105 research outputs found
Surface directed electrokinetic flows in microfluidic devices:
No full textElectroosmotic flow control in microfluidic devices is an important and challenging problem, as electroosmosis directly influences separation efficiencies in lab-on-chip applications. In this study, a non-mechanical passive flow directing method is presented for electrokinetically driven flow. Due to the high surface-area-to-volume (SA/V) ratio, surface properties dominate the flow in microfluidic channels. For electrokinetically driven flows, the main surface property affecting electroosmotic flows is the surface ζ potential, which is related to the effective surface charge density. By changing the effective surface charge density, the electroosmotic flow rates of charged species can be controlled in microfluidic channels. In this work, to change the effective surface charge density, surfaces were chemically modified with –Br, –NH2 and –CH3 functional groups by ‘click’ chemistry. Since these functional surface layers are integrated within model glass microfluidic devices prepared by standard microfabrication procedures, the first step was to investigate the stability of the adherent surface layers to a variety of microfabrication conditions. A model “Y” shaped glass microfluidic device was developed. One leg of this model microfluidic device was selectively chemically modified to alter the ζ potential and thereby increase or decrease the electroosmotic flow with respect to rest of the device. Electroosmotic flow is visualized by using marker dyes under a fluorescent microscope. In addition, experiments were validated by using the CFD code in COMSOL. The experiments concluded that the surface layers are stable to a variety of conditions including a wide pH range (pH 3 – pH 11), solvent exposure, acid and base exposure, and UV light. Extreme conditions such as a piranha solution or oxidative plasma degrade the surface layers. Electrokinetic flow experiments show that depending on the charge of a species the electroosmotic flow is preferentially directed as a function of the ζ potential in the microfluidic channels.M.S.Includes bibliographical references (p. 78-81)by Mehmet Basar Karaco
Topics in decentralized detection
No full textIn this thesis we obtain several new results in the areas of decentralized sequential detection and robust decentralized detection.In the area of decentralized sequential detection, we first consider the case in which each sensor performs a sequential test on its observations and arrives at a local decision about the true hypothesis; subsequently, the local decisions of all of the sensors are used for a common purpose. Here we assume that decision errors at the sensors are penalized through a common cost function and that each time step taken by the detectors as a team is assigned a positive cost. We show that optimal sensor decision functions can be found in the class of generalized sequential probability ratio tests with monotonically convergent thresholds. We present a technique for obtaining optimal thresholds.We also consider the case in which each sensor sends a sequence of summary messages to a fusion center in which a sequential test is carried out to determine the true hypothesis. Here we assume that decision errors at the fusion center are penalized through a cost function and that each time step taken to arrive at the final decision costs a positive amount. We show that the problem is tractable when the information structure in the system is quasiclassical. In particular, we show that an optimal fusion center policy has a simple structure resembling a sequential probability ratio test and that a stationary set of monotone likelihood ratio tests is optimal at the sensors. Finally, we compute the optimal decision functions for some representative examples.In the area of robust decentralized detection, we consider the case in which the sensor distributions are assumed to belong to known uncertainty classes. We show for a broad class of such decentralized detection problems that a set of least favorable distributions exists for minimax robust testing between the hypotheses. We thus establish that minimax robust tests are obtained as solutions to simple decentralized detection problems in which the sensor distributions are specified to be the least favorable distributions.Made available in DSpace on 2011-05-07T12:48:37Z (GMT). No. of bitstreams: 2
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Model simplification and robust control in deterministic and stochastic systems using singular perturbation methods
No full text"The class of uncertainties that may be present in dynamical systems includes, but is not limited to, unknown disturbance inputs, unpredictable abrupt structural changes, unknown parameters, and unmodeled fast dynamics. A number of different stochastic and deterministic models that incorporate these uncertainties have been proposed in the literature, and these have led to different robust control and filtering problem formulations, methodologies, and resulting robust designs. This thesis presents novel formulations of three different classes of problems featuring the types of uncertainties described above, studies them from the points of view of model reduction and robust controller design, and develops new theory and methodology for their solutions. The common thread that runs through these three classes of