Impacts of CO2 emission constraints on technology selection and energy resources for power generation in Bangladesh

This paper examines the impacts of CO₂ emission reduction target and carbon tax on future technologies selection and energy use in Bangladesh power sector during 2005–2035. The analyses are based on a long-term energy system model of Bangladesh using the MARKAL framework. The analysis shows that Bangladesh will not be able to meet the future energy demand without importing energy. However, alternative policies on CO₂ emission constraints reduce the burden of imported fuel, improve energy security and reduce environmental impacts. The results show that the introduction of the CO₂ emission reduction targets and carbon taxes directly affect the shift of technologies from high carbon content fossil-based to low carbon content fossil-based and clean renewable energy-based technologies compared to the base scenario. With the cumulative CO₂ emission reduction target of 10–20% and carbon tax of 2500 Taka/ton, the cumulative net energy imports during 2005–2035 would be reduced in the range of 39–65% and 37%, respectively, compared to the base scenario emission level. The total primary energy requirement would be reduced in the range of 4.5–22.3% in the CO₂ emission reduction targets and carbon tax 2500 Taka/ton scenarios and the primary energy supply system would be diversified compared to the base scenario.     

Network coding for unicast in a WiFi hotspot: Promises,challenges, and testbed implementation

In offices and residential buildings, WiFi networks have become a primary means for providing Internet access to wireless devices whose dominant traffic pattern is unicast. In the meantime, the emergence of network coding has brought about great promises for multicast in communication networks where intermediate nodes are allowed to process independent incoming information flows. Little is known about network coding for unicast, however. The objective of this paper is thus to depart from multicast scenarios and shed light on several possible unicast scenarios to which network coding may be applied in a WiFi hotspot in order to obtain communication benefits such as throughput gain, fairness, and reduced protocol complexity. We identify five representative scenarios in which network coding may be used to benefit unicasting in a WiFi hotspot. Several open research issues and practical challenges related to each scenario are discussed individually. To illustrate the benefits of network coding for unicast in a WiFi hotspot, we propose and implement iCORE: The interface COoperation Repeater-aided network coding Engine. iCORE is a practical system in which multi-channel multi-radio repeaters are used to relay unicast traffic for those terminals sitting far away from an access point and suffering from weak signals at a WiFi hotspot. It is based on our last scenario which illustrates the synergy among network coding, opportunistic routing, and interface management. Utilizing idle wireless interfaces and listening to traffic opportunistically, iCORE allows packets to move across the interfaces and to be coded across flows whenever it sees more transmission opportunities. We evaluate iCORE on a four-node chain-like topology testbed implemented using IEEE 802.11b/g radios and compare it to MORE – the state-of-art intra-flow network coding implementation based on opportunistic routing. Our experimental results reveal promising gains in terms of throughput over MORE.     

High vacuum tribology of polycrystalline diamond coatings

Polycrystalline diamond coatings have been grown on unpolished side of Si(100) wafers by hot filament chemical vapour deposition process. The morphology of the grown coatings has been varied from cauliflower morphology to faceted morphology by manipulation of the growth temperature from 700°C to 900°C and methane gas concentration from 3% to 1·5%. It is found that the coefficient of friction of the coatings under high vacuum of 133·32×10^?7 Pa (10^?7 torr) with nanocrystalline grains can be manipulated to 0·35 to enhance tribological behaviour of bare Si substrates.     

Approximate methods in Bayesian point process spatial models

A range of point process models which are commonly used in spatial epidemiology applications for the increased incidence of disease are compared. The models considered vary from approximate methods to an exact method. The approximate methods include the Poisson process model and methods that are based on discretization of the study window. The exact method includes a marked point process model, i.e., the conditional logistic model. Apart from analyzing a real dataset (Lancashire larynx cancer data), a small simulation study is also carried out to examine the ability of these methods to recover known parameter values. The main results are as follows. In estimating the distance effect of larynx cancer incidences from the incinerator, the conditional logistic model and the binomial model for the discretized window perform relatively well. In explaining the spatial heterogeneity, the Poisson model (or the log Gaussian Cox process model) for the discretized window produces the best estimate.     

