Topological design of freely vibrating continuum structures for maximum values of simple and multiple eigenfrequencies and frequency gaps

A frequent goal of the design of vibrating structures is to avoid resonance of the structure in a given interval for external excitation frequencies. This can be achieved by, e.g., maximizing the fundamental eigenfrequency, an eigenfrequency of higher order, or the gap between two consecutive eigenfrequencies of given order. This problem is often complicated by the fact that the eigenfrequencies in question may be multiple, and this is particularly the case in topology optimization. In the present paper, different approaches are considered and discussed for topology optimization involving simple and multiple eigenfrequencies of linearly elastic structures without damping. The mathematical formulations of these topology optimization problems and several illustrative results are presented. An erratum to this article can be found at     

On simultaneous shape and orientational design for eigenfrequency optimization

Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design of an orthotropic material that can be considered as a fiber-net within each finite element. This fiber-net is optimally oriented in the individual elements of the finite element discretization. The optimizations are performed using the finite element method for analysis, and the optimization approach is a two-step method. In the first step, we find the best design on the basis of a recursive optimization procedure based on optimality criteria. In the second step, mathematical programming and sensitivity analysis are applied to find the final optimized design.     

Simple and accurate four-node axisymmetric element

Based on the assumed strain method, a simple four-node axisymmetric solid element is introduced. The assumed strain field is carefully selected to preserve the correct rank of the element stiffness matrix and to achieve high accuracy. The strain field is developed in conjunction with orthogonal projections and no matrix inversions are needed. The coarse mesh accuracy in bending and in typical axisymmetric load cases is excellent even for nearly incompressible materials. The strain-driven format obtained is well suited for materials with non-linear stress–strain relations. Several numerical examples are presented where the excellent performance of the proposed simple element is verified. Copyright © 2006 John Wiley & Sons, Ltd.     

Distributed Bayesian diagnosis for modular assembly systems—A case study

The growing interest in modular and distributed approaches for the design and control of intelligent manufacturing systems gives rise to new challenges. One of the major challenges that have not yet been well addressed is monitoring and diagnosis in distributed manufacturing systems. In this paper we propose the use of a multi-agent Bayesian framework known as Multiply Sectioned Bayesian Networks (MSBNs) as the basis for multi-agent distributed diagnosis in modular assembly systems. We use a close-to-industry case study to demonstrate how MSBNs can be used to build component-based Bayesian sub-models, how to verify the resultant models, and how to compile the multi-agent models into runtime structures to allow consistent multi-agent belief update and inference.     

Flood regulation using nonlinear model predictive control

In this paper the flood problem of the river Demer, a river located in Belgium, is discussed. First a simplified model of the Demer basin is derived based on the conceptual reservoir modeling concept. This model was calibrated to simulations results with a more detailed full hydrodynamic model. Afterwards, the focus is shifted to a nonlinear model predictive controller (NMPC) which is based on a new semi-condensed optimization procedure combined with a line search approach. Finally, simulations are performed based on historical data in which the NMPC is compared with the current control strategy used by the local water administration. Uncertainties are added to the rainfall predictions in order to assess the robustness of the NMPC.     

High-sensitivity and high-resolution low-energy ion scattering

Low-Energy Ion Scattering (LEIS or ISS) is used to selectively analyze the atomic composition of the outer atomic layer of surfaces. In addition, the spectrum gives (non-destructively) the in-depth distribution. Using a double toroidal energy analyzer with parallel energy detection and time-of-flight filtering a high sensitivity and mass resolution of LEIS is achieved. This is demonstrated for a highly dispersed catalyst of Pt/Au on γ-alumina. The improved depth resolution is illustrated for self-assembled monolayers of alkanethiols (12-20 carbon atoms) on gold. Even for these low Z carbon atoms a clear shift of 8 eV/carbon atom is observed (using 1.5 keV ⁴He⁺ ion scattering). This opens many new possibilities for studies of ultra-thin diffusion barriers, high-k dielectrics and biosensors.     

