A Combined FEM-CFD Methodology to Study and Optimize Acoustic Properties of Marine Exhaust Lines

Lo sviluppo di sistemi di abbattimento compatti in grado di ridurre sia NOx che SOx è di forte interesse, per la difficoltà di combinare su una nave sia sistemi di riduzione catalitica selettiva che tecnologie di scrubber. Quindi, la ricerca sviluppata in questa tesi nasce dalla necessità di integrazione del sistema lungo la linea di scarico per risparmiare spazio e dalla necessità di disporre di un modello numerico adeguato per simulare le proprietà acustiche dei sistemi di depurazione dei gas di scarico per la loro ottimizzazione. L'obiettivo di questa tesi è sviluppare una metodologia numerica efficiente dal punto di vista computazionale che utilizzi una combinazione di simulazioni CFD e FEM, per consentire lo studio e l'ottimizzazione delle proprietà acustiche dei componenti della linea di scarico, rispettando i limiti imposti sia ai parametri geometrici che alle caratteristiche del flusso dalle reazioni chimiche necessarie per soddisfare le normative NOx e SOx. Sono stati eseguiti alcuni studi preliminari per ottimizzare l’onere computazionale delle simulazioni numeriche. Inoltre, sono state eseguite misurazioni sperimentali, sia su un set-up semplificato (tubo di impedenza) sia su un mockup di una linea di scarico di un Genset marino, al fine di valutare i risultati numerici. Le simulazioni CFD e FEM validate sono poi utilizzate per l'approccio combinato che, in primo luogo, calcola il campo di flusso (velocità e temperatura) con una simulazione CFD in regime stazionario e, poi, importa questo campo nel modello acustico FEM tramite il mesh mapping per valutare la trnsmission loss della geometria studiata in presenza di flusso. L'approccio combinato è stato quindi utilizzato per valutare e modellare le proprietà acustiche sia del catalizzatore di ossidazione diesel che dello scrubber costruiti per il Genset. La loro transmission loss raggiunge valori fino a 60 dB, permettendo di eliminare il silenziatore tradizionale, riducendo così l'ingombro della linea di scarico.The development of compact abatement systems capable of reducing both NOx and SOx is of strong interest, due to the difficulty of combining both selective catalytic reduction systems and scrubber technologies on a ship. So, the research developed in this thesis comes from the need for system integration along the exhaust line to save space and the need to have a proper numerical model to simulate the acoustic properties of exhaust gas cleaning systems for their optimization. The objective of this thesis is to develop a computationally-efficient numerical methodology employing a combination of both CFD and FEM simulations, to allow the investigation and optimization of acoustic properties of exhaust line components, while respecting the limits imposed on both geometrical parameters and flow characteristics by the chemical reactions needed to satisfy NOx and SOx regulations. Some preliminary studies are performed to optimize computational effort of numerical simulations. Moreover, experimental measurements are performed on both a simplified set-up (impedance tube) and a mockup of a marine Genset exhaust line in order to assess the numerical results. The assessed CFD and FEM simulations are used for the combined approach that, firstly, calculates the flow field (velocity and temperature) with a steady-state CFD simulation and, then, imports this field into the acoustic FEM model through mesh mapping to evaluate the transmission loss of the studied geometry in presence of flow. The combined approach is then used on real systems, to assess and model the acoustics properties of both diesel oxidation catalyst and scrubber constructed for a Genset mockup. Their transmission loss reach values up to 60 dB, which allows elimination of the traditional silencer, thus reducing the overall dimensions

Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform

Small business innovation research. Abstracts of 1988 phase 1 awards

Non-proprietary proposal abstracts of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA are presented. Projects in the fields of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robots, computer sciences, information systems, data processing, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

Flow Control Applications

Flow control has a long history with many successes across a plethora of applications. This report addresses the characteristics of the approaches that are actually used, why they are used, the many approaches that are not used, and why. Analysis indicates ways forward to increase applicability/usefulness, and efficiency of flow control research. Overall, greater and more effective progress in flow control requires utilization of far more detailed information early in the research process regarding application details and requirements

Multi-fidelity strategies for lean burn combustor design

In combustor design and development, the use of unsteady computational fluid dynamics (CFD) simulations of transient combustor aero-thermo-dynamics to provide an insight into the complex reacting flow-field is expensive in terms of computational time. A large number of such high-fidelity reactive CFD analyses of the objective and constraint functions are normally required in combustor design and optimisation process. Hence, traditional design strategies utilizing only high-fidelity CFD analyses are often ruled out, given the complexity in obtaining accurate flow predictions and limits on available computational resources and time. This necessitates a careful design of fast, reliable and efficient design strategies. Surrogate modeling design strategies, including Kriging models, are currently being used to balance the challenges of accuracy and computational resource to accelerate the combustor design process. However, its feasibility still largely relies on the total number of design variables, objective and constraint functions, as only high-fidelity CFD analyses are used to construct the surrogate model.This thesis explores these issues in combustor design by aiming to minimize the total number of high fidelity CFD runs and to accelerate the process of finding a good design earlier in the design process. Initially, various multi-fidelity design strategies employing a co-Kriging surrogate modeling approach were developed and assessed for performance and confidence against a traditional Kriging based design strategy, within a fixed computational budget. Later, a time-parallel combustor CFD simulation methodology is proposed, based on temporal domain decomposition, and further developed into a novel time-parallel co-Kriging based multi-fidelity design strategy requiring only a single CFD simulation to be setup for various fidelities. The performance and confidence assessment of the newly developed multi-fidelity strategies shows that they are, in general, competitive against the traditional Kriging based design strategy, and evidence exists of finding a good design early in the design optimisation proces

