Design optimization of short-stroke single-phase tubular permanent-magnet motor for refrigeration applications

This paper describes a design methodology to achieve optimal performance for a short-stroke single-phase tubular permanent-magnet motor which drives a reciprocating vapor compressor. The steady-state characteristic of the direct-drive linear-motor compressor system is analyzed, an analytical formula for predicting iron loss is presented, and a motor-design procedure which takes into account the effect of compressor loads under nominal operating condition is formulated. It is shown that the motor efficiency can be optimized with respect to two leading dimensional ratios. Experimental results validate the proposed design methodology. Copyright © 2010 IEEE.

Multiobjective design optimization of IGBT power modules considering power cycling and thermal cycling

Insulated-gate bipolar transistor (IGBT) power modules find widespread use in numerous power conversion applications where their reliability is of significant concern. Standard IGBT modules are fabricated for general-purpose applications while little has been designed for bespoke applications. However, conventional design of IGBTs can be improved by the multiobjective optimization technique. This paper proposes a novel design method to consider die-attachment solder failures induced by short power cycling and baseplate solder fatigue induced by the thermal cycling which are among major failure mechanisms of IGBTs. Thermal resistance is calculated analytically and the plastic work design is obtained with a high-fidelity finite-element model, which has been validated experimentally. The objective of minimizing the plastic work and constrain functions is formulated by the surrogate model. The nondominated sorting genetic algorithm-II is used to search for the Pareto-optimal solutions and the best design. The result of this combination generates an effective approach to optimize the physical structure of power electronic modules, taking account of historical environmental and operational conditions in the field.

The evolution of "classical mythology" within marketing measure development

Purpose - This paper provides a deeper examination of the fundamentals of commonly-used techniques - such as coefficient alpha and factor analysis - in order to more strongly link the techniques used by marketing and social researchers to their underlying psychometric and statistical rationale. Design/methodology approach - A wide-ranging review and synthesis of psychometric and other measurement literature both within and outside the marketing field is used to illuminate and reconsider a number of misconceptions which seem to have evolved in marketing research. Findings - The research finds that marketing scholars have generally concentrated on reporting what are essentially arbitrary figures such as coefficient alpha, without fully understanding what these figures imply. It is argued that, if the link between theory and technique is not clearly understood, use of psychometric measure development tools actually runs the risk of detracting from the validity of the measures rather than enhancing it. Research limitations/implications - The focus on one stage of a particular form of measure development could be seen as rather specialised. The paper also runs the risk of increasing the amount of dogma surrounding measurement, which runs contrary to the spirit of this paper. Practical implications - This paper shows that researchers may need to spend more time interpreting measurement results. Rather than simply referring to precedence, one needs to understand the link between measurement theory and actual technique. Originality/value - This paper presents psychometric measurement and item analysis theory in easily understandable format, and offers an important set of conceptual tools for researchers in many fields. © Emerald Group Publishing Limited.

Chemical studies of plasma etchants used in integrated circuit manufacture

Plasma or "dry" etching is an essential process for the production of modern microelectronic circuits. However, despite intensive research, many aspects of the etch process are not fully understood. The results of studies of the plasma etching of Si and Si02 in fluorine-containing discharges, and the complementary technique of plasma polymerisation are presented in this thesis. Optical emission spectroscopy with argon actinometry was used as the principle plasma diagnostic. Statistical experimental design was used to model and compare Si and Si02 etch rates in CF4 and SF6 discharges as a function of flow, pressure and power. Etch mechanisms m both systems, including the potential reduction of Si etch rates in CF4 due to fluorocarbon polymer formation, are discussed. Si etch rates in CF4 /SF6 mixtures were successfully accounted for by the models produced. Si etch rates in CF4/C2F6 and CHF3 as a function of the addition of oxygen-containing additives (02, N20 and CO2) are shown to be consistent with a simple competition between F, 0 and CFx species for Si surface sites. For the range of conditions studied, Si02 etch rates were not dependent on F-atom concentration, but the presence of fluorine was essential in order to achieve significant etch rates. The influence of a wide range of electrode materials on the etch rate of Si and Si02 in CF4 and CF4 /02 plasmas was studied. It was found that the Si etch rate in a CF4 plasma was considerably enhanced, relative to an anodised aluminium electrode, in the presence of soda glass or sodium or potassium "doped" quartz. The effect was even more pronounced in a CF4 /02 discharge. In the latter system lead and copper electrodes also enhanced the Si etch rate. These results could not be accounted for by a corresponding rise in atomic fluorine concentration. Three possible etch enhancement mechanisms are discussed. Fluorocarbon polymer deposition was studied, both because of its relevance to etch mechanisms and its intrinsic interest, as a function of fluorocarbon source gas (CF4, C2F6, C3F8 and CHF3), process time, RF power and percentage hydrogen addition. Gas phase concentrations of F, H and CF2 were measured by optical emission spectroscopy, and the resultant polymer structure determined by X-ray photoelectron spectroscopy and infrared spectroscopy. Thermal and electrical properties were measured also. Hydrogen additions are shown to have a dominant role in determining deposition rate and polymer composition. A qualitative description of the polymer growth mechanism is presented which accounts for both changes in growth rate and structure, and leads to an empirical deposition rate model.

