Modelling fat and protein concentration curves for Irish dairy cows

peer-reviewedThe objective of this study was to acquire a well-fitting, single-equation model that would represent the fat and protein concentration curves of milk from Irish dairy cows. The dataset consisted of 16,086 records from both spring and autumn calving cows from both experimental and commercial herds. Many models cited in the literature to represent milk yield were examined for their suitability to model constituent curves. Models were tested for goodness-of-fit, adherence to the assumptions of regression analysis, and their ability to predict total fat and protein concentration for an entire lactation. Wilmink’s model best satisfied these criteria. It had the best Mean Square Prediction Error (goodness-of-fit) value, it satisfied the assumptions of regression analysis (multicollinearity, heteroskedasticity, autocorrelation and normality of distribution), and it predicted the actual concentration of the constituents to within 0.01 percentage point

In-flight boundary-layer measurements on a hollow cylinder at a Mach number of 3.0

Skin temperatures, shear forces, surface static pressures, boundary layer pitot pressures, and boundary layer total temperatures were measured on the external surface of a hollow cylinder that was 3.04 meters long and 0.437 meter in diameter and was mounted beneath the fuselage of the YF-12A airplane. The data were obtained at a nominal free stream Mach number of 3.0 (a local Mach number of 2.9) and at wall to recovery temperature ratios of 0.66 to 0.91. The local Reynolds number had a nominal value of 4,300,000 per meter. Heat transfer coefficients and skin friction coefficients were derived from skin temperature time histories and shear force measurements, respectively. In addition, boundary layer velocity profiles were derived from pitot pressure measurements, and a Reynolds analogy factor was obtained from the heat transfer and skin friction measurements. The measured data are compared with several boundary layer prediction methods

An autonomous fault detection, isolation, and recovery system for a 20-kHz electric power distribution test bed

Future space explorations will require long term human presence in space. Space environments that provide working and living quarters for manned missions are becoming increasingly larger and more sophisticated. Monitor and control of the space environment subsystems by expert system software, which emulate human reasoning processes, could maintain the health of the subsystems and help reduce the human workload. The autonomous power expert (APEX) system was developed to emulate a human expert's reasoning processes used to diagnose fault conditions in the domain of space power distribution. APEX is a fault detection, isolation, and recovery (FDIR) system, capable of autonomous monitoring and control of the power distribution system. APEX consists of a knowledge base, a data base, an inference engine, and various support and interface software. APEX provides the user with an easy-to-use interactive interface. When a fault is detected, APEX will inform the user of the detection. The user can direct APEX to isolate the probable cause of the fault. Once a fault has been isolated, the user can ask APEX to justify its fault isolation and to recommend actions to correct the fault. APEX implementation and capabilities are discussed

Reentry heat transfer analysis of the space shuttle orbiter

A structural performance and resizing finite element thermal analysis computer program was used in the reentry heat transfer analysis of the space shuttle. Two typical wing cross sections and a midfuselage cross section were selected for the analysis. The surface heat inputs to the thermal models were obtained from aerodynamic heating analyses, which assumed a purely turbulent boundary layer, a purely laminar boundary layer, separated flow, and transition from laminar to turbulent flow. The effect of internal radiation was found to be quite significant. With the effect of the internal radiation considered, the wing lower skin temperature became about 39 C (70 F) lower. The results were compared with fight data for space transportation system, trajectory 1. The calculated and measured temperatures compared well for the wing if laminar flow was assumed for the lower surface and bay one upper surface and if separated flow was assumed for the upper surfaces of bays other than bay one. For the fuselage, good agreement between the calculated and measured data was obtained if laminar flow was assumed for the bottom surface. The structural temperatures were found to reach their peak values shortly before touchdown. In addition, the finite element solutions were compared with those obtained from the conventional finite difference solutions

Detection of abnormal recordings in Irish milk recorded data

peer-reviewedThe objective of this study was to detect abnormal recordings of milk yield, fat concentration and protein concentration in Irish milk-recorded data. The data consisted of 14,956 records from both commercial and experimental herds with 92% of the recordings recorded manually and the remainder recorded electronically. The method used in this paper was a modified version of the method employed by the Animal Improvement Programs Laboratory in Maryland, USA and conformed with the guidelines outlined by the International Committee of Animal Recording. The results illustrate the effectiveness of detecting abnormal recordings in Irish milk records. The method described in this paper, defines the upper and lower limits for each production trait and these limits along with the slope parameters were used to determine if a recording was abnormal or not. Three percent of milk yield recordings, 5% of fat concentration recordings and less than 1% of protein concentration recordings were found to be abnormal. The proportion of values declared abnormal in manually recorded and electronically recorded data were examined and found to be significantly different for fat concentration

Anisotropy in Fracking: A Percolation Model for Observed Microseismicity

Hydraulic fracturing (fracking) using high pressures and a low viscosity fluid allow the extraction of large quantiles of oil and gas from very low permeability shale formations. The initial production of oil and gas at depth leads to high pressures and an extensive distribution of natural fractures which reduce the pressures. With time these fractures heal, sealing the remaining oil and gas in place. High volume fracking opens the healed fractures allowing the oil and gas to flow the horizontal productions wells. We model the injection process using invasion percolation. We utilize a 2D square lattice of bonds to model the sealed natural fractures. The bonds are assigned random strengths and the fluid, injected at a point, opens the weakest bond adjacent to the growing cluster of opened bonds. Our model exhibits burst dynamics in which the clusters extends rapidly into regions with weak bonds. We associate these bursts with the microseismic activity generated by fracking injections. A principal object of this paper is to study the role of anisotropic stress distributions. Bonds in the $y$-direction are assigned higher random strengths than bonds in the $x$-direction. We illustrate the spatial distribution of clusters and the spatial distribution of bursts (small earthquakes) for several degrees of anisotropy. The results are compared with observed distributions of microseismicity in a fracking injection. Both our bursts and the observed microseismicity satisfy Gutenberg-Richter frequency-size statistics.Comment: 14 pages, 10 figure