Search Results (299)

Steam traps are essential for industrial systems, ensuring steam quality and energy efficiency by removing condensate and preventing steam leakage. However, their failure results in energy loss, operational disruptions, and increased greenhouse gas emissions. This paper proposes a novel predictive maintenance system for steam traps that integrates statistical time series features and transformer encoder–decoder models for fault diagnosis and visualization. The proposed system combines IoT sensor data, operational parameters, open data (e.g., weather information and public holiday calendars), machine learning, and two-dimensional diagnostic projection to improve reliability and interpretability. Experiments were conducted in two industrial plants: an aluminum processing plant and a food manufacturing plant, and the system achieved superior defect detection accuracy and diagnostic reliability compared to existing methods. The transformer-based model outperformed traditional methods, including random forest, gradient boosting, and variational autoencoder, in classification and clustering. The system also demonstrated an average 6.92% reduction in thermal energy across both sites, highlighting its potential to improve energy efficiency and reduce carbon emissions. This research highlights the transformative impact of AI-based predictive maintenance technologies in industrial operations and provides a framework for sustainable manufacturing practices. Full article

This paper conducts a comprehensive experimental comparison of two widely used additive manufacturing (AM) processes, Fused Deposition Modeling (FDM) and Stereolithography (SLA), under standardized conditions using the same test geometries and protocols. FDM parts were printed with both Polylactic Acid (PLA) and Acrylonitrile Butadiene Styrene (ABS) filaments, while SLA used a general-purpose photopolymer resin. Quantitative evaluations included surface roughness, dimensional accuracy, tensile properties, production cost, and energy consumption. Additionally, environmental considerations and process reliability were assessed by examining waste streams, recyclability, and failure rates. The results indicate that SLA achieves superior surface quality ($R_a\approx 2\mathsf{\mu }\mathrm{m}$ vs. 12–$13\mathsf{\mu }\mathrm{m}$) and dimensional tolerances ($\pm 0.05\mathrm{mm}$ vs. $\pm 0.15$–$0.20\mathrm{mm}$), along with higher tensile strength (up to $70\mathrm{MPa}$). However, FDM provides notable advantages in cost (approximately 60% lower on a per-part basis), production speed, and energy efficiency. Moreover, from an environmental perspective, FDM is more favorable when using biodegradable PLA or recyclable ABS, whereas SLA resin waste is hazardous. Overall, the study highlights that no single process is universally superior. FDM offers a rapid, cost-effective solution for prototyping, while SLA excels in precision and surface finish. By presenting a detailed, data-driven comparison, this work guides engineers, product designers, and researchers in choosing the most suitable AM technology for their specific needs. Full article

Heaters are critical components in various heating control systems, and their faults are often a primary cause of system failure, drawing significant attention from engineers and researchers. Early and accurate fault diagnosis is crucial to prevent cascading failures. Many diagnostic methods target faults under generally stable and simple operating conditions, such as constant load or steady-state temperature. However, real-world scenarios are often complex and variable, involving dynamic loads, nonlinear temperature rises, and other challenges, which limit diagnostic accuracy. To address this issue, this paper proposes an intelligent fault diagnosis model based on a one-dimensional convolutional neural network (CNN), using the heater’s current and voltage as the input to the neural network. The effectiveness and accuracy of the proposed model were validated through experimental data under two different conditions, achieving an average accuracy rate of 98%. The disconnection faults were generated during actual operation and occurred in the early stages, differing significantly from artificially simulated faults, thereby increasing the difficulty of accurate diagnosis. Analysis and comparison of the experimental results demonstrate the feasibility of the intelligent diagnostic model and its high diagnostic accuracy. Full article

Metal additive manufacturing has emerged as a revolutionary technology for the fabrication of high-complexity components. However, this technique presents unique challenges related to the structural integrity and final strength of the parts produced due to inherent defects, such as porosity, cracks, and geometric deviations. These defects significantly impact the fatigue life of the material by acting as stress concentrators that accelerate failure under cyclic loading. On the one hand, this type of model is very complicated in its approach, since, even with encouraging results, the complexity of the calculation with these variables makes it difficult to obtain a simple result that allows for a generalized interpretation. On the other hand, using more familiar methods, it is possible to qualitatively guess the behavior that helps obtain results with better applicability, even at limited levels of precision. This paper presents a simplified finite element method combined with a statistical approach to model the presence of porosity in metal components produced by additive manufacturing. The proposed model considers a two-dimensional square plate subjected to tensile stress, with randomly introduced defects characterized by size, shape, and orientation. The percentage of porosity that affects each aspect determines the adjustment of the mechanical properties of finite elements. A series of simulations were performed to generate multiple models with random defect distributions to estimate maximum stress values. This approach demonstrates that complex models are not always necessary for a preliminary practical estimate of the effects of new manufacturing techniques. Furthermore, it demonstrates the potential for the extension of frugal computational techniques, which aim to minimize computational and experimental costs in the engineering field. The article discusses future research directions, particularly those related to potential business applications, including commercial uses. This follows a discussion of the existing limitations of this study. Full article

