Computational modelling of dump combustors flowfield

A computational model aimed at predicting the flowfield of dump combustors is presented. The turbulent combustion model is based on the conserved scalar approach and on a convenient specification of its probability density function, which reduces the computation of the mean density to a closed form. Turbulence is modeled by means of the k-epsilon model. The averaged conservation equations are solved by a technique based on a staggered grid and on the SIMPLE solver. The computational model is applied to a simple dump combustor to assess the computer time requirements and accuracy. The turbulent combustion model is shown to reduce the computer time by an order of magnitude when compared to evaluating the mean density by numerical quadrature

MACHINE LEARNING AND CAUSALITY FOR INTERPRETABLE AND AUTOMATED DECISION MAKING

This abstract explores two key areas in decision science: automated and interpretable decision making. In the first part, we address challenges related to sparse user interaction data and high item turnover rates in recommender systems. We introduce a novel algorithm called Multi-View Interactive Collaborative Filtering (MV-ICTR) that integrates user-item ratings and contextual information, improving performance, particularly for cold-start scenarios. In the second part, we focus on Student Prescription Trees (SPTs), which are interpretable decision trees. These trees use a black box teacher model to predict counterfactuals based on observed covariates. We experiment with a Bayesian hierarchical binomial regression model as the teacher and employ statistical significance testing to control tree growth, ensuring interpretable decision trees. Overall, our research advances the field of decision science by addressing challenges in automated and interpretable decision making, offering solutions for improved performance and interpretability

Frictional properties of cartilage loaded against cartilage by using a pin on disc tribometer

Articular cartilage is a specialised, aneural and avascular connective tissue that lines the end of synovial joints. Its main functions are minimising friction and wear during the movements between the joint surfaces, and spreading and transmitting loads and shocks over a larger area within articulations. Many studies have been performed to shed light on the outstanding tribological features of this soft poroelastic material. However, despite the effort expended, many aspects remain unclear. This paper presents an experimental investigation on the effect of the load and static loading time over the frictional properties of adult bovine articular cartilage

Entomofauna e parassiti del mirto

Myrtle pests are mainly represented by Rhinchota homoptera and Thisanoptera. In particular, Saissetia oleae, Partenolecanium corni e Ceroplastes rusci are the most frequent species reported in Sardinia whereas Heliothrips haemorroidalis is a harmful pest in other Italian regions. Pest control in myrtle cultivations is possible only following the plant protection regulation of European organic agriculture. In fact, in Italy there currently are no conventional insecticides authorized for myrtle destined to liquor or essential oil production

A Numerical Study Investigating Sensitivity of Radar Wave Propagation to the Marine Atmospheric Boundary Layer Environment

Radar is a remote sensor that is useful in scientific and military applications. The environment affects the accuracy of radar measurements as well as the predictability of a radar system’s performance. Because of the complexity of the dynamic processes occurring in the marine atmospheric boundary layer (MABL), which includes the lowermost troposphere and ocean surface, the impact of the environment on radar is intricate and difficult to assess. To better understand the relative importance of various aspects of the MABL environment on radar wave propagation, this study evaluates the sensitivity of radar wave propagation to the MABL environment using a global sensitivity analysis (SA) method, the extended Fourier amplitude sensitivity test (EFAST), and the Variable Terrain Radio Parabolic Equation (VTRPE) simulation, which calculates propagation power of radar waves in a wide variety of marine atmospheric conditions. A total of 16 environmental parameters are examined, 8 parameterizing the rough ocean surface, and 8 parameterizing the atmospheric vertical refractivity profiles. Radar frequencies of 3, 9, and 15 GHz are each simulated with horizontal (HH) and vertical (VV) polarization, resulting in sensitivity calculations for 6 different cases. The study is conducted for a domain of 1 km in altitude and 60 km in range using a low grazing angle generic air/sea surveillance radar. The relative importance of the different parameters varied much more with frequency than polarization. The EFAST method takes into account parameter interactions, which are found to be significant and can be essential to correctly interpret the significance of a parameter. Results show that the atmospheric mixed layer parameters are most important, particularly the height of the mixed layer. Overall, swell period is the most significant ocean surface parameter. However, sea directionality is also important at 3 GHz, and sea surface roughness and salinity are important at 9 and 15 GHz, respectively. Sensitivities to ocean surface parameters, except those related to directionality, become more prominent as radar frequency increases, and some sensitivity differences with respect to polarization occur regarding sea surface characteristics. Due to spatial variability of sensitivity throughout the domain, regional analysis is performed, using short (0-10 km), mid (10-30 km), and long (30-60 km) range, and low (0-200 m), mid (200-600 m), and high (600-1000 m) altitude divisions (9 regions). The most sensitive parameter in each low altitude region, from short to long range, is evaporation duct height and mixed layer height (mid and long range). The mixed layer height is the most sensitive parameter in all mid-altitude regions. At high altitude, the most sensitive parameter varies with frequency, except at short range where it is the mixed layer refractivity gradient (i.e., M-gradient). At mid-range, the most sensitive parameters are the inversion layer strength, mixed layer M-gradient, and mixed layer height for 3, 9, and 15 GHz respectively. At long range, the inversion strength is the most sensitive parameter at 3 GHz, while at 9 and 15 GHz it is the wind speed. These regional sensitivity results, along with those for the whole domain, can be used to determine which environmental parameters need to be specified with high accuracy when accounting for their effects on propagation for various radar systems and applications. This sensitivity information can also be used to help guide field measurements for simulation validation studies as it indicates what aspects of the environment need to be focused on for such experimental campaigns. Furthermore, these results provide guidance on prioritization of environmental characterization in numerical weather prediction (NWP) and inversion studies (e.g., refractivity from clutter (RFC) studies), which are the two most common numerical methods currently used to address environmental effects on propagation. Additionally, the methodology presented in this study can be used and applied to similar problems that seek to understand the sensitivity to environmental effects on other remote sensors, such as infrared (IR), optical, and acoustic sensors