916 resultados para Instrumental variable probit
Resumo:
Ever since the invention of the internal combustion engine, generating more power and achieving better efficiency has been a major goal for the designers. Variable compression ratio technology is way to achieve those goals. This paper will discuss the method of varying the compression ratio of an inline 4-cylinder engine through the use of a 4-bar linkage and gear mechanism. This mechanism was proven to easily vary the compression ratio of the engine and shows promise of becoming a technology used for future engine designer.
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There is a need by engine manufactures for computationally efficient and accurate predictive combustion modeling tools for integration in engine simulation software for the assessment of combustion system hardware designs and early development of engine calibrations. This thesis discusses the process for the development and validation of a combustion modeling tool for Gasoline Direct Injected Spark Ignited Engine with variable valve timing, lift and duration valvetrain hardware from experimental data. Data was correlated and regressed from accepted methods for calculating the turbulent flow and flame propagation characteristics for an internal combustion engine. A non-linear regression modeling method was utilized to develop a combustion model to determine the fuel mass burn rate at multiple points during the combustion process. The computational fluid dynamic software Converge ©, was used to simulate and correlate the 3-D combustion system, port and piston geometry to the turbulent flow development within the cylinder to properly predict the experimental data turbulent flow parameters through the intake, compression and expansion processes. The engine simulation software GT-Power © is then used to determine the 1-D flow characteristics of the engine hardware being tested to correlate the regressed combustion modeling tool to experimental data to determine accuracy. The results of the combustion modeling tool show accurate trends capturing the combustion sensitivities to turbulent flow, thermodynamic and internal residual effects with changes in intake and exhaust valve timing, lift and duration.
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The problem of optimal design of a multi-gravity-assist space trajectories, with free number of deep space maneuvers (MGADSM) poses multi-modal cost functions. In the general form of the problem, the number of design variables is solution dependent. To handle global optimization problems where the number of design variables varies from one solution to another, two novel genetic-based techniques are introduced: hidden genes genetic algorithm (HGGA) and dynamic-size multiple population genetic algorithm (DSMPGA). In HGGA, a fixed length for the design variables is assigned for all solutions. Independent variables of each solution are divided into effective and ineffective (hidden) genes. Hidden genes are excluded in cost function evaluations. Full-length solutions undergo standard genetic operations. In DSMPGA, sub-populations of fixed size design spaces are randomly initialized. Standard genetic operations are carried out for a stage of generations. A new population is then created by reproduction from all members based on their relative fitness. The resulting sub-populations have different sizes from their initial sizes. The process repeats, leading to increasing the size of sub-populations of more fit solutions. Both techniques are applied to several MGADSM problems. They have the capability to determine the number of swing-bys, the planets to swing by, launch and arrival dates, and the number of deep space maneuvers as well as their locations, magnitudes, and directions in an optimal sense. The results show that solutions obtained using the developed tools match known solutions for complex case studies. The HGGA is also used to obtain the asteroids sequence and the mission structure in the global trajectory optimization competition (GTOC) problem. As an application of GA optimization to Earth orbits, the problem of visiting a set of ground sites within a constrained time frame is solved. The J2 perturbation and zonal coverage are considered to design repeated Sun-synchronous orbits. Finally, a new set of orbits, the repeated shadow track orbits (RSTO), is introduced. The orbit parameters are optimized such that the shadow of a spacecraft on the Earth visits the same locations periodically every desired number of days.
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The accuracy of simulating the aerodynamics and structural properties of the blades is crucial in the wind-turbine technology. Hence the models used to implement these features need to be very precise and their level of detailing needs to be high. With the variety of blade designs being developed the models should be versatile enough to adapt to the changes required by every design. We are going to implement a combination of numerical models which are associated with the structural and the aerodynamic part of the simulation using the computational power of a parallel HPC cluster. The structural part models the heterogeneous internal structure of the beam based on a novel implementation of the Generalized Timoshenko Beam Model Technique.. Using this technique the 3-D structure of the blade is reduced into a 1-D beam which is asymptotically equivalent. This reduces the computational cost of the model without compromising its accuracy. This structural model interacts with the Flow model which is a modified version of the Blade Element Momentum Theory. The modified version of the BEM accounts for the large deflections of the blade and also considers the pre-defined structure of the blade. The coning, sweeping of the blade, tilt of the nacelle and the twist of the sections along the blade length are all computed by the model which aren’t considered in the classical BEM theory. Each of these two models provides feedback to the other and the interactive computations lead to more accurate outputs. We successfully implemented the computational models to analyze and simulate the structural and aerodynamic aspects of the blades. The interactive nature of these models and their ability to recompute data using the feedback from each other makes this code more efficient than the commercial codes available. In this thesis we start off with the verification of these models by testing it on the well-known benchmark blade for the NREL-5MW Reference Wind Turbine, an alternative fixed-speed stall-controlled blade design proposed by Delft University, and a novel alternative design that we proposed for a variable-speed stall-controlled turbine, which offers the potential for more uniform power control and improved annual energy production.. To optimize the power output of the stall-controlled blade we modify the existing designs and study their behavior using the aforementioned aero elastic model.
