Effects of process parameters upon the shape memory and pseudo-elastic behaviors of laser-welded NiTi thin foil

This article discusses the effects of laser welding parameters such as power, welding speed, and focus position on the weld bead profile, microstructure, pseudo-elasticity (PE), and shape memory effect (SME) of NiTi foil with thickness of 250 um using 100W CW fiber laser. The parameter settings to produce the NiTi welds for analysis in this article were chosen from a fractional factorial design to ensure the welds produced were free of any apparent defect. The welds obtained were mainly of cellular dendrites with grain sizes ranging from 2.5 to 4.8 um at the weld centerline. A small amount of Ni3Ti was found in the welds. The onset of transformation temperatures (As and Ms) of the NiTi welds shifted to the negative side as compared to the as-received NiTi alloy. Ultimate tensile stress of the NiTi welds was comparable to the as received NiTi alloy, but a little reduction in the pseudo-elastic property was noted. Full penetration welds with desirable weld bead profiles and mechanical properties were successfully obtained in this study.

Parameter studies of fibre laser micro-welding of AISI 316L using Taguchi method

This paper discusses the application of the Taguchi experimental design approach in optimizing the key process parameters for micro-welding of thin AISI 316L foil using the 100W CW fibre laser. A L16 Taguchi experiment was conducted to systematically understand how the power, scanning velocity, focus position, gas flow rate and type of shielding gas affect the bead dimensions. The welds produced in the L16 Taguchi experiment was mainly of austenite cellular-dendrite structure with an average grain size of 5µm. An exact penetration weld with the largest penetration to fusion width ratio was obtained. Among those process parameters, the interaction between power and scanning velocity presented the strongest effect to the penetration to fusion width ratio and the power was found to be the predominantly important factor that drives the interaction with other factors to appreciably affect the bead dimensions.

Parameter study on laser welding of nitinol wire by Taguchi method

A L27 Taguchi experiment was done to investigate the effect of laser power, welding time, laser mode (CW and two pulsed modes), focus position, and their possible interactions on the weld-bead aspect ratio of laser-welded NiTi wires by using a 100W fibre laser. The optimized parameter setting to produce the full penetrated weldment with minimum welding defects is successfully determined in the Taguchi experiment. The laser mode is found to be the most important parameter that directly controls the weld-bead aspect ratio. The focus position is the secondly important parameter for the laser welding of NiTi wires. Strong interaction between the power and focus position is found in the Taguchi experiment. The optimized weldment produced by the Taguchi experiment is mainly of columnar dendritic structure in the weld zone (WZ) with the size of 1-3µm, while the HAZ exhibits equiaxed grain structure with the size of 5-10µm. The Vickers micro-hardness test indicted that the WZ and HAZ in the weldment are softened to certain extends after fibre laser welding.

Parameter estimation and equation formulation in Business Dynamics

System Dynamics enables modelling and simulation of highly non-linear feedback systems to predict future system behaviour. Parameter estimation and equation formulation are techniques in System Dynamics, used to retrieve the values of parameters or the equations for ?ows and/or variables. These techniques are crucial for the annotations and thereafter the simulation. This paper critically examines existing and well established approaches in parameter estimation and equation formulation along with their limitations, identifying performance gaps as well as providing directions for potential future research.

The role of SRC-CAS interactions in cellular transformation:ectopic expression of the carboxy terminus of CAS inhibits SRC-CAS interaction but has no effect on cellular transformation

Several lines of evidence indicate that the adapter molecule p130CAS (crk-associated substrate (CAS)) is required for src-mediated cellular transformation. CAS has been shown to be heavily tyrosine-phosphorylated in src-transformed cells, and genetic variants of src that are deficient in CAS binding are also unable to mediate cellular transformation. In this report, we investigated whether CAS phosphorylation and/or its association with src are required elements of the transformation process. Expression of the carboxy-terminal src binding domain of CAS in Rat 1 fibroblasts expressing a temperature-sensitive allele of v-src inhibited the formation of src-CAS complexes and also inhibited tyrosine phosphorylation of CAS. However, expression of this protein had no effect on morphological transformation, src-mediated actin rearrangements, or anchorage-independent growth of these cells when grown at the src-permissive temperature. Thus, the ability of activated src to mediate cellular transformation is either largely independent of endogenous CAS phosphorylation and/or its association with CAS or, alternatively, the carboxy-terminus of CAS may substitute for endogenous CAS in the process of src-mediated transformation.

The identification of p130cas-binding proteins and their role in cellular transformation

Adaptor proteins play an important role in signal transduction by regulating the establishment and maintenance of functionally important protein complexes. A recently described member of this group of proteins is p130cas (CAS), which contains numerous sequence motifs predicted to be involved in mediating protein-protein interactions. We propose that adaptor molecules like CAS may help determine the response of a cell to a particular signal by interacting with specific subsets of cellular proteins. To test this hypothesis, we have identified potential binding partners of CAS that may play a rote in cellular transformation by the oncoproteins v-SRC and/or v-CRK. We show that individual domains of CAS associate with specific subsets of proteins in vitro, and that many of these interactions are dependent on the state of tyrosine-phosphorylation of CAS. Sequences necessary for interacting with the focal adhesion kinase pp125FAK (FAK), v-SRC and v-CRK have been mapped to distinct regions of CAS. In addition, the identification of a number of putative CAS-binding partners that are present in crk-transformed cell extracts but undetectable in normal and src-transformed cell extracts supports a model in which unique protein complexes are formed in response to different signals.

