Compact ultra‐wideband bandpass filter with variable notch characteristics based on transversal signal‐interaction concepts

A novel technique is presented to design highly compact microstrip ultra‐wideband (UWB) bandpass filters that exhibit high selectivity quasi‐elliptical response. The design is based on transversal signal‐interaction concepts that enable the inclusion of single or dual notch‐bands within the filter's passband to eliminate interference from other services that coexist within the UWB spectrum. The filter configuration comprises of two transmission paths which include folded T‐shaped stepped impedance resonators (SIRs) that are capacitively coupled with the input/output lines to enable signal transmission. It is shown that by combining the filters of different passband centre frequencies an UWB filter can be realised with either a single‐ or dual‐notch function. The theoretical performance of the filter is corroborated via measurements to confirm that the proposed filter exhibits UWB passband of 123% for a 3 dB fractional bandwidth, a flat group‐delay with maximum variation of less than 0.3 ns, passband insertion loss less than 0.94 dB, high selectivity, a sharp rejection notch‐band with attenuation of ?23 dB, and a good overall out‐of‐band performance. Furthermore, the filter occupies a significantly small area of 94 mm² compared with its classical counterparts. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:549–559, 2014.     

Unit commitment-based load uncertainties based on improved particle swarm optimisation

This paper presents an intelligent method based on Improved Particle Swarm Optimisation to solve a unit commitment problem that takes into account the uncertainty in the demand. This uncertainty is included in the optimisation problem as a joint chance constraint that bounds the minimum value of the probability to jointly meet the deterministic power balance constraints. The demand is modelled as a multivariate, normally distributed, random variable and the correlation among different time periods is also considered. To demonstrate the effectiveness and robustness of the proposed algorithm, a system with 10 thermal and wind units with various conditions is simulated. The results and numerical experiments are compared with other methods to provide valuable information for both operational and planning problems.     

台中城市文化馆

本案是由de Architekten Cie,设计的台中城市文化馆竞赛方案。设计师将这座由博物馆、图书馆两栋分楼和共同的底层构成的文化馆建筑设计成柔性结构,以适应博物馆和图书馆两种功能频繁变化的使用需求。     

New design equations for assessment of load carrying capacity of castellated steel beams: a machine learning approach

This paper presents an innovative machine learning approach for the formulation of load carrying capacity of castellated steel beams (CSB). New design equations were developed to predict the load carrying capacity of CSB using linear genetic programming (LGP), and an integrated search algorithm of genetic programming and simulated annealing, called GSA. The load capacity was formulated in terms of the geometrical and mechanical properties of the castellated beams. An extensive trial study was carried out to select the most relevant input variables for the LGP and GSA models. A comprehensive database was gathered from the literature to develop the models. The generalization capabilities of the models were verified via several criteria. The sensitivity of the failure load of CSB to the influencing variables was examined and discussed. The employed machine learning systems were found to be effective methods for evaluating the failure load of CSB. The prediction performance of the optimal LGP model was found to be better than that of the GSA model.     

FIVE-SPOT INJECTION/PRODUCTION WELL LOCATION DESIGN BASED ON FRACTURE GEOMETRICAL CHARACTERISTICS IN HEAVY OIL FRACTURED RESERVOIRS DURING MISCIBLE DISPLACEMENT: AN EXPERIMENTAL APPROACH

Mapping fracture characteristics by using seismic acquisition and processing is important not only to identify sweet spots, but also to optimize production, especially for unconventional heavy oil reservoirs. In this experimental work we used five-spot micromodels initially saturated with heavy oil to find the optimum well locations during first-contact miscible displacement. The experiments were performed at a fixed injection rate on fractured micromodels with various patterns. The optimum location for injection/production wells was found in the pattern where fractures make an angle of 45° with the mean flow direction. Moreover, oil recovery was increased with the density, length, level of scattering, and discontinuity of fractures. The analysis of the experimentally measured recovery curve revealed that there are three distinct stages for each displacement. The efficiency of the first stage was found to be dominated by dispersion and diffusion. However, the recovery of the second stage was significantly affected by the fracture orientation. The displacement efficiency of the third stage was controlled by solvent dispersion, which is at maximum for the pattern with higher density, length, scattering, and discontinuity of fractures. Saturation monitoring showed that the fracture geometrical characteristics strongly affected the splitting, spreading, and shielding of the produced fingers and solvent front shape and consequently affected the recovery factor. As a result, five-spot micromodels can be used to investigate the optimum location of injection/production wells during miscible displacements in fractured heavy oil reservoirs.     

