Dissertations / Theses: 'Roughness optimization'

1

Vandadi, Aref. "Optimization of Superhydrophobic Surfaces to Maintain Continuous Dropwise Condensation." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc500016/.

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In the past decade, the condensation on superhydrophobic surfaces has been investigated abundantly to achieve dropwise condensation. There is not a specific approach in choosing the size of the roughness of the superhydrophobic surfaces and it was mostly selected arbitrarily to investigate the behavior of condensates on these surfaces. In this research, we are optimizing the size of the roughness of the superhydrophobic surface in order to achieve dropwise condensation. By minimizing the resistances toward the transition of the tails of droplets from the cavities of the roughness to the top of the roughness, the size of the roughness is optimized. It is shown that by decreasing the size of the roughness of the superhydrophobic surface, the resistances toward the transition of the tails of droplets from Wenzel state to Cassie state decrease and consequently dropwise condensation becomes more likely.

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2

Hu, Chen. "Surface Optimization of the Silicon Templates for Monolithic Photonics Integration." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-37226.

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Silicon photonics is emerging as a potential field to achieve optical interconnects towards the realization of ultra high bandwidth. The indirect band-gap property of silicon still remains as a big challenge to incorporate silicon photonic active device, for example, silicon-based laser. In the Laboratory of Semiconductor Materials at KTH, a monolithic integration platform based on nano-epitaxial lateral overgrowth (nano-ELOG) technique has been proposed to integrate III-V semiconductor materials with silicon for light source application. The integration process involves uneven surface morphology at different stages. The surfaces of the indium phosphide seed layer on silicon used for ELOG, the mask deposited on it (the silicon/silicon dioxide waveguide) and the ELOG indium phosphide layer grown on it prior to laser growth are often rough. In this thesis work, we have optimized chemical mechanical polishing (CMP) technique in order to achieve an even surface. The same procedure is also necessary to reach the optimal thickness of different layers to enable effective coupling of light from the laser source into the waveguide. CMP of indium phosphide to obtain an average surface roughness of < 1 nm has been optimized by a two-step polishing using different slurries; it results in a step height of ca 3 nm. Similarly the surface of silicon/silicon dioxide “waveguide” has also been optimized with the roughness of ~ 0.5 nm. In the latter case, a step height of 40 nm is retained and this increase with respect to InP is identified to be mainly due to limitations of the polishing machine which is different from that used for indium phosphide. The reduction in step heights with polishing time is analyzed and compared with an existing theoretical model. Our results are in good qualitative agreement with the model. The optimized surface morphology obtained in this work was tested for its suitability for integration. For this evaluation, InP was grown by ELOG in a hydride vapour phase epitaxy reactor with and without CMP of the involved surfaces. The surface after CMP yields layers of better surface morphology with fewer defects as revealed by atomic force microscopy, surface profilometer and cathodoluminescence analysis. The results indicate that the CMP process is useful for monolithic integration for silicon photonics.

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O'Hanley, Harrison Fagan. "Separate effects of surface roughness, wettability and porosity on boiling heat transfer and critical heat flux and optimization of boiling surfaces." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/78208.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering; and, (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 157-161).
The separate effects of surface wettability, porosity, and roughness on critical heat flux (CHF) and heat transfer coefficient (HTC) were examined using carefully-engineered surfaces. All test surfaces were prepared on nanosmooth indium tin oxide - sapphire heaters and tested in a pool boiling facility in MIT's Reactor Thermal Hydraulics Laboratory. Roughness was controlled through fabrication of micro-posts of diameter 20[mu]m and height 15[mu]m; intrinsic wettability was controlled through deposition of thin compact coatings made of hydrophilic SiO₂ (typically, 20nm thick) and hydrophobic fluorosilane (monolayer thickness); porosity and pore size were controlled through deposition of layer-by-layer coatings made of SiO₂ nanoparticles. The ranges explored were: 0 - 15[mu] for roughness (Rz), 0 - 135 degrees for intrinsic wettability, and 0 - 50% and 50nm for porosity and pore size, respectively. During testing, the active heaters were imaged with an infrared camera to map the surface temperature profile and locate distinct nucleation sites. It was determined that wettability can play a large role on a porous surface, but has a limited effect on a smooth non-porous surface. Porosity had very pronounced effects on CHF. When coupled with hydrophilicity, a porous structure enhanced CHF by approximately 50% - 60%. However, when combined with a hydrophobic surface, porosity resulted in a reduction of CHF by 97% with respect to the reference surface. Surface roughness did not have an appreciable effect, regardless of the other surface parameters present. Hydrophilic porous surfaces realized a slight HTC enhancement, while the HTC of hydrophobic porous surfaces was greatly reduced. Roughness had little effect on HTC. A second investigation used spot patterning aimed at creating a surface with optimal characteristics for both CHF and HTC. Hydrophobic spots (meant to be preferential nucleation sites) were patterned on a porous hydrophilic surface. The spots indeed were activated as nucleation sites, as recognized via the IR signal. However, CHF and HTC were not enhanced by the spots. In some instances, CHF was actually decreased by the spots, when compared to a homogenous porous hydrophilic surface.
by Harrison Fagan O'Hanley.
S.B.
S.M.

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Sällberg, Gustav, and Pontus Söderbäck. "Thesis - Optimizing Smooth Local Volatility Surfaces with Power Utility Functions." Thesis, Linköpings universitet, Produktionsekonomi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-120090.

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The master thesis is focused on how a local volatility surfaces can be extracted by optimization with respectto smoothness and price error. The pricing is based on utility based pricing, and developed to be set in arisk neutral pricing setting. The pricing is done in a discrete multinomial recombining tree, where the timeand price increments optionally can be equidistant. An interpolation algorithm is used if the option that shallbe priced is not matched in the tree discretization. Power utility functions are utilized, where the log-utilitypreference is especially studied, which coincides with the (Kelly) portfolio that systematically outperforms anyother portfolio. A fine resolution of the discretization is generally a property that is sought after, thus a seriesof derivations for the implementation are done to restrict the computational encumbrance and thus allow finer discretization. The thesis is mainly focused on the derivation of the method rather than finding optimal parameters thatgenerate the local volatility surfaces. The method has shown that smooth surfaces can be extracted, whichconsider market prices. However, due to lacking available interest and dividend data, the pricing error increasessymmetrically for longer option maturities. However, the method shows exponential convergence and robustnessto different initial (flat) volatilities for the optimization initiation. Given an optimal smooth local volatility surface, an arbitrary payoff function can then be used to price thecorresponding option, which could be path-dependent, such as barrier options. However, only vanilla optionswill be considered in this thesis. Finally, we find that the developed

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5

Lapushkina, Elizaveta. "Anti-corrosion coatings fabricated by cold spray technique : Optimization of spray condition and relationship between microstructure and performance." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEI054.

