3,603 research outputs found

    On the influence of crossing angle on long-term rail damage evolution in railway crossings

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    The rails in railway crossings are subjected to severe load environment leading to degradation of running surface due to wear and accumulated plastic deformation. To compare long-term degradation of three fixed crossings with different crossing angles, nominally designated 1:12, 1:15, and 1:18.5, a multidisciplinary simulation methodology is applied to predict damage of the crossing rail. For a given traffic scenario, including up to 65 MGT of facing move passenger traffic in through route, the results show that damage increases with increasing crossing angle. The ratio between the maximum damage for the crossings with the largest and smallest crossing angles is found to be about three in terms of wear and about two for plastic deformation. Initially high rate of plastic deformation reduces significantly after the first 2–5 MGT, and after 10–30 MGT it approaches a nearly constant value that is significantly lower than the wear rate

    Metamodelling of wheel–rail normal contact in railway crossings with elasto-plastic material behaviour

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    A metamodel considering material plasticity is presented for computationally efficient prediction of wheel–rail normal contact in railway switches and crossings (S&C). The metamodel is inspired by the contact theory of Hertz, and for a given material, it computes the size of the contact patch and the maximum contact pressure as a function of the normal force and the local curvatures of the bodies in contact. The model is calibrated based on finite element (FE) simulations with an elasto-plastic material model and is demonstrated for rail steel grade R350HT. The error of simplifying the contact geometry is discussed and quantified. For a moderate difference in contact curvature between wheel and rail, the metamodel is able to accurately predict the size of the contact patch and the maximum contact pressure. The accuracy is worse when there is a small difference in contact curvature, where the influence of variation in curvature within the contact patch becomes more significant. However, it is shown that such conditions lead to contact stresses that contribute less to accumulated plastic deformation. The metamodel allows for a vast reduction of computational effort compared to the original FE model as it is given in analytical form

    Long-term rail profile damage in a railway crossing: Field measurements and numerical simulations

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    Railway crossings are subjected to a severe load environment leading to a degradation of rail profiles due to wear and accumulated plastic deformation. This damage is the result of the high magnitudes of contact pressure and traction generated in the wheel–rail contact during each wheel transition between wing rail and crossing nose. An extensive measurement campaign has been carried out at a test site in Austria in a particularly severely loaded crossing manufactured from an explosion depth hardened (EDH) manganese steel grade. For an accumulated traffic load of 65 Mega-Gross-Tonnes (MGT), the evolution of profile degradation for 16 cross-sections along the crossing rail has been recorded on multiple occasions. The results from the measurement campaign are used to validate a previously presented multidisciplinary and iterative simulation methodology for the prediction of long-term rail damage. It is shown that the predicted rail profile degradation exceeds the measured degradation for some of the cross-sections but generally a good qualitative agreement is observed. Possible reasons for the higher predicted damage are the uncertain distribution of traffic at the test site and differences in material properties between the crossing in the field and the test specimens used for calibration of the cyclic plasticity model. The influence of the frequency of updating the rail profiles in the iterative simulation methodology, and the compromise between computational cost and the number of load cases accounted for in the applied load sequence, are addressed

    Adaptations in metabolism and protein translation give rise to the Crabtree effect in yeast

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    Aerobic fermentation, also referred to as the Crabtree effect in yeast, is a well-studied phenomenon that allows many eukaryal cells to attain higher growth rates at high glucose availability. Not all yeasts exhibit the Crabtree effect, and it is not known why Crabtree-negative yeasts can grow at rates comparable to Crabtree-positive yeasts. Here, we quantitatively compared two Crabtree-positive yeasts, Saccharomyces cerevisiae and Schizosaccharomyces pombe, and two Crabtree-negative yeasts, Kluyveromyces marxianus and Scheffersomyces stipitis, cultivated under glucose excess conditions. Combining physiological and proteome quantification with genome-scale metabolic modeling, we found that the two groups differ in energy metabolism and translation efficiency. In Crabtree-positive yeasts, the central carbon metabolism flux and proteome allocation favor a glucose utilization strategy minimizing proteome cost as proteins translation parameters, including ribosomal content and/or efficiency, are lower. Crabtree-negative yeasts, however, use a strategy of maximizing ATP yield, accompanied by higher protein translation parameters. Our analyses provide insight into the underlying reasons for the Crabtree effect, demonstrating a coupling to adaptations in both metabolism and protein translation

    Condition Monitoring of Railway Crossing Geometry via Measured and Simulated Track Responses

