Design of a GNSS receiver for the ESEO mission

This thesis was carried out inside the ESA's ESEO mission and focus in the design of one of the secondary payloads carried on board the spacecraft: a GNSS receiver for orbit determination. The purpose of this project is to test the technology of the orbit determination in real time applications by using commercial components. The architecture of the receiver includes a custom part, the navigation computer, and a commercial part, the front-end, from Novatel, with COCOM limitation removed, and a GNSS antenna. This choice is motivated by the goal of demonstrating the correct operations in orbit, enabling a widespread use of this technology while lowering the cost and time of the device’s assembly. The commercial front-end performs GNSS signal acquisition, tracking and data demodulation and provides raw GNSS data to the custom computer. This computer processes this raw observables, that will be both transferred to the On-Board Computer and then transmitted to Earth and provided as input to the recursive estimation filter on-board, in order to obtain an accurate positioning of the spacecraft, using the dynamic model. The main purpose of this thesis, is the detailed design and development of the mentioned GNSS receiver up to the ESEO project Critical Design Review, including requirements definition, hardware design and breadboard preliminary test phase design.

Etablierung eines Triple-Kultur-Modells der oberen Atemwege unter Einbeziehung immunkompetenter Zellen

Organophosphate können chronische Lungenerkrankungen und Vergiftungen hervorrufen. Bei der Vergiftung erfolgt eine Immunreaktion, welche noch nicht erforscht ist. In dieser Arbeit wurden Toxizitätsstudien an dendritischen Zellen und einem bronchialen Triple-Kultur-Modell durchgeführt. Dendritische Zellen spielen bei der ersten Immunabwehr in der Lunge eine große Rolle. Aus der Zell-Linie THP-1 und primären Monozyten wurden reife dendritische Zellen differenziert und mittels Durchflusszytometrie und Immunfluoreszenz auf spezifische Zellmarker, wie zum Beispiel CD11c, CD83 oder auch CD209, charakterisiert und etabliert. Durch die Vergiftung der Zellen mit Dimethoat und Chlorpyrifos konnte eine Erhöhung des Zelltodes, die Sekretion von proinflammatorischen Mediatoren, Veränderungen in der Morphologie der Zellen und ein Effekt auf den Proteinkinase-Signalweg festgestellt werden. Spezifische dendritische Zellmarker (CD83, CD209) wurden inhibiert und die Dendriten der Dendritischen Zellen kürzer und beschädigt. Die Schädigung von Chlorpyrifos war erheblich größer, als die bei Dimethoat.rnDie weiteren Toxizitätsstudien wurden an einem bronchialen Triple-Kultur-Modell durchgeführt. Hierzu wurden auf Transwell-Filtermembranen bronchiale Epithelzellen, Fibroblastenzellen und Dendritische Zellen verwendet. Die bronchialen Epithelzellen und Fibroblastenzellen waren hier physiologisch voneinander getrennt, konnten aber durch Poren in der Membran miteinander interagieren. Die Etablierung des Triple-Kultur-Modells erfolgte durch die Untersuchung von Entzündungsprozessen, durch Stimulation mit LPS, TNF-alpha und Interferon-gamma. In der Ko-Kultur konnten Zell-Zell-Kontakt Schädigungen und Erhöhung von proinflammatorischen Markern, wie zum Beispiel IL-1ß, IL-6 oder auch IL-8 gemessen werden. Versuche in der Triple-Kultur zeigten den positiven Effekt von Dendritischen Zellen. Bei höheren Konzentrationsbereichen von Dimethoat und Chlorpyrifos konnte ein Wandern der Zellen zu den geschädigten Zell-Zell-Kontakten nachgewiesen werden. Die Ausschüttung der proinflammatorischen Mediatoren wurde inhibiert, vor allem bei IL-10 war eine deutliche Reduktion, um mehr als 70% messbar. Ebenso konnten Veränderungen in dem Apoptose-Signalblick festgestellt werden. Vor allem anti-apoptotische Proteine wurden nach einer Vergiftung der Triple-Kultur induziert. Interventionsstudien mit Vitamin C zeigten allerdings keinen positiven Effekt.

How different is water crystallization from polymer crystallization under confinement?

