Launch Envelope Optimization of Virtual Sliding Target Guidance Scheme

This paper presents an optimization of the performance of a recently proposed virtual sliding target (VST) guidance scheme in terms of maximization of its launch envelope for three- dimensional (3-D) engagements. The objective is to obtain the launch envelope of the missile using the VST guidance scheme for different lateral launch angles with respect to the line of sight (LOS) and demonstrate its superiority over kinematics-based guidance laws like proportional navigation (PN). The VST scheme uses PN as its basic guidance scheme and exploits the relation between the atmospheric properties, missile aerodynamic characteristics, and the optimal trajectory of the missile. The missile trajectory is shaped by controlling the instantaneous position and the speed of a virtual target which the missile pursues during the midcourse phase. In the proposed method it is shown that an appropriate value of initial position for the virtual target in 3-D, combined with optimized virtual target parameters, can significantly improve the launch envelope performance. The paper presents the formulation of the optimization problem, obtains the approximate models used to make the optimization problem more tractable, and finally presents the optimized performance of the missile in terms of launch envelope and shows significant improvement over kinematic-based guidance laws. The paper also proposes modification to the basic VST scheme. Some simulations using the full-fledged six degrees-of-freedom (6-DOF) models are also presented to validate the models and technique used.

Design of multiunit electronic exchanges through decomposition

In this paper, we exploit the idea of decomposition to match buyers and sellers in an electronic exchange for trading large volumes of homogeneous goods, where the buyers and sellers specify marginal-decreasing piecewise constant price curves to capture volume discounts. Such exchanges are relevant for automated trading in many e-business applications. The problem of determining winners and Vickrey prices in such exchanges is known to have a worst-case complexity equal to that of as many as (1 + m + n) NP-hard problems, where m is the number of buyers and n is the number of sellers. Our method proposes the overall exchange problem to be solved as two separate and simpler problems: 1) forward auction and 2) reverse auction, which turns out to be generalized knapsack problems. In the proposed approach, we first determine the quantity of units to be traded between the sellers and the buyers using fast heuristics developed by us. Next, we solve a forward auction and a reverse auction using fully polynomial time approximation schemes available in the literature. The proposed approach has worst-case polynomial time complexity. and our experimentation shows that the approach produces good quality solutions to the problem. Note to Practitioners- In recent times, electronic marketplaces have provided an efficient way for businesses and consumers to trade goods and services. The use of innovative mechanisms and algorithms has made it possible to improve the efficiency of electronic marketplaces by enabling optimization of revenues for the marketplace and of utilities for the buyers and sellers. In this paper, we look at single-item, multiunit electronic exchanges. These are electronic marketplaces where buyers submit bids and sellers ask for multiple units of a single item. We allow buyers and sellers to specify volume discounts using suitable functions. Such exchanges are relevant for high-volume business-to-business trading of standard products, such as silicon wafers, very large-scale integrated chips, desktops, telecommunications equipment, commoditized goods, etc. The problem of determining winners and prices in such exchanges is known to involve solving many NP-hard problems. Our paper exploits the familiar idea of decomposition, uses certain algorithms from the literature, and develops two fast heuristics to solve the problem in a near optimal way in worst-case polynomial time.

Optimization and design of energy transport system for solar cooking application

This paper proposes a hybrid solar cooking system where the solar energy is transported to the kitchen. The thermal energy source is used to supplement the Liquefied Petroleum Gas (LPG) that is in common use in kitchens. Solar energy is transferred to the kitchen by means of a circulating fluid. Energy collected from sun is maximized by changing the flow rate dynamically. This paper proposes a concept of maximum power point tracking (MPPT) for the solar thermal collector. The diameter of the pipe is selected to optimize the overall energy transfer. Design and sizing of different components of the system are explained. Concept of MPPT is validated with simulation and experimental results. (C) 2010 Elsevier Ltd. All rights reserved.

Manipulating Crystallographic Texture of Sn Coatings by Optimization of Electrodeposition Process Conditions to Suppress Growth of Whiskers

The effects of two major electrodeposition process conditions, electrolyte bath temperature and current density, on the microstructure and crystallographic texture of pure tin coatings on brass and, ultimately, on the extent of whisker formation have been examined. The grain size of the deposited coatings increased with increasing electrolyte bath temperature and current density, which significantly affected the dominant texture: (211) or (420) was the dominant texture at low current densities whereas, depending on deposition temperature, (200) or (220) became the dominant texture at high current densities. After deposition, coatings were subjected to different environmental conditions, for example isothermal aging (room temperature, 50A degrees C, or 150A degrees C) for up to 90 days and thermal cycling between -25A degrees C and 85A degrees C for 100 cycles, and whisker growth was studied. The Sn coatings with low Miller index planes, for example (200) and (220), and with moderate aging temperature were more prone to whiskering than coating with high Miller index planes, for example (420), and high aging temperature. A processing route involving the optimum combination of current density and deposition temperature is proposed for suppressing whisker growth.

