Multi-Objective Optimisation of A Centrifugal Compressor for a Micro Gas Turbine Operated by Concentrated Solar Power

Solar powered micro-gas turbines (MGTs) are required to work over a wide range of operating conditions due to the fluctuations in the solar insulation. This means that the compressor has to perform efficiently over a wider range than in conventional MGTs. To be able to extend the efficient operating range of a compressor at the design stage, both impeller blades and diffuser passage need to be optimised. Vaneless diffusers could offer more flexibility to extend the operating range than typical diffuser vanes. This paper presents a methodology for the design and optimisation of a centrifugal compressor for a 6 kW micro-gas turbine intended for operation using a Concentrated Solar Power (CSP) system using a parabolic dish concentrator. Preliminary design parameters were obtained from the overall system specifications and detailed cycle analysis combined with practical constraints. The compressor’s geometry optimisation has been performed using a fast and computationally efficient method, which involves the Latin hypercube Design of Experiment (DoE) technique coupled with the response surface method (RSM) in order to build a regression model through CFD simulations. Three different RSM techniques were compared with the aim to choose the most suitable technique for this specific application and then a genetic algorithm was applied. The CFD analysis for the optimised compressor showed that the high efficiency operating range has increased compared to the baseline design. Cycle analysis for the plant has been performed in order to evaluate the effect of the new compressor design on the system performance. The simulations demonstrated that the operating range of the plant was increased by over 30%

Multi-Objective Optimization of Two-Stage Centrifugal Pump using NSGA-II Algorithm

Improving the efficiency and suction capability of a multistage centrifugal pump poses a major challenge for the designer of this type of equipment. This paper deals with the optimization of a two stage centrifugal pump using Non-dominated Sorting Genetic Algorithm II (NSGA-II), coupled with three-dimensional Reynolds-averaged Navier-Stokes (3D-RANS) flow solver. The first stage comprises a suction impeller with a diffuser while the second stage is formed by a second impeller connected to a volute. Both impellers are of different dimensions and are inter-connected by a return channel. This arrangement increases the number of varying parameters and thus can add further constraints on the overall optimization process; as a result, a high computational complexity of NSGA-II and a higher computational fluid dynamics (CFD) simulation cost is incurred. In order to save running time, optimization with CFD simulations are performed on each stage separately shall enable to obtain better parameterization flexibility; therefore, permitting to adopt only three objective functions in as well as limiting other geometrical constraints. The objectives of this study are to maximize the head and hydraulic efficiency at a time where the net positive suction head inception (NPSHi) is kept to minimum. The overall efficiency as well as the head of the optimized pump were increased by 9.8% and 15.7%, respectively, at best efficiency point (BEP) (rotational speed N=2600 rpm); the NPSHi of suction impeller was reduced by 13.6%. At N=1450 rpm (BEP), an improvement of 14.9% in the head and 6.52% for the overall efficiency is observed. An important improvement in performance at different operating flow rates was obtained; this was in addition to other enhancements in the volumetric and hydraulic efficiencies. Unsteady CFD simulations were also performed to predict fluctuations in the pressure field, leakage flows and interactions between impellers and collectors. The obtained results were in agreement with experimental data. The head fluctuation of the optimized pump was also reduced by 22.5% in amplitude; this was favored by the presence of a tapered blade towards the trailing edge and the extended radial gap by 4.86% between the second impeller and cutwater, which was caused by the reduction of the impeller diameter

CFD Modelling and Simulation of Water Turbines

The design and development of water turbines requires accurate methods for performance prediction. Numerical methods and modelling are becoming increasingly important tools to achieve better designs and more efficient turbines, reducing the time required in physical model testing. This book is focused on applying numerical simulations and models for water turbines to predict tool their performance. In this Special Issue, the different contributions of this book are classified into three state-of-the-art Topics: discussing the modelling of pump-turbines, the simulation of horizontal and vertical axis turbines for hydrokinetic applications and the modelling of hydropower plants. All the contributions to this book demonstrate the importance of the modelling and simulation of water turbines for hydropower energy. This new generation of models and simulations will play a major role in the global energy transition and energy crisis, and, of course, in the mitigation of climate change

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

Metodologia de Projeto do Conjunto Rotor-Difusor de Bombas Multifásicas com Base em CFD e Técnicas de Otimização