[Report of] Specialist Committee V.4: ocean, wind and wave energy utilization

The committee's mandate was :Concern for structural design of ocean energy utilization devices, such as offshore wind turbines, support structures and fixed or floating wave and tidal energy converters. Attention shall be given to the interaction between the load and the structural response and shall include due consideration of the stochastic nature of the waves, current and wind

Optimization and analysis by CFD of mixing-controlled combustion concepts in compression ignition engines

El trabajo presentado en esta Tesis está motivado por la necesidad de los motores de combustión interna alternativos de reducir el consumo de combustible y las emisiones de CO2 mientras se satisfacen las cada vez más restrictivas regulaciones de emisiones contaminantes. Por lo tanto, el objetivo principal de este estudio es optimizar un sistema de combustión de encendido por compresión controlado por mezcla para probar su potencial como motores de futura generación. Con esta meta se ha desarrollado un sistema automático que combina CFD con métodos de optimización avanzados para analizar y entender las configuraciones óptimas. Los resultados presentados en este trabajo se dividen en dos bloques principales. El primero corresponde a la optimización de un sistema de encendido por compresión convencional alimentado con diésel. El segundo se centra en un concepto de combustión avanzado donde se ha sustituido el fuel por Dimetil-eter. En ambos casos, el estudio no sólo halla una configuración óptima sino que también se describen las relaciones causa/efecto entre los parámetros más relevantes del sistema de combustión. El primer bloque aplica métodos de optimización no-evolutivos a un motor medium-duty alimentado por diésel tratando de minimizar consumo a la vez que se mantienen las emisiones contaminantes por debajo de los estándares de emisiones contaminantes impuestos. Una primera parte se centra en la optimización de la geometría de la cámara de combustión y el inyector. Seguidamente se extiende el estudio añadiendo los settings de renovación de la carga de y de inyección al estudio, ampliando el potencial de la optimización. El estudio demuestra el limitado potencial de mejora de consumo que tiene el motor de referencia al mantener los niveles de emisiones contaminantes. Esto demuestra la importancia de incluir parámetros de renovación de la carga e inyección al proceso de optimización. El segundo bloque aplica una metodología basada en algoritmos genéticos al diseño del sistema de combustión de un motor heavy-duty alimentado con Dimetileter. El estudio tiene dos objetivos, primero la optimización de un sistema de combustión convencional controlado por mezcla con el objetivo de lograr mejorar el consumo y reducir las emisiones contaminantes hasta niveles inferiores a los estándares US2010. Segundo la optimización de un sistema de combustión trabajando en condiciones estequiométricas acoplado con un catalizador de tres vías buscando reducir consumo y controlar las emisiones contaminantes por debajo de los estándares 2030. Ambas optimizaciones incluyen tanto la geometría como los parámetros más relevantes de renovación de la carga y de inyección. Los resultados presentan un sistema de combustión convencional óptimo con una notable mejora en rendimiento y un sistema de combustión estequiométrica que es capaz de ofrecer niveles de NOx menores al 1% de los niveles de referencia manteniendo niveles competitivos de rendimiento. Los resultados presentados en esta Tesis ofrecen una visión extendida de las ventajas y limitaciones de los motores MCCI y el camino a seguir para reducir las emisiones de futuros sistemas de combustión por debajo de los estándares establecidos. A su vez, este trabajo también demuestra el gran potencial que tiene el Dimetil-eter como combustible para futuras generaciones de motores.The work presented in this Thesis was motivated by the needs of internal combustion engines (ICE) to decrease fuel consumption and CO2 emissions, while fulfilling the increasingly stringent pollutant emission regulations. Then, the main objective of this study is to optimize a mixing-controlled compression ignition (MCCI) combustion system to show its potential for future generation engines. For this purpose an automatic system based on CFD coupled with different optimization methods capable of optimizing a complete combustion system with a reasonable time cost was designed together with the methodology to analyze and understand the new optimum systems. The results presented in this work can be divided in two main blocks, firstly an optimization of a conventional diesel combustion system and then an optimization of a MCCI system using an alternative fuel with improved characteristics compared to diesel. Due to the methodologies used in this Thesis, not only the optimum combustion system configurations are described, but also the cause/effect relations between the most relevant inputs and outputs are identified and analyzed. The first optimization block applies non-evolutionary optimization methods in two sequential studies to optimize a medium-duty engine, minimizing the fuel consumption while fulfilling the emission limits in terms of NOx and soot. The first study targeted four optimization parameters related to the engine hardware including piston bowl geometry, injector nozzle configuration and mean swirl number. After the analysis of the results, the second study extended to six parameters, limiting the optimization of the engine hardware to the bowl geometry, but including the key air management and injection settings. The results confirmed the limited benefits, in terms of fuel consumption, with constant NOx emission achieved when optimizing the engine hardware, while keeping air management and injection settings. Thus, including