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doi: 10.11729/syltlx20220017
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doi: 10.11729/syltlx20210194
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doi: 10.11729/syltlx20200119
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doi: 10.11729/syltlx20210066
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2022, 36(3): 1-10.
doi: 10.11729/syltlx20220005
Abstract:
The scientific experimental design method can significantly improve the quality and efficiency of scientific research and industrial production. This paper introduces and summarizes the research progress of modern test design methods. Firstly, this paper summarizes the differences between OFAT（One Fact at A Time） method and MDOE（Modern Design Of Experiments） method in the wind tunnel test in three aspects: the test purpose, organization strategy and test results, and analyzes the advantages of MDOE method. Secondly, it summarizes the status quo of the MDOE method in three aspects: the experimental design, model establish-ment and result analysis. Then we demonstrate the experimental design method with standard functions and aerodynamic examples. Finally, some key scientific problems and future research directions are discussed.
The scientific experimental design method can significantly improve the quality and efficiency of scientific research and industrial production. This paper introduces and summarizes the research progress of modern test design methods. Firstly, this paper summarizes the differences between OFAT（One Fact at A Time） method and MDOE（Modern Design Of Experiments） method in the wind tunnel test in three aspects: the test purpose, organization strategy and test results, and analyzes the advantages of MDOE method. Secondly, it summarizes the status quo of the MDOE method in three aspects: the experimental design, model establish-ment and result analysis. Then we demonstrate the experimental design method with standard functions and aerodynamic examples. Finally, some key scientific problems and future research directions are discussed.
2022, 36(3): 11-19.
doi: 10.11729/syltlx20210155
Abstract:
Advanced aircraft research requires rapid acquisition of correct-key data on the aerodynamic shape. The development of our country's aerospace equipment has gradually entered a stage of independent innovation. The exploration, innovation, and optimization of the aerodyna-mic design for a new generation of aircraft need to be supported by matching wind tunnel test capabilities. The development trend of high-performance and high-precision advanced aircraft has put forward higher requirements on the “quantity” and “quality” of wind tunnel test data, which means the design of traditional wind tunnel test schemes and data analysis modes have become increasingly unsatisfactory. It is necessary to make breakthroughs in wind tunnel test design and test data analysis technology. Based on aircraft ground test analysis, this paper uses the support vector machine（SVM） to model and analyze the test data, develop wind tunnel test plan optimization, design methods and test data intelligent analysis methods, and explore the new internal correlation between the aerodynamic data and aircraft geometric parameters. Building a wind tunnel test auxiliary design and analysis system to improve the efficiency of wind tunnel test and the accuracy of test data provides technical support for the aerodynamic design of high-performance aircraft.
Advanced aircraft research requires rapid acquisition of correct-key data on the aerodynamic shape. The development of our country's aerospace equipment has gradually entered a stage of independent innovation. The exploration, innovation, and optimization of the aerodyna-mic design for a new generation of aircraft need to be supported by matching wind tunnel test capabilities. The development trend of high-performance and high-precision advanced aircraft has put forward higher requirements on the “quantity” and “quality” of wind tunnel test data, which means the design of traditional wind tunnel test schemes and data analysis modes have become increasingly unsatisfactory. It is necessary to make breakthroughs in wind tunnel test design and test data analysis technology. Based on aircraft ground test analysis, this paper uses the support vector machine（SVM） to model and analyze the test data, develop wind tunnel test plan optimization, design methods and test data intelligent analysis methods, and explore the new internal correlation between the aerodynamic data and aircraft geometric parameters. Building a wind tunnel test auxiliary design and analysis system to improve the efficiency of wind tunnel test and the accuracy of test data provides technical support for the aerodynamic design of high-performance aircraft.