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Experimental work and analysis was done to investigate engine startup robustness and emissions of a flex-fuel spark ignition (SI) direct injection (DI) engine. The vaporization and other characteristics of ethanol fuel blends present a challenge at engine startup. Strategies to reduce the enrichment requirements for the first engine startup cycle and emissions for the second and third fired cycle at 25°C ± 1°C engine and intake air temperature were investigated. Research work was conducted on a single cylinder SIDI engine with gasoline and E85 fuels, to study the effect on first fired cycle of engine startup. Piston configurations that included a compression ratio change (11 vs 15.5) and piston geometry change (flattop vs bowl) were tested, along with changes in intake cam timing (95,110,125) and fuel pressure (0.4 MPa vs 3 MPa). The goal was to replicate the engine speed, manifold pressure, fuel pressure and testing temperature from an engine startup trace for investigating the first fired cycle for the engine. Results showed bowl piston was able to enable lower equivalence ratio engine starts with gasoline fuel, while also showing lower IMEP at the same equivalence ratio compared to flat top piston. With E85, bowl piston showed reduced IMEP as compression ratio increased at the same equivalence ratio. A preference for constant intake valve timing across fuels seemed to indicate that flattop piston might be a good flex-fuel piston. Significant improvements were seen with higher CR bowl piston with high fuel pressure starts, but showed no improvement with low fuel pressures. Simulation work was conducted to analyze initial three cycles of engine startup in GT-POWER for the same set of hardware used in the experimentations. A steady state validated model was modified for startup conditions. The results of which allowed an understanding of the relative residual levels and IMEP at the test points in the cam phasing space. This allowed selecting additional test points that enable use of higher residual levels, eliminating those with smaller trapped mass incapable of producing required IMEP for proper engine turnover. The second phase of experimental testing results for 2nd and 3rd startup cycle revealed both E10 and E85 prefer the same SOI of 240°bTDC at second and third startup cycle for the flat top piston and high injection pressures. E85 fuel optimal cam timing for startup showed that it tolerates more residuals compared to E10 fuel. Higher internal residuals drives down the Ø requirement for both fuels up to their combustion stability limit, this is thought to be direct benefit to vaporization due to increased cycle start temperature. Benefits are shown for an advance IMOP and retarded EMOP strategy at engine startup. Overall the amount of residuals preferred by an engine for E10 fuel at startup is thought to be constant across engine speed, thus could enable easier selection of optimized cam positions across the startup speeds.
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BACKGROUND: The extent to which mortality differs following individual acquired immunodeficiency syndrome (AIDS)-defining events (ADEs) has not been assessed among patients initiating combination antiretroviral therapy. METHODS: We analyzed data from 31,620 patients with no prior ADEs who started combination antiretroviral therapy. Cox proportional hazards models were used to estimate mortality hazard ratios for each ADE that occurred in >50 patients, after stratification by cohort and adjustment for sex, HIV transmission group, number of antiretroviral drugs initiated, regimen, age, date of starting combination antiretroviral therapy, and CD4+ cell count and HIV RNA load at initiation of combination antiretroviral therapy. ADEs that occurred in <50 patients were grouped together to form a "rare ADEs" category. RESULTS: During a median follow-up period of 43 months (interquartile range, 19-70 months), 2880 ADEs were diagnosed in 2262 patients; 1146 patients died. The most common ADEs were esophageal candidiasis (in 360 patients), Pneumocystis jiroveci pneumonia (320 patients), and Kaposi sarcoma (308 patients). The greatest mortality hazard ratio was associated with non-Hodgkin's lymphoma (hazard ratio, 17.59; 95% confidence interval, 13.84-22.35) and progressive multifocal leukoencephalopathy (hazard ratio, 10.0; 95% confidence interval, 6.70-14.92). Three groups of ADEs were identified on the basis of the ranked hazard ratios with bootstrapped confidence intervals: severe (non-Hodgkin's lymphoma and progressive multifocal leukoencephalopathy [hazard ratio, 7.26; 95% confidence interval, 5.55-9.48]), moderate (cryptococcosis, cerebral toxoplasmosis, AIDS dementia complex, disseminated Mycobacterium avium complex, and rare ADEs [hazard ratio, 2.35; 95% confidence interval, 1.76-3.13]), and mild (all other ADEs [hazard ratio, 1.47; 95% confidence interval, 1.08-2.00]). CONCLUSIONS: In the combination antiretroviral therapy era, mortality rates subsequent to an ADE depend on the specific diagnosis. The proposed classification of ADEs may be useful in clinical end point trials, prognostic studies, and patient management.
