969 resultados para control-flow checking
Resumo:
Gene flow, or the exchange of genes between populations, is important because it determines the evolutionary trajectory of a species, including the relative influences of genetic drift and natural selection in the process of population differentiation. Gene flow differs among species because of variation in dispersal capability and abundances across taxa, and historical forces related to geological or lineage history. Both history and ecology influence gene flow in potentially complicated ways, and accounting for their effects remains an important problem in evolutionary biology. This research is a comparative study of gene flow and life-history in a monophyletic group of stream fishes, the darters. As a first step in disentangling historical and ecological effects, I reconstructed the phylogenetic relationships of the study species from nucleotide sequences in the mtDNA control region. I then used this phylogeny and regional glaciation history to infer historical effects on life-history evolution and gene flow in 15 species of darters. Gene flow was estimated indirectly, using information from 20 resolvable and polymorphic allozyme loci. When I accounted for historical effects, comparisons across taxa revealed that gene flow rates were closely associated with differences in clutch sizes and reproductive investment patterns. I hypothesized that differences in larval dispersal among taxa explained this relationship. Results from a field study of larval drift were consistent with this hypothesis. Finally, I asked whether there was an interaction between species' ecology and genetic differentiation across biogeographically distinct regions. Information from allozymes and mtDNA sequences revealed that life history plays an important role in the magnitude of species divergence across biogeographic boundaries. These results suggested an important association between life histories and rates of speciation following an allopatric isolation event. This research, along with other studies from the literature, further illustrates the enormous potential of North American freshwater fishes as a system for studying speciation processes. ^
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If we classify variables in a program into various security levels, then a secure information flow analysis aims to verify statically that information in a program can flow only in ways consistent with the specified security levels. One well-studied approach is to formulate the rules of the secure information flow analysis as a type system. A major trend of recent research focuses on how to accommodate various sophisticated modern language features. However, this approach often leads to overly complicated and restrictive type systems, making them unfit for practical use. Also, problems essential to practical use, such as type inference and error reporting, have received little attention. This dissertation identified and solved major theoretical and practical hurdles to the application of secure information flow. ^ We adopted a minimalist approach to designing our language to ensure a simple lenient type system. We started out with a small simple imperative language and only added features that we deemed most important for practical use. One language feature we addressed is arrays. Due to the various leaking channels associated with array operations, arrays have received complicated and restrictive typing rules in other secure languages. We presented a novel approach for lenient array operations, which lead to simple and lenient typing of arrays. ^ Type inference is necessary because usually a user is only concerned with the security types for input/output variables of a program and would like to have all types for auxiliary variables inferred automatically. We presented a type inference algorithm B and proved its soundness and completeness. Moreover, algorithm B stays close to the program and the type system and therefore facilitates informative error reporting that is generated in a cascading fashion. Algorithm B and error reporting have been implemented and tested. ^ Lastly, we presented a novel framework for developing applications that ensure user information privacy. In this framework, core computations are defined as code modules that involve input/output data from multiple parties. Incrementally, secure flow policies are refined based on feedback from the type checking/inference. Core computations only interact with code modules from involved parties through well-defined interfaces. All code modules are digitally signed to ensure their authenticity and integrity. ^
Resumo:
Long-term management plans for restoration of natural flow conditions through the Everglades increase the importance of understanding potential nutrient impacts of increased freshwater delivery on Florida Bay biogeochemistry. Planktonic communities respond quickly to changes in water quality, thus spatial variability in community composition and relationships to nutrient parameters must be understood in order to evaluate future downstream impacts of modifications to Everglades hydrology. Here we present initial results combining flow cytometry analyses of phytoplankton and bacterial populations (0.1–50 μm size fraction) with measurements of δ13C and δ15N composition and dissolved inorganic nutrient concentrations to explore proxies for planktonic species assemblage compositions and nutrient cycling. Particulate organic material in the 0.1–50 μm size fraction was collected from five stations in Northeastern and Western Florida Bay to characterize spatial variability in species assemblage and stable isotopic composition. A dense bloom of the picocyanobacterium, Synechococcus elongatus, was observed at Western Florida Bay sites. Smaller Synechococcus sp. were present at Northeast sites in much lower abundance. Bacteria and detrital particles were also more abundant at Western Florida Bay stations than in the northeast region. The highest abundance of detritus occurred at Trout Creek, which receives freshwater discharge from the Everglades through Taylor Slough. In terms of nutrient availability and stable isotopic values, the S. elongatus population in the Western bay corresponded to low DIN (0.5 μM NH 4 + ; 0.2 μM NO 3 − ) concentrations and depleted δ15N signatures ranging from +0.3 to +0.8‰, suggesting that the bloom supported high productivity levels through N2-fixation. δ15N values from the Northeast bay were more enriched (+2.0 to +3.0‰), characteristic of N-recycling. δ13C values were similar for all marine Florida Bay stations, ranging from −17.6 to −14.4‰, however were more depleted at the mangrove ecotone station (−25.5 to −22.3‰). The difference in the isotopic values reflects differences in carbon sources. These findings imply that variations in resource availability and nutrient sources exert significant control over planktonic community composition, which is reflected by stable isotopic signatures.
