Search Results (34,907)

Miniaturized pressure sensors fabricated via micro-electro-mechanical systems (MEMSs) technology are ubiquitous in modern applications. However, the massively produced MEMS pressure sensors, prior to being practically used, need to be calibrated one by one to eliminate or minimize nonlinearity and zero drift. This paper presents a systematic design for the testing and calibration process of MEMS-based absolute pressure sensors. Firstly, a numerical analysis is carried out using finite element method (FEM) simulation, which verifies the accuracy of the temperature control of the physical calibration system. The simulation results reveal a slight non-uniformity of temperature distribution, which is then taken into consideration in the calibration algorithm. Secondly, deploying a home-made calibration system, the MEMS pressure sensors are tested automatically and rapidly. The experimental results show that each batch, which consists of nine sensors, can be calibrated in 80 min. The linearity and temperature coefficient (TC) of the pressure sensors are reduced from 46.5% full-scale (FS) and −1.35 × 10⁻⁴ V·K⁻¹ to 1.5% FS and −8.8 × 10⁻⁷ V·K⁻¹. Full article

Power flow analysis of low-voltage network (LVN) is one of the most crucial methods for achieving refined management of such networks. To accurately calculate the three-phase (TP) probabilistic power flow (PPF) distribution in LVN, this paper first draws on the injection-type Newton method; by leveraging TP power measurements relative to the neutral point obtained from smart meters, the injected power is expressed in terms of injected current equations, thereby establishing TP power flow models for various components within the low-voltage distribution transformer area grid. Subsequently, addressing the stochastic fluctuation models of load power and photovoltaic output, this paper employs conventional numerical methods and an improved Latin hypercube sampling technique. Utilizing linearized power flow equations and based on the improved semi-invariant method (SIM) and Gram–Charlier (GC) series fitting, a calculation method for three-phase PPF in low-voltage distribution transformer area grids using the improved semi-invariant is proposed. Finally, simulations of the proposed three-phase PPF method are conducted using the IEEE-13 node distribution system. The simulation results demonstrate that the proposed method can effectively perform three-phase PPF calculations for the distribution transformer area grid and accurately obtain probabilistic distribution information of the TP power flow within the grid. Full article

Urban lifeline Natech events are coupled systems composed of multiple risks and entities with complex dynamic transmission chains. Predicting risk evolution probabilities is the core task for achieving the safety management of urban lifeline Natech events. First, the risk evolution mechanism is analyzed, where urban lifeline Natech events exhibit spatial evolution characteristics, which involves dissecting the parallel and synergistic effects of risk evolution in spatial dimensions. Next, based on fitting marginal probability distribution functions for natural hazard and urban lifeline risk evolution, a Multi-dimensional Copula (MdC) function for the joint probability distribution of urban lifeline Natech event risk evolution is constructed. Building upon the MdC function, a Markov Chain Monte Carlo (MCMC) model for predicting risk evolution probabilities of urban lifeline Natech events is developed using the Metropolis–Hastings (M-H) algorithm and Gibbs sampling. Finally, taking the 2021 Zhengzhou ‘7·20’ catastrophic rainstorm as a case study, joint probability distribution functions for risk evolution under Rainfall-Wind speed scenarios are fitted for traffic, electric, communication, water supply, and drainage systems (including different risk transmission chains). Numerical simulations of joint probability distributions for risk evolution are conducted, and visualizations of joint probability predictions for risk evolution are generated. Full article

