Visualizing engineering design data using a modified two-level self-organizing map clustering approach

Engineers tasked with designing large and complex systems are continually in need of decision-making aids able to sift through enormous amounts of data produced through simulation and experimentation. Understanding these systems often requires visualizing multidimensional design data. Visual cues such as size, color, and symbols are often used to denote specific variables (dimensions) as well as characteristics of the data. However, these cues are unable to effectively convey information attributed to a system containing more than three dimensions. Two general techniques can be employed to reduce the complexity of information presented to an engineer: dimension reduction, and individual variable comparison. Each approach can provide a comprehensible visualization of the resulting design space, which is vital for an engineer to decide upon an appropriate optimization algorithm. Visualization techniques, such as self-organizing maps (SOMs), offer powerful methods able to surmount the difficulties of reducing the complexity of n-dimensional data by producing simple to understand visual representations that quickly highlight trends to support decision-making. The SOM can be extended by providing relevant output information in the form of contextual labels. Furthermore, these contextual labels can be leveraged to visualize a set of output maps containing statistical evaluations of each node residing within a trained SOM. These maps give a designer a visual context to the data set’s natural topology by highlighting the nodal performance amongst the maps. A drawback to using SOMs is the clustering of promising points with predominately less desirable data. Similar data groupings can be revealed from the trained output maps using visualization techniques such as the SOM, but these are not inherently cluster analysis methods. Cluster analysis is an approach able to assimilate similar data objects into “natural groups” from an otherwise unknown prior knowledge of a data set. Engineering data composed of design alternatives with associated variable parameters often contain data objects with unknown classification labels. Consequently, identifying the correct classifications can be difficult and costly. This thesis applies a cluster analysis technique to SOMs to segment a high-dimensional dataset into “meta-clusters”. Furthermore, the thesis will describe the algorithm created to establish these meta-clusters through the development of several computational metrics involving intra and inter cluster densities. The results from this work show the presented algorithm’s ability to narrow a large-complex system’s plethora of design alternatives into a few overarching set of design groups containing similar principal characteristics, which saves the time a designer would otherwise spend analyzing numerous design alternatives

Performance of 19XB-2A Gas Turbine

An investigation of the 19XB-2A gas turbine is being conducted at the Cleveland laboratory to determine the effect on turbine performance of various inlet pressures, inlet temperatures, pressure ratios, and wheel speeds. The engine of which this turbine is a component is designed to operate at an air flow of 30 pounds per second at a compressor rotor speed of 17,000 rpm at sea-level conditions. At these conditions the total-pressure ratio is 2.08 across the turbine and the turbine inlet total temperature is 2000 degrees R. Runs have been made with turbine inlet total pressures of 20, 30, 40, and 45 inches of mercury absolute for a constant total pressure ratio across the turbine of 2.40, the maximum value that could be obtained. Additional runs have been made with total pressure ratios of 1.50 and 2.00 at an inlet total pressure of 45 inches of mercury absolute. All runs were made with an inlet total temperature of 800 degrees R over a range of corrected turbine wheel speeds from 40 to 150 percent of the corrected speed at the design point. The turbine efficiencies at these conditions are presented

Investigation of a Full-scale, Cascade-type Thrust Reverser

A double set of turning vanes was carried inside the jet tailpipe. To produce reverse thrust, the tailpipe opens into two side sections and the turning vanes move outward to form a V-shaped cascade, which deflects the exhaust-gas flow. Forward and reverse net thrust were measured over a range of engine speeds with the airplane stationary. Taxi tests were made to determine the comparative stopping distances using wheel braking and reverse thrust separately, and a combination of both. The effect of turning-vane spacing on thrust-reverser performance was determined by scale-model tests using unheated air

Hydrogen Bonding Between the Carbonyl Group and Wyoming Bentonite

The vibrational frequencies of atom to atom bonds within a molecule are a function of the bond energies. Each bond has its characteristic frequency, and most of these frequencies can be detected with the infrared spectrophotometer. When one compound reacts with another or is adsorbed on the surface of a solid, detectable frequency changes or shifts may occur. These changes or shifts yield valuable information about the bonds which are formed or broken

Stochastic 3D Navier‐Stokes Flow in Self‐Affine Fracture Geometries Controlled by Anisotropy and Channeling

This study presents a probabilistic analysis of 3D Navier‐Stokes (NS) fluid flow through 30 randomly generated sheared fractures with equal roughness properties (Hurst exponent = 0.8). The results of numerous 3D NS realizations are compared with the highly simplified local cubic law (LCL) solutions regarding flow orientations and regimes. The transition between linear and nonlinear flow conditions cannot be described with a generally valid critical Reynolds number urn:x-wiley:00948276:media:grl62319:grl62319-math-0001, but rather depends on the individual fracture\u27s void geometry. Over 10% reduction in flow is observed for increased global Re (>100) due to the increasing impact of nonlinear conditions. Furthermore, the fracture geometry promotes flow anisotropy and the formation of channels. Flow perpendicular to the shearing leads to increased channeling and fluid flow (∼40% higher) compared to flow parallel to the shearing. In the latter case, dispersed flow and irregular flow paths cause a reduction of LCL validity

Spatial Characterization of Channeling in Sheared Rough‐Walled Fractures in the Transition to Nonlinear Fluid Flow

Accurate quantification of spatially resolved fluid flow within fractures is crucial for successful reservoir development, such as Enhanced Geothermal Systems. This study presents an innovative workflow designed to model and characterize preferential flow paths (channels) within rough-walled shear fractures. A set of 30 rough-walled self-affine fractures, all possessing identical roughness characteristics, is stochastically generated. By solving the nonlinear Navier-Stokes equations in 420 individual realizations, the transition from linear to nonlinear flow regimes and the two extreme flow directions perpendicular and parallel to the shearing are numerically captured. A distinguishing feature of this approach is its comprehensive statistical analysis, which encompasses both the geometric and transport properties of flow paths in the non-simplified three-dimensional fractured void space under typical geothermal flow conditions. In a perpendicular orientation of flow and shearing, fluid flow exhibits pronounced localization, with more than one-third of the volumetric flow concentrated within 15% of the fracture volume. In contrast, parallel to the shearing, a complex pattern of individual tortuous channels emerges, with flow occurring in 22% of the void space. Nonlinear effects primarily manifest outside these channels, suggesting that complex flow phenomena may dominate irregular fracture structures, such as contact zones or asperities. In the parallel case, increased flow rates lead to an amplification of channeling processes resulting in less affected volume and diminished tortuosity of the main flow path, while in perpendicular orientation nonlinear effects are only of minor importance. The small-scale flow regime of both extreme cases tends to converge with increasing flow rates