Ziel der vorliegenden Dissertation war es, Einblicke in das Kristallisationsverhalten weicher Materie („soft matter“), wie verschiedener Polymere oder Wasser, unter räumlicher Einschränkung („confinement“) zu erlangen. Dabei sollte untersucht werden, wie, weshalb und wann die Kristallisation in nanoporösen Strukturen eintritt. Desweiteren ist Kristallisation weicher Materie in nanoporösen Strukturen nicht nur aus Aspekten der Grundlagenforschung von großem Interesse, sondern es ergeben sich zahlreiche praktische Anwendungen. Durch die gezielte Steuerung der Kristallinität von Polymeren könnten somit Materialien mit verschiendenen mechanischen und optischen Eigenschaften erhalten werden. Desweiteren wurde auch räumlich eingeschränktes Wasser untersucht. Dieses spielt eine wichtige Rolle in der Molekularbiologie, z.B. für das globuläre Protein, und als Wolkenkondensationskeime in der Atmosphärenchemie und Physik. Auch im interstellaren Raum ist eingeschränktes Wasser in Form von Eispartikeln anzutreffen. Die Kristallisation von eingeschränktem Wasser zu verstehen und zu beeinflussen ist letztlich auch für die Haltbarkeit von Baumaterialien wie etwa Zement von großem Interesse.rnUm dies zu untersuchen wird Wasser in der Regel stark abgekühlt und das Kristallisationsverhalten in Abhängigkeit des Volumens untersucht. Dabei wurde beobachtet, dass Mikro- bzw. Nanometer große Volumina erst ab -38 °C bzw. -70 °C kristallisieren. Wasser unterliegt dabei in der Regel dem Prozess der homogenen Nukleation. In der Regel gefriert Wasser aber bei höheren Temperaturen, da durch Verunreinigungen eine vorzeitige, heterogene Nukleation eintritt.rnDie vorliegende Arbeit untersucht die sachdienlichen Phasendiagramme von kristallisierbaren Polymeren und Wasser unter räumlich eingeschränkten Bedingungen. Selbst ausgerichtetes Aluminiumoxid (AAO) mit Porengrößen im Bereich von 25 bis 400 nm wurden als räumliche Einschränkung sowohl für Polymere als auch für Wasser gewählt. Die AAO Nanoporen sind zylindrisch und parallel ausgerichtet. Außerdem besitzen sie eine gleichmäßige Porenlänge und einen gleichmäßigen Durchmesser. Daher eignen sie sich als Modelsystem um Kristallisationsprozesse unter wohldefinierter räumlicher Einschränkung zu untersuchen.rnEs wurden verschiedene halbkristalline Polymere verwendet, darunter Poly(ethylenoxid), Poly(ɛ-Caprolacton) und Diblockcopolymere aus PEO-b-PCL. Der Einfluss der Porengröße auf die Nukleation wurde aus verschiedenen Gesichtspunkten untersucht: (i) Einfluss auf den Nukleationmechanismus (heterogene gegenüber homogener Nukleation), (ii) Kristallorientierung und Kristallinitätsgrad und (iii) Zusammenhang zwischen Kristallisationstemperatur bei homogener Kristallisation und Glasübergangstemperatur.rnEs konnte gezeigt werden, dass die Kristallisation von Polymeren in Bulk durch heterogene Nukleation induziert wird und das die Kristallisation in kleinen Poren hauptsächlich über homogene Nukleation mit reduzierter und einstellbarer Kristallinität verläuft und eine hohe Kristallorientierung aufweist. Durch die AAOs konnte außerdem die kritische Keimgröße für die Kristallisation der Polymere abgeschätzt werden. Schließlich wurde der Einfluss der Polydispersität, von Oligomeren und anderen Zusatzstoffen auf den Nukleationsmechanismus untersucht.rn4rnDie Nukleation von Eis wurde in den selben AAOs untersucht und ein direkter Zusammenhang zwischen dem Nukleationstyp (heterogen bzw. homogen) und der gebildeten Eisphase konnte beobachtet werden. In größeren Poren verlief die Nukleation heterogen, wohingegen sie in kleineren Poren homogen verlief. Außerdem wurde eine Phasenumwandlung des Eises beobachtet. In den größeren Poren wurde hexagonales Eis nachgewiesen und unter einer Porengröße von 35 nm trat hauptsächlich kubisches Eis auf. Nennenswerter Weise handelte es sich bei dem kubischem Eis nicht um eine metastabile sondern eine stabile Phase. Abschließend wird ein Phasendiagramm für räumlich eingeschränktes Wasser vorgeschlagen. Dieses Phasendiagramm kann für technische Anwendungen von Bedeutung sein, so z.B. für Baumaterial wie Zement. Als weiteres Beispiel könnten AAOs, die die heterogene Nukleation unterdrücken (Porendurchmesser ≤ 35 nm) als Filter für Reinstwasser zum Einsatz kommen.rnNun zur Anfangs gestellten Frage: Wie unterschiedlich sind Wasser und Polymerkristallisation voneinander unter räumlicher Einschränkung? Durch Vergleich der beiden Phasendiagramme kommen wir zu dem Schluss, dass beide nicht fundamental verschieden sind. Dies ist zunächst verwunderlich, da Wasser ein kleines Molekül ist und wesentlich kleiner als die kleinste Porengröße ist. Wasser verfügt allerdings über starke Wasserstoffbrückenbindungen und verhält sich daher wie ein Polymer. Daher auch der Name „Polywasser“.

