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Alkali metal catalysts show great application potential in the gasification process of coal attributed to their characteristics of high activity and reusability. However, this type of catalysts has strong water absorption, which causes the agglomerating during storage and limits pipeline transportation by water. In order to solve the hydration of alkali metal catalysts and to release them at the target temperatures, they were encapsulated by cost effective and environment friend inorganic materials. The capsules were fabricated through in situ formation of calcium carbonate as shell. The water resistance, water erosion resistance and shell rupture temperature of the capsules were tested. And the effect of temperature on the properties of capsules was studied. The microstructure and composition were characterized by SEM and XRD. The results showed that the best performance of the capsules was obtained after heat treatment at 600 °C, with the pH of catalyst solution was reduced from 13.65 to 10.89 before and after encapsulation. The percentage of capsule breakage after 2 h of water scouring was 8.46 %. And the catalysts were fully released between 700–750 °C due to the crack of shell. The shell was composed mainly of CaCO 3 -AlPO 4 -Al 4 (P 2 O 7) 3. The shell was porous in the middle, gradually denser outwards, and eventually formed a dense layer in the outer layer. This was attributed to the volume expansion caused by the reaction of calcium oxide and calcium hydroxide to form calcium carbonate. This study provides a novel approach for the transportation of alkali metal catalyst and expands its application in coal gasification. [Display omitted] • The alkali metal catalysts were successfully encapsulated by CaCO 3 shells. • The pH of catalyst was reduced from 13.65 to 10.89 before and after encapsulation. • The percentage of capsule breakage after 2 h of water scouring was 8.46 %. • The catalysts were fully released between 700–750 °C due to the crack of shell. [ABSTRACT FROM AUTHOR]

In the process of oil–gas mixing transportation, a too-high gas–oil ratio (GOR) will lead to instable flow pattern and high pipeline pressure, which has great safety risks. Therefore, it is important to determine the maximum GOR. At present, it relies mainly on commercial software to simulate the operation of the mixture transportation pipeline and the hydrothermal operating parameters to determine the maximum GOR under certain condition. This enumeration method is time-consuming and does not apply to continuously parameters. To solve this problem, a data-driven predictive model is developed. The new features are constructed by analyzing the factors influencing the transportable maximum gas–oil ratio (TMGOR), and the highly correlated features are selected from them as the new features. After analyzing the characteristics of the target variables, data mapping is performed, and the processed data set is fed into a neural network for training to obtain a data-driven predictive model of TMGOR. Finally, the validation is carried out with field data from an oilfield block in northwest China. The results showed that the average relative error of the model does not exceed 8.2% compared with the simulation results of commercial software, which has a high accuracy and can provide a rationale for the decision-making of mixed transfer in the field. [ABSTRACT FROM AUTHOR]

In response to China's dual carbon call, the petroleum industry is committed to green transformation, promoting the energy green revolution, focusing on domestic offshore CO2 -enriched oil and gas reservoirs, and carrying out offshore platform carbon capture, utilization, and storage–enhanced oil recovery (CCUS-EOR) pilot projects. CO2 continuously displaces crude oil while being injected into deep-sea oil and gas reservoirs for carbon sequestration, achieving an increase in oil recovery and residual oil recovery. However, the implementation of offshore CCUS-EOR technology relies on the safe transportation of supercritical CO2 pipelines. Due to the unique physical and chemical properties of supercritical CO2 , the safe transportation of supercritical CO2 pipelines faces multiple threats. This paper focuses on the current status of safe transportation technology for supercritical CO2 pipelines on offshore platforms, and summarizes multiple operational challenges, including obtaining high CO2 gas sources, high construction costs of pipelines, complex phase change of media, and internal and external corrosion of pipelines. The risk factors for failure of supercritical CO2 pipelines on offshore platforms were systematically identified, and the mechanism of leakage hazards of supercritical CO2 pipelines was determined. Based on the six-step cycle of pipeline integrity management, a targeted integrity management method for supercritical CO2 pipelines on offshore platforms is proposed, providing reference for improving the safety transportation technology system of supercritical CO2 pipelines on offshore platforms. [ABSTRACT FROM AUTHOR]

Over the years, Carbon Capture and Sequestration (CCS) has been recognized as a crucial element in the toolkit of measures to combat climate change. At the European Union (EU) level, CCS plays a vital role in climate policy, particularly in reducing CO2 emissions from hard-to-abate industries. However, no comprehensive legal framework covers all stages of CCS. These stages include carbon capture techniques, transportation by ships or pipelines, injection, site closure, and post-closure management. Each of these stages is regulated by different legal frameworks that address various topics such as geoengineering, climate change, industrial activities, property, transportation, port operations, waste management, dumping, health, and the environment. Critical legal questions remain unanswered, such as who is liable for discharges in the marine environment during the transportation of CO2 by ships and for the long-term management of sub-seabed storage sites. As the transportation of CO2 by ships will likely have transboundary implications, we explore the legal possibilities, limitations and risks associated with exporting CO2 streams for sequestration under the sub-seabed. [ABSTRACT FROM AUTHOR]

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pipelines are widely used as the main transportation method in petrochemical and metallurgical industries. However, the special nature of the materials transported in pipelines means they are often subjected to high temperature, high pressure and corrosive conditions. This can lead to defects, such as thinning and cracking, resulting in pipeline failure and causing serious economic losses. Therefore, regular non-destructive testing of pipelines is particularly important. This paper uses the non-destructive testing method with pulsed eddy current technology to characterise pipeline thinning and defects. A preliminary study is conducted on the pulsed eddy current detection signal patterns for pipeline crack defects with varying orientations and quantities. A more portable pulsed eddy current detection device with an extended wall thickness detection range is developed. It can achieve measurements with a maximum thickness of 30 mm for detections of pipelines with rectangular defects and thickness-stepped reduced. The experimental results are consistent with modelling results, and the accuracy for pipelines with insulation layer is also investigated. On-site measurements using the PEC system are conducted on equipment sections with pipe thickness within 20 mm in a petrochemical plant. It is confirmed that the developed PEC inspection device can accurately characterises the thickness of pipelines with 0–50 mm cladding. [ABSTRACT FROM AUTHOR]