The antiproton depth-dose curve measured with alanine detectors

In this paper we report on the measurement of the antiproton depth-dose curve, with alanine detectors. The results are compared with simulations using the particle energy spectrum calculated by FLUKA, and using the track structure model of Hansen and Olsen for conversion of calculated dose into response. A good agreement is observed between the measured and calculated relative effectiveness although an underestimation of the measured values beyond the Bragg-peak remains unexplained. The model prediction of response of alanine towards heavy charged particles encourages future use of the alanine detectors for dosimetry of mixed radiation fields.     

Single word production in English: The role of subsyllabic units during phonological encoding.

Five experiments investigated the role of sublexical units in English single word production L. Ferrand, J. Segui, and G. W. Humphreys (1997) reported a priming effect that was most effective when primes and targets shared the first syllable. Experiments 1A and 1B failed to replicate this effect but Experiment 1B showed that subsyllabic units play a role in speech production. This role was further explored using a picture naming task in Experiment 2. Naming latencies were shortest when the segmental overlap between prime and target (picture name) was largest, regardless of the syllable structure of the target. Experiments 3 and 4 replicated this segmental overlap effect with different sets of words as targets. Experiment 5 showed that the magnitude of the overlap effect increased with longer prime exposure duration. The implications of these results for theories of phonological encoding in speech production are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Jama Legal Narrative Part I: The JAMA Model and Narrative Interpretation Patterns

For the purposes of starting to tackle, within artificial intelligence (AI), the narrative aspects of legal narratives in a criminal evidence perspective, traditional AI models of narrative understanding can arguably supplement extant models of legal narratives from the scholarly literature of law, jury studies, or the semiotics of law. Not only: the literary (or cinematic) models prominent in a given culture impinge, with their poetic conventions, on the way members of the culture make sense of the world. This shows glaringly in the sample narrative from the Continent-the Jama murder, the inquiry, and the public outcry-we analyse in this paper. Apparently in the same racist crime category as the case of Stephen Lawrence's murder (in Greenwich on 22 April 1993) with the ensuing still current controversy in the UK, the Jama case (some 20 years ago) stood apart because of a very unusual element: the eyewitnesses identifying the suspects were a group of football referees and linesmen eating together at a restaurant, and seeing the sleeping man as he was set ablaze in a public park nearby. Professional background as witnesses-cum-factfinders in a mass sport, and public perceptions of their required characteristics, couldn't but feature prominently in the public perception of the case, even more so as the suspects were released by the magistrate conducting the inquiry. There are sides to this case that involve different expected effects in an inquisitorial criminal procedure system from the Continent, where an investigating magistrate leads the inquiry and prepares the prosecution case, as opposed to trial by jury under the Anglo-American adversarial system. In the JAMA prototype, we tried to approach the given case from the coign of vantage of narrative models from AI.     

A GC–MS-based metabonomic investigation of blood serum from irritable bowel syndrome patients undergoing intervention with acidified milk products

In the present study, the use of gas chromatography mass spectrometry (GC–MS)-based metabonomics to characterize blood serum in an intervention study of patients suffering from the common gastrointestinal disorder irritable bowel syndrome (IBS) was investigated. The patients included in the study consumed an acidified milk product with (n = 30) or without probiotics (n = 31) (Lactobacillus paracasei F19, Lactobacillus acidophilus LA-5 and Bifidobacterium lactis BB-12) for an 8-week period, and blood serum samples were collected before and after the intervention. Acidified milk is commonly used as a delivering vector for probiotics in commercial consumer settings. The serum samples were extracted and derivatized using N-Methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA), and GC–MS analysis was carried out. Multivariate data analysis including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), and S-plot was applied on the obtained GC–MS data, which revealed higher serum lactate, glutamine, proline creatinine/creatine, and aspartic acid levels and lower serum glucose levels after the intervention period for both treatment groups. Consequently, the present study indicated an effect of acidified milk consumption on the plasma metabolite profile, which was independent of a concomitant intake of probiotics. In addition, the present study demonstrates that GC–MS is a useful analytical technique for metabonomics studies of blood serum.