Microstructural modeling of dynamic recrystallization using irregular cellular automata

Cellular automaton (CA) was used to simulate dynamic recrystallization (DRX) during thermomechanical deformation. Initial grain size, initial grain orientation and dislocation density were used as input data to the CA model. Flow curve, dislocation density, final grain size and orientation, and DRX volume fraction were the output data which were compared with experimental data to validate the model. The model proposed in this work considered the thermomechanical parameters (e.g., temperature and strain rate) and their role on the nucleation and growth kinetics during DRX. It was shown that the CA model can predict the final microstructure and flow curve to a high degree of accuracy and was able to successfully simulate the volume fraction of DRX as a function of strain for a wide range of deformation conditions.

Design of experiments and springback prediction for AHSS automotive components with complex geometry

With the drive towards implementing Advanced High Strength Steels (AHSS) in the automotive industry; stamping engineers need to quickly answer questions about forming these strong materials into elaborate shapes.
Commercially available codes have been successfully used to accurately predict formability, thickness and strains in complex parts. However, springback and twisting are still challenging subjects in numerical simulations of AHSS components. Design of Experiments (DOE) has been used in this paper to study the sensitivity of the implicit and explicit numerical results with respect to certain arrays ofuser input parameters in the forming ofan AHSS component. Numerical results were compared to experimental measurements of the parts stamped in an industrial production line. The forming predictions of the implicit and explicit codes were in good agreement with the experimental measurements for the conventional steel grade, while lower accuracies were observed for the springback predictions. The forming
predictions of the complex component with an AHSS material were also in good correlation with the respective experimental measurements. However, much lower accuracies were observed in its springback predictions. The number of integration points through the thickness and tool offset were found to be of significant importance, while coefficient of friction and Young's modulus (modeling input parameters) have no significant effect on the accuracy of the predictions for the complex geometry.

Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model

Directly modeling the inherent hierarchy and shared structures of human behaviors, we present an application of the hierarchical hidden Markov model (HHMM) for the problem of activity recognition. We argue that to robustly model and recognize complex human activities, it is crucial to exploit both the natural hierarchical decomposition and shared semantics embedded in the movement trajectories. To this end, we propose the use of the HHMM, a rich stochastic model that has been recently extended to handle shared structures, for representing and recognizing a set of complex indoor activities. Furthermore, in the need of real-time recognition, we propose a Rao-Blackwellised particle filter (RBPF) that efficiently computes the filtering distribution at a constant time complexity for each new observation arrival. The main contributions of this paper lie in the application of the shared-structure HHMM, the estimation of the model's parameters at all levels simultaneously, and a construction of an RBPF approximate inference scheme. The experimental results in a real-world environment have confirmed our belief that directly modeling shared structures not only reduces computational cost, but also improves recognition accuracy when compared with the tree HHMM and the flat HMM.

Mesityltellurenyl cations stabilized by triphenylpnictogens [MesTe(EPh₃)] + (E = P, As, Sb)

The homoleptic 1:1 Lewis pair (LP) complex [MesTe(TeMes₂)]O₃SCF₃ (1) featuring the cation [MesTe(TeMes₂)]+ (1a) was obtained by the reaction of Mes₂Te with HO₃SCF₃. The reaction of 1 with Ph₃E (E = P, As, Sb, Bi) proceeded with substitution of Mes₂Te and provided the heteroleptic 1:1 LP complexes [MesTe(EPh₃)]O₃SCF₃ (2, E = P; 3, E = As) and [MesTe(SbPh₃)][Ph₂Sb(O₃SCF₃)₂] (4) featuring the cations [MesTe(EPh₃)]+ (2a, E = P; 3a, E = As; 4a, E = Sb) and the anion [Ph₂Sb(O₃SCF₃)₂]− (4b). In the reaction with Ph₃Bi, the crude product contained the cation [MesTe(BiPh₃)]+ (5a) and the anion [Ph₂Bi(O₃SCF₃)₂]− (5b); however, the heteroleptic 1:1 LP complex [MesTe(BiPh₃)][Ph₂Bi(O₃SCF₃)₂] (5) could not be isolated because of its limited stability. Instead, fractional crystallization furnished a large amount of Ph₂BiO₃SCF₃ (6), which was also obtained by the reaction of Ph₃Bi with HO₃SCF₃. The formation of the anions 4b and 5b involves a phenyl group migration from Ph₃E (E = Sb, Bi) to the MesTe+ cation and afforded MesTePh as the byproduct, which was identified in the mother liquor. The heteroleptic 1:1 LP complexes 2–4 were also obtained by the one-pot reaction of Mes₂Te, Ph₃E (E = P, As, Sb) and HO₃SCF₃. Compounds 1–4 and 6 were investigated by single-crystal X-ray diffraction. The molecular structures of 1a–4a were used for density functional theory calculations at the B3PW91/TZ level of theory and studied using natural bond order (NBO) analyses as well as real-space bonding descriptors derived from an atoms-in-molecules (AIM) analysis of the theoretically obtained electron density. Additionally, the electron localizability indicator (ELI-D) and the delocalization index are derived from the corresponding pair density.