A hydrogen economy will require the use of steel pipelines to transport and store hydrogen. Methods and materials are urgently needed to prevent the embrittlement of steel pipelines in hydrogen service. In this work, we show that hydrogen permeation into pipeline steel can be mitigated by organic inhibitors, as demonstrated by a typical organic inhibitor benzotriazole (BTA) under simulated X65 steel pipeline cathodic protection conditions. Electrochemical and surface analytical techniques were used to probe the efficiency and mechanism of hydrogen permeation inhibition. In particular, a novel multi-electrode array method was designed to probe the inhibitor film by measuring local impedance and hydrogen charging currents. The ability and efficiency of BTA to inhibit hydrogen permeation were found to be closely associated with the formation and coverage of inhibitor films on steel surfaces. A model is proposed to illustrate the mechanism of hydrogen permeation inhibition by organic inhibitors. • The efficiency and mechanism of an organic hydrogen permeation inhibitor is investigated. • A multi-electrode array was used to probe the inhibitor film formation and coverage. • The capability of hydrogen permeation inhibition is related to inhibitor film formation. • The efficiency of hydrogen permeation inhibition is affected by inhibitor film coverage. • A model is proposed to explain the mechanism of hydrogen permeation inhibition. [ABSTRACT FROM AUTHOR]

The gelation of crude oil with high wax and asphaltene content at low temperatures often results in the block of transportation pipeline in Africa. In recent years, it was reported that surface hydrophobicmodified nanoparticles have important applications in crude oil flow modification. In this work, four kinds of core-shell hybride nanoparticles by grafting poly (octadecyl, docosyl acrylate) and poly (acrylate-a-olefin) onto the surface of nano-sized SiO2 were synthesized by grafting polymerization method. The chemical structure of nanoparticles was analyzed by Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). The rheological behaviors of crude oil and precipitation of asphaltenes in the presence of nanoparticles were studied by measuring the viscose-temperature relationship curve, the cumulative wax precipitation amount, and morphology of waxes and asphaltenes. The results indicate that the docosyl polyacrylate@SiO2 nanoparticle (PDA@SiO2) can reduce the cumulative wax precipitation amount of crude oil by 72.8%, decline the viscosity of crude oil by 85.6% at 20 ℃, reduce the average size of wax crystals by 89.7%, and inhibit the agglomeration of asphaltene by 74.8%. Therefore, the nanoparticles not only adjust the crystalline behaviors of waxes, but also inhibit the agglomeration of asphaltenes. Apparently, core-shell hybride nanoparticles provides more heterogeneous nucleation sites for the crystallization of wax molecules, thus inhibiting the formation of three-dimensional network structure. The core-shell polymer@SiO2 hybride nanoparticles are one of promising additives for inhibiting crystallization of waxes and agglomeration of asphaltenes in crude oil. [ABSTRACT FROM AUTHOR]

Oil and gas pipelines are subject to soil corrosion and medium pressure factors, resulting in stress concentration and pipe rupture and explosion. Non-destructive testing technology can identify the stress concentration and defect corrosion area of the pipeline to ensure the safety of pipeline transportation. In view of the problem that the traditional pipeline inspection cannot identify the stress signal at the defect, this paper proposes a detection method using strong and weak magnetic coupling technology. Based on the traditional J-A (Jiles–Atherton) model, the pinning coefficient is optimized and the stress demagnetization factor is added to establish the defect of the ferromagnetic material. The force-magnetic relationship optimization model is used to calculate the best detection magnetic field strength. The force-magnetic coupling simulation of Q235 steel material is carried out by ANSYS 2019 R1 software based on the improved J-A force-magnetic model. The results show that the effect of the stress on the pipe on the magnetic induction increases first and then decreases with the increase in the excitation magnetic field strength, and the magnetic signal has the maximum proportion of the stress signal during the excitation process; the magnetic induction at the pipe defect increases linearly with the increase in the stress trend. Through the strong and weak magnetic scanning detection of cracked pipeline materials, the correctness of the theoretical analysis and the validity of the engineering application of the strong and weak magnetic detection method are verified. [ABSTRACT FROM AUTHOR]

The high viscosity of Indian heavy crude oils makes their pipeline transportation highly complicated and challenging. A huge pressure drop is observed while transporting heavy crude through pipelines. The present article addresses this complication by preparing a surfactant stabilized heavy crude oil-in-water (O/W) emulsion of a flowable viscosity to ease flow through pipelines. Different O/W emulsion samples were prepared with varying concentrations of a novel anionic surfactant, linear alkylbenzene sulfonic acid (LABSA), to achieve an optimized formulation based on rheological and stability studies. The article also discusses the effect of varying surfactant concentrations on interfacial tension, droplet size and distribution, and zeta potential of the developed emulsions. The optimized emulsion, having 60 vol% oil and 2 wt% surfactant, was further considered to simulate and analyze the flow characteristics (static pressure and velocity profiles) across the horizontal pipelines of three different inner diameters (0.1, 0.05, and 0.025 m) under three different inlet flow velocities (0.1, 0.05, and 0.001 m/s), using a computational fluid dynamics (CFD) approach. A remarkable decrease in the viscosity of heavy crude was noted after emulsification. Subsequently, the pressure drop across the pipeline was reduced significantly by order of three for the flow of O/W emulsion when compared to that of the heavy crude oil through a pipe diameter of 0.1 m at an inlet velocity of 0.1 m/s. The static pressure drop across the pipeline decreased with the increase in the pipe diameter; in contrast, it increased with the increase in the inlet velocity. [ABSTRACT FROM AUTHOR]

The paper provides an analysis of key parameters such as: heat transfer coefficients, flow, pressure drop, pump power, heat losses and temperature drop in the oil pipeline. Tests were performed on a real oil pipeline plant with a diameter of 457 mm and a length of 91000 m. The oil pipeline is dig into the ground at a depth of 1.5 m. As an experimental fluid, crude oil of the paraffinic type, with a pour point of +8 to +26 oC, was used. In order to improve transport properties and prevent the appearance of paraffin inside the pipeline, the crude oil was heated to a temperature in the range of +20 to +50 oC. Origin software was used to display the research results. An analysis of the key transport parameters and their mutual dependencies and influences is also given. The aim of the work is to analyze and determine the optimal parameters of crude oil transport, as well as to determine the relation between heating temperature, paraffin content, flow temperature and cooling rate, where oil solid content will not occur. For such research, paraffin type oil was chosen as the experimental fluid. [ABSTRACT FROM AUTHOR]

