| 1. |
- Lin, G., et al.
(författare)
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A regularizing Kohn-Vogelius formulation for the model-free adsorption isotherm estimation problem in chromatography
- 2018
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Ingår i: Applicable Analysis. - : Informa UK Limited. - 0003-6811 .- 1563-504X. ; 97:1, s. 13-40
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Tidskriftsartikel (refereegranskat)abstract
- Competitive adsorption isotherms must be estimated in order to simulate and optimize modern continuous modes of chromatography in situations where experimental trial-and-error approaches are too complex and expensive. The inverse method is a numeric approach for the fast estimation of adsorption isotherms directly from overloaded elution profiles. However, this identification process is usually ill-posed. Moreover, traditional model-based inverse methods are restricted by the need to choose an appropriate adsorption isotherm model prior to estimate, which might be very hard for complicated adsorption behavior. In this study, we develop a Kohn-Vogelius formulation for the model-free adsorption isotherm estimation problem. The solvability and convergence for the proposed inverse method are studied. In particular, using a problem-adapted adjoint, we obtain a convergence rate under substantially weaker and more realistic conditions than are required by the general theory. Based on the adjoint technique, a numerical algorithm for solving the proposed optimization problem is developed. Numerical tests for both synthetic and real-world problems are given to show the efficiency of the proposed regularization method.
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| 2. |
- Muhammad, Dost, et al.
(författare)
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A Generalized Deep Learning Approach to Seismic Activity Prediction
- 2023
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 13:3
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Tidskriftsartikel (refereegranskat)abstract
- Seismic activity prediction has been a challenging research domain: in this regard, accurate prediction using historical data is an intricate task. Numerous machine learning and traditional approaches have been presented lately for seismic activity prediction; however, no generalizable model exists. In this work, we consider seismic activity predication as a binary classification problem, and propose a deep neural network architecture for the classification problem, using historical data from Chile, Hindukush, and Southern California. After obtaining the data for the three regions, a data cleaning process was used, which was followed by a feature engineering step, to create multiple new features based on various seismic laws. Afterwards, the proposed model was trained on the data, for improved prediction of the seismic activity. The performance of the proposed model was evaluated and compared with extant techniques, such as random forest, support vector machine, and logistic regression. The proposed model achieved accuracy scores of 98.28%, 95.13%, and 99.29% on the Chile, Hindukush, and Southern California datasets, respectively, which were higher than the current benchmark model and classifiers. In addition, we also conducted out-sample testing, where the evaluation metrics confirmed the generality of our proposed approach.
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| 3. |
- Polvi, Lina E., et al.
(författare)
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Seismic Monitoring of a Subarctic River : Seasonal Variations in Hydraulics, Sediment Transport, and Ice Dynamics
- 2020
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Ingår i: Journal of Geophysical Research - Earth Surface. - : American Geophysical Union (AGU). - 2169-9003 .- 2169-9011. ; 125:7
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Tidskriftsartikel (refereegranskat)abstract
- High-latitude rivers are commonly covered by ice for up to one third of the year. Our understanding of the effects of ice on channel morphodynamics and bedload transport is hindered by the difficulties of sensing through the ice and dangers of field work on thin ice or during ice break-up. To avoid this drawback, we used seismic signals to interpret processes and quantify water and sediment fluxes. Our objective was to determine seasonal differences in hydraulics and bedload sediment transport under ice-covered versus open-channel flow conditions using a small seismic network and to provide a first-order estimation of sediment flux in a Fennoscandian river. Our study reach was on a straight, low-gradient section of the Savar River in northern Sweden. Interpretations of seismic signals, from a station 40 m away from the river, and inverted physical models of river stage and bedload flux indicate clear seasonal differences between ice-covered and open-channel flow conditions. Diurnal cycles in seismic signals reflecting turbulence and sediment transport are evident directly after ice break-up. Analysis of seismic signals of ice-cracking support our visual interpretation of ice break-up timing and the main ice break-up mechanism as thermal rather than mechanical. Assuming the bulk of sediment moves during ice break-up and the snowmelt flood, we calculate a minimum annual sediment flux of 56.2 +/- 0.7 t/km(2), which drastically reduces the uncertainty from previous estimates (0-50 t/km(2)) that exclude ice-covered or ice break-up periods.
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| 4. |
- Swantesson, Jan O.H. 1952-
(författare)
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Weathering and Erosion of Rock Carvings in Sweden during the Period 1994-2003 : Micro Mapping with Laser Scanner for Assessment of Breakdown Rates
- 2005
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This research report describes a 10-year long monitoring project for assessments of recent downwearing rates on rock carvings in southern and central Sweden. The investigations have been made by repeated measurements on the same sites with a laser scanner, especially constructed for the purpose. The scanner records the microtopography of rock surfaces with a resolution of 0.025 mm. From the field data accurate micro maps of areas up to 40x40 cm can be made. Deterioration rates are calculated by computerised comparisons of micro maps from consecutive measurements. A total number of 26 sites have been followed from 1994 to 2003. There are large variations in downwearing rates between the investigated places. Averages are, however, similar to those that can be expected from crystalline rocks in general in Scandinavia. It has also been revealed that the micro weathering is episodic. This means that periods with fast breakdown alternate with periods when almost nothing happens. Furthermore the spatial variation within the laser scanned areas of where downwearing takes place could be studied. Usually deterioration at times only takes place on limited spots while most of the micro mapped area is left unaffected. After material losses have taken place from these spots weathering continues at other places.
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| 5. |
- Zhang, Ye, 1984-, et al.
(författare)
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An adaptive regularization algorithm for recovering the rate constant distribution from biosensor data
- 2018
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Ingår i: Inverse Problems in Science and Engineering. - Oxon, UK : Taylor & Francis. - 1741-5977 .- 1741-5985. ; 26:10, s. 1464-1489
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Tidskriftsartikel (refereegranskat)abstract
- We present here the theoretical results and numerical analysis of a regularization method for the inverse problem of determining the rate constant distribution from biosensor data. The rate constant distribution method is a modern technique to study binding equilibrium and kinetics for chemical reactions. Finding a rate constant distribution from biosensor data can be described as a multidimensional Fredholm integral equation of the first kind, which is a typical ill-posed problem in the sense of J. Hadamard. By combining regularization theory and the goal-oriented adaptive discretization technique, we develop an Adaptive Interaction Distribution Algorithm (AIDA) for the reconstruction of rate constant distributions. The mesh refinement criteria are proposed based on the a posteriori error estimation of the finite element approximation. The stability of the obtained approximate solution with respect to data noise is proven. Finally, numerical tests for both synthetic and real data are given to show the robustness of the AIDA.
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