A probabilistic model for fatigue crack propagation analysis

A simple probabilistic model for predicting crack growth behavior under random loading is presented. In the model, the parameters c and m in the Paris-Erdogan Equation are taken as random variables, and their stochastic characteristic values are obtained through fatigue crack propagation tests on an offshore structural steel under constant amplitude loading. Furthermore, by using the Monte Carlo simulation technique, the fatigue crack propagation life to reach a given crack length is predicted. The tests are conducted to verify the applicability of the theoretical prediction of the fatigue crack propagation.

Probabilistic Modeling of Rosette Formation

英文摘要: Rosetting, or forming a cell aggregate between a single target nucleated cell and a number of red blood cells (RBCs), is a simple assay for cell adhesion-mediated by specific receptor-ligand interaction. For example, rosette formation between sheep RBC and human lymphocytes has been used to differentiate T cells from B cells. Rosetting assay is commonly used to determine the interaction of Fc gamma-receptors (Fc gamma R) expressed on inflammatory cells and IgG-coated on RBCs. Despite its wide use in measuring cell adhesion, the biophysical parameters of rosette formation have not been well characterized. Here we developed a probabilistic model to describe the distribution of rosette sizes, which is Poissonian. The average rosette size is predicted to be proportional to the apparent two-dimensional binding affinity of the interacting receptor-ligand pair and their site densities. The model has been supported by experiments of rosettes mediated by four molecular interactions: Fc gamma RIII interacting with IgG, T cell receptor and coreceptor CD8 interacting with antigen peptide presented by major histocompatibility molecule, P-selectin interacting with P-selectin glycoprotein ligand 1 (PSGL-1), and L-selectin interacting with PSGL-1. The latter two are structurally similar and are different from the former two. Fitting the model to data enabled us to evaluate the apparent effective two-dimensional binding affinity of the interacting molecular pairs: 7.19x10(-5) mu m(4) for Fc gamma RIII-IgG interaction, 4.66x10(-3) mu m(4) for P-selectin-PSGL-1 interaction, and 0.94x10(-3) mu m(4) for L-selectin-PSGL-1 interaction. These results elucidate the biophysical mechanism of rosette formation and enable it to become a semiquantitative assay that relates the rosette size to the effective affinity for receptor-ligand binding.

Effects of geometric shape on the hydrodynamics of a self-propelled flapping foil

The hydrodynamics of a free flapping foil is studied numerically. The foil undergoes a forced vertical oscillation and is free to move horizontally. The effect of chord-thickness ratio is investigated by varying this parameter while fixing other ones such as the Reynolds number, the density ratio, and the flapping amplitude. Three different flow regimes have been identified when we increase the chord-thickness ratio, i.e., left-right symmetry, back-and-forth chaotic motion, and unidirectional motion with staggered vortex street. It is observed that the chord-thickness ratio can affect the symmetry-breaking bifurcation, the arrangement of vortices in the wake, and the terminal velocity of the foil. The similarity in the symmetry-breaking bifurcation of the present problem to that of a flapping body under constraint is discussed. A comparison between the dynamic behaviors of an elliptic foil and a rectangular foil at various chord-thickness ratios is also presented.

Smoothed Particle Hydrodynamics (SPH): an Overview and Recent Developments

Smoothed particle hydrodynamics (SPH) is a meshfree particle method based on Lagrangian formulation, and has been widely applied to different areas in engineering and science. This paper presents an overview on the SPH method and its recent developments, including (1) the need for meshfree particle methods, and advantages of SPH, (2) approximation schemes of the conventional SPH method and numerical techniques for deriving SPH formulations for partial differential equations such as the Navier-Stokes (N-S) equations, (3) the role of the smoothing kernel functions and a general approach to construct smoothing kernel functions, (4) kernel and particle consistency for the SPH method, and approaches for restoring particle consistency, (5) several important numerical aspects, and (6) some recent applications of SPH. The paper ends with some concluding remarks.

Hydrodynamics in an expanded bed of large size ion-exchange resin, and natural product adsorption

Successful applications of expanded bed adsorption (EBA) technology have been widely reported in the literature for protein purification. Little has been reported on the recovery of natural products and active components of Chinese herbal preparations using EBA technology. In this study, the hydrodynamic behavior in an expanded bed of cation resin, 001 x 7 Styrene-DVB, was investigated. Ephedrine hydrochloride (EH) was used as a model natural product to test the dynamic binding capacity (DBC) in the expanded bed. EBA of EH directly from a feedstock containing powdered herbs has also been investigated. These particles are different from commercially available expanded bed adsorbents by virtue of their large size (20S to 1030 gm). When the adsorbent bed is expanded to approximately 1.3 to 1.5 times its settled bed height, the axial liquid-phase dispersion coefficient was found to be of the order 10(-5) m(2) s(-1), which falls into the range 1.0 x 10(-6) to 1.0 X 10(-5) m(2) s(-1) observed previously in protein purification. Because of the favorable column efficiency (low axial dispersion coefficient), the recovery yield and purification factor values of EH directly from a feedstock reached 86.5% and 18, respectively. The results suggest that EBA technology holds promise for the recovery of natural products and active components of Chinese herbal preparations.

achieving on-time delivery: a two-stage probabilistic scheduling strategy for software projects

Chinese Academy of Sciences (ISCAS)

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.

Probabilistic modelling of soil moisture dynamics of irrigated cropland in the North China Plain

A probabilistic soil moisture dynamic model is used to estimate the soil moisture probability distribution and plant water stress of irrigated cropland in the North China Plain. Soil moisture and meteorological data during the period of 1998 to 2003 were obtained from an irrigated cropland ecosystem with winter wheat and maize in the North China Plain to test the probabilistic soil moisture dynamic model. Results showed that the model was able to capture the soil moisture dynamics and estimate long-term water balance reasonably well when little soil water deficit existed. The prediction of mean plant water stress during winter wheat and maize growing season quantified the suitability of the wheat-maize rotation to the soil and climate environmental conditions in North China Plain under the impact of irrigation. Under the impact of precipitation fluctuations, there is no significant bimodality of the average soil moisture probability density function.