Finite element analysis of combined forming processes by means of rate dependent ductile damage modelling

Sheet metal forming is an inherent part of todays production industry. A major goal is to increase the forming limits of classical deep-drawing processes. One possibility to achieve that is to combine the conventional quasi-static (QS) forming process with electromagnetic high-speed (HS) post-forming. This work focuses on the finite element analysis of such combined forming processes to demonstrate the improvement which can be achieved. For this purpose, a cooperation of different institutions representing different work fields has been established. The material characterization is based on flow curves and forming limit curves for low and high strain rates obtained by novel testing devices. Further experimental investigations have been performed on the process chain of a cross shaped cup, referring to both purely quasi-static and quasi-static combined with electromagnetic forming. While efficient mathematical optimization algorithms support the new viscoplastic ductile damage modelling to find the optimum parameters based on the results of experimental material characterization, the full process chain is studied by means of an electro-magneto-mechanical finite element analysis. The constitutive equations of the material model are integrated in an explicit manner and implemented as a user material subroutine into the commercial finite element package LS-DYNA.     

Revealing determinants of two‐phase dynamics of P53 network under gamma irradiation based on a reduced 2D relaxation oscillator model

This study proposes a two‐dimensional (2D) oscillator model of p53 network, which is derived via reducing the multidimensional two‐phase dynamics model into a model of ataxia telangiectasia mutated (ATM) and Wip1 variables, and studies the impact of p53‐regulators on cell fate decision. First, the authors identify a 6D core oscillator module, then reduce this module into a 2D oscillator model while preserving the qualitative behaviours. The introduced 2D model is shown to be an excitable relaxation oscillator. This oscillator provides a mechanism that leads diverse modes underpinning cell fate, each corresponding to a cell state. To investigate the effects of p53 inhibitors and the intrinsic time delay of Wip1 on the characteristics of oscillations, they introduce also a delay differential equation version of the 2D oscillator. They observe that the suppression of p53 inhibitors decreases the amplitudes of p53 oscillation, though the suppression increases the sustained level of p53. They identify Wip1 and P53DINP1 as possible targets for cancer therapies considering their impact on the oscillator, supported by biological findings. They model some mutations as critical changes of the phase space characteristics. Possible cancer therapeutic strategies are then proposed for preventing these mutations’ effects using the phase space approach.Inspec keywords: physiological models, cellular biophysics, cancer, difference equations, delays, enzymes, biochemistry, molecular biophysics, gamma‐rays, radiation therapyOther keywords: two‐phase dynamics model, P53 network, gamma irradiation, 2D relaxation oscillator model, ATM model, Wip1 variables, p53‐regulators, cell fate decision, excitable relaxation oscillator, Wip1 time delay, state‐dependent delay differential equation, cell cycle arrest, cell apoptosis, cancer therapies, Wip1 overexpression, Wip1 downregulation, ATM deficiency, Mdm2 overexpression, Mdm2 downregulation, mutation effects, phase space approach     

Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm

Classification of brain hemorrhage computed tomography (CT) images provides a better diagnostic implementation for emergency patients. Attentively, each brain CT image must be examined by doctors. This situation is time-consuming, exhausting, and sometimes leads to making errors. Hence, we aim to find the best algorithm owing to a requirement for automatic classification of CT images to detect brain hemorrhage. In this study, we developed OzNet hybrid algorithm, which is a novel convolution neural networks (CNN) algorithm. Although OzNet achieves high classification performance, we combine it with Neighborhood Component Analysis (NCA) and many classifiers: Artificial neural networks (ANN), Adaboost, Bagging, Decision Tree, K-Nearest Neighbor (K-NN), Linear Discriminant Analysis (LDA), Naïve Bayes and Support Vector Machines (SVM). In addition, Oznet is utilized for feature extraction, where 4096 features are extracted from the fully connected layer. These features are reduced to have significant and informative features with minimum loss by NCA. Eventually, we use these classifiers to classify these significant features. Finally, experimental results display that OzNet-NCA-ANN excellent classifier model and achieves 100% accuracy with created Dataset 2 from Brain Hemorrhage CT images.     

Multiobjective evolutionary clustering of Web user sessions: a case study in Web page recommendation

In this study, we experiment with several multiobjective evolutionary algorithms to determine a suitable approach for clustering Web user sessions, which consist of sequences of Web pages visited by the users. Our experimental results show that the multiobjective evolutionary algorithm-based approaches are successful for sequence clustering. We look at a commonly used cluster validity index to verify our findings. The results for this index indicate that the clustering solutions are of high quality. As a case study, the obtained clusters are then used in a Web recommender system for representing usage patterns. As a result of the experiments, we see that these approaches can successfully be applied for generating clustering solutions that lead to a high recommendation accuracy in the recommender model we used in this paper.     

