| 1. |
- Ericsson, Niklas, 1968
(författare)
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A Framework for Approximation of the Stokes Equations in an Axisymmetric Domain
- 2021
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Ingår i: Computational Methods in Applied Mathematics. - : Walter de Gruyter GmbH. - 1609-4840 .- 1609-9389. ; 21:4
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Tidskriftsartikel (refereegranskat)abstract
- We develop a framework for solving the stationary, incompressible Stokes equations in an axisymmetric domain. By means of Fourier expansion with respect to the angular variable, the three-dimensional Stokes problem is reduced to an equivalent, countable family of decoupled two-dimensional problems. By using decomposition of three-dimensional Sobolev norms, we derive natural variational spaces for the two-dimensional problems, and show that the variational formulations are well-posed. We analyze the error due to Fourier truncation and conclude that, for data that are sufficiently regular, it suffices to solve a small number of two-dimensional problems. © 2021 Ericsson, published by De Gruyter 2021.
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| 2. |
- Jenkins, Samantha, 1967-, et al.
(författare)
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The role of hydrogen bonding in nanocolloidal amorphous silica particles in electrolyte solutions
- 2009
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Ingår i: Journal of colloid and interface science. - : Elsevier BV. - 1095-7103 .- 0021-9797.
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Tidskriftsartikel (refereegranskat)abstract
- Explicit solvent (water) molecular dynamics simulations were undertaken containing three pairs of amorphous silica nanoparticles, having diameters of 2.0nm, 2.4nm and 2.8nm, respectively. Mean forces acting between the silica nanoparticles were calculated in a background electrolyte, i.e., NaCl at four different concentrations. Dependence of the inter-particle potential of mean force on the center of mass separation, silicon to sodium ratio (Si:Na(+)), background electrolyte concentration, number of hydrogen bonds directly linking pairs of silica nanoparticles and the density of charged surface sites, are calculated. The pH was indirectly accounted for via the ratio of silicon to sodium used in the simulations. The close relationship between the variation of the number of hydrogen bonds between the pairs of silica nanoparticles and the inter-particle potential of mean force indicates that the degree of inter-particle hydrogen bonding quantifies, for a given size of nanoparticle, the degree of nanoparticle 'stickiness'. Simulations also show that the number of hydrogen bonds between the charged surface (O(-)) sites and the surrounding water molecules increases with increase in charged sites, in agreement with the interaction behavior of silica nanoparticles usually seen in experiments.
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| 3. |
- Bagherbandi, Mohammad, et al.
(författare)
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Recovery of Moho's undulations based on the Vening Meinesz-Moritz theory from satellite gravity gradiometry data : A simulation study
- 2012
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Ingår i: Advances in Space Research. - : Elsevier BV. - 0273-1177 .- 1879-1948. ; 49:6, s. 1097-1111
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Tidskriftsartikel (refereegranskat)abstract
- In the gravimetric approach to determine the Moho depth an isostatic hypothesis can be used. The Vening Meinesz-Moritz isostatic hypothesis is the recent theory for such a purpose. Here, this theory is further developed so that the satellite gravity gradiometry (SGG) data are used for recovering the Moho depth through a nonlinear integral inversion procedure. The kernels of its forward and inverse problems show that the inversion should be done in a larger area by 5 than the desired one to reduce the effect of the spatial truncation error of the integral formula. Our numerical study shows that the effect of this error on the recovered Moho depths can reach 6 km in Persia and it is very significant. The iterative Tikhonov regularization in a combination with either generalized cross validation or quasi-optimal criterion of estimating the regularization parameter seems to be suitable and the solution is semi-convergent up to the third iteration. Also the Moho depth recovered from the simulated SGG data will be more or less the same as that obtained from the terrestrial gravimetric data with a root mean square error of 2 km and they are statistically consistent.
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| 4. |
- Eshagh, Mehdi, 1977-, et al.
(författare)
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Quality description for gravimetric and seismic Moho models of Fennoscandia through a combined adjustment
- 2012
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Ingår i: Acta Geodaetica et Geophysica Hungarica. - : Akademiai Kiado. - 1217-8977 .- 1587-1037. ; 47:4, s. 388-401
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Tidskriftsartikel (refereegranskat)abstract
- The gravimetric model of the Moho discontinuity is usually derived based on isostatic adjustment theories considering floating crust on the viscous mantle. In computation of such a model some a priori information about the density contrast between the crust and mantle and the mean Moho depth are required. Due to our poor knowledge about them they are assumed unrealistically constant. In this paper, our idea is to improve a computed gravimetric Moho model, by the Vening Meinesz-Moritz theory, using the seismic model in Fennoscandia and estimate the error of each model through a combined adjustment with variance component estimation process. Corrective surfaces of bi-linear, bi-quadratic, bi-cubic and multi-quadric radial based function are used to model the discrepancies between the models and estimating the errors of the models. Numerical studies show that in the case of using the bi-linear surface negative variance components were come out, the bi-quadratic can model the difference better and delivers errors of 2.7 km and 1.5 km for the gravimetric and seismic models, respectively. These errors are 2.1 km and 1.6 km in the case of using the bi-cubic surface and 1 km and 1.5 km when the multi-quadric radial base function is used. The combined gravimetric models will be computed based on the estimated errors and each corrective surface.
