With the proportional reduction of MOSFET size, the leakage-to-barrier reduction (DIBL) effect leads to a more significant increase in the tunneling current on the gate, and the appearance of the gate tunneling current also seriously affects the static characteristics of the device. In this paper, a new theoretical model of the relationship between the direct tunneling current and the thickness of the oxide layer under the DIBL effect is proposed for the MOSFET device with ultra-thin oxide layer. On this basis, the characteristics of the MOSFET device are studied in detail by using HSPICE, and their working conditions are quantitatively analyzed. The characteristic variation trend of small-size devices under the influence of gate tunneling current is predicted. The simulation results using BSIM4 model are consistent with the theoretical model. The theory and data in this paper will provide useful reference for large scale integrated circuit design.

The application of naturally ventilated pig buildings (NVPBs) with outdoor exercise yards is on the rise mainly due to animal welfare considerations, while the issue of emissions from the buildings to the surrounding environment is important. Since air pollutants are mainly transported by airflow, the knowledge on the airflow characteristics downwind the building is required. The objective of this research was to investigate airflow properties downwind of a NVPB with a roofed outdoor exercise yard for roof slopes of 5°, 15°, and 25°. Air velocities downwind a 1:50 scaled NVPB model were measured using a Laser Doppler Anemometer in a large boundary layer wind tunnel. A region with reduced mean air velocities was found along the downwind side of the building with a distance up to 0.5 m (i.e. 3.8 times building height), in which the emission concentration might be high. It was found that a smaller roof slope (i.e. 5° slope) resulted in a higher and shorter wake zone and thus a shorter air pollutant dispersion distance. It was concluded that a smaller roof slope could contribute to the dilution of air pollutants and a lower air pollutant concentration near the ground.

Every intervention of planning, implementation, and monitoring of agricultural and agri-environmental policies requires assessment tools that should have the characteristics of relevance, completeness, interpretability, data quality, efficiency, and overlapping. Despite the extensive selection of bibliographies and numerous projects designed to develop agri-environmental indicators necessary for assessing the sustainability of new policies, it is difficult to have an integrated and updated set of indicators available, which can be an effective and practical application tool to assists policymakers, researchers, and actors in policy design, monitoring and impact assessment. Particularly, such need is pressing to face the new environmental challenges imposed by the upcoming European Union Green Deal on the Common Agricultural Policy (CAP) post 2023. This study, therefore, aims to fill this gap by proposing a selection methodology and different pools of agri-environmental indicators differentiated based on a scale approach (crop-farm-district-region). Furthermore, we have attempted to validate our approach by quantifying selected indicators for a specific evaluation necessity, represented in this case by an assessment of environmental impact of land use change induced by CAP greening requirements in the Northern Italy context. Results of this validation show original crops’ impacts comparison, but also highlight great knowledge gaps in the available literature.

Aerodynamic performance of a floating offshore wind turbine (FOWT) is significantly influenced by platform surging motions. Accurate prediction of the unsteady aerodynamic loads is imperative for determining the fatigue life, ultimate loads on key components such as FOWT rotor blades, gearbox and power converter. The current study examines the predictions of numerical codes by comparing with unsteady experimental results of a scaled floating wind turbine rotor. The influence of platform surge amplitude together with the tip speed ratio on the unsteady aerodynamic loading has been simulated through unsteady CFD. It is shown that the unsteady aerodynamic loads of FOWT are highly sensitive to the changes in frequency and amplitude of the platform motion. Also, the surging motion significantly influences the windmill operating state due to strong flow interaction between the rotating blades and generated blade-tip vortices. Almost in all frequencies and amplitudes, CFD, LR-BEM and LR-uBEM predictions of mean thrust shows a good correlation with experimental results.

This paper presents a steady-state and transient heat conduction analysis framework using the polygonal scaled boundary finite element method (PSBFEM) with polygon/quadtree meshes. The PSBFEM is implemented with commercial finite element code Abaqus by the User Element Subroutine (UEL) feature. The detailed implementation of the framework, defining the UEL element, and solving the stiffness/mass matrix by the eigenvalue decomposition are presented. Several benchmark problems from heat conduction are solved to validate the proposed implementation. Results show that the PSBFEM is reliable and accurate for solving heat conduction problems. Not only can the proposed implementation help engineering practitioners analyze the heat conduction problem using polygonal mesh in Abaqus, but it also provides a reference for developing the UEL to solve other problems using the scaled boundary finite element method.

The first objective of this paper is to investigate the scaling behavior of liquid-vapor phase transition in FCC and BCC metals starting from the zero-temperature four-parameter formula for cohesive energy. The effective potentials between the atoms in the solid are determined using lattice inversion techniques as a function of scaling variables in the above formula. These potentials are split into repulsive and attractive parts as per the Weeks-Chandler-Anderson prescription, and used in the coupling-parameter expansion for solving the Ornstein-Zernike equation supplemented with an accurate closure. Thermodynamic quantities obtained via the correlation functions are used to obtain critical point parameters and liquid-vapor phase diagrams. Their dependence on the scaling variables in the cohesive energy formula are also determined. Equally important second objective of the paper is to revisit coupling parameter expansion for solving the Ornstein-Zernike equation. The Newton-Armijo non-linear solver and Krylov-space based linear solvers are employed in this regard. These methods generate a robust algorithm that can be used to span the entire fluid region, except very low temperatures. Accuracy of the method is established by comparing the phase diagrams with those obtained via computer simulation. Avoidance of the 'no-solution-region' of Ornstein-Zernike equation in coupling-parameter expansion is also discussed. Details of the method and the complete algorithm provided here would make this technique more accessible to researchers investigating thermodynamic properties of one component fluids.

This article introduces a new way of using a Fibre Bragg Grating (FBG) sensor for detecting the presence and number of occupants in the monitored space in a Smart Home (SH). CO₂ sensors are used to determine the CO₂ concentration of the monitored rooms in an SH. CO₂ sensors can also be used for occupancy recognition of the monitored spaces in SH. To determine the presence of occupants in the monitored rooms of the SH, the newly devised method of CO₂ prediction, by means of an Artificial Neural Network (ANN) with a Scaled Conjugate Gradient (SCG) algorithm using measurements of typical operational technical quantities (indoor temperature, relative humidity indoor and CO₂ concentration in the SH) is used. The goal of the experiments is to verify the possibility of using the FBG sensor in order to unambiguously detect the number of occupants in the selected room (R104) and, at the same time, to harness the newly proposed method of CO₂ prediction with ANN SCG for recognition of the SH occupancy status and the SH spatial location (rooms R104, R203, and R204) of an occupant. The designed experiments will verify the possibility of using a minimum number of sensors for measuring the non-electric quantities of indoor temperature and indoor relative humidity and the possibility of monitoring the presence of occupants in the SH using CO₂ prediction by means of the ANN SCG method with ANN learning for the data obtained from only one room (R203). The prediction accuracy exceeded 90% in certain experiments. The uniqueness and innovativeness of the described solution lie in the integrated multidisciplinary application of technological procedures (the BACnet technology control SH, FBG sensors) and mathematical methods (ANN prediction with SCG algorithm, the Adaptive Filtration with of LMS algorithm) employed for the recognition of number persons and occupancy recognition of selected monitored rooms of SH.