DESIGN OF 3D VIRTUAL AND ADDITIVE MANUFCTURED MODELS FOR CULTURAL HERITAGE

It is well known that reverse engineering and additive manufacturing may be suitably integrated to develop different kinds of customized devices. Starting from image capture and analysis techniques, it is possible to manufacture an object or a functional part in a layer-by-layer fashion. Today many objects may be fabricated by additive manufacturing, benefiting from user-friendly computer programs and from the availability of open source 3-D printers. In the field of cultural heritage, there are many potential applications of the reverse engineering tools and methods, ranging from dissemination (e.g., virtual museums), reproduction (e.g., via additive manufacturing) and maintenance, to condition monitoring. Accordingly, in the proposed research 3D virtual and physical scale models of buildings and artworks were properly developed. 3D physical models were fabricated by fused deposition modeling (FDM), starting from the optimization of the process and instrument parameters. The processability of the materials (i.e., thermoplastic polymers) was assessed through functional and calorimetric analyses. Image capture and analysis techniques allowed to reproduce the geometry and morphology

Reducing The Computational Requirements for Simulating Tunnel Fires by Combining Multiscale Modelling and Multiple Processor Calculation

Multiscale modelling of tunnel fires that uses a coupled 3D (fire area) and 1D (the rest of the tunnel) model is seen as the solution to the numerical problem of the large domains associated with long tunnels. The present study demonstrates the feasibility of the implementation of this method in FDS version 6.0, a widely used fire-specific, open source CFD software. Furthermore, it compares the reduction in simulation time given by multiscale modelling with the one given by the use of multiple processor calculation. This was done using a 1200 m long tunnel with a rectangular cross-section as a demonstration case. The multiscale implementation consisted of placing a 30 MW fire in the centre of a 400 m long 3D domain, along with two 400 m long 1D ducts on each side of it, that were again bounded by two nodes each. A fixed volume flow was defined in the upstream duct and the two models were coupled directly. The feasibility analysis showed a difference of only 2% in temperature results from the published reference work that was performed with Ansys Fluent (Colella et al., 2010). The reduction in simulation time was significantly larger when using multiscale modelling than when performing multiple processor calculation (97% faster when using a single mesh and multiscale modelling; only 46% faster when using the full tunnel and multiple meshes). In summary, it was found that multiscale modelling with FDS v.6.0 is feasible, and the combination of multiple meshes and multiscale modelling was established as the most efficient method for reduction of the calculation times while still maintaining accurate results. Still, some unphysical flow oscillations were predicted by FDS v.6.0 and such results must be treated carefully

Multiscale Modelling of Tunnel Ventilation Flows and Fires

F Colella, Multiscale analysis of tunnel ventilation flows and fires, PhD Thesis, Politecnico di Torino, Dipartimento di Energetica. May 2010Tunnels represent a key part of world transportation system with a role both in people and freight transport. Past events show that fire poses a severe threat to safety in tunnels. Indeed in the past decades over four hundred people worldwide have died as a result of fires in road, rail and metro tunnels. In Europe alone, fires in tunnels have brought vital parts of the road network to a standstill and have cost the European economy billions of euros. Disasters like Mont Blanc tunnel (Italy, 1999) and the more recent three Channel Tunnel fires (2008, 2006 and 1996) show that tunnel fire emergencies must be managed by a global safety system and strategies capable of integrating detection, ventilation, evacuation and fire fighting response, keeping as low as possible damage to occupants, rescue teams and structures. Within this safety strategy, the ventilation system plays a crucial role because it takes charge of maintaining tenable conditions to allow safe evacuation and rescue procedures as well as fire fighting. The response of the ventilation system during a fire is a complex problem. The resulting air flow within a tunnel is dependent on the combination of the fire-induced flows and the active ventilation devices (jet fans, axial fans), tunnel layout, atmospheric conditions at the portals and the presence of vehicles. The calculation of tunnel ventilation flows and fires is more economical and time efficient when done using numerical models but physical accuracy is an issue. Different modelling approaches can be used depending on the accuracy required and the resources available. If details of the flow field are needed, 2D or 3D computational fluid dynamics (CFD) tools can be used providing details of the flow behaviour around walls, flames, ventilation devices and obstructions. The computational cost of CFD is very high, even for medium size tunnels (few hundreds meters). If the analysis requires only bulk flow velocities, 1D models can be adopted. Their low computational cost favours large number of parametric studies involving broad range ventilation scenarios, portal conditions and fire sizes/locations.Another class of methods, called multiscale methods, adopts different levels of complexity in the numerical representation of the system. Regions of interest are described using more detailed models (i.e. CFD models), while the rest of the system XIX can be represented using a simpler approach (i.e. 1D models). Multiscale methods are characterized by low computational complexity compared to full CFD models but provide the same accuracy. The much lower computational cost is of great engineering value, especially for parametric and sensitivity studies required in the design or assessment of ventilation and fire safety systems. Multiscale techniques are used here for the first time to model tunnel ventilation flows and fires.This thesis provides in Chapter 1 a general introduction on the fundamentals of tunnel ventilation flows and fires. Chapter 2 contains a description of 1D models, and a case study on the Frejus tunnel (IT) involving some comparisons to experimental data. Chapter 3 discusses CFD techniques with an extensive review of the literature in the last 30 years. The chapter provides also two model validations for cold ventilation flows in the Norfolk Tunnels (AU) and fire induced flows in a small scale tunnel. Chapter 4 introduces multiscale methods and addresses the typical 1D-CFD coupling strategies. Chapter 5 applies multiscale modelling for cold flow steady-state scenarios in the Dartford Tunnels (UK) where a further validation against experimental data has been introduced. Chapter 6 present the calculations from coupling fire and ventilation flows in realistic modern tunnel layout and investigates the accuracy of the multiscale predictions as compared to full CFD. Chapter 7 represents application of multiscale computing techniques to transient problems involving the dynamic response of the ventilation system. The multiscale model has been demonstrated to be a valid technique for the simulation of complex tunnel ventilation systems both in steady-state and timedependent problems. It is as accurate as full CFD models and it can be successfully adopted to conduct parametric and sensitivity studies in long tunnels, to design ventilation systems, to assess system redundancy and the performance under different hazards conditions. Time-dependent simulations allow determining the evolution of hazardous zones in the tunnel domain or to determine the correct timing for the activation of fixed fire fighting systems. Another significant advantage is that it allows for full coupling of the fire and the whole tunnel domain including the ventilation devices. This allows for an accurate assessment of the fire throttling effect that is shown here to be significant and for a prediction of the minimum number of jet fans needed to cope with a certain fire size. Furthermore, it is firmly believed that the multiscale methodology represents the only feasible tool to conduct accurate simulations in tunnels longer than few kilometres, when the limitation of the computational cost becomes too restrictive

