Search Results (755)

Relay protection devices must operate continuously throughout the year without anomalies. With the integration of advanced technology and process chips in secondary equipment, new risks need to be addressed to ensure the reliability of these relay protection devices. One such risk is the impact of α-particles inducing single event effects (SEEs) on the secondary equipment. To date, there has been limited assessment of the effects of α-particles on relay protection devices from a system perspective. This study evaluates the impact of SEE on relay protection devices through a Monte Carlo simulation, which is verified by α-particle radiation, fault injection, and fault tree analysis. It discusses the influence of SEEs with and without hardening measures in place. Additionally, this study examines the soft error probability when the target processor runs both general workloads and specific application workloads. The current research proposes a low-cost and effective reliability assessment method for secondary equipment considering single event effects. The findings provide new insights for the enhancement of future electric power grid systems. Full article

Field implementations of fully underground sensor networks face many practical challenges that have limited their overall adoption. Power management is a commonly cited issue, as operators are required to either repeatedly excavate batteries for recharging or develop complex underground power infrastructures. Prior works have proposed wireless inductive power transfer (IPT) as a potential solution to these power management issues, but misalignment is a persistent issue in IPT systems, particularly in applications involving moving vehicles or obscured (e.g., underground) coils. This paper presents an automated methodology to sense misalignments and align IPT coils using robotic actuators and sequential Monte Carlo methods. The misalignment of a Class EF inverter-driven IPT system was modeled by tracking changes as its coils move apart laterally and distally. These models were integrated with particle filters to estimate the location of a hidden coil in 3D, given a sequence of sensor measurements. During laboratory tests on a Cartesian robot, these algorithms aligned the IPT system within 1 cm (0.025 coil diameters) of peak lateral alignment. On average, the alignment algorithms required less than four sensor measurements for localization. After laboratory testing, this approach was implemented with an agricultural sensor platform at the Utah Agricultural Experiment Station in Kaysville, Utah. In this implementation, a buried sensor platform was successfully charged using an aboveground, vehicle-mounted transmitter. Overall, this work contributes to the field of underground sensor networks by successfully integrating a self-aligning wireless power delivery system with existing agricultural infrastructure. Furthermore, the alignment strategy presented in this work accomplishes coil misalignment correction without the need for complex sensor or coil architectures. Full article

Pharmaceutical waste is a type of bio-waste inevitably generated by the pharmaceutical industry, often due to regulatory changes, product deterioration, or expiration. However, their collection and valorization can be approached from a sustainable perspective, offering potential energy-efficient solutions. In this work, the expired Eslicarbazepine acetate drug (ESLD) was utilized as a sustainable anticorrosive agent against mild steel in a 3 M HCl wash solution. Experimental tests combined with theoretical Density Functional Theory (DFT) and Monte Carlo (MC) simulations revealed the corrosion inhibition potential of ESLD. The gasometrical results revealed a high inhibition efficiency rate of 98% upon increases in concentration of expired ESLD from 0.25 to 1.00 mg·L⁻¹, whereas hydrogen gas evolution decreased to 0.7 mL. An impedance investigation evidenced the pivotal role of charge transfer in reducing the disintegration process. As per DFT computations and MC simulation, electron-rich elements in the expired ESLD were key in controlling the dissolution through the adsorption process. Contact angle studies revealed that the increment in the contact angle from 61° to 80° in the presence of expired ESLD validates the chemical, electrochemical, and computational results. This approach not only mitigates pharmaceutical pollution, but also exemplifies the integration of green chemistry principles into corrosion protection, contributing to energy-efficient and sustainable industrial practices. Full article

This study proposes a time-dependent reliability analysis method for aqueduct structures based on concrete carbonation and finite element analysis. The primary goal of this study is to improve the reliability assessment of reinforced concrete aqueducts by incorporating environmental factors such as carbonation over time. First, a three-dimensional finite element model of a reinforced concrete aqueduct is established using the Midas 2022 Civil software, incorporating a time-varying function derived from a predictive model of concrete carbonation depth. Point estimation is then integrated with structural finite element analysis to calculate the first four moments of random variables as functions of concrete carbonation. Additionally, the original performance function is transformed into a normal distribution using dual power transformation and the Jarque–Bera test. The high-order unscented transformation (HUT) is subsequently employed to estimate the first four moments of the transformed performance function, facilitating the calculation of time-varying reliability indices for the carbonated concrete aqueduct. Based on the time-varying reliability index data, a reliability function corresponding to different time points is fitted and applied to service life prediction. The results demonstrate that the proposed method effectively reduces large errors associated with the fourth-moment method in calculating large reliability indices. Furthermore, the comparison with Monte Carlo simulation (MCS) results validates the high efficiency and accuracy of the proposed method, offering a valuable tool for addressing the reliability challenges of aqueducts exposed to carbonation and other environmental factors over time. Full article

