Search Results (248)

Ordinary architectural conditions interact through arrangements that static representations often detach from time and use. This study examines six selected Turkish popular films as a mediated comparative corpus of apartments, neighborhood interfaces, mobile (route-vehicle) interiors, and domestic spaces in use. Comparative visual–spatial analysis of 24 scene-clusters traces how spatial domains and boundary/connection devices organize visibility, audibility, access, movement, bodily proximity, and collective attention. We define architectures of exposure as an event-level mismatch between scene-supported expected control over sight, sound, access, or bodily distance and the interactional field enabled by a configuration. A provisional, construction-corpus-derived layered model separates four primary spatial domains from boundary/connection devices, six interactional mechanisms, four control relations, three intensifiers, and contingent outcomes. Ten clusters directly demonstrate the mismatch; three show strategic or transformative widening, six provide partial or qualified evidence, and five delimit the concept through intended permeability or retained control. Cross-case comparison shows that the same device can preserve refusal, transmit distress, enable rescue, or support solidarity, while comparable spatial mechanisms acquire different narrative and ethical significance under comic and non-comic framing. The study contributes a scene-cluster method for treating fiction film as mediated architectural evidence and a diagnostic framework for future observation, acoustic assessment, visibility analysis, and post-occupancy research. Full article

In the broader context of ecological transition, it is essential to identify solutions that ensure indoor environmental quality encompassing thermal, visual, acoustic, and indoor air quality conditions to safeguard occupant health and well-being. These solutions should also meet the demand for energy-efficient buildings. With specific regard to thermal environments, a distinction must be made between residential and non-residential settings, where comfort conditions can be achieved, and industrial environments, where thermal stress—and consequently health risks—may arise. To evaluate the quality of a thermal environment, key metrics are necessary. These include the Predicted Mean Vote (PMV) and the Predicted Percentage of Dissatisfied (PPD) for global thermal comfort, Predicted Heat Strain (PHS) and the Wet Bulb Globe Temperature (WBGT) for hot environments, and Required Insulation (IREQ) for cold environments, all governed by ISO-EN standards. The use of indices in residential and non-residential buildings outlines two critical challenges. The first relates to the fact that, in certain instances involving non-air-conditioned buildings, conditions can be borderline between comfort and thermal stress, which must be accurately identified. Secondly, the application of indices frequently neglects necessary variables, disregarding the fundamental limitations and operational boundaries inherent to both objective and personal input quantities. Moreover, the use of measurement devices inconsistent with the minimum requirements laid down by the standards in the field results in unwanted biases with unforeseeable consequences. This review explores the formulation, use, and limitations of the four indices mentioned, providing a perspective on their future development. It establishes the criteria for reliable long-term assessments of thermal and energy environments, encompassing the analysis of both heat and cold strain. Full article

Mineral-scale deposition remains a persistent flow-assurance and asset-integrity constraint in oil and gas production. Calcium carbonate, calcium sulfate, barium sulfate, iron sulfide, and mixed inorganic scale deposits reduce tubing internal diameter. They also impair near-wellbore permeability, block safety-critical valves, reduce heat-transfer efficiency, and intensify under-deposit corrosion. Conventional management relies on prediction, chemical inhibition, squeeze treatments, acid dissolution, chelation, mechanical scraping, milling, jetting, and operational water management. These methods are indispensable, but each has a restricted operating envelope. Key limitations include mineral selectivity, corrosion risk, environmental discharge, intervention cost, debris generation, and poor effectiveness against chemically resistant sulfate scales, particularly BaSO₄. Ultrasound has therefore attracted interest as a non-chemical technology. Acoustic cavitation, microstreaming, pressure oscillation, mechanical vibration, and micro jetting may suppress nucleation, disturb boundary layers, weaken adhesion, and fragment brittle deposits. This review critically evaluates ultrasound-assisted scale prevention and removal, with emphasis on production tubing and oilfield relevance. Existing studies show credible mechanistic plausibility and promising laboratory performance for CaCO₃, CaSO₄/gypsum, KCl, NaCl, and membrane or heat-transfer fouling systems. It also compares performance metrics, field cases, and technology-readiness barriers. The evidence is less mature for long steel tubulars operating under high-pressure, high-temperature, multiphase production conditions. Current evidence positions ultrasound at technology-readiness level (TRL) 3–4 for CaCO₃ and CaSO₄ systems, where laboratory and bench-scale validation is established, and at TRL 2–3 for BaSO₄, where mechanistic plausibility exists but controlled experimental validation remains absent. The technology is not yet at the pilot–production transition for downhole tubing applications, but it is approaching that threshold for surface process equipment. Its most credible near-term role is as an intensifier paired with low-dose chemical inhibitors, where acoustic boundary-layer disruption can reduce the minimum inhibitory concentration threshold of inhibitors, and with mild chelating agents for early-stage BaSO₄ management, where ultrasound-enhanced mass transfer may accelerate chelant penetration into deposit microstructure. Advancing ultrasound from its current TRL toward field qualification requires targeted BaSO₄ scale validation in steel tubing systems, acoustic field mapping under HPHT multiphase conditions, mass-removal metrics, and a structured pilot programme. Full article

