On the bi-Hamiltonian Geometry of WDVV Equations

We consider the WDVV associativity equations in the four dimensional case. These nonlinear equations of third order can be written as a pair of six component commuting two-dimensional non-diagonalizable hydrodynamic type systems. We prove that these systems possess a compatible pair of local homogeneous Hamiltonian structures of Dubrovin--Novikov type (of first and third order, respectively).Comment: 21 pages, revised published version; exposition substantially improve

Systems of conservation laws with third-order Hamiltonian structures

We investigate $n$-component systems of conservation laws that possess third-order Hamiltonian structures of differential-geometric type. The classification of such systems is reduced to the projective classification of linear congruences of lines in $\mathbb{P}^{n+2}$ satisfying additional geometric constraints. Algebraically, the problem can be reformulated as follows: for a vector space $W$ of dimension $n+2$, classify $n$-tuples of skew-symmetric 2-forms $A^{\alpha} \in \Lambda^2(W)$ such that $$\phi_{\beta \gamma}A^{\beta}\wedge A^{\gamma}=0,$$ for some non-degenerate symmetric $\phi$.Comment: 31 page

Numerical-Experimental Assessment of a Hybrid FE-MB Model of an Aircraft Seat Sled Test

This paper deals with the development of an established hybrid finite element multibody (FE-MB) model for the simulation of an experimental sled test of a single row of a double passenger seat placed in front of a fuselage bulkhead, by considering a single anthropomorphic Hybrid II 50th dummy arranged on one of the seat places. The numerical investigation has been carried out by focusing on the passenger passive safety. Specifically, the occupant injury assessment has been quantitatively monitored by means of the head injury criterion (HIC), which, based on the average value of the dummy head acceleration during a crash event, should not exceed, according to the standards, the value of 1000. Numerical results provided by the hybrid model have been compared with the experimental ones provided by the Geven S.p.A. company and with the results carried out by a full FE model. The hybrid model simulates with a good level of accuracy the experimental test and allows reducing significantly the computing time with respect to the full FE one

Mapping combined wildfire and heat stress hazards to improve evidence-based decision making

Heat stress and forest fires are often considered highly correlated hazards as extreme temperatures play a key role in both occurrences. This commonality can influence how civil protection and local responders deploy resources on the ground and could lead to an underestimation of potential impacts, as people could be less resilient when exposed to multiple hazards. In this work, we provide a simple methodology to identify areas prone to concurrent hazards, exemplified with, but not limited to, heat stress and fire danger. We use the combined heat and forest fire event that affected Europe in June 2017 to demonstrate that the methodology can be used for analysing past events as well as making predictions, by using reanalysis and medium-range weather forecasts, respectively. We present new spatial layers that map the combined danger and make suggestions on how these could be used in the context of a Multi-Hazard Early Warning System. These products could be particularly valuable in disaster risk reduction and emergency response management, particularly for civil protection, humanitarian agencies and other first responders whose role is to identify priorities during pre-interventions and emergencies

A generalised multi-attribute task sequencing approach for robotics optical inspection systems

Robot programming usually consists of four steps: (1) task planning; (2) task sequencing; (3) path planning and (4) motion planning. Task (2) and (3–4) are strongly coupled. For example, the optimal robot path, which is function of the robot kinematics, relies on the pre-defined schedule of tasks, whose sequencing is computed based on the assumption that the travelling “cost” from one task to the next is only driven by the Euclidean distance in Cartesian space. Current methods tends to decouple the problem and sequentially compute the task sequencing in the T-space, and then compute the robot path by solving the inverse kinematics in the C-space. However, those approaches suffer the capability to reach a global optimum. This paper aims at developing a novel approach which integrates some of the key computational requirements of the path planning in the early stage of the task sequencing. Multi-attribute objectives are introduced to take into account: robot pose and reachability, data quality, obstacles avoidance, overall cycle time. The paper introduces a novel multi-attribute approach to find the optimized task sequencing via candidate poses solving inverse kinematics in the T-space. This is based on the core idea to combine T-space and C-space. The proposed solution has been tested on a vision-based inspection robot system with application to automotive body assembly systems. Results could however impact a wider area, from navigation systems, game and graph theory, to autonomous driving systems

Validation of a small scale woody biomass downdraft gasification plant coupled with gas engine

In recent years, small scale cogeneration systems (< 500 kWe) distributed in different geographical locations using biomass has received special attention as economically competitive and environmentally friendly ways of producing energy. These systems can be integrated to industrial and agricultural activities where biomass residues are generated and can be converted into electricity and thermal energy by combustion or gasification. The legislations of many European countries such as Italy concerning renewable energy and energy efficiency along the taxation schemes have raised the incentives for small scale cogeneration plants. Consequently, there is a clear economic interest of the companies in this sector and there is also a scientific interest towards demonstration of their energetic efficiency, environmental performance and reliability. Among the suggested technologies for the biomass conversion into energy, downdraft gasification (using air as gasification agent), coupled with internal combustion engines, has the advantage of high electric efficiency (~ 25%) and low tar generation, making easier the gas cleaning process necessary for its use into engines. In the present work, the results of a measurement campaign performed on a commercial scale 350 kWth downdraft woodchips gasification plant, coupled with an SI internal combustion engine (ICE), are presented and discussed. The main goals of this first experimental campaign have been to verify the stability of gasifier and engine operation, operability of the plant and to determine its energy efficiency. The campaign verified a stable operation of the gasifier and the plant produced a syngas with a composition suitable for a gas engine. The energy balance resulted in a potential overall wood fuel to electricity efficiency of about 23 %