problems (which involve both deterministic and stochastic systems) is the use of ""singular perturbations,"" either as a modeling tool or as a computational tool. The reason for adopting the singular perturbations framework is threefold. First, we must study robustness with respect to fast unmodeled dynamics of different control or filtering designs. The second reason is to incorporate appropriate knowledge on fast dynamics into the design, without using the full-order system, so as to improve performance and to alleviate the numerical ill-conditioning associated with the computation of the full-order solution. Third, we must obtain ""reliable"" reduced-order models for large-scale systems that exhibit two or multi time-scale behavior, such that the solution to the reduced-order model can achieve a desired performance for the full-order system."The thesis can naturally be divided into three parts. In the first part, the problem of optimal control and model reduction for singularly perturbed linear Gaussian systems under an exponential-of-quadratic performance index is addressed, for which a complete solution is obtained that achieves all three objectives stated above. In the second part, which comprises two chapters, solutions to the problem of model reduction for large-scale jump linear systems are presented. The original system is again assumed to exhibit a two-time-scale behavior, and two types of time-scale separations are studied in detail in two separate chapters. Finally, in the last part of the thesis, which also comprises two chapters, solutions to problems of robust parameter identification and robust adaptive control are presented. For these classes of problems, the original system may not exhibit a two-time-scale behavior at the outset, but time-scale decomposition arises naturally due to singularity in the measurement scheme. A singular perturbation analysis is then employed to construct reduced-order identifiers and controllers and to prove their optimality. Again, the three objectives are achieved for the closed-loop system. The thesis ends with some concluding remarks, delineation of its main contributions, and some discussions on future extensions of these results.Made available in DSpace on 2011-05-07T12:51:23Z (GMT). No. of bitstreams: 2
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Design of minimax controllers for nonlinear systems using cost-to-come methods
No full textThis thesis develops and utilizes the cost-to-come methodology for the construction of minimax controllers for nonlinear systems with partial-state information (PSI), which are subjected to deterministic uncertainty. It introduces the notion of a cost-to-come function and shows how it leads to necessary and sufficient conditions for the existence of a minimax controller. These conditions are the existence of the cost-to-come function and the existence of a solution to an auxiliary full-information (FI) minimax problem. It is also proven that a solution of the FI problem leads directly to a solution of the original PSI problem. The significance of this result is that the auxiliary FI problem can be solved using better-known dynamic programming (DP) techniques."Generally, the auxiliary problem has an infinite-dimensional state, which may make the cost-to-come methodology impractical. Toward resolving this impediment, the thesis first identifies two classes of problems for which cost-to-come methods offer significant insights: one, problems that satisfy a certainty-equivalence principle (which is attributed to the case when a minimax controller can be chosen to be a full-state information (FSI) minimax controller with the state replaced by a ""worst-case"" value of the state), and two, problems for which the cost-to-come function can be characterized by a finite number of parameters (which is attributed to the case where the auxiliary FI problem has a finite-dimensional state). Outside these two classes, bounding techniques can be used to reduce the problem complexity, at the expense of some possible performance degradation. By bounding the FSI cost-to-go function from above, the certainty-equivalence principle can be generalized to gain some insight into the structure of cost-bounding controllers, which may lead to alternative parameter design methods. Bounding the cost-to-come function by finite-dimensional structured cost-to-come functions allows the construction of an auxiliary FI problem, which leads to a cost-bounding controller policy."As an application of the cost-to-come methodology, a class of affine-quadratic (AQ) disturbance attenuation problems is considered in some detail. This class contains H\sp\infty-optimal control and filtering problems, problems of parameter identification and nonlinear adaptive control, and memoryless control problems. For the former subclass, cost-to-come methods provide an alternative derivation of the well-known necessary and sufficient conditions and of a minimax policy. For the latter three subclasses, new algorithms are developed that lead either directly or recursively to optimal solutions. Some numerical examples and simulation studies are provided to illustrate the theoretical results.Made available in DSpace on 2011-05-07T14:21:39Z (GMT). No. of bitstreams: 2
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Dynamic multi-person optimization with weakly coupled agents