Low-resource written-query keyword spotting detects a text-specified target in speech without spoken enrollment or full automatic speech recognition. We present Tibetan Phonology-Aware Speech Evidence Matching (Tibetan-PASEM), a method that encodes graphemic, approximate phonological, and dialect-related query information, matches it with local acoustic windows, aggregates window-level evidence, and applies a validation-selected operating point. Querybank198 contains 198 Tibetan written queries derived from four public speech resources. A complete-file and decoded pulse-code modulation (PCM) audit produced a corrected 213,128-pair evaluation with no identified recording-content, source-qualified speaker, or session-proxy overlap across the development-to-held-out boundary. In a three-seed corrected-index re-evaluation, the acoustically strengthened PASEM (PASEM-AS) achieved F1 scores of 66.16 ± 2.14% on seen_test, 26.51 ± 3.42% on unseen_test, and 72.10 ± 1.39% on the confusable-negative diagnostic condition, which comprises 20 training-exposed query forms and is used for negative-set analysis rather than difficulty ranking. Under the original pre-correction pair index, PASEM with transfer regularization (PASEM-TR) increased the unseen_test F1 from 25.80 ± 2.71% to 35.25 ± 4.17% and the Recall from 18.48 ± 2.98% to 33.85 ± 8.22%; the corresponding seed-level 95% confidence intervals were 24.89–45.61% and 13.43–54.27%. These results establish strong familiar-query discrimination, an audited fixed-threshold evaluation protocol, and partial, seed-sensitive transfer to held-out written queries. Full article

A tight conglomerate is mechanically heterogeneous because gravel particles, the matrix, and their contacts can perturb hydraulic-fracture paths. This study presents an exploratory comparison of three 2.0 m × 2.0 m × 1.0 m reconstituted conglomerate specimens, identified as specimen 97 (Condition A), specimen 98 (Condition B), and specimen 99 (Condition C). One meter-scale specimen was tested under each formulation condition using the same applied boundary stresses, nominal pumping rate, and fluid viscosity. Post-fracturing surface observations, inlet-pressure histories, and laboratory acoustic-emission (AE) event locations were examined. After event-quality control, DBSCAN-based spatial filtering was performed in Z-score-standardized coordinates, and three-dimensional alpha shapes were constructed from the retained event coordinates in meters to calculate geometric AE-event-envelope volumes. The external surface-fracture traces were more spatially distributed in specimen 97 and more localized in specimen 99. The available DBSCAN–alpha-shape calculation outputs yielded geometric AE-event-envelope volumes of 0.2832, 0.2460, and 0.0937 m³ for specimens 97, 98, and 99, respectively. Because only one specimen was tested under each condition, the specimen formulations and gravel characteristics were not identical, the gravel–matrix interfacial properties were not measured directly, and the pumping histories differed, the observations were interpreted as descriptive case differences rather than as a statistically validated single-factor relationship. Full article

