Main Pipe Research Articles

Creep life prediction of 10CrMo910 steel main steam pipes based on carbide evolution and machine learning

Creep life prediction of 10CrMo910 steel main steam pipes based on carbide evolution and machine learning

Design of an Automatic Cut Chrysanthemum Cultivation Device

In practice, flexible nets are applied, but their support to chrysanthemum is insecure, unable to make it keep upright. Especially, when chrysanthemum is in full blossom, it is likely to fall, which has severely affected marketability of cut chrysanthemum. In this paper, an automatic cut chrysanthemum cultivation device has been proposed, consisting of the holding system, the irrigation and fertilization system and the control system. The holding system enables the stems of cut chrysanthemum to be upright. It is composed of the holding net, the lifting device and the support framework. The irrigation and fertilization system irrigates and fertilizes the cut chrysanthemum. It is composed of the water tank, the water pump, the filter, the macroelement fertilization tank, the macroelement fertilizer applicator, the microelement fertilization tank, the microelement fertilizer applicator, the main pipe, the branch pipe, and the water dropper. The control system controls the lifting of the holding net and start/shutdown of the irrigation and fertilization device. It is composed of the controller, the monitor, the moisture sensor and the fertility sensor. It has been proved to achieve automated irrigation and fertilization, improve the cultivation efficiency of cut chrysanthemum, and at the same time, effectively maintain the uprightness of the plants to prevent them from falling, increasing the yield and quality of finished products.

Ultrasonic Inspection Design and Application for Maincoolant Pipes of Third-Generation Nuclear Power Plants

This paper reviews the global development of third-generation nuclear power plants and examines the evolving requirements for main pipe inspection processes in the in-service inspection standards. Third-generation nuclear plants offer significant improvements in design and safety over previous generations. However, with the continued advancement of nuclear technology, the inspection technologies for primary loop main pipes face increasingly complex challenges, especially the detection of narrow gap welds, which has become a critical technical issue for nuclear plant safety. Using the operational EPR and Hualong One nuclear power plants in China as examples, the paper analyzes the characteristics, specifications, layout, and inspection scope of narrow gap welds in the main pipes. The narrow gaps and complex layouts make it difficult for conventional inspection methods to fully cover the welds, particularly in confined spaces and irregular pipe structures. Achieving high-precision, high-efficiency inspections is a key challenge for engineers. Through an in-depth analysis of the surrounding environment and nuclear island facility layout, the paper highlights the spatial constraints in the design of main pipe inspection equipment. The compact arrangement of the reactor and auxiliary facilities further complicates inspection tasks. To address these challenges, the paper introduces a lightweight, high-load automatic ultrasonic scanner designed to improve inspection efficiency in complex environments. This scanner uses advanced ultrasonic testing technology to efficiently inspect welds in confined spaces. Its core components include a high-load probe holder and a remote control system for real-time data analysis. The paper also discusses the practical application of this technology at Taishan and Hualong One nuclear power plants, where the new equipment has significantly improved inspection accuracy and efficiency, supporting safe plant operations. Finally, the paper looks forward to the future development of main pipe inspection technology, emphasizing advancements in automation, data processing, and remote operation, which will enhance the safety and efficiency of nuclear plants, supporting the sustainable growth of the global nuclear industry.

Creep Failure Behavior in the Weak Areas of 12Cr1MoV Main Steam Pipe Elbow Utilized in Thermal Power Plants.

