Similarity Criteria Research Articles

Research on the Influence of Sand-Mud Interlayer Properties on the Expansion of SAGD Steam Chamber

Summary Thermal recovery techniques serve as the primary approach for developing heavy oil due to its high viscosity and poor flowability. In this study, we established a high-temperature and high-pressure 3D physical experimental and numerical model based on the unique reservoir characteristics of the sand-mud interlayer in the Long Lake oil sands of Canada, using similarity criteria. Physical and numerical experiments employing steam-assisted gravity drainage (SAGD) were conducted to investigate the impact of sand-mud interlayer properties on the expansion limit of steam chambers during SAGD development. The results indicate that the expansion mode and limit of the steam chamber play a decisive role in heavy oil mobilization. Notably, heat loss during steam chamber expansion and the flow resistance caused by the interlayer are critical factors influencing the SAGD process. The presence of the interlayer extends the mobilization range in the lower portion of the reservoir, but it also limits the upward expansion of the steam chamber, resulting in a reduced mobilization range above the interlayer. Moreover, the steam chamber above the interlayer exhibits a distinct expansion pattern, featuring concave sides and a convex middle, resembling a “positive triangle.” Furthermore, the properties of the sand-mud interlayer and production parameters significantly affect the expansion limit of the steam chamber. Permeability and position exert a substantial impact on recovery, whereas thickness has a minor influence. Specifically, at an injection rate of 20 mL·min–1, steam quality of approximately 0.7, and a production/injection ratio of approximately 1.0, the steam chamber can successfully penetrate interlayers with a thickness of either 3.5 m and a permeability of 100×10−3 μm2 or 4.5 m and a permeability of 200×10−3 μm2.

The Determination of Effective Modes of Wind-Bridge Coupling System Based on Stabilization Clustering Method

Modal identification is the core content of the full-bridge aeroelastic model wind tunnel test. Modal consistency is the most direct and effective basis to ensure that the model and the real bridge meet the similarity criteria. Accurate, simple and fast identification of modal parameters has very important practical significance for the evaluation and correction of aeroelastic models. In this paper, the eigensystem realization algorithm (ERA) and stochastic subspace identification (SSI) is improved, and the automatic identification theory of effective modes of bridge aeroelastic model based on stable clustering method is proposed. The stable diagram eliminates the unstable modes by comparing the results of different system orders, and the pedigree clustering further polarizes the stable modes to obtain multi-order and high-precision system modes. Numerical simulation examples and wind tunnel engineering examples show that the method has high accuracy and good adaptability, and can solve the problem of unstable damping identification results to a certain extent. In the wind tunnel test, the stable clustering method is one of the effective methods to identify the modal of the bridge aeroelastic model excited by the wind environment.

Study on Characteristics of Steam Chamber and Factors Influencing Nitrogen-Assisted Vertical–Horizontal Steam Drainage Development

With the notable achievements attained through the implementation of steam-assisted gravity drainage (SAGD), the vertical–horizontal steam drive (VHSD) emerges as a pivotal technological advancement aimed at significantly enhancing the efficiency of thin reservoir heavy oil recovery subsequent to steam cyclic stimulation. The inclusion of nitrogen assistance has proven effective in enhancing the efficacy of gravity drainage techniques in reservoir development. However, it is noteworthy that this method has only led to improvements in approximately 50% of the well groups within the observed field. The comprehensive evaluation index of VHSD was proposed, and as the objective function, it was determined that the greatest contribution to the VHSD technique lies in oil saturation, accounting for 40% of the overall evaluations. This differs from conventional SAGD operations, where reservoir thickness serves as the primary determinant. Building upon an enhanced physical simulation similarity criterion, two comparative injection scheme experiments were conducted to explore the impact of nitrogen injection on the performance of VHSD and the characteristics of the steam chamber. Nitrogen is distributed in the vicinity of the steam chamber, leading to the formation of a dual mechanism characterized by ‘top heat insulation and lateral traction’ on the steam chamber. The lateral traction accounts for approximately 25% of the team chamber volume. Additionally, the inducement of nitrogen causes a downward displacement of crude oil, resulting in its accumulation within the high-temperature region of the steam chamber. This, in turn, enhances the contact area between the high-temperature steam and the crude oil, ultimately leading to improvement in production efficiency. Further validation of the impact of nitrogen on steam lateral traction and interlayer steam drainage within the reservoir was confirmed using Xinjiang oilfield testing. The well temperature increased from 75 °C to 130 °C.

Criterial dependencies of the movement of the melt refractory material in the bath of an ore thermal furnace under electromagnetic influence

In this work, for the first time, criterion dependencies of the speed of movement of the melt in the bath of an ore-thermal furnace during electric arc melting of oxide refractory materials under external electromagnetic influence were obtained. The initial quantitative characteristics for generalization in the form of the dependence of the speed in the zone of intense movement of the melt on the currents in the electrodes and the electromagnetic device were taken on the electrolyte and mercury physical models of an ore-smelting furnace with an electromagnetic device. Physical modeling was carried out while maintaining the invariance of the derived similarity criteria: the electrovortex flow parameter πμ and the external magnetic field parameter πl. In order to extend the experimental results obtained to a whole group of similar phenomena, the dependences of the dimensionless speed of melt movement (Reynolds criterion) on the dimensionless parameters of the external magnetic field and electric vortex flow were obtained and constructed. Since for all similar processes the similarity criteria retain the same values, then the criterion dependencies for them will be the same, and the results obtained can be extended to all similar cases.

Research on the Accounting and Prediction of Carbon Emission from Wave Energy Convertor Based on the Whole Lifecycle

Wave energy, as a significant renewable and clean energy source with vast global reserves, exhibits no greenhouse gas or other pollution during real-sea operational conditions. However, throughout the entire lifecycle, wave energy convertors can produce additional CO2 emissions due to the use of raw materials and emissions during transportation. Based on laboratory test data from a wave energy convertor model, this study ensures consistency between the model and the actual sea-deployed wave energy convertors in terms of performance, materials, and geometric shapes using similarity criteria. Carbon emission factors from China, the European Union, Brazil, and Japan are selected to predict the carbon emissions of wave energy convertors in real-sea conditions. The research indicates: (1) The predicted carbon emission coefficient for unit electricity generation (EFco2) of wave energy is 0.008–0.057 kg CO2/kWh; when the traditional steel production mode is adopted, the EFco2 in this paper is 0.014–0.059 kg CO2/kWh, similar to existing research conclusions for the emission factor of CO2 for wave energy convertor (0.012–0.050 kg CO2/kWh). The predicted data on carbon emissions in the lifecycle of wave energy convertors aligns closely with actual operational data. (2) The main source of carbon emissions in the life cycle of a wave energy converter, excluding the recycling of manufacturing metal materials, is the manufacturing stage, which accounts for 90% of the total carbon emissions. When the recycling of manufacturing metal materials is considered, the carbon emissions in the manufacturing stage are reduced, and the carbon emissions in the transport stage are increased, from about 7% to about 20%. (3) Under the most ideal conditions, the carbon payback period for a wave energy convertor ranges from 0.28 to 2.06 years, and the carbon reduction during the design lifespan (20 years) varies from 238.33 t CO2 (minimum) to 261.80 t CO2 (maximum).

Adaptable software tools for searching objects-analogues tasks 
 in NO-CODE concept

The paper is devoted to the problem of methodological and software support for the search of object analogues, performed when solving the problems of modelling and designing the development of oil and gas fields. The article shows that there is no single generally accepted methodology for searching analogues, existing methodologies differ in applied similarity criteria and search algorithms, are adapted to the search conditions, and are modernised. With the inconsistency of methods computer programs for searching analogues are created at a low level of abstraction, for a limited range of tasks, the existing developments are integrated with corporate databases and in general do not solve the problem of providing analysts with pro-software tools. As a solution we propose the development of programs for searching analogues in the concept of "no-code" (without programming) on the basis of analytical platforms. The "no-code" approach will allow analysts without involving programmers to create software tools for searching analogues, implementing their own variant methods. The article presents the authors' algorithm for express analysis of data at the initial stage of analogue search and the software tool that implements it, created "no code" on the basis of the Russian analytical platform Loginom.