Civil engineering is essential to the transportation industry, and the maintenance of concrete components is a critical aspect. Recently, the IE (Impact-Echo) method has become a significant technique for void detection. However, conventional IE approaches have limitations and are susceptible to subjective factors. Consequently, AI (artificial intelligence) methods have attracted increasing attention. Although progress has been made, many issues persist in real-world situations. To address these shortcomings, such as weak transient characteristic comprehension, insufficient analysis of periodic features, and inadequate handling of impact-induced resonance and boundary reflection, we propose a novel three-stream input heterogeneous fusion framework. Our contributions are as follows: (1) GAF (Gramian Angular Field) representations that refine the analysis of energy distribution and asymmetric acoustic fingerprint variation rate; (2) MTF (Markov Transition Field) representations that enhance analysis of state transitions; (3) a BiLSTM (Bidirectional Long Short-Term Memory) module with dynamic constraints and the Flood Algorithm to improve time-frequency domain information comprehension. Experimental results demonstrate an average recognition accuracy of up to 96% across four tasks in complex working conditions, approaching competitive performance and indicating practical application value. Full article

This study investigates the effects of the length-to-diameter (L/D) ratio on the indirect tensile strength of red sandstone using Brazilian splitting tests combined with acoustic emission (AE) and digital image correlation (DIC) technology. Brazilian splitting tests were conducted on red sandstone disk specimens with a constant diameter of 50 mm and L/D ratios of 1.0, 0.8, 0.6, and 0.5. The results show that the apparent splitting strength decreased from 5.05 MPa at L/D = 0.5 to 1.35 MPa at L/D = 1.0, a reduction of 73.3%. As the L/D ratio decreased, the AE ring counts and energy release became increasingly concentrated near the peak load and exhibited more pronounced burst-like characteristics. Shear-type AE events increased from 62.4% to 82.9%, and tensile-type events decreased from 37.6% to 17.1%. The decrease in the AE b-value prior to failure indicates a transition of damage evolution from distributed small-scale microcrack activity to localized large-scale crack initiation, propagation, and coalescence. DIC showed that primary cracks initiated near the specimen center, whereas lower L/D ratios produced stronger localization, more secondary inclined cracks, and more abrupt failure. The higher calculated strengths obtained under low L/D conditions should be interpreted as apparent Brazilian splitting strengths resulting from the combined effects of specimen geometry and boundary constraints, rather than being directly regarded as the intrinsic tensile strength of red sandstone. Full article

Accurate target detection in side-scan sonar imagery is important for marine resource investigation, underwater infrastructure inspection, and maritime security. However, Side-scan sonar images are often affected by low contrast, acoustic speckle, weak target boundaries, and cluttered seabed backgrounds, which make target detection particularly challenging, especially under limited training data conditions. To improve the representation of sonar-specific structures, this study proposes a multi-feature early fusion detection network, referred to as MFEF-Det, for side-scan sonar target detection. The method combines multiple handcrafted features with data-driven representations to provide complementary information. In particular, a directional contrast core response feature (DCCR) is introduced to better emphasize the echo–shadow structure commonly observed in side-scan sonar imagery. An adaptive fusion strategy is then adopted to combine multiple feature maps before feeding them into a detection network, and an attention refinement module is further employed for complex scenes to improve the discrimination between target-related regions and cluttered backgrounds. Experiments were conducted on two publicly available sonar datasets. Experiments on the KLSG and SSS-Bottom datasets demonstrate that MFEF-Det achieves 0.933 ± 0.016 mAP@0.5 and 0.866 ± 0.052 mAP@0.5, respectively. The results indicate that the proposed feature representation can improve detection performance in both relatively clean and more challenging noisy scenes. These findings suggest that incorporating sonar-specific priors can be beneficial for side-scan sonar detection in marine survey and maritime-security applications. Full article

To investigate the effects of different moisture conditions and numbers of freeze–thaw cycles on the damage deterioration behavior of red sandstone, three freeze–thaw conditions were used in this study: GA (sealed water-retaining state after saturation), GB (semi-immersed state after saturation), and GC (full immersion state after saturation). The samples were subjected to 20, 40, and 60 freeze–thaw cycles, followed by uniaxial compression tests and acoustic emission (AE) monitoring. By analysing the stress–strain curves, tangent modulus–strain curves, crack-closure parameters, brittleness indices, AE counts, and energy dissipation characteristics, the freeze–thaw damage mechanism of red sandstone samples under disparate moisture boundary conditions was revealed. The results show that as the number of freeze–thaw cycles increases, the uniaxial compressive strength and tangential deformation modulus of red sandstone samples gradually decrease, whereas the peak strain and full compaction strain increase. The crack-closure stage is prolonged, and the failure process changes from sudden brittle failure to progressive damage failure. The degree of damage differed among the samples under different moisture conditions; overall, the GB group (semi-immersed state) exhibited the most pronounced deterioration, followed by the GC group (fully immersed state), whereas the GA group (sealed water-retaining state) experienced relatively weak deterioration. Energy analysis indicates that freeze–thaw cycling decreases the elastic energy storage capacity and increases the proportion of dissipated energy. The freeze–thaw damage variable established on the basis of the peak dissipated energy ratio can be used to characterize the strength attenuation and deformation growth processes effectively. Full article

This study proposes a surrogate-assisted framework to characterize system-level equivalent stiffness parameters of composite resilient floor subsystems from global resonance features, calibrated and assessed for consistency using actual building acoustic tests. Since intrinsic material characterization alone may not fully capture the contribution of resilient layers under complex in situ boundary conditions, a parametric finite element model utilizing a transversely isotropic formulation with five independent stiffness-related parameters is coupled with Gaussian Process surrogates and a genetic algorithm. Repeated laboratory impact tests provide empirical bending and torsion resonance targets near 60 Hz and 155–160 Hz. The trained surrogates predict these targets with a root mean square error (RMSE) below 0.02, enabling the inverse estimation to identify representative parameter sets within a ±5% tolerance. The optimization yields a finite admissible parameter region, reflecting the inherent non-uniqueness of the inverse problem. To establish framework consistency, the identified equivalent parameters are integrated into a hybrid vibro-acoustic scheme and assessed for consistency against sound pressure level measurements from real-world building tests. Crucially, the sensitivity analysis indicates a mechanical divergence: in-plane stiffness primarily governs resonance-frequency reproduction, whereas out-of-plane stiffness is more influential in the noise-related structural wall-response-energy assessment within the admissible solution region. This behavioral mismatch demonstrates resonance matching alone is insufficient for design prioritization. The proposed framework establishes a configuration-level tool to systematically evaluate structural improvement directions without direct intrinsic material testing. Full article

This paper deals with the use of the singular boundary method for analysis of time-harmonic acoustic scattering by penetrable obstacles. There are many formulations of boundary-type meshless methods, distinguished mainly by the manner in which the singularity of the fundamental solution at the source point is treated. The article presents the singular boundary method (SBM), a boundary-only, integration-free collocation technique in which the source points are placed directly on the physical boundary, so that no volume mesh, no auxiliary boundary and no element connectivity are required. The scattered field in the exterior and the transmitted field inside each obstacle are each represented by a single layer of fundamental solutions. The determination of the origin intensity factors (OIFs), which replace the singular self-interaction of the single-layer fundamental solution and of its normal derivative, is the crucial part of the method. A closed-form OIF is employed for the Dirichlet boundary condition and a purely geometric OIF based on the signed boundary curvature is employed for the Neumann boundary condition, so that only two boundary operators are required instead of the four operators used in the direct formulation. The accuracy of the method has been compared with the analytical Mie series and the third-order deltaBEM. Third-order convergence and reasonable accuracy, when compared to the exact solution, are obtained throughout. Full article

This study proposes a Variational AutoEncoder (VAE)-based Quality Controlled (QC) generative augmentation framework for North Atlantic right whale (NARW) upcall detection. Existing generative augmentation methods can generate synthetic samples; however, they do not provide a sample-level criterion for determining whether each generated sample is a positive sample that contributes to improved detector performance or a synthetic outlier that should be removed. This study learns manually extracted upcall frequency contours using a 1D-VAE and evaluates generated contour candidates in a 10-dimensional acoustic morphology feature space. The QC score is computed with respect to the reference distribution of manually extracted real upcall contours, and stochastic acceptance probabilities for borderline samples around the hard threshold are calibrated using same-call manual re-extraction variability. QC-passed contours are converted into detector training spectrograms using smooth amplitude modulation and Gaussian noise injection based on SNR statistics. Using 30,000 acoustic segments from the Kaggle NARW dataset, Original, Denoising Diffusion Probabilistic Models (DDPM), Contour-VAE without QC, and VAE-QC conditions were compared under the same detector and augmentation budget. VAE-QC with α = 0.97 achieved the highest mean AUC of 0.901, outperforming Original training (0.802), DDPM (0.845), and Contour-VAE without QC (0.810). Feature distribution and QC-score analyses further showed that VAE-QC suppresses morphology outlier tails observed in unfiltered generation. These results indicate that the key factor in generative augmentation is the QC process that defines feature boundaries useful for detector learning and selects synthetic positive samples accordingly. Full article

