Sheet-metal press line parameter tuning using a combined DIRECT and Nelder-Mead algorithm

It is a great challenge to obtain an efficient algorithm for global optimisation of nonlinear, nonconvex and high dimensional objective functions. This paper shows how the combination of DIRECT and Nelder-Mead algorithms can improve the efficiency in the parameter tuning of a sheet-metal press line. A combined optimisation algorithm is proposed that determines and utilises all local optimal points from DIRECT algorithm as Nelder-Mead starting points. To reduce the total optimisation time, all Nelder-Mead optimisations can be executed in parallel. Additionally, a Collision Inspection Method is implemented in the simulation model to reduce the evaluation time. Altogether, this results in an industrially useful parameter tuning method. Improvements of an increased production rate of 7% and 40% smoother robot motions have been achieved

Automatic constraint-based synthesis of non-uniform rational B-spline surfaces

In this dissertation a technique for the synthesis of sculptured surface models subject to several constraints based on design and manufacturability requirements is presented. A design environment is specified as a collection of polyhedral models which represent components in the vicinity of the surface to be designed, or regions which the surface should avoid. Non-uniform rational B-splines (NURBS) are used for surface representation, and the control point locations are the design variables. For some problems the NURBS surface knots and/or weights are included as additional design variables. The primary functional constraint is a proximity metric which induces the surface to avoid a tolerance envelope around each component. Other functional constraints include: an area/arc-length constraint to counteract the expansion effect of the proximity constraint, orthogonality and parametric flow constraints (to maintain consistent surface topology and improve machinability of the surface), and local constraints on surface derivatives to exploit part symmetry. In addition, constraints based on surface curvatures may be incorporated to enhance machinability and induce the synthesis of developable surfaces;The surface synthesis problem is formulated as an optimization problem. Traditional optimization techniques such as quasi-Newton, Nelder-Mead simplex and conjugate gradient, yield only locally good surface models. Consequently, simulated annealing (SA), a global optimization technique is implemented. SA successfully synthesizes several highly multimodal surface models where the traditional optimization methods failed. Results indicate that this technique has potential applications as a conceptual design tool supporting concurrent product and process development methods

Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine

Optimal performance of the electric machine/drive system is mandatory to improve the energy consumption and reliability. To achieve this goal, mathematical models of the electric machine/drive system are necessary. Hence, this motivated the editors to instigate the Special Issue “Mathematical Approaches to Modeling, Optimally Designing, and Controlling Electric Machine”, aiming to collect novel publications that push the state-of-the art towards optimal performance for the electric machine/drive system. Seventeen papers have been published in this Special Issue. The published papers focus on several aspects of the electric machine/drive system with respect to the mathematical modelling. Novel optimization methods, control approaches, and comparative analysis for electric drive system based on various electric machines were discussed in the published papers

Full-wave analysis of dielectric-loaded cylindrical waveguides and cavities using a new four-port ring network

“© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”In this paper, a full-wave method for the electromagnetic analysis of dielectric-loaded cylindrical and coaxial waveguides and cavities is developed. For this purpose, a new four-port ring network is proposed, and the mode-matching method is applied to calculate the generalized admittance matrix of this new structure. A number of analyses on dielectric-loaded waveguide structures and cavities have been conducted in order to validate and to assess the accuracy of the new approach. The results have been compared with theoretical values, numerical modeling from the literature, and data from commercial electromagnetic simulators. The method has been also applied to the accurate determination of dielectric properties, and we provide an example of these measurements as another way to validate this new method. © 1963-2012 IEEE.This work was supported by the Ministry of Science and Innovation of Spain under Project MONIDIEL (TEC2008-04109). The work of F. L. Penarada-Foix was supported by the Conselleria de Educacion of the Generalitat Valenciana for economic support (BEST/2010/210).Penaranda-Foix, FL.; Janezic, MD.; Catalá Civera, JM.; Canós Marín, AJ. (2012). Full-wave analysis of dielectric-loaded cylindrical waveguides and cavities using a new four-port ring network. IEEE Transactions on Microwave Theory and Techniques. 60(9):2730-2740. https://doi.org/10.1109/TMTT.2012.2206048S2730274060

