Research Object Research Articles

Research on the internal flow characteristics of centrifugal pump based on streamlined anti-guide vane

Abstract Anti-guide vane is part of the radial guide vane in multi-stage centrifugal pump, and the hydraulic loss of anti-guide vane is the dominant factor affecting the performance of radial guide vane. In this paper, the radial guide vane is chosen as the research object, an optimization scheme of streamlined anti-guide vane is proposed based on the arc-shaped anti-guide vane with inlet angle α=25°. The simulation calculation of multi-stage centrifugal pump is drawn using the SST k-ω turbulence model. and the influence of the streamlined anti-guide vane on the hydraulic performance is studied. The result shows that: Under various flow conditions, the head of the multistage centrifugal pump with streamlined anti-guide vanes is higher than that of the prototype. When the flow rate is 1.3Q, the head is increased by 7.2%. and the efficiency is increased by 2.3%. The amplitude of pressure fluctuation of the streamlined anti-guide vane is significantly decreased at each monitoring point compared to the prototype, indicating that the streamlined anti-guide vane weakens the influence of the pressure fluctuation. Furthermore, the streamlined anti-guide vane enhances the pre-swirl of the inlet fluid to the secondary impeller, reduces the impact loss, and improves the pressurization capacity of the secondary impeller.

Construction of data base containing flow field information under different blade placement of pumping station in digital twin

Abstract The data base in digital twin technology includes various data such as the structure, performance, and operating status of the physical object. And the data base is the key point for the construction of the digital twin system. However, the data bases of different digital twin systems usually contain different information. In this paper, the flow state of the pumping station under different angles of four blades is selected as the research object. The research methods in this paper mainly include Latin hypercube sampling, numerical simulation and neural network prediction. The Latin hypercube sampling is used to select the typical Angle difference model. The numerical simulation is used to obtain flow field information. The neural network prediction method is used to construct a complete data base. The study incorporates an actual large-scale mixed-flow pump station to head, efficiency, and shaft power as the prediction targets. It utilizes the different angle difference data of ten sets of four blades as the training set, forty sets of remaining samples as the experiment set, and employs the backpropagation neural network method for constructing the prediction network. By changing the experiment set and test set, the method can efficiently complete the construction of data base including actual test and numerical simulation, which provides a solid foundation for the construction of digital twin platform.

Study on flood level forecasting of tidal reach in Puyang River basin

Abstract The downstream section of the Puyang River is a tidal river reach subject to both upstream floods and downstream tides. This combined impact results in an unstable relationship between water level and discharge at the forecast station, making flood level forecasting challenging. This paper took the Linpu station on the Puyang River in Zhejiang Province as the research object. Based on the historical flood data, the cause of high water levels at Linpu station was analyzed. The flood levels at Linpu station were decomposed into flood increments and basic tidal levels. Using the multiple regression method, the prediction formula for upstream flood-induced water level increments was obtained. A flood level forecasting method based on the flood increment was developed. The result of the scheme accuracy evaluation indicates that this method has good forecasting performance. The flood level forecasting method for the tidal channel proposed in this paper has a simple structure and high accuracy, which provides a scientific basis for the prevention and control of flood and drought hazards and the decision-making of project scheduling in the tidal river.

Molecular dynamics simulation of the interaction between ionic liquid [OPy][BF4] and SO2

Ionic liquids possess novel properties and can efficiently absorb harmful gases, potentially serving as a new type of absorbent. In this study, the binary system of ionic liquid N-octylpyridinium tetrafluoroborate [OPy][BF4] and sulfur dioxide (SO2) has been selected as the research object, and the structure and properties of the system have been studied by molecular dynamics simulation. The interaction between SO2 and ionic liquids is explored by using the radial distribution functions (RDFs), coordination numbers (CNs) and spatial distribution functions (SDFs). The results of microstructures show that due to the strong interaction with anions, SO2 is mostly orderly distributed around the anions of ionic liquids. However, the coordination ability of the polar region of the ionic liquid and SO2 is nearly equivalent to that of the non-polar region. At the same time, it is found that the addition of SO2 enhanced the order degree of the polar and the non-polar regions of ionic liquids, especially on non-polar regions. Through the discussion of the interaction between [OPy][BF4] and SO2, it can be concluded that the mechanism of SO2 absorption by [OPy][BF4] is the combined effect of anions and cations. This study aims to provide new insights for the potential applications of ionic liquids in industrial fields such as petroleum and flue gas desulfurization.

