Entropy based adaptive particle filter

We propose a particle filter for the estimation of a partially observed Markov chain that has a non dynamic component. Such systems arise when we include unknown parameters or when we decompose non ergodic systems to their ergodic classes. Our main assumption is that the value of the non dynamic component determines the limiting distribution of the observation process. In such cases, we do not want to resample the particles that correspond to the non dynamic component of the Markov chain. Instead, we take a weighted average of particle filters corresponding to different values of the non dynamic component. The computation of the weights is based on entropy and the number of particles corresponding to each particle filter is proportional to the weights

A space-time multivariate Bayesian model to analyse road traffic accidents by severity

The paper investigates the dependences between levels of severity of road traffic accidents, accounting at the same time for spatial and temporal correlations. The study analyses road traffic accidents data at ward level in England over the period 2005–2013. We include in our model multivariate spatially structured and unstructured effects to capture the dependences between severities, within a Bayesian hierarchical formulation. We also include a temporal component to capture the time effects and we carry out an extensive model comparison. The results show important associations in both spatially structured and unstructured effects between severities, and a downward temporal trend is observed for low and high levels of severity. Maps of posterior accident rates indicate elevated risk within big cities for accidents of low severity and in suburban areas in the north and on the southern coast of England for accidents of high severity. The posterior probability of extreme rates is used to suggest the presence of hot spots in a public health perspective.Areti Boulieri acknowledges support from the National Institute for Health Research and the Medical Research Council Doctoral Training Partnership. Marta Blangiardo acknowledges support from the National Institute for Health Research and the Medical Research Council–Public Health England Centre for Environment and Health. Silvia Liverani acknowledges support from the Leverhulme Trust (grant ECF-2011-576)

Zeta functions and Dynamical Systems

In this brief note we present a very simple strategy to investigate dynamical determinants for uniformly hyperbolic systems. The construction builds on the recent introduction of suitable functional spaces which allow to transform simple heuristic arguments in rigorous ones. Although the results so obtained are not exactly optimal the straightforwardness of the argument makes it noticeable.Comment: 7 pages, no figuer

Additive manufacturing of AISI 420 stainless steel: process validation, defect analysis and mechanical characterization in different process and post-process conditions

Stainless steel (SS) alloys produced by laser-based powder bed fusion (LPBF) offers comparable and sometime superior mechanical properties compared to conventionally processed materials. Some of these steels have been extensively studied over the last decade; however additively manufactured martensitic SS, such as AISI 420, need further research in characterizing their post-built quality and mechanical behaviour. This lack of information on martensitic SS is not consistent with their growing demand in the automotive, medical and aerospace industries due to their good corrosion resistance, high hardness and good tensile properties. Selection of the appropriate process parameters and post treatments plays a fundamental role in determining final properties. For this reason, the effect of LPBF process parameters and different heat treatments on density, defect characteristics and locations, roughness and mechanical properties of AISI 420 were investigated in this paper. A first experimental campaign was carried out to establish a set of suitable process parameters for industrial applications. Starting from this result, detected defect properties were investigated by computed tomography (CT) scans. Dimensions, sphericity and distributions of defects inside the volume were analysed and compared between samples manufactured with different parameters. In the second part of the paper, the influence of process and post-process conditions on mechanical properties was investigated. The final presented results establish a correlation between the employed production cycle and the resulting properties of LPBF AISI 420 specimens

A design of experiment approach to 3D-printed mouthpieces sound analysis

Nowadays additive manufacturing is affected by a rapid expansion of possible applications. It is defined as a set of technologies that allow the production of components from 3D digital models in a short time by adding material layer by layer. It shows enormous potential to support wind musical instruments manufacturing because the design of complex shapes could produce unexplored and unconventional sounds, together with external customization capabilities. The change in the production process, material and shape could affect the resulting sound. This work aims to compare the music performances of 3D-printed trombone mouthpieces using both Fused Deposition Modelling and Stereolithography techniques, compared to the commercial brass one. The quantitative comparison is made applying a Design of Experiment methodology, to detect the main additive manufacturing parameters that affect the sound quality. Digital audio processing techniques, such as spectral analysis, cross-correlation and psychoacoustic analysis in terms of loudness, roughness and fluctuation strength have been applied to evaluate sounds. The methodology herein applied could be used as a standard for future studies on additively manufactured musical instruments

Beyond Conjugacy for Chain Event Graph Model Selection

Chain event graphs are a family of probabilistic graphical models that generalise Bayesian networks and have been successfully applied to a wide range of domains. Unlike Bayesian networks, these models can encode context-specific conditional independencies as well as asymmetric developments within the evolution of a process. More recently, new model classes belonging to the chain event graph family have been developed for modelling time-to-event data to study the temporal dynamics of a process. However, existing Bayesian model selection algorithms for chain event graphs and its variants rely on all parameters having conjugate priors. This is unrealistic for many real-world applications. In this paper, we propose a mixture modelling approach to model selection in chain event graphs that does not rely on conjugacy. Moreover, we show that this methodology is more amenable to being robustly scaled than the existing model selection algorithms used for this family. We demonstrate our techniques on simulated datasets