The main steam pipe elbow is a critical metallic component in thermal power plants. Due to prolonged exposure to high temperatures and pressures, it experiences microstructural degradation and creep damage, thereby affecting its service life. Currently, there is debate regarding the location of the weakest region within the elbow, with uncertainty over whether it lies in the inner arc or neutral plane area. This study investigates the microstructure and creep properties of both the inner arc and neutral surface regions of an elbow that has been in operation for 183,088 h, aiming to identify the actual weak region and explore the underlying creep damage mechanisms. The results indicate that under identical temperature and stress conditions, samples from the neutral plane region exhibit significantly higher creep rates and shorter creep rupture times compared to those from the inner arc region. This suggests that the creep life in the vicinity of the inner surface in the neutral plane is markedly lower than that in the inner arc region. Microstructural analysis before and after creep fracture reveals that key factors influencing the creep performance of 12Cr1MoV elbows include carbide size, precipitation amount and distribution, grain size and morphology, as well as the stability and uniformity of grain orientation. Specifically, the growth of intragranular precipitates, the accumulation and non-uniform distribution of grain boundary carbides, and the non-uniform distribution of grain sizes all contribute to the rapid formation of creep cracks and premature material failure. This study concludes that the weakest region in the elbow is located at the inner surfaces of the neutral plane. Future inspections and life assessments of thermal power plant elbows should therefore focus on this area to enhance the accuracy of life evaluations and ensure the safety of thermal power plants.

Modelling of the water distribution system and determination of losses: the case of Halaba Kulito town, Central Ethiopia

As urbanization trends and aging infrastructure take hold worldwide, water utilities face mounting challenges meeting the growing demand for water. This study outlines an innovative approach to assess water supply and demand, physicochemical water quality analysis, improving leakage management using data analytics and hydraulic simulation in Halaba Kulito town of Central Ethiopia Regional State. The Water Geospatial Engineering Modeling System (WaterGEMS v8i) model was used for the hydraulic analysis of the distribution network by means of the data on the water distribution network and the master plan map of the Town. Water losses were determined by indicators including Non-Revenue Water (NRW), Losses per Service Connection (LSC), Losses per Main Pipe Length (LMPL), Current and Unavoidable Annual real Losses, CARL and UARL respectively and infrastructure leakage index (ILI). To achieve this, data was collected from the field, including geographical coordinates, altitude, water level in tanks and physical parameters of the water sampled. Besides, water production, consumption, distribution network, and population data were also collected. The nodal area, city contour and study area were drawn using ArcGIS. Google Earth Pro helped locate points in the water distribution system. Hydraulic simulations of an existing network system were carried out to ensure reliable parameters, such as pressure, head loss and water flow. The analysis showed that the current maximum daily demand of the town is 5,030 m3/day, the water supply coverage is 52% and the average water consumption per capital is 22 l/c/day. The town's NRW was identified as 27% of the total water production. The town's overall hydraulic performance was poor, reflected in low water connection, high losses and low coverage. The model simulation results showed that 70% of the pipes were in either sedimentation or stagnation, causing peak and off-peak velocities respectively and 25% of the nodes also had pressures below recommended standards at peak hours. Furthermore, the physicochemical quality of the water showed that out of 19 parameters, 16 were within the acceptable limits recommended by the World Health Organization (WHO), but the remaining parameters failed to meet the WHO standard. This requires improving the capacity and quality of water distribution networks and reducing water losses, drilling additional wells and increasing coverage. To ensure safe drinking water supplies, proper maintenance, monitoring and management are essential.

Deep Neural Network for Valve Fault Diagnosis Integrating Multivariate Time-Series Sensor Data

Faults in valves that regulate fluid flow and pressure in industrial systems can significantly degrade system performance. In systems where multiple valves are used simultaneously, a single valve fault can reduce overall efficiency. Existing fault diagnosis methods struggle with the complexity of multivariate time-series data and unseen fault scenarios. To overcome these challenges, this study proposes a method based on a one-dimensional convolutional neural network (1D CNN) for diagnosing the location and severity of valve faults in a multi-valve system. An experimental setup was constructed with 17 sensors, including 8 pressure sensors at the inlets and outlets of 4 valves, 4 flow sensors, and 5 pressure sensors along the main pipe. Sensor data were collected to observe the sensor values corresponding to valve behavior, and foreign objects of varying sizes were inserted into the valves to simulate faults of different severities. These data were used to train and evaluate the proposed model. The proposed method achieved robust prediction accuracy (MAE: 0.0306, RMSE: 0.0629) compared to existing networks, performing on both trained and unseen fault severities. It identified the location of the faulty valve and quantified fault severity, demonstrating generalization capabilities.

