Dynamic assessment of capacity investment in electricity market considering complementary capacity mechanisms

This paper proposes a decentralized market-based model for long-term capacity investment decisions in a liberalized electricity market. Investment decisions are fundamentally based on total revenues gained by investors. In most electricity markets, the complementary mechanisms are designed to ensure a desired level of reliability while covering investment costs of the suppliers. In such an environment, investment decisions are highly sensitive to expectation of price signals in both of energy market and capacity mechanisms. In this work, the system dynamics concepts are used to model the structural characteristics of electricity market such as, long-term firms’ behavior and relationships between variables, feedbacks, and time delays by appropriately bundling the energy market and capacity mechanisms. The market oriented capacity price as well as non-competitive capacity payments and a proposed hybrid capacity mechanism are linked with the energy market in the model. Such a decision model enables both the generation companies and the regulators gaining perfect insights into the possible consequences of different decisions they make under different policies and market conditions. In order to examine the performance of the electricity market with different capacity mechanisms, a case study is presented which exhibits the effectiveness of the proposed model.     

Nitrate removal using different carbon substrates in a laboratory model

Agricultural fields have been frequently identified as major contributors of nitrate leaching into surface and ground waters. Tile drains can act as direct pathways, transferring leached nitrate to surface water. Bioreactor filters are useful for the removal of nitrate from drainage waters; however, these filters require an external carbon supply to sustain denitrification. In this study, four organic carbon sources including wood, barley straw, rice husks, and date palm leaf, were used to enhance denitrification and the effects of water velocity and influent nitrate concentration on the nitrate removal were evaluated. Cumulative nitrate removal was highest for the date palm leaf treatments and was lowest for the wood treatments. The effects were in decreasing order for date palm leaf, barley straw, rice husks, and wood, respectively. The performance of the biofilters improved with increasing influent nitrate concentration and decreasing water velocity, allowing for high nitrate removal rates to be achieved. The results showed that all of the treatments had reduced the effluent nitrate concentrations below the USEPA maximum contaminant level for drinking water of 45 mg L(-1) nitrate at the end of the study.     

Evaluation of pre-rigor injection of beef with proteases on cooked meat volatile profile after 1day and 21days post-mortem storage

This research was carried out to determine the effects of pre-rigor injection of beef semimembranosus muscle with nine proteases from plant and microbial sources, on the volatile profile of cooked beef after 1 day and 21 days post-mortem (PM) storage using Solid-phase microextraction gas chromatography mass spectrometry analysis. A total of 23 aldehydes, 5 ketones, 3 furans, 8 nitrogen and sulphur compounds, 4 alkanes, 7 alcohols and 6 terpenes were detected. Eleven volatile compounds characteristic of ginger flavour were detected in zingibain-treated meat. Benzaldehyde significantly increased (p<0.05) only in kiwifruit juice (KJ), fungal 31 protease and Asparagus protease (ASP) treated samples from 1day to 21days PM storage. A significant increase (p<0.05) in 3-methylbutanal was observed in KJ, bacterial and fungal protease treated samples at 21days PM storage. Treatments with bromelain, papain, ASP, actinidin, and KJ (except KJ 21days) proteases resulted in flavour profiles closer to that of the control beef sample.     

Novel Sensor Fabrication for the Determination of Nanomolar Concentrations of Hg2+ in Some Foods and Water Samples Based on Multi-walled Carbon Nanotubes/Ionic Liquid and a New Schiff Base

The air and water stable room temperature ionic liquid 1-butyl-1-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide, [BMP]Tf₂N, multi-walled carbon nanotubes (MWCNTs), graphite powder and also a new synthesized Schiff base have been used to fabricate a new carbon composite electrode with very attractive sensing behavior. The new Schiff base was synthesized to apply as a selective agent in electrochemical responses of the voltammetric sensor for the determination of mercury (II) ions in aqueous solutions. The proposed sensor allowed the determination of mercury (II) in the wide linear dynamic range of 0.2–260.0 nmol l^?1. The limit of detection (LOD) was noticed to be 0.05 nmol l^?1. The prepared electrode was used for mercury (II) determination in the real samples.     

Synthesis and characterization of nano-sized γ-Al2O3 for investigation the effect of temperature on catalytic dehydration of methanol to dimethyl ether

The new high surface area and high active nano-sized porous γ-Al₂O₃ catalyst was produced by a co-precipitation method. The synthesized catalyst was characterized by X-ray diffraction, Fourier transform infrared, NH₃-temperature programmed desorption, and Brunauer-Emmett-Teller techniques. The results of characterization tests showed excellent textural and acidic properties of the synthesized catalyst for the methanol dehydration reaction. Catalytic dehydration of methanol to dimethyl ether was performed in an adiabatic fixed bed reactor using the new nano-sized catalyst at different operating temperatures. The results showed that the highest methanol conversion occurs in the temperature range of 300–350°C. Finally, a new correlation was developed to predict methanol conversion from operating temperature.     