Rutting-induced permeability loss of open graded friction course mixtures

Functionality of an open graded friction course (OGFC) depends on the high interconnected air voids or pores of the OGFC mixture. The authors' previous study indicated that the pores in the OGFC mixture were easily clogged by rutting deformation. Such a deformation-related clogging can cause a significant rutting-induced permeability loss in the OGFC mixture. The objective of this study was to control and reduce the rutting-induced permeability loss of the OGFC based on mixture design and layer thickness. Eight types of the OGFC mixtures with different air void contents, gradations, and nominal maximum aggregate sizes were fabricated in the laboratory. Wheel-tracking rutting tests were conducted on the OGFC slabs to simulate the deformation-related clogging. Permeability tests after different wheel load applications were performed on the rutted OGFC slabs using a falling head permeameter developed in the authors' previous study. The relationships between permeability loss and rutting depth as well as dynamic stability were developed based on the eight OGFC mixtures' test results. The thickness effects of the single-layer and the two-layer OGFC slabs were also discussed in terms of deformation-related clogging and the rutting-induced permeability loss. Results showed that the permeability coefficient decreases linearly with an increasing rutting depth of the OGFC mixtures. Rutting depth was recommended as a design index to control permeability loss of the OGFC mixture rather than the dynamic stability. Permeability loss due to deformation-related clogging can be effectively reduced by using a thicker single-layer OGFC or two-layer OGFC.

Implementation of pseudo J-integral based Paris’ law for fatigue cracking in asphalt mixtures and pavements

Pavement analysis and design for fatigue cracking involves a number of practical problems like material assessment/screening and performance prediction. A mechanics-aided method can answer these questions with satisfactory accuracy in a convenient way when it is appropriately implemented. This paper presents two techniques to implement the pseudo J-integral based Paris’ law to evaluate and predict fatigue cracking in asphalt mixtures and pavements. The first technique, quasi-elastic simulation, provides a rational and appropriate reference modulus for the pseudo analysis (i.e., viscoelastic to elastic conversion) by making use of the widely used material property: dynamic modulus. The physical significance of the quasi-elastic simulation is clarified. Introduction of this technique facilitates the implementation of the fracture mechanics models as well as continuum damage mechanics models to characterize fatigue cracking in asphalt pavements. The second technique about modeling fracture coefficients of the pseudo J-integral based Paris’ law simplifies the prediction of fatigue cracking without performing fatigue tests. The developed prediction models for the fracture coefficients rely on readily available mixture design properties that directly affect the fatigue performance, including the relaxation modulus, air void content, asphalt binder content, and aggregate gradation. Sufficient data are collected to develop such prediction models and the R2 values are around 0.9. The presented case studies serve as examples to illustrate how the pseudo J-integral based Paris’ law predicts fatigue resistance of asphalt mixtures and assesses fatigue performance of asphalt pavements. Future applications include the estimation of fatigue life of asphalt mixtures/pavements through a distinct criterion that defines fatigue failure by its physical significance.