A Bacterial Foraging Optimization and Learning Automata Based Feature Selection for Motor Imagery EEG Classification

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

Dynamic optimization of track components to minimize rail corrugation

In this paper, the influence on corrugation of the most significant track parameters has been examined. After this parametric study, the optimization of the track parameters to minimize the undulatory wear growth has been achieved. Finally, the influence of the dispersion of the track and contact parameters on corrugation growth has been studied. A method has been developed to obtain an optimal solution of the track parameters which minimizes corrugation growth, thus ensuring that this solution remains optimum despite dispersion of track parameters and wheel-rail contact uncertainties. This work is based on the computer application RACING (RAil Corrugation INitiation and Growth) which has been developed by the authors to predict rail corrugation features.

Band Engineering in Thermoelectric Materials Using Optical, Electronic, and Ab-Initio Computed Properties

Thermoelectric materials have demanded a significant amount of attention for their ability to convert waste heat directly to electricity with no moving parts. A resurgence in thermoelectrics research has led to significant enhancements in the thermoelectric figure of merit, zT, even for materials that were already well studied. This thesis approaches thermoelectric zT optimization by developing a detailed understanding of the electronic structure using a combination of electronic/thermoelectric properties, optical properties, and ab-initio computed electronic band structures. This is accomplished by applying these techniques to three important classes of thermoelectric materials: IV-VI materials (the lead chalcogenides), Half-Heusler’s (XNiSn where X=Zr, Ti, Hf), and CoSb₃ skutterudites.

In the IV-VI materials (PbTe, PbSe, PbS) I present a shifting temperature-dependent optical absorption edge which correlates well to the computed ab-initio molecular dynamics result. Contrary to prior literature that suggests convergence of the primary and secondary bands at 400 K, I suggest a higher convergence temperature of 700, 900, and 1000 K for PbTe, PbSe, and PbS, respectively. This finding can help guide electronic properties modelling by providing a concrete value for the band gap and valence band offset as a function of temperature.

Another important thermoelectric material, ZrNiSn (half-Heusler), is analyzed for both its optical and electronic properties; transport properties indicate a largely different band gap depending on whether the material is doped n-type or p-type. By measuring and reporting the optical band gap value of 0.13 eV, I resolve the discrepancy in the gap calculated from electronic properties (maximum Seebeck and resistivity) by correlating these estimates to the electron-to-hole weighted mobility ratio, A, in narrow gap materials (A is found to be approximately 5.0 in ZrNiSn).

I also show that CoSb₃ contains multiple conduction bands that contribute to the thermoelectric properties. These bands are also observed to shift towards each other with temperature, eventually reaching effective convergence for T>500 K. This implies that the electronic structure in CoSb₃ is critically important (and possibly engineerable) with regards to its high thermoelectric figure of merit.

Optimization and Control of Power Flow in Distribution Networks

Climate change is arguably the most critical issue facing our generation and the next. As we move towards a sustainable future, the grid is rapidly evolving with the integration of more and more renewable energy resources and the emergence of electric vehicles. In particular, large scale adoption of residential and commercial solar photovoltaics (PV) plants is completely changing the traditional slowly-varying unidirectional power flow nature of distribution systems. High share of intermittent renewables pose several technical challenges, including voltage and frequency control. But along with these challenges, renewable generators also bring with them millions of new DC-AC inverter controllers each year. These fast power electronic devices can provide an unprecedented opportunity to increase energy efficiency and improve power quality, if combined with well-designed inverter control algorithms. The main goal of this dissertation is to develop scalable power flow optimization and control methods that achieve system-wide efficiency, reliability, and robustness for power distribution networks of future with high penetration of distributed inverter-based renewable generators.

Proposed solutions to power flow control problems in the literature range from fully centralized to fully local ones. In this thesis, we will focus on the two ends of this spectrum. In the first half of this thesis (chapters 2 and 3), we seek optimal solutions to voltage control problems provided a centralized architecture with complete information. These solutions are particularly important for better understanding the overall system behavior and can serve as a benchmark to compare the performance of other control methods against. To this end, we first propose a branch flow model (BFM) for the analysis and optimization of radial and meshed networks. This model leads to a new approach to solve optimal power flow (OPF) problems using a two step relaxation procedure, which has proven to be both reliable and computationally efficient in dealing with the non-convexity of power flow equations in radial and weakly-meshed distribution networks. We will then apply the results to fast time- scale inverter var control problem and evaluate the performance on real-world circuits in Southern California Edison’s service territory.

The second half (chapters 4 and 5), however, is dedicated to study local control approaches, as they are the only options available for immediate implementation on today’s distribution networks that lack sufficient monitoring and communication infrastructure. In particular, we will follow a reverse and forward engineering approach to study the recently proposed piecewise linear volt/var control curves. It is the aim of this dissertation to tackle some key problems in these two areas and contribute by providing rigorous theoretical basis for future work.