This study proposes an electrohydrodynamic multiphysics modeling and finite element analysis technique to accurately simulate corona-streamer discharges in a two-phase flow medium. The discharge phenomenon is modeled as a multiphysics system, coupling the Poisson equation for the electric field with a charge dynamics model based on fluid methods and a thermofluid field for temperature effects. To optimize the numerical simulation, the tip-flat plate electrode model was simplified to two-dimensional axisymmetry, and an unordered lattice network was used to reduce computational time while maintaining high resolution in the region of interest. A high DC voltage was applied to the model to generate a local non-uniform electric field exceeding 10 MV/m, allowing the numerical simulations of ionization, recombination, and charge attachment in the streamer channel. The numerical results were compared with voltage and current measurements from full-scale experiments under identical geometry and initial conditions to verify the effectiveness of the proposed method. The results of this study enhance the understanding of the multiphysical mechanisms behind electrical discharge phenomena and can enable the prediction of insulation failure through simple simulations, eliminating insulation experiments on devices. Full article

The fracturing pump serves as a critical piece of equipment in enhancing oil and gas recovery rates. However, under the coupled action of high-pressure fluid pulsation circulation in the pump body and the vibration of fracturing equipment, the bolts connecting the fracturing pump and fracturing manifold flange are prone to fatigue failure. In this paper, a three-dimensional finite-element model of the threaded bolt connection structure at the fracturing pump outlet end with a fine thread structure was established, and the measured vibrational displacement of the fracturing pump under different driven modes was used as the load to obtain the internal stress state of the full-thread bolt and the double-headed bolt used in the fracturing operation site. Based on the stress state, the fatigue life of the two types of bolts under various loading conditions was then simulated using the Brown—Miller fatigue damage criterion. The results indicate that for bolts of the same structural type, the maximum stress and stress variation amplitude increase in the sequence of the diesel-driven, single-motor-driven, and dual-motor-driven methods. Additionally, under the same load, the stress of the full-thread bolt is lower than that of double-headed bolt. The fatigue life analysis results show that under the vibrational load of diesel drive, the full-thread bolt can obtain a longer fatigue life of approximately 2042.89 h. However, under the load of dual-motor-driven method, the fatigue life of double-headed bolt is the lowest, only 717.46 h. A comparison with the fatigue life of bolts in actual engineering projects indicates that the predicted fatigue life of the bolts is consistent with the actual service life, which can provide effective guidance for the inspection and maintenance of fracturing pump equipment. Full article

According to the World Health Organization (WHO), floods are one of the most important natural disasters in the world, resulting in the severe loss of human lives and intense destruction of infrastructure. The frequent floods in recent decades have caused most parts of Iran to be affected by periodic and destructive floods. Consequently, the casualties and financial losses of floods have increased significantly. The present study aims to investigate redesigning the fuse plug, emergency overflow, and flood system at Ramshir Dam, Iran. In this regard, using a two-dimensional mathematical model, floods with a return period of 10 and 100 years with different scenarios have been investigated. Four scenarios were analyzed, including the current situation, flood channel dredging scenario, flood channel overhaul scenario, and flood channel overhaul scenario with reservoir dredging. The results show the following: (1) The flood channel in its current state cannot even discharge flows lower than the design, i.e., 1400 m³/s, and the flow overflows from the embankments on its sides. (2) Also, the reservoir dredging prevents the failure of the second fuse plug in the 100-year return period (flow rate 4370 m³/s). (3) Discharge more than 2400 m³/s cubic meters led to the activation of the first fuse plug. (4) The present research findings are of particular and essential importance in flood management. (5) The results of this research were based on the rehabilitation and simulation of the diversion dam facilities in the control and conveyance of flood and on three factors of spillway, flood channel, and flood plain, and the correct function of the fuse plug was reviewed. Full article

