Model vahdation

Ekambra etal. [21] compared the results from ID, 2D, and 3D simulations of a bubble column with experimental results. They obtained similar results for holdup and axial velocity, while eddy viscosity, Reynolds stresses, and energy dissipation were very different in the three simulations as shown in Figure 15.7. This example also illustrates the importance of selecting the right variables for model vahdation. A 2D model will yield good results for velocity but will predict all variables based on turbulent characteristics poorly. 

I found in the model-vaHdation phase with the omission of any diagnostic that... 

Fletcher, S., Cununmgs, C.G., Rivas, K., Katt, W.P., Homey, C., Buckner, F.S., Chakrabarti, D., Sebti, S.M., Gelb, M.H., Van Voorhis, W.C., and Hamilton, A.D. (2008). Potent, plasmodium-selective famesyltransferase inhibitors that arrest the growth of malaria parasites structure-activity relationships of ethylenediamine-analogue scaffolds and homology model vahdation. J Med Chem 51 5176-5197. 

Moreover, a final 3D-QSAR model vahdation was done using a prospective study with an external test set. The 82 compounds from the data set were used in a lead optimization project. A CoMFA model gave an (cross validated) value of 0.698 for four relevant PLS components and a conventional of 0.938 were obtained for those 82 compounds. The steric descriptors contributed 54% to the total variance, whereas the electrostatic field explained 46%. The CoMSIA model led to an (cross vahdated) value of 0.660 for five PLS components and a conventional of 0.933. The contributions for steric, electrostatic, and hydrophobic fields were 25, 44, and 31%. As a result, it was proved that the basic S4-directed substituents should be replaced against more hydrophobic building blocks to improve pharmacokinetic properties. The structural and chemical interpretation of CoMFA and CoMSIA contour maps directly pointed to those regions in the Factor Xa binding site, where steric, electronic, or hydrophobic effects play a dominant role in ligand-receptor interactions. 

Figure 6.8 Depiction of the recursive process used in our laboratory to develop QSAR models for predicting estrogen receptor binding. The process starts with data from an initial set of chemicals from the literature QSAR modeling. These preliminary QSAR models are used prospectively to define a set of chemicals that will further improve the model s robustness and predictive capability. The new chemicals are assayed, and these data are then used to challenge and refine the QSAR models. Vahdation of the model is critical. The process emphasizes the living model concept.

Turner, D.B., Willett, P., Eerguson, A.M. and Heritage, T.W. (1999) Evaluation of a novel molecular vibration-based descriptor (EVA) for QSAR studies. 2. Model vahdation using a benchmark steroid dataset /. Comput. Aid. Mol. Des., 13, 271—296. 

The maximum number of balances equals the number of metabolic knots. An additional balance around the whole cell may be useful for later model vahdation, but does not give additional information besides the balances around the individual knots. 

Obviously, the less the model to be apphed is vahdated by experimental results or the more the conditions of the experiments used for model vahdation differ from the conditions of the model apphcation, the larger becomes the model uncertainty. 

Paul CS, van Sint Annaland M, Kuipers JAM Fluidised bed membrane reactor for ultrapure hydrogen production via methane steam reforming experimental demonstration and model vahdation, Chem Eng Sci 62 2989—3007, 2007. 

Model vahdation phase consists in establishing the range of validity and the accuracy of the code in describing fuel cell behaviour under different operating con-... 

Chapter 9 shows how compartmental models may be used to describe physiological systems, for example, pharmacokinetics. The production, distribution, transport, and interaction of exogenous materials, such as drugs or tracers, and endogenous materials, such as hormones, are described. Examples of both linear and nonlinear compartmental models are presented, as well as parameter estimation, optimal experiment design, and model vahdation. 

In GA-PLS, model vahdation was achieved through leave-one-out cross-validation (LOO CV) to find the best number of latent variables (Lv) to be used in calibration and prediction. External validation (for a test set), and the predictive ability was statistically evaluated through the root mean square errors of calibration (RMSEC) and vahdation (RMSECV). The results indicate that four latent variables are the best number to make a model. The following equation represents the best model achieved by GA-PLS ... 

An observation of the results of cross-validation revealed that all but one of the compounds in the dataset had been modeled pretty well. The last (31st) compound behaved weirdly. When we looked at its chemical structure, we saw that it was the only compound in the dataset which contained a fluorine atom. What would happen if we removed the compound from the dataset The quahty ofleaming became essentially improved. It is sufficient to say that the cross-vahdation coefficient in-CTeased from 0.82 to 0.92, while the error decreased from 0.65 to 0.44. Another learning method, the Kohonen s Self-Organizing Map, also failed to classify this 31st compound correctly. Hence, we had to conclude that the compound containing a fluorine atom was an obvious outlier of the dataset. 

