Home About us Contact
|
Home About us Contact | ||
|
|
||
Design Point (design + point)
Selected AbstractsPower-delay optimization of D-latch/MUX source coupled logic gatesINTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 1 2005M. Alioto In this paper a design strategy for MUX, XOR and D-latch source coupled logic (SCL) gates is proposed. To this end, an analytical model of the delay and the noise margin as a function of the transistors' aspect ratio and bias current is first introduced. Successively, analytical equations of the transistors' aspect ratio to meet a given noise margin specification are derived as a function of the bias current, and are then used along with the delay model to express the delay as an explicit function of the bias current and noise margin. The simplified delay expression explicitly relates speed performance to power dissipation and the noise margin, thereby providing the designer with the required understanding of the trade-offs involved in the design. Therefore, the criteria proposed allow the designer to consciously manage the power-delay trade-off. The delay dependence on the logic swing is also investigated with results showing that this delay is not necessarily reduced by reducing the logic swing, in contrast with the usual assumption. Since the results obtained are valid for all SCL gates and are independent of the CMOS process used, the guidelines provided afford a deeper understanding of SCL gates from a design point of view. Copyright © 2005 John Wiley & Sons, Ltd. [source] Influence of the heat recovery steam generator design parameters on the thermoeconomic performances of combined cycle gas turbine power plantsINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 14 2004Manuel Valdés Abstract This paper proposes a methodology to identify the most relevant design parameters that impact on the thermal efficiency and the economic results of combined cycle gas turbine power plants. The analysis focuses on the heat recovery steam generator (HRSG) design and more specifically on those operating parameters that have a direct influence on the economic results of the power plant. These results are obtained both at full and part load conditions using a dedicated code capable of simulating a wide number of different plant configurations. Two different thermoeconomic models aimed to select the best design point are proposed and compared: the first one analyzes the generating cost of the energy while the second one analyzes the annual cash flow of the plant. Their objective is to determine whether an increase in the investment in order to improve the thermal efficiency is worth from an economic point of view. Both models and the different HRSG configurations analysed are compared in the results section. Some parametric analysis show how the design parameters might be varied in order to improve the power plant efficiency or the economic results. Copyright © 2004 John Wiley & Sons, Ltd. [source] Two-stage computing budget allocation approach for the response surface methodINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 6 2007J. Peng Abstract Response surface methodology (RSM) is one of the main statistical approaches to search for an input combination that optimizes the simulation output. In the early stages of RSM, an iterative steepest ascent search procedure is frequently used. In this paper, we attempt to improve this procedure by considering a more realistic case where there are computing budget constraints, and formulate a new computing budget allocation problem to look into the important issue of allocating computing budget to the design points in the local region of experimentation. We propose a two-stage computing budget allocation approach, which uses a limited budget to estimate the response surface in the first stage and then uses the rest of the budget to improve the lower bound of the estimated response at the center of the next design region in the second stage. Several numerical experiments are carried out to compare the two-stage approach with the regular factorial design, which allocates budget equally to each design point. The results show that our two-stage allocation outperforms the equal allocation, especially when the system noise is large. [source] A near-infrared spectroscopic investigation of relative density and crushing strength in four-component compactsJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 3 2009Steven M. Short Abstract Near-infrared spectroscopy (NIRS) is commonly employed for the analysis of chemical and physical attributes of intact pharmaceutical compacts. Specifically, NIRS has proven useful in the nondestructive measurement of tablet hardness or crushing strength. Near-infrared (NIR) reflectance and transmittance spectra were acquired for 174 13-mm compacts, which were produced according to a four-constituent mixture design (29 points) composed of anhydrous theophylline, lactose monohydrate, microcrystalline cellulose, and soluble starch. Six compacts were produced for each design point by compacting at multiple pressures. Physical testing and regression analyses were used to model the effect of variation in relative density (and crushing strength) on NIR spectra. Chemometric analyses demonstrated that the overall spectral variance was strongly influenced by anhydrous theophylline as a result of the experimental design and the component's spectroscopic signature. The calibration for crushing strength was more linear than the relative density model, although accuracy was poorer in comparison to the density model due to imprecision of the reference measurements. Based on the consideration of reflectance and transmittance measurements, a revised rationalization for NIR sensitivity to compact hardness is presented. © 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:1095,1109, 2009 [source] Investigation of the Influence of Volute Design