Operational research applied to regional healthcare system

In this thesis we focus on optimization and simulation techniques applied to solve strategic, tactical and operational problems rising in the healthcare sector. At first we present three applications to Emilia-Romagna Public Health System (SSR) developed in collaboration with Agenzia Sanitaria e Sociale dell'Emilia-Romagna (ASSR), a regional center for innovation and improvement in health. Agenzia launched a strategic campaign aimed at introducing Operations Research techniques as decision making tools to support technological and organizational innovations. The three applications focus on forecast and fund allocation of medical specialty positions, breast screening program extension and operating theater planning. The case studies exploit the potential of combinatorial optimization, discrete event simulation and system dynamics techniques to solve resource constrained problem arising within Emilia-Romagna territory. We then present an application in collaboration with Dipartimento di Epidemiologia del Lazio that focuses on population demand of service allocation to regional emergency departments. Finally, a simulation-optimization approach, developed in collaboration with INESC TECH center of Porto, to evaluate matching policies for the kidney exchange problem is discussed.

Performance Analysis and Improvements for the Future Aeronautical Mobile Airport Communications System (AeroMACS)

This thesis deals with the development of the upcoming aeronautical mobile airport communications system (AeroMACS) system. We analyzed the performance of AeroMACS and we investigated potential solutions for enhancing its performance. Since the most critical results correspond to the channel scenario having less diversity1, we tackled this problem investigating potential solutions for increasing the diversity of the system and therefore improving its performance. We accounted different forms of diversity as space diversity and time diversity. More specifically, space (antenna and cooperative) diversity and time diversity are analyzed as countermeasures for the harsh fading conditions that are typical of airport environments. Among the analyzed techniques, two novel concepts are introduced, namely unequal diversity coding and flexible packet level codes. The proposed techniques have been analyzed on a novel airport channel model, derived from a measurement campaign at the airport of Munich (Germany). The introduced techniques largely improve the performance of the conventional AeroMACS link; representing thus appealing solutions for the long term evolution of the system.

Soil application of Meliaceae derivatives: effect on carbon and nitrogen dynamics in the soil-plant system

The effect of soil incorporation of 7 Meliaceae derivatives (6 commercial neem cakes and leaves of Melia azedarach L.) on C and N dynamics and on nutrient availability to micropropagated GF677 rootstock was investigated. In a first laboratory incubation experiment the derivatives showed different N mineralization dynamics, generally well predicted by their C:N ratio and only partly by their initial N concentration. All derivatives increased microbial biomass C, thus representing a source of C for the soil microbial population. Soil addition of all neem cakes (8 g kg-1) and melia leaves (16 g kg-1) had a positive effect on plant growth and increased root N uptake and leaf green colour of micropropagated plants of GF677. In addition, the neem cakes characterized by higher nutrient concentration increased P and K concentration in shoot and leaves 68 days after the amendment. In another experiment, soil incorporation of 15N labeled melia leaves (16 g kg-1) had no effect on the total amount of plant N, however the percentage of melia derived-N of treated plants ranged between 0.8% and 34% during the experiment. At the end of the growing season, about 7% of N added as melia leaves was recovered in plant, while 70% of it was still present in soil. Real C mineralization and the priming effect induced by the addition of the derivatives were quantified by a natural 13C abundance method. The real C mineralization of the derivatives ranged between 22% and 40% of added-C. All the derivatives studied induced a positive priming effect and, 144 days after the amendment, the amount of C primed corresponded to 26% of added-C, for all the derivatives. Despite this substantial priming effect, the C balance of the soil, 144 days after the amendment, always resulted positive.

Dynamics of undeactuated cable-driven parallel robots

This thesis focuses on the dynamics of underactuated cable-driven parallel robots (UACDPRs), including various aspects of robotic theory and practice, such as workspace computation, parameter identification, and trajectory planning. After a brief introduction to CDPRs, UACDPR kinematic and dynamic models are analyzed, under the relevant assumption of inextensible cables. The free oscillatory motion of the end-effector (EE), which is a unique feature of underactuated mechanisms, is studied in detail, from both a kinematic and a dynamic perspective. The free (small) oscillations of the EE around equilibria are proved to be harmonic and the corresponding natural oscillation frequencies are analytically computed. UACDPR workspace computation and analysis are then performed. A new performance index is proposed for the analysis of the influence of actuator errors on cable tensions around equilibrium configurations, and a new type of workspace, called tension-error-insensitive, is defined as the set of poses that a UACDPR EE can statically attain even in presence of actuation errors, while preserving tensions between assigned (positive) bounds. EE free oscillations are then employed to conceive a novel procedure aimed at identifying the EE inertial parameters. This approach does not require the use of force or torque measurements. Moreover, a self-calibration procedure for the experimental determination of UACDPR initial cable lengths is developed, which consequently enables the robot to automatically infer the EE initial pose at machine start-up. Lastly, trajectory planning of UACDPRs is investigated. Two alternative methods are proposed, which aim at (i) reducing EE oscillations even when model parameters are uncertain or (ii) eliminate EE oscillations in case model parameters are perfectly known. EE oscillations are reduced in real-time by dynamically scaling a nominal trajectory and filtering it with an input shaper, whereas they can be eliminated if an off-line trajectory is computed that accounts for the system internal dynamics.

