176 research outputs found

    An AI-based non-intrusive reduced-order model for extended domains applied to multiphase flow in pipes

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    The modeling of multiphase flow in a pipe presents a significant challenge for high-resolution computational fluid dynamics (CFD) models due to the high aspect ratio (length over diameter) of the domain. In subsea applications, the pipe length can be several hundreds of meters vs a pipe diameter of just a few inches. Approximating CFD models in a low-dimensional space, reduced-order models have been shown to produce accurate results with a speed-up of orders of magnitude. In this paper, we present a new AI-based non-intrusive reduced-order model within a domain decomposition framework (AI-DDNIROM), which is capable of making predictions for domains significantly larger than the domain used in training. This is achieved by (i) using a domain decomposition approach; (ii) using dimensionality reduction to obtain a low-dimensional space in which to approximate the CFD model; (iii) training a neural network to make predictions for a single subdomain; and (iv) using an iteration-by-subdomain technique to converge the solution over the whole domain. To find the low-dimensional space, we compare Proper Orthogonal Decomposition with several types of autoencoder networks, known for their ability to compress information accurately and compactly. The comparison is assessed with two advection-dominated problems: flow past a cylinder and slug flow in a pipe. To make predictions in time, we exploit an adversarial network, which aims to learn the distribution of the training data, in addition to learning the mapping between particular inputs and outputs. This type of network has shown the potential to produce visually realistic outputs. The whole framework is applied to multiphase slug flow in a horizontal pipe for which an AI-DDNIROM is trained on high-fidelity CFD simulations of a pipe of length 10 m with an aspect ratio of 13:1 and tested by simulating the flow for a pipe of length 98 m with an aspect ratio of almost 130:1. Inspection of the predicted liquid volume fractions shows a good match with the high fidelity model as shown in the results. Statistics of the flows obtained from the CFD simulations are compared to those of the AI-DDNIROM predictions to demonstrate the accuracy of our approach

    Development of a Flow-Trough Microarray based Reverse Transcriptase Multiplex Ligation-Dependent Probe Amplification Assay for the Detection of European Bunyaviruses

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    It is suspected that apart from tick-borne encephalitis virus several additional European Arboviruses such as the sandfly borne Toscana virus, sandfly fever Sicilian virus and sandfly fever Naples virus, mosquito-borne Tahyna virus, Inkoo virus, Batai virus and tick-borne Uukuniemi virus cause aseptic meningo-encephalitis or febrile disease in Europe. Currently, the microarray technology is developing rapidly and there are many efforts to apply it to infectious diseases diagnostics. In order to arrive at an assay system useful for high throughput analysis of samples from aseptic meningo-encephalitis cases the authors developed a combined multiplex ligation-dependent probe amplification and flow-through microarray assay for the detection of European Bunyaviruses. These results show that this combined assay indeed is highly sensitive, and specific for the accurate detection of multiple viruses

    Studies of new Higgs boson interactions through nonresonant HH production in the b¯bγγ fnal state in pp collisions at √s = 13 TeV with the ATLAS detector

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    A search for nonresonant Higgs boson pair production in the b ¯bγγ fnal state is performed using 140 fb−1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. This analysis supersedes and expands upon the previous nonresonant ATLAS results in this fnal state based on the same data sample. The analysis strategy is optimised to probe anomalous values not only of the Higgs (H) boson self-coupling modifer κλ but also of the quartic HHV V (V = W, Z) coupling modifer κ2V . No signifcant excess above the expected background from Standard Model processes is observed. An observed upper limit µHH < 4.0 is set at 95% confdence level on the Higgs boson pair production cross-section normalised to its Standard Model prediction. The 95% confdence intervals for the coupling modifers are −1.4 < κλ < 6.9 and −0.5 < κ2V < 2.7, assuming all other Higgs boson couplings except the one under study are fxed to the Standard Model predictions. The results are interpreted in the Standard Model efective feld theory and Higgs efective feld theory frameworks in terms of constraints on the couplings of anomalous Higgs boson (self-)interactions

    Measurement of the H → γ γ and H → ZZ∗ → 4 cross-sections in pp collisions at √s = 13.6 TeV with the ATLAS detector