Drifted Uncertainty Evaluation of a Compact Machine Tool Spindle Error Measurement System

The accurate measurement of spindle errors, especially quasi-static errors, is one of the key issues for the analysis and compensation of machine tool thermal errors in machining accuracy. To quantitatively analyze the influence of the measurement system’s own drift on the measurement results, a drifted uncertainty evaluation method of the precision instrument considering the time drift coefficient is proposed. This study also produced a high-precision compact spindle error measurement device (with a displacement measurement error of less than ±1.33 μm and an angular measurement error of less than ±1.42 arcsecs) as the research object to verify the proposed drift uncertainty evaluation method. A method for evaluating the drift uncertainty of the measurement system is proposed to quantitatively evaluate the system error and drift uncertainty of the measurement device. Experiments show that the drift uncertainty evaluation method proposed in this paper is more suitable for evaluating the uncertainty changes in measurement instruments during long-term measurements compared to traditional methods.

Optimization of geometrical parameters of positive guide vane for multi-stage pump as turbine based on orthogonal test

Abstract Multi-stage pumps as turbines (PAT) are commonly employed in the petrochemical, coal chemical, and other process industries to recover liquid residual pressure energy. This study focused on improving the performance of multi-stage PAT, specifically targeting the slope of the power-flow(P-Q) curve and hydraulic efficiency at the rated flow point. A two-stage PAT was selected as the research object for this study. According to the relationship between the power and the geometrical parameters of the positive guide vane derived based on the basic equation of the multi-stage PAT, four parameters of the positive guide vane were selected as the test factors for the orthogonal experimental study. A four-factor, three-level orthogonal table of type L9(34) was established. Using Fluent software and the RNG k-ε turbulence model to carry out numerical calculations of constant flow, the results showed that: for the slope of the P-Q curve, the influence of geometric parameter factors of the positive guide vane are in the order of the throat area, the outlet placement angle, the positive guide vanes number, and the base circle diameter; and for the hydraulic efficiency, the influence of geometric parameter factors of the positive guide vane are in the order of the throat area, the positive guide vanes number, the outlet placement angle, and the base circle diameter of the positive guide vane. At the rated flow point, the P-Q curve of the optimized solution decreased by 0.24, resulting in a flatter curve and a 0.3% increase in hydraulic efficiency. There was little change in the vicinity at the rated flow point. The best efficiency point of the optimized scheme is biased toward the high flow rate, the efficiency is increased by 1.85%, and the best efficiency zone is wider. Therefore, selecting appropriate positive guide vane geometry parameters can flatten the P-Q curve, improve internal flow, and enhance hydraulic efficiency.

Pengaruh Faktor Pengungkapan Corporate Social Responsibility

Research objective: To empirically test the influence of business risk, financial risk and operational risk on corporate social responsibility. The research object is gas, oil and coal sub-sector companies listed on the Indonesian stock exchange. The total sample was 17 companies for 5 years. Hypothesis testing uses the F test and t test. The results of the F test show that simultaneously business risk factors, financial risk factors and operational risk factors influence corporate social responsibility. Meanwhile, the results of the hypothesis using tests show that each factor of business risk, financial risk and operational risk has a partial effect on corporate social responsibility.

Research on thermal comfort of human body under localized automotive air conditioning

Abstract In this study, we design localized automotive air conditioning to balance the contradiction between the thermal comfort of the driver in the cockpit and the energy saving and environmental protection of an automobile's air conditioner. The simplified model of a certain car cockpit is selected as the research object. Three types of air outlet structures of localized automotive air conditioning are designed, and numerical simulation is performed to study flow field distribution and human thermal comfort in the cockpit under different air outlet combinations of localized automotive air conditioning. The final evaluation result indicates that the thermal comfort of the driver is good under localized automotive air conditioning. Moreover, the energy-saving effect of localized automotive air conditioning is remarkable and its cooling rate is faster. Localized automotive air conditioning achieves about 41.4% more energy saving than ordinary automotive air conditioning.

