Microstructure evolution of 6061 O Al alloy during ultrasonic consolidation:An insight from electron backscatter diffraction

6061 O Al alloy foils were welded to form monolithic and SiC fibre-embedded samples using the ultrasonic consolidation (UC) process. Contact pressures of 135, 155 and 175 MPa were investigated at 20 kHz frequency, 50% of the oscillation amplitude, 34.5 mm s sonotrode velocity and 20 °C. Deformed microstructures were analysed using electron backscatter diffraction (EBSD). At all contact pressures deformation occurs by non-steady state dislocation glide. Dynamic recovery is active in the upper and lower foils. Friction at the welding interface, instantaneous internal temperatures (0.5-0.8 of the melting temperature, T), contact pressure and fast strain rates result in transient microstructures and grain size reduction by continuous dynamic recrystallization (CDRX) within the bonding zone. Bonding occurs by local grain boundary migration, which allows diffusion and atom interlocking across the contact between two clean surfaces. Textures weaken with increasing contact pressure due to increased strain hardening and different grain rotation rates. High contact pressures enhance dynamic recovery and CDRX. Deformation around the fibre is intense within 50 μm and extends to 450 μm from it. © 2009 Acta Materialia Inc.

Timing movements to interval durations specified by discrete or continuous sounds

Understanding how the timing of motor output is coupled to sensory temporal information is largely based on synchronisation of movements through small motion gaps (finger taps) to mostly empty sensory intervals (discrete beats). This study investigated synchronisation of movements between target barriers over larger motion gaps when closing time gaps of intervals were presented as either continuous, dynamic sounds, or discrete beats. Results showed that although synchronisation errors were smaller for discrete sounds, the variability of errors was lower for continuous sounds. Furthermore, finger movement between targets was found to be more sinusoidal when continuous sensory information was presented during intervals compared to discrete. When movements were made over larger amplitudes, synchronisation errors tended to be more positive and movements between barriers more sinusoidal, than for movements over shorter amplitudes. These results show that the temporal control of movement is not independent from the form of the sensory information that specifies time gaps or the magnitude of the movement required for synchronisation.

Identifying strategies to maximise recruitment and retention of practices and patients in a multicentre randomised controlled trial of an intervention to optimise secondary prevention for coronary heart disease in primary care.

Background Recruitment and retention of patients and healthcare providers in randomised controlled trials (RCTs) is important in order to determine the effectiveness of interventions. However, failure to achieve recruitment targets is common and reasons why a particular recruitment strategy works for one study and not another remain unclear. We sought to describe a strategy used in a multicentre RCT in primary care, to report researchers’ and participants’ experiences of its implementation and to inform future strategies to maximise recruitment and retention. Methods In total 48 general practices and 903 patients were recruited from three different areas of Ireland to a RCT of an intervention designed to optimise secondary prevention of coronary heart disease. The recruitment process involved telephoning practices, posting information, visiting practices, identifying potential participants, posting invitations and obtaining consent. Retention involved patients attending reviews and responding to questionnaires and practices facilitating data collection. Results We achieved high retention rates for practices (100%) and for patients (85%) over an 18-month intervention period. Pilot work, knowledge of the setting, awareness of change in staff and organisation amongst participant sites, rapid responses to queries and acknowledgement of practitioners’ contributions were identified as being important. Minor variations in protocol and research support helped to meet varied, complex and changing individual needs of practitioners and patients and encouraged retention in the trial. A collaborative relationship between researcher and practice staff which required time to develop was perceived as vital for both recruitment and retention. Conclusions Recruiting and retaining the numbers of practices and patients estimated as required to provide findings with adequate power contributes to increased confidence in the validity and generalisability of RCT results. A continuous dynamic process of monitoring progress within trials and tailoring strategies to particular circumstances, whilst not compromising trial protocols, should allow maximal recruitment and retention.

