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.

Parameter Optimization on Laser Welding of NiTi Wires by Taguchi Method

In this research, a preliminary study was done to find out the initial parameter window to obtain the full-penetrated NiTi weldment. A L27 Taguchi experiment was then carried out to statistically study the effects of the welding parameters and their possible interactions on the weld bead aspect ratio (or penetration over fuse-zone width ratio), and to determine the optimized parameter settings to produce the full-penetrated weldment with desirable aspect ratio. From the statistical results in the Taguchi experiment, the laser mode was found to be the most important factor that substantially affects the aspect ratio. Strong interaction between the power and focus position was found in the Taguchi experiment. The optimized weldment was mainly of columnar dendritic structure in the weld zone (WZ), while the HAZ exhibited equiaxed grain structure. The XRD and DSC results showed that the WZ remained the B2 austenite structure without any precipitates, but with a significant decrease of phase transformation temperatures. The results in the micro-hardness and tensile tests indicated that the mechanical properties of NiTi were decreased to a certain extent after fibre laser welding.

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.

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.

Electrical conduction and rheological behaviour of composites of poly(epsilon-caprolactone) and MWCNTs

Two mechanisms of conduction were identified from temperature dependent (120 K-340 K) DC electrical resistivity measurements of composites of poly(c-caprolactone) (PCL) and multi-walled carbon nanotubes (MWCNTs). Activation of variable range hopping (VRH) occurred at lower temperatures than that for temperature fluctuation induced tunneling (TFIT). Experimental data was in good agreement with the VRH model in contrast to the TFIT model, where broadening of tunnel junctions and increasing electrical resistivity at T > T-g is a consequence of a large difference in the coefficients of thermal expansion of PCL and MWCNTs. A numerical model was developed to explain this behavior accounting for a thermal expansion effect by supposing the large increase in electrical resistivity corresponds to the larger relative deformation due to thermal expansion associated with disintegration of the conductive MWCNT network. MWCNTs had a significant nucleating effect on PCL resulting in increased PCL crystallinity and an electrically insulating layer between MWCNTs. The onset of rheological percolation at similar to 0.18 vol% MWCNTs was clearly evident as storage modulus, G' and complex viscosity, vertical bar eta*vertical bar increased by several orders of magnitude. From Cole-Cole and Van Gurp-Palmen plots, and extraction of crossover points (G(c)) from overlaying plots of G' and G '' as a function of frequency, the onset of rheological percolation at 0.18 vol% MWCNTs was confirmed, a similar MWCNT loading to that determined for electrical percolation. 

Cavity-aided quantum parameter estimation in a bosonic double-well Josephson junction

We describe an apparatus designed to make non-demolition measurements on a Bose-Einstein condensate (BEC) trapped in a double-well optical cavity. This apparatus contains, as well as the bosonic gas and the trap, an optical cavity. We show how the interaction between the light and the atoms, under appropriate conditions, can allow for a weakly disturbing yet highly precise measurement of the population imbalance between the two wells and its variance. We show that the setting is well suited for the implementation of quantum-limited estimation strategies for the inference of the key parameters defining the evolution of the atomic system and based on measurements performed on the cavity field. This would enable {\it de facto} Hamiltonian diagnosis via a highly controllable quantum probe.

Synthesis, thermal characterization and rheological properties of a homologous series of polymethacrylate-based side-chain liquid crystal polymers

A new homologous series of side-chain liquid crystal polymers, the poly[omega-(4-cyanoazobenzene-4'-oxy)alkyl methacrylate]s, have been prepared in which the length of the flexible alkyl spacer is varied from 3 to 12 methylene units. All the polymers exhibit liquid crystalline behaviour; specifically, crystal E, smectic A and nematic phases are observed. The glass transition temperatures decrease on increasing spacer length before reaching a limiting value at ca. 30 degrees C. The clearing temperatures exhibit an odd-even effect on varying the length and parity of the spacer. This is attributed to the change in the average shape of the side chain as the parity of the spacer is varied. This rationalization also accounts for the observed alternation in the entropy change associated with the clearing transition. A weak relaxation is observed theologically for several members of this polymer series at temperatures above their respective glass transition temperatures. This is attributed either to specific motions of the smectic layers or to 180 degrees reorientational jumps of the long axis of the mesogenic unit about the polymer backbone. (C) 1997 Elsevier Science Ltd. All rights reserved.

Energy Saving - Another Perspective for Parameter Optimization of P and PI Controllers

Modern control methods like optimal control and model predictive control (MPC) provide a framework for simultaneous regulation of the tracking performance and limiting the control energy, thus have been widely deployed in industrial applications. Yet, due to its simplicity and robustness, the conventional P (Proportional) and PI (Proportional–Integral) control are still the most common methods used in many engineering systems, such as electric power systems, automotive, and Heating, Ventilation and Air Conditioning (HVAC) for buildings, where energy efficiency and energy saving are the critical issues to be addressed. Yet, little has been done so far to explore the effect of its parameter tuning on both the system performance and control energy consumption, and how these two objectives are correlated within the P and PI control framework. In this paper, the P and PI controllers are designed with a simultaneous consideration of these two aspects. Two case studies are investigated in detail, including the control of Voltage Source Converters (VSCs) for transmitting offshore wind power to onshore AC grid through High Voltage DC links, and the control of HVAC systems. Results reveal that there exists a better trade-off between the tracking performance and the control energy through a proper choice of the P and PI controller parameters.

A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells

Mathematical models are useful tools for simulation, evaluation, optimal operation and control of solar cells and proton exchange membrane fuel cells (PEMFCs). To identify the model parameters of these two type of cells efficiently, a biogeography-based optimization algorithm with mutation strategies (BBO-M) is proposed. The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm. Numerical experiments have been conducted on ten benchmark functions with 50 dimensions, and the results show that BBO-M can produce solutions of high quality and has fast convergence rate. Then, the proposed BBO-M is applied to the model parameter estimation of the two type of cells. The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells.

Solubility parameter based screening methods for early stage formulation development of itraconazole amorphous solid dispersions

Objectives: This article uses conventional and newly extended solubility parameter (δ) methods to identify polymeric materials capable of forming amorphous dispersions with itraconazole (itz). Methods: Combinations of itz and Soluplus, Eudragit E PO (EPO), Kollidon 17PF (17PF) or Kollidon VA64 (VA64) were prepared as amorphous solid dispersions using quench cooling and hot melt extrusion. Storage stability was evaluated under a range of conditions using differential scanning calorimetry and powder X-ray diffraction. Key findings: The rank order of itz miscibility with polymers using both conventional and novel δ-based approaches was 17PF > VA64 > Soluplus > EPO, and the application of the Flory–Huggins lattice model to itz–excipient binary systems corroborated the findings. The solid-state characterisation analyses of the formulations manufactured by melt extrusion correlated well with pre-formulation screening. Long-term storage studies showed that the physical stability of 17PF/vitamin E TPGS–itz was poor compared with Soluplus and VA64 formulations, and for EPO/itz systems variation in stability may be observed depending on the preparation method. Conclusion: Results have demonstrated that although δ-based screening may be useful in predicting the initial state of amorphous solid dispersions, assessment of the physical behaviour of the formulations at relevant temperatures may be more appropriate for the successful development of commercially acceptable amorphous drug products.