The migration of acid gases through the pressure sheath of flexible pipes may induce a corrosive environment that can lead to steel armors’ failure by SCC (stress corrosion cracking). This permeation process depends on temperature, partial pressures, materials, and the pipe’s geometry. However, there are few works related to permeation modeling in flexible pipes, and these works usually contain significant simplification in pipes’ geometry. Hence, this work proposes two finite element (FE) permeation models and discusses the effects of the pipe’s characteristics. The models were developed in Ansys^®, considering two- (2DFE) and three-dimensional (3DFE) approaches, and rely on gas fugacities instead of concentrations to describe the mass transport phenomenon. A radial temperature gradient is also considered, and the heat transfer is uncoupled from the mass transfer. Dry and flooded annulus analyses were conducted with the proposed models. In dry conditions, the results obtained with the 2DFE and the 3DFE approaches showed no significant differences, demonstrating that 3D effects are irrelevant. Hence, the permeation phenomenon is ruled by the permeation properties of the polymeric layers (pressure and outer sheaths) and possible shield effects promoted by the metallic armors. In contrast, the flooded annulus analyses resulted in a non-uniform fugacity distribution in the annulus with significant differences between the 2DFE and the 3DFE approaches, showing the importance of modeling the helical geometries of the metallic armors in this condition. Finally, a conservative 2DFE approach, which neglects the contribution of the pressure sheath, is proposed to analyze the flooded annulus condition, aiming to overcome the high computational cost demanded by the 3DFE approach. Full article

The reasonable and efficient prediction of dam failure events is of great significance to the emergency rescue operations and the reduction in dam failure losses. This work presents a model that is based on the physical mechanism. It is coupled with a multi-architecture (multi-CPU and GPU) open-source two-dimensional flood model, which is based on high-precision terrain and land use data. The aim is to enhance the accuracy of dam break flood process simulations. The model uses DEM data as a computational grid and updates it at each time step to reflect breach evolution. Simultaneously, the breach evolution model incorporates an analysis of stress on sediment particles, establishing the initial erosion state and lateral expansion model while accounting for seepage. The determination of the overflow of the breach is resolved through the application of a two-dimensional hydrodynamic model. This approach achieves a robust connection between the upstream reservoir, the dam structure, and the downstream inundation area. The coupled model is utilized to calculate the failure of earth-rock dams and landslide dams, and a sensitivity analysis is conducted. Taum Sauk Dam and Tangjiashan landslide dam were selected to represent earth dam break and barrier lake break, respectively, which are the main types of dam breaks. The obtained results demonstrate strong concurrence with the measured data, the relative errors of the four important parameters of the application case, the peak discharge of the breach, the top width of the final breach, the depth of the breach and the arrival time of the maximum peak discharge are all within ±10%. Although the relative error of the completion time of the final breach is greater than 10%, it is about 30% less than the relative error of the physical model. Full article

Modular Multilevel Converters (MMCs) play a crucial role in new energy grid connection and renewable energy conversion systems due to the significant merits of good modularity, flexible scalability, and lower operating loss. However, reliability is a significant challenge for MMCs, which consist of a large number of Insulated Gate Bipolar Transistors (IGBTs). Failures of the IGBTs in submodules (SMs) are a critical issue that affect the performance and operation of MMCs. The insufficient ability of convolutional neural networks to learn key fault features affects the accuracy of MMC fault diagnosis. To resolve this issue, this paper proposes a novel deep fault diagnosis framework named the Multiscale Adaptive Fusion Network (MSAFN) for MMC fault diagnosis. In the proposed MSAFN, the fault features of the raw current in an MMC are extracted by employing multiscale convolutional neural networks (CNNs) firstly, and then a channel attention mechanism is added to adaptively select the channel containing key features, so as to improve the fault diagnosis ability of the MMC in a noisy environment. Finally, the adaptive size of a one-dimensional CNN is adopted to adjust the weight of the feature channels of different scales, which are adaptively fused for fault diagnosis. Experimental validation is performed on two different MMC datasets. Experimental results confirm that the introduction of an attention mechanism of the multiscale feature adaptive fusion channel improves the recognition accuracy of the model by an average of $15.6\%$. Moreover, comparative experiments under different signal-to-noise ratios (SNRs) demonstrate that the MSAFN maintains accuracy levels above $96.7\%$, highlighting its excellent performance, particularly under noisy conditions. Full article

This study presents three-dimensional finite element analyses of two marine structures subjected to lateral loading to approximate environmental forces (e.g., wind, waves, currents, earthquakes). The first structure is a marine jetty supported by twenty-four piles, representative of an existing structure in Cyprus, while the second is a simplified four-pile marine structure. Soil–pile interaction is modelled using nonlinear p-y, τ-z, and q-z springs that are distributed along the piles, while steel plasticity is also considered. This study examines the relationship between failure modes, deformation modes, and plastic hinge locations with soil behaviour and soil reaction forces. It also aims at investigating the behaviour of the above structures in lateral loading and quantifying the consequences of unrealistic assumptions such as soil and steel linearity or tension-resistant q-z springs. The results indicate that such assumptions can lead to the wrong prediction of failure modes, plastic hinges, and critical elements while emphasising the crucial role of soil nonlinearity and axial pile–soil behaviour on the structural response. It is demonstrated that the dominant nonlinear sources relevant to this study, whether soil nonlinearity, plastic hinge formation, or a combination of the two, are primarily influenced by the axial capacity of soil–pile foundation systems, particularly their tensile component. Full article

