A numerical investigation on the visco-plastic response of structures to different pulse loading shapes

The time varying intensity character of a load applied to a structure poses many difficulties in analysis. A remedy to this situation is to substitute a complex pulse shape by a rectangular equivalent one. It has been shown by others that this procedure works well for perfectly plastic elementary structures. This paper applies the concept of equivalent pulse to more complex structures. Special attention is given to the material behavior, which is allowed to be strain rate and strain hardening sensitive. Thanks to the explicit finite element solution, it is shown in this article that blast loads applied to complex structures made of real materials can be substituted by equivalent rectangular loads with both responses being practically the same. (c) 2007 Elsevier Ltd. All rights reserved.

Failure assessments of corroded pipelines with axial defects using stress-based criteria: Numerical studies and verification analyses

Conventional procedures used to assess the integrity of corroded piping systems with axial defects generally employ simplified failure criteria based upon a plastic collapse failure mechanism incorporating the tensile properties of the pipe material. These methods establish acceptance criteria for defects based on limited experimental data for low strength structural steels which do not necessarily address specific requirements for the high grade steels currently used. For these cases, failure assessments may be overly conservative or provide significant scatter in their predictions, which lead to unnecessary repair or replacement of in-service pipelines. Motivated by these observations, this study examines the applicability of a stress-based criterion based upon plastic instability analysis to predict the failure pressure of corroded pipelines with axial defects. A central focus is to gain additional insight into effects of defect geometry and material properties on the attainment of a local limit load to support the development of stress-based burst strength criteria. The work provides an extensive body of results which lend further support to adopt failure criteria for corroded pipelines based upon ligament instability analyses. A verification study conducted on burst testing of large-diameter pipe specimens with different defect length shows the effectiveness of a stress-based criterion using local ligament instability in burst pressure predictions, even though the adopted burst criterion exhibits a potential dependence on defect geometry and possibly on material`s strain hardening capacity. Overall, the results presented here suggests that use of stress-based criteria based upon plastic instability analysis of the defect ligament is a valid engineering tool for integrity assessments of pipelines with axial corroded defects. (C) 2008 Elsevier Ltd. All rights reserved.

Numerical modeling of ductile crack extension in high pressure pipelines with longitudinal flaws

This study examines the applicability of a micromechanics approach based upon the computational cell methodology incorporating the Gurson-Tvergaard (GT) model and the CTOA criterion to describe ductile crack extension of longitudinal crack-like defects in high pressure pipeline steels. A central focus is to gain additional insight into the effectiveness and limitations of both approaches to describe crack growth response and to predict the burst pressure for the tested cracked pipes. A verification study conducted on burst testing of large-diameter, precracked pipe specimens with varying crack depth to thickness ratio (a/t) shows the potential predictive capability of the cell approach even though both the CT model and the CTOA criterion appear to depend on defect geometry. Overall, the results presented here lend additional support for further developments in the cell methodology as a valid engineering tool for integrity assessments of pipelines with axial defects. (C) 2011 Elsevier Ltd. All rights reserved,

Estimating wave spectra from the motions of moored vessels: Experimental validation

The practicability of estimating directional wave spectra based on a vessel`s 1st order response has been recently addressed by several researchers. Different alternatives regarding statistical inference methods and possible drawbacks that could arise from their application have been extensively discussed, with an apparent preference for estimations based on Bayesian inference algorithms. Most of the results on this matter, however, rely exclusively on numerical simulations or at best on few and sparse full-scale measurements, comprising a questionable basis for validation purposes. This paper discusses several issues that have recently been debated regarding the advantages of Bayesian inference and different alternatives for its implementation. Among those are the definition of the best set of input motions, the number of parameters required for guaranteeing smoothness of the spectrum in frequency and direction and how to determine their optimum values. These subjects are addressed in the light of an extensive experimental campaign performed with a small-scale model of an FPSO platform (VLCC hull), which was conducted in an ocean basin in Brazil. Tests involved long and short crested seas with variable levels of directional spreading and also bimodal conditions. The calibration spectra measured in the tank by means of an array of wave probes configured the paradigm for estimations. Results showed that a wide range of sea conditions could be estimated with good precision, even those with somewhat low peak periods. Some possible drawbacks that have been pointed out in previous works concerning the viability of employing large vessels for such a task are then refuted. Also, it is shown that a second parameter for smoothing the spectrum in frequency may indeed increase the accuracy in some situations, although the criterion usually proposed for estimating the optimum values (ABIC) demands large computational effort and does not seem adequate for practical on-board systems, which require expeditious estimations. (C) 2009 Elsevier Ltd. All rights reserved.

