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Electron-neutrino charged-current interactions with xenon nuclei were modeled in the nEXO neutrinoless double-beta decay detector (~5-tonne, 90% ${}^{136}$Xe, 10% ${}^{134}$Xe) to evaluate its sensitivity to supernova neutrinos. Predictions for event rates and detectable signatures were modeled using the MARLEY event generator. We find good agreement between MARLEY's predictions and existing theoretical calculations of the inclusive cross sections at supernova neutrino energies. The interactions modeled by MARLEY were simulated within the nEXO simulation framework and were run through an example reconstruction algorithm to determine the detector's efficiency for reconstructing these events. The simulated data, incorporating the detector response, were used to study the ability of nEXO to reconstruct the incident electron-neutrino spectrum and these results were extended to a larger xenon detector of the same isotope enrichment. We estimate that nEXO will be able to observe electron-neutrino interactions with xenon from supernovae as far as 5 to 8 kpc from earth, while the ability to reconstruct incident electron-neutrino spectrum parameters from observed interactions in nEXO is limited to closer supernovae., Comment: 17 pages, 16 figures

Cystinuria is one of various disorders that cause biomineralization in the urinary system, including bladder stone formation in humans. It is most prevalent in children and adolescents and more aggressive in males. There is no cure, and only limited disease management techniques help to solubilize the stones. Recurrence, even after treatment, occurs frequently. Other than a buildup of cystine, little is known about factors involved in the formation, expansion, and recurrence of these stones. This study sought to define the growth of bladder stones, guided by micro-computed tomography imaging, and to profile dynamic stone proteome changes in a cystinuria mouse model. After bladder stones developed in vivo, they were harvested and separated into four developmental stages (sand, small, medium and large stone), based on their size. Data-dependent and data-independent acquisitions allowed deep profiling of stone proteomics. The proteomic signatures and pathways illustrated major changes as the stones grew. Stones initiate from a small nidus, grow outward, and show major enrichment in ribosomal proteins and factors related to coagulation and platelet degranulation, suggesting a major dysregulation in specific pathways that can be targeted for new therapeutic options.

Background: Severe COVID-19 induced acute respiratory distress syndrome (ARDS) often requires extracorporeal membrane oxygenation (ECMO). Recent German health insurance data revealed low ICU survival rates. Patient characteristics and experience of the ECMO center may determine intensive care unit (ICU) survival. The current study aimed to identify factors affecting ICU survival of COVID-19 ECMO patients. Methods: 673 COVID-19 ARDS ECMO patients treated in 26 centers between January 1st 2020 and March 22nd 2021 were included. Data on clinical characteristics, adjunct therapies, complications, and outcome were documented. Block wise logistic regression analysis was applied to identify variables associated with ICU-survival. Results: Most patients were between 50 and 70 years of age. PaO2/FiO(2) ratio prior to ECMO was 72 mmHg (IQR: 58-99). ICU survival was 31.4%. Survival was significantly lower during the 2nd wave of the COVID-19 pandemic. A subgroup of 284 (42%) patients fulfilling modified EOLIA criteria had a higher survival (38%) (p = 0.0014, OR 0.64 (CI 0.41-0.99)). Survival differed between low, intermediate, and high-volume centers with 20%, 30%, and 38%, respectively (p = 0.0024). Treatment in high volume centers resulted in an odds ratio of 0.55 (CI 0.28-1.02) compared to low volume centers. Additional factors associated with survival were younger age, shorter time between intubation and ECMO initiation, BMI > 35 (compared to < 25), absence of renal replacement therapy or major bleeding/thromboembolic events. Conclusions: Structural and patient-related factors, including age, comorbidities and ECMO case volume, determined the survival of COVID-19 ECMO. These factors combined with a more liberal ECMO indication during the 2nd wave may explain the reasonably overall low survival rate. Careful selection of patients and treatment in high volume ECMO centers was associated with higher odds of ICU survival.

A principal component analysis (PCA) and artificial neural network (ANN) based chemistry tabulation approach is presented. ANNs are used to map the thermochemical state onto a low-dimensional manifold consisting of five control variables that have been identified using PCA. Three canonical configurations are considered to train the PCA-ANN model: a series of homogeneous reactors, a nonpremixed flamelet, and a two-dimensional lifted flame. The performance of the model in predicting the thermochemical manifold of a spatially-developing turbulent jet flame in diesel engine thermochemical conditions is a priori evaluated using direct numerical simulation (DNS) data. The PCA-ANN approach is compared with a conventional tabulation approach (tabulation using ad hoc defined control variables and linear interpolation). The PCA-ANN model provides higher accuracy and requires several orders of magnitude less memory. These observations indicate that the PCA-ANN model is superior for chemistry tabulation, especially for modelling complex chemistries that present multiple combustion modes as observed in diesel combustion. The performance of the PCA-ANN model is then compared to the optimal estimator, i.e. the conditional mean from the DNS. The results indicate that the PCA-ANN model gives high prediction accuracy, comparable to the optimal estimator, especially for major species and the thermophysical properties. Higher errors are observed for the minor species and reaction rate predictions when compared to the optimal estimator. It is shown that the prediction of minor species and reaction rates can be improved by using training data that exhibits a variation of parameters as observed in the turbulent flame. The output of the ANN is analysed to assess mass conservation. It is observed that the ANN incurs a mean absolute error of 0.05% in mass conservation. Furthermore, it is demonstrated that this error can be reduced by modifying the cost function of the ANN to penalise for dev

