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Orbits that are frozen in an averaged model, including the effect of a disturbing body laying on the equatorial plane of the primary body and the influence of the oblateness of the primary body, have been applied to probes orbiting the Moon. In this scenario, the main disturbing body is represented by the Earth, which is characterized by a certain obliquity with respect to the equatorial plane of the Moon. As a consequence of this, and of the perturbing effects that are not included in the averaged model, such solutions are not perfectly frozen. However, the orbit eccentricity, inclination, and argument of pericenter present limited variations and can be set to guarantee the fulfillment of requirements useful for lunar telecommunication missions and navigation services. Taking advantage of this, a practical case of a Moon-based mission was investigated to propose useful solutions for potential near-future applications.

The dynamics of a probe orbiting a moon can be significantly influenced by the non-coincidence between the moon’s equatorial and orbital planes. Thus, we performed a general analysis about the effects of the angle (obliquity) between the above-mentioned planes and of the angle (nodal phasing) between the nodal lines of the mother planet’s apparent orbit and the probe orbit on the lifetime of the probe. The lifetime, strictly correlated to the variations in eccentricity of the probe orbit, was evaluated starting from low values of the semi-major axis, moderate eccentricity, and high inclination to offer high ground spatial resolution and extend latitudinal coverage of the natural satellite. This investigation, carried out through numerical simulations, may be useful for identifying the optimal initial conditions of the probe’s orbit elements, leading to an important increase in the probe lifetime in missions devoted to the exploration of natural satellites.

ABSTRACTEnergy systems are regularly subject to major disruptions affecting economic activities, operation of infrastructure and the society as a whole. Resilience assessment comprises the pre-event oriented classical risk assessment as a central element, but it goes beyond that because it also includes and evaluates post-event strategies to improve the functioning of the system during its future operation. First, an overview of resilience definitions used across various scientific disciplines is presented, followed by an in-depth analysis of resilience assessment and quantification for energy systems. The relevant literature is classified by approach and according to four key functions of resilience: resist, restabilize, rebuild, and reconfigure. Findings show that irrespective of the research field, a resilient system always operates with an aim to minimize the potential consequences resulting from a disruptive event and to efficiently recover from a potential system performance loss.

In the field of satellite constellations, an important requirement is often represented by the possibility to exchange data among the satellites or exploit mutual visibility to carry out measurements on the parameters of the Earth’s atmosphere. Therefore, recursive and routing algorithms are usually implemented to evaluate inter-satellite visibility intervals. However, to design the configuration of the constellation, it is important to consider the orbital conditions that guarantee the mutual visibility between couples of satellites. Thus, in this study, a geometric analysis was performed to identify the optimal inter-satellite visibility conditions, expressed in terms of the difference in the true anomaly between satellites characterized by different orbital configurations. This approach allows a handy constellation design, without performing a numerical analysis. It is particularly useful in the case of a high number of satellites, when numerical techniques require significant computational effort. Therefore, it is possible to considerably simplify the design of a constellation in which the mutual visibility between couples of satellites is always guaranteed. This type of constellation, usually referred to as satellite chain, can be exploited in several network services and remote sensing systems devoted to enhancing the knowledge of atmospheric parameters.

Nanomaterials are becoming widely used in areas such as biomedical applications, food, environmental protection, energy production, information technology and agriculture. As such, more research has been conducted on their synthesis and manufacturing from a variety of feedstocks. However, concerns regarding their impact on human health and the environment leads researchers to conduct a variety of ‘sustainability’assessments. The purpose of this paper was to review the current opinion of sustainability assessments concerning nanomaterials. Major assessment tools were reviewed including life cycle assessment, risk assessment and multi-criteria decision analysis, along with subcategories. The review found that each assessment tool did positively contribute to sustainability assessments, but each also had drawbacks of varying degrees. In particular, multi-criteria decision analysis provides the most relevant tool for conducting a sustainability assessment as it can handle criteria of any typology and provide multiple types of decision recommendations, including rankings, scores and classifications.

We propose a novel approach to multiple criteria sorting incorporating a threshold-based value-driven procedure. The parameters deciding upon the shape of marginal value functions and separating class thresholds are inferred through preference disaggregation from the Decision Maker's incomplete assignment examples and partial requirements on the type of (non-)monotonicity for each marginal value function. These types include standard monotonic shapes, level-monotonic functions, A- and V-types combining increasing and decreasing value trends, and unknown monotonicity constraints. A representative instance of the sorting model compatible with the preference information is constructed by solving a dedicated Mixed-Integer Linear Programming problem. Its complexity is controlled by minimizing the number of changes in monotonicity between all subsequent sub-intervals of marginal value functions. The assignments derived using the constructed representative model are validated against the outcomes of robustness analysis. The proposed method is applied to a real-world problem of exposure management of engineered nanomaterials. We develop a model for predicting precaution level while handling nanomaterials in certain conditions using a respirator. The model captures interrelations between ten accounted evaluation criteria, including both monotonic and non-monotonic criteria, and the recommended class assignment. This makes it suitable for the management of exposure scenarios, which have not been directly judged by the experts. [ABSTRACT FROM AUTHOR]