Influence of particle size, density and concentration on bend erosive wear in pneumatic conveyors

Particle concentration is a principal factor that affects erosion rate of solid surfaces under particle impact, such as pipe bends in pneumatic conveyors; it is well known that a reduction in the specific erosion rate occurs under high particle concentrations, a phenomenon referred to as the “shielding effect”. The cause of shielding is believed to be increased likelihood of inter-particulate collisions, the high collision probability between incoming and rebounding particles reducing the frequency and the severity of particle impacts on the target surface. In this study, the effects of particle concentration on erosion of a mild steel bend surface have been investigated in detail using three different particulate materials on an industrial scale pneumatic conveying test rig. The materials were studied so that two had the same particle density but very different particle size, whereas two had very similar particle size but very different particle density. Experimental results confirm the shielding effect due to high particle concentration and show that the particle density has a far more significant influence than the particle size, on the magnitude of the shielding effect. A new method of correcting for change in erosivity of the particles in repeated handling, to take this factor out of the data, has been established, and appears to be successful. Moreover, a novel empirical model of the shielding effects has been used, in term of erosion resistance which appears to decrease linearly when the particle concentration decreases. With the model it is possible to find the specific erosion rate when the particle concentration tends to zero, and conversely predict how the specific erosion rate changes at finite values of particle concentration; this is critical to enable component life to be predicted from erosion tester results, as the variation of the shielding effect with concentration is different in these two scenarios. In addition a previously unreported phenomenon has been recorded, of a particulate material whose erosivity has steadily increased during repeated impacts.

Experimental characterization and modelling of a servo-pneumatic system for a knee loading apparatus

The new knee test rig developed in University of Bologna used pneumatic cylinder as actuator system. Specific characterization and modelling about the pneumatic cylinder and the related devices are needed in better controlling the test rig. In this thesis, an experimental environment for the related device is set up with data acquisition system using Real-time Windows Target, Simulink, MatLab. Based on the experimental data, a fitted model for the pneumatic cylinder friction is found.

Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Design of an indirectly fired gas turbine integrated with an organic rankine cycle unit for combined heat and power production

In the last years, the European countries have paid increasing attention to renewable sources and greenhouse emissions. The Council of the European Union and the European Parliament have established ambitious targets for the next years. In this scenario, biomass plays a prominent role since its life cycle produces a zero net carbon dioxide emission. Additionally, biomass can ensure plant operation continuity thanks to its availability and storage ability. Several conventional systems running on biomass are available at the moment. Most of them are performant either in the large-scale or in the small power range. The absence of an efficient system on the small-middle scale inspired this thesis project. The object is an innovative plant based on a wet indirectly fired gas turbine (WIFGT) integrated with an organic Rankine cycle (ORC) unit for combined heat and power production. The WIFGT is a performant system in the small-middle power range; the ORC cycle is capable of giving value to low-temperature heat sources. Their integration is investigated in this thesis with the aim of carrying out a preliminary design of the components. The targeted plant output is around 200 kW in order not to need a wide cultivation area and to avoid biomass shipping. Existing in-house simulation tools are used: They are adapted to this purpose. Firstly the WIFGT + ORC model is built; Zero-dimensional models of heat exchangers, compressor, turbines, furnace, dryer and pump are used. Different fluids are selected but toluene and benzene turn out to be the most suitable. In the indirectly fired gas turbine a pressure ratio around 4 leads to the highest efficiency. From the thermodynamic analysis the system shows an electric efficiency of 38%, outdoing other conventional plants in the same power range. The combined plant is designed to recover thermal energy: Water is used as coolant in the condenser. It is heated from 60°C up to 90°C, ensuring the possibility of space heating. Mono-dimensional models are used to design the heat exchange equipment. Different types of heat exchangers are chosen depending on the working temperature. A finned-plate heat exchanger is selected for the WIFGT heat transfer equipment due to the high temperature, oxidizing and corrosive environment. A once-through boiler with finned tubes is chosen to vaporize the organic fluid in the ORC. A plate heat exchanger is chosen for the condenser and recuperator. A quasi-monodimensional model for single-stage axial turbine is implemented to design both the WIFGT and the ORC turbine. The system simulation after the components design shows an electric efficiency around 34% with a decrease by 10% compared to the zero-dimensional analysis. The work exhibits the system potentiality compared to the existing plants from both technical and economic point of view.