Numerical simulation has played a crucial role in modeling the behavior of natural gas hydrate (NGH). However, the existing numerical simulators worldwide have exhibited limitations in functionality, convergence, and computational efficiency. In this study, we present a novel numerical simulator, GPSFlow/Hydrate, for modeling the behavior of hydrate-bearing geologic systems and for addressing the limitations in the existing simulators. It is capable of simulating multiphase and multicomponent flow in hydrate-bearing subsurface reservoirs under ambient conditions. The simulator incorporates multiple mass components, various phases, as well as heat transfer, and sand is treated as an independent non-Newtonian flow and modeled as a Bingham fluid. The CH₄ or binary/ternary gas hydrate dissociation or formation, phase changes, and corresponding thermal effects are fully accounted for, as well as various hydrate formation and dissociation mechanisms, such as depressurization, thermal stimulation, and sand flow behavior. In terms of computation, the simulator utilizes a domain decomposition technology to achieve hybrid parallel computing through the use of distributed memory and shared memory. The verification of the GPSFlow/Hydrate simulator are evaluated through two 1D simulation cases, a sand flow simulation case, and five 3D gas production cases. A comparison of the 1D cases with various numerical simulators demonstrated the reliability of GPSFlow/Hydrate, while its application in modeling the sand flow further highlighted its capability to address the challenges of gas hydrate exploitation and its potential for broader practical use. Several successful 3D gas hydrate reservoir simulation cases, based on parameters from the Shenhu region of the South China Sea, revealed the correlation of initial hydrate saturation and reservoir condition with hydrate decomposition and gas production performance. Furthermore, multithread parallel computing achieved a 2–4-fold increase in efficiency over single-thread approaches, ensuring accurate solutions for complex physical processes and large-scale grids. Overall, the development of GPSFlow/Hydrate constitutes a significant scientific contribution to understanding gas hydrate formation and decomposition mechanisms, as well as to advancing multicomponent flow migration modeling and gas hydrate resource development. Full article

Understanding the multi-crack coupling fracture behavior in brittle materials is particularly critical for aging dam infrastructure, where 78% of structural failures originate from crack network coalescence. In this study, we introduce the concepts of crack distance ratio (DR) and size ratio (SR) to describe the relationship between crack position and length and employ the discrete element method (DEM) for extensive numerical simulations. Specifically, a crack density function is introduced to assess microscale damage evolution, and the study systematically examines the macroscopic mechanical properties, failure modes, and microscale damage evolution of rock-like materials under varying DR and SR conditions. The results show that increasing the crack distance ratio and crack angle can inhibit the crack formation at the same tip of the prefabricated crack. The increase in the size ratio will promote the formation of prefabricated cracks on the same side. The increase in the distance ratio and size ratio significantly accelerate the rapid increase in crack density in the second stage. The crack angle provides the opposite effect. In the middle stage of loading, the growth rate of crack density decreases with the increase in crack angle. Overall, the size ratio has a greater influence on the evolution of microscopic damage. This research provides new insights into understanding and predicting the behavior of materials under complex stress conditions, thus contributing to the optimization of structural design and the improvement of engineering safety. Full article

Improving sowing quality is crucial for ensuring wheat emergence and healthy growth. To address issues of poor wheat sowing quality, such as uneven sowing depth and inadequate soil coverage, in the Yangtze River Delta region of China, this study systematically analyzed the effects of the implement’s structural and operational parameters on sowing quality. Based on this analysis, a double-shaft rotary tillage and double-press seeder was designed. Protrusions on the grooving press roller are used to form seed furrows, rotary tiller blades cover the seeds with soil, and the rear press roller compacts the soil. DEM-MBD (discrete element method–multibody dynamics) coupled simulations, combined with single-factor and central composite design (CCD) experiments, were conducted with seeding depth as the evaluation index and four experimental factors: the protrusion height on the press grooving roller, forward speed, seed mass in the seed box, and straw mulching amount. The optimal protrusion height was 29 mm. The effects of rotary tiller blade working depth, rotational speed, and forward speed on soil-covering mass and its coefficient of variation were evaluated through discrete element method (DEM) simulations. The optimal working depth and rotational speed were found to be 55 mm and 350 r·min⁻¹, respectively, based on single-factor and Box–Behnken Design experiments. Field experiments based on optimized parameters showed results consistent with the simulations. The qualified rate of seeding depth decreased as forward speed increased. The optimal forward speed was 4.5 km·h⁻¹, at which the average seeding depth was 25.7 mm, the qualified seeding depth rate was 90%, the soil-covering mass within a 50 cm² area was 143.2 g, and the coefficient of variation was 13.21%, meeting the requirements for wheat sowing operations. Full article