Effects of karst conduit structure on breakthrough curves: Experiments and modeling.

Effects of karst conduit structure on breakthrough curves: Experiments and modeling.

A Comprehensive Framework for Evaluation of Skeletonization Impacts on Urban Drainage Network Model Simulations

AbstractUrban drainage network models (UDNMs) have been widely used to facilitate flood management. Typically, a UDNM is developed using data from Geographic Information Systems (GIS), and hence it consists of many short pipes and connection nodes or manholes. To improve modeling efficiency, a GIS‐based model is generally skeletonized by removing many elements. However, there has been surprisingly a lack of knowledge on to what extent such skeletonization can affect the model's simulation accuracy, resulting in uncertainty in flood risk estimation. This paper makes the first attempt to quantitatively evaluate multidimensional impacts of different skeletonization levels on hydraulic properties of UDNMs. This goal is achieved by a new evaluation framework comprising of eight existing and new metrics that make use of hydrographs, main pipe hydraulics and flood distribution properties. A real‐life UDNM is used to illustrate the new framework under various rainfall conditions and different skeletonization levels. The new framework is also used to compare the performance of two compensation methods in mitigating impacts caused by model skeletonization. Results obtained show that: (a) model skeletonization can significantly affect the magnitude of peak flow at the outfall, with a maximum overestimation of up to 20%, (b) hydraulics in main pipes can also be affected by model skeletonization with the maximum flow increasing up to 35%, and (c) model skeletonization may significantly alter the flood distribution properties which has been largely ignored in past studies. These findings provide guidance for UDNM skeletonization, where their associated impacts should be aware in engineering practice.

Stress Prediction Processes of Metal Pressure-Bearing Complex Components in Thermal Power Plants Based on Machine Learning

The real-time stress assessment of metal pressure components is one of the key factors in ensuring the safe operation of thermal power plants. To address the challenge of real-time prediction of stress in the key areas of complex special-shaped metal pressure-bearing components in a certain domestic 300 MW thermal power plant, three typical complex metal pressure-bearing components, the main steam pipe tee (MSPT), the steam drum downcomer joint (DDJ) and the header ligament (HL), were taken as research objects. The stress distribution of the three complex metal pressure-bearing components under different conditions was analyzed through the finite element method, and the stress results at the dangerous points were used as samples to establish training sample data. Subsequently, different machine learning methods were employed to train the sample data. The training results indicate that neural networks (NNs) and the Auto-Sklearn Regression (ASR) models can accurately predict the stress of the key parts of complex metal pressure-bearing components in real time. The ASR method demonstrates better performance in stress prediction of the main steam pipe tee, with a prediction accuracy of ≥96%. The NN model shows better prediction for the header ligament, with a prediction accuracy of ≥94%. These research findings provide effective support for the high-temperature lifespan assessment and safe operation of thermal power plants.

Steam Generator Maintenance Robot Design and Obstacle Avoidance Path Planning.

To solve the issue of inconvenient and dangerous manual operation during the installation and removal of the main pipe plugging plate in the steam generator in nuclear power plants, a ten-degree-of-freedom plugging robot was designed in the present study that includes a collaborative robotic arm coupled with a servo electric cylinder. By establishing a joint coordinate system for the robot model, a D-H parameter model for the plate plugging robot was established, and the forward and inverse kinematics were solved. The volume level approximate convex decomposition algorithm was used to fit the steam generator model with a convex packet, and an experimental simulation platform was constructed. Lastly, path planning was carried out by using the RRT algorithm, with the paths divided into three phases for analysis. The simulation results show that the path in the first stage is relatively smooth, and the parameter changes in each joint are relatively stable. The path in the second stage exhibits zigzagging, with the parameter change curve of joint 9 being particularly evident, and the path in the third stage still exhibits zigzagging-the parameter change curves of joints 3 and 10 are particularly evident. The results of the present study show that, although the paths show a certain degree of zigzagging in complex environments, the plate plugging robot is still able to automatically complete the plate plugging task while avoiding obstacles, which greatly reduces the risk posed to the operator when exposed to a high-radiation environment, in addition to having certain research and application value.