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Des revêtements anticorrosion de zinc et d'aluminium ont été développés respectivement par des techniques de pulvérisation à froid à haute pression et à basse pression. Pour les revêtements de zinc, la dépendance de la température de pulvérisation sur l'épaisseur a été analysée et la température critique de dépôt a été trouvée à 230°C. Des variations de pression de 2 MPa, 2,5 MPa et 3 MPa à température constante 290 °C ont montré la valeur d'épaisseur de couche plus élevée à 2 MPa. Il a été également confirmé que l'épaisseur du revêtement à tendance à diminuer avec la pression. Le taux d'alimentation en poudre ainsi que la distance de pulvérisation ont également été considérés comme des paramètres influençant l'épaisseur. Les conditions optimales de projection ont été trouvées pour 3 rps et 30 mm, respectivement. Enfin, la température et la pression du gaz ont été optimisées par le plan d’experience dit de Doehlert. Leurs influences sur la qualité du revêtement de zinc ont été discutées en termes de microstructure, de porosité, d'épaisseur et de résistance à la corrosion. Une porosité maximale de 4,2% a été atteinte avec la pression la plus élevée et avec une température modérée (260 ° C < T < 300 ° C). Ces conditions favorisait l'érosion du substrat et la faible déformation des particules lors de l'impact. Deux conditions optimales ont ainsi été trouvées: 320 ° C – 2,5 MPa et 260 ° C – 2,5 MPa. Des expériences électrochimiques macroscopiques et locales ont été ensuite réalisées. Une résistance à la corrosion plus élevée a été détectée pour la condition 320 ° C – 2,5 MPa. Les revêtements étaient alors suffisamment épais pour protéger le substrat et le mécanisme de corrosion était liée au comportement des couches d'hydroxyde et d'oxyde de Zn. Il est a noter que la rugosité du revêtement devra être pour réduire l'amorçage de la corrosion. Pour les revêtements d'aluminium, les paramètres de déposition optimaux ont été trouvés à 400 ° C / 0,65 MPa. Des particules de céramique ont été ajoutées pour densifier le revêtement permettant une réduction de porosité de 8% à 6,4%. Un traitement de surface par laser a été ensuite effectué. Dans ce travail, la puissance du laser s’est révelée insuffisante pour atteindre le point de fusion de l’aluminium, cependant, la dureté des revêtement a pu être modifée. Les résultats ont montré une augmentation de la microdureté des revêtements de 5% avec l'ajout de particules céramiques tandis qu’une réduction de dureté de 39% et 35% a été mesurée sur le revêtement en aluminium pur et composite respecitvement. La diminution de dureté lors le traitement au laser a été attribuée au recuit de surface, à la libération de contraintes internes et à une possible recristallisation locale. Enfin, les caractérisations électrochimiques ont montré une résistance à la corrosion plus élevée pour les revêtements composites céramiques que l'aluminium pur et les revêtements traités au laser
Anticorrosion coatings of Zinc and Aluminium were developed by high pressure and low-pressure Cold Spray techniques, respectively. For Zinc coatings, the dependence of spraying temperature on thickness has been analyzed and the critical temperature of deposition was found at 230 oC. For lower temperatures, the coating was considerably thinner. Dependence of thickness on pressure variation 2 MPa, 2,5 MPa and 3 MPa at constant temperature 290 oC has shown the highest thickness value at 2 MPa. It was confirmed that the coating thickness tends to decrease with the pressure rise. The powder feeding rate as well as the spraying distance were also considered to influence the thickness. The optimal conditions were found for 3ps and 30 mm, respectively. Finally, the gas temperature and pressure were optimized by a Doehlert uniform shell design. Their influences on the zinc coating quality were discussed in terms of microstructure, porosity, thickness, and corrosion resistance. A maximum porosity of 4.2% was reached with the highest pressure and with a moderate temperature (260 °C < T < 300 °C). These conditions promoted erosion of the substrate and a lower accommodation of particles at the impact. Thicker coatings were obtained at higher temperatures because of better particle straining. Two optimal conditions were then identified: 320 °C–2.5 MPa and 260 °C–2.5 MPa. Macroscopic and local electrochemical experiments were performed. Higher corrosion resistance was detected for the condition 320 °C–2.5 MPa. Coatings were enough thick to protect the substrate and the corrosion mechanism was driven by the classical Zn hydroxide and oxide layers. Note that the coating roughness may be optimized later to reduce the corrosion initiation. For aluminum coatings deposited by a low-pressure cold spray method, the optimal spraying parameters according to deposition efficiency were found at 400 °C /0.65 MPa. Ceramic particles were added to densify the coating and allowed to reduce porosity from 8% to 6.4%. Instead of ceramic particle addition, laser surface treatment was performed after coating design. Laser power was not enough high to reach the surface melting, however, the coating microhardness was modified. Results showed a microhardness increase of coatings of 5% with the addition of hard particles whereas the microhardness decreased after the post-heat treatment (pure aluminum coating reduction of 39% and for composite coating 35%). The hardness reduction during the laser treatment was attributed to surface annealing and the release of internal stresses and possible recrystallization with the subsequent grain growth. Finally, the results of the electrochemical investigations showed higher corrosion resistance of ceramic composite coatings than both pure aluminum and laser-treated coatings

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6

Masiagutova, Elina. "Étude de la génération des topographies de surfaces latérales issues du procédé LPBF pour un alliage d’aluminium AlSi10Mg." Thesis, Lyon, 2022. http://www.theses.fr/2022LYSEE002.