on Journal Bearing Bias Force Using Computational Fluid DynamicsARTIFICIAL ORGANS, Issue 9 2010Roland Graefe Abstract Hydrodynamic fluid film bearings represent an optimal possibility for rotary blood pump (RBP) miniaturization and wear-free operation. Size is a key parameter in the development of ventricular assist devices (VADs) as smaller patients and the pediatric population become eligible for the device. In order to maintain rotor suspension, radial journal bearings have been widely used in industrial applications as well as in some VADs. A main influence on the performance of such a bearing is the applied hydraulic bias force. This study combines numerical and analytical approaches to determine the bias force of different impeller-volute configurations and the resulting eccentricity for the hydraulic design point and also for off-design operation. Significant differences occur for different impeller-volute configurations, with the circular volute displaying the most beneficial properties for a stable impeller suspension. Moreover, an analytical prediction of eccentricity was found to be incorrect for the relatively small forces that occur in RBPs. [source] Shape Optimization of the Diffuser Blade of an Axial Blood Pump by Computational Fluid DynamicsARTIFICIAL ORGANS, Issue 3 2010Lailai Zhu Abstract Computational fluid dynamics (CFD) has been a viable and effective way to predict hydraulic performance, flow field, and shear stress distribution within a blood pump. We developed an axial blood pump with CFD and carried out a CFD-based shape optimization of the diffuser blade to enhance pressure output and diminish backflow in the impeller,diffuser connecting region at a fixed design point. Our optimization combined a computer-aided design package, a mesh generator, and a CFD solver in an automation environment with process integration and optimization software. A genetic optimization algorithm was employed to find the pareto-optimal designs from which we could make trade-off decisions. Finally, a set of representative designs was analyzed and compared on the basis of the energy equation. The role of the inlet angle of the diffuser blade was analyzed, accompanied by its relationship with pressure output and backflow in the impeller,diffuser connecting region. [source] Hydrothermal carbonization of biomass: A summary and discussion of chemical mechanisms for process engineeringBIOFUELS, BIOPRODUCTS AND BIOREFINING, Issue 2 2010Axel Funke Abstract Hydrothermal carbonization can be defined as combined dehydration and decarboxy lation of a fuel to raise its carbon content with the aim of achieving a higher calorific value. It is realized by applying elevated temperatures (180,220°C) to biomass in a suspension with water under saturated pressure for several hours. With this conversion process, a lignite-like, easy to handle fuel with well-defined properties can be created from biomass residues, even with high moisture content. Thus it may contribute to a wider application of biomass for energetic purposes. Although hydrothermal carbonization has been known for nearly a century, it has received little attention in current biomass conversion research. This review summarizes knowledge about the chemical nature of this process from a process design point of view. Reaction mechanisms of hydrolysis, dehydration, decarboxylation, aromatization, and condensation polymerization are discussed and evaluated to describe important operational parameters qualitatively. The results are used to derive fundamental process design improvements. Copyright © 2010 Society of Chemical Industry and John Wiley & Sons, Ltd [source] Estimating Long-term Trends in Tropospheric Ozone LevelsINTERNATIONAL STATISTICAL REVIEW, Issue 1 2002Michael Smith Summary This paper develops Bayesian methodology for estimating long-term trends in the daily maxima of tropospheric ozone. The methods are then applied to study long-term trends in ozone at six monitoring sites in the state of Texas. The methodology controls for the effects of meteorological variables because it is known that variables such as temperature, wind speed and humidity substantially affect the formation of tropospheric ozone. A semiparametric regression model is estimated in which a nonparametric trivariate surface is used to model the relationship between ozone and these meteorological variables because, while it is known that the relatinship is a complex nonlinear one, its functional form is unknown. The model also allows for the effects of wind direction and seasonality. The errors are modeled as an autoregression, which is methodologically challenging because the observations are unequally spaced over time. Each function in the model is represented as a linear combination of basis functions located at all of the design points. We also estimate an appropriate data transformation simulataneously with the functions. The functions are estimated nonparametrically by a Bayesian hierarchical model that uses indicator variables to allow a non-zero probability that the coefficient of each basis term is zero. The entire model, including the nonparametric surfaces, data transformation and autoregression for the unequally spaced errors, is estimated using a Markov chain Monte Carlo sampling scheme with a computationally efficient transition kernel for generating the indicator variables. The empirical results indicate that key meteorological variables explain most of the variation in daily ozone maxima through a nonlinear interaction and that their effects are consistent across the six sites. However, the estimated trends vary considerably from site to site, even within the same city. [source] Two-stage computing budget allocation approach for the response surface methodINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 6 2007J. Peng Abstract Response surface methodology (RSM) is one of the main statistical