Copyright of Cotton Textile Technology is the property of Cotton Textile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Low-Carbon Chemistry & Chemical Engineering is the property of Low-Carbon Chemistry & Chemical Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In district cooling systems, substituting the conventional cooling medium with ice slurry represents an ideal approach to achieve economical operation. During pipeline transportation, ice slurry exhibits heterogeneous flow characteristics distinct from those of pure fluids. Consequently, investigating the flow field characteristics of non-homogeneous ice slurry, quantitatively analyzing the rheological variations and flow resistance laws due to the uneven distribution of ice particles, and standardizing the comprehension and depiction of flow patterns within ice slurry pipes hold significant theoretical importance and practical value. This study analyzes the heterogeneous isothermal flow characteristics of ice slurry in a straight pipe by employing particle dynamics and the Euler–Euler dual-fluid model. Taking into account the impact of ice particles' non-uniform distribution on the rheological properties of ice slurry, a particle concentration diffusion equation is incorporated to develop an isothermal flow resistance model for ice slurry. The flow behavior of ice slurry with initial average ice particle fractions (IPFs) ranging from 0% to 20% in DN20 horizontal straight and elbow pipes is examined. The findings reveal that the degree of heterogeneous flow in ice slurry is inversely proportional to the initial velocity and directly proportional to the initial concentration of ice particles. When the flow velocity is close to 0.5 m/s, the flow resistance of ice particles exhibits a linear positive correlation with changes in flow velocity, whereas the flow resistance of the fluid-carrying phase displays a linear negative correlation. As the flow rate increases to 1 m/s, the contribution of each phase to the total flow resistance becomes independent of the initial velocity parameter. Additionally, the drag fraction of the ice particle phase is positively associated with the initial concentration of ice particles. Furthermore, the phenomenon of "secondary flow" arises when ice slurry flows through an elbow, enhancing the mixing of ice particles with the carrier fluid. The extent of this mixing intensifies with a decrease in the turning radius and an increase in the initial velocity. [ABSTRACT FROM AUTHOR]

Carbon capture and storage technologies play crucial roles in mitigating atmospheric greenhouse gases (GHGs). Pipeline transportation is the primary method of CO2 transportation, making pipeline safety a priority. In this study, Fluent software was used to create a model for annular edge leakage flanges, which significantly differs from the traditional pinhole leakage model. This study aims to examine the impact of CO2 pipeline flow and pressure on the diffusion of gas leaking from the flange and to develop a precise correlation between the diffusion distance and substance concentration. The results indicate that an increase in flow and pressure intensifies the diffusion of the flange leakage. Specifically, for a leakage lasting 96 s at flow rates of 0.7 and 10 m3/h, the diffusion ranges for the 5% concentration alarm threshold are 0.47 and 2.86 m, respectively. Furthermore, at a speed of 10 m/s and a pressure of 0.4 MPa, the diffusion ranges for 5 and 2% alarms are similar, spanning from 0.33 to 0.35 m. This study provides theoretical support and technical improvements to ensure the safe operation of pipelines. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Copyright of Transportation Science & Technolgy is the property of Transportation Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The straight part of the corrugated steel plate (CSP) pipe-arch structure in soil may cause local buckling instability due to insufficient load-bearing capacity. Recently, composite CSP pipe-arch has been widely utilized to enhance structural stability, and their stability needs to be thoroughly investigated. This paper studies the local buckling stability problem of the straight part of composite CSP pipe-arch in soil by simplifying the soil support and introducing the inter-layer bonding effect. Based on elastic stability theory, a theoretical mechanical model of composite CSP pipe-arch was proposed. The Rayleigh–Ritz method and the semi-combined composite structure stiffness approximation were used to derive the critical buckling conditions for the straight part of the composite CSP pipe-arch. Through numerical calculation and influencing factors analysis, it is concluded that the critical buckling load of the straight part of the composite CSP pipe-arch structure is affected by the elastic modulus, thickness, Poisson's ratio, rotational restraint stiffness and side length of the straight part of the material. In particular, it is found that as the inter-layer bonding coefficient increases, the critical buckling load is improved, while the critical buckling wave number is mainly influenced by the width of the straight part, elastic modulus, and inter-layer bonding coefficient. Additionally, we discussed the coupling effect of several key parameters on the stability of the structure. The results of this study offer theoretical foundations and guidance for the application of composite CSP pipe-arch in soil engineering, such as culverts, tunnels, and pipeline transportation. [ABSTRACT FROM AUTHOR]

The transition to cleaner energy sources necessitates an in-depth understanding of the transport characteristics, losses, and opportunities associated with various gaseous fuels, including hydrogen, methane, and their mixtures, such as hythane. Hydrogen (H2), the most abundant element in the universe, is increasingly recognized as a viable alternative to fossil fuels, primarily due to its potential to reduce carbon footprints as a cleaner energy source. Gradually gaining prominence in the energy market, it is displacing other fuels such as methane. In some transport systems, hydrogen is mixed with methane (CH4) in order to reduce the carbon footprint while using the same existing production equipment. As more and more large methane consumers are implementing this mixture, we would like to see how the research has followed the market trend. An up-to-date research, development, and implementation status review is critical. This study aims to identify the main indicators of H2 and CH4 transport losses in pipes, providing a review of the state of the art in the specific literature. To deliver this, a systematic literature review (SLR) was carried out using preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology, pinpointing the research trends and results in peer review-published articles over a period of twelve years (2012–2024). Findings: this review identifies and points out, in numbers, the boundaries of the 2012–2024 timeline research. [ABSTRACT FROM AUTHOR]

To alleviate the shortage of natural gas supply, the in-situ conversion of coal to natural gas is more beneficial for advancing the clean and efficient use of energy. Since in-situ coal gas contains complex components, such as H2, CH4, and CO, their leakage poses a serious risk to human life and property. Currently, the area of consequence of the harm caused by a leak in a gathering pipeline transporting in-situ coal gas has not been clarified. Therefore, this paper adopted the method of numerical simulation to pre-study the concentration distribution of each component and determined that the main components of concern are CO and H2 components. Afterward, the diffusion law of in-situ coal gas is analyzed and studied under different working conditions, such as wind speed, temperature, pipe diameter, leakage direction, and leakage aperture ratio. The results indicate that when a pipeline leak occurs, the CO component has the largest influence range. With increasing wind speed, the warning boundary of CO rapidly expands downwind, then gradually diminishes, reaching a peak value of 231.62 m at 7 m/s. The range of influence of the leaked gas is inversely proportional to temperature and directly proportional to pipe diameter and leakage aperture ratio. When the gas leaks laterally, the diffusion early warning boundary value of each component is maximal. Among them, the leakage aperture ratio has a significant impact on the concentration distribution of in-situ coal gas, whereas the effect of temperature is relatively minor. This study contributes to an understanding of the leakage and diffusion characteristics of in-situ coal gas-gathering pipelines. [ABSTRACT FROM AUTHOR]