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Dans le cadre de ce travail, la génération des surfaces produites par le procédé de fusion laser sur lit de poudre LPBF a été étudiée. Le LPBF est un procédé de fabrication additive qui peut conduire à de nouvelles opportunités (fabrication de structures complexes avec canaux internes, structures lattices). Ce procédé attire donc une attention considérable en particulier dans l'industrie aéronautique. Une étude de l’influence des paramètres primaires du procédé LPBF sur la génération des surfaces a été réalisée. Au cours de cette étude, la relation entre la rugosité des surfaces supérieures et latérales et la densité du matériau a été établie. Cela a permis de déterminer la première fenêtre de paramètres optimaux.Une analyse de la dispersion de la rugosité et la reproductibilité du procédé ont ensuite été réalisées. Cette analyse a révélé une importante dispersion de la rugosité, notamment d'une face à l'autre. En conséquence, des recommandations sur les mesures de surface ont été proposées.L'effet de différents paramètres secondaires est également étudié afin de mieux comprendre la génération de la surface latérale et de l'optimiser. Cette étude a montré que les compensations et les réglages de contour sont des paramètres clés qui peuvent contribuent à la réduction de la rugosité des surfaces latérales. Sur la base des résultats de ces études, la rugosité a pu être diminuée d’un Sa de 40 µm à un Sa de 10 μm.Enfin, cette thèse présente une nouvelle approche de modélisation de génération des topographies des surfaces latérales. L’approche est basée sur la géométrie du cordon (rayons de courbure). Elle permet de prendre en compte la position des cordons et des couches et prédit la rugosité pour différentes stratégies de lasage et paramètres de compensation
In the current study, surface generation during additive manufacturing (AM), especially the laser powder bed fusion (LPBF) process was studied. LPBF is a progressive process that can lead to new opportunities, such as applications that require complex structures (internal channels or lightweight lattice structures). It has therefore attracted considerable attention, which has led to research and development in many industries, particularly in the aerospace industry.A surface generation study to optimize surface roughness and material density by examining the influence of the primary LPBF process parameters was therefore performed. During this study, the relationship between the roughness of the top and side surfaces and the density of the material was established. This made it possible to determine the first window of optimal parameters.An analysis of the roughness dispersion and process reproducibility were then carried out. This analysis revealed a significant roughness dispersion, especially from one side to the other. As a result, recommendations on surface measurements have been proposed.The effect of different process options (secondary parameters) are also studied in order to better understand the generation of the side surface and optimize it. This study showed that compensations and contour settings are key parameters that can help reduce the side surface roughness. Indeed, the geometric positioning of the different weld tracks is an important issue that must be addressed to reduce surface roughness. Based on the results of this study, it is possible to reduce the average surface roughness Sa from 40 to 10 μm.Finally, this thesis presents a new approach to modeling side surfaces roughness (at 0°). The approach is based on the weld track geometry (radii of curvature). It allows to take into account the weld tracks and layers position in relation to each other and thus to predict the roughness for different scanning strategies, compensation parameters

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7

Jeng, Jiun-Fu, and 鄭竣夫. "Optimization of ceramic grinding the surface roughness." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/95664049138441506559.

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碩士
建國科技大學
機械工程系暨製造科技研究所
102
This study is based on diamond grinding rods on the degree of purity of 99.7% alumina (Al_2 O_3) ceramic processing, and with response surface method to find the optimal parameters. Grinding of the surface roughness experiment: Selected the spindle speed、feed rate、cutting depth of three experimental factors, know shaft speed is 13121rpm、feed rate is 33 mm / min、cut depth is 0.020mm can obtained the minimum reaction value(arithmetical mean deviation) 0.359μm, actual milling compared with simulation, the error value is 7.43%.

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8

CHAO, CHIH-CHIEH, and 趙致傑. "Roughness Optimization of CO2 Laser Removing Rust and Modal Analysis." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/5p6x5d.

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碩士
國立聯合大學
機械工程學系碩士班
105
This study aims to investigate the roughness of carbon steel through CO2 laser removing. In order to reduce experimental cost and time, using the Taguchi method to optimize the parameters and also using the signal-to-noise with analysis of variance to find the important factors and the best combination of parameters which affect the surface roughness. The control factors are: (A) laser power, (B) processing speed, (C) focal distance, and (D) carving step. Each control factors has three levels. The results show that the optimal combination of laser removing is (A3B1C2D1). The control factors affect the processing quality are A>D>C>B. Furthermore, this study also discusses the vibration of carbon dioxide laser machine by the finite element analysis (FEA) and also using the laser vibration meters to measure the vibration when using the CO2 laser machine. The results show that the practical measurements aren’t the same with the theoretical values. Therefore, it doesn’t cause the resonance when using the CO2 laser machine.

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9

Chen, Cheng-Yang, and 陳正陽. "Optimization Study of Ultrasonic Horn to Ceramic Plates Surface Roughness." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/87920412992573268657.

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碩士
國立中興大學
精密工程學系所
101
This thesis aims to explore the ultrasonic horn processing parameters effect on the hole wall surface roughness of ceramic plates. The finite element analysis (FEA) method was used to simulate natural frequencies of various plates and horns. Experimental parameters including feed rate, feed flute, ultrasonic power were tested for the optimal result. The surface roughness of hole wall surface was measured by a laser displacement instrument. Stainless steel horn with natural frequency in axial vibration mode was 21.4 KHz from the FEA simulation. The experimental measurement showed that the stainless steel horn is 21.913 KHz. There is only 2.3% difference between the simulation and experiment. The experiment used the horn diameter ψ1000 μm to drill hole and examined the optimal parameter for wall surface roughness. The achieved wall surface roughness is Ra 1.49μm when using feed rate 10 mm/min, feed flute 0.1/mm, and ultrasonic power 99%. This study is practical for ultrasonic horn processing to drill holes on plates.

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Lin, Chi-Chen, and 林豈臣. "Surface Roughness Prediction and Cutting Parameter Optimization in Milling Process." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5311038%22.&searchmode=basic.