Este trabalho apresenta uma metodologia para o projeto hidrodinâmico do estágio, Rotor-Difusor, de uma bomba multifásica hélico-axial (BMHA) operando escoamento bifásico, água-ar. O procedimento de projeto foi realizado com base em metodologias convencionais de rotores axiais, através da aplicação de um método de abordagem combinada, que usa a teoria da asa da sustentação, a condição de vórtice livre, a equação de equilíbrio radial, conceitos de escoamento bifásico e o relatório técnico 824 NACA. Posteriormente, foram utilizadas técnicas de Dinâmica dos Fluidos Computacional (CFD) para determinar as principais características de desempenho da bomba numa ampla faixa de operação. Por último, é utilizado um procedimento de otimização com o objetivo de atingir a máxima eficiência possível, através da parametrização geométrica de algumas caraterísticas do difusor. Para isso foram empregadas diferentes ferramentas, que auxiliaram num processo mais abrangente, começando com FORTRAN, onde se programou o código do projeto hidrodinâmico, que gerou as coordenadas das geometrias do Rotor-Difusor, seguido do uso de diferentes programas do pacote ANSYS (BladeGen®, TurboGrid® e CFX15®) para às análises do escoamento, finalizando com a integração de FORTRAN (com o código para geração da superfície de resposta) e ferramentas de ModeFrontier® (onde se otimizou sobre a superfície de resposta usando Algoritmos Genéticos) para o procedimento de otimização. A integração de técnicas de CFD, a construção de superfícies de resposta e Algoritmos Genéticos mostrou-se como uma ferramenta apropriada para o projeto do estágio da BMHA, pois permitiu definir eficazmente alguns parâmetros geométricos, conseguindo melhorar o desempenho da bomba multifásica e reduzindo consideravelmente o custo computacional

Orthogonal decomposition as a design tool: With application to a mixing impeller

Digital manufacturing eliminates the expense and time required to develop custom products. By utilizing this technology, designers can quickly create a customized product specifically for their performance needs. But the timescale and expense from the engineering design workflows used to develop these customized products have not been adapted from the workflows used in mass production. In many cases these customized designs build upon already successful mass-produced products that were developed using conventional engineering design workflows. Many times as part of this conventional design process significant time is spent creating and validating high fidelity models that accurately predict the performance of the final design. These existing validated high fidelity models used for the mass-produced design can be reused for analysis and design of unknown products. This thesis explores the integration of reduced order modeling and detailed analysis into the engineering design workflow developing a customized design using digital manufacturing. Specifically, detailed analysis is coupled with proper orthogonal decomposition to enable the exploration of the design space while simultaneously shaping the model representing the design. This revised workflow is examined using the design of a laboratory scale overhead mixer impeller. The case study presented here is compared with the design of the Kar Dynamic Mixer impeller developed by The Dow Chemical Company. The result of which is a customized design for a refined set of operating conditions with improved performance

Development of a Methodology for Performance Optimisation and Manufacturing Sensitivity Studies for Radial Flow Turbocharger Compressors for 21st Century Legislation

The use of algorithmic optimisation techniques whereby several designs are evaluated automatically in batches using Computational Structural Mechanics (CSM) and or Computational Fluid Dynamics (CFD) modelling to improve performance, has become an integral part of turbomachinery design process. Designing radial compressors for better performance as well as manufacturing the impeller such that there are no discrepancies between the designed surface and machined surface represents a significant challenge for the industry. Accounting for geometric variability (to model manufacturing errors) during the design/optimisation phase where hundreds of candidate geometries are evaluated is costly due to the large number of calculations required to analyse the possible combinations of manufacture errors for each new geometry design. This thesis addressed the problem by separating the design phase from the manufacture uncertainty calculations phase, focusing on a common 5-axis milling type error – undercut; and using a low cost high throughput computing cluster to meet the computational requirements of both phases. A bespoke parametric CAD algorithm was developed to automate the geometry creation during the optimisation phase. The Differential Evolution for Multi-Objective Optimisation (DEMO) algorithm was used to drive the optimisation calculations. In-house meshing software from Napier Turbochargers Ltd, subsequently referred to as Napier, was used to mesh the computational domain, which was then solved using a commercial CFD solver. The compressor in the high-pressure (HP) stage of a two-stage turbocharger was optimised, and shows significant improvements in measured parameters - up to 1.6 points of efficiency gain and 20% increase in map width, respectively. The calculations were carried out on a HTCondor cluster of 8 Linux workstations. Moreover, a study on the sensitivity of radial compressor aerodynamic performance to the presence of an undercut on the impeller surface was also carried out. In-house software from Napier was used to create an undercut on the impeller surface by modifying the CAD geometry file. The impact of the undercut on performance was quantified using detail 3D CFD analysis. Various undercut height and width levels at 13 different locations on the blade surface were analysed for three compressor designs. A unique sensitivity distribution for each compressor impeller is calculated and used to create a variable tolerance map on the impeller surface. This approach was shown to facilitate savings in cost by reducing scrap rate. In addition, a bespoke 1-D algorithm for estimating the size of a radial compressor impeller required to meet a design mass flow and pressure ratio at a given rotor speed was developed. The model can be used PhD Thesis – O. F. Okhuahesogie Page 5 as a preliminary tool when designing a new compressor (where there is no previous experimental or numerical data). The algorithm is based on a combination of fundamental turbomachinery physics equations, correlations extracted from literature and statistical modelling. Finally, an algorithm for calculating the flow area and air mass flow of the low pressure (LP) and high pressure (HP) compressors and turbines in a two-stage turbocharger required to meet a diesel engine specification was developed. The algorithm was used to validate the flow specification of a two-stage turbocharger for a test diesel engine

Development of a multi-objective optimization algorithm based on lichtenberg figures