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STATEMENT OF PROBLEM: A tapered implant with continuously changing threads purported to provide stable tissue support and allow immediate function has been developed. Treatment success and stabilization of supporting tissues over time require documentation. PURPOSE: The purpose of this prospective, randomized, controlled, multicenter study was to evaluate changes in bone level and soft tissue behavior between the novel implant (NobelActive/NA) and a standard tapered implant (NobelReplace Tapered Groovy/NR) with regard to immediate function. MATERIAL AND METHODS: A total of 177 patients randomly allocated to 3 treatment groups (2 different test implant groups: NA Internal (n=117; internal connection) and External (n=82), and 1 standard treatment group, NR (n=126)) received 325 implants. Implants were placed into healed sites, and all but 6 implants were immediately nonocclusally loaded. Clinical and radiographic evaluations of treatment success, crestal bone levels, and soft tissue changes were performed at the time of placement and after 3, 6, and 12 months. Log-Rank test was used to analyze the differences in survival rate. Marginal bone level was compared using the Kruskal-Wallis test and Mann-Whitney U-test (alpha=.05). RESULTS: One-year cumulative survival rates were comparable (96.6% for NA Internal; 96.3% for NA External; 97.6% for NR; P=.852; Log-Rank). Mean (SD) change in bone level was -0.95 mm (1.37) for NA Internal, -0.64 mm (0.97) for NA External, and -0.63 mm (1.18) for NR (P=.589; Kruskal-Wallis). Stable soft tissues and significantly increased papilla scores (P<.001; Wilcoxon signed-rank) were observed for all implant types. CONCLUSIONS: The novel implants showed high survival rates as well as stable bone and soft tissue levels after 1 year, and may be recommended for clinical use, even under immediate function.
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A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.
Resumo:
In this paper we propose two cooperation schemes to compose new parallel variants of the Variable Neighborhood Search (VNS). On the one hand, a coarse-grained cooperation scheme is introduced which is well suited for being enhanced with a solution warehouse to store and manage the so far best found solutions and a self-adapting mechanism for the most important search parameters. This makes an a priori parameter tuning obsolete. On the other hand, a fine-grained scheme was designed to reproduce the successful properties of the sequential VNS. In combination with the use of parallel exploration threads all of the best solutions and 11 out of 20 new best solutions for the Multi Depot Vehicle Routing Problem with Time Windows were found.
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One of the most influential statements in the anomie theory tradition has been Merton’s argument that the volume of instrumental property crime should be higher where there is a greater imbalance between the degree of commitment to monetary success goals and the degree of commitment to legitimate means of pursing such goals. Contemporary anomie theories stimulated by Merton’s perspective, most notably Messner and Rosenfeld’s institutional anomie theory, have expanded the scope conditions by emphasizing lethal criminal violence as an outcome to which anomie theory is highly relevant, and virtually all contemporary empirical studies have focused on applying the perspective to explaining spatial variation in homicide rates. In the present paper, we argue that current explications of Merton’s theory and IAT have not adequately conveyed the relevance of the core features of the anomie perspective to lethal violence. We propose an expanded anomie model in which an unbalanced pecuniary value system – the core causal variable in Merton’s theory and IAT – translates into higher levels of homicide primarily in indirect ways by increasing levels of firearm prevalence, drug market activity, and property crime, and by enhancing the degree to which these factors stimulate lethal outcomes. Using aggregate-level data collected during the mid-to-late 1970s for a sample of relatively large social aggregates within the U.S., we find a significant effect on homicide rates of an interaction term reflecting high levels of commitment to monetary success goals and low levels of commitment to legitimate means. Virtually all of this effect is accounted for by higher levels of property crime and drug market activity that occur in areas with an unbalanced pecuniary value system. Our analysis also reveals that property crime is more apt to lead to homicide under conditions of high levels of structural disadvantage. These and other findings underscore the potential value of elaborating the anomie perspective to explicitly account for lethal violence.