Optimal regimes of heavy oil transportation through a heated pipeline

Bekibayev, T. T.; Zhapbasbayev, U. K.; Ramazanova, G. I.

doi:10.1016/j.jprocont.2022.04.020

Cited by 13 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The topology of the object consists of the topology of the linear part of the pipeline and the topology of the stations. The accuracy of the simulation results of hot oil pumping is determined by the calculations of pressure and temperature in the oil pipeline [ [22], [23]].…”

Section: Problem Statementmentioning

confidence: 99%

“…In the linear part, the oil temperature decreases due to heat exchange with the surrounding soil of the pipeline, and there are various models for calculating the heat exchange of the oil flow with the surrounding soil [ [22], [23]]. Some calculation parameters are known: flow rate, insulation, soil temperature, and the properties of oil and metal pipes.…”

Section: Temperature Distribution Calculation Along the Pipelinementioning

confidence: 99%

See 1 more Smart Citation

Mismatch problem of the model and topology of oil pumping facilities

Bekibayev¹,

Bossinov²,

Zhapbasbayev³

et al. 2023

KIMS/CUMR/MShKP

View full text Add to dashboard Cite

The mismatch of the model and the topology of real objects is important in modeling technological processes, which is the purpose of this paper. The problem is considered when modeling hot oil pumping in the "Kasymov–Bolshoy Chagan" oil pipeline. In this problem, the topology of objects consists of the linear part of the pipeline and technological equipment (pumps and heating furnaces) of the stations. The accuracy of the simulation results is determined by the calculations of pressure and temperature in the oil pipeline. The pressure in the pipeline is created by pumps at the stations and is determined by the dependence of the pressure and efficiency of the pump on the oil flow rate. These characteristics change depending on the service life of the pump. The identification of the actual dependences of the pressure and efficiency of the pump on the oil flow rate was carried out by the regression analysis of experimental data. The pressure in the linear part is determined by the hydraulic resistance of the pipeline. The actual dependence of the hydraulic resistance coefficient on the Reynolds number and wall roughness was obtained by regression analysis of experimental data. The temperature in the oil pipeline is created at the stations by heating furnaces. The identification of the actual characteristics of the heating furnace was also found by regression analysis of the experimental data. The temperature distribution in the linear part is determined by the heat transfer of oil with the surrounding environment. An undefined parameter for calculating heat transfer is the soil thermal conductivity, which depends on the type of rock and the degree of soil moisture. The soil thermal conductivity is determined in such a way that at a given oil flow rate, oil temperatures at the beginning of the section and soil at the section, the calculated oil temperature at the end of the section has the smallest discrepancy with the actual one. Thus, the determination of the actual dependencies of the objects makes it possible to increase the accuracy of the results of hot pumping modeling and eliminates the mismatches of the model and the topology of the objects.

show abstract

Section: Problem Statementmentioning

confidence: 99%

Section: Temperature Distribution Calculation Along the Pipelinementioning

confidence: 99%

Mismatch problem of the model and topology of oil pumping facilities

Bekibayev¹,

Bossinov²,

Zhapbasbayev³

et al. 2023

KIMS/CUMR/MShKP

View full text Add to dashboard Cite

show abstract

“…A number of papers are known on the development and improvement of modeling and control approaches for the catalytic reforming process (Gumen, 2018, Orazbayev, et al, 2022, Panchenkov, 2018, Rubekin, 2018, Zhorov, 2017, Nazarova, et al, 2020. The following is implemented in the known systems of the catalytic reforming process control: optimal temperature distribution at the inlet of reforming reactors (Rakhmetov, et al, 2022); optimization of process modes of the reforming unit operation (Bekibayev, et al, 2022), catalyst quality control in the stabilization unit of the catalytic reforming unit (Dzhambekov, et al, 2022); situational control of the reforming process (Moldasheva, et al, 2022). These and other works insufficiently study and solve the issues of modeling and optimization of the reforming process in a fuzzy environment.…”

Section: Introductionmentioning

confidence: 99%

“…to produce high quality motor fuels -high-octane motor road als for petrochemical synthesis (Orazbayev, et al, 2022). A t and improvement of modeling and control approaches for Orazbayev, et al, 2022, Panchenkov, 2018, Rubekin, 2018 wing is implemented in the known systems of the catalytic distribution at the inlet of reforming reactors (Rakhmetov, et reforming unit operation (Bekibayev, et al, 2022), catalyst alytic reforming unit (Dzhambekov, et al, 2022);situational t al., 2022). These and other works insufficiently study and the reforming process in a fuzzy environment.…”

Section: Introductionmentioning

confidence: 99%

“…Since the problem of controlling the modes of the research object operation is characterized by multi-criteria and fuzziness of constraints the methods of modeling, multi-criteria optimization and decision making (Orazbayev et al, 2019:, Orazbayev, et al, 2022, Nazarova, et al, 2020, Bekibayev, et al, 2022, Makhazhanova, et al, 2020, Ospanov, et al, 2016, methods of fuzzy set theories and expert evaluations (Orazbayev, et al, 2022, Dzhambekov, et al, 2022, Orazbayev, et al, 2020:, Turekulova, et al, 2022, Jovanovic, et al, 2022, Gutsykova, et al, 2017 are applied for formulation and solution of this problem in a fuzzy environment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Heuristic Approach to Fuzzy Control of the Reforming Process in Refining and Geology