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| 5. |
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| 6. |
- Mårtensson, Stig-Göran
(författare)
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Simple computation of coordinates and uncertainty of ‘hidden’ points from two coordinated points that are collinear with the hidden point
- 2022
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Ingår i: Survey review - Directorate of Overseas Surveys. - : Informa UK Limited. - 0039-6265 .- 1752-2706. ; 54:387, s. 543-553
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Tidskriftsartikel (refereegranskat)abstract
- Estimating the measurement uncertainties of coordinates of points that are not accessible by direct geodetic surveying (hidden points) is the topic of this study. The simplicity by which the uncertainties can be found for such hidden points when practicing indirect observations by total station or by Global Navigation Satellite System (GNSS) is demonstrated. A three-dimensional solution is obtained by total station observations using a two-prism hidden-point rod and a two-dimensional solution by GNSS observations on the ground. An intention with the study is that methods and results should apply for general geodetic purposes, like engineering surveying. The derived uncertainty formulae have been verified by Monte Carlo simulations. An important finding is their geometric dependence by the quotient between the two distances involved when two coordinated points are collinear with a third hidden point.
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| 7. |
- Amoson, Jonas, 1973-
(författare)
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Building complex GUIs in Plan 9
- 2009
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Ingår i: Proceedings 4th International Workshop on Plan9. - Athens, GA : University of Georgia. ; , s. 15-21
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- How can non-trivial graphical user interfaces be designed in Plan 9 without them losing their minimalistic style? Different toolkits are discussed, and a proposal for a tabbed toolbar is suggested as a way to add functionality without cluttering the interface and avoiding the use of pop-up dialog boxes. A hypothetical port to the GUI in LyX is used as an example.
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| 8. |
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| 9. |
- Lindgren, Erik, 1980, et al.
(författare)
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Analysis of industrial X-ray computed tomography data with deep neural networks
- 2021
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Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 0277-786X .- 1996-756X. ; 11840
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Konferensbidrag (refereegranskat)abstract
- X-ray computed tomography (XCT) is increasingly utilized industrially at material- and process development as well as in non-destructive quality control; XCT is important to many emerging manufacturing technologies, for example metal additive manufacturing. These trends lead to increased needs of safe automatic or semi-automatic data interpretation, considered an open research question for many critical high value industrial products such as within the aerospace industry. By safe, we mean that the interpretation is not allowed to unawarely or unexpectedly fail; specifically the algorithms must react sensibly to inputs dissimilar to the training data, so called out-of-distribution (OOD) inputs. In this work we explore data interpretation with deep neural networks to address: robust safe data interpretation which includes a confidence estimate with respect to OOD data, an OOD detector; generation of realistic synthetic material aw indications for the material science and nondestructive evaluation community. We have focused on industrial XCT related challenges, addressing difficulties with spatially correlated X-ray quantum noise. Results are reported on training auto-encoders (AE) and generative adversarial networks (GAN), on a publicly available XCT dataset of additively manufactured metal. We demonstrate that adding modeled X-ray noise during training reduces artefacts in the generated imperfection indications as well as improves the OOD detector performance. In addition, we show that the OOD detector can detect real and synthetic OOD data and still model the accepted in-distribution data down to the X-ray noise levels.
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| 10. |
- Lindgren, Erik, et al.
(författare)
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Deep-learning-based out-of distribution data detection in visual inspection images
- 2023
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Ingår i: Proceedings Of Spie 12489, NDE 4.0, Predictive Maintenance, Communication, and Energy Systems. - : Spie Digital Library. ; 12489
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Konferensbidrag (refereegranskat)abstract
- Within quality critical industries, e.g. aerospace, quality control with non-destructive evaluation (NDE) is essential. The surface quality is often important and e.g. visual inspection is often applied. Part of the inspection is the data interpretation, not easily made automatic for critical products. Recent studies on the automatization have indicated promising results utilizing deep-learning-based artificial intelligence. However, many such algorithms are known to be overconfident when subjected to unexpected input (e.g. new/rare material defects) far from the training dataset, so-called out-of-distribution (OOD) data. We claim that safe computer-based interpretation of NDE data within quality critical applications, must respond sensible also to OOD data. A sensible response could be that the algorithms identify such OOD data and forward it to a human for further analysis. Such an OOD detector could facilitate a human-machine collaboration in a NDE 4.0 vision. In this work we have explored if a recently proposed (for industrial x-ray images) auto-encoder-based approach can be utilized as OOD detector (one-class classifier) for visual inspection data. The model is trained in an unsupervised manner on accepted input to reconstruct it at high precision. Simultaneously it is trained to remove synthetically added defect indications to generate a clean image patch, similar to denoising-auto-enoders. The difference between the input and reconstructed input is analyzed for OOD detection. We train and test the algorithm on a publicly available visual inspection dataset with surface defects. We achieve true positive rates at 0.90 with true negative rates at 0.99 and demonstrate detection of OOD data.
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