Robust equivalent circuit model parameters identification scheme for State of Charge (SOC) estimation based on maximum correntropy criterion

Equivalent circuit model (ECM) parameters identification, which aims to identify the model parameters of ECM accurately is vital for assessing battery status and refining battery management systems (BMS), extensive research has been conducted in this field. However, most of the existing studies rely on global similarity criteria such as Root Mean Square Error (RMSE) and Sum of Squares due to Error (SSE), which are highly sensitive to non-Gaussian noise, so they may not perform effectively when faced with the non-Gaussian noise which is often encountered in battery working environments. This article presents a robust ECM parameter identification scheme termed the Maximum Correntropy Criterion-based Gradient Ascending scheme (MCCGA). The proposed MCCGA scheme adopts correntropy for similarity assessment and leverages a gradient ascent algorithm to optimize the model parameters iteratively. Through these methods, the MCCGA scheme not only identifies model parameters with precision but also remains robustness to non-Gaussian noise. Extensive experimental results based on public dataset are provided, which validate the effectiveness, robustness and convergence of the proposed MCCGA scheme.

Решение задач тепло- и массообмена в технических объектах на основе компьютерного моделирования

The purpose of the work is to carry out the necessary theoretical research and practical research for the possibility of using modern methods of ventilation of premises or using these methods in various technical installations of a nuclear reactor. The study is based on the study of the aerodynamic characteristics of an object (a crowded ship room or a nuclear reactor) at reference points. The scientific novelty of the work consists in the use of patented technologies (originally proposed by the author, and then patented by the responsible executor of the topic, a hydroaerodynamic transformer) and equipment for solving these problems for use in nuclear energy. The results of scientific research may be of interest to a wide range of specialists and scientists, mainly for nuclear energy. The research methods are based on the methods of similarity theory (Reynolds similarity criterion) and differential equations. A mathematical approach to modeling the system under study and heat and mass transfer processes occurring in an industrial nuclear power plant or spatial objects of ship premises has been formed. A general methodological approach and a scheme for the research installation of a nuclear reactor have been developed, and a model based on second-order regression equations has been constructed. Based on mathematical models and confirmed theoretical results, the distribution of gas-liquid flows is empirically visualized in experimental studies. The intensification of heat and mass transfer in the fuel assembly of a nuclear reactor is considered.

A Machine Learning-Based Surrogate Model for Similarity Criterion of Solidification

A Machine Learning-Based Surrogate Model for Similarity Criterion of Solidification

Improving model choice in classification: an approach based on clustering of covariance matrices

This work introduces a refinement of the Parsimonious Model for fitting a Gaussian Mixture. The improvement is based on the consideration of clusters of the involved covariance matrices according to a criterion, such as sharing Principal Directions. This and other similarity criteria that arise from the spectral decomposition of a matrix are the bases of the Parsimonious Model. We show that such groupings of covariance matrices can be achieved through simple modifications of the CEM (Classification Expectation Maximization) algorithm. Our approach leads to propose Gaussian Mixture Models for model-based clustering and discriminant analysis, in which covariance matrices are clustered according to a parsimonious criterion, creating intermediate steps between the fourteen widely known parsimonious models. The added versatility not only allows us to obtain models with fewer parameters for fitting the data, but also provides greater interpretability. We show its usefulness for model-based clustering and discriminant analysis, providing algorithms to find approximate solutions verifying suitable size, shape and orientation constraints, and applying them to both simulation and real data examples.