Development, characterization, and application of flowing atmospheric-pressure afterglow ionization for mass spectrometric analysis of ambient organic aerosols

Addressing current limitations of state-of-the-art instrumentation in aerosol research, the aim of this work was to explore and assess the applicability of a novel soft ionization technique, namely flowing atmospheric-pressure afterglow (FAPA), for the mass spectrometric analysis of airborne particulate organic matter. Among other soft ionization methods, the FAPA ionization technique was developed in the last decade during the advent of ambient desorption/ionization mass spectrometry (ADI–MS). Based on a helium glow discharge plasma at atmospheric-pressure, excited helium species and primary reagent ions are generated which exit the discharge region through a capillary electrode, forming the so-called afterglow region where desorption and ionization of the analytes occurs. Commonly, fragmentation of the analytes during ionization is reported to occur only to a minimum extent, predominantly resulting in the formation of quasimolecular ions, i.e. [M+H]+ and [M–H]– in the positive and the negative ion mode, respectively. Thus, identification and detection of signals and their corresponding compounds is facilitated in the acquired mass spectra. The focus of the first part of this study lies on the application, characterization and assessment of FAPA–MS in the offline mode, i.e. desorption and ionization of the analytes from surfaces. Experiments in both positive and negative ion mode revealed ionization patterns for a variety of compound classes comprising alkanes, alcohols, aldehydes, ketones, carboxylic acids, organic peroxides, and alkaloids. Besides the always emphasized detection of quasimolecular ions, a broad range of signals for adducts and losses was found. Additionally, the capabilities and limitations of the technique were studied in three proof-of-principle applications. In general, the method showed to be best suited for polar analytes with high volatilities and low molecular weights, ideally containing nitrogen- and/or oxygen functionalities. However, for compounds with low vapor pressures, containing long carbon chains and/or high molecular weights, desorption and ionization is in direct competition with oxidation of the analytes, leading to the formation of adducts and oxidation products which impede a clear signal assignment in the acquired mass spectra. Nonetheless, FAPA–MS showed to be capable of detecting and identifying common limonene oxidation products in secondary OA (SOA) particles on a filter sample and, thus, is considered a suitable method for offline analysis of OA particles. In the second as well as the subsequent parts, FAPA–MS was applied online, i.e. for real time analysis of OA particles suspended in air. Therefore, the acronym AeroFAPA–MS (i.e. Aerosol FAPA–MS) was chosen to refer to this method. After optimization and characterization, the method was used to measure a range of model compounds and to evaluate typical ionization patterns in the positive and the negative ion mode. In addition, results from laboratory studies as well as from a field campaign in Central Europe (F–BEACh 2014) are presented and discussed. During the F–BEACh campaign AeroFAPA–MS was used in combination with complementary MS techniques, giving a comprehensive characterization of the sampled OA particles. For example, several common SOA marker compounds were identified in real time by MSn experiments, indicating that photochemically aged SOA particles were present during the campaign period. Moreover, AeroFAPA–MS was capable of detecting highly oxidized sulfur-containing compounds in the particle phase, presenting the first real-time measurements of this compound class. Further comparisons with data from other aerosol and gas-phase measurements suggest that both particulate sulfate as well as highly oxidized peroxyradicals in the gas phase might play a role during formation of these species. Besides applying AeroFAPA–MS for the analysis of aerosol particles, desorption processes of particles in the afterglow region were investigated in order to gain a more detailed understanding of the method. While during the previous measurements aerosol particles were pre-evaporated prior to AeroFAPA–MS analysis, in this part no external heat source was applied. Particle size distribution measurements before and after the AeroFAPA source revealed that only an interfacial layer of OA particles is desorbed and, thus, chemically characterized. For particles with initial diameters of 112 nm, desorption radii of 2.5–36.6 nm were found at discharge currents of 15–55 mA from these measurements. In addition, the method was applied for the analysis of laboratory-generated core-shell particles in a proof-of-principle study. As expected, predominantly compounds residing in the shell of the particles were desorbed and ionized with increasing probing depths, suggesting that AeroFAPA–MS might represent a promising technique for depth profiling of OA particles in future studies.

Entwicklung von chiralen- sowie RP-HPLC-Methoden in Verbindung mit hochauflösender MS und deren Anwendung zur Analyse sekundärer organischer Aerosole in der Atmosphäre

