Search results for "experimental data"
showing 10 items of 137 documents
Parameter identification and state estimation of a microalgae dynamical model in sulphur deprived conditions: Global sensitivity analysis, optimizati…
2014
International audience; In this article, a dynamic model describing the growth of the green microalgae Chlamydomonas reinhardtii , under light attenuation and sulphur‐deprived conditions leading to hydrogen production in a photobioreactor is presented. The strong interactions between biological and physical phenomena require complex mathematical expressions with an important number of parameters. This article presents a global identification procedure in three steps using data from batch experiments. First, it includes the application of a sensitivity function analysis, which allows one to determine the parameters having the greatest influence on model outputs. Secondly, the most influentia…
Flow measurement using circular portable flume
2018
Abstract The circular portable flume is a simple device to measure discharge in circular drainage networks. Since the unit can be easily installed and removed, it is helpful in water distribution measurement and management. First in this paper the available studies are reviewed for highlighting the effect of both the contraction ratio and the flume slope on the stage-discharge relationship. Then the Buckingham's Theorem of the dimensional analysis and the self-similarity theory are used to deduce the stage-discharge curve of the circular flume. The new theoretical stage-discharge equation is calibrated by the literature available experimental data and those obtained in this experimental inv…
Graph-theoretical derivation of brain structural connectivity
2020
Brain connectivity at the single neuron level can provide fundamental insights into how information is integrated and propagated within and between brain regions. However, it is almost impossible to adequately study this problem experimentally and, despite intense efforts in the field, no mathematical description has been obtained so far. Here, we present a mathematical framework based on a graph-theoretical approach that, starting from experimental data obtained from a few small subsets of neurons, can quantitatively explain and predict the corresponding full network properties. This model also changes the paradigm with which large-scale model networks can be built, from using probabilisti…
Practical Calculation Models for Column Footing and Comparison with Experimental Data
2017
In this paper, a simplified calculation model for the prediction of the load-carrying capacity of an RC column footing with a square cross section is presented. A detailed background of available experimental data and existing models for the prediction of the load-carrying capacity of slender and deep footings is presented. Cases of flexural failure and punching shear failures for slender footing and concrete strut crushing and tie yielding in deep members are analyzed. The aim of the paper is to propose a simple design formula for slender and deep footing verified by available experimental data and in agreement with other existing expressions. Expressions of the maximum mechanical ratio of…
A deeper look into natural sciences with physics-based and data-driven measures
2021
Summary With the development of machine learning in recent years, it is possible to glean much more information from an experimental data set to study matter. In this perspective, we discuss some state-of-the-art data-driven tools to analyze latent effects in data and explain their applicability in natural science, focusing on two recently introduced, physics-motivated computationally cheap tools—latent entropy and latent dimension. We exemplify their capabilities by applying them on several examples in the natural sciences and show that they reveal so far unobserved features such as, for example, a gradient in a magnetic measurement and a latent network of glymphatic channels from the mous…
Experimental data of the laboratory investigation for the design of a new filter cartridge for water treatment
2019
Abstract The data provided here refers to the experimental laboratory investigation conducted in the Laboratory of Environmental and Maritime Hydraulics (LIDAM) of University of Salerno, Italy, with the aim of developing a new filtering cartridge for water treatment capable of overcoming the main inconveniences shown by usual commercial cartridges. Specifically, the proposed filtering cartridge is an economic, non-toxic, low-resistance and long-life cartridge, currently under a patent pending status, whose main advantage is to permit to significantly reduce, compared with the commercial cartridges, average head losses induced by the cartridge even for high clogging degrees, and to increase,…
Monod-based ‘single-data’ strategy for biodegradation screening tests
2020
Environmental contextObtaining biodegradation data over time can be difficult, especially when dealing with environmental compartments of increasing complexity. We evaluated the possibility of obtaining a full biodegradation depletion curve from a single biodegradation-time experimental measurement, and found that environmental information related to potential chemical persistence can be derived. The applicability of this ‘single-data’ strategy is illustrated using simulated and experimental data for several compounds. AbstractInformation obtained from biodegradability tests, e.g. half-life (t50) or kinetics parameters, is relevant in environmental risk assessment of new chemicals. In thes…
Neural Classification of HEP Experimental Data
2009
High Energy Physics (HEP) experiments require discrimination of a few interesting events among a huge number of background events generated during an experiment. Hierarchical triggering hardware architectures are needed to perform this tasks in real-time. In this paper three neural network models are studied as possible candidate for such systems. A modified Multi-Layer Perception (MLP) architecture and a E alpha Net architecture are compared against a traditional MLP Test error below 25% is archived by all architectures in two different simulation strategies. E alpha Net performance are 1 to 2% better on test error with respect to the other two architectures using the smaller network topol…
A COMPARATIVE STUDY OF PHENOMENOLOGICAL MODELS OF MR BRAKE BASED ON NEURAL NETWORKS APPROACH
2013
In this paper a full-scale commercially available magnetorheological (MR) brake installed in a semi-active suspension (SAS) system is modeled and simulated. Two well-known phenomenological hysteresis models are explored: Bouc–Wen and Dahl ones. In particular, influence of their parameters on the response is evaluated and assessed. The next step is to introduce the artificial neural networks and discuss their application in the field of systems identification. Subsequently, two feedforward neural networks are created and trained to estimate parameters characterizing each of the MR damper models described. The semi-active suspension (SAS) system equipped with a MR brake is described and the …
Simplified technique for constitutive analysis of SFRC
2014
Steel fibre reinforced concrete (SFRC) has become widespread material in areas such as underground shotcrete structures and industrial floors. However, due to the absence of material models of SFRC reliable for numerical analysis, application fields of this material are still limited. Due to interaction of concrete with fibres, a cracked section is able to carry a significant portion of tensile stresses, called the residual stresses. In present practices, residual stresses used for strength, deflection and crack width analysis are quantified by means of standard tests. However, interpretation of these test results is based on approximation using empirically deduced relationships, adequacy o…