Diabetes prediction model based on GA-XGBoost and stacking ensemble algorithm.

Diabetes, as an incurable lifelong chronic disease, has profound and far-reaching effects on patients. Given this, early intervention is particularly crucial, as it can not only significantly improve the prognosis of patients but also provide valuable reference information for clinical treatment. This study selected the BRFSS (Behavioral Risk Factor Surveillance System) dataset, which is publicly available on the Kaggle platform, as the research object, aiming to provide a scientific basis for the early diagnosis and treatment of diabetes through advanced machine learning techniques. Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. The results show: (1) Random oversampling, ADASYN, SMOTE, and SMOTEENN were used for data balance processing, among which SMOTEENN showed better efficiency and effect in dealing with data imbalance. (2) The GA-XGBoost model optimized the hyperparameters of the XGBoost model through a genetic algorithm to improve the model's predictive accuracy. Combined with the better-performing LightGBM model and random forest model, a two-layer Stacking model was constructed. This model not only outperforms single machine learning models in predictive effect but also provides a new idea and method in the field of model integration. (3) Shapley value analysis identified features that have a significant impact on the prediction of diabetes, such as age and body mass index. This analysis not only enhances the transparency of the model but also provides more precise treatment decision support for doctors and patients. In summary, this study has not only improved the accuracy of predicting the risk of diabetes by adopting advanced machine learning techniques and model integration strategies but also provided a powerful tool for the early diagnosis and personalized treatment of diabetes.

Exploring Effective Paths for Artificial Intelligence to Empower Freshmen's Autonomous English Learning in an “Internet Plus” Environment

In the environment of "Internet plus", the combination of artificial intelligence technology and education has broken the time and space limitations of autonomous learning, subversively changed the way students learn, and brought more possibilities and challenges to both teachers' "teaching" and students' "learning". It brings more possibilities and challenges for both teachers' "teaching" and students' "learning". This study takes the freshmen non-English majors of Beijing Institute of Petrochemical Technology as the research object, based on the multiple intelligences theory and the constructivist learning theory, investigates the status and ability of freshmen's autonomous learning of English in the context of the era of "Internet plus", and explores the effects of the learning tools and learning environments supported by the new technology of artificial intelligence on students’ autonomous learning ability and learning effect. It explores the impact of learning tools and learning environment supported by the new technology of artificial intelligence on students’ autonomous learning ability and learning effect, so as to further explore the effective path to improve students' English autonomous learning ability. It provides empirical data support and suggestions for autonomous learning research and university English teaching, and facilitates teachers to make scientific adjustments in the selection of teaching content, monitoring of teaching platforms, design of teaching activities, and application of teaching methods to promote the improvement of students' autonomous learning ability, and at the same time, it also helps students to identify their problems in autonomous learning, find effective paths to solve the problems, and improve their learning efficiency.

SYNTHESIS OF N-BENZYLPIPERIDINE-4-ON DERIVATIVES (Review)

In the field of organic synthetic pharmaceuticals, methods for the discovery, creation, and synthesis of universal molecules with pharmacological activity are rapidly advancing worldwide. Optimal synthesis methods enable the production of analytically pure biologically active compounds with the highest possible yields and minimal waste, which helps conserve resources, time, and money. The diversity of biologically active drug groups increases the ability to meet the medical needs of the population. The search for optimal synthesis methods drives the development of new technologies and techniques, which, in turn, contributes to scientific discoveries in the fields of Medicine and Chemistry. The purpose of this review is to examine the literature on methods for obtaining biologically active derivatives of N-benzylpiperidin-4-one published in scientific journals. Research Object: Derivatives of N-benzylpiperidin-4-one. Research results: The study of the reactivity of Nbenzylpiperidin-4-one derivatives confirms their versatility in various chemical reactions, highlighting their utility as chemical compounds. The results compiled in scientific literature demonstrate the potential of N-benzylpiperidin-4-one derivatives in the development of new drugs with various pharmacological properties. Conclusion: The properties of the N-benzylpiperidin-4-one molecule as a universal chemical building block indicate its wide application in medicine and pharmacology, enhancing its significance in further scientific research and the synthesis of new compounds.

