Mountain regions and the important ecosystem services they provide are considered to be very vulnerable to the current warming, and recent studies suggest that high-mountain environments experience ...more rapid changes in temperature than environments at lower elevations. Here we analysed weather records for the period 1975-2010 from the Eastern Italian Alps that show that warming occurred both at high and low elevations, but it was less pronounced at high elevations. This negative elevation-dependent trend was consistent for mean, maximum and minimum air temperature. Global radiation data measured at different elevations, surface energy fluxes measured above an alpine grassland and above a coniferous forest located at comparable elevations for nine consecutive years as well as remote sensing data (MODIS) for cloud cover and aerosol optical depth were analysed to interpret this observation. Increasing global radiation at low elevations turned out to be a potential driver of this negative elevation-dependent warming, but also contributions from land use and land cover changes at high elevations (abandonment of alpine pastures, expansion of secondary forest succession) were taken into account. We emphasise though, that a negative elevation-dependent warming is not universal and that future research and in particular models should not neglect the role of land use changes when determining warming rates over elevation.
Vegetation has a substantial impact on the local climate. Land cover changes through afforestation or deforestation can amplify or mitigate climate warming by changes in biophysical and ...biogeochemical mechanisms. In the montane to subalpine area of the Eastern Alps in Europe, where forests have constantly expanded in the last four decades, data of meteorological stations show a consistent reduction in incoming global radiation for the period 2000-2015. To assess the potential role of forests in contributing to such a reduction, three site pairs in Central Europe with neighbouring forest and non-forest sites were analysed. In all the pairs, a lower amount of incoming radiation was recorded at the forest site. When biophysical mechanisms such as albedo, surface roughness and Bowen ratio changes were modelled together with changes in global radiation, the total radiative forcing accounted for a rate of change in air temperature was equal to 0.032 °C ± 0.01 °C per Wm−2. These results suggest that local climate is influenced by land cover change through afforestation both via albedo and radiation feedbacks but also by means of indirect biophysical and species-dependent mechanisms. The data obtained for the site pairs in Central Europe are finally discussed to infer the occurrence of similar forest-driven effects in the Eastern Alps which may explain part of the solar dimming observed in high elevation weather stations.
In this paper, the problem of improving the performance of a discharge air temperature (DAT) system using a PID controller and augmenting it with neural network based tuning and tracking functions is ...explored. The DAT system is modeled as a SISO (single input single output) system. The architecture of the real time neuro-PID controller and simulation results obtained under realistic operating conditions are presented. The neural network assisted PID tuning method is simple to implement. Results show that the network assisted PID controller is able to track both constant and variable set point trajectories efficiently in the presence of disturbances acting on the DAT system.
Nowadays to monitor and to control the recent generation of high complexity Heating Ventilation Air Conditioning (HVAC) building systems under a wide variety of occupancy and load related operating ...conditions represents one of the most difficult and challenging task. The main objective of this study is to develop a new approach of the fault detection, diagnosis and isolation (FDDI) automated techniques applied to the valve actuator failures in HVAC systems. These techniques are based on the dual Extended Kalman Filter that combines state estimation and parameter estimation to detect the faulty valve (stuck opened and stuck closed), to determine the fault severity and finally to isolate it. The superiority of this approach is its simplicity and its application to a wide range of similar applications. This algorithm is implemented in a simulation environment, and the fault diagnosis results could be evaluated for a several fault scenarios in terms of the injection fault, detection time, and its severity.
Nanofilled polymeric matrices have demonstrated remarkable mechanical, electrical, and thermal properties. Compounding polymers with nanofiller is widely used for the preparation of new materials. ...Polyamide/polypropylene (PA/PP) composites are interesting because both components are relatively cheap, with advantageous properties, and are processable by melt blending. The compatibilisation of binary polymer compounds can be made by the addition of graft copolymer, segments of which have physical or chemical affinity with two immiscible homopolymers. In this case, polypropylene grafted with maleic anhydride (PP-g-MA) it was used. Polymer nanocomposites containing graphite have been considered as a new generation of composites materials due to their expected unique properties attributed to the high aspect ratio of the inorganic pellets. Combined effects of graphite treatment and compatibilizer polymers (PP-g-MA) on the structure and properties of PA/PP/PP-g-MA/graphene oxide composites were studies. The optimum formulation was used to prepare a series of nanocomposites under different technological conditions. The nanocomposites PA/PP/PP-g-MA/graphene oxide were characterized by scanning electron microscopy (SEM), Fourier transformation infrared spectrum (FT-IR) and physico-mechanical.
