A note on water quality associated with slaughter premises in Bangladesh

Water quality used for washing carcasses and abattoir premises was assessed at two sites in southeast Bangladesh. In addition, the effect of discharging untreated washings from slaughter premises on water purity in the receiving waterways was assessed from pH, dissolved oxygen and electrical conductivity measurements. Premises effluents did not have a significant effect on the physico-chemical properties of the water in the receiving canals, as determined from the difference between the 4 m upstream and 4 m downstream samples, relative to the entry point of the effluent. When a water shortage occurred at one of the premises, water was sourced for washing the carcasses and premises from a canal that was also used for conveying municipal effluent. The discharge water from the premises at this time had a pH, dissolved oxygen content and conductivity of 7.93, 1.84 mg/L and 6.06 mS/cm respectively, and this would be a threat to survival of freshwater animal life.     

Performance analysis of hybrid/single nanofluids on augmentation of heat transport in lid-driven undulated cavity

This numerical study reveals the heat transfer performance of hybrid/single nanofluids inside a lid-driven sinusoidal trapezoidal-shaped enclosure. The right and left inclined surfaces of the trapezium have been considered as insulated, whereas the bottom sinusoidal wavy and the flat top surfaces of the enclosure as hot and cold, respectively. The governing partial differential equations of fluid's velocity and temperature have been resolved by applying the finite element method. The implications of Prandtl number (4.2-6.2), Richardson number (0.1-10.0), undulation number (0-3), nanoparticles volume fraction (0%-3%), and nanofluid/base fluid (water, water–copper (Cu), water–Cu–carbon nanotube, water–Cu–copper oxide (CuO), water–Cu–TiO₂, and water–Cu–Al₂O₃) on the velocity and temperature profiles have been studied. Simulated findings have been represented by means of streamlines, isothermal lines, and average Nusselt number of above-mentioned hybrid nanofluids for varying the governing parameters. The comparison of heat transfer rates using hybrid nanofluids and pure water has been also shown. The heat transfer rate is increased about 15% for varying Richardson number from 0.1 to 10.0. Blending of two nanoparticles suspension in base fluid has a higher heat transfer rate—approximately 5% than a mononanoparticle. Moreover, a higher average Nusselt number is obtained by 14.7% using the wavy surface than the flat surface of the enclosure. Thus, this study showed that applying hybrid nanofluid may be beneficial to obtain expected thermal performance.     

Robot trajectory optimisation with dynamic constraints

Objects located within a robot arm workspace fragment this space, since a path obstructed by an object is non-viable. Point-to-point motion of a robot arm in such a fragmented workspace has to be carefully planned in order to avoid collision. The problem of planning the trajectory of the robot arm can be represented as a constrained optimisation problem from which an optimal time can be deduced. The solution of the optimisation problem for an optimal continuous trajectory is complex and costly. However, a motion strategy, whereby the robot arm path is formed of single linear segments, renders the optimisation problem solvable and produces a sub-optimal but practical trajectory. This paper describes a motion strategy that is based on the concept of defining via intermediate and control points which the robot arm has to pass by along its path, and takes into consideration the torque limitation of the different axis drives. Joint motion planning is based on a function of time approximated by a sequence of polynomials with boundary conditions that would result in continuous motion at the via points. Motion between each two points is divided into two transition zones and a constant speed zone in between. A result is obtained by selecting polynomial coefficients that would minimise, subject to the constraints of the robot dynamics, the time required to accelerate and decelerate the joint to the appropriate speeds at the boundary of these zones. The joint is allowed to move at the maximum speed for the remainder of the time.     

