Samoa technical report - Review of volcanic hazard maps for Savai'i and Upolu

Both main islands of Samoa, Savai'i and Upolu need to be considered as potentially volcanically active. The most recent eruptions in historic times happened on Savai'i in 1905-1911, 1902 and 1760 (estimated). Though detailed volcanic studies and dating of volcanic events are very limited there is evidence for repeated volcanic activity on both islands since the time of human occupation of the islands marked by prominent and fresh appearance of tuff cones as Tafua (= fire mountain) Savai'i, the island of Apolima, Tafua Upolu and offshore Cape Tapaga. This report examines the volcanic risks for both islands and defines for disaster management considerations potential eruption scenarios based on eyewitness accounts of previous eruptions, geological field evidence, remote sensing information and experiences from similar volcanoes. A detailed timeline of events, potential impacts and required emergency response activities are listed for the five potential eruption types (1) long-term lava field (2) short-term spatter-cone (3) explosive phreatomagmatic (4) explosive scoria-cone and (5) submarine flank collapse. Given the nature of volcanism in Samoa with hundreds of individual "one-off" volcanoes scattered along zones of structural weakness within the Savai'i - Upolu Platform - predicting the exact location of future eruption centres is impossible. At the current stage of knowledge a presentation of a volcanic hazard map is inadequate and would require additional baseline studies to statistically define recurrence intervals and areas of higher volcanic activity. Taking these limitations into account, maps showing the relative potential for new eruption vents on Upolu and Savai'i are derived from geomorphologic features. To improve our understanding and management of the volcanic risks of Samoa, suggestions for achievable future work are listed and prioritised. These recommendations include geological/volcanological baseline studies (e.g. dating/detailed analyses of past events, rock chemistry, volcano structure); installation of early warning and monitoring network (e.g. permanent GPS, seismometers); and disaster preparedness and volcanic crisis response planning

Deterministic and robust optimisation strategies for metal forming proceesses

Product improvement and cost reduction have always been important goals in the metal forming industry. The rise of\ud Finite Element simulations for metal forming processes has contributed to these goals in a major way. More recently, coupling\ud FEM simulations to mathematical optimisation techniques has shown the potential to make a further contribution to product\ud improvement and cost reduction.\ud Mathematical optimisation consists of the modelling and solving of optimisation problems. Although both the\ud modelling and the solving are essential for successfully optimising metal forming problems, much of the research published until\ud now has focussed on the solving part, i.e. the development of a specific optimisation algorithm and its application to a specific\ud optimisation problem for a specific metal forming process.\ud In this paper, we propose a generally applicable optimisation strategy which makes use of FEM simulations of metal\ud forming processes. It consists of a structured methodology for modelling optimisation problems related to metal forming.\ud Subsequently, screening is applied to reduce the size of the optimisation problem by selecting only the most important design\ud variables. Screening is also utilised to select the best level of discrete variables, which are in such a way removed from the\ud optimisation problem. Finally, the reduced optimisation problem is solved by an efficient optimisation algorithm. The strategy is\ud generally applicable in a sense that it is not constrained to a certain type of metal forming problems, products or processes. Also\ud any FEM code may be included in the strategy.\ud However, the above strategy is deterministic, which implies that the robustness of the optimum solution is not taken\ud into account. Robustness is a major item in the metal forming industry, hence we extended the deterministic optimisation\ud strategy in order to be able to include noise variables (e.g. material variation) during optimisation. This yielded a robust\ud optimisation strategy that enables to optimise to a robust solution of the problem, which contributes significantly to the industrial\ud demand to design robust metal forming processes. Just as the deterministic optimisation strategy, it consists of a modelling,\ud screening and solving stage.\ud The deterministic and robust optimisation strategies are compared to each other by application to an analytical test\ud function. This application emphasises the need to take robustness into account during optimisation, especially in case of\ud constrained optimisation. Finally, both the deterministic and the robust optimisation strategies are demonstrated by application to\ud an industrial hydroforming example

Solving optimisation problems in metal forming using Finite Element simulation and metamodelling techniques

