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The aim of the study was to evaluate the effect of type of irrigation and of amount of water supplied on vine growth, yield and fruit quality at harvest and after 2 and 4 months of cold storage. The study was carried out in 2019, in northern Italy, on kiwifruit Gold 3®(A. chinensis var. chinensis) grafted onto micro-propagated 'Hayward' (A. chinensis var. deliciosa) rootstocks in 2012, planted at a distance of 4.5×2 m apart. The investigated irrigation systems included: 1) control (T0); 2) drip irrigation with a single line (T1); 3) drip irrigation with double lines (T2); 4) sprinkler (T3); 5) drip irrigation with double lines + sprinkler (T2+T3). Water management in the control treatment was carried out with drip irrigation with a single pipeline according to the advisory service, based on daily evapotranspiration only. In T1, T2, T3, and T2+T3 water was applied according to the soil water content measured by potentiometric probes, located at two depths: 0.20 and 0.60 m, and two distances from the line of the trees: 0.20 and 1 m. Irrigation started when soil water content got down below the field capacity (-0.03 MPa) and returned the same amount of water lost the day before and measured by a PAN evaporimeter. Compared to the control, T1 reduced the volume of water applied by 34%, T2 by 3%, while T3 increased the irrigation volume by 14% and T2+T3 by 17%. Sprinkler application induced an excess of water in the inter row, where soil structure was impaired by the frequent passes of machines, reducing soil permeability. No effect of treatments on vine yield was observed, however, fruit soluble solid concentration and fruit dry matter at harvest was increased by T2 compared to the other treatments. A similar response was also found after 2 months of cold storage, but disappeared after 4 months. The incidence of storage break down (SBD) was higher in fruits of the control and T3 (22 and 40% of the fruits, respectively), while T2 and T2+T3 irrigation strategies showed the lowest percentage (5-8%, respectively). Finally, the incidence of SBD was negatively correlated with the fruit dry matter (r=-0.88; P≤0.05).

Within the context of modern industries, additive manufacturing (AM) plays a critical role. Design for AM (DfAM) requires defining design actions related to the product’s geometry under development. DfAM affects design choices such as the type of process, the material, the geometry, and the model’s features. Knowledge-based engineering (KBE) is promising for integrating DfAM principles in the early phases of product development. Still, few limitations are noticed, such as the real interoperability between DfAM and 3D CAD systems, leading to the application of proper DfAM rules downstream of the 3D modeling. This paper aims to describe a method to formalize AM engineering knowledge used as a repository to develop a CAD-integrated decision support tool by acknowledging the current gap. The method uses, as input, geometrical data retrieved by the feature analysis of the 3D CAD model (feature recognition approach) and manufacturing information related to AM processes. The method will allow closing the gap between the design and production departments by creating a knowledge-based system. The outcome of this system does not concern the possibility of predicting the AM process parameters. The system will support engineers in delivering product designs compliant with AM processes. Based on this system, a CAD-integrated DfAM tool can be developed in the future.

Obiettivo dello studio è stato di stabilire la dinamica di assorbimento dei nutrienti minerali e la loro ripartizione tra i diversi organi della pianta di kiwi a polpa gialla. La prova è stata condotta a Brisighella, in un frutteto impiantato nel 2014 su un terreno franco-argilloso di buona fertilità. Dal mese di maggio sono stati determinati periodicamente la lunghezza dei germogli e il numero di foglie, la crescita del frutto (diametro, peso e sostanza secca), mentre ogni quattro settimane sono stati prelevati campioni di foglie e frutti per la determinazione della composizione minerale. A fine stagione, infine, sono state raccolte e pesate le foglie abscisse e il legno di potatura, anch’essi analizzati per macro e micronutrienti. Alla raccolta, nei frutti erano presenti rispettivamente 77, 10, 74, 11, 5 e 6 kg ha-1 di N, P, K, Ca, Mg e S. Boro e Fe sono risultati i micronutrienti più presenti nei frutti alla raccolta (circa 100 g ha-1). L’accumulo di N, P e K nelle foglie e nei frutti è aumentato linearmente fino alla raccolta; l’accumulo di Ca nei frutti si è interrotto ad agosto, mentre nelle foglie è continuato fino alla senescenza fogliare. Tenuto conto dei diversi organi della pianta (frutti diradati, legno di potatura, frutti raccolti e foglie abscisse), le quantità di N, P, K, Ca e Mg assorbite durante la stagione sono state rispettivamente pari a 143, 16, 105, 202 e 38 kg ha-1.

Modularization is a current issue in the context of plant design. A modular system aims to reduce lead time and cost in design phases. An oil & gas plant consists of many Engineered-To-Order solutions to be submitted and approved during the negotiation phase. In this context, design tools and methods are necessary to support the design life cycle from the conceptual study to the detailed project. The paper proposes an approach to optimize the design of modularized oil & gas plants with a focus on the related steel structures. A test case shows the configuration workflow applied to a modular steel structure of about 400 tons. The modularized layout has been optimized using genetic algorithms. A Knowledge Base has been described to support the configuration phase related to the conceptual design. Design rules and metrics have been formalized from the analysis of past solutions.

