Control of Boundary Layer over NACA0015 Using Fuzzy Logic by Suction Technique

تعتبر طريقة اعادة التصاق الجزء المنفصل من الطبقة المتاخمة واحدة من اهم الطرق المستخدمة لتحسين الجريان فوق الاجسام. وقد ركزت هذه الدراسة على تصميم وبناء نظام سيطرة يعمل وفقا للمنطق الضبابي للسيطرة على أنفصال الطبقة المتاخمة من على سطح مقطع جناح طراز ((NACA0015وذلك من خلال التحكم بسرعة محرك جهاز التفريغ الذي يقوم بسحب الجزء المنفصل من الطبقة المتاخمة من خلال خمسة ثقوب موزعة على طول المحور العرضي للجناح وعلى خط يبعد مسافة (75%) من طول الوتر مقاسة من مقدمة المقطع. كل التجارب العملية تم اجرائها في نفق هوائي دون الصوتي ذي مقطع اختبار (300x300x 600) mm وعند قيم رقم ريبنولد وزوايا هجوم مختلفة. واهم النتائج التي تم الحصول عليها هي: ان استخدام نظام سيطرة يعمل وفقا للمنطق الضبابي في السيطرة على تقنية المص سوف يؤدي الى زيادة في قيمة معامل الرفع للجناح (CL) بمقدار (14.72%) عنه في الحالة الاعتيادية كذلك فان قيمة زاوية الانفصال سوف تزداد من 15o الى 17o. ايضا ان استخدام قواعد المنطق الضبابي في برمجة نظام السيطرة اعطى تحسينا مستقرا عند قيم معامل سحب CQ مقبولة.Re-attachment the separation of boundary layer using suction method is one of the important techniques, which improve the flow over bodies. This study focused on the design of fuzzy logic controller to control on the separation of the boundary layer, using suction delayed separation technique from the surface of NACA 0015 airfoil. The airfoil was designed and fabricated depending on the airfoil tool with (300x300) mm chord and span length respectively. The upper surface was developed with five holes  6mm diameter to suck the delayed boundary layer along the span of the airfoil about 75% from leading edge . Also there are four BMP180 Piezoelectric pressure sensors distributed with constant pitch on upper surface of model used to sense the pressure difference. Sub sonic wind tunnel with (300x300x 600) mm work section is used. (1.354, 1.915, 2.345, 2.708 and 3.028 x 105) Reynolds numbers and (0o, 3o, 6o, 9o, 12o, 15o, 16o and 17o) are the angles of attack were used as a conditions boundary of the experimental work. The model was tested without applying suction to determine the stall condition. Pneumatic vacuum cleaner with (0.00737 to 0.01329) discharge coefficient range was used to perform the suction experiment. Pressure difference and angle of attack were input of fuzzy logic controller which programmed by using commercial Matlab softwar. The results of applying suction showed an increase of 14.72% in the lift coefficient and increase the stall angle from 15o to more than 17o. Also lift/drag ratio increased when angle of attack increased. Fuzzy logic rules gave steady enhancement at range of suction coefficient CQ universally acceptable

Development of Fuzzy Applications for High Performance Induction Motor Drive

This chapter develops a sliding mode and fuzzy logic-based speed controller, which is named adaptive fuzzy sliding-mode controller (AFSMC) for an indirect field-oriented control (IFOC) of an induction motor (IM) drive. Essentially, the boundary layer approach is the most popular method to reduce the chattering phenomena, which leads to trade-off between control performances, and chattering elimination for uncertain nonlinear systems. For the proposed AFSMC, a fuzzy system is assigned as the reaching control part of the fuzzy sliding-mode controller so that it improves the control performances and eliminates the chattering completely despite large and small uncertainties in the system. A nonlinear adaptive law is also implemented to adjust the control gain with uncertainties of the system. The adaptive law is developed in the sense of Lyapunov stability theorem to minimize the control effort. The applied adaptive fuzzy controller acts like a saturation function in the thin boundary layer near the sliding surface to guarantee the stability of the system. The proposed AFSMC-based IM drive is implemented in real-time using digital signal processor (DSP) board TI TMS320F28335. The experimental and simulation results show the effectiveness of the proposed AFSMC-based IM drive at different operating conditions such as load disturbance, parameter variations, etc

