The inversion method for generating non-uniform random variates has some advantages compared to other generation methods, since it monotonically transforms uniform random numbers into non-uniform random variates. Hence it is the method of choice in the simulation literature. However, except for some simple cases where the inverse of the cumulative distribution function is a simple function we need numerical methods. Often inversion by ``brute force" is used, applying either very slow iterative methods or linear interpolation of the CDF and huge tables. But then the user has to accept unnecessarily large errors or excessive memory requirements, that slow down the algorithm. In this paper we demonstrate that with Hermite interpolation of the inverse CDF we can obtain very small error bounds close to machine precision. Using our adaptive interval splitting method this accuracy is reached with moderately sized tables that allow for a fast and simple generation procedure. The algorithms described in this paper have been implemented in ANSI C in a library called UNURAN which is available via anonymous ftp. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

In today’s fast adjustment to renewable energy, new battery technologies are needed to meetthe ever-growing demands of energy storage. Cheaper and easier to produce materials areneeded, as well as materials with a lower environmental impact. One new and interestingtechnology is the dual-ion battery, and more specifically the aluminum dual-ion battery. Thisbattery uses cheap and abundant aluminum together with a graphitic cathode to work. However,a lot of research today uses expensive and sophisticated cathode materials to make this type ofbattery work. Therefore, this thesis focuses on creating a cheap and easy to produce graphitecathode material through the phase inversion method for the use in aluminum dual-ionbatteries, that is also freestanding for better energy density. Graphene is also used as anadditive to improve the electrical conductivity of the material, and the material is later tested in afull cell with the typical ionc liquid electrolyte EMImCL/AlCl4.Through phase inversion, a freestanding graphite cathode is produced with 8 wt% PVDF binderand 0.4 wt% graphene. The material has a porous structure and an enhanced electricalconductivity with the graphene added. Through CV cycling and symmetric Al-Al tests the batteryreactions are shown to work. However, when cycling the cell with a constant current there areproblems, probably coming from some sort of soft shorting or side reactions. It is revealed thatapart from the expected reactions, Ni dissolution from the contact tabs also takes place, andmay cause problems. Further tests are needed to validate if this material works. However,because no new active materials have been introduced to the battery chemistry, it is reasonableto believe that the battery will work with some small changes.Tek nisk-naturvetensk apliga fak ulteten, Upps ala universitet. Utgiv nings ort U pps al a/Vis by . H andledare: Anwar Ahniy az , Äm nesgranskar e: D aniel Brandell, Ex aminator: Lena Klintberg

Over the last years, due to the development of quieter engines and drivetrains, the importance of addressing the vehicle wind noise problem has significantly increased.In this thesis work, several existing Transfer Path Analysis methods have been applied on an experimental database acquired during a wind tunnel test on a passenger car with the objective of analyzing the distribution of the wind noise sources and their contribution to the target microphones located inside the vehicle. A major challenge for the Transfer Path Analysis (TPA) consists of the high complexity of the aerodynamic sources exciting the structure. Moreover, the existence of multiple incoherent source phenomena, and the presence of distributed coherent source regions of different correlation scales make the analysis very complex.The thesis work provides a solid and comprehensive analysis of the results obtained by different methods. The outcomes can be potentially useful for optimizing the vehicle NVH performance in future practical cases. / Under de senaste åren har vikten av att arbeta med vägfordons problem med aerodynamisk ljudgenerering ökat avsevärt på grund av utvecklingen av tystare motorer och drivlinor. I det här projektet har flera existerande metoder för Transfer Path Analysis (TPA) tillämpats på en databas med experimentella data som samlats in vid vindtunneltest på en personbil, med målet att analysera fördelningen av källorna orsakade av vindbruset och deras påverkan på ljudnivån vid de uppsatta målmikrofonerna inuti fordonet. En stor utmaning för TPA är den höga komplexiteten hos de aerodynamiska källorna som exciterar strukturen. Vidare gör förekomsten av flera okorrelerade källor, och närvaron av distribuerade koherenta källregioner med olika korrelationsskalor, analysen mycket komplex. Arbetet presenterar en solid och omfattande analys av resultat som erhållits med olika metoder. Resultaten är potentiellt användbara för att optimera fordonets NVH-prestanda i praktiktiken i framtiden.

We present a numerical inversion method for generating random variates from continuous distributions when only the density function is given. The algorithm is based on polynomial interpolation of the inverse CDF and Gauss-Lobatto integration. The user can select the required precision which may be close to machine precision for smooth, bounded densities; the necessary tables have moderate size. Our computational experiments with the classical standard distributions (normal, beta, gamma, t-distributions) and with the noncentral chi-square, hyperbolic, generalized hyperbolic and stable distributions showed that our algorithm always reaches the required precision. The setup time is moderate and the marginal execution time is very fast and the same for all distributions. Thus for the case that large samples with fixed parameters are required the proposed algorithm is the fastest inversion method known. Speed-up factors up to 1000 are obtained when compared to inversion algorithms developed for the specific distributions. This makes our algorithm especially attractive for the simulation of copulas and for quasi-Monte Carlo applications. (author´s abstract) / Series: Research Report Series / Department of Statistics and Mathematics