Modelling of guided wave propagation with spectral element: application in structural engineering

Among many structural health monitoring (SHM) methods, guided wave (GW) based method has been found as an effective and efficient way to detect incipient damages. In comparison with other widely used SHM methods, it can propagate in a relatively long range and be sensitive to small damages. Proper use of this technique requires good knowledge of the effects of damage on the wave characteristics. This needs accurate and computationally efficient modeling of guide wave propagation in structures. A number of different numerical computational techniques have been developed for the analysis of wave propagation in a structure. Among them, Spectral Element Method (SEM) has been proposed as an efficient simulation technique. This paper will focus on the application of GW method and SEM in structural health monitoring. The GW experiments on several typical structures will be introduced first. Then, the modeling techniques by using SEM are discussed. © (2014) Trans Tech Publications, Switzerland.

A heuristic model selection scheme for representing hot flow data using the hot torsion test results

The problem of "model selection" for expressing a wide range of constitutive behaviour adequately using hot torsion test data was considered here using a heuristic approach. A model library including several nested parametric linear and non-linear models was considered and applied to a set of hot torsion test data for API-X 70 micro-alloyed steel with a range of strain rates and temperatures. A cost function comprising the modelled hot strength data and that of the measured data were utilized in a heuristic model selection scheme to identify the optimum models. It was shown that a non-linear rational model including ten parameters is an optimum model that can accurately express the multiple regimes of hardening and softening for the entire range of the experiment. The parameters for the optimum model were estimated and used for determining variations of hot strength of the samples with deformation.

Improving casthouse throughput using discrete-event modeling

The scheduling of metal to different casters in a casthouse is a complicated problem, attempting to find the balance between pot-line, crucible carrier, furnace and casting machine capacity. in this paper, a description will be given of a casthouse modelling system designed to test different scenarios for casthouse design and operation. Using discrete-event simulation, the casthouse model incorporates variable arrival times of metal carriers, crucible movements, caster operation and furnace conditions. Each part of the system is individually modelled and synchronised using a series of signals or semaphores. in addition, an easy to operate user interface allows for the modification of key parameters, and analysis of model output. Results from the model will be presented for a case study, which highlights the effect different parameters have on overall casthouse performance. The case study uses past production data from a casthouse to validate the model outputs, with the aim to perform a sensitivity analysis on the overall system. Along with metal preparation times and caster strip-down/setup, the temperature evolution within the furnaces is one key parameter in determining casthouse performance.

An in situ method for the study of strain broadening using synchrotron X-ray diffraction

A tensonometer for stretching metal foils has been constructed for the study of strain broadening in X-ray diffraction line profiles. This device, which is designed for use on powder diffractometers and was tested on Station 2.3 at Daresbury Laboratory, allows in situ measurements to be performed on samples under stress. It can be used for data collection in either transmission or reflection modes using either symmetric or asymmetric diffraction geometries. As a test case, measurements were carried out on an 18 µm-thick copper foil experiencing strain levels of up to 5% using both symmetric reflection and symmetric transmission diffraction. All the diffraction profiles displayed peak broadening and asymmetry which increased with strain. The measured profiles were analysed by the fundamental-parameters approach using the TOPAS peak-fitting software. All the observed broadened profiles were modelled by convoluting a refineable diffraction profile, representing the dislocation and crystallite size broadening, with a fixed instrumental profile predetermined using high-quality LaB6 reference powder. The deconvolution process yielded `pure' sample integral breadths and asymmetry results which displayed a strong dependence on applied strain and increased almost linearly with applied strain. Assuming crystallite size broadening in combination with dislocation broadening arising from f.c.c. a/2〈110〉{111} dislocations, the variation of mechanical property with strain has been extracted. The observation of both peak asymmetry and broadening has been interpreted as a manifestation of a cellular structure with cell walls and cell interiors possessing high and low dislocation densities.

The influence of yarn parameters on the ultraviolet protection of yarns

 Improving ultraviolet (UV) protection of textiles is essential to protect wearers against UV radiation induced risks. In addition to fabric parameters, yarn parameters are important factors affecting UV protection of textiles. This work is to examine the influence of yarn parameters on UV protection in order to set up a statistical model for predicting the UV protection of yarns. Wool yarns with different variables were used to test the ultraviolet protection factor (UPF) values for data analysis and the model verification. The model provides the optimized parameters for the UV protective fabric design. This work is helpful as a pre-cursor to the development of a more advanced optical model, which will look at understanding the penetration of UV light through fibres, yarns and fabrics.