Advanced representation of the ocean/sea ice dynamics at high latitudes

Sea ice is a fundamental element of global climate system, with numerous impacts on the polar environment. The ongoing drastic changes in the Earth’s sea ice cover highlight the necessity of monitoring the polar regions and systematically evaluating the quality of different numerical products. The main objective of this thesis is to improve our knowledge of the representation of Arctic and Antarctic sea ice using comprehensive global ocean reanalyses and coupled climate models. The dissertation will explore (i) the Antarctic marginal ice zone (MIZ) and pack ice area in the ensemble mean of four global ocean reanalyses called GREP; (ii) historical representation of the Arctic and Antarctic sea ice state in HighResMIP models; (iii) the future evolution of Arctic sea ice in HighResMIP models. Global ocean reanalyses and GREP are found to adequately capture interannual and seasonal variability in both pack ice and MIZ areas at hemispheric and regional scales. The advantage of the ensemble-mean approach is proved as GREP smooths the strengths and weaknesses of single systems and provides the most consistent and reliable estimates. This work is intended to encourage the use of GREP in a wide range of applications. The analysis of sea ice representation in the coupled climate models shows no systematic impact of the increased horizontal resolution. We argue that a few minor improvements in sea ice representation with the enhanced horizontal resolution are presumably not worth the major effort of costly computations. The thesis highlights the critical importance to distinguish the MIZ from consolidated pack ice both for investigating changes in sea ice distribution and evaluating the product’s performance. Considering that the MIZ is predicted to dominate the Arctic sea ice cover, the model physics parameterizations and sea ice rheology might require modifications. The results of the work can be useful for modelling community.

Navigation design and flight dynamics operations of the ArgoMoon cis-lunar CubeSat.

On November 16, 2022, the NASA’s Space Launch System (SLS) has been launched for the first time in the context of Artemis-1 mission where, together with the Orion Multi-Purpose Crew Vehicle, a set of 10 CubeSats have been delivered into a translunar trajectory. Among the small satellites deployed during Artemis-1 there is ArgoMoon, a 6U CubeSat built by the Italian company Argotec and coordinated by Italian Space Agency (ASI). The primary goal of ArgoMoon is to capture images of the Interim Cryogenic Propulsion Stage. The ArgoMoon trajectory has been designed as a highly elliptical geocentric orbit, with several encounters with the Moon. In order to successfully fly ArgoMoon along the designed cis-lunar trajectory, a ground-based navigation system has been developed exploiting the guidance techniques also used for regular deep space missions. The navigation process is subdivided into Orbit Determi- nation (OD) and a Flight Path Control (FPC), and it is designed to follow the reference trajectory, prevent impacts with the Earth and the Moon, intensively test the navigation techniques, and guarantee the spacecraft disposal at the end of the mission. The work done in this thesis has accomplished the navigation of ArgoMoon, covering all aspects of the project life, from pre-launch design and analysis to actual operations. Firstly, the designed navigation process and the pre-mission assessment of its performance will be presented. Then, the results of the ArgoMoon navigation operations performed after the launch in November 2022 will be described in detail by discussing the main encountered challenges and the adopted solutions. The results of the operations confirmed the robustness of the designed navigation which allowed to accurately estimate the trajectory of ArgoMoon despite a series of complex events.

Novel methods of state estimation and parameter identification for high-performance motorcycles

This research activity aims at providing a reliable estimation of particular state variables or parameters concerning the dynamics and performance optimization of a MotoGP-class motorcycle, integrating the classical model-based approach with new methodologies involving artificial intelligence. The first topic of the research focuses on the estimation of the thermal behavior of the MotoGP carbon braking system. Numerical tools are developed to assess the instantaneous surface temperature distribution in the motorcycle's front brake discs. Within this application other important brake parameters are identified using Kalman filters, such as the disc convection coefficient and the power distribution in the disc-pads contact region. Subsequently, a physical model of the brake is built to estimate the instantaneous braking torque. However, the results obtained with this approach are highly limited by the knowledge of the friction coefficient (μ) between the disc rotor and the pads. Since the value of μ is a highly nonlinear function of many variables (namely temperature, pressure and angular velocity of the disc), an analytical model for the friction coefficient estimation appears impractical to establish. To overcome this challenge, an innovative hybrid solution is implemented, combining the benefit of artificial intelligence (AI) with classical model-based approach. Indeed, the disc temperature estimated through the thermal model previously implemented is processed by a machine learning algorithm that outputs the actual value of the friction coefficient thus improving the braking torque computation performed by the physical model of the brake. Finally, the last topic of this research activity regards the development of an AI algorithm to estimate the current sideslip angle of the motorcycle's front tire. While a single-track motorcycle kinematic model and IMU accelerometer signals theoretically enable sideslip calculation, the presence of accelerometer noise leads to a significant drift over time. To address this issue, a long short-term memory (LSTM) network is implemented.