• Title/Summary/Keyword: growth optimization

Search Result 624, Processing Time 0.032 seconds

Design optimization of the outlet holes for bone crystal growing with bioactive materials in dental implants: Part I. cross-sectional area

  • Lee, Yong Keun;Lee, Kangsoo
    • Journal of the Korean Crystal Growth and Crystal Technology
    • /
    • v.23 no.2
    • /
    • pp.67-75
    • /
    • 2013
  • In order to improve osseo-integration of a dental implant with bone crystal we studied an implant with holes inside its body to deliver bioactive materials based on a proposed patent. After bioactive material is absorbed, bone crystal can grow into holes to increase implant bonding in addition to surface integration. The larger cross section area of outlet holes showed the less values of the maximum stress, and the stress concentrations near the uppermost outlet holes were also reduced with an increasing number of outlet holes. The conclusion, that the uppermost outlet design improvement was most effective to reduce the stress concentration and improve the growth rate of bone crystal, could be drawn. After the design optimizations, Type 6-C had provided the best results in this study. The overall shape optimization studies on the shape, location, number, and so on, of the outlet holes, should be carried out further.

Basic Study on Spatial Optimization Model for Sustainability using Genetic Algorithm - Based on Literature Review - (유전알고리즘을 이용한 지속가능 공간최적화 모델 기초연구 - 선행연구 분석을 중심으로 -)

  • Yoon, Eun-Joo;Lee, Dong-Kun
    • Journal of the Korean Society of Environmental Restoration Technology
    • /
    • v.20 no.6
    • /
    • pp.133-149
    • /
    • 2017
  • As cities face increasing problems such as aging, environmental pollution and growth limits, we have been trying to incorporate sustainability into urban planning and related policies. However, it is very difficult to generate a 'sustainable spatial plans' because there are trade-offs among environmental, society, and economic values. This is a kind of non-linear problem, and has limitations to be solved by existing qualitative expert knowledge. Many researches from abroad have used the meta heuristic optimization algorithms such as Genetic Algorithms(GAs), Simulated Annealing(SA), Ant Colony Optimization(ACO) and so on to synthesize competing values in spaces. GAs is the most frequently applied theory and have been known to produce 'good-enough plans' in a reasonable time. Therefore we collected the research on 'spatial optimization model based GAs' and analyzed in terms of 'study area', 'optimization objective', 'fitness function', and 'effectiveness/efficiency'. We expect the results of this study can suggest that 'what problems the spatial optimization model can be applied to' and 'linkage possibility with existing planning methodology'.

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 1

  • Raghunath, Chaitra;Watson, Layne T.;Jrad, Mohamed;Kapania, Rakesh K.;Kolonay, Raymond M.
    • Advances in aircraft and spacecraft science
    • /
    • v.4 no.3
    • /
    • pp.297-316
    • /
    • 2017
  • With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

Service ORiented Computing EnviRonment (SORCER) for deterministic global and stochastic aircraft design optimization: part 2

  • Raghunath, Chaitra;Watson, Layne T.;Jrad, Mohamed;Kapania, Rakesh K.;Kolonay, Raymond M.
    • Advances in aircraft and spacecraft science
    • /
    • v.4 no.3
    • /
    • pp.317-334
    • /
    • 2017
  • With rapid growth in the complexity of large scale engineering systems, the application of multidisciplinary analysis and design optimization (MDO) in the engineering design process has garnered much attention. MDO addresses the challenge of integrating several different disciplines into the design process. Primary challenges of MDO include computational expense and poor scalability. The introduction of a distributed, collaborative computational environment results in better utilization of available computational resources, reducing the time to solution, and enhancing scalability. SORCER, a Java-based network-centric computing platform, enables analyses and design studies in a distributed collaborative computing environment. Two different optimization algorithms widely used in multidisciplinary engineering design-VTDIRECT95 and QNSTOP-are implemented on a SORCER grid. VTDIRECT95, a Fortran 95 implementation of D. R. Jones' algorithm DIRECT, is a highly parallelizable derivative-free deterministic global optimization algorithm. QNSTOP is a parallel quasi-Newton algorithm for stochastic optimization problems. The purpose of integrating VTDIRECT95 and QNSTOP into the SORCER framework is to provide load balancing among computational resources, resulting in a dynamically scalable process. Further, the federated computing paradigm implemented by SORCER manages distributed services in real time, thereby significantly speeding up the design process. Part 1 covers SORCER and the algorithms, Part 2 presents results for aircraft panel design with curvilinear stiffeners.