A novel dual-band dual-mode wearable button antenna for wireless body area network (WBAN) applications is proposed in this paper. The antenna ingeniously integrates a monopole structure and an optimized planar inverted-F antenna (PIFA) configuration in a shared radiator, enabling dual-mode operation with a compact size. In the low-frequency band, the monopole structure generates an omnidirectional radiation pattern, facilitating efficient on-body communication. Meanwhile, the PIFA structure in the high-frequency band exhibits directed radiation, optimizing off-body communication. To enhance bandwidth, a parasitic structure is incorporated into the design. Both numerical simulations and experimental measurements are conducted to evaluate the antenna’s bandwidth and radiation performance in free space and on-body environments, with results showing excellent agreement. The measured bandwidth of the antenna on the human tissue is 300 MHz (2.3–2.6 GHz) in the low-frequency band and 4.5 GHz (5.5–10 GHz) in the high-frequency band. The maximum radiation efficiency reaches 76% in the low band (2.4–2.4835 GHz) and 93% in the upper band (5.725–5.875 GHz). Additionally, the peak gain on the human body can achieve 2.5 dB and 6.9 dB for the low and upper bands, respectively. The results confirm that the antenna meets the design requirements for Industrial, Scientific, and Medical (ISM) band applications, making it a promising candidate for WBAN systems. Full article

The continuous-wave (CW) illuminator, whose fundamentals are related to the theoretical understanding of loop antennas loaded with ferrite materials, is a device which plays an important role in electromagnetic pulse (EMP) susceptibility assessment. However, existing theoretical formulas do not consider cases where ferrite materials are loaded into the loop antenna. This paper provides a new explicit theoretical formula for the impedance of a circular loop antenna loaded with ferrite materials for CW illuminator design, and explores the variation regularity of its input impedance. Loading ferrite materials affects the internal impedance of the loop antenna and forces some modifications to the classical calculation procedure, resulting in an asymptotic numerical calculation method and a closed-form solution. The full-wave simulation results from CST Studio Suite show a maximum error of less than 0.99%, compared to the classical theory. With ferrite material loaded, the input impedance of the loop antenna is significantly reduced and smoothed in a wide range of normalized radii. For a loop antenna with a fixed circumference, the input impedance indicates that the Q-factor decreases as the thickness of the ferrite material increases. Conversely, for a ferrite-loaded loop antenna with a constant material thickness, a larger loop circumference results in a higher Q-factor. In summary, this study provides a fast and accurate computational method for the input impedance design of CW illuminators, while also offering an effective tool for further research on the performance of ferrite-loaded loop antennas. Full article

This study aims to investigate the mechanical behavior of cement mortar and concrete through a hybrid approach that integrates artificial intelligence (AI) techniques with finite element modeling (FEM). Support Vector Machine (SVM) models with Radial Basis Function (RBF) and polynomial kernels, along with Multilayer Perceptron (MLP) neural networks, were employed to predict the compressive strength (Fc) and flexural strength (Fs) of cement mortar incorporating nano-silica (NS) and micro-silica (MS). The dataset comprises 89 samples characterized by six input parameters: water-to-cement ratio (W/C), sand-to-cement ratio (S/C), nano-silica-to-cement ratio (NS/C), micro-silica-to-cement ratio (MS/C), and curing age. Simultaneously, the axial compressive behavior of C20-grade concrete was numerically simulated using the Concrete Damage Plasticity (CDP) model in ABAQUS, with stress–strain responses benchmarked against the analytical models proposed by Mander, Hognestad, and Kent–Park. Due to the inherent limitations of the finite element software, it was not possible to define material models incorporating NS and MS; therefore, the simulations were conducted using the mechanical properties of conventional concrete. The SVM-RBF model demonstrated the highest predictive accuracy with RMSE values of 0.163 (R² = 0.993) for Fs and 0.422 (R² = 0.999) for Fc, while the Mander model showed the best agreement with experimental results among the FEM approaches. The study demonstrates that both the SVM-RBF and CDP-based modeling approaches serve as robust and complementary tools for accurately predicting the mechanical performance of cementitious composites. Furthermore, this research addresses the limitations of conventional FEM in capturing the effects of NS and MS, as well as the existing gap in integrated AI-FEM frameworks for blended cement mortars. Full article