A principal component analysis (PCA) and artificial neural network (ANN) based chemistry tabulation approach is presented. ANNs are used to map the thermochemical state onto a low-dimensional manifold consisting of five control variables that have been identified using PCA. Three canonical configurations are considered to train the PCA-ANN model: a series of homogeneous reactors, a nonpremixed flamelet, and a two-dimensional lifted flame. The performance of the model in predicting the thermochemical manifold of a spatially-developing turbulent jet flame in diesel engine thermochemical conditions is a priori evaluated using direct numerical simulation (DNS) data. The PCA-ANN approach is compared with a conventional tabulation approach (tabulation using ad hoc defined control variables and linear interpolation). The PCA-ANN model provides higher accuracy and requires several orders of magnitude less memory. These observations indicate that the PCA-ANN model is superior for chemistry tabulation, especially for modelling complex chemistries that present multiple combustion modes as observed in diesel combustion. The performance of the PCA-ANN model is then compared to the optimal estimator, i.e. the conditional mean from the DNS. The results indicate that the PCA-ANN model gives high prediction accuracy, comparable to the optimal estimator, especially for major species and the thermophysical properties. Higher errors are observed for the minor species and reaction rate predictions when compared to the optimal estimator. It is shown that the prediction of minor species and reaction rates can be improved by using training data that exhibits a variation of parameters as observed in the turbulent flame. The output of the ANN is analysed to assess mass conservation. It is observed that the ANN incurs a mean absolute error of 0.05% in mass conservation. Furthermore, it is demonstrated that this error can be reduced by modifying the cost function of the ANN to penalise for dev

Increasing energy demand and stringent pollution norms necessitate the design of engines with higher efficiency and lower emission levels. A fundamental understanding of combustion in diesel engines can enable the design of such engines. Of special interest is the lift-off height, the distance between the injector orifice and the start of the high-temperature reaction zone. The lift-off height controls the amount of mixing between fuel and oxidiser before combustion and hence combustion efficiency and pollutant levels. A comprehensive understanding of the flame stabilisation mechanism, which determines the lift-off height, is thus critical. Arriving at this understanding is not trivial due to the high-temperature and high-pressure conditions present in diesel engines which limit the capabilities of experiments. Consequently, important aspects such as the flame structure and its stabilisation mechanism are not well understood. With the aim to elucidate the flame structure and stabilisation mechanism in diesel engine conditions, direct numerical simulations are performed in this thesis. The ambient conditions are matched to the Engine Combustion Network’s Spray A flame. A canonical configuration of two-dimensional laminar lifted flame is considered first. The response of the flames to inlet velocity and scalar dissipation rate is studied. The flames transition from attached, to lifted propagation stabilised to lifted ignition stabilised upon increasing the inlet velocity. A complex multibrachial flame structure with up to five branches is observed. The propagation stabilised and ignition stabilised flames exhibit characteristically different structure, transport budget and displacement speeds. These observations are then employed to identify the stabilisation mechanism of a three-dimensional spatially developing turbulent round jet flame. The turbulent flame structure, transport budget and the displacement speed at the flame base closely resemble the characteristics o

Rich premixed turbulent n-dodecane/air flames at diesel engine conditions are analyzed using direct numerical simulations. The conditions correspond to a parametric variation of the Engine Combustion Network Spray A (pressure 60 atm; oxidizer oxygen level and temperature 21% and 900 K, respectively; fuel temperature 363 K). Three simulations with equivalence ratios of 3, 5, and 7 are performed with a Karlovitz number (Ka, based on flame time) of order 100 to match the estimated Ka of the rich premixed combustion region in Spray A. At these conditions, the reference laminar flames exhibit a complex structure which involves both low-temperature chemistry (LTC) and high-temperature chemistry over a wide range of length scales. In the presence of turbulence, the flame structure is strongly affected in physical space and the reaction zone exhibits a very complex structure in which broken, distributed, and thin regions co-exist, especially for the leanest case. However, the contribution of the LTC pathway is only weakly affected by turbulence. In progress variable space, the mean flame structure, including the chemical source terms, is found to match remarkably well that of the corresponding unity Lewis number laminar flame, particularly for the 3 and 5 cases. This behavior is attributed to the strong turbulent mixing occurring throughout the flames/reaction zones, which suppresses differential diffusion effects. Nevertheless, large conditional fluctuations around the mean chemical source terms are identified. These are found to correlate very well with radical species mass fractions such as OH. In addition, a similar functional dependence is obtained from counterflow laminar flames. As such, it appears from these results that laminar flame models have a potential to be used to represent the thermochemical state of rich premixed turbulent flames under diesel engine conditions.