Fabrication of High Performance PM Nanocrystalline Bulk AA2124

AA2124 nanopowders <100 nm in particle size and 20 nm internal structure produced by high energy ball milling of gas-atomized micronpowders ~45 μm in particle size and 700 nm internal structure were processed in to bulk rods. The micro- and nanopowders were hot compacted using uniaxial pressing for preliminary densification at 0.7T _m of the alloy. Selected intact hot compacts (HCs) were promoted for warm severe plastic deformation via equal channel angular pressing (ECAP) at the minimum possible deforming temperature for final densification. Effect of the fabrication method of the consolidated powders was investigated. A combined processing via HC/ECAP produced bulk nanostructured rods 2.5 μm and 50-60 nm in grain size for the micro- and nanopowder consolidates, respectively. The powder properties controlled the degree of densification and mechanical behavior during the hot compaction stage, which influenced strongly the deformation behavior during subsequent ECAP. At the end of HC/ECAP one pass, the HC stage was responsible for about 83 and 95% of the total grain coarsening encountered for the micro- and nanopowder HCs, respectively. Throughout the various consolidation stages employed, the ball-milled (BM) nanopowder consolidates exhibited 2/3 the grain growth and displayed almost twice the hardness and compressive strength values of the gas-atomized micronpowder ones. Influence of BM and HC on the Al₂O₃ layer formed around the individual powder particles was also investigated.     

A committee machine with intelligent systems for estimation of total organic carbon content from petrophysical data: An example from Kangan and Dalan reservoirs in South Pars Gas Field,Iran

Total organic carbon (TOC) content present in reservoir rocks is one of the important parameters, which could be used for evaluation of residual production potential and geochemical characterization of hydrocarbon-bearing units. In general, organic-rich rocks are characterized by higher porosity, higher sonic transit time, lower density, higher γ-ray, and higher resistivity than other rocks. Current study suggests an improved and optimal model for TOC estimation by integration of intelligent systems and the concept of committee machine with an example from Kangan and Dalan Formations, in South Pars Gas Field, Iran. This committee machine with intelligent systems (CMIS) combines the results of TOC predicted from intelligent systems including fuzzy logic (FL), neuro-fuzzy (NF), and neural network (NN), each of them has a weight factor showing its contribution in overall prediction. The optimal combination of weights is derived by a genetic algorithm (GA). This method is illustrated using a case study. One hundred twenty-four data points including petrophysical data and measured TOC from three wells of South Pars Gas Field were divided into 87 training sets to build the CMIS model and 37 testing sets to evaluate the reliability of the developed model. The results show that the CMIS performs better than any one of the individual intelligent systems acting alone for predicting TOC.     

Sustainability of Groundwater Resources in the North-Eastern Region of Bangladesh

Water is essential for economic, social, and environmental development. Global water resources are vulnerable due to increasing demand related to population growth, pollution potential, and climate change. Competition for water between different sectors is increasing. To meet the increasing demand, the use of groundwater is increasing worldwide. In this paper, the water-table dynamics of the north-eastern region of Bangladesh were studied using the MEKESENS software. This study reveals that the depth to water-table (WT) of almost all the wells is declining slowly. In many cases, the depth will approximately double by the year 2040, and almost all will double by 2060, if the present trend continues. If the decline of the water-table is allowed to continue in the long run, the result could be a serious threat to the ecology and to the sustainability of food production, which is vital for the nation’s food security. Therefore, necessary measures should be taken to sustain water resources and thereby agricultural production. Demand-side management of water and the development of alternative surface water sources seem to be viable strategies for the area. These strategies could be employed to reduce pressure on groundwater and thus maintain the sustainability of the resource.     

Shear Strength of Fiber-Reinforced Sands

Soil reinforcement using discrete randomly distributed fibers has been widely investigated over the last 30 years. Several models were suggested to estimate the improvement brought by fibers to the shear strength of soils. The objectives of this paper are to (1) supplement the data available in the literature on the behavior of fiber-reinforced sands; (2) study the effect of several parameters which are known to affect the shear strength of fiber-reinforced sands; and (3) investigate the effectiveness of current models in predicting the improvement in shear strength of fiber-reinforced sand. An extensive direct shear testing program was implemented using coarse and fine sands tested with three types of fibers. Results indicate the existence of a fiber-grain scale effect which is not catered for in current prediction models. A comparison between measured and predicted shear strengths indicates that the energy dissipation model is effective in predicting the shear strength of fiber-reinforced specimens in reference to the tests conducted in this study. On the other hand, the effectiveness of the predictions of the discrete model is affected by the parameters of the model, which may depend on the test setup and the procedure used for mixing the fibers.