Regression models with correlated errors lead to nonadditivity of the information matrix. This makes the usual approach of design optimization (approximation with a continuous design, application of an equivalence theorem, numerical calculations by a gradient algorithm) impossible. A method is presented that allows the construction of a gradient algorithm by altering the information matrices through adding of supplementary noise. A heuristic is formulated to circumvent the nonconvexity problem and the method is applied to typical examples from the literature. (author's abstract) / Series: Forschungsberichte / Institut für Statistik

At micrometer length scales of material removal, size effect is observed in mechanical micro-cutting where the energy per unit volume i.e. specific cutting energy increases nonlinearly as the uncut chip thickness is reduced from several hundred microns to a few microns (or less). There is no consensus in the literature on the cutting mechanism that causes this size effect. Noticeable discrepancy is also observed in the surface roughness produced at small feeds in micro-turning between the theoretical and the measured roughness. To date, there has been little effort made to develop a detailed process model for micro-cutting to accurately predict the size effect in specific cutting energy, and to develop a fundamental understanding of surface generation at the low feeds typical of micro-cutting processes. The main objective of this thesis is therefore to develop a predictive process model of micro-cutting of ductile metals that is capable of accurately predicting the size effect in specific cutting energy based on strain gradient based material strengthening considerations. In addition, this thesis attempts to explain the discrepancy between the theoretical and measured surface roughness at small feeds in micro-turning via a model that accounts for the size effect due to material strengthening. A coupled thermo-mechanical finite element model formulation incorporating strain gradient plasticity is developed to simulate orthogonal micro-cutting process. The thermo-mechanical model is experimentally validated in orthogonal micro-cutting of a strain rate insensitive aluminum alloy Al5083-H116. The model is then used to analyze the contributions of two major material strengthening factors to the size effect in specific cutting energy: strain gradient and temperature. The effects of cutting edge radius on the specific cutting energy and its role relative to the material length scale arising from strain gradient plasticity are also examined. A surface roughness model for micro-turning that incorporates the effects of kinematic roughness, cutting edge roughness and surface roughening due to plastic side flow is developed and shown to explain the observed discrepancy between the theoretical and measured surface roughness in micro-cutting. In addition, the model is found to accurately capture the increase in surface roughness at very low feeds.

A relatively new preconditioning technique called support graph preconditioning has many merits over the traditional incomplete factorization based methods. A major limitation of this technique is that it is applicable to symmetric diagonally dominant matrices only. This work presents a technique that can be used to transform the symmetric positive definite matrices arising from elliptic finite element problems into symmetric diagonally dominant M-matrices. The basic idea is to approximate the element gradient matrix by taking the gradients along chosen edges, whose unit vectors form a new coordinate system. For Lagrangian elements, the rows of the element gradient matrix in this new coordinate system are scaled edge vectors, thus a diagonally dominant symmetric semidefinite M-matrix can be generated to approximate the element stiffness matrix. Depending on the element type, one or more such coordinate systems are required to obtain a global nonsingular M-matrix. Since such approximation takes place at the element level, the degradation in the quality of the preconditioner is only a small constant factor independent of the size of the problem. This technique of element coordinate transformations applies to a variety of first order Lagrangian elements. Combination of this technique and other techniques enables us to construct an M-matrix preconditioner for a wide range of second order elliptic problems even with higher order elements. Another contribution of this work is the proposal of a new variant of Vaidya’s support graph preconditioning technique called modified domain partitioned support graph preconditioners. Numerical experiments are conducted for various second order elliptic finite element problems, along with performance comparison to the incomplete factorization based preconditioners. Results show that these support graph preconditioners are superior when solving ill-conditioned problems. In addition, the domain partition feature provides inherent parallelism, and initial experiments show a good potential of parallelization and scalability of these preconditioners.

The purpose of the inverse-transport problems that we address is to reconstruct the material distribution inside an unknown object undergoing a nondestructive evaluation. We assume that the object is subjected to incident beams of photons or particles and that the exiting radiation is measured with detectors around the periphery of the object. In the present work we focus on problems in which radiation can undergo significant scattering within the optically thick object. We develop a set of reconstruction strategies to infer the material distribution inside such objects. When we apply these strategies to a set of neutron-tomography test problems we find that the results are substantially superior to those obtained by previous methods. We first demonstrate that traditional analytic methods such as filtered back projection (FBP) methods do not work for very thick, highly scattering problems. Then we explore deterministic optimization processes, using the nonlinear conjugate gradient iterative updating scheme to minimize an objective functional that characterizes the misfits between forward predicted measurements and actual detector readings. We find that while these methods provide more information than the analytic methods such as FBP, they do not provide sufficiently accurate solutions of problems in which the radiation undergoes significant scattering. We proceed to present some advances in inverse transport methods. Our strategies offer several advantages over previous reconstruction methods. First, our optimization procedure involves the systematic use of both deterministic and stochastic methods, using the strengths of each to mitigate the weaknesses of the other. Another key feature is that we treat the material (a discrete quantity) as the unknown, as opposed to individual cross sections (continuous variables). This changes the mathematical nature of the problem and greatly reduces the dimension of the search space. In our hierarchical approach we begin by learning some characteristics of the object from relatively inexpensive calculations, and then use knowledge from such calculations to guide more sophisticated calculations. A key feature of our strategy is dimension-reduction schemes that we have designed to take advantage of known and postulated constraints. We illustrate our approach using some neutron-tomography model problems that are several mean-free paths thick and contain highly scattering materials. In these problems we impose reasonable constraints, similar to those that in practice would come from prior information or engineering judgment. Our results, which identify exactly the correct materials and provide very accurate estimates of their locations and masses, are substantially better than those of deterministic minimization methods and dramatically more efficient than those of typical stochastic methods.

