An experimental study on air window collector having a vertical blind for active solar heating

In this study, an air window collector having vertical black blinds was investigated experimentally under actual outdoor conditions. The vertical blind was installed between two 120 × 80 cm glass panes. It can rotate about the vertical axis. The fully open position makes a 90° angle with the vertical plane. A commercially available blind made of cloth and coated with black paint was tested. The air circulation in the system is provided by a fan parallel to blinds. Various parameters were measured and recorded using a data acquisition system. The effect of these parameters on the thermal performance of the system were determined experimentally.     

An experimental and three-dimensional numerical study of natural convection heat transfer between two horizontal parallel plates

In this study, experimental and three-dimensional numerical studies were performed to investigate the effects of plate spacing and temperature difference on natural convection between isothermally heated upward-facing lower horizontal plate and externally insulated horizontal upper plate. Air is used as the heat transfer medium. Rayleigh number varied in the 1108–2.339 × 10⁵ range. Several numerical simulations for three-dimensional steady laminar and turbulent flows heat transfer were carried out using a commercial CFD code Fluent 6.2. Results have shown that there is a good agreement between the numerical and present experimental results as well as with available data in literature.     

Viscoelastic and Processing Effects on the Fiber-Matrix Interphase Strength. Part I. The Effects of Loading Rate, Test Temperature, Fiber Sizing and Global Strain Level

The effects of loading rate, fiber sizing, test temperature and global strain level on the adhesion strength between carbon fibers and a thermosetting epoxy (Epon 815) are studied using the single fiber fragmentation test procedure. Analytical methodology describing the viscoelastic behavior observed is also presented. The possibility of rate-temperature-interphase thickness superposition for the interfacial strength function is illustrated based on the analytical models discussed. Experimental data are discussed using Weibull statistics and also presented in the form of percent relative frequency histograms for the fiber fragments in a collective fashion. The use of histograms allows for interpretation of the skewness in the data population.     

A performance study of multiprocessor task scheduling algorithms

Multiprocessor task scheduling is an important and computationally difficult problem. A large number of algorithms were proposed which represent various tradeoffs between the quality of the solution and the computational complexity and scalability of the algorithm. Previous comparison studies have frequently operated with simplifying assumptions, such as independent tasks, artificially generated problems or the assumption of zero communication delay. In this paper, we propose a comparison study with realistic assumptions. Our target problems are two well known problems of linear algebra: LU decomposition and Gauss–Jordan elimination. Both algorithms are naturally parallelizable but have heavy data dependencies. The communication delay will be explicitly considered in the comparisons. In our study, we consider nine scheduling algorithms which are frequently used to the best of our knowledge: min–min, chaining, A^*, genetic algorithms, simulated annealing, tabu search, HLFET, ISH, and DSH with task duplication. Based on experimental results, we present a detailed analysis of the scalability, advantages and disadvantages of each algorithm.

Active time scheduling for rechargeable sensor networks

Recent progress in energy harvesting technologies made it possible to build sensor networks with rechargeable nodes which target an indefinitely long operation. In these networks, the goal of energy management is to allocate the available energy such that the important performance metrics, such as the number of detected threats, are maximized. As the harvested energy is not sufficient for continuous operation, the scheduling of the active and inactive time is one of the main components of energy management. The active time scheduling protocols need to maintain the energy equilibrium of the nodes, while considering the uncertainties of the energy income, which is strongly influenced by the weather, and the energy expenditures, which are dependent on the behavior of the targets. In this paper, we describe and experimentally compare three active time scheduling protocols: (a) static active time, (b) dynamic active time based on a multi-parameter heuristic and (c) utility-based uniform sensing. We show that protocols which take into consideration the probabilistic models of the energy income and expenditure and can dynamically adapt to changes in the environment, can provide a significant performance advantage.     

A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model.     

A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers

It is well known that “green” principles and strategies have become vital for companies as the public awareness increased against their environmental impacts. A company’s environmental performance is not only related to the company’s inner environmental efforts, but also it is affected by the suppliers’ environmental performance and image. For industries, environmentally responsible manufacturing, return flows, and related processes require green supply chain (GSC) and accompanying suppliers with environmental/green competencies. During recent years, how to determine suitable and green suppliers in the supply chain has become a key strategic consideration. Therefore this paper examines GSC management (GSCM) and GSCM capability dimensions to propose an evaluation framework for green suppliers. However, the nature of supplier selection is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. The identified components are integrated into a novel hybrid fuzzy multiple criteria decision making (MCDM) model combines the fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL), the Analytical Network Process (ANP), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) in a fuzzy context. A case study is proposed for green supplier evaluation in a specific company, namely Ford Otosan.     

Stochastic Model for Landfill Gas Transport and Energy Recovery

Predicting the amount of landfill gas (LFG) that will be recovered at a sanitary landfill is generally associated with a high level of uncertainty, which is primarily due to the uncertainty in the definition of the parameters that control the LFG generation rate and LFG transport. To quantify these uncertainties, a three-dimensional stochastic model for the generation and transport of LFG is proposed. Using Monte Carlo simulations, multiple realizations of key input parameters are generated. For each realization, LFG transport is simulated and then used to evaluate probabilistically the rates and efficiency of energy recovery. For demonstration, the stochastic model is applied to the Kemerburgaz landfill in Istanbul, Turkey. Uncertainty in the definition of three key parameters, namely: the LFG production rate, the waste gas permeability and the soil cover gas permeability were accounted for. Modeling results suggest that the collection system is sufficient to capture most of the generated gas, but that uncertainty in the factors controlling LFG production is the main source of uncertainty in the amount of energy that will be recovered.     

Biosorption of Acid Red P-2BX by lichens as low-cost biosorbents

The aim of this study is to examine the dye biosorption properties of lichen species called Cladonia convoluta and Evernia prunastri. Since lichens are extensively found in the environment, their suitability as a cheap adsorbent has been investigated in this study. The optimal parameters for textile dye biosorption were also determined. The dried lichen biomass showed better dye biosorption capacity than ash lichen biomass. C. convoluta had better dye biosorption capacity than E. prunastri. Dye biosorption rate was found as 71.41% at optimal conditions. This study concluded that C. convoluta was a successful and cheap biosorbent for treatment of water contaminated by Acid Red P-2BX dye.     

Investigation of factors affecting the dispersibility of clays and estimation of dispersivity

Dispersive soils have caused failure of many slopes and earth fills due to external and internal erosion. This study aims to investigate various factors used for identification of dispersivity and to develop some new approaches for the prediction of dispersivity of clays. To achieve this purpose, physical and index properties, as well as degree of dispersivity of 29 clay samples taken from five different locations in and around the city of Ankara were determined. Various statistical prediction models were used for prediction of new dispersivity classes obtained by weighting ranking method. It was determined that dispersivity classes obtained from physical and chemical dispersivity tests performed on the same clay samples using distilled water were different from each other. In addition, crumb and pinhole tests were performed by using test waters with varying TDS values on five selected samples to find the impact of water chemistry on dispersivity. It is concluded from all dispersivity tests that total dissolved salts (TDS) values and sodium percentage (SP) remarkably affect the degree of dispersivity, and the use of these two parameters give more reliable results for the determination of dispersivity. By considering all these facts and to predict the most reliable dispersivity class, all dispersivity classes obtained from physical and chemical dispersivity tests were reevaluated by a weighted ranking system, and new dispersivity classes were assigned. In order to estimate these new dispersivity classes, various statistical models were established by using results of chemical analysis of pore water of clay samples. For this purpose, prediction models including soft computing methods such as decision tree and logistic regression are used and most reliable prediction models having the highest prediction performance are suggested.