Development of an innovative non rule-based energy management strategy for a Hybrid Electric Vehicle, structured for predictive driving controls based on external information knowledge

Recently, the interest of the automotive market for hybrid vehicles has increased due to the more restrictive pollutants emissions legislation and to the necessity of decreasing the fossil fuel consumption, since such solution allows a consistent improvement of the vehicle global efficiency. The term hybridization regards the energy flow in the powertrain of a vehicle: a standard vehicle has, usually, only one energy source and one energy tank; instead, a hybrid vehicle has at least two energy sources. In most cases, the prime mover is an internal combustion engine (ICE) while the auxiliary energy source can be mechanical, electrical, pneumatic or hydraulic. It is expected from the control unit of a hybrid vehicle the use of the ICE in high efficiency working zones and to shut it down when it is more convenient, while using the EMG at partial loads and as a fast torque response during transients. However, the battery state of charge may represent a limitation for such a strategy. That’s the reason why, in most cases, energy management strategies are based on the State Of Charge, or SOC, control. Several studies have been conducted on this topic and many different approaches have been illustrated. The purpose of this dissertation is to develop an online (usable on-board) control strategy in which the operating modes are defined using an instantaneous optimization method that minimizes the equivalent fuel consumption of a hybrid electric vehicle. The equivalent fuel consumption is calculated by taking into account the total energy used by the hybrid powertrain during the propulsion phases. The first section presents the hybrid vehicles characteristics. The second chapter describes the global model, with a particular focus on the energy management strategies usable for the supervisory control of such a powertrain. The third chapter shows the performance of the implemented controller on a NEDC cycle compared with the one obtained with the original control strategy.

Computer vision in aseptic pharmaceutical manufacturing: a deep learning-based approach to vial inspection and pack formation during a lyophilizer loading cycle

Vision systems are powerful tools playing an increasingly important role in modern industry, to detect errors and maintain product standards. With the enlarged availability of affordable industrial cameras, computer vision algorithms have been increasingly applied in industrial manufacturing processes monitoring. Until a few years ago, industrial computer vision applications relied only on ad-hoc algorithms designed for the specific object and acquisition setup being monitored, with a strong focus on co-designing the acquisition and processing pipeline. Deep learning has overcome these limits providing greater flexibility and faster re-configuration. In this work, the process to be inspected consists in vials’ pack formation entering a freeze-dryer, which is a common scenario in pharmaceutical active ingredient packaging lines. To ensure that the machine produces proper packs, a vision system is installed at the entrance of the freeze-dryer to detect eventual anomalies with execution times compatible with the production specifications. Other constraints come from sterility and safety standards required in pharmaceutical manufacturing. This work presents an overview about the production line, with particular focus on the vision system designed, and about all trials conducted to obtain the final performance. Transfer learning, alleviating the requirement for a large number of training data, combined with data augmentation methods, consisting in the generation of synthetic images, were used to effectively increase the performances while reducing the cost of data acquisition and annotation. The proposed vision algorithm is composed by two main subtasks, designed respectively to vials counting and discrepancy detection. The first one was trained on more than 23k vials (about 300 images) and tested on 5k more (about 75 images), whereas 60 training images and 52 testing images were used for the second one.

Utilizzo di sistemi bioreattori per l’ingegnerizzazione di sostituti del tessuto cartilagineo

La mancanza di vascolarizzazione dei costrutti tissutali cartilaginei ingegnerizzati rende opportuno e necessario l’impiego di bioreattori che permettano di indurre un flusso nel terreno di coltura favorendo il trasporto di massa e quindi lo sviluppo del metabolismo e del differenziamento cellulare. I bioreattori intendono replicare gli stimoli fisici fisiologici, nello specifico condrogenici, e a regolare la formazione della matrice extracellulare tramite meccanotrasduzione, il fenomeno biologico che traduce le sollecitazioni meccaniche applicate alle cellule in segnali biochimici che suscitano risposte adattative. In questo elaborato sono riportati i risultati di un recente lavoro - pubblicato da J. Hallas, A. J. Janvier, K. F. Hoettges & J. R. Henstock e intitolato “Pneumatic piston hydrostatic bioreactor for cartilage tissue engineering – che propone la realizzazione di un bioreattore idrostatico a pistone pneumatico, realizzato con componenti facilmente acquisibili a basso costo in commercio. Il bioreattore è collegato a una camera di coltura tramite un connettore pneumatico e un tubo per l’aria in polipropilene. La camera di coltura è realizzata in acido polilattico (PLA) tramite stampante 3D. Il dispositivo è in grado di applicare a una coltura cellulare tridimensionale una pressione idrostatica intermittente con ampiezza compresa tra 0 e 400 kPa e frequenza massima di 3,5 Hz. Condrociti provenienti dalla cartilagine di un’articolazione di ginocchio sono stati coltivati all’interno della camera di coltura del bioreattore dove sono stati sottoposti a una pressione di picco di 300 kPa per 3 ore al giorno per un totale di 5 giorni. Al termine della coltura si è ottenuto un aumento dell’attività metabolica cellulare del 21% e un aumento significativo del contenuto di glicosamminoglicani nell’ECM.