Numerical study on local scour characteristics around submarine pipelines in the Yellow River Delta silty sandy soil under waves and currents

Due to their high reliability and cost-efficiency,submarine pipelines are widely used in offshore oil and gas resource engineering.Due to the interaction of waves,currents,seabed,and pipeline structures,the soil around submarine pipelines is prone to local scour,severely affecting their operational safety.With the Yellow River Delta as the research area and based on the renormalized group(RNG)k-εturbulence model and Stokes fifth-order wave theory,this study solves the Navier-Stokes(N-S)equation using the finite difference method.The volume of fluid(VOF)method is used to describe the fluid-free surface,and a threedimensional numerical model of currents and waves-submarine pipeline-silty sandy seabed is established.The rationality of the numerical model is verified using a self-built waveflow flume.On this basis,in this study,the local scour development and characteristics of submarine pipelines in the Yellow River Delta silty sandy seabed in the prototype environment are explored and the influence of the presence of pipelines on hydrodynamic features such as surrounding flow field,shear stress,and turbulence intensity is analyzed.The results indicate that(1)local scour around submarine pipelines can be divided into three stages:rapid scour,slow scour,and stable scour.The maximum scour depth occurs directly below the pipeline,and the shape of the scour pits is asymmetric.(2)As the water depth decreases and the pipeline suspension height increases,the scour becomes more intense.(3)When currents go through a pipeline,a clear stagnation point is formed in front of the pipeline,and the flow velocity is positively correlated with the depth of scour.This study can provide a valuable reference for the protection of submarine pipelines in this area.

Mn-doped SrCoO_(3-δ) Perovskite Oxides for Ethylene Production via Chemical Looping Oxidative Dehydrogenation of Ethane

Chemical looping oxidative dehydrogenation (CL-ODH) is an economically promising method for convertingethane into higher value-added ethylene utilizing lattice oxygen in redox catalysts, also known as oxygen carriers. Inthis study, perovskite-type oxide SrCoO_(3-δ) and B-site Mn ion-doped oxygen carriers (SrCo_(1-x)MnxO_(3-δ), x=0.1, 0.2, 0.3)were prepared and tested for the CL-ODH of ethane. The oxygen-deficient perovskite SrCoO_(3-δ) exhibited high ethyleneselectivity of up to 96.7% due to its unique oxygen vacancies and lattice oxygen migration rates. However, its low ethyleneyield limits its application in the CL-ODH of ethane. Mn doping promoted the reducibility of SrCoO_(3-δ) oxygen carriers,thereby improving ethane conversion and ethylene yield, as demonstrated by characterization and evaluation experiments.X-ray diffraction results confirmed the doping of Mn into the lattice of SrCoO_(3-δ), while X-ray photoelectron spectroscopy(XPS) indicated an increase in lattice oxygen ratio upon incorporation of Mn into the SrCoO_(3-δ) lattice. Additionally, H2temperature-programmed reduction (H2-TPR) tests revealed more peaks at lower temperature reduction zones and a declinein peak positions at higher temperatures. Among the four tested oxygen carriers, SrCo0.8Mn0.2O_(3-δ) exhibited satisfactoryperformance with an ethylene yield of 50% at 710 °C and good stability over 20 redox cycles. The synergistic effect of Mnplays a key role in increasing ethylene yields of SrCoO_(3-δ) oxygen carriers. Accordingly, SrCo0.8Mn0.2O_(3-δ) shows promisingpotential for the efficient production of ethylene from ethane via CL-ODH.

Multi-lump Kinetic Parameter Estimation and Simulation of Trickle-bed Reactor for Ultra-deep Hydrodesulfurization of Diesel

A three-lumping Langmuir-Hinshelwood kinetic model was established based on the structures and reactivities of sulfur compounds.This model described the ultra-deep hydrodesulfurization(UDHDS)performance of diesel,reducing sulfur content from 10000μg/g to less than 10μg/g,with experimental and predicted data showing a discrepancy of less than 10%.The diesel UDHDS reaction was simulated by combining the mass transfer,reaction kinetics model,and physical properties of diesel.The results showed how the concentrations of H2S,hydrogen,and sulfur in the gas,liquid,and solid phases varied along the reactor length.Moreover,the study discussed the effects of each process parameter and impurity concentrations(H2S,basic nitrogen and,non-basic nitrogen)on diesel UDHDS.