Can a carbon nano-coating resist metallic phase transformation in silicon substrate during nanoimpact?

Nanomechanical response of a silicon specimen coated with a sp3 crystalline carbon coating (1.8 nm thickness) was investigated using MD simulation. A sharp conical rigid tip was impacted at the speed of 50 m/sec up to a depth of ~80% of the coating thickness. Unlike pure silicon specimen, no metallic phase transformation was observed i.e. a thin coating was able to resist Si-I to Si-II metallic phase transformation signifying that the coating could alter the stress distribution and thereby the contact tribology of the substrate. The stress state of the system, radial distribution function and the load-displacement curve were all aligned with above observations

Reconstructing the quantum state of oscillator networks with a single qubit

We introduce a scheme to reconstruct arbitrary states of networks composed of quantum oscillators-e. g., the motionalstate of trapped ions or the radiation state of coupled cavities. The scheme involves minimal resources and minimal access, in the sense that it (i) requires only the interaction between a one-qubit probe and a single node of the network; (ii) provides the Weyl characteristic function of the network directly from the data, avoiding any tomographic transformation; (iii) involves the tuning of only one coupling parameter. In addition, we show that a number of quantum properties can be extracted without full reconstruction of the state. The scheme can be used for probing quantum simulations of anharmonic many-body systems and quantum computations with continuous variables. Experimental implementation with trapped ions is also discussed and shown to be within reach of current technology.

Using CAD parameter sensitivities for stack-up tolerance allocation

Tolerance allocation is an important step in the design process. It is necessary to produce high quality components cost-effectively. However, the process of allocating tolerances can be time consuming and difficult, especially for complex models. This work demonstrates a novel CAD based approach, where the sensitivities of product dimensions to changes in the values of the feature parameters in the CAD model are computed. These are used to automatically establish the assembly response function for the product. This information has been used to automatically allocate tolerances to individual part dimensions to achieve specified tolerances on the assembly dimensions, even for tolerance allocation in more than one direction simultaneously. It is also shown how pre-existing constraints on some of the part dimensions can be represented and how situations can be identified where the required tolerance allocation is not achievable. A methodology is also presented that uses the same information to model a component with different amounts of dimensional variation to simulate the effects of tolerance stack-up. © 2014 Springer-Verlag France.

Characterisation of Passive Intermodulation in Passive RF Devices with X-parameter

A novel approach to the modelling of passive intermodulation (PIM) generation in passive components with distributed weak nonlinearities is outlined. Based upon the formalism of X-parameters, it provides a unified framework for co-design of antenna beamforming networks, filters, combiners, phase shifters and other passive and active devices containing nonlinearities at RF front-end. The effects of discontinuities and complex circuit layouts can be efficiently evaluated with the aid of the equivalent networks of the canonical nonlinear elements. The main concepts are illustrated by examples of numerical simulations of PIM generation in the transmission lines and comparison with the measurement results.

Transform both sides model: A parametric approach

A parametric regression model for right-censored data with a log-linear median regression function and a transformation in both response and regression parts, named parametric Transform-Both-Sides (TBS) model, is presented. The TBS model has a parameter that handles data asymmetry while allowing various different distributions for the error, as long as they are unimodal symmetric distributions centered at zero. The discussion is focused on the estimation procedure with five important error distributions (normal, double-exponential, Student's t, Cauchy and logistic) and presents properties, associated functions (that is, survival and hazard functions) and estimation methods based on maximum likelihood and on the Bayesian paradigm. These procedures are implemented in TBSSurvival, an open-source fully documented R package. The use of the package is illustrated and the performance of the model is analyzed using both simulated and real data sets.

Improving parameter learning of Bayesian nets from incomplete data

This paper addresses the estimation of parameters of a Bayesian network from incomplete data. The task is usually tackled by running the Expectation-Maximization (EM) algorithm several times in order to obtain a high log-likelihood estimate. We argue that choosing the maximum log-likelihood estimate (as well as the maximum penalized log-likelihood and the maximum a posteriori estimate) has severe drawbacks, being affected both by overfitting and model uncertainty. Two ideas are discussed to overcome these issues: a maximum entropy approach and a Bayesian model averaging approach. Both ideas can be easily applied on top of EM, while the entropy idea can be also implemented in a more sophisticated way, through a dedicated non-linear solver. A vast set of experiments shows that these ideas produce significantly better estimates and inferences than the traditional and widely used maximum (penalized) log-likelihood and maximum a posteriori estimates. In particular, if EM is adopted as optimization engine, the model averaging approach is the best performing one; its performance is matched by the entropy approach when implemented using the non-linear solver. The results suggest that the applicability of these ideas is immediate (they are easy to implement and to integrate in currently available inference engines) and that they constitute a better way to learn Bayesian network parameters.