Calculation of Torsional Vibrations and Prediction of Print Quality in Sheetfed Offset Printing Presses

In sheetfed offset printing presses the synchronous drive of the paper-carrying cylinders is achieved by a continuous geared drive train. Due to the mechanical compliance of the drive train, the system is capable of torsional oscillations, which are excited by a multiplicity of phenomena. The oscillations of the gear train have a direct effect on print quality. The color register must not fluctuate from sheet to sheet, since fluctuations on the order of a few μm lead to unacceptable printing results. The excitation frequencies or orders in the printing press lead to register errors with corresponding orders on the printed sheets. Using a mechanical model of the printing press, the effects of the excitations on the system can be simulated and, thus, predictions of register variation can be made using a sheet-tracking algorithm. In a practical example, it is shown how due to a harmonic disturbance acting on the main drive motor, register variations occur with a corresponding rhythm. By compensating the excitation (feed-forward control), the torsional vibrations of the machine can be suppressed and the print quality can thus be ensured. This is shown both in the simulation and on the basis of measured data. It is thus possible to predict the effect of mechanical or control-related changes in the design of the printing machine, which ultimately saves time and money during machine development and manufacturing

Stability Analysis of parameter-excited linear Vibration Systems with Time Delay, using the Example of a Sheetfed Offset Printing Press

This article describes stability studies on parameter-excited linear vibration systems with time delay. A method for stability analysis is presented. Therefore, the transcendental transmission element of the time delay e-st is approximated as an all-pass element with the rational transfer function by means of the so-called Padé approximation. The system can be represented in the state space and the methods of the Floquet theory can also be applied to the system with approximated time delay. The process can be implemented without great effort in a standardized simulation environment such as MATLAB/SIMULINK, whereby existing models and methods can be reused. The suitability of the method is shown in the well-known example of the Mathieu differential equation with time delay. Variations between different solvers and approximation orders are described. An extended view and the transfer to an industrial application take place with the example of the drive of a sheetfed offset printing machine. The relevant vibration system is represented by an oscillator with several degrees of freedom. The belt, which couples the degrees of freedom of the drive motor and the machine, leads to a periodic (harmonic) parameter excitation of the system due to its inhomogeneous nature. The speed and position control of the drive motor (PI controller) is associated with a time delay, resulting in a system of the type described above

Reducing model bias in a deep learning classifier using domain adversarial neural networks in the MINERvA experiment

We present a simulation-based study using deep convolutional neural networks (DCNNs) to identify neutrino interaction vertices in the MINERvA passive targets region, and illustrate the application of domain adversarial neural networks (DANNs) in this context. DANNs are designed to be trained in one domain (simulated data) but tested in a second domain (physics data) and utilize unlabeled data from the second domain so that during training only features which are unable to discriminate between the domains are promoted. MINERvA is a neutrino-nucleus scattering experiment using the NuMI beamline at Fermilab. $A$-dependent cross sections are an important part of the physics program, and these measurements require vertex finding in complicated events. To illustrate the impact of the DANN we used a modified set of simulation in place of physics data during the training of the DANN and then used the label of the modified simulation during the evaluation of the DANN. We find that deep learning based methods offer significant advantages over our prior track-based reconstruction for the task of vertex finding, and that DANNs are able to improve the performance of deep networks by leveraging available unlabeled data and by mitigating network performance degradation rooted in biases in the physics models used for training.Comment: 41 page

Measurement of Total and Differential Cross Sections of Neutrino and Antineutrino Coherent π±\pi^\pm Production on Carbon

Neutrino induced coherent charged pion production on nuclei, $\overline{\nu}_\mu A\to\mu^\pm\pi^\mp A$, is a rare inelastic interaction in which the four-momentum squared transfered to the nucleus is nearly zero, leaving it intact. We identify such events in the scintillator of MINERvA by reconstructing |t| from the final state pion and muon momenta and by removing events with evidence of energetic nuclear recoil or production of other final state particles. We measure the total neutrino and antineutrino cross sections as a function of neutrino energy between 2 and 20 GeV and measure flux integrated differential cross sections as a function of $Q^2$, $E_\pi$ and $\theta_\pi$. The $Q^2$ dependence and equality of the neutrino and anti-neutrino cross-sections at finite $Q^2$ provide a confirmation of Adler's PCAC hypothesis

Single neutral pion production by charged-current νˉμ\bar{\nu}_\mu interactions on hydrocarbon at ⟨Eν⟩=\langle E_\nu \rangle = 3.6 GeV

Single neutral pion production via muon antineutrino charged-current interactions in plastic scintillator (CH) is studied using the \minerva detector exposed to the NuMI low-energy, wideband antineutrino beam at Fermilab. Measurement of this process constrains models of neutral pion production in nuclei, which is important because the neutral-current analog is a background for $\bar{\nu}_e$ appearance oscillation experiments. The differential cross sections for $\pi^0$ momentum and production angle, for events with a single observed $\pi^0$ and no charged pions, are presented and compared to model predictions. These results comprise the first measurement of the $\pi^0$ kinematics for this process.Comment: 6 pages, 5 figures, submitted to Physics Letters

MINERvA neutrino detector response measured with test beam data

The MINERvA collaboration operated a scaled-down replica of the solid scintillator tracking and sampling calorimeter regions of the MINERvA detector in a hadron test beam at the Fermilab Test Beam Facility. This article reports measurements with samples of protons, pions, and electrons from 0.35 to 2.0 GeV/c momentum. The calorimetric response to protons, pions, and electrons are obtained from these data. A measurement of the parameter in Birks' law and an estimate of the tracking efficiency are extracted from the proton sample. Overall the data are well described by a Geant4-based Monte Carlo simulation of the detector and particle interactions with agreements better than 4%, though some features of the data are not precisely modeled. These measurements are used to tune the MINERvA detector simulation and evaluate systematic uncertainties in support of the MINERvA neutrino cross section measurement program.Comment: as accepted by NIM