Silicon photonic Bragg-based devices : hardware and software

L'avènement de la photonique intégrée a attiré beaucoup de recherche et d'attention industrielle au cours des deux dernières décennies, plusieurs croyant qu'il s'agit d'une révolution équivalente à la microélectronique. Tout en tirant parti des procédés de fabrication de masse hérités de la microélectronique, la photonique sur silicium est compacte, éconergitique et permet l'intégration complète de dispositifs et de circuits photoniques à l'échelle nanométrique pour des applications cruciales dans les télécommunications, la détection et le calcul optique. À l'instar des débuts de la microélectronique, les efforts de recherche actuels en photonique sur silicium sont principalement consacrés à la proposition, à la conception et la caractérisation de composants standardisés en vue d'une éventuelle intégration de masse dans des circuits photoniques. Les principaux défis associés à ce développement comprennent la complexité de la théorie électromagnétique dans le fonctionnement des dispositifs, les variations et les non-uniformités du procédé de fabrication limitant les performances, et les ressources informatiques considérables nécessaires pour modéliser avec précision des circuits photoniques complexes. Dans ce mémoire, ces trois limitations sont abordées sous forme de contributions de recherche originales. Basées sur des dispositifs photoniques sur silicium et l'apprentissage machine, les contributions de ce mémoire concernent toutes les réseaux de Bragg intégrés, dont le principe de fonctionnement de base est la réflexion optique sélective en fréquence. Premièrement, un nouveau filtre optique double-bande basé sur les réseaux de Bragg multimodes est introduit pour des applications dans les télécommunications. Deuxièmement, une nouvelle architecture de filtre accordable basée sur un coupleur contra-directionnel à étage unique avec un dispositif de micro-chauffage segmenté permettant des profils de température arbitraires démontre une accordabilité de la bande passante record et des capacités de compensation des erreurs de fabrication lorsqu'opérée par un algorithme de contrôle. Troisièmement, un modèle d'apprentissage machine basé sur un réseau de neurones artificiels est introduit et démontré pour la conception de coupleurs contra-directionnels et le diagnostic de fabrication, ouvrant la voie à la production de masse de systèmes photoniques intégrés basée sur les données.The advent of integrated photonics has attracted a lot of research and industrial attention in the last two decades, as it is believed to be a hardware revolution similar to microelectronics. While leveraging microelectronics-inherited mass-production-grade fabrication processes for full scalability, the silicon photonic paradigm is compact, energy efficient and allows the full integration of nano-scale optical devices and circuits for crutial applications in telecommunications, sensing, and optical computing. Similar to early-day microelectronics, current research efforts in silicon photonics are put toward the proposal, design and characterization of standardized components in sights of eventual black-box building block circuit design. The main challenges associated with this development include the complexity of electromagnetic theory in device operation, the performance-limiting fabrication process variations and non-uniformities, and the considerable computing resources required to accurately model complex photonic circuitry. In this work, these three bottlenecks are addressed in the form of original research contributions. Based on silicon photonic devices and machine learning, the contributions of this thesis pertain to integrated Bragg gratings, whose basic operating principle is frequency-selective optical transmission. First, a novel dual-band optical filter based on multimode Bragg gratings is introduced for applications in telecommunications. Second, a novel tunable filter architecture based on a single-stage contra-directional coupler with a segmented micro-heating device allowing arbitrary temperature profiles demonstrates record-breaking bandwidth tunability and on-chip fabrication error compensation capabilities when operated by a control algorithm. Third, an artificial neural network-based machine learning model is introduced and demonstrated for large-parameter-space contra-directional coupler inverse design and fabrication diagnostics, paving the way for the data-driven mass production of integrated photonic systems

Multi-transit Echo Suppression for Passive Wireless Surface Acoustic Wave Sensors Using 3rd Harmonic Unidirectional Transducers and Walsh-Hadamard-like Reflectors

A passive wireless surface acoustic wave sensor of a delay-line type is composed of an antenna, a transducer that converts the EM signal into a surface acoustic wave, and a set of acoustic reflectors that reflect the incoming signal back out through the antenna. A cavity forms between the transducer and the reflectors, trapping energy and causing multiple unwanted echoes. The work in this dissertation aims to reduce the unwanted echoes so that only the main transit signal is left--the signal of interest with sensor information. The contributions of this dissertation include reflective delay-line device response in the form of an infinite impulse response (IIR) filter. This may be used in the future to subtract out unwanted echoes via post-processing. However, this dissertation will use a physical approach to echo suppression by using a unidirectional transducer. Thus a unidirectional transducer is used and also optimized for 3rd harmonic operation. Both the directionality and the coupling of the 3rd harmonic optimized SPUDT are improved over a standard electrode width controlled (EWC) SPUDT. New type of reflectors for the reflective delay-line device are also presented. These use BPSK type coding, similar to that of the Walsh-Hadamard codes. Two types are presented, variable reflectivity and variable chip-lengths. The COM model is used to simulate devices and compare the predicted echo suppression level to that of fabricated devices. Finally, a device is mounted on a tunable antenna and the echo is suppressed on a wireless operating device

Combining adaptive and designed statistical experimentation : process improvement, data classification, experimental optimization and model building