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碩士
國立中興大學
機械工程學系所
107
In this study, the spindle and vise vibrations as well as the spindle current were measured synchronously during the process of milling Inconel 718. The surface roughness (represented by Ra) of workpiece was investigated by determining the correlation among the Ra, the signals of vibration, the cutting parameters, and the current signals, under the different combinations of cutting parameters. The prediction models of workpiece surface roughness were built through the Elman neural network. In the experiment, the features of signals were extracted through the Empirical Mode Decomposition (EMD), envelope analysis, fast Fourier transform(FFT), and the determination of root-mean-square, kurtosis, skewness, and multiscale entropy. The Pearson correlation analysis was utilized to select the features that have high correlation with the Ra value. The Elman neural network model is then trained by the selected features and employed for predicting the workpiece surface roughness. The surface roughness prediction model was employed to optimize the cutting parameters according to the constraints. In this study, the feed rate is maximized under the constraints of certain Ra values in the optimization process. The optimal combination of cutting parameters were obtained through the process of genetic algorithm and the particle swarm algorithm. The optimized cutting parameters were validated by the experiment result. The result of using different signal features and different optimization algorithms are also compared and discussed.

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11

Yang-Lai, Shih, and 賴世陽. "Analysis and Optimization of Surface Roughness and Roundness on Turning Operation." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/31371751942569365762.

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碩士
國立海洋大學
機械與輪機工程學系
90
The objective of this research is to build a precision turning model for accurate prediction of surface roughness and roundness by using Neural Network and Regressional modeling Methods with limited experimental results. Both models are evaluated and their prediction results are compared. The effects of each machining parameters to the surface roughness and roundness are carefully discussed. Furthermore, a multi-objective optimization has been conducted to find a set of best solutions of machining parameters. The optimization technique used in this thesis incorporates Pareto optimal sets, Tournament Sharing Selection and G-bit local search into the Genetic Algorithm to form a Hybrid Multi-Objective Genetic Algorithm (MOGA). The optimization procedures are based on minimum surface roughness and maximum MRR, or minimum roundness and maximum MRR, or minimum surface roughness, roundness and maximum MRR. Finally one optimal solution can be provided to the decision maker by using the shortest distance method .

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LIANG, CHIN-CHUAN, and 梁金荃. "An Analysis of Nickel-Based Alloy Surface Roughness and Machining Parameter Optimization." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/rs6zar.

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碩士
國立虎尾科技大學
機械與電腦輔助工程系碩士班在職專班
106
Nickel-based alloys, Inconel 625, is mainly been used in high tech fields, such as chemical industries and aerospace industries. Base on its excellent high-temperature strength, stability, thermal fatigue and hardening characteristic after processing make nickel-based alloys unfavorable to machining. In particular, the surface roughness after machining has always been an important indicator for evaluating the quality of cutting. This not only affects the performance of the part itself, but also the amount of machining time and quotation cost, Therefore, during the cutting processes, the surface roughness requirement of the machined part must meet the design requirements and processing cost must be taken into consideration. Finding out the optimal machining parameter that meets the required surface roughness of the material to obtain a higher processing cost advantage is already a research topic that the processing technology must face. In this research, the surface roughness is set as the performance indicator. Based on the Taguchi method, use cause-and-effect diagram to find the main factors which affect the surface roughness of nickel-base alloy machining. Then, use L9(34) orthogonal array to set the factor of Inconel 625 machining parameters. By using end mill down milling and side milling method for actual cutting test, to analyze result of the experiment the measurement data. Successfully achieved machining parameters optimization of the cutting speed: 60m/min, Feed per tooth: 0.075mm/tooth, Radial cutting depth 0.06mm and axial cutting depth: 12mm. Finally, confirmed by verification experiment. Applying optimized machining parameters not only has better surface roughness and S/N ratio, but also the material removal rate is 4.38 times higher than the original parameter, Effectively improve the machining efficiency and quality of nickel alloy Inconel 625.

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Lin, Deng-Wen, and 林登文. "Study of Taguchi Method on Surface Roughness Optimization of Zirconia Plane Grinding Parameters." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/75541939760052193246.

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碩士
國立中興大學
機械工程學系所
101
With the application of ceramic materials more widely, its processing quality requirements become increasingly harsh. In order to maintain good performance of the element, there must be a high level of dimensional accuracy and a smooth surface without damage. The surface quality of ceramic materials is usually dependent on the polishing, polishing almost no ability to remove material, only suitable for the final machining program. In this regard, the grinding has compromise advantages. By adjusting the grinding parameters, it is effective to make the surface roughness becomes better, and can directly trimmed workpiece flatness. This research expects to achieve the precision grinding of ceramic materials on a plane grinder, through the adjustment of the plane grinding parameters to optimize the surface quality of zirconia. First, the optimal surface roughness as the goal of the research, planning grinding parameters using Taguchi’s method, in order to get the trend of grinding parameters and optimize the parameters. And then, implementation of advanced optimization experiments by the relevant parameters. The surface quality of the study, not only the surface roughness analysis, also carried out flatness grinding experiments and microscopic observation of the surface quality. On the other hand, also discusses the grinding efficiency and grinding wheel experience. The results of this research successfully obtain optimization parameters of zirconia plane grinding in surface roughness, and verification by ANOVA. Through advanced optimization experiments, vitrified diamond wheel plane grinding roughness can reach Ra0.0218μm, and the workpiece flatness of 0.9μm. Resin diamond wheel plane grinding even reach Ra0.0072μm, the workpiece surface such as a mirror-like smooth.

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Lin, Zhe-jun, and 林哲君. "Optimization of surface roughness of GaN LED for enhancement of light extraction efficiency." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/97793077702979373308.

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碩士
國立中央大學
光電科學研究所
99
The subject of this thesis is to promote the light extraction of light emitting diodes by using the concept of optical waveguide. We use the Finite-Difference Beam Propagation Method (FD-BPM) to simulate the GaN LED waveguide and calculate the angle ( ) corresponding to strongest guided mode. According to the simulation results of FD-BPM, we can design the maximum transmission efficiency grating structure to roughen the surface of the GaN to increase the light extraction. First, we used FD-BPM to compute the relationship between the position of the Multi Quantum Wells (MQWs) and the strongest modes. From the simulation results, the angles of the strongest modes can be obtained. According to the angles of the strongest modes obtained by FD-BPM, we adopted the Rigorous Coupled Wave Analysis (RCWA) to compute the transmission efficiency of the grating structure and the Genetic Algorithms (GAs) to optimize the parameters of the grating structure to find the maximum transmission efficiency. From the results of the GAs, the optimum parameters of the grating structure at the wavelength of 460 nm the grating period were 2.07 ?m, filling factor 0.51 and etching depth 0.2 ?m. The light extraction efficiency of the grating structure compared to the slab structure was promoted to 36 %. The LED with the periodic structure can be rapidly determined by the FD-BPM and the RCWA based on the GAs to optimize the light extraction.

