Search Results (131)

The estimation of leakage faults in evaporation tubes of supercharged boilers is crucial for ensuring the safe and stable operation of the central steam system. However, leakage faults of evaporation tubes feature high time dependency, strong coupling among monitoring parameters, and interference from noise. Additionally, the large number of monitoring parameters (approximately 140) poses a challenge for spatiotemporal feature extraction, feature decoupling, and establishing a mapping relationship between high-dimensional monitoring parameters and leakage, rendering the precise quantitative estimation of evaporation tube leakage extremely difficult. To address these issues, this study proposes a novel deep learning framework (LSTM-CNN–attention), combining a Long Short-Term Memory (LSTM) network with a dual-pathway spatial feature extraction structure (ACNN) that includes an attention mechanism(attention) and a 1D convolutional neural network (1D-CNN) parallel pathway. This framework processes temporal embeddings (LSTM-generated) via a dual-branch ACNN—where the 1D-CNN captures local spatial features and the attention models’ global significance—yielding decoupled representations that prevent cross-modal interference. This architecture is implemented in a simulated supercharged boiler, validated with datasets encompassing three operational conditions and 15 statuses in the supercharged boiler. The framework achieves an average diagnostic accuracy (ADA) of over 99%, an average estimation accuracy (AEA) exceeding 90%, and a maximum relative estimation error (MREE) of less than 20%. Even with a signal-to-noise ratio (SNR) of −4 dB, the ADA remains above 90%, while the AEA stays over 80%. This framework establishes a strong correlation between leakage and multifaceted characteristic parameters, moving beyond traditional threshold-based diagnostics to enable the early quantitative assessment of evaporator tube leakage. Full article

Electric submersible progressive-cavity pumps (ESPCPs) deliver high lifting efficiency but are prone to failure in the high-temperature, high-pressure, and multiphase down-hole environment, leading to production losses and elevated maintenance costs. To achieve reliable condition recognition under these noisy and highly imbalanced data constraints, we fuse deep residual feature learning, ensemble decision-making, and generative augmentation into a unified diagnosis pipeline. A class-aware TimeGAN first synthesizes realistic minority-fault sequences, enlarging the training pool derived from 360 field records. The augmented data are then fed to a CNN backbone equipped with ResNet blocks, and its deep features are classified by a Random-Forest head (CNN-ResNet-RF). Across five benchmark architectures—including plain CNN, CNN-ResNet, GRU-based, and hybrid baselines—the proposed model attains the highest overall validation accuracy (≈97%) and the best Macro-F1, while the confusion-matrix diagonal confirms marked reductions in the previously dominant misclassification between tubing-leakage and low-parameter states. These results demonstrate that residual encoding, ensemble voting, and realistic data augmentation are complementary in coping with sparse, noisy, and class-imbalanced ESPCP signals. The approach therefore offers a practical and robust solution for the real-time down-hole monitoring and preventive maintenance of ESPCP systems. Full article

The generation and propagation mechanisms of acoustic waves from leakage below the annular liquid level in gas wells have attracted widespread attention. To study the characteristics of acoustic sources beneath the liquid level, a physical model of leakage in the casing–tubing annulus was established by simulating the distribution patterns of the flow field and acoustic field within the annulus under tubing leakage conditions. Distinct from the traditional acoustic analysis of wellbore leakage in gas wells, this study focuses on acoustic waves generated by leaks located below the annular protection fluid level. It analyzes the flow regime and acoustic source characteristics beneath the liquid level under various operating conditions (including leakage aperture, velocity, and position). The research summarizes the evolution patterns of flow regimes when gas leaks into the annular protection fluid under different conditions and elucidates the generation mechanism of sub-liquid leakage noise and its propagation mechanism across the liquid surface. This work lays the theoretical foundation for detecting sub-liquid leakage at the wellhead using acoustic methods. Full article

Accurate detection of downhole tubing leakage in gas wells is essential for planning effective repair operations and mitigating safety risks in annulus pressure buildup wells. Current localization methods employ autocorrelation analysis to exploit the time-delay features of acoustic signals traveling through the tubing–casing annulus. This allows non-invasive wellhead detection, avoiding costly tubing retrieval or production shutdowns. However, field data show that multiphase flow noise, overlapping reflected waves, and coupled multi-leakage points in the wellbore frequently introduce multi-peak interference in acoustic autocorrelation curves. Such interference severely compromises the accuracy of time parameter extraction. To resolve this issue, our study experimentally analyzes how leakage pressure differential, aperture size, depth, and multiplicity affect the autocorrelation coefficients of acoustic signals generated by leaks. It compares the effects of different noise reduction parameters on leakage localization accuracy and proposes a characteristic time selection principle for autocorrelation curves, providing a new solution for precise leakage localization under complex downhole conditions. Full article

