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Optimization Design (optimization + design)

Distribution by Scientific Domains

Engineering	50%

Selected Abstracts

Research on the thermal corridor of a hypersonic vehicle

HEAT TRANSFER - ASIAN RESEARCH (FORMERLY HEAT TRANSFER-JAPANESE RESEARCH), Issue 4 2008
Ling Jin
Abstract The establishment of a reasonable physical model and an effective solution scheme for the thermal corridor is very important to thermal protection structure design, trajectory selection, aerodynamic configuration optimization design, etc. The concept of a thermal corridor for a hypersonic vehicle was analyzed and a physical model was proposed in this paper. Furthermore, the governing equations and the corresponding algorithm for the thermal corridor were discussed. The envelopes of the height,velocity curves at typical positions of the vehicle X43 were calculated, the characteristics of the thermal corridor were summarized, the effect of the thermal protection material on the thermal corridor was discussed, and the emission coefficient of the thermal protection material was defined. The results indicate that the thermal corridor depends on the emission coefficient of the surface material, the flow conditions, and turbulence transition position. © 2008 Wiley Periodicals, Inc. Heat Trans Asian Res, 37(4): 218,223, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/htj.20203 [source]

Enhancing the Production of Fc Fusion Protein in Fed-Batch Fermentation of Pichia pastoris by Design of Experiments

BIOTECHNOLOGY PROGRESS, Issue 3 2007
Henry Lin
This study focuses on the feasibility of producing a therapeutic Fc fusion protein in Pichia pastoris (P. pastoris) and presents an optimization design of experiment (DOE) strategy in a well-defined experimental space. The parameters examined in this study include pH, temperature, salt supplementation, and batch glycerol concentration. The effects of these process conditions were captured by statistical analysis focusing on growth rate and titer responses. Batch medium and fermentation conditions were also investigated prior to the DOE study in order to provide a favorable condition to enable the production of this Fc fusion protein. The results showed that approximately 373 mg/L of the Fc fusion protein could be produced. The pH was found to be particularly critical for the production of this Fc fusion protein. It was significantly higher than the conventional, recommended pH for P. pastoris fermentation. The development of this process shows that protein production in P. pastoris is protein specific, and there is not a set of pre-defined conditions that can work well for all types of proteins. Thorough process development would need to be performed for every type of protein in order for large-scale production in P. pastoris to be feasible. [source]

Optimal Design of the Adaptive Sample Size and Sampling Interval np Control Chart

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 6 2004
Zhang Wu
Abstract Recent research has shown that the adaptive control charts are quicker than the traditional static charts in detecting process shifts. This paper develops the algorithm for the optimization designs of the adaptive np control charts for monitoring the process fraction non-conforming p. It includes the variable sample size chart, the variable sampling interval chart, and the variable sample size and sampling interval chart. The performance of the adaptive np charts is measured by the average time to signal under the steady-state mode, which allows the shift in p to occur at any time, even during the sampling inspection. By studying the performance of the adaptive np charts systematically, it is found that they do improve effectiveness significantly, especially for detecting small or moderate process shifts. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Framework for the Rapid Optimization of Soluble Protein Expression in Escherichia coli Combining Microscale Experiments and Statistical Experimental Design

BIOTECHNOLOGY PROGRESS, Issue 4 2007
R. S. Islam
A major bottleneck in drug discovery is the production of soluble human recombinant protein in sufficient quantities for analysis. This problem is compounded by the complex relationship between protein yield and the large number of variables which affect it. Here, we describe a generic framework for the rapid identification and optimization of factors affecting soluble protein yield in microwell plate fermentations as a prelude to the predictive and reliable scaleup of optimized culture conditions. Recombinant expression of firefly luciferase in Escherichia coli was used as a model system. Two rounds of statistical design of experiments (DoE) were employed to first screen (D-optimal design) and then optimize (central composite face design) the yield of soluble protein. Biological variables from the initial screening experiments included medium type and growth and induction conditions. To provide insight into the impact of the engineering environment on cell growth and expression, plate geometry, shaking speed, and liquid fill volume were included as factors since these strongly influence oxygen transfer into the wells. Compared to standard reference conditions, both the screening and optimization designs gave up to 3-fold increases in the soluble protein yield, i.e., a 9-fold increase overall. In general the highest protein yields were obtained when cells were induced at a relatively low biomass concentration and then allowed to grow slowly up to a high final biomass concentration, >8 g·L,1. Consideration and analysis of the model results showed 6 of the original 10 variables to be important at the screening stage and 3 after optimization. The latter included the microwell plate shaking speeds pre- and postinduction, indicating the importance of oxygen transfer into the microwells and identifying this as a critical parameter for subsequent scale translation studies. The optimization process, also known as response surface methodology (RSM), predicted there to be a distinct optimum set of conditions for protein expression which could be verified experimentally. This work provides a generic approach to protein expression optimization in which both biological and engineering variables are investigated from the initial screening stage. The application of DoE reduces the total number of experiments needed to be performed, while experimentation at the microwell scale increases experimental throughput and reduces cost. [source]