Ana Ivanovic

Using a Lumped Parameter Dynamic Model of a Rock Bolt to Produce Training Data for a Neural Network for Diagnosis of Real Data

Ground anchorage systems are used extensively throughout the world as supporting devices for civil engineering structures such as bridges and tunnels. The condition monitoring of ground anchorages is a new area of research, with the long term objective being a wholly automated or semi-automated condition monitoring system capable of repeatable and accurate diagnosis of faults and anchorage post-tension levels. The ground anchorage integrity testing (GRANIT) system operates by applying an impulse of known force by means of an impact device that is attached to the tendon of the anchorage. The vibration signals that arise from this impulse are complex in nature and require analysis to be undertaken in order to extract information from the vibrational response signatures that is relevant to the condition of the anchorage. Novel artificial intelligence techniques are used in order to learn the complicated relationship that exists between an anchorage and its response to an impulse. The system has a worldwide patent and is currently licensed commercially.A lumped parameter dynamic model has been developed which is capable of describing the general frequency relationship with increasing post-tension level as exhibited by the signals captured from real anchorages. The normal procedure with the system is to train a neural network on data that has been taken from an anchorage over a range of post-tension levels. Further data is needed in order to test the neural network. This process can be time consuming, and the lumped parameter dynamic model has the potential of producing data that could be used for training purposes, thereby reducing the amount of time needed on site, and reducing the overall cost of the systems operation.This paper presents data that has been produced by the lumped parameter dynamic model and compares it with data from a real anchorage. Noise is added to the results produced by the lumped parameter dynamic model in order to match more closely the experimental data. A neural network is trained on the data produced by the model, and the results of diagnosis of real data are presented. Problems are encountered with the diagnosis of the neural network with experimental data, and a new method for the training of the neural network is explored. The improved results of the neural network trained on data produced by the lumped parameter dynamic model to experimental data are shown. It is shown how the results from the lumped parameter dynamic model correspond well to the experimental results.

Use of neural networks in the condition monitoring of ground anchorages

The GRANIT system is a non-destructive integrity testing method for ground anchorages. It has won two major UK Awards--the Design Council Millennium Product Status in 1999 and the John Logie Baird Award in 1997. It makes use of novel artificial intelligence techniques in order to learn the complicated relationship that exists between an anchorage and its frequency response to an impulse. The GRANIT system has a worldwide patent and is currently licensed to AMEC plc.It is widely recognised that non-destructive testing methods for ground anchorages need to be developed as a high priority [A National Agenda for Long-term and Fundamental Research for Civil Engineering in the United Kingdom (1992)], with only between 1 and 5% of anchorages currently being monitored in service [British Standard Code of Practice for Ground Anchorages (8081) (1989)] using currently available techniques. The GRANIT system is a solution for this requirement, and this paper describes how the use of artificial intelligence techniques enabled, for the first time, the cross-anchorage diagnosis of ground anchorages, where data taken from one anchorage was used to train a neural network, which was then used to diagnose the condition of an adjacent anchorage.The results presented in this paper describe the training of a neural network on data taken from a bolt anchorage, and the diagnosis, using this neural network, of further test data taken from the same anchorage. Data taken from an adjacent anchorage of similar construction is also presented to the neural network, and the cross-anchorage diagnosis of the load level of the second anchorage is achieved.

Friction Forces Between Seabed and Fishing Gear Components

Bottom trawls are still the most common, and most energy consuming type of fishing gear. For this type of fishing gear, as well as other types with bottom contact, the contact forces between gear elements and seabed have a significant influence on both resistance and shape.This paper describes the work that has been done in research programs at SINTEF in Norway and Marine Scotland Science in Scotland. In both studies sections of rock hoppers were examined, full scale sections and 1:5 scaled model sections were tested at sea and in laboratory, respectively. Scaled models at SINTEF were tested with the submerged models in water along with the additional tests in order to establish associated hydrodynamic forces. The tests were undertaken at angle of attack 0–90 degrees. Similar procedure was followed for full scale models giving a scope for potential comparison. The coefficients of friction for each model are presented as a function of penetration depth, towing speed and angle of attack, and the relevance as friction load models for fishing and off-shore gear are discussed.© 2012 ASME

Condition Monitoring of Ground Anchorages by Dynamic Impulses: GRANIT system

The GRANIT system operates by applying an impulse of known force by means of an impact device that is attached to the tendon of the anchorage. The vibration response signals resulting from this impulse are complex in nature and require analysis to be undertaken in order to extract information from the vibrational response signatures that is relevant to the condition of the anchorage. In the system, the complicated relationship that exists between characteristics of an anchorage and its response to an impulse is identified and learned by a novel artificial intelligence network based on artificial intelligence techniques.The results presented in this paper demonstrate the potential of the GRANIT system to diagnose the integrity of ground anchorages at a site near Stone, England, by using a trained neural network capable of diagnosing the post-tension level of the anchorage. This neural network was used for the diagnosis of load in a second ground anchorage adjacent to the original anchorage used for the training of the neural network. Further tests were taken with a different anchor head configuration of the anchorage and a different relationship between the signature response of the anchorage to an applied impulse and its post-tension level was found.Problems encountered during the diagnosis of this second set of test signatures by the trained neural network are investigated with the use of a lumped parameter dynamic model. This model is able to identify the parameters in the anchorage system that affect this change in response signature. The results from the investigation lead to a new form of classification for the installed anchorages, based on their anchor head configuration.Laboratory strand anchorage tests were undertaken in order to compare with and validate the results obtained from the field tests and the lumped parameter dynamic model.

Influence of a Roller Clump on the Seabed

The effect of the impact of trawl gears on benthic communities has been of concern during the last couple of decades. Knowledge of the response of benthic habitats to impacts from fishing gear is of great importance to the ecosystem and the management of sustainable fisheries. A European project, DEGREE (DEvelopment of Fishing Gears with Reduced Effects on the Environment), addresses this concern by focusing on quantifying the environmental and ecological impacts of fishing, developing fishing gears with reduced environmental impact, and assessing the socio-economic consequences of these changes. This paper is a preliminary study focusing primarily on the comparison between laboratory and finite element (FE) modelling of the interaction between a gear component, the roller clump of a twin trawl, and the seabed in terms of penetration and disturbance of the sediment. The FE model and experimental rig are described. Initial outputs of penetration depth from the FE calculations show that the model is highly sensitive to the yield stress and that further investigation is required to achieve full parity with laboratory observations on dry sand.Copyright

Comparison of mechanical disturbance in soft sediments due to tickler-chain SumWing trawl vs. electro-fitted PulseWing trawl

&NA; Tickler‐chain SumWing and electrode‐fitted PulseWing trawls were compared to assess seabed impacts. Multi‐beam echo sounder (MBES) bathymetry confirmed that the SumWing trawl tracks were consistently and uniformly deepened to 1.5 cm depth in contrast to 0.7 cm following PulseWing trawling. MBES backscatter strength analysis showed that SumWing trawls (3.11 dB) flattened seabed roughness significantly more than PulseWing trawls (2.37 dB). Sediment Profile Imagery (SPI) showed that SumWing trawls (mean, SD) homogenised the sediment deeper (3.4 cm, 0.9 cm) and removed more of the oxidised layer than PulseWing trawls (1 cm, 0.8 cm). The reduced PulseWing trawling impacts allowed a faster re‐establishment of the oxidised layer and micro‐topography. Particle size analysis suggested that SumWing trawls injected finer particles into the deeper sediment layers (˜4 cm depth), while PulseWing trawling only caused coarsening of the top layers (winnowing effect). Total penetration depth (mean, SD) of the SumWing trawls (4.1 cm, 0.9 cm) and PulseWing trawls (1.8 cm, 0.8 cm) was estimated by the depth of the disturbance layer and the layer of mobilized sediment (SumWing = 0.7 cm; PulseWing trawl = 0.8 cm). PulseWing trawls reduced most of the mechanical seabed impacts compared to SumWing trawls for this substrate and area characteristics.

Contribution of Axial Soil Resistance in Buckle Initiation of the HPHT Pipelines on Sleepers

The objective of this paper is to assess the impact of soil axial resistance on initiation of the buckles on sleepers. It also covers the effects of history of pressure and temperature increase on effective axial force as well as the incorporation of external pressure in the Finite Element (FE) models. This is carried out for 6″, 8″, 10″ and 12″ pipelines laying on sleepers with different heights for a range of axial soil frictions and mobilisations. Knowing the sensitivity of buckle initiation to soil parameters can help in simplifying engineering analysis by avoiding repetitive simulations for parameters with less importance.To carry out the above, a series of FE models including normal and bi-linear axial contacts between pipeline and sleeper / seabed were built in Abaqus FE package and at the point of initiation of the buckles, the effective axial force was extracted by a Python script. FE models were validated by comparison of the simulation results with analytical solutions and experimental results from published literature.Copyright

Influence of Iceberg Geometry and Scour Depth on Drag Force in Sand

The seabed disturbance in Arctic regions comes predominently through horizontal cutting mechanisms induced by natural processes such as iceberg scour. The zone of soil being disturbed by the iceberg and the soil resistance to the object movement is of interest to the geotechnical engineer. The influence of the iceberg on potential movement of the pipeline buried in the seabed has been of concern recently with recovery of the oil and gas assets situated in Arctic region.Despite the significant developments in recent years in numerical modelling the ice gouging process still remains a challenge and further work is required to obtain a fully calibrated and validated numerical model. This paper therefore aims at developing a validated numerical model of the interaction between the iceberg and seabed through a series of laboratory tests undertaken at the University of Aberdeen.This paper reports on a preliminary study focusing primarily on the comparison between laboratory and finite element (FE) modelling of the interaction between an iceberg and the seabed in terms of drag force and disturbance of the sediment. The FE model and experimental rig are described. The effect of the shape of the iceberg and the depth at which it penetrates has been investigated. Outputs of drag force from FE calculations showed a good agreement with the results obtained from the laboratory model giving the confidence to move to the next stage where both the inclusion of a pipeline segment and sand with different densities will be considered.Copyright

An Investigation of the Drag Induced on a Tool in a Granular Medium

An investigation of the drag induced by pulling a tool through a granular medium is reported. The work is aimed at understanding the drag on an offshore cable-laying tool with the objective of producing a model capable of predicting the force required to pull the tool through a granular medium. Experiments were run at 1g in a laboratory rig comprising a channel, containing the granular medium and a frame, in which the tool was inserted into the sand to a fixed depth and pulled through it at a constant velocity. The width, length and depth of insertion of the tool, the shape of the tool face and velocity of towing were investigated in dry sand only. The results show little change in drag force with velocity, over the range investigated, but indicate a power law relation to the depth of insertion. Increase in face width produces a near proportional increase in drag while increases in length produce smaller increases in drag force. The use of a rounded nose on the tool reduces the drag by a factor of up to 30%. A numerical model is proposed which is matched to the data and used to predict the loads on a full-scale device.Copyright

Physical Impact of a Roller Clump on the Seabed

The envionmental impact of towed demersal gears on benthic communities has been of concern for the last couple of decades. Knowledge of the response of benthic habitats to impacts from fishing gears is of great importance to the ecosystem and the long-term management of sustainable fisheries. An on-going EU project, DEGREE (DE velopment of F ishing G ears with R educed E ffects on the Environment), addresses this concern by focusing on quantifying the environmental and ecological impacts of fishing, developing fishing gears with reduced environmental impact, and assessing the socio-economic consequences of these changes. This paper focuses primarily on the modelling of the interaction between a gear component, the roller clump of a twin trawl, and the seabed in terms of penetration and disturbance of the seabed. A finite element model of this interface has been developed and is able to predict the penetration depth, sediment displacement and the pressure field associated with each gear component. In order to verify these predictions, sea trials have taken place over a range of sediment types at depths accessible to scientific divers using SCUBA diving techniques. This has allowed sampling of the seabed and profiling of the disturbed region for comparison with the model results. Good agreement is found.Copyright