Control of robust design in multiobjective optimization under uncertainties

In design and optimization problems, a solution is called robust if it is stable enough with respect to perturbation of model input parameters. In engineering design optimization, the designer may prefer a use of robust solution to a more optimal one to set a stable system design. Although in literature there is a handful of methods for obtaining such solutions, they do not provide a designer with a direct and systematic control over a required robustness. In this paper, a new approach to robust design in multiobjective optimization is introduced, which is able to generate robust design with model uncertainties. In addition, it introduces an opportunity to control the extent of robustness by designer preferences. The presented method is different from its other counterparts. For keeping robust design feasible, it does not change any constraint. Conversely, only a special tunable objective function is constructed to incorporate the preferences of the designer related to the robustness. The effectiveness of the method is tested on well known engineering design problems.     

Precision positioning using a novel six axes compliant nano-manipulator

In this paper, a novel micro-scale nano-manipulator capable of positioning in six degrees of freedom (DOF) is introduced. Undesired deflections, while operating in a specific DOF, are restricted by the aid of distinctive design of flexure hinges and actuators’ arrangements. The compliant mechanism is actuated by thermo-electro-mechanical actuators, as they could be integrated and exert large forces in a nanometer resolution. The actuators are bidirectional capable of applying force in both transverse and longitudinal directions. Performance of the two degrees of freedom actuator is thoroughly explored via numerical and analytical analyses, showing a good agreement. The workspace and performance of the precision positioner is studied using finite element methods. Finally, identification of forward and inverse kinematic of the nano-manipulator is performed utilizing neural network concept. A well-trained and appropriate neural network can efficiently replace the time-consuming and complex analytical and experimental methods.

     

A multi-stage sigma-delta modulator based on noise-coupling and digital feed-forward techniques

This paper presents a new structure for high-resolution, low-power and wideband discrete time multi-stage (DT-MASH) sigma-delta (ΣΔ) modulators. It uses multi-bit digital input feed forward path (DFF) and noise coupling (NC) techniques. With the DFF technique, the modulator does not need a power-consuming analog adder at the quantizer input, and the number of comparators of the quantizer will be reduced significantly. Also, because of the reduced swing of the modulator’s integrators, low power integrators can be used. Using a second-order NC technique with no extra active block, the order of the modulator, which uses some paths between analog stages, is increased, and its performance is improved with zero-optimization of the modulator’s noise transfer function (NTF). Behavioral simulations and extensive mathematical analyses confirm the effectiveness of the proposed structure. The effect of the non-idealities in the DFF and NC paths were considered in the behavioral simulations. To examine its performance, a MASH 2–1 modulator was designed in the circuit level with a 180-nm CMOS technology and 1.8 V power supply. The integrators use a new op-amp switching technique to reduce total power consumption. With an over-sampling ratio (OSR) of 8 for the 10 MHz signal bandwidth, the proposed structure improves the signal-to-noise and distortion ratio (SNDR) by 28 dB compared with a conventional MASH 2–1 structure at approximately the same power consumption and very low complexity.

     

High voltage gain dual-input dual-output DC-DC converter with reduced voltage stress on semiconductors

This paper proposes a new nonisolated multiport DC-DC converter with two inputs and two outputs with different voltage levels. Different energy sources with distinct voltage-current characteristics can be utilized as the input sources. Regarding multiple outputs, the proposed converter can be utilized in electric vehicles (EVs) to supply the DC traction motor and the auxiliary loads. The main advantages of the proposed converter include the high voltage gain with small values of the duty cycles, low normalized peak voltage stress (NPVS) across the semiconductors, and the continuous input currents. The voltage stress across the semiconductors is lower than the maximum output voltage. This feature makes it possible to use the switches with low turn-on resistance and the diodes with reduced rating voltage. Performance principals of the proposed converter along with the steady-state analysis, such as the derivation of the voltage gains, voltage and current stresses of the semiconductors, etc, are carried out. Experimental measurements made for the laboratory prototype of the proposed converter confirm the theoretical analysis.     

A multi-stage stochastic transmission expansion planning method

This paper presents a multi-stage stochastic model for short-term transmission expansion planning considering the available transfer capability (ATC). The ATC can have a huge impact on the power market outcomes and the power system reliability. The transmission expansion planning (TEP) studies deal with many uncertainties, such as system load uncertainties that are considered in this paper. The Monte Carlo simulation method has been applied for generating different scenarios. A scenario reduction technique is used for reducing the number of scenarios. The objective is to minimize the sum of investment costs (IC) and the expected operation costs (OC). The solution technique is based on the benders decomposition algorithm. The N-1 contingency analysis is also done for the TEP problem.The proposed model is applied to the IEEE 24 bus reliability test system and the results are efficient and promising.     

