Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.

A microstructure based model of the deformation mechanisms and flow stress during elevated temperature straining of a magnesium alloy

We show that the variation of flow stress with strain rate and grain size in a magnesium alloy deformed at a constant strain rate and 450 °C can be predicted by a crystal plasticity model that includes grain boundary sliding and diffusion. The model predicts the grain size dependence of the critical strain rate that will cause a transition in deformation mechanism from dislocation creep to grain boundary sliding, and yields estimates for grain boundary fluidity and diffusivity.

Circulation dynamics and its influence on European and Mediterranean January-April climate over the past half millennium: results and insights from instrumental data, documentary evidence and coupled climate models

We use long instrumental temperature series together with available field reconstructions of sea-level pressure (SLP) and three-dimensional climate model simulations to analyze relations between temperature anomalies and atmospheric circulation patterns over much of Europe and the Mediterranean for the late winter/early spring (January–April, JFMA) season. A Canonical Correlation Analysis (CCA) investigates interannual to interdecadal covariability between a new gridded SLP field reconstruction and seven long instrumental temperature series covering the past 250 years. We then present and discuss prominent atmospheric circulation patterns related to anomalous warm and cold JFMA conditions within different European areas spanning the period 1760–2007. Next, using a data assimilation technique, we link gridded SLP data with a climate model (EC-Bilt-Clio) for a better dynamical understanding of the relationship between large scale circulation and European climate. We thus present an alternative approach to reconstruct climate for the pre-instrumental period based on the assimilated model simulations. Furthermore, we present an independent method to extend the dynamic circulation analysis for anomalously cold European JFMA conditions back to the sixteenth century. To this end, we use documentary records that are spatially representative for the long instrumental records and derive, through modern analogs, large-scale SLP, surface temperature and precipitation fields. The skill of the analog method is tested in the virtual world of two three-dimensional climate simulations (ECHO-G and HadCM3). This endeavor offers new possibilities to both constrain climate model into a reconstruction mode (through the assimilation approach) and to better asses documentary data in a quantitative way.

[(99m)Tc]Demomedin C, a radioligand based on human gastrin releasing peptide(18-27): synthesis and preclinical evaluation in gastrin releasing peptide receptor-expressing models

The synthesis and preclinical evaluation of [(99m)Tc]Demomedin C in GRPR-expressing models are reported. Demomedin C resulted by coupling a Boc-protected N(4)-chelator to neuromedin C (human GRP(18-27)), which, after (99m)Tc-labeling, afforded [(99m)Tc]Demomedin C. Demomedin C showed high affinity and selectivity for the GRPR during receptor autoradiography on human cancer samples (IC(50) in nM: GRPR, 1.4 ± 0.2; NMBR, 106 ± 18; and BB(3)R, >1000). It triggered GRPR internalization in HEK-GRPR cells and Ca(2+) release in PC-3 cells (EC(50) = 1.3 nM). [(99m)Tc]Demomedin C rapidly and specifically internalized at 37 °C in PC-3 cells and was stable in mouse plasma. [(99m)Tc]Demomedin C efficiently and specifically localized in human PC-3 implants in mice (9.84 ± 0.81%ID/g at 1 h pi; 6.36 ± 0.85%ID/g at 4 h pi, and 0.41 ± 0.07%ID/g at 4 h pi block). Thus, human GRP-based radioligands, such as [(99m)Tc]Demomedin C, can successfully target GRPR-expressing human tumors in vivo while displaying attractive biological features--e.g. higher GRPR-selectivity--vs their frog-homologues.

Defining new criteria for selection of cell-based intestinal models using publicly available databases

The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies.

Fastener-Based Computational Models of Cold-Formed Steel Shear Walls

Cold-formed steel (CFS) combined with wood sheathing, such as oriented strand board (OSB), forms shear walls that can provide lateral resistance to seismic forces. The ability to accurately predict building deformations in damaged states under seismic excitations is a must for modern performance-based seismic design. However, few static or dynamic tests have been conducted on the non-linear behavior of CFS shear walls. Thus, the purpose of this research work is to provide and demonstrate a fastener-based computational model of CFS wall models that incorporates essential nonlinearities that may eventually lead to improvement of the current seismic design requirements. The approach is based on the understanding that complex interaction of the fasteners with the sheathing is an important factor in the non-linear behavior of the shear wall. The computational model consists of beam-column elements for the CFS framing and a rigid diaphragm for the sheathing. The framing and sheathing are connected with non-linear zero-length fastener elements to capture the OSB sheathing damage surrounding the fastener area. Employing computational programs such as OpenSees and MATLAB, 4 ft. x 9 ft., 8 ft. x 9 ft. and 12 ft. x 9 ft. shear wall models are created, and monotonic lateral forces are applied to the computer models. The output data are then compared and analyzed with the available results of physical testing. The results indicate that the OpenSees model can accurately capture the initial stiffness, strength and non-linear behavior of the shear walls.