Nonlinear neuro-models for a discharge air temperature (DAT) system are developed. Experimental data gathered in a heating ventilating and air conditioning (HVAC) test facility is used to develop ...multi-input multi-output (MIMO) and single-input single-output (SISO) neruo-models. Several different network architectures were explored to build the models. Results show that a three layer second order neural network structure is necessary to achieve good accuracy of the predictions. Results from the developed models are compared, and some observations on sensitivity and standard deviation errors are presented.
In this paper, we propose to use as an alternative to Extended Kalman Filter Estimator (EKFE), the joint version of Unscented Kalman Filter (UKF) Estimator (UKFE) to solve simultaneously the state ...and parameter estimation problems, suitable integrated in our proposed Fault Detection and Diagnosis (FDDI) strategy. This strategy is useful to monitor and to control the recent generation of high complexity Heating Ventilation Air Conditioning (HVAC) building systems under a wide variety of occupancy and load related operating conditions that represents one of the most difficult and challenging task. The main objective of this study is to develop a new approach of the fault detection, diagnosis and isolation (FDDI) automated techniques applied to the valve actuator failures in HVAC systems. Our approach is based on the Joint Unscented Kalman Filter (JUKF) as a suitable alternative to the Extended Kalman Filter Estimator (EKFE) due to its superiority compared to that. In UKF joint approach the state space dynamics is augmented by the dynamics of the faulty parameters to detect and isolate the faulty valve (stuck opened and stuck closed), and also to determine the fault severity. The simulations results reveal similar performance compared to EKFE, namely its accuracy and robustness to the changes in the system structure. The superiority of this approach is its capability to deal with the nonlinear dynamics of the system, compared to EKFE that is based on the linearization of the nonlinear dynamics computing Jacobean matrices. This algorithm is implemented in a simulation environment, and the fault diagnosis results could be evaluated for a several fault scenarios in terms of the injection fault, detection time, and its severity.
Monitoring and controlling the modern and sophisticated heating ventilation air conditioning (HVAC) building systems under a wide variety of occupancy and load related operating conditions represents ...a difficult and challenging task. Their complexity drastically increases and the control becomes more difficult task due to the several control loops that interact between them. The main objective of this study is to compare the performance of the automated strategies for fault detection, diagnosis and isolation (FDDI) based on frequency and spectral analysis (FA) of the system response, and an interactive multiple model (IMM), based on the unscented Kalman Filter (UKF) estimation technique to the problem of fault detection diagnosis and isolation (FDDI) of the valve actuator failures in discharge air temperature (DAT) loop of the HVAC systems. The both techniques are HVAC model-driven based and the simulations results reveal the superiority of the interactive multiple model based on unscented Kalman filter estimation algorithm (IMM_UKF) concerning its accuracy and robustness to the changes in the system structure parameters. These algorithms are implemented in a simulation environment, and the fault diagnosis results are presented for a several fault scenarios in terms of mode probabilities and active fault index. From the preliminaries simulations, for different scenarios we found that the IMM_UKF algorithm is robust to the choice of the matrix probability and to the small changes in process and measurement noise level, result that is confirmed in the literature.
Nowadays monitoring and controlling the modern and sophisticated heating ventilation air conditioning (HVAC) building systems under a wide variety of occupancy and load related operating conditions ...is becoming a difficult and challenging task. Their complexity drastically increases and the control becomes more difficult task due to the several control loops that interact between them. Among these control loops the discharge air temperature (DAT) loop, the static pressure loop (SP), and the variable air volume (VAV) terminal unit loop are the candidate loops requiring frequent re-tuning. Equipment failures and loss of control leading to less than acceptable indoor environment conditions is a common problem reported in these systems. In our paper we consider the degradation in the DAT loop performance caused by a gradual increase in backlash of the valve actuator. The main objective of this paper is to describe the application of an interactive multiple model (IMM) based on the unscented Kalman filter (UKF) estimation algorithm (IMMUKF) to the problem of fault detection diagnosis and isolation (FDDI) of the valve actuator failures in DAT loop of the HVAC systems. The proposed algorithm is an alternative to the interactive multiple model (IMM) developed in the literature based on the extended Kalman filter standard technique, the most popular estimation technique used in the last 40 years. The main advantage of the proposed algorithm is the less computation, consequently more faster, high accuracy, robustness and eliminates completely the linearization of the system dynamics
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