MODELING THE HYDROCRACKING PROCESS USING ARTIFICIAL NEURAL NETWORKS

Feed-forward neural networks that models the hydrocracking process of Arabian light vacuum gas oil are presented. The input-output data to the neural networks was obtained from actual local refineries. Several network architectures were tried and the networks that best simulate the hydrocracking process were retained. The networks are able to predict yields and properties of products of the hydrocracking unit (e.g. iC₄, nC₄, light and heavy naphtha, light and heavy ATK, Diesel, etc.). The predictions of yields and properties of various desired and undesired products at different conditions are required by refineries for process optimization, control, design, catalyst selection, and planning. The predictions of the prepared neural networks have been cross validated against data not originally used in the training process. The networks compared well against this new set of data with an average percent error always less than 8.71 for the different products of the hydrocracking unit.     

New correlation for predicting the viscosity of heavy petroleum fractions

A new, simple and reliable empirical correlation for predicting the viscosities of heavy petroleum fractions is proposed, applicable to fractions with mid-boiling points from 80 to 550°C over a wide range of viscosities (0.4 to 260 mm² s⁻¹) and measurement temperatures (40 to 200°C). This correlation showed better accuracy in the prediction of heavy petroleum fraction viscosities than that of the most accurate and much more complicated predictive methods in the literature, since it gave an overall average absolute deviation of 6.5% when tested on 296 data for medium and heavy petroleum fractions.     

Occurrence of infected amoebae in cooling towers compared with natural aquatic environments: implications for emerging pathogens

Many species of bacteria pathogenic to humans, such as Legionella, are thought to have evolved in association with amoebal hosts. Several novel unculturable bacteria related to Legionella have also been found in amoebae, a few of which have been thought to be causes of nosocomial infections in humans. Because amoebae can be found in cooling towers, we wanted to know whether cooling tower environments might enhance the association between amoebae and bacterial pathogens of amoebae in order to identify potential "hot spots" for emerging human pathogens. To compare occurrence of infected amoebae in natural environments with those in cooling towers, 40 natural aquatic environments and 40 cooling tower samples were examined. Logistic regression analysis determined variables that were significant predictors of the occurrence of infected amoebae, which were found in 22 of 40 cooling tower samples but in only 3 of the 40 natural samples. An odds ratio showed that it is over 16 times more likely to encounter infected amoebae in cooling towers than in natural environments. Environmental data from cooling towers and natural habitats combined revealed dissolved organic carbon (DOC) and pH were predictors of the occurrence of the pathogens, however, when cooling tower data alone were analyzed, no variables accounted for the occurrence. Several bacteria have novel rRNA sequences, and most strains were not culturable outside of amoebae. Such pathogens of amoebae may spread to the environment via aerosols from cooling towers. Studies of emerging infectious diseases should strongly consider cooling towers as a source of amoeba-associated pathogens.     

Breakthrough studies with mono- and binary-metal ion systems comprising of Fe(II) and As(III) using community prepared wooden charcoal packed columns

Groundwater of Assam (India) contains excessive amounts of As(III) and Fe(II). The rural and semi-urban population of Assam uses indigenous household iron filters fabricated using community prepared wooden charcoal (CPWC) to reduce Fe(II) concentration, however no efforts are made to reduce As(III) concentrations before use. The present work is directed toward assessing the potential of CPWC for metal removal from mono- and binary-metal ion systems comprising of Fe(II) and As(III) through continuous mode column studies. A decrease in breakthrough throughput volumes (V_B) from mono- and binary-metal ion systems is observed with increase in flow rates and decrease in bed depths. The order of breakthrough of metal ions observed as As(III) followed by Fe(II) from binary-metal ion system and hence the V_B for As(III) is termed as critical V_B as Fe(II) is yet to breakthrough through the beds. An early breakthrough for Fe(II) and As(III) from binary-metal ion system compared to respective mono-metal ion systems is observed for all the cases of flow rates and bed depths. It indicates impact on the uptake of a selected metal ion [either Fe(II) or As(III)] by the presence of the other metal ion [either As(III) or Fe(II)] present in the binary-metal ion system. The minimum and maximum errors involved between the predicted and experimental BDST curves for As(III) uptake till critical V_B from the binary-metal ion system varied between 1.0% and 24.8%.