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Bakker, Craig Kent Reddick. "A differential geometry framework for multidisciplinary design optimization." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.708688.
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Liu, Qiang. "EBF3GLWingOpt: A Framework for Multidisciplinary Design Optimization of Wings Using SpaRibs." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/49665.
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A global/local framework for multidisciplinary optimization of generalized aircraft wing structure has been developed. The concept of curvilinear stiffening members (spars, ribs and stiffeners) has been applied in the optimization of a wing structure. A global wing optimization framework EBF3WingOpt, which integrates the static aeroelastic, flutter and buckling analysis, has been implemented for exploiting the optimal design at the wing level. The wing internal structure is optimized using curvilinear spars and ribs (SpaRibs). A two-step optimization approach, which consists of topology optimization with shape design variables and size optimization with thickness design variables, is implemented in EBF3WingOpt. A local panel optimization EBF3PanelOpt, which includes stress and buckling evaluation criteria, is performed to optimize the local panels bordered by spars and ribs for further structural weight saving. The local panel model is extracted from the global finite element model. The boundary conditions are defined on the edges of local panels using the displacement fields obtained from the global model analysis. The local panels are optimized to satisfy stress and buckling constraints. Stiffened panel with curvilinear stiffeners is implemented in EBF3PanelOpt to improve the buckling resistance of the local panels. The optimization of stiffened panels has been studied and integrated in the local panel optimization. EBF3WingOpt has been applied for the optimization of the wing structure of the Boeing N+2 supersonic transport wing and NASA common research model (CRM). The optimization results have shown the advantage of curvilinear spars and ribs concept. The local panel optimization EBF3PanelOpt is performed for the NASA CRM wing. The global-local optimization framework EBF3GLWingOpt, which incorporates global wing optimization module EBF3WingOpt and local panel optimization module EBF3PanelOpt, is developed using MATLAB and Python programming to integrate several commercial software: MSC.PATRAN for pre and post processing, MSC.NASTRAN for finite element analysis. An approximate optimization method is developed for the stiffened panel optimization so as to reduce the computational cost. The integrated global-local optimization approach has been applied to subsonic NASA common research model (CRM) wing which proves the methodology's application scaling with medium fidelity FEM analysis. Both the global wing design variables and local panel design variables are optimized to minimize the wing weight at an acceptable computational cost.Ph. D.
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Zheng, Panni. "The Design and Optimization of a Lithium-ion Battery Direct Recycling Process." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/93212.
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Nowadays, Lithium-ion batteries (LIBs) have dominated the power source market in a variety of applications. Lithium cobalt oxide (LiCoO2) is one of the most common cathode materials for LIBs in consumer electronics. The recycling of LIBs is important because cobalt is an expensive element that is dependent on foreign sources for production. Lithium-ion batteries need to be recycled and disposed properly when they reach the end of life (EOL) to avoid negative environmental impact. This project focuses on recycling cathode material (LiCoO2) by direct method. Two automation stages, tape peeling stage and unrolling stage, are designed for disassembling prismatic winding cores. Different sintering conditions (e.g., temperature, sintering atmosphere, the amount of lithium addition) are investigated to recycle EOL cathode materials. The results show that the capacity of the recycled cathode materials increases with increasing temperature. The extra Li addition leads to worse cycling performance. In addition, the sintering atmosphere has little influence on small- scale sintering. Also, most of directly recycled cathode materials have better electrochemical (EC) performance than commercial LiCoO2 (LCO) from Sigma, especially when cycling with 4.45V cutoff voltage.Master of Science
Nowadays, Lithium-ion batteries (LIBs) have dominated the power source market in a variety of applications. A LIB contains an anode, a cathode and electrolyte. The cathode material is the most valuable component in the LIB. Lithium cobalt oxide (LiCoO2) is one of the most common cathode materials for LIBs in consumer electronics. The recycling of LIBs is important because cobalt is an expensive element that is dependent on foreign sources for production. Lithium-ion batteries need to be recycled and disposed properly when they reach end of life (EOL) to avoid negative environmental impact. The direct recycling is a cost effective and energy conservative method which can be divided into two steps: retrieving the cathode materials from EOL LIBs and regenerating the cathode materials. This project focuses on recycling LiCoO2 by direct method. Two automation modules, tape peeling stage and unrolling stage, are designed for a disassembling line which is the automation line to collect the cathodes materials. The EOL cathode materials is lithium deficient (Li1-xCoO2). To regenerate the EOL cathode materials, lithium is added into structure of cathode materials which is called the re-lithiation process. The different sintering conditions (e.g., temperature, sintering atmosphere, the amount of lithium addition) are investigated for the re-lithiation process. The results show that the capacity of the recycled cathode materials increases with increasing temperature. The extra Li addition in iv Li1-xCoO2 leads to worse cycling performance. In addition, sintering atmosphere has little influence on small- scale sintering. Most of directly recycled cathode materials have better electrochemical (EC) performance than commercial LiCoO2, especially when cycling with 4.45V cutoff voltage.
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Bowman, Kelly Eric. "Optimization Constrained CAD Framework with ISO-Performing Design Generator." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2599.pdf.
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Xiong, Haoyi. "Near-optimal mobile crowdsensing : design framework and algorithms." Thesis, Evry, Institut national des télécommunications, 2015. http://www.theses.fr/2015TELE0005/document.
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Aujourd’hui, il y a une demande croissante de fournir les informations d'environnement en temps réel tels que la qualité de l'air, le niveau de bruit, état du trafic, etc. pour les citoyens dans les zones urbaines a des fins diverses. La prolifération des capteurs de smartphones et la mobilité de la population font des Mobile Crowdsensing (MCS) un moyen efficace de détecter et de recueillir des informations a un coût faible de déploiement. En MCS, au lieu de déployer capteurs statiques dans les zones urbaines, les utilisateurs avec des périphériques mobiles jouent le rôle des capteurs de mobiles à capturer les informations de leurs environnements, et le réseau de communication (3G, WiFi, etc.) pour le transfert des données pour MCS applications. En général, l'application MCS (ou tâche) non seulement exige que chaque participant de périphérique mobile de posséder la capacité de réception missions de télédétection, de télédétection et de renvoi détecte résultats vers un serveur central, il exige également de recruter des participants, attribuer de télédétection tâches aux participants, et collecter les résultats obtenues par télédétection ainsi que représente les caractéristiques de la cible zone de détection. Afin de recruter un nombre suffisant de participants, l'organisateur d'une MCS tâche devrait considérer la consommation énergétique causée par MCS applications pour chaque participant et les questions de protection dans la vie privée, l'organisateur doit donner a chaque participant un certain montant des incitations comme un encouragement. En outre, afin de recueillir les résultats obtenues par télédétection et représentant la région cible, l'organisateur doit s'assurer que les données de télédétection qualité des résultats obtenues par télédétection, p. ex., la précision et la spatio-temporelle la couverture des résultats obtenus par télédétection. Avec la consommation d'énergie, la protection de la vie privée, les mesures d'incitation, de télédétection et qualité des données à l'esprit, dans cette thèse nous avons étudié quatre problèmes d'optimisation de mobile crowdsensing et mené après quatre travaux de recherche [...]Nowadays, there is an increasing demand to provide real-time environment information such as air quality, noise level, traffic condition, etc. to citizens in urban areas for various purposes. The proliferation of sensor-equipped smartphones and the mobility of people are making Mobile Crowdsensing (MCS) an effective way to sense and collect information at a low deployment cost. In MCS, instead of deploying static sensors in urban areas, people with mobile devices play the role of mobile sensors to sense the information of their surroundings and the communication network (3G, WiFi, etc.) is used to transfer data for MCS applications. Typically, an MCS application (or task) not only requires each participant's mobile device to possess the capability of receiving sensing tasks, performing sensing and returning sensed results to a central server, it also requires to recruit participants, assign sensing tasks to participants, and collect sensed results that well represents the characteristics of the target sensing region. In order to recruit sufficient participants, the organizer of the MCS task should consider energy consumption caused by MCS applications for each individual participant and the privacy issues, further the organizer should give each participant a certain amount of incentives as encouragement. Further, in order to collect sensed results well representing the target region, the organizer needs to ensure the sensing data quality of the sensed results, e.g., the accuracy and the spatial-temporal coverage of the sensed results. With the energy consumption, privacy, incentives, and sensing data quality in mind, in this thesis we have studied four optimization problems of mobile crowdsensing and conducted following four research works: • EEMC - In this work, the MCS task is splitted into a sequence of sensing cycles, we assume each participant is given an equal amount of incentive for joining in each sensing cycle; further, given the target region of the MCS task, the MCS task aims at collecting an expected number of sensed results from the target region in each sensing cycle.Thus, in order to minimize the total incentive payments and the total energy consumption of the MCS task while meeting the predefined data collection goal, we propose EEMC which intends to select a minimal number of anonymous participants to join in each sensing cycle of the MCS task while ensuring an minimum number of participants returning sensed results. • EMC3 - In this work, we follow the same sensing cycles and incentives assumptions/settings from EEMC; however, given a target region consisting of a set of subareas, the MCS task in this work aims at collecting sensed results covering each subarea of the target region in each sensing cycle (namely full coverage constraint).Thus, in order to minimize the total incentive payments and the total energy consumption of the MCS task under the full coverage constraint, we propose EMC3 which intends to select a minimal number of anonymous participaNts to join in each sensing cycle of the MCS task while ensuring at least one participant returning sensed results from each subarea. • CrowdRecruiter - In this work, we assume each participant is given an equal amount of incentive for joining in all sensing cycles of the MCS task; further, given a target region consisting of a set of subareas, the MCS task aims at collecting sensed results from a predefined percentage of subareas in each sensing cycle (namely probabilistic coverage constraint).Thus, in order to minimize the total incentive payments the probabilistic coverage constraint, we propose CrowdRecruiter which intends to recruit a minimal number of participants for the whole MCS task while ensuring the selected participants returning sensed results from at least a predefined percentage of subareas in each sensing cycle. • CrowdTasker - In this work, we assume each participant is given a varied amount of incentives according to [...]
