94 research outputs found
Effects of varied lithology on soft-cliff recession rates
No full textGeomorphic modelling is a key method to understand the soft cliff recession process to predict future rates of retreat and responses to climate change. A range of process-based models have been used; however the influence of varied vertical lithology has yet to be quantified. This paper describes modifications to the 2D SCAPE (Soft Cliff and Platform Erosion) model, carried out to explore such interactions between vertical changes in cliff resistive strength and prevailing coastal conditions. As expected, weaker (/more resistant) layers lead to more (/less) rapid retreat. However, this effect is strongly influenced by the position of such layers relative to mean sea level, where the erosive potential is greatest. Moreover, model simulations reveal that layers of variable resistance give an asymmetric response in terms of both rates of retreat and the timeframe for the effect to be realised. For example, a reduction of material strength of 1/5 (in comparison to the remainder of the cliff) about mean sea level results in a rapid 130% increase in the rate of retreat in comparison to the introduction of a five times more resistant layer of the same characteristics. This variation in response can be attributed to the different magnitudes of feedback governing profile reshaping associated with the change in lithology. For example, the introduction of a weaker layer amplifies erosion through its greater erosive potential combined with steepening of the overlying section. The results have important implications for the management of coastal cliffs exhibiting variable stratigraphy, combined with the potential for future interactions with sea-level rise
Model wave impulse loads on caisson breakwater aeration, scale and structural response
No full textSIGLEAvailable from British Library Document Supply Centre-DSC:DXN026768 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Coupled long-term probabilistic erosion and flood risk assessment under accelerated sea-level rise
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Cliff retreat and sea bed morphology under monochromatic wave forcing: Experimental study
No full textWave flume experiments have been performed to investigate a sandy cliff recession under monochromatic wave forcing. We varied the wave climate through the wave energy flux F and the surf similarity parameter j. The various processes of the cliff erosion cycle are depicted. The sea bed evolution mostly depends on the surf similarity parameter j. Steep planar (j > 0.7), gentle planar (0.5 < j < 0.7) and bared (j < 0.5) profiles are observed. We observed different bar dynamics, including steady and unsteady self-sustained oscillating states. Then we analyze the role of the eroded material on the cliff recession rate. We show that the cliff recession rate increases with the wave energy flux. Moreover, for a given wave energy flux, it is larger for a gentle planar profile than for a bared profile. However it is similar for both a bared profile and a steep planar profile. The cliff recession rate is not a monotonic function of the cliff height as the type of bottom profile influences the wave energy at the cliff
Integrated analysis of risks of coastal flooding and cliff erosion under scenarios of long term change
No full textThe risks to human populations in coastal areas are changing due to climate and socio-economic changes, and these trends are predicted to accelerate during the twenty-first century. To understand these changing risks, and the resulting choices and pathways to successful management and adaptation, broad-scale integrated assessment is essential. Due to their complexity the two risks of flooding and erosion are usually managed independently, yet frequently they are interconnected by longshore exchange of sediments and the resulting broad scale morphological system behaviour. In order to generate new insights into the effects of climate change and coastal management practises on coastal erosion and flood risk, we present an integrated assessment of 72 km of shoreline over the twenty-first century on the East Anglian coast of England which is a site of significant controversy about how to manage coastal flood and erosion risks over the twenty-first century. A coupled system of hydrodynamic, morphological, reliability and socio-economic models has been developed for the analysis, implemented under scenarios of coastal management, climate and socio-economic change. The study is unique in coastal management terms because of the large spatial scale and extended temporal scale over which the analysis is quantified. This study for the first time quantifies what has for some years been argued qualitatively: the role of sediments released from cliff erosion in protecting neighbouring low-lying land from flooding. The losses and benefits are expressed using the common currency of economic risk. The analysis demonstrates that over the twenty-first century, flood risk in the study area is expected to be an order of magnitude greater than erosion risk. Climate and socio-economic change and coastal management policy have a significant influence on flood risk. This study demonstrates that the choices concerning coastal management are profound, and there are clear tradeoffs between erosion and flood impacts
Robot-learning using a Tree-based Policy Representation
No full textLearning is an important aspect in creating versatile robots. Pre-programming a robot to acquire a wide variety of skills in an ever changing environment is unfeasible. Robot learning provides a promising alternative. Two well-established learning techniques are Programming by Demonstration (PbD) and Learning from Exploration (LfE). PbD and LfE are often combined to strengthen each other. PbD is used because it allows fast learning: with only a few demonstrations, robots are able to reproduce tasks with reasonable performance. After these demonstrations, LfE is used to improve the robot's task performance or to adjust this skills to changing environments. Robots often use continuous mappings between states and actions to represent a skill. Such mappings are called policies and are represented by function approximators. The shape of the policy is determined by the parameters. During learning the robot tries to find optimal parameters for the policy. As the complexity of the skill increases, the number of parameters required to accurately describe the policy for this skill also increases. As the number of parameters increases, the complexity of the solution space increases as well. It is most likely that the LfE algorithm requires more trials to converge for these complex search spaces than simpler search spaces, thus the LfE performance decreases as the complexity of the search space increases. In this thesis a novel multi-resolution policy representation is investigated. The method, called Tree-based policy representation, creates a multi-resolution model based on demonstration data. After this initialization, LfE can use the structure of the Multi-resolution policy to increase learning performance. The method is tested in multiple experimental scenarios. The Tree-based policy representation achieves better learning performance compared to conventional `flat' policy representations, when learning motions that clearly have a multi-resolution aspect. In other cases, the Tree-based movement representation performs equally well or worse compared to standard `flat' policy representations.BMDBioMechanical EngineeringMechanical, Maritime and Materials Engineerin
CO2 reduction as a market opportunity. A product design for Nuon, in order to anticipate the need for CO2 reduction in the business market.
No full textTechnology, Policy and Managemen
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