Combine harvesters operate under harsh, time-varying field conditions, where unplanned downtime causes significant timeliness losses. This review systematically examines advances in structural fault diagnosis for combine harvesters, tracing the evolution from passive structural redundancy to active state perception and simulation-driven health management. Following a systematic search and screening methodology, the review analyzes the boundaries of structural optimization under fluctuating field conditions, evaluates traditional machine learning (ML) methods with handcrafted features, and surveys deep learning (DL) and multi-sensor fusion advances across vibration, acoustic, and visual modalities. A structured comparison across feature learning, generalization, diagnostic coverage, computational cost, and interpretability highlights the complementary strengths of traditional ML and DL paradigms. Key deployment challenges are identified: weak fault features under strong field noise, data distribution shift under multi-condition coupling, extreme sample scarcity and class imbalance, limited onboard computing and real-time latency constraints, interpretability gaps, hydraulic and pneumatic diagnostic neglect, functional safety compliance (ISO 25119), and the heightened reliability demands of unmanned autonomous operation. To address these challenges, future directions include physics-informed hybrid models, self-supervised pre-training and few-shot learning, lightweight edge inference, staged pre-deployment verification, model updating and lifelong learning strategies, cross-energy-domain diagnosis with fault-tolerant control, human-factors-aware interface design, and digital twin (DT) augmentation—the latter regarded as a strategic research vision requiring incremental validation rather than a near-term deployable solution. This review provides a reference for enhancing combine harvester mission reliability through the integration of AI-enabled perception, multi-source fusion, and simulation-driven health management. Full article

Leakage-induced transients in natural gas transmission pipelines can significantly affect operational safety and emergency response. This study develops a physics-based analytical framework for predicting transient pressure evolution, leakage dynamics, and emergency valve response in high-pressure gas pipelines while deriving a closed-form criterion for optimal valve spacing. The governing equations of compressible gas flow are reduced to a diffusion-type model incorporating acoustic wave propagation and frictional attenuation. A dynamic Robin-type boundary condition is introduced to describe valve–pipeline interactions, and closed-form analytical solutions are obtained using the Laplace transform method. An analytical leakage function and an explicit valve spacing criterion are derived directly from the governing equations and boundary conditions. Parametric investigations under representative transmission pipeline operating conditions demonstrate that the optimal valve spacing depends systematically on attenuation characteristics, activation thresholds, and allowable response times. The analytical solution further predicts a narrow quasi-invariant valve activation interval of approximately 112–116 s, which is theoretically explained through the dominant acoustic–diffusive balance of the proposed model. Verification against an independent finite difference solution shows excellent agreement, with the maximum relative deviation remaining below 1%, thereby confirming the accuracy and numerical consistency of the analytical formulation. The proposed framework provides a physically interpretable and computationally efficient tool for leakage assessment, emergency valve design, and safety-oriented analysis of conventional natural gas transmission pipelines. Full article

A novel strong-form meshless method based on Lagrange interpolation is proposed for vibro-acoustic coupling analysis. The governing equations of acoustic and structural domains, together with the coupling interface conditions, are discretized directly in differential form without relying on predefined meshes, thereby improving geometric flexibility. The computational domain is partitioned into local subdomains, within which Lagrange interpolation is employed to construct approximation functions from nodal distributions. In this manner, the proposed framework combines the flexibility of meshless formulations with a zonal parameterization strategy similar to that used in isogeometric analysis. Moreover, spatial derivatives and system matrices are directly evaluated and assembled at nodal points, avoiding numerical integration and simplifying the implementation procedure. Owing to the Kronecker delta property of Lagrange polynomials, boundary conditions can be imposed accurately and conveniently. For transient analysis, the Newmark-$\beta$ scheme is adopted to integrate both first- and second-order temporal terms, ensuring stable and accurate time integration. Finally, numerical examples, including comparisons with commercial software, demonstrate the accuracy and effectiveness of the proposed method for complex vibro-acoustic problems. Full article