Novel Tornado-Like Vortex Generator with Intelligent Controller

Cooking fumes may cause multiple adverse health effects, and range hoods play central roles in controlling indoor air pollution caused by cooking fumes. However, the traditional design of the range hoods has a low efficiency due to its working principle, and the efficiency decreases rapidly as the mounting height of the exhaust hood increases. This thesis is aimed at design and building a novel tornado-like vortex generator (TLVG) with an intelligent controller to enhance the efficiency of traditional range hood. Both experimental results and numerical simulation indicate that most of the cooking fumes are spreading to surrounding areas when the traditional range hood is working alone, while the cooking fumes are drawn into the tornado-like vortex and exhausted through the range hood when the novel TLVG is on. The effects of various factors on the efficiency of sucking cooking fumes are analyzed by orthogonal experiment design. The results show that the key factor affecting the performance of the TLVG is the horizontal jet angle. A higher jet velocity results in a lower negative pressure, which helps concentrate and exhaust the fume. The results also reveal that the exhaust flow velocity marginally affects the pressure around the source of cooking fumes, but the tornado-like vortex cannot be produced when the value of the exhaust flow velocity is too high. In addition, the figures of the velocity field, pressure field, and tracking particle field are plotted and analyzed. In this thesis, an intelligent controller of TLVG is designed and simulated to adapt to various types of range hoods. Adaptive-Network-based Fuzzy Inference System (ANFIS) is used in this intelligent controller, which combines the merits of both Fuzzy Inference Systems and Neural Networks. The results from the numerical simulation of the TLVG can be used to train and test the neural fuzzy system. Besides, Particle Swarm Optimization (PSO) is used for effective training in ANFIS networks. Digital simulation results demonstrate that the designed ANFIS-Swarm controller realizes a better prediction of the checking data than that from a basic ANFIS controller. This study provides information for improving the kitchen environment, and it can also be applied to different types of range hood, exhaust ventilation system, and air pollution control

Integrated Thermal Systems and Controls Modelling for AUTO Mode Simulation and Optimization

Virtual product development has become the preferred approach for vehicle A/C system development. The advantages provided by virtual modelling compared to traditional approach are accelerated development pace and reduced cost. The thesis focuses on virtual modelling of the A/C system on a SUV vehicle based on experimental data. A virtual model of the A/C system is constructed and calibrated in Simcenter Amesim. The model includes a vapour-compression refrigeration cycle and a cabin air model. The components are modelled and calibrated based on supplier data. The two thermal systems interact thermally at the evaporator level. The cabin air blower unit with a PI controller and a small DC motor is also modelled in MATLAB/Simulink. The virtual thermal model is able to simulate the cabin air temperature development during High Ambient AUTO mode drive cycle. The controlled DC motor system tracks reference speed to provide adequate air flow for the cabin. The virtual models can be used for A/C system and components performance analysis and optimization. The modelling process provides deeper understanding on thermal and control systems design

Hybrid Intelligent Optimization Methods for Engineering Problems

The purpose of optimization is to obtain the best solution under certain conditions. There are numerous optimization methods because different problems need different solution methodologies; therefore, it is difficult to construct patterns. Also mathematical modeling of a natural phenomenon is almost based on differentials. Differential equations are constructed with relative increments among the factors related to yield. Therefore, the gradients of these increments are essential to search the yield space. However, the landscape of yield is not a simple one and mostly multi-modal. Another issue is differentiability. Engineering design problems are usually nonlinear and they sometimes exhibit discontinuous derivatives for the objective and constraint functions. Due to these difficulties, non-gradient-based algorithms have become more popular in recent decades. Genetic algorithms (GA) and particle swarm optimization (PSO) algorithms are popular, non-gradient based algorithms. Both are population-based search algorithms and have multiple points for initiation. A significant difference from a gradient-based method is the nature of the search methodologies. For example, randomness is essential for the search in GA or PSO. Hence, they are also called stochastic optimization methods. These algorithms are simple, robust, and have high fidelity. However, they suffer from similar defects, such as, premature convergence, less accuracy, or large computational time. The premature convergence is sometimes inevitable due to the lack of diversity. As the generations of particles or individuals in the population evolve, they may lose their diversity and become similar to each other. To overcome this issue, we studied the diversity concept in GA and PSO algorithms. Diversity is essential for a healthy search, and mutations are the basic operators to provide the necessary variety within a population. After having a close scrutiny of the diversity concept based on qualification and quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles

Modélisation dynamique et commande optimale d'un système de réfrigération à base d'éjecteur