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15

Kuo, Tsung-Ying, and 郭聰穎. "A Dressing Parameters Optimization of Cylindrical Grinder and Image Construction of Surface Roughness." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/ttn8t7.

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碩士
國立彰化師範大學
工業教育與技術學系
106
The purpose of this thesis is to research in a dressing parameters optimization of cylindrical grinder and image construction of surface roughness. Experiment with different dressing factors and levels, then grind the test chip with the grinding wheel. Analyze the experimental data of the surface roughness by the test chip to find the optimum dressing parameters. This thesis will explore the dressing speed ratio, crossing feet ratio, dressing depth, dressing times and dressing smooth times of five dressing parameters , the surface roughness and processing efficiency. Dressing experiment uses "L16" ("4" ^"5" ) orthogonal array of Taguchi Methods and sequence of experiment, and grinds the test chip with grinding wheel after dressing. After obtain the experimental data, calculate the S/N ratio base on the quality characteristics. Find the multiple target optimum dressing parameters by principal component analysis and grey correlation analysis. Verifying the optimum dressing parameters can achieve the best or target grinding quality under better processing efficiency. Using CCD capture the image of the grinding wheel which dressed by optimum dressing parameters, and then calculate the effective area in the image which was processed. Researching the relationship between the effective area and the grinding quality, then find the effective area is inversely proportional to the grinding quality. Helps to monitor the condition of the grinding wheel in real time and indirectly monitor the grinding quality. Keyword：Taguchi Methods, Principal Component Analysis, Grey Relation Analysis , Grinding Wheel Dressing, Surface Roughness, Image Processing

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Lu, Huai-Shiun, and 呂淮熏. "The Study for Prediction of Surface Roughness and Optimization of Parameters in Side Milling." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/30304129487733738281.

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博士
國立高雄第一科技大學
工程科技研究所
95
Side milling is a machining process in end milling operations that utilizes the peripheral cutting edge of an end mill to perform broad surface machining upon the vertical wall of workpieces. It is a common manufacturing process used in molding and mechanical components. The corresponding performance is closely related to several cutting parameters, such as cutting speed, feed per tooth, axial depth of cut, radial depth of cut, overhang length, and flank wear of peripheral cutting edge. Conventionally, a cutting condition selected by operators is mostly based on their experiences and is not an optimal and economical solution for best performance. Therefore, it is imperative to construct a prediction model that can effectively evaluate processing results and offer a solution for optimizing cutting conditions. This research consists of two parts. First, the polynomial network is adopted to construct a prediction model for surface roughness. Second, the grey-relational analysis combined with two-stage experimental design, principle component analysis, and fuzzy logic is proposed to achieve an optimal design of cutting parameters. A series of experiments are organized in a ) 3 2 ( 12 11 36 × L orthogonal array and performed on a B8 machine center. The analysis of variance is used to convert the results into F values for each cutting parameters with which number of input parameters vi of polynomial network and thereby a prediction model for various definitions of surface roughness can be developed using an abductive modeling technique. Finally, a set of experimental data is utilized to test all the developed prediction models. The results show that the more input parameters the polynomial network is implemented, the higher capability of prediction for surface roughness it can achieve (i.e. the predicted values are closer to the experimental data). Recently, the grey-relational analysis has been widely applied in the optimal design of cutting parameters with multiple performance characteristics. In this study, a grey relational analysis is applied to a set of two –stage experiments designed to determine the cutting parameters for optimizing the side milling process with multiple performance characteristics. The cutting parameters under consideration are cutting speed, feed per tooth, axial depth of cut, radial depth of cut, overhang length, and flank wear of peripheral cutting edge. In this study, the L36 and L9 orthogonal arrays were introduced for the two-stage experimental designs and trials. Lower-the-better was used as a quality characteristic to evaluate the experimental results. It was found that applying the grey relational analysis with a two-round experimental design strategy is simple, effective and efficient in developing an optimal cutting parameters combination. The results of the confirmation test also show that this new approach can greatly improve the cutting performance of side milling process. Accordingly, the optimal combination of cutting parameters obtained using two-stage experiment approach can be closer to the ideal one. In order to objectively reflect the corresponding weighting value of each performance characteristic, the grey-relational analysis is specially integrated with the principle component analysis to deal with the optimization problems with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used as a performance index to determine the optimal combination of cutting parameters. The principle component analysis is used to calculate the corresponding weighting value of each performance characteristic while applying grey-relational analysis. The confirmation test shows that the predicted values of grey relational grade obtained based on the optimal combination of cutting parameters is significantly close vii to the experiment values. Thus, this support the proposed application of the additive model. Furthermore, the repeatability of experiment with this combination is excellent. Side milling can be classified as heavy cutting and finishing cutting based on their types of processes. This paper presents an optimal cutting parameter design of heavy cutting in side milling for SUS304 stainless steel. The selected cutting parameters are spindle speed, feed per tooth, axial depth of cut, and radial depth of cut, while the considered performance characteristics are tool life and metal removal rate. The orthogonal array with grey-fuzzy logics is applied to optimize the side milling process with multiple performance characteristics. A grey-fuzzy reasoning grade obtained from the grey- fuzzy logics analysis is used as a performance index to determine the optimal cutting parameters. The results indicate that this optimization algorithm can effectively and swiftly acquire an optimal combination of cutting parameters. Hence, it is believed that this optimal result can be applied to practical processes to effectively reduce manufacturing cost and greatly enhance manufacturing efficiency.

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LIAO, YUNG-FU, and 廖永富. "Analysis of Surface Roughness and Parameter Optimization for Titanium Machining Based on Taguchi Method." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/05481908237486932241.

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碩士
逢甲大學
材料與製造工程所
99
Surface roughness is one of the most important factors for evaluating machining quality. In the thesis, the surface roughness is set as the performance index and the study is focused on the machining of the titanium alloy (Ti-6Al-4V ELI). In the analysis, the machining parameters include the spindle speed, feed rate, depth of cut, etc. Based on the Taguchi method, an orthogonal table is scheduled to determine the concerned factors and the level of importance, and then to obtain the optimal set of machining parameters. Consequently, we have achieved the improvement in machining quality and efficiency reached 337.7%.

