Railway freight transport and logistics: Methods for relief, algorithms for verification and proposals for the adjustment of tunnel inner surfaces

In Europe, the attention to efficiency and safety of international railway freight transport has grown in recent years and this has drawn attention to the importance of verifying the clearance between vehicle and lining, mostly when different and variable rolling stock types are expected. This work consists of defining an innovative methodology, with the objective of surveying the tunnel structures, verifying the clearance conditions, and designing a retrofitting work if necessary. The method provides for the use of laser scanner, thermocameras, and ground penetrating radar to survey the geometrical and structural conditions of the tunnel; an algorithm written by the authors permits to verify the clearances. Two different types of works are possible if the inner tunnel surfaces interfere with the profile of the rolling stock passing through: modification of the railroad track or modification of the tunnel intrados by mean milling of its lining. The presented case study demonstrates that the proposed methodology is useful for verifying compatibility between the design vehicle gauge and the existing tunnel intrados, and to investigate the chance to admit rolling stocks from different states. Consequently, the results give the railway management body a chance to perform appropriate measurements in those cases where the minimum clearance requirements are not achieved

Towards Model-Based Condition Monitoring of Railway Switches and Crossings

Railway switches and crossings (S&C, turnouts) connect different track sections and create a railway network by allowing for trains to change between tracks. This functionality comes at a cost as the load-inducing rail discontinuities in the switch and crossing panels cause much higher degradation rates for S&C compared to regular plain line track. The high degradation rates create a potential business case for condition monitoring systems that can allow for improved maintenance decisions compared to what can be achieved from periodic inspection intervals using measurement vehicles or visual inspection by engineers in track. \ua0To this end, this thesis addresses the development of tailored processing tools for the analysis of measured data from accelerometers mounted adjacent to the crossing transition in crossing panels. With the presented tools, a condition monitoring framework is established. The analysis procedures showed robustness in processing large datasets. The framework includes the extraction of different crossing panel condition indicators for which the interpretation is supported by multi-body simulations (MBS) of dynamic train–track interaction. Additionally, a demonstrator is presented for MBS model calibration to the measured track responses.A particularly important signal processing tool is the development of a novel sleeper displacement reconstruction method based on frequency-domain integration. Using the reconstructed displacements, the track response is separated into quasi-static and dynamic domains based on deformation wavelength regions. This separation is shown to be a promising strategy for independent observations of the ballast condition and the crossing rail geometry condition from a single measurement source. In addition to sleeper acceleration measurements, field measurements have been performed in which crossing rail geometries were scanned. The scanned geometries have been implemented into a MBS software with a structural representation of the crossing panel, where analyses have been performed to relate the concurrently measured accelerations and crossing rail geometries. To address the variation in operational conditions in the MBS environment, a sample of measured wheel profiles was accounted for in the analysis. This MBS study showed that there is a strong correlation between the crossing rail geometry condition, wheel–rail contact force, and crossing condition indicators computed from the dynamic track responses. Contrasting measured and simulated track responses from the six investigated crossing panels showed a good agreement. This observation supports the validity of the simulation-based condition assessment of crossing rail geometry. Based on the work in this thesis, a foundation is set for developing methods for automatic calibration of S&C MBS models and subsequent damage evolution modelling based on operational online condition monitoring data. This development aims to address S&C service life in a digital environment and presents a key component for building a Digital Twin prototype for S&C condition monitoring

Terrestrial laser scanning as a key element in the integrated monitoring of tidal influences on a twin-tube concrete tunnel

In 2012, for the first time in Belgium, integrated monitoring was carried out to assess the deformations of a twin-tube tunnel below the River Scheldt in Antwerp under the influence of estuarine tides. Levelling measurements during a tide cycle showed a variation in the height of levelling bolts of up to 10mm between low and high tide. Simultaneous strain-gauge measurements also showed a significant difference in strains. A deformation of the tunnel section during each twice-daily tide cycle, resulting in an eccentric egg or pumpkin shape, could hold large risks for the strength and durability of the tunnel structure. However, laser scanning results showed that there were no significant deformations of the tunnel's shape during the tide cycle. The laser scanning measurements resulted in a more thorough view of the deformation pattern which was much needed and improved the long-term risk assessment of the tunnel

Evaluation of new technologies to support asset management of metro systems

Since 1930, London Underground Limited (LUL) has performed visual inspections to understand the condition of the physical assets such as tunnels, bridges and structures. The major problem with this kind of inspection is the lack in quality of the data, as it depends on the ability of the inspector to assess and interpret the condition of the asset both accurately and with repeatability. In addition, data collection is time-consuming and, therefore, costly when the whole of the metro network needs to be regularly inspected and there are limited periods when access is available. The problems associated with access to the infrastructure have increased significantly with the implementation of the night tube and will increase further as the night tube is extended over the next 5 to 10 years. To determine the condition of metro assets and to predict the need for intervention, monitoring the changes in the assets’ condition is key to any further evaluation and maintenance planning. This thesis presents the outcomes of using new technologies such as Thermography, Kinematic and Static Laser Scanning, Close-Range Photogrammetry and Total Station to measure defects, such as water seepage, mortar loss in joints, lining face loss (in brick tunnels), cracks, corrosion, voids, cavities and spalls. Each technique is explored through three case studies that evaluate the performance and limitation in the determination of the asset condition. The first case study was performed to compare and contrast the use of Euroconsult’s high definition laser survey against a Principal Inspection Report to determine the level of consistency in predicting the asset condition. During this case study, reports from laser surveys and principal inspections of brick tunnels and covered ways were compared. This analysis showed that a direct comparison between the two inspections is not appropriate because the laser inspection does not capture all the defects mentioned in the Engineering Standard S1060. It also showed that to close the gap between the laser survey and visual inspection, laser surveys would have to be performed every year in brick tunnels and then compare any changes in asset condition with that from the previous scan. The second case study was performed using Infrared Thermography (IRT) to identify water seepage in the brick tunnels as well as test the system in a configuration that would allow the survey to be done from an engineering train. A set of calibration tests were performed in the lab and later the technique was trialled on an engineering train. The results showed that it is possible to measure the level of moisture on specific parts of the lining and that the comparison of surveys performed at different times can allow asset managers to react before a seepage is established, potentially reducing the risk of system disruption caused by water ingress in tunnels. The data also revealed that this technique could be used for other purposes, such as examining the condition of other assets such as brackets, cable supports and broken light bulbs. The third case study was performed using a Terrestrial Laser Scanner, Close-Range Photogrammetry and Total Station Survey to identify defects in structures. In order to test these technologies, a wing wall, located on the north-east wing of the HC3 underbridge at Ladbroke Grove Station, was chosen. This case study demonstrated that LUL can easily implement this type of technology to inspect rapidly their buildings and structures, being able to identify defects and monitor their assets for translation, rotation and changes in shape during changes in loading or the decay of the structure (insidious decline) and the construction of nearby assets. In this research, a large volume of data was captured, and further work is needed in order to manage the data using ‘big data’ concepts. Although it may not be possible to fully understand the insidious decline of an asset, the use of these techniques allows us to better understand how a civil asset behaves, potentially reducing the amount of reactive maintenance to a minimum, consequently reducing service costs and falls in revenue due to disruptions in the system. To successfully analyse the data from new technologies a combination of skills is required and different or retrained personal will be needed

Bridge Construction Monitoring using LIDAR for Quantified, Objective Quality-Control Quality-Assurance (QOQCQA)

Transportation infrastructure construction quality control and quality assurance demands construction monitoring by field inspectors. Currently, these inspectors monitor infrastructure by measuring and photographing structures. These tasks allow them to assess any correction decision during construction or to inform about the quality of the construction process for the future. In order to promote and objective decisions obtained during infrastructure construction, the proposed research project developed and implemented a methodology to measure construction progress and compared it with the designed 3D shape, quantifying the difference. This proposed project includes implementation for the development of DOT standards that could be added in near future bridge construction documents. The New Mexico Department of Transportation (NMDOT) showed a strong interest in this topic. The experience of the PIs on bridge design and construction, field inspection, and LIDAR technology was integrated in order to evaluate the results with impact both in research and in industry. Specifically, the research results outline recommendations about standards for implementation of technology in specifications for NMDOT or other DOTs

