von-Mises Model Research Articles

An isotropic damage model based on fracture mechanics for concrete

This paper presents an isotropic damage model for quasi-brittle materials and demonstrates its performance in crack propagation analysis for concrete. The suggested damage model is based on fracture mechanics for concrete in terms of the fracture energy and is therefore capable of simulating strain-softening behavior without mesh-size dependency. After the cohesive crack model is incorporated into a damage model in a 1D setting, the 1D model is extended to multi-dimensional problems by means of the equivalent strain of the modified von-Mises model. Several numerical examples are presented to examine the fundamental characteristics of the proposed damage model. In particular, we demonstrate that finite element solutions with the damage model are independent of mesh size and that the energy balance evaluated for the fracture process in a three-point bending test for a specimen with a single-edge notch is consistent with the fracture energy. A benchmark test for a mixed-mode fracture is also conducted to demonstrate the performance of the proposed damage model.

Analysis of forming characteristics of Ta EFP according to material model

This paper presents numerical analysis result of forming characteristics of Ta explosively formed penetrator (EFP) according to various material models and their values. Dynamic material properties of Ta were measured with static tensile testing machine and Hopkinson pressure bar tests. We used AUTODYN hydrodynamic code to simulate these phenomena. We used three material models, such as Von-Mises model, linear hardening model and Johnson-Cook model. We also compared the numerical results with the EFP forming test data. The numerical results show that material model and its parameter are so important to predict the shape of formed penetrator and Von-Mises model predicts the shape of the formed liner most well. We also analysed the influence of liner thickness on EFP formation using the verified numerical model.

Assessment of Long-Term Habituation Correlates in Event-Related Potentials Using a von Mises Model

In our preliminary work we were able to demonstrate habituation by analyzing attention correlates in single-trial sequences of auditory event-related potentials (ERPs). Despite different quantitative studies of instantaneous phase of ERPs in long-term habituation, there have been no former studies in generative process underlying the distribution of instantaneous phase information in the context of long-term habituation and its relation to attentional binding. For this means we used a von Mises model, representing the phase information over a set of single trial responses. Additionally we use a quantitative neurofunctional model to predict the dynamics of the instantaneous phase in single-trial ERP data during the long-term habituation. Measured habituation data is used to cross-validate the model's prediction. We conclude that the described method allows for an assessment of dynamic changes in the course of long-term habituation. The results also reinforce our neurofunctional multiscale model of long-term habituation and show the applicability of the described method for the experimental/clinical neurodiagnostic assessment of attentional binding.

Behavior analysis of elderly using topic models

This paper describes two new topic models for the analysis of human behavior in homes that are equipped with sensor networks. The models are based on Latent Dirichlet Allocation (LDA) topic models and can detect patterns in sensor data in an unsupervised manner. LDA–Gaussian, the first variation of the model, is a combination of a Gaussian Mixture Model and the LDA model. Here the multinomial distribution that is normally used in the LDA model is replaced by a set of Gaussian distributions. LDA–Poisson, the second variation of the model, uses a set of Poisson distribution to model the observations. The Poisson distribution is better suited to handle counts of stochastic events but less well-suited to model time. For this we use the von Mises distribution, resulting in ‘LDA–Poisson–von-Mises’. The parameters of the models are determined with an EM-algorithm. The models are evaluated on more than 450 days of real-world sensor data, gathered in the homes of five elderly people, and are compared with a baseline approach where standard k-means clustering is used to quantize the data. We show that the new models find more meaningful topics than the baseline and that a semantic description of these topics can be given. We also evaluated the models quantitatively, using perplexity as measure for the model fit. Both LDA–Gaussian and LDA–Poisson result in much better models than the baseline, and our experiments show that, of the proposed models, the LDA–Poisson–von-Mises model performs best.

Springback Prediction Using the Split-Ring Test Based on a Combined Anisotropic Hardening Model

Material model which could describe the Bauschinger effect is essential to accurately predict springback since strain path reverse is quite common in sheet metal forming. In this paper, a combined isotropic-kinematic hardening law which can capture the Bauschinger effect, transient behavior and permanent softening was used to model the hardening behavior. Also, the non-quadratic anisotropic yield function, Yld2000-2d, was chosen to describe the anisotropy. An inverse identificat- ion method was carried out to calibrate the material parameters by using uni-axial tension and Bauschinger simple shear tests. Experiments of cylindrical cup drawing and following split-ring tests were performed. Similar processes were carried out by numerical simulation, and springback predicted by present model was compared with experiments and that of vonMises model. The result shows that the current model significantly improves the accuracy of springback prediction.