Die Erdatmosphäre besteht hauptsächlich aus Stickstoff (78%), Sauerstoff (21%) und Edelga¬sen. Obwohl Partikel weniger als 0,1% ausmachen, spielen sie eine entscheidende Rolle in der Chemie und Physik der Atmosphäre, da sie das Klima der Erde sowohl direkt als auch indirekt beeinflussen. Je nach Art der Bildung unterscheidet man zwischen primären und sekundären Partikeln, wobei primäre Partikel direkt in die Atmosphäre eingetragen werden. Sekundäre Partikel hingegen entstehen durch Kondensation von schwerflüchtigen Verbindungen aus der Gasphase, welche durch Reaktionen von gasförmigen Vorläufersubstanzen (volatile organic compounds, VOCs) mit atmosphärischen Oxidantien wie Ozon oder OH-Radikalen gebildet werden. Da die meisten Vorläufersubstanzen organischer Natur sind, wird das daraus gebil¬dete Aerosol als sekundäres organisches Aerosol (SOA) bezeichnet. Anders als die meisten primären Partikel stammen die VOCs überwiegend aus biogenen Quellen. Es handelt sich da¬bei um ungesättigte Kohlenwasserstoffe, die bei intensiver Sonneneinstrahlung und hohen Temperaturen von Pflanzen emittiert werden. Viele der leichtflüchtigen Vorläufersubstanzen sind chiral, sowohl die Vorläufer als auch die daraus gebildeten Partikel werden aber in den meisten Studien als eine Verbindung betrachtet und gemeinsam analysiert. Die mit Modellen berechneten SOA-Konzentrationen, welche auf dieser traditionellen Vorstellung der SOA-Bil¬dung beruhen, liegen deutlich unterhalb der in der Atmosphäre gefundenen, so dass neben diesem Bildungsweg auch noch andere SOA-Bildungsarten existieren müssen. Aus diesem Grund wird der Fokus der heutigen Forschung vermehrt auf die heterogene Chemie in der Partikelphase gerichtet. Glyoxal als Modellsubstanz kommt hierbei eine wichtige Rolle zu. Es handelt sich bei dieser Verbindung um ein Molekül mit einem hohen Dampfdruck, das auf Grund dieser Eigenschaft nur in der Gasphase zu finden sein sollte. Da es aber über zwei Alde¬hydgruppen verfügt, ist es sehr gut wasserlöslich und kann dadurch in die Partikelphase über¬gehen, wo es heterogenen chemischen Prozessen unterliegt. Unter anderem werden in An¬wesenheit von Ammoniumionen Imidazole gebildet, welche wegen der beiden Stickstoff-He¬teroatome lichtabsorbierende Eigenschaften besitzen. Die Verteilung von Glyoxal zwischen der Gas- und der Partikelphase wird durch das Henrysche Gesetz beschrieben, wobei die Gleichgewichtskonstante die sogenannte Henry-Konstante ist. Diese ist abhängig von der un¬tersuchten organischen Verbindung und den im Partikel vorhandenen anorganischen Salzen. Für die Untersuchung chiraler Verbindungen im SOA wurde zunächst eine Filterextraktions¬methode entwickelt und die erhaltenen Proben anschließend mittels chiraler Hochleistungs-Flüssigchromatographie, welche an ein Elektrospray-Massenspektrometer gekoppelt war, analysiert. Der Fokus lag hierbei auf dem am häufigsten emittierten Monoterpen α-Pinen und seinem Hauptprodukt, der Pinsäure. Da bei der Ozonolyse des α-Pinens das cyclische Grund¬gerüst erhalten bleibt, können trotz der beiden im Molekül vorhanden chiralen Zentren nur zwei Pinsäure Enantiomere gebildet werden. Als Extraktionsmittel wurde eine Mischung aus Methanol/Wasser 9/1 gewählt, mit welcher Extraktionseffizienzen von 65% für Pinsäure Enan¬tiomer 1 und 68% für Pinsäure Enantiomer 2 erreicht werden konnten. Des Weiteren wurden Experimente in einer Atmosphärensimulationskammer durchgeführt, um die Produkte der α-Pinen Ozonolyse eindeutig zu charakterisieren. Enantiomer 1 wurde demnach aus (+)-α-Pinen gebildet und Enantiomer 2 entstand aus (-)-α-Pinen. Auf Filterproben aus dem brasilianischen Regenwald konnte ausschließlich Pinsäure Enantiomer 2 gefunden werden. Enantiomer 1 lag dauerhaft unterhalb der