Introduction to the development of an information management system for soil mix technology using artificial neural networks

This paper introduces current work in collating data from different projects using soil mix technology and establishing trends using artificial neural networks (ANNs). Variation in unconfined compressive strength as a function of selected soil mix variables (e.g., initial soil water content and binder dosage) is observed through the data compiled from completed and on-going soil mixing projects around the world. The potential and feasibility of ANNs in developing predictive models, which take into account a large number of variables, is discussed. The main objective of the work is the management and effective utilization of salient variables and the development of predictive models useful for soil mix technology design. Based on the observed success in the predictions made, this paper suggests that neural network analysis for the prediction of properties of soil mix systems is feasible. © ASCE 2011.

Angular dependence of domain wall resistivity in artificial magnetic domain structures.

We exploit the ability to precisely control the magnetic domain structure of perpendicularly magnetized Pt/Co/Pt trilayers to fabricate artificial domain wall arrays and study their transport properties. The scaling behavior of this model system confirms the intrinsic domain wall origin of the magnetoresistance, and systematic studies using domains patterned at various angles to the current flow are excellently described by an angular-dependent resistivity tensor containing perpendicular and parallel domain wall resistivities. We find that the latter are fully consistent with Levy-Zhang theory, which allows us to estimate the ratio of minority to majority spin carrier resistivities, rho downward arrow/rho upward arrow approximately 5.5, in good agreement with thin film band structure calculations.

Breaking of symmetry in microfluidic propulsion driven by artificial cilia.

In this Brief Report we investigate biomimetic fluid propulsion due to an array of periodically beating artificial cilia. A generic model system is defined in which the effects of inertial fluid forces and the spatial, temporal, and orientational asymmetries of the ciliary motion can be individually controlled. We demonstrate that the so-far unexplored orientational asymmetry plays an important role in generating flow and that the flow increases sharply with Reynolds number and eventually becomes unidirectional. We introduce the concept of configurational symmetry that unifies the spatial, temporal, and orientational symmetries. The breaking of configurational symmetry leads to fluid propulsion in microfluidic channels.

Magnetically actuated artificial cilia: the effect of fluid inertia.

Natural cilia are hairlike microtubule-based structures that are able to move fluid on the micrometer scale using asymmetric motion. In this article, we follow a biomimetic approach to design artificial cilia lining the inner surfaces of microfluidic channels with the goal of propelling fluid. The artificial cilia consist of polymer films filled with superparamagnetic nanoparticles, which can mimic the motion of natural cilia when subjected to a rotating magnetic field. To obtain the magnetic field and associated magnetization local to the cilia, we solve the Maxwell equations, from which the magnetic body moments and forces can be deduced. To obtain the ciliary motion, we solve the dynamic equations of motion, which are then fully coupled to the Navier-Stokes equations that describe the fluid flow around the cilia, thus taking full account of fluid inertial forces. The dimensionless parameters that govern the deformation behavior of the cilia and the associated fluid flow are arrived at using the principle of virtual work. The physical response of the cilia and the fluid flow for different combinations of elastic, fluid viscous, and inertia forces are identified.

Magnetically-actuated artificial cilia for microfluidic propulsion.

In this paper we quantitatively analyse the performance of magnetically-driven artificial cilia for lab-on-a-chip applications. The artificial cilia are fabricated using thin polymer films with embedded magnetic nano-particles and their deformation is studied under different external magnetic fields and flows. A coupled magneto-mechanical solid-fluid model that accurately captures the interaction between the magnetic field, cilia and fluid is used to simulate the cilia motion. The elastic and magnetic properties of the cilia are obtained by fitting the results of the computational model to the experimental data. The performance of the artificial cilia with a non-uniform cross-section is characterised using the numerical model for two channel configurations that are of practical importance: an open-loop and a closed-loop channel. We predict that the flow and pressure head generated by the artificial cilia can be as high as 18 microlitres per minute and 3 mm of water, respectively. We also study the effect of metachronal waves on the flow generated and show that the fluid propelled increases drastically compared to synchronously beating cilia, and is unidirectional. This increase is significant even when the phase difference between adjacent cilia is small. The obtained results provide guidelines for the optimal design of magnetically-driven artificial cilia for microfluidic propulsion.