The purpose of this study is to develop an understanding of the behavior of metallic structures in small scales. Structural materials display strong size dependence when deformed non-uniformly into the inelastic range. This phenomenon is widely known as size effect. The primary focus of this study is on developing analytical models to predict some of the most commonly observed size effects in structural metals and validating them by comparing with experimental results. A nonlocal rate-dependent and gradient dependent theory of plasticity on a thermodynamically consistent framework is adopted for this purpose. The developed gradient plasticity theory is applied to study size effects observed in biaxial and thermal loading of thin films and indentation tests. One important intrinsic material property associated with this study is material length scale. The work also presents models for predicting length scales and discusses their physical interpretations. It is found that the proposed theory is successful for the interpretation of indentation size effects in micro/nano-hardness when using pyramidal or spherical indenters and gives sound interpretation of the size effects in thin films under biaxial or thermal loading.

Tens of millions of dollars have been spent to control Tamarix (saltcedar) trees along waterways in the Southwestern United States for the purpose of increasing streamflow yet no increase in streamflow has been demonstrated. The Pecos River Ecosystem Project (PREP) served as a case study to characterize surface and groundwater interaction along the Pecos River in Texas, assess the influence of saltcedar transpiration on stream stage and water table fluctuations, and evaluate the impacts of large-scale saltcedar control on baseflows. This is the first study that has investigated the influence of saltcedar transpiration on surface and groundwater interaction and the first to provide a mechanistic explanation for the lack of measurable increase in streamflow. Neither saltcedar transpiration nor saltcedar removal influenced hydraulic gradients, streambank seepage, or stream elevations. The results of the plot scale studies indicate saltcedar transpiration along the Pecos River is lower than reported elsewhere and therefore may not yield detectable increases in baseflow. To extend the study to a much larger scale, we analyzed annual baseflows at the downstream end of 340 km river reach from 1999 (pretreatment) through 2009. Surprisingly, baseflows declined for four years after the project began despite additional acreages of saltcedar treatment each year. However, baseflow surged in 2005 and remained higher than the pretreatment year (1999) through 2009. Additional detailed analyses of reservoir release and delivery records and rainfall are needed to better understand contributions of rainfall and flow regulation to this increase. Tracer based studies to determine the relative contributions of releases and groundwater would also enable a better interpretation of the change in baseflows. We did not investigate any other reported benefits, such as restoration of native plant species, or reduced soil salinity, of saltcedar control.

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The fish disease epidemiology is urgent to be investigated for the surveillance and prevention. The diseased fish showed splenomegaly with diffusion of white nodules and microscopical granulomatous formation. It is important to develop a method of pathogens isolated from clinical samples with serial dilution method and disc diffusion method. Representative colonies were selected from diseased cobia on BHIA plate and were inoculated onto MacConkey agar, TCBS agar, and blood agar. The cage-culture of the different bacterial groups detected in the survey of bacteria isolated from THOD, HDSB, EMD with serial dilution method. 119 from 128 isolated strains were Gram¡¦s negative (93%), including pathogenic Vibrio spp. 57% (73/128) in THOD. 54 from 90 isolated strains were Gram¡¦s negative (60%), including pathogenic Vibrio spp. 12.2% (11/90) in HDSB. 61 from 104 isolated strains were Gram¡¦s negative (59%), including pathogenic Vibrio spp. 70.2% (77/90) in EMD. In different times diseased grouper, 104 from 139 isolated strains were Gram¡¦s negative (75%), including pathogenic Vibrio spp. 88% (123/139), in 2003. While 24 from 44 isolated strains were Gram¡¦s negative (55%), including pathogenic Vibrio spp. 73% (32/44), in 2004. 66 from 75 isolated strains were Gram¡¦s negative (88%), including pathogenic Vibrio spp. 97% (73/75) by disc dilution method in EMD. 9 from 31 isolated strains were Gram¡¦s negative (30%), including pathogenic Vibrio spp. 26% (8/31), by disc dilution method of grouper in PCG. A DGGE (denaturing gradient gel electrophoresis) technique can identify six groups of bacteria from cobia, and J6, R13, T29 have similarity 100%. Quantity One Version 4.5 (Bio-Rad) can identify six groups of bacteria from diffusion methods that F group diluted the bacterial strain from serial dilution method. B group and E group diluted the bacterial strain from disc diffusion method. Higher resistance rates of the different bacterial strains isolated from cobia and were £]-lactam and susceptible were observed in quinolones.

No description available.