Nachweisgrenze von 18,27 ng/mL. Im borealen Nadelwald war das Verhältnis umgekehrt und Pinsäure Enantiomer 1 überwog vor Pinsäure Enantiomer 2. Das Verhältnis betrug 56% Enantiomer 1 zu 44% Enantiomer 2. Saisonale Verläufe im tropischen Regenwald zeigten, dass die Konzentrationen zur Trockenzeit im August höher waren als wäh¬rend der Regenzeit im Februar. Auch im borealen Nadelwald wurden im Sommer höhere Kon¬zentrationen gemessen als im Winter. Die Verhältnisse der Enantiomere änderten sich nicht im jahreszeitlichen Verlauf. Die Bestimmung der Henry-Konstanten von Glyoxal bei verschiedenen Saataerosolen, nämlich Ammoniumsulfat, Natriumnitrat, Kaliumsulfat, Natriumchlorid und Ammoniumnitrat sowie die irreversible Produktbildung aus Glyoxal in Anwesenheit von Ammoniak waren Forschungs¬gegenstand einer Atmosphärensimulationskammer-Kampagne am Paul-Scherrer-Institut in Villigen, Schweiz. Hierzu wurde zunächst das zu untersuchende Saataerosol in der Kammer vorgelegt und dann aus photochemisch erzeugten OH-Radikalen und Acetylen Glyoxal er¬zeugt. Für die Bestimmung der Glyoxalkonzentration im Kammeraerosol wurde zunächst eine beste¬hende Filterextraktionsmethode modifiziert und die Analyse mittels hochauflösender Mas¬senspektrometrie realisiert. Als Extraktionsmittel kam 100% Acetonitril, ACN zum Einsatz wo¬bei die Extraktionseffizienz bei 85% lag. Für die anschließende Derivatisierung wurde 2,4-Di¬nitrophenylhydrazin, DNPH verwendet. Dieses musste zuvor drei Mal mittels Festphasenex¬traktion gereinigt werden um störende Blindwerte ausreichend zu minimieren. Die gefunde¬nen Henry-Konstanten für Ammoniumsulfat als Saataerosol stimmten gut mit in der Literatur gefundenen Werten überein. Die Werte für Natriumnitrat und Natriumchlorid als Saataerosol waren kleiner als die von Ammoniumsulfat aber größer als der Wert von reinem Wasser. Für Ammoniumnitrat und Kaliumsulfat konnten keine Konstanten berechnet werden. Alle drei Saataerosole führten zu einem „Salting-in“. Das bedeutet, dass bei Erhöhung der Salzmolalität auch die Glyoxalkonzentration im Partikel stieg. Diese Beobachtungen sind auch in der Litera¬tur beschrieben, wobei die Ergebnisse dort nicht auf der Durchführung von Kammerexperi¬menten beruhen, sondern mittels bulk-Experimenten generiert wurden. Für die Trennung der Imidazole wurde eine neue Filterextraktionsmethode entwickelt, wobei sich ein Gemisch aus mit HCl angesäuertem ACN/H2O im Verhältnis 9/1 als optimales Extrak¬tionsmittel herausstellte. Drei verschiedenen Imidazole konnten mit dieser Methode quanti¬fiziert werden, nämlich 1-H-Imidazol-4-carbaldehyd (IC), Imidazol (IM) und 2,2‘-Biimidazol (BI). Die Effizienzen lagen für BI bei 95%, für IC bei 58% und für IM bei 75%. Kammerexperimente unter Zugabe von Ammoniak zeigten höhere Imidazolkonzentrationen als solche ohne. Wurden die Experimente ohne Ammoniak in Anwesenheit von Ammoni¬umsulfat durchgeführt, wurden höhere Imidazol-Konzentrationen gefunden als ohne Ammo¬niumionen. Auch die relative Luftfeuchtigkeit spielte eine wichtige Rolle, da sowohl eine zu hohe als auch eine zu niedrige relative Luftfeuchtigkeit zu einer verminderten Imidazolbildung führte. Durch mit 13C-markiertem Kohlenstoff durchgeführte Experimente konnte eindeutig gezeigt werden, dass es sich bei den gebildeten Imidazolen und Glyoxalprodukte handelte. Außerdem konnte der in der Literatur beschriebene Bildungsmechanismus erfolgreich weiter¬entwickelt werden. Während der CYPHEX Kampagne in Zypern konnten erstmalig Imidazole in Feldproben nach¬gewiesen werden. Das Hauptprodukt IC zeigte einen tageszeitlichen Verlauf mit höheren Kon¬zentrationen während der Nacht und korrelierte signifikant aber schwach mit der Acidität und Ammoniumionenkonzentration des gefundenen Aerosols.

Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.

Predicting spike timing of neocortical pyramidal neurons by simple threshold models

Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current--is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 layer 5 pyramidal neurons from rat somatosensory cortex, stimulated intracellularly by a fluctuating current simulating synaptic bombardment in vivo. The model generates output spikes whenever the membrane voltage (a filtered version of the input current) reaches a dynamic threshold. We find that for input currents with large fluctuation amplitude, up to 75% of the spike times can be predicted with a precision of +/-2 ms. Some of the intrinsic neuronal unreliability can be accounted for by a noisy threshold mechanism. Our results suggest that, under random current injection into the soma, (i) neuronal behavior in the subthreshold regime can be well approximated by a simple linear filter; and (ii) most of the nonlinearities are captured by a simple threshold process.

A multivariate approach for processing magnetization effects in triggered event-related functional magnetic resonance imaging time series

Triggered event-related functional magnetic resonance imaging requires sparse intervals of temporally resolved functional data acquisitions, whose initiation corresponds to the occurrence of an event, typically an epileptic spike in the electroencephalographic trace. However, conventional fMRI time series are greatly affected by non-steady-state magnetization effects, which obscure initial blood oxygen level-dependent (BOLD) signals. Here, conventional echo-planar imaging and a post-processing solution based on principal component analysis were employed to remove the dominant eigenimages of the time series, to filter out the global signal changes induced by magnetization decay and to recover BOLD signals starting with the first functional volume. This approach was compared with a physical solution using radiofrequency preparation, which nullifies magnetization effects. As an application of the method, the detectability of the initial transient BOLD response in the auditory cortex, which is elicited by the onset of acoustic scanner noise, was used to demonstrate that post-processing-based removal of magnetization effects allows to detect brain activity patterns identical with those obtained using the radiofrequency preparation. Using the auditory responses as an ideal experimental model of triggered brain activity, our results suggest that reducing the initial magnetization effects by removing a few principal components from fMRI data may be potentially useful in the analysis of triggered event-related echo-planar time series. The implications of this study are discussed with special caution to remaining technical limitations and the additional neurophysiological issues of the triggered acquisition.

Photon-beam subsource sensitivity to the initial electron-beam parameters

One limitation to the widespread implementation of Monte Carlo (MC) patient dose-calculation algorithms for radiotherapy is the lack of a general and accurate source model of the accelerator radiation source. Our aim in this work is to investigate the sensitivity of the photon-beam subsource distributions in a MC source model (with target, primary collimator, and flattening filter photon subsources and an electron subsource) for 6- and 18-MV photon beams when the energy and radial distributions of initial electrons striking a linac target change. For this purpose, phase-space data (PSD) was calculated for various mean electron energies striking the target, various normally distributed electron energy spread, and various normally distributed electron radial intensity distributions. All PSD was analyzed in terms of energy, fluence, and energy fluence distributions, which were compared between the different parameter sets. The energy spread was found to have a negligible influence on the subsource distributions. The mean energy and radial intensity significantly changed the target subsource distribution shapes and intensities. For the primary collimator and flattening filter subsources, the distribution shapes of the fluence and energy fluence changed little for different mean electron energies striking the target, however, their relative intensity compared with the target subsource change, which can be accounted for by a scaling factor. This study indicates that adjustments to MC source models can likely be limited to adjusting the target subsource in conjunction with scaling the relative intensity and energy spectrum of the primary collimator, flattening filter, and electron subsources when the energy and radial distributions of the initial electron-beam change.

Control algorithms for large scale adaptive optics

In this dissertation, the problem of creating effective large scale Adaptive Optics (AO) systems control algorithms for the new generation of giant optical telescopes is addressed. The effectiveness of AO control algorithms is evaluated in several respects, such as computational complexity, compensation error rejection and robustness, i.e. reasonable insensitivity to the system imperfections. The results of this research are summarized as follows: 1. Robustness study of Sparse Minimum Variance Pseudo Open Loop Controller (POLC) for multi-conjugate adaptive optics (MCAO). The AO system model that accounts for various system errors has been developed and applied to check the stability and performance of the POLC algorithm, which is one of the most promising approaches for the future AO systems control. It has been shown through numerous simulations that, despite the initial assumption that the exact system knowledge is necessary for the POLC algorithm to work, it is highly robust against various system errors. 2. Predictive Kalman Filter (KF) and Minimum Variance (MV) control algorithms for MCAO. The limiting performance of the non-dynamic Minimum Variance and dynamic KF-based phase estimation algorithms for MCAO has been evaluated by doing Monte-Carlo simulations. The validity of simple near-Markov autoregressive phase dynamics model has been tested and its adequate ability to predict the turbulence phase has been demonstrated both for single- and multiconjugate AO. It has also been shown that there is no performance improvement gained from the use of the more complicated KF approach in comparison to the much simpler MV algorithm in the case of MCAO. 3. Sparse predictive Minimum Variance control algorithm for MCAO. The temporal prediction stage has been added to the non-dynamic MV control algorithm in such a way that no additional computational burden is introduced. It has been confirmed through simulations that the use of phase prediction makes it possible to significantly reduce the system sampling rate and thus overall computational complexity while both maintaining the system stable and effectively compensating for the measurement and control latencies.

