871 resultados para Construction. Indicators System. Performance. Ergonomics. Validation


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Compared to phosphorus (P), nitrogen (N) has received little attention across the Everglades landscape. Despite this lack of attention, N plays important roles in many Everglades systems, including being a significant pollutant in Florida Bay and the Gulf of Mexico, the limiting nutrient in highly P-impacted areas, and an important substrate for microbial metabolism. Storage and transport of N throughout the Everglades is dominated by organic forms, including peat soils and dissolved organic N in the water column. In general, N sources are highest in the northern areas; however, atmospheric deposition and active N2 fixation by the periphyton components are a significant N source throughout most systems. Many of the processes involved in the wetland N cycle remain unmeasured for most of the Everglades systems. In particular, the lack of in situ rates for N2 fixation and denitrification prevent the construction of system-level budgets, especially for the Southern mangrove systems where N export into Florida Bay is critical. There is also the potential for several novel N processes (e.g., Anammox) with an as yet undetermined importance for nitrogen cycling and function of the Everglades ecosystem. Phosphorus loading alters the N cycle by stimulating organic N mineralization with resulting flux of ammonium and DON, and at elevated P concentrations, by increasing rates of N2 fixation and N assimilation. Restoration of hydrology has a potential for significantly impacting N cycling in the Everglades both in terms of affecting N transport, but also by altering aerobic-anaerobic transitions at the soil-water interface or in areas with seasonal drawdowns (e.g., marl prairies). Based on the authors’ understanding of N processes, much more research is necessary to adequately predict potential impacts from hydrologic restoration, as well as the function of Everglades systems as sinks, sources, and transformers of N in the South Florida landscape.

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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.

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Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^

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Variable Speed Limit (VSL) strategies identify and disseminate dynamic speed limits that are determined to be appropriate based on prevailing traffic conditions, road surface conditions, and weather conditions. This dissertation develops and evaluates a shockwave-based VSL system that uses a heuristic switching logic-based controller with specified thresholds of prevailing traffic flow conditions. The system aims to improve operations and mobility at critical bottlenecks. Before traffic breakdown occurrence, the proposed VSL’s goal is to prevent or postpone breakdown by decreasing the inflow and achieving uniform distribution in speed and flow. After breakdown occurrence, the VSL system aims to dampen traffic congestion by reducing the inflow traffic to the congested area and increasing the bottleneck capacity by deactivating the VSL at the head of the congested area. The shockwave-based VSL system pushes the VSL location upstream as the congested area propagates upstream. In addition to testing the system using infrastructure detector-based data, this dissertation investigates the use of Connected Vehicle trajectory data as input to the shockwave-based VSL system performance. Since the field Connected Vehicle data are not available, as part of this research, Vehicle-to-Infrastructure communication is modeled in the microscopic simulation to obtain individual vehicle trajectories. In this system, wavelet transform is used to analyze aggregated individual vehicles’ speed data to determine the locations of congestion. The currently recommended calibration procedures of simulation models are generally based on the capacity, volume and system-performance values and do not specifically examine traffic breakdown characteristics. However, since the proposed VSL strategies are countermeasures to the impacts of breakdown conditions, considering breakdown characteristics in the calibration procedure is important to have a reliable assessment. Several enhancements were proposed in this study to account for the breakdown characteristics at bottleneck locations in the calibration process. In this dissertation, performance of shockwave-based VSL is compared to VSL systems with different fixed VSL message sign locations utilizing the calibrated microscopic model. The results show that shockwave-based VSL outperforms fixed-location VSL systems, and it can considerably decrease the maximum back of queue and duration of breakdown while increasing the average speed during breakdown.