Renewable energy communities (RECs) are widely regarded as a transformative opportunity to enhance the management of electricity distribution networks, benefiting the system as a whole and its participants through local energy production, increased self-consumption, and empowering citizens. However, their proliferation introduces significant challenges for distribution system management, particularly at the low-voltage (LV) level, where participants are primarily located. Despite its critical role, the LV network is often overlooked in favor of studies focusing on the system-level impacts. This paper addresses this gap by evaluating the impact of RECs on LV networks and the broader distribution system. The study analyzes various LV networks representative of the Italian context, encompassing both rural and urban areas. By leveraging the software tool OpenDSS and Monte Carlo simulations over an entire year, the analysis captures the inherent variability of load demand and photovoltaic generation, as well as the resulting network imbalances under diverse policy scenarios. The findings reveal that the increasing level of self-consumption could significantly challenge distribution network operation, limiting also the sourcing of flexibility. These results underscore the necessity for advanced management strategies and targeted investments in grid flexibility to ensure the reliability and efficiency of distribution networks integrating RECs. Full article

Species richness is a crucial factor in maintaining ecological balance and promoting ecosystem services. However, simulating population dynamics is a complex task that requires a comprehensive understanding of ecological systems. The current tools for wildlife research face three major challenges: insufficient multi-view assessment, a high learning curve, and a lack of seamless secondary development with Python. To address these issues, we developed a novel software tool named WAPET (Wildlife Analysis and Population Ecology Tool) (Python 3.10.12). WAPET integrates Monte Carlo simulation with ecological models, including Logistic Growth, Random Walk, and Cellular Automata, to provide a multi-perspective assessment of ecological systems. Our tool employs a fully parameterized input paradigm, allowing users without coding to easily explore simulations. Additionally, WAPET’s development is entirely Python-based, utilizing PySide6 and Mesa libraries and enabling seamless development in Python environments. Our contributions include the following: (I) integrating multiple ecological models for a comprehensive understanding of ecological processes, (II) developing a no-code mode of human–computer interaction for biodiversity stakeholders and researchers, and (III) implementing a Python-based framework for easy extension and customization. WAPET bridges the gap between comprehensive modeling capabilities and user-friendly interfaces, positioning itself as a versatile tool for both experienced researchers and non-computational stakeholders in biodiversity decision-making processes. Full article

This study presents a novel rod–cable hybrid planar cable-driven parallel robot inspired by the biological synergy of bones and muscles. The design integrates rigid rods and flexible cables to enhance structural stability and precision in motion control. The rods emulate bones, providing foundational support, while the cables mimic muscles, driving motion through coordinated tension. This design enables planar motions with three degrees of freedom, and a structural configuration that mitigates sagging and vibration for improved stability and accuracy by introducing rigid structure. The study develops detailed kinematic models, including Jacobian analysis for motion control, and evaluates the workspace using geometric and Monte Carlo methods. Full article

Among the coronal mass ejections (CMEs) and solar proton events (SPEs) frequently observed by near-Earth spacecraft, the SPE that occurred on 28 October 2021 stands out as a remarkable research event. This is due to the infrequency of reported ground-level enhancements it induced. The CSES (China seismo-electromagnetic satellite) is equipped with high-energy particle detectors, namely, HEPP and HEPD, capable of measuring protons within an energy range of 2 MeV to 143 MeV. These detectors provide valuable opportunities for studying solar activity. By utilizing the Monte Carlo method to simulate the pile-up effect and accounting for the detector’s dead time, with the assistance of real-time incident counting rates, we successfully corrected the spectra in the 10–50 MeV range. The energy spectrum is important for understanding solar proton events. We used the data from the HEPP (high-energy particle package) and HEPD (high-energy particle detector) to obtain the total event-integrated spectrum, which possessed good continuity. Additionally, we compared the observations from the CSES with those from the NOAA satellite and achieved reasonable agreement. We also searched for ground-based responses to this solar activity in China and discovered Forbush decreases detected by the Yang Ba Jing Muon Telescope experiment. In conclusion, the HEPP and HEPD can effectively combine to study solar activity and obtain a smooth and consistent energy spectrum of protons across a very wide energy range. Full article