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Dynamic modeling of active regeneration in catalyzed and non-catalyzed diesel particulate filters

Particulate matter (PM) emissions standards set by the US Environmental Protection Agency (EPA) have become increasingly stringent over the years. The EPA regulation for PM in heavy duty diesel engines has been reduced to 0.01 g/bhp-hr for the year 2010. Heavy duty diesel engines make use of an aftertreatment filtration device, the Diesel Particulate Filter (DPF). DPFs are highly efficient in filtering PM (known as soot) and are an integral part of 2010 heavy duty diesel aftertreatment system. PM is accumulated in the DPF as the exhaust gas flows through it. This PM needs to be removed by oxidation periodically for the efficient functioning of the filter. This oxidation process is also known as regeneration. There are 2 types of regeneration processes, namely active regeneration (oxidation of PM by external means) and passive oxidation (oxidation of PM by internal means). Active regeneration occurs typically in high temperature regions, about 500 - 600 °C, which is much higher than normal diesel exhaust temperatures. Thus, the exhaust temperature has to be raised with the help of external devices like a Diesel Oxidation Catalyst (DOC) or a fuel burner. The O2 oxidizes PM producing CO2 as oxidation product. In passive oxidation, one way of regeneration is by the use of NO2. NO2 oxidizes the PM producing NO and CO2 as oxidation products. The passive oxidation process occurs at lower temperatures (200 - 400 °C) in comparison to the active regeneration temperatures. Generally, DPF substrate walls are washcoated with catalyst material to speed up the rate of PM oxidation. The catalyst washcoat is observed to increase the rate of PM oxidation. The goal of this research is to develop a simple mathematical model to simulate the PM depletion during the active regeneration process in a DPF (catalyzed and non-catalyzed). A simple, zero-dimensional kinetic model was developed in MATLAB. Experimental data required for calibration was obtained by active regeneration experiments performed on PM loaded mini DPFs in an automated flow reactor. The DPFs were loaded with PM from the exhaust of a commercial heavy duty diesel engine. The model was calibrated to the data obtained from active regeneration experiments. Numerical gradient based optimization techniques were used to estimate the kinetic parameters of the model.

Kinetic characterization for pretreatment of timber varieties and switchgrass using diluted acid hydrolysis

In recent years, growing attention has been devoted to the use of lignocellulosic biomass as a feedstock to produce renewable carbohydrates as a source of energy products, including liquid alternatives to fossil fuels. The benefits of developing woody biomass to ethanol technology are to increase the long-term national energy security, reduce fossil energy consumption, lower greenhouse gas emissions, use renewable rather than depletable resources, and create local jobs. Currently, research is driven by the need to reduce the cost of biomass-ethanol production. One of the preferred methods is to thermochemically pretreat the biomass material and subsequently, enzymatically hydrolyze the pretreated material to fermentable sugars that can then be converted to ethanol using specialized microorganisms. The goals of pretreatment are to remove the hemicellulose fraction from other biomass components, reduce bioconversion time, enhance enzymatic conversion of the cellulose fraction, and, hopefully, obtain a higher ethanol yield. The primary goal of this research is to obtain kinetic detailed data for dilute acid hydrolysis for several timber species from the Upper Peninsula of Michigan and switchgrass. These results will be used to identify optimum reaction conditions to maximize production of fermentable sugars and minimize production of non-fermentable byproducts. The structural carbohydrate analysis of the biomass species used in this project was performed using the procedure proposed by National Renewable Energy Laboratory (NREL). Subsequently, dilute acid-catalyzed hydrolysis of biomass, including aspen, basswood, balsam, red maple, and switchgrass, was studied at various temperatures, acid concentrations, and particle sizes in a 1-L well-mixed batch reactor (Parr Instruments, ii Model 4571). 25 g of biomass and 500 mL of diluted acid solution were added into a 1-L glass liner, and then put into the reactor. During the experiment, 5 mL samples were taken starting at 100°C at 3 min intervals until reaching the targeted temperature (160, 175, or 190°C), followed by 4 samples after achieving the desired temperature. The collected samples were then cooled in an ice bath immediately to stop the reaction. The cooled samples were filtered using 0.2 μm MILLIPORE membrane filter to remove suspended solids. The filtered samples were then analyzed using High Performance Liquid Chromatography (HPLC) with a Bio-Rad Aminex HPX-87P column, and refractive index detection to measure monomeric and polymeric sugars plus degradation byproducts. A first order reaction model was assumed and the kinetic parameters such as activation energy and pre-exponential factor from Arrhenius equation were obtained from a match between the model and experimental data. The reaction temperature increases linearly after 40 minutes during experiments. Xylose and other sugars were formed from hemicellulose hydrolysis over this heat up period until a maximum concentration was reached at the time near when the targeted temperature was reached. However, negligible amount of xylose byproducts and small concentrations of other soluble sugars, such as mannose, arabinose, and galactose were detected during this initial heat up period. Very little cellulose hydrolysis yielding glucose was observed during the initial heat up period. On the other hand, later in the reaction during the constant temperature period xylose was degraded to furfural. Glucose production from cellulose was increased during this constant temperature period at later time points in the reaction. The kinetic coefficient governing the generation of xylose from hemicellulose and the generation of furfural from xylose presented a coherent dependence on both temperature and acid concentration. However, no effect was observed in the particle size. There were three types of biomass used in this project; hardwood (aspen, basswood, and red maple), softwood (balsam), and a herbaceous crop (switchgrass). The activation energies and the pre-exponential factors of the timber species and switchgrass were in a range of 49 - 180 kJ/mol and from 7.5x104 - 2.6x1020 min-1, respectively, for the xylose formation model. In addition, for xylose degradation, the activation energies and the preexponential factors ranged from 130 - 170 kJ/mol and from 6.8x1013 - 3.7x1017 min-1, respectively. The results compare favorably with the literature values given by Ranganathan et al, 1985. Overall, up to 92 % of the xylose was able to generate from the dilute acid hydrolysis in this project.

