Efficiency of bio- and socio-inspired optimization algorithms for axial turbomachinery design

Turbomachinery design is a complex problem which requires a lot of experience. The procedure may be speed up by the development of new numerical tools and optimization techniques. The latter rely on the parameterization of the geometry, a model to assess the performance of a given geometry and the definition of an objective functions and constraints to compare solutions. In order to improve the reference machine performance, two formulations including the off-design have been developed. The first one is the maximization of the total nominal efficiency. The second one consists to maximize the operation area under the efficiency curve. In this paper five optimization methods have been assessed for axial pump design: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Cuckoo Search (CS), Teaching Learning Based Optimization (TLBO) and Sequential Linear Programming (SLP). Four non-intrusive methods and the latter intrusive. Given an identical design point and set of constraints, each method proposed an optimized geometry. Their computing time, the optimized geometry and its performances (flow rate, head (H), efficiency (η), net pressure suction head (NPSH) and power) are compared. Although all methods would converge to similar results and geometry, it is not the case when increasing the range and number of constraints. The discrepancy in geometries and the variety of results are presented and discussed. The computational fluid dynamics (CFD) is used to validate the reference and optimized machines performances in two main formulations. The most adapted approach is compared with some existing approaches in literature

Coupling of inverse method and cuckoo search algorithm for multiobjective optimization design of an axial flow pump

This work describes the application of a multiobjective cuckoo search method for turbomachinery design optimization of an axial pump. Maximization of the total efficiency and minimization of the required net positive suction head of the pump are the two objective functions considered for the optimization problem. The optimization process is carried out on a range of imposed volumetric flow rates, with taking into account at each discretized radius between the hub and tip of the rotor: the profile camber, rotor wall thickness, angular deviation, and the solidity, regarded as geometrical constraints and nominal flow rate as mechanical constraint. Two strategies are proposed in order to solve the problem. In the first one, three forms of mono-objective model with two variables, total efficiency and net positive suction head, are considered. In the second one, a multiobjective model with nondominated sorting scheme is adopted. A comparative evaluation of results obtained from the proposed approach with those of a reference machine and genetic algorithm allowed us to validate the present work

Genetic optimization of turbomachinery components using the volute of a transonic centrifugal compressor as a case study

One elementary part of a centrifugal compressor is the volute, which is located downstream the impeller. Its purpose is to collect the flow and increase the static pressure by converting kinetic energy into potential energy. Despite its significant effect onto the design point and operating range of the compressor, the number of publications regarding this component is quite small. Therefore, a numerical optimization of the volute housing is performed in order to identify important geometric parameters and find an optimal volute geometry. For this purpose, a new density-based CFD solver for all Mach numbers is developed as well as an automated geometry generation tool for the volute housing. The results show, that a volute with an inlet eccentricity of 0.9 and a slightly lower radial volute channel offers the best compressor efficiency. Moreover, the actual cross-sectional shape of the volute has only a minor influence onto the performance. As a result, the isentropic efficiency could be improved by up to 2 % compared to the reference compressor model, in particular at high off-design flow rates. These results are a novelty in the scientific community and help to design more efficient compressors.Das Spiralgehäuse eines Radialverdichters wird im Gegensatz zum Laufrad kaum in wissenschaftlichen Arbeiten untersucht. Um wichtige Geometrieparameter und Einflussfaktoren dieses Bauteils zu identifizieren, wird daher eine Optimierung mittels genetischer Algorithmen durchgeführt. Dazu wird zunächst ein dichte-basierter CFD-Löser entwickelt und validiert, um die komplexe Strömung in einem Radialverdichter mit hoher Genauigkeit simulieren zu können. Darauf aufbauend wird das Spiralgehäuse parametrisiert und ein Programm entwickelt, welches die komplexe Geometrie automatisiert erstellt. Durch die neuartige Kombination von numerischer Optimierung, automatisierter Geometrieerstellung und CFD-Simulation des Spiralgehäuses können erstmals Aussagen zur optimalen Geometrie sowie über Verlusteffekte für eine Vielzahl an Geomtrievarianten getroffen werden. Mit Hilfe dieses Wissens können sparsamere und effizientere Radialkompressoren für viele Bereiche des Maschinenbaus entwickelt werden

Air Force Institute of Technology Research Report 2019

This Research Report presents the FY19 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Daftar Ebook Engineering Science Terbitan Springer Tahun 2018

Artikel ini memuat daftar judul ebook bidang ilmu teknik yang diterbitkan oleh Springer pada tahun 2018 yang dimiliki oleh Unand

Air Force Institute of Technology Research Report 2020

This Research Report presents the FY20 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

ECOS 2012

The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology