Zoals gepland?! Onderzoek naar de betrouwbaarheid van de planning van het boorproces van de Groene Harttunnel

Van oudsher heeft Nederland te maken met rivieroverstromingen. Door de eeuwen heen werd er in het kader van de aanleg van de Hogesnelheidslijn tussen Amsterdam en Parijs (HSL-Zuid) zal in het Groene Hart tussen Leiderdorp en Hazerswoude een 7 kilometer lange boortunnel worden gerealiseerd. Deze Groene Harttunnel bestaat uit ssn buis voor beide richtingen en heeft een diameter van 14,5 meter. Hiermee zal dit de grootste boortunnel worden die tot nu toe in de wereld is gebouwd. De tunnel wordt aangelegd door de Frans-Nederlandse aannemerscombinatie Bouygues/ Koop. Het contract dat met de aannemerscombinatie is gesloten, is gemaakt op grond van Design & Construct. Dit betekent dat de aannemer zorgdraagt voor het ontwerp en de uitvoering van het project. De rol van de opdrachtgever wordt hierbij verzorgd door Projectorganisatie HSL-Zuid, waarbij met name Projectbureau Noordelijk Holland direct betrokken is bij de boortunnel. Deze controleert de aannemer en zorgt voor het contact met de verschillende overheden. Als onderdeel van de controlerende taak van het Projectbureau wordt de planning van het project in de gaten gehouden. De aannemer heeft in de aanbestedingsfase een planning opgesteld en wordt geacht zich daar gedurende het realisatiefase aan te houden. Omdat echter door de opdrachtgever niet goed kon worden ingeschat hoe betrouwbaar deze planning eigenlijk is, is in dit rapport studie hiernaar gedaan, waarbij de vraag is gesteld: Wat is de betrouwbaarheid van de planning van het boorproces van de Groene Hart-boortunnel? Hierbij is dus vooral gekeken naar het belangrijkste deel van het totale project, namelijk het boorproces. Voor het onderzoek is gekozen te werken volgens twee afzonderlijke methoden. De eerste aanpak behelst een analyse waarbij het Groene Hartproject wordt vergeleken met zoveel mogelijk andere projecten wereldwijd. De tweede aanpak is een beschouwing waarbij een planning van het boorproces is opgezet op grond van de planningspecificatie en het risico-dossier van de aannemer. Deze planning is vervolgens op een probabilistische manier doorgerekend met de zogenaamde Monte Carlo-methode. Aan de hand van een vergelijking met andere boorprojecten kan worden opgemerkt dat de maximale boorsnelheid van 17 m/dag en de ringbouwtijd, zoals die zijn ingeschat door de aannemer, realistisch te noemen zijn. Daarnaast is gekeken naar de invloed van de geologie, de lengte van het project, de boordiameter en de opzet van het bouwproces op de voortgang van het proces. Hierbij blijkt dat vooral de geologie grote invloed heeft op de voortgangsnelheid. De zandige ondergrond zal bij de Groene Harttunnel vooral gunstig werken. Verder mag verwacht worden dat de opstartfase van het project juist meer tijd en geboorde afstand zal kosten dan door de aannemer is ingepland. Omdat het moeilijk bleek om gedetailleerde informatie te vinden van veel projecten en zodoende weinig gezegd zou kunnen worden over voortgang- en stilstandtijd is een effectiviteitsfactor gedefinieerd. Deze factor geeft de verhouding tussen de gemiddelde en de maximale voortgangsnelheid van een project. Opvallend hierbij is dat de effectiviteit van de verschillende boorprojecten die hiermee bepaald werd gemiddeld slechts 40% is. Bij vergelijking van deze waarde met die van de Groene Harttunnel (50%) blijkt dat de voortgang van deze te boren tunnel erg gunstig is ingeschat.Hydraulic EngineeringCivil Engineering and Geoscience

Buiten spelen: Amsterdam voor alle leeftijden

UrbanismArchitecture and The Built Environmen

Computational 3D resolution enhancement for optical coherence tomography with a narrowband visible light source

Phase-preserving spectral estimation optical coherence tomography (SE-OCT) enables combining axial resolution improvement with computational depth of field (DOF) extension. We show that the combination of SE-OCT with interferometric synthetic aperture microscopy (ISAM) and computational adaptive optics (CAO) results in high 3D resolution over a large depth range for an OCT system with a narrow bandwidth visible light super-luminescent diode (SLD). SE-OCT results in up to five times axial resolution improvement from 8 µm to 1.5 µm. The combination with ISAM gives a sub-micron lateral resolution over a 400 µm axial range, which is at least 16 times the conventional depth of field. CAO can be successfully applied after SE and ISAM and removes residual aberrations, resulting in high quality images. The results show that phase-preserving SE-OCT is sufficiently accurate for coherent post-processing, enabling the use of cost-effective SLDs in the visible light range for high spatial resolution OCT.ImPhys/Computational ImagingImPhys/Kalkman grou

Computational 3D resolution enhancement for optical coherence tomography with a narrowband visible light source

Phase-preserving spectral estimation optical coherence tomography (SE-OCT) enables combining axial resolution improvement with computational depth of focus (DOF) extension. We combine SE-OCT with interferometric synthetic aperture microscopy (ISAM) to obtain a high 3D resolution over a large depth range with a narrow bandwidth visible light super-luminescent diode (SLD). SE-OCT gives a five times axial resolution improvement to 1.5 micrometer. The combination with ISAM gives a sub-micron lateral resolution over a 300 micrometer axial range, 12 times the conventional DOF. The results show that phase-preserving SE-OCT is sufficiently accurate for coherent post-processing, enabling the use of cost-effective SLDs in the visible light range for high spatial resolution OCT.ImPhys/Computational ImagingImPhys/Kalkman grou