2022, 36(3): 20-32.
doi: 10.11729/syltlx20210179
Abstract:
Modern Design of Experiments （MDOE） is an important technical approach to improve wind tunnel test efficiency. Although the modern design of experiment method based on Latin Hypercube Sampling has high theoretical efficiency, the practical efficiency of the random sampling points designed by it decreases significantly when the automatic attitude control system of the wind tunnel model is coordinated. In this paper, a modern design of experiment method based on the Stratified Latin Hypercube design is proposed to meet the requirements of the multi-variable wind tunnel test design in the automatic attitude control system. It is applied to the two-variable test and three-variable test design of the 6 Mach number wind tunnel model. The results which were compared with the One Factor at A Time （OFAT） method show that MDOE method only needs about 20% of the sample size of OFAT method in the two-variable test and only needs about 30% of the sample size of OFAT method in the three-variable test. Compared with the classical Latin Hypercube method, the Stratified Latin Hypercube method developed in this paper combined with the existing wind tunnel test equipment can effectively reduce the change of test runs, improve the test efficiency and shorten the test period.
Modern Design of Experiments （MDOE） is an important technical approach to improve wind tunnel test efficiency. Although the modern design of experiment method based on Latin Hypercube Sampling has high theoretical efficiency, the practical efficiency of the random sampling points designed by it decreases significantly when the automatic attitude control system of the wind tunnel model is coordinated. In this paper, a modern design of experiment method based on the Stratified Latin Hypercube design is proposed to meet the requirements of the multi-variable wind tunnel test design in the automatic attitude control system. It is applied to the two-variable test and three-variable test design of the 6 Mach number wind tunnel model. The results which were compared with the One Factor at A Time （OFAT） method show that MDOE method only needs about 20% of the sample size of OFAT method in the two-variable test and only needs about 30% of the sample size of OFAT method in the three-variable test. Compared with the classical Latin Hypercube method, the Stratified Latin Hypercube method developed in this paper combined with the existing wind tunnel test equipment can effectively reduce the change of test runs, improve the test efficiency and shorten the test period.
2022, 36(3): 33-43.
doi: 10.11729/syltlx20210073
Abstract:
Accurate aerodynamic characteristic data under different conditions is the prerequisite and fundamental guarantee for the fast design of a flight vehicle, the improvement of a control system, the evaluation of performances and performance appraisal. The cross synthesis between the machine learning technology （ML） based on deep neural network （DNN） and fluid mechanics is developing fast and has achieved remarkable progresses in the modification of turbulence models, modeling of systems, prediction of the aerodynamic and aeroacoustic characteristics, optimization of control parameters and reconstruction of the flow field. To effectively apply the powerful representative capability of DNN, according to the demand of intelligent optimization and design of weapon bays, this paper first established a database of aerodynamic loads for flows past cavities and then built deep forward neural network model for the prediction of aerodynamic loads. To enhance the robustness of the model, random search and Bayesian optimization are introduced during the training of the model. Numerical results show that the trained DNN model is able to predict the aerodynamic loads and aeroacoustic characteristics accurately and efficiently, which provides a useful tool for the prediction and control of the aeroacoustic characteristics of the cavity.
Accurate aerodynamic characteristic data under different conditions is the prerequisite and fundamental guarantee for the fast design of a flight vehicle, the improvement of a control system, the evaluation of performances and performance appraisal. The cross synthesis between the machine learning technology （ML） based on deep neural network （DNN） and fluid mechanics is developing fast and has achieved remarkable progresses in the modification of turbulence models, modeling of systems, prediction of the aerodynamic and aeroacoustic characteristics, optimization of control parameters and reconstruction of the flow field. To effectively apply the powerful representative capability of DNN, according to the demand of intelligent optimization and design of weapon bays, this paper first established a database of aerodynamic loads for flows past cavities and then built deep forward neural network model for the prediction of aerodynamic loads. To enhance the robustness of the model, random search and Bayesian optimization are introduced during the training of the model. Numerical results show that the trained DNN model is able to predict the aerodynamic loads and aeroacoustic characteristics accurately and efficiently, which provides a useful tool for the prediction and control of the aeroacoustic characteristics of the cavity.
