Digital Preservation and Web Access to the Konkoly Observatory Schmidt Telescope Plate Archive

ACM Computing Classification System (1998): J.2.

Design and flux-weakening control of an interior permanent magnet synchronous motor for electric vehicles

Permanent magnet synchronous motors (PMSMs) provide a competitive technology for EV traction drives owing to their high power density and high efficiency. In this paper, three types of interior PMSMs with different PM arrangements are modeled by the finite element method (FEM). For a given amount of permanent magnet materials, the V shape interior PMSM is found better than the U-shape and the conventional rotor topologies for EV traction drives. Then the V shape interior PMSM is further analyzed with the effects of stator slot opening and the permanent magnet pole chamfering on cogging torque and output torque performance. A vector-controlled flux-weakening method is developed and simulated in matlab to expand the motor speed range for EV drive system. The results show good dynamic and steady-state performance with a capability of expanding speed up to 4 times of the rated. A prototype of the V shape interior PMSM is also manufactured and tested to validate the numerical models built by the finite element method.

Improving Storage with Stackable Extensions

Storage is a central part of computing. Driven by exponentially increasing content generation rate and a widening performance gap between memory and secondary storage, researchers are in the perennial quest to push for further innovation. This has resulted in novel ways to "squeeze" more capacity and performance out of current and emerging storage technology. Adding intelligence and leveraging new types of storage devices has opened the door to a whole new class of optimizations to save cost, improve performance, and reduce energy consumption. In this dissertation, we first develop, analyze, and evaluate three storage extensions. Our first extension tracks application access patterns and writes data in the way individual applications most commonly access it to benefit from the sequential throughput of disks. Our second extension uses a lower power flash device as a cache to save energy and turn off the disk during idle periods. Our third extension is designed to leverage the characteristics of both disks and solid state devices by placing data in the most appropriate device to improve performance and save power. In developing these systems, we learned that extending the storage stack is a complex process. Implementing new ideas incurs a prolonged and cumbersome development process and requires developers to have advanced knowledge of the entire system to ensure that extensions accomplish their goal without compromising data recoverability. Futhermore, storage administrators are often reluctant to deploy specific storage extensions without understanding how they interact with other extensions and if the extension ultimately achieves the intended goal. We address these challenges by using a combination of approaches. First, we simplify the storage extension development process with system-level infrastructure that implements core functionality commonly needed for storage extension development. Second, we develop a formal theory to assist administrators deploy storage extensions while guaranteeing that the given high level goals are satisfied. There are, however, some cases for which our theory is inconclusive. For such scenarios we present an experimental methodology that allows administrators to pick an extension that performs best for a given workload. Our evaluation demostrates the benefits of both the infrastructure and the formal theory.

Dynamic modeling and analysis of single-stage boost inverters under normal and abnormal conditions

Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies.^ The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task.^ This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation. ^

Positron emission tomography (PET) tumor segmentation and quantification: Development of new algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera's point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ∼10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera's PSF. The algorithm can also improve dose estimation and treatment planning.^