Fast and accurate spectral-estimation axial super-resolution optical coherence tomography

Spectral-estimation OCT (SE-OCT) is a computational method to enhance the axial resolution beyond the traditional bandwidth limit. However, it has not yet been used widely due to its high computational load, dependency on user-optimized parameters, and inaccuracy in intensity reconstruction. In this study, we implement SE-OCT using a fast implementation of the iterative adaptive approach (IAA). This non-parametric spectral estimation method is optimized for use on OCT data. Both in simulations and experiments we show an axial resolution improvement with a factor between 2 and 10 compared to standard discrete Fourier transform. Contrary to parametric methods, IAA gives consistent peak intensity and speckle statistics. Using a recursive and fast reconstruction scheme the computation time is brought to the sub-second level for a 2D scan. Our work shows that SE-OCT can be used for volumetric OCT imaging in a reasonable computation time, thus paving the way for wide-scale implementation of superresolution OCT.ImPhys/Computational Imagin

Classification of human activity using radar and video multimodal learning

In the defence and security domain, camera systems are widely used for surveillance. The major advantage of using camera systems for surveillance is that they provide high‐resolution imagery, which is easy to interpret. However, the use of camera systems and optical imagery has some drawbacks, especially for application in the military domain. In poor lighting conditions, dust or smoke the image quality degrades and, additionally, cameras cannot provide range information too. These drawbacks can be mitigated by exploiting the strengths of radar. Radar performance can be largely maintained during the night, in various weather conditions and in dust and smoke. Moreover, radar provides the distance to detected objects. Since, the strongpoints and weaknesses of radar and camera systems seem complementary, a natural question is: can radar and camera systems learn from each other? Here the potential of radar/video multimodal learning is evaluated for human activity classification. The novelty of this work is the use of radar spectrograms and related video frames for classification with a multimodal neural network. Radar spectrograms and video frames are both two‐dimensional images, but the information they contain is of different nature. This approach was adopted to limit the required preprocessing load, while maintaining the complementary nature of the sensor data.Microwave Sensing, Signals & System

Quantification of plant morphology and leaf thickness with optical coherence tomography

Optical coherence tomography (OCT) can be a valuable imaging tool for in vivo and label-free digital plant phenotyping. However, for imaging leaves, air-filled cavities limit the penetration depth and reduce the image quality. Moreover, up to now quantification of leaf morphology with OCT has been done in one-dimensional or two-dimensional images only, and has often been limited to relative measurements. In this paper, we demonstrate a significant increase in OCT imaging depth and image quality by infiltrating the leaf air spaces with water. In the obtained high-quality OCT images the top and bottom surface of the leaf are digitally segmented. Moreover, high-quality en face images of the leaf are obtained from numerically flattened leaves. Segmentation in three-dimensional OCT images is used to quantify the spatially resolved leaf thickness. Based on a segmented leaf image, the refractive index of an infiltrated leaf is measured to be 1.345 ± 0.004, deviating only 1.2% from that of pure water. Using the refractive index and a correction for refraction effects at the air-leaf interface, we quantitatively mapped the leaf thickness. The results show that OCT is an efficient and promising technique for quantitative phenotyping on leaf and tissue level.ImPhys/Computational Imagin

Radar and video multimodal learning for human activity classification

Camera systems are widely used for surveillance in the security and defense domains. The main advantages of camera systems are their high resolution, their ease of use, and the fact that optical imagery is easy to interpret for human operators. However, particularly when considering application in the defense domain, cameras have some disadvantages. In poor lighting conditions, dust or smoke the image quality degrades and, additionally, cameras cannot provide range information. These issues may be alleviated by exploiting the strongpoints of radar. Radar performance is largely preserved during nighttime, in varying weather conditions and in dust and smoke. Furthermore, radar provides range information of detected objects. Since their qualities appear to be complementary, can radar and camera systems learn from each other? In the current study, the potential of radar/video multimodal learning is assessed for the classification of human activity.Accepted author manuscriptMicrowave Sensing, Signals & System

Evacuation plan of the city of almere: Simulating the impact of driving behavior on evacuation clearance time

The evacuation clearance time is one of the key indicators in an evacuation plan and is determined by the expected behavior of the endangered residents and roadway network characteristics. The city of Almere has developed an evacuation plan in case of the emergency of a flooding, but assumes a normal driving behavior of the evacuees. In this paper a microscopic S-Paramics simulation framework in an evacuation condition is set up to assess the impact of variations in driving behavior on the evacuation clearance time. Different scenarios in terms of acceleration rate, maximum speed, mean headway and minimum gap distance have been developed. The results show that increases in acceleration rate and in maximum speed do not have a significant impact on the evacuation clearance time. It is also found that a reduction both in mean headway and in minimum gap significantly reduce the evacuation time. Therefore, it is very important to consider the driving behavior in an evacuation condition for an evacuation plan.Transport & PlanningCivil Engineering and Geoscience

Frequency Domain Two-Stage Beamforming for Phased Array Imaging Using the Fast Hankel Transform

The huge amount of data that needs to be transferred between probe and imaging system becomes a major issue when the data transfer capacity is limited, e.g. in handheld systems, wireless probes and miniaturized probes. The amount of data can be significantly reduced by using two-stage beamforming. The first stage consists of a fixed focus algorithm that compresses channel data to scanline data. This can be done by integrated electronics in the handle. In the second stage the scanline data is further beamformed in the imaging system to obtain images that are synthetically focused at all depths. Here we present a wave equation two-stage beamforming method for phased array imaging that is computationally efficient and outperforms PSASB, a time-of-flight alternative, in terms of lateral resolution and contrast-to-noise ratio.Accepted Author ManuscriptImPhys/Acoustical Wavefield ImagingImPhys/Quantitative Imagin