An Automated Optimal Design of a Fan Blade Using an Integrated CFD/MDO Computer Environment

The objective of the investigation is the development of more efficient design methodologies based on the applications of established design tools including Computational Fluid Dynamics (CFD) and non-linear Multidisciplinary Design Optimization (MDO) algorithms. Well known evolutionary type optimization algorithms include the Particle Swarm Optimization (PSO), Response Surface Optimization (RSO) and Genetic (GA) Algorithms. The benchmark case study is the optimal design of a low speed fan for an industrial air-conditioning application using the Response Surface Optimization (RSO) algorithm. The optimization algorithm controls the variations of parameters that describe the three-dimensional geometry of the blade while applying performance and geometrical constraints on blade shapes that are investigated. The optimal design is defined as the blade geometry which produces the maximum total efficiency subject to specified constraints on the volume flow rate (CFM) and rotational rate (RPM) of the fan

Numerical optimization for radiated noises of centrifugal pumps in the near-field and far-field based on a novel MLGA-PSO algorithm

As the flow structure in the centrifugal pump is complicated, it always causes serious noises, which has become an important problem in environmental protections. Some works have been completed for optimizing and reducing radiated noises of centrifugal pumps, but optimized algorithms are traditional and easily fall into local extreme values, so that final results are not always the optimal. For overcoming disadvantages of traditional algorithms, this paper proposed a novel MLGA-PSO (Multi-layer Genetic Algorithm-Particle Swarm Optimization) algorithm to make an optimization for noises and hydraulic performance of centrifugal pumps. This algorithm starts from the organizational structure of individuals and separates the global search from the local search, which can not only accelerate the convergence speed, but also avoid reducing the global search ability. The algorithm could effectively overcome the contradiction between global search ability and convergence speed. Inlet diameter, impeller blade outlet width, blade outlet angle and amount of blades are as designed variables. In order to verify advantages of the proposed MLGA-PSO algorithm in global search ability, optimizing speed and stability, GA (Genetic Algorithm), PSO (Particle Swarm Optimization) and GA-PSO (Genetic Algorithm-Particle Swarm Optimization) algorithms are chosen to carry out the compared experiment. Results show that the proposed MLGA-PSO algorithm has higher efficiency and accuracy. Finally, total noises of the optimized noise in the near-field and far-field using MLGA-PSO algorithm are 181 dB and 74 dB, respectively. Total noises in the near-field are reduced by 4.7 %, while those in the far-field are reduced by 16.9 %. It is clearly that the optimized centrifugal pump presents an obvious noise reduction effect

Multi-disciplinary performance studies on propulsion system integration for military aircraft.

Military aircraft propulsion systems represent one of the most challenging sectors of jet engine design: Operating at an extremely variable environment strongly influenced by aircraft aerodynamics, these engines should pack high thrust output at the minimum possible size without compromising reliability and operating cost. In addition, the multidisciplinary nature of military aircraft operations frequently introduces contradicting performance objectives which are hard to incorporate to engine design. All the above are combined with the very high cost of engine development, necessitating proper selections early in the design phase to ensure the success of the development process and the viability of new engine concepts. Despite the significant volume of research in the field and perhaps due to the sensitivity of the data involved, studies published to date are focused on rather specific topics without addressing the full multidisciplinary aircraft-propulsion system integration problem. In order to achieve this, a new synthesis of methods needs to be established combining aspects and contributions from different areas of research. This project investigates the development of a new methodology for interconnecting engine preliminary design to aircraft operational requirements. Under this scope, a representation of a generic military airframe is constructed and combined with engine performance models and simulation tools to investigate propulsion system effects on aircraft mission performance and survivability. More specifically, the project’s contributions in the field of military aircraft propulsion system integration are focused on three domains: • A new military aircraft representation modelling critical aspects of the interaction between the aircraft and the propulsion system: Aircraft aerodynamics, airframe/propulsion system aerodynamic interference, IR and noise signature. The model has low computational requirements and is suitable for use in the context of large-scale parametric studies and trajectory optimization cases. • New simulation-based techniques for estimating climb performance and assessing the mission capabilities of aircraft/engine configurations in realistic mission scenarios. Points of novelty within the developed methods include a multi-objective formulation to the climb trajectory problem, a technique for Altitude-Mach tracking, an expansion of the Energy-Manoeuvrability (E-M) technique allowing for the concurrent optimization of the aircraft trajectory and engine schedule and the introduction of minimum noise and IR trajectories for military aircraft. • The quantification of propulsion system effects on aircraft survivability, taking into account both the aircraft’s IR signature and aircraft/missile kinematic performance. This is achieved through a combination of an aircraft IR model with kinematic simulations of missile-vs-aircraft and aircraft-vs-aircraft which are used to measure an aircraft’s susceptibility to attacks, along with its own ability to attack manoeuvring targets. The above methods are developed and validated using published data and applied to investigate aircraft performance trends in a series of test cases where the effectiveness of different propulsion system designs is evaluated in a variety of simulated mission tasks. The results successfully demonstrate the developed methods’ ability to quantify the relation between aircraft performance and engine design, providing a basis for understanding the performance trade-offs that result from the adoption of different propulsion system configurations, to maximize the efficiency of the powerplant design process.PhD in Aerospac