The engine combustion network (ECN) Spray A is modelled using the Reynolds-averaged Navier-Stokes-transported probability density function (RANS-TPDF) approach to validate the application of a new multiple mapping conditioning (MMC) mixing model to multiphase reactive flows. The composition TPDF equations are solved using a Lagrangian stochastic approach and the spray is modelled with a discrete particle approach. The model is first validated under non-reacting conditions (at 900 K) using experimental mixture-fraction data. Reactive simulations are then performed for three different ambient temperatures (800, 900, 1100 K) and oxygen concentrations (13, 15, 21%) at an ambient density of 22.8 kg/m3. The MMC mixing model is compared with the interaction by exchange with the mean (IEM) mixing model. The ignition delay predictions are not sensitive to the mixing model and are predicted well by both the mixing models under all the tested ambient conditions. The IEM model overpredicts the flame lift-off length (FLOL) at high temperature and high oxygen conditions with a mixing constant Cφ=2. The MMC model with Cφ=2 and a target correlation coefficient rt=0.935 between the mixture fraction and a reference variable used to condition mixing predicts good FLOL under all the conditions except 800 K. It is demonstrated that the lift-off length is controllable by changing the target correlation coefficient, while Cφ and therefore the mixing fields are held fixed. In comparison to the MMC model, the IEM model predicts a higher variance of temperature conditioned on mixture fraction near the flame base owing to its lacking the property of localness. The mixing distance between the notional TPDF particles in the composition space is also higher with the IEM model and it is demonstrated that by changing rt, different levels of mixing locality can be achieved.

In the present work, nonpremixed temporally evolving planar spray jet flames are simulated using both direct numerical simulation (DNS) and the composition transported probability density function (TPDF) method. The objective is to assess the performance of various mixing and evaporation source term distribution models which are required to close the PDF transport equation in spray flames. Quantities which would normally be provided to the TPDF solver by spray models and turbulence models are provided from the DNS: the mean flow velocity, turbulent diffusivity, mixing frequency, and cell-mean evaporation source term. Two cases with different Damköhler numbers (Da) are considered. The low Da case (Da-) features extinction followed by reignition while extinction in the high Da case (Da+) is insignificant. The TPDF modelling considers two mixing models: interaction by exchange with the mean (IEM) and Euclidean minimum spanning trees (EMST). Three models for distribution of the evaporation source terms are considered: EQUAL which distributes them in proportion to notional particles' mass weight, NEW which creates new particles of pure fuel, and SAT which distributes the sources preferentially to notional particles close to saturation. It is found that the IEM model overpredicts the extinction when used with any evaporation model for both Da- and Da+ cases. The EMST model captures well the trend for extinction and reignition for the Da- case when it is coupled with the EQUAL evaporation model, but it overpredicts the extinction when coupled with the NEW or SAT evaporation model. For the Da+ case, all evaporation models reasonably capture the flame dynamics when coupled with EMST. The flame temperature in the mixture fraction space was examined to further assess the model performance. In general the EMST model results in narrow PDFs with little conditional fluctuation, while the IEM model produces bimodal PDFs with burning and partial extinction branches.

The use of color-ratio pyrometry (CRP) methods, with variable or prescribed soot content (KL) to image flame–wall interactions was examined, with results compared with that obtained using the more mature two-color pyrometry (TCP) technique. The CRP and TCP methods were applied to flame–wall impingement images recorded in a optically-accessible constant volume combustion chamber (CVCC) under compression-ignition (CI) engine conditions. Good correlation in the result trends were observed for the CRP method with fixed KL output and that generated using TCP. Slight discrepancies in the predicted absolute temperature values were observed, which were linked to the difference in the KL value prescribed to the CRP method, and the KL value predicted using TCP. No useful output was obtained with CRP method with variable soot output because of channel noise. A simplified flame transparency modeling was performed to assess the inherent errors associated with the pyrometry methods. The results indicated that the uncertainties arising from the fixing of the KL output appeared acceptable.

© 2018 Energy Institute The use of color-ratio pyrometry (CRP) methods, with variable or prescribed soot content (KL) to image flame–wall interactions was examined, with results compared with that obtained using the more mature two-color pyrometry (TCP) technique. The CRP and TCP methods were applied to flame–wall impingement images recorded in a optically-accessible constant volume combustion chamber (CVCC) under compression-ignition (CI) engine conditions. Good correlation in the result trends were observed for the CRP method with fixed KL output and that generated using TCP. Slight discrepancies in the predicted absolute temperature values were observed, which were linked to the difference in the KL value prescribed to the CRP method, and the KL value predicted using TCP. No useful output was obtained with CRP method with variable soot output because of channel noise. A simplified flame transparency modeling was performed to assess the inherent errors associated with the pyrometry methods. The results indicated that the uncertainties arising from the fixing of the KL output appeared acceptable.