Algorithmic approach to discrete fracture network flow modeling in consideration of realistic connections in large-scale fracture networks

Analyzing rock mass seepage using the discrete fracture network(DFN)flow model poses challenges when dealing with complex fracture networks.This paper presents a novel DFN flow model that incorporates the actual connections of large-scale fractures.Notably,this model efficiently manages over 20,000 fractures without necessitating adjustments to the DFN geometry.All geometric analyses,such as identifying connected fractures,dividing the two-dimensional domain into closed loops,triangulating arbitrary loops,and refining triangular elements,are fully automated.The analysis processes are comprehensively introduced,and core algorithms,along with their pseudo-codes,are outlined and explained to assist readers in their programming endeavors.The accuracy of geometric analyses is validated through topological graphs representing the connection relationships between fractures.In practical application,the proposed model is employed to assess the water-sealing effectiveness of an underground storage cavern project.The analysis results indicate that the existing design scheme can effectively prevent the stored oil from leaking in the presence of both dense and sparse fractures.Furthermore,following extensive modification and optimization,the scale and precision of model computation suggest that the proposed model and developed codes can meet the requirements of engineering applications.

Local Scour Mechanisms and Prediction Methods Around Offshore Wind Turbine Foundations:Insights and Future Directions

Local scour around offshore wind turbine foundations presents a considerable challenge due to its potential influence on structural stability,driven by hydrodynamic forces.While research has made strides in comprehending scouring mechanisms,notable complexities persist,specifically with newer foundation types.Addressing these limitations is vital for advancing our understanding of scour mechanisms and for improving mitigation strategies in offshore wind energy development.This review synthesizes current findings on local scour across various offshore foundations,encompassing field observations,data-driven approaches,turbulence-sediment interactions,scour evolution processes,influencing factors,and numerical model advancements.The objective is to enrich our understanding of local scour mechanisms.In addition,future research directions are outlined,including the development of robust arti-ficial intelligence models for accurate predictions,the exploration of vortex structure characteristics,and the refinement of numerical models to strengthen prediction capabilities while minimizing computational efforts.

Computational Strategy Research on the Development of Kiruna,in Sweden

In Kiruna,nearly all the residents support the migration plan in order to make LKAB able to continue the mining process.Based on current condition,a larger part of this town will be demolished by the sinking land caused by iron ore mining processing operated by LKAB.Since then,most of the buildings in the sinking district will be relocated in another district.However,the situation in Kiruna is not quite the same as when this kind of migration happens in another place.In other place,while migration happens,even if not most,a large part of the local residents will resist and fight for their house and properties.Concentrated on the ownership of different buildings and tried find the relationship between the public and private buildings to discover some issue that will help to work on the computational urban design.

Energy Consumption and Analysis on Energy Saving Measures at SINOPEC's Large Refineries

This article sums up the energy consumption of process units and the overall energy consumption of 10 Mt/a class refineries constructed or revamped in recent years. The energy saving measures adopted in design of these refineries are analyzed and discussed. Finally, this article also makes comments and puts forward recommendations on the objectives for energy conservation at refineries in the future.

Advances in Sinopec's Shale Gas Drilling Technologies

In order to economically and effectively develop shale gas in China, Sinopec introduced foreign technologies and integrated them with available domestic technologies and self-developed tools according to geological characteristics and complicated mountainous geomorphology in marine shale plays of southern China. A technology series composed of innovated theories concerning geological characterization during drilling, new generation of PDC bits, friction-reducing tools, low-cost oil-based drilling fluid system, high-efficient washing fluid and elastic mud systems, integrated drilling engineering design, long lateral cementing, modified well facto~ drilling method and etc., was developed to ful）qll fast and optimized drilling for shale gas wells. The application of the technology series in about 251 wells of Fuling gas Jield, Chongqing City, southwestern China, showed positive results： mechanical rotating speed increased by 191%, drilling duration redueed by 53%, and quality passing percent 100%.

Zinc influences on brain development, pituitary and thyroid function in iodine-deficient pregnant and neonatal rats