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references.Research interest in the use of adaptive experimentation has returned recently. This historic technique adapts and learns from each experimental run but requires quick runs and large effects. The basis of this renewed interest is to improve experimental response and it is supported by fast, deterministic computer experiments and better post-experiment data analysis. The unifying concept of this thesis is to present and evaluate new ways of using adaptive experimentation combined with the traditional statistical experiment. The first application uses an adaptive experiment as a preliminary step to a more traditional experimental design. This provides experimental redundancy as well as greater model robustness. The number of extra runs is minimal because some are common and yet both methods provide estimates of the best setting. The second use of adaptive experimentation is in evolutionary operation. During regular system operation small, nearly unnoticeable, variable changes can be used to improve production dynamically. If these small changes follow an adaptive procedure there is high likelihood of improvement and integrating into the larger process development. Outside of the experimentation framework the adaptive procedure is shown to combine with other procedures and yield benefit. Two examples used here are an unconstrained numerical optimization procedure as well as classification parameter selection. The final area of new application is to create models that are a combination of an adaptive experiment with a traditional statistical experiment.(cont.) Two distinct areas are examined, first, the use of the adaptive experiment to determine the covariance structure, and second, the direct incorporation of both data sets in an augmented model. Both of these applications are Bayesian with a heavy reliance on numerical computation and simulation to determine the combined model. The two experiments investigated could be performed on the same physical or analytical model but are also extended to situations with different fidelity models. The potential for including non-analytical, even human, models is also discussed. The evaluative portion of this thesis begins with an analytic foundation that outlines the usefulness as well as the limitations of the procedure. This is followed by a demonstration using a simulated model and finally specific examples are drawn from the literature and reworked using the method. The utility of the final result is to provide a foundation to integrate adaptive experimentation with traditional designed experiments. Giving industrial practitioners a solid background and demonstrated foundation should help to codify this integration. The final procedures represent a minimal departure from current practice but represent significant modeling and analysis improvement.by Chad Ryan Foster.Sc.D

Liquid crystal hyperspectral imager

Hyperspectral imaging is the collection, processing and analysis of spectral data in numerous contiguous wavelength bands while also providing spatial context. Some of the commonly used instruments for hyperspectral imaging are pushbroom scanning imaging systems, grating based imaging spectrometers and more recently electronically tunable filters. Electronically tunable filters offer the advantages of compactness and absence of mechanically movable parts. Electronically tunable filters have the ability to rapidly switch between wavelengths and provide spatial and spectral information over a large wavelength range. They involve the use of materials whose response to light can be altered in the presence of an external stimulus. While these filters offer some unique advantages, they also present some equally unique challenges. This research work involves the design and development of a multichannel imaging system using electronically tunable Liquid Crystal Fabry-Perot etalons. This instrument is called the Liquid Crystal Hyperspectral Imager (LiCHI). LiCHI images four spectral regions simultaneously and presents a trade-off between spatial and spectral domains. This simultaneity of measurements in multiple wavelengths can be exploited for dynamic and ephemeral events. LiCHI was initially designed for multispectral imaging of space plasmas but its versatility was demonstrated by testing in the field for multiple applications including landscape analysis and anomaly detection. The results obtained after testing of this instrument and analysis of the images are promising and demonstrate LiCHI as a good candidate for hyperspectral imaging. The challenges posed by LiCHI for each of these applications have also been explored

A multi-criteria design framework for the synthesis of complex pressure swing adsorption cycles for CO2 capture

Pressure Swing Adsorption (PSA) is the most efficient option for middle scale separation processes. PSA is a cyclic process whose main steps are adsorption, at high pressure, and regeneration of the adsorbent, at low pressure. The design of PSA cycles is still mainly approached experimentally due to the computational challenges posed by the complexity of the simulation and by the need to detect the performance at cyclic steady state (CSS). Automated tools for the design of PSA processes are desirable to allow a better understanding of the the complex relationship between the performance and the design variables. Furthermore, the operation is characterised by trade-o�ffs between conflicting criteria. A multi-objective flowsheet design framework for complex PSA cycles is presented. A suite of evolutionary procedures, for the generation of alternative PSA con�figurations has been developed, including simple evolution, simulated annealing as well as a population based procedure. Within this evolutionary procedure the evaluation of each cycle confi�guration generated requires the solution of a multi-objective optimisation problem which considers the conflicting objectives of recovery and purity. For this embedded optimisation problem a multi-objective genetic algorithm (MOGA), with a targeted fi�tness function, is used to generate the approximation to the Pareto front. The evaluation of each alternative design makes use of a number of techniques to reduce the computational burden. The case studies considered include the separation of air for N2 production, a fast cycle operation which requires a detailed di�ffusion model, and the separation of CO2 from flue gases, where complex cycles are needed to achieve a high purity product. The novel design framework is able to determine optimal configurations and operating conditions for PSA for these industrially relevant case studies. The results presented by the design framework can help an engineer to make informed design decisions