ABSTRACT As an important infrastructure for oil and gas transportation, the safe and stable operation of long‐distance pipelines is significant for guaranteeing national energy security and economic development. However, pipelines are susceptible to corrosion due to various factors. Therefore, it is crucial to take effective corrosion protection measures. Pulse current cathodic protection technology, as an advanced pipeline corrosion protection technology, is superior to traditional cathodic protection technology. This paper mainly summarizes the research progress of pulse current cathodic protection technology for long‐distance pipelines in recent years. It briefly discusses the protection mechanism, characteristic parameters, challenges, and development trends of pulse current cathodic protection technology, which provides a useful reference for the further promotion and application of pulse current cathodic protection technology for long‐distance transport pipelines. [ABSTRACT FROM AUTHOR]

During the transportation of hydrogen-blended natural gas (HBNG) through the natural gas pipeline network, the accuracy of the physical property model for real gas greatly influences the reliability of aerodynamic performance of compressor systems and the hydrothermal characteristics of pipeline networks. In this study, the adaptability of various equations of state (EOS) in predicting physical property parameters including compressibility factor, enthalpy difference, entropy difference, specific heat capacity, specific heat ratio and viscosity of natural gas (NG) and HBNG is evaluated based on the experimental data and NIST REFPROP firstly. The properties calculated using NIST REFPROP are compared with those from the EOSs, such as cubic EOSs (Redlich–Kwong EOS (RK), Soave–Redlich–Kwong EOS (SRK), Peng–Robinson EOS (PR)) and Soave-Benedict-Webb-Rubin (BWRS) EOS. After confirming the reliability of NIST REFPROP as the calculation benchmark, the accuracy of the four EOSs in calculating the physical properties of HBNG is assessed within the temperature range of 250∼350 K, pressure range of 1∼25 MPa, and hydrogen doping ratio of 0%–30%. Besides, the mixing rules of different equations of state (EOSs) are compared based on the NIST REFPROP calculation results. The results indicate that, except for specific heat capacity calculation, the mixing rule has little influence on the prediction accuracy of cubic EOS models, and the maximum calculation error between different mixing rules of the same EOS model does not exceed 0.5%. Under specific conditions, the traditional mixing rule exhibits better prediction accuracy and can be prioritized due to its simplicity. Furthermore, the pressure has a significant impact on the accuracy of EOS models, with the prediction accuracy decreasing as the pressure increased. The influence of temperature on the prediction accuracy is less significant than that of pressure. Generally, lower temperatures exhibit lower prediction accuracy, while higher temperatures show higher prediction accuracy. Among the cubic EOS models, the RK equation performs better than the SRK and PR EOS models. While the cubic EOSs show minimal differences in predicting specific heat ratio with an average relative error below 1%, the RK EOS shows significant advantages in predicting other physical parameters. The simple structure of RK EOS meets the calculation requirements for HBNG engineering. The comprehensive comparisons reveal that, the BWRS EOS has higher accuracy in predicting various physical properties parameters, with the maximum average relative error not exceeding 5% for each physical property parameter, and its stability is also better compared to the cubic EOSs. The further analysis shows that, the calculation of viscosity is influenced not only by the EOS but also by the viscosity model. When calculating viscosity using the LU-Model, the PR EOS provides the most accurate results. In contrast, when utilizing the LGE-Model or LBC-Model, the BWRS EOS demonstrates superior accuracy compared to other EOSs. • Mixing rules slightly effect state equations' accuracy across different x-H2, besides heat capacity calculations. • Unlike other parameters, the viscosity calculation depends on both the viscosity model and the equations. • Apart from viscosity calculations, Redlich-Kwong equation performs the best among the cubic state equations. • The Benedict-Webb-Rubin-Starling equation is more accurate than the cubic state equations overall. • The impact of pressure on equations' accuracy for hydrogen-blended natural gas is more obvious than that of temperature. [ABSTRACT FROM AUTHOR]

Hydrogen production is a vital development trend to improve the economics and penetration rate of offshore wind farms (OWFs), and distributed hydrogen production (DHP) is a preferred solution for deep and far sea OWFs without expensive submarine cables and offshore substations. The export pathway of OWF-DHP consists of collection pipelines, transmission pipelines, and offshore compressor stations. In this paper, mathematical programming is introduced to explore the export pathway planning problem of OWF-DHP. Firstly, the area of OWF is discretized into multiple grids with the center of the grids being the candidate locations of the offshore compressor station. Then, a binary integer quadratic programming problem is established to optimize both the offshore compressor station location and pipeline construction with different topologies. Further, the mathematical model is solved by the branch and cut algorithm integrated with the proposed dimension reduction methods. Finally, the effectiveness of the proposed export pathway planning approach is verified by the actual data of Baltic Eagle OWF in Germany, which would support the construction of the OWF-DHP project. [Display omitted] • Studying export pathway planning (EPP) for OWF-distributed hydrogen production. • Introducing mathematical programming to model EPP as a BIQP problem. • Proposing dimension reduction methods to accelerate BIQP problem solving. • Verifying the effectiveness of the EPP approach with the Baltic Eagle OWF case. • Conducting sensitivity analysis on transportation carrier and pipeline topology. [ABSTRACT FROM AUTHOR]

Objective To support achieving the "dual carbon" goals by clarifying the adaptability and economic feasibility of CO2 pipeline transportation under different phases. Methods This study is set against research on key CCUS-EGR technologies in the carbonate gas reservoirs of PetroChina Southwest Oil and Gas Field. We optimized and established economic estimation models for CO2 pipeline transportation in three phases: gas phase, liquid phase, and supercritical phase. The impacts of flow rate, transportation distance, and transportation volume on the relative total cost were analyzed. Results The findings indicate that: first, the minimum transportation costs follow the order: gas phase pipeline> liquid phase pipeline> supercritical pipeline; second, the economical flow rate ranges are 3.0- 4.0 m/s for gas phase, 1.0-1.8 m/s for liquid phase, and 2.0-2.4 m/s for supercritical phase; third, the relative total cost increases with transportation distance at different conveying distances; fourth, the relative total cost also increases with transportation volume at different throughput, where the transportation cost for pipe diameters above DN200 rises slowly with volume, whereas the cost for DN100 diameter pipes varies significantly with volume. Conclusion By establishing an economic estimation model for CO2 pipeline transportation and analyzing its economic feasibility under different phases, this study provides a solid basis and reference for constructing CO2 pipeline transportation projects. [ABSTRACT FROM AUTHOR]

