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Major accidents in the process industry often lead to the release of light or dense gases, which can mean a thread to employees, local residents or to the environment. Possible scenarios are therefore analyzed and evaluated in advance for approval issues. There is a trend, where simple empirical models are being replaced with more complex numerical models. Gaussian dispersion models or models based on dimensional analysis approaches are for example, increasingly replaced by CFD simulations. The main reason for this is the potentially higher accuracy. However, usually scenarios using sharp parameter values are calculated, since comprehensive consideration of parameter distributions via Monte Carlo or Latin Hypercube Sampling fails due to the numerical effort. This includes the risk that the influence of uncertainties on the simulation results is not taken into account. Response surface methods offer an alternative, with which the CFD problem can be mapped onto an algebraic surrogate model. If this is sufficiently precise, parameter sampling can also be carried out with the surrogate as well, as shown in some publications. Previous investigations only demonstrated the basic principle using trivial dispersion models. In this paper two realistic CFD simulations from the plant safety area are considered: VOC emissions from a storage tank and near-ground dense gas emissions. The entire procedure of response surface determination and parameter studies was automated and parallelized for high-performance-computing, and is carried out on the underlying CFD grids. For the CFD simulations as well as for all visualizations, the commercial software ANSYS CFX and the open source software OpenFOAM were used. The aim of this paper is to demonstrate the method using industry-relevant applications as well as to show how this can be used in practical engineering applications. The quality of surrogate modeling, the numerical effort and advantages that can result from the procedure are discussed as well as advantages which may result from taking parameter uncertainties into account in safety studies.
To prevent future alkali-aggregate reaction (AAR) damage, which has occurred frequently in the German highway network in recent years, a new regulation has been drafted. This regulation severely limits the use of alkali-sensitive aggregates by requiring that their suitability be verified by certified inspectors using newly developed AAR concrete tests that involve the external supply of alkali. This has led to a significant limitation in the number of aggregates usable for concrete pavements. A novel AAR avoidance strategy is now being pursued, which aims to enable the use of borderline alkali-sensitive aggregates through the application of an internal water-repellent treatment. The addition of water repellents during concrete production should significantly reduce the ingress of water and external de-icing salts into the concrete pavement, thus reducing the potential for AAR damage.
This paper presents the results of laboratory tests to assess the suitability of this new AAR prevention strategy. Representative, highly AAR-susceptible road paving concrete made with an alkali-sensitive greywacke and various water repellents were used as the basis for these experiments. The tests for concrete suitability included determining the conventional fresh and hardened concrete properties as well as concrete prism tests with external alkaline supply. Building on these results, laser-induced breakdown spectroscopy (LIBS) analyses of de-icing-salt intrusion as well as microscopic examinations for verification of the AAR characteristics were carried out.
The results of the AAR concrete tests with external alkaline supply support the conclusion that, when hydrophobic agents containing a suitable active ingredient are used, the AAR damage process in road paving concrete can be sufficiently prevented.
In Germany, BAM is the competent authority in the field of dangerous goods transport. The international dangerous goods transportation rules are presented and their adaptation into German law is described. BAM is responsible for dangerous goods packaging testing, manufacturer surveillance, packaging approvals and inspection of IBC and provides “Gefahrgutregeln” (GGR) to define the processes, e.g. of dangerous goods packagings approvals and surveillance.”
A prediction software has been developed by BAM. The following topics have still be solved. A realistic irregularity spectrum can be derived from axle-box measurements. It agrees wel with the spectrum used for the high-speed 2 project in the United Kingdom. In addition, the scattering of axle pulses should be included. This mid-frequency component can also be found in the HS2 procedure. Finally, the reduction in case of a tunnel line compared to a surface line should be included. Some measurement results of BAM, HS2 and other institutes show a certain mid-frequency reduction. This is due to the load distribution of the tunnel which yields softer axle pulses and the scattered axle impulses are reduced.
Es wird ein faseroptisches Messsystem vorgestellt, welches auf Basis der Rayleigh-Rückstreumessung eine ortsauflösende Detektion von signifikant großen Dehnungen bei Bauvorhaben im von Anwendern geforderten Größenordnungsbereich von 3 % bis 10 % ermöglicht. Mit dem Verfahren der digitalen inkohärenten optischen Frequenzbereichsreflek-tometrie (I-OFDR) werden materialspezifische Vorteile robuster perfluorierter polymeroptischer Fasern (PF-POF) erschlossen. Für den angestrebten industriellen Einsatz für die Zustandsüberwachung im Bereich des Tunnel- und Spezialtiefbaus soll die spezifische Rückstreuzunahme in der PF-POF hochauflösend gemessen werden. In diesem
Vortrag wird gezeigt, dass sich in ersten Projektergebnissen das digitale I-OFDR für eine Dehnungsdetektion von bis zu 10% eignet.
