Matematisk institutt
http://hdl.handle.net/10852/5
Wed, 14 Apr 2021 22:27:40 GMT2021-04-14T22:27:40ZTwo-phase co-current flow simulations using periodic boundary conditions in horizontal, 4, 10 and 90° inclined eccentric annulus, flow prediction using a modified interFoam solver and comparison with experimental results
http://hdl.handle.net/10852/85219
Two-phase co-current flow simulations using periodic boundary conditions in horizontal, 4, 10 and 90° inclined eccentric annulus, flow prediction using a modified interFoam solver and comparison with experimental results
Friedemann, Christopher; Mortensen, Mikael; Nossen, Jan
Two-phase oil and gas flow were simulated in an entirely eccentric annulus and compared with experimental data at horizontal, 4, 10, and 90° inclination. The gas-phase was sulphur hexafluoride and the liquid phase a mixture of Exxsol D60 and Marcol 82 for the inclined cases (5–16), and pure Exxsol D60 for the horizontal cases (1–4). The diameter of the outer and inner cylinders was 0.1 and 0.04 m, respectively, for the inclined domains and 0.1 and 0.05 m for the horizontal domain. The cases studied consist of liquid phase fractions between 0.3 and 0.65 and mixture velocities from 1.2 to 4.25 m/s. The mean pressure gradient is within 33% of the expected experimental behavior for all inclined cases. In contrast, the low-velocity horizontal domains exhibit significant deviation, with a drastic over-prediction of the mean pressure gradient by as much as 200–335% for cases 1 and 2. The two remaining horizontal cases (3 and 4) are within 22% of the expected mean pressure gradient. Cases 13–16 are a replication of cases 5–8 at an increased inclination; the mean pressure gradient is within 6.5% of the expected increase due to the increase in hydrostatic pressure. By comparing cases 1–4 to previous published simulations at a lower eccentricity, we found a decrease of the mean pressure gradient by 30–40%, which is in line with existing literature, although for single-phase flows. The simulated and experimental liquid holdup profiles are in good agreement when comparing the fractional data; wave and slug frequencies match to within 0.5 Hz; however, at closer inspection, it is apparent that there is a decrease in the amount of phase-mixing of the simulations compared to the experiments. When increasing the mesh density from 115 k cells/m to 2 million cells/m, the simulations exhibit significantly more phase mixing, but are still unable to produce conventional slugs. In a simplified case, conventional slugs are observed at grid sizing of 1 × 1 × 1 mm, whereas the cells of the 2 million cells/m mesh are roughly 1.5 × 1.5 × 1.5 mm.
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10852/852192021-01-01T00:00:00ZChanges in soil organic carbon under perennial crops
http://hdl.handle.net/10852/85172
Changes in soil organic carbon under perennial crops
Ledo, Alicia; Smith, Pete; Zerihun, Ayalsew; Whitaker, Jeanette; Vicente‐Vicente, José Luis; Qin, Zhangcai; McNamara, Niall P.; Zinn, Yuri L.; Llorente, Mireia; Liebig, Mark; Kuhnert, Matthias; Dondini, Marta; Don, Axel; Diaz‐Pines, Eugenio; Datta, Ashim; Bakka, Haakon C.; Aguilera, Eduardo; Hillier, Jon
This study evaluates the dynamics of soil organic carbon (SOC) under perennial crops across the globe. It quantifies the effect of change from annual to perennial crops and the subsequent temporal changes in SOC stocks during the perennial crop cycle. It also presents an empirical model to estimate changes in the SOC content under crops as a function of time, land use, and site characteristics. We used a harmonized global dataset containing paired‐comparison empirical values of SOC and different types of perennial crops (perennial grasses, palms, and woody plants) with different end uses: bioenergy, food, other bio‐products, and short rotation coppice. Salient outcomes include: a 20‐year period encompassing a change from annual to perennial crops led to an average 20% increase in SOC at 0–30 cm (6.0 ± 4.6 Mg/ha gain) and a total 10% increase over the 0–100 cm soil