24 resultados para Hidroponic system with treated sewage


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The use of sustainability indicators for evaluating sanitation systems is applied to the Erdos Eco- Town Project (EETP) in China for illustration. The EETP is the largest urban settlement in the world employing ecological sanitation, which incorporates separation of waste streams, dry toilets, and resource recovery. The EETP’s dry sanitation system is compared against the Dongsheng District’s conventional sewer and centralised STP. The two systems are compared based on technological, environmental, economic, and societal indicators. Overall, the two systems perform reasonably well from a technological perspective. The conventional system performs significantly better than the dry system with regards to land and energy requirements, and global warming potential; it also performs better based on freshwater aquatic and terrestrial ecotoxicity potentials, but by a smaller margin. The dry system has superior environmental performance based on water consumption, eutrophication potential, and nutrient and organic matter recovery. The dry system is a more costly system as it requires greater infrastructure and higher operational costs, and does not benefit from economies of scale. The waterborne system performs better based on the societal indicators largely because it is a well-established system.

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A method is presented for the digital simulation of multiple degrees-of-freedom lumped parameter vibrating systems with arbitrary constitutive elements in an inertial frame of reference. The geometry of the system is treated independently of the constitutive elements and as a result nonlinear (time domain) or linearised (frequency domain) calculations may be performed using a single input description. The method is used to simulate a 3-axle rigid heavy commercial vehicle for harsh vibrating conditions. Some of the assumptions to which the calculations are sensitive are examined. Agreement between the response of a 3-dimensional whole vehicle model and measurements on the test vehicle is satisfactory.

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In multi-carrier systems, small carrier frequency offsets result in significant degradation of performance and this offset should be compensated before demodulation can be performed. In this paper, we consider a generic multi-carrier system with pulse shaping and estimate the frequency offset by exploiting the cyclostationarity of the received signal. By transforming the time domain signal to the cyclic correlation domain we are able to estimate the frequency offset without the aid of pilot symbols or the cyclic prefix. The Bayesian framework is used to obtain the estimate and we show how we can simplify the estimation process. © 1999 IEEE.

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The use of anti-roll bars to provide additional roll stiffness and therefore to reduce the trade-off between ride and rollover performance has previously been studied. However, little work has been carried out to investigate the benefits of a switchable roll stiffness. Such a semi-active anti-roll system has the ability to have a low roll stiffness during straight-ahead driving for improved ride performance and high roll stiffness during cornering for improved roll performance. Modelling of such a system is conducted and the model is validated against a semi-active anti-roll system fitted to an experimental vehicle. Experimental and theoretical investigations are used to investigate the performance of such a system with several different strategies employed to switch to the high-stiffness state. The use of an air suspension on the vehicle to roll into corners is also investigated, as is the possibility of exploiting the road layout by allowing the vehicle to be in a low-roll-stiffness configuration during a corner, and then to switch to the high-roll-stiffness configuration midcorner, hence 'locking in' a roll angle. The best rollover performance improvement that was achieved was 12.5 per cent. © IMechE 2008.

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We study graphene growth on hafnia (HfO2) nanoparticles by chemical vapour deposition using optical microscopy, high resolution transmission electron microscopy and Raman spectroscopy. We find that monoclinic HfO2 nanoparticles neither reduce to a metal nor form a carbide while nucleating nanometer domain-sized few layer graphene. Hence we regard this as an interesting non-metallic catalyst model system with the potential to explore graphene growth directly on a (high-k) dielectric. HfO2 nanoparticles coated with few layer graphene by atmospheric pressure CVD with methane and hydrogen at 950 °C. (© 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) Graphene growth on hafnia (HfO2) nanoparticles by chemical vapour deposition (CVD) is studied. It is found that monoclinic HfO2 nanoparticles neither reduce to a metal nor form a carbide while nucleating nanometer domain-sized few layer graphene. Hence the authors of this Letter regard this as an interesting non-metallic catalyst model system with the potential to explore graphene growth directly on a (high-k) dielectric. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Gaussian processes are gaining increasing popularity among the control community, in particular for the modelling of discrete time state space systems. However, it has not been clear how to incorporate model information, in the form of known state relationships, when using a Gaussian process as a predictive model. An obvious example of known prior information is position and velocity related states. Incorporation of such information would be beneficial both computationally and for faster dynamics learning. This paper introduces a method of achieving this, yielding faster dynamics learning and a reduction in computational effort from O(Dn2) to O((D - F)n2) in the prediction stage for a system with D states, F known state relationships and n observations. The effectiveness of the method is demonstrated through its inclusion in the PILCO learning algorithm with application to the swing-up and balance of a torque-limited pendulum and the balancing of a robotic unicycle in simulation. © 2012 IEEE.

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A free space optical wireless communication system with 3 degree angular coverage and 1.25 GHz modulation bandwidth is reported, in which relatively narrow laser beam of a simultaneous high power, high modulation speed and ultra high modulation efficiency directly modulated two-electrode tapered laser diode is steered using a nematic phase-only Liquid-Crystal On Silicon Spatial Light Modulator (LCOS SLM) by displaying reconfigurable 256 phase level gratings. © 1983-2012 IEEE.

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Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

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Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics. © 2014 by the authors; licensee MDPI, Basel, Switzerland.