Search Results (2,272)

Complex engineering systems—such as ultra-long horizontal wells in energy exploitation and distributed rail transit infrastructure—operate under harsh physical and environmental conditions, where accurate physical modeling and real-time parameter estimation are essential for ensuring safety, efficiency, and reliability. Traditional empirical and black-box data-driven approaches often fail to account for the underlying physical mechanisms, thereby limiting interpretability and generalizability. To address this, we propose a unified framework that integrates physics-informed scenario-based modeling with data-driven parameter inversion. In the first stage, critical system parameters—such as friction coefficients in drill string movement or contact forces in rail–wheel interactions—are explicitly formulated based on mechanical theory, leveraging symmetries and boundary conditions to improve model structure and reduce computational complexity. In the second stage, model parameters are identified or updated through inverse modeling using historical or real-time field data, enhancing predictive performance and engineering insight. The proposed methodology is demonstrated through two representative cases. The first involves friction estimation during tripping operations in the SU77-XX-32H5 ultra-long horizontal well of the Sulige Gas Field, where a mechanical load model is constructed and field-calibrated. The second applies the framework to rail transit systems, where wheel–rail friction is estimated from dynamic response signals to support condition monitoring and wear prediction. The results from both scenarios confirm that incorporating physical symmetry and data-driven inversion significantly enhances the accuracy, robustness, and interpretability of engineering analyses across domains. Full article

Generally, most inversion approaches model the seabed as a stack of range-independent homogeneous layers with unknown geoacoustic parameters and layer numbers. In our previous study, we established a layered geoacoustic seabed model based on sub-bottom profiler data to characterize low-frequency (100–500 Hz) airgun signal propagation at short ranges (0–20 km). However, when applying the same model to simulate high-frequency (500–1000 Hz) explosive sound signal propagation, it failed to adequately reproduce the observed significant transmission loss phenomenon. Through systematic analysis of transmission loss (including water column sound speed profiles, seabed topography, and sediment properties), this study proposes a range-dependent layered geoacoustic model using the Range-dependent Acoustic Model–Parabolic Equation (RAM-PE). Stepwise inversion implementation has successfully explained the observed experimental phenomena. To generalize the proposed model, this study further introduces a trans-dimensional inversion framework that automatically resolves sediment property interfaces along propagation paths. The method effectively combines prior information with trans-dimensional inversion techniques, providing improved characterization of range-dependent seabed environments. Full article

In this work, a new approach to high-speed multi-coordinate milling was developed. The new approach is based on a new model of trochoidal machining; this is, in turn, based on the theoretical thickness of a chip and its ratio to the cutting edge’s radius, allowing us to establish the vibroacoustic indicators of cutting efficiency. The new model can be used for the real-time assessment of prevailing cutting mechanisms and chip formation. A set of new indicators and parameters for trochoidal high-speed milling (HSM), which can be used to calculate tool paths during technological preparation of slotting, was determined and verified. The size effect in the multi-coordinate HSM of slots on cast iron was identified based on the dependency of vibroacoustic signals on the cutting tooth’s geometry, HSM’a operational machining modes, theoretical chip thicknesses, the sizes of the cut chips, and the quality/roughness of the surface being machined. Based on the analysis of vibroacoustic signals, a set of the most important indicators for monitoring HSM and determining cutting and crack-formation mechanisms during chip deformation was derived. Based on the new model, recommendations for monitoring HSM and for assigning the tool path relative to the workpiece during production preparation were developed and validated. Full article