This doctoral dissertation presents the most important concepts of multi-objective optimization and a systematic review of the most cited articles in the last years of this subject in mechanical engineering. The State of the Art shows a trend towards the use of metaheuristics and the use of a posteriori decision-making techniques to solve engineering problems. This fact increases the demand for algorithms, which compete to deliver the most accurate answers at the lowest possible computational cost. In this context, a new hybrid multi-objective metaheuristic inspired by lightning and Linchtenberg Figures is proposed. The Multi-objective Lichtenberg Algorithm (MOLA) is tested using complex test functions and explicit contrainted engineering problems and compared with other metaheuristics. MOLA outperformed the most used algorithms in the literature: NSGA-II, MOPSO, MOEA/D, MOGWO, and MOGOA. After initial validation, it was applied to two complex and impossible to be analytically evaluated problems. The first was a design case: the multi-objective optimization of CFRP isogrid tubes using the finite element method. The optimizations were made considering two methodologies: i) using a metamodel, and ii) the finite element updating. The last proved to be the best methodology, finding solutions that reduced at least 45.69% of the mass, 18.4% of the instability coefficient, 61.76% of the Tsai-Wu failure index and increased by at least 52.57% the natural frequency. In the second application, MOLA was internally modified and associated with feature selection techniques to become the Multi-objective Sensor Selection and Placement Optimization based on the Lichtenberg Algorithm (MOSSPOLA), an unprecedented Sensor Placement Optimization (SPO) algorithm that maximizes the acquired modal response and minimizes the number of sensors for any structure. Although this is a structural health monitoring principle, it has never been done before. MOSSPOLA was applied to a real helicopter’s main rotor blade using the 7 best-known metrics in SPO. Pareto fronts and sensor configurations were unprecedentedly generated and compared. Better sensor distributions were associated with higher hypervolume and the algorithm found a sensor configuration for each sensor number and metric, including one with 100% accuracy in identifying delamination considering triaxial modal displacements, minimum number of sensors, and noise for all blade sections.Esta tese de doutorado traz os conceitos mais importantes de otimização multi-objetivo e uma revisão sistemática dos artigos mais citados nos últimos anos deste tema em engenharia mecânica. O estado da arte mostra uma tendência no uso de meta-heurísticas e de técnicas de tomada de decisão a posteriori para resolver problemas de engenharia. Este fato aumenta a demanda sobre os algoritmos, que competem para entregar respostas mais precisas com o menor custo computacional possível. Nesse contexto, é proposta uma nova meta-heurística híbrida multi-objetivo inspirada em raios e Figuras de Lichtenberg. O Algoritmo de Lichtenberg Multi-objetivo (MOLA) é testado e comparado com outras metaheurísticas usando funções de teste complexas e problemas restritos e explícitos de engenharia. Ele superou os algoritmos mais utilizados na literatura: NSGA-II, MOPSO, MOEA/D, MOGWO e MOGOA. Após validação, foi aplicado em dois problemas complexos e impossíveis de serem analiticamente otimizados. O primeiro foi um caso de projeto: otimização multi-objetivo de tubos isogrid CFRP usando o método dos elementos finitos. As otimizações foram feitas considerando duas metodologias: i) usando um meta-modelo, e ii) atualização por elementos finitos. A última provou ser a melhor metodologia, encontrando soluções que reduziram pelo menos 45,69% da massa, 18,4% do coeficiente de instabilidade, 61,76% do TW e aumentaram em pelo menos 52,57% a frequência natural. Na segunda aplicação, MOLA foi modificado internamente e associado a técnicas de feature selection para se tornar o Seleção e Alocação ótima de Sensores Multi-objetivo baseado no Algoritmo de Lichtenberg (MOSSPOLA), um algoritmo inédito de Otimização de Posicionamento de Sensores (SPO) que maximiza a resposta modal adquirida e minimiza o número de sensores para qualquer estrutura. Embora isto seja um princípio de Monitoramento da Saúde Estrutural, nunca foi feito antes. O MOSSPOLA foi aplicado na pá do rotor principal de um helicóptero real usando as 7 métricas mais conhecidas em SPO. Frentes de Pareto e configurações de sensores foram ineditamente geradas e comparadas. Melhores distribuições de sensores foram associadas a um alto hipervolume e o algoritmo encontrou uma configuração de sensor para cada número de sensores e métrica, incluindo uma com 100% de precisão na identificação de delaminação considerando deslocamentos modais triaxiais, número mínimo de sensores e ruído para todas as seções da lâmina

NASA university program management information system, FY 1994

The University Program report, Fiscal Year 1994, provides current information and related statistics for 7841 grants/contracts/cooperative agreements active during the reporting period. NASA field centers and certain Headquarters program offices provide funds for those activities in universities which contribute to the mission needs of that particular NASA element. This annual report is one means of documenting the NASA-university relationship, frequently denoted, collectively, as NASA's University Program

NASA University Program Management Information System: FY 1995

The University Program Report, Fiscal Year 1995, provides current information and related statistics for grants/contracts/cooperative agreements active during the report period. NASA field centers and certain Headquarters program offices provide funds for those R&D activities in universities which contribute to the mission needs of that particular NASA element. This annual report is one means of documenting the NASA-university relationship, frequently denoted, collectively, as NASA's University Program