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Publication Metadata only A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions(Elsevier, 2017) N/A; N/A; Department of Industrial Engineering; Kabatepe, Bora; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956Electric vehicles (EV) are emerging as a mobility solution to reduce emissions in the transportation sector. The studies environmental impact analysis of EVs in the literature are based on the average energy mix or pre-defined generation scenarios and construct policy recommendations with a cost minimization objective. However, the environmental performance of EVs depends on the source of the marginal electricity provided to the grid and single objective models do not provide a thorough analysis on the economic and environmental impacts of EVs. In this paper, these gaps are addressed by a four step methodology that analyzes the effects of EVs under different charging and market penetration scenarios. The methodology includes a bi-criteria optimization model representing the electricity market operations. The results from a real-life case analysis show that EVs decrease costs and emissions significantly compared to conventional vehicles.Publication Metadata only A blind fractionally spaced equalization algorithm with global convergence(IEEE, 2007) Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 41624In this article we present a fractionally spaced extension of the SubGradient based Blind equalization Algorithm (SGBA). The basic features of the proposed algorithm are the non-linear constraint on the search vector and the selection of the weighting and step size applied to the search vector. It is proven that the algorithm is globally convergent to a perfect equalization point under the well known equalizability conditions for the fractionally spaced setting. The simulation results provided at the end of the article illustrates the relative merit of the proposed algorithm in comparison to the state of the art algorithms.Publication Metadata only A CAM-based path generation method for rapid prototyping applications(Springer London Ltd, 2011) N/A; Department of Mechanical Engineering; Lazoğlu, İsmail; N/A; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); N/A; College of Engineering; N/A; 179391A wide range of rapid prototyping (RP) methods are available commercially. Even though the hardware and production materials of these RP methods differ, their production techniques are built on the same idea: layer-by-layer material additive manufacturing. Whatever the material is used, it is deposited, vulcanized, or melted by following a pre-determined path, and each layer is stowed on the previous one to create the 3D model which is designed by using a computer-aided design program. The path which is followed while creating the model is very crucial. In this paper, a novel idea for path generation for RP processes is introduced. This new method is based on computer numerical controlled milling operation. Although the RP process and the milling process are completely opposite of each other since one of them is an additive and the other one is a subtractive method, the paths which are followed for these operations are very similar and based on the same idea: The progress goes on layer by layer. In this novel method, cutter location source files are used to create paths for RP processes. Examples of the prototypes produced by using this new method are also presented in the paper.Publication Metadata only A class of bounded component analysis algorithms for the separation of both independent and dependent sources(IEEE-inst Electrical Electronics Engineers inc, 2013) Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 41624Bounded Component analysis (BCa) is a recent approach which enables the separation of both dependent and independent signals from their mixtures. in this approach, under the practical source boundedness assumption, the widely used statistical independence assumption is replaced by a more generic domain separability assumption. This article introduces a geometric framework for the development of Bounded Component analysis algorithms. Two main geometric objects related to the separator output samples, namely Principal Hyper-Ellipsoid and Bounding Hyper-Rectangle, Are introduced. the maximization of the volume ratio of these objects, and its extensions, Are introduced as relevant optimization problems for Bounded Component analysis. the article also provides corresponding iterative algorithms for both real and complex sources. the numerical examples illustrate the potential advantage of the proposed BCa framework in terms of correlated source separation capability as well as performance improvement for short data records.Publication Open Access A comparative study on GaSb epilayers grown on nominal and vicinal Si(100) substrates by molecular beam epitaxy(Institute of Physics (IOP) Publishing, 2020) Arpapay, Burcu; Suyolcu, Y. Eren; van Aken, Peter A.; Gülgün, Mehmet Ali; Serincan, Uğur; Çorapçıoğlu, Gülcan; n2STAR-Koç University Nanofabrication and Nanocharacterization Center for Scientifc and Technological Advanced ResearchThe direct growth of GaSb buffer layers on Si substrates is attracting considerable interest in the integration of group III-Sb based device structures on lower-cost Si substrates. Here, we present the effect of various growth steps on the defect types and defect density that are crucial for advancing high crystal quality GaSb buffer layer on nominal/vicinal Si substrate. As a growth step, the applied thermal annealing at an intermediate step provided a decrease in the threading dislocation (TD) density down to 1.72 x 10(8) cm(-2), indicating a more effective method compared to post-growth annealing. Additionally, the importance of period number and position of GaSb/AlSb superlattice layers inserted in GaSb epilayers is demonstrated. In the case of the GaSb epilayers grown on vicinal substrates, the APB density as low as 0.06 mu m(-1) and TD density of 1.98 x 10(8) cm(-2) were obtained for the sample grown on 4 degrees miscut Si(100) substrate.Publication Open Access A computational multicriteria optimization approach to controller design for pysical human-robot interaction(Institute of Electrical and Electronics Engineers (IEEE), 2020) Tokatlı, Ozan; Patoğlu, Volkan; Department of Mechanical Engineering; Aydın, Yusuf; Başdoğan, Çağatay; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 125489Physical human-robot interaction (pHRI) integrates the benefits of human operator and a collaborative robot in tasks involving physical interaction, with the aim of increasing the task performance. However, the design of interaction controllers that achieve safe and transparent operations is challenging, mainly due to the contradicting nature of these objectives. Knowing that attaining perfect transparency is practically unachievable, controllers that allow better compromise between these objectives are desirable. In this article, we propose a multicriteria optimization framework, which