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Since the introduction of fiber reinforced polymers (FRP) for the repair and retrofit of concrete structures in the 1980’s, considerable research has been devoted to the feasibility of their application and predictive modeling of their performance. However, the effects of flaws present in the constitutive components and the practices in substrate preparation and treatment have not yet been thoroughly studied. This research aims at investigating the effect of surface preparation and treatment for the pre-cured FRP systems and the groove size tolerance for near surface mounted (NSM) FRP systems; and to set thresholds for guaranteed system performance. The research included both analytical and experimental components. The experimental program for the pre-cured FRP systems consisted of a total of twenty-four (24) reinforced concrete (RC) T-beams with various surface preparation parameters and surface flaws, including roughness, flatness, voids and cracks (cuts). For the NSM FRP systems, a total of twelve (12) additional RC T-beams were tested with different grooves sizes for FRP bars and strips. The analytical program included developing an elaborate nonlinear finite element model using the general purpose software ANSYS. The model was subsequently used to extend the experimental range of parameters for surface flatness in pre-cured FRP systems, and for groove size study in the NSM FRP systems. Test results, confirmed by further analyses, indicated that contrary to the general belief in the industry, the impact of surface roughness on the global performance of pre-cured FRP systems was negligible. The study also verified that threshold limits set for wet lay-up FRP systems can be extended to pre-cured systems. The study showed that larger surface voids and cracks (cuts) can adversely impact both the strength and ductility of pre-cured FRP systems. On the other hand, frequency (or spacing) of surface cracks (cuts) may only affect system ductility rather than its strength. Finally, within the range studied, groove size tolerance of +1/8 in. does not appear to have an adverse effect on the performance of NSM FRP systems.

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The primary purpose of this thesis was to present a theoretical large-signal analysis to study the power gain and efficiency of a microwave power amplifier for LS-band communications using software simulation. Power gain, efficiency, reliability, and stability are important characteristics in the power amplifier design process. These characteristics affect advance wireless systems, which require low-cost device amplification without sacrificing system performance. Large-signal modeling and input and output matching components are used for this thesis. Motorola's Electro Thermal LDMOS model is a new transistor model that includes self-heating affects and is capable of small-large signal simulations. It allows for most of the design considerations to be on stability, power gain, bandwidth, and DC requirements. The matching technique allows for the gain to be maximized at a specific target frequency. Calculations and simulations for the microwave power amplifier design were performed using Matlab and Microwave Office respectively. Microwave Office is the simulation software used in this thesis. The study demonstrated that Motorola's Electro Thermal LDMOS transistor in microwave power amplifier design process is a viable solution for common-source amplifier applications in high power base stations. The MET-LDMOS met the stability requirements for the specified frequency range without a stability-improvement model. The power gain of the amplifier circuit was improved through proper microwave matching design using input/output-matching techniques. The gain and efficiency of the amplifier improve approximately 4dB and 7.27% respectively. The gain value is roughly .89 dB higher than the maximum gain specified by the MRF21010 data sheet specifications. This work can lead to efficient modeling and development of high power LDMOS transistor implementations in commercial and industry applications.

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The research aimed to construct and validate a data collection instrument of pregnant couple as part of primary care. It was considered hypothesis that level of agreement from 70% among participants to validate the expert panel. The document has been based on the Theory of Human Needs by Horta and adjusted by Garcia and Cubas. It is a study of methodological type developed in four stages: identification of empirical indicators to pregnant women through an integrative literature review; evaluation of empirical indicators and their relation to human needs by focus group; structuring of the second version of instrument by categorization of indicators and appearance and content validation of the third version of instrument by judges, by use of Delphi technique. The collection of data was the first stage in months from August to October 2014 in the Journal of Midwifery and Women's Health and Scopus, PubMed, Lilacs, CINAHL, Cochrane databases. The remaining steps were carried out from November 2014 to February 2015. For the focus group was counted with participation of six experts through two meetings. As for the judges, it was obtained a population of 63 and final sample of 51 judges divided into 46 basic health units of Municipal City Health Natal/RN, Brazil. The study was approved by the Research Ethics Committee of Universidade Federal do Rio Grande do Norte, under Protocol number 876.200. For data analysis of the first stage it was used descriptive statistics and results are presented in tables and charts. At that stage were identified 162 empirical indicators and, when they were related to human needs, 64 by them were on psycobiological, 97 on psychosocial and one (1) on psychospiritual needs. Regarding the second and third stages, data were treated by process of categorizing and analyzing the Content Validity Index. The indicators obtained a 100% validation index. In appearance and content validation phase of instrument non-validated items were excluded and other items obtained index above 70%. Furthermore, it obtained 99% content validity index in the second version and 95.7% in the third version of the instrument as a whole and, therefore, validated tool. This instrument contains Health Institution, pregnant woman and her partner identification data, information on the human needs of the pregnant and items pertaining to systematize the collection of pregnant couple data during prenatal care. By the conclusion of the study, nurse shall have an instrument to collect the data of pregnant couple in primary care innovative by considering psychobiological, psychosocial and psychospiritual pregnant needs and insert health and sociodemographic data of pregnant partner in the context of pregnancy. Also, the document will serve as a tool for teaching and research in obstetrical nursing.