air management and injection settings in the optimization is mandatory to significantly decrease the fuel consumption while keeping the emission limits. The second optimization block applies a genetic algorithm optimization methodology to the design of the combustion system of a heavy-duty Diesel engine fueled with dimethyl ether (DME). The study has two objectives, the optimization of a conventional mixing-controlled combustion system aiming to achieve US2010 targets and the optimization of a stoichiometric mixing-controlled combustion system coupled with a three way catalyst to further control NOx emissions and achieve US2030 emission standards. These optimizations include the key combustion system related hardware, bowl geometry and injection nozzle design as input factors, together with the most relevant air management and injection settings. The target of the optimizations is to improve net indicated efficiency while keeping NOx emissions, peak pressure and pressure rise rate under their corresponding target levels. Compared to the baseline engine fueled with DME, the results of the study provide an optimum conventional combustion system with a noticeable NIE improvement and an optimum stoichiometric combustion system that offers a limited NIE improvement keeping tailpipe NOx values below 1% of the original levels. The results presented in this Thesis provide an extended view of the advantages and limitations of MCCI engines and the optimization path required to achieve future emission standards with these engines. Additionally, this work showed how DME is a promising fuel for future generation engines since it is able to achieve future emission standards while maintaining diesel-like efficiencyEl treball presentat en esta Tesi està motivat per la necessitat dels motors de combustió interna alternatius de reduir el consum de combustible i les emissions de CO2 mentres se satisfan les cada vegada mes restrictives regulacions d'emissions contaminants. Per tant, l'objectiu principal d'este estudi es optimitzar un sistema de combustió d'encesa per compressió controlat per mescla per a provar el seu potencial com a motors de futura generació. Amb esta meta s'ha desenrotllat un sistema automàtic que combina CFD amb mètodes d'optimització avançats per a analitzar i entendre les configuracions òptimes. Els resultats presentats en este treball es dividixen en dos blocs principals. El primer correspon a l'optimització d'un sistema d'encesa per compressió convencional alimentat amb dièsel. El segon se centra en un concepte de combustió avançat on s'ha substituït el fuel per Dimetil-eter. En ambdós casos, l'estudi no sols troba una configuració òptima sinó que també es descriuen les relacions causa/efecte entre els paràmetres més rellevants del sistema de combustió. El primer bloc aplica mètodes d'optimització no-evolutius a un motor mediumduty alimentat per dièsel tractant de minimitzar consum al mateix temps que es mantenen les emissions contaminants per davall dels estàndards d'emissions contaminants impostos. Una primera part se centra en l'optimització de la geometria de la cambra de combustió i l'injector. A continuació s'estén l'estudi afegint els settings de renovació de la càrrega de i d'injecció a l'estudi, ampliant el potencial de l'optimització. L'estudi demostra el limitat potencial de millora de consum que té el motor de referència al mantindre els nivells d'emissions contaminants. Açò demostra la importància d'incloure paràmetres de renovació de la càrrega i injecció al procés d'optimització. El segon bloc aplica una metodologia basada en algoritmes genètics al disseny del sistema de combustió d'un motor heavy-duty alimentat amb Dimetil-eter. L'estudi té dos objectius, primer l'optimització d'un sistema de combustió convencional controlat per mescla amb l'objectiu d'aconseguir millorar el consum i reduir les emissions contaminants fins nivells inferiors als estàndards US2010. Segon l'optimització d'un sistema de combustió treballant en condicions estequiomètriques acoblat amb un catalitzador de tres vies buscant reduir consum i controlar les emissions contaminants per davall dels estàndards 2030. Ambdós optimitzacions inclouen tant la geometria com els paràmetres més rellevants de renovació de la càrrega i d'injecció. Els resultats presenten un sistema de combustió convencional òptim amb una notable millora en rendiment i un sistema de combustió estequiomètrica que és capaç d'oferir nivells de NOx menors al 1% dels nivells de referència mantenint nivells competitius de rendiment. Els resultats presentats en esta Tesi oferixen una visió estesa dels avantatges i limitacions dels motors MCCI i el camï que s'ha de seguir per a reduir les emissions de futurs sistemes de combustió per davall dels estàndards establits. Al seu torn, este treball també demostra el gran potencial que té el Dimetil-eter com a combustible per a futures generacions de motors.Hernández López, A. (2018). Optimization and analysis by CFD of mixing-controlled combustion concepts in compression ignition engines [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/103826TESI

Improving aircraft performance using machine learning: a review

This review covers the new developments in machine learning (ML) that are impacting the multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics (experimental and numerical), aerodynamics, acoustics, combustion and structural health monitoring. We review the state of the art, gathering the advantages and challenges of ML methods across different aerospace disciplines and provide our view on future opportunities. The basic concepts and the most relevant strategies for ML are presented together with the most relevant applications in aerospace engineering, revealing that ML is improving aircraft performance and that these techniques will have a large impact in the near future