Ecosystem structure in disturbed and restored subtropical seagrass meadows

Shallow seagrass ecosystems frequently experience physical disturbance from vessel groundings. Specific restoration methods that modify physical, chemical, and biological aspects of disturbances are used to accelerate recovery. This study evaluated loss and recovery of ecosystem structure in disturbed seagrass meadows through plant and soil properties used as proxies for primary and secondary production, habitat quality, benthic metabolism, remineralization, and nutrient storage and exchange. The efficacy of common seagrass restoration techniques in accelerating recovery was also assessed. Beyond removal of macrophyte biomass, disturbance to seagrass sediments resulted in loss of organic matter and stored nutrients, and altered microbial and infaunal communities. Evidence of the effectiveness of restoration actions was variable. Fill placement prevented additional erosion, but the resulting sediment matrix had different physical properties, low organic matter content and nutrient pools, reduced benthic metabolism, and less primary and secondary production relative to the undisturbed ecosystem. Fertilization was effective in increasing nitrogen and phosphorus availability in the sediments, but concurrent enhancement of seagrass production was not detected. Seagrass herbivores removed substantial seagrass biomass via direct grazing, suggesting that leaf loss to seagrass herbivores is a spatially variable but critically important determinant of seagrass transplanting success. Convergence of plant and sediment response variables with levels in undisturbed seagrass meadows was not detected via natural recovery of disturbed sites, or through filling and fertilizing restoration sites. However, several indicators of ecosystem development related to primary production and nutrient accumulation suggest that early stages of ecosystem development have begun at these sites. This research suggests that vessel grounding disturbances in seagrass ecosystems create more complex and persistent resource losses than previously understood by resource managers. While the mechanics of implementing common seagrass restoration actions have been successfully developed by the restoration community, expectations of consistent or rapid recovery trajectories following restoration remain elusive.

Photo degradation of contaminants of emerging concern (CECs) under simulated solar radiation: Implications for their environmental fate

Contaminants of emerging concern (CECs) are continuously being released into the environment mainly because of their incomplete removal in the sewage treatment plants (STPs). The CECs selected for the study include antibiotics (macrolides, sulfonamides and ciprofloxacin), sucralose (an artificial sweetener) and dioctyl sulfosuccinate (DOSS, chemical dispersant used in the Deepwater Horizon oil spill). After being discharged into waterways from STPs, photo degradation is a key factor in dictating the environmental fate of antibiotics and sucralose. Photodegradation efficiency depends on many factors such as pH of the matrix, matrix composition, light source and structure of the molecule. These factors exert either synergistic or antagonistic effects in the environment and thus experiments with isolated factors may not yield the same results as the natural environmental processes. Hence in the current study photodegradation of 13 CECs (antibiotics, sucralose and dicotyl sulfosuccinate) were evaluated using natural water matrices with varying composition (deionized water, fresh water and salt water) as well as radiation of different wavelengths (254 nm, 350 nm and simulated solar radiation) in order to mimic natural processes. As expected the contribution of each factor on the overall rate of photodegradation is contaminant specific, for example under similar conditions, the rate in natural waters compared to pure water was enhanced for antibiotics (2-11 fold), significantly reduced for sucralose (no degradation seen in natural waters) and similar in both media for DOSS. In general, it was observed that the studied compounds degraded faster at 254 nm, while when using a simulated sunlight radiation the rate of photolysis of DOSS increased and the rates for antibiotics decreased in comparison to the 350 nm radiation. The photo stability of the studied CECs followed the order sucralose > DOSS > macrolides > sulfonamides > ciprofloxacin and a positive relationship was observed between photo stability and their ubiquitous presence in natural aquatic matrices. An online LC-MS/MS method was developed and validated for sucralose and further applied to reclaimed waters (n =56) and drinking waters (n = 43) from South Florida. Sucralose was detected in reclaimed waters with concentrations reaching up to 18 μg/L. High frequency of detection (> 80%) in drinking waters indicate contamination of ground waters in South Florida by anthropogenic activity.^

