Optimal Water Allocation of Surface and Ground Water Resources Under Climate Change with WEAP and IWOA Modeling

Water Resources Management - The water evaluation and planning (WEAP) approach and the invasive weed optimization algorithm (IWOA) are herein employed to determine the optimal operating policies in...     

Multi-criteria Decision-making Approach for Environmental Impact Assessment to Reduce the Adverse Effects Of Dams

Water Resources Management - Environmental Impact Assessments (EIAs) of development projects are necessary to minimize negative impacts and maximize benefits. The objective of this paper is to...     

Profiling selected phytochemicals and nutrients in different tissues of the multipurpose tree Moringa oleifera L., grown in Ghana

The purpose of this new study was to determine the types and levels of major phytochemicals (non-nutrients) and nutrients in the different tissues from vegetative and flowering Moringa oleifera L. an important multipurpose crop. Rhamnose and acetyl-rhamnose-substituted glucosinolates were found in all of the M. oleifera tissues with different profiles depending on the tissue. In addition the tissues of M. oleifera had a relatively complex flavonoid profile consisting of glucosides, rutinosides, malonylglucosides and traces of acetylglucosides of kaempferol, quercetin and isorhamnetin. Fatty acid profiling of the different tissues showed that leaves were rich in palmitic (16:0) and linolenic (18:3) acid whereas seeds were predominated by oleic acid (18:1). Roots were rich in palmitic and oleic acid, whereas stems and twigs predominately contained palmitic acid. Potassium, magnesium and calcium were the predominant minerals in all of the tissues. Low levels of selenium were detected only in whole seeds.     

GDQ METHOD FOR NATURAL CONVECTION IN A SQUARE CAVITY USING VELOCITY–VORTICITY FORMULATION

ABSTRACT

This article describes a compact numerical algorithm based on the generalized differential quadrature (GDQ) method for the numerical analysis of natural convection in a differentially heated square cavity. The velocity–vorticity form of the Navier–Stokes equations and energy equation are used to represent the mass, momentum, and energy conservations of the fluid medium in the cavity. The GDQ form of the governing equations and the vorticity definition at the boundaries are solved by a coupled solution algorithm using a global matrix scheme for all the field variables. The vorticity values at the boundary are correctly imposed using the GDQ method, which approximates a given space derivative with higher-order accuracy compared to the existing schemes based on Taylor's series expansion. This has assured a divergence-free solution for the flow field by satisfying the continuity constraint, though the pressure term is not used directly in the present formulation. The proposed algorithm is validated for a lid-driven cavity flow for Reynolds number Re = 100, 400, and 1,000, and the predicted velocity profiles are in excellent agreement with the benchmark solutions. The algorithm is then used to compute the average Nusselt number and flow parameters for natural convection in a square cavity for Rayleigh number Ra = 10³, 10⁴, 10⁵, and 10⁶. These results are in better agreement with the benchmark solutions than the results obtained by other numerical schemes, which used much finer grids compared to the present scheme.     

机织物在各个方向上的剪切性能

剪切性能是影响机织物外观及力学行为的重要特性之一。本文在Kilby等人工作的基础上建立模型 ,预测机织物在各个方向上的剪切刚度。基于现有文献 ,我们发现剪切刚度 (G)、0 5°及 5°角的剪切滞后有明显的线性关系。因此通过比较理论结果与实验数据 ,并将它们在极坐标图上展现出来 ,证明该模型亦可用于预测大范围类型机织物的剪切滞后。实验结果表明 ,剪切刚度与剪切滞后的这种线性关系不仅存在于经、纬两个主方向上 ,也存在于与经纬向成各种夹角的方向上。在实验中还发现 ,机织物剪切刚度的最大值出现在与经纬向成± 45°夹角的方向上。…     

Rate of evolution of the specific surface area of surface snow layers

The snowpack can impact atmospheric chemistry by exchanging adsorbed or dissolved gases with the atmosphere. Modeling this impact requires the knowledge of the specific surface area (SSA) of snow and its variations with time. We have therefore measured the evolution of the SSA of eight recent surface snow layers in the Arctic and the French Alps, using CH4 adsorption at liquid nitrogen temperature (77 K). The SSA of fresh snow layers was found to decrease with time, from initial values in the range 613-1540 cm2/g to values as low as 257 cm2/g after 6 days. This is explained by snow metamorphism, which causes modifications in crystal shapes, here essentially crystal rounding and the disappearance of microstructures. A parametrization of the rate of SSA decrease is proposed. We fit the SSA decrease to an exponential law and find that the time constant alpha(exp) (day(-1)) depends on temperature according to alpha(exp) = 76.6 exp (-1708/7), with Tin kelvin. Our parametrization predicts that the SSA of a snow layer evolving at -40 degrees C will decrease by a factor of 2 after 14 days, while a similar decrease at -1 degrees C will only require 5 days. Wind was found to increase the rate of SSA decrease, but insufficient data did not allow a parametrization of this effect.     