How Traditional Fishing Villages Move Towards Sustainable Management: A Case Study of Industrial Transformation and Multi-Party Governance Models

The purpose of this study is to explore the key roles and functions of institutions or organizations in the process of the spatial activation and industrial transformation of leisure fishing villages and to summarize this operating model. This study takes Xunpu Village, Quanzhou City, Fujian Province as the research object, which is well-known for its recreational fisheries. It mainly uses case study methods and uses on-site surveys and interviews to understand the formation time, spatial distribution, and business type information of the Zanhuawei shops in Xunpu Village. Zanhuawei, which refers to the traditional hairstyle of Xunpu women, was later applied for national intangible cultural heritage status in China. After the outbreak, the spread of Zanhuawei on the Internet inspired a large number of tourists to visit Xunpu Village to experience Zanhuawei. The study found that (1) Zanhuawei industry replaced traditional fishery and became the leading industry type in Xunpu Village. (2) The operating model led by the government and integrating public and private funds has had a stimulating effect on the revitalization of local commercial and residential space, and a large number of idle spaces have been reactivated. (3) The cooperation model between a large number of investors and local fisherwomen has completely changed the economic model of the village. Zanhuawei industry mobilized all official and media resources to promote spatial activation at various scales, including regions, settlements and commercial spaces.

Applying information mining technology in online entrepreneurship training course

The purpose of this study is to deeply explore the application of information mining technology in online entrepreneurship training courses, and to improve students’ learning effects and entrepreneurship success rate through systematic analysis and optimization of key data in the teaching process. With the development of online education, how to effectively use big data technology to meet personalized learning needs has become an important issue. This study takes several online entrepreneurship training courses as the research object, and uses information mining technology to extract and analyze students’ behavioral data during course participation, including data on study time, interaction frequency, assessment results, etc. Through machine learning algorithms and association rule mining, the research revealed the main factors that affect students’ learning effects and entrepreneurial success, and designed targeted teaching strategies, such as dynamically adjusting learning content, providing personalized feedback, optimizing learning paths, etc. Experimental results show that online courses using information mining technology significantly improve students’ knowledge mastery and entrepreneurial success rate, especially in terms of personalized learning experience and teaching efficiency. In addition, this study also explores the application prospects of information mining technology in future online education. It is believed that through the combination with artificial intelligence (AI) technology, the intelligence and adaptability of online courses can be further enhanced to meet more diversified learning needs.

Analysis Of Bankruptcy Prediction Using Springate, Zmijewski, Grover. And Altman Z-Score Models On Retail Companies Listed On The Indonesia Stock Exchange

The retail sector plays a significant role and contributes greatly to the national economy. The slowdown in domestic economic growth and decreased consumer purchasing power have significantly impacted the retail business in Indonesia. This is evident from the high number of retail companies declared bankrupt and many large retail companies closing their stores. The aim of this study is to assess the health level of retail companies, determine the differences in scores among the research models, and evaluate the accuracy of the Springate, Zmijewski, Grover, and Altman models. This research is a quantitative study with a descriptive approach. The research objects are retail companies listed on the Indonesia Stock Exchange during the period 2019-2021. Sampling technique used is purposive sampling. The results of this study indicate that the highest accuracy level is achieved by the Grover model with an accuracy of 77.7%, followed by the Zmijewski model with an accuracy level of 72.2%. Meanwhile, the Springate and Altman models have the same accuracy level of 66.6%.

Analysis of spatial and temporal evolution and driving factors of carbon emission in Shandong Province: based on the perspective of land use

