Towards effective flow simulations in realistic Discrete Fracture Networks

We focus on the simulation of underground flow in fractured media, modeled by means of Discrete Fracture Networks. Focusing on a new recent numerical approach proposed by the authors for tackling the problem avoiding mesh generation problems, we further improve the new family of methods making a step further towards effective simulations of large, multi-scale, heterogeneous networks. Namely, we tackle the imposition of Dirichlet boundary conditions in weak form, in such a way that geometrical complexity of the DFN is not an issue; we effectively solve DFN problems with fracture transmissivities spanning many orders of magnitude and approaching zero; furthermore, we address several numerical issues for improving the numerical solution also in quite challenging networks

A three-field based optimization formulation for flow simulations in networks of fractures on non-conforming meshes

A new numerical scheme is proposed for flow computation in complex discrete fracture networks. The method is based on a three-field domain decomposition framework, in which independent variables are introduced at the interfaces generated in the process of decoupling the original problem on the whole network into a set of fracture-local problems. A PDE-constrained formulation is then used to enforce compatibility conditions at the interfaces. The combination of the three-field domain decomposition and of the optimization based coupling strategy results in a novel method which can handle non-conforming meshes, independently built on each geometrical object of the computational domain, and ensures local mass conservation property at fracture intersections, which is of paramount importance for hydro-geological applications. An iterative solver is devised for the method, suitable for parallel implementation on parallel computing architectures

Molecular and Functional Characterization of the Odorant Receptor2 (OR2) in the Tiger Mosquito Aedes albopictus

In mosquitoes, the olfactory system plays a crucial role in many types of behavior, including nectar feeding, host preference selection and oviposition. Aedes albopictus, known also as the tiger mosquito, is an anthropophilic species, which in the last few years, due to its strong ecological plasticity, has spread throughout the world. Although long considered only a secondary vector of viruses, the potential of its vector capacity may constitute a threat to public health. Based on the idea that an improved understanding of the olfactory system of mosquitoes may assist in the development of control methods that interfere with their behavior, we have undertaken a study aimed at characterizing the A. albopictus Odorant Receptors. Here we report the identification, cloning and functional characterization of the AalOR2 ortholog, that represents the first candidate member of the odorant receptor (OR) family of proteins from A. albopictus. AalOR2 is expressed in the larval heads and antennae of adults. Our data indicate that A. albopictus OR2 (AalOR2) shares a high degree of identity with other mosquito OR2 orthologs characterized to date, confirming that OR2 is one of the most conserved mosquito ORs. Our data indicate that AalOR2 is narrowly tuned to indole, and inhibited by (-)-menthone. In agreement with this results, these two compounds elicit two opposite effects on the olfactory-based behavior of A. albopictus larvae, as determined through a larval behavioral assay. In summary, this work has led to the cloning and de-orphaning of the first Odorant Receptor in the tiger mosquito A. albopictus. In future control strategies this receptor may be used as a potential molecular target

Erythropoietin in amyotrophic lateral sclerosis: a multicentre, randomised, double blind, placebo controlled, phase III study

OBJECTIVE: To assess the efficacy of recombinant human erythropoietin (rhEPO) in amyotrophic lateral sclerosis (ALS). METHODS: Patients with probable laboratory-supported, probable or definite ALS were enrolled by 25 Italian centres and randomly assigned (1:1) to receive intravenous rhEPO 40,000 IU or placebo fortnightly as add-on treatment to riluzole 100 mg daily for 12 months. The primary composite outcome was survival, tracheotomy or >23 h non-invasive ventilation (NIV). Secondary outcomes were ALSFRS-R, slow vital capacity (sVC) and quality of life (ALSAQ-40) decline. Tolerability was evaluated analysing adverse events (AEs) causing withdrawal. The randomisation sequence was computer-generated by blocks, stratified by centre, disease severity (ALSFRS-R cut-off score of 33) and onset (spinal or bulbar). The main outcome analysis was performed in all randomised patients and by intention-to-treat for the entire population and patients stratified by severity and onset. The study is registered, EudraCT 2009-016066-91. RESULTS: We randomly assigned 208 patients, of whom 5 (1 rhEPO and 4 placebo) withdrew consent and 3 (placebo) became ineligible (retinal thrombosis, respiratory insufficiency, SOD1 mutation) before receiving treatment; 103 receiving rhEPO and 97 placebo were eligible for analysis. At 12 months, the annualised rate of death (rhEPO 0.11, 95% CI 0.06 to 0.20; placebo: 0.08, CI 0.04 to 0.17), tracheotomy or >23 h NIV (rhEPO 0.16, CI 0.10 to 0.27; placebo 0.18, CI 0.11 to 0.30) did not differ between groups, also after stratification by onset and ALSFRS-R at baseline. Withdrawal due to AE was 16.5% in rhEPO and 8.3% in placebo. No differences were found for secondary outcomes. CONCLUSIONS: RhEPO 40,000 IU fortnightly did not change the course of ALS

Non-stationary transport phenomena in networks of fractures: effective simulations and stochastic analysis

Among the major challenges in performing underground flow simulations in fractured media are geometrical complexities in the domain and uncertainty in the problem parameters, including the geometrical configuration. The Discrete Fracture Network (DFN) model is largely applied in order to properly account for the directionality of the flow in fractured media. Generation of DFN configurations is usually based on stochastic data and this contributes to generate very complex geometrical configurations for which a conforming mesh generation is often infeasible. Moreover, uncertainty in the geometrical and hydro-geological properties calls for a deep uncertainty quantification analysis; the corresponding huge computational cost of the simulations requires modern efficient approaches faster and cheaper than the classical Monte Carlo approach. In this paper we numerically investigate both these aspects, proposing a viable solution for dealing with geometrical complexities arising in the computation of the hydraulic head and in the solution of the unsteady transport problem of a passive scalar in the DFN, and for dealing with uncertainties in hydro-geological parameters of the fracture distribution considered

Unsteady advection-diffusion simulations in complex Discrete Fracture Networks with an optimization approach

It is widely recognized that the prediction of transport of contaminants in a fractured rock mass requires models that preserve several distinctive features of the inner fracture network, like heterogeneity and directionality; in this respect, Discrete Fracture Networks (DFNs) play a significant role. The solution of the associated equations would claim a high computational demand, that could be met only by using agile and robust numerical techniques. In this note a new numerical technique, fully validated from a mathematical standpoint, is applied to engineering problems, also introducing dispersion models for the description of non-stationary transport phenomena. The method results in a fast and scalable resolution tool, based on a PDE-constrained optimization approach designed to avoid mesh generation problems and allowing for transport simulations with an Eulerian approach. Examples are reported to show the quality of the solution obtained, even by using relatively coarse meshes and quite geometrically complex DFNs

Uncertainty quantification in Discrete Fracture Network models: stochastic geometry

We consider the problem of uncertainty quantification analysis of the output of underground flow simulations. We consider in particular fractured media described via the discrete fracture network model; within this framework, we address the relevant case of networks in which the geometry of the fractures is described by stochastic parameters. In this context, due to a possible lack of smoothness in the quantity of interest with respect to the stochastic parameters, well assessed techniques such as stochastic collocation may fail in providing reliable estimates of first order moments of the quantity of interest. In this paper we overcome this issue by applying the Multilevel Monte Carlo method, using as underlying solver an extremely robust method