Establishment of a calibration curve for an isocentric cobalt unit using Monte Carlo simulation

Measurement of dose distribution in patients during radiotherapy is impossible. The Monte Carlo simulation is an alternative method for dose calculations. In routine radiotherapy, the source-to-surface distance(SSD)method is not practical for an isocentric unit because it requires numerous values of tissue–air ratios and inverse square law. Therefore, this method is time consuming. In this paper, the curves of relative depth doses were obtained for three different SSDs using the MCNP4C Monte Carlo simulation and approximated with a single curve called calibration curve. This curve was compared to the curve obtained by published data, differing in approximately 5% in the worst case. It was also observed that the obtained results were more accurate for distances between-5 and 10 cm from source-to-axis distance.     

Effect of chemical solvents on the technological characteristics of hemp fibre/polypropylene composites

The effects of different chemical solvents on the technological properties of hemp fibre-reinforced polypropylene composites were evaluated in this experimental work. Composite profiles consisting of hemp fibre and polypropylene at 50% weight ratios, with 2% of coupling agent were fabricated using melt compounding followed by injection moulding. The composite specimens were then immersed in CH₃COOH, HNO₃, H₂SO₄, NaOH, NH₃, and C₆H₅NH₂ for different time intervals. Then, the weight loss and mechanical strength of samples were measured. Results indicated that the chemical reagents had significant effect on the weight loss of the composites. The weight loss ratio of the control samples was lower than that of those samples exposure to the chemical solvents. The tensile strength and modulus, and impact strength of composite specimens decreased after exposure to the chemical solvents. The highest mechanical reduction was observed in the case of NaOH. SEM micrographs showed that the extent of degradation increased in composites when they are exposed to chemical solvents.     

Experimental analysis of properties of materials for rapid prototyping

Rapid prototyping (RP) can substantially shorten the time and reduce the cost of developing a new product from the initial idea to production. Rapid prototyping can help in recognizing the basic defects whose subsequent correction may prove very expensive, especially if they have already been made when the product is ready for production. There are also many restrictions of RP procedures, primarily in the number of available materials and their properties, which may differ significantly from the properties of end product materials. In this work, based on the stipulated standards of the 3D printing machines (ZPrinter 310 Plus) and the hybrid Polyjet technique (Objet Eden 330), adequate test specimens were made. Furthermore, with adequate equipment, we carried out the analysis of the dimensions, roughness of surfaces, and mechanical properties of prototype test specimens. Then, based on the data obtained by testing of properties, we provided a critical commentary regarding the data stipulated by their producers.     

Rigorous modeling of gypsum solubility in Na–Ca–Mg–Fe–Al–H–Cl–H2O system at elevated temperatures

Precipitation and scaling of calcium sulfate have been known as major problems facing process industries and oilfield operations. Most scale prediction models are based on aqueous thermodynamics and solubility behavior of salts in aqueous electrolyte solutions. There is yet a huge interest in developing reliable, simple, and accurate solubility prediction models. In this study, a comprehensive model based on least-squares support vector machine (LS-SVM) is presented, which is mainly devoted to calcium sulfate dihydrate (or gypsum) solubility in aqueous solutions of mixed electrolytes covering wide temperature ranges. In this respect, an aggregate of 880 experimental data were gathered from the open literature in order to construct and evaluate the reliability of presented model. Solubility values predicted by LS-SVM model are in well accordance with the observed values yielding a squared correlation coefficient (R ²) of 0.994. Sensitivity of the model for some important parameters is also checked to ascertain whether the learning process has succeeded. At the end, outlier diagnosis was performed using the method of leverage value statistics to find and eliminate the falsely recorded measurements from assembled dataset. Results obtained from this study indicate that LS-SVM model can successfully be applied in predicting accurate solubility of calcium sulfate dihydrate in Na–Ca–Mg–Fe–Al–H–Cl–H₂O system over temperatures ranging from 283.15 to 371.15 K.