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Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.
Resumo:
Protecting confidential information from improper disclosure is a fundamental security goal. While encryption and access control are important tools for ensuring confidentiality, they cannot prevent an authorized system from leaking confidential information to its publicly observable outputs, whether inadvertently or maliciously. Hence, secure information flow aims to provide end-to-end control of information flow. Unfortunately, the traditionally-adopted policy of noninterference, which forbids all improper leakage, is often too restrictive. Theories of quantitative information flow address this issue by quantifying the amount of confidential information leaked by a system, with the goal of showing that it is intuitively "small" enough to be tolerated. Given such a theory, it is crucial to develop automated techniques for calculating the leakage in a system. ^ This dissertation is concerned with program analysis for calculating the maximum leakage, or capacity, of confidential information in the context of deterministic systems and under three proposed entropy measures of information leakage: Shannon entropy leakage, min-entropy leakage, and g-leakage. In this context, it turns out that calculating the maximum leakage of a program reduces to counting the number of possible outputs that it can produce. ^ The new approach introduced in this dissertation is to determine two-bit patterns, the relationships among pairs of bits in the output; for instance we might determine that two bits must be unequal. By counting the number of solutions to the two-bit patterns, we obtain an upper bound on the number of possible outputs. Hence, the maximum leakage can be bounded. We first describe a straightforward computation of the two-bit patterns using an automated prover. We then show a more efficient implementation that uses an implication graph to represent the two- bit patterns. It efficiently constructs the graph through the use of an automated prover, random executions, STP counterexamples, and deductive closure. The effectiveness of our techniques, both in terms of efficiency and accuracy, is shown through a number of case studies found in recent literature. ^
Resumo:
Mechanical conditioning has been shown to promote tissue formation in a wide variety of tissue engineering efforts. However the underlying mechanisms by which external mechanical stimuli regulate cells and tissues are not known. This is particularly relevant in the area of heart valve tissue engineering (HVTE) owing to the intense hemodynamic environments that surround native valves. Some studies suggest that oscillatory shear stress (OSS) caused by steady flow and scaffold flexure play a critical role in engineered tissue formation derived from bone marrow derived stem cells (BMSCs). In addition, scaffold flexure may enhance nutrient (e.g. oxygen, glucose) transport. In this study, we computationally quantified the i) magnitude of fluid-induced shear stresses; ii) the extent of temporal fluid oscillations in the flow field using the oscillatory shear index (OSI) parameter, and iii) glucose and oxygen mass transport profiles. Noting that sample cyclic flexure induces a high degree of oscillatory shear stress (OSS), we incorporated moving boundary computational fluid dynamic simulations of samples housed within a bioreactor to consider the effects of: 1) no flow, no flexure (control group), 2) steady flow-alone, 3) cyclic flexure-alone and 4) combined steady flow and cyclic flexure environments. We also coupled a diffusion and convention mass transport equation to the simulated system. We found that the coexistence of both OSS and appreciable shear stress magnitudes, described by the newly introduced parameter OSI-t , explained the high levels of engineered collagen previously observed from combining cyclic flexure and steady flow states. On the other hand, each of these metrics on its own showed no association. This finding suggests that cyclic flexure and steady flow synergistically promote engineered heart valve tissue production via OSS, so long as the oscillations are accompanied by a critical magnitude of shear stress. In addition, our simulations showed that mass transport of glucose and oxygen is enhanced by sample movement at low sample porosities, but did not play a role in highly porous scaffolds. Preliminary in-house in vitro experiments showed that cell proliferation and phenotype is enhanced in OSI-t environments.