Contemporary construction faces the need to reduce its negative impact on the environment, prompting designers, investors, and contractors to seek more sustainable materials and technologies. One area of dynamic development is the use of natural fibers as an alternative to conventional, often synthetic, building components. Plant- and animal-based fibers, such as hemp, flax, jute, straw, bamboo, and sheep’s wool, are characterized by low energy consumption in production, renewability, and biodegradability. Their use is in line with the concept of a circular economy and reduces the carbon footprint of buildings. Natural fibers offer a number of beneficial physical and functional properties, including good thermal and acoustic insulation parameters, as well as hygroscopicity, which allows for the regulation of indoor humidity, improving air quality and comfort of use. In recent years, there has also been a renaissance of traditional building techniques, such as straw construction, often combined with modern engineering standards. Their potential is particularly recognized in green and energy-efficient construction. The article provides an overview of the types of natural fibers available for use in construction and analyzes their technical, environmental, and economic properties. It also draws attention to current regulations, standards, and certifications (e.g., LEED, BREEAM) that promote the popularization of these solutions. In light of the analyzed data, the role of natural fibers as a viable alternative supporting the transformation of the construction sector towards sustainable development is considered. Full article

The acoustics of St Paul’s Cathedral, London, have been discussed in previous studies as a space of historical, cultural, societal, and architectural interest in the capital city of the United Kingdom. This paper presents the results from recent acoustic measurements carried out within the space, making use of state-of-the-art measurement techniques and equipment. The results from these measurements provide a new perspective on the acoustic properties of different and distinct spaces within the cathedral, including coupling effects between the main areas, and the whispering gallery effect that can be heard around the walkway at the base of the dome. The discussion includes the analysis of room acoustic parameters included in the international standards and speech intelligibility parameters, and an indirect comparison between the techniques used here and those used in previous studies of this space. Full article

Traditional Chinese courtyard theaters in Taiwan possess a unique architectural and performative identity, distinct from Western-style proscenium theaters that dominate contemporary performance venues. These Western configurations often impose spatial and acoustic constraints that hinder the authentic expression of traditional Chinese opera. In contrast, courtyard-style theaters—characterized by open-air layouts and architectural enclosures—offer inherent acoustic advantages rooted in structural coupling and boundary reflections. This study focuses on the Da-Hua Hall at the Wu-Feng Lin Family Mansion, employing on site acoustic measurements to characterize its sound environment not only distribute sound energy and calibrate a sound tracing and a wave-based simulation model. The finite element method framework enables precise modeling of low-frequency acoustic phenomena, including modal behavior and resonance, which were conducted to assess the impact of stage permeability, vessel geometry, and wall-mounted resonators on acoustic parameters. The results demonstrate that the interaction between sub-stage resonators and architectural elements, specifically the width of stage floorboard joints and the presence of embedded jars, significantly influences acoustic performance, notably affecting the distribution of sound waves. These findings underscore the acoustically responsive architectural design in preserving the sonic integrity of traditional Chinese opera and highlight the value of simulation-based approaches in heritage research. Full article

This study investigates a non-destructive, compact pulse-echo ultrasonic method that combines an external transmitter with a single receiving sensor to identify different surface treatments applied to cementitious materials. The primary objective was to evaluate whether treatment-induced acoustic changes could be reliably quantified using time-domain signal parameters. Three types of surface conditions were examined: untreated reference specimens (R), specimens treated with a standard lithium silicate solution (A), and those treated with an enriched formulation containing hexylene glycol (B) intended to enhance pore sealing via gelation. A broadband piezoelectric receiver collected the backscattered echoes, from which the maximum amplitude, root mean square (RMS) voltage, signal energy, and effective duration were extracted. Receiver operating characteristic (ROC) analysis was conducted to quantify the discriminative power of each parameter. The results showed excellent classification performance between groups involving the B-treatment (AUC ≥ 0.96), whereas the R vs. A comparison yielded moderate separation (AUC ≈ 0.61). Optimal cut-off values were established using the Youden index, with sensitivity and specificity exceeding 96% in the best-performing scenarios. The results demonstrate that a single-receiver, one-sided pulse-echo arrangement coupled with straightforward amplitude metrics provides a rapid, cost-effective, and field-adaptable tool for the quality control of silicate-surface treatments. By translating laboratory ultrasonics into a practical on-site protocol, this study helps close the gap between the experimental characterisation and real-world implementation of surface-treatment verification. Full article

