Artificial Test Cases Research Articles

Estimation of biogeochemical rates from concentration profiles: A novel inverse method

A numerical procedure is proposed to estimate net microbiological and chemical consumption and production rates from measured solute profiles in limnic and marine sediments, as well as pelagic aquatic systems. The estimation process builds on the one-dimensional steady state diagenetic transport-reaction equation for dissolved compounds (e.g. electron acceptors, nutrients, or metabolic products). This equation is inverted by a technique called Tikhonov regularization which is a common and robust technique for solving ill-conditioned inverse problems.The new procedure (REC model, Rate Estimation from Concentrations) is tested with both some artificial test cases and real measurements of sulfate and methane profiles in marine sediments. Furthermore, the technique is compared with results obtained from the models of Berg et al. (1998) and Wang et al. (2008).The REC model results demonstrate that the proposed numerical procedure is well suited to estimate robust and reasonable rate profiles for relative concentration measurement uncertainties not larger than ±5%. At larger uncertainties, the model provides an estimation of a nearly constant mean rate profile.Our new approach has a similar performance as the PROFILE model of Berg et al. (1998) and the model of Wang et al. (2008). However, the REC model has the advantage of providing smooth rate profiles and estimation of the position of discrete zones of enhanced biogeochemical activities, more accurately.

Isogeometric analysis for strain field measurements

In this paper, the potential of isogeometric analysis for strain field measurement by digital image correlation is investigated. Digital image correlation (DIC) is a full field kinematics measurement technique based on gray level conservation principle and the formulation we adopt allows for using arbitrary displacement bases. The high continuity properties of Non-Uniform Rational B-Spline (NURBS) functions are exploited herein as an additional regularization of the initial ill-posed problem. k-Refinement is analyzed on an artificial test case where the proposed methodology is shown to outperform the usual finite element-based DIC. Finally a fatigue tensile test on a thin aluminum sheet is analyzed. Strain localization occurs after a certain number of cycles and combination of NURBS into a DIC algorithm clearly shows a great potential to improve the robustness of non-linear constitutive law identification.

Interpolation of Steady‐State Concentration Data by Inverse Modeling

In most groundwater applications, measurements of concentration are limited in number and sparsely distributed within the domain of interest. Therefore, interpolation techniques are needed to obtain most likely values of concentration at locations where no measurements are available. For further processing, for example, in environmental risk analysis, interpolated values should be given with uncertainty bounds, so that a geostatistical framework is preferable. Linear interpolation of steady-state concentration measurements is problematic because the dependence of concentration on the primary uncertain material property, the hydraulic conductivity field, is highly nonlinear, suggesting that the statistical interrelationship between concentration values at different points is also nonlinear. We suggest interpolating steady-state concentration measurements by conditioning an ensemble of the underlying log-conductivity field on the available hydrological data in a conditional Monte Carlo approach. Flow and transport simulations for each conditional conductivity field must meet the measurements within their given uncertainty. The ensemble of transport simulations based on the conditional log-conductivity fields yields conditional statistical distributions of concentration at points between observation points. This method implicitly meets physical bounds of concentration values and non-Gaussianity of their statistical distributions and obeys the nonlinearity of the underlying processes. We validate our method by artificial test cases and compare the results to kriging estimates assuming different conditional statistical distributions of concentration. Assuming a beta distribution in kriging leads to estimates of concentration with zero probability of concentrations below zero or above the maximal possible value; however, the concentrations are not forced to meet the advection-dispersion equation.

GOSA, a simulated annealing-based program for global optimization of nonlinear problems, also reveals transyears

Transyears in biology have been documented thus far by the extended cosinor approach, including linear-nonlinear rhythmometry. We here confirm the existence of transyears by simulated annealing, a method originally developed for a much broader use, but described and introduced herein for validating its application to time series. The method is illustrated both on an artificial test case with known components and on biological data. We provide a table comparing results by the two methods and trust that the procedure will serve the budding sciences of chronobiology (the study of mechanisms underlying biological time structure), chronomics (the mapping of time structures in and around us), and chronobioethics, using the foregoing disciplines to add to concern for illnesses of individuals, and to budding focus on diseases of nations and civilizations.

Reading Demanians Reading de Man

Now that the dust has begun to settle after the furor surrounding the discovery after Paul de Man's death in 1983 of his war-time journalism in Nazi-occupied Belgium, it is time to ask what there is to learn from the entire affair aside from the reminder that academics like a good fight as much as everyone else. Certainly, part of what fueled the intensity of the controversy was the sense that the reputation of deconstruction (and, in a sense, literary theory itself) was on the line. So it seems appropriate to ask now what are the consequences of the controversy for deconstruction and, more generally, for literary theory. I am not going to argue for (or against) the proposition that what the young Paul de Man did, said, thought, and wrote between 1940 and 1944 has consequences or implications for deconstruction, as I see no very direct linkbetween the ideas expressed by de Man then and the practice and theory of reading known as deconstruction developed by him, Jacques Derrida, and others twenty to forty years later.' But this does not mean that the controversy over de Man is without consequences for deconstruction or without lessons for literary theorists. On the contrary. What the de Man affair provides is the fullest display we are likely to have of how deconstructive critics actually read texts. In a sense, the de Man affair accomplished what was attempted in the 1979 collection, Deconstruction and Criticism, in which Derrida, de Man, J. Hillis Miller, Geoffrey Hartman, and Harold Bloom all were supposed to read the same poem, Shelley's Triumph of Life. Faced with the discovery of de Man's wartime journalism, these critics, with of course the exception of de Man (and that of Harold Bloom), but now joined by Jonathan Culler, Shoshana Felman, and a host of younger critics, read and interpreted the same texts, de Man's wartime writings, with a focus and intensity not found in the earlier, rather artificial test case. The theoretical interest of the de Man affair is thus that the body of commentary on de Man's wartime journalism gives us an unparalleled occasion to examine the relation between deconstructive interpretive theory and practice. In the 1970s, theorists commonly insisted that practice needed to accord with theory; in keeping with this, phrases of condemna-