There arise two problems when the expectation of some function with respect to a nonuniform multivariate distribution has to be computed by (quasi-) Monte Carlo integration: the integrand can have singularities when the domain of the distribution is unbounded and it can be very expensive or even impossible to sample points from a general multivariate distribution. We show that importance sampling is a simple method to overcome both problems. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

We present a numerical inversion method for generating random variates from continuous distributions when only the density function is given. The algorithm is based on polynomial interpolation of the inverse CDF and Gauss-Lobatto integration. The user can select the required precision which may be close to machine precision for smooth, bounded densities; the necessary tables have moderate size. Our computational experiments with the classical standard distributions (normal, beta, gamma, t-distributions) and with the noncentral chi-square, hyperbolic, generalized hyperbolic and stable distributions showed that our algorithm always reaches the required precision. The setup time is moderate and the marginal execution time is very fast and nearly the same for all distributions. Thus for the case that large samples with fixed parameters are required the proposed algorithm is the fastest inversion method known. Speed-up factors up to 1000 are obtained when compared to inversion algorithms developed for the specific distributions. This makes our algorithm especially attractive for the simulation of copulas and for quasi-Monte Carlo applications. <P> This paper is the revised final version of the working paper no. 78 of this research report series. / Series: Research Report Series / Department of Statistics and Mathematics

This Online Supplement summarizes our computational experiences with Algorithm NINIGL presented in our paper "Random Variate Generation by Numerical Inversion when only the Density Is Known" (Report No. 90). It is a numerical inversion method for generating random variates from continuous distributions when only the density function is given. The algorithm is based on polynomial interpolation of the inverse CDF and Gauss-Lobatto integration. The user can select the required precision which may be close to machine precision for smooth, bounded densities; the necessary tables have moderate size. Our computational experiments with the classical standard distributions (normal, beta, gamma, t-distributions) and with the noncentral chi-square, hyperbolic, generalized hyperbolic and stable distributions showed that our algorithm always reaches the required precision. The setup time is moderate and the marginal execution time is very fast and nearly the same for all these distributions. Thus for the case that large samples with fixed parameters are required the proposed algorithm is the fastest inversion method known. Speed-up factors up to 1000 are obtained when compared to inversion algorithms developed for the specific distributions. Thus our algorithm is especially attractive for the simulation of copulas and for quasi-Monte Carlo applications. / Series: Research Report Series / Department of Statistics and Mathematics

The present work was initiated to investigate the stability, structural and thermodynamic properties of transition metal carbides, nitrides and carbo-nitrides by atomistic simulations and experimentations. The interatomic pair potentials of Cr-Cr, Mn-Mn, Fe-Fe, C-C, Cr-C, Mn-C, Fe-C, Cr-Fe, Cr-N and Mn-N were inverted by the lattice inversion method and ab initio cohesive energies, and then employed to investigate the properties of Cr-, Mn- and Fe-carbides by atomistic simulations in this work. For the binary M7C3 carbide, the structural properties of M7C3 (M = Cr, Mn, Fe) were investigated by atomistic simulations. The results show that the stable structure for these compounds is hexagonal structure with P63mc space group. The cohesive energy of M7C3 calculated in this work indicates that the stability of carbides decreases with the increasing in metal atomic number. Further, the vibrational entropy of Cr7C3 was calculated at different temperatures and compared with the entropy obtained by experimentations. The comparison demonstrates that the main contribution to the entropy is made by the vibrational entropy. For the binary τ-carbides, the structural properties of Cr23C6 and Mn23C6, as well as the vibrational entropy of Cr23C6 were computed. Further, the site preference of ternary element Fe among 4a, 8c, 32f and 48h symmetry sites in Cr23-xFexC6 was studied. It has been seen that Fe atoms would firstly occupy 4a sites and then 8c sites. The lattice constant and stability of Cr23-xFexC6 were also computed with different Fe content. In order to understand the relative stability of the transition metal carbides and nitrides, the standard formation Gibbs energies of carbides and nitrides for Cr, Mn and Fe were compared. The order of carbon and nitrogen affinities for Cr, Mn and Fe was further clarified by the comparison of the interatomic pair potentials among Cr-C, Mn-C, Fe-C, Cr-N and Mn-N. It was found that Cr-N interaction was very strong in comparison with other binary interactions above and consequently, nitrogen addition would lead to a strong decrease in the thermodynamic activity of chromium in Cr-containing alloys. This was confirmed by the investigations of thermodynamic activities of Cr in the Fe-Cr-N and Fe-Cr-C-N alloys. The activities were measured in the temperature range 973-1173 K by solid-state galvanic cell method involving CaF2 solid electrolyte under the purified N2 gas. In addition, the analysis of nitrogen content and phase relationships in the Fe-Cr-N and Fe-Cr-C-N alloys equilibrated at 1173 K were carried out by inert-gas fusion thermal conductivity method, X-ray diffraction and scanning electron microscopy technique. The experimental results show that the solubility of nitrogen in the alloys decreases with the decreasing chromium content, as well as the increasing temperature. The addition of nitrogen to the alloys was found to have a strong negative impact on the Cr activity in Fe-Cr-N and Fe-Cr-C-N systems. / QC 20100929