With the high-quality development and construction of national economic and livelihood projects, oil and gas have become an important strategic reserve resource for China's economic, political and military security, and the foundation and driving force for comprehensive development and modernization. Among them, the oil and gas pipelines used to transport oil and natural gas are known as the main arteries of national energy development. Due to the high flammability and explosiveness of oil and gas products, the high risk in the operation of oil and gas pipelines, the large number of key components of infrastructure and the complexity of the system, and the frequent occurrence of oil and gas pipeline failure accidents at home and abroad, the research on the prevention and control of oil and gas pipelines in China is still lacking in systematization. This paper systematically reviews the development trend of accident causation theory, leakage monitoring technology and numerical simulation research at home and abroad, and on this basis, summarizes the challenges faced in constructing a systematic accident causation analysis model and the whole life cycle detection simulation, so as to provide a reference for improving the operation safety of oil and gas pipelines in China. [ABSTRACT FROM AUTHOR]

The disposal of tailings has always been a focal point in the mining industry. Semi-dry tailings stockpiling, specifically high-concentration tailings stockpiling, has emerged as a potential solution. To enhance the stability of tailings stockpiling and minimize its costs, the incorporation of a low-cost curing agent into high-concentration tailings is essential. Therefore, this study focuses on the development of a curing agent for high-concentration unclassified tailings stockpiling. The composition of a low-cost curing agent system is determined based on theoretical analysis, and the curing reaction mechanisms of each composition are researched. Subsequently, an orthogonal experiment is designed, and the strength of the modified unclassified tailings solidified samples at different curing ages is measured. Furthermore, the rheological properties of the modified unclassified tailings slurries are tested, and the feasibility of industrial transportation of the unclassified tailings slurries modified with the optimized curing agent is analyzed. Lastly, the microscopic morphologies of each material and the modified unclassified tailings solidified samples are characterized, their chemical compositions are tested, and the action mechanism of the curing agent in the curing system is further investigated. The results show that the optimal proportions of each material in the curing agent are as follows: slag, 58%; quicklime, 15%; cement, 8%; gypsum, 9%; and bentonite, 10%. The dominance of industrial waste slag exceeding 50% reflects the low-cost nature of the curing agent. Under this condition, the modified unclassified tailings slurry with a mass concentration of 75% exhibited a yield stress of 43.62 Pa and a viscosity coefficient of 0.67 Pa·s, which is suitable for pipeline transportation. These findings lay a foundation for subsequent decisions regarding stockpiling processes and equipment selection. [ABSTRACT FROM AUTHOR]

Wax deposition of diesel oil and contamination of gasoline by diesel wax deposit is a severe problem in sequential transportation of product oil in pipes. However, it has long been neglected by the pipeline transportation industry. In response, this work aims to present a unique perspective on wax deposition of diesel oil and consequent contamination of gasoline. A cold finger apparatus was designed and constructed. Model oil composed of diesel and refined wax was prepared for wax deposition. Shear dispersion was excluded for wax deposition of diesel oil. Moreover, dissolution experiments of diesel wax deposit in gasoline were conducted. It was found that the dissolution rate increases with oil temperature and decreases with cold finger temperature and shear stress. Analysis on gasoline quality after diesel wax deposit dissolution indicated that contamination of gasoline caused by diesel wax deposit severely deteriorates its distillation range, but the octane number remains acceptable. This work features an interesting investigation on the wax-deposition mechanism of diesel oil, dissolution characteristics of diesel wax deposit, as well as quality deterioration of subsequent gasoline. It would be helpful in scheduling a product oil-transportation program. [ABSTRACT FROM AUTHOR]

Mineral slurry preparation and pipeline transport require careful particle size distribution and additive selection to ensure cost-effective and reliable transportation. The research described here was aimed to better understand the flow behavior of a limestone sample by combining coarse and fine particles and a low-cost natural additive, Saponin, derived from Sapindus laurifolia. Four distinct bi-modal suspension samples were formed using various mixtures of limestone samples with sizes varying from 0–53 and 75–106 µm. The rheological characteristics of the suspension were investigated at shear rates of 50 to 500 s−1 for solid concentrations 40–70% by weight. The additive's critical micelle concentration was found to be 1.8 weight percent. The Hershel-Bulkley model fits the experimental data the best. The appropriate proportion of coarse particles was discovered to be 30% based on critical factors such as apparent viscosity and pressure drop. The addition of the surfactant reduced the surface tension, increased the wettability, and decreased the particle-particle interaction to stabilize the limestone-water suspension. [ABSTRACT FROM AUTHOR]

Under the trend of carbon neutrality, the adoption of electric mineral transportation equipment is steadily increasing. Accurate monitoring of the operational status of electric check valves in diaphragm pumps is crucial for ensuring transportation safety. However, accurately identifying the operational characteristics of electric check valves under complex excitation and noisy environments remains challenging. This paper proposes a monitoring method for the status of electric check valves based on the integration of Adaptive Focal Loss (AFL) with residual networks and Extreme Learning Machines (AFL-ResNet-ELMs). Firstly, to address the issue of unclear feature representation in one-dimensional vibration signals, grayscale operations are employed to transform the one-dimensional data into grayscale images with more distinct features. Residual networks are then utilized to extract the state features of the check valve, with Extreme Learning Machines serving as the feature classifier. Secondly, to overcome the issue of imbalanced industrial data distribution, a new Adaptive Focal Loss function is designed. This function focuses the training process on difficult-to-classify data samples, balancing the recognition difficulty across different samples. Finally, experimental studies are conducted using industrially measured vibration data of the electric check valve. The results indicate that the proposed method achieves an average accuracy of 99.60% in identifying four health states of the check valve. This method provides a novel approach for the safety monitoring of slurry pipeline transportation processes. [ABSTRACT FROM AUTHOR]