2022, 36(3): 44-54.
doi: 10.11729/syltlx20210168
Abstract:
The flow control actuator is the core of the active flow control technology. The design level and performance of actuator directly determine the application direction and effect of active flow control. In order to obtain the action law of the flow control actuator, a large number of experiments are needed to study the influence of excitation parameters on control effect parameters, and the experimental cost is large. In this paper, the experimental data of jet shock control in reverse plasma synthesis are used, and the Gaussian process regression model in machine learning is used to obtain the mapping law from the actuator parameters （head cone diameter, cavity volume, discharge capacitance and outlet diameter） to the control effect parameters （maximum out of body distance）. We compare the prediction effects of Gaussian process regression under various kernel functions, and analyze the influence of actuator parameters on control effect parameters by using the characteristic importance analysis method. The results show that for this small sample problem, Gaussian process regression with the quadratic polynomial kernel function Poly2 obtains the highest accuracy; in characteristic importance analysis, the head cone diameter has the greatest influence on the maximum separation distance, followed by discharge capacitance and cavity volume. The influence of these two parameters is similar, and the influence of the outlet diameter is the least. The work of this paper can provide some guidance for the setting of various parameters of the actuator in the flow control experiment of the high-speed complex flow field.
The flow control actuator is the core of the active flow control technology. The design level and performance of actuator directly determine the application direction and effect of active flow control. In order to obtain the action law of the flow control actuator, a large number of experiments are needed to study the influence of excitation parameters on control effect parameters, and the experimental cost is large. In this paper, the experimental data of jet shock control in reverse plasma synthesis are used, and the Gaussian process regression model in machine learning is used to obtain the mapping law from the actuator parameters （head cone diameter, cavity volume, discharge capacitance and outlet diameter） to the control effect parameters （maximum out of body distance）. We compare the prediction effects of Gaussian process regression under various kernel functions, and analyze the influence of actuator parameters on control effect parameters by using the characteristic importance analysis method. The results show that for this small sample problem, Gaussian process regression with the quadratic polynomial kernel function Poly2 obtains the highest accuracy; in characteristic importance analysis, the head cone diameter has the greatest influence on the maximum separation distance, followed by discharge capacitance and cavity volume. The influence of these two parameters is similar, and the influence of the outlet diameter is the least. The work of this paper can provide some guidance for the setting of various parameters of the actuator in the flow control experiment of the high-speed complex flow field.
2022, 36(3): 55-64.
doi: 10.11729/syltlx20210085
Abstract:
A jet closed-loop control system based on Deep Reinforcement Learning （DRL） was built, and an experimental study was carried out on the separation flow control at high angles of attack on the NACA0012 airfoil. The airfoil chord length is 200 mm and the wind speed was 10 m/s. The Reynolds number was 1.36×105 based on the chord length. The jet actuator was arranged on the upper surface of the airfoil and the solenoid valve was used for stepless control. The pressure coefficient of the airfoil surface and the action output of the agent itself were taken as the observation of the agent. The pressure coefficient of the trailing edge of the airfoil was used as the reward function to train the agent. Our results showed that the trained agent successfully suppresses the flow separation at high angles of attack and the cost-effectiveness ratio is reduced by 50% compared with steady blowing. At the same time, the agent could also stabilize the pressure coefficient of the trailing edge near the target value. The state input and the change of the reward function also have different effects on the final training effect.
A jet closed-loop control system based on Deep Reinforcement Learning （DRL） was built, and an experimental study was carried out on the separation flow control at high angles of attack on the NACA0012 airfoil. The airfoil chord length is 200 mm and the wind speed was 10 m/s. The Reynolds number was 1.36×105 based on the chord length. The jet actuator was arranged on the upper surface of the airfoil and the solenoid valve was used for stepless control. The pressure coefficient of the airfoil surface and the action output of the agent itself were taken as the observation of the agent. The pressure coefficient of the trailing edge of the airfoil was used as the reward function to train the agent. Our results showed that the trained agent successfully suppresses the flow separation at high angles of attack and the cost-effectiveness ratio is reduced by 50% compared with steady blowing. At the same time, the agent could also stabilize the pressure coefficient of the trailing edge near the target value. The state input and the change of the reward function also have different effects on the final training effect.
2016, 30(1): 28-42.
doi: 10.11729/syltlx20150069
摘要：
粒子图像测速技术目前已经发展成为实验流体力学领域应用最广泛的非接触激光测试方法之一,为认知复杂流动机理提供直观的流场信息.本文基于超声速流场PIV技术研究实践,针对示踪粒子布撒器设计、粒子松弛特性模型构建、激波流场测试分析、超声速平板湍流边界层结构分析等方面具体问题的研究和认识,从理论、定量化的角度深入分析了应用于超声速流场PIV技术现阶段依然存在的问题.从应用于超声速流场PIV技术的原理出发,针对高速复杂流场的PIV测试现状,总结了应用于超声速流场PIV技术发展过程中的光学部件、示踪粒子及布撒系统所遇到的一系列挑战,以及国内外利用PIV技术在高速复杂流场研究中所取得的成就,针对PIV技术能否适用于高超声速流场的测量做了系统化地探索.并根据实践经验提出了应用于超声速流场PIV技术未来的发展方向:通用的精确的PIV方法不存在,必须从具体研究的流动机理角度改造相应的PIV测试手段.