profile (5.7 ± 10.9 Mg/ha). A change from natural pasture to perennial crop decreased SOC stocks by 1% over 0–30 cm (−2.5 ± 4.2 Mg/ha) and 10% over 0–100 cm (−13.6 ± 8.9 Mg/ha). The effect of a land use change from forest to perennial crops did not show significant impacts, probably due to the limited number of plots; but the data indicated that while a 2% increase in SOC was observed at 0–30 cm (16.81 ± 55.1 Mg/ha), a decrease in 24% was observed at 30–100 cm (−40.1 ± 16.8 Mg/ha). Perennial crops generally accumulate SOC through time, especially woody crops; and temperature was the main driver explaining differences in SOC dynamics, followed by crop age, soil bulk density, clay content, and depth. We present empirical evidence showing that the FAO perennialization strategy is reasonable, underscoring the role of perennial crops as a useful component of climate change mitigation strategies.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/851722020-01-01T00:00:00ZSpectra of products of digraphs
http://hdl.handle.net/10852/85099
Spectra of products of digraphs
Catral, Minerva; Ciardo, Lorenzo; Hogben, Leslie; Reinhart, Carolyn
A unified approach to the determination of eigenvalues and eigenvectors of specific matrices associated with directed graphs is presented. Matrices studied include the new distance matrix, with natural extensions to the distance Laplacian and distance signless Laplacian, in addition to the new adjacency matrix, with natural extensions to the Laplacian and signless Laplacian. Various sums of Kronecker products of nonnegative matrices are introduced to model the Cartesian and lexicographic products of digraphs. The Jordan canonical form is applied extensively to the analysis of spectra and eigenvectors. The analysis shows that Cartesian products provide a method for building infinite families of transmission regular digraphs with few distinct distance eigenvalues.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/850992020-01-01T00:00:00ZRegularity properties of the stochastic flow of a skew fractional Brownian motion
http://hdl.handle.net/10852/85078
Regularity properties of the stochastic flow of a skew fractional Brownian motion
Amine, Oussama; Baños, David; Proske, Frank Norbert
In this paper we prove, for small Hurst parameters, the higher-order differentiability of a stochastic flow associated with a stochastic differential equation driven by an additive multi-dimensional fractional Brownian noise, where the bounded variation part is given by the local time of the unknown solution process. The proof of this result relies on Fourier analysis-based variational calculus techniques and on intrinsic properties of the fractional Brownian motion.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/850782020-01-01T00:00:00ZDirection and magnitude of cerebrospinal fluid flow vary substantially across central nervous system diseases
http://hdl.handle.net/10852/85064
Direction and magnitude of cerebrospinal fluid flow vary substantially across central nervous system diseases
Eide, Per K; Valnes, Lars M; Lindstrøm, Erika K; Mardal, Kent-Andre; Ringstad, Geir
Background
Several central nervous system diseases are associated with disturbed cerebrospinal fluid (CSF) flow patterns and have typically been characterized in vivo by phase-contrast magnetic resonance imaging (MRI). This technique is, however, limited by its applicability in space and time. Phase-contrast MRI has yet to be compared directly with CSF tracer enhanced imaging, which can be considered gold standard for assessing long-term CSF flow dynamics within the intracranial compartment.
Methods
Here, we studied patients with various CSF disorders and compared MRI biomarkers of CSF space anatomy and phase-contrast MRI at level of the aqueduct and cranio-cervical junction with dynamic intrathecal contrast-enhanced MRI using the contrast agent gadobutrol as CSF tracer. Tracer enrichment of cerebral ventricles was graded 0–4 by visual assessment. An intracranial pressure (ICP) score was used as surrogate marker of intracranial compliance.