The transportation of coal-based solid waste filling slurry (CSWFS) through pipelines for underground goaf injection is essential for enhancing mine safety and promoting green, low-carbon coal mining. To address the issue of pipeline blockage caused by the suspension sensitivity of CSWFS during long-distance transportation, this study proposes the addition of the suspending agent hydroxypropyl methyl cellulose (HPMC) to transform the filling slurry into a stable suspending slurry. The mechanism by which the suspending agent modifies the rheological property of CSWFS was elucidated and verified. Firstly, an evaluation index system for the suspending state of CSWFS based on the "experimental test and theoretical calculation" was established. The values for layering degree, bleeding rate time-loss, and the corresponding average time-loss rate over 0 to 120 min of A1–A5 CSWFS were recorded as 24 mm–2 mm, 3.0–0.2%, 252.4–54.2%, and 149.6–14.6%, respectively. The concentration gradient evaluation result, C/CA = 0.91 (≥0.8), confirmed that the suspending agent maintained a stable suspending state over time for CSWFS. Secondly, it was demonstrated that the suspending agent HPMC modified the rheological property of A1–A5 CSWFS by increasing its plastic viscosity, which strengthened the viscous resistance to particle settling, thereby transforming a semi-stable slurry into a stable one. Additionally, the formation of a spatial suspending network by the suspending agent ensures that no pipeline blockage accidents occured in practical engineering applications. Furthermore, the XRD and SEM tests were utilized to verify the microstructure of the top (T) and bottom (B) samples in A4 block. It was concluded that the type of hydration products, occurrence forms, lapping compactness, and microstructural development were consistent, ultimately forming a high-strength, dense, hardened filling block. Finally, numerical simulation confirmed that the addition of suspending agent in A4 slurry formed a comprehensive spatial suspending network and a well-structured, unified system. This is one effective approach which could contribute to addressing the technical issue of pipeline blockage during long-distance pipeline transportation. [ABSTRACT FROM AUTHOR]

Pipelines are the most common way to transport crude oil. The crude oil developed from different fields is mixed first and then transported. The pour point of mixed crude oil is very important for pipeline schemes and ensuring the safe, efficient, and flexible operation of the pipeline. An integrated machine learning model based on XGBoost is identified as optimal to predict the pour point of mixed crude oil by comprehensive comparison among six different types of machine learning models: multiple linear regression, random forest, support vector machine, LightGBM, backpropagation neural network, and XGBoost. A mixed crude oil pour point prediction model with strong engineering adaptability is proposed, focusing on enhancing the flexibility of machine learning model inputs (using density and viscosity instead of component crude oil pour points) and addressing challenges such as data volume and input missing in engineering scenarios. With the inputs of pour point Tg, density ρ, viscosity μ, and ratio Xi in component oils, the mean absolute error of the model prediction estimations after training with 8912 data is 1.12 °C, when the pour point Tg of the component crude oil is missing, the mean absolute error is 1.93 °C and the percentage of the predicted absolute error within 2 °C is 88.0%. This study can provide support for the intelligent control of flow properties of pipeline transport mixed oil. [ABSTRACT FROM AUTHOR]

Copyright of Natural Gas Industry is the property of Natural Gas Industry Journal Agency and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Natural Gas Industry is the property of Natural Gas Industry Journal Agency and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose:Taking the tailings discharged from a tin ore beneficiation plant in Yunnan as the object, this study analyzes the influencing factors of tailings slurry pipeline transportation mode and sand transportation efficiency through experimental research and numerical simulation. Method: The distribution pattern of tailings gradation was measured through water screen test, and the rheological characteristics of slurry were measured through slurry rheological test. Combined with ANSYS-FLUENT, the slurry pipeline transportation model was simulated and calculated. Conclusion: By comparing and analyzing the shortcomings criteria of Wasp et al.,a new criterion for pipeline transportation mode based on particle size distribution was proposed. The sand transportation efficiency was calculated by combining the distribution model and rheological parameters. The absolute error between the results and the measured values was within 5%,indicating that the new criterion is reasonable. At the same time, a new model for calculating sand transportation efficiency was constructed. Significance: The research provides a new criterion for the pipeline transportation mode of tailings slurry, which can provide a certain reference value for the application of similar situations in mine tailings slurry pipeline transportation. [ABSTRACT FROM AUTHOR]

As one of the important parameters of flow characteristics, flow velocity occupies an important position in the study of vertical pipeline lifting efficiency. To more accurately measure flow velocity and reveal the flow dynamics of vertical pipeline conveying systems, we focus on the solid–liquid two-phase flow in pipelines. In this paper, we study the method of pipeline velocity measurement and reveal the flow characteristics of the pipeline system. First, we use a high-speed camera to transform the flow velocity measurement into a computer vision problem, and combine the computer vision problem with deep learning technology to propose an A-RAFT (attention-based recurrent all-pairs field transforms) neural network model based on the attention mechanism. The model uses a convolutional layer to extract feature information and reduces the computational load through a pooling layer. Additionally, we introduce a correlation layer to perform inter-correlation operations on the feature information and calculate pixel displacement. In this process, the attention mechanism focuses on regions with flow velocity changes, enhancing the ability of the network to estimate velocity field variations. This helps the model better select and focus on key features in the input data, providing more accurate feature information for matching. Consequently, the estimation accuracy of the model is improved, particularly for the boundary regions of solid particles in solid–liquid two-phase flow. The model also effectively estimates flow rates for particles of varying shapes and sizes, with enhanced overall performance and accuracy. In addition, this paper constructs a combined real and virtual dataset for training the neural network model. The dataset is based on nine types of classical single-phase flow field data, and real particle texture information is fused into the dataset through real experiments to enhance data diversity. This dataset effectively simulates the optical flow changes of the pixels in the front and back frames in real experiments. The proposed model is evaluated with this dataset, and the results show that the model achieves high-precision velocity field computation on synthetic images, and the estimation error is 15.6% lower than those of other existing models. In the simulation experiments of solid particle transportation in vertical pipelines, the proposed model demonstrates accurate estimation performance on the collected real flow field data, with relative errors of lower than 5% for the measurement of particle velocities. These errors are derived from comparisons with the true values. The results validate the method in terms of both estimation accuracy and the generalization ability of the model. This study can provide new insights for solid–liquid two-phase flow characterization in energy extraction, tunneling, wastewater treatment, and long-distance pipeline transportation.