jointly optimizes the stability robustness and transparency of a closed-loop pHRI system for a given interaction controller. In particular, we propose a Pareto optimization framework that allows the designer to make informed decisions by thoroughly studying the tradeoff between stability robustness and transparency. The proposed framework involves a search over the discretized controller parameter space to compute the Pareto front curve and a selection of controller parameters that yield maximum attainable transparency and stability robustness by studying this tradeoff curve. The proposed framework not only leads to the design of an optimal controller, but also enables a fair comparison among different interaction controllers. In order to demonstrate the practical use of the proposed approach, integer and fractional order admittance controllers are studied as a case study and compared both analytically and experimentally. The experimental results validate the proposed design framework and show that the achievable transparency under fractional order admittance controller is higher than that of integer order one, when both controllers are designed to ensure the same level of stability robustness.Publication Metadata only A dual-mode quadruple precision floating-point divider(IEEE, 2006) N/A; N/A; N/A; İşseven, Aytunç; Akkaş, Ahmet; Master Student; Faculty Member; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/AMany scientific applications require more accurate computations than double precision or double-extended precision floating-point arithmetic. This paper presents the design of a dual-mode quadruple precision floating-point divider that also supports two parallel double precision division. A radix- 4 SRT division algorithm with minimal redundancy is used to implement the dual-mode quadruple precision floating-point divider. To estimate area and worst case delay, a double, a quadruple, a dual-mode double, and a dual-mode quadruple precision floating-point division units are implemented in VHDL and synthesized. The synthesis results show that the dual-mode quadruple precision divider requires 22% more area than the quadruple precision divider and the worst case delay is 1% longer. A quadruple precision division takes fifty nine cycles and two parallel double precision division take twenty nine cycles.Publication Open Access A machine learning approach for implementing data-driven production control policies(Taylor _ Francis, 2021) Department of Business Administration; N/A; Tan, Barış; Khayyati, Siamak; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; Graduate School of Sciences and Engineering; 28600; N/AGiven the extensive data being collected in manufacturing systems, there is a need for developing a systematic method to implement data-driven production control policies. For an effective implementation, first, the relevant information sources must be selected. Then, a control policy that uses the real-time signals collected from these sources must be implemented. We analyse the production control policy implementation problem in three levels: choosing the information sources, forming clusters of information signals to be used by the policy and determining the optimal policy parameters. Due to the search-space size, a machine-learning-based framework is proposed. Using machine learning speeds up optimisation and allows utilising the collected data with simulation. Through two experiments, we show the effectiveness of this approach. In the first experiment, the problem of selecting the right machines and buffers for controlling the release of materials in a production/inventory system is considered. In the second experiment, the best dispatching policy based on the selected information sources is identified. We show that selecting the right information sources and controlling a production system based on the real-time signals from the selected sources with the right policy improve the system performance significantly. Furthermore, the proposed machine learning framework facilitates this task effectively.Publication Open Access A method for estimating stock-out-based substitution rates by using point-of-sale data(Taylor _ Francis, 2009) Öztürk, Ömer Cem; Department of Business Administration; Tan, Barış; Karabatı, Selçuk; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; 38819Empirical studies in retailing suggest that stock-out rates are quite high in many product categories. Stock-outs result in demand spillover, or substitution, among items within a product category. Product assortment and inventory management decisions can be improved when the substitution rates are known. In this paper, a method is presented to estimate product substitution rates by using only Point-Of-Sale (POS) data. The approach clusters POS intervals into states where each state corresponds to a specific substitution scenario. Then available POS data for each state is consolidated and the substitution rates are estimated using the consolidated information. An extensive computational analysis of the proposed substitution rate estimation method is provided. The computational analysis and comparisons with an estimation method from the literature show that the proposed estimation method performs satisfactorily with limited information.Publication Metadata only A microstructure-sensitive model for simulating the impact response of a high-manganese austenitic steel(Asme, 2016) N/A; N/A; Department of Mechanical Engineering; Mirzajanzadeh, Morad; Canadinç, Demircan; PhD Student; Faculty Member; Department of Mechanical Engineering; Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); Graduate School of Sciences and Engineering; College of Engineering; N/A; 23433Microstructurally informed macroscopic impact response of a high-manganese austenitic steel was modeled through incorporation of the viscoplastic self-consistent (VPSC) crystal plasticity model into the ANSYS LS-DYNA nonlinear explicit finite-element (FE) frame. Voce hardening flow rule, capable of modeling plastic anisotropy in microstructures, was utilized in the VPSC crystal plasticity model to predict the micromechanical response of the material, which was calibrated based on experimentally measured quasi-static uniaxial tensile deformation response and initially measured textures. Specifically, hiring calibrated Voce parameters in VPSC, a modified material response was predicted employing local velocity gradient tensors obtained from the initial FE analyses as a new boundary condition for loading state. The updated micromechanical response of the material was then integrated into the macroscale material model by calibrating the Johnson-Cook (JC) constitutive relationship and the corresponding damage parameters. Consequently, we demonstrate the role of geometrically necessary multi-axial stress state for proper modeling of the impact response of polycrystalline metals and validate the presented approach by experimentally and numerically analyzing the deformation response of the Hadfield steel (HS) under impact loading.