Results
The study included 94 patients and disclosed marked variation of CSF flow measures across disease categories. The grade of supra-aqueductal reflux of tracer varied, with strong reflux (grades 3–4) in half of patients. Ventricular tracer reflux correlated with stroke volume and aqueductal CSF pressure gradient. CSF flow in the cerebral aqueduct was retrograde (from 4th to 3rd ventricle) in one third of patients, with estimated CSF net flow volume about 1.0 L/24 h. In the cranio-cervical junction, net flow was cranially directed in 78% patients, with estimated CSF net flow volume about 4.7 L/24 h.
Conclusions
The present observations provide in vivo quantitative evidence for substantial variation in direction and magnitude of CSF flow, with re-direction of aqueductal flow in communicating hydrocephalus, and significant extra-cranial CSF production. The grading of ventricular reflux of tracer shows promise as a clinical useful method to assess CSF flow pattern disturbances in patients.
Graphic abstract
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10852/850642021-01-01T00:00:00ZAnalysis of the risk premium in the forward market for salmon
http://hdl.handle.net/10852/85009
Analysis of the risk premium in the forward market for salmon
Benth, Fred Espen; Eikeset, Anne Maria; Levin, Simon A.; Ren, Wanjuan
We analyse forward prices observed at the Fishpool market, and propose a two-factor continuous-time stochastic process for modelling the time dynamics. The data analysis reveals that the two factors can be assumed to be a non-stationary compound Poisson process and a stationary continuous-time autoregressive dynamics, describing the bumps observed in the forward curves. We use the model to analyse the risk premium in the forward markets, and find a negative premium in the long end of the market which is in line with the theory of normal backwardation. However, contracts with short time to maturity have a risk premium with randomly changing sign, pointing towards a hedging pressure also induced by the demand-side of the market.
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10852/850092021-01-01T00:00:00ZYield stress of aerated cement paste
http://hdl.handle.net/10852/84960
Yield stress of aerated cement paste
Feneuil, Blandine Fleur Prudence; Roussel, Nicolas; Pitois, Olivier
Yield stress of aerated cement paste is studied. Samples are prepared by mixing aqueous foam with cement paste, which allows controlling bubble size, gas volume fraction and yield stress of the cement paste. Two distinct behaviors are observed depending on the surfactant used to prepare the precursor aqueous foam: (i) For a surfactant with low adsorption ability with respect to cement grains, bubbles tend to decrease the yield stress of the paste with magnitude governed by the Bingham capillary number, which accounts for bubble deformability. (ii) For a surfactant with high adsorption ability, bubbles increase significantly the yield stress. This behavior is shown to result from the surfactant-induced hydrophobization of the cement grains, which adsorb at the surface of the bubbles and tend to rigidify them. Within this regime, the effect of air incorporation is comparable to the effect of added solid particles.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/849602020-01-01T00:00:00ZThe separating semigroup of a real curve
http://hdl.handle.net/10852/84951
The separating semigroup of a real curve
Shaw, Kristin; Kummer, Mario
We introduce the separating semigroup of a real algebraic curve of dividing type. The elements of this semigroup record the possible degrees of the covering maps obtained by restricting separating morphisms to the real part of the curve. We also introduce the hyperbolic semigroup which consists of elements of the separating semigroup arising from morphisms which are compositions of a linear projection with an embedding of the curve to some projective space.