Recently, the ejector-based refrigeration system (ERS) has been widely used in the cooling industry as an appropriate alternative to the compressor-based cooling systems. However, the advantages of ERS such as the reliable operation and low operation and maintenance costs are overshadowed by its low efficiency and design complexity. In this context, this thesis presents the efforts to develop a control model enabling the ERS to operate in its optimal operational conditions. The extensive experimental studies of ERS revealed that at a fixed condenser inlet condition, there exists an optimal primary stream mass flow rate (generating pressure) that simultaneously maximizes the compression ratio (Cr) and exergy efficiency and minimizes the evaporating pressure. Then, the steady state models of the heat exchangers were developed and used to investigate the influence of the increase in generating pressure on the coefficient of performance (COP) of the system and it showed that increasing the generating pressure reduces the COP, linearly. In order to predict the choking regime of the ejector and explain the reasons of observed physical phenomenon, the 1D model of a fixed geometry ejector installed within an R245fa ERS was developed. The developed model demonstrated that the ejector operates in the subcritical mode when the generating pressure is below the Cr optimum point, while it operates in critical mode at or above the optimum generating pressure. Next, a dynamic model of the ERS was built to evaluate the ERS transient response to an increase in the primary stream mass flow rate. Since the ERS dynamics is mainly dominated by the thermal dynamics of the heat exchangers, the dynamic models of the heat exchangers were developed using the moving boundary approach and connected to the developed models of the ejector and steady state models of the pump and expansion valve to build a single dynamic model of the system. The built dynamic model of an ERS was used to estimate the time response of the system in the absence of accurate experimental data of the system’s dynamics. Finally, a control model was designed to drive an ERS towards its optimal operation condition. A self-optimizing, model-free control strategy known as Extremum seeking control (ESC) was adopted to minimize evaporating pressure in a fixed condenser thermal fluid inlet condition. The innovative ESC model named batch phasor ESC (BPESC) was proposed based on estimating the gradient by evaluating the phasor of the output, in batch time. The simulation results indicated that the designed BPESC model can seek and find the optimum evaporating pressure with good performance in terms of predicting the steady state optimal values and the convergence rates.Récemment, le système de réfrigération à éjecteur (SRE) a été largement utilisé dans l'industrie du refroidissement en tant que solution de remplacement appropriée aux systèmes de refroidissement à compresseur. Cependant, les avantages du SRE, tels que le fonctionnement fiable et les faibles couts d'exploitation et de maintenance, sont éclipsés par son faible rendement et sa complexité de conception. Dans ce contexte, ce projet de recherche de doctorat a détaillé les efforts déployés pour développer une stratégie de commande permettant au système de fonctionner dans ses conditions opérationnelles optimales. Les études expérimentales approfondies du SRE ont révélé que, dans une condition d'entrée de condensateur constante, il existe un débit massique optimal du flux primaire (générant une pression) qui maximise simultanément le taux de compression (Cr) et l'efficacité exergétique, et minimise la pression d’évaporation. Ensuite, les modèles à l’état d’équilibre des échangeurs de chaleur ont été développés et utilisés pour étudier l’influence de l’augmentation de la pression générée sur le coefficient de performance (COP) du système et il en ressort que l'augmentation de la pression génératrice réduit le COP de manière linéaire. Afin de prédire le régime d'étouffement de l'éjecteur et d'expliquer les raisons du phénomène physique observé, le modèle 1D d'un éjecteur à géométrie fixe installé dans un système SRE R245fa a été développé. Le modèle développé a démontré que l'éjecteur fonctionne en mode sous-critique lorsque la pression génératrice est inférieure au point optimal de Cr, alors qu'il fonctionne en mode critique à une pression égale ou supérieure à la pression génératrice optimale. Ensuite, un modèle dynamique du SRE a été développé pour étudier la réponse transitoire du SRE lors d’une augmentation du débit massique du flux primaire. Puisque la dynamique du SRE est principalement dominée par la dynamique thermique des échangeurs de chaleur, les modèles dynamiques des échangeurs de chaleur ont été développés à l'aide de l'approche des limites mobiles et connectés aux modèles développés de l'éjecteur et des modèles à l'état stationnaire de la pompe et de la vanne un seul modèle dynamique du système. En l’absence de données expérimentales précises sur la dynamique d’un système SRE, le modèle dynamique développé du SRE a été simulé numériquement pour étudier sa réponse temporelle. Enfin, une stratégie de commande extrêmale (ESC) a été élaboré pour régler automatiquement le SRE à ses conditions de fonctionnement optimales, c’est-à-dire pour trouver la vitesse de la pompe qui minimise la pression dans des conditions d'entrée de condenseur fixes. Afin de proposer une ESC implémentable en temps discret sur une installation réelle sujette à un bruit de mesure important et un traitement hors-ligne par trame, une nouvelle commande extrémale basée sur une approche par phaseur avec une procédure de traitement de signal par trame (BPESC) a été développée et simulée avec le modèle numérique. Les résultats de la simulation ont indiqué que le modèle BPESC peut trouver la vitesse optimale de la pompe avec de bonnes performances en termes de précision et de vitesse de convergence

Application of non-linear system identification approaches to modelling, analysis, and control of fluid flows.