Gas hydrate-bearing sediments in marine environments represent both a future energy source and a geohazard risk, prompting increasing international research attention. In the Shenhu area of the South China Sea, a large volume of drilling and laboratory data has been acquired in recent years, yet a comprehensive framework for evaluating the characteristics of key reservoir parameters remains underdeveloped. This study presents a spatially integrated and statistically grounded framework that captures regional-scale heterogeneity using multi-source in situ datasets. It incorporates semi-variogram modeling to assess spatial variability and provides statistical reference values for geological and geotechnical properties across the Shenhu Area. By synthesizing core sampling results, acoustic logging, and triaxial testing data, representative probability distributions and variability scales of hydrate saturation, porosity, permeability, and mechanical strength are derived, which are essential for numerical simulations of gas production and slope stability. Our results support the development of site-specific reservoir models and improve the reliability of early-phase hydrate exploitation assessments. This work facilitates the rapid screening of hydrate reservoirs, contributing to the efficient selection of potential production zones in hydrate-rich continental margins. Full article

In practical applications, intelligent diagnostic methods for actuator-integrated gearboxes in industrial driving systems encounter challenges such as the scarcity of fault samples and variable operating conditions, which undermine diagnostic accuracy. This paper introduces a multi-layer feature fusion meta-learning (MLFFML) approach to address fault diagnosis problems in cross-condition scenarios with class imbalance. First, meta-training is performed to develop a mature fault diagnosis model on the source domain, obtaining cross-domain meta-knowledge; subsequently, meta-testing is conducted on the target domain, extracting meta-features from limited fault samples and abundant healthy samples to rapidly adjust model parameters. For data augmentation, this paper proposes a frequency-domain weighted mixing (FWM) method that preserves the physical plausibility of signals while enhancing sample diversity. Regarding the feature extractor, this paper integrates shallow and deep features by replacing the first layer of the feature extraction module with a dual-stream wavelet convolution block (DWCB), which transforms actuator vibration or acoustic signals into the time-frequency space to flexibly capture fault characteristics and fuses information from both amplitude and phase aspects; following the convolutional network, an encoder layer of the Transformer network is incorporated, containing multi-head self-attention mechanisms and feedforward neural networks to comprehensively consider dependencies among different channel features, thereby achieving a larger receptive field compared to other methods for actuation system monitoring. Furthermore, this paper experimentally investigates cross-modal scenarios where vibration signals exist in the source domain while only acoustic signals are available in the target domain, specifically validating the approach on industrial actuator assemblies. Full article

This article presents a comprehensive experimental and theoretical study and substantiation of the hydraulic parameters of a prototype multi-gear pump. The proposed pump design, which features one drive gear and four driven gears, aims to address the common disadvantages of traditional gear pumps, including radial force imbalance, uneven flow, high acoustic noise, and increased fluid leakage. Tests of the prototype multi-stage pump were conducted on a specialized test stand in the “Hydraulics” workshop of “Hansa-Flex Hydraulik Almaty” LLP. Experimental analysis, supported by theoretical calculations, established the optimal operating speed range for the prototype to be between 900 and 1450 rpm, with the volumetric efficiency remaining stable between 70% and 88% when using VMGZ hydraulic oil (45 cSt). A significant deterioration in performance, including a sharp drop in volumetric efficiency to 30% and a decrease in the pressure generated, was observed at rotational speeds below 900 rpm due to an increase in internal leaks. In addition, this study examined the effect of kinematic viscosity, which revealed a 15–20% decrease in performance and power when using a fluid with lower viscosity (15 cSt) with a slight increase in noise level. This study also examines in detail the linear relationship between useful power and pressure in the system and analyzes noise characteristics under various operating conditions. Full article