A Pipeline of 3D Scene Reconstruction from Point Clouds

3D technologies are becoming increasingly popular as their applications in industrial, consumer, entertainment, healthcare, education, and governmental increase in number. According to market predictions, the total 3D modeling and mapping market is expected to grow from $1.1 billion in 2013 to$7.7 billion by 2018. Thus, 3D modeling techniques for different data sources are urgently needed. This thesis addresses techniques for automated point cloud classification and the reconstruction of 3D scenes (including terrain models, 3D buildings and 3D road networks). First, georeferenced binary image processing techniques were developed for various point cloud classifications. Second, robust methods for the pipeline from the original point cloud to 3D model construction were proposed. Third, the reconstruction for the levels of detail (LoDs) of 1-3 (CityGML website) of 3D models was demonstrated. Fourth, different data sources for 3D model reconstruction were studied. The strengths and weaknesses of using the different data sources were addressed. Mobile laser scanning (MLS), unmanned aerial vehicle (UAV) images, airborne laser scanning (ALS), and the Finnish National Land Survey’s open geospatial data sources e.g. a topographic database, were employed as test data. Among these data sources, MLS data from three different systems were explored, and three different densities of ALS point clouds (0.8, 8 and 50 points/m2) were studied. The results were compared with reference data such as an orthophoto with a ground sample distance of 20cm or measured reference points from existing software to evaluate their quality. The results showed that 74.6% of building roofs were reconstructed with the automated process. The resulting building models provided an average height deviation of 15 cm. A total of 6% of model points had a greater than one-pixel deviation from laser points. A total of 2.5% had a deviation of greater than two pixels. The pixel size was determined by the average distance of input laser points. The 3D roads were reconstructed with an average width deviation of 22 cm and an average height deviation of 14 cm. The results demonstrated that 93.4% of building roofs were correctly classified from sparse ALS and that 93.3% of power line points are detected from the six sets of dense ALS data located in forested areas. This study demonstrates the operability of 3D model construction for LoDs of 1-3 via the proposed methodologies and datasets. The study is beneficial to future applications, such as 3D-model-based navigation applications, the updating of 2D topographic databases into 3D maps and rapid, large-area 3D scene reconstruction. 3D-teknologiat ovat tulleet yhä suositummiksi niiden sovellusalojen lisääntyessä teollisuudessa, kuluttajatuotteissa, terveydenhuollossa, koulutuksessa ja hallinnossa. Ennusteiden mukaan 3D-mallinnus- ja -kartoitusmarkkinat kasvavat vuoden 2013 1,1 miljardista dollarista 7,7 miljardiin vuoteen 2018 mennessä. Erilaisia aineistoja käyttäviä 3D-mallinnustekniikoita tarvitaankin yhä enemmän. Tässä väitöskirjatutkimuksessa kehitettiin automaattisen pistepilviaineiston luokittelutekniikoita ja rekonstruoitiin 3D-ympäristöja (maanpintamalleja, rakennuksia ja tieverkkoja). Georeferoitujen binääristen kuvien prosessointitekniikoita kehitettiin useiden pilvipisteaineistojen luokitteluun. Työssä esitetään robusteja menetelmiä alkuperäisestä pistepilvestä 3D-malliin eri CityGML-standardin tarkkuustasoilla. Myös eri aineistolähteitä 3D-mallien rekonstruointiin tutkittiin. Eri aineistolähteiden käytön heikkoudet ja vahvuudet analysoitiin. Testiaineistona käytettiin liikkuvalla keilauksella (mobile laser scanning, MLS) ja ilmakeilauksella (airborne laser scanning, ALS) saatua laserkeilausaineistoja, miehittämättömillä lennokeilla (unmanned aerial vehicle, UAV) otettuja kuvia sekä Maanmittauslaitoksen avoimia aineistoja, kuten maastotietokantaa. Liikkuvalla laserkeilauksella kerätyn aineiston osalta tutkimuksessa käytettiin kolmella eri järjestelmällä saatua dataa, ja kolmen eri tarkkuustason (0,8, 8 ja 50 pistettä/m2) ilmalaserkeilausaineistoa. Tutkimuksessa saatuja tulosten laatua arvioitiin vertaamalla niitä referenssiaineistoon, jona käytettiin ortokuvia (GSD 20cm) ja nykyisissä ohjelmistoissa olevia mitattuja referenssipisteitä. 74,6 % rakennusten katoista saatiin rekonstruoitua automaattisella prosessilla. Rakennusmallien korkeuksien keskipoikkeama oli 15 cm. 6 %:lla mallin pisteistä oli yli yhden pikselin poikkeama laseraineiston pisteisiin verrattuna. 2,5 %:lla oli yli kahden pikselin poikkeama. Pikselikoko määriteltiin kahden laserpisteen välimatkan keskiarvona. Rekonstruoitujen teiden leveyden keskipoikkeama oli 22 cm ja korkeuden keskipoikkeama oli 14 cm. Tulokset osoittavat että 93,4 % rakennuksista saatiin luokiteltua oikein harvasta ilmalaserkeilausaineistosta ja 93,3 % sähköjohdoista saatiin havaittua kuudesta tiheästä metsäalueen ilmalaserkeilausaineistosta. Tutkimus demonstroi 3D-mallin konstruktion toimivuutta tarkkuustasoilla (LoD) 1-3 esitetyillä menetelmillä ja aineistoilla. Tulokset ovat hyödyllisiä kehitettäessä tulevaisuuden sovelluksia, kuten 3D-malleihin perustuvia navigointisovelluksia, topografisten 2D-karttojen ajantasaistamista 3D-kartoiksi, ja nopeaa suurten alueiden 3D-ympäristöjen rekonstruktiota