Background/Objectives: The leakage of 5-fluorouracil (5-FU) from elastomeric infusion pumps used in cancer therapy poses a potential risk of unintentional exposure to multiple individuals, including patients’ relatives and healthcare professionals, and may also compromise the accurate administration of 5-FU dosages to patients. This study aimed to develop, validate, and apply an analytical method to detect and quantify 5-FU residues on the external surfaces of infusion pumps. Methods: A high-performance liquid chromatography with diode-array detection (HPLC-DAD) method was optimized for the quantification of 5-FU contamination across different components of the infusion pump, including the hard casing, infusion tubing, and catheter connection port. A mobile phase containing 5% acetic acid was used to obtain more efficient separation of 5-FU and the detection was performed at 260 nm. The method was evaluated for linearity, sensitivity, precision, accuracy, selectivity, robustness, and stability. Results: The method demonstrated linearity within the range of 0.150 to 3.000 µg/cm², with limits of detection and quantification of 0.05 µg/cm² and 0.14 µg/cm², respectively. Relative standard deviations ranged from 1.8% to 12.7%, and accuracy exceeded 85%. In real sample analysis, detectable residues were found around the catheter connection port. Conclusions: This screening-oriented method addresses an existing gap, as previous contamination reports were based solely on self-reported user observations. The detection of 5-FU residues highlights the critical need for safe handling practices and the consistent use of personal protective equipment (PPE) to protect healthcare workers, especially nursing staff involved in the removal of the infusion pumps, after treatment. Full article

In response to the limitations of experimental methods for detecting oil and gas well tubing leaks, this study developed a full-scale indoor simulation system for oil tubing leakage. The system consists of three components: a wellbore simulation device, a dynamic leakage simulation module, and a multi-parameter monitoring system. The wellbore simulator employs a jacketed structure to replicate real-world conditions, while the leakage module incorporates a precision flow control device to regulate leakage rates. The monitoring system integrates high-sensitivity acoustic sensors and pressure sensors. Through multi-condition experiments, the system simulated complex scenarios, including leakage apertures of 1–5 mm, different leakage positions relative to the annular liquid level, and multiple leakage point combinations. A comprehensive acoustic signal processing framework was established, incorporating time–domain features, frequency–domain characteristics, and time–frequency joint analysis. Experimental results indicate that when the leakage point is above the annular liquid level, the acoustic signals received at the wellhead exhibit high-frequency characteristics typical of gas turbulence. In contrast, leaks below the liquid level produce acoustic waves with distinct low-frequency fluid cavitation signatures, accompanied by noticeable medium-coupled attenuation during propagation. These differential features provide a foundation for accurately identifying leakage zones and confirm the feasibility of using acoustic detection technology to locate concealed leaks below the annular liquid level. The study offers experimental support for improving downhole leakage classification and early warning systems. Full article

This paper proposes a novel tube hydro-joining process, which combines piercing, hole flanging, and nut inlaying. The nut punch shape design proposed by this paper can deliver three advantages of no scrap, no oil leakage, and longer flange length, which can achieve stronger clamping force and accordingly increase the pull out load. First, we use the finite element analysis to investigate the elasto-plastic deformation of the aluminum alloy A6063 tube during the hydro-joining process. A punch-shaped nut with a tapered locking part is designed to increase the elasto-binding strength of the pierced tube and the pull out load of the inlayed nut. The effects of hydro-joining loading paths on the formability of the A6063 tubes and punch-shaped nuts are examined. Additionally, the effects of fit zone size, nut punch stroke length, internal pressure, nut diameter, and the die hole diameter on the pull out load and twisting torque are explored. Finally, experiments on hydro-joining of A6063 tubes are conducted to validate the finite element modeling and the simulation results. Full article

This paper presents a discrete Fourier transform (DFT)-based signal processing framework for eddy current non-destructive testing (NDT), aiming to enhance signal quality for precise defect characterization in critical nuclear components. By enforcing strict periodicity matching between sampling points and signal frequencies, the proposed approach mitigates DFT spectrum leakage, validated via phase linearity analysis with errors of ≤0.07° across the 20 Hz–1 MHz frequency range. A high-resolution 24-bit analog-to-digital converter (ADC) hardware architecture eliminates complex analog balancing circuits, reducing system-wide noise by overcoming the limitations of traditional 16-bit ADCs. A 6 × 6 mm application-specific integrated circuit (ASIC) for array sensors enables three-dimensional (3D) defect visualization, complemented by Gaussian filtering to suppress vibration-induced noise. Our experimental results demonstrate that the digital method yields smoother signal waveforms and superior 3D defect imaging for nuclear power plant tubes, enhancing result interpretability. Field tests confirm stable performance, showcasing clear 3D defect distributions and improved inspection performance compared to conventional techniques. By integrating DFT signal processing, hardware optimization, and array sensing, this study introduces a robust framework for precise defect localization and characterization in nuclear components, addressing key challenges in eddy current NDT through systematic signal integrity enhancement and hardware innovation. Full article