Fragility analysis of nuclear steam supply system components of a pressurized water reactor

Abstract The present paper deals with the fragility analysis of the nuclear steam supply system (NSSS) at Gösgen nuclear power plant (KKG), a three-loop pressurized water reactor (PWR). The analysis covers the stability and integrity of the main NSSS components and piping: reactor pressure vessel (RPV), steam generators (SG), reactor coolant pumps (RCP), pressurizer, main coolant lines, surge line, main feedwater and main steam lines (inside the reactor building). Furthermore, the fragility of the reactor trip is analyzed with respect to failure modes associated with the RPV internals (RPVI). The fragilities are based on a probabilistic soil-structure interaction analysis with a coupled model of the reactor building and the above mentioned NSSS components/piping, see Rangelow et al. (2019. Probabilistic SSI analysis of a reactor building to facilitate fragility assessment. Transactions, SMiRT-25, Charlotte, NC, USA). The ground motion is represented by time histories corresponding to the median uniform hazard spectra (UHS) with an annual probability of exceedance of 10−4. The fragility analysis is performed according to the separation-of-variables method, following guidance documents such as EPRI (2009. Seismic fragility applications guide update, Report 1019200. Palo Alto, CA) and EPRI (2018. Seismic fragility and seismic margin guidance for seismic probabilistic risk assessments, Report 3002012994. Palo Alto, CA). For the RPV internals, the fragility is based on two non-linear analysis models: a refined one for the evaluation of the fuel assembly spacer grids and a more global one for the remaining failure modes. A combined fragility has also been derived for the RPV internals, as the union of the individual failure modes. The paper discusses the method, the input data and selected results of the analysis.

Flow separation characteristics of non-Newtonian oil and polymer solution fluids in T-junctions of offshore production platforms

Currently, offshore oil exploitation widely uses polymer flooding techniques, which result in the produced fluid exhibiting non-Newtonian characteristics. This creates an urgent need for efficient and compact separators for oil–water separation in polymer-containing produced fluids. This study establishes a numerical model for T-junctions based on the Euler–Euler multiphase flow model, Reynolds stress turbulence model, and a non-Newtonian force model. It explores the effects of various operational parameters (such as inlet oil content, inlet velocity, split ratio, and oil phase density) and structural parameters (such as branch pipe angle and number of branches) on the separation efficiency of non-Newtonian oil and polymer solution two-phase flow in T-junctions. The results indicate that reducing the inlet velocity and decreasing the branch pipe angle can significantly lower the turbulence intensity within the main pipe, promote fluid stratification, and improve separation efficiency. Particularly, at a flow split ratio of 0.5, the separation efficiency peaks. Furthermore, a comparison between heavy oil–water two-phase flow and non-Newtonian oil and polymer solution two-phase flow disclose that the former achieves a maximum separation efficiency of approximately 87% under six branch conditions, while the latter shows poorer stratification and separation efficiency in the front section of the main pipe. By investigating the key factors affecting separation performance, this study provides theoretical support for the design and development of separation devices tailored to non-Newtonian polymer-containing produced fluids.

Unscented Kalman Filtering for in-situ Bulk Identification of District Heating Meter Temperature Offsets and Service Pipe Insulation Level Detection

Unscented Kalman Filtering is applied to district heating meter data and GIS-data from a utility network to simultaneously identify temperature offsets in utility meters and service pipe insulation. Implementing estimation of the temperature in the main pipe allows for more accurate results, which also respect physical constraints. Unscented Transformations allow for easier implementation of the algorithm compared to existing solutions, as linearization is avoided. Correcting for potential offsets in the temperature measurement of the utility meter allows for a better estimation of the insulation level of the service pipe, improving the ability for the utilities to pinpoint their efforts in optimizing their renovation activities over several areas of interest.