Experimental study on reinjection enhancement of sandstone with radial wells

Geothermal resources are abundant and can be vigorously developed. Vertical well reinjection is widely used in sandstone geothermal resources, but the efficiency is low due to near-well blockage. There is a lack of existing measures to improve reinjection efficiency. For sandstone reservoirs, a new method using radial well technology is proposed to enhance reinjection efficiency. Firstly, based on similarity criteria and non-dimensional analysis, the main experiment parameters and materials are determined. Secondly, a geothermal reinjection enhancement experiment system is constructed. Finally, reinjection experiments are conducted with radial well branch number, layer number, and phase angle to explore the impact of each parameter on reinjection efficiency. Results indicate that, in comparison to vertical well, radial wells can markedly increase the total fluid uptake. The maximum reinjection enhancements of radial wells is 90.49 %. The pressure drop coefficients can reach a minimum of 0.025. Within the same radial well type, the total fluid uptake shows an overall rising trend with an increase in the number of branch wells. Compared to single-layer radial wells, double-layer radial wells demonstrate better overall reinjection efficiency. Additionally, when comparing double-layer parallel and double-layer intersecting radial wells, the latter exhibits a more advantageous overall reinjection enhancement. The study suggests that radial wells can alleviate near-wellbore clogging, significantly increase reinjection capacity in sandstone reservoirs, and provide an effective technical approach and experiment evidence for efficient reinjection development in sandstone.

Suitability of Polymers for 3D-Printing Laboratory Models for Shaking Table Experiments: Discussion and Indications.

This paper presents a comprehensive assessment of the suitability of seven commercially available polymers for crafting laboratory models designed for dynamic shaking-table tests using 3D-printing technology. The objective was to determine whether 3D-printed polymer models are effective for dynamic assessments of structures. The polymers underwent experimental investigations to assess their material properties, i.e., the elastic modulus, the mass density, and the limit of linear-elastic behaviour. The following methodology was applied to obtain the correct values of elasticity moduli and yield points of the polymers: (1) the uniaxial tensile test, (2) the compression test, and (3) the three-point loading test. The filament density was determined as the ratio of sample mass to its volume. The results indicate substantial variations in stiffness, density, and elasticity limits among them. For the similarity analysis, an existing reinforced concrete chimney 120 m high was chosen as a prototype. A geometric similarity scale of 1:120 for a laboratory mock-up was adopted, and a numerical model of the mock-up was created. The similarity scales were calculated for mock-ups made of each filament. Based on these scales, numerical calculations of natural frequencies and dynamic performance under a strong earthquake were carried out for models made of different polymers. Assessment of the polymers' suitability for laboratory models revealed positive outcomes. The agreement between field experiments, shaking-table tests, and numerical predictions in terms of natural frequencies was observed. Maximum stresses resulting from the earthquake indicated the satisfactory performance of the model below the linear-elastic limit. Despite differences in material properties, the selected polymers were deemed suitable for 3D-printing models for shaking-table tests. However, the discussion raised some important considerations. The upper frequency limit of the shaking-table imposes restrictions on the number of natural frequencies that can be determined. Numerical assessments of natural frequencies are recommended to prevent underestimation and to assess the feasibility of their determination. Additionally, resonance during natural frequency determination may lead to exceeding the linear-elastic limit, affecting filament properties, and making the similarity criteria invalid. Practically, this research contributes insights for planning shaking-table tests, aiding in selecting the most suitable filament and highlighting crucial considerations to ensure reliable and accurate dynamic assessments.

Self-Adjusted Consensus Clustering with Agglomerate Algorithms

This paper reports of theoretical and computational results related to an original concept of consensus clustering involving what we call the projective distance between partitions. This distance is defined as the squared difference between a partition incidence matrix and its image over the orthogonal projection in the linear space spanning the other partition incidence matrix. It appears, provided that the ensemble clustering is of a sufficient size, agglomerate clustering with the semi-average within-cluster similarity criterion effectively solves the problem of consensus partition and, moreover, of the number of clusters in it.