During the last decades, Finite Element (FEM) simulations\ud of metal forming processes have become important\ud tools for designing feasible production processes. In more\ud recent years, several authors recognised the potential of\ud coupling FEM simulations to mathematical optimisation\ud algorithms to design optimal metal forming processes instead\ud of only feasible ones.\ud Within the current project, an optimisation strategy is being\ud developed, which is capable of optimising metal forming\ud processes in general using time consuming nonlinear\ud FEM simulations. The expression “optimisation strategy”\ud is used to emphasise that the focus is not solely on solving\ud optimisation problems by an optimisation algorithm, but\ud the way these optimisation problems in metal forming are\ud modelled is also investigated. This modelling comprises\ud the quantification of objective functions and constraints\ud and the selection of design variables.\ud This paper, however, is concerned with the choice for\ud and the implementation of an optimisation algorithm for\ud solving optimisation problems in metal forming. Several\ud groups of optimisation algorithms can be encountered in\ud metal forming literature: classical iterative, genetic and\ud approximate optimisation algorithms are already applied\ud in the field. We propose a metamodel based optimisation\ud algorithm belonging to the latter group, since approximate\ud algorithms are relatively efficient in case of time consuming\ud function evaluations such as the nonlinear FEM calculations\ud we are considering. Additionally, approximate optimisation\ud algorithms strive for a global optimum and do\ud not need sensitivities, which are quite difficult to obtain\ud for FEM simulations. A final advantage of approximate\ud optimisation algorithms is the process knowledge, which\ud can be gained by visualising metamodels.\ud In this paper, we propose a sequential approximate optimisation\ud algorithm, which incorporates both Response\ud Surface Methodology (RSM) and Design and Analysis\ud of Computer Experiments (DACE) metamodelling techniques.\ud RSM is based on fitting lower order polynomials\ud by least squares regression, whereas DACE uses Kriging\ud interpolation functions as metamodels. Most authors in\ud the field of metal forming use RSM, although this metamodelling\ud technique was originally developed for physical\ud experiments that are known to have a stochastic na-\ud ¤Faculty of Engineering Technology (Applied Mechanics group),\ud University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands,\ud email: [email protected]\ud ture due to measurement noise present. This measurement\ud noise is absent in case of deterministic computer experiments\ud such as FEM simulations. Hence, an interpolation\ud model fitted by DACE is thought to be more applicable in\ud combination with metal forming simulations. Nevertheless,\ud the proposed algorithm utilises both RSM and DACE\ud metamodelling techniques.\ud As a Design Of Experiments (DOE) strategy, a combination\ud of a maximin spacefilling Latin Hypercubes Design\ud and a full factorial design was implemented, which takes\ud into account explicit constraints. Additionally, the algorithm\ud incorporates cross validation as a metamodel validation\ud technique and uses a Sequential Quadratic Programming\ud algorithm for metamodel optimisation. To overcome\ud the problem of ending up in a local optimum, the\ud SQP algorithm is initialised from every DOE point, which\ud is very time efficient since evaluating the metamodels can\ud be done within a fraction of a second. The proposed algorithm\ud allows for sequential improvement of the metamodels\ud to obtain a more accurate optimum.\ud As an example case, the optimisation algorithm was applied\ud to obtain the optimised internal pressure and axial\ud feeding load paths to minimise wall thickness variations\ud in a simple hydroformed product. The results are satisfactory,\ud which shows the good applicability of metamodelling\ud techniques to optimise metal forming processes using\ud time consuming FEM simulations

A metamodel based optimisation algorithm for metal forming processes

Cost saving and product improvement have always been important goals in the metal\ud forming industry. To achieve these goals, metal forming processes need to be optimised. During\ud the last decades, simulation software based on the Finite Element Method (FEM) has significantly\ud contributed to designing feasible processes more easily. More recently, the possibility of\ud coupling FEM to mathematical optimisation algorithms is offering a very promising opportunity\ud to design optimal metal forming processes instead of only feasible ones. However, which\ud optimisation algorithm to use is still not clear.\ud In this paper, an optimisation algorithm based on metamodelling techniques is proposed\ud for optimising metal forming processes. The algorithm incorporates nonlinear FEM simulations\ud which can be very time consuming to execute. As an illustration of its capabilities, the\ud proposed algorithm is applied to optimise the internal pressure and axial feeding load paths\ud of a hydroforming process. The product formed by the optimised process outperforms products\ud produced by other, arbitrarily selected load paths. These results indicate the high potential of\ud the proposed algorithm for optimising metal forming processes using time consuming FEM\ud simulations

