A quantum computing-based numerical method of mixed-integer optimal control problems under uncertainty for alkali–surfactant–polymer flooding

Liu, Zhe; Li, Shurong; Ge, Yulei

doi:10.1080/0305215x.2020.1741568

Cited by 11 publications

(3 citation statements)

References 19 publications

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“…Salt consumption is a very important factor in the composite drive of an alkali-free ternary emulsion system, which directly affects the success or failure of an oil drive. 20 There are many factors affecting salt consumption, and it is complex; so this model will be processed with some simplifications to achieve the purpose of describing the main salt consumption phenomena better and having a strong practicality at the same time. The salt consumption in the model is described by the chemical reaction term R. It is expressed as follows.…”

Section: Analysis Methodsmentioning

confidence: 99%

Numerical Simulation of Component Transfer and Oil Drive of Nonalkali Ternary Emulsion Systems

Liu,

Wu,

et al. 2023

ACS Omega

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So far, alkali/surfactant/polymer flooding is widely used in oilfields to improve recovery. However, the introduction of alkali to the ternary composite leads to substantial damage formation, accelerates the scaling and corrosion loss in all aspects of surface injection and recovery, and consequently increases the cost of oil recovery in the ternary composite drive field. Therefore, environmentally friendly means are in urgent demand. Alternatively, a new non-alkali ternary drive system with salt instead of alkali has been developed based on the basis of ternary composite drive in the Daqing oilfield. In this experiment, a mathematical model of oil repelling by a salt-substituted alkali-free ternary emulsion system is formed, followed by the verification of the wet-lab experiments. The results show that the alkali-free ternary emulsion system can have a synergistic effect of complex salt and petroleum sulfonate surfactant and represents a wide range of ultralow interfacial tensions and good oil-repelling performances. The chromatographic separation occurs in the transmission process due to the adsorption of porous media, and the lower the permeability and the lower the injection rate, the higher the chromatographic separation degree. The use of multistage plug injection can narrow the difference of flow rate between high and low permeability layers and improve the recovery rate to 61.59%. Herein, the results provide theoretical guidance for the application of an alkali-free ternary emulsification system.

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Section: Analysis Methodsmentioning

confidence: 99%

Numerical Simulation of Component Transfer and Oil Drive of Nonalkali Ternary Emulsion Systems

Liu,

Wu,

et al. 2023

ACS Omega

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“…CAD/CAM technology is a technology that uses computers for design and manufacturing. CAD allows engineers to use computers for design work, including drawing and model creation [4]. CAM, on the other hand, uses computers to control machine tools and manufacturing processes and is particularly important in the programming of CNC machines [5].…”

Section: Introductionmentioning

confidence: 99%

Research on CNC programming and machining process based on CAD/CAM technology

Zhang,

Bai

2024

Applied Mathematics and Nonlinear Sciences

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Focusing on CNC process data, this paper provides an in-depth analysis, characterization and mining of macro machining processes by associating CAD and CAM models. The article introduces a Bayesian inference method to construct an association relationship between the manufacturing features of the query part and the macroscopic process of the manufactured part, which avoids the need for a direct similarity comparison between the geometry of the query part and the part to be manufactured. In addition, the study calculated the overall similarity between the query part and the CNC programming process data instances through the guidance of the process skeleton, thus realizing the precise evaluation from the CNC programming perspective. The algorithm for generating tool trajectories in multi-axis CNC programming is analyzed. By selecting representative surfaces and performing tool processing calculations, this study explores the process planning and tool parameter selection of usual parts of surfaces in multi-axis CNC programming machining. It optimizes the nonlinear error in tool trajectory processing by combining CAD/CAM technology. The results show that the optimized process proposed in this paper significantly improves the machining efficiency by 36.94%. In the cutting at tool corners, the maximum cutting force generated by the optimized machining process is only 190.3N, which is only 67.2% of the leading cutting force of the Cimatron process. In addition, when the engagement frequency is 780 Hz, the optimized process proposed in this paper has the smallest vibration amplitude, which is only 21.4% of the Cimatron strategy. Therefore, this study significantly improves the machining efficiency while ensuring the machining quality, which has important practical application value.

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“…4 (2023) 2 https://internationalpubls.com to quantum calculations; furthermore, there is an additional set of challenges associated with encoding conventional nonlinear optimization problems into a quantum form appropriate for quantum processing [6]. Working together, quantum physicists and optimization researchers are essential for developing strong quantum algorithms [7], which necessitates knowledge of both quantum information science and optimization theory [8]. Quantum computers have the potential to completely transform optimization, the field is still in its early stages [9].…”

Section: Introductionmentioning

confidence: 99%

Quantum Computing Algorithms for Nonlinear Optimization Problems

Vishwakarma

2023

cana

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The increasing complexity of real-world optimization problems highlights the importance of this research since classical algorithms are unable to provide efficient answers in these cases. Innovative methods for fast and scalable resolution of nonlinear optimization problems are required because these problems are prevalent in many fields. The potential for quantum computing to speed up optimization processes and overcome classical limitations is great, owing to its superposition principles and intrinsic parallelism. The integration of quantum algorithms (I-QA) into real-world applications, however, will not always be smooth sailing. There are significant challenges associated with preserving quantum coherence, correcting errors, and working within hardware limits. To enable the simultaneous exploration of solution spaces through quantum parallelism, this research proposes the Hybrid Quantum Gradient -Classical Approach (HQG-CA), which makes use of parameterized quantum circuits to represent probable solutions. Additionally, improves convergence rates through applying quantum gradient information to direct optimization in the quantum state space. Optimization of portfolios in finance, adjustment of model parameters in machine learning, and optimization of routes in logistics are a few examples of the many industries that find use for HQG-CA. These applications are explored in this abstract, which highlights the revolutionary potential of HQG-CA to solve optimization problems in the real world. The effectiveness of HQG-CA is assessed through a thorough simulation experiment. Performance measures such algorithmic speedup, solution accuracy, and scalability are discussed, which is based on extensive testing and comparison with classical alternatives. The present research provides a comprehensive evaluation of HQG-CA's potential for tackling nonlinear optimization problems.

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A quantum computing-based numerical method of mixed-integer optimal control problems under uncertainty for alkali–surfactant–polymer flooding

Cited by 11 publications

References 19 publications

Numerical Simulation of Component Transfer and Oil Drive of Nonalkali Ternary Emulsion Systems

Numerical Simulation of Component Transfer and Oil Drive of Nonalkali Ternary Emulsion Systems

Research on CNC programming and machining process based on CAD/CAM technology

Quantum Computing Algorithms for Nonlinear Optimization Problems

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