No full textIn this thesis, we study multiple decision maker problems where the decision makers are coupled through a small parameter . The class of systems considered exhibit the common feature that when the weak coupling is completely absent (i.e., when the coupling parameter = 0), the problem decomposes into a number of independent tractable problems or into a single tractable problem, but when the coupling is strong the problem may be difficult to solve. We are interested in the intermediate case when the coupling is neither absent nor strong. The central idea behind the construction of approximate solutions is to start with the zeroth order solution (obtained by setting = 0) and iteratively obtain successively better approximations to the optimal or equilibrium solution. Specifically, we have studied LQG teams featuring a nonclassical information pattern, nonlinear deterministic differential games, LQG nonzero-sum games and Markov decision problems. In the case of LQG teams, we showed the existence of finite-dimensional linear controllers (FDLCs) which approximate the optimal cost to O(). Then, by restricting ourselves to the class of FDLCs, we obtained higher order approximations to the optimal cost by solving a sequence of single decision maker LQG stochastic control problems. In LQG nonzero-sum games, we established the existence of a finite-dimensional Nash equilibrium for small values of the coupling parameter; further, we also showed that this equilibrium solution is well-posed and admissible as tends to zero. For the class of nonlinear, nonzero-sum differential games, we considered two types of information structures. In the case of the open-loop information structure, we have shown that approximate Nash equilibria can be obtained by solving the zeroth order problems and a sequence of LQ optimal control problems. When the information structure is dynamic, the decomposition involves the solution of the zeroth order problems and a sequence of cost evaluations (no control involved) followed by static optimization problems. We have also shown the existence of solutions to Markov decision problems featuring nonclassical information under the assumption of a finite-control set. Through the weak-coupling approach, we have thus been able to identify a class of tractable problems which were long thought to be intractable.Made available in DSpace on 2011-05-07T13:47:05Z (GMT). No. of bitstreams: 2
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Ethical Leadership and Prosocial Silence: An Evidence from Academia
No full textThe attached data is a part of already approved Ph.D. research by the BASAR, COMSATS University Islamabad.Briefly, the data attached herein is cross-sectional data collected using convenience sampling. Please contact the author for more information..</div
National economic policy simulations with global interdependencies : a sensitivity analysis for Germany
No full text"Policy simulations for national economies with econometric models in general are done using a stand alone national model with exogenous export values and import prices. In a globalised world such an exercise is critical, since the policy in question may change the export prices and the import volumes of the particular country and induce via international trade a change of the economic activities of the global economy and a feed back to the export values and import prices of the particular country. The paper at hand presents a sensitivity analysis for Germany comparing the impacts of a shock on investment in a stand alone simulation using the multisector model INFORGE with the results, which occur, if the same model is linked to the global multicountry/multisector model GINFORS endogenising Germany's export values and import prices. The results are striking: The effect on real GDP is 50% higher in the global simulation than in the stand alone case. Because of the specialisation in trade the differences on the sector level are even stronger." (Author's abstract, IAB-Doku) ((en))Wirtschaftspolitik, Globalisierung - Auswirkungen, Export, Preisniveau, Importquote, Exportquote, Welthandel, Ökonometrie - Modell, Bruttoinlandsprodukt, volkswirtschaftliche Gesamtrechnung, Außenhandelspolitik, Außenhandelsentwicklung
Assessing Vulnerability in Earthquake-Resistant Cities: A Multiple Regression Analysis for Sahinali, Nigde
No full textThe study aims to analyze the correlation between decisions on location, construction style, function, and building height in residential areas and an earthquake-resilient urban approach using multivariate linear regression analysis. The selected study area is Sahinali Neighborhood in the city center of Nigde, impacted by in the Kahramanmaras Earthquake Sequence (the 7.8 and 7.5 Mw earthquakes) in Turkey on February 6, 2023. Findings reveal that site selection is the most crucial factor influencing earthquake damage vulnerability, followed by building function, layout, and number of floors. The results emphasize that city-scale decisions made through zoning plans directly influence the development of an earthquake-resistant city. © 2024 The author
ON WORST CASE DESIGN STRATEGIES††The research of the first author has been supported by the U.S. Air Force under Contract AFOSR 84-0056, while the research of the second author has been supported by the National Science Foundation under Grant ECS-83-04435 and the U.S. A.R.O. under Contract DAAG-29-85-K-0094.
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