The Nugget Formation in the Anschutz Ranch East field, northeast Utah and southwest Wyoming, provides an exceptional example of how primary eolian rock properties have a considerable influence on the style of structural deformation. Both new and existing subsurface data were integrated for an overall characterization of sedimentologic and diagenetic heterogeneities, which demonstrate relationships with different styles of structural compartmentalization in reservoirs. The Anschutz Ranch East field is a large asymmetric anticlinal trap in the Utah-Wyoming thrust belt. Three cores were analyzed in order to investigate brittle deformation in eolian facies: dune, apron, and interdune. Selected cores are located along the back limb of the main structure and are nearly perpendicular to the fold axis. Each eolian facies appears to have an associated style of deformation that generally occurs within this tectonic setting. Within the dune facies, deformation bands are the most common style of deformation, unless a fault is present; when faults are present open fractures and breccia occur. In the apron facies, open fractures are more prevalent; however deformation bands are still very frequent. The primary styles of brittle deformation observed in interdune facies are breccias and closed fractures. This relationship between facies and rheology also correlates with porosity. These results support a hypothesis that high porosity rocks tend to be weaker and develop deformation bands, while low porosity rocks have a greater strength and will deform brittlely.

The overall goal was to understand the capabilities of a dairy based meat alternative. This was done in three phases: 1) the production of a dairy protein gel as a base for a dairy based meat alternative, 2) texturization of the dairy protein gel base to produce a nugget like texture, and 3) a consumer test to determine the acceptability of the dairy based nugget compared to meat and meat alternatives on the market. For phase I, a dairy protein gel base was tested to understand the textural attributes. Milk to whey percentages and level of acidification were examined to determine their effects on instrumental textural attributes of the protein gel. The milk to whey percentages and level of acidification that were tested were 5/95, 10/90, and 15/85, and pH 5.70-5.60, 5.15-5.05, and 4.6-4.5; respectively. The texture was objectively measured using a texture analyzer. The results showed that there was an increase in the hardness, gumminess and chewiness which was associated with an increase of the milk to whey ratio. Also a firmer dairy protein gel was produced using a low pH. A milk to whey percentage of 15/85 and a pH of 4.6-4.5 produced the highest overall instrumental textural attributes, specifically . For phase II, the dairy protein gel composed of a milk to whey ratio of 15/85 and pH of 4.6 was evaluated in the formulation of a dairy based nugget. The grinding of the dairy protein gel was used to determine if different size grinding plates and the presence of a gum can influence the textural attributes of the dairy protein gel. The dairy protein gel base was evaluated by a trained sensory panel to compare to the results of the objective texture analyzer. The dairy protein gel was processed using a meat grinder with a grind size of 3 mm, 6 mm and a blend of 4 parts 6 mm grinded and 1 part 3 mm. The increase in the grind size produced an increased instrumental hardness, springiness, cohesiveness, chewiness and gumminess. The usage of gum in the dairy protein gel system produced a higher instrumental adhesiveness. The sensory results showed that an increase in the grind size increased the sensory attributes; hardness, cohesiveness, chewiness and adhesiveness. The use of gum in the system had no influence on the sensory textural attributes. Both the texture analyzer and trained sensory testing showed a similar trend for the texture attributes. No correlation between the texture analyzer and sensory was found. This was a surprise because literature indicates there are significant correlations between instrumental textural attributes and sensory texture attributes. The lack of correlation may be explained by the variability of the panelists (P-value<0.05) for each sample. For phase III, an acceptability test was performed on untrained consumers of chicken nuggets to determine if the dairy based meat alternative was acceptable compared to meat nuggets and meat alternatives on the market. Texture, flavor, and appearance were evaluated by a consumer panel. The consumers evaluated the dairy based meat alternative and concluded that the appearance, texture and flavor needed improvement. From this research, it was concluded that a dairy based meat alternative can be created to imitate meat and meat alternative textures. By understanding the processing conditions to produce the dairy protein gel base and grinding of the product, an acceptable meat alternative can be produced. Dairy based meat alternative texture attributes were produced from a milk to whey percentage of 15/85 and a pH of 4.6, and a large grind plate of 6 mm with the use of methylcellulose.

