Optimization of downhole pump setting depths in liquid-dominated geothermal systems: A case study on the Balcova-Narlidere field,Turkey

Downhole pumps are being used increasingly more often in low-enthalpy geothermal wells. The depth at which these pumps are installed depends on the physical and chemical characteristics of the geothermal fluid, the production flow rate, and the reservoir pressure and permeability. In this study we have investigated the factors affecting pump setting depths in low-temperature, liquid-dominated geothermal systems and defined the relationship between flow rate and pressure drawdown based on multi-rate test results. The methodology proposed was applied to the Balcova-Narlidere geothermal field, Turkey. It was found that the most important parameters for determining the capacity and setting depth of a downhole pump were flow performance, non-condensable gas concentration, and temperature. The implementation of the methodology is illustrated.     

Mechanical behaviour of SiC fibre-reinforced titanium/titanium aluminide hybrid composites

The viability of developing an SiC fibre-reinforced titanium/titanium aluminide hybrid matrix composite was explored. The hybrid composites are expected to be used at temperatures beyond those attainable in conventional titanium matrix composites while improving the damage tolerance of the titanium aluminide matrix composites. The room-temperature mechanical characteristics studied were tensile strength, fracture toughness, low-cycle fatigue life and fatigue crack growth rate. The mechanisms of damage initiation and propagation under various loading conditions were also characterized. The directions for developing a satisfactory composite with hybrid titanium/titanium aluminide matrix are also addressed.     

Microarchitectures for Managing Chip Revenues under Process Variations

As transistor feature sizes continue to shrink intothe sub-90nm range and beyond, the effects of process variationson critical path delay and chip yields have amplified. A commonconcept to remedy the effects of variation is speed-binning, bywhich chips from a single batch are rated by a discrete range offrequencies and sold at different prices. In this paper, we discussstrategies to modify the number of chips in different bins andhence enhance the profits obtained from them. Particularly, wepropose a scheme that introduces a small Substitute Cacheassociated with each cache way to replicate the data elementsthat will be stored in the high latency lines. Assuming a fixedpricing model, this method increases the revenue by as much as13.8% without any impact on the performance of the chips.     

Synthesis and characterization of novel polyacrylate-clay sol-gel materials

Organo-functional silanes which were able to form chemical bonds with kaolinite and could also have an affinity to the materials of concern here, were studied by the sol-gel process. Polymethacrylate with trialkoxy silyl functional groups were prepared, hydrolysed and co-condensed with kaolinite. The progress of the hydrolysis, which proceeded very slowly, was followed by Karl-Fischer titration. Thermal behavior was investigated by differential thermal analysis. The extent of the reaction leading to network formation was qualitatively followed by Fourier transform-infrared spectroscopy and X-ray diffraction. Free-radical polymerization was carried out ultrasonically in the presence of a catalyst. Trimethoxy silane end-capped silane was found to be covalently bonded to kaolinite. The copolymers, with various amounts of kaolinite, were then hydrolysed and co-condensed in the presence of a catalyst to yield sol-gel materials which have a controllable combination of properties of both the polymer and kaolinite.     

Corrosion behavior of tempered dual-phase steel embedded in concrete

Dual-phase(DP) steels with different martensite contents were obtained by appropriate heat treatment of an SAE1010 structural carbon steel,which was cheap and widely used in the construction industry. The corrosion behavior of DP steels in con-crete was investigated under various tempering conditions. Intercritical annealing heat treatment was applied to the reinforcing steel to obtain DP steels with different contents of martensite. These DP steels were tempered at 200,300,and 400°C for 45 min and then coo...     

Dispersion-strengthening effect of Cu-based Mn, Al, and Zn rich alloys

In this systematic study, dispersion-strengthening effect of the Cu–25.91Mn (wt.%), Cu–26.62Mn–8.99Al (wt.%), Cu–22.17Mn–12.32Zn (wt.%) ingot alloys have been investigated. Samples were homogenized at a high fixed temperature in different periods and cooled with different cooling rates. After processes, microanalysis of the samples were interpreted by using scanning electron microscope (SEM) and weight percentages of the elements of the occurrence phases in the samples obtained by using electron dispersion spectroscopy (EDS) technique. Additionally, some characteristic properties of the heat treated samples with different conditions of Cu–Mn, Cu–Mn–Al, Cu–Mn–Zn ingot alloys were also discussed.     

Generic visual analysis for multi- and hyperspectral image data

Multi- and hyperspectral imaging and data analysis has been investigated in the last decades in the context of various fields of application like remote sensing or microscopic spectroscopy. However, recent developments in sensor technology and a growing number of application areas require a more generic view on data analysis, that clearly expands the current, domain-specific approaches. In this context, we address the problem of interactive exploration of multi- and hyperspectral data, consisting of (semi-)automatic data analysis and scientific visualization in a comprehensive fashion. In this paper, we propose an approach that enables a generic interactive exploration and easy segmentation of multi- and hyperspectral data, based on characterizing spectra of an individual dataset, the so-called endmembers. Using the concepts of existing endmember extraction algorithms, we derive a visual analysis system, where the characteristic spectra initially identified serve as input to interactively tailor a problem-specific visual analysis by means of visual exploration. An optional outlier detection improves the robustness of the endmember detection and analysis. An adequate system feedback of the costly unmixing procedure for the spectral data with respect to the current set of endmembers is ensured by a novel technique for progressive unmixing and view update which is applied at user modification. The progressive unmixing is based on an efficient prediction scheme applied to previous unmixing results. We present a detailed evaluation of our system in terms of confocal Raman microscopy, common multispectral imaging and remote sensing.     

Krylov projection framework for Fourier model reduction

This paper analyzes the Fourier model reduction (FMR) method from a rational Krylov projection framework and shows how the FMR reduced model, which has guaranteed stability and a global error bound, can be computed in a numerically efficient and robust manner. By monitoring the rank of the Krylov subspace that underlies the FMR model, the projection framework also provides an improved criterion for determining the number of Fourier coefficients that are needed, and hence the size of the resulting reduced-order model. The advantages of applying FMR in the rational Krylov projection framework are demonstrated on a simple example.     

A Model for Cross-Domain Opinion Target Extraction in Sentiment Analysis

Opinion target extraction is one of the core tasks in sentiment analysis on text data. In recent years, dependency parser–based approaches have been commonly studied for opinion target extraction. However, dependency parsers are limited by language and grammatical constraints. Therefore, in this work, a sequential pattern-based rule mining model, which does not have such constraints, is proposed for cross-domain opinion target extraction from product reviews in unknown domains. Thus, knowing the domain of reviews while extracting opinion targets becomes no longer a requirement. The proposed model also reveals the difference between the concepts of opinion target and aspect, which are commonly confused in the literature. The model consists of two stages. In the first stage, the aspects of reviews are extracted from the target domain using the rules automatically generated from source domains. The aspects are also transferred from the source domains to a target domain. Moreover, aspect pruning is applied to further improve the performance of aspect extraction. In the second stage, the opinion target is extracted among the aspects extracted at the former stage using the rules automatically generated for opinion target extraction. The proposed model was evaluated on several benchmark datasets in different domains and compared against the literature. The experimental results revealed that the opinion targets of the reviews in unknown domains can be extracted with higher accuracy than those of the previous works.