© 2018 The Combustion Institute. Laminar one-dimensional (1D) flames in a stagnation flow stabilised at a wall are used to study flame-wall interaction under diesel engine conditions. The thermochemical conditions correspond to that of the Engine Combustion Network (ECN) Spray A reference case. A range of inflow velocities is considered, where the lowest inflow velocity is chosen such that the flame is detached from the inlet. The presence of a wall is shown to have a significant impact on the flame structure and emission formation. The 1D flame and homogeneous reactor results exhibit two distinct reaction zones due to low- and high-temperature chemistry (LTC and HTC, respectively). The burner-stabilised flames are overall dominated by autoignition for all inflow velocities. For the impinging jet flames, the response of the LTC reaction zone follows closely that of the burner-stabilised flames up to relatively high inflow velocities. The HTC reaction zone, however, deviates strongly from the burner-stabilised flames, already at low inflow velocities and quenches at high inflow velocities. A budget analysis revealed a strong contribution from diffusion in the HTC reaction zone, resulting in an increasing importance of deflagrative combustion as opposed to autoignition. This trend was attributed to enhanced strain rates at higher inlet velocity leading to higher gradients. Wall heat transfer was also investigated. The highest wall heat transfer rates were observed for mixtures between . Φ=1.0 and Φ=1.5 and for inlet velocities just below the quenching limit. This was attributed jointly to the higher peak product temperatures for these mixtures and to their enhanced resilience to quenching under strain which leads to higher temperature gradients at the wall just before quenching. NO formation was studied. The highest NO formation was observed near . Φ=1.0, though the response to strain rate was different for stoichiometric and rich mixtures, which was attributed to dif

Post injection is a multiple-injection strategy that is commonly used as a particulate matter control measure to reduce soot emissions, yet the mechanisms and the interactions between the main and post injections are only vaguely understood. For this work, experiments were performed to assess the effects of varying dwell time between the main and post injections in a compression-ignition (CI) engine environment simulated using a constant-volume combustion chamber. The ambient density, bulk temperature, and oxygen concentration used for this work were controlled at 19.4 kg/m3, 900 K, and 15 vol % O2, respectively. A canola oil-based biodiesel was tested and injected at a fixed injection pressure of 100 MPa into the simulated CI engine environment. A mass ratio of 80%-20% was maintained between the main and post injections, with the dwell time between the injections varied from 1.5 to 2.5 ms. Comparative measurements were performed using the same fuel and injection schedules, but at a higher ambient gas temperature condition of 1100 K. Optical diagnostics methods, including diffused-back illumination and high-speed flame luminosity imaging, were used to assess the spray and combustion processes of the post injection test case. Under the conditions of this work, it was found that the ignition delays, ignition locations, and flame lift-off lengths of the post injection flames are consistently shorter than those of the main injections, with the variations influenced by the extent of the interaction of the post injection with the combustion products from the main injection. A two-color pyrometry technique was also used to measure the soot temperature and soot concentration factor information on the main-post injection cases. The data revealed a greater interaction between the main and post injections resulted in a more rapid development of the soot zone of the post injection with higher temperature after ignition. The distribution of the most probable soot concentration f

Combustion systems such as internal combustion engines and gas turbine engines are expected to remain as the primary energy conversion approaches for the foreseeable future. There is a need for better combustion models to design engines with higher efficiency and lower pollutant emissions. The transported probability density function (TPDF) method is appealing since the chemical source term is not approximated and it can be applied to multiple modes of combustion and processes having wide range of time scales. However, the TPDF method requires a mixing model to represent the transport in high-dimensional composition space. The objective of this thesis is to develop a novel variant of multiple mapping conditioning (MMC) mixing model for nonpremixed combustion where a reference variable is statistically similar to that of the mixture fraction. This statistical similarity renders the new model physically more intuitive and numerically more stable than the original MMC mixing model.This thesis is a combination of statistics, computational mathematics and combustion science. Firstly, the new MMC model is developed and validated against ideal flow cases. The model constant settings are derived under homogeneous isotropic turbulence conditions and Monte Carlo simulations are performed to test its applicability to simplified cases. It is observed that the decay rate of the unconditional and conditional variance can be controlled independently. To demonstrate the robustness of the model constants for different flow configurations, the model constant settings are derived for a canonical test case with a mean scalar gradient. The localness property of the new model is further shown in a flamelet combustion test case. Secondly, the model is applied successfully to single-phase, nonpremixed, inhomogeneous turbulent flames, namely Sandia flames D-F. Good agreement between the experimental data and numerical simulations is reported and the model is shown to be able to capture the

The Engine Combustion Network (ECN) Spray A target case corresponds to high-pressure liquid fuel injection in conditions relevant to diesel engines. Following the procedure by Wehrfritz et al. (2016), we utilize large-eddy simulation (LES) and flamelet generated manifold (FGM) methods to carry out an injection pressure sensitivity study for Spray A at 50, 100 and 150 MPa. Comparison with experiments is shown for both non-reacting and reacting conditions. Validation results in non-reacting conditions indicate relatively good agreement between the present LES and experimental data, with some deviation in mixture fraction radial profiles. In reacting conditions, the simulated flame lift-off length (FLOL) increases with injection pressure, deviating from the experiments by 4–14%. Respectively, the ignition delay time (IDT) decreases with increasing injection pressure and it is underpredicted in the simulations by 10–20%. Analysis of the underlying chemistry manifold implies that the observed discrepancies can be explained by the differences between experimental and computational mixing processes.