Evaluation of chemical quality characteristics of water collected from some groundwater sources in Tabuk City during 2024

The evaluation of water quality for drinking purpose is differed from that of other purposes such as domestic uses, irrigation of for certain laboratory preparations. The aim of this study was to evaluate the chemical parameters of Tabuk groundwater compared to the local standards of drinking water quality. Samples were taken from 12 groundwater sources that are randomly selected to represent Tabuk City. Samples (500 ml) were taken from the main outlet pipe, and it were kept in clean and aseptic plastic containers. The chemical tests were conducted in the Laboratory, Food health and safety, municipality of Tabuk using the standard devices, methods and solutions. The obtained data were compared to the local quality standards of MEWA (2022). The results showed that, pH for all samples agreed with the local standard, as same as in EC, TDS and Hardness with exception of some samples. Also, the concentrations of Bicarbonate and nitrate for all samples did not exceed the upper standard limits, while sulfate and ammonia agreed with local limit of standard with some exceptions. The concentrations of fluoride and lead in all samples were far more below the upper limits, unlike the concentrations of chloride that more than 30-folds exceeded the upper limit in all samples. Lead is still far from its potential critical concentration. Ion most samples, the concentrations of Sodium and Potassium were below the upper standard limits. Moderate concentrations of Mg were recorded for most samples, but all samples contained low concentrations of Fe element far more than the upper required limit. The samples that did not agreed with the local standards should be investigated and the concentrations of Na, K, Mg and Fe should be considered seriously from their physiological requirements to human body.

Development and Demonstration of a Manually Operated Sugarcane Mother Shoot Cutter

India ranks second in the world for sugarcane cultivation after Brazil, with an area of 4.7 million hectares and a productivity of 72 tonnes per hectare. However, traditional sugarcane farming methods require significant inputs such as water, seed, labor, land and fertilizers. Additionally, conventional tools like secateurs, knives, and sickles used for removing the mother shoot are inefficient and unsafe, leading to increased physical strain, a higher risk of hand and eye injuries and excessive drudgery for agricultural laborers. This study aimed to develop a more efficient and safer tool for removing the mother shoot in sugarcane cultivation, in line with the Sustainable Sugarcane Initiative (SSI). A manually operated sugarcane mother shoot cutter was developed, incorporating key components like a main conduit pipe, secateurs, operating lever, handle and handle grip. The tool was designed for use in a standing posture, reducing effort and physical strain. After being evaluated and demonstrated to sugarcane farmers in field conditions, the developed tool proved effective. Weighing only 0.8 kg, it allows operators to work in a standing position with minimal effort. The tool cuts approximately 800 shoots per hour, resulting in a 16% time saving and a 19% reduction in costs. It not only lowers cultivation costs but also reduces human drudgery. The tool's key innovation lies in its simple design, which enables efficient operation while standing, decreasing the risk of injuries associated with traditional tools and eliminating the physical strain commonly encountered during the labor intensive process of mother shoot removal. By aligning with the principles of the Sustainable Sugarcane Initiative, the tool optimizes resource usage and enhances productivity.

Development of the new machine-learning approach in pipeline condition assessment prediction and optimizing rehabilitation strategies

Purpose This paper aims to outlines a model for water main rehabilitation in Kitchener, Ontario, using a machine-learning approach. Water main networks are vital infrastructure, requiring regular condition assessments to ensure consistent service. Budgets are often allocated for nondestructive testing methods, but using machine learning to predict network conditions offers cost benefits. Design/methodology/approach The study focuses on a prediction approach that includes the rehabilitation requirement model. The Decision Tree machine learning method was applied to predict water main pipe breaks in 2024. Based on the predictions, 24 pipes were identified for rehabilitation, and the appropriate Trenchless Rehabilitation Method was selected accordingly. Findings The model, applied to data from Kitchener, successfully predicted 24 water main pipe breaks for 2024. The largest pipe diameter was 1200 mm, and the longest length was 6977 m. A cost comparison, factoring in Environmental and Social (E&S) costs, showed that open-cut methods were 25% more expensive than Cured-in-Place Pipe (CIPP). When E&S costs were included, the total cost of the open-cut method increased by approximately 300% compared to sliplining. Originality/value Based on the pipe characteristics, CIPP lining and sliplining are recommended for rehabilitation by the City of Kitchener. This study presents a novel approach using Decision Tree machine learning techniques to predict pipe breaks, with a 97% prediction accuracy, making it a promising alternative to traditional models.