approaches to search for an input combination that optimizes the simulation output. In the early stages of RSM, an iterative steepest ascent search procedure is frequently used. In this paper, we attempt to improve this procedure by considering a more realistic case where there are computing budget constraints, and formulate a new computing budget allocation problem to look into the important issue of allocating computing budget to the design points in the local region of experimentation. We propose a two-stage computing budget allocation approach, which uses a limited budget to estimate the response surface in the first stage and then uses the rest of the budget to improve the lower bound of the estimated response at the center of the next design region in the second stage. Several numerical experiments are carried out to compare the two-stage approach with the regular factorial design, which allocates budget equally to each design point. The results show that our two-stage allocation outperforms the equal allocation, especially when the system noise is large. [source] Optimization of carbon black and nanoclay filler loading in chlorobutyl vulcanizates using response surface methodologyPOLYMER COMPOSITES, Issue 6 2009V. Sridhar In this article, an attempt has been made to study the applicability of using organo nanoclay (Cloisite 30B) and carbon black (HAF, N330) in chlorinated isobutyl isoprene rubber vulcanizates. Statistical design of experimentation was adopted so that maximum information can be obtained from a minimum number of experiments. Response surface methodology was applied successfully to rubber compound design using a rotatable central compound design. Compounding trials were carried out at design points, and the rubber vulcanizates were characterized for modulus, tensile strength, elongation at break, tear strength, bound rubber, and free volume parameters ,3 and I3. The experimental data was used to generate mathematical models by multiple linear regression analysis using MATLAB (version 6) package. The variability of the postulated models was tested by analysis of variance (ANOVA) and R2 tests and was found to be adequate. The accuracy of the models generated was tested by making an experimental trial. POLYM. COMPOS., 2009. © 2009 Society of Plastics Engineers [source] Cost-constrained G -efficient Response Surface Designs for Cuboidal RegionsQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 2 2006Youjin Park Abstract In many industrial experiments there are restrictions on the resource (or cost) required for performing the runs in a response surface design. This will require practitioners to choose some subset of the candidate set of experimental runs. The appropriate selection of design points under resource constraints is an important aspect of multi-factor experimentation. A well-planned experiment should consist of factor-level combinations selected such that the resulting design will have desirable statistical properties but the resource constraints should not be violated or the experimental cost should be minimized. The resulting designs are referred to as cost-efficient designs. We use a genetic algorithm for constructing cost-constrained G -efficient second-order response surface designs over cuboidal regions when an experimental cost at a certain factor level is high and a resource constraint exists. Consideration of practical resource (or cost) restrictions and different cost structures will provide valuable information for planning effective and economical experiments when optimizing statistical design properties. Copyright © 2005 John Wiley & Sons, Ltd. [source] Robust designs for misspecified exponential regression modelsAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 2 2009Xiaojian Xu Abstract We consider the construction of designs for exponential regression. The response function is an only approximately known function of a specified exponential function. As well, we allow for variance heterogeneity. We find minimax designs and corresponding optimal regression weights in the context of the following problems: (1) for nonlinear least-squares (LS) estimation with homoscedasticity, determine a design to minimize the maximum value of the integrated mean-squared error (IMSE), with the maximum being evaluated for the possible departures from the response function; (2) for nonlinear LS estimation with heteroscedasticity, determine a design to minimize the maximum value of IMSE, with the maximum being evaluated over both types of departures; (3) for nonlinear weighted LS estimation, determine both weights and a design to minimize the maximum IMSE; and (4) choose weights and design points to minimize the maximum IMSE, subject to a side condition of unbiasedness. Solutions to (1),(4) are given in complete generality. Copyright © 2009 John Wiley & Sons, Ltd. [source] Bayesian Optimal Designs for Phase I Clinical TrialsBIOMETRICS, Issue 3 2003Linda M. Haines Summary. A broad approach to the design of Phase I clinical trials for the efficient estimation of the maximum tolerated dose is presented. The method is rooted in formal optimal design theory and involves the construction of constrained Bayesian c - and D -optimal designs. The imposed constraint incorporates the optimal design points and their weights and ensures that the probability that an administered dose exceeds the maximum acceptable dose is low. Results relating to these constrained designs for log doses on the real line are described and the associated equivalence theorem is given. The ideas are extended to more practical situations, specifically to those involving discrete doses. In particular, a Bayesian sequential optimal design scheme comprising a pilot study on a small number of patients followed by the allocation of patients to doses one at a time is developed and its properties explored by simulation. [source] | ||||||||||||||||