Solving unit commitment problem using a novel version of harmony search algorithm

In this context, a novel structure was proposed for improving harmony search (HS) algorithm to solve the unit comment (UC) problem. The HS algorithm obtained optimal solution for defined objective function by improvising, updating and checking operators. In the proposed improved self-adaptive HS (SGHS) algorithm, two important control parameters were adjusted to reach better solution from the simple HS algorithm. The objective function of this study consisted of operation, start-up and shut-down costs. To confirm the effectiveness, the SGHS algorithm was tested on systems with 10, 20, 40 and 60 generating units, and the obtained results were compared with those of the simple HS algorithm and other related works.     

In situ synthesis of leucite-based feldspathic dental porcelain with minor kalsilite and Fe2O3 impurities

K-Feldspar was used as a raw material for in situ synthesis of leucite particles by solid-state reaction method. Prior to synthesis of leucite, K-Feldspar was treated by oxalic acid (C₂H₂O₄) to eliminate Fe content. The parameters affecting the structure and amount of Fe in K-Feldspar was investigated to reach an optimal leaching condition. Next, kasilite removal was studied by introducing CaF₂ to the composition of dental porcelain. To synthesis leucite, the prepared materials were heated up to 1450°C for 3 hours until fusion phenomena occurred, then cooled down to 865°C to permit the leucite crystals nucleate and grow. To find out the chemical composition of powder, XRF, EDX, and Atomic absorption spectroscopy were used. Fourier Transform Infrared Spectroscopy and X-Ray Diffractometer and Scanning Electron Microscopy were employed to study the structure of mineral. Spectrophotometry was chosen to analyze whiteness index of powder after acid treatment. Differential Thermal Analysis was employed to determine the crystallization temperature. Results indicated a dramatic decrease in Fe content (0.018%wt) by employing C₂H₂O₄ as a leachant at 50°C. In addition, whiteness index of 91% was achieved through this procedure for raw feldspar. Finally, 1%wt of CaF₂ prevented formation of kalsilite.     

A review of fault ride through of PV and wind renewable energies in grid codes

This paper presents a comprehensive review of fault ride through (FRT) in the grid code of 38 selected countries with an emphasis on renewable energy (REN) sources–related rules. Grid codes are the rules legislated usually by the transmission system operators (TSOs) to determine the grid integration requirements of electrical power generators. Each country establishes its grid code for satisfying the minimum required technical criteria and revises it frequently to cope with new modifications of the utility. Growing the penetration of REN sources have influenced many operational aspects of the power system such as protection, power quality, reliability, and stability. Thereupon, regulations must ensure the power system's secure and controllable operation of REN sources. FRT is one of the main parts of the grid code, and its characteristics affect the performance and rating of power system apparatus. FRT defines the performance of electric power generators during and in postfault conditions. FRT of solar photovoltaic (PV) and wind turbines (WTs) as the main REN sources of energy has great importance in the grid codes. In this paper, a comparison of FRTs in the grid code of 38 countries, including low‐voltage ride through (LVRT), zero‐voltage ride through (ZVRT), and high‐voltage ride through (HVRT) are provided and surveyed.     

Processing of Hyperion data set for detection of indicative minerals using a hybrid method in Dost-Bayli,Iran

In recent years hyperspectral remote sensing has played an important role in discovering of the earth surface and unmixing is an indispensable part of the hyperspectral data analysis. The most challenging stage in the spectral unmixing is determination of endmembers (EMs). Because of the absence of pure pixels, common methods based on pure pixel assumption do not yield accurate results. On the other hand, Hyperion hyperspectral data acquired by National Aeronautics and Space Administration (NASA)’s Earth Observing-1 (EO-1) system, is available widely but with a lower signal-to-noise ratio (SNR) in comparison to airborne spectrometers. Therefore, the methods with less sensitivity to noise amount will be more efficient in processing of the Hyperion data. Minimum Volume Constrained Nonnegative Matrix Factorization (MVC-NMF) algorithm is then an appropriate technique for EM detection in this case. It, however, has shortcomings in dealing with large data. To fix this problem the first module of Optical Real-time Adaptive Spectral Identification System (ORASIS) was applied for data reduction before running of the MVC-NMF algorithm. The modified technique was then investigated on a set of noisy synthetic data that the outcomes proved its functionality. The Hyperion image of Dost-Bayli area located in the Ardabil province in northwestern Iran, was then unmixed by the mentioned approach. To validate the accuracy of detected minerals, 20 surface samples were collected from the study area and analysed by X-ray diffraction (XRD) for detection of their mineralogical constituents and spectrometry to create a native spectral library. However, both native and United States Geological Survey (USGS) spectral libraries were applied in identification of estimated EMs. The signatures of the obtained EMs by hybrid method were appropriately similar to reference spectra. The mineral abundances maps were therefore generated by linear spectral unmixing (LSU), which have proper consistency with XRD results.     

Optimization of sensitized perovskite solar cells with Zn–Cu–In–Se quantum dots to increase quantum efficiency

Journal of Materials Science: Materials in Electronics - Perovskite solar cells are efficient units in systems with modern renewable energy sources. Increasing the efficiency of solar cells is...