We present some numerical results on piston and tilt detection by using the Young experiment with Genetic Algorithms (GAs). We have simulated the cophasing of a flat surface by following the experimental setup and the mathematical model for Optical Path Difference (OPD) in the Young experiment to characterize piston and tip–tilt misalignment images in the order of a few nanometers, considering diffraction effects and random noise of 5%. Thus, the best fitness obtained by the genetic algorithm is considered as a determining factor to decide a complete error measurement because the proposed algorithm is capable of extracting the values of piston and tilt separately, regardless of which error is present or both. As a result, we have developed a study on piston detection from (0.001, 10) mm with a tilt present in the same pattern from (0, $\lambda /2$) by using GAs embedded in a computational application. Full article

This study investigates the impact of different duct designs on the energy-harvesting performance of oscillating-wing systems in both partially and fully confined environments. Numerical simulations were conducted to examine the effects of straight, convergent–straight, and convergent–divergent duct configurations on the aerodynamic forces and overall energy extraction efficiency. Under partial confinement, the convergent–divergent duct demonstrated a significant improvement of 67.5% in power output over the ductless baseline configuration. This enhancement is attributed to the increased incoming flow velocity and amplified pressure difference around the wing, which improve the effectiveness of energy generation. However, the straight and convergent–straight ducts reduced the harvester’s performance due to the diminished flow velocity within each duct. Under full confinement, all duct configurations substantially enhanced energy-harvesting performance, with the convergent–straight duct providing the highest efficiency gain (84.9%). This improvement is primarily due to the increased velocity and pressure differential across the wing surfaces, which maximise the heaving force and overall energy generation performance. These findings highlight the critical role of duct geometry in optimising energy-harvesting performance, both in partially confined and fully confined flow environments. Full article

A key requirement in containing contagious diseases, like the COVID-19 pandemic, is the ability to efficiently carry out mass diagnosis over large populations, especially when testing resources are limited and rapid identification is essential for outbreak control. Some of the leading testing procedures, such as those utilizing qualitative polymerase chain reaction, involve using dedicated machinery which can simultaneously process a limited amount of samples. A candidate method to increase the test throughput is to examine pooled samples comprised of a mixture of samples from different patients. In this work, we study pooling-based tests which operate in a one-shot fashion, while providing an indication not solely on the presence of infection, but also on its level, without additional pool-tests, as often required in COVID-19 testing. As these requirements limit the application of traditional group-testing (GT) methods, we propose a multi-level GT scheme, which builds upon GT principles to enable accurate recovery using much fewer tests than patients, while operating in a one-shot manner and providing multi-level indications. We provide a theoretical analysis of the proposed scheme and characterize conditions under which the algorithm operates reliably and at affordable computational complexity. Our numerical results demonstrate that multi-level GT accurately and efficiently detects infection levels, while achieving improved performance and less pooled tests over previously proposed oneshot COVID-19 pooled-testing methods. Our simulations show that the efficient method proposed in this work can correctly identify the infected items and their infection levels with high probability at the known upper bound (for a maximum likelihood decoder in GT) on the number of tests. We also show that the method works well in practice when the number of infected items is not assumed to be known in advance. Full article

