Implementation of a cogeneration plant for a food processing facility. A case study

The present work presents an investigation regarding the feasibility analysis of a cogeneration plant for a food processing facility with the aim to decrease the cost of energy supply. The monthly electricity and heat consumption profiles are analyzed, in order to understand the consumption profiles, as well as the costs of the current furniture of electricity and gas. Then, a detailed thermodynamic model of the cogeneration cycle is implemented and the investment costs are linked to the thermodynamic variables by means of cost functions. The optimal electricity power of the co-generator is determined with reference to various investment indexes. The analysis highlights that the optimal dimension varies according to the chosen indicator, therefore it is not possible to establish it univocally, but it depends on the financial/economic strategy of the company through the considered investment index

Optimal Regulation Criteria for Building Heating System by Using Lumped Dynamic Models

Abstract Energy efficiency of buildings has gained an important role with respect to possible energy saving policy measures, mainly for space heating demand which represents the dominant energy end-use. The present contribution addresses the problem of estimating building heating energy consumptions by using numerical models able to simulate the dynamic interaction between the building and the heating system. A dynamic numerical code in the Engineering Equation Solver (EES) is developed to simulate both building and heating system and the influence of heating system regulation criteria on different parameters (mainly energy saving and internal comfort) is investigated in an optimization perspective

Markerless 3D human pose tracking through multiple cameras and AI: Enabling high accuracy, robustness, and real-time performance

Tracking 3D human motion in real-time is crucial for numerous applications across many fields. Traditional approaches involve attaching artificial fiducial objects or sensors to the body, limiting their usability and comfort-of-use and consequently narrowing their application fields. Recent advances in Artificial Intelligence (AI) have allowed for markerless solutions. However, most of these methods operate in 2D, while those providing 3D solutions compromise accuracy and real-time performance. To address this challenge and unlock the potential of visual pose estimation methods in real-world scenarios, we propose a markerless framework that combines multi-camera views and 2D AI-based pose estimation methods to track 3D human motion. Our approach integrates a Weighted Least Square (WLS) algorithm that computes 3D human motion from multiple 2D pose estimations provided by an AI-driven method. The method is integrated within the Open-VICO framework allowing simulation and real-world execution. Several experiments have been conducted, which have shown high accuracy and real-time performance, demonstrating the high level of readiness for real-world applications and the potential to revolutionize human motion capture.Comment: 19 pages, 7 figure

Toward Autonomous Guidance and Control: A Robust AI-Based Solution for Low-Thrust Orbit Transfers

The focus of our initial application scenario centers around a low-thrust orbit transfer in Low-Earth Orbit (LEO). This specific use-case has been chosen due to its inherent challenges, including the requirements for robustness and real-time computation. We propose an AI-based solution capable of autonomous and robust on-board G&C. The core of our approach leverages a Deep Neural Network (DNN) trained through Reinforcement Learning (RL) techniques. Our method aims at enhancing a traditional guidance approach by managing environmental perturbations, it processes the on-board navigation coordinates and provides the thrust to be imposed by the propulsion subsystem. Our approach demonstrates effectiveness in performing maneuvers changing semi-major axis (SMA), eccentricity (ECC), and inclination (INC), operating continuously with a control horizon of several days. Robustness is tested by using physical model uncertainties, introducing disturbances in the mission coordinates, and injecting perturbations in subsystems

Paroxysmal Atrial Fibrillation Triggered By A Monomorphic Ventricular Couplet In A Patient With Acute Coronary Syndrome

Atrial fibrillation is a common arrhythmia in patients suffering from acute myocardial infarction, however its pathophysiological mechanisms are not fully understood. We describe the unusual case of a 76-year old woman admitted for non-ST-segment elevation myocardial infarction, who developed multiple episodes of paroxysmal atrial fibrillation triggered by monomorphic ventricular couplets. Beta-blocking and amiodarone therapy resulted efficacious in preventing arrhythmic recurrences. We then discuss the possible arrhythmogenic mechanisms, with special emphasis on the unique electrophysiological, hemodynamic, cellular and anatomical milieu created by acute myocardial ischemia

Selectivity-permeability optimization of functionalised CNT-polymer membranes for water treatment:A modeling study

Polymer membranes incorporating carbon nanotubes (CNT) belong to two broad categories: Vertically aligned (VA-CNT) membranes, where the polymer acts solely as a matrix embedding an aligned forest of nanotubes, and thin film composite (CNT-TFC) membranes which incorporate randomly aligned nanotubes in their selective layer. The former can achieve orders-of-magnitude higher permeability than many commercial membranes but cannot be scaled up industrially. The latter are based on commercial technology but provide only modest flux increases. Furthermore, filtration in VA-CNT is based on steric hindrance determined by the tubes' diameter, whereas in CNT-TFCs, the tubes are embedded in the polymer with selectivity given by the polymer alone. In this work, a novel computational method to optimize the selectivity-permeability of an ideal CNT membrane encompassing the advantages of VA-CNTs and CNT-TFCs is presented. In analogy to the former, the tubes are all aligned with the membrane selectivity provided by their diameter; to the latter, the polymer matrix also contributed to the total membrane permeability. As nanotubes with larger internal diameter would provide higher flow, ab-initio modeling was used to improve their selectivity by functionalizing the tips of large multiwall nanotubes with PIM-1 monomers, achieving simultaneously an increase in selectivity toward small molecules (e.g. rac-fluoxetine, glucose, ethanol and water) and an increase in permeability (due to the large diameter). Results show up to 3 orders of magnitude increase in water permeability compared to a CNT-TFC membrane in the literature with randomly oriented tubes of comparable size and an increase in rejection of a factor of 2.5 and 2, for rac-fluoxetine and glucose, respectively, compared to water. The proposed methodology is of general use and requires no fitting parameters, only the chemical structure of the solutes to test and the tubes' geometry</p