Real time optimization of fed-batch culture of recombinant yeast

  • Na, Jeong-Geol;Kim, Hyeon-Han;Jang, Yong-Geun;Jeong, Bong-Hyeon
    • 한국생물공학회:학술대회논문집
    • /
    • 2001.11a
    • /
    • pp.81-84
    • /
    • 2001
  • A real time optimization algorithm for fed-batch cultures of recombinant yeast to determine the optimal substrate feed rate profile has been developed. Its development involved four key steps: (1) development of reliable adaptive model. (2) development of optimization algorithm. (3) design of on-line model update algorithm to be incorporated into the optimization algorithm and (4) experimental validation. A recombinant Saccharomyces cerevisiae producing human parathyroid hormone (hPTH) was chosen as the model strain. It was found to be very successful in maintaining cell growth and galactose consumption at leigh levels, thus resulting in significant improvements in the productivity (up to 2.1 times) and intact hPTH concentration (up to 1.5 times) compared with the case of an intermittent glucose and galactose, or galactose feeding.

  • PDF

A Short-Term Wind Speed Forecasting Through Support Vector Regression Regularized by Particle Swarm Optimization

  • Kim, Seong-Jun;Seo, In-Yong
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.11 no.4
    • /
    • pp.247-253
    • /
    • 2011
  • A sustainability of electricity supply has emerged as a critical issue for low carbon green growth in South Korea. Wind power is the fastest growing source of renewable energy. However, due to its own intermittency and volatility, the power supply generated from wind energy has variability in nature. Hence, accurate forecasting of wind speed and power plays a key role in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. This paper presents a short-term wind speed prediction method based on support vector regression. Moreover, particle swarm optimization is adopted to find an optimum setting of hyper-parameters in support vector regression. An illustration is given by real-world data and the effect of model regularization by particle swarm optimization is discussed as well.

Model Development for Lactic Acid Fermentation and Parameter Optimization Using Genetic Algorithm

  • LIN , JIAN-QIANG;LEE, SANG-MOK;KOO, YOON-MO
    • Journal of Microbiology and Biotechnology
    • /
    • v.14 no.6
    • /
    • pp.1163-1169
    • /
    • 2004
  • An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

Approximate Multi-Objective Optimization of Bike Frame Considering Normal Load (수직하중을 고려한 자전거 프레임의 다중목적 최적설계)

  • Chae, Yunsik;Lee, Jongsoo
    • Journal of the Korean Society of Manufacturing Technology Engineers
    • /
    • v.24 no.2
    • /
    • pp.211-216
    • /
    • 2015
  • Recently, because of the growth in the leisure industry and interest in health, the demand for bicycles has increased. In this research, considering the vertical load on a bike frame under static state conditions, the deflection and mass of the bike frame were minimized by satisfying the service condition and performing optimization. The thickness of the bicycle-frame tube was set to a design variable, and its sensitivity was confirmed by an analysis of means (ANOM). To optimize the solution, a response-surface-method (RSM) model was constructed using D-Optimal and central composite design(CCD). The optimization was performed using a non-dominant sorting genetic algorithm (NSGA-II), and the optimal solution was verified by finite-element analysis.

Optimization of Tyrosinase Production using Neurospora crassa (Neurospora crassa를 이용한 Tyrosinase 생산의 최적화)

  • 채희정;유영제
    • Microbiology and Biotechnology Letters
    • /
    • v.19 no.3
    • /
    • pp.281-289
    • /
    • 1991
  • Neurospora crassa (KCTC 6079) produces tyrosinase (EC 1.14.18.1) during sexual differentiation under derepressed conditions in the presence of inducers such as amino acid analogues, antimetabolites or protein synthesis inhibitors. The selection of inducer concentration and induction time as well as inducer type are critical for the optimization of the enzyme production. The best inducer was found to be cycloheximide. Since cycloheximide was toxic to the cells, an optimal inducer concentration and an optimal induction time were determined to maximize the enzyme production from batch cultures. Mathematical models for the cell growth and the enzyme production were proposed and used for process optimization. By optimizing the induction conditions, maximum tyrosinase productivity was increased significantly.

  • PDF