Measurement-based statistical model and simulation of mobile station anisotropic power angular spectrum

A statistical channel model of mobile station (MS) anisotropic power azimuth spectrum (PAS) is presented. This model is based on extensive outdoor urban/suburban channel measurements, and it uses the Von Mises (VM) function. We propose a method to generate the VM model parameters from the direction spread (DS) knowledge. Combined with a random generation of DS, we obtain a statistical PAS simulation.

Phase analysis of circadian-related genes in two tissues.

BackgroundRecent circadian clock studies using gene expression microarray in two different tissues of mouse have revealed not all circadian-related genes are synchronized in phase or peak expression times across tissues in vivo. Instead, some circadian-related genes may be delayed by 4–8 hrs in peak expression in one tissue relative to the other. These interesting biological observations prompt a statistical question regarding how to distinguish the synchronized genes from genes that are systematically lagged in phase/peak expression time across two tissues.ResultsWe propose a set of techniques from circular statistics to analyze phase angles of circadian-related genes in two tissues. We first estimate the phases of a cycling gene separately in each tissue, which are then used to estimate the paired angular difference of the phase angles of the gene in the two tissues. These differences are modeled as a mixture of two von Mises distributions which enables us to cluster genes into two groups; one group having synchronized transcripts with the same phase in the two tissues, the other containing transcripts with a discrepancy in phase between the two tissues. For each cluster of genes we assess the association of phases across the tissue types using circular-circular regression. We also develop a bootstrap methodology based on a circular-circular regression model to evaluate the improvement in fit provided by allowing two components versus a one-component von-Mises model.ConclusionWe applied our proposed methodologies to the circadian-related genes common to heart and liver tissues in Storch et al. [2], and found that an estimated 80% of circadian-related transcripts common to heart and liver tissues were synchronized in phase, and the other 20% of transcripts were lagged about 8 hours in liver relative to heart. The bootstrap p-value for being one cluster is 0.063, which suggests the possibility of two clusters. Our methodologies can be extended to analyze peak expression times of circadian-related genes across more than two tissues, for example, kidney, heart, liver, and the suprachiasmatic nuclei (SCN) of the hypothalamus.

Experimental investigations on the ‘shallow crack effect’, on the 10 MnMoNi 5 5 steel, and computational analysis in the upper shelf by means of the global and local approaches

Shallow cracks have been of great interest for some years now, since it has been observed that standard fracture toughness parameters, determined on deep crack specimens, exhibit a geometrical dependence and that most of the structures containing cracks (in particular pressure vessels) exhibit crack depth to width ratios a/W much lower than fracture mechanics specimens tested in the laboratory. This study performed at MPA Stuttgart in collaboration with EDF, aimed first of all at investigating the ‘shallow crack effect’ on the high ductile, high strength, low strain-hardening shape welded 10 MnMoNi 5 5 steel over the whole temperature range of the transition region of toughness. Deep crack (CT25 and TPB25 with a/W=0.55) and shallow crack (TPB25 with a/W=0.066) specimens were tested, providing K IC, J i and J IC results. At the same time, computations were performed, in the upper shelf with, on the one hand, the usual elastic–plastic model (Von Mises model) and on the other hand, the local approach model of Rousselier. Experiments did not exhibit any shallow crack effect in the lower shelf (no increase in K IC) and show a slight effect in the transition region and in the upper shelf (slight increase in J i, larger increase in J IC). Computations confirmed the ability of the ‘modified’ Rousselier model to describe the macroscopical behaviour (F-CMOD curves) of the three types of specimens as well as to simulate their crack propagation behaviour (CMOD-Δ a curves). The combination of the Rousselier model with the line contour integral method enables us to develop the draft of an experimental method to determine the J-integral for any material and any initial crack length ( a/W remaining within 0.05 and 0.7), taking crack growth into account. This method, based on the measurement of the energy under the F-CMOD curve and an η c factor indexed on the current a/W ratio, provided an agreement within 10% and most of the time 5% between the experimental and computational J-integral results. Consequently, computations with the Rousselier model also correctly predicted the experimentally observed crack resistance curves, especially their geometrical dependence. The observation during crack growth of the triaxiality of the stress state in the first millimeters of the ligament enabled one to understand this geometrical dependence, high triaxiality accelerating crack growth leading to lower J–R curves. For shallow crack specimens, the crack tip being located close to the top surface, a stress relaxation occurs at this top surface leading to a loss of triaxiality at the crack tip and in the ligament, delaying crack growth and leading to higher crack resistance curves. Finally, the Rousselier model was found to confirm the experimentally observed J i values on the various tested specimens. Therefore, assuming that the Rousselier model can correctly describe initiation, computations with different stress–strain curves (different yield stress values and strain-hardening behaviours) were performed: it seems that the ‘shallow crack effect’ ( J i(shallow crack)/ J i(deep crack)) is controlled by strain-hardening independently of the yield stress, the absence of strain-hardening leading to the most important effect.