The peak load boiler (PLB) is a heat production facility that uses SA178 Gr. A and SA516 Gr. 70 low-carbon steels as tube and plate materials, respectively. Recently, failures were frequently observed near plugged tubes due to water leakage, raising concerns about corrosion mechanisms and their impact on tube durability. This work investigates the corrosion failure mechanisms using a combination of endoscopy, ultrasound inspection, oxide scale analysis (X-ray diffraction), chemical analysis (ion chromatography and inductively coupled plasma mass spectrometry), and computational fluid dynamics simulations. The undamaged tube near the leaked tube exhibited oxide scale levels comparable to those directly affected. Surface examinations revealed gas-side pits indicative of localized corrosion, while oxide scales were predominantly composed of iron oxides formed under humid conditions and sodium compounds derived from boiler water. Analysis of the leaked water revealed its mixture with combustion gases, forming an acidic, chloride-rich environment that significantly accelerates corrosion. Computational fluid dynamics simulations demonstrated that leaked water vapor facilitated the condensation of acidic ions near affected tubes, promoting dew point corrosion. These phenomena, driven by localized condensation and chemical concentration at the dew point temperature, exacerbate material degradation, emphasizing the importance of targeted prevention strategies. Full article

Zirconium alloys are essential materials for nuclear fuel cladding. During a loss-of-coolant accident (LOCA), zirconium alloy cladding can oxidize in high-temperature steam (>1000 °C), generating hydrogen and releasing significant heat. Without timely emergency actions, this can result in hydrogen explosions or nuclear leakage. In this study, titanium nitride (TiN), chromium (Cr), and TiN–Cr composite coatings were deposited on the surface of Zr-4 alloy using the magnetron sputtering method. The coatings’ surface and cross-sectional morphologies were examined using scanning electron microscopy (SEM), and their phase structures were analyzed with X-ray diffraction (XRD). The mechanical properties were evaluated using scratch tests, and their resistance to high-temperature steam oxidation was tested in a tube furnace connected to a steam generator. The results showed that the TiN, Cr, and TiN–Cr coatings exhibited strong adhesion to the Zr-4 substrates, with distinct interfaces and pure phase structures. After high-temperature steam oxidation, cracks appeared on the surfaces of the TiN, Cr, and TiN–Cr coatings, likely due to differences in the thermal expansion coefficients of TiO₂, Cr₂O₃, and residual Cr layers. These cracks created pathways for the oxidizing medium, potentially leading to the oxidation of the substrate or inner layers of the composite coatings. For the Cr and TiN–Cr coatings, despite cracking of the Cr layer and melting of the TiN layer at high temperatures, the residual Cr layer effectively restricted oxygen diffusion into the Zr-4 substrate. This study suggests that layers with low melting points, such as TiN, are unsuitable for composite coatings in high-temperature applications. However, adding a Cr layer on top of the TiN layer to form a TiN–Cr composite coating improves adhesion between the coating and the substrate. The TiN–Cr composite coating functions as an effective diffusion barrier at temperatures up to 1200 °C, comparable to a pure Cr coating. Full article

The new eco-friendly flammable refrigerant in air conditioners has resulted in an annual increase in fire incidents associated with these units. Fire investigators face significant challenges in identifying the causes of these fires. In this study, copper tube samples were extracted from various locations of air conditioner condenser debris post fire. The morphology characteristics of the ruptured copper tubes formed by a high-temperature flame in fire and that formed by corrosion were analyzed, respectively. The findings indicate that the ruptures in the copper tubes of air conditioners may be classified into two types based on their origins: ruptures resulting from fire and ruptures resulting from corrosion. The ruptures in the copper tubes resulting from fire are associated with the presence of aluminum alloy fins. At elevated temperatures, the copper and aluminum atoms persist in diffusing and fracturing. A significant quantity of silver-white aluminum is present surrounding the ruptures, and distinct elemental layers may be seen in the cross-section. The corrosion-induced ruptures in the copper tubes are associated with ant nest corrosion. Despite the influence of high-temperature flame melting on surface corrosion pits, they will not entirely obscure the pits and the cross-section continues to exhibit the bifurcated structure characteristic of ant nest corrosion. This investigation demonstrates that corrosion of ant nests is the root cause of copper tube breakage obscured by flames. An investigation method for the refrigerant leakage air conditioning fire is proposed. The above findings can provide proof and method for air conditioning fire investigation. Full article