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In the Oil industry, oil and gas pipelines are commonly utilized to perform the transportation of production fluids to longer distances. The maintenance of the pipelines passes through the analysis of several tools, in which the most currently used are the pipelines inspection cells, popularly knowing as PIG. Among the variants existing in the market, the instrumented PIG has a significant relevance; acknowledging that through the numerous sensors existing in the equipment, it can detect faults or potential failure along the inspected line. Despite its versatility, the instrumented PIG suffers from speed variations, impairing the reading of sensors embedded in it. Considering that PIG moves depending on the speed of the production fluid, a way to control his speed is to control the flow of the fluid through the pressure control, reducing the flow rate of the produced flow, resulting in reduction of overall production the fluid in the ducts own or with the use of a restrictive element (valve) installed on it. The characteristic of the flow rate/pressure drop from restrictive elements of the orifice plate is deducted usually from the ideal energy equation (Bernoulli’s equation) and later, the losses are corrected normally through experimental tests. Thus, with the objective of controlling the fluids flow passing through the PIG, a valve shutter actuated by solenoid has been developed. This configuration allows an ease control and stabilization of the flow adjustment, with a consequent response in the pressure drops between upstream and downstream of the restriction. It was assembled a test bench for better definition of flow coefficients; composed by a duct with intern diameter of four inches, one set of shutters arranged in a plate and pressure gauges for checking the pressure drop in the test. The line was pressurized and based on the pressure drop it was possible to draw a curve able to characterize the flow coefficient of the control valve prototype and simulate in mockup the functioning, resulting in PIG speed reduction of approximately 68%.
Resumo:
Automation of managed pressure drilling (MPD) enhances the safety and increases efficiency of drilling and that drives the development of controllers and observers for MPD. The objective is to maintain the bottom hole pressure (BHP) within the pressure window formed by the reservoir pressure and fracture pressure and also to reject kicks. Practical MPD automation solutions must address the nonlinearities and uncertainties caused by the variations in mud flow rate, choke opening, friction factor, mud density, etc. It is also desired that if pressure constraints are violated the controller must take appropriate actions to reject the ensuing kick. The objectives are addressed by developing two controllers: a gain switching robust controller and a nonlinear model predictive controller (NMPC). The robust gain switching controller is designed using H1 loop shaping technique, which was implemented using high gain bumpless transfer and 2D look up table. Six candidate controllers were designed in such a way they preserve robustness and performance for different choke openings and flow rates. It is demonstrated that uniform performance is maintained under different operating conditions and the controllers are able to reject kicks using pressure control and maintain BHP during drill pipe extension. The NMPC was designed to regulate the BHP and contain the outlet flow rate within certain tunable threshold. The important feature of that controller is that it can reject kicks without requiring any switching and thus there is no scope for shattering due to switching between pressure and flow control. That is achieved by exploiting the constraint handling capability of NMPC. Active set method was used for computing control inputs. It is demonstrated that NMPC is able to contain kicks and maintain BHP during drill pipe extension.
Resumo:
Germanium (Ge) nanowires are of current research interest for high speed nanoelectronic devices due to the lower band gap and high carrier mobility compatible with high K-dielectrics and larger excitonic Bohr radius ensuing a more pronounced quantum confinement effect [1-6]. A general way for the growth of Ge nanowires is to use liquid or a solid growth promoters in a bottom-up approach which allow control of the aspect ratio, diameter, and structure of 1D crystals via external parameters, such as precursor feedstock, temperature, operating pressure, precursor flow rate etc [3, 7-11]. The Solid-phase seeding is preferred for more control processing of the nanomaterials and potential suppression of the unintentional incorporation of high dopant concentrations in semiconductor nanowires and unrequired compositional tailing of the seed-nanowire interface [2, 5, 9, 12]. There are therefore distinct features of the solid phase seeding mechanism that potentially offer opportunities for the controlled processing of nanomaterials with new physical properties. A superior control over the growth kinetics of nanowires could be achieved by controlling the inherent growth constraints instead of external parameters which always account for instrumental inaccuracy. The high dopant concentrations in semiconductor nanowires can result from unintentional incorporation of atoms from the metal seed material, as described for the Al catalyzed VLS growth of Si nanowires [13] which can in turn be depressed by solid-phase seeding. In addition, the creation of very sharp interfaces between group IV semiconductor segments has been achieved by solid seeds [14], whereas the traditionally used liquid Au particles often leads to compositional tailing of the interface [15] . Korgel et al. also described the superior size retention of metal seeds in a SFSS nanowire growth process, when compared to a SFLS process using Au colloids [12]. Here in this work we have used silver and alloy seed particle with different compositions to manipulate the growth of nanowires in sub-eutectic regime. The solid seeding approach also gives an opportunity to influence the crystallinity of the nanowires independent of the substrate. Taking advantage of the readily formation of stacking faults in metal nanoparticles, lamellar twins in nanowires could be formed.