An online low-dimension fuzzy modeling method for time-varying processes

Many industrial processes are full of nonlinearity and noise. Fuzzy modeling often leads to issues with dimension disaster and poor robustness for such processes. To address these issues, an online low-dimension fuzzy method (OLDF) is proposed here. First, an explicit mapping-based low-dimension fuzzy method (EMLF) is proposed to handle intricate nonlinear and noisy processes. In this method, similar fuzzy sets are combined into larger ones using a novel similarity criterion to reduce the fuzzy rules. Then, an explicit mapping strategy is developed to represent the local nonlinearities in each enlarged fuzzy set through an explicit mapping function. Subsequently, a robust objective function is constructed to improve the robustness of EMLF model. This objective function minimizes both the mean and variance of the modeling error, ensuring robust performance even in scenarios featuring non-Gaussian noise or outliers. After that, an online update strategy is designed to account for time-varying dynamics. It designs an adaptive detection mechanism to identify changes in dynamic behaviors. Following detection, global and local updating strategies are developed to dynamically update model parameters. Further analysis and proof highlight the effectiveness of the proposed method. Experiments with time-varying processes also confirm its success.

Методика циклических испытаний образцов-моделей коленчатого вала судового двигателя внутреннего сгорания на изгиб с кручением

It is proposed to consider the bending fatigue strength of the crankshaft as the main criterion of its operability during operation. It is noted that thermomechanical straightening with heating by stress relaxation method is most acceptable for straightening critical shafts that have received a curvature of the longitudinal axis during operation. Bending fatigue tests of round samples with a diameter of 20 mm in a dangerous section were carried out to substantiate the correction technology, test modes and evaluate the results of the correction. It was found that an increase in diameter leads to a decrease in the endurance limit of structural steels. The loading scheme of the experimental sample is adopted – transverse bending with torsion. A semicircular notch in the sample was used to focus the fracture site, and the radius of the notch was calculated. The size of the sample tuck is determined by the formula based on the similarity criterion adopted in the statistical theory of similarity of fatigue failure of parts, proposed by V. P. Kogaev. The requirements for the roughness of the surface of a circular groove of at least Ra 0.16 are established. The need for control of the manufacturing technology of the experimental sample is noted. An experimental installation for testing flexural fatigue strength is proposed. A cone cartridge was used to securely fasten and prevent the sample from turning during the experiment. Experimental samples were used-models with deflection arrows of 1, 2, 3, 4 and 5 mm. The method and equipment for obtaining samples with the necessary deflection arrows have been determined. Diagrams of a model sample for testing cantilever bending with torsion, an experimental installation for testing model samples, bending to a given deflection arrow, and a model sample with a curved longitudinal axis are presented.

MCMSTStream: applying minimum spanning tree to KD-tree-based micro-clusters to define arbitrary-shaped clusters in streaming data

Stream clustering has emerged as a vital area for processing streaming data in real-time, facilitating the extraction of meaningful information. While efficient approaches for defining and updating clusters based on similarity criteria have been proposed, outliers and noisy data within stream clustering areas pose a significant threat to the overall performance of clustering algorithms. Moreover, the limitation of existing methods in generating non-spherical clusters underscores the need for improved clustering quality. As a new methodology, we propose a new stream clustering approach, MCMSTStream, to overcome the abovementioned challenges. The algorithm applies MST to micro-clusters defined by using the KD-Tree data structure to define macro-clusters. MCMSTStream is robust against outliers and noisy data and has the ability to define clusters with arbitrary shapes. Furthermore, the proposed algorithm exhibits notable speed and can handling high-dimensional data. ARI and Purity indices are used to prove the clustering success of the MCMSTStream. The evaluation results reveal the superior performance of MCMSTStream compared to state-of-the-art stream clustering algorithms such as DenStream, DBSTREAM, and KD-AR Stream. The proposed method obtained a Purity value of 0.9780 and an ARI value of 0.7509, the highest scores for the KDD dataset. In the other 11 datasets, it obtained much higher results than its competitors. As a result, the proposed method is an effective stream clustering algorithm on datasets with outliers, high-dimensional, and arbitrary-shaped clusters. In addition, its runtime performance is also quite reasonable.