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    This paper presents methods for continuous condition monitoring of railway switches and crossings (S&C, turnout) via sleeper-mounted accelerometers at the crossing transition. The methods are developed from concurrently measured sleeper accelerations and scanned crossing geometries from six in situ crossing panels. These measurements combined with a multi-body simulation (MBS) model with a structural track model and implemented scanned crossing geometries are used to derive the link between the crossing geometry condition and the resulting track excitation. From this analysis, a crossing condition indicator Cλ1-λ2,γ is proposed. The indicator is defined as the root mean square (RMS) of a track response signal γ that has been band-passed between frequencies corresponding to track deformation wavelength bounds of λ1 and λ2 for the vehicle passing speed (f = v/ λ). In this way, the indicator ignores the quasi-static track response with wavelengths pre-dominantly above λ1 and targets the dynamic track response caused by the kinematic wheel-cross-ing interaction governed by the crossing geometry. For the studied crossing panels, the indicator C1-0.2 m,γ (λ1 = 1 and λ2 = 0.2) was evaluated for γ = u, v, or a as in displacements, velocities, and accelerations, respectively. It is shown that this condition indicator has a strong correlation with vertical wheel–rail contact forces that is sustained for various track conditions. Further, model calibrations were performed to measured sleeper displacements for the six investigated crossing panels. The calibrated models show (1) a good agreement between measured and simulated sleeper displacements for the lower frequency quasi-static track response and (2) improved agreement for the dynamic track response at higher frequencies. The calibration also improved the agreement between measurements and simulation for the crossing condition indicator demonstrating the value of model calibration for condition monitoring purposes

    Reconstruction of sleeper displacements from measured accelerations for model-based condition monitoring of railway crossing panels

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    Railway switches and crossings (S&C, turnouts) connect different track sections and create a railway network by allowing trains to change tracks. This functionality comes at a cost as the load-inducing rail discontinuities in the switch and crossing panels cause much larger degradation rates for S&C compared to regular plain line tracks. The high degradation rates make remote condition monitoring an interesting prospect for infrastructure managers to optimise maintenance and ensure safe operations. To this end, this paper addresses the development of tailored signal processing tools for condition monitoring using embedded accelerometers in crossing panels. Multibody simulations of the dynamic train–track interaction are used to aid the interpretation of the measured signals in a first step towards building a model-based condition monitoring system. An analysis is performed using sleeper acceleration measurement data generated by 100 000 train passages in eight crossing panels. Based on the given data, a novel frequency-domain displacement reconstruction method is developed and the robustness of the method with respect to encountered operational variability of the measured data is demonstrated. The separation of the track response into quasi-static and dynamic domains based on deformation wavelength regions is proposed as a promising strategy to observe the ballast condition and the crossing geometry condition, respectively

    Decoherence Rates in Large Scale Quantum Computers and Macroscopic Systems

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    Markovian regime decoherence effects in quantum computers are studied in terms of the fidelity for the situation where the number of qubits N becomes large. A general expression giving the decoherence time scale in terms of Markovian relaxation elements and expectation values of products of system fluctuation operators is obtained, which could also be applied to study decoherence in other macroscopic systems such as Bose condensates and superconductors. A standard circuit model quantum computer involving three-state lambda system ionic qubits is considered, with qubits localised around well-separated positions via trapping potentials. The centre of mass vibrations of the qubits act as a reservoir. Coherent one and two qubit gating processes are controlled by time dependent localised classical electromagnetic fields that address specific qubits, the two qubit gating processes being facilitated by a cavity mode ancilla, which permits state interchange between qubits. With a suitable choice of parameters, it is found that the decoherence time can be made essentially independent of N.Comment: Minor revisions. To be published in J Mod Opt. One figur

    Proteome reallocation from amino acid biosynthesis to ribosomes enables yeast to grow faster in rich media

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    Several recent studies have shown that the concept of proteome constraint, i.e., the need for the cell to balance allocation of its proteome between different cellular processes, is essential for ensuring proper cell function. However, there have been no attempts to elucidate how cells\u27 maximum capacity to grow depends on protein availability for different cellular processes. To experimentally address this, we cultivated Saccharomyces cerevisiae in bioreactors with or without amino acid supplementation and performed quantitative proteomics to analyze global changes in proteome allocation, during both anaerobic and aerobic growth on glucose. Analysis of the proteomic data implies that proteome mass is mainly reallocated from amino acid biosynthetic processes into translation, which enables an increased growth rate during supplementation. Similar findings were obtained from both aerobic and anaerobic cultivations. Our findings show that cells can increase their growth rate through increasing its proteome allocation toward the protein translational machinery

    Sources of variation in cell-type RNA-Seq profiles

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    Cell-type specific gene expression profiles are needed for many computational methods operating on bulk RNA-Seq samples, such as deconvolution of cell-type fractions and digital cytometry. However, the gene expression profile of a cell type can vary substantially due to both technical factors and biological differences in cell state and surroundings, reducing the efficacy of such methods. Here, we investigated which factors contribute most to this variation. We evaluated different normalization methods, quantified the variance explained by different factors, evaluated the effect on deconvolution of cell type fractions, and examined the differences between UMI-based single-cell RNA-Seq and bulk RNA-Seq. We investigated a collection of publicly available bulk and single-cell RNA-Seq datasets containing B and T cells, and found that the technical variation across laboratories is substantial, even for genes specifically selected for deconvolution, and this variation has a confounding effect on deconvolution. Tissue of origin is also a substantial factor, highlighting the challenge of using cell type profiles derived from blood with mixtures from other tissues. We also show that much of the differences between UMI-based single-cell and bulk RNA-Seq methods can be explained by the number of read duplicates per mRNA molecule in the single-cell sample. Our work shows the importance of either matching or correcting for technical factors when creating cell-type specific gene expression profiles that are to be used together with bulk samples
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