粒子图像测速技术目前已经发展成为实验流体力学领域应用最广泛的非接触激光测试方法之一,为认知复杂流动机理提供直观的流场信息.本文基于超声速流场PIV技术研究实践,针对示踪粒子布撒器设计、粒子松弛特性模型构建、激波流场测试分析、超声速平板湍流边界层结构分析等方面具体问题的研究和认识,从理论、定量化的角度深入分析了应用于超声速流场PIV技术现阶段依然存在的问题.从应用于超声速流场PIV技术的原理出发,针对高速复杂流场的PIV测试现状,总结了应用于超声速流场PIV技术发展过程中的光学部件、示踪粒子及布撒系统所遇到的一系列挑战,以及国内外利用PIV技术在高速复杂流场研究中所取得的成就,针对PIV技术能否适用于高超声速流场的测量做了系统化地探索.并根据实践经验提出了应用于超声速流场PIV技术未来的发展方向:通用的精确的PIV方法不存在,必须从具体研究的流动机理角度改造相应的PIV测试手段.
2016, 30(4): 7-13.
doi: 10.11729/syltlx20150112
摘要：
通过刚性模型测压风洞试验，研究了圆柱的气动阻力、气动升力系数和风压系数随雷诺数的变化规律，从流场分布的角度分析了气动力变化的原因，并研究了雷诺数影响下的流场在圆柱轴向的相关性。结果表明：在亚临界雷诺数区域，在时间平均上流场沿模型两侧呈对称分布，雷诺数对平均阻力系数和流场影响较小，平均升力系数基本为零。在临界雷诺数区域，随着特定区域大负压区的出现，流场不再对称，出现不容忽视的平均升力和脉动升力。在超临界雷诺数区域，随着对称侧大负压区的出现，流场恢复对称状态，平均升力基本消失。雷诺数对流场的轴向相关性有显著的影响。在雷诺数较低时（亚临界区域），卡门涡在轴向上的尺度相对较大，而随着雷诺数的提高，该尺度逐渐减小，各断面流场的相关性降低。
通过刚性模型测压风洞试验，研究了圆柱的气动阻力、气动升力系数和风压系数随雷诺数的变化规律，从流场分布的角度分析了气动力变化的原因，并研究了雷诺数影响下的流场在圆柱轴向的相关性。结果表明：在亚临界雷诺数区域，在时间平均上流场沿模型两侧呈对称分布，雷诺数对平均阻力系数和流场影响较小，平均升力系数基本为零。在临界雷诺数区域，随着特定区域大负压区的出现，流场不再对称，出现不容忽视的平均升力和脉动升力。在超临界雷诺数区域，随着对称侧大负压区的出现，流场恢复对称状态，平均升力基本消失。雷诺数对流场的轴向相关性有显著的影响。在雷诺数较低时（亚临界区域），卡门涡在轴向上的尺度相对较大，而随着雷诺数的提高，该尺度逐渐减小，各断面流场的相关性降低。
2016, 30(2): 67-74.
