Feeding level and frequency for freshwater angelfish

The objective of this study was to determine the optimal feeding level and feeding frequency for the culture of freshwater angelfish (Pterophyllum scalare). A randomized block design in a factorial scheme (3 × 2) with three feeding levels (30, 60 and 90 g/kg of body weight (BW)/day) and two feeding frequencies (1x and 2x/day) was set up in duplicate, representing 24 experimental units. Data were analyzed using two-way ANOVA and the Tukey test for comparison between means. After 84 days, results indicated that both factors influenced fish performance. No interaction between these factors was, however, observed. Increased feeding level and feeding frequency resulted in increased feed intake. The feed conversion ratio was negatively affected by feeding level, but not affected by feeding frequency. Final weights were higher when fish were fed twice daily, at levels of 60 or 90 g/kg BW/day. Specific growth rate was higher when fish received 60 or 90 g/kg BW/day, regardless of the feeding frequency. Survival was not affected by any treatment, with mean survival rates higher than 90%. It is recommended that juveniles be fed at a level of 60 g/kg BW/day with a minimum of two meals per day, to attain optimal survival, growth and feed efficiency.

TEST-ANALYSIS MODEL CORRELATION AND CALIBRATION OF A MULTI-COMPONENT PLASTIC PART

The goal of this project is to learn the necessary steps to create a finite element model, which can accurately predict the dynamic response of a Kohler Engines Heavy Duty Air Cleaner (HDAC). This air cleaner is composed of three glass reinforced plastic components and two air filters. Several uncertainties arose in the finite element (FE) model due to the HDAC’s component material properties and assembly conditions. To help understand and mitigate these uncertainties, analytical and experimental modal models were created concurrently to perform a model correlation and calibration. Over the course of the project simple and practical methods were found for future FE model creation. Similarly, an experimental method for the optimal acquisition of experimental modal data was arrived upon. After the model correlation and calibration was performed a validation experiment was used to confirm the FE models predictive capabilities.

Bayesian Estimation of Small Proportions Using Binomial Group Test

Group testing has long been considered as a safe and sensible relative to one-at-a-time testing in applications where the prevalence rate p is small. In this thesis, we applied Bayes approach to estimate p using Beta-type prior distribution. First, we showed two Bayes estimators of p from prior on p derived from two different loss functions. Second, we presented two more Bayes estimators of p from prior on π according to two loss functions. We also displayed credible and HPD interval for p. In addition, we did intensive numerical studies. All results showed that the Bayes estimator was preferred over the usual maximum likelihood estimator (MLE) for small p. We also presented the optimal β for different p, m, and k.

Design Optimization of Modern Machine-drive Systems for Maximum Fault Tolerant and Optimal Operation

Modern electric machine drives, particularly three phase permanent magnet machine drive systems represent an indispensable part of high power density products. Such products include; hybrid electric vehicles, large propulsion systems, and automation products. Reliability and cost of these products are directly related to the reliability and cost of these systems. The compatibility of the electric machine and its drive system for optimal cost and operation has been a large challenge in industrial applications. The main objective of this dissertation is to find a design and control scheme for the best compromise between the reliability and optimality of the electric machine-drive system. The effort presented here is motivated by the need to find new techniques to connect the design and control of electric machines and drive systems. A highly accurate and computationally efficient modeling process was developed to monitor the magnetic, thermal, and electrical aspects of the electric machine in its operational environments. The modeling process was also utilized in the design process in form finite element based optimization process. It was also used in hardware in the loop finite element based optimization process. The modeling process was later employed in the design of a very accurate and highly efficient physics-based customized observers that are required for the fault diagnosis as well the sensorless rotor position estimation. Two test setups with different ratings and topologies were numerically and experimentally tested to verify the effectiveness of the proposed techniques. The modeling process was also employed in the real-time demagnetization control of the machine. Various real-time scenarios were successfully verified. It was shown that this process gives the potential to optimally redefine the assumptions in sizing the permanent magnets of the machine and DC bus voltage of the drive for the worst operating conditions. The mathematical development and stability criteria of the physics-based modeling of the machine, design optimization, and the physics-based fault diagnosis and the physics-based sensorless technique are described in detail. To investigate the performance of the developed design test-bed, software and hardware setups were constructed first. Several topologies of the permanent magnet machine were optimized inside the optimization test-bed. To investigate the performance of the developed sensorless control, a test-bed including a 0.25 (kW) surface mounted permanent magnet synchronous machine example was created. The verification of the proposed technique in a range from medium to very low speed, effectively show the intelligent design capability of the proposed system. Additionally, to investigate the performance of the developed fault diagnosis system, a test-bed including a 0.8 (kW) surface mounted permanent magnet synchronous machine example with trapezoidal back electromotive force was created. The results verify the use of the proposed technique under dynamic eccentricity, DC bus voltage variations, and harmonic loading condition make the system an ideal case for propulsion systems.

Atmospheric calibration for sub-millimeter radio astronomy

This thesis is focused on improving the calibration accuracy of sub-millimeter astronomical observations. The wavelength range covered by observational radio astronomy has been extended to sub-millimeter and far infrared with the advancement of receiver technology in recent years. Sub-millimeter observations carried out with airborne and ground-based telescopes typically suffer from 10% to 90% attenuation of the astronomical source signals by the terrestrial atmosphere. The amount of attenuation can be derived from the measured brightness of the atmospheric emission. In order to do this, the knowledge of the atmospheric temperature and chemical composition, as well as the frequency-dependent optical depth at each place along the line of sight is required. The altitude-dependent air temperature and composition are estimated using a parametrized static atmospheric model, which is described in Chapter 2, because direct measurements are technically and financially infeasible. The frequency dependent optical depth of the atmosphere is computed with a radiative transfer model based on the theories of quantum mechanics and, in addition, some empirical formulae. The choice, application, and improvement of third party radiative transfer models are discussed in Chapter 3. The application of the calibration procedure, which is described in Chapter 4, to the astronomical data observed with the SubMillimeter Array Receiver for Two Frequencies (SMART), and the German REceiver for Astronomy at Terahertz Frequencies (GREAT), is presented in Chapters 5 and 6. The brightnesses of atmospheric emission were fitted consistently to the simultaneous multi-band observation data from GREAT at 1.2 ∼ 1.4 and 1.8 ∼ 1.9 THz with a single set of parameters of the static atmospheric model. On the other hand, the cause of the inconsistency between the model parameters fitted from the 490 and 810 GHz data of SMART is found to be the lack of calibration of the effective cold load temperature. Besides the correctness of atmospheric modeling, the stability of the receiver is also important to achieving optimal calibration accuracy. The stabilities of SMART and GREAT are analyzed with a special calibration procedure, namely the “load calibration". The effects of the drift and fluctuation of the receiver gain and noise temperature on calibration accuracy are discussed in Chapters 5 and 6. Alternative observing strategies are proposed to combat receiver instability. The methods and conclusions presented in this thesis are applicable to the atmospheric calibration of sub-millimeter astronomical observations up to at least 4.7 THz (the H channel frequency of GREAT) for observations carried out from ∼ 4 to 14 km altitude. The procedures for receiver gain calibration and stability test are applicable to other instruments using the same calibration approach as that for SMART and GREAT. The structure of the high performance, modular, and extensible calibration program used and further developed for this thesis work is presented in the Appendix C.