Improvement and Sensitivity Analysis of Thermal Thin-Ice Thickness Retrievals

Considering the sea ice decline in the Arctic during the last decades, polynyas are of high research interest since these features are core areas of new ice formation. The determination of ice formation requires accurate retrieval of polynya area and thin-ice thickness (TIT) distribution within the polynya. We use an established energy balance model to derive TITs with MODIS ice surface temperatures $(T_{s})$ and NCEP/DOE Reanalysis II in the Laptev Sea for two winter seasons. Improvements of the algorithm mainly concern the implementation of an iterative approach to calculate the atmospheric flux components taking the atmospheric stratification into account. Furthermore, a sensitivity study is performed to analyze the errors of the ice thickness. The results are the following: 1) 2-m air temperatures $(T_{a})$ and $T_{s}$ have the highest impact on the retrieved ice thickness; 2) an overestimation of $T_{a}$ yields smaller ice thickness errors as an underestimation of $T_{a}$; 3) NCEP $T_{a}$ shows often a warm bias; and 4) the mean absolute error for ice thicknesses up to 20 cm is $pm$4.7 cm. Based on these results, we conclude that, despite the shortcomings of the NCEP data (coarse spatial resolution and no polynyas), this data set is appropriate in combination with MODIS $T_{s}$ for the retrieval of TITs up to 20 cm in the Laptev Sea region. The TIT algorithm can be applied to other polynya regions and to past and future time periods. Our TIT product is a valuable data set for verification of other model and remote sensing ice thickness data

3D based analysis for PCB jet printing using ultra-close range photogrammetry

Das PCB Jet Printing ist eine innovative Methode um Lotpaste ohne die Verwendung von Schablonen auf Leiterplatten (PCB - printed circtuit board) zu applizieren. In Fertigungslinien enthaltene Inspektionssysteme sind in der Lage zu entscheiden, ob eine Leiterplatte korrekt bedruckt wurde und somit weiterverwendbar ist. Eine Korrektur fehlerhafter Platten ist in diesem Schritt mit vertretbaren Kosten und Aufwand jedoch nicht mehr möglich. Das Ziel dieser Arbeit ist daher die Entwicklung eines integrierbaren und online-fähigen Inspektionssystems um den Druckprozess zu überwachen. Dazu soll das Volumen der Lotpunkte ermittelt werden um dieses bei Bedarf zu korrigieren, bevor die Leiterplatte den Drucker verlässt. Somit können Unsicherheiten reduziert und die Effizienz des Systems erhöht werden. Für die Umsetzung wird eine photogrammertrische Rekonstruktion etabliert. Dies beinhaltet das Design und die Realisierung eines Demonstratorsystems. Es wurde ein neuartiger Ansatz für die Kamerakalibrierung im neu eingeführten Bereich der ultra-close range normal case photogrammetry vorgeschlagen und über den 2D Reprojektionsfehler sowie den 3D Rekonstruktionsfehler evaluiert. Um effizient Bildmerkmale zu extrahieren wurden bekannte Merkmalsextraktoren und -deskriptoren untersucht und beispielsweise in Bezug auf eine Skalenraumprozessierung angepasst. Für die Evaluierung wurde ein neuer Parameter eingeführt (Solder Joint Feature Coverage - SolFeC), welcher die Abdeckung der Lotpunkte mit Bildmerkmalen beschreibt. Das kalibrierte Kameramodell wurde neben der Rekonstruktion zur modellbasierten Punktkorrespondenzkorrektur verwendet, da dieser Schritt im Nahbereich aufgrund des identischen Erscheinungsbildes verschiedener Lotpunkte eine hohe Herausforderung darstellt. Die Ergebnisse des feature matchings wurde über die Parameter precision und recall sowie über das Rekonstruktionsergebnis bewertet. Mittels angepasster Kameramodelle wurden die Punktkorrespondenzen zur 3D Rekonstruktion einer Punktwolke verwendet. Diese wird in ein Clustering überführt. Anschließend wird jede Lotpunktwolke über eine konkave Hülle vermascht und gefiltert. Die Abweichung der berechneten Volumina innerhalb der Lotpunkte mit einem Volumen von mehr als 30 nl beträgt weniger als 12%, was mit der Schwankung des Lotpastendrucks korrespondiert. Die allgemeine Abweichung beträgt 14%.PCB Jet-Printing is an innovative method to deposit solder paste on printed circuit boards (PCB) without stencils. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. The objective of this thesis was the development of a quality assessment system in order to realize a built-in, real-time inspection of the printing process. In this respect, the solder joints volume should be measured before the PCB leaves the jet printer in order to correct the volume if necessary to minimize the uncertainties and thus increase the efficiency of the process. In the framework of this thesis, a photogrammetric reconstruction process including software and demonstrator system was designed, implemented and evaluated. A novel camera calibration method was proposed for the newly introduced field of ultra-close range normal case photogrammetry. Well-known feature detectors and descriptors were employed and adapted to efficiently and reliably obtain image features. The methods are evaluated based on a newly introduced parameter, called Solder Joint Feature Coverage, that describes if a solder joint is properly covered by feature points. The calibrated camera model was used in the processing step of image based feature extraction and model based matching correction in order to obtain true feature point correspondences. The evaluation shows the best results for a combination of the BRIEF descriptor and a hamming distance based feature matching with a subsequent camera model based matching correction. The solder joint areas in the images are detected by a texture based classification using the texture features of Haralick. The camera models are used in combination with the corrected feature matches to reconstruct a 3D point cloud of the PCB. The calculated solder joint volumes are evaluated using a structured light based ground truth. The results show a suitable estimation with deviation of less than 12% for large solder joints with a volume of more than 30 nl, which coincides with the volume deviation of the printer. The overall deviation of the calculated volumes is 14%. The implemented real-time pipeline allows for these obtained solder joint volumes to be fed back to the printer to correct errors immediately during the printing process