In the literature on rotating machinery, many articles discuss the analysis of various rotor and bearing defects, including both sliding and rolling bearings. Defects in the rotor supporting system are investigated much less frequently. In rotor-bearing-supporting structure systems, where there are couplings between the individual sub-systems, damage to the supporting structure can significantly impact the dynamic properties of the entire machine. The authors of this article have, therefore, focused on analysing the defects that can occur in the supporting system of the rotor and bearings. This article presents the results of a numerical analysis of two common defects in the supporting structure: cracks in the bolted joints attaching the machine body to the foundation and a decrease in foundation stiffness. The research object was a test rig that accurately reproduced the dynamic phenomena occurring in rotating machinery, such as vapour and gas turbines. In the numerical model of the rotating machine, a three-dimensional linear model of the supporting structure was combined with a beam model of the rotor line via a nonlinear fluid film-bearing model. The developed model allowed for the analysis of two different failures in the supporting system over a wide range of rotational speeds. The calculations showed that damage to the supporting structure can significantly impact the dynamic characteristics of the entire rotating machine. Full article

This study delves into a market characterized by vertical product differentiation. Product qualities are represented on a one-dimensional interval scale. The research investigates the equilibrium within a monopoly scenario, considering a production cost that is strictly convex. The monopoly offers a strategy comprising various quality–price combinations, with consumer choices determining profits. The analysis involves a comparison between two analogous models: one with a continuous range of consumers and the other with a finite number of consumers. The study explores disparities in the potential for market failure between these two settings. Notably, numerical illustrations underscore these divergences in both market contexts. Full article

Rare-earth-based permanent magnets (PMs) have a vital role in numerous sustainable energy systems, such as electrical machines (EMs). However, their production can greatly harm the environment and their supply chain monopoly presents economic threats. Alternative materials are emerging, but the use of rare-earth PMs remains dominant due to their exceptional performance. Damage to magnet structure can cause loss of performance and efficiency, and propagation of cracks in PMs can result in breaking. In this context, prolonging the service life of PMs and ensuring that they remain damage-free and suitable for re-use is important both for sustainability reasons and cost management. This paper presents a new harmonic content diagnosis and motor performance analysis caused by various magnet structure defects or faults, such as cracked or broken magnets. The proposed method is used for modeling the successive physical failure of the magnet structure in the form of crack formation, crack growth, and magnet breakage. A surface-mounted permanent magnet synchronous motor (PMSM) is studied using simulation in Ansys Maxwell software (Version 2023), and different cracks and PM faults are modeled using the two-dimensional finite element method (FEM). The frequency domain simulation results demonstrate the influence of magnet cracks and their propagation on EM performance measures, such as stator current, distribution of magnetic flux density, back EMF, flux linkage, losses, and efficiency. The results show strong potential for application in health monitoring systems, which could be used to reduce the occurrence of in-service failures, thus reducing the usage of rare-earth magnet materials as well as cost. Full article

This paper investigates, experimentally and numerically, the shear strengthening of Normal Concrete (NC) beams using post-tensioning steel bars and Engineered Cementitious Composite (ECC) reinforced with chemically cured Palm Fronds (PFs). The benefits of strain-hardening ECC and the tensile strength of PFs cured with 6% wt Alkali NaOH solution beside post-tensioned bars have been employed herein. Seven full-scale Reinforced Concrete (RC) beams were fabricated and experimented with under three-point loading until failure. The test parameters include the strengthening technique, type, and configuration of the material used for strengthening. The strengthening process has been implemented through two techniques: Externally Bonded Reinforcement (EBR) and Near-Surface Mounted (NSM) Reinforcement. The strengthening materials have been configured and placed in horizontal, vertical, and inclined positions. The effectiveness of the strengthening methods has been evaluated by examining their cracking propagations, load-deflection responses, collapse modes, elastic stiffness, and absorbed energy. It was found that the proposed strengthening systems could significantly control the crack pattern and failure mode, and they could enhance the ultimate load amplitude up to 37% and 50% for NSM ECC with PFs and EBR post-tensioning steel bars, respectively. Nonlinear three-dimensional finite element models of the tested beams were developed and validated with the test data, where it was found that finite element models predict the structural performance of tested beams with a maximum error of only 2%. Full article