For industries like the cement industry, switching to a carbon-neutral production process is impossible. They must rely on carbon capture, utilization and storage (CCUS) technologies to reduce their production processes' inevitable carbon dioxide ( CO 2 ) emissions. For transporting continuously large amounts of CO 2 , utilizing a pipeline network is the most effective solution; however, building such a network is expensive. Therefore minimizing the cost of the pipelines to be built is extremely important to make the operation financially feasible. In this context, we investigate the problem of finding optimal pipeline diameters from a discrete set of diameters for a tree-shaped network transporting captured CO 2 from multiple sources to a single sink. The general problem of optimizing arc capacities in potential-based fluid networks is already a challenging mixed-integer nonlinear optimization problem. The problem becomes even more complex when adding the highly sensitive nonlinear behavior of CO 2 regarding temperature and pressure changes. We propose an iterative algorithm splitting the problem into two parts: (a) the pipe-sizing problem under a fixed supply scenario and temperature distribution and (b) the thermophysical modeling, including mixing effects, the Joule–Thomson effect, and heat exchange with the surrounding environment. We demonstrate the effectiveness of our approach by applying our algorithm to a real-world network planning problem for a CO 2 network in Western Germany. Further, we show the robustness of the algorithm by solving a large artificially created set of network instances. [ABSTRACT FROM AUTHOR]

Copyright of Petroleum Geology & Oilfield Development in Daqing is the property of Editorial Department of Petroleum Geology & Oilfield Development in Daqing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to develop a sustainable freight transportation network considering capacitated cross-docks for minimising the overall supply chain costs, including carbon emission cost. The problem is inspired by a major retail company based in India, which would like to expand its product portfolio in the new region. A mathematical model is developed to minimise total costs encompassing transportation cost, pipeline and retailers inventory cost, fixed cost of cross-dock and carbon emission costs. The deterministic time dependant demand, multiple products and multiple sourcing and distribution are some of the challenges faced by the retail industry. A two-level self-adaptive variable neighbourhood search algorithm is applied to solve a computationally complex problem. The results based on a two-level self-adaptive variable neighbourhood search algorithm are compared with the variable neighbourhood search algorithm to test the robustness of the developed model. Results reveal that an increase in retailers over suppliers significantly influences the number of open cross-docks. A multiple-case scenario approach captures the implications of varying capacity on the number of open cross-docks; thus, supporting the freight distribution managers in making sustainability-driven decisions. [ABSTRACT FROM AUTHOR]

We investigate the challenges and options for repurposing existing natural gas pipelines for hydrogen transportation. Challenges of re-purposing are mainly related to safety and due to the risk of hydrogen embrittlement of pipeline steels and the smaller molecular size of the gas. From an economic perspective, the lower volumetric energy density of hydrogen compared to natural gas is a challenge. We investigate three pipeline repurposing options in depth: a) no modification to the pipeline but enhanced maintenance, b) use of gaseous inhibitors, and c) the pipe-in-pipe approach. The levelized costs of transportation of these options are compared for the case of the German Norddeutsche Erdgasleitung (NEL) pipeline. We find a similar cost range for all three options. This indicates that other criteria such as the sunk costs, public acceptance, and consumer requirements are likely to shape the decision making for gas pipeline repurposing. • Three options for repurposing a natural gas pipeline to use with hydrogen are considered. • The levelized costs of hydrogen transport of each option are calculated. • The calculations are for the case study of the NEL pipeline in Germany. • Levelized costs of hydrogen transport are similar between the three options. [ABSTRACT FROM AUTHOR]

Hydrogen is a promising solution for the decarbonisation of several hard-to-abate end uses, which are mainly in the industrial and transport sectors. The development of an extensive hydrogen delivery infrastructure is essential to effectively activate and deploy a hydrogen economy, connecting production, storage, and demand. This work adopts a mixed-integer linear programming model to study the cost-optimal design of a future hydrogen infrastructure in presence of cross-sectoral hydrogen uses, taking into account spatial and temporal variations, multiple production technologies, and optimised multi-mode transport and storage. The model is applied to a case study in the region of Sicily in Italy, aiming to assess the infrastructural needs to supply the regional demand from transport and industrial sectors and to transfer hydrogen imported from North Africa towards Europe, thus accounting for the region's role as transit point. The analysis integrates multiple production technologies (electrolysis supplied by wind and solar energy, steam reforming with carbon capture) and transport options (compressed hydrogen trucks, liquid hydrogen trucks, pipelines). Results show that the average cost of hydrogen delivered to demand points decreases from 3.75 €/kg H2 to 3.49 €/kg H2 when shifting from mobility-only to cross-sectoral end uses, indicating that the integrated supply chain exploits more efficiently the infrastructural investments. Although pipeline transport emerges as the dominant modality, delivery via compressed hydrogen trucks and liquid hydrogen trucks remains relevant even in scenarios characterised by large hydrogen flows as resulting from cross-sectoral demand, demonstrating that the system competitiveness is maximised through multi-mode integration. [Display omitted] • A hydrogen supply chain model is extended to study delivery to multi-sector demand. • Industrial uses impose flat profiles with large quantities, while mobility demand is more variable. • The cost-optimal hydrogen infrastructure relies on combined transport modes. • Cross-sectoral deployment of hydrogen has positive impact on the cost of infrastructure. [ABSTRACT FROM AUTHOR]

In the field of CO2 capture and sequestration, ensuring the safety of pipeline infrastructure is paramount to successful climate change mitigation efforts. This study investigates the dynamics of CO2 dispersion from pipeline systems, assessing not only the transport process but also the physical properties and associated hazards. Advanced simulation techniques are used to model how different states of CO2 (gas, liquid, and supercritical) and varying pipeline characteristics—such as perforation sizes, flow rates, and orientations—affect the dispersion patterns in the event of a leak. Simulations cover a range of atmospheric conditions, emphasizing the role of atmospheric stability and wind speed in shaping dispersion and defining potential impact zones. An analysis of historical pipeline accidents is included to inform risk management strategies. The results show that the orientation of the pipeline has a significant effect on dispersion, with downward leaks causing the largest impact zones, particularly under supercritical conditions. The results highlight the need for adaptive safety strategies that take into account real-time CO2 transport conditions and localized environmental data. By integrating these factors, the study recommends refining safety protocols and emergency response strategies to improve pipeline resilience and public safety against potential leaks. Key findings include the quantification of the relationship between leak parameters and dispersion areas, providing a valuable framework for future safety improvements. [ABSTRACT FROM AUTHOR]

Deep-sea mining, as a critical direction for the future development of mineral resources, places significant importance on the mechanical characteristics of its transportation pipelines for the safety and efficiency of the entire mining system. This paper establishes a simulation model of the deep-sea mining system based on oceanic environmental loads and the mechanical theory of deep-sea mining transportation pipelines. Through a static analysis, the effective tension along the pipeline length, the maximum values of bending moment, and the minimum values of bending radius are determined as critical points for the dynamic analysis of pipeline mechanical characteristic monitoring. A dynamic simulation analysis of the pipeline's mechanical characteristics was conducted, and simulation sensor data were obtained as inputs for the prediction model construction. A prediction model of pipeline mechanical characteristics based on the BP neural network was constructed, with the model's prediction correlation coefficients all exceeding 0.95, enabling an accurate prediction of pipeline state parameters. [ABSTRACT FROM AUTHOR]