We completely determine both semigroups in the case of maximal curves. We also prove that any embedding of a real curve of dividing type to projective space of sufficiently high degree is hyperbolic. Using these semigroups we show that the hyperbolicity locus of an embedded curve is in general not connected.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/849512020-01-01T00:00:00ZThe myodural bridge of the American alligator (Alligator mississippiensis) alters CSF flow
http://hdl.handle.net/10852/84839
The myodural bridge of the American alligator (Alligator mississippiensis) alters CSF flow
Young, Bruce A.; Adams, James; Beary, Jonathan M.; Mardal, Kent-Andre; Schneider, Robert; Kondrashova, Tatyana
ABSTRACT Disorders of the volume, pressure or circulation of the cerebrospinal fluid (CSF) lead to disease states in both newborns and adults; despite this significance, there is uncertainty regarding the basic mechanics of the CSF. The suboccipital muscles connect to the dura surrounding the spinal cord, forming a complex termed the ‘myodural bridge’. This study tests the hypothesis that the myodural bridge functions to alter the CSF circulation. The suboccipital muscles of American alligators were surgically exposed and electrically stimulated simultaneously with direct recordings of CSF pressure and flow. Contraction of the suboccipital muscles significantly changed both CSF flow and pressure. By demonstrating another influence on CSF circulation and pulsatility, the present study increases our understanding of the mechanics underlying the movement of the CSF.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/848392020-01-01T00:00:00ZClog-free trilobite filtration: Tunable flow setup and velocity measurements
http://hdl.handle.net/10852/84837
Clog-free trilobite filtration: Tunable flow setup and velocity measurements
Mossige, Endre Joachim; Jensen, Atle
The ability to separate and filter out microscopic objects lies at the core of many biomedical applications. However, a persistent problem is clogging, as biomaterials stick to the internal chip surface and limit device efficiency and liability. Here, we review an alternative technique that could solve these clogging issues. By leveraging tunable flow fields and particle inertia around special trilobite-shaped filtration units, we perform filtration of plastic beads by size and we demonstrate sorting of live cells. The separation and filtration are performed completely without signs of clogging. However, a clog-free operation relies on a controlled flow configuration to steer the particles and cells away from the filter structures. In this paper, we describe the tunable flow system for such an operation and we describe an optical setup enabling hydrodynamical interactions between particles and cells with the flow fields and direct interactions with the filter structures to be characterized. The optical setup is capable of measuring particle and flow velocities (by Particle Tracking Velocimetry (PTV), Micro Particle Image Velocimetry (μPIV), and streakline visualization) in meters per second necessary to avoid clogging. However, accurate measurements rely on strict calibration and validation procedures to be followed, and we devote a substantial portion of our paper to laying out such procedures. A comparison between μPIV data and a known flow profile is particularly valuable for assessing measurement accuracy, and this important validation has not been previously published by us. The detail level in our description of the flow configuration and optical system is sufficient to replicate the experiments. In the last part of the paper, we review an assessment of the device performance when handling rigid spheres and live cells. We deconvolute the influences of cell shape from effects of size and find that the shape has only a weak influence on device performance.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/848372020-01-01T00:00:00ZThe Consumption Euler Equation or the Keynesian Consumption Function?
http://hdl.handle.net/10852/84836
The Consumption Euler Equation or the Keynesian Consumption Function?
Boug, Pål; Cappelen, Ådne; Jansen, Eilev S; Swensen, Anders Rygh
We formulate a general cointegrated vector autoregressive (CVAR) model that nests both a class of consumption Euler equations and various Keynesian‐type consumption functions. Using likelihood‐based methods and Norwegian data, we find support for cointegration between consumption, income and wealth once a structural break around the time of the financial crisis is allowed for. The fact that consumption cointegrates with both income and wealth and not only with income points to the empirical irrelevance of an Euler equation. Moreover, we find that consumption equilibrium corrects to changes in income and wealth, but not that income equilibrium corrects to changes in consumption, which would follow from an Euler equation. We also find that most of the parameters stemming from the class of Euler equations are not corroborated by the data when conditional expectations of future consumption and income in CVAR models are considered. Only habit formation seems important in explaining Norwegian consumer behaviour. Our estimated conditional Keynesian‐type consumption function implies a first year marginal propensity to consume (MPC) out of income of close to 40%.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/848362020-01-01T00:00:00ZWeighted quasi-interpolant spline approximations: Properties and applications