Seasonal River Discharge Forecasting Using Support Vector Regression: A Case Study in the Italian Alps

In this contribution we analyze the performance of a monthly river discharge forecasting model with a Support Vector Regression (SVR) technique in a European alpine area. We considered as predictors the discharges of the antecedent months, snow-covered area (SCA), and meteorological and climatic variables for 14 catchments in South Tyrol (Northern Italy), as well as the long-term average discharge of the month of prediction, also regarded as a benchmark. Forecasts at a six-month lead time tend to perform no better than the benchmark, with an average 33% relative root mean square error (RMSE%) on test samples. However, at one month lead time, RMSE% was 22%, a non-negligible improvement over the benchmark; moreover, the SVR model reduces the frequency of higher errors associated with anomalous months. Predictions with a lead time of three months show an intermediate performance between those at one and six months lead time. Among the considered predictors, SCA alone reduces RMSE% to 6% and 5% compared to using monthly discharges only, for a lead time equal to one and three months, respectively, whereas meteorological parameters bring only minor improvements. The model also outperformed a simpler linear autoregressive model, and yielded the lowest volume error in forecasting with one month lead time, while at longer lead times the differences compared to the benchmarks are negligible. Our results suggest that although an SVR model may deliver better forecasts than its simpler linear alternatives, long lead-time hydrological forecasting in Alpine catchments remains a challenge. Catchment state variables may play a bigger role than catchment input variables; hence a focus on characterizing seasonal catchment storage—Rather than seasonal weather forecasting—Could be key for improving our predictive capacity.JRC.H.1-Water Resource

A novel TRNSYS type for short-term borehole heat exchanger simulation: B2G model

[EN] Models of ground source heat pump (GSHP) systems are used as an aid for the correct design and optimization of the system. For this purpose, it is necessary to develop models which correctly reproduce the dynamic thermal behavior of each component in a short-term basis. Since the borehole heat exchanger (BHE) is one of the main components, special attention should be paid to ensuring a good accuracy on the prediction of the short-term response of the boreholes. The BHE models found in literature which are suitable for short-term simulations usually present high computational costs. In this work, a novel TRNSYS type implementing a borehole-to-ground (B2G) model, developed for modeling the short-term dynamic performance of a BHE with low computational cost, is presented. The model has been validated against experimental data from a GSHP system located at Universitat Politecnica de Valencia, Spain. Validation results show the ability of the model to reproduce the short-term behavior of the borehole, both for a step-test and under normal operating conditions. (C) 2015 Elsevier Ltd. All rights reserved.The present work has been supported by the FP7 European project Advanced ground source heat pump systems for heating and cooling in Mediterranean climate (GROUND-MED).De Rosa, M.; Ruiz Calvo, F.; Corberán Salvador, JM.; Montagud Montalvá, CI.; Tagliafico, L. (2015). A novel TRNSYS type for short-term borehole heat exchanger simulation: B2G model. Energy Conversion and Management. 100:347-357. https://doi.org/10.1016/j.enconman.2015.05.021S34735710

Retrieval and intercomparison of volcanic SO2 injection height and eruption time from satellite maps and ground-based observations

Syneruptive gas flux time series can, in principle, be retrieved from satellite maps of SO2 collected during and immediately after volcanic eruptions, and used to gain insights into the volcanic processes which drive the volcanic activity. Determination of the age and height of volcanic plumes are key prerequisites for such calculations. However, these parameters are challenging to constrain using satellite-based techniques. Here, we use imagery from OMI and GOME-2 satellite sensors and a novel numerical procedure based on back-trajectory analysis to calculate plume height as a function of position at the satellite measurement time together with plume injection height and time at a volcanic vent location. We applied this new procedure to three Etna eruptions (12 August 2011, 18 March 2012 and 12 April 2013) and compared our results with independent satellite and ground-based estimations. We also compare our injection height time-series with measurements of volcanic tremor, which reflects the eruption intensity, showing a good match between these two datasets. Our results are a milestone in progressing towards reliable determination of gas flux data from satellite-derived SO2 maps during volcanic eruptions, which would be of great value for operational management of explosive eruptions.1) European Research Council under the European Union's Seventh Framework Programme (FP/2.007-2013)/ERC Grant Agreement no. 279802, project 283 CO2Volc. 2) MEDiterranean SUpersite Volcanoes 280 (MED-SUV) WP 3.3.3Published79-915V. Dinamica dei processi eruttivi e post-eruttiviJCR Journa