5,938 research outputs found

    Sensitivity study of crack driving force predictions in heterogeneous welds using Vickers hardness maps

    Get PDF
    Weld flaws often require an engineering critical assessment (ECA) to judge on the necessity for weld repair. ECA is a fracture mechanics based prediction of the integrity of welds under operating conditions. Adding to the complexity of an ECA is the occurrence of local constitutive property variations in the weldment (‘weld heterogeneity’). Their quantification is important to allow for an accurate assessment. Hereto, hardness measurements are widely adopted given their theoretical relation with ultimate tensile strength. However, various standards and procedures report a wide variety of different hardness transfer functions and additionally recognize substantial scatter in predictions of strength. Within this context, this paper investigates the suitability of hardness mapping to perform an accurate weld ECA. A finite element analysis has been conducted on welds originating from steel pipelines to simulate their crack driving force response using single-edge notched tension (SE(T)) specimens. Vickers hardness maps and hardness transfer functions are combined to assign element-specific constitutive properties to the model. The resulting crack driving force curves are probed against experimental results. The variable agreement between simulations and experiments highlights the need for further research into the characterization of local constitutive properties of heterogeneous welds. A hardness transfer procedure based on all weld metal tensile testing appears to be particularly promising

    Idealized model for changes in equilibrium temperature, mixed layer depth, and boundary layer cloud over land in a doubled CO2 climate

    Get PDF
    An idealized equilibrium model for the undisturbed partly cloudy boundary layer (BL) is used as a framework to explore the coupling of the energy, water, and carbon cycles over land in midlatitudes and show the sensitivity to the clear‐sky shortwave flux, the midtropospheric temperature, moisture, CO2, and subsidence. The changes in the surface fluxes, the BL equilibrium, and cloud cover are shown for a warmer, doubled CO2 climate. Reduced stomatal conductance in a simple vegetation model amplifies the background 2 K ocean temperature rise to an (unrealistically large) 6 K increase in near‐surface temperature over land, with a corresponding drop of near‐surface relative humidity of about 19%, and a rise of cloud base of about 70 hPa. Cloud changes depend strongly on changes of mean subsidence; but evaporative fraction (EF) decreases. EF is almost uniquely related to mixed layer (ML) depth, independent of background forcing climate. This suggests that it might be possible to infer EF for heterogeneous landscapes from ML depth. The asymmetry of increased evaporation over the oceans and reduced transpiration over land increases in a warmer doubled CO2 climate

    Automatic Filters for the Detection of Coherent Structure in Spatiotemporal Systems

    Full text link
    Most current methods for identifying coherent structures in spatially-extended systems rely on prior information about the form which those structures take. Here we present two new approaches to automatically filter the changing configurations of spatial dynamical systems and extract coherent structures. One, local sensitivity filtering, is a modification of the local Lyapunov exponent approach suitable to cellular automata and other discrete spatial systems. The other, local statistical complexity filtering, calculates the amount of information needed for optimal prediction of the system's behavior in the vicinity of a given point. By examining the changing spatiotemporal distributions of these quantities, we can find the coherent structures in a variety of pattern-forming cellular automata, without needing to guess or postulate the form of that structure. We apply both filters to elementary and cyclical cellular automata (ECA and CCA) and find that they readily identify particles, domains and other more complicated structures. We compare the results from ECA with earlier ones based upon the theory of formal languages, and the results from CCA with a more traditional approach based on an order parameter and free energy. While sensitivity and statistical complexity are equally adept at uncovering structure, they are based on different system properties (dynamical and probabilistic, respectively), and provide complementary information.Comment: 16 pages, 21 figures. Figures considerably compressed to fit arxiv requirements; write first author for higher-resolution version

    Compressive Imaging Using RIP-Compliant CMOS Imager Architecture and Landweber Reconstruction

    Get PDF
    In this paper, we present a new image sensor architecture for fast and accurate compressive sensing (CS) of natural images. Measurement matrices usually employed in CS CMOS image sensors are recursive pseudo-random binary matrices. We have proved that the restricted isometry property of these matrices is limited by a low sparsity constant. The quality of these matrices is also affected by the non-idealities of pseudo-random number generators (PRNG). To overcome these limitations, we propose a hardware-friendly pseudo-random ternary measurement matrix generated on-chip by means of class III elementary cellular automata (ECA). These ECA present a chaotic behavior that emulates random CS measurement matrices better than other PRNG. We have combined this new architecture with a block-based CS smoothed-projected Landweber reconstruction algorithm. By means of single value decomposition, we have adapted this algorithm to perform fast and precise reconstruction while operating with binary and ternary matrices. Simulations are provided to qualify the approach.Ministerio de Economía y Competitividad TEC2015-66878-C3-1-RJunta de Andalucía TIC 2338-2013Office of Naval Research (USA) N000141410355European Union H2020 76586

    Formal Definitions of Unbounded Evolution and Innovation Reveal Universal Mechanisms for Open-Ended Evolution in Dynamical Systems

    Full text link
    Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an equivalent isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) in which the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, widely regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.Comment: Main document: 17 pages, Supplement: 21 pages Presented at OEE2: The Second Workshop on Open-Ended Evolution, 15th International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV), Canc\'un, Mexico, 4-8 July 2016 (http://www.tim-taylor.com/oee2/

    On the correlation between Ca and Halpha solar emission and consequences for stellar activity observations

    Full text link
    The correlation between Ca and Halpha chromospheric emission, known to be positive in the solar case, has been found to vary between -1 and 1 for other stars. Our objective is to understand the factors influencing this correlation in the solar case, and then to extrapolate our interpretation to other stars. We characterize the correlation between both types of emission in the solar case for different time scales. Then we determine the filling factors due to plages and filaments, and reconstruct the Ca and Halpha emission to test different physical conditions in terms of plage and filament contrasts. We have been able to precisely determine the correlation in the solar case as a function of the cycle phase. We interpret the results as reflecting the balance between the emission in plages and the absorption in filaments. We found that correlations close to zero or slightly negative can be obtained when considering the same spatio-temporal distribution of plages and filaments than on the sun but with greater contrast. However, with that assumption, correlations close to -1 cannot be obtained for example. Stars with a very low Halpha contrast in plages and filaments well correlated with plages could produce a correlation close to -1. This study opens new ways to study stellar activity, and provides a new diagnosis that will ultimately help to understand the magnetic configuration of stars other than the sun.Comment: 10 pages, 13 figures, accepted in Astronomy and Astrophysic

    Complexity and Information: Measuring Emergence, Self-organization, and Homeostasis at Multiple Scales

    Full text link
    Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this paper we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self-organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales.Comment: 42 pages, 11 figures, 2 table
    corecore