Post injection is a multiple-injection strategy that is commonly used as a particulate matter control measure to reduce soot emissions, yet the mechanisms and the interactions between the main and post injections are only vaguely understood. For this work, experiments were performed to assess the effects of varying dwell time between the main and post injections in a compression-ignition (CI) engine environment simulated using a constant-volume combustion chamber. The ambient density, bulk temperature, and oxygen concentration used for this work were controlled at 19.4 kg/m3, 900 K, and 15 vol % O2, respectively. A canola oil-based biodiesel was tested and injected at a fixed injection pressure of 100 MPa into the simulated CI engine environment. A mass ratio of 80%-20% was maintained between the main and post injections, with the dwell time between the injections varied from 1.5 to 2.5 ms. Comparative measurements were performed using the same fuel and injection schedules, but at a higher ambient gas temperature condition of 1100 K. Optical diagnostics methods, including diffused-back illumination and high-speed flame luminosity imaging, were used to assess the spray and combustion processes of the post injection test case. Under the conditions of this work, it was found that the ignition delays, ignition locations, and flame lift-off lengths of the post injection flames are consistently shorter than those of the main injections, with the variations influenced by the extent of the interaction of the post injection with the combustion products from the main injection. A two-color pyrometry technique was also used to measure the soot temperature and soot concentration factor information on the main-post injection cases. The data revealed a greater interaction between the main and post injections resulted in a more rapid development of the soot zone of the post injection with higher temperature after ignition. The distribution of the most probable soot concentration f

The Engine Combustion Network (ECN) Spray A target case corresponds to high-pressure liquid fuel injection in conditions relevant to diesel engines. Following the procedure by Wehrfritz et al. (2016), we utilize large-eddy simulation (LES) and flamelet generated manifold (FGM) methods to carry out an injection pressure sensitivity study for Spray A at 50, 100 and 150 MPa. Comparison with experiments is shown for both non-reacting and reacting conditions. Validation results in non-reacting conditions indicate relatively good agreement between the present LES and experimental data, with some deviation in mixture fraction radial profiles. In reacting conditions, the simulated flame lift-off length (FLOL) increases with injection pressure, deviating from the experiments by 4–14%. Respectively, the ignition delay time (IDT) decreases with increasing injection pressure and it is underpredicted in the simulations by 10–20%. Analysis of the underlying chemistry manifold implies that the observed discrepancies can be explained by the differences between experimental and computational mixing processes.

Post injection is a multiple-injection strategy that is commonly used as a particulate matter control measure to reduce soot emissions, yet the mechanisms and the interactions between the main and post injections are only vaguely understood. For this work, experiments were performed to assess the effects of varying dwell time between the main and post injections in a compression-ignition (CI) engine environment simulated using a constant-volume combustion chamber. The ambient density, bulk temperature, and oxygen concentration used for this work were controlled at 19.4 kg/m3, 900 K, and 15 vol % O2, respectively. A canola oil-based biodiesel was tested and injected at a fixed injection pressure of 100 MPa into the simulated CI engine environment. A mass ratio of 80%-20% was maintained between the main and post injections, with the dwell time between the injections varied from 1.5 to 2.5 ms. Comparative measurements were performed using the same fuel and injection schedules, but at a higher ambient gas temperature condition of 1100 K. Optical diagnostics methods, including diffused-back illumination and high-speed flame luminosity imaging, were used to assess the spray and combustion processes of the post injection test case. Under the conditions of this work, it was found that the ignition delays, ignition locations, and flame lift-off lengths of the post injection flames are consistently shorter than those of the main injections, with the variations influenced by the extent of the interaction of the post injection with the combustion products from the main injection. A two-color pyrometry technique was also used to measure the soot temperature and soot concentration factor information on the main-post injection cases. The data revealed a greater interaction between the main and post injections resulted in a more rapid development of the soot zone of the post injection with higher temperature after ignition. The distribution of the most probable soot concentration f

In the present study, unsteady flamelet calculations were used to compare chemical mechanisms for n-dodecane at thermochemical conditions corresponding to the Engine Combustion Network Spray A reference case. The calculations were carried out for a broad range of scalar dissipation rates and the results were anal-ysed in terms of ignition delay times and location in composition space. The results indicate only a weak dependency of the ignition delay times on the scalar dissipation rate, up to a certain value for which ignition cannot occur any more (χign). While this behaviour is consistent for all investigated mechanisms, the value of χign varies between them. A more detailed investigation of the effect of mixing showed a significant broadening of the heat release profile in composition space. Consequently, the ignition location shifts to much richer mixtures, even for low scalar dissipation rates. This shift is predicted for all mechanisms, though the extend varies between the mechanisms. The results reveal valuable information with respect to the ignition characteristics of each mechanism, but also indicate that further analysis is needed.

The further development of compression-ignition engines would be facilitated by the availability of sufficiently general combustion models capable of accounting for all relevant in-cylinder processes, which include multi-mode combustion, fast and slow kinetics, and significant interactions of turbulence and chemistry. The transported probability density function approach (TPDF) is one method that, in principle, can account for all these phenomena. The TPDF approach requires a model for molecular mixing to represent transport in composition space. Experience with nonpremixed and premixed flames has shown that the property of localness (i.e. mixing occurring between fluid regions having similar compositions) is beneficial for model performance. On the basis of this observation, a novel multiple mapping conditioning (MMC) based mixing model has been proposed recently in which mixing is conditioned on a reference scalar that is statistically similar, but not identical to mixture fraction. The model has been found to perform well in the context of single-phase nonpremixed combustion due to its localness property. In the present work, the MMC mixing model is validated against the non-reacting Engine Combustion Network (ECN) spray-A case to test its applicability to multi-phase flows. Mass consistency is a major issue in PDF algorithms and a robust coupling between the spray and gas field ensures that the mass conservation law is not violated. The simulation results are validated using liquid length, vapour penetration and mixture-fraction field data. The degree of control over the obtained localness is assessed by comparing statistics of mixture fraction and the reference scalar.