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Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

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Smart structures and systems have the main purpose to mimic living organisms, which are essentially characterized by an autoregulatory behavior. Therefore, this kind of structure has adaptive characteristics with stimulus-response mechanisms. The term adaptive structure has been used to identify structural systems that are capable of changing their geometry or physical properties with the purpose of performing a specific task. In this work, a sliding mode controller with fuzzy inference is applied for active vibration control in an SMA two-bar truss. In order to obtain a simpler controller, a polynomial model is used in the control law, while a more sophisticated version, which presents close agreement with experimental data, is applied to describe the SMA behavior of the structural elements. This system has a rich dynamic response and can easily reach a chaotic behavior even at moderate loads and frequencies. Therefore, this approach has the advantage of not only obtaining a simpler control law, but also allows its robustness be evidenced. Numerical simulations are carried out in order to demonstrate the control system performance.

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The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

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The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

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In this thesis, we introduce DeReEs-4v, an algorithm for unsupervised and automatic registration of two video frames captured depth-sensing cameras. DeReEs-4V receives two RGBD video streams from two depth-sensing cameras arbitrary located in an indoor space that share a minimum amount of 25% overlap between their captured scenes. The motivation of this research is to employ multiple depth-sensing cameras to enlarge the field of view and acquire a more complete and accurate 3D information of the environment. A typical way to combine multiple views from different cameras is through manual calibration. However, this process is time-consuming and may require some technical knowledge. Moreover, calibration has to be repeated when the location or position of the cameras change. In this research, we demonstrate how DeReEs-4V registration can be used to find the transformation of the view of one camera with respect to the other at interactive rates. Our algorithm automatically finds the 3D transformation to match the views from two cameras, requires no human interference, and is robust to camera movements while capturing. To validate this approach, a thorough examination of the system performance under different scenarios is presented. The system presented here supports any application that might benefit from the wider field-of-view provided by the combined scene from both cameras, including applications in 3D telepresence, gaming, people tracking, videoconferencing and computer vision.

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The purpose of this study was to explore the socialization of teachers in physical education, with a focus on their experiences of teaching and learning to teach children living with physical disabilities. Data were collected using qualitative interviews and through analysis of program calendars for publicly-funded institutions offering pre-service teacher education programs. Despite being largely viewed as the least effective form of socialization, pre-service teacher education has the potential to influence a teacher’s confidence and performance in the classroom. Results of this study indicate that the socialization experiences of teachers continue to be strong indicators of performance, and that both specialist and generalist teachers lack positive socialization experiences that include students with physical disabilities in physical education. This limits the experience, knowledge and skills they have to draw on in their physical education teaching practice. Coupled with a lack of resources and expertise available, teachers are left under-prepared and without enough resources to provide high quality physical education to children living with physical disabilities.

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Compensation of the detrimental impacts of nonlinearity on long haul wavelength division multiplexed system performance is discussed, and the difference between transmitter, receiver and in-line compensation analyzed. The impact of system imperfections is also outlined.

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Compensation of the detrimental impacts of nonlinearity on long-haul wavelength division multiplexed system performance is discussed, and the difference between transmitter, receiver and in-line compensation analyzed. We demonstrate that ideal compensation of nonlinear noise could result in an increase in the signal-to-noise ratio (measured in dB) of 50%, and that reaches may be more than doubled for higher order modulation formats. The influence of parametric noise amplification is discussed in detail, showing how increased numbers of optical phase conjugators may further increase the received signal-tonoise ratio. Finally the impact of practical real world system imperfections, such as polarization mode dispersion, are outlined.