Performance of the LHCb Vertex Detector Alignment Algorithm determined with Beam Test Data

LHCb is the dedicated heavy flavour experiment at the Large Hadron Collider at CERN. The partially assembled silicon vertex locator (VELO) of the LHCb experiment has been tested in a beam test. The data from this beam test have been used to determine the performance of the VELO alignment algorithm. The relative alignment of the two silicon sensors in a module and the relative alignment of the modules has been extracted. This alignment is shown to be accurate at a level of approximately 2 micron and 0.1 mrad for translations and rotations, respectively in the plane of the sensors. A single hit precision at normal track incidence of about 10 micron is obtained for the sensors. The alignment of the system is shown to be stable at better than the 10 micron level under air to vacuum pressure changes and mechanical movements of the assembled system.Comment: accepted for publication in NIM

Collaborative development of diffraction-limited beamline optical systems at US DOE light sources

An ongoing collaboration among four US Department of Energy (DOE) National Laboratories has demonstrated key technology prototypes and software modeling tools required for new high-coherent flux beamline optical systems. New free electron laser (FEL) and diffraction-limited storage ring (DLSR) light sources demand wavefront preservation from source to sample to achieve and maintain optimal performance. Fine wavefront control was achieved using a novel, roomtemperature cooled mirror system called REAL (resistive element adjustable length) that combines cooling with applied, spatially variable auxiliary heating. Single-grating shearing interferometry (also called Talbot interferometry) and Hartmann wavefront sensors were developed and used for optical characterization and alignment on several beamlines, across a range of photon energies. Demonstrations of non-invasive hard x-ray wavefront sensing were performed using a thin diamond single-crystal as a beamsplitter

3D Object Reconstruction from Imperfect Depth Data Using Extended YOLOv3 Network

State-of-the-art intelligent versatile applications provoke the usage of full 3D, depth-based streams, especially in the scenarios of intelligent remote control and communications, where virtual and augmented reality will soon become outdated and are forecasted to be replaced by point cloud streams providing explorable 3D environments of communication and industrial data. One of the most novel approaches employed in modern object reconstruction methods is to use a priori knowledge of the objects that are being reconstructed. Our approach is different as we strive to reconstruct a 3D object within much more difficult scenarios of limited data availability. Data stream is often limited by insufficient depth camera coverage and, as a result, the objects are occluded and data is lost. Our proposed hybrid artificial neural network modifications have improved the reconstruction results by 8.53 which allows us for much more precise filling of occluded object sides and reduction of noise during the process. Furthermore, the addition of object segmentation masks and the individual object instance classification is a leap forward towards a general-purpose scene reconstruction as opposed to a single object reconstruction task due to the ability to mask out overlapping object instances and using only masked object area in the reconstruction process

Leak localization in water distribution networks using a mixed model-based/data-driven approach

“The final publication is available at Springer via http://dx.doi.org/10.1016/j.conengprac.2016.07.006”This paper proposes a new method for leak localization in water distribution networks (WDNs). In a first stage, residuals are obtained by comparing pressure measurements with the estimations provided by a WDN model. In a second stage, a classifier is applied to the residuals with the aim of determining the leak location. The classifier is trained with data generated by simulation of the WDN under different leak scenarios and uncertainty conditions. The proposed method is tested both by using synthetic and experimental data with real WDNs of different sizes. The comparison with the current existing approaches shows a performance improvement.Peer ReviewedPostprint (author's final draft

Investigation of the Viscoelastic Effect on Optical- Fiber Sensing and Its Solution for 3D-Printed Sensor Packages

Viscoelasticity is an effect seen in a wide range of materials and it affects the reliability of static measurements made using Fiber Bragg Grating-based sensors, because either the target structure, the adhesive used, or the fiber itself could be viscoelastic. The effect of viscoelasticity on FBG-based sensing has been comprehensively researched through theoretical analysis and simulation using a finite-element approach and a further data processing method to reconstruct the graphical data has been developed. An integrated sensor package comprising of an FBG-based sensor in a polymer host and manufactured by using three-dimensional printing was investigated and examined through tensile testing to validate the approach. The application of the 3D-printed FBG-based sensor package, coupled to the data process method has been explored to monitor the height of a railway pantograph, a critical measurement requirement to monitor elongation, employing a method that can be used in the presence of electromagnetic interference. The results show that the effect of viscoelasticity can be effectively eliminated, and the graphical system response allows results that are sufficiently precise for field use to be generated

Commissioning of the ATLAS Muon Spectrometer with cosmic rays

The ATLAS detector at the Large Hadron Collider has collected several hundred million cosmic ray events during 2008 and 2009. These data were used to commission the Muon Spectrometer and to study the performance of the trigger and tracking chambers, their alignment, the detector control system, the data acquisition and the analysis programs. We present the performance in the relevant parameters that determine the quality of the muon measurement. We discuss the single element efficiency, resolution and noise rates, the calibration method of the detector response and of the alignment system, the track reconstruction efficiency and the momentum measurement. The results show that the detector is close to the design performance and that the Muon Spectrometer is ready to detect muons produced in high energy proton–proton collisions