We present results from direct numerical simulations (DNS) of laminar lifted two-dimensional (2D) n-dodecane flames at thermochemical conditions corresponding to the Engine Combustion Network (ECN) target flame known as Spray A, which canonically represents conditions in a diesel engine. Simulations were performed for three distinct inlet velocities. Results indicate that the flames present a multibrachial structure. The number of branches depends on the inlet velocity and changes from five branches for the 2.5 m/s case to four branches for the 0.6 m/s case. For the 2.5 m/s case the flame consists of a typical triple flame (consisting of a diffusion, a rich premixed, and a lean premixed flames) with additional upstream low temperature chemistry (LTC) and high temperature chemistry (HTC) branches. With decreasing inlet velocity, the triple flame moves closer to the upstream HTC branch, ultimately overtaking it for an inlet velocity of 0.6 m/s. This indicates that the triple flame propagation velocity is O(1 m/s). These results provide an important baseline to compare against a 3D turbulent Spray A flame and investigate how turbulence changes the flame structure and stabilisation mechanism.

Als Graphen bezeichnet man eine einzelne freistehende Lage des Schichtkristalls Graphit. Im Gegensatz zur mechanischen Isolation von Graphit bietet die Züchtung auf Siliziumkarbid eine Methode zur großflächigen Herstellung von Graphen. Aufgrund der besonderen physikalischen Eigenschaften werden für Graphen viele verschieden Einsatzmöglichkeiten in diversen Bereichen prognostiziert. Mit seiner hohen Ladungsträgerbeweglichkeit ist Graphen besonders als Kanalmaterial für Feldeffekttransistoren (FET) interessant. Allerdings muss hierfür unter anderem ein geeignetes FET-Isolatormaterial gefunden werden. In dieser Arbeit wird eine detaillierte, theoretische Beschreibung der Graphen-FETs vorgestellt, die es erlaubt die steuerspannungsabhängige Hall-Konstante zu berechnen. Mit der dadurch möglichen Analyse können wichtige Kenngrößen, wie z. B. die Grenzflächenzustandsdichte des Materialsystems bestimmt werden. Außerdem wurden zwei Methoden zur Isolatorabscheidung auf Graphen untersucht. Siliziumnitrid, welches mittels plasmaangeregter Gasphasenabscheidung aufgetragen wurde, zeichnet sich durch seine n-dotierende Eigenschaft aus. Damit ist es vor allem für quasi-freistehendes Graphen auf Siliziumkarbid interessant. Bei der zweiten Methode handelt es sich um einen atomaren Schichtabscheidungsprozess, der ohne eine Saatschicht auskommt. An beiden Graphen- Isolator-Kombinationen wurde die neue Charakterisierung mittels der Hall-Datenanalyse angewandt.:1 Einleitung 2 Graphen 3 Methoden 4 Die Hall-Konstante von Graphen 5 Siliziumnitrid als Dielektrikum für Graphentransistoren 6 Aluminiumoxid auf epitaktischem Graphen 7 Zusammenfassung A Anhang

Als Graphen bezeichnet man eine einzelne freistehende Lage des Schichtkristalls Graphit. Im Gegensatz zur mechanischen Isolation von Graphit bietet die Züchtung auf Siliziumkarbid eine Methode zur großflächigen Herstellung von Graphen. Aufgrund der besonderen physikalischen Eigenschaften werden für Graphen viele verschieden Einsatzmöglichkeiten in diversen Bereichen prognostiziert. Mit seiner hohen Ladungsträgerbeweglichkeit ist Graphen besonders als Kanalmaterial für Feldeffekttransistoren (FET) interessant. Allerdings muss hierfür unter anderem ein geeignetes FET-Isolatormaterial gefunden werden. In dieser Arbeit wird eine detaillierte, theoretische Beschreibung der Graphen-FETs vorgestellt, die es erlaubt die steuerspannungsabhängige Hall-Konstante zu berechnen. Mit der dadurch möglichen Analyse können wichtige Kenngrößen, wie z. B. die Grenzflächenzustandsdichte des Materialsystems bestimmt werden. Außerdem wurden zwei Methoden zur Isolatorabscheidung auf Graphen untersucht. Siliziumnitrid, welches mittels plasmaangeregter Gasphasenabscheidung aufgetragen wurde, zeichnet sich durch seine n-dotierende Eigenschaft aus. Damit ist es vor allem für quasi-freistehendes Graphen auf Siliziumkarbid interessant. Bei der zweiten Methode handelt es sich um einen atomaren Schichtabscheidungsprozess, der ohne eine Saatschicht auskommt. An beiden Graphen- Isolator-Kombinationen wurde die neue Charakterisierung mittels der Hall-Datenanalyse angewandt.:1 Einleitung 2 Graphen 3 Methoden 4 Die Hall-Konstante von Graphen 5 Siliziumnitrid als Dielektrikum für Graphentransistoren 6 Aluminiumoxid auf epitaktischem Graphen 7 Zusammenfassung A Anhang