Moisture-induced instability in rock masses presents a significant threat to the safety and sustainability of underground infrastructure. This study proposes a nonlinear energy signal fusion framework to predict failure in moisture-affected limestone by integrating acoustic emission data with energy dissipation metrics. Uniaxial compression tests were carried out under controlled moisture conditions, with real-time monitoring of AE signals and strain energy evolution. The results reveal that increasing moisture content reduces the compressive strength and elastic modulus, prolongs the compaction phase, and induces a transition in failure mode from brittle shear to ductile tensile–shear behavior. An energy partitioning analysis shows a clear shift from storage-dominated to dissipation-dominated failure. A dissipation factor (η) is introduced to characterize the failure process, with critical thresholds η_min and η_f identified. A nonlinear AE-energy coupling model incorporating water-sensitive parameters is proposed. Furthermore, an energy-based instability criterion integrating multiple indicators is established to quantify failure transitions. The proposed method offers a robust tool for intelligent monitoring and predictive stability assessment. By integrating data-driven indicators with environmental sensitivity, the study provides engineering insights that support adaptive support design, long-term resilience, and sustainable decision making in groundwater-rich rock environments. Full article

Complex non-Newtonian glues are widely used in electrical vehicle (EV) manufacturing plants. In this paper, we focus on initial transient and compressibility issues which are closely associated with high pressure, boundary conditions, and flexible tubes, as well as their respective fluid–structure interaction effects. Both thixotropic and power law non-Newtonian nearly compressible fluid models have been employed to couple with flexible tubes with two different sets of material properties, namely, Young’s modulus and density. In addition to thick-wall cylindrical pressure vessel solutions, different pressure and velocity boundary conditions have also been studied with the consideration of initial transient and steady solutions for acoustic models. Moreover, the radial direction displacement distributions through the tube wall thickness and axial directions compare well within 4 to 9 percentage points with theoretical solutions of thick-wall cylinders under internal and external pressures. Finally, inverse optimization methods have been employed for the calibration of key parameters in comparison with experimental and computational results. Full article

This study introduces a real-time acoustic emission (AE) monitoring system for the micro-milling of fluorine-doped tin oxide (FTO) thin films, a critical transparent conductive oxide (TCO) material. The system uses AE sensors to capture high-frequency elastic waves generated during the micro-milling process. We combine experimental and theoretical analyses to investigate how various milling parameters influence the AE signals. To address the crucial challenge of ensuring ductile mode cutting in brittle materials like FTO, we employed a convolutional neural network (CNN) to identify the transition between ductile and brittle machining modes. A CNN was trained on energy-based features extracted from the AE signals, achieving a classification accuracy of 97.37%. This high accuracy demonstrates the effectiveness of integrating AE sensing with deep learning for interpreting complex micro-machining data. The results confirm that this combined approach offers a powerful, non-destructive, and intelligent monitoring solution for improving process control and understanding in the micro-milling of fragile conductive thin films. Full article

This study proposes a novel diagnostic system for the early detection of cutaneous melanoma based on morphological and biochemical changes during tumor formation. The methods used in this system are acoustic microscopy and infrared (IR) spectroscopy. The former identifies the anatomical parameters of the developing tumor, whilst the latter identifies its biochemical features, both at the micron scale. To implement this diagnostic method, an animal model that mimics human melanoma was developed. The results of this investigation show that using high-frequency (>20 $\mathrm{MHz}$) acoustic microscopy in conjunction with spectroscopic images provides useful information about distinct features of melanoma tumors’ 3D structures. The structures and cytoarchitecture of the tumors were assessed using conventional histology, and their malignant nature was confirmed using histological and immumohistochemical analysis. The proposed approach may provide an invaluable tool in diagnostic dermatology, as it is noninvasive and produces highly detailed and accurate data about the early appearance and development of melanoma tumors. Full article

As coal mining progresses to greater depths, the complex geological conditions significantly increase the risk of compound disasters. With increasing mining depth, elevated ground stress and gas pressure exacerbate the coupling effects of rockburst and gas outburst. This study employs laboratory tests and theoretical analysis to investigate gas disasters under varying gas and confining pressures. The experimental results are analyzed in terms of mechanical parameters, crack propagation, and acoustic emission (AE) time–frequency evolution. Under conventional compression, coal failure exhibits shear damage with axial splitting or debris ejection. The peak strength demonstrates a clear confining pressure strengthening effect and gas pressure weakening effect. At constant gas pressure, the elastic modulus increases with confining pressure, whereas at constant confining pressure, it decreases with rising gas pressure. Full article