Micro/Nano Manufacturing

Micro manufacturing involves dealing with the fabrication of structures in the size range of 0.1 to 1000 µm. The scope of nano manufacturing extends the size range of manufactured features to even smaller length scales—below 100 nm. A strict borderline between micro and nano manufacturing can hardly be drawn, such that both domains are treated as complementary and mutually beneficial within a closely interconnected scientific community. Both micro and nano manufacturing can be considered as important enablers for high-end products. This Special Issue of Applied Sciences is dedicated to recent advances in research and development within the field of micro and nano manufacturing. The included papers report recent findings and advances in manufacturing technologies for producing products with micro and nano scale features and structures as well as applications underpinned by the advances in these technologies

CFD Modeling of Complex Chemical Processes: Multiscale and Multiphysics Challenges

Computational fluid dynamics (CFD), which uses numerical analysis to predict and model complex flow behaviors and transport processes, has become a mainstream tool in engineering process research and development. Complex chemical processes often involve coupling between dynamics at vastly different length and time scales, as well as coupling of different physical models. The multiscale and multiphysics nature of those problems calls for delicate modeling approaches. This book showcases recent contributions in this field, from the development of modeling methodology to its application in supporting the design, development, and optimization of engineering processes

Biomechanics and Remodelling for Design and Optimisation in Oral Prosthesis and Therapeutical Procedure

The purpose of dental prostheses is to restore the oral function for edentulous patients. Introducing any dental prosthesis into mouth will alter biomechanical status of the oral environment, consequently inducing bone remodelling. Despite the advantageous benefits brought by dental prostheses, the attendant clinical complications and challenges, such as pain, discomfort, tooth root resorption, and residual ridge reduction, remain to be addressed. This thesis aims to explore several different dental prostheses by understanding the biomechanics associated with the potential tissue responses and adaptation, and thereby applying the new knowledge gained from these studies to dental prosthetic design and optimisation. Within its biomechanics focus, this thesis is presented in three major clinical areas, namely prosthodontics, orthodontics and dental implantology. In prosthodontics, the oral mucosa plays a critical role in distributing occlusal forces a denture to the underlying bony structure, and its response is found in a complex, dynamic and nonlinear manner. It is discovered that interstitial fluid pressure in mocosa is the most important indicator to the potential resorption induced by prosthetic denture insertion, and based on this finding, patient-specific analysis is performed to investigate the effects caused by various types of dentures and prediction of the bone remodelling activities. In orthodontic treatments, a dynamic algorithm is developed to analyse and predict potential bone remodelling around the target tooth during orthodontic treatment, thereby providing a numerical approach for treatment planning. In dental implantology, a graded surface morphology of an implant is designed to improve osseointegration over that of a smooth uniform surface in both the short and long term. The graded surface can be optimised to achieve the best possible balance between the bone-implant contact and the peak Tresca stress for the specific clinical application need

Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)

Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016.The PhD Symposium was a very good opportunity for the young researchers to share information and knowledge, to present their current research, and to discuss topics with other students in order to look for synergies and common research topics. The idea was very successful and the assessment made by the PhD Student was very good. It also helped to achieve one of the major goals of the NESUS Action: to establish an open European research network targeting sustainable solutions for ultrascale computing aiming at cross fertilization among HPC, large scale distributed systems, and big data management, training, contributing to glue disparate researchers working across different areas and provide a meeting ground for researchers in these separate areas to exchange ideas, to identify synergies, and to pursue common activities in research topics such as sustainable software solutions (applications and system software stack), data management, energy efficiency, and resilience.European Cooperation in Science and Technology. COS

Path planning in time dependent flows using level set methods

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 167-177).Autonomous underwater vehicles such as gliders have emerged as valuable scientific platforms due to their increasing uses in several oceanic applications, ranging from security, acoustic surveillance and military reconnaissance to collection of ocean data at specific locations for ocean prediction, monitoring and dynamics investigation. Gliders exhibit high levels of autonomy and are ideal for long range missions. As these gliders become more reliable and affordable, multi-vehicle coordination and sampling missions are expected to become very common in the near future. This endurance of gliders however, comes at an expense of being susceptible to typical coastal ocean currents. Due to the physical limitations of underwater vehicles and the highly dynamic nature of the coastal ocean, path planning to generate safe and fast vehicle trajectories becomes crucial for their successful operation. As a result, our motivation in this thesis is to develop a computationally efficient and rigorous methodology that can predict the time-optimal paths of underwater vehicles navigating in continuous, strong and dynamic ow-fields. The goal is to predict a sequence of steering directions so that vehicles can best utilize or avoid ow currents to minimize their travel time. In this thesis, we fist review existing path planning methods and discuss their advantages and drawbacks. Then, we discuss the theory of level set methods and their utility in solving front tracking problems. Then, we present a rigorous (partial differential equation based) methodology based on the level set method, which can compute time-optimal paths of swarms of underwater vehicles, obviating the need for any heuristic control based approaches. We state and prove a theorem, along with several corollaries, that forms the foundation of our approach for path planning. We show that our algorithm is computationally efficient - the computational cost grows linearly with the number of vehicles and geometrically with spatial directions. We illustrate the working and capabilities of our path planning algorithm by means of a number of applications. First, we validate our approach through simple benchmark applications, and later apply our methodology to more complex, realistic and numerically simulated ow-fields, which include eddies, jets, obstacles and forbidden regions. Finally, we extend our methodology to solve problems of coordinated motion of multiple vehicles in strong dynamic ow-fields. Here, coordination refers to maintenance of specific geometric patterns by the vehicles. The level-set based control scheme that we derive is shown to provide substantial advantages to a local control approach. Specifically, the illustrations show that the resulting coordinated vehicle motions can maintain specific patterns in dynamic flow fields with strong and complex spatial gradients.by Sri Venkata Tapovan Lolla.S.M