Hydrogen safety remains a paramount concern in pipeline transportation. Once hydrogen leaks and ignites, it quickly escalates into a jet fire incident. The substantial thermal radiation released poses significant risks of fire and explosion. Therefore, studying the thermal radiation characteristics of hydrogen jet fires and developing accurate prediction models are crucial for establishing relevant safety standards. To address the oversimplified consideration of weighted coefficients in thermal radiation prediction models, this study investigated the thermal radiation characteristics of hydrogen jet fire by carrying out experiments and numerical simulations. The results reveal the significant impacts of the leakage diameter and pressure on thermal radiation. Increases in both the leakage diameter and pressure lead to a rapid escalation in the thermal radiation release, highlighting their critical importance in establishing safety standards for hydrogen pipeline transportation. Additionally, this study optimized the weight coefficients in the multi-point source prediction model based on temperature distribution along the flame axis. The optimized model was validated through comparison with experimental data. After optimization, the prediction error of the multi-point source radiation model was reduced from 19.5% to 13.9%. This model provides significant support for accurately evaluating the risk of hydrogen jet fire. [ABSTRACT FROM AUTHOR]

In the context of dual-carbon strategy, the insulation performance of the gathering and transportation pipeline affects the safety gathering and energy saving management in the oilfield production process. PCM has the characteristics of phase change energy storage and heat release, combining it with the gathering and transmission pipeline not only improves the insulation performance of collecting and transporting pipes, but also extends the safe shut time during the shutdown. Proposed a thermal model of a PCM-based composite energy storage pipeline combining the character of phase transformation between PCM and crude oil has been established. The heat preservation performance of the combined energy storage pipeline was evaluated by numerical simulation.This paper analyses the heat transfer performance of complex energy storage pipes, and considers the influence of natural convection and variable temperature zone on insulation performance.On this basis, the structure design of cascade phase transition was proposed, the optimized cascading composite pipe was presented, and the performance of different insulation structures was compared. [ABSTRACT FROM AUTHOR]

Gas–liquid two-phase bubbly flow has significant applications across multiple fields, including reactor design and separation processes in chemical engineering, oil well extraction and pipeline transportation in the oil and gas industry, cooling systems in the nuclear industry, and wastewater treatment in environmental engineering. Bubble monitoring is crucial in these applications as it can enhance mass and heat transfer efficiency, improve flow stability, and ensure the safe operation of systems. This study developed an advanced algorithm aimed at precisely detecting and segmenting small bubbles at the gas–liquid interface using semantic segmentation techniques. This technology leverages deep learning models to analyze images, automatically identifying bubbles at the gas–liquid interface and accurately delineating their boundaries. The technique provides precise contours for each bubble, offering essential foundational data for further bubble dynamics analysis. Building on this, the deep learning detection algorithm was combined with the Deep Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT) algorithm, tracking algorithm, enabling the system to rapidly and accurately identify and track the movement of the same bubble across consecutive frames. [ABSTRACT FROM AUTHOR]

Some of the foremost parameters effecting the slurry rheology, preferably the slurry concentration, particle size distribution, and modal distributions, were studied in the current findings, figuring out the variation in shear stress and apparent viscosity using a rotational rheometer. The particle size considered for the test ranges from fine particle size of −75 µm to coarse particle size of +75–300 µm, separated at varied size fractions of +75–105, +105–150, +150–210, and +210–300 µm. The −75 µm bauxite slurry at 60 wt% has shown a maximum static settled concentration (Cw-max) under gravity after 48 h free settlement. This fine particle slurry at varying concentrations of Cw = 45–65% is discerned to behave like a Non-Newtonian Bingham plastic fluid at lower concentrations, unlike the other coarse fraction bauxite slurries at Cw = 55%, which exhibit shear thickening behavior. The present work carried out adds knowledge on the rheological behavior of bimodal, trimodal, and multimodal with four and five different size fraction bauxite slurries in finding the optimum mass concentration for a particle size fraction of (coarse):(fine), obtained in the ratio (25):(75), (25:25):(50), (25:25:10):(40), and (15:15:15:15):(40), respectively of the total 60 wt%. Certain parameters, like yield stress, consistency index (k), and flow behavior index (n), were estimated upon fitting the modal distributions to the Herschel Bulkley model to choose the best particle size distribution of the bauxite sample showing improved slurry stability, rheology, and flow characteristics. [ABSTRACT FROM AUTHOR]

Copyright of Chemical Engineering (China) / Huaxue Gongcheng is the property of Hualu Engineering Science & Technology Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the rapid development of the pipeline transportation and exploitation of mineral resources, there is an urgent requirement for high-performance polymer matrix composites with low friction and wear, especially under oxidative and prolonged working conditions. In this work, ultra-high-molecular-weight polyethylene (UHMWPE) matrix composites with the addition of carbon fibers (CFs), TiC, and MoS2 were prepared by the hot press sintering method. The influence of thermal oxygen aging time (90 °C, 0 h–64 h) on their mechanical and frictional performance was investigated. The results showed that TiC ceramic particles can increase wear resistance, especially by aging times up to 32 and 64 h. The wear mechanisms were analyzed based on the results of SEM images, EDS, and Raman spectra. The knowledge obtained herein will facilitate the design of long-service-life polymer matrix composites with promising low friction and wear performances. [ABSTRACT FROM AUTHOR]

Pipeline transportation is the main means of transportation of oil, natural gas and other energy sources. During transportation, corrosive substances in oil and natural gas can cause damage to the pipeline structure. A non-destructive testing technology for pipeline corrosion based on electromagnetic ultrasound technology was proposed to improve the stability and safety of energy pipeline transportation systems. This technology utilized empirical mode decomposition and singular spectrum analysis to denoise electromagnetic ultrasound signals. The designed electromagnetic signal denoising algorithm completely removed mild noise pollution. When using this method to detect pipeline corrosion, the maximum calculation error of pipeline wall thickness was 0.1906 mm, and the lowest was 0.0015 mm. When detecting small area corrosion deficiency, the amplitude of the detection signal increased with the depth, up to a maximum of around 24 V, which accurately reflected small area defects. This non-destructive testing technology for pipelines can effectively detect the pipeline corrosion, which is helpful for the regular maintenance of pipeline energy transmission systems. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)