Land use/cover change is the second major contributor to carbon emissions, following energy emissions. Studying provincial land-use carbon emissions is crucial for achieving the “double carbon” goal. This study selects 16 prefecture-level cities in Shandong Province as the research object. It analyzes the spatial and temporal distribution pattern of carbon emissions in Shandong Province based on land-use data and energy consumption. In terms of net carbon emissions, this study utilizes the standard deviation ellipse and kernel density estimation to analyze net carbon emissions change from the municipal and regional perspectives. In terms of carbon ecological carrying capacity, not only the carbon ecological carrying capacity of forest and grassland was considered, but also the carbon ecological carrying capacity of crops in Shandong Province, which is a large grain province. Using the geographic detector to explore the drivers. Research findings indicate that carbon sources and sinks show a clear spatial and temporal distribution pattern, with the center of gravity of net carbon emissions extending to the northeast. Areas with high carbon ecological carrying capacity have high forest coverage, grassland coverage, and crop yields. Regarding driving factors, the urbanization rate, economic aggregate, and technological progress demonstrate significant explanatory power through single and interaction tests, suggesting that these factors are critical drivers of land-use carbon emissions within Shandong Province. Based on the spatiotemporal pattern analysis of land-use carbon emissions in Shandong Province, each city's growth rate and spatial distribution characteristics can be clarified, providing a scientific basis for the local government to formulate regional and differentiated emission-reduction policies. In addition, by exploring the driving factors of land-use carbon emissions in Shandong Province, the influence level of factors on carbon emissions can be revealed to provide references for formulating regional sustainable development strategies.

The improvement strategy of fresh produce supply chain resilience based on extenics.

Nowadays, the world is in turmoil, climate and environmental problems are prominent, the import and export of fresh agricultural products are restricted, etc. The impact of the growing demand for fresh agricultural products and healthy lifestyle choices, and fresh agricultural products are essential for people's daily life, which are perishable, fragile, seasonal, and other unstable factors. Therefore, when the fresh produce supply chain faces various pressures and difficulties, how to enhance the resilience of the supply chain against various problems and risks with flexible and multi-dimensional strategies and methods has become the focus of extensive attention. This kind of problem is a typical contradictory problem, and previous studies have failed to achieve good results. In this paper, based on extenics, we are able to one-dimensionalise the multi-dimensional contradictory problems and multi-dimensionalise the one-dimensional contradictory problems to solve such problems in a scientific and effective way. Firstly, taking fresh agricultural products supply chain enterprise M as the research object, we constructed the fresh agricultural products supply chain enterprise toughness system and identified the toughness state of each index. Secondly, we found the low-evaluation toughness indexes that need to be solved and constructed a extension model of incompatible problems of enterprise toughness. Thirdly, we analysed the objectives and conditions of toughness incompatible problems of fresh agricultural products supply chain enterprises numerically and quantitatively, and then, with the objective of toughness improvement, we analyzed the correlation of the condition basic-elements of incompatible problems and carried out extension transformations. Again, the objectives and conditions of the incompatible problems of fresh produce supply chain enterprises are analysed numerically and quantitatively, and with toughness enhancement as the objective, the correlation analysis and extension transformation of the condition basic-elements of the incompatible problems are implemented to generate the set of toughness enhancement strategies that can solve the incompatible problems in a multidimensional and scientific way. Finally, the optimal toughness enhancement strategies are selected through the superiority evaluation and composed into a new strategy to enhance the toughness of the fresh produce supply chain. Combined with extenics calculations and screening, a new strategy for supply chain resilience enhancement of fresh agricultural products was finally formed. The existing problems are solved from six aspects: product supply type, product demand, product supply efficiency, human resource quantity, production and processing equipment, and logistics guarantee ability. It provides a certain reference significance for the fresh agricultural products supply chain toughness enhancement, and helps enterprises to strengthen their competitiveness and sustainability through the enhancement of toughness.

Investigating the Impact of Robotic Milling Parameters on the Surface Roughness of Al-Alloy Fabricated by Wire Arc Additive Manufacturing

This paper takes the single-wall wall manufactured by wire arc additive manufacturing (WAAM) as the research object and compares it with the as-cast aluminum alloy with the same series. By using feed rate, cutting depth, spindle speed, etc., as single or compound parameters, the machinability of the sample is analyzed. The results indicate that the influence of varying parameters on the as-deposited aluminum alloy follows the order of feed rate > cutting depth > spindle speed. As the feed rate increases, the surface roughness initially decreases and then increases, with the optimal surface quality achieved at 12 mm/s (with a surface roughness of 2.013 μm). Different from the as-deposited alloy, the influence of the parameters on the as-cast alloys follows the order of spindle speed > cutting depth > feed rate. The experiments reveal that, for both as-deposited and as-cast states, the trends of the impact of cutting depth and spindle speed on surface quality are consistent. However, at low feed rates (2–12 mm/s), for as-deposited states, the surface quality of as-deposited samples becomes smoother as the feed rate increases (contrary to common knowledge). This result can be attributed to the elevated milling temperature, which softens the material, making it easier to remove and reducing the surface roughness.