doi: 10.11729/syltlx20150091
摘要：
采用粒子成像速度场仪(PIV)和数值模拟(CFD)对Taylor-Couette 流场进行测量,获得各转速下涡流场信息。将同等条件下PIV测量结果与数值模拟结果相联系,对比分析不同旋转雷诺数范围内涡流场中不同径线和中轴线上各向速度的变化特征。结果表明,各种特征存在一定的转速分段范围:在2~7r/min(Re为100~350)时,各向速度特征为层流涡特性,在7~40r/min(Re为350~2000)时,各向速度特征为波状涡特性,在40~60r/min (Re为2000~3000)时,各向速度特征为调制波状涡特性,当转速大于60r/min(Re大于3000)时,各向速度特征为湍流涡特性。根据不同角度获得的各向速度特征对应的内筒转速、旋转雷诺数与流场涡形态的关系,明确分析出特定几何条件下,泰勒涡发生形态转变的旋转雷诺数,以便于深入探究泰勒涡流场的特性,定量分析涡运动形态特征。
采用粒子成像速度场仪(PIV)和数值模拟(CFD)对Taylor-Couette 流场进行测量,获得各转速下涡流场信息。将同等条件下PIV测量结果与数值模拟结果相联系,对比分析不同旋转雷诺数范围内涡流场中不同径线和中轴线上各向速度的变化特征。结果表明,各种特征存在一定的转速分段范围:在2~7r/min(Re为100~350)时,各向速度特征为层流涡特性,在7~40r/min(Re为350~2000)时,各向速度特征为波状涡特性,在40~60r/min (Re为2000~3000)时,各向速度特征为调制波状涡特性,当转速大于60r/min(Re大于3000)时,各向速度特征为湍流涡特性。根据不同角度获得的各向速度特征对应的内筒转速、旋转雷诺数与流场涡形态的关系,明确分析出特定几何条件下,泰勒涡发生形态转变的旋转雷诺数,以便于深入探究泰勒涡流场的特性,定量分析涡运动形态特征。
2017, 31(2): 1-11.
doi: 10.11729/syltlx20160129
摘要：
高超声速边界层感受性是边界层转捩预测与控制的关键环节，其对高超声速飞行器研究至关重要。目前关于高超声速边界层感受性的实验研究仍然十分匮乏，为了更好地理解高超声速边界层感受性过程并指导该领域的实验研究，文章梳理了近20年来国际上高超声速边界层感受性问题的研究内容，包括对自由流扰动和壁面扰动的感受性，并主要介绍了Fedorov的前缘感受性理论和模态转化机制。最后总结了自由流扰动中感受性的不同发展路径。
高超声速边界层感受性是边界层转捩预测与控制的关键环节，其对高超声速飞行器研究至关重要。目前关于高超声速边界层感受性的实验研究仍然十分匮乏，为了更好地理解高超声速边界层感受性过程并指导该领域的实验研究，文章梳理了近20年来国际上高超声速边界层感受性问题的研究内容，包括对自由流扰动和壁面扰动的感受性，并主要介绍了Fedorov的前缘感受性理论和模态转化机制。最后总结了自由流扰动中感受性的不同发展路径。
2016, 30(1): 1-14,27.
doi: 10.11729/syltlx20150159
摘要：
火箭冲压组合发动机包含多个工作模态,不同模态灵活组合的优势使其具有宽速域和广空域的工作特点,兼具加速和巡航的优点.火箭冲压组合发动机燃烧室中存在着亚声速、跨声速和超声速共存的流动结构,具有流动速度高、混合时间短、反应强度大、燃烧空间受限和波系结构复杂等特点.围绕火箭射流的强剪切性、燃烧模式的多样性和燃烧过程的动态性,分析了火箭冲压组合发动机的流动与燃烧特征,总结了面向发动机的高速湍流燃烧研究进展,研究了火箭冲压组合发动机中超声速反应混合层的生长特性、燃烧模式与空间释热分布和动态燃烧特性等问题.通过对碳氢燃料详细化学动力学机理的简化、校验,获得了分别适合于工程计算和细致燃烧机理研究的总包反应与框架机理.从火箭射流主导的反应混合层生长模型,宽范围、变来流工作中流动燃烧过程的不确定性和碳氢燃料动力学的简化与加速算法研究出发,提出了火箭冲压组合发动机基础研究中需要突破的问题,为认识发动机中多尺度燃烧机理、优化多模态燃烧组织提供参考.