BACKGROUND： Zinc （Zn） has been shown to greatly influence brain development. Zn supplements may reduce injury to cell membranes of the thyroid gland due to iodine deficiency. OBJECTIVE： To establish an iodine deficiency rat model using low-iodine food, which was supplemented with compound Zn and Zn gluconate, to observe the effects of Zn on brain development, as well as pituitary gland and thyroid gland function in iodine-deficient rats. DESIGN, TIME AND SETTING： Randomized grouping study of neural development was performed in the central laboratory of Shandong Institute for Prevention and Treatment of Endemic Disease from 1998 to 1999. MATERIALS： A total of 270 Wistar, female rats, one month after weaning, were used in this study, including 150 pregnant and 120 neonatal rats. Rats were randomly divided into six groups： normal control, model, iodine, compound Zn, iodine and compound Zn, and zinc gluconate. Each group contained 25 pregnant rats and 20 neonatal rats. METHODS： The pregnant rats and 20 neonatal rats, and well as the normal group, were fed standard chow and allowed free access to tap water （containing 5 u g/L iodine and 1 mg/L Zn）. The remaining five groups were fed low-iodine chow. However, the model group received distilled water, the iodine group received potassium-iodide distilled water （containing 300 u g/L iodine）, the compound Zn group received distilled water and intragastrically administrated 10 mL/kg compound Zn solution, once per day, the iodine and compound Zn group received distilled water with 300 u g/L iodine and intragastrically administrated 10 mL/kg compound Zn solution, once per day. All treatments lasted 90 days. MAIN OUTCOME MEASURES： All pregnant rats were sacrificed on the day 21 of pregnancy. Body mass number and rate of fetal absorption, as well as fetal death and malformation, were determined. Thyroid and pituitary gland weights were measured, as well as serum levels of thyroid hormone, gonadotropin, and sex hormones. In the experimental study of neonatal rats, the animals normally gave birth at day 21. At day 45 after birth of the neonatal rats, thyroid and pituitary gland weights were measured, and protein, DNA, and RNA concentrations were measured. RESULTS： Pregnant rats in the iodine group exhibited decreased urine iodine and body mass （F = 7.37, P 〈 0.01 ）, increased thyroid absolute and relative weight （F= 7.01, 50.27, P 〈 0.01）, as well as decreased T4 and FF4 （F = 7.01, 29.32, P 〈 0.01 ） and increased T3 and VI＇3 （F = 41.20, 5.94, P 〈 0.01）. Gonadotropic and sexual hormones were abnormal. The pregnant rats displayed decreased weight gain, and the rates of malformation, dead, and absorbed fetuses were increased. Compared with the control group, the neonatal rats with iodine deficiency exhibited lower brain weights （P 〈 0.01 ）. Brain protein, DNA, and RNA, concentrations were decreased, with a rate of RNA/DNA （F = 5.70, 55.86, 25.65, 5.44, P 〈 0.01）. Body mass was gradually increased （F= 6.74, P 〈 0.01）, and the thyroid glands were enlarged （F= 50.01, 76.13, P 〈 0.01）. Following Zn administration, thyroid gland weight was decreased in pregnant rats （P 〈 0.01 ）. Thyroid hormone, gonadotropic hormones, and sexual hormones were restored to some degree. Fetal weight was increased, and the rates of malformation, dead, and absorbed fetuses were decreased. At the same time, neonatal rats gained body weight, displayed decreased thyroid gland weight, as well as increased protein, DNA, and RNA concentrations in the brain. The ratio of RNA/DNA and protein/DNA increased following Zn administration （P 〈 0.01 ）. CONCLUSION： Zn supplementation may decrease the degree of goiter, ameliorate thyroid hormone disorder, as well as gonadotropic and sexual hormone disorders, and increase protein, DNA, and RNA content. Zn supplementation antagonized reproductive abnormalities in pregnant rats, decreased fetal growth,and disturbed brain development in neonatal rats as a result of iodine deficiency.

Degradation of chemical and mechanical properties of cements with different formulations in CO_(2)-containing HTHP downhole environment

The increasing energy demand has pushed oil and gas exploration and development limits to extremely challenging and harsher HTHP (High Temperature and High Pressure) environments. Maintaining wellbore integrity in these environments, particularly in HPHT reservoirs with corrosive gases, presents a significant challenge. Robust risk evaluation and mitigation strategies are required to address these reservoirs' safety, economic, and environmental uncertainties. This study investigates chemo-mechanical properties degradations of class G oil well cement blended with silica fume, liquid silica, and latex when exposed to high temperature (150 °C) and high partial pressure of CO_(2) saturated brine. The result shows that these admixtures surround the cement grains and fill the interstitial spaces between the cement particles to form a dense crystal system of C–S–H. Consequently, the cement's percentage of pore voids, permeability, and the content of alkali compounds reduce, resulting in increased resistance to CO_(2) corrosion. Liquid silica, a specially prepared silica suspension, is a more effective alternative to silica fume in protecting oil well cement against CO_(2) chemical degradation. Micro-indentation analysis shows a significant deterioration in the mechanical properties of the cement, including average elastic modulus and hardness, particularly in the outer zones in direct contact with corrosive fluids. This study highlights the significance of incorporating admixtures to mitigate the effects of CO_(2) corrosion in HPHT environments and provides a valuable technique for quantitatively evaluating the mechanical-chemical degradation of cement sheath.