INNOVATIVE APPROACH TO ENSURING THE QUALITY OF GAS TURBINE ENGINE PARTS PRODUCED BY SELECTIVE LASER SINTERING FOR UAV

The research objects are gas turbine engines parts, manufactured using an innovative method of additive manufacturing – selective laser sintering. The main problem solved in this work is the low quality of the surface layer and the residual porosity of the parts obtained by this method, which significantly limits their operational characteristics and durability. As a result of the experimental studies, rational operating parameters of diamond smoothing were established. This allowed to significantly improve the surface quality and increase the operational characteristics of parts made of heat-resistant alloys INCONEL 718 and an intermetallic alloy based on titanium aluminide OX45-3ODS. The effectiveness of diamond smoothing is explained by local plastic deformation and compaction of the surface layer of parts under the influence of high contact pressures and temperatures. This leads to a significant reduction in surface roughness, an increase in the surface hardness due to strain hardening and a significant reduction in the size and number of residual pores. A characteristic feature of the obtained results is the ability to control the quality parameters of the surface layer by varying the diamond smoothing operating parameters – smoothing force, feed, radius, and geometry of the smoother's working part. The established regularities of the smoothing operating parameters have an impact on the quality characteristics of the surface. This information can be utilized in the development of highly efficient technological processes for the production and restoration of gas turbine engines, critical components of unmanned aerial vehicles, obtained through selective laser sintering. Implementing the elaborated technological recommendations will permit broadening the range of goods produced by additive manufacturing and enhancing their capacity and dependability during operation under conditions of cyclical loads and extreme temperatures.

STUDY ON THE IMPACT OF DEFORMATIONS OF MULTI-STOREY BUILDINGS IN ALMATY

The article provides an assessment of the stability of buildings and structures in the city of Almaty under the influence of frequent earthquakes. Studying this process is not only interesting from a scientific point of view but also has great practical significance for ensuring the safety and stability of buildings in the city. The aim of the work is to investigate the condition of buildings in Almaty in terms of seismic safety characteristics. The research tasks include studying the types of buildings common in the city of Almaty and conducting stability calculations for buildings. This article selects the main and most common type of buildings and structures in each district of the city of Almaty as the research object. The calculations of the level of buildings' stability to seismic vibrations in different areas of the city, information on the estimated seismic resistance level of most buildings, and the calculation of their possible stability indicators are provided. The results show that the stability of buildings and structures in the city depends on reducing seismic activity from bottom to top based on their location (on the map). According to the calculation conclusions, it is necessary to increase the number of design organizations responsible for construction quality and use different building structures and construction methods in different parts of the city. Problems related to building deformation are relevant everywhere. Studying this process in Almaty will contribute to the global knowledge base and help create new technical solutions for safe construction.

Experimental study on the mechanical properties of red sandstone with fractures under different loading rates

In order to study the effects of crack inclination angle and loading rate on rock mechanical properties, creep characteristics, and failure characteristics. Taking homogeneous red sandstone with different fracture angles as the research object, uniaxial compression tests and uniaxial compression creep tests were conducted at different loading rates. The results showed that under the same fracture angle, the loading rate was positively correlated with the peak strength, elastic modulus, instantaneous strain, creep strain, and steady-state creep rate of the sample, while negatively correlated with the peak strain. At the same loading rate, the mechanical properties and creep properties of the sample were controlled by the crack inclination angle α. With the increase of α, the peak strength, peak strain, instantaneous strain, creep strain and steady-state creep rate decreased first and then increased, and the elastic modulus increased. On the basis of rock creep testing, it is also important to establish a creep model that conforms to the actual test situation for studying rock creep characteristics. However, many models currently used cannot accurately describe the three stages of rock creep, especially the accelerated creep stage. Therefore, based on Burgers elements, this paper introduces plastic damage bodies based on damage rates and software components based on fractional calculus, A new creep model was obtained and its rationality was verified through experimental results. The results showed that the fit between the model and experimental data was above 0.97, indicating that the model can better describe the three stages of rock creep, especially reflecting the non-linear characteristics of the accelerated creep stage.