Nasopharyngeal ventilation (NPV) is a common technique used to support breathing, particularly when a patient’s respiration is inadequate, such as under sedation. It involves delivering oxygen through an endotracheal tube positioned above the glottis. Accurate tidal volume measurement is crucial for anesthesiologists, with the gold standard being a pneumotachograph. However, due to leakage from the mouth or mask, this method has limitations when applied to NPV. This study introduces a computational model that calculates respiratory flow in real time by accounting for leak flow. Results show that tidal volume measurements using this method are comparable to the gold standard, assuming the model’s assumptions hold true. Full article

Various models of ionization and fission chambers for ionizing radiation detection, designed to operate under harsh conditions such as those found in fusion reactors or particle accelerators, have been experimentally characterized and numerically simulated. These models were calibrated using a photon beam in the X-ray spectrum. Irradiations were performed at the Biomedical Research Center of the University of Granada (CIBM) with a bipolar metal-ceramic X-ray tube operating at a voltage of 150 kV and a dose rate ranging from 0.05 to 2.28 Gy/min. All detectors under study featured identical external structures but varied in detection volume, anode configuration, and filling gas composition. To assess inter- and intra-model response variations, the tested models included 12 micro-ionization chambers (CRGR10/C5B/UG2), 3 micro-fission chambers (CFUR43/C5B-U5/UG2), 8 micro-fission chambers (CFUR43/C5B-U8/UG2), and 3 micro-fission chambers (CFUR44/C5B-U8/UG2), all manufactured by Photonis (Merignac, France). The experimental setup was considered suitable for the tests, as the leakage current was below 20 pA. The optimal operating voltage range was determined to be 130–150 V, and the photon sensitivities for the chambers were measured as 29.8 ± 0.3 pA/(Gy/h), 43.0 ± 0.8 pA/(Gy/h), 39.2 ± 0.3 pA/(Gy/h), and 96.0 ± 0.9 pA/(Gy/h), respectively. Monte Carlo numerical simulations revealed that the U layer in the fission chambers was primarily responsible for their higher sensitivities due to photoelectric photon absorption. Additionally, the simulations explained the observed differences in sensitivity based on the filling gas pressure. The detectors demonstrated linear responses to dose rates and high reproducibility, making them reliable tools for accurate determination of ionizing photon beams across a range of applications. Full article

The research on the thermal insulation performance of experimental systems in the liquid helium temperature range is relatively scarce. This paper presents the theoretical design and establishment of a liquid helium storage system for insulation research, consisting of a liquid helium Dewar, a daily boil-off rate test subsystem, and a helium recovery subsystem. The passive thermal insulation structure consisted of a multilayer insulation (MLI) system with hollow glass microspheres serving as spacers. Based on self-built data acquisition, experiments were conducted to investigate the liquid helium insulation characteristics of an experimental system. A theoretical thermal analysis of the Dewar was conducted, resulting in the derivation of an expression for the heat leak of the Dewar. The analysis indicates that the evaporation capacity from the liquid helium Dewar was significantly affected by the structure of the neck tube. The overall relative error between the simulated and experimental temperature distribution of the insulation layer is 14.3%, with a maximum error of 22.3%. The system had an average daily boil-off rate of 14.4%, a heat leakage of 7.5 W, and a heat flux of 2.254 W/m², while the effective thermal conductivity of the MLI with hollow glass microspheres was determined to be 2.887 × 10⁻⁴ W/(m·K). Furthermore, the apparent thermal conductivity between different layers of MLI significantly fluctuated with increasing temperature, ranging from a maximum of 5.342 × 10⁻⁴ W/(m·K) to a minimum of 1.721 × 10⁻⁴ W/(m·K). Full article

While submissions of microfluidic-based medical devices to the Food and Drug Administration (FDA) have increased in recent years, leakage remains a common but difficult failure mode to detect in microfluidic systems. Here, we have developed a sensitive tool to measure and verify leakages ranging from 0.1% to 10% in leakage detection systems, which can then be used to detect leak in microfluidic devices. Our methodology includes an analytical model that applies hydrodynamic resistance using different fluid-contacting elements (e.g., tubing, junctions, and connectors) to tune the leakage rate based on the application-specific acceptance criteria. We then used three polymer-based microfluidic systems to target leakage rates of approximately 0.1, 1.0, and 10%. The experimental uncertainties in Polyether Ether Ketone (PEEK) tubing were 23.08%, 13.64%, and 1.16%, respectively, while the PEEK-Coated Fused Silica (PEEKsil) tubing system had errors of 0.00%, 0.72%, and 1.59%, respectively, relative to the theoretical values for the same target leak rates. The commonly used commercial grade Cyclic Olefin Copolymer (COC) microfluidic chips produced errors of 7.69% and 5.05%, respectively, for target leakage rates of 0.24% and 1.88%. We anticipate that the proposed bench test method can be useful for device developers as a verification tool for leakage detection systems before assessing flow-mediated leakage failure modes in microfluidic medical devices. Full article