The checklist of Admiralty Bay polychaetes elaborated on the basis of historical and current data includes 120 benthic and 5 pelagic species. Admiralty Bay is the most intensively sampled area in the Antarctic, taking into account polychaete fauna, and the checklist of Polychaeta may be therefore considered as a rather comprehensive one. In the sublittoral soft bottom three dominant species: Leitoscoloplos kerguelensis, Tauberia gracilis and Ophelina syringopyge constitute almost 50% of all collected polychaetes (20%, 16% and 13% respectively). Rhodine intermedia, Tharyx cincinnatus, Aricidea (Acesta) strelzovi, Apistobranchus sp., Cirrophorus brevicirratus, Microspio moorei, Maldane sarsi antarctica, Aglaophamus ornatus and Asychis amphiglypta make up a group of species of considerable abundance (a further 30% of author's collection). The average abundance of polychaetes of the sublittoral soft bottom was estimated at 120 individuals per 0.1 m2, with the observed maximum 390 individuals per 0.1 m2.
In this paper we describe our own construction of a tuneable light source based on a set of light emitting diodes covering the visible spectrum using a homogenizing rod instead commonly used low energy-efficient integrating spheres. The expected prime application of the source is a medical endoscopic system, however it is possible to use it also for other purposes requiring both multispectral operation and a tuneable white light source. We describe the construction of the source and include precise characterization of the output white light – distribution of CCT, Duv, Δu′ v ′ and colour rendering indexes (Ra, R9, Rf , Rg) of light in several planes located at various distances. The obtained results prove that our source is characterized by very good colour rendition according to the Ra and Rf method for various correlated colour temperatures (2700–6500) K. As an example of application images of the Macbeth colour chart registered with an RGB camera included in the laboratory measurement stand are presented. The obtained results prove that, after whole system calibration, this source can be used in many applications, where evaluation of objects requires precise analysis of their colour and multispectral procedures.
Automation of earth moving machineries is a widely studied problem. This paper focusses on one of the main challenges in automation of the earth moving industry, estimation of loading torque acting on the machinery. Loading torque acting on the excavation machinery is a very significant aspect in terms of both machine and operator safety. In this study, a disturbance observer-assisted control system for the estimation of loading torque acting on a robotic backhoe during excavation process is presented. The proposed observer does not use any acceleration measurements, rather, is proposed as a function of joint velocity. Numerical simulations are performed to demonstrate the effectiveness of the proposed control scheme in tracking the reaction torques for a given dig cycle. Co-simulation experiments demonstrate robust performance and accurate tracking of the proposed control in both disturbance torque and position tracking. Further, the performance and sensitivity of the proposed control are also analyzed through the help of performance error quantifiers, the root-mean-square (RMS) values of the position and disturbance tracking errors.
This study was carried out on the background of Sutong Bridge project based on fracture mechanics, aiming at analyzing the growth mechanism of fatigue cracks of a bridge under the load of vehicles. Stress intensity factor (SIF) can be calculated by various methods. Three steel plates with different kinds of cracks were taken as the samples in this study. With the combination of finite element analysis software ABAQUS and the J integral method, SIF values of the samples were calculated. After that, the extended finite element method in the simulation of fatigue crack growth was introduced, and the simulation of crack growth paths under different external loads was analyzed. At last, we took a partial model from the Sutong Bridge and supposed its two dangerous parts already had fine cracks; then simulative vehicle load was added onto the U-rib to predict crack growth paths using the extended finite element method.