Начальный этап разработки математической модели для управления процессом магнитно-гравитационной сепарации в режиме реального времени

The initial stage of the mathematical model development designed to control in real time the enrichment of magnetite ores in magnetic gravity separators is presented the article. A significantly lower computational complexity in comparison with models using computational fluid dynamics tools is a main requirement for the created model. The study uses physical modeling and applies similarity criteria which well-known in hydrodynamics. As a result of processing of the laboratory experiments data, the structure of the model was established, the values of its parameters for boundary cases were obtained and the directions of further research on improving the model were determined.

Numerical validation of the dynamic aerodynamic similarity criterion for floating offshore wind turbines under equivalent pitch motions

Floating offshore wind turbines, as large equipment for deep-sea wind energy utilization, must be carefully studied for their aerodynamic performances under platform motions. In experiments, the model wind turbine designed by the traditional thrust coefficient similarity is usually insufficient for unsteady aerodynamic reproductions of the prototype wind turbine. In this paper, a dynamic aerodynamic similarity criterion based on the mapping of the optimal tip speed ratio is introduced for wind tunnel model tests, and a model wind turbine is designed using the NREL 5-MW prototype wind turbine. In this case, to avoid the over-height model tower aroused in pitch motions, a method of equivalent surge motions instead of pitch motions is proposed and validated for feasibility. Then dynamic aerodynamic similarities under different pitch amplitudes and frequencies are validated by the Unsteady Blade Element Momentum theory. Results indicate that temporal and spatial characteristics and hysteresis effects of thrust and power coefficients all maintain better similarity with those of the prototype wind turbine than those of the model wind turbine designed by the traditional criterion. This paper provides a criterion with equivalent pitch motions for unsteady aerodynamic studies in wind tunnel model tests, especially the high-fidelity Hardware/Software-In-the-Loop test.

Design of an axial hydrocyclone for preliminary water separation using CFD, RSM, and SUS

Preliminary water separators can effectively solve the problem of high-water-cut produced fluids in oil wells. In this study, we propose a co-design method for the serialization of an axial inlet preliminary water separator based on the combination of cyclone separation theory, computational fluid dynamics (CFD) simulations, response surface method (RSM) optimization, experimental verification, and a scale-up strategy (SUS). For an inlet water cut ≥ 70%, the water separation rate was ≥ 50% and the oil concentration of heavy phase outlet (HPO) was ≤ 1000 mg/L. The indoor experimental results indicated that the performance of the preliminary water separator could achieve better results obtained through the CFD simulation results were taken as sample points and the optimal structural size was found by machine learning method (MLM). The field pilot test results showed that the Hy similarity criterion based SUS did not affect the separation effect. For water cut in the range of 85.0–92.7%, the water separation rate was ≥ 50% and the HPO oil concentration was < 1321.6 mg/L. Our results can provide reference and guidance for the design and optimization of hydrocyclones for preliminary water separation of oilfield produced fluids.

FractalRG: Advanced fractal region growing using Gaussian mixture models for left atrium segmentation

This paper presents an advanced region growing method for precise left atrium (LA) segmentation and estimation of atrial wall thickness in CT/MRI scans. The method leverages a Gaussian mixture model (GMM) and fractal dimension (FD) analysis in a three-step procedure to enhance segmentation accuracy. The first step employs GMM for seed initialization based on the probability distribution of image intensities. The second step utilizes fractal-based texture analysis to capture image self-similarity and texture complexity. An enhanced approach for generating 3D fractal maps is proposed, providing valuable texture information for region growing. In the last step, fractal-guided 3D region growing is applied for segmentation. This process expands seed points iteratively by adding neighboring voxels meeting specific similarity criteria. GMM estimations and fractal maps are used to restrict the region growing process, reducing the search space for global segmentation and enhancing computational efficiency. Experiments on a dataset of 10 CT scans with 3,947 images resulted in a Dice score of 0.85, demonstrating superiority over traditional techniques. In a dataset of 30 MRI scans with 3,600 images, the proposed method achieved a competitive Dice score of 0.89±0.02, comparable to Deep Learning-based models. These results highlight the effectiveness of our approach in accurately delineating the LA region across diverse imaging modalities.