Modeling companion diagnostics in economic evaluations of targeted oncology therapies: systematic review and methodological checklist

The successful use of a targeted therapy is intrinsically linked to the ability of a companion diagnostic to correctly identify patients most likely to benefit from treatment. The aim of this study was to review the characteristics of companion diagnostics that are of importance for inclusion in an economic evaluation. Approaches for including these characteristics in model-based economic evaluations are compared with the intent to describe best practice methods. Five databases and government agency websites were searched to identify model-based economic evaluations comparing a companion diagnostic and subsequent treatment strategy to another alternative treatment strategy with model parameters for the sensitivity and specificity of the companion diagnostic (primary synthesis). Economic evaluations that limited model parameters for the companion diagnostic to only its cost were also identified (secondary synthesis). Quality was assessed using the Quality of Health Economic Studies instrument. 30 studies were included in the review (primary synthesis n = 12; secondary synthesis n = 18). Incremental cost-effectiveness ratios may be lower when the only parameter for the companion diagnostic included in a model is the cost of testing. Incorporating the test's accuracy in addition to its cost may be a more appropriate methodological approach. Altering the prevalence of the genetic biomarker, specific population tested, type of test, test accuracy and timing/sequence of multiple tests can all impact overall model results. The impact of altering a test's threshold for positivity is unknown as it was not addressed in any of the included studies. Additional quality criteria as outlined in our methodological checklist should be considered due to the shortcomings of standard quality assessment tools in differentiating studies that incorporate important test-related characteristics and those that do not. There is a need to refine methods for incorporating the characteristics of companion diagnostics into model-based economic evaluations to ensure consistent and transparent reimbursement decisions are made.

A simple test for cointegration in dependent panels with structural breaks

This paper develops a very simple test for the null hypothesis of no cointegration in panel data. The test is general enough to allow for heteroskedastic and serially correlated errors, unit-specific time trends, cross-sectional dependence and unknown structural breaks in both the intercept and slope of the cointegrated regression, which may be located at different dates for different units. The limiting distribution of the test is derived, and is found to be normal and free of nuisance parameters under the null. A small simulation study is also conducted to investigate the small-sample properties of the test. In our empirical application, we provide new evidence concerning the purchasing power parity hypothesis. © Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2008.

A panel CUSUM test of the null of cointegration

This paper proposes a simple residual-based panel CUSUM test of the null hypothesis of cointegration. The test has a limiting normal distribution that is free of nuisance parameters, it is robust to heteroskedasticity and it allows for mixtures of cointegrated and spurious alternatives. Our Monte Carlo results suggest that the test has small-size distortions and reasonable power. In our empirical application to international R&D spillovers, we present evidence suggesting that total factor productivity is heterogeneously cointegrated with foreign and domestic R&D capital stocks. © Blackwell Publishing Ltd, 2005.

Modeling intermittent cycling performance in hypoxia using the critical power concept

PURPOSE: This study investigated the efficacy of an intermittent critical power model, termed the "work-balance" (W'BAL) model, during high-intensity exercise in hypoxia. METHODS: Eleven trained, male cyclists (mean ± SD; age 27 ± 6.6 yr, V[Combining Dot Above]O2peak 4.79 ± 0.56 L.min) completed a maximal ramp test and a 3 min "all-out" test to determine critical power (CP) and work performed above CP (W'). On another day an intermittent exercise test to task failure was performed. All procedures were performed in normoxia (NORM) and hypoxia (HYPO; FiO2 ≈ 0.155) in a single-blind, randomized and counter-balanced experimental design. The W'BAL model was used to calculate the minimum W' (W'BALmin) achieved during the intermittent test. W'BALmin in HYPO was also calculated using CP + W' derived in NORM (N+H). RESULTS: In HYPO there was an 18% decrease in V[Combining Dot Above]O2peak (4.79 ± 0.56 vs 3.93 ± 0.47 L.min ; P<0.001) and a 9% decrease in CP (347 ± 45 vs 316 ± 46 W; P<0.001). No significant change for W' occurred (13.4 ± 3.9 vs 13.7 ± 4.9 kJ; P=0.69; NORM vs HYPO). The change in V[Combining Dot Above]O2peak was significantly correlated with the change in CP (r = 0.72; P=0.01). There was no difference between NORM and HYPO for W'BALmin (1.1 ± 0.9 kJ vs 1.2 ± 0.6 kJ). The N+H analysis grossly overestimated W'BALmin (7.8 ± 3.4 kJ) compared with HYPO (P<0.001). CONCLUSION: The W'BAL model produced similar results in hypoxia and normoxia, but only when model parameters were determined under the same environmental conditions as the performance task. Application of the W'BAL model at altitude requires a modification of the model, or that CP and W' are measured at altitude.