The increasing integration of renewable energy sources (RESs) into power systems has introduced new complexities due to the inherent variability and uncertainty of these energy sources. In addition to the uncertainty in RES generation, the demand-side load of power systems is also subject to fluctuations, further complicating system operations. Addressing these challenges requires effective modeling and assessment techniques to quantify and mitigate the risks associated with system uncertainties. This paper evaluates the impact of various uncertainty modeling techniques on power system reliability with wind farm integration. Furthermore, this paper reviews the state of the art of the various uncertainty and risk modeling techniques in power systems. Through a detailed case study, the performance of these techniques in modeling uncertainties of wind speeds is analyzed. Based on the results, the integration of wind turbines improves the system’s overall reliability when there is a reduction in conventional power plants (CPPs)’ generation, which are dispatchable energy sources providing a stable and flexible supply. However, the generation of wind farms is associated with uncertainty. The results show Monte Carlo simulation combined with the K-Means method is consistently a more accurate uncertainty model for wind speeds, closely aligning with real-case scenarios, compared to other methods such as Markov Chain Monte Carlo (MCMC), robust optimization (RO), and information-gap decision theory (IGDT). Full article

This paper analyzes the behavior of the entropy of a nuclear fuel rod under deep burnup conditions, beyond standard operational ranges, reaching up to 60 years. The evolution of the neutron source distribution in a pressurized water reactor (PWR) fuel pin was analyzed using the Monte Carlo method and Shannon information entropy. To maintain proper statistics, a novel scaling method was developed, adjusting the neutron population based on the fission rate. By integrating reactor physics with information theory, this work aimed at the deeper understanding of nuclear fuel behavior under extreme burnup conditions. The results show a “U-shaped” entropy evolution: an initial decrease due to self-organization, followed by stabilization and eventual increase due to degradation. A minimum entropy state is reached after approximately 45 years of pin operation, showing a steady-state condition with no entropy change. This point may indicate a physical limit for fuel utilization. Beyond this point, entropy rises, reflecting system degradation and lower energy efficiency. The results show that entropy analysis can provide valuable insights into fuel behavior and operational limits. The proposed scaling method may also serve to control a Monte Carlo simulation, especially for the analysis of long-life reactors. Full article

The Pamir is located on the northwestern margin of the Tibetan Plateau, which is an area of intense continental deformation and part of the famous India–Himalaya collision zone. The dominant structural deformation in the eastern Pamir is characterized by a 250 km long east–west extensional fault system, known as the Kongur Shan extensional system (KSES), which has developed a series of faults with different orientations and characteristics, resulting in highly complex structural deformation and lacking sufficient geodetic constraints. We collected Sentinel-1 SAR data from December 2016 to March 2023, obtained high-resolution ascending and descending LOS velocities and 3D deformation fields, and combined them with GPS data to constrain the current motion characteristics of the northeastern Pamirs for the first time. Based on the two-dimensional screw dislocation model and using the Bayesian Markov chain Monte Carlo (MCMC) inversion method, the kinematic parameters of the fault were calculated, revealing the fault kinematic characteristics in this region. Our results demonstrate that the present-day deformation of the KSES is dominated by nearly E–W extension, with maximum extensional motion concentrated in its central segment, reaching peak extension rates of ~7.59 mm/yr corresponding to the Kongur Shan. The right-lateral Muji fault at the northern end exhibits equivalent rates of extensional motion with a relatively shallow locking depth. The strike-slip rate along the Muji fault gradually increases from west to east, ranging approximately between 4 and 6 mm/yr, significantly influenced by the eastern normal fault. The Tahman fault (TKF) at the southernmost end of the KSES shows an extension rate of ~1.5 mm/yr accompanied by minor strike-slip motion. The Kashi anticline is approaching stability, while the Mushi anticline along the eastern Pamir frontal thrust (PFT) remains active with continuous uplift at ~2 mm/yr, indicating that deformation along the Tarim Basin–Tian Shan boundary has propagated southward from the South Tian Shan thrust (STST). Overall, this study demonstrates the effectiveness of integrated InSAR and GPS data in constraining contemporary deformation patterns along the northeastern Pamir margin, contributing to our understanding of the region’s tectonic characteristics. Full article