火箭冲压组合发动机包含多个工作模态,不同模态灵活组合的优势使其具有宽速域和广空域的工作特点,兼具加速和巡航的优点.火箭冲压组合发动机燃烧室中存在着亚声速、跨声速和超声速共存的流动结构,具有流动速度高、混合时间短、反应强度大、燃烧空间受限和波系结构复杂等特点.围绕火箭射流的强剪切性、燃烧模式的多样性和燃烧过程的动态性,分析了火箭冲压组合发动机的流动与燃烧特征,总结了面向发动机的高速湍流燃烧研究进展,研究了火箭冲压组合发动机中超声速反应混合层的生长特性、燃烧模式与空间释热分布和动态燃烧特性等问题.通过对碳氢燃料详细化学动力学机理的简化、校验,获得了分别适合于工程计算和细致燃烧机理研究的总包反应与框架机理.从火箭射流主导的反应混合层生长模型,宽范围、变来流工作中流动燃烧过程的不确定性和碳氢燃料动力学的简化与加速算法研究出发,提出了火箭冲压组合发动机基础研究中需要突破的问题,为认识发动机中多尺度燃烧机理、优化多模态燃烧组织提供参考.
2016, 30(1): 81-90.
doi: 10.11729/syltlx20150037
摘要：
投弃式海流剖面仪(Expendable Current Profiler,XCP)周围流场是典型的旋转圆柱绕流.探头周围流场对探头的运动状态起决定性作用,这直接关系到探头的测量性能,因此有必要对旋转圆柱周围流场进行实验研究.实验在循环水槽中进行,通过PIV对雷诺数保持不变(Re=1000)、不同圆柱旋转速度比(α=0、0.5、1.0、1.5、2.0、2.5、3.0、3.5、4.0、4.5和5.0)的圆柱下游尾流场进行研究.通过选取不同旋转速度比的任一时刻的瞬态流场,来分析旋转对圆柱尾流结构的影响.为了获得流场的频率信息,对所获得流场信息进行能谱分析来获取涡旋的脱落频率,并进一步使用正交模态分解对流场进行分析,给出了流场主要拟序结构及其能量与转速比的变化趋势.发现圆柱旋转改变圆柱尾流结构,使尾迹尺度变小.在旋转速度比0≤α≤2.0时,存在明显的周期性涡旋脱落,并且涡旋脱落的频率有逐渐升高的趋势;而且当转速比2.0<α≤5.0时尾迹流场的周期性减弱,涡旋脱落变得不明显,流场表现出低频、剪切层的区域特征.随着转速变大,涡旋尺度变小.在较高旋转速度比时,流场中能量被重新分布.
投弃式海流剖面仪(Expendable Current Profiler,XCP)周围流场是典型的旋转圆柱绕流.探头周围流场对探头的运动状态起决定性作用,这直接关系到探头的测量性能,因此有必要对旋转圆柱周围流场进行实验研究.实验在循环水槽中进行,通过PIV对雷诺数保持不变(Re=1000)、不同圆柱旋转速度比(α=0、0.5、1.0、1.5、2.0、2.5、3.0、3.5、4.0、4.5和5.0)的圆柱下游尾流场进行研究.通过选取不同旋转速度比的任一时刻的瞬态流场,来分析旋转对圆柱尾流结构的影响.为了获得流场的频率信息,对所获得流场信息进行能谱分析来获取涡旋的脱落频率,并进一步使用正交模态分解对流场进行分析,给出了流场主要拟序结构及其能量与转速比的变化趋势.发现圆柱旋转改变圆柱尾流结构,使尾迹尺度变小.在旋转速度比0≤α≤2.0时,存在明显的周期性涡旋脱落,并且涡旋脱落的频率有逐渐升高的趋势;而且当转速比2.0<α≤5.0时尾迹流场的周期性减弱,涡旋脱落变得不明显,流场表现出低频、剪切层的区域特征.随着转速变大,涡旋尺度变小.在较高旋转速度比时,流场中能量被重新分布.
2016, 30(3): 98-103.