Leveraging symbiotic relationships for emulation of computer networks

The lack of analytical models that can accurately describe large-scale networked systems makes empirical experimentation indispensable for understanding complex behaviors. Research on network testbeds for testing network protocols and distributed services, including physical, emulated, and federated testbeds, has made steady progress. Although the success of these testbeds is undeniable, they fail to provide: 1) scalability, for handling large-scale networks with hundreds or thousands of hosts and routers organized in different scenarios, 2) flexibility, for testing new protocols or applications in diverse settings, and 3) inter-operability, for combining simulated and real network entities in experiments. This dissertation tackles these issues in three different dimensions. First, we present SVEET, a system that enables inter-operability between real and simulated hosts. In order to increase the scalability of networks under study, SVEET enables time-dilated synchronization between real hosts and the discrete-event simulator. Realistic TCP congestion control algorithms are implemented in the simulator to allow seamless interactions between real and simulated hosts. SVEET is validated via extensive experiments and its capabilities are assessed through case studies involving real applications. Second, we present PrimoGENI, a system that allows a distributed discrete-event simulator, running in real-time, to interact with real network entities in a federated environment. PrimoGENI greatly enhances the flexibility of network experiments, through which a great variety of network conditions can be reproduced to examine what-if questions. Furthermore, PrimoGENI performs resource management functions, on behalf of the user, for instantiating network experiments on shared infrastructures. Finally, to further increase the scalability of network testbeds to handle large-scale high-capacity networks, we present a novel symbiotic simulation approach. We present SymbioSim, a testbed for large-scale network experimentation where a high-performance simulation system closely cooperates with an emulation system in a mutually beneficial way. On the one hand, the simulation system benefits from incorporating the traffic metadata from real applications in the emulation system to reproduce the realistic traffic conditions. On the other hand, the emulation system benefits from receiving the continuous updates from the simulation system to calibrate the traffic between real applications. Specific techniques that support the symbiotic approach include: 1) a model downscaling scheme that can significantly reduce the complexity of the large-scale simulation model, resulting in an efficient emulation system for modulating the high-capacity network traffic between real applications; 2) a queuing network model for the downscaled emulation system to accurately represent the network effects of the simulated traffic; and 3) techniques for reducing the synchronization overhead between the simulation and emulation systems.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Study of Ammonia Borane and its Derivatives: Influence of Nanoconfinements and Pressures

Recently, ammonia borane has increasingly attracted researchers’ attention because of its merging applications, such as organic synthesis, boron nitride compounds synthesis, and hydrogen storage. This dissertation presents the results from several studies related to ammonia borane. The pressure-induced tetragonal to orthorhombic phase transition in ammonia borane was studied in a diamond anvil cell using in situ Raman spectroscopy. We found a positive Clapeyron-slope for this phase transformation in the experiment, which implies that the phase transition from tetragonal to orthorhombic is exothermic. The result of this study indicates that the rehydrogenation of the high pressure orthorhombic phase is expected to be easier than that of the ambient pressure tetragonal phase due to its lower enthalpy. The high pressure behavior of ammonia borane after thermal decomposition was studied by in situ Raman spectroscopy at high pressures up to 10 GPa. The sample of ammonia borane was first decomposed at ~140 degree Celcius and ~0.7 GPa and then compessed step wise in an isolated sample chamber of a diamond anvil cell for Raman spectroscopy measurement. We did not observe the characteristic shift of Raman mode under high pressure due to dihydrogen bonding, indicating that the dihydrogen bonding disappears in the decomposed ammonia borane. Although no chemical rehydrogenation was detected in this study, the decomposed ammonia borane could store extra hydrogen by physical absorption. The effect of nanoconfinement on ammonia borane at high pressures and different temperatures was studied. Ammonia borane was mixed with a type of mesoporous silica, SBA-15, and restricted within a small space of nanometer scale. The nano-scale ammonia borane was decomposed at ~125 degree Celcius in a diamond anvil cell and rehydrogenated after applying high pressures up to ~13 GPa at room temperature. The successful rehydrogenation of decomposed nano-scale ammonia borane gives guidance to further investigations on hydrogen storage. In addition, the high pressure behavior of lithium amidoborane, one derivative of ammonia borane, was studied at different temperatures. Lithium amidoborane (LAB) was decomposed and recompressed in a diamond anvil cell. After applying high pressures on the decomposed lithium amidoborane, its recovery peaks were discovered by Raman spectroscopy. This result suggests that the decomposition of LAB is reversible at high pressures.