Resumo:
Nature is challenged to move charge efficiently over many length scales. From sub-nm to μm distances, electron-transfer proteins orchestrate energy conversion, storage, and release both inside and outside the cell. Uncovering the detailed mechanisms of biological electron-transfer reactions, which are often coupled to bond-breaking and bond-making events, is essential to designing durable, artificial energy conversion systems that mimic the specificity and efficiency of their natural counterparts. Here, we use theoretical modeling of long-distance charge hopping (Chapter 3), synthetic donor-bridge-acceptor molecules (Chapters 4, 5, and 6), and de novo protein design (Chapters 5 and 6) to investigate general principles that govern light-driven and electrochemically driven electron-transfer reactions in biology. We show that fast, μm-distance charge hopping along bacterial nanowires requires closely packed charge carriers with low reorganization energies (Chapter 3); singlet excited-state electronic polarization of supermolecular electron donors can attenuate intersystem crossing yields to lower-energy, oppositely polarized, donor triplet states (Chapter 4); the effective static dielectric constant of a small (~100 residue) de novo designed 4-helical protein bundle can change upon phototriggering an electron transfer event in the protein interior, providing a means to slow the charge-recombination reaction (Chapter 5); and a tightly-packed de novo designed 4-helix protein bundle can drastically alter charge-transfer driving forces of photo-induced amino acid radical formation in the bundle interior, effectively turning off a light-driven oxidation reaction that occurs in organic solvent (Chapter 6). This work leverages unique insights gleaned from proteins designed from scratch that bind synthetic donor-bridge-acceptor molecules that can also be studied in organic solvents, opening new avenues of exploration into the factors critical for protein control of charge flow in biology.
Resumo:
The identification of transport parameters by inverse modeling often suffers from equifinality or parameter correlation when models are fitted to observations of the solute breakthrough in column outflow experiments. This parameters uncertainty can be approached by the application of multiple experimental designs such as column experiments in open-flow mode and the recently proposed closed-flow mode. Latter are characterized by the recirculation of the column effluent into the solution supply vessel that feeds the inflow. Depending on the experimental conditions, the solute concentration in the solution supply vessel and the effluent follows a damped sinusoidal oscillation. As a result, the closed-flow experiment provides additional observables in the breakthrough curve. The evaluation of these emergent features allows intrinsic control over boundary conditions and impacts the uncertainty of parameters in inverse modeling. We present a comprehensive sensitivity analysis to illustrate the potential application of closed-flow experiments. We show that the sensitivity with respect to the apparent dispersion can be controlled by the experimenter leading to a decrease in parameter uncertainty as compared to classical experiments by an order of magnitude for optimal settings. With these finding we are also able to reduce the equifinality found for situations, where rate-limited interactions impede a proper determination of the apparent dispersion and rate coefficients. Furthermore, we show the expected breakthrough curve for equilibrium and kinetic sorption, the latter showing strong similarities to the behavior found for completely mixed batch reactor experiments. This renders the closed-flow mode a useful complementary approach to classical column experiments.