In this presentation, a cost-efficient distributed fiber optic measurement system based on Rayleigh scattering is shown. The distributed digital incoherent optical frequency domain reflectometry (I-OFDR) method is devel-oped for detection of significantly large strain in the range from 3 % up to 10 % as required by end users. For this purpose, a vector network analyzer used in the I-OFDR is replaced by a compact and costeffective digital data acquisition system. This digital emitting/receiving unit enables the recording of the complex transfer function carrying information about the local deformations along the entire sensing fiber.
Am Fallturm auf dem Testgelände Technische Sicherheit (TTS) der BAM wurden bei Inspektionen Vorspannungsverluste in den Bolzen der Stahlverbindungen festgestellt. Um ein Verständnis für die zugrundeliegenden Trag- und Schädigungsmechanismen zu erlangen und um den Zustand der vorgespannten Schraubverbindungen langzeitlich zu überwachen, wurde am Fallturm ein Structural Health Monitoring (SHM) System installiert. Für die Auslegung des Monitoringsystems sowie zur Unterstützung der Untersuchung des Schädigungsprozesses wurde ein numerisches Modell erstellt und in Bezug auf die gemessenen Antworten des Tragwerks kalibriert.
Im Vortrag werden die experimentellen und numerischen Untersuchungen zur Systemidentifikation des Stahlrohrgitterturms als auch die Überwachungskampagne mit dem eingesetzten Monitoringsystem sowie die Messergebnisse und deren Bewertung vorgestellt.
Structural health monitoring is a promising technology to automatically detect structural changes based on permanently installed sensors. Vibration-based methods that evaluate the global system response to ambient excitation are suited to diagnose changes in boundary conditions, i.e., changes in member prestress or imposed displacements. In this paper, these changes are evaluated based on sensitivity-based statistical tests, which are capable of detecting and localizing parametric structural changes. The main contribution is the analytical calculation of sensitivity vectors for changes in boundary conditions (i.e., changes in prestress or support conditions) based on stress stiffening, and the combination with a numerically efficient algorithm, i.e., Nelson’s method. One of the main advantages of the employed damage diagnosis algorithm is that, although it uses physical models for damage detection, it considers the uncertainty in the data-driven features, which enables a reliabilitybased approach to determine the probability of detection. Moreover, the algorithm can be trained and the probability of detecting future damages can be predicted based on data and a model from the undamaged structure,
in an unsupervised learning mode, making it particularly relevant for unique structures, where no data from the damaged state is available. For proof of concept, a numerical case study is presented. The study assesses the loss of prestress in a two-span reinforced concrete beam and showcases suitable validation approaches for the sensitivity calculation.
Usually, geometric irregularities are considered as the main cause of ground vibrations from trains. A varying stiffness of the track, the track support and the soil can also generate ground vibrations. The regular stiffness variation of the track on and between the sleepers results in a deterministic dynamic axle load. The random stiffness variation of the track support yields also dynamic axle loads which are generated by the acceleration of the unsprung mass (from the varying wheel displacements under the static axle load). The random stiffness variation has a second effect. The pulses from the passage of the static axle loads are superposed regularly to the quasi-static response, but also irregularly to yield a “scattered” part of the axle pulses. The same holds for a random variation of the soil stiffness. All these effects of stiffness variations have been calculated by wavenumber-domain multi-beam track models, a random finite-element soil model and the superposition of axle impulses in a stochastic simulation. The results are confronted with many measurements at different sites. It is concluded that the stiffness variation of the track and the soil generate an important ground vibration component near railway lines.
A simple and fast prediction scheme is presented for train-induced ground and building vibrations. For the emission, finite-element boundary-element or multiple-beam-on-continuous-soil models of the track have been analysed and approximated by faster track-on-Winkler-soil models. The vehicle-track interaction due to irregularities yields the excitation forces. For the transmission of waves in the soil, the wavenumber integral of the compliance of layered soils has been evaluated. The calculation time is reduced for the prediction by using the solution of a homogeneous half-space with a frequency-dependent wave velocity (the dispersion) of the soil. For the immision, many 2 and 3-dimenisonal finite-element building models have been investigated, and a good approximation has been established by a 1-dimensional soil-wall-floor model. In addition, the axle sequence of the train, the quasi-static and the “scattered” response of the soil, and the wave propagation from a tunnel to a pile foundation of a building have been included.