Orazbayev¹,

Kabibullin²,

Bissembayeva³

et al. 2022

SGTS

View full text Add to dashboard Cite

Бас редактор ЖҰРЫНОВ Мұрат Жұрынұлы, химия ғылымдарының докторы, профессор, ҚР ҰҒА академигі, Қазақстан Республикасы Ұлттық Ғылым академиясының президенті, АҚ «Д.В. Сокольский атындағы отын, катализ және электрохимия институтының» бас директоры (Алматы, Қазақстан) H = 4 АБСАДЫКОВ Бахыт Нарикбайұлы, техника ғылымдарының докторы, профессор, ҚР ҰҒА жауапты хатшысы, А.Б. Бектұров атындағы химия ғылымдары институты (Алматы, Қазақстан) H = 5 Р е д а к ц и я л ы қ а л қ а: ӘБСАМЕТОВ Мәліс Құдысұлы (бас редактордың орынбасары), геология-минералогия ғылымдарының докторы, профессор, ҚР ҰҒА академигі, «У.М. Ахмедсафина атындағы гидрогеология және геоэкология институтының» директоры (Алматы, Қазақстан) H = 2 ЖОЛТАЕВ Герой Жолтайұлы (бас редактордың орынбасары), геология-минералогия ғылымдарының докторы, профессор, Қ.И. Сатпаев тындағы геология ғылымдары институтының директоры (Алматы, Қазақстан) Н=2 СНОУ Дэниел, Рһ.D, қауымдастырылған профессор, Небраска университетінің Су ғылымдары зертханасының директоры (Небраска штаты, АҚШ) H = 32 ЗЕЛЬТМАН Реймар, Рһ.D, табиғи тарих мұражайының Жер туралы ғылымдар бөлімінде петрология және пайдалы қазбалар кен орындары саласындағы зерттеулердің жетекшісі (Лондон, Англия) H = 37 ПАНФИЛОВ Михаил Борисович, техника ғылымдарының докторы, Нанси университетінің профессоры (Нанси, Франция) Н=15 ШЕН Пин, Рһ.D, Қытай геологиялық қоғамының тау геологиясы комитеті директорының орынбасары, Американдық экономикалық геологтар қауымдастығының мүшесі (Пекин, Қытай) H = 25 ФИШЕР Аксель, Ph.D, Дрезден техникалық университетінің қауымдастырылған профессоры (Дрезден, Берлин) Н = 6 КОНТОРОВИЧ Алексей Эмильевич, геология-минералогия ғылымдарының докторы, профессор, РҒА академигі, А.А. Трофимука атындағы мұнай-газ геологиясы және геофизика институты (Новосибирск, Ресей) H = 19 АГАБЕКОВ Владимир Енокович, химия ғылымдарының докторы, Беларусь ҰҒА академигі, Жаңа материалдар химиясы институтының құрметті директоры (Минск, Беларусь) H = 13 КАТАЛИН Стефан, Рһ.D, Дрезден техникалық университетінің қауымдастырылған профессоры (Дрезден, Берлин) H = 20 СЕЙТМҰРАТОВА Элеонора Юсуповна, геология-минералогия ғылымдарының докторы, профессор, ҚР ҰҒА корреспондент-мүшесі, Қ.И. Сатпаев атындағы Геология ғылымдары институты зертханасының меңгерушісі (Алматы, Қазақстан) Н=11 САҒЫНТАЕВ Жанай, Ph.D, қауымдастырылған профессор, Назарбаев университеті (Нұр-Сұлтан, Қазақстан) H = 11 ФРАТТИНИ Паоло, Рһ.D, Бикокк Милан университеті қауымдастырылған профессоры (Милан, Италия) H = 28

show abstract

Gastrointestinal‐Peristalsis‐Inspired Hydrogel Actuators for NIR‐Controlled Transport of Viscous Liquids

Zhang

Chen

et al. 2023

Advanced Materials

View full text Add to dashboard Cite

Liquid transportation is fundamentally important in microfluidics, water collection, biosensing, and printing, and has attracted enormous research interest in the past decades. However, despite substantial progress, it remains a big challenge to achieve the controlled transport of viscous liquids (>100 mPa s) commonly existing in daily life and the chemical industry. Inspired by the gastrointestinal peristalsis of mammalians that can efficiently transport viscous chyme (viscosity up to 2000 mPa s) by the synergistic combination of contraction driving force and lubrication, here, the design and construction of double‐layered tubular hydrogel actuators for directional transport of highly viscous liquids ranging from ≈1000 mPa s to >80 000 mPa s under the control of an applied 808 nm laser, which is attributed to the cooperation of outer layer contraction and water film lubrication of the inner layer, is reported. It is demonstrated that the actuators are capable of transporting polymerizing liquid whose viscosity significantly increases to ≈11 182 mPa s in 2 h. This work paves a new avenue toward directional transport of highly viscous liquids, which not only expands the research scope of liquid transportation, but will spur the design of new liquid actuators with potential applications in viscous‐liquid‐based microfluidics, artificial blood vessels, and soft robots.

show abstract

Optimal regimes of heavy oil transportation through a heated pipeline

Cited by 13 publications

References 14 publications

Mismatch problem of the model and topology of oil pumping facilities

Mismatch problem of the model and topology of oil pumping facilities

Heuristic Approach to Fuzzy Control of the Reforming Process in Refining and Geology

Gastrointestinal‐Peristalsis‐Inspired Hydrogel Actuators for NIR‐Controlled Transport of Viscous Liquids

Contact Info

Product

Resources

About