Flow control has become a topic of great importance for several applications, ranging from commercial aircraft, to intercontinental pipes and skyscrapers. In these applications, and many more, the interaction with a fluid flow can have a significant influence on the performance of the system. In many cases the fluids encountered are turbulent and detrimental to the latter. Several attempts have been made to solve this problem. However, due to the non-linearity and infinite dimensionality of fluid flows and their governing equations, a complete understanding of turbulent behaviour and a feasible control approach has not been obtained. In this thesis, model reduction approaches that exploit non-linear system identification are applied using data obtained from numerical simulations of turbulent three-dimensional channel flow, and two-dimensional flow over the backward facing step. A multiple-input multiple-output model, consisting of 27 sub-structures, is obtained for the fluctuations of the velocity components of the channel flow. A single-input single-output model for fluctuations of the pressure coefficient, and two multiple-input single-output models for fluctuations of the velocity magnitude are obtained in flow over the BFS. A non-linear model predictive control strategy is designed using identified one- and multi-step ahead predictors, with the inclusion of integral action for robustness. The proposed control approach incorporates a non-linear model without the need for expensive non-linear optimizations. Finally, a frequency domain analysis of unmanipulated turbulent flow is perfumed using five systems. Higher order generalized frequency response functions (GFRF) are computed to study the non-linear energy transfer phenomena. A more detailed investigation is performed using the output FRF (OFRF), which can elucidate the contribution of the n-th order frequency response to the output frequency response

Simulation and feedback control of the flow past the Ahmed body

This research investigates the turbulent flow past a blunt bluff body. The square-back Ahmed body is considered a canonical bluff body, representing a simplified road vehicle. Wall resolving Large Eddy Simulations (LES) were used to investigate the dynamics of the unforced flow and accordingly inform control strategies for drag reduction. The turbulent wake behind a square-back Ahmed body in close proximity to the ground exhibits bi-modal switching. This manifests as the centre of the wake switching between one of two asymmetric positions, either horizontally or vertically. Switches occur over random timescales, with the wake recovering symmetry in the long time-average. The present work investigates numerically feedback control for suppressing horizontal (lateral) wake bi-modality of a square-back Ahmed body at Re_H ∼ 3.3 × 10^4 based on the body height. Base-mounted pressure sensors are used to estimate the position of the wake as an input signal for the controller, while actuation targets the near-wake region via synthetic jets emanating from a gap around the perimeter of the Ahmed body base. A nonlinear feedback controller based on a Langevin model of the wake dynamics is synthesised. This successfully suppresses the wake lateral bi-modal switching. However, this switching is replaced by a time-periodic streamwise motion of the large coherent structure occupying the near-wake region. Further, the controller amplifies the higher frequency dynamical wake modes. The action of feedback control also leads to base pressure recovery and a reduction in pressure drag. A trade-off between the degree of bi-modality suppression and drag reduction is observed upon varying the controller parameters. A maximum drag reduction of 7.4% is achieved for a semi-symmetrised wake, with a fully symmetrised wake achieving a 2.5% reduction. Wake bi-modality is found to be sensitive to different parameters, including the free stream turbulent intensity, the underbody flow and the dynamics of the upstream boundary layers developed along the longitudinal surfaces. Boundary layers separate and reattach close to the body’s fore-end before reaching the base. Following this recently-established link by Hesse and Morgans (2021), the second part of this research investigates the effect of suppressing boundary layer separations on wake bi-modality. Hairpin vortices, formed at the reattachment points, grow along the surfaces before breaking down upstream of the base. The resultant smaller vortices from the top and side surfaces interact as they are convected downstream, which is suggested to be a trigger of the wake bi-modal switching. Suppressing boundary layer separations interrupts this interaction, which is found to have a damping effect on the fluctuations just upstream of the base. Steady suction was applied on the longitudinal surfaces of the body to suppress boundary layer separations. The results showed that horizontal bi-modality is completely suppressed by suppressing the separation of the boundary layers on the surfaces normal to the switching direction without affecting the vertical wake position. Different configurations for suppressing boundary layer separations affect the momentum and the turbulent kinetic energy of underbody flow. The wake can fully be symmetrised by reducing the momentum of the underbody flow with a reflected vertical symmetric position. The results of these cases open doors for using feed-forward controllers with actuation significantly upstream the base separation to reduce the drag rather than forcing the wake directly, which involves some trade-offs between different dynamics in the wake.Open Acces