A hierarchical classification scheme to define and order the design space for integral snap-fit assembly

The diversity of integral attachment snap-fit feature types (e.g. cantilever hooks, bayonet-fingers, compressive hooks, annular snaps, and others), and their possible combinations, sizes and locations and orientations on parts to enable assembly has made it appear that design possibilities may be unbounded. Attempts at understanding, no less optimization, seemed intractable. This paper presents a hierarchical classification scheme that brings order to the design space, and uses that classification scheme to define boundaries and size of the design space for achieving attachment at a level above feature detailing. Classification is based on the essential geometry of parts being assembled. The result is surprising order and simplicity, and the ability to reduce viable options for any assembly situation to a number (e.g. 8–10) that will permit true optimization.     

Preparation and Thermodynamic Properties of Camphene/Stearic Acid Composites as Phase-Change Materials in Buildings

In this study, a series of shape-stabilized phase-change materials (PCMs) of camphene/stearic acid (CS) were prepared and their thermal properties were measured by differential scanning calorimetry. The results indicated that the mixture consisting of 60 mass% camphene and 40 mass% stearic acid is the most favorable as a PCM, in terms of the phase-change temperature and latent heat. Thereafter, the CS was absorbed in fly ash, pyroclastic, barite, and marble powder, which acts as a supporting material, to prepare four kinds of composite-based PCMs. DSC, FT-IR, and scanning electron microscopy measurements were made to investigate the structures and properties of the PCMs. DSC results showed that the latent heats of melting and freezing of the composite PCMs were sharply decreased. Morphology and structural characterization revealed that, in form-stable PCMs, the dispersion of the supporting materials in the camphene/stearic acid matrix is homogeneous and there is no chemical interaction between the CS and composites. The composite PCMs showed excellent thermal stabilities and reliabilities, when their phase-change temperatures were concerned. These indicate that the prepared composite-based PCMs are suitable for thermal energy storage because of their applicable temperature range, thermal reliability, and chemical stability.     

Development of multiple soft computing models for estimating organic and inorganic constituents in coal

The distribution of the various organic and inorganic constituents and their influences on the combustion of coal has been comprehensively studied. However, the combustion characteristics of pulverized coal depend not only on rank but also on the composition, distribution, and combination of the macerals.Unlike the proximate and ultimate analyses, determining the macerals in coal involves the use of sophisticated microscopic instrumentation and expertise. In this study, an attempt was made to predict the amount of macerals(vitrinite, inertinite, and liptinite) and total mineral matter from the Witbank Coalfields samples using the multiple input single output white-box artificial neural network(MISOWB-ANN), gene expression programming(GEP), multiple linear regression(MLR), and multiple nonlinear regression(MNLR). The predictive models obtained from the multiple soft computing models adopted are contrasted with one another using difference, efficiency, and composite statistical indicators to examine the appropriateness of the models. The MISOWB-ANN provides a more reliable predictive model than the other three models with the lowest difference and highest efficiency and composite statistical indicators.     

Effects of coal properties on the production rate of combustion solid residue

The production rates of furnace bottom ash in a pulverized coal-fired power plant were monitored for a two-year period and its variations with respect to coal properties were analyzed. The power plant was originally designed to fire the coal sludge generated from a washing process; however, the coal sludge and its mixture with low-rank bituminous coal have been started to be used as the main fuel with time. The results of the hardgrove grindability measurements have shown that the grinding properties of sludge or its mixtures could not be predicted based on proximate analysis (moisture, ash, carbon and volatile contents); it could only be determined by experiments. The production rate of bottom ash in this particular power plant remained relatively insensitive to the high ash and moisture contents and could be estimated almost only by knowing the calorific value of the source coal. The evaluated dependency was linear.     

Determination of optimum ejector operating pressures for anodic recirculation in SOFC systems

In this study, a numerical analysis of an ejector for micro combined heat and power system based on 18 kW Solid Oxide Fuel Cell (SOFC) using methane as fuel is presented. An ejector design, which reflects the real system conditions in the view of the flow characteristics, is provided and the ejector performance is numerically investigated for various methane pressure to exhaust pressure ratios and methane inlet temperatures. The results show that the fuel inlet temperature and the pressure ratio of the methane to exhaust significantly affect the steam to carbon ratio (STCR) and entrainment ratio. The higher pressure ratio and methane temperature allow a high entrainment ratio and STCR, but as pressure ratio and methane temperature increase, STCR and entrainment ratio remain unchanged after a specific value. 1140 different scenarios related with the inlet and outlet pressures of the ejector and methane temperature are created to determine the optimum operating conditions. The simulations show that the optimum methane inlet pressure is 7 bar and exhaust pressure is 1.159 bar for the ejector geometry of the interest. The entrainment ratio and STCR are determined as 2.05 and 0.92, respectively at this optimum scenario.     

Hybrid resonant inverter-based induction heating converter with CFPDM

This article proposes a 50?kHz hybrid (series–parallel) resonant inverter-based induction heating (IH) converter which is controlled with commercial frequency pulse density modulation (CFPDM). Since the hybrid resonant inverter enhances the series resonant inverter performance due to short-circuit handling capability and current gain, it has been successfully employed in IH. High power conversion efficiency and wide output power range can be obtained using CFPDM. In addition, some harmonic current problems occurred in conventional pulse density modulation because of the resonant frequency of non-smoothing filter are eliminated via CFPDM. There is no need for the application of any additional switches or passive components in CFPDM. In this article, CFPDM hybrid resonant inverter-based IH converter is modelled and the analysis of the converter is presented in detail. The operation principle of CFPDM controller is shown. In addition, the advantages of hybrid resonant inverter and CFPDM are stated. The theoretical analysis is verified via simulation and experimental studies, which are in very good agreement.     

Epidemic-based reliable and adaptive multicast for mobile ad hoc networks

An emerging approach to distributed systems exploits the self-organization, autonomy and robustness of biological epidemics. In this article, we propose a novel bio-inspired protocol: EraMobile (Epidemic-based Reliable and Adaptive Multicast for Mobile ad hoc networks). We also present extensive performance analysis results for it. EraMobile supports group applications that require high reliability. The protocol aims to deliver multicast data reliably with minimal network overhead, even under adverse network conditions. With an epidemic-based multicast method, it copes with dynamic and unpredictable topology changes due to mobility. Our epidemic mechanism does not require maintaining any tree- or mesh-like structure for multicasting. It requires neither a global nor a partial view of the network, nor does it require information about neighboring nodes and group members. In addition, it substantially lowers overhead by eliminating redundant data transmissions. Another distinguishing feature is its ability to adapt to varying node densities. This lets it deliver data reliably in both sparse networks (where network connectivity is prone to interruptions) and dense networks (where congestion is likely). We describe the working principles of the protocol and study its performance through comparative and extensive simulations in the ns-2 network simulator.     

Stochastic convergence tests for US regional per capita personal income; some further evidence: a research note

This paper contributes to the time-series literature on US regional income convergence. We apply unit root tests to metropolitan and nonmetropolitan per capita personal income series from 1969 to 2001. We show that some of the mixed results on regional income convergence in the time-series literature may be the result of using different unit root tests. We demonstrate these mixed results with our data. Then, using a test we consider the most appropriate, we generate results which reject the hypothesis that US regional incomes are nonstationary. Thus, we provide additional support for the regional convergence of US per capita regional income.