Information updates and inventory decisions for supply chain management.

Information updates and inventory decisions for supply chain management

MODEL VALIDATION VIA UNCERTAINTY PROPAGATION USING RESPONSE Surface Models

Model validation has become a primary means to evaluate accuracy and reliability of computational simulations in engineering design. Mathematical models enable engineers to establish what the most likely response of a system is. However, despite the enormous power of computational models, uncertainty is inevitable in all model-based engineering design problems, due to the variation in the physical system itself, or lack of knowledge, and the use of assumptions by model builders. Therefore, realistic mathematical models should contemplate uncertainties. Due to the uncertainties, the assessment of the validity of a modeling approach must be conducted based on stochastic measurements to provide designers with the confidence of using a model. In this paper, a generic model validation methodology via uncertainty propagation is presented. The approach reduces the number of physical testing at each design setting to one by shifting the evaluation effort to uncertainty propagation of the computational model. Response surface methodology is used to create metamodels as less costly approximations of simulation models for uncertainty propagation. The methodology is illustrated with the examination of the validity of a finiteelement analysis model for predicting springback angles in a sample flanging process

Northwestern University

1 Model validation has become a primary means to evaluate accuracy and reliability of computational simulations in engineering design. Due to uncertainties involved in modeling, manufacturing processes, and measurement systems, the assessment of the validity of a modeling approach must be conducted based on stochastic measurements to provide designers with the confidence of using a model. In this paper, a generic model validation methodology via uncertainty propagation and data transformations is presented. The approach reduces the number of physical tests at each design setting to one by shifting the evaluation effort to uncertainty propagation of the computational model. Response surface methodology is used to create metamodels as less costly approximations of simulation models for the uncertainty propagation. Methods for validating models with both normal and nonnormal response distributions are proposed. The methodology is illustrated with the examination of the validity of two finite element analysis models for predicting springback angles in a sample flanging process

Approaches for model validation: Methodology and illustration on a sheet metal flanging process

Model validation has become an increasingly important issue in the decisio

Neuroprotective and cerebrovascular effects of endogenous N-Arachidonoyl-GABA and its putative Cox-2 metabolite – GABA conjugate with Prostaglandin E2

Introduction: The aim of the study was to compare the neuroprotective and cerebrovascular effects of bioactive, endogenous lipid – N-arachidonoyl-GABA (AA-GABA) and GABA conjugate with prostaglandin E2 (PGE2-GABA) by evaluation of a morphological state of rat brain tissue and lipofuscin levels under the condition of permanent focal brain ischemia, as well as cerebral circulation under the condition of global transient ischemia. Materials and methods: The study has been implemented using the models of the left middle cerebral artery occlusion (MCAO) and global transient ischemia of the brain. A morphological examination of the brain tissue, a registration of local blood flow by laser flowmeter, and quantitative measurement of lipofuscin by fluorescence spectroscopy were used. Results and discussion: AA-GABA and the putative COX-2 metabolite PGE2-GABA showed significant neuroprotective and cerebrovascular effects in rat models of global and focal cerebral ischemia. In the MCAO model, AA-GABA and PGE2-GABA at a dose of 2 mg/kg/day administered i.p. for 6 or 12 days led to: 1) significant restoration of neurons and glial cells with intracellular regeneration of cytoplasmic and nuclear structures, 2) decrease in brain tissue edema; 3) attenuated thrombosis and stasis, and 4) absence of large necrotic foci in rat brain tissue. AA-GABA and PGE2-GABA at the same dose prevented excessive accumulation of lipofuscin in both brain hemispheres in rats with MCAO. All the studied compounds increase cerebral blood circulation in rats subjected to global transient ischemia. However, the cerebrovascular effect of PGE2-GABA was superior to the activity of AA-GABA and all other tested compounds. AA-GABA and PGE2-GABA, unlike PGE2 and nimodipine, increase the cerebral blood flow in rats with global transient brain ischemia and have no influence on the intact animals. Apparently, the GABAergic vascular system of the brain is involved in the mechanisms of the neuroprotective action of AA-GABA and PGE2-GABA. Conclusion: For the first time, we demonstrated the ability of AA-GABA and its putative metabolite COX-2 PGE2-GABA to improve cerebral circulation, attenuate structural damage and lipofuscin accumulation during cerebral ischemia. The natural origin of AA-GABA, which possesses neuroprotective and cerebrovascular activity, as well as anti-aggregatory activity, allows considering AA-GABA as one of the endogenous protective factors in ischemic brain lesions. Graphical abstract