Modeling and Simulation in Engineering

This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results

Pavement Surface Evaluation Using Mobile Terrestrial LiDAR Scanning Systems

Periodic measurement of pavement surfaces for pavement management system (PMS) data collection is vital for state transportation agencies. Vehicle-based mobile light detection and ranging (LiDAR) systems can be used as a versatile tool to collect point data throughout a roadway corridor. The overall goal of this research is to investigate if mobile terrestrial LiDAR Scanning (MTLS) systems can be used as an efficient and effective method to create accurate digital pavement surfaces for. LiDAR data were collected by five MTLS vendors. In particular, the research is interested in three things: 1) how accurate MTLS is for collecting roadway cross slopes; 2) what is the potential for using MTLS digital pavement surfaces to do materials calculations for pavement rehabilitation projects; and 3) examine the benefit of using MTLS to identify pavement rutting locations. Cross slopes were measured at 23 test stations using traditional surveying methods (conventional leveling served as ground-truth) and compared with adjusted and unadjusted MTLS extracted cross slopes. The results indicate that both adjusted and unadjusted MTLS derived cross slopes meet suggested cross slope accuracies (±0.2%). Application of unadjusted MTLS instead of post-processed MTLS point clouds may decrease/eliminate the cost of a control surveys. The study also used a novel approach to process the MTLS data in a geographic information system (GIS) environment to create a 3-dimension raster representation of a roadway surface. MTLS data from each vendor was evaluated in terms of the accuracy and precision of their raster surface. The resultant surfaces were compared between vendors and with a raster surface created from a centerline profile and 100-ft. cross-section data obtained using traditional surveying methods. When comparing LiDAR data between compliant MTLS vendors, average raster cell height differences averaged 0.21 inches, indicating LiDAR data has considerable potential for creating accurate pavement material volume estimates. The application of MTLS data was also evaluated in terms of the accuracy of collected transverse profiles. Transverse profiles captured from MTLS systems have been compared to 2-inch interval field data collection using partial curve mapping (PCM), Frechet distance, area, curve length, and Dynamic Time Warping (DTW) techniques. The results indicated that there is potential for MTLS systems for use in creating an accurate transverse profile for potential identification of pavement rut areas. This research also identified a novel approach for determining pavement rut areas based on the shape of grid cells. This rather simplistic approach is easily implementable on a network wide basis depending on MTLS point cloud availability. The method does not require the calculation/estimation of an ideal surface to determine rut depths/locations