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Amadori, Kristian. "On Aircraft Conceptual Design : A Framework for Knowledge Based Engineering and Design Optimization." Licentiate thesis, Linköping : Department of Management and Engineering, Linköpings universitet, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11873.
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Nezhadali, Vaheed. "Multi-objective optimization of Industrial robots." Thesis, Linköpings universitet, Maskinkonstruktion, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-113283.
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Industrial robots are the most widely manufactured and utilized type of robots in industries. Improving the design process of industrial robots would lead to further developments in robotics industries. Consequently, other dependant industries would be benefited. Therefore, there is an effort to make the design process more and more efficient and reliable. The design of industrial robots requires studies in various fields. Engineering softwares are the tools which facilitate and accelerate the robot design processes such as dynamic simulation, structural analysis, optimization, control and so forth. Therefore, designing a framework to automate the robot design process such that different tools interact automatically would be beneficial. In this thesis, the goal is to investigate the feasibility of integrating tools from different domains such as geometry modeling, dynamic simulation, finite element analysis and optimization in order to obtain an industrial robot design and optimization framework. Meanwhile, Meta modeling is used to replace the time consuming design steps. In the optimization step, various optimization algorithms are compared based on their performance and the best suited algorithm is selected. As a result, it is shown that the objectives are achievable in a sense that finite element analysis can be efficiently integrated with the other tools and the results can be optimized during the design process. A holistic framework which can be used for design of robots with several degrees of freedom is introduced at the end.
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Smaling, Rudolf M. "System architecture selection in a multi-disciplinary system design optimization framework." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/91788.
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Mahdavi, Babak. "The design of a distributed, object-oriented, component-based framework in multidisciplinary design optimization /." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=79039.
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The Multidisciplinary Design Optimization (MDO) can be defined as a methodology for the design of complex engineering systems where collaboration and abilities to mutually interacting between different disciplines are fundamental. In this thesis, Virtual Aircraft Design and Optimization fRamework (VADOR), a distributed, object-oriented, component-based framework enabling MDO practice at Bombardier Aerospace is introduced. The purpose of the VADOR framework is to enable the seamless integration of commercial and in-house analysis applications in a heterogeneous, distributed computing environment, and allow the management and sharing of the data. The VADOR distributed environment offers visibility to the process, permitting the teams to monitor progress or track changes in design projects and problems. Documentation of the MDO process is vital to ensure clear communication of the process within the team defining it and in the broader design team interacting with it. VADOR is implemented in Java, providing an object-oriented, platform-independent framework. The concepts of design pattern and component-based approach are used along with multi-tiered distributed design to deliver highly modular and flexible architecture. (Abstract shortened by UMI.)
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Lee, Bin Hong Alex. "Empty container logistics optimization : an implementation framework and methods." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90715.
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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 68-70).
Empty container logistics is a huge cost component in an ocean carrier's operations. Managing this cost is important to ensure profitability of the business. This thesis proposes a 3-stage framework to handle empty container logistics with cost management as the objective. The first stage studies the forecasting of laden shipment demand, which provides the empty container supply requirement. Based on the supply needs, the problem of optimizing the fleet size was then addressed by using an inventory model to establish the optimal safety stock level. Simulations were used to understand the sensitivity of safety stock to desired service level. The final stage involves using mathematical programming to optimize repositioning costs incurred by carriers to ship empty containers to places which need them due to trade imbalance. At the same time, costs that are incurred due to leasing and storage are considered. A comparison between just-in-time and pre-emptive replenishment was performed and impact due to uncertainties is investigated. The framework is then implemented in a Decision Support System for an actual ocean carrier and is used to assist the empty container logistics team to take the best course of action in daily operations. The results from the optimizations show that there are opportunities for the carrier to reduce its fleet size and cut empty container logistics related costs.
by Bin Hong Alex Lee.
S.M. in Engineering and Management
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Yazdani, Aliakbar. "Novel Approach to Design, Optimization, and Application of Thermal Batteries and Beyond." Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1617360759548812.
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Li, Rongsha. "Situational awareness framework for risk ranking." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/106961.
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Thesis: S.M., Massachusetts Institute of Technology, School of Engineering, Center for Computational Engineering, Computation for Design and Optimization Program, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 75-76).
Today, organizations are generating large volumes of data. However, the challenge of extracting valuable information from the data has been a large and long-standing problem. Here, we address the problem of quantifying risks and detecting fraud in heterogeneous financial big data. Great financial losses are pressuring institutions to devise innovative solutions for risk and fraud detection. Current approaches in government suffer from issues such as high false positive rates and low adaptability to the continuous evolution of newer fraud. In this thesis, we propose an open and extensible framework called "Situational Awarness FrAamework for RIsk ranking" (SAFARI). SAFARI aims to quantify and rank risk with unlabeled, complex data in the financial world. The framework integrates and analyzes different perspectives of financial data, and extends risk scores for decision makers. SAFARI also utilizes machine learning techniques to learn from examined cases to improve the calculation of risks and adapt to the changing behavior of fraudulent activities. The work includes designing, implementing, testing, extending and evaluating the proposed framework. In the overpayment detection scenario, results show SAFARI can effectively find overpayments with low false positive rates. Furthermore, SAFARI can be extended to assist decision making in a variety of environment thanks to its general applicability.
by Rongsha Li.
S.M.
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Rawat, Sharad. "DEEP LEARNING BASED FRAMEWORK FOR STRUCTURAL TOPOLOGY DESIGN." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1559560543458263.
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Alam, Tariq Rizvi. "Modeling and Design of Betavoltaic Batteries." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/89648.
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The betavoltaic battery is a type of micro nuclear battery that harvests beta emitting radioactive decay energy using semiconductors. The literature results suggest that a better model is needed to design a betavoltaic battery. This dissertation creates a comprehensive model that includes all of the important factors that impact betavoltaic battery output and efficiency.
Recent advancements in micro electro mechanical systems (MEMS) necessitate an onboard miniaturized power source. As these devices are highly functional, longevity of the power source is also preferred. Betavoltaic batteries are a very promising power source that can fulfill these requirements. They can be miniaturized to the size of a human hair. On the other hand, miniaturization of chemical batteries is restricted by low energy density. That is why betavoltaics are a viable option as a power source for sophisticated MEMS devices. They can also be used for implantable medical devices such as pacemakers; for remote applications such as spacecraft, undersea exploration, polar regions, mountains; military equipment; for sensor networks for environmental monitoring; and for sensors embedded in bridges due to their high energy density and long lifetime (up to 100 years).
