Probabilistic fault identification using vibration data and neural networks

Bayesian formulated neural networks are implemented using hybrid Monte Carlo method for probabilistic fault identification in cylindrical shells. Each of the 20 nominally identical cylindrical shells is divided into three substructures. Holes of (12±2) mm in diameter are introduced in each of the substructures and vibration data are measured. Modal properties and the Coordinate Modal Assurance Criterion (COMAC) are utilized to train the two modal-property-neural-networks. These COMAC are calculated by taking the natural-frequency-vector to be an additional mode. Modal energies are calculated by determining the integrals of the real and imaginary components of the frequency response functions over bandwidths of 12% of the natural frequencies. The modal energies and the Coordinate Modal Energy Assurance Criterion (COMEAC) are used to train the two frequency-response-function-neural-networks. The averages of the two sets of trained-networks (COMAC and COMEAC as well as modal properties and modal energies) form two committees of networks. The COMEAC and the COMAC are found to be better identification data than using modal properties and modal energies directly. The committee approach is observed to give lower standard deviations than the individual methods. The main advantage of the Bayesian formulation is that it gives identities of damage and their respective confidence intervals.

Viscoelastic properties of bone as a function of hydration state determined by nanoindentation

Spherical indentation creep testing was used to examine the effect of hydration state on bone mechanical properties. Analysis of creep data was based on the elastic-viscoelastic correspondence principle and utilized a direct solution for the finite loading-rate experimental conditions. The zero-time shear modulus was computed from the creep compliance function and compared to the indentation modulus obtained via conventional indentation analysis, based on an elastic unloading response. The method was validated using a well-known polymer material under three different loading conditions. The method was applied to bone samples prepared with different water content by partial exchange with ethanol, where 70% ethanol was considered as the baseline condition. A hydration increase was associated with a 43% decrease in stiffness, while a hydration decrease resulted in a 20% increase in bone tissue stiffness.

Nanoindentation measurements of bone viscoelasticity as a function of hydration state

Bone is an anisotropic material, and its mechanical properties are determined by its microstructure as well as its composition. Mechanical properties of bone are a consequence of the proportions of, and the interactions between, mineral, collagen and water. Water plays an important role in maintaining the mechanical integrity of the composite, but the manner in which water interacts within the ultrastructure is unclear. Dentine being an isotropic two-dimensional structure presents a homogenous composite to examine the dehydration effects. Nanoindentation methods for determining the viscoelastic properties have recently been developed and are a subject of great interest. Here, one method based on elastic-viscoelastic correspondence for 'ramp and hold' creep testing (Oyen, J. Mater. Res., 2005) has been used to analyze viscoelastic behavior of polymeric and biological materials. The method of 'ramp and hold' allows the shear modulus at time zero to be determined from fitting of the displacement during the maximum load hold. Changes in the viscoelastic properties of bone and dentine were examined as the material was systematically dehydrated in a series of water:solvent mixes. Samples of equine dentine were sectioned and cryo-polished. Shear modulus was obtained by nanoindentation using spherical indenters with a maximum load hold of 120s. Samples were tested in different solvent concentrations sequentially, 70% ethanol to 50% ethanol, 70 % ethanol to 100% ethanol, 70% ethanol to 70% methanol to 100% methanol, and 70% ethanol to 100% acetone, after storage in each condition for 24h. By selectively removing and then replacing water from the composite, insights in to the ultrastructure of the tissue can be gained from the corresponding changes in the experimentally determined moduli, as well as an understanding of the complete reversibility of the dehydration process. © 2006 Materials Research Society.

Dissecting Arabidopsis thaliana DICER function in small RNA processing, gene silencing and DNA methylation patterning.

Small RNAs have several important biological functions. MicroRNAs (miRNAs) and trans-acting small interfering RNAs (tasiRNAs) regulate mRNA stability and translation, and siRNAs cause post-transcriptional gene silencing of transposons, viruses and transgenes and are important in both the establishment and maintenance of cytosine DNA methylation. Here, we study the role of the four Arabidopsis thaliana DICER-LIKE genes (DCL1-DCL4) in these processes. Sequencing of small RNAs from a dcl2 dcl3 dcl4 triple mutant showed markedly reduced tasiRNA and siRNA production and indicated that DCL1, in addition to its role as the major enzyme for processing miRNAs, has a previously unknown role in the production of small RNAs from endogenous inverted repeats. DCL2, DCL3 and DCL4 showed functional redundancy in siRNA and tasiRNA production and in the establishment and maintenance of DNA methylation. Our studies also suggest that asymmetric DNA methylation can be maintained by pathways that do not require siRNAs.

Contact and channel modelling using part and function libraries in a function-based design approach

To support the development and analysis of engineering designs at the embodiment stage, designers work iteratively with representations of those designs as they consider the function and form of their constituent parts. Detailed descriptions of "what a machine does" usually include flows of forces and active principles within the technical system, and their localization within parts and across the interfaces between them. This means that a representation should assist a designer in considering form and function at the same time and at different levels of abstraction. This paper describes a design modelling approach that enables designers to break down a system architecture into its subsystems and parts, while assigning functions and flows to parts and the interfaces between them. In turn, this may reveal further requirements to fulfil functions in order to complete the design. The approach is implemented in a software tool which provides a uniform, computable language allowing the user to describe functions and flows as they are iteratively discovered, created and embodied. A database of parts allows the user to search for existing design solutions. The approach is illustrated through an example: modelling the complex mechanisms within a humanoid robot. Copyright © 2010 by ASME.

Feedback modulation: a window into cortical function.

A recent study demonstrates involvement of primary motor cortex in task-dependent modulation of rapid feedback responses; cortical neurons resolve locally ambiguous sensory information, producing sophisticated responses to disturbances.

Verifying stability of approximate explicit MPC

Several authors have proposed algorithms for approximate explicit MPC [1],[2],[3]. These algorithms have in common that they develop a stability criterion for approximate explicit MPC that require the approximate cost function to be within a certain distance from the optimal cost function. In this paper, stability is instead ascertained by considering only the cost function of the approximate MPC. If a region of the state space is found where the cost function is not decreasing, this indicates that an improved approximation (to the optimal control) is required in that region. If the approximate cost function is decreasing everywhere, no further refinement of the approximate MPC is necessary, since stability is guaranteed. ©2009 IEEE.

Air traffic control with an expected value criterion

in this contribution we discuss a stochastic framework for air traffic conflict resolution. The conflict resolution task is posed as the problem of optimizing an expected value criterion. Optimization is carried out by Monte Carlo Markov Chain (MCMC) simulation. A numerical example illustrates the proposed strategy. Copyright © 2005 IFAC.