“Click” Polymer‐Supported Palladium Nanoparticles as Highly Efficient Catalysts for Olefin Hydrogenation and Suzuki Coupling Reactions under Ambient Conditions

Complexation of palladium(II) acetate [Pd(OAc)₂] or dipotassium tetrachloropalladate [K₂PdCl₄] to “click” polymers functionalized with phenyl, ferrocenyl and sodium sulfonate groups gave polymeric palladium(II)‐triazolyl complexes that were reduced to “click” polymer‐stabilized palladium nanoparticles (PdNPs). Transmission electron microscopy (TEM) showed that reduction using sodium borohydride (NaBH₄) produced PdNPs in the 1–3 nm range of diameters depending on the nature of the functional group, whereas slow reduction using methanol yielded PdNPs in the 22–25 nm range. The most active of these PdNPs (0.01% mol Pd), stabilized by poly(ferrocenyltriazolylmethyl)styrene, catalyzed the hydrogenation of styrene at 25 °C and 1 atm hydrogen, with turnover numbers (TONs) of 200,000. When stabilized by the water‐soluble poly(sodium sulfonate‐triazolylmethyl)styrene, the PdNPs (0.01% mol Pd) catalyze the Suzuki–Miyaura coupling between iodobenzene (PhI) and phenylboronic acid [PhB(OH)₂] in water/ethanol (H₂O/EtOH) at 25 °C with TONs of 8,200. This high catalytic activity is comparable to that obtained with “click” dendrimer‐stabilized PdNPs under ambient conditions.     

A fault-tolerant control architecture for induction motor drives in automotive applications

This paper describes a fault-tolerant control system for a high-performance induction motor drive that propels an electrical vehicle (EV) or hybrid electric vehicle (HEV). In the proposed control scheme, the developed system takes into account the controller transition smoothness in the event of sensor failure. Moreover, due to the EV or HEV requirements for sensorless operations, a practical sensorless control scheme is developed and used within the proposed fault-tolerant control system. This requires the presence of an adaptive flux observer. The speed estimator is based on the approximation of the magnetic characteristic slope of the induction motor to the mutual inductance value. Simulation results, in terms of speed and torque responses, show the effectiveness of the proposed approach.     

Critical success factors for World Bank projects: An empirical investigation

This paper analyzes the results of a survey that aims to explore World Bank project success factors and specifically the relationship between critical success factors (CSFs) and project success as perceived by World Bank Task Team Leaders (project supervisors). The exploratory factor analysis highlights a specific set of five CSFs: monitoring, coordination, design, training, and institutional environment. The regression analysis shows that there is a statistically significant and positive relationship between each of the five CSFs and project success. Consistent with theory and practice, the most prominent CSFs for project supervisors are design and monitoring. The findings contribute to the project CSF literature by conceptualizing project supervision as a multidimensional construct and by confirming supervision as a generic CSF for World Bank projects. The World Bank project supervisors and managers should strengthen project design and monitoring and thus improve project implementation as well as the chances for project success.     

A data-driven approach to multi-product production network planning

The clearing function models the non-linear relationship between work-in-process and throughput and has been proposed for production planning in environments with queuing (congestion) effects. One approach in multi-product, multi-stage environments has been to model the clearing function at the bottleneck machine only. However, since the bottleneck shifts as the product release mix changes, this approach has its limitations. The other approach is the Alternative Clearing Function formulation, where the clearing function is first estimated at the resource level using piecewise linear regression from simulation experiments, and then embedded into a linear programme. This paper develops an alternative to the Allocated Clearing Function formulation, wherein system throughput is estimated at discrete work-in-process points. A mixed integer programming formulation is then presented to use these throughput estimates for discrete release choices. The strength of the formulation is illustrated with a numerical example and the new approach is compared with the ACF.     

Selective maintenance optimisation for series-parallel systems alternating missions and scheduled breaks with stochastic durations

This paper deals with the selective maintenance problem for a multi-component system performing consecutive missions separated by scheduled breaks. To increase the probability of successfully completing its next mission, the system components are maintained during the break. A list of potential imperfect maintenance actions on each component, ranging from minimal repair to replacement is available. The general hybrid hazard rate approach is used to model the reliability improvement of the system components. Durations of the maintenance actions, the mission and the breaks are stochastic with known probability distributions. The resulting optimisation problem is modelled as a non-linear stochastic programme. Its objective is to determine a cost-optimal subset of maintenance actions to be performed on the components given the limited stochastic duration of the break and the minimum system reliability level required to complete the next mission. The fundamental concepts and relevant parameters of this decision-making problem are developed and discussed. Numerical experiments are provided to demonstrate the added value of solving this selective maintenance problem as a stochastic optimisation programme.     

Adaptive state observers for sensorless control of switched reluctance motors

In this paper, we address the problem of state observation for sensorless control of switched reluctance motors (SRMs), that is, the regulation of the motor measuring only the voltage and the current of the electrical supply. Instrumental for the construction of the observer is the derivation of algebraic relations, which define regression models, between the unknown rotor flux and the measured quantities. With the knowledge of the flux, it is shown that the mechanical coordinates can be estimated with suitably tailored adaptive nonlinear observers. Replacing the observed states, in a certainty equivalent manner, with a full information stabilizing law completes the sensorless controller design. In contrast with other motors, there is no universally accepted mathematical model to describe the dynamics of SRMs. To widen our target audience, we present the results for four different mathematical models reported in the literature. Simulation results with a precise (finite element) model of the SRM are used to illustrate the performance of the proposed observer and sensorless control.     

Geophysical wavelet library: Applications of the continuous wavelet transform to the polarization and dispersion analysis of signals

In the present paper, we consider and summarize applications of the continuous wavelet transform to 2C and 3C polarization analysis and filtering, modeling the dispersed and attenuated wave propagation in the time–frequency domain, and estimation of the phase and group velocity and the attenuation from a seismogram. Along with a mathematical overview of each of the presented methods, we show that all these algorithms are logically combined into one software package “Geophysical Wavelet Library” developed by the authors. The novelty of this package is that we incorporate the continuous wavelet transform into the library, where the kernel is the time–frequency polarization and dispersion analysis. This library has a wide range of potential applications in the field of signal analysis and may be particularly suitable in geophysical problems that we illustrate by analyzing synthetic, geomagnetic and real seismic data.