Experimental and numerical investigation of dynamic heat transfer parameters in packed bed

Dynamic experiments in a nonadiabatic packed bed were carried out to evaluate the response to disturbances in wall temperature and inlet airflow rate and temperature. A two-dimensional, pseudo-homogeneous, axially dispersed plug-flow model was numerically solved and used to interpret the results. The model parameters were fitted in distinct stages: effective radial thermal conductivity (K (r)) and wall heat transfer coefficient (h (w)) were estimated from steady-state data and the characteristic packed bed time constant (tau) from transient data. A new correlation for the K (r) in packed beds of cylindrical particles was proposed. It was experimentally proved that temperature measurements using radially inserted thermocouples and a ring-shaped sensor were not distorted by heat conduction across the thermocouple or by the thermal inertia effect of the temperature sensors.

Residence time distribution in holding tubes using generalized convection model and numerical convolution for non-ideal tracer detection

A procedure is proposed for the determination of the residence time distribution (RTD) of curved tubes taking into account the non-ideal detection of the tracer. The procedure was applied to two holding tubes used for milk pasteurization in laboratory scale. Experimental data was obtained using an ionic tracer. The signal distortion caused by the detection system was considerable because of the short residence time. Four RTD models, namely axial dispersion, extended tanks in series, generalized convection and PER + CSTR association, were adjusted after convolution with the E-curve of the detection system. The generalized convection model provided the best fit because it could better represent the tail on the tracer concentration curve that is Caused by the laminar velocity profile and the recirculation regions. Adjusted model parameters were well cot-related with the now rate. (C) 2010 Elsevier Ltd. All rights reserved.

Avoiding Divergence in the Shalvi-Weinstein Algorithm

The most popular algorithms for blind equalization are the constant-modulus algorithm (CMA) and the Shalvi-Weinstein algorithm (SWA). It is well-known that SWA presents a higher convergence rate than CMA. at the expense of higher computational complexity. If the forgetting factor is not sufficiently close to one, if the initialization is distant from the optimal solution, or if the signal-to-noise ratio is low, SWA can converge to undesirable local minima or even diverge. In this paper, we show that divergence can be caused by an inconsistency in the nonlinear estimate of the transmitted signal. or (when the algorithm is implemented in finite precision) by the loss of positiveness of the estimate of the autocorrelation matrix, or by a combination of both. In order to avoid the first cause of divergence, we propose a dual-mode SWA. In the first mode of operation. the new algorithm works as SWA; in the second mode, it rejects inconsistent estimates of the transmitted signal. Assuming the persistence of excitation condition, we present a deterministic stability analysis of the new algorithm. To avoid the second cause of divergence, we propose a dual-mode lattice SWA, which is stable even in finite-precision arithmetic, and has a computational complexity that increases linearly with the number of adjustable equalizer coefficients. The good performance of the proposed algorithms is confirmed through numerical simulations.

Numerical study of tensile tests conducted on systems with elastic-plastic films deposited onto elastic-plastic substrates

In this work, a series of two-dimensional plane-strain finite element analyses was conducted to further understand the stress distribution during tensile tests on coated systems. Besides the film and the substrate, the finite element model also considered a number of cracks perpendicular to the film/substrate interface. Different from analyses commonly found in the literature, the mechanical behavior of both film and substrate was considered elastic-perfectly plastic in part of the analyses. Together with the film yield stress and the number of film cracks, other variables that were considered were crack tip geometry, the distance between two consecutive cracks and the presence of an interlayer. The analysis was based on the normal stresses parallel to the loading axis (sigma(xx)), which are responsible for cohesive failures that are observed in the film during this type of test. Results indicated that some configurations studied in this work have significantly reduced the value of sigma(xx) at the film/substrate interface and close to the pre-defined crack tips. Furthermore, in all the cases studied the values of sigma(xx) were systematically larger at the film/substrate interface than at the film surface. (C) 2010 Elsevier B.V. All rights reserved.