In this paper we discuss an algorithm for the construction of D-optimal experimental designs for the parameters in a regression model when the errors have a correlation structure. We show that design points can collapse under the presence of some covariance structures and a so called nugget can be employed in a natural way. We also show that the information of equidistant design on covariance parameter is increasing with the number of design points under exponential variogram, however these designs are not D-optimal. Also in higher dimensions the exponential structure without nugget leads to collapsing of the D-optimal design when also parameters of covariance structure are of interest. However, if only trend parameters are of interest, the designs covering uniformly the whole design space are very efficient. For illustration some numerical examples are also included. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

During the design process for an aerospace vehicle, decision-makers must have an accurate understanding of how each choice will affect the vehicle and its performance. This understanding is based on experiments and, increasingly often, computer models. In general, as a computer model captures a greater number of phenomena, its results become more accurate for a broader range of problems. This improved accuracy typically comes at the cost of significantly increased computational expense per analysis. Although rapid analysis tools have been developed that are sufficient for many design efforts, those tools may not be accurate enough for revolutionary concepts subject to grueling flight conditions such as transonic or supersonic flight and extreme angles of attack. At such conditions, the simplifying assumptions of the rapid tools no longer hold. Accurate analysis of such concepts would require models that do not make those simplifying assumptions, with the corresponding increases in computational effort per analysis. As computational costs rise, exploration of the design space can become exceedingly expensive. If this expense cannot be reduced, decision-makers would be forced to choose between a thorough exploration of the design space using inaccurate models, or the analysis of a sparse set of options using accurate models. This problem is exacerbated as the number of free parameters increases, limiting the number of trades that can be investigated in a given time. In the face of limited resources, it can become critically important that only the most useful experiments be performed, which raises multiple questions: how can the most useful experiments be identified, and how can experimental results be used in the most effective manner? This research effort focuses on identifying and applying techniques which could address these questions. The demonstration problem for this effort was the modeling of a reusable booster vehicle, which would be subject to a wide range of flight conditions while returning to its launch site after staging. Contour-based sampling, an adaptive sampling technique, seeks cases that will improve the prediction accuracy of surrogate models for particular ranges of the responses of interest. In the case of the reusable booster, contour-based sampling was used to emphasize configurations with small pitching moments; the broad design space included many configurations which produced uncontrollable aerodynamic moments for at least one flight condition. By emphasizing designs that were likely to trim over the entire trajectory, contour-based sampling improves the predictive accuracy of surrogate models for such designs while minimizing the number of analyses required. The simplified models mentioned above, although less accurate for extreme flight conditions, can still be useful for analyzing performance at more common flight conditions. The simplified models may also offer insight into trends in the response behavior. Data from these simplified models can be combined with more accurate results to produce useful surrogate models with better accuracy than the simplified models but at less cost than if only expensive analyses were used. Of the data fusion techniques evaluated, Ghoreyshi cokriging was found to be the most effective for the problem at hand. Lastly, uncertainty present in the data was found to negatively affect predictive accuracy of surrogate models. Most surrogate modeling techniques neglect uncertainty in the data and treat all cases as deterministic. This is plausible, especially for data produced by computer analyses which are assumed to be perfectly repeatable and thus truly deterministic. However, a number of sources of uncertainty, such as solver iteration or surrogate model prediction accuracy, can introduce noise to the data. If these sources of uncertainty could be captured and incorporated when surrogate models are trained, the resulting surrogate models would be less susceptible to that noise and correspondingly have better predictive accuracy. This was accomplished in the present effort by capturing the uncertainty information via nuggets added to the Kriging model. By combining these techniques, surrogate models could be created which exhibited better predictive accuracy while selecting the most informative experiments possible. This significantly reduced the computational effort expended compared to a more standard approach using space-filling samples and data from a single source. The relative contributions of each technique were identified, and observations were made pertaining to the most effective way to apply the separate and combined methods.

