Comparison of single-cell testing,short-stack testing and mathematical modeling methods for a direct methanol fuel cell

In this paper, a comparison between direct methanol fuel cell (DMFC) measurements performed on a single cell and a short-stack, and the results of a mathematical model for a DMFC, is presented. The testing of a short-stack, which consists of 5 cells with an active area of 315 cm², was performed at various current densities, permeation current densities, and cathode flow rates (CFR) in order to determine the voltage outputs of each cell. Methanol concentration and stack temperature results obtained from short-stack testing were then integrated into the single cell test and single cell mathematical model as the input parameters. For the mathematical modelling, transport equations originating from methanol, water, and oxygen were coupled with the electrochemical relations. Therefore, a comparison between these three methods is made in order to gain a deeper understanding of the effects of the operating parameters on DMFC performance. This study showed that the model could describe experimental results well when lower methanol concentrations (under 1.2 M) and temperature (under 60 °C) values are used as input parameters. The results also show very good agreement at lower methanol permeation rates and therefore lower temperatures. It is found that the voltage output for a given current density is higher for the theoretical model than that of the experimental studies; and the differences in the results can be up to 0.04 V for a cell.     

A Rigorous Wavelet-Packet Transform to Retrieve Snow Depth from SSMIS Data and Evaluation of its Reliability by Uncertainty Parameters

Water Resources Management - This study demonstrates the application of wavelet transform comprising discrete wavelet transform, maximum overlap discrete wavelet transform (MODWT), and...     

Heat exchanger network design of an organic Rankine cycle integrated waste heat recovery system of a marine vessel using pinch point analysis

The coexistence of different kinds of waste heat sources on marine vessels with various temperature ranges increases the need for an optimal heat exchanger network (HEN) design for the heat collection process to reduce the unutilizable heat that needs to be discharged to overboard. The optimal HEN design has not been taken into consideration by using pinch point analysis in previous studies of marine organic Rankine cycle (ORC) systems that utilize from different kinds of waste heat sources. The objective of the study is to determine the optimal HEN design for an ORC integrated waste heat recovery system of a marine vessel by utilizing the pinch point analysis to improve the overall energy efficiency. Lubricating oil, high-temperature cooling water and scavenge air of the main engine, and the exhaust gas emitted from the boiler plant were identified as the major waste heat sources of a reference container ship. A heat collection stream, in which thermal oil is used as the heat transfer fluid that transfers the collected heat to an ORC system, was proposed. The pinch point analysis showed that the optimum waste heat recovery could be gained by separating the scavenge air cooler into three stages and the lubricating oil cooler into two stages. The results of the parametric study for the varying evaporator inlet pressure between 1000 and 3000 kPa showed that R1234ze(Z) yields the best performance among nine different organic working fluids with the thermal efficiency and exergy efficiency of 15.24% and 86.47% for the ORC system, respectively. For the proposed configuration, the unavailable waste heat that cannot be transferred to thermal oil was found as 23.71%, 16.56%, 13.17%, and 7.81% of the total waste heat produced by the heat sources, and also 8.24%, 9.80%, 11.55%, and 12.93% of the net power output produced by the main engine can be recovered for 25%, 50%, 76%, and 100% maximum continuous rating (MCR), respectively.     

A comparative study on different analysis approaches for estimating the axial loads on columns and structural walls at tall buildings

Estimating axial loads on columns and structural walls at tall buildings is a complicated task because time‐dependent deformations of concrete and the way the building is constructed affect the way the gravity loads are carried by them. The accurate computation of axial loads is crucial for determining the size and strengths of columns and structural walls. This study investigates several analysis approaches commonly used during the design of such buildings. Construction sequences, time‐dependent deformations and longitudinal reinforcement were considered, and their influences on results were discussed. A simplified model of an actual 37‐story building was used as a case study. The results indicated that the column and wall axial load might vary up to 45% depending on the type of analysis and effects that were considered. Copyright © 2011 John Wiley & Sons, Ltd.     

Evapotranspiration Modeling Using Linear Genetic Programming Technique

The study investigates the accuracy of linear genetic programming (LGP), which is an extension to genetic programming (GP) technique, in daily reference evapotranspiration (ET0) modeling. The daily climatic data, solar radiation, air temperature, relative humidity, and wind speed from three stations, Windsor, Oakville, and Santa Rosa, in central California, are used as inputs to the LGP to estimate ET0 obtained using the FAO-56 Penman-Monteith equation. The accuracy of the LGP is compared with those of the support vector regression (SVR), artificial neural network (ANN), and those of the following empirical models: the California irrigation management system Penman, Hargreaves, Ritchie, and Turc methods. The root-mean-square errors, mean-absolute errors, and determination coefficient (R2) statistics are used for evaluating the accuracy of the models. Based on the comparison results, the LGP is found to be superior alternative to the SVR and ANN techniques.