doi: 10.11729/syltlx20150107
摘要：
岩心微流动可视化是研究化学驱油微观机理的一项重要流体实验新方法,重点介绍采用低场核磁共振成像技术研究天然岩心中流体分布可视化的新进展。提出和分析了国产低场核磁共振成像岩心驱替装置面临的图像不清、材料干扰等问题,通过合理选材、优化参数,从硬件和软件2方面进行了改进与优化,消除了干扰因素。开展了天然岩心的驱替实验,采集了油水的实时 NMR信号与 MRI 成像信号,以及不同驱替阶段油水的 NMR-T2谱,得到分辨率较高的油水分布图像。结果显示残余油随着驱替PV数的增加而减少,具有初期减少明显而后趋缓的特点,并发现岩心中存在端部油残滞现象,其范围距端部4mm左右。研究了通过获得的油水分布图像计算含油饱和度的方法,其结果与传统方法一致,误差在10%以内,这也说明了油水分布图像的可靠性。这不仅为计算饱和度提供了一种新方法,而且该方法的另一个优势是可以分析任意局部位置的油水饱和度。研究结果表明,在研究岩心微流动过程中流体分布的可视化方面,核磁共振成像技术是值得深入研究的新方法。
岩心微流动可视化是研究化学驱油微观机理的一项重要流体实验新方法,重点介绍采用低场核磁共振成像技术研究天然岩心中流体分布可视化的新进展。提出和分析了国产低场核磁共振成像岩心驱替装置面临的图像不清、材料干扰等问题,通过合理选材、优化参数,从硬件和软件2方面进行了改进与优化,消除了干扰因素。开展了天然岩心的驱替实验,采集了油水的实时 NMR信号与 MRI 成像信号,以及不同驱替阶段油水的 NMR-T2谱,得到分辨率较高的油水分布图像。结果显示残余油随着驱替PV数的增加而减少,具有初期减少明显而后趋缓的特点,并发现岩心中存在端部油残滞现象,其范围距端部4mm左右。研究了通过获得的油水分布图像计算含油饱和度的方法,其结果与传统方法一致,误差在10%以内,这也说明了油水分布图像的可靠性。这不仅为计算饱和度提供了一种新方法,而且该方法的另一个优势是可以分析任意局部位置的油水饱和度。研究结果表明,在研究岩心微流动过程中流体分布的可视化方面,核磁共振成像技术是值得深入研究的新方法。
2016, 30(5): 55-60.
doi: 10.11729/syltlx20160026
摘要：
OH和CH2O平面激光诱导荧光（PLIF)同时成像技术在研究火焰结构和燃烧反应中间产物二维分布等方面能够发挥重要作用。OH的分布被用来表征火焰反应区的结构，而CH2O的分布则被用来显示火焰预热区的分布。利用OH和CH2O PLIF同时成像技术研究了甲烷/空气部分预混火焰的结构。从实验系统、光路调节、时序同步、OH A-X（1，0)扫谱、数据采集和处理等方面讨论了PLIF同时成像技术的实验方法。实验结果表明，OH和CH2O PLIF同时成像能够分别呈现甲烷/空气部分预混火焰反应区和预热区不同形状的瞬时结构；由于反应区在相邻位置的结合，在火焰中能够局部生成新的分裂的预热区。
OH和CH2O平面激光诱导荧光（PLIF)同时成像技术在研究火焰结构和燃烧反应中间产物二维分布等方面能够发挥重要作用。OH的分布被用来表征火焰反应区的结构，而CH2O的分布则被用来显示火焰预热区的分布。利用OH和CH2O PLIF同时成像技术研究了甲烷/空气部分预混火焰的结构。从实验系统、光路调节、时序同步、OH A-X（1，0)扫谱、数据采集和处理等方面讨论了PLIF同时成像技术的实验方法。实验结果表明，OH和CH2O PLIF同时成像能够分别呈现甲烷/空气部分预混火焰反应区和预热区不同形状的瞬时结构；由于反应区在相邻位置的结合，在火焰中能够局部生成新的分裂的预热区。
2017, 31(4): 8-15.