http://hdl.handle.net/10852/84835
Weighted quasi-interpolant spline approximations: Properties and applications
Raffo, Andrea; Biasotti, Silvia
Continuous representations are fundamental for modeling sampled data and performing computations and numerical simulations directly on the model or its elements. To effectively and efficiently address the approximation of point clouds, we propose the weighted quasi-interpolant spline approximation method (wQISA). We provide global and local bounds of the method and discuss how it still preserves the shape properties of the classical quasi-interpolation scheme. This approach is particularly useful when the data noise can be represented as a probabilistic distribution: from the point of view of non-parametric regression, the wQISA estimator is robust to random perturbations, such as noise and outliers. Finally, we show the effectiveness of the method with several numerical simulations on real data, including curve fitting on images, surface approximation, and simulation of rainfall precipitations.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/848352020-01-01T00:00:00ZData-driven quasi-interpolant spline surfaces for point cloud approximation
http://hdl.handle.net/10852/84834
Data-driven quasi-interpolant spline surfaces for point cloud approximation
Raffo, Andrea; Biasotti, Silvia
In this paper we investigate a local surface approximation, the Weighted Quasi Interpolant Spline Approximation (wQISA), specifically designed for large and noisy point clouds. We briefly describe the properties of the wQISA representation and introduce a novel data-driven implementation, which combines prediction capability and complexity efficiency. We provide an extended comparative analysis with other continuous approximations on real data, including different types of surfaces and levels of noise, such as 3D models, terrain data and digital environmental data.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/848342020-01-01T00:00:00ZThe circle action on topological Hochschild homology of complex cobordism and the Brown–Peterson spectrum
http://hdl.handle.net/10852/84830
The circle action on topological Hochschild homology of complex cobordism and the Brown–Peterson spectrum
Rognes, John
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/848302020-01-01T00:00:00ZNumerical methods for conservation laws with rough flux
http://hdl.handle.net/10852/84829
Numerical methods for conservation laws with rough flux
Hoel, Håkon; Karlsen, Kenneth Hvistendahl; Risebro, Nils Henrik; Storrøsten, Erlend Briseid
Finite volume methods are proposed for computing approximate pathwise entropy/kinetic solutions to conservation laws with flux functions driven by low-regularity paths. For a convex flux, it is demonstrated that driving path oscillations may lead to “cancellations” in the solution. Making use of this property, we show that for α-Hölder continuous paths the convergence rate of the numerical methods can improve from O(COST−γ), for some γ∈[α/(12−8α),α/(10−6α)], with α∈(0,1), to O(COST−min(1/4,α/2)). Numerical examples support the theoretical results.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/848292020-01-01T00:00:00ZMachine learning dihydrogen activation in the chemical space surrounding Vaska's complex
http://hdl.handle.net/10852/84748
Machine learning dihydrogen activation in the chemical space surrounding Vaska's complex
Friederich, Pascal; Dos Passos Gomes, Gabriel; De Bin, Riccardo; Aspuru-Guzik, Alán; Balcells, David
Homogeneous catalysis using transition metal complexes is ubiquitously used for organic synthesis, as well as technologically relevant in applications such as water splitting and CO2 reduction. The key steps underlying homogeneous catalysis require a specific combination of electronic and steric effects from the ligands bound to the metal center. Finding the optimal combination of ligands is a challenging task due to the exceedingly large number of possibilities and the non-trivial ligand–ligand interactions. The classic example of Vaska's complex, trans-[Ir(PPh3)2(CO)(Cl)], illustrates this scenario. The ligands of this species activate iridium for the oxidative addition of hydrogen, yielding the dihydride cis-[Ir(H)2(PPh3)2(CO)(Cl)] complex. Despite the simplicity of this system, thousands of derivatives can be formulated for the activation of H2, with a limited number of ligands belonging to the same general categories found in the original complex. In this work, we show how DFT and machine learning (ML) methods can be combined to enable the prediction of reactivity within large chemical spaces containing thousands of complexes. In a space of 2574 species derived from Vaska's complex, data from DFT calculations are used to train and test ML models that predict the H2-activation barrier. In contrast to experiments and calculations requiring