A betavoltaic battery simulation model was developed using Monte Carlo particle transport codes such as MCNP and PENELOPE whereas many researchers used simple empirical equations. These particle transport codes consider the comprehensive physics theory for electron transport in materials. They are used to estimate the energy deposition and the penetration depth of beta particles in the semiconductors. A full energy spectrum was used in the model to take into account the actual radioactive decay energy of the beta particles. These results were compared to the traditional betavoltaic battery design method of estimating energy deposition and penetration depth using monoenergetic beta average energy. Significant differences in results were observed that have a major impact on betavoltaic battery design. Furthermore, the angular distribution of the beta particles was incorporated in the model in order to take into account the effect of isotropic emission of beta decay. The backscattering of beta particles and loss of energy with angular dependence were analyzed. Then, the drift-diffusion semiconductor model was applied in order to estimate the power outputs for the battery, whereas many researchers used the simple collection probability model neglecting many design parameters. The results showed that an optimum junction depth can maximize the power output. The short circuit current and open circuit voltage of the battery varied with the semiconductor junction depth, angular distribution, and different activities. However, the analysis showed that the analytical results overpredicted the experimental results when self-absorption was not considered. Therefore, the percentage of self-absorption and the source thickness were estimated using a radioisotope source model. It was then validated with the thickness calculated from the specific activity of the radioisotope. As a result, the battery model was improved significantly. Furthermore, different tritiated metal sources were analyzed and the beta fluxes were compared. The optimum source thicknesses were designed to increase the source efficiencies. Both narrow and wide band gap semiconductors for beryllium tritide were analyzed.PHD
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Perrot, Vincent P. (Vincent Paul) 1980. "A design optimization framework for enhanced compressor stability using dynamic system modeling." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/82794.
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Azari, Amin. "Energy Efficient Machine-Type Communications over Cellular Networks : A Battery Lifetime-Aware Cellular Network Design Framework." Licentiate thesis, KTH, Kommunikationssystem, CoS, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-194416.
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Internet of Things (IoT) refers to the interconnection of uniquely identifiable smart devices which enables them to participate more actively in everyday life. Among large-scale applications, machine-type communications (MTC) supported by cellular networks will be one of the most important enablers for the success of IoT. The existing cellular infrastructure has been optimized for serving a small number of long-lived human-oriented communications (HoC) sessions, originated from smartphones whose batteries are charged in a daily basis. As a consequence, serving a massive number of non-rechargeable machine-type devices demanding a long battery lifetime is a big challenge for cellular networks. The present work is devoted to energy consumption modeling, battery lifetime analysis, and lifetime-aware network design for massive MTC services over cellular networks. At first, we present a realistic model for energy consumption of machine devices in cellular connectivity, which is employed subsequently in deriving the key performance indicator, i.e. network battery lifetime. Then, we develop an efficient mathematical foundation and algorithmic framework for lifetime-aware clustering design for serving a massive number of machine devices. Also, by extending the developed framework to non-clustered MTC, lifetime-aware uplink scheduling and power control solutions are derived. Finally, by investigating the delay, energy consumption, spectral efficiency, and battery lifetime tradeoffs in serving coexistence of HoC and MTC traffic, we explore the ways in which energy saving for the access network and quality of service for HoC traffic can be traded to prolong battery lifetime for machine devices. The numerical and simulation results show that the proposed solutions can provide substantial network lifetime improvement and network maintenance cost reduction in comparison with the existing approaches.QC 20161103
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Meaders, John Christian. "An Optimization-Based Framework for Designing Robust Cam-Based Constant-Force Compliant Mechanisms." BYU ScholarsArchive, 2008. https://scholarsarchive.byu.edu/etd/1423.
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Constant-force mechanisms are mechanical devices that provide a near-constant output force over a prescribed deflection range. This thesis develops various optimization-based methods for designing robust constant-force mechanisms. The configuration of the mechanisms that are the focus of this research comprises a cam and a compliant spring fixed at one end while making contact with the cam at the other end. This configuration has proven to be an innovative solution in several applications because of its simplicity in manufacturing and operation. In this work, several methods are introduced to design these mechanisms, and reduce the sensitivity of these mechanisms to manufacturing uncertainties and frictional effects. The mechanism's sensitivity to these factors is critical in small scale applications where manufacturing variations can be large relative to overall dimensions, and frictional forces can be large relative to the output force. The methods in this work are demonstrated on a small scale electrical contact on the order of millimeters in size. The method identifies a design whose output force is 98.20% constant over its operational deflection range. When this design is analyzed using a Monte Carlo simulation the standard deviation in constant force performance is 0.76%. When compared to a benchmark design from earlier research, this represents a 34% increase in constant-force performance, and a reduction from 1.68% in the standard deviation of performance. When this new optimal design is evaluated to reduce frictional effects a design is identifed that shows a 36% reduction in frictional energy loss while giving up, however, 18.63% in constant force.
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Potter, Charles Lee. "A conceptual level framework for wing box structural design and analysis using a physics-based approach." Diss., Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/54940.
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There are many challenges facing the aerospace industry that can be addressed with new concepts, technologies, and materials. However, current design methods make it difficult to include these new ideas early in the design of aircraft. This is especially true in the structures discipline, which often uses weight-based methods based upon statistical regressions of historical data. A way to address this is to use physics-based structural analysis and design to create more detailed structural data. Thus, the overall research objective of this dissertation is to develop a physics-based structural analysis method to incorporate new concepts, technologies, and materials into the conceptual design phase.
The design space of physics-based structural design problem is characterized as highly multimodal with numerous discontinuities; thus, a large number of alternatives must be explored. Current physics-based structural design methods tend to use high fidelity modeling and analysis tools that are computationally expensive. This dissertation proposes a modeling & simulation environment based on classical structural analysis methods. Using classical structural analysis will enable increased exploration of the design space by reducing the overall run time necessary to evaluate one alternative.
The use of physics-based structural optimization using classical structural analysis is tested through experimentation. First the underlying hypotheses are tested in a canonical example by comparing different optimization algorithms ability to locate a global optimum identified through design space exploration. Then the proposed method is compared to a method based on higher fidelity finite element analysis as well as a method based on weight-based empirical data to validate the overall research objective.
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Parno, Matthew David. "A multiscale framework for Bayesian inference in elliptic problems." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65322.
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Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2011.Page 118 blank. Cataloged from PDF version of thesis.
Includes bibliographical references (p. 112-117).
The Bayesian approach to inference problems provides a systematic way of updating prior knowledge with data. A likelihood function involving a forward model of the problem is used to incorporate data into a posterior distribution. The standard method of sampling this distribution is Markov chain Monte Carlo which can become inefficient in high dimensions, wasting many evaluations of the likelihood function. In many applications the likelihood function involves the solution of a partial differential equation so the large number of evaluations required by Markov chain Monte Carlo can quickly become computationally intractable. This work aims to reduce the computational cost of sampling the posterior by introducing a multiscale framework for inference problems involving elliptic forward problems. Through the construction of a low dimensional prior on a coarse scale and the use of iterative conditioning technique the scales are decouples and efficient inference can proceed. This work considers nonlinear mappings from a fine scale to a coarse scale based on the Multiscale Finite Element Method. Permeability characterization is the primary focus but a discussion of other applications is also provided. After some theoretical justification, several test problems are shown that demonstrate the efficiency of the multiscale framework.
by Matthew David Parno.
S.M.
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Hanchate, Narender. "A game theoretic framework for interconnect optimization in deep submicron and nanometer design." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001523.
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Safavi, Edris. "Collaborative Multidisciplinary Design Optimization : A Framework Applied on Aircraft Systems and Industrial Robots." Licentiate thesis, Linköpings universitet, Maskinkonstruktion, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-91292.
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In a product development process, it is crucial to understand and evaluate multiple and synergic aspects of systems such as performance, cost, reliability and safety. In order to improve the foundations for decision-making, this thesis presents methods that are intended to increase the engineering knowledge in the early design phases. In complex products, different systems from a multitude of engineering disciplines have to work tightly together. Collaborative design is defined as a process where a product is designed through the collective and joint efforts of domain experts. Thus, a Collaborative Multidisciplinary Design Optimization (CMDO) process is proposed in the conceptual design phase in order to increase the likelihood of more accurate decisions being taken early on. To enable higher fidelity based CMDO, it is necessary to validate the tools and models utilized. This can be done with so-called low cost demonstrators. The physical demonstrators increase the engineer’s confidence regarding the final product by validating the models as well as revealing many unknowns and thus further increasing the engineering knowledge. The performance of the presented methods is demonstrated with two industrial applications, aircraft conceptual system design and industrial robot design.
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Butler, Brian Jeffrey. "Dynamic Model Creation and Scripting Support in the Horizon Simulation Framework." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/697.
