Analysis of Three-Dimensional Protein Images

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the three-dimensional (3D) conformation of a protein, yet it remains labor intensive and relies on an expert's ability to derive and evaluate a protein scene model. In this paper, the problem of protein structure determination is formulated as an exercise in scene analysis. A computational methodology is presented in which a 3D image of a protein is segmented into a graph of critical points. Bayesian and certainty factor approaches are described and used to analyze critical point graphs and identify meaningful substructures, such as alpha-helices and beta-sheets. Results of applying the methodologies to protein images at low and medium resolution are reported. The research is related to approaches to representation, segmentation and classification in vision, as well as to top-down approaches to protein structure prediction.Comment: See http://www.jair.org/ for any accompanying file

Critical parameters for coarse coal underground slurry haulage systems

Factors are identified which must be considered in meeting the requirements of a transportation system for conveying, in a pipeline, the coal mined by a continuous mining machine to a storage location neat the mine entrance or to a coal preparation plant located near the surface. For successful operation, the slurry haulage the system should be designed to operated in the turbulent flow regime at a flow rate at least 30% greater than the deposition velocity (slurry flow rate at which the solid particles tend to settle in the pipe). The capacity of the haulage system should be compatible with the projected coal output. Partical size, solid concentration, density, and viscosity of the suspension are if importance as well as the selection of the pumps, pipes, and valves. The parameters with the greatest effect on system performance ar flow velocity, pressure coal particle size, and solids concentration

A novel powder factor based bench blast design method for large surface coal mines

Large surface coal mines in Wyoming\u27s Powder River Basin ship millions of tons of coal per annum, moving millions of cubic yards of overburden to mine the coal. Much of this volume is blasted in the form of benches, a common mining technique. Increases in production and scale of equipment in the past thirty-five years have created a paradigm shift for drill and blast personnel at these large surface mines, and the explosives industry has yet to create a blast design method specifically tailored for large surface coal mine bench blasting. This research examines the typical scale of bench blasting at large surface coal mines, develops a new method of design tailored for these operations, and tests the new method against two widely accepted traditional blast design methods. Novel contributions of the research include a new universal scale of energy distribution known as Available Energy, and an entirely powder factor based blast design method that uses cut width as part of the design process. Numerical comparison testing is done at both small borehole diameters (corresponding to the original domain of the traditional blast design methods) and at large borehole diameters. A comparison of the new method and existing major methods of traditional blast design is monitored graphically, and linear regression is used to track the improvement of the accuracy of the match. Finally, the new design method is presented in nomograph form to facilitate use in the field. Development of the nomograph is discussed and sample nomographs for specific design conditions are included. Recommendations for future work and broader applications of the Available Energy paradigm are given to conclude the dissertation. --Abstract, page iii

Immiscible displacement of trapped oil through experimental and data mining techniques.

Extensive experimental and data mining techniques have been applied to investigate the potential and competitiveness of gases used in immiscible gas-enhanced oil recovery (EOR) processes. Methane (CH4), Nitrogen (N2), Air (21%O2/N2) and Carbon Dioxide (CO2) are some of the gases injected in reservoirs to displace trapped oil from reservoir pores. The EOR screening process has been well-documented in the literature. However, for immiscible gas EOR technology, very few resources are available for evaluating the selection and performance criteria for commonly-injected EOR gases; immiscible EOR gases are usually lumped up in published screening models, and the gases are reportedly selected based on availability and accessibility, rather than on technical criteria such as displacement efficiency. Furthermore, available experimental studies have investigated EOR gases only separately. This research has been able to fill these gaps and more, through rigorous data mining and gas experiments processes. The methodology utilised empirical approaches set in three phases. Phase I applied data mining techniques to 10,850 data from 484 EOR field projects, to identify twenty-four EOR geological and engineering quantities, and objective functions. Phase II utilised Phase I outcomes to design and execute a set of rigorous gas experiments, involving 1,920 experimental runs (comprising five reservoir analogous core samples, eight gases, eight isobars and six isotherms), to generate and analyse 15,360 experimental data points. Several established and modified constitutive equations were used to model gas responses to EOR geological and engineering quantities. In Phase III, Phase I and Phase II results were coupled for the purpose of knowledge validation and application. This research's outcomes have contributed to reservoir engineering practice and knowledge in providing useful information on EOR gases' competitiveness. Results from Phase I indicate that immiscible gas EOR can be unbundled through data mining and clustering techniques. A novel screening model has been developed for immiscible gas EOR that incorporates sensitivity and criticality markers for each petrophysical quantity investigated. It has been demonstrated in Phase II that, in a heterogeneous system, CH4 is the most competitive gas for ten geological and engineering quantities and objective functions, such as Volumetric Rate, Interstitial Velocity, and Well Density. Similarly, CO2 is most competitive for ten other quantities investigated, such as Mobility and Interstitial Momentum. N2 is the most competitive for the cost of injected gas per area coverage. Air is second-best for several objective functions. Suffice to state that at some structural settings and operational conditions (such as porosity, pore size, surface area and temperature), the competitiveness ranking of the gases switches position. Such was observed between N2 and CO2 in low porosity (4% and 3%) core samples. EOR gas mixtures and non EOR gases - such as 20% CH4/N2, He, and Ar - were added to the experiments to investigate the relationship between gas flow and gas properties. It was observed that the structural variability (heterogeneity) of the system distorts the correlation between gas properties, such as molecular weight, and the performance criteria of the respective gases. The results from Phase I and II couple significantly in Phase III. Based on well number and placement, it has been demonstrated that the well placement of CH4, CO2, and Air favours a negative pore size gradient, while N2 favours a positive gradient. The economic analysis demonstrates that CO2 incurs the least cumulative injectant cost and the highest capital expenditure cost (CAPAX). The three Phases validate the field and laboratory well density profile. CH4 requires the least well density (0.2 well/acre, 1.0 well/cm2) compared to CO2 (0.7 well/acre, 2.0 well/cm2). In some analyses, it was discovered that gas mixture, such as 20%CH4/N2, performs better than when the individual component gas acted alone. Single-phase and two-phase relationships have been analytically and experimentally coupled. The experimental findings at low pressure could also lend utility to the gas separation, fluidised bed, and catalytic reaction processes and industry

A review of data visualization: opportunities in manufacturing sequence management.

Data visualization now benefits from developments in technologies that offer innovative ways of presenting complex data. Potentially these have widespread application in communicating the complex information domains typical of manufacturing sequence management environments for global enterprises. In this paper the authors review the visualization functionalities, techniques and applications reported in literature, map these to manufacturing sequence information presentation requirements and identify the opportunities available and likely development paths. Current leading-edge practice in dynamic updating and communication with suppliers is not being exploited in manufacturing sequence management; it could provide significant benefits to manufacturing business. In the context of global manufacturing operations and broad-based user communities with differing needs served by common data sets, tool functionality is generally ahead of user application

Investigating the micro mechanics of cemented sand using DEM

The discrete element method has been used to investigate the micro mechanics of cemented sand. High pressure drained triaxial tests are modelled in 3D using a flexible membrane which allows the correct deformation to develop. Simulations with up to 12 MPa confining pressure are presented, which are compared with laboratory experiments on a sand with a range of cement contents. Cementation is modelled using ‘parallel bonds’, and various parameters and strength distributions are investigated. Varying levels of cementation are successfully modelled, with the correct qualitative behaviour observed, and the separate effects of cementation and confining pressures demonstrated. The triaxial behaviour is found to be highly influenced by the distribution of bond strengths