A dynamic-inner LSTM prediction method for key alarm variables forecasting in chemical process

With the increase in the complexity of industrial system, simply detecting and diagnosing a fault may be insufficient in some cases, and prognosing the fault ahead of time could have a certain necessity. Accurate prediction of key alarm variables in chemical process can indicate the possible change to reduce the probability of abnormal conditions. According to the characteristics of chemical process data, this work proposed a key alarm variables prediction model in chemical process based on dynamic-inner principal component analysis(DiPCA) and long short-term memory(LSTM). DiPCA is used to extract the most dynamic components for prediction. While LSTM is used to learn the relationship and predict the key alarm variables. This work used a simulation data set and a real hydrogenation process data set for applications and explained the model validity from the essential characteristics. Comparison of results with different models shows that our model has better prediction accuracy and performance, which can provide the basis for fault prognosis and health management.

Effects of Ethylene Tar-Based Pitch Coatings on the Electrochemical Properties of Graphite Anode Materials

To improve the electrochemical performance of graphite anode materials,pitches with various softening points(150℃,180℃,200℃,and 250℃)were prepared from ethylene tar and used to coat graphite through a liquid coating process.The effects of the softening point of the pitch and the coating amount on the microstructure and electrochemical properties of graphite were studied by methods including thermogravimetric analysis,X-ray diffraction,Raman spectroscopy,surface area analysis,scanning electron microscopy,transmission electron microscopy,and electrochemical testing.The graphite particles were coated uniformly by the pyrolytic carbon in the pitch.The coating changed the degree of graphitization,decreased the average specific surface area,and improved the electrochemical performance significantly.The best battery anode performance was obtained when the mass ratio of pitch to graphite was 10%,the heat treatment temperature was 1100℃,and the softening point of the pitch was 250℃.Under the optimum conditions,the irreversible capacity loss in the first cycle at 0.1 C was only 23 mAh/g,and the first Coulombic efficiency reached 94.2%.The capacity retention rate was 98.3%after 100 charge-discharge cycles at 0.1 C.

Positioning of Hydrogen Energy and Development of Hydrogen Pipeline Transportation Technology in the Context of Carbon Neutrality

The correct understanding of the role of hydrogen energy in the carbon neutrality strategy,and the scientific development of the technical layout of hydrogen energy industry chain are key factors in determining whether the hydrogen energy industry and enterprises can achieve healthy sustainable development by following the national trend.This paper discusses the role of hydrogen energy in the implementation of the carbon neutrality strategy,and analyzes the necessity of hydrogen pipeline transportation,and the main technical challenges brought about by the physical and chemical differences between hydrogen and natural gas.We also introduce the technical breakthroughs and main achievements against the construction of the“West-East Hydrogen Transport”pipeline project to provide guidance and reference for the hydrogen energy industry and the construction of hydrogen transportation pipelines.In order to better promote the steady and healthy development of the domestic hydrogen pipeline transportation industry,we offer some proposals for the spatial layout integration and optimization of carbon,nitrogen,hydrogen,and oxygen elements and the research and application of large-scale hydrogen storage technology based on the work practices.

Signed Directed Graph and Qualitative Trend Analysis Based Fault Diagnosis in Chemical Industry

In the past 30 years,signed directed graph(SDG) ,one of the qualitative simulation technologies,has been widely applied for chemical fault diagnosis.However,SDG based fault diagnosis,as any other qualitative method,has poor diagnostic resolution.In this paper,a new method that combines SDG with qualitative trend analysis(QTA) is presented to improve the resolution.In the method,a bidirectional inference algorithm based on assumption and verification is used to find all the possible fault causes and their corresponding consistent paths in the SDG model.Then an improved QTA algorithm is used to extract and analyze the trends of nodes on the consis-tent paths found in the previous step.New consistency rules based on qualitative trends are used to find the real causes from the candidate causes.The resolution can be improved.This method combines the completeness feature of SDG with the good diagnostic resolution feature of QTA.The implementation of SDG-QTA based fault diagno-sis is done using the integrated SDG modeling,inference and post-processing software platform.Its application is illustrated on an atmospheric distillation tower unit of a simulation platform.The result shows its good applicability and efficiency.