Als Graphen bezeichnet man eine einzelne freistehende Lage des Schichtkristalls Graphit. Im Gegensatz zur mechanischen Isolation von Graphit bietet die Züchtung auf Siliziumkarbid eine Methode zur großflächigen Herstellung von Graphen. Aufgrund der besonderen physikalischen Eigenschaften werden für Graphen viele verschieden Einsatzmöglichkeiten in diversen Bereichen prognostiziert. Mit seiner hohen Ladungsträgerbeweglichkeit ist Graphen besonders als Kanalmaterial für Feldeffekttransistoren (FET) interessant. Allerdings muss hierfür unter anderem ein geeignetes FET-Isolatormaterial gefunden werden. In dieser Arbeit wird eine detaillierte, theoretische Beschreibung der Graphen-FETs vorgestellt, die es erlaubt die steuerspannungsabhängige Hall-Konstante zu berechnen. Mit der dadurch möglichen Analyse können wichtige Kenngrößen, wie z. B. die Grenzflächenzustandsdichte des Materialsystems bestimmt werden. Außerdem wurden zwei Methoden zur Isolatorabscheidung auf Graphen untersucht. Siliziumnitrid, welches mittels plasmaangeregter Gasphasenabscheidung aufgetragen wurde, zeichnet sich durch seine n-dotierende Eigenschaft aus. Damit ist es vor allem für quasi-freistehendes Graphen auf Siliziumkarbid interessant. Bei der zweiten Methode handelt es sich um einen atomaren Schichtabscheidungsprozess, der ohne eine Saatschicht auskommt. An beiden Graphen- Isolator-Kombinationen wurde die neue Charakterisierung mittels der Hall-Datenanalyse angewandt.:1 Einleitung 2 Graphen 3 Methoden 4 Die Hall-Konstante von Graphen 5 Siliziumnitrid als Dielektrikum für Graphentransistoren 6 Aluminiumoxid auf epitaktischem Graphen 7 Zusammenfassung A Anhang

Als Graphen bezeichnet man eine einzelne freistehende Lage des Schichtkristalls Graphit. Im Gegensatz zur mechanischen Isolation von Graphit bietet die Züchtung auf Siliziumkarbid eine Methode zur großflächigen Herstellung von Graphen. Aufgrund der besonderen physikalischen Eigenschaften werden für Graphen viele verschieden Einsatzmöglichkeiten in diversen Bereichen prognostiziert. Mit seiner hohen Ladungsträgerbeweglichkeit ist Graphen besonders als Kanalmaterial für Feldeffekttransistoren (FET) interessant. Allerdings muss hierfür unter anderem ein geeignetes FET-Isolatormaterial gefunden werden. In dieser Arbeit wird eine detaillierte, theoretische Beschreibung der Graphen-FETs vorgestellt, die es erlaubt die steuerspannungsabhängige Hall-Konstante zu berechnen. Mit der dadurch möglichen Analyse können wichtige Kenngrößen, wie z. B. die Grenzflächenzustandsdichte des Materialsystems bestimmt werden. Außerdem wurden zwei Methoden zur Isolatorabscheidung auf Graphen untersucht. Siliziumnitrid, welches mittels plasmaangeregter Gasphasenabscheidung aufgetragen wurde, zeichnet sich durch seine n-dotierende Eigenschaft aus. Damit ist es vor allem für quasi-freistehendes Graphen auf Siliziumkarbid interessant. Bei der zweiten Methode handelt es sich um einen atomaren Schichtabscheidungsprozess, der ohne eine Saatschicht auskommt. An beiden Graphen- Isolator-Kombinationen wurde die neue Charakterisierung mittels der Hall-Datenanalyse angewandt.:1 Einleitung 2 Graphen 3 Methoden 4 Die Hall-Konstante von Graphen 5 Siliziumnitrid als Dielektrikum für Graphentransistoren 6 Aluminiumoxid auf epitaktischem Graphen 7 Zusammenfassung A Anhang

Graphene field effect transistors (GFETs) are considered as a candidate for future high-frequency applications. For their realization, the optimal combination of substrate, graphene preparation, and insulator deposition and composition is required.This optimization must be based on an in-depth characterization of the obtained graphene insulator metal (GIM) stack. Hall effect measurements are frequently employed to study such systems, thereby focussing primarily on the charge carrier mobility. In this work we show how an analysis of the sheet Hall coefficient can reveal further important properties of the GIM stack, like, e.g., the interface trap density and the spacial charge inhomogeneity. To that end, we provide an extensive description of the GIM diode, which leads to an accurate calculation of the sheet Hall coefficient dependent on temperature and gate voltage. The gate dependent inverse sheet Hall coefficient is discussed in detail before we introduce the concept of an equivalent temperature, which is a measure of the spacial charge inhomogeneity. In order to test the concept, we apply it to evaluate already measured Hall data taken from the literature. This evaluation allows us to determine the Drude mobility, even at the charge neutrality point, which is inaccessible with a simple one band Hall mobility analysis, and to shed light on the spacial charge inhomogeneity. The formalism is easily adaptable and provides experimentalists a powerful tool for the characterization of their graphene field effect devices.