Improving Storage Performance Through Layout Optimizations

Disk drives are the bottleneck in the processing of large amounts of data used in almost all common applications. File systems attempt to reduce this by storing data sequentially on the disk drives, thereby reducing the access latencies. Although this strategy is useful when data is retrieved sequentially, the access patterns in real world workloads is not necessarily sequential and this mismatch results in storage I/O performance degradation. This thesis demonstrates that one way to improve the storage performance is to reorganize data on disk drives in the same way in which it is mostly accessed. We identify two classes of accesses: static, where access patterns do not change over the lifetime of the data and dynamic, where access patterns frequently change over short durations of time, and propose, implement and evaluate layout strategies for each of these. Our strategies are implemented in a way that they can be seamlessly integrated or removed from the system as desired. We evaluate our layout strategies for static policies using tree-structured XML data where accesses to the storage device are mostly of two kinds - parent-tochild or child-to-sibling. Our results show that for a specific class of deep-focused queries, the existing file system layout policy performs better by 5-54X. For the non-deep-focused queries, our native layout mechanism shows an improvement of 3-127X. To improve performance of the dynamic access patterns, we implement a self-optimizing storage system that performs rearranges popular block accesses on a dedicated partition based on the observed workload characteristics. Our evaluation shows an improvement of over 80% in the disk busy times over a range of workloads. These results show that applying the knowledge of data access patterns for allocation decisions can substantially improve the I/O performance.

Aplicação da destilação simulada por cromatografia gasosa e da termogravimetria para a avaliação da influência da redução do teor de enxofre sobre as propriedades físico-químicas do óleo diesel

One of the main problems related to the use of diesel as fuel is the presence of sulfur (S) which causes environmental pollution and corrosion of engines. In order to minimize the consequences of the release of this pollutant, Brazilian law established maximum sulfur content that diesel fuel may have. To meet these requirements, diesel with a maximum sulfur concentration equal to 10 mg/kg (S10) has been widely marketed in the country. However, the reduction of sulfur can lead to changes in the physicochemical properties of the fuel, which are essential for the performance of road vehicles. This work aims to identify the main changes in the physicochemical properties of diesel fuel and how they are related to reduction of sulfur content. Samples of diesel types S10, S500 and S1800 were tested according with the methods of the American Society for Testing and Materials (ASTM). The fuels were also characterized by thermogravimetric analysis (TG) and subjected to physical distillation (ASTM D86) and simulated distillation gas chromatography (ASTM D2887). The results showed that the reduction of sulfur turned the fuel lighter and fluid, allowing a greater applicability to low temperature environments and safer for transportation and storage. Through the simulated distillation data was observed that decreasing sulfur content resulted in higher initial boiling point temperatures and the decreasing of the boiling temperature of the medium and heavy fractions. Thermogravimetric analysis showed a loss event mass attributed to volatilization or distillation of light and medium hydrocarbons. Based on these data, the kinetic behavior of the samples was investigated and it was observed that the activation energies (Ea) did not show significant changes throughout conversion. Considering the average of these energies, the S1800 had the highest Ea during the conversion and the S10 the lowest values

Development of InAlN HEMTs for space application

This thesis investigates the emerging InAlN high electron mobility transistor (HEMT) technology with respect to its application in the space industry. The manufacturing processes and device performance of InAlN HEMTs were compared to AlGaN HEMTs, also produced as part of this work. RF gain up to 4 GHz was demonstrated in both InAlN and AlGaN HEMTs with gate lengths of 1 μm, with InAlN HEMTs generally showing higher channel currents (~150 c.f. 60 mA/mm) but also degraded leakage properties (~ 1 x 10-4 c.f. < 1 x 10-8 A/mm) with respect to AlGaN. An analysis of device reliability was undertaken using thermal stability, radiation hardness and off-state breakdown measurements. Both InAlN and AlGaN HEMTs showed excellent stability under space-like conditions, with electrical operation maintained after exposure to 9.2 Mrad of gamma radiation at a dose rate of 6.6 krad/hour over two months and after storage at 250°C for four weeks. Furthermore a link was established between the optimisation of device performance (RF gain, power handling capabilities and leakage properties) and reliability (radiation hardness, thermal stability and breakdown properties), particularly with respect to surface passivation. Following analysis of performance and reliability data, the InAlN HEMT device fabrication process was optimised by adjusting the metal Ohmic contact formation process (specifically metal stack thicknesses and anneal conditions) and surface passivation techniques (plasma power during dielectric layer deposition), based on an existing AlGaN HEMT process. This resulted in both a reduction of the contact resistivity to around 1 x 10-4 Ω.cm2 and the suppression of degrading trap-related effects, bringing the measured gate-lag close to zero. These discoveries fostered a greater understanding of the physical mechanisms involved in device operation and manufacture, which is elaborated upon in the final chapter.