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18

Chang, Chun-Chin, and 張竣欽. "Line Width Roughness Optimization of A Multiple Layer Thin Film Structure by Reactive Ion Etch." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/jw8a87.

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碩士
國立交通大學
光電科技學程
103
Implementation of TiN hard mask for copper/ultra low-k interconnect is the standard technique for back end of line (BEOL) integration. Compared with the photo resist (PR) mask approach, the metal hard mask (MHM) approach has the advantages of lower stack-to-mask ratio and better etch selectivity. In addition, metal hard mask minimizes plasma induced low-k damage during low-k dual damascene etch. As device node reach 28nm and beyond, line width roughness (LWR) or line edge roughness (LER) control become a big challenge because LWR of gate directly affects Ion/Ioff property in logic devices, and affects Vth variation directly in memory devices[1-3]. In this study will put focus on different chemistry to improve LWR and control space CD with RIE tool in TiN hard mask approach.

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19

Liao, Jung-Chiang, and 廖容瑲. "Research of the Surface Roughness Optimization Techniques of 45 Degrees Thick-Film Polymers Micro Mirrors." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/73389963818099317465.

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碩士
明志科技大學
機電工程研究所
97
In this paper we apply an inclined-exposure technology and a special design inclined-exposure aiming system to make a new optical micro-structure and replace the traditional mechanical extra work or injection molding optical component. The thick-film negative photoresist SU-8 was used in the experiment, because the polymer material have the feature of stronger and not easy to be changed shape in high temperature (~100°C). At the mean time, using inclined-exposure mechanism to help the angle accuracy to ±30’, and lower the surface roughness to in 300μm×300μm range. The structure of micro reflective mirror is using polymer material with a 1.4mm high micro structure, which is made by low spin and surface tension. In order to resolve the diffraction phenomenon bringing from the non flatness of thick-photoresist, we apply the material, which has the same refractove index as photoresist, to fill in between mask and photoresist, and make use of filter to filter out the UV light, which is lower than 365nm to improve the non parallel structure caused by the difference of the penetration depth of different wavelength. In this research we also developed the anti-reflection technology, and used Fresnel equation to solve the problem of second reflection from substrate surface caused by inclined-exposure. In order to deal with the difficulty of coating on micro mirror, we used optical UV tape as the material when coating and making a pair of mirror group, inaccuracy of shift can be reduced to 60μm-80μm. If this technology could be successfully developed, it can help to improve the design and fabricate of optical pick-up device.

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20

Ahmed, N., M. Rafaqat, S. Pervaiz, U. Umer, H. Alkhalefa, Muhammad A. Shar, and S. H. Mian. "Controlling the material removal and roughness of Inconel 718 in laser machining." 2019. http://hdl.handle.net/10454/17198.

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No
Nickel alloys including Inconel 718 are considered as challenging materials for machining. Laser beam machining could be a promising choice to deal with such materials for simple to complex machining features. The machining accuracy is mainly dependent on the rate of material removal per laser scan. Because of the involvement of many laser parameters and complexity of the machining mechanism it is not always simple to achieve machining with desired accuracy. Actual machining depth extremely varies from very low to aggressively high values with reference to the designed depth. Thus, a research is needed to be carried out to control the process parameters to get actual material removal rate (MRRact) equals to the theoretical material removal rate (MRRth) with minimum surface roughness (SR) of the machined surfaces. In this study, five important laser parameters have been used to investigate their effects on MRR and SR. Statistical analysis are performed to identify the significant parameters with their strength of effects. Mathematical models have been developed and validated to predict the machining responses. Optimal set of laser parameters have also been proposed and confirmed to achieve the actual MRR close to the designed MRR (MRR% = 100.1%) with minimum surface roughness (Ra = 2.67 µm).
The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group number RG-1440-026.

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21

Ahmed, N., M. Rafaqat, S. Pervaiz, U. Umer, H. Alkhalefa, Muhammad A. S. Baloch, and S. H. Mian. "Controlling the material removal and roughness of Inconel 718 in laser machining." 2001. http://hdl.handle.net/10454/17198.

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No
Nickel alloys including Inconel 718 are considered as challenging materials for machining. Laser beam machining could be a promising choice to deal with such materials for simple to complex machining features. The machining accuracy is mainly dependent on the rate of material removal per laser scan. Because of the involvement of many laser parameters and complexity of the machining mechanism it is not always simple to achieve machining with desired accuracy. Actual machining depth extremely varies from very low to aggressively high values with reference to the designed depth. Thus, a research is needed to be carried out to control the process parameters to get actual material removal rate (MRRact) equals to the theoretical material removal rate (MRRth) with minimum surface roughness (SR) of the machined surfaces. In this study, five important laser parameters have been used to investigate their effects on MRR and SR. Statistical analysis are performed to identify the significant parameters with their strength of effects. Mathematical models have been developed and validated to predict the machining responses. Optimal set of laser parameters have also been proposed and confirmed to achieve the actual MRR close to the designed MRR (MRR% = 100.1%) with minimum surface roughness (Ra = 2.67 µm).
The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group number RG-1440-026.

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22

Tsai, Hsiu-Shan, and 蔡修善. "Process Parameters Optimization for Desired Surface Roughness and Identification of Radial Cutter Runout Parametersin Micro-end-milling." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/ucnp27.