Experimental Investigation of Nozzle/Plume Aerodynamics at Hypersonic Speeds

The work performed by D. W. Bogdanoff and J.-L. Cambier during the period of 1 Feb. - 31 Oct. 1992 is presented. The following topics are discussed: (1) improvement in the operation of the facility; (2) the wedge model; (3) calibration of the new test section; (4) combustor model; (5) hydrogen fuel system for combustor model; (6) three inch calibration/development tunnel; (7) shock tunnel unsteady flow; (8) pulse detonation wave engine; (9) DCAF flow simulation; (10) high temperature shock layer simulation; and (11) the one dimensional Godunov CFD code

DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives

We present a new parallel algorithm for probabilistic graphical model optimization. The algorithm relies on data-parallel primitives (DPPs), which provide portable performance over hardware architecture. We evaluate results on CPUs and GPUs for an image segmentation problem. Compared to a serial baseline, we observe runtime speedups of up to 13X (CPU) and 44X (GPU). We also compare our performance to a reference, OpenMP-based algorithm, and find speedups of up to 7X (CPU).Comment: LDAV 2018, October 201

The observation of the thin-ice thickness distribution within the Laptev Sea polynya using MODIS data

Polynyas are of high research interest since these features are areas of extensive new ice formation. The calculation of accurate ice-production values requires the knowledge of polynya area and thin-ice thickness distribution. These two variables can be derived by remote sensing data. However, a cross-validation study of various remote sensing data sets indicates that the spatial resolution issue is essential for the retrieval of accurate thin-ice thickness distribution. Thus, high-resolution remote sensing data must be used. MODIS thermal-infrared data with a spatial resolution of 1 km × 1 km is appropriate for the retrieval of thin-ice thickness distribution within the polynya. The algorithm to derive thermal-infrared thin-ice thickness is improved to state-of-the-art parameterizations. The mean absolute error of thin-ice thickness is ±4.7 cm for ice below 20 cm of thickness. The thin-ice thickness maps lack full coverage due to the restriction of the algorithm to cloud-free and nighttime data. Therefore, a compositing method is applied to compute daily thin-ice thickness maps. These maps cover on average 70 % of the Laptev Sea polynya. In order to fill the remaining gaps a combined remote sensing – model approach is developed to provide a consistent time series of high-resolution thin-ice thickness maps. This data set is valuable for the retrieval of accurate ice production within polynyas

Ice production of polynyas in the Laptev Sea calculated from mesoscale NWP model simulations for the winters 2007/08 and 2008/09

The Laptev Sea area of the Siberian Arctic is known as being a highly productive area for the formation of new ice throughout the winter season. This area is characterized by flaw polynyas which occur at the edge of the fast ice surrounding the coastal zones during wintertime. Due to large turbulent atmospheric heat fluxes, polynyas are strong sea ice producers. However, estimates of sea ice production in the Laptev Sea polynyas are arguable since high resolution and high quality atmospheric data is not available for that area. Previous estimations of ice production rely on global reanalyses as atmospheric forcing, such as NCEP with about 280km horizontal resolution, which is too coarse to take polynyas into account. In our study, we use the limited area model COSMO with a prescribed sea ice coverage by daily AMSR-E satellite data. Runs with 15 and 5 km horizontal resolution (nested in global GME model data) are performed for the two winter periods (Nov-May) 2007/08 and 2008/09. The net energy loss of the polynya surface is used to determine ice production. COSMO is run in a forecast mode for overlapping daily 30h runs. We use a thermodynamic sea ice module for COSMO and varied the ice thickness in the polynya area from 0 to 10 cm. This allows for a new approach for estimating the ice production in the Laptev Sea polynyas. The total polynya ice production is calculated as 51.25 km3 in 2007/08 and 126.87 km3 in 2008/09 for the assumption of ice free polynyas. A coverage with 10 cm of thin ice reduces the ice production by about 30 %. An AMSR-E- and NCEP-based study gives a value of 46.37 km3 for 2007/08 and an average of 55.2 km3 for 1979-2008 with a maximum of 73.3 km3 in 2003/04 and a minimum 35.7 km3. Hence, interannual variability between the two COSMO-simulated years outnumbers the long-term mean interannual variability of satellite-based study with NCEP forcing. Our study leads to the conclusion that interannual variability is underestimated by previous studies, which are not able to take into account the interaction between the polynya and the overlying atmospheric boundary layer. In future, we will use ERA-Interim data as forcing data for COSMO to extend the modeled time range to 10 years

Monitoring of thin ice in the Laptev Sea Polynya

It is estimated that a considerable fraction of new ice formation on Arctic shelf areas takes place in the Laptev Sea polynyas. However, the different studies reveal strong discrepancies in ice production rates. For an accurate monitoring of surface heat loss and hence, ice production within polynyas it is important to know the thin ice distribution within the polynya. We use an established thin-ice algorithm with several modifications to retrieve the thin ice thickness distribution up to 50 cm based on MODIS ice surface temperatures and atmospheric data from model simulations. We verify the MODIS ice surface temperatures with a data set measured during a field campaign in the Laptev Sea. For the calculation of thin ice thicknesses we use NCEP reanalyses, GME analyses and COSMO simulations in comparison as different atmospheric forcing data. We find that from the several atmospheric variables the air temperature at 2 m has the greatest impact on the ice thickness calculation. At ice thicknesses above 20 cm the algorithm responds sensitively to errors in the atmospheric data. In regions of very thin ice the errors in the atmospheric data are masked due to larger temperature differences between surface and atmosphere. However, a reliable atmospheric data set is necessary for the calculation of accurate thin ice thicknesses