Physico-chemical and structural changes of red-fleshed dragon fruit (Hylocereus polyrhizus) during fruit development

BACKGROUND: Determination of physico‐chemical (weight, length, diameter, stomatal density, respiration rate, colour, soluble solids concentration, titratable acidity, chlorophyll and betacyanin content) and structural changes of red‐fleshed dragon fruit (Hylocereus polyrhizus (Weber) Britton & Rose) was carried out from 5 to 35 days after pollination (DAP) in order to explain their growth, development, maturations and ripening stages. RESULTS: Fruit growth of red‐fleshed dragon fruit followed a sigmoid growth pattern. Significant changes in colour were obtained in both peel and pulp as DAP progressed, which were indicated by reductions of L*, C* and h° values as both changed from green to red–violet colour at ripening. Red–violet betacyanin was manifested earlier in pulp at 25 DAP, followed by peel 4–5 days later, and finally both peel and pulp turned full red–violet by 30 DAP. There was a significant increase in soluble solids concentration and titratable acidity with the continuous increase in betacyanin content as DAP progressed. CONCLUSION: The physico‐chemical and betacyanin accumulation of red‐fleshed dragon fruit changed as it developed, matured and ripened which coincided with structural changes. Copyright © 2010 Society of Chemical Industry     

Clean Manufacture of 2,4,6-Trinitrotoluene (TNT) via Improved Regioselectivity in the Nitration of Toluene

The U.S. Department of Defense requires an environmentally benign synthesis route to manufacture military grade trinitrotoluene (TNT), which eliminates the production of red water arising from the sulfiting process for removing unsymmetrical trinitrotoluene isomers. We have found that by using a novel nitrating system, N₂O₅ in dichloromethane, the proportion of metasubstituted nitrotoluenes can be suppressed, and improvements have also been made to the di- and trinitration steps. As a result, TNT with a set point near that of the Mil. Spec. can be made by our process, without the need for sulfite washing; after recrystallization it exceeds the specification.     

DEVELOPMENT OF HIGH-PERFORMANCE HEAVY OIL HYDROCRACK1NG CATALYSTS: CHARACTERIZATION OF ATMOSPHERIC RESIDUE FEED

ABSTRACT

The characterization results of the atmospheric residue obtained from Saudi Arabian Light crude oil show the complex nature and composition of this material. The distillation results showed that about 50 percent of Arab Light crude is the atmospheric residue. The elemental analysis of the residue showed that high amount of carbon, sulfur and nitrogen is present along with heavy metals such as nickel and vanadium. The determination of hydrocarbon types by HPLC exhibited that 12% polars and 27% aromatics are present along with 6% asphaltenes. Nuclear magnetic resonance study conducted on the residue and its fraction provides a detailed composition in terms of aliphatic and aromatic nature of the residue and its fractions. The results showed that the residue contains 21% aromatic and 79% aliphatic carbon. The aliphatic carbon is present in saturates and as side chains of aromatic and polar molecules whereas the aromatic carbons are those in the ring structure. Asphaltenes separated from the residue were characterized for their different properties to understand its complexity. The use of electron spin resonance spectroscopy provides determination of the free radicals present in the residue. Asphaltenes were analyzed using the state-of-the-art high temperature high pressure electron spin resonance (ESR) technique in the temperature range 20 to 625 °C and at 30 and 50 bar hydrogen pressure. The ESR determination at 30 bar shows that me pressure was not enough to prevent the boiling of the asphaltene and thus a decrease in the spin concentration was observed beyond 350 °C temperature. The data at 50 bar pressure showed the adequacy of this pressure for ESR measurement. The PMRTA analysis of asphaltene showed a decrease in residual hydrogen with increasing temperature.     

Identification of Critical Flood Prone Areas in Data-Scarce and Ungauged Regions: A Comparison of Three Data Mining Models

Flood is one of the most devastating natural disasters with socio-economic consequences. Thus, preparation of the flood prone areas (FPA) map is essential for flood disaster management, and for planning further development activities. The main goal of this study is to investigate new applications of the evidential belief function (EBF), random forest (RF), and boosted regression trees (BRT) models for identifying the FPA in the Galikesh region, Iran. This research was conducted in three main stages such as data preparation, flood susceptibility mapping using EBF, RF, and BRT models and validation of constructed models using receiver operating characteristic (ROC) curve. At first, a flood inventory map was prepared using documentary sources of Iranian Water Resources Department (IWRD) and extensive field surveys. In total, 63 flood locations were identified in the study area. Of these, 47 (75%) floods were randomly selected as training/model building and the remaining 16 (25%) cases were used for the validation purposes. The flood conditioning factors considered in the study area are altitude, slope aspect, slope angle, topographic wetness index, plan curvature, geology, landuse, distance from rivers, drainage density, and soil texture. Subsequently, the FPA maps were prepared using EBF, RF, and BRT models in a GIS environment. Finally, the results were validated using ROC curve and area under the curve (AUC) analysis. From the analysis, it was seen that the EBF (AUC?=?78.67%) and BRT models (AUC?=?78.22%) performed better than RF model (AUC?=?73.33%). Therefore, the resultant FPA maps can be useful for researchers and planner in flood mitigation strategies.     

Unconfined laminar nanofluid flow and heat transfer around a square cylinder

The momentum and forced convection heat transfer for a laminar and steady free stream flow of nanofluids past an isolated square cylinder have been studied numerically. Different nanofluids consisting of Al₂O₃ and CuO with base fluids of water and a 60:40 (by mass) ethylene glycol and water mixture were selected to evaluate their superiority over conventional fluids. Recent correlations for the thermal conductivity and viscosity of nanofluids, which are functions of particle volumetric concentration as well as temperature, have been employed in this paper. The simulations have been conducted for Pe = 25, 50, 100 and 200, with nanoparticle diameters of 30 and 100 nm and particle volumetric concentrations ranging from 0% to 4%. The results of heat transfer characteristics of nanofluid flow over a square cylinder showed marked improvement comparing with the base fluids. This improvement is more evident in flows with higher Peclet numbers and higher particle volume concentration, while the particle diameter imposes an adverse effect on the heat transfer characteristics. In addition, it was shown that for any given particle diameter there is an optimum value of particle concentration that results in the highest heat transfer coefficient.