Analysis and Validation of Sponge City Construction in Mountainous Cities based on SWMM - Taking Nanan District of Chongqing as an Example

Sponge city construction is one of the key topics in today’s research. China’s sponge city construction has gradually entered the stage of optimization and effect evaluation. However, there are still some gaps in issues such as the verification of the effect of sponge cities. Therefore, in this paper, Storm Water Management Model (SWMM) is carried out by collecting data on surface runoff, waterlogging, peak flow, control rate, etc. in Nanan District of Chongqing City. At the same time, reasonable Low Impact Developments (LID) facilities such as rain gardens, permeable paving, bioretention tanks, rain barrels, rooftop rainwater harvesting and rooftop gardens are incorporated into the sponge city design and verified by using a typical rainfall process with a return period of 5a and a duration of 3 hours. The results of the study showed that the surface runoff drainage time in one catchment was 11.1% faster before and after the LID facilities were installed in contrast, the peak flow reduction rate of the main pipe was 71.55%, and the average runoff control rate in each catchment was around 40.57%. In conclusion, the LID facilities are not effective enough to reduce the rainfall runoff above the medium rainfall, while they are more effective below the medium rainfall.

Metode Pengumpulan Data Debit Air Pada Saluran Distribusi Air PDAM Makassar Berbasis IoT

Water is an important resource for human survival as well as various economic sectors. PDAM is responsible for providing water supply to the community. One of the major challenges faced in managing water supply is the problem of water loss or leakage. This research aims to overcome this problem by designing an innovative method to collect water discharge data on the distribution channel of PDAM Makassar using Internet of Things (IoT) technology. This method uses the ESP32-CAM to take images of the water meter on the main pipe and save it to a database. Optical Character Recognition (OCR) technology is used to convert the image into text that can be processed. The test results show that the average error in meter readings is 0.215% with an average accuracy rate of 98%. Overall the system works well in reading digital meters and is reliable in monitoring water consumption visually and in real-time. Thus, this method can be an effective solution in detecting water leaks and improving the efficiency of water supply management by PDAMs, as well as saving resources and operational costs.

Enhanced performance of cyclone separator through coupling of centrifugal force, electrostatic force and particle pre-charge

Enhanced performance of cyclone separator through coupling of centrifugal force, electrostatic force and particle pre-charge

Study on Mechanical and Microstructural Evolution of P92 Pipes During Long-Time Operation

To investigate the mechanical properties and microstructure evolution of P92 steel during long-term service, the operated P92 main steam pipes from the first ultra-supercritical units in China were sectioned into samples representing various service durations and stresses (0# (as-received state, 1# (82,000 h, 67.3 MPa), 2# (85,000 h, 78.0 MPa), and 3# (100,000 h, 80.3 MPa)). Thereafter, a comprehensive assessment of their mechanical properties, including tensile strength, impact, hardness, and creep resistance, as well as a detailed microstructure analysis, was carried out. The effect of stress on the aging of material properties during operation is discussed. The results show that the circumferential stress caused by the increase in the internal steam pressure can significantly promote the creep life consumption of P92 steel, resulting in the degradation of mechanical properties and the expedited aging of the microstructure. The Rp0.2 and Rm of the P92 main steam pipe at room temperature and 605 °C decreased with the service time increase, reflecting the influence of stress in operation, which is expected to be used for the residual life evaluation of P92 steel. The relationship between the impact absorption energy (FATT50), Brinell hardness, and the operating time of P92 operating pipes is non-monotonic, indicating that these parameters are not sensitive indicators of material aging due to stress. The evaluation of performance degradation in P92 operating pipes due to stress-induced aging is not reliably discernible through optical metallography alone. To achieve a thorough assessment, the use of transmission electron microscopy (TEM) is essential.