• Biotechnology and Bioprocess Engineering:BBE
• /
• v.11 no.1
• /
• pp.61-66
• /
• 2006

The simple Langmuir isotherm is frequently employed to describe the equilibrium behavior of protein adsorption on a wide variety of adsorbents. The two adjustable parameters of the Langmuir isotherm - the saturation capacity, or $q_m$, and the dissociation constant, $K_d$ - are usually estimated by fitting the isotherm equation to the equilibrium data acquired from batch equilibration experiments. In this study, we have evaluated the possibility of estimating $q_m$ and $K_d$ for the adsorption of bovine serum albumin to a cation exchanger using batch kinetic data. A rate model predicated on the kinetic form of the Langmuir isotherm, with three adjustable parameters ($q_m,\;K_d$, and a rate constant), was fitted to a single kinetic profile. The value of $q_m$ determined as the result of this approach was quantitatively consistent with the $q_m$ value derived from the traditional batch equilibrium data. However, the $K_d$ value could not be retrieved from the kinetic profile, as the model fit proved insensitive to this parameter. Sensitivity analysis provided significant insight into the identifiability of the three model parameters.

• Journal of applied mathematics & informatics
• /
• v.26 no.3_4
• /
• pp.519-530
• /
• 2008

This paper studies the multi-domain coupled system of one dimensional Arctic temperature field and establishes identification model about the thermodynamic parameters of sea ice (heat storage capacity, density and conductivity) by the so-called output least-square estimate according to the temperature data acquired by a monitor buoy installed in the Arctic ocean. By the optimal control theory, the existence and dependability of weak solution and the identifiability of identification model have been given. Moreover, necessary optimality condition is proposed. Furthermore, the optimal algorithm for the identification model is constructed. By using the optimal thermodynamic parameters of Arctic sea ice, the numerical simulation is implemented, and the numerical results of temperature distribution of Arctic sea ice are demonstrated.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.22 no.4
• /
• pp.151-165
• /
• 1997

We propose a method for estimating the probability of perfect PM from successive failure times of a repairable system. The system under study is maintained preventively at periodic times, and it undergoes minimal repair at failure. We consider Brown-Proschan imperfect PM model in which the system is restored to a condition as good as new with probability P and is otherwise restored to its condition just prior to failure. We discuss the identifiability problem when the PM modes are not recorded. The expectation-maximization principle is employed to handle the incomplete data problem. We assume that the lifetime distribution belongs to a parametric family with increasing failure rate. For the two parameter Weibull lifetime distribution, we propose a specific algorithm for finding the maximum lifelihood estimates of the reliability parameters : the probability of perfect PM (P), as well as the distribution parameters. The estimation method will provide useful results for maintaining real systems.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.9 no.2
• /
• pp.217-224
• /
• 2005

A methodology of selecting an optimal model is proposed for applying a frequency-domain SI method effectively. Instead of using a reduced finite element model, a reasonably detail finite element model is established first and then the model is identified. To satisfy the identifiability criterion, a parameter grouping scheme is applied to control the number of unknowns. Among the simulated member grouping cases, an optimal model is selected as the one with the minimal statistical error. The proposed approach has been examined through simulation studies on a single span box-girder bridge.