Investigation of Ant System parameter interactions by using design of experiments for job-shop scheduling problems

In recent years, one of the most important and promising research fields has been metaheuristics to find optimal or near-optimal solutions for NP-hard combinatorial optimization problems. Improving the quality of the solution or the solution time is basic research area on metaheuristics. Modifications of the existing ones or creation of hybrid approaches are the focus of these efforts. Another area of improving the solution quality of metaheuristics is finding the optimal combination of algorithm control parameters. This is usually done by design of experiments or one-at-a-time approach in genetic algorithms, simulated annealing and similar metaheuristics. We observe that, in studies which use Ant Colonies Optimization (ACO) as an optimization technique; the levels of control parameters are determined by some non-systematic initial experiments and the interactions of the parameters are not studied yet.In this study, the parameters of Ant System have been investigated on different sized and randomly generated job-shop scheduling problems by using design of experiments. The effects and interactions of the parameters have been interpreted with the outputs of the experiments. Referring to the statistical analysis it is observed that none of the interactions between the Ant System parameters has a significant effect on makespan value. A specific fractional experimental design is suggested instead of the full factorial design. Depending on the findings from the benchmark problems it will be a reliable approach to use the suggested design for saving time and effort in experiments without sacrificing the solution quality.     

An adaptive signal compression system with pre-specified reconstruction quality and compression rate

Two essential properties of a signal compression method are the compression rate and the distance between the original signal and the reconstruction from the compressed signal. These two properties are used to assess the performance and quality of the method. In a recent work [B. Tümer, B. Demir?z, Lecture Notes in Computer Science-Computer and Information Sciences, volume 2869, chapter Signal Compression Using Growing Cell Structures: A Transformational Approach, Springer Verlag, 2003, pp. 952-959], an adaptive signal compression system (ACS) is presented which defines the performance of the system as a function of the system complexity, system sensitivity and data size. For a compression method, it is desirable to formulate the performance of the system as a function of the system complexity and sensitivity to optimize the performance of the system. It would be further desirable to express the reconstruction quality in terms of the same system parameters so as to know up front what compression rate to end up with for a specific reconstruction quality. In this work, we modify ACS such that the modified ACS (MACS) estimates the reconstruction quality for a given system complexity and sensitivity. Once this relation is identified it is possible to optimize either compression rate or reconstruction quality with respect to system sensitivity and system complexity while limiting the other one.     

Profiling hospitals based on emergency readmission: a multilevel transition modelling approach

Emergency readmission is seen as an important part of the United Kingdom government policy to improve the quality of care that patients receive. In this context, patients and the public have the right to know how well different health organizations are performing. Most methods for profiling estimate the expected numbers of adverse outcomes (e.g. readmission, mortality) for each organization. A number of statistical concerns have been raised, such as the differences in hospital sizes and the unavailability of relevant data for risk adjustment. Having recognized these statistical concerns, a new framework known as the multilevel transition model is developed. Hospital specific propensities of the first, second and further readmissions are considered to be measures of performance, where these measures are used to define a new performance index. During the period 1997 and 2004, the national (English) hospital episodes statistics dataset comprise more than 5 million patient readmissions. Implementing a multilevel model using the complete population dataset could possibly take weeks to estimate the parameters. To resolve the problem, we extract 1000 random samples from the original data, where each random sample is likely to lead to differing hospital performance measures. For computational efficiency a Grid implementation of the model is developed. Analysing the output from the full 1000 sample, we noticed that 4 out of the 5 worst performing hospitals treating cancer patients were in London. These hospitals are known to be the leading NHS Trusts in England, providing diverse range of services to complex patients, and therefore it is inevitable to expect higher numbers of emergency readmissions.     

Experiments and simulations of short-pulse laser-pumped extreme ultraviolet lasers

Recent experimental work on the development of extreme ultraviolet lasers undertaken using as the pumping source the VULCAN laser at the Rutherford Appleton Laboratory is compared to detailed simulations. It is shown that short duration (/spl sim/picosecond) pumping can produce X-ray laser pulses of a few picosecond duration and that measurement of the emission from the plasma can give an estimate of the duration of the gain coefficient. The Ehybrid fluid and atomic physics code developed at the University of York is used to simulate X-ray laser gain and plasma emission. Two postprocessors to the Ehybrid code are utilized: 1) to raytrace the X-ray laser beam amplification and refraction and 2) to calculate the radiation emission in the kiloelectronvolt photon energy range. The raytracing and spectral simulations are compared, respectively, to measured X-ray laser output and the output of two diagnostics recording transverse X-ray emission. The pumping laser energy absorbed in the plasma is examined by comparing the simulations to experimental results. It is shown that at high pumping irradiance (>10/sup 15/ Wcm/sup -2/), fast electrons are produced by parametric processes in the preformed long scalelength plasmas. These fast electrons do not pump the population inversion and so pumping efficiency is reduced at high irradiance.     

Investigating the effect of production process of ball mill refiner on some physical quality parameters of compound chocolate: response surface methodology approach

Chocolate compound was produced using ball mill refiner, and the effect of agitator shaft speed and refining time on the physical quality parameters (particle size, colour and steady‐state rheology) of compound chocolate was determined using response surface methodology. The shaft speed and refining time range were selected between 40–60 r.p.m. and 10–30 min, respectively. Determination coefficient of the models established for particle size, Newtonian viscosity and colour parameters (brightness, chroma and hue angle) were found to be very close to unity. Increasing shaft speed and time induced a reduction in particle size and an increase in viscosity of the samples. Temperature sweep test was also performed, and the obtained data were successfully fitted to Arrhenius equation to calculate the corresponding parameters representing temperature dependency of the compounds. The results highlighted that the establishment of such models can provide essential information in terms of optimisation of production processes regarding usage purpose of the compound chocolate.