Roles of organic acids during exectrooxidation reaction over Pt-supported carbon electrodes in direct methanol fuel cells

A comprehensive study has been made to explore the role of organic acids on electrocatalytic performances of platinum (Pt) nanoparticles supported on carbon porous materials (CPMs) in proton exchange membrane fuel cells (PEMFCs). In particular, the effects of carboxylic acids (R–COOH), viz. formic acid, acetic acid, propionic acid, and butyric acid on catalytic activity, stability, and durability of anodic Pt/CPM electrocatalyst in direct methanol fuel cells (DMFCs) were investigated. In the presence of doped carboxylic acids, the electrooxidative activity of Pt/CPM follows the trend: HCOOH < CH₃COOH < C₂H₅COOH < C₃H₇COOH, revealing a consistent increase in the severity of catalyst deactivation with the number of carbons on the alkyl chain of the dopant. The Pt/CPM was found to exhibit electrocatalytic performances and tolerance for poisoning than a commercial Pt/XC-72 catalyst with a similar Pt loading (20 wt%). Moreover, a notable increase in mass activity up to ca. 150% over the spent Pt/CPM catalyst was observed up on removing the organic acid in the feed stream, indicating that catalyst poisoning by deactivation may be revived, even to its “intrinsic” activity.     

Applying real options analysis to assess cleaner energy development strategies

The energy industry, accounts for the largest portion of CO₂ emissions, is facing the issue of compliance with the national clean energy policy. The methodology for evaluating the energy mix policy is crucial because of the characteristics of lead time embedded with the power generation facilities investment and the uncertainty of future electricity demand. In this paper, a modified binomial model based on sequential compound options, which may account for the lead time and uncertainty as a whole is established, and a numerical example on evaluating the optional strategies and the strategic value of the cleaner energy policy is also presented. It is found that the optimal decision at some nodes in the binomial tree is path dependent, which is different from the standard sequential compound option model with lead time or time lag concept. The proposed modified binomial sequential compound real options model can be generalized and extensively applied to solve the general decision problems that deal with the long lead time of many government policies as well as capital intensive investments.     

Photo fermentative hydrogen production using dominant components (acetate, lactate, and butyrate) in dark fermentation effluents

Engineering strategies were applied to promote the phototrophic H₂ production of an indigenous purple nonsulfur bacterium Rhodopseudomonas palustris WP3-5 using major components (i.e., acetate, butyrate, and lactate) of dark fermentation effluents as carbon sources. First, performance of cell growth and photo-H₂ production on each carbon source was examined individually. It appeared that acetate was the most effective carbon source for photo-H₂ production, giving an overall H₂ production rate and H₂ yield of 12.68 ml/h/l and 67.1%, respectively. Next, the effect of substrate concentration of each carbon source on photo-hydrogen production was investigated. Kinetic models were developed to describe the correlation between maximum specific growth rate/specific H₂ production rate and the substrate concentration. The results show that using acetate and lactate as the carbon source, the kinetics for the cell growth and photo-hydrogen production can be described by Monod-type and Michaelis–Menten models, respectively, whereas substrate inhibition occurred when using butyrate as the carbon source. The continuous cultures were also conducted at a hydraulic retention time of 96 h using synthetic dark fermentation soluble metabolites (with a 5 and 10 fold dilution) as the influent. The phototrophic H₂ production efficiency was stably maintained for over 30 days with an overall H₂ yield 10.30 and 11.97 mol H₂/mol sucrose, when using 5-fold and 10-fold diluted dark fermentation effluent, respectively, as the substrate for dark fermentation. This demonstrates the feasibility of using the sequential dark and photo fermentation for high-yield biohydrogen production.     

Optimization of Run-of-River Hydropower Plant Design under Climate Change Conditions

The assessment of climate change and its impacts on hydropower generation is a complex issue. This paper evaluates the application of representative concentration pathways (RCPs, 2.6, 4.5, and 8.5) with the change factor (CF) method and the statistical downscaling method (SDSM) to generate six climatic scenarios of monthly temperature and rainfall over the period 2020–2049 in the Karkheh basin, Iran. The identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) model was employed to simulate runoff for the purpose of designing a run-of-river hydropower plant in the Karkheh basin. The non-dominated sorting genetic algorithm (NSGA)-II was employed to maximize yearly energy generation and the plant factor, simultaneously. Results indicate the runoff scenarios associated with the SDSM lead to higher run-of-river hydropower generation in 2020–2049 compared to the CF results.