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碩士
國立高雄應用科技大學
機械與精密工程研究所
102
The primarily process parameters in micro-end-milling are spindle speed, feed rate and axial depth of cut,etc. The decision of process parameters affectdirectly the surface quality of workpiece, manufacturing time and cost. This research aims to the SKD11 mold steel in micro-end-milling, applies experimental design and response surface methodology (RMS) to establish the relation of surface roughness to processing parameters, then takes it as the objective function of process parameters optimization for desired surface roughness of a biochip micro-channel when using four evolutionary algorithm methods, which are differential evolution (DE), hybrid particle swarm optimization (HPSO), particle swarm optimization (PSO) and genetic algorithm (GA), etc. In addition, the surface roughness can be predicted by a proposed theoretical analytical model. Finally, the micro-end-milling experiments are conducted with the optimal parameters obtained using those methods, compared with the desired, measured and predicted value of the surface roughness, it reveals that the result of HPSO method is the best. In addition, we derive the surface morphology parameters prediction model implicitly expressed in parametersof cutterrunoutbased on the measured topography surface height of the micro-milled workpiece, and Newton-Raphson methodis applied to solve the proposed model for the radial cutter runout and phase angle. According to the predictive surface topography height, the surface roughness values can then be calculated and comparedwith measured values, the error between both results only 3.01%. The results of this study showed that for SKD11 mold steel in micro-end-milling, the response surface methodology can be usedfor determining the objective function of the surface roughness optimization, and the HPSO method can obtain the best results for desired surface roughness of workpiece in micro-end-milling of SKD11. In addition, based on the proposed surface topography model and the measured values of experiment, the Newton-Raphson method canbe used successfully for solving the radial cutter runout and phase angle in micro-end-mill.

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23

Chang, Ching-Shui, and 張清水. "An Investigation on Optimization Parameters of Roughness and Roundness by Boring with a CNC Turning Machine Center." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/77972538788527004960.

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碩士
國立屏東科技大學
機械工程系所
104
In this study a CNC turning machine center is used for boring S45C carbon steel, the characteristics of surface roughness and the hole roundness are investigated respectively. In addition, the optimum parameters are obtained by using single objective quality analysis with conducting arranged experiments. An orthogonal array of Taguchi method is used to arrange the boring parameters, including spindle speed, feed rate, cutting amount of workpiece. The measurements of surface roughness and the hole roundness are conducted. The results showed that a 1.2468μm for surface roughness amount with milling and a 1.2174μm for surface roughness amount with turning and a 2.702μm for roundness amount with milling and a 2.128μm for roundness amount with turning are found by selecting optimum parameters in single objective quality analysis respectively. Therefore this leads to a conclusion that use a turning and milling combined machine tool can ensure the precision and handle several processes during operation. It can also raise the productivity. The achievement of this research can be used as reference in boring related research and industrial applications.

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Liao, Hsueh-Yu, and 廖學佑. "Artificial Intelligence Machining Surface Roughness Prediction Model and MRR Optimization – A Case Study of Plastic Injection Mold Milling." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/nbzk5j.

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碩士
國立中興大學
機械工程學系所
103
Technical products have characteristics such as short life cycle, high surface quality request and large quantity. Therefore, manufacturing factories gradually tend to use general types machine tool equipped with intelligent management, intelligent design and monitoring systems. Recently, with technological development, there are more and more indirect sensors which are normally used, and computer efficiency is higher than the past. The obstacles of hardware are gradually removed. Accordingly, in the field of manufacturing, many researchers use artificial neural networks (ANNs) to predict the surface roughness. They use milling experiment data for training ANNs, and get the relationship between inputs and outputs. In most of cases, well trained ANNs can predict workpiece surface roughness effectively. The prediction system can achieve the intelligentization of rising process quality. However, when their systems got the prediction of workpiece surface quality, the data did not be further used. This research project will investigate the use of ANNs with sensor fusion to construct an effective surface quality prediction system by making use of force and acoustic emission signals. The prediction system was then optimized under the constraint that the workpiece surface roughness must be lower than the requested surface roughness. The optimization system determined the best parameter combination by maximizing the material removal rate (MRR), and then relaying this information to the machine tool controller. The optimization system experiments show that the maximum error of is about 11%, and the Mean absolute percentage error is about 5.2%, and each optimization operation takes around 110 sec. The performance of system is excellent. The optimization system can be modify and setup on pc-based CNC controller. Let manufacturing industry field can achieve the intelligentization of rising process efficiency.

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25

Hsieh, Shih-Yo, and 謝士佑. "Signal Feature Extraction for Predicting Surface Roughness of Inconel 718 in Milling Process and Cutting Parameter Optimization via Genetic Algorithm." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/w2ua6n.

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26

Ban, Yong Chan. "Lithography variability driven cell characterization and layout optimization for manufacturability." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-05-3372.

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Standard cells are fundamental circuit building blocks designed at very early design stages. Nanometer standard cells are prone to lithography proximity and process variations. How to design robust cells under variations plays a crucial role in the overall circuit performance and yield. This dissertation studies five related research topics in design and manufacturing co-optimization in nanometer standard cells. First, a comprehensive sensitivity metric, which seamlessly incorporates effects from device criticality, lithographic proximity, and process variations, is proposed. The dissertation develops first-order models to compute these sensitivities, and perform robust poly and active layout optimization by minimizing the total delay sensitivity to reduce the delay under the nominal process condition and by minimizing the performance gap between the fastest and the slowest delay corners. Second, a new equivalent source/drain (S/D) contact resistance model, which accurately calculates contact resistances from contact area, contact position, and contact shape, is proposed. Based on the impact of contact resistance on the saturation current, robust S/D contact layout optimization by minimizing the lithography variation as well as by maximizing the saturation current without any leakage penalty is performed. Third, this dissertation describes the first layout decomposition methods of spacer-type self-aligned double pattering (SADP) lithography for complex 2D layouts. The favored type of SADP for complex logic interconnects is a two-mask approach using a core mask and a trim mask. This dissertation describes methods for automatically choosing and optimizing the manufacturability of base core mask patterns, generating assist core patterns, and optimizing trim mask patterns to accomplish high quality layout decomposition in SADP process. Fourth, a new cell characterization methodology, which considers a random (line-edge roughness) LER variation to estimate the device performance of a sub-45nm design, is presented. The thesis systematically analyzes the random LER by taking the impact on circuit performance due to LER variation into consideration and suggests the maximum tolerance of LER to minimize the performance degradation. Finally, this dissertation proposes a design aware LER model which claims that LER is highly related to the lithographic aerial image fidelity and the neighboring geometric proximity. With a new LER model, robust LER aware poly layout optimization to minimize the leakage power is performed.
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27

Chang, Hsiao-Cheng, and 張孝崢. "Optimization and analysis the surface roughness of Ti-6Al-4V titanium alloy in finishing grinding process with cold air gun coolant system." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/61316330984336197399.