Hot deformation characteristics of a nitride strengthened martensitic heat resistant steel

Constitutive equations including an Arrhenius term have been applied to analyze the hot deformation behavior of a nitride-strengthened (NS) martensitic heat resistant steel in temperature range of 900–1200 °C and strain rate range of 0.001–10 /s. On the basis of analysis of the deformation data, the stress–strain curves up to the peak were divided into four regions, in sequence, representing four processes, namely hardening, dynamic recovery (DRV), dynamic strain induced transformation (DSIT), and dynamic recrystallization (DRX), according to the inflection points in ∂θ/∂σ∂θ/∂σ and ∂(∂θ/∂σ)/∂σ∂(∂θ/∂σ)/∂σ curves. Some of the inflection points have their own meanings. For examples, the minimum of ∂θ/∂σ∂θ/∂σ locates the start of DRV and the maximum of it indicates the start of DRX. The results also showed that the critical strain of DRX was sensitive to ln(Z) below 40, while the critical stress of DRX was sensitive to it above 40. The final microstructures under different deformation conditions were analyzed in terms of softening processes including DRV, DRX, metadynamic crystallization (MDRX) and DSIT.

Analysis of deformation behavior and workability of advanced 9Cr-Nb-V ferritic heat resistant steels

Hot compression tests were carried out on 9Cr–Nb–V heat resistant steels in the temperature range of 600–1200 °C and the strain rate range of 10−2–100 s−1 to study their deformation characteristics. The full recrystallization temperature and the carbon-free bainite phase transformation temperature were determined by the slope-change points in the curve of mean flow stress versus the inverse of temperature. The parameters of the constitutive equation for the experimental steels were calculated, including the stress exponent and the activation energy. The lower carbon content in steel would increase the fraction of precipitates by increasing the volume of dynamic strain-induced (DSIT) ferrite during deformation. The ln(εc) versus ln(Z) and the ln(σc) versus ln(Z) plots for both steels have similar trends. The efficiency of power dissipation maps with instability maps merged together show excellent workability from the strain of 0.05 to 0.6. The microstructure of the experimental steels was fully recrystallized upon deformation at low Z value owing to the dynamic recrystallization (DRX), and exhibited a necklace structure under the condition of 1050 °C/0.1 s−1 due to the suppression of the secondary flow of DRX. However, there were barely any DRX grains but elongated pancake grains under the condition of 1000 °C/1 s−1 because of the suppression of the metadynamic recrystallization (MDRX).

Dynamic in situ optical and magneto-optical monitoring of the growth of Co-Pd multilayers

In situ ellipsometry and Kerr polarimetry have been used to follow the continuous evolution of the optical and magneto- optical properties of multiple layers of Co and Pd during their growth. Films were sputter deposited onto a Pd buffer layer on glass substrates up to a maximum of N = 10 bi-layer periods according to the scheme glass/Pd(10)Ar x (0.3Co/3Pd) (nm). Magnetic hysteresis measurements taken during the deposition consistently showed strong perpendicular anisotropy at all stages of film growth following the deposition of a single monolayer of Co. Magneto-optic signals associated with the normal-incidence polar Kerr effect indicated strong polarization of Pd atoms at both Co-Pd and Pd-Co interfaces and that the magnitude of the complex magneto-optic Voigt parameter and the magnetic moment of the Pd decrease exponentially with distance from the interface with a decay constant of 1.1 nm(- 1). Theoretical simulations have provided an understanding of the observations and allow the determination of the ultrathin- film values of the elements of the skew-symmetric permittivity tensor that describe the optical and magneto-optical properties for both CO and Pd. Detailed structure in the observed Kerr ellipticity shows distinct Pd-thickness-dependent oscillations with a spatial period of about 1.6 nm that are believed to be associated with quantum well levels in the growing Pd layer.