More rapid climate change promotes evolutionary rescue through selection for increased dispersal distance

Acknowledgements This research was funded by FWO projects G.0057.09 to DB and JB, and G.0610.11 to DB, JB and RS. JMJT, DB and RS are supported by the FWO Research Network EVENET.Peer reviewedPublisher PD

Spiders as indicators for habitat evaluation in the Flemish coastal dunes

During this lecture, we present the results of a detailed study on the occurrence and ecology of spiders in the Flemish coastal dunes, as a tool for evaluating the conservation importance of dune arthropod species in general. Spider diversity is evaluated in function of the different assemblages, which are habitat specific. Especially dune grasslands, dune slacks and Marram dunes represent the highest value for nature conservation because of the presence of dune characteristic and dune specific species. These habitats are now heavily fragmented because of grass- and scrub encroachment. This fragmentation results in decreasing habitat surfaces, which affect the diversity and assemblage stability negatively. Habitat fragmentation not only affects the species diversity, but can also influence the viability of population. Within this framework we present the results of research on the effects of grassland fragmentation on the population dynamics, genetics and viability of our model species Pardosa monticola. Our results indicate that arthropod (spider) conservation will not only depend on the conservation of suitable habitat but also on the general landscape configuration

Colour variation and crypsis in relation to habitat selection in the males of the crab spider <i>Xysticus sabulosus</i> (Hahn, 1832) (Araneae: Thomisidae)

The crab spider Xysticus sabulosus (HAHN, 1832) is a sit-and-wait predator, typical for sandy habitats in Europe and Flanders. In the Flemish coastal dunes, the species is very abundant in grey and blond dunes. lts abdominal and cephalothorical colour varies from almost completely white to dark brown. During autumn 2001, we investigated crypsis as a function ofthe occupied micro- and macrohabitat. Our results indicate that (1) Colouration differs between the populations. The species is darker in a grey dune completely covered with dried (brown) mosses and in a humid dune slack covered with algae, than in populations from a sea inlet and from a blond dune. The colouration of a population from a grey dune with mosses, lichens and bare sand is intermediate. (2) Individual cephalothoracal colouration is, in contrast to abdominal colouration, related to microhabitat selection: individuals with darker cephalothoraxes occupy hunting sites with a higher coverage of mosses, while those with a pale one are found in microhabitats with a high amount of nude sand. The observed spider colour-environment covariation between populations is probably the result of natural selection or colour alteration during the juvenile development. Further research on these possible underlying mechanisms remains, however, necessary

Life history, habitat use and dispersal of a dune wolf spider (<i>Pordosa monticola</i> (Clerck, 1757) Lycosidae, Araneae) in the Flemish coastal dunes (Belgium)

Pardosa monticola (Araneae, Lycosidae) is a rare spider in Flanders. It is restricted to thermophilic mesotrophic (dune and heath) grasslands. Its life cycle and its habitat preference in the coastal dunes were analysed by interpreting data of more than 200 year-round pitfall-samplings. Viable populations are found in short dune grasslands (grazed by rabbits) and in mown young dune slacks. The life cycle is mixed annual-biannual and hibernation takes place in the juvenile or sub-adult instars. In short grasslands, the species overwinters in the rough neighbouring vegetation, in dune slacks, in litter accumulations. In the latter, the species survives submerging during winter inundation. Dispersal between suitable habitats can occur by male terrestrial movements via xerophylic habitats and dense grassland vegetation. Aeronautic dispersal is a rare phenomenon in the first instars that takes place only in periods of food shortage. Although a low proportion of the population exhibits this behaviour, this kind of dispersal can be of great importance for gene exchange between distant or strongly isolated populations. The implications and the importance of these data are discussed in relation to contemporary nature management