Degradation rates and productivity signals of organic-walled dinoflagellate cyst species in surface sediment samples

To understand the role of the ocean within the global carbon cycle, detailed information is required on key-processes within the marine carbon cycle; bio-production in the upper ocean, export of the produced material to the deep ocean and the storage of carbon in oceanic sediments. Quantification of these processes requires the separation of signals of net primary production and the rate of organic matter decay as reflected in fossil sediments. This study examines the large differences in degradation rates of organic-walled dinoflagellate cyst species to separate these degradation and productivity signals. For this, accumulation rates of cyst species known to be resistant (R-cysts) or sensitive (S-cysts) to aerobic degradation of 62 sites are compared to mean annual chlorophyll-a, sea-surface temperature, sea-surface salinity, nitrate and phosphate concentrations of the upper waters and deep-water oxygen concentrations. Furthermore, the degradation of sensitive cysts, as expressed by the degradation constant k and reaction time t, has been related to bottom water [O2]. The studied sediments were taken from the Arabian Sea, north-western African Margin (North Atlantic), western-equatorial Atlantic Ocean/Caraibic, south-western African margin (South Atlantic) and Southern Ocean (Atlantic sector). Significant relationships are observed between (a) accumulation rates of R-cysts and upper water chlorophyll-a concentrations, (b) accumulation rates of S-cysts and bottom water [O2] and (c) degradation rates of S-cysts (kt) and bottom water [O2]. Relationships that are extremely weak or are clearly insignificant on all confidence intervals are between (1) S-cyst accumulation rates and chlorophyll-a concentrations, sea-surface temperature (SST), sea-surface salinity (SSS), phosphate concentrations (P) and nitrate concentrations (N), (2) between R-cyst accumulation rates and bottom water [O2], SST, SSS, P and N, and between (3) kt and water depth. Co-variance is present between the parameters N and P, N, P and chlorophyll-a, oxygen and water depth. Correcting for this co-variance does not influence the significance of the relationship given above. The possible applicability of dinoflagellate cyst degradation to estimate past net primary production and deep ocean ventilation is discussed.

Secure and Scalable Statistical Computation of Questionnaire Data in R

Collecting data via a questionnaire and analyzing them while preserving respondents’ privacy may increase the number of respondents and the truthfulness of their responses. It may also reduce the systematic differences between respondents and non-respondents. In this paper, we propose a privacy-preserving method for collecting and analyzing survey responses using secure multi-party computation (SMC). The method is secure under the semi-honest adversarial model. The proposed method computes a wide variety of statistics. Total and stratified statistical counts are computed using the secure protocols developed in this paper. Then, additional statistics, such as a contingency table, a chi-square test, an odds ratio, and logistic regression, are computed within the R statistical environment using the statistical counts as building blocks. The method was evaluated on a questionnaire dataset of 3,158 respondents sampled for a medical study and simulated questionnaire datasets of up to 50,000 respondents. The computation time for the statistical analyses linearly scales as the number of respondents increases. The results show that the method is efficient and scalable for practical use. It can also be used for other applications in which categorical data are collected.