PLA is one of the most promising bio-compostable and bio-degradable thermoplastic polymers made from renewable sources. PLA is generally produced by ring opening polymerization (ROP) of lactide using the metallic/bimetallic catalyst (Sn, Zn, and Al) or other organic catalysts in a suitable solvent. In this work, reactive extrusion experiments using stannous octoate Sn(Oct)₂ and tri-phenyl phosphine (PPh)₃ were considered to perform ROP of lactide. Ultrasound energy source was used for activating and/or boosting the polymerization as an alternative energy (AE) source. Ludovic^® software, designed for simulation of the extrusion process, had to be modified in order to simulate the reactive extrusion of lactide and for the application of an AE source in an extruder. A mathematical model for the ROP of lactide reaction was developed to estimate the kinetics of the polymerization process. The isothermal curves generated through this model were then used by Ludovic software to simulate the “reactive” extrusion process of ROP of lactide. Results from the experiments and simulations were compared to validate the simulation methodology. It was observed that the application of an AE source boosts the polymerization of lactide monomers. However, it was also observed that the predicted residence time was shorter than the experimental one. There is potentially a case for reducing the residence time distribution (RTD) in Ludovic^® due to the ‘liquid’ monomer flow in the extruder. Although this change in parameters resulted in validation of the simulation, it was concluded that further research is needed to validate this assumption.

Autonomous survey vessels can increase the efficiency and availability of wide-area river environment surveying as a tool for environment protection and conservation. A key challenge is the accurate localisation of the vessel, where bank-side vegetation or urban settlement preclude the conventional use of line-of-sight global navigation satellite systems (GNSS). In this paper, we evaluate unaided visual odometry, via an on-board stereo camera rig attached to the survey vessel, as a novel, low-cost localisation strategy. Feature-based and appearance-based visual odometry algorithms are implemented on a six degrees of freedom platform operating under guided motion, but stochastic variation in yaw, pitch and roll. Evaluation is based on a 663 m-long trajectory (>15,000 image frames) and statistical error analysis against ground truth position from a target tracking tachymeter integrating electronic distance and angular measurements. The position error of the feature-based technique (mean of ±0.067 m) is three times smaller than that of the appearance-based algorithm. From multi-variable statistical regression, we are able to attribute this error to the depth of tracked features from the camera in the scene and variations in platform yaw. Our findings inform effective strategies to enhance stereo visual localisation for the specific application of river monitoring.

Recent legislative approaches to improve the quality of rivers have resulted in the design and implementation of extensive and intensive monitoring programmes that are costly and time consuming. An important component of assessing the ecological status of a water body as required by the Water Framework Directive is characterising the hydromorphology. Recent advances in autonomous operation and the spatial coverage of monitoring systems enables more rapid 3D models of the river environment to be produced. This study presents a Structure from Motion (SfM) semi-autonomous based framework for the estimation of key reach hydromorphological measures such as water surface area, wetted water width, bank height, bank slope and bank-full width, using in-channel stereo-imagery. The framework relies on a stereo-camera that could be positioned on an autonomous boat. The proposed approach is demonstrated along three 40 m long reaches with differing hydromorphological characteristics. Results indicated that optimal stereo-camera settings need to be selected based on the river appearance. Results also indicated that the characteristics of the reach have an impact on the estimation of the hydromorphological measures; densely vegetated banks, presence of debris and sinuosity along the reach increased the overall error in hydromorphological measure estimation. The results obtained highlight a potential way forward towards the autonomous monitoring of freshwater ecosystems.