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Dynamic model creation and support for the Lua scripting language was added to the Horizon Simulation Framework used for the verification and validation of system-level requirements. The addition of scripting support allows for subsystem models and their algorithms to be defined using a simpler scripting language, rather than C++. The Luabind library by Rasterbind software is used to expose the C++ algorithms and classes to Lua that are already defined in the framework. Interoperability between Lua and C++ code allows for the ease of use of a scripting language while utilizing the utility classes and functions already created. The dynamic model creation algorithm developed allows for the structure and logic of the simulated system to be defined completely using XML and text files as input to the framework. Dynamic model creation prevents the need to re-compile the framework every time small changes are made and greatly simplifies the changes required to simulate a different model. A runtime analysis shows that using a scripting language does not decrease the performance significantly, while increasing usability and decreasing the time required to set up simulations. Tests where the scripted code uses only classes and function exposed by luabind show that there is virtually no performance decrease when compared to the same algorithms in C++. Performance decreases as more of the algorithm implemented is executed in Lua. An example test scenario that represents the typical use of the framework showed only a minor decrease in performance. The multi-threaded scheduler developed works with the scripting support and allows for modern multi-core or multi-processor computers to be used most efficiently for simulations. This thesis describes the algorithms of dynamic model creation and scripting support, as well as the methodology used to expose C++ code to Lua. This thesis also presents the architecture changes required to support dynamic model creation, scripting support, and multi-threaded scheduling. Finally, runtime results of the added scripting support are presented.
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Meckstroth, Christopher. "Incorporation of Physics-Based Controllability Analysis in Aircraft Multi-Fidelity MADO Framework." University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1575557306181006.
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Ollar, Jonathan. "A multidisciplinary design optimisation framework for structural problems with disparate variable dependence." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/24715.
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Multidisciplinary design optimisation incorporates several disciplines in one integrated optimisation problem. The benefi t of considering all requirements at once rather than in individual optimisations is that synergies between disciplines can be exploited to fi nd superior designs to what would otherwise be possible. The main obstacle for the use of multidisciplinary design optimisation in an industrial setting is the related computational cost which may become prohibitively large. This work is focused on the development of a multidisciplinary design optimisation framework that extends the existing trust-region based optimisation method known as the mid-range approximation method. The main novel contribution is an approach to solving multidisciplinary design optimisation problems using metamodels built in sub-spaces of the design variable space. Each metamodel is built in the sub-space relevant to the corresponding discipline while the optimisation problem is solved in the full design variable space. Since the metamodels are built in a space of reduced dimensionality, the computational budget for building them can be reduced without compromising their quality. Furthermore, a method for efficiently building kriging metamodels is proposed. This is done by means of a two-step hyper parameter tuning strategy. The fi rst step is a line search where the set of tuning parameters is treated as a single variable. The solution of the fi rst step is used in the second step, a gradient based hyper parameter optimisation where partial derivatives are obtained using the adjoint method. The framework is demonstrated on two examples, a multidisciplinary design optimisation of a thin-walled beam section subject to static and impact requirements, and a multidisciplinary design optimisation of an aircraft wing subject to static and bird strike requirements. In both cases the developed technique demonstrates a reduced computational effort compared to what would typically be achieved by existing methods.
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Ghoman, Satyajit Sudhir. "A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23113.
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The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness.The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE.
The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of fitness-driven retention. This strategy capitalizes on the advantages of evolutionary algorithm as well as POD-based reduced order modeling, while overcoming the shortcomings inherent with these techniques. When linked with M3 DOE, this strategy offers a computationally efficient methodology for problems with high level of complexity and a challenging design-space. This newly developed framework is demonstrated for its robustness on a non-conventional supersonic tailless air vehicle wing shape optimization problem.
Ph. D.
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Tohme, Tony. "The Bayesian validation metric : a framework for probabilistic model calibration and validation." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126919.
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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, May, 2020Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 109-114).
In model development, model calibration and validation play complementary roles toward learning reliable models. In this thesis, we propose and develop the "Bayesian Validation Metric" (BVM) as a general model validation and testing tool. We show that the BVM can represent all the standard validation metrics - square error, reliability, probability of agreement, frequentist, area, probability density comparison, statistical hypothesis testing, and Bayesian model testing - as special cases while improving, generalizing and further quantifying their uncertainties. In addition, the BVM assists users and analysts in designing and selecting their models by allowing them to specify their own validation conditions and requirements. Further, we expand the BVM framework to a general calibration and validation framework by inverting the validation mathematics into a method for generalized Bayesian regression and model learning. We perform Bayesian regression based on a user's definition of model-data agreement. This allows for model selection on any type of data distribution, unlike Bayesian and standard regression techniques, that "fail" in some cases. We show that our tool is capable of representing and combining Bayesian regression, standard regression, and likelihood-based calibration techniques in a single framework while being able to generalize aspects of these methods. This tool also offers new insights into the interpretation of the predictive envelopes in Bayesian regression, standard regression, and likelihood-based methods while giving the analyst more control over these envelopes.
by Tony Tohme.
S.M.
S.M. Massachusetts Institute of Technology, Computation for Design and Optimization Program
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Larson, Bradley Jared. "Mathematical Framework for Early System Design Validation Using Multidisciplinary System Models." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3000.
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A significant challenge in the design of multidisciplinary systems (e.g., airplanes, robots, cell phones) is to predict the effects of design decisions at the time these decisions are being made early in the design process. These predictions are used to choose among design options and to validate design decisions. System behavioral models, which predict a system's response to stimulus, provide an analytical method for evaluating a system's behavior. Because multidisciplinary systems contain many different types of components that have diverse interactions, system behavioral models are difficult to develop early in system design and are challenging to maintain as designs are refined. This research develops methods to create, verify, and maintain multidisciplinary system models developed from models that are already part of system design. First, this research introduces a system model formulation that enables virtually any existing engineering model to become part of a large, trusted population of component models from which system behavioral models can be developed. Second, it creates a new algorithm to efficiently quantify the feasible domain over which the system model can be used. Finally, it quantifies system model accuracy early in system design before system measurements are available so that system models can be used to validate system design decisions. The results of this research are enabling system designers to evaluate the effects of design decisions early in system design, improving the predictability of the system design process, and enabling exploration of system designs that differ greatly from existing solutions.
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Cott, Andrew. "An examination of analysis and optimization procedures within a PBSD framework." Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/2318.
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Gates, Nathaniel Spencer. "Combined Trajectory, Propulsion and Battery Mass Optimization for Solar-Regenerative High-Altitude Long-Endurance Aircraft." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/8980.
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This thesis presents the work of two significant projects. In the first project, a suite of benchmark problems for grid energy management are presented which demonstrate several issues characteristic to the dynamic optimization of these systems. These benchmark problems include load following, cogeneration, tri-generation, and energy storage, and each one assumes perfect foresight of the entire time horizon. The Gekko Python package for dynamic optimization is introduced and two different solution methods are discussed and applied to solving these benchmarks. The simultaneous solve mode out-performs the sequential solve mode in each benchmark problem across a wide range of time horizons with increasing resolution, demonstrating the ability of the simultaneous mode to handle many degrees of freedom across a range of problems of increasing difficulty. In the second project, combined optimization of propulsion system design, flight trajectory planning and battery mass optimization is applied to solar-regenerative high-altitude long-endurance (SR-HALE) aircraft through a sequential iterative approach. This combined optimization approach yields an increase of 20.2% in the end-of-day energy available on the winter solstice at 35°N latitude, resulting in an increase in flight time of 2.36 hours. The optimized flight path is obtained by using nonlinear model predictive control to solve flight and energy system dynamics over a 24 hour period with a 15 second time resolution. The optimization objective is to maximize the total energy in the system while flying a station-keeping mission, staying within a 3 km radius and above 60,000 ft. The propulsion system design optimization minimizes the total energy required to fly the optimal path. It uses a combination of blade element momentum theory, blade composite structures, empirical motor and motor controller mass data, as well as a first order motor performance model. The battery optimization seeks to optimally size the battery for a circular orbit. Fixed point iteration between these optimization frameworks yields a flight path and propulsion system that slightly decreases solar capture, but significantly decreases power expended. Fully coupling the trajectory and design optimizations with this level of accuracy is infeasible with current computing resources. These efforts show the benefits of combining design and trajectory optimization to enable the feasibility of SR-HALE flight.
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Ruderman, Alex Michael. "A framework for simulation-based multi-attribute optimum design with improved conjoint analysis." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31811.
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Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010.Committee Chair: Choi, Seung-Kyum; Committee Member: Allen, Janet K.; Committee Member: Paredis, Chris. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Botero, Oscar. "Heterogeneous RFID framework design, analysis and evaluation." Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00714120.