Some heuristic algorithms for total tardiness minimization in a flowshop with blocking

The flowshop scheduling problem with blocking in-process is addressed in this paper. In this environment, there are no buffers between successive machines: therefore intermediate queues of jobs waiting in the system for their next operations are not allowed. Heuristic approaches are proposed to minimize the total tardiness criterion. A constructive heuristic that explores specific characteristics of the problem is presented. Moreover, a GRASP-based heuristic is proposed and Coupled with a path relinking strategy to search for better outcomes. Computational tests are presented and the comparisons made with an adaptation of the NEH algorithm and with a branch-and-bound algorithm indicate that the new approaches are promising. (c) 2007 Elsevier Ltd. All rights reserved.

Spatial portability of numerical models of leaf wetness duration based on empirical approaches

Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.

Evaluation of algorithms used to order markers on genetic maps

When building genetic maps, it is necessary to choose from several marker ordering algorithms and criteria, and the choice is not always simple. In this study, we evaluate the efficiency of algorithms try (TRY), seriation (SER), rapid chain delineation (RCD), recombination counting and ordering (RECORD) and unidirectional growth (UG), as well as the criteria PARF (product of adjacent recombination fractions), SARF (sum of adjacent recombination fractions), SALOD (sum of adjacent LOD scores) and LHMC (likelihood through hidden Markov chains), used with the RIPPLE algorithm for error verification, in the construction of genetic linkage maps. A linkage map of a hypothetical diploid and monoecious plant species was simulated containing one linkage group and 21 markers with fixed distance of 3 cM between them. In all, 700 F(2) populations were randomly simulated with and 400 individuals with different combinations of dominant and co-dominant markers, as well as 10 and 20% of missing data. The simulations showed that, in the presence of co-dominant markers only, any combination of algorithm and criteria may be used, even for a reduced population size. In the case of a smaller proportion of dominant markers, any of the algorithms and criteria (except SALOD) investigated may be used. In the presence of high proportions of dominant markers and smaller samples (around 100), the probability of repulsion linkage increases between them and, in this case, use of the algorithms TRY and SER associated to RIPPLE with criterion LHMC would provide better results. Heredity (2009) 103, 494-502; doi:10.1038/hdy.2009.96; published online 29 July 2009

Numerical Study of Hypersonic Leeward Flow over a Blunt Nosed Delta Wing

A kinetic theory based Navier-Stokes solver has been implemented on a parallel supercomputer (Intel iPSC Touchstone Delta) to study the leeward flowfield of a blunt nosed delta wing at 30-deg incidence at hypersonic speeds (similar to the proposed HERMES aerospace plane). Computational results are presented for a series of grids for both inviscid and laminar viscous flows at Reynolds numbers of 225,000 and 2.25 million. In addition, comparisons are made between the present and two independent calculations of the some flows (by L. LeToullec and P. Guillen, and S. Menne) which were presented at the Workshop on Hypersonic Flows for Re-entry Problems, Antibes, France, 1991.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Comparison of experimental and numerical studies of ionizing flow over a cylinder

Comparisons are made between experimental measurements and numerical simulations of ionizing flows generated in a superorbital facility. Nitrogen, with a freestream velocity of around 10 km/s, was passed over a cylindrical model, and images were recorded using two-wavelength holographic interferometry. The resulting density, electron concentration, and temperature maps were compared with numerical simulations from the Langley Research Center aerothermodynamic upwind relaxation algorithm. The results showed generally good agreement in shock location and density distributions. Some discrepancies were observed for the electron concentration, possibly, because simulations were of a two-dimensional flow, whereas the experiments were likely to have small three-dimensional effects.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).