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Validation of the CDC Biofilm Reactor as a Dynamic Model for Assessment of Encrustation Formation on Urological Device Materials

Contemporary medical science is reliant upon the rational selection and utilization of devices, and therefore, an increasing need has developed for in vitro systems aimed at replicating the conditions to which urological devices will be subjected to during their use in vivo. We report the development and validation of a novel continuous flow encrustation model based on the commercially available CDC biofilm reactor. Proteus mirabilis-induced encrustation formation on test biomaterial sections under varying experimental parameters was analyzed by X-ray diffraction, infrared- and Raman spectroscopy and by scanning electron microscopy. The model system produced encrusted deposits similar to those observed in archived clinical samples. Results obtained for the system are highly reproducible with encrustation being rapidly deposited on test biomaterial sections. This model will have utility in the rapid screening of encrustation behavior of biomaterials for use in urological applications. (C) 2010 Wiley Periodicals. Inc. J Biomed Mater Res Part B: Appl Biomater 93B: 128-140, 2010

Dynamic pricing models for used products in remanufacturing with lost-sales and uncertain quality

In this paper, we investigate the remanufacturing problem of pricing single-class used products (cores) in the face of random price-dependent returns and random demand. Specifically, we propose a dynamic pricing policy for the cores and then model the problem as a continuous-time Markov decision process. Our models are designed to address three objectives: finite horizon total cost minimization, infinite horizon discounted cost, and average cost minimization. Besides proving optimal policy uniqueness and establishing monotonicity results for the infinite horizon problem, we also characterize the structures of the optimal policies, which can greatly simplify the computational procedure. Finally, we use computational examples to assess the impacts of specific parameters on optimal price and reveal the benefits of a dynamic pricing policy. © 2013 Elsevier B.V. All rights reserved.

Dynamic pricing for used products in remanufacturing with back orders(ABS 3* Journal, Accepted with Revision on 2nd December 2011).

In remanufacturing, the supply of used products and the demand for remanufactured products are usually mismatched because of the great uncertainties on both sides. In this paper, we propose a dynamic pricing policy to balance this uncertain supply and demand. Specifically, we study a remanufacturer’s problem of pricing a single class of cores with random price-dependent returns and random demand for the remanufactured products with backlogs. We model this pricing task as a continuous-time Markov decision process, which addresses both the finite and infinite horizon problems, and provide managerial insights by analyzing the structural properties of the optimal policy. We then use several computational examples to illustrate the impacts of particular system parameters on pricing policy.

Modeling continuous self-report measures of perceived emotion using generalized additive mixed models

Emotion research has long been dominated by the “standard method” of displaying posed or acted static images of facial expressions of emotion. While this method has been useful it is unable to investigate the dynamic nature of emotion expression. Although continuous self-report traces have enabled the measurement of dynamic expressions of emotion, a consensus has not been reached on the correct statistical techniques that permit inferences to be made with such measures. We propose Generalized Additive Models and Generalized Additive Mixed Models as techniques that can account for the dynamic nature of such continuous measures. These models allow us to hold constant shared components of responses that are due to perceived emotion across time, while enabling inference concerning linear differences between groups. The mixed model GAMM approach is preferred as it can account for autocorrelation in time series data and allows emotion decoding participants to be modelled as random effects. To increase confidence in linear differences we assess the methods that address interactions between categorical variables and dynamic changes over time. In addition we provide comments on the use of Generalized Additive Models to assess the effect size of shared perceived emotion and discuss sample sizes. Finally we address additional uses, the inference of feature detection, continuous variable interactions, and measurement of ambiguity.

Theoretical investigation of the use of a moving vehicle to identify bridge dynamic parameters

Pavements and bridges are subject to a continuous degradation due to traffic aggressiveness, ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure in order to provide adequate maintenance and guarantee the required levels of transport service and safety. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamics of bridges. A simplified quarter carbridge interaction model is used in theoretical simulations and the natural frequency of the bridge is extracted from the spectra of the vehicle accelerations. The accuracy is better at lower speeds and for smooth road profiles. The structural damping of the bridge was also monitored for smooth and rough road profiles. The magnitude of peaks in the power spectral density of the vehicle accelerations decreased with increasing bridge damping and this decrease was easier to detect the smoother the road profile.

Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.