This study introduces the Lindley Stochastic Frontier Analysis—LSFA model, a novel approach that incorporates the Lindley distribution to enhance the flexibility and accuracy of efficiency estimation. The LSFA model is compared against traditional SFA models, including the half-normal, exponential, and gamma models, using advanced numerical methods such as the Gauss–Hermite Quadrature, Monte Carlo Integration, and Simulated Maximum Likelihood Estimation for parameter estimation. Simulation studies revealed that the LSFA model outperforms in scenarios involving small sample sizes and complex, skewed distributions, particularly those characterized by gamma distributions. In contrast, traditional models such as the half-normal model perform better in larger samples and simpler settings, while the gamma model is particularly effective under exponential inefficiency distributions. Among the numerical techniques, the Gauss–Hermite Quadrature demonstrates a strong performance for half-normal distributions, the Monte Carlo Integration offers consistent results across models, and the Simulated Maximum Likelihood Estimation shows robustness in handling gamma and Lindley distributions despite higher errors in simpler cases. The application to a banking dataset assessed the performance of 12 commercial banks pre-COVID-19 and during COVID-19, demonstrating LSFA’s superior ability to handle skewed and intricate data structures. LSFA achieved the best overall reliability in terms of the root mean square error and bias, while the gamma model emerged as the most accurate for minimizing absolute and percentage errors. These results highlight LSFA’s potential for evaluating efficiency during economic shocks, such as the COVID-19 pandemic, where data patterns may deviate from standard assumptions. This study highlights the advantages of the Lindley distribution in capturing non-standard inefficiency patterns, offering a valuable alternative to simpler distributions like the exponential and half-normal models. However, the LSFA model’s increased computational complexity highlights the need for advanced numerical techniques. Future research may explore the integration of generalized Lindley distributions to enhance model adaptability with enriched numerical optimization to establish its effectiveness across diverse datasets. Full article

I propose a possible way to introduce the effect of temperature (defined through the virial theorem) into Einstein’s theory of general relativity. This requires the computation of a path integral on a ten-dimensional flat space in a four-dimensional spacetime lattice. Standard path integral Monte Carlo methods can be used to compute this. Full article

Rainfall-induced landslides are widespread in Indonesia, particularly in West Java, where volcanic residual soils are typically stable but may become unstable during heavy rainfall. This study aims to back analyze the geotechnical factors contributing to the Cimanggung landslide in 2021. The methods applied in this study include site investigations, laboratory testing, and numerical modeling. We performed deterministic, coupled seepage-slope stability analysis and Monte Carlo probabilistic analysis to assess the slope performance prior to and after rainfall infiltration. The results reveal that the initial water level significantly affects slope stability, and heavy rainfall infiltration triggered the landslide’s initiation. The deep water table (over 20 m below ground level) maintains the slope stability, and increasing the water table to 16 m compromises its stability. Heavy rainfall infiltration reduces suction in the unsaturated zone, decreasing the shear strength and triggering landslides. The heavy rainfall infiltration did not penetrate deep enough to raise the water table; rather, poor urban drainage on the upper slope caused it. Rainfall infiltration caused wetting in the upper zone, weakening the slope and causing loss of support. It is recommended that effective drainage management and integrated slope monitoring be applied to mitigate landslide risks in this region. Full article

This study investigates the dual dynamics of investment shocks and policy responses in stabilizing South Korea’s macroeconomy during the COVID-19 pandemic, utilizing a Bayesian DSGE framework. The model integrates sophisticated mathematical components, including stochastic differential equations, Bayesian inference, and impulse response functions, to analyze the transmission mechanisms of investment shocks and the relative efficacy of fiscal and monetary interventions. The estimation is conducted through Markov Chain Monte Carlo simulations. Using data from the first quarter of 2020 to the first quarter of 2023, the analysis quantifies the pandemic-induced shocks’ impact on critical macroeconomic indicators, including enterprise output, household consumption, employment, and investment. The findings reveal that heightened investment costs significantly constrained economic performance, with fiscal measures, such as increased government spending and targeted stimulus packages, demonstrating superior stabilization effects compared to monetary interventions. These results emphasize the importance of well-coordinated policy responses in mitigating economic disruptions and enhancing resilience during crises. This study not only provides novel insights into the mathematical modeling of economic stabilization strategies but also offers actionable recommendations for policymakers navigating pandemic-induced challenges. Full article