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碩士
修平科技大學
精密機械與製造科技碩士班
104
The machinability evaluation of cold air gun coolant system in the fine grinding process of Ti-6Al-4V titanium alloy was investigated by modeling and optimization. A high-quality cooling and lubrication system can effectively improve the quality of surface finish. Under normal circumstances, cutting fluids are customarily used to control the cutting temperature in the cutting zone. A cold air gun coolant system was used in the experiments and produced a jet of compressed cold air in the air-cooling process during the metal grinding cutting process. In this paper, the mathematical model was presented to model the machinability evaluation through the response surface methodology (RSM). The quadratic model of response surface methodology associated with the sequential approximation optimization (SAO) method would be used to explain the relation of the finishing grinding process parameters and machining characteristic, and to find optimum values of machining parameters for the face cutting process of Titanium alloys. Observed in experiments, the cold air flow increases and reduce the cold air temperature will get better cooling and lubrication between the grinding wheel and the workpiece. Also reduce the friction and adhesion of materials, thus obtaining better quality of surface finish. The results of the experiment was confirmed by analysis of variance (ANOVA). All the experiment values are found in 95% prediction interval, and it’s enough to confirm the accuracy of the quadratic model. Using the optimum values of machining parameters for the finishing grinding process, compared with the best surface roughness Ra value and the initial value of the surface roughness was reduced 22.5%.

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28

Kulkarni, Ruturaj Jayant. "AI Based Modelling and Optimization of Turning Process." 2012. http://hdl.handle.net/1805/3418.

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Indiana University-Purdue University Indianapolis (IUPUI)
In this thesis, Artificial Neural Network (ANN) technique is used to model and simulate the Turning Process. Significant machining parameters (i.e. spindle speed, feed rate, and, depths of cut) and process parameters (surface roughness and cutting forces) are considered. It is shown that Multi-Layer Back Propagation Neural Network is capable to perform this particular task. Design of Experiments approach is used for efficient selection of values of parameters used during experiments to reduce cost and time for experiments. The Particle Swarm Optimization methodology is used for constrained optimization of machining parameters to minimize surface roughness as well as cutting forces. ANN and Particle Swarm Optimization, two computational intelligence techniques when combined together, provide efficient computational strategy for finding optimum solutions. The proposed method is capable of handling multiple parameter optimization problems for processes that have non-linear relationship between input and output parameters e.g. milling, drilling etc. In addition, this methodology provides reliable, fast and efficient tool that can provide suitable solution to many problems faced by manufacturing industry today.

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29

Wang, Jing. "Functional Principal Component Analysis for Discretely Observed Functional Data and Sparse Fisher’s Discriminant Analysis with Thresholded Linear Constraints." 2016. http://scholarworks.gsu.edu/math_diss/35.

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We propose a new method to perform functional principal component analysis (FPCA) for discretely observed functional data by solving successive optimization problems. The new framework can be applied to both regularly and irregularly observed data, and to both dense and sparse data. Our method does not require estimates of the individual sample functions or the covariance functions. Hence, it can be used to analyze functional data with multidimensional arguments (e.g. random surfaces). Furthermore, it can be applied to many processes and models with complicated or nonsmooth covariance functions. In our method, smoothness of eigenfunctions is controlled by directly imposing roughness penalties on eigenfunctions, which makes it more efficient and flexible to tune the smoothness. Efficient algorithms for solving the successive optimization problems are proposed. We provide the existence and characterization of the solutions to the successive optimization problems. The consistency of our method is also proved. Through simulations, we demonstrate that our method performs well in the cases with smooth samples curves, with discontinuous sample curves and nonsmooth covariance and with sample functions having two dimensional arguments (random surfaces), repectively. We apply our method to classification problems of retinal pigment epithelial cells in eyes of mice and to longitudinal CD4 counts data. In the second part of this dissertation, we propose a sparse Fisher’s discriminant analysis method with thresholded linear constraints. Various regularized linear discriminant analysis (LDA) methods have been proposed to address the problems of the LDA in high-dimensional settings. Asymptotic optimality has been established for some of these methods when there are only two classes. A difficulty in the asymptotic study for the multiclass classification is that for the two-class classification, the classification boundary is a hyperplane and an explicit formula for the classification error exists, however, in the case of multiclass, the boundary is usually complicated and no explicit formula for the error generally exists. Another difficulty in proving the asymptotic consistency and optimality for sparse Fisher’s discriminant analysis is that the covariance matrix is involved in the constraints of the optimization problems for high order components. It is not easy to estimate a general high-dimensional covariance matrix. Thus, we propose a sparse Fisher’s discriminant analysis method which avoids the estimation of the covariance matrix, provide asymptotic consistency results and the corresponding convergence rates for all components. To prove the asymptotic optimality, we provide an asymptotic upper bound for a general linear classification rule in the case of muticlass which is applied to our method to obtain the asymptotic optimality and the corresponding convergence rate. In the special case of two classes, our method achieves the same as or better convergence rates compared to the existing method. The proposed method is applied to multivariate functional data with wavelet transformations.

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30

Grant, Michael. "New modelling and simulation methods to support clean marine propulsion." Thesis, 2021. http://hdl.handle.net/1828/13308.

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The marine industry has increased its adoption of pure-electric, diesel-electric, and other non-traditional propulsion architectures to reduce ship emissions and fuel consumption. While these technologies can improve performance, the design of a propulsion system becomes challenging, given that no single technology is superior across all vessel types. Furthermore, even identical ships with different operating patterns may be better suited to different propulsion technologies. Addressing this problem, previous research has shown that if key elements of a vessel's operational pro file are known, simulation and optimization techniques can be employed to evaluate multiple propulsion architectures and result in a better propulsion system design and energy management strategy for a given vessel. While these studies have demonstrated the performance improvements that can be achieved from optimizing clean marine propulsion systems, they rely on vessel operational profiles obtained through physical measurement from existing ships. From a practical point of view, the optimization of a vessel's propulsion system needs to occur prior to a vessel's construction and thus precludes physical measurement. To this end, this thesis introduces a marine simulation platform for producing vessel operational profiles which enable propulsion system optimization during the ship design process. Core subsystem modules are constructed for simulating ship motions in 3 degrees of freedom and result in operational profile time-series, including propulsion power. Data is acquired from a benchmark vessel to validate the simulation. Results show the proposed approach strikes a balance between speed, accuracy, and complexity compared with other available tools.
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Dissertations / Theses on the topic 'Roughness optimization'

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