1,722,723 research outputs found
A Step-based framework to combine creativity, project management, and technical development in industrial innovation
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Virtual prototyping in the design process of optimized mould gating system for high pressure die casting
No full textPurpose – High Pressure Die Casting is a widely used industrial process to manufacture complex-shaped products in light alloys. Virtual prototyping techniques, especially numeric based simulations of the casting process, allow the die filling process to be evaluated and help faster optimization of the gating system, which is the most critical element of the mould. This paper presents a four step approach to design optimal moulds taking advantage of the simulation tools.
Design/methodology/approach - No formalized method to design an optimal gating system is available yet and the majority of the studies aim to optimize existing geometries or to choose from alternative solutions. Rather than optimizing the geometries of predefined designs by running attempt trials, the proposed approach defines a procedure to position cavities, gating systems and, finally, to determine the whole mould geometry.
Findings - The approach is demonstrated through three different industrial applications. The design of a 6-cavity mould for gas cooking burners is reported at first. Then, two test cases, a cup and a radiator, are reported for showing different arrangements of the gating system. The reached quality of the mould design has been assessed using metallographic analyses of the casts.
Originality/value – The design of a mould is strictly correlated to its product and mainly based on a trial-and-error approach. Numerical simulations offer a powerful and not expensive way to study the effectiveness of different die designs and filling processes. The paper proposes a structured approach for the definition of the gating system. It ultimately leads to improvements in both product quality and process productivity, including more effective control of the die filling and die thermal performance
Improving the Learning Experience within MCAD Education: A Tool for Students to Assist in Self-Assessment during Modeling Exercises
Get PDFAutomation of CAD model grading is obviously capable of considerably reducing the time required for analyzing and assessing CAD models created by students, though the type and complexity of CAD model that can be analyzed, and the quality of the feedback that is generated, are still quite limited. Recent trends to allow students to use the same software tools as teachers use for grading CAD models suffer, from the methodological and conceptual approach, because grading provides feedback that is based on a finalized result, and thus always contains one assessment criterion that is related to the completeness of the solution. Being structured in this manner, it cannot be a direct part of the process and learning experience during the performance itself, that is the design, creation, and alteration of a CAD model. This paper reports on efforts and results from the first step of a two-step project to improve this situation as follows. Firstly, a learningexperience-oriented approach is presented, aimed at improving skill and expertise development in regard to robust and alterable parametric feature-based solid model creation. Secondly, a novel concept and a key metric for CAD model assessment and core behavior evaluation are introduced. Thirdly, a newly developed software tool is presented. This tool is dedicated to supporting students in putting into practice this learning-experience-oriented approach
Search for the Higgs boson decaying into two muons with the CMS experiment
No full textThe Higgs boson was discovered at the CERN LHC by both the ATLAS and CMS collaborations with a mass near 125 GeV in 2012. The measurement of the Higgs boson properties has been one of the main targets of LHC experiments since the discovery. In order to probe the mechanism giving mass to fermions and bosons, the Higgs boson couplings have to be measured. The Standard Model Higgs couplings can be extracted by measuring Higgs boson production and decay rates. Therefore a lot of effort has been done to observe every single experimentally accessible decay in various production modes in the last few years. The bosonic decay modes of the Higgs in gamma gamma, ZZ, and WW have been established using data collected until 2012 (LHC Run 1) while the data collected in 2016 and 2017 allowed to measure the decays to the third generation fermions. The decay of the Higgs boson into tautau has been observed using 2016 data and it confirmed the coupling of the Higgs with leptons. The decay of the Higgs boson into bb has been observed in 2018, hence establishing the coupling with down-type quark. The ttH production mode has also been observed, thus probing directly the coupling to up-type quarks. So far, the Higgs boson couplings have been observed only with the third generation of fermions, thus, the next step would be the search for decays into the second generation. Among those, the Higgs decay into c-quark pairs is the one with the higher event rate. Probing the Standard Model expected event rate is notwithstanding impossible at the LHC because of the large amount of irreducible background and because of the low mass resolution in the dijet final state. Instead, the Higgs boson decay into muons has smaller rates but it also has a clean final state that can be reconstructed with high efficiency and excellent mass resolution, thanks to the CMS tracking and muon systems. However, since the branching fraction B(H→mu mu) is very small (2x104) and the LHC produces abundant backgrounds, an observation of this decay has not been reached yet and upper limits only have been set. My work took part in the most recent search for the Higgs boson decaying to two muons performed by the CMS collaboration. The analysis uses the full proton-proton collision data collected by the CMS experiment at \sqrt{s}=13 TeV during Run 2, corresponding to an integrated luminosity of 137.4 fb-1. The search of the Higgs boson to muon decay targets each of the four main Higgs production channels at the LHC. The four searches use orthogonal data and their results are combined in a single measurement. My work has been dedicated to the improvement of the search in the vector boson fusion (VBF) production mode. In this work, we demonstrate that the VBF channel is the most sensitive among the four H→mu mu searches. The VBF dedicated analysis is based on the fit of a multivariate discriminator, in contrast with the other three dedicated Higgs searches where the fit is performed on the dimuon mass distribution. Moreover, the background estimation is completely based on Monte-Carlo simulations. These two aspects make the strategy to be very similar to the one adopted by two important CMS measurements: the measurement of electroweak production of two jets in association with a Z boson, and the measurement of the Higgs boson decaying into b-quark pairs. Machine learning is a fundamental tool to improve the sensitivity of this search. Two different machine learning techniques are tested for the H→ mu mu search: boosted decision tree (BDT) and deep neural network (DNN). The performance of the two algorithms are compared and the results are extracted from the algorithm that separates better the signal from the background on simulated data. The Higgs boson signal strength is extracted among several regions with a simultaneous maximum likelihood fit and the results are computed for a Standard Model Higgs boson with a mass of 125.38 GeV. In the VBF channel, an excess of events is observed with a strength of 1.36+0.69-0.61, defined as the ratio between the expected and the observed event rate sigmaobs(pp→H→mu mu)/sigmaSM(pp→H→mu mu). The observed excess of events corresponds to a signal significance of 2.4 standard deviations above the background-only hypothesis. The excess of events observed from the combination of the four dedicated searches corresponds to a signal significance of 3.0 standard deviations and it constitutes the evidence of the Higgs boson decay into muons. The results obtained with the data collected at 13 TeV are combined with the ones obtained during Run 1 at the center of mass energies of 7 and 8 TeV. The final combination improves the results of about 1%, resulting in a signal strength of 1.19+0.40-0.30(stat)+0.15-0.14(syst). The thesis is structured as follows. The Standard Model and the Higgs mechanism are introduced in chapter 1. Moreover, the most important measurements of the Higgs boson properties are summarized in that chapter. In chapter 2 the experimental apparatus is described. Firstly, the LHC machine is introduced, then the CMS experiment and the various subdetectors are presented. The algorithms used by CMS to reconstruct physics objects are introduced in chapter 3. In particular, lepton reconstruction and identification are described in the first half of the chapter, while the second half is dedicated to jets. Chapter 4 introduces the search for H with CMS Run 2 data. An overview of the entire analysis is given and the dedicated searches in the ggH, VH, and ttH channels are summarized. The VBF analysis that I have carried out is described in detail in chapter 5. Finally, chapter 6 presents the results of the VBF dedicated search and the results obtained from the combination with the other three dedicated searches and with the data collected during Run 1
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