Model Updating Strategy of the DLR-AIRMOD Test Structure

Considerable progresses have been made in computer-aided engineering for the high fidelity analysis of structures and systems. Traditionally, computer models are calibrated using deterministic procedures. However, different analysts produce different models based on different modelling approximations and assumptions. In addition, identically constructed structures and systems show different characteristic between each other. Hence, model updating needs to take account modelling and test-data variability. Stochastic model updating techniques such as sensitivity approach and Bayesian updating are now recognised as powerful approaches able to deal with unavoidable uncertainty and variability. This paper presents a high fidelity surrogate model that allows to significantly reduce the computational costs associated with the Bayesian model updating technique. A set of Artificial Neural Networks are proposed to replace multi non-linear input-output relationships of finite element (FE) models. An application for updating the model parameters of the FE model of the DRL-AIRMOD structure is presented. © 2017 The Authors. Published by Elsevier Ltd

Anthropogenic impact on amorphous silica pools in temperate soils

Human land use changes perturb biogeochemical silica (Si) cycling in terrestrial ecosystems. This directly affects Si mobilisation and Si storage and influences Si export from the continents, although the magnitude of the impact is unknown. A major reason for our lack of understanding is that very little information exists on how land use affects amorphous silica (ASi) storage in soils. We have quantified and compared total alkali-extracted (PSi<sub>a</sub>) and easily soluble (PSi<sub>e</sub>) Si pools at four sites along a gradient of anthropogenic disturbance in southern Sweden. Land use clearly affects ASi pools and their distribution. Total PSi</sub>a</sub> and PSi<sub>e</sub> for a continuous forested site at Siggaboda Nature Reserve (66 900 ± 22 800 kg SiO<sub>2</sub> ha<sup>−1</sup> and 952 ± 16 kg SiO<sub>2</sub> ha<sup>−1</sup>) are significantly higher than disturbed land use types from the Råshult Culture Reserve including arable land (28 800 ± 7200 kg SiO<sub>2</sub> ha<sup>−1</sup> and 239 ± 91 kg SiO<sub>2</sub> ha<sup>−1</sup>), pasture sites (27 300 ± 5980 kg SiO<sub>2</sub> ha<sup>−1</sup> and 370 ± 129 kg SiO<sub>2</sub> ha<sup>−1</sup>) and grazed forest (23 600 ± 6370 kg SiO<sub>2</sub> ha<sup>−1</sup> and 346 ± 123 kg SiO<sub>2</sub> ha<sup>−1</sup>). Vertical PSi<sub>a</sub> and PSi<sub>e</sub> profiles show significant (<i>p</i> < 0.05) variation among the sites. These differences in size and distribution are interpreted as the long-term effect of reduced ASi replenishment, as well as changes in ecosystem specific pedogenic processes and increased mobilisation of the PSi<sub>a</sub> in disturbed soils. We have also made a first, though rough, estimate of the magnitude of change in temperate continental ASi pools due to human disturbance. Assuming that our data are representative, we estimate that total ASi storage in soils has declined by ca. 10 % since the onset of agricultural development (3000 BCE). Recent agricultural expansion (after 1700 CE) may have resulted in an average additional export of 1.1 ± 0.8 Tmol Si yr<sup>−1</sup> from the soil reservoir to aquatic ecosystems. This is ca. 20 % to the global land-ocean Si flux carried by rivers. It is necessary to update this estimate in future studies, incorporating differences in pedology, geology and climatology over temperate regions, but data are currently not sufficient. Yet, our results emphasize the importance of human activities for Si cycling in soils and for the land-ocean Si flux

Sensitivity or Bayesian model updating: a comparison of techniques using the DLR AIRMOD test data

Deterministic model updating is now a mature technology widely applied to large-scale industrial structures. It is concerned with the calibration of the parameters of a single model based on one set of test data. It is, of course, well known that different analysts produce different finite element models, make different physics-based assumptions, and parameterize their models differently. Also, tests carried out on the same structure, by different operatives, at different times, under different ambient conditions produce different results. There is no unique model and no unique data. Therefore, model updating needs to take account of modeling and test-data variability. Much emphasis is now placed on what has become known as stochastic model updating where data are available from multiple nominally identical test structures. In this paper two currently prominent stochastic model updating techniques (sensitivity-based updating and Bayesian model updating) are described and applied to the DLR AIRMOD structure

Adaptive intertidal seed-based seagrass restoration in the Dutch Wadden Sea

Seagrasses form the foundation of many coastal ecosystems but are rapidly declining on a global scale. The Dutch Wadden Sea once supported extensive subtidal seagrass meadows that have all disappeared. Here, we report on the setbacks and successes of intertidal seed-based restoration experiments in the Dutch Wadden Sea between 2014-2017. Our main goals were to 1) optimize plant densities, and 2) reduce seed losses. To achieve our goals, we conducted research-based, adaptive seagrass (Zostera marina) restoration, adjusting methods yearly based on previous results. We applied various seeding methods in three subsequent years-from Buoy Deployed Seeding (BuDS), and 'BuDS-in-frame' in fall, to a newly developed 'Dispenser Injection Seeding' (DIS) method. Our adaptive experimental approach revealed high seed losses between seeding and seedling establishment of the BuDS methods (&gt;99.9%), which we mitigated by controlled harvest and storage of seeds throughout fall and winter, followed by DIS-seeding in spring. These iterative innovations resulted in 83 times higher plant densities in the field (0.012 to 1.00 plants m-2) and a small reduction in seed loss (99.94 to 99.75%) between 2015-2017. Although these developments have not yet resulted in self-sustaining seagrass populations, we are one step closer towards upscaling seagrass restoration in the Dutch Wadden Sea. Our outcomes suggest that an iterative, research-based restoration approach that focuses on technological advancement of precision-seeding may result in advancing knowledge and improved seed-based seagrass restoration successes.</p