Mode-locking intracavity dynamics:modeling nonlinear power and energy fluctuations

Modern high-power, pulsed lasers are driven by strong intracavity fluctuations. Critical in driving the intracavity dynamics is the nontrivial phase profiles generated and their periodic modification from either nonlinear mode-coupling, spectral filtering or dispersion management. Understanding the theoretical origins of the intracavity fluctuations helps guide the design, optimization and construction of efficient, high-power and high-energy pulsed laser cavities. Three specific mode-locking component are presented for enhancing laser energy: waveguide arrays, spectral filtering and dispersion management. Each component drives a strong intracavity dynamics that is captured through various modeling and analytic techniques.

Uniform design for the optimization of Al2O3 nanofilms produced by electrophoretic deposition

Surface modification by means of nanostructures is of interest to enhance boiling heat transfer in various applications including the organic Rankine cycle (ORC). With the goal of obtaining rough and dense aluminum oxide (Al2O3) nanofilms, the optimal combination of process parameters for electrophoretic deposition (EPD) based on the uniform design (UD) method is explored in this paper. The detailed procedures for the EPD process and UD method are presented. Four main influencing conditions controlling the EPD process were identified as nanofluid concentration, deposition time, applied voltage and suspension pH. A series of tests were carried out based on the UD experimental design. A regression model and statistical analysis were applied to the results. Sensitivity analyses of the effect of the four main parameters on the roughness and deposited mass of Al2O3 films were also carried out. The results showed that Al2O3 nanofilms were deposited compactly and uniformly on the substrate. Within the range of the experiments, the preferred combination of process parameters was determined to be nanofluid concentration of 2 wt.%, deposition time of 15 min, applied voltage of 23 V and suspension pH of 3, yielding roughness and deposited mass of 520.9 nm and 161.6 × 10− 4 g/cm2, respectively. A verification experiment was carried out at these conditions and gave values of roughness and deposited mass within 8% error of the expected ones as determined from the UD approach. It is concluded that uniform design is useful for the optimization of electrophoretic deposition requiring only 7 tests compared to 49 using the orthogonal design method.

Inference and optimization of real edges on sparse graphs:A statistical physics perspective

Inference and optimization of real-value edge variables in sparse graphs are studied using the Bethe approximation and replica method of statistical physics. Equilibrium states of general energy functions involving a large set of real edge variables that interact at the network nodes are obtained in various cases. When applied to the representative problem of network resource allocation, efficient distributed algorithms are also devised. Scaling properties with respect to the network connectivity and the resource availability are found, and links to probabilistic Bayesian approximation methods are established. Different cost measures are considered and algorithmic solutions in the various cases are devised and examined numerically. Simulation results are in full agreement with the theory. © 2007 The American Physical Society.

Efficient algorithm for routing optimization via statistical mechanics

Many practical routing algorithms are heuristic, adhoc and centralized, rendering generic and optimal path configurations difficult to obtain. Here we study a scenario whereby selected nodes in a given network communicate with fixed routers and employ statistical physics methods to obtain optimal routing solutions subject to a generic cost. A distributive message-passing algorithm capable of optimizing the path configuration in real instances is devised, based on the analytical derivation, and is greatly simplified by expanding the cost function around the optimized flow. Good algorithmic convergence is observed in most of the parameter regimes. By applying the algorithm, we study and compare the pros and cons of balanced traffic configurations to that of consolidated traffic, which provides important implications to practical communication and transportation networks. Interesting macroscopic phenomena are observed from the optimized states as an interplay between the communication density and the cost functions used. © 2013 IEEE.

DFIG machine design for maximizing power output based on surrogate optimization algorithm

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Surrogate-based analysis and optimization for the design of heat sinks with jet impingement

Heat sinks are widely used for cooling electronic devices and systems. Their thermal performance is usually determined by the material, shape, and size of the heat sink. With the assistance of computational fluid dynamics (CFD) and surrogate-based optimization, heat sinks can be designed and optimized to achieve a high level of performance. In this paper, the design and optimization of a plate-fin-type heat sink cooled by impingement jet is presented. The flow and thermal fields are simulated using the CFD simulation; the thermal resistance of the heat sink is then estimated. A Kriging surrogate model is developed to approximate the objective function (thermal resistance) as a function of design variables. Surrogate-based optimization is implemented by adaptively adding infill points based on an integrated strategy of the minimum value, the maximum mean square error approach, and the expected improvement approaches. The results show the influence of design variables on the thermal resistance and give the optimal heat sink with lowest thermal resistance for given jet impingement conditions.