several days to be completed, the ML models were trained and used on a laptop on a time-scale of minutes. As a first approach, we combined Bayesian-optimized artificial neural networks (ANN) with features derived from autocorrelation and deltametric functions. The resulting ANNs achieved high accuracies, with mean absolute errors (MAE) between 1 and 2 kcal mol−1, depending on the size of the training set. By using a Gaussian process (GP) model trained with a set of selected features, including fingerprints, accuracy was further enhanced. Remarkably, this GP model minimized the MAE below 1 kcal mol−1, by using only 20% or less of the data available for training. The gradient boosting (GB) method was also used to assess the relevance of the features, which was used for both feature selection and model interpretation purposes. Features accounting for chemical composition, atom size and electronegativity were found to be the most determinant in the predictions. Further, the ligand fragments with the strongest influence on the H2-activation barrier were identified.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/847482020-01-01T00:00:00ZMaking the most of data in dairy farming research-how twenty-first century statistical learning methods can contribute
http://hdl.handle.net/10852/84528
Making the most of data in dairy farming research-how twenty-first century statistical learning methods can contribute
Hansen, Bjørn Gunnar
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/845282020-01-01T00:00:00ZTests of homogeneity and change-point inference
http://hdl.handle.net/10852/84429
Tests of homogeneity and change-point inference
Hagen, Elisabeth Nesheim
We study sequences of independent observations and test whether the observations stem from the same underlying probability distribution. We focus on being able to detect a potential sudden change in the parameters of the distribution, which we call a change-point. Before constructing a test, we define a focus parameter which captures the aspect of the distribution that we want to test. We construct a monitoring process for our focus parameter that converges to a Brownian bridge under the hypothesis of omogeneity. We then use our monitoring process to construct a test statistic for testing homogeneity. We look at the power of our hypothesis test, compared to other tests. We look at how our monitoring process behaves when the null hypothesis is false and suggest a way to estimate the change-point based on the process. We describe two different ways to assess the uncertainty around an estimated change-point with confidence curves.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10852/844292020-01-01T00:00:00ZThe deconvolution as a method to deal with gaps in ocean wave measurements
http://hdl.handle.net/10852/84170
The deconvolution as a method to deal with gaps in ocean wave measurements
Støle-Hentschel, Susanne; Nieto Borge, Jose Carlos; Trulsen, Karsten
This work introduces the deconvolution as a technique to reconstruct missing information in data. While the method was originally developed for ocean waves, it will be useful in a wider range of applications where gaps in data may alter the statistics or spikes have to be eliminated without removing extreme values. For the application to ocean waves, it is estimated that gaps as long as half of the peak period may be reconstructed well. It is possible to reconstruct data of longer gaps, however, in total the amount of missing points should be less than 50% of all points and the missing data should not be clustered.
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10852/841702021-01-01T00:00:00ZFault detection and diagnosis of nonlinear dynamical processes through correlation dimension and fractal analysis based dynamic kernel PCA
http://hdl.handle.net/10852/84160
Fault detection and diagnosis of nonlinear dynamical processes through correlation dimension and fractal analysis based dynamic kernel PCA
Bounoua, Wahiba; Bakdi, Azzeddine
A novel Dynamic Kernel PCA (DKPCA) method is developed for process monitoring in nonlinear dynamical systems. Classical DKPCA approaches still exhibit vague linearity assumptions to determine the number of principal components and to construct the dynamical structure. The optimal Static PCA (SPCA) and Dynamic PCA (DPCA) structures are constructed herein through the powerful theory of the nonlinear Fractal Dimension (FDim). While DKPCA offers a generic data-driven modelling of nonlinear dynamical systems, the fractal correlation dimension provides an intrinsic measure of the data complexity counting for the nonlinear dynamics and the chaotic behaviour. The proposed Fractal-based DKPCA (FDKPCA) integrates the two strategies to overcome SPCA/DPCA/DKPCA shortcomings, FDim allows verifying the degree of fitting and ensures optimal dimensionality reduction. The novel fault detection and diagnosis method is validated through seven applications using the Process Network Optimization (PRONTO) benchmark with real heterogeneous data, FDKPCA showed superior performance compared to contemporary approaches.
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10852/841602021-01-01T00:00:00Z