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The Internet of Things paradigm establishes interaction and communication with a huge amount of actors. The concept is not a new-from-scratch one; actually, it combines a vast number of technologies and protocols and surely adaptations of pre-existing elements to offer new services and applications. One of the key technologies of the Internet of Things is the Radio Frequency Identification just abbreviated RFID. This technology proposes a set of solutions that allow tracking and tracing persons, animals and practically any item wirelessly. Considering the Internet of Things concept, multiple technologies need to be linked in order to provide interactions that lead to the implementation of services and applications. The challenge is that these technologies are not necessarily compatible and designed to work with other technologies. Within this context, the main objective of this thesis is to design a heterogeneous framework that will permit the interaction of diverse devices such as RFID, sensors and actuators in order to provide new applications and services. For this purpose in this work, our first contribution is the design and analysis of an integration architecture for heterogeneous devices. In the second contribution, we propose an evaluation model for RFID topologies and an optimization tool that assists in the RFID network planning process. Finally, in our last contribution, we implemented a simplified version of the framework by using embedded hardware and performance metrics are provided as well as the detailed configuration of the test platform
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Kirkpatrick, Brian E. ""Picasso" Interface for Horizon Simulation Framework." DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/372.
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The Horizon Simulation Framework, or HSF, is a modeling and simulation framework compiled from C/C++ source code into a command line program. Picasso is an interface designed to control the input files to Horizon by providing visual tools to create and manipulate the XML files used to define an HSF system of assets, their environment, and other simulation parameters. Picasso also supports the visualization of Horizon output in several different forms, and import mechanics from online space object catalogues.
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Luther, Shaun. "SYSML BASED CUBESAT MODEL DESIGN AND INTEGRATION WITH THE HORIZON SIMULATION FRAMEWORK." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1591.
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This thesis examines the feasibility of substituting the system input script of Cal Poly’s Horizon Simulation Framework (HSF) with a Model Based Systems Engineering (MBSE) model designed with the Systems Modeling Language (SysML). A concurrent student project, SysML Output Interface Creation for the Horizon Simulation Framework, focused on design of the HSF Translator Plugin which converts SysML models to an HSF specific XML format. A SysML model of the HSF test case, Aeolus, was designed. The original Aeolus HSF input script and the translated SysML input script retained the format and dependency structure required by HSF. Both input scripts returned identical results and thus validated the feasibility of linking SysML with HSF through the HSF Translator Plugin. A second SysML model of the Cal Poly CubeSat mission, ExoCube, was also designed and converted into an HSF input script. The ExoCube input script also retained the format and dependency structure required by HSF. This demonstrated that future SysML models can be used in conjunction with the HSF Translator Plugin to create a functional HSF system input script.
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Venkateswaran, Jayashankar. "A unified optimization framework for design of CDMA cellular networks with uplink and downlink rate guarantees." Ann Arbor, Mich. : ProQuest, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3271252.
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Thesis (M.S. in Electrical Engineering)--S.M.U., 2007.Title from PDF title page (viewed Mar. 18, 2008). Source: Dissertation Abstracts International, Volume: 68-06, Section: B, page: 4040. Adviser: Dinesh Rajan. Includes bibliographical references.
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Sredojević, Ranko Radovin. "Bridging the gap : an optimization-based framework for fast, simultaneous circuit & system design space exploration." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/43066.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 107-110).
Design of modern mixed signal integrated circuits is becoming increasingly difficult. Continued MOSFET scaling is approaching the global power dissipation limits while increasing transistor variability, thus requiring careful allocation of power and area resources to achieve increasingly more aggressive performance specifications. In this tightly constrained environment traditional iterative system-to-circuit redesign loop, is becoming inefficient. With complex system architectures and circuit specifications approaching technological limits of the process employed, the designers have less room to margin for the overhead of strict system and circuit design interdependencies. Severely constrained modern mixed IC design can take many iterations to converge in such a design flow. This is an expensive and time consuming process. The situation is particularly acute in high-speed links. As an important building block of many systems (high speed I/O, on-chip communication, ...) power efficiency and area footprint are of utmost importance. Design of these systems is challenging in both system and circuit domain. On one hand system architectures are becoming increasingly complex to provide necessary performance increase. On the other, circuit implementation of these increasingly complicated systems is difficult to achieve under tight power and area budget. To bridge this gap between system and circuit design, we formulate a circuit-to-system optimization-driven framework. It is an equation-based description, powered by a human designer. Provided with equation-based model we use fast optimization tools to quickly scout the available design space. Presence of a designer in the flow is invaluable resource enabling significant saving by simplifying the models to capture only the relevant information and constraining the search space to areas where meaningful solutions might be expected to be found.
(cont) Thus, the computational effort overhead that plagues the simulation-based design space exploration and design optimization is greatly reduced. The flow is powered by a signomial optimization engine. The key challenge is to bring, from the modeling point of view, very different problems such as circuit design and system design into the realm of an optimization engine that can solve them jointly, thus breaking the re-design loop or at least cutting it shorter. Relying on signomial programming is necessary in order to accurately model all the necessary phenomenons that arise in electrical circuits and at system level. For example, defining regions of operation of transistors under polarization conditions can not be modeled accurately with simpler type of equations. Similarly, calculating the effect of filtering to a signal also requires possibility to handle signomial equations. Thus, signomial programming is necessary yet not fully explored and finding suitable formulation might take some experimenting as we will see in this thesis. Signomial programming, as a general non-convex optimization problem, is still an active research area. Most of the solutions proposed so far involve local convexification of the problem in addition to branch & bound type of search. Furthermore, most of the non-convex problems are solved for one particular system of equations, and general methodology that is reliable and efficient is not known. Thus, a big part the work to be presented in this thesis is detailing how to construct a system formulation that the optimization engine can solve efficiently and reliably. We tested different formulations and their performance measured in terms of parsing and solving speed and accuracy. From these tests we motivate and explain how a series of transformations we introduce improve our formulation and arrive to a well-behaved and reliable form. We show how to apply our design flow in high-speed link design.
(cont) By restructuring the traditional design flow we derive system and circuit abstractions. These sub-problems are interfaced through a set of well defined interface variables, which enables code level separation of problem descriptions, thus building a modular and easy to read and maintain system and circuit model. Finally we develop a set of scripts to automate formulating parametrized system level description. We explain how our transformations influence the speed of this process as well as the size of the model produced.
by Ranko Sredojević.
S.M.
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Schwalbach, Marc [Verfasser], and Nicolas R. [Akademischer Betreuer] Gauger. "An Efficient CAD-Based Multidisciplinary Optimization Framework for Turbomachinery Design / Marc Schwalbach ; Betreuer: Nicolas R. Gauger." Kaiserslautern : Technische Universität Kaiserslautern, 2021. http://d-nb.info/1228334285/34.
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Dowling, Alexander W. "An Equation-based Framework for Large-Scale Flowsheet Optimization and Applications for Oxycombustion Power System Design." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/568.
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Over the past thirty years, flowsheet optimization methods have evolved from “black box” approaches to sophisticated equation-oriented methods for simultaneous flowsheet convergence and optimization. This thesis explores the next generation of flowsheet optimization tools that leverage completely open models (with exact first and second derivatives) and utilizes start-of-theart nonlinear programming (optimization) solvers. A five part framework is proposed in this thesis: 1. Embedded cubic equation of state thermodynamic models with complementarity constraints to accommodate vanishing and reappearing phases 2. Simultaneous heat integration and process optimization using the pinch location method 3. Aggregate short-cut and rigorous tray-by-tray distillation models 4. Steam cycle equipment (e.g., turbine) and boiler models 5. Trust region optimization algorithm to incorporate models with expensive derivatives into the equations-based framework A systematic initialization routine based on model refinement and multistart procedure are also presented as practical alternatives to global optimization. Complementarity constraints are used throughout the framework to model switches, such as vanishing phases. Degeneracy Hunter, an algorithm that identifies irreducible sets of degenerate constraints (i.e., constraints with a rank deficient Jacobian) is proposed and used to refine the models. The framework is demonstrated in a series of case studies related to the design of oxycombustion power systems with CO2 capture. Two case studies focus on the simultaneous optimization of gases separation systems and their accompanying multistream heat exchangers. In one of these case studies, the optimization procedure identifies common air separation unit configurations with comparable specific energy requirements to industrial designs. The framework is also used to optimize regenerate Rankine cycles, where steam flowrates from nine extraction points for boiler feedwater heating are considered as optimization variables. This allows for waste heat from compression to the completely integrated into the steam cycle. Steam table lookups (without derivatives) are incorporated using reduced models and a trust region optimization algorithm.