Optimization of InGaAs Quantum Dots for Optoelectronic Applications

Self-assembled In_0.35Ga_0.65As/GaAs quantum dots with low indium content are grown under different growth temperature and investigated using contact atomic force microscopy(AFM). In order to obtain high density and high uniformityu of quantum dots, optimized conditions are concluded for MBE growth. Optimized growth condi-tions also compared with these of InAs/GaAs quantum dots. This will be very useful for InGaAs/GaAs QDs opto-electronic applications, such as quantum dots lasers and quantum dots infrared photodetectors.

Statistical method of modeling and optimization for wireless sensor nodes with different interconnect technologies and substrates

A comparison study was carried out between a wireless sensor node with a bare die flip-chip mounted and its reference board with a BGA packaged transceiver chip. The main focus is the return loss (S parameter S11) at the antenna connector, which was highly depended on the impedance mismatch. Modeling including the different interconnect technologies, substrate properties and passive components, was performed to simulate the system in Ansoft Designer software. Statistical methods, such as the use of standard derivation and regression, were applied to the RF performance analysis, to see the impacts of the different parameters on the return loss. Extreme value search, following on the previous analysis, can provide the parameters' values for the minimum return loss. Measurements fit the analysis and simulation well and showed a great improvement of the return loss from -5dB to -25dB for the target wireless sensor node.

Turbulence modelling and its effects on electronic systems

This paper presents simulated computational fluid dynamics (CFD) results for comparison against experimental data. The performance of four turbulence models has been assessed for electronic application areas considering both fluid flow and heat transfer phenomenon. CFD is vast becoming a powerful and almost essential tool for design, development and optimization in engineering problems. However turbulence models remain to be the key problem issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the performance of the turbulence model employed together with the wall functions implemented. To be able to resolve the abrupt changes in the turbulent energy and other parameters near the wall a particularly fine mesh is necessary which unfortunately increases the computer storage capacity requirements. The objective of turbulence modelling is to enhance computational procdures of sufficient acccuracy and generality for engineers to anticipate the Reynolds stresses and the scalar transport terms.

Low Reynolds number turbulence models for accurate thermal simulations of electronic components

The electronics industry and the problems associated with the cooling of microelectronic equipment are developing rapidly. Thermal engineers now find it necessary to consider the complex area of equipment cooling at some level. This continually growing industry also faces heightened pressure from consumers to provide electronic product miniaturization, which in itself increases the demand for accurate thermal management predictions to assure product reliability. Computational fluid dynamics (CFD) is considered a powerful and almost essential tool for the design, development and optimization of engineering applications. CFD is now widely used within the electronics packaging design community to thermally characterize the performance of both the electronic component and system environment. This paper discusses CFD results for a large variety of investigated turbulence models. Comparison against experimental data illustrates the predictive accuracy of currently used models and highlights the growing demand for greater mathematical modelling accuracy with regards to thermal characterization. Also a newly formulated low Reynolds number (i.e. transitional) turbulence model is proposed with emphasis on hybrid techniques.

Turbulence modelling and its impact on CFD predictions for cooling of electronic components

This paper will discuss Computational Fluid Dynamics (CFD) results from an investigation into the accuracy of several turbulence models to predict air cooling for electronic packages and systems. Also new transitional turbulence models will be proposed with emphasis on hybrid techniques that use the k-ε model at an appropriate distance away from the wall and suitable models, with wall functions, near wall regions. A major proportion of heat emitted from electronic packages can be extracted by air cooling. This flow of air throughout an electronic system and the heat extracted is highly dependent on the nature of turbulence present in the flow. The use of CFD for such investigations is fast becoming a powerful and almost essential tool for the design, development and optimization of engineering applications. However turbulence models remain a key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt fluctuations experienced by the turbulent energy and other parameters located at near wall regions and shear layers a particularly fine computational mesh is necessary which inevitably increases the computer storage and run-time requirements. The PHYSICA Finite Volume code was used for this investigation. With the exception of the k-ε and k-ω models which are available as standard within PHYSICA, all other turbulence models mentioned were implemented via the source code by the authors. The LVEL, LVEL CAP, Wolfshtein, k-ε, k-ω, SST and kε/kl models are described and compared with experimental data.

Response Surface Modeling and Optimisation for Reliable Electronic Products

The aim of integrating computational mechanics (FEA and CFD) and optimization tools is to speed up dramatically the design process in different application areas concerning reliability in electronic packaging. Design engineers in the electronics manufacturing sector may use these tools to predict key design parameters and configurations (i.e. material properties, product dimensions, design at PCB level. etc) that will guarantee the required product performance. In this paper a modeling strategy coupling computational mechanics techniques with numerical optimization is presented and demonstrated with two problems. The integrated modeling framework is obtained by coupling the multi-physics analysis tool PHYSICA - with the numerical optimization package - Visua/DOC into a fuJly automated design tool for applications in electronic packaging. Thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and life-time under thermal cycling. Also a thermal management design based on multi-physics analysis with coupled thermal-flow-stress modeling is discussed. The Response Surface Modeling Approach in conjunction with Design of Experiments statistical tools is demonstrated and used subsequently by the numerical optimization techniques as a part of this modeling framework. Predictions for reliable electronic assemblies are achieved in an efficient and systematic manner.