Free water surface constructed wetlands can be effective systems for contaminant removal, but their performance is sensitive to interactions among flow dynamics, vegetation, and bed topography. This study presents a numerical investigation into how heterogeneous bed topographies influence hydraulic and contaminant transport behavior in a rectangular wetland. Topographies were generated using a correlated pseudo-random pattern generator, and flow and solute transport were simulated with a two-dimensional, depth-averaged model. Residence time distributions and contaminant removal efficiencies were analyzed as functions of the variance and correlation length of the bed elevation. Results indicate that increasing the variability of bed elevation leads to greater dispersion in residence times, reducing hydraulic efficiency. Moreover, as the variability of bed elevation increases, so does the spread in hydraulic performance among wetlands with the same statistical topographic parameters, indicating a growing sensitivity of flow behavior to the specific spatial configurations of bed features. Larger spatial correlation lengths were found to reduce the residence time variance, as shorter correlation lengths promoted complex flow structures with lateral dead zones and internal islands. Contaminant removal efficiency, evaluated under the assumption of uniform vegetation, was influenced by bed topography, with variations becoming more pronounced under conditions of lower vegetation density. The results underscore the significant impact of bed topography on hydraulic behavior and contaminant removal performance, highlighting the importance of careful topographic design to ensure high wetland efficiency. Full article

Urban planning in arid climates must overcome numerous nonclimatic constraints that often result in outdoor thermal discomfort. This is particularly evident in Béchar, a city in southern Algeria known for its long, intense summers with temperatures frequently exceeding 45 °C. This study investigates the influence of urban morphology on thermal comfort and explores architectural and digital solutions to enhance energy performance in buildings. This research focuses on Béchar’s city center, where various urban configurations were analyzed using a multidisciplinary approach that combines typomorphological and climatic analysis with numerical simulations (ENVI-met 3.0 and TRNSYS 16). The results show that shaded zones near buildings have lower thermal loads (under +20 W/m²), while open areas may reach +100 W/m². The thermal comfort rate varies between 22% and 60%, depending on wall materials and occupancy patterns. High thermal inertia materials, such as stone and compressed stabilized earth blocks (CSEBs), reduce hot discomfort hours to under 1700 h/year but may increase cold discomfort. Combining these materials with targeted insulation improves thermal balance. Key recommendations include compact urban forms, vegetation, shading devices, and high-performance envelopes. Early integration of these strategies can significantly enhance thermal comfort and reduce energy demand in Saharan cities. Full article

To ensure the safe and reliable operation of hydrogen-blended natural gas (HBNG) pipelines in urban utility tunnels, this study conducted a comprehensive CFD simulation of the leakage and diffusion characteristics of HBNG in confined underground environments. Utilizing ANSYS CFD software (2024R1), a three-dimensional physical model of a utility tunnel was developed to investigate the influence of key parameters, such as leak sizes (4 mm, 6 mm, and 8 mm)—selected based on common small-orifice defects in utility tunnel pipelines (e.g., corrosion-induced pinholes and minor mechanical damage) and hydrogen blending ratios (HBR) ranging from 0% to 20%—a range aligned with current global HBNG demonstration projects (e.g., China’s “Medium-Term and Long-Term Plan for Hydrogen Energy Industry Development”) and ISO standards prioritizing 20% as a technically feasible upper limit for existing infrastructure, on HBNG diffusion behavior. The study also evaluated the adequacy of current accident ventilation standards. The findings show that as leak orifice size increases, the diffusion range of HBNG expands significantly, with a 31.5% increase in diffusion distance and an 18.5% reduction in alarm time as the orifice diameter grows from 4 mm to 8 mm. Furthermore, hydrogen blending accelerates gas diffusion, with each 5% increase in HBR shortening the alarm time by approximately 1.6 s and increasing equilibrium concentrations by 0.4% vol. The current ventilation standard (12 h⁻¹) was found to be insufficient to suppress concentrations below the 1% safety threshold when the HBR exceeds 5% or the orifice diameter exceeds 4 mm—thresholds derived from simulations showing that, under 12 h⁻¹ ventilation, equilibrium concentrations exceed the 1% safety threshold under these conditions. To address these gaps, this study proposes an adaptive ventilation strategy that uses variable-frequency drives to adjust ventilation rates in real time based on sensor feedback of gas concentrations, ensuring alignment with leakage conditions, thereby ensuring enhanced safety. These results provide crucial theoretical insights for the safe design of HBNG pipelines and ventilation optimization in utility tunnels. Full article