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Usan, Massimo 1967. "Automotive component product development enhancement through multi-attribute system design optimization in an integrated concurrent engineering framework." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34814.
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Thesis (S.M.)--Massachusetts Institute of Technology, System Design & Management Program, 2005.Includes bibliographical references (p. 211-218).
Automotive industry is facing a tough period. Production overcapacity and high fixed costs constrain companies' profits and challenge the very same existence of some corporations. Strangulated by the reduced cash availability and petrified by the organizational and products' complexity, companies find themselves more and more inadequate to stay in synch with the pace and the rate of change of consumers' and regulations' demands. To boost profits, nearly everyone pursue cost cutting. However, aggressive cost cutting as the sole approach to fattening margins results invariably in a reduction of operational capabilities which is likely to result in a decline in sales volume that leads to further cost reductions in a continuous death spiral. Long-term profitable growth requires, instead, a continuous flow of innovative products and processes. The focus should be, therefore, shifted from cost reduction to increased throughput. Automotive companies need to change their business model, morphing into new organizational entities based on systems thinking and change, which are agile and can swiftly adapt to the new business environment. The advancement of technology and the relentless increase in computing power will provide the necessary means for this radical transformation. This transformation cannot happen if the Product Development Process (PDP) does not break the iron gate of cycle time-product cost-development expenses-reduced product performance that constrains it. A new approach to PD should be applied to the early phases, where the leverage is higher, and should be targeted to dramatic reduction of the time taken to perform design iterations, which, by taking 50-70% of the total development time, are a burden of today's practice. Multi-disciplinary Design
(cont.) Analysis and Optimization, enabled by an Integrated Concurrent Engineering virtual product development framework has the required characteristics and the potential to respond to today's and tomorrow's automotive challenges. In this new framework, the product or system is not defined by a rigid CAD model which is then manipulated by product team engineers, but by a parametric flexible architecture handled by optimization and analysis software, with limited user interaction. In this environment, design engineers govern computer programs, which automatically select appropriately combinations of geometry parameters and drive seamlessly the analyses software programs (structural, fluid dynamic, costing, etc) to compute the system's performance attributes. Optimization algorithms explore the design space, identifying the Pareto optimal set of designs that satisfy the multiple simultaneous objectives they are given and at the same time the problem's constraints. Examples of application of the MDO approach to automotive systems are multiplying. However, the number of disciplines and engineering aspects considered is still limited to few (two or three) thus not exploiting the full potential the approach deriving from multi-disciplinarity. In the present work, a prototype of an Enhanced Development Framework has been set up for a particular automotive subsystem: a maniverter (a combination of exhaust manifold and catalytic converter) for internal combustion engines ...
by Massimo Usan.
S.M.
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Aithala, Karkada Nagesha. "A Collaborative Computational Framework for Multidisciplinary and Reliability-based Analysis and Optimization Using SORCER." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1316463759.
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Ran, Hongjun. "A Framework for the Determination of Weak Pareto Frontier Solutions under Probabilistic Constraints." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/14511.
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A framework is proposed that combines separately developed multidisciplinary optimization, multi-objective optimization, and joint probability assessment methods together but in a decoupled way, to solve joint probabilistic constraint, multi-objective, multidisciplinary optimization problems that are representative of realistic conceptual design problems of design alternative generation and selection. The intent here is to find the Weak Pareto Frontier (WPF) solutions that include additional compromised solutions besides the ones identified by a conventional Pareto frontier. This framework starts with constructing fast and accurate surrogate models of different disciplinary analyses. A new hybrid method is formed that consists of the second order Response Surface Methodology (RSM) and the Support Vector Regression (SVR) method. The three parameters needed by SVR to be pre-specified are automatically selected using a modified information criterion based on model fitting error, predicting error, and model complexity information. The model predicting error is estimated inexpensively with a new method called Random Cross Validation. This modified information criterion is also used to select the best surrogate model for a given problem out of the RSM, SVR, and the hybrid methods. A new neighborhood search method based on Monte Carlo simulation is proposed to find valid designs that satisfy the deterministic constraints and are consistent for the coupling variables featured in a multidisciplinary design problem, and at the same time decouple the three loops required by the multidisciplinary, multi-objective, and probabilistic features. Two schemes have been developed. One scheme finds the WPF by finding a large enough number of valid design solutions such that some WPF solutions are included in those valid solutions. Another scheme finds the WPF by directly finding the WPF of each consistent design zone. Then the probabilities of the PCs are estimated, and the WPF and corresponding design solutions are found. Various examples demonstrate the feasibility of this framework.
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Johnson, Alexander W. "CubeSat Astronomy Mission Modeling Using the Horizon Simulation Framework." DigitalCommons@CalPoly, 2019. https://digitalcommons.calpoly.edu/theses/2067.
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The CubeSat Astronomy Network is a proposed system of multiple CubeSat spacecraft capable of performing follow-up observations of astronomical targets of interest. The system is intended to serve as a space-borne platform that can complement existing systems utilized for astronomical research by undergraduate and high school students. Much research and development work has been performed to develop model-based system engineering methodologies and products for CubeSat missions, including the Horizon Simulation Framework. The Horizon Simulation Framework enables the development of system models using the Extended Markup Language (XML), and its simulation program can generate system simulations over model-specified timespans. System requirements and constraints, as well as subsystem dependencies and functions, can also be directly specified in these models. Previous work using the framework has been performed to characterize “day-in-the-life” operations for Earth-observing spacecraft. A similar goal is intended for modeling the CubeSat Astronomy Network: simulating mission operations during nominal conditions to validate system and subsystem requirements. By developing this model, system and subsystem requirements derived in the course of preliminary design for the Network can be analyzed, modelled, and evaluated for feasibility. These results can then be used to inform design decisions related to system architecture and concept of operations at the early stages of design, while the models themselves can grow and mature alongside project development and be re-used for future design work.
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Khiabani, Amir, and Alanis Daniel Acebo. "Cooling Fan Optimization for Heavy Electrified Vehicles : A study on performance and noise." Thesis, KTH, Flygdynamik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280145.
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Vehicle electrification plays a significant role in the effort to reduce the environmental impact of the automotive industry. Scania is one of the leading manufacturers ofheavy vehicles which is currently moving towards a sustainable transport system by manufacturing a new generation of heavy vehicles powered by batteries. Oneof the major concerns with these vehicles is related to the noise generated by the electric axial fans used in the cooling system. This project was conducted with thepurpose of investigating the factors that positively affect both noise and performance in the electric fans. Based on two different blade design methods and several noisecontrol techniques, 11 fan models were developed. The fan models created with design method 1 are equipped with cambered-plate blades, while the models madewith design method 2 consist of airfoil-shaped blades. Moreover, the performance of these models was analyzed by using theoretical methods and Computational FluidDynamics (CFD). In addition, two empirical approaches were used to estimate the acoustic energy emitted by the fan models. Furthermore, the developed modelswere compared with two commercially available fans. It was found that both design methods provide similar performance in low pressure differences. On the other hand,the efficiency and acoustic energy are influenced by the choice of the noise control methods.Fordonselektrifiering har en väsentlig roll i arbetet med att minska bilindustrins miljöpåverkan. Scania är en av de ledande tillverkarna av tunga fordon som för närvarandegår mot ett hållbart transportsystem, genom att tillverka en ny generation tunga fordon drivna med batterier. Ett stort bekymmer med dessa fordon är relaterattill det ljud som genereras av de elektriska axialfläktarna som används i kylsystemet. Detta projekt genomfördes i syfte till att undersöka de faktorer som positivtpåverkar både buller och prestanda hos de elektriska fläktarna. Baserat på två olika bladdesignmetoder och flera brusstyrningstekniker, utvecklades 11 fläktmodeller.Fläktmodellerna som är utformade med konstruktionsmetod 1 är utrustade med krökformade plattor, medan modellerna som skapades med designmetod 2 bestårav vingprofil blad. Dessutom analyserades prestandan för dessa modeller med användning av teoretiska metoder och strömningsmekaniska beräkningar. Ytterligaretvå empiriska tillvägagångssätt användes för att uppskatta den akustiska energin som släppts ut av fläktmodellerna. Utöver det jämfördes de utvecklade modellernamed två kommersiellt tillgängliga fläktar. Detta visade att båda konstruktionsmetoderna resulterar i liknande prestanda vid lågtrycksskillnader, däremot påverkasverkningsgraden och den akustiska energin av valet av brusstyrningsmetoder.
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Li, Huaxia. "An integrated multibody dynamics computational framework for design optimization of wind turbine drivetrains considering wind load uncertainty." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2240.