Nomenclature for the Upper Triassic and Lower Jurassic strata along the south flank of the Uinta Mountains has been somewhat confusing because of the position of the study area between southern Wyoming, where one set of names is used, and central/southern Utah where a different set of formation names is used. The Nugget Sandstone or Glen Canyon Sandstone of the eastern Uinta Mountains overlies the Upper Triassic Popo Agie or Chinle Formation. The nature of the contact between these two formations is unclear both in stratigraphic location and conformability. The Chinle Formation consists, in ascending order, of the Gartra Member, the purple unit, the ocher unit, and the upper red unit. The overlying Nugget Sandstone consists of two members, the lower Bell Springs Member and the overlying unnamed cross-bedded member, typically believed to be Navajo Sandstone equivalent. These two units of the Nugget Sandstone are thought to represent the Glen Canyon Group of the Colorado Plateau, although no obvious Wingate or Kayenta Formation equivalents have been recognized. The Bell Springs Member contains abundant fine-grained, ripple-laminated sandstones, red and green mudstones, occasional mudcracks and salt casts, evidence of burrowing and exposure, and some medium- to coarse-grained sandstones with small-scale (30-40 cm high) cross-beds. This member was deposited in a marine tidal flat environment, quite different from the mainly eolian environment of the rest of the Nugget Sandstone. The Bell Springs Member appears to be entirely Upper Triassic, based upon dinosaur tracks, while the upper windblown unit's age is unknown, but probably straddles the Triassic-Jurassic boundary. During mapping in the Donkey Flat, Steinaker Reservoir, Dry Fork, and Lake Mountain quadrangles, the Bell Springs Member of the Nugget Sandstone was mapped as a separate unit.

Conventional resistance spot welds are not visible from the outside. Therefore, it is not straightforward to evaluate the joint quality non-destructively. The pulse-echo method of manual ultrasonic is widely used for non-destructive testing. Another option is the passive magnetic flux density testing, which is being developed at Technische Universität Dresden, Germany. The spot weld is magnetized in the normal direction and the residual magnetic flux density is measured on top of the surface of the joint. This method is suitable for spot welds on typical car body steels. Previous investigations show that the magnetic properties of the materials influence the test result. In order to develop this new non-destructive testing method further, it is necessary to know the magnetic properties of the different microstructure regions of a spot weld. This article focuses on methods to measure and evaluate the magnetic properties of these regions, especially of the base material and the weld. Different measuring methods and approaches are presented and compared with each other. Based on the results, recommendations for future measurements for magnetic characterizations are given.

The Al-Zn-Mg-Cu (7XXX series) alloys are amongst the strongest aluminum available. However, they are considered unweldable with conventional fusion techniques due to the negative effects that arise with conventional welding, including hydrogen porosity, hot cracking, and stress corrosion cracking. For this reason, friction stir welding has emerged as the preferred technique to weld 7XXX series alloys. Aluminum 7449 is one of the highest strength 7XXX series aluminum alloy. This is due to its higher zinc content, which leads to a higher volume fraction of eta' precipitates. It is typically used in a slight overaged condition since it exhibits better corrosion resistance. In this work, the welds of friction stir welded aluminum 7449 were studied extensively. Specific focus was placed in the heat affected zone (HAZ) and nugget. Thermocouples were used in the heat affected zone for three different depths to obtain thermal profiles as well as cooling/heating profiles. Vicker microhardness testing, transmission electron microscope (TEM), and differential scanning calorimeter (DSC) were used to characterize the welds. Two different tempers of the alloy were used, a low overaged temper and a high overaged temper. A thorough comparison of the two different tempers was done. It was found that highly overaged aluminum 7449 tempers show better properties for friction stir welding. A heat gradient along with a high conducting plate (Cu) used at the bottom of the run, resulted in welds with two separate microstructures in the nugget. Due to the microstructure at the bottom of the nugget, higher strength than the base metal is observed. Furthermore, the effects of natural aging and artificial aging were studied to understand re-precipitation. Large improvements in strength are observed after natural aging throughout the welds, including improvements in the HAZ.