Algorithms for spacecraft formation flying navigation based on wireless positioning system measurements

Spacecraft formation flying navigation continues to receive a great deal of interest. The research presented in this dissertation focuses on developing methods for estimating spacecraft absolute and relative positions, assuming measurements of only relative positions using wireless sensors. The implementation of the extended Kalman filter to the spacecraft formation navigation problem results in high estimation errors and instabilities in state estimation at times. This is due tp the high nonlinearities in the system dynamic model. Several approaches are attempted in this dissertation aiming at increasing the estimation stability and improving the estimation accuracy. A differential geometric filter is implemented for spacecraft positions estimation. The differential geometric filter avoids the linearization step (which is always carried out in the extended Kalman filter) through a mathematical transformation that converts the nonlinear system into a linear system. A linear estimator is designed in the linear domain, and then transformed back to the physical domain. This approach demonstrated better estimation stability for spacecraft formation positions estimation, as detailed in this dissertation. The constrained Kalman filter is also implemented for spacecraft formation flying absolute positions estimation. The orbital motion of a spacecraft is characterized by two range extrema (perigee and apogee). At the extremum, the rate of change of a spacecraft’s range vanishes. This motion constraint can be used to improve the position estimation accuracy. The application of the constrained Kalman filter at only two points in the orbit causes filter instability. Two variables are introduced into the constrained Kalman filter to maintain the stability and improve the estimation accuracy. An extended Kalman filter is implemented as a benchmark for comparison with the constrained Kalman filter. Simulation results show that the constrained Kalman filter provides better estimation accuracy as compared with the extended Kalman filter. A Weighted Measurement Fusion Kalman Filter (WMFKF) is proposed in this dissertation. In wireless localizing sensors, a measurement error is proportional to the distance of the signal travels and sensor noise. In this proposed Weighted Measurement Fusion Kalman Filter, the signal traveling time delay is not modeled; however, each measurement is weighted based on the measured signal travel distance. The obtained estimation performance is compared to the standard Kalman filter in two scenarios. The first scenario assumes using a wireless local positioning system in a GPS denied environment. The second scenario assumes the availability of both the wireless local positioning system and GPS measurements. The simulation results show that the WMFKF has similar accuracy performance as the standard Kalman Filter (KF) in the GPS denied environment. However, the WMFKF maintains the position estimation error within its expected error boundary when the WLPS detection range limit is above 30km. In addition, the WMFKF has a better accuracy and stability performance when GPS is available. Also, the computational cost analysis shows that the WMFKF has less computational cost than the standard KF, and the WMFKF has higher ellipsoid error probable percentage than the standard Measurement Fusion method. A method to determine the relative attitudes between three spacecraft is developed. The method requires four direction measurements between the three spacecraft. The simulation results and covariance analysis show that the method’s error falls within a three sigma boundary without exhibiting any singularity issues. A study of the accuracy of the proposed method with respect to the shape of the spacecraft formation is also presented.

Sediment yield reduction in an agricultural watershed

With proper application of Best Management Practices (BMPs), the impact from the sediment to the water bodies could be minimized. However, finding the optimal allocation of BMP can be difficult, since there are numerous possible options. Also, economics plays an important role in BMP affordability and, therefore, the number of BMPs able to be placed in a given budget year. In this study, two methodologies are presented to determine the optimal cost-effective BMP allocation, by coupling a watershed-level model, Soil and Water Assessment Tool (SWAT), with two different methods, targeting and a multi-objective genetic algorithm (Non-dominated Sorting Genetic Algorithm II, NSGA-II). For demonstration, these two methodologies were applied to an agriculture-dominant watershed located in Lower Michigan to find the optimal allocation of filter strips and grassed waterways. For targeting, three different criteria were investigated for sediment yield minimization, during the process of which it was found that the grassed waterways near the watershed outlet reduced the watershed outlet sediment yield the most under this study condition, and cost minimization was also included as a second objective during the cost-effective BMP allocation selection. NSGA-II was used to find the optimal BMP allocation for both sediment yield reduction and cost minimization. By comparing the results and computational time of both methodologies, targeting was determined to be a better method for finding optimal cost-effective BMP allocation under this study condition, since it provided more than 13 times the amount of solutions with better fitness for the objective functions while using less than one eighth of the SWAT computational time than the NSGA-II with 150 generations did.