doi: 10.11729/syltlx20160207
摘要：
流体推力矢量技术不采用机械偏转，以流动控制方式实现推力转向，有望成为一种更加高效的推力矢量控制方法。目前实现流体推力矢量的主要方法有激波矢量法、双喉道方法、逆流控制方法和同向流方法等，对以上方法选择具有共性的计算与试验数据，对喷管的推力矢量效率、推力损失和流量系数进行了对比分析。结果表明激波矢量方法、双喉道方法和逆流方法能够在大落压比范围内（NPR=1.89~10）实现推力矢量控制，并且具有俯仰/偏航耦合甚至多轴控制的潜力。相比激波矢量法和逆流方法，双喉道和同向流方法在减少推力损失和提高矢量效率上占有优势，不足之处是双喉道方法对喉道进行控制限制了流量系数，而同向流方法的适用落压比范围受到严重限制。为寻求更加高效的矢量喷管技术，国内外相继发展了多种新概念流体推力矢量方法，对每种方法的控制原理、潜在优势和存在的问题挑战进行了探讨，新方法着眼于从喷流出口下游进行控制，对主流的干扰很小，值得深入研究，同时也为流体推力矢量的下一步研究方向提供了借鉴参考。
流体推力矢量技术不采用机械偏转，以流动控制方式实现推力转向，有望成为一种更加高效的推力矢量控制方法。目前实现流体推力矢量的主要方法有激波矢量法、双喉道方法、逆流控制方法和同向流方法等，对以上方法选择具有共性的计算与试验数据，对喷管的推力矢量效率、推力损失和流量系数进行了对比分析。结果表明激波矢量方法、双喉道方法和逆流方法能够在大落压比范围内（NPR=1.89~10）实现推力矢量控制，并且具有俯仰/偏航耦合甚至多轴控制的潜力。相比激波矢量法和逆流方法，双喉道和同向流方法在减少推力损失和提高矢量效率上占有优势，不足之处是双喉道方法对喉道进行控制限制了流量系数，而同向流方法的适用落压比范围受到严重限制。为寻求更加高效的矢量喷管技术，国内外相继发展了多种新概念流体推力矢量方法，对每种方法的控制原理、潜在优势和存在的问题挑战进行了探讨，新方法着眼于从喷流出口下游进行控制，对主流的干扰很小，值得深入研究，同时也为流体推力矢量的下一步研究方向提供了借鉴参考。
2018, 32(1): 64-70.
doi: 10.11729/syltlx20170099
摘要：
采用时间解析PIV（采样频率为1000Hz）在0.55m×0.4m声学风洞中测量了直径D=20mm圆柱后方7.5倍直径、圆柱两侧各3.3倍直径所围成范围内的绕流尾迹在雷诺数Re=2.74×104下的非定常流场。针对PIV获得的速度场数据，进行流场和频谱特性分析，探讨了圆柱绕流尾迹中的平均流场和脉动流场特性，以及旋涡脱落的频率特性。提出了基于速度场之间相关性的相位平均分析方法，系统分析了圆柱上下两侧旋涡交替生成、脱落、发展并耗散的完整演化过程。结果表明：在圆柱后方存在一个低速回流区，其中心0.8D的位置附近是流动结构变化最剧烈的区域；圆柱后方1.9D位置附近是上/下两侧脱落旋涡交汇、耦合的区域，湍流脉动最强；圆柱绕流尾迹中，旋涡脱落频率对应的斯特劳哈尔数稳定在0.2左右；基于速度场之间相关性的相位平均分析方法简单有效，可以准确地识别绕流尾迹中旋涡交替脱落和发展的时空演化过程，在非定常流场测量方面具有普遍推广意义。
采用时间解析PIV（采样频率为1000Hz）在0.55m×0.4m声学风洞中测量了直径D=20mm圆柱后方7.5倍直径、圆柱两侧各3.3倍直径所围成范围内的绕流尾迹在雷诺数Re=2.74×104下的非定常流场。针对PIV获得的速度场数据，进行流场和频谱特性分析，探讨了圆柱绕流尾迹中的平均流场和脉动流场特性，以及旋涡脱落的频率特性。提出了基于速度场之间相关性的相位平均分析方法，系统分析了圆柱上下两侧旋涡交替生成、脱落、发展并耗散的完整演化过程。结果表明：在圆柱后方存在一个低速回流区，其中心0.8D的位置附近是流动结构变化最剧烈的区域；圆柱后方1.9D位置附近是上/下两侧脱落旋涡交汇、耦合的区域，湍流脉动最强；圆柱绕流尾迹中，旋涡脱落频率对应的斯特劳哈尔数稳定在0.2左右；基于速度场之间相关性的相位平均分析方法简单有效，可以准确地识别绕流尾迹中旋涡交替脱落和发展的时空演化过程，在非定常流场测量方面具有普遍推广意义。
2022, 36(2): 49-73.
doi: 10.11729/syltlx20210110
Abstract:
2021, 35(4): 1-9.
doi: 10.11729/syltlx20210006
Abstract:
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