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The objective of this study is to develop an integrated multibody dynamics computational framework for the deterministic and reliability-based design optimization of wind turbine drivetrains to obtain an optimal wind turbine gear design that ensures a target reliability under wind load and gear manufacturing uncertainties. Gears in wind turbine drivetrains are subjected to severe cyclic loading due to variable wind loads that are stochastic in nature. Thus, the failure rate of drivetrain systems is reported to be relatively higher than the other wind turbine components. It is known in wind energy industry that improving reliability of drivetrain designs is one of the key issues to make wind energy competitive as compared to fossil fuels. Furthermore, a wind turbine is a multi-physics system involving random wind loads, rotor blade aerodynamics, gear dynamics, electromagnetic generator and control systems. This makes an accurate prediction of product life of drivetrains challenging and very limited studies have been carried out regarding design optimization including the reliability-based design optimization (RBDO) of geared systems considering wind load and manufacturing uncertainties.
In order to address these essential and challenging issues on design optimization of wind turbine drivetrains under wind load and gear manufacturing uncertainties, the following issues are discussed in this study: (1) development of an efficient numerical procedure for gear dynamics simulation of complex multibody geared systems based on the multi-variable tabular contact search algorithm to account for detailed gear tooth contact geometry with profile modifications or surface imperfections; (2) development of an integrated multibody dynamics computational framework for deterministic and reliability-based design optimization of wind turbine drivetrains using the gear dynamics simulation software developed in (1) and RAMDO software by incorporating wide spatiotemporal wind load uncertainty model, pitting gear tooth contact fatigue model, and rotor blade aerodynamics model using NREL AeroDyn/FAST; and (3) deterministic and reliability-based design optimization of wind turbine drivetrain to minimize total weight of a drivetrain system while ensuring 20-year reliable service life with wind load and gear manufacturing uncertainties using the numerical procedure developed in this study.
To account for the wind load uncertainty, the joint probability density function (PDF) of 10-minute mean wind speed (V₁₀) and 10-minute turbulence intensity (I₁₀) is introduced for wind turbine drivetrain dynamics simulation. To consider wide spatiotemporal wind uncertainty (i.e., wind load uncertainty for different locations and in different years), uncertainties of all the joint PDF parameters of V₁₀, I₁₀ and copula are considered, and PDF for each parameter is identified using 249 sets of wind data. This wind uncertainty model allows for the consideration of a wide range of probabilistic wind loads in the contact fatigue life prediction. For a given V₁₀ and I₁₀ obtained from the stochastic wind model, the random time-domain wind speed data is generated using NREL TurbSim, and then inputted into NREL FAST to perform the aerodynamic simulation of rotor blades to predict the transmitted torque and speed of the main shaft of the drivetrain that are sent to the multibody gear dynamics simulation as an input.
In order to predict gear contact fatigue life, a high-fidelity gear dynamics simulation model that considers the detailed gear contact geometry as well as the mesh stiffness variation needs to be developed to find the variability of maximum contact stresses under wind load uncertainty. This, however, leads to a computationally intensive procedure. To eliminate the computationally intensive iterative online collision detection algorithm, a numerical procedure for the multibody gear dynamics simulation based on the tabular contact search algorithm is proposed. Look-up contact tables are generated for a pair of gear tooth profiles by the contact geometry analysis prior to the dynamics simulation and the contact points that fulfill the non-conformal contact condition and mesh stiffness at each contact point are calculated for all pairs of gears in the drivetrain model.
This procedure allows for the detection of gear tooth contact in an efficient manner while retaining the precise contact geometry and mesh stiffness variation in the evaluation of mesh forces, thereby leading to a computationally efficient gear dynamics simulation suited for the design optimization procedure considering wind load uncertainty. Furthermore, the accuracy of mesh stiffness model introduced in this study and transmission error of gear tooth with tip relief are discussed, and a wind turbine drivetrain model developed using this approach is validated against test data provided in the literature.
The gear contact fatigue life is predicted based on the gear tooth pitting fatigue criteria and is defined by the sum of the number of stress cycles required for the fatigue crack initiation and the number required for the crack to propagate from the initial to the critical crack length based on Paris-Erdogan equation for Mode II fracture. All the above procedures are integrated into the reliability-based design optimization software RAMDO for design optimization and reliability analysis of wind turbine drivetrains under wind load and manufacturing uncertainties.
A 750kW GRC wind turbine gearbox model is used to perform the design optimization and the reliability analysis. A deterministic design optimization (DDO) is performed first using an averaged joint PDF of wind load to ensure a 20-year service life. To this end, gear face width and tip relief (profile modification) are selected as design variables and optimized such that 20-year fatigue life is ensured while minimizing the total weight of drivetrains. It is important to notice here that an increase in face width leads to a decrease in the fatigue damage, but an increase in total weight. On the other hand, the tip relief has almost no effect on the total weight, but it has a major impact on the fatigue damage. It is shown in this study that the optimum tip relief allows for lowering the greatest maximum shear stresses on the tooth surface without relying heavily on face width widening to meet the 20-year fatigue life constraint and it leads to reduction of total drivetrain weight by 8.4%. However, if only face width is considered as design variable, total weight needs to be increased by 4.7% to meet the 20-year fatigue life constraint.
Furthermore, the reliability analysis at the DDO optimum design is carried out considering the large spatiotemporal wind load uncertainty and gear manufacturing uncertainty. Local surrogate models at DDO optimum design are generated using Dynamic Kriging method in RAMDO software to evaluate the gear contact fatigue damage. 49.5% reliability is obtained at the DDO optimum design, indicating that the probability of failure is 50.5%, which is as expected for the DDO design. RBDO is, therefore, necessary to further improve the reliability of the wind turbine drivetrain.
To this end, the sampling-based reliability analysis is carried out to evaluate the probability of failure for each design using the Monte Carlo Simulation (MCS) method. However, the use of a large number of MCS sample points leads to a large number of contact fatigue damage evaluation time using the 10-minute multibody drivetrain dynamics simulation, resulting in the RBDO calculation process being computational very intensive. In order to overcome the computational difficulty resulting from the use of high-fidelity wind turbine drivetrain dynamics simulation, intermediate surrogate models are created prior to the RBDO process using the Dynamic Kriging method in RAMDO and used throughout the entire RBDO iteration process. It is demonstrated that the RBDO optimum obtained ensures the target 97.725 % reliability (two sigma quality level) with only 1.4 % increase in the total weight from the baseline design with 8.3 % reliability. This result clearly indicates the importance of incorporating the tip relief as a design variable that prevents larger increase in the face width causing an increase in weight. This, however, does not mean that a larger tip relief is always preferred since an optimum tip relief amount depends on stochastic wind loads and an optimum tip relief cannot be found deterministically. Furthermore, accuracy of the RBDO optimum obtained using the intermediate surrogate models is verified by the reliability analysis at the RBDO optimum using the local surrogate models. It is demonstrated that the integrated design optimization procedure developed in this study enables the cost effective and reliable design of wind turbine drivetrains.
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Benjamin, Alex (Alex Robert). "The (travel) times they are a changing : a computational framework for the diagnosis of non-alcoholic fatty liver disease (NAFLD)." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111506.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2017.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 57-61).
We propose and validate a non-invasive method to diagnose Non-Alcoholic Fatty Liver Disease (NAFLD). The proposed method is based on two fundamental concepts: 1) the speed of sound in a fatty liver is lower than that in a healthy liver and 2) the quality of an ultrasound image is maximized when the beamforming speed of sound used in image formation matches the speed in the medium under examination. The proposed method uses image brightness and sharpness as quantitative image-quality metrics to predict the true sound speed and capture the effects of fat infiltration, while accounting for the transmission through subcutaneous fat. Validation using nonlinear acoustic simulations indicated the proposed method's ability to predict the speed of sound within a medium under examination with little sensitivity to the transducer's frequency (errors less than 2%). Additionally, ex vivo testing on sheep liver, mice livers, and tissue-mimicking phantoms indicated the method's ability to predict the true speed of sound with errors less than 0.5% (despite the presence of subcutaneous fat) and its ability to quantify the relationship between fat content and speed of sound. Additionally, this work starts to create a framework which allows for the determination of the spatial distribution of the longitudinal speed of sound, thereby providing a promising method for diagnosing NAFLD over time.
by Alex Benjamin.
S.M.
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Barceló, Adrover Salvador. "An advanced Framework for efficient IC optimization based on analytical models engine." Doctoral thesis, Universitat de les Illes Balears, 2013. http://hdl.handle.net/10803/128968.