The study focuses mainly on two gas hydrate-related targets, located on the Northern Cascadia Margin, offshore Vancouver Island: (1) a recently identified 70-80-m high carbonate mound, Cucumber Ridge, located ~3.5-km west of Ocean Drilling Program (ODP) Site 889 and Integrated Ocean Drilling Program (IODP) Site U1327, and (2) a large cold vent, Bullseye vent, which is up to ~500 m in diameter and was drilled by IODP at Site U1328. The objective of this thesis is to analyze seismic data that provide indicators of locally focused fluid flow and characteristics of the gas hydrate occurrence associated with these two features. A grid of closely-spaced single channel seismic (SCS) data was collected at Cucumber Ridge in July/August 2001, and deep-towed multichannel seismic (MCS) lines were collected using Deep-towed Acoustics and Geophysics System (DTAGS) at the Bullseye vent area and at Cucumber Ridge in October 2002. The high-resolution SCS data, with a frequency bandpass of 40-150 Hz, recorded coherent reflectivity down to about 400 m beneath the seafloor, and provide excellent images of the subseafloor structure of Cucumber Ridge and of the gas hydrate bottom-simulating reflector (BSR) beneath it. Cucumber Ridge is interpreted to have developed as a structural topographic high in the hanging wall of a large reverse fault formed at the base of the current seaward slope. The fault zone provides pathways for fluids including gas to migrate to the seafloor where diagenetic carbonate forms and cements the near-surface sediments. Over the seismic grid, heat flow was derived from the depth of the BSR. A simple 2-D analytical correction for theoretical heat flow variations due to topography is applied to the data. Across the mound, most of the variability in heat flow is explained by topographic effects, including a local 6 mW/m2 negative anomaly over the central mound and a large 20 mW/m2 positive anomaly over the mound steep side slope. However, just south of the mound, there is a 6-7 mW/m2 positive anomaly in a 2-km-long band that has predominantly flat seafloor. Most of this anomaly is probably unrelated to topographic effects, but rather likely due to warm upward fluid flow along faults or fracture zones. Towed ~300 m above seafloor, the high frequency (220-1k Hz) DTAGS signal can provide high vertical resolution images with increased lateral resolution. The major problems of DTAGS are significant nonlinear variations of the source depths and receivers locations. New routines were developed for optimal DTAGS data processing, mainly including (1) cable geometry estimation by node depths, direct arrivals and seasurface reflections using a Genetic Algorithm inversion method, (2) acoustic image stitching based on accurate relative-source positioning by crosscorrelation of redundant data between two adjacent shots, and (3) velocity inversion of wide-angle traveltimes using a nonlinear global grid search method. The final processed DTAGS images resolve multiple seismic blanking zones and fine details of subseafloor features in the slope sediments. At Bullseye vent, where a 35-m-thick near-surface massive hydrate layer was drilled at U1328, the DTAGS data resolved the upper part of layer as a dipping diffraction zone, likely corresponding to a fracture zone. The inverted velocity structure in upper 100 m sediments successfully revealed a 17-m-thick layer of high velocity (~1650 m/s) just below seafloor, probably related to carbonate presence. A local high velocity zone, with a positive velocity anomaly of ~40-80 m/s in the upper 50 m beneath seafloor, was observed over the ~100-m wide region between U1328 and the deepest part of a seafloor depression; the high velocity zone is consistent with the dipping diffraction zone in the DTAGS image and with the massive hydrate drilled at U1328.

<p dir="ltr">There is a growing need to reconstruct high quality tomographic images from sparse view measurements to accommodate time and space constraints as well as patient well-being in medical CT. Analytical methods perform poorly with sub-Nyquist acquisition rates. In extreme cases with 4 or fewer views, effective reconstruction approaches must be able to incorporate side information to constrain the solution space of an otherwise under-determined problem. This thesis presents two sparse view tomography problems that are solved using techniques that exploit. knowledge of the structural and physical properties of the scanned objects.</p><p dir="ltr"><br></p><p dir="ltr">First, we reconstruct four view CT datasets obtained from an in-situ imaging system used to observe Kolsky bar impact experiments. Test subjects are typically 3D-printed out ofhomogeneous materials into shapes with circular cross sections. Two advanced prior modelsare formulated to incorporate these assumptions in a modular fashion into the iterativeradiographic inversion framework. The first is a Multi-Slice Fusion and the latter is TotalVariation regularization that operates in cylindrical coordinates.</p><p dir="ltr"><br></p><p dir="ltr">In the second problem, artificial neural networks (NN) are used to directly invert a temporal sequence of four radiographic images of discontinuities propagating through an imploding steel shell. The NN is fed the radiographic features that are robust to scatter and is trained using density simulations synthesized as solutions to hydrodynamic equations of state. The proposed reconstruction pipeline learns and enforces physics-based assumptions of hydrodynamics and shock physics to constrain the final reconstruction to a space ofphysically admissible solutions.</p>