A real-time optimization (RTO) system determines set point changes and implements them via the computer control system without intervention from unit operators. The RTO system completes all data transfer, optimization c culations, and set point implementation before unit conditions change and invahdate the computed optimum. In addition, the RTO system should perform all tasks without upsetting plant operations. Several steps are necessaiy for implementation of RTO, including determination of the plant steady state, data gathering and vahdation, updating of model parameters (if necessaiy) to match current operations, calculation of the new (optimized) set points, and the implementation of these set points. 

To determine if a process unit is at steady state, a program monitors key plant measurements (e.g., compositions, product rates, feed rates, and so on) and determines if the plant is steady enough to start the sequence. Only when all of the key measurements are within the allowable tolerances is the plant considered steady and the optimization sequence started. Tolerances for each measurement can be tuned separately. Measured data are then collec ted by the optimization computer. The optimization system runs a program to screen the measurements for unreasonable data (gross error detection). This validity checkiug automatically modifies tne model updating calculation to reflec t any bad data or when equipment is taken out of service. Data vahdation and reconciliation (on-line or off-line) is an extremely critical part of any optimization system. 

The method for estimating point efficiency, outhned here, is not the only approach available for sieve plates, and more mechanistic methods are under development. For example, Prado and Fair [Ind. Eng. Chem. Re.s., 29, 1031 (1990)] have proposed a method whereby bubbling and jetting are taken into account however the method has not been vahdated tor nonaqueous systems. Chen and Chuang [Ind. Eng. Chem. Re.s., 32, 701 (1993)] have proposed a more mechanistic model for predicting point efficiency, but it needs evaluation against a commercial scale distillation data bank. One can expect more development in this area of plate efficiency prediction. 

Unfortunately, models are rarely exac4. The semblance of sophistication inherent in the model and used to develop parameter estimates frequentlv masks their deficiencies. Models are only approximate, and their predictions when the parameter estimates are based on analysis of plant performance must be considered as approximate. Vahdation of the model and the parameter estimates using other operating conditions will reduce the likelihood that the conclusions have significant... 

Many of the initial theoretical models used to vahdate the concept of coherent control and optimal control have been based on the interaction of the electric field of the laser light with a molecular dipole moment [43, 60, 105]. This represents just the first, or lowest, term in the expression for the interaction of an electric field with a molecule. Many of the successful optimal control experiments have used electric fields that are capable of ionizing the molecules and involve the use of electric field strengths that lead to major distortions of the molecular electronic structure. With this in mind, there has been discussion in the... 

QSAR model validation is an essential task in developing a statistically vahd and predictive model, because the real utility of a QSAR model is in its ability to predict accurately the modeled property for new compounds. The following approaches have been used for the vahdation of QSAR Eqs. 1-20 ... 

Aqueous solubility is selected to demonstrate the E-state application in QSPR studies. Huuskonen et al. modeled the aqueous solubihty of 734 diverse organic compounds with multiple linear regression (MLR) and artificial neural network (ANN) approaches [27]. The set of structural descriptors comprised 31 E-state atomic indices, and three indicator variables for pyridine, ahphatic hydrocarbons and aromatic hydrocarbons, respectively. The dataset of734 chemicals was divided into a training set ( =675), a vahdation set (n=38) and a test set (n=21). A comparison of the MLR results (training, r =0.94, s=0.58 vahdation r =0.84, s=0.67 test, r =0.80, s=0.87) and the ANN results (training, r =0.96, s=0.51 vahdation r =0.85, s=0.62 tesL r =0.84, s=0.75) indicates a smah improvement for the neural network model with five hidden neurons. These QSPR models may be used for a fast and rehable computahon of the aqueous solubihty for diverse orgarhc compounds. 

Taylor PDF, De Bievre P, Walder AJ, Entwistle A (1995) Vahdation of the analytical linearity and mass discrimination correction model exhibited by a Multiple Collector Inductively Coupled Plasma Mass Spectrometer by means of a set of synthetic uranium isotope mixtures. J Anal At Spectrom 10 395-398... 

Annaswamy, A. M., M. Fleifil, J. W. Rumsey, R. Prasanth, J.P. Hathout, and A. F. Ghoniem. 2000. Thermoacoustic instability Model based optimal control designs and experimental vahdation. IEEE Transactions on Control Systems Technology 8(6). 

The WHO/IPCS international workshop on skin sensitization in chemical risk assessment (WHO/IPCS 2007) concluded (Q)SARs and expert systems for identification of sensitizing capacity have not been vahdated to date, but may be used as part of a weight of evidence approach for identifying the sensitizing capacity of chemicals. There are certain local (Q)SARs that can be used for a small range of chemicals. However, these are currently insufficient to cover the full range of chemicals. The Workshop recommended that QSAR models need to be further developed, and the apphcabihty domain of each model needs to be established. ... 

The US-EPA s Office of Pollution Prevention and Toxics (OPPT) uses a tiered approach to exposure assessment (US-EPA 2007a). Exposure assessments may use measured data or model estimates. Representative measured data of known quahty are preferred over model estimates and are needed to vahdate and improve models. The US-EPA Guidelines for Exposure Assessment... 

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