Graphene field effect transistors (GFETs) are considered as a candidate for future high-frequency applications. For their realization, the optimal combination of substrate, graphene preparation, and insulator deposition and composition is required.This optimization must be based on an in-depth characterization of the obtained graphene insulator metal (GIM) stack. Hall effect measurements are frequently employed to study such systems, thereby focussing primarily on the charge carrier mobility. In this work we show how an analysis of the sheet Hall coefficient can reveal further important properties of the GIM stack, like, e.g., the interface trap density and the spacial charge inhomogeneity. To that end, we provide an extensive description of the GIM diode, which leads to an accurate calculation of the sheet Hall coefficient dependent on temperature and gate voltage. The gate dependent inverse sheet Hall coefficient is discussed in detail before we introduce the concept of an equivalent temperature, which is a measure of the spacial charge inhomogeneity. In order to test the concept, we apply it to evaluate already measured Hall data taken from the literature. This evaluation allows us to determine the Drude mobility, even at the charge neutrality point, which is inaccessible with a simple one band Hall mobility analysis, and to shed light on the spacial charge inhomogeneity. The formalism is easily adaptable and provides experimentalists a powerful tool for the characterization of their graphene field effect devices.

Graphene field effect transistors (GFETs) are considered as a candidate for future high-frequency applications. For their realization, the optimal combination of substrate, graphene preparation, and insulator deposition and composition is required.This optimization must be based on an in-depth characterization of the obtained graphene insulator metal (GIM) stack. Hall effect measurements are frequently employed to study such systems, thereby focussing primarily on the charge carrier mobility. In this work we show how an analysis of the sheet Hall coefficient can reveal further important properties of the GIM stack, like, e.g., the interface trap density and the spacial charge inhomogeneity. To that end, we provide an extensive description of the GIM diode, which leads to an accurate calculation of the sheet Hall coefficient dependent on temperature and gate voltage. The gate dependent inverse sheet Hall coefficient is discussed in detail before we introduce the concept of an equivalent temperature, which is a measure of the spacial charge inhomogeneity. In order to test the concept, we apply it to evaluate already measured Hall data taken from the literature. This evaluation allows us to determine the Drude mobility, even at the charge neutrality point, which is inaccessible with a simple one band Hall mobility analysis, and to shed light on the spacial charge inhomogeneity. The formalism is easily adaptable and provides experimentalists a powerful tool for the characterization of their graphene field effect devices.

Graphene field effect transistors (GFETs) are considered as a candidate for future high-frequency applications. For their realization, the optimal combination of substrate, graphene preparation, and insulator deposition and composition is required.This optimization must be based on an in-depth characterization of the obtained graphene insulator metal (GIM) stack. Hall effect measurements are frequently employed to study such systems, thereby focussing primarily on the charge carrier mobility. In this work we show how an analysis of the sheet Hall coefficient can reveal further important properties of the GIM stack, like, e.g., the interface trap density and the spacial charge inhomogeneity. To that end, we provide an extensive description of the GIM diode, which leads to an accurate calculation of the sheet Hall coefficient dependent on temperature and gate voltage. The gate dependent inverse sheet Hall coefficient is discussed in detail before we introduce the concept of an equivalent temperature, which is a measure of the spacial charge inhomogeneity. In order to test the concept, we apply it to evaluate already measured Hall data taken from the literature. This evaluation allows us to determine the Drude mobility, even at the charge neutrality point, which is inaccessible with a simple one band Hall mobility analysis, and to shed light on the spacial charge inhomogeneity. The formalism is easily adaptable and provides experimentalists a powerful tool for the characterization of their graphene field effect devices.

The global stability of confined wakes is studied numerically, using two-dimensionallinear global modes and nonlinear direct numerical simulations (DNS).The wake inflow velocity is varied between different amounts of co-flow (basebleed), while the density and viscosity are assumed to be constant everywherein the flow domain. In accordance with previous studies, we find that thefrequencies of both the most unstable linear and the saturated nonlinear globalmode increase with confinement. Here, we also find that for wake Reynoldsnumber Re = 100, the confinement is stabilising. It decreases both the growthrate of the linear and the saturation amplitude of the nonlinear modes. Weconclude that the dampening effect is connected to the streamwise developmentof the base flow, and for higher Reynolds numbers this effect decreases, sincethe flow becomes more parallel. The linear analysis reveals that the criticalwake velocities below which the flow becomes unstable are almost identicalfor unconfined and confined wakes at Re ≈ 400. Also, the present resultsare compared with literature data for an inviscid parallel wake due to thesimilarity of inflow profile. The confined wake is found to be more stable thanits inviscid counterpart, while the unconfined wake is more unstable than theinviscid wake. The main reason to both can be explained by the base flowdevelopment. A detailed comparison of the linear and nonlinear results revealsthat the most unstable linear global mode gives an excellent prediction of theinitial nonlinear behaviour and therefore the stability boundary, in all cases.However, the nonlinear saturated state is quite different in particular for higherReynolds numbers. For Re = 100, the saturated frequency also differs less than5% from the linear frequency, and trends regarding confinement observed in thelinear analysis are confirmed.141, QC 20110530