Design optimization is a common practice in industry. Different mathematical algorithms have been developing to support the optimization in engineering design. The integration between optimization methods and simulations is an interesting issue in engineering design. A typical optimization workflow can include simulation steps; however, the Virtual Prototyping analysis is more time-consuming than analytical calculations. The study of Constraints Satisfaction Problems is a mathematical topic which can be applied for solving engineering issues in design. The strength of this approach is the velocity on searching the satisfied solutions. This paper proposes a design methodology which considers the use of CSP models and calculation tools to optimize the sizing of columns and beams in the design of a steel structure. The calculation tools regard analytical models and numerical analysis. While the analytical approach regards the computing of cost and weight, the numerical analysis is used to verify and check the engineering performance in terms of deformation and stress state. A customized application, based on MiniZinc platform, has been developed and proposed to solve the CSP model for a test case steel structure. The CSP problem has been limited to the calculation of analytical constraints such as cost and weight. Finally, the resultant set of solutions has been evaluated using numerical solution to complete the optimization analysis.

Nowadays, electromagnetic high-frequency induction is very used for different non-contact heating applications such as the molding process. Every molding process requires the preheating and the thermal maintenance of the molds, to enhance the filling phase and the quality of the final products. In this context, an induction heating system, mostly, is a customized equipment. The design and definition of an induction equipment depends on the target application. This technology is highly efficient and performant, however it provides a high-energy consumption. Therefore, optimization strategies are very suitable to reduce energy cost and consumption. The proposed paper aims to define a method to optimize the induction heating of a mold in terms of time, consumption, and achieved temperature. The proposed optimization method involves genetic algorithms to define the design parameters related to geometry and controller. A test case describes the design of an induction heating system for a polyurethane molding process, which is the soles foaming. This case study deals with the multiobjective optimization of parameters such as the geometrical dimensions, the inductor sizing, and the controller setting. The multi-objective optimization aims to reduce the energy consumption and to increase the wall temperature of the mold.

The paper proposes a methodological approach to support the multi-objective (i.e. cost and structural performance) optimization of complex systems, typical of the oil & gas sector. The complexity is managed through a double-level of optimization. The first one, based on simplified product models (1-D and 0-D), considers an analytical approach for the structural behavior and a parametric one for the cost estimation. The second level considers the use of a 3-D FEM solver for structural simulations, and an analytical tool for the cost estimation. As case study, the paper proposes the design optimization of an oil & gas chimney for gas turbines. The workflow analyzed during the case study describes the use of a multi-objective and multilevel approach to optimize cost, weigh, and structural behavior of oil & gas ducts.

The market of the hybrid electric vehicles has been increasing for several years. Different commercial EV and PHEV solutions are available for passenger cars and light vehicles for freight deliveries. However, the market of heavy trucks still regards traditional ICE vehicles powered by diesel oil fuel. The recent interest for electric solutions have been pushing the development of the hybrid solutions, but only micro-hybrid systems are considered feasible for heavy truck applications. The proposed research aims to define a methodological approach with a virtual model in order to simulate the behavior of a hybrid heavy truck. The scope of this research is the feasibility analysis of a retrofit hybrid heavy truck. A real driving cycle has been used in order to obtain reliable results in terms of cost, energy consumption and gas emission. The layout of the hybrid system has been proposed as well as the sizing of battery and electric motor. A commercial tool has been used for the vehicle modelling and simulation. As a test case, an 18-ton truck has been analyzed with a 10-liter diesel engine. Firstly, the simulation of the diesel truck has been reproduced considering the real driving cycle data. Secondly, the simulation activity has been focused on the evaluation of the hybrid system behavior by investigating different battery sizes with the same boundary conditions related to the real driving cycle.

Nowadays in many industrial applications, i.e. electrical household appliances, it is necessary to have a robust and safe control for some variables involved in the analysis of the performances of different products. In addition, the recent ecodesign directives require products increasingly eco-friendly and eco-efficient, preserving high-performance but a low power consumption. For these reasons, the physical prototypes of products require many expensive and complex tests in term of time, resources and qualified personnel involved. To overcome these limitations, the proposed approach is focused on the use of virtual prototyping tools, which support and reduce the expensive physical experiments. The main objective of this paper is the development, implementation and testing of an innovative methodology, which could be an improvement for the sustainable design of induction hobs. Induction heating applied to the domestic cooking has significantly evolved since the first cooking hobs appeared. Different issues such as maximum power available for heating a pot, dimensional compactness of the hobs, or inverter electronics efficiency have achieved a great development. The proposed methodology provides the development of a multi-physic model which is able to estimate the efficiency of the induction hobs starting from the design data of the project. In particular, the multi-physic model is composed by an electromagnetic simulation and a thermal simulation. The electromagnetic simulation, starting from electrical values such as voltage, current and frequency, is able to simulate the eddy current induced in the bottom of the pot, and resistance leads to the Joulean heating of the material. The thermal simulation is able to measure the energy consumption during the operational phase and the temperature reached by the materials. Therefore, the thermal power obtained by the Joulean heating is, at the same time, the output of the electromagnetic simulation and the input of the thermal one. The proposed model can be applied to design product and simulate the performance considering different operating conditions such as different types of cookers, different coils and different materials. Through the use of virtual prototyping tools is possible to control the heat flux on the whole system (stove, pot, water), and to evaluate the energy efficiency during the operational phase. The proposed tool makes the productengineer more aware about decision-making strategies in order to achieve an energy saving, calculated over the whole life cycle.