The role of filler wire and scanning strategy in laser welding of difficult-to-weld aluminum alloys

Laser welding of dissimilar aluminum alloys has gained interest over recent years, especially for the production of lightweight components. Pore and crack formation is one of the most critical factors to be taken into consideration for such applications, in particular when one or more parts are produced by die casting or additive manufacturing (AM). Current laser systems offer several methods for defect reduction and process control, while optimized process strategies must be correlated to key factors influencing welding outcomes. In light of these aspects, the current paper investigates the welding of AA6082 sheets with AlSi10Mg parts produced by AM in a lap-joint configuration typical of battery housings in the e-mobility industry. Both laser welding with and without filler wire are investigated, along with the potential advantages of using a wobbling scanning strategy, in order to understand the impact of process strategies on weld bead quality. The importance of process parameter optimization is highlighted for all of the employed strategies, with special emphasis on defects, weld bead chemical composition, joint morphology, and dilution between the materials involved. The findings demonstrate that by introducing filler wire and employing active wobbling, highly reflective alloys can be welded correctly (porosity below 1%, equivalent ultimate strength up to 204 MPa) with good tolerance to variations in process parameters, while filler wire can be excluded in high-productivity welding where linear scanning is employed and detailed optimization of process parameters is performed (porosity below 2%, equivalent ultimate strength up to 190 MPa

Design for six sigma (DFSS) applied to a new eco-motorbike

The primary purpose of this work is to organize, in the best possible way, the design of an ecological transport vehicle, using an advanced design methodology, namely design for six sigma (DFSS). The DFSS is indeed a design approach, able to implement, in a logical and integrated way, other advanced methodologies of systematic design, such as quality function deployment (QFD), TRIZ (in Russian, Teorija Resenija Izobretatel'skich Zadac), benchmarking, top-flop analysis and others, in order to propose design solutions oriented both to quality and innovation, for satisfying customers. The above described has been demonstrated through the application of DFSS to a case study in which the set up phase of an industrial project was completed, without having overlooked any aspect useful for obtaining a new attractive product. The case study concerns the application of DFSS to a new low-polluting motorcycle. At the end of the work, the designer obtained the achievement of the conceptual project

Conformal 3D Material Extrusion Additive Manufacturing for Large Moulds

Industrial engineering applications often require manufacturing large components in composite materials to obtain light structures; however, moulds are expensive, especially when manufacturing a limited batch of parts. On the one hand, when traditional approaches are carried out, moulds are milled from large slabs or laminated with composite materials on a model of the part to produce. In this case, the realisation of a mould leads to adding time-consuming operations to the manufacturing process. On the other hand, if a fully additively manufactured approach is chosen, the manufacturing time increases exponentially and does not match the market’s requirements. This research proposes a methodology to improve the production efficiency of large moulds using a hybrid technology by combining additive manufacturing and milling tools. A block of soft material such as foam is milled, and then the printing head of an additive manufacturing machine deposits several layers of plastic material or modelling clay using conformal three-dimensional paths. Finally, the mill can polish the surface, thus obtaining a mould of large dimensions quickly, with reduced cost and without needing trained personnel and handcraft polishing. A software tool has been developed to modify the G-code read by an additive manufacturing machine to obtain material deposition over the soft mould. The authors forced conventional machining instructions to match those of an AM machine. Thus, additive deposition of new material uses 3D conformal trajectories typical of CNC machines. Consequently, communication between two very different instruments using the same language is possible. At first, the code was tested on a modified Fused Filament Fabrication machine whose firmware has been adapted to manage a milling tool and a printing head. Then, the software was tested on a large machine suitable for producing moulds for the large parts typical of marine and aerospace engineering. The research demonstrates that AM technologies can integrate conventional machinery to support the composite materials industry when large parts are required

Design and development of a peristaltic pump for constant flow applications

In wide-ranging areas, including hydraulics, biomedical, automotive, and aerospace, there is often a need to move a fluid with a constant flow rate. This is difficult to achieve with any type of pump and usually other elements are inserted to regularize the output. This study focused on the peristaltic pump because there are few studies on it and it has some interesting features, such as extreme simplicity, a small number of components, and the extreme compactness of the whole system. The first part of this study is focused on analyzing the classical geometry of the peristaltic pump to understand the origin of the discontinuity in the flow rate; the second part proposes a new geometry that mitigates the flow irregularity by more than 200%. In this way, it is possible to use it in all the sectors where a constant flow rate is required but where insulation between the fluid and the machine is required. Together with the flow study, an analysis of how the main geometric parameters affect the operation of the pump is provided, complete with explanatory graphs and tables. A prototype made through additive manufacturing technologies is also proposed