Full textAbstract:
En base als reptes sorgits a conseqüència de l'escalat de la tecnologia, la present tesis desenvolupa i analitza un conjunt d'eines orientades a avaluar la sensibilitat a la propagació d'esdeveniments SET en circuits microelectrònics. S'han proposant varies mètriques de propagació de SETs considerant l'impacto dels emmascaraments lògic, elèctric i combinat lògic-elèctric. Aquestes mètriques proporcionen una via d'anàlisi per quantificar tant les regions més susceptibles a propagar SETs com les sortides més susceptibles de rebre'ls. S'ha desenvolupat un conjunt d'algorismes de cerca de camins sensibilitzables altament adaptables a múltiples aplicacions, un sistema lògic especific i diverses tècniques de simplificació de circuits. S'ha demostrat que el retard d'un camí donat depèn dels vectors de sensibilització aplicats a les portes que formen part del mateix, essent aquesta variació de retard comparable a la atribuïble a les variacions paramètriques del proces.En base a los desafíos surgidos a consecuencia del escalado de la tecnología, la presente tesis desarrolla y analiza un conjunto de herramientas orientadas a evaluar la sensibilidad a la propagación de eventos SET en circuitos microelectrónicos. Se han propuesto varias métricas de propagación de SETs considerando el impacto de los enmascaramientos lógico, eléctrico y combinado lógico-eléctrico. Estas métricas proporcionan una vía de análisis para cuantificar tanto las regiones más susceptibles a propagar eventos SET como las salidas más susceptibles a recibirlos. Ha sido desarrollado un conjunto de algoritmos de búsqueda de caminos sensibilizables altamente adaptables a múltiples aplicaciones, un sistema lógico especifico y diversas técnicas de simplificación de circuitos. Se ha demostrado que el retardo de un camino dado depende de los vectores de sensibilización aplicados a las puertas que forman parte del mismo, siendo esta variación de retardo comparable a la atribuible a las variaciones paramétricas del proceso.
Based on the challenges arising as a result of technology scaling, this thesis develops and evaluates a complete framework for SET propagation sensitivity. The framework comprises a number of processing tools capable of handling circuits with high complexity in an efficient way. Various SET propagation metrics have been proposed considering the impact of logic, electric and combined logic-electric masking. Such metrics provide a valuable vehicle to grade either in-circuit regions being more susceptible of propagating SETs toward the circuit outputs or circuit outputs more susceptible to produce SET. A quite efficient and customizable true path finding algorithm with a specific logic system has been constructed and its efficacy demonstrated on large benchmark circuits. It has been shown that the delay of a path depends on the sensitization vectors applied to the gates within the path. In some cases, this variation is comparable to the one caused by process parameters variations.
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Yost, Morgan. "An Iteration on the Horizon Simulation Framework to Include .NET and Python Scripting." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1607.
Full textAbstract:
Modeling and Simulation is a crucial element of the aerospace engineering design pro- cess because it allows designers to thoroughly test their solution before investing in the resources to create it. The Horizon Simulation Framework (HSF) v3.0 is an aerospace modeling and simulation tool that allows the user to verify system level requirements in the early phases of the design process. A low fidelity model of the system that is created by the user is exhaustively tested within the built-in Day-in-the-Life simulator to provide useful information in the form of failed requirements, system bottle necks and leverage points, and potential schedules of operations. The model can be stood up quickly with Extended Markup Language (XML) input files or can be customly created with Python Scripts that interact with the framework at runtime. The goal of the work presented in this thesis is to progress HSF from v2.3 to v3.0 in order to take advantage of current software development technologies. This includes converting the codebase from C++ and Lua scripting to C♯ and Python Scripting. The particulars of the considerations, benefits, and implementation of the new framework are discussed in detail. The simulation data and performance run time of the new framework were compared to that of the old framework. The new framework was found to produce similar data outputs with a faster run time.
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Häll, Carl Henrik. "A Framework for Evaluation and Design of an Integrated Public Transport System." Licentiate thesis, Linköping University, Linköping University, Department of Science and Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7519.
Full textAbstract:
Operators of public transport always try to make their service as attractive as possible, to as many persons as possible and in a so cost effective way as possible. One way to make the service more attractive, especially to elderly and disabled, is to offer door-to-door transportation. The cost for the local authorities to provide this service is very high and increases every year.
To better serve the needs of the population and to reduce the cost for transportation of elderly and disabled, public transportation systems are evolving towards more flexible solutions. One such flexible solution is a demand responsive service integrated with a fixed route service, together giving a form of flexible public transport system. The demand responsive service can in such a system be used to carry passengers from their origin to a transfer location to the fixed route network, and/or from the fixed route network to their destination.
This thesis concerns the development of a framework for evaluation and design of such an integrated public transport service. The framework includes a geographic information system, optimization tools and simulation tools. This framework describes how these tools can be used in combination to aid the operators in the planning process of an integrated service. The thesis also presents simulations made in order to find guidelines of how an integrated service should be designed. The guidelines are intended to help operators of public transport to implement integrated services and are found by evaluating the effects on availability, travel time, cost and other service indicators for variations in the design and structure of the service.
In a planning system for an integrated public transport service, individual journeys must in some way be scheduled. For this reason the thesis also presents an exact optimization model of how journeys should be scheduled in this kind of service.
Report code: LiU-TEK-LIC- 2006:38
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Collins, Kyle Brian. "A multi-fidelity framework for physics based rotor blade simulation and optimization." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26481.
Full textAbstract:
Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009.Committee Co-Chair: Dr. Dimitri Mavris; Committee Co-Chair: Dr. Lakshmi N. Sankar; Committee Member: Dr. Daniel P. Schrage; Committee Member: Dr. Kenneth S. Brentner; Committee Member: Dr. Mark Costello. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Pröbstl, Alma [Verfasser], Samarjit [Akademischer Betreuer] Chakraborty, Andreas [Gutachter] Jossen, Qi [Gutachter] Zhu, and Samarjit [Gutachter] Chakraborty. "Multi-Scale System Design and Management for Battery Health Optimization / Alma Pröbstl ; Gutachter: Andreas Jossen, Qi Zhu, Samarjit Chakraborty ; Betreuer: Samarjit Chakraborty." München : Universitätsbibliothek der TU München, 2020. http://d-nb.info/1220320706/34.
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Al-Naeem, Tariq Abdullah Computer Science & Engineering Faculty of Engineering UNSW. "A quality-driven decision-support framework for architecting e-business applications." Awarded by:University of New South Wales. Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/23419.
Full textAbstract:
Architecting e-business applications is a complex design activity. This is mainly due to the numerous architectural decisions to be made, including the selection of alternative technologies, software components, design strategies, patterns, standards, protocols, platforms, etc. Further complexities arise due to the fact that these alternatives often vary considerably in their support for different quality attributes. Moreover, there are often different groups of stakeholders involved, with each having their own quality goals and criteria. Furthermore, different architectural decisions often include interdependent alternatives, where the selection of one alternative for one particular decision impacts the selections to be made for alternatives from other different decisions. There have been several research efforts aiming at providing sufficient mechanisms and tools for facilitating the architectural evaluation and design process. These approaches, however, address architectural decisions in isolation, where they focus on evaluating a limited set of alternatives belonging to one architectural decision. This has been the primary motivation behind the development of the Architectural DEcision-Making Support (ADEMS) framework, which basically aims at supporting stakeholders and architects during the architectural decision-making process by helping them determining a suitable combination of architectural alternatives. ADEMS framework is an iterative process that leverages rigorous quantitative decision-making techniques available in the literature of Management Science, particularly Multiple Attribute Decision-Making (MADM) methods and Integer Programming (IP). Furthermore, due to the number of architectural decisions involved as well as the variety of available alternatives, the architecture design space is expected to be huge. For this purpose, a query language has been developed, known as the Architecture Query Language (AQL), to aid architects in exploring and analyzing the design space in further depth, and also in examining different ???what-if??? architectural scenarios. In addition, in order to support leveraging ADEMS framework, a support tool has been implemented for carrying out the sophisticated set of mathematical computations and comparisons of the large number of architectural combinations, which might otherwise be hard to conduct using manual techniques. The primary contribution of the tool is in its help to identify, evaluate, and rank all potential combinations of alternatives based on their satisfaction to quality preferences provided by the different stakeholders. Finally, to assess the feasibility of ADEMS, three different case studies have been conducted relating to the architectural evaluation of different e-business and enterprise applications. Results obtained for the three case studies were quite positive as they showed an acceptable accuracy level for the decisions recommended by ADEMS, and at a reasonable time and effort costs for the different system stakeholders.