Characteristics of tar,NOx precursors and their absorption performance with different scrubbing solvents during the pyrolysis of sewage sludge

Recently thermal utilizations of sewage sludge, especially pyrolysis and gasification, are regarded as promising technologies due to efficient utilization of fuel gas. In this study, characteristics of tar and NOx precursors were investigated during the pyrolysis of sewage sludge. Moreover, absorption performance for tar and NOx precursors were also studied by using four kinds of scrubbing mediums: cooking oil, diesel oil, BDF and water. The results showed that nitrogenous light PAHs were the major components of nitrogenous tar produced from the pyrolysis of sewage sludge. As for gravimetric tar and major nitrogenous tar compounds removal, cooking oil was the most suitable absorbent. With respect to NOx precursors, it was concluded that HCN, sharing of about 39.5% of total nitrogen of the sewage sludge, was the main NOx precursor gas whereas NH₃ content could be neglected. Absorption capacity of hydrophobic scrubbing mediums against NOx precursor gases could be arranged as followed: diesel oil > cooking oil > BDF.     

Epitaxial p-type SiC as a self-driven photocathode for water splitting

Solar-to-hydrogen conversion efficiencies of water-splitting photochathodes using epitaxially grown p-type 4H-, 6H- and 3C-SiC were estimated in a two-electrode system without applying any external bias. By using electrode materials with small oxygen overpotentials as counter electrodes, the photocurrent became comparable to that observed in a three-electrode system with a suitable bias. Estimated efficiencies seem to depend on the bandgap of the SiC polytypes. For the 3C-SiC, the obtained efficiency was 0.38%, which is so far the highest value reported for SiC. We confirmed that the hydrogen volumes estimated from the photocurrent were almost the same as actual volumes observed by gas chromatography.     

Robot-vision architecture for real-time 6-DOF object localization

This paper presents a new robot-vision system architecture for real-time moving object localization. The 6-DOF (3 translation and 3 rotation) motion of the objects is detected and tracked accurately in clutter using a model-based approach without information of the objects’ initial positions. An object identification task and an object tracking task are combined under this architecture. The computational time-lag between the two tasks is absorbed by a large amount of frame memory. The tasks are implemented as independent software modules using stereo-vision-based methods which can deal with objects of various shapes with edges, including planar to smooth-curved objects, in cluttered environments. This architecture also leads to failure-recoverable object tracking, because the tracking processes can be automatically recovered, even if the moving objects are lost while tracking. Experimental results obtained with prototype systems demonstrate the effectiveness of the proposed architecture.     

2D artificial life system using network-type assembly-like language: influence of change in environment with costs of instructions

To unlock the full potential of evolution in digital media, a Tierra-like system using network-type assembly-like language has been constructed. In the system, like Avida, digital creatures, self-replicating programs, live in a discrete 2D torus space and an interaction between creatures is restricted locally. Bearing a genetic network in mind, network structure is introduced. In the previous works, it is shown that the possibility that the network-type model has more potential of evolution than a linear-type model like Avida in a simple environment. In this paper, to study the potential of evolution more precisely, we model the effects of environment other than creatures. As one of the simplest models of such environment, the cost of execution, i.e. executing time, is introduced. The difficult environment to live in costs high to execute instructions, the easy environment does low. In computer experiments, we have investigated the influence of change in environment by analyzing the process of evolution and diversity of the system. Experimental results show that the network-type system keeps more stable diversity than the linear-type system does, even when the environment changes drastically. This indicates the possibility that the network-type system has more potential of evolution than the linear-type system has. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Digital RAC with a disturbance observer for underwater vehicle-manipulator systems

Most control methods of underwater vehiclemanipulator systems (UVMS) are based on the computed torque method that is used for underwater robotic vehicles. We have proposed a resolved acceleration control (RAC) method for UVMS. In this article, we propose a disturbance compensation control method for both vehicle and manipulator based on the RAC method. Experimental results using an underwater robot with a vertical planar 2-link manipulator show that the proposed control method has good control performance.