Exclusively catalytic oxidation of toluene to benzaldehyde in an O/W emulsion stabilized by hexadecylphosphate acid terminated mixed-oxide nanoparticles

A series of hexadecylphosphate acid(HDPA) terminated mixed-oxide nanoparticles have been investigated to catalyze the oxidation of toluene exclusive to benzaldehyde under mild conditions in an emulsion of toluene/water with the catalysts as stabilizers. With the HDPA-Fe2 O3/Al2 O3 as the basic catalyst, a series of transition metals, such as Mn, Co, Ni, Cu, Cr, Mo, V, and Ti, was respectively doped to the basic catalyst to modify the performance of the catalytic system, in expectation of influencing the mobility of the lattice oxygen species in the oxide catalysts. Under normally working conditions of the catalytic system, the nanoparticles of catalysts located themselves at the interface between the oil and water phases, constituting the Pickering emulsion. Both the doped iron oxide and its surface adsorbed hexadecylphosphate molecules were essential to the catalytic system for excellent performances with high toluene conversions as well as the exclusive selectivity to benzaldehyde. Under optimal conditions, ~83% of toluene conversion and >99% selectivity to benzaldehyde were obtained, using molecular oxygen as oxidant and HDPA-(Fe2 O3-Ni O)/Al2 O3 as the catalyst. This process is green and low cost to produce high quality benzaldehyde from O2 oxidation of toluene.

Hydraulic model optimization of a multi-product pipeline

An optimization model is established for a multi-product pipeline which has a known delivery demand and operation plan for each off-take station.The aim of this optimization model is to minimize the total pumping operation cost,considering not only factors including the energy equilibrium constraint,the maximum and minimum suction and discharge pressures constraints of pump stations,and pressure constraint at special elevation points,but also the regional differences in electricity prices along the pipeline.The dynamic programming method is applied to solve the model and to find the optimal pump configuration.

Cold Model Study and Commercial Test on Novel Vapor-Liquid Distributor of Hydroprocessing Reactor

A novel vapor-liquid distributor was developed on the basis of sufficient study on the existing distributors applied in hydroprocessing reactors. The cold model test data showed that the fluid distribution performance of the novel vapor-liquid distributor was evidently better than the traditional one. Com- mercial tests of the new distributor were carded out in the 300 kt/a gas oil hydrotreating reactor at SINOPEC Changling Branch Company, showing that the new vapor-liquid distributor could improve the fluid distribution, promote the hydrotreating efficiency and lead to better performance than the traditional one.

Resid Contact Cracking and Coke Gasification Integrated Technology

In order to utilize petroleum resources efficiently and greenly,and solve the problems of high coke yield,highsulfur coke utilization,and environmental protection concerns in China’s refineries,a resid contact cracking and coke gasification integrated technology is being developed by the Research Institute of Petroleum Processing(RIPP).Based on the three technical characteristics including thin films cracking,partial oxidation,and rapid cracking,this technology not only can reduce the production rate of coke and dry gas formed during the process,but also can increase the liquid yield.Moreover,the in-situ low-temperature gasification technology is used to solve the clean utilization of high-sulfur petroleum coke,which can play the role of“Utility Island”and is a green and low-carbon technology for low-quality heavy oil upgrading.

Hydrodynamics performance and tray efficiency analysis of the novel vertical spray packing tray

Column setup has been widely utilized in the petroleum and chemistry industries. However, with the fast progress of industries and the increasingly serious energy shortage, designing a new column setup with better performance and higher capacity becomes more urgent. In order to improve column's capacity and expand operating condition, a new type of column tray named novel vertical spray packing(NVSP) tray was designed and experimented. The performances of the novel tray, including pressure drop, weeping, entrainment and tray efficiency, were tested in a plexiglass column. In addition, performances of the novel tray were compared with that of the sieve tray and the Glitsch V1 valve tray. Based on the experiment data, the mathematical correlations of pressure drop, weeping and entrainment for the novel tray were established by regression analysis method. A fundamental model of dry pressure drop of the novel tray was promoted at the form of sum mode. The results indicate that the novel tray has wider operating condition and better performance.

Systematic rationalization approach for multivariate correlated alarms based on interpretive structural modeling and Likert scale

Alarm flood is one of the main problems in the alarm systems of industrial process. Alarm root-cause analysis and alarm prioritization are good for alarm flood reduction. This paper proposes a systematic rationalization method for multivariate correlated alarms to realize the root cause analysis and alarm prioritization. An information fusion based interpretive structural model is constructed according to the data-driven partial correlation coefficient calculation and process knowledge modification. This hierarchical multi-layer model is helpful in abnormality propagation path identification and root-cause analysis. Revised Likert scale method is adopted to determine the alarm priority and reduce the blindness of alarm handling. As a case study, the Tennessee Eastman process is utilized to show the effectiveness and validity of proposed approach. Alarm system performance comparison shows that our rationalization methodology can reduce the alarm flood to some extent and improve the performance.