Multiscale analysis of tunnel ventilation flows and fires

Presentazione a 11èmes journées du GDR Incendie, CSTB - Champs sur Marne, Paris (Fr), 17th -18th June 201

Effects of Anionic Liposome Delivery of All–Trans–Retinoic Acid on Neuroblastoma Cell Differentiation

All–trans–retinoic acid (ATRA) has long been known to affect cell growth and differentiation. To improve ATRA’s therapeutic efficacy and pharmacodynamics, several delivery systems have been used. In this study, free ATRA and anionic–liposome–encapsulated ATRA were compared for their effects on SK–N–SH human neuroblastoma cell growth and differentiation. Anionic liposomes made of L–α –phosphatidylcholine (PC) and L–α –phosphatidic acid (PA), empty (PC–PA) and loaded with ATRA (PC–PA–ATRA), were characterized by dynamic light scattering (DLS) and electrophoretic mobility measurements, and drug entrapment efficiency (EE%) was measured to evaluate the applicability of the new colloidal formulation. The results of brightfield microscopy and cell growth curves indicated that ATRA, whether free or encapsulated, reduced growth and induced differentiation, resulting in SK–N–SH cells changing from epithelioid to neuronal–like morphologies, and producing a significant increase in neurite growth. To further characterize the neuro-differentiation of SK–N–SH cells, the expression of βIII–Tubulin and synaptophysin and mitochondria localization were analyzed via immunofluorescence. Increased expression of neuronal markers and a peculiar localization of mitochondria in the neuritic extensions were apparent both in ATRA– and PC–PA–ATRA–differentiated cells. As a whole, our results strongly indicate that ATRA treatment, by any means, can induce the differentiation of parent SK–N–SH, and they highlight that its encapsulation in anionic liposomes increases its differentiation ability in terms of the percentage of neurite–bearing cells. Interestingly, our data also suggest an unexpected differentiation capability of anionic liposomes per se. This work highlights the importance of developing and carefully testing novel delivery nanocarriers, which are a necessary first “step” in the development of new therapeutic settings

Overcrowding analysis in emergency department through indexes: a single center study

Overcrowding in the Emergency Department (ED) is one of the major issues that must be addressed in order to improve the services provided in emergency circumstances and to optimize their quality. As a result, in order to help the patients and professionals engaged, hospital organizations must implement remedial and preventative measures. Overcrowding has a number of consequences, including inadequate treatment and longer hospital stays; as a result, mortality and the average duration of stay in critical care units both rise. In the literature, a number of indicators have been used to measure ED congestion. EDWIN, NEDOCS and READI scales are considered the most efficient ones, each of which is based on different parameters regarding the patient management in the ED

Prediction of Power Outages in Distribution Network with Grey Theory

Annual power outages in distribution network are highly related to the reliability of the power grid and directly affect the customers' satisfaction. The severe weather conditions, increasing loads as well as aging equipment are all potential threatens to the electrical grid infrastructure. A good prediction of the number of outages is essential for the maintenance planning and cost benefit analysis of investment. In order to predict the out-of-service cases in the power grid, the GM (1,1) (first-order Grey Modelling) forecasting method is introduced in this paper. To improve the accuracy of the prediction, the PSO (particle swarm optimization) algorithm is applied for the parameter optimization in the modeling. The number of outages in the next two years of a medium-voltage urban distribution network are predicted based on the records in the past 7 years. The good performance of the simulation results verifies the proposed forecasting method