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The electric vehicle (EV) market has seen a rapid growth in the recent past. With an increase in the number of electric vehicles on road, there is an increase in the number of high capacity battery banks interfacing the grid. The battery bank of an EV, besides being the fuel tank, is also a huge energy storage unit. Presently, it is used only when the vehicle is being driven and remains idle for rest of the time, rendering it underutilized. Whereas on the other hand, there is a need of large energy storage units in the grid to filter out the fluctuations of supply and demand during a day. EVs can help bridge this gap. The EV battery bank can be used to store the excess energy from the grid to vehicle (G2V) or supply stored energy from the vehicle to grid (V2G ), when required. To let power flow happen, in both directions, a bidirectional AC-DC converter is required. This thesis concentrates on the bidirectional AC-DC converters which have a control on power flow in all four quadrants for the application of EV battery interfacing with the grid. This thesis presents a bidirectional interleaved full bridge converter topology. This helps in increasing the power processing and current handling capability of the converter which makes it suitable for the purpose of EVs. Further, the benefit of using the interleaved topology is that it increases the power density of the converter. This ensures optimization of space usage with the same power handling capacity. The proposed interleaved converter consists of two full bridges. The corresponding gate pulses of each switch, in one cell, are phase shifted by 180 degrees from those of the other cell. The proposed converter control is based on the one-cycle controller. To meet the challenge of new requirements of reactive power handling capabilities for grid connected converters, posed by the utilities, the controller is modified to make it suitable to process the reactive power. A fictitious current derived from the grid voltage is introduced in the controller, which controls the converter performance. The current references are generated using the second order generalized integrators (SOGI) and phase locked loop (PLL). A digital implementation of the proposed control ii scheme is developed and implemented using DSP hardware. The simulated and experimental results, based on the converter topology and control technique discussed here, are presented to show the performance of the proposed theory.
Resumo:
Bidirectional DC-DC converters are widely used in different applications such as energy storage systems, Electric Vehicles (EVs), UPS, etc. In particular, future EVs require bidirectional power flow in order to integrate energy storage units into smart grids. These bidirectional power converters provide Grid to Vehicle (V2G)/ Vehicle to Grid (G2V) power flow capability for future EVs. Generally, there are two control loops used for bidirectional DC-DC converters: The inner current loop and The outer loop. The control of DAB converters used in EVs are proved to be challenging due to the wide range of operating conditions and non-linear behavior of the converter. In this thesis, the precise mathematical model of the converter is derived and non-linear control schemes are proposed for the control system of bidirectional DC-DC converters based on the derived model. The proposed inner current control technique is developed based on a novel Geometric-Sequence Control (GSC) approach. The proposed control technique offers significantly improved performance as compared to one for conventional control approaches. The proposed technique utilizes a simple control algorithm which saves on the computational resources. Therefore, it has higher reliability, which is essential in this application. Although, the proposed control technique is based on the mathematical model of the converter, its robustness against parameter uncertainties is proven. Three different control modes for charging the traction batteries in EVs are investigated in this thesis: the voltage mode control, the current mode control, and the power mode control. The outer loop control is determined by each of the three control modes. The structure of the outer control loop provides the current reference for the inner current loop. Comprehensive computer simulations have been conducted in order to evaluate the performance of the proposed control methods. In addition, the proposed control have been verified on a 3.3 kW experimental prototype. Simulation and experimental results show the superior performance of the proposed control techniques over the conventional ones.
Resumo:
Mineral and chemical composition of alluvial Upper-Pleistocene deposits from the Alto Guadalquivir Basin (SE Spain) were studied as a tool to identify sedimentary and geomorphological processes controlling its formation. Sediments located upstream, in the north-eastern sector of the basin, are rich in dolomite, illite, MgO and KB2BO. Downstream, sediments at the sequence base are enriched in calcite, smectite and CaO, whereas the upper sediments have similar features to those from upstream. Elevated rare-earth elements (REE) values can be related to low carbonate content in the sediments and the increase of silicate material produced and concentrated during soil formation processes in the neighbouring source areas. Two mineralogical and geochemical signatures related to different sediment source areas were identified. Basal levels were deposited during a predominantly erosive initial stage, and are mainly composed of calcite and smectite materials enriched in REE coming from Neogene marls and limestones. Then the deposition of the upper levels of the alluvial sequences, made of dolomite and illitic materials depleted in REE coming from the surrounding Sierra de Cazorla area took place during a less erosive later stage of the fluvial system. Such modification was responsible of the change in the mineralogical and geochemical composition of the alluvial sediments.
Resumo:
This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.