Energy Retrofit of a Historic Building Using Simplified Dynamic Energy Modeling

Energy retro-commissioning of historical buildings is an important challenge that implies both historic-artistic and technological aspects concerning the improvement in energy efficiency and comfort. A critical analysis of each possibility is essential in order to preserve the balance between efficiency and architecture. The research focuses on a historical building owned by ANCE (Associazione Nazionale Costruttori Edili), situated in Rome in the Nomentano district. Retrofitting hypothesis were made in order to improve HVAC systems, building's envelope and building's management, always respecting its architectural features. An energy audit has been done in order to evaluate the possibilities. The first step of the study consisted of a measure campaign conducted by Avvenia to know more about the actual use of the building. Next, a dynamic simplified energy modeling of the building has been built using the software Archi Energy. This allowed to preview the effect of modifications on the HVAC and envelope systems. Although starting from an original medium energy performance, simulations showed that it would be possible to reach a further reduction of energy needs by making simple changes in the management/controls domain and, with higher costs, by upgrading envelope components. This study shows that a correct approach can lead to both relevant energetic results and the conservation of architectural characteristics of historical buildings

The Role of Data in Model Building and Prediction: A Survey Through Examples

The goal of Science is to understand phenomena and systems in order to predict their development and gain control over them. In the scientific process of knowledge elaboration, a crucial role is played by models which, in the language of quantitative sciences, mean abstract mathematical or algorithmical representations. This short review discusses a few key examples from Physics, taken from dynamical systems theory, biophysics, and statistical mechanics, representing three paradigmatic procedures to build models and predictions from available data. In the case of dynamical systems we show how predictions can be obtained in a virtually model-free framework using the methods of analogues, and we briefly discuss other approaches based on machine learning methods. In cases where the complexity of systems is challenging, like in biophysics, we stress the necessity to include part of the empirical knowledge in the models to gain the minimal amount of realism. Finally, we consider many body systems where many (temporal or spatial) scales are at play and show how to derive from data a dimensional reduction in terms of a Langevin dynamics for their slow components

An optimum design of the magnetic circuit of a PM linear electrical generator for the exploitation of sea waves.

In this paper an approach to the optimization of the magnetic design of a Permanent Magnet (PM) linear generator for the exploitation of the energy contained in sea waves is presented. This approach consists of a two step procedure: the first one takes into account the stochastic features of the sea wave motion and describe the working condition of the machine under this motion by adopting a lumped parameter model. In this step the objective function is the energy production. The second step optimizes the generator by using the results obtained in the first step as the constraints that must be fulfilled by a design based on a Finite Element Method (FEM) analysis. Furthermore, the approach is applied to design and build a PM linear generator. Some experimental tests carried on the built linear generator are presented

The role of data in model building and prediction: a survey through examples

The goal of Science is to understand phenomena and systems in order to predict their development and gain control over them. In the scientific process of knowledge elaboration, a crucial role is played by models which, in the language of quantitative sciences, mean abstract mathematical or algorithmical representations. This short review discusses a few key examples from Physics, taken from dynamical systems theory, biophysics, and statistical mechanics, representing three paradigmatic procedures to build models and predictions from available data. In the case of dynamical systems we show how predictions can be obtained in a virtually model-free framework using the methods of analogues, and we briefly discuss other approaches based on machine learning methods. In cases where the complexity of systems is challenging, like in biophysics, we stress the necessity to include part of the empirical knowledge in the models to gain the minimal amount of realism. Finally, we consider many body systems where many (temporal or spatial) scales are at play-and show how to derive from data a dimensional reduction in terms of a Langevin dynamics for their slow components

Understanding causation via correlations and linear response theory

In spite of the (correct) common-wisdom statement correlation does not imply causation, a proper employ of time correlations and of fluctuation-response theory allows to understand the causal relations between the variables of a multi-dimensional linear Markov process. It is shown that the fluctuation-response formalism can be used both to find the direct causal links between the variables of a system and to introduce a degree of causation, cumulative in time, whose physical interpretation is straightforward. Although for generic non-linear dynamics there is no simple exact relationship between correlations and response functions, the described protocol can still give a useful proxy also in presence of weak nonlinear terms

Modello per la valutazione energetica di grandi patrimoni edilizi

Il gruppo di ricerca cui appartengo è impegnato da lungo tempo in studi nel campo dell’efficienza energetica dei sistemi edificio/impianto. In questo campo le problematiche di calcolo sono spesso complesse ed interessano al tempo stesso aspetti termici, elettrici, illuminotecnici, economici, di comfort, ecc. E’ dunque imprescindibile l’utilizzo di supporti informatici in grado di svolgere i calcoli rapidamente e accuratamente. Su questo punto si è da sempre ravvisata la mancanza di un software in grado di soddisfare adeguatamente le molteplici esigenze richieste, specialmente nel caso in cui debbano essere valutate soluzioni innovative che non trovano già larga applicazione nella pratica. E’ stato quindi sviluppato un nuovo software personalizzato, chiamato Archi‐Energy, ritagliato sulle esigenze specifiche del mondo della ricerca e con caratteristiche open‐source che permettono un potenziale e continuo contributo dall’intera comunità scientifica. Le applicazioni del software possono essere le più svariate. Il primo studio di grande rilevanza eseguito con una versione iniziale di Archi‐Energy ha riguardato la valutazione energetica dei fabbisogni energetici dell’edilizia residenziale della città di Roma. Questo studio è stato inserito nel Piano d’Azione di Roma per l’Efficienza Energetica (SEAP ‐ Sustainable Energy Action Plan), realizzato con il patrocinio dell’esimio Prof. Jeremy Rifkin e approvato dalla giunta comunale di Roma Capitale il 19 Ottobre 2011. Grazