of temperature throughout the entire cutting process. The friction coefficient is more sensitive to sliding velocity, and the temperature distribution is more sensitive to the friction model than to different working conditions. Whether by modifying the friction coefficient or maximum friction shear stress, and regardless of whether adding parameters affected by velocity or temperature changes the fluctuation range, period, and local peaks of the cutting force prediction curve, improving the accuracy of predictions within certain working condition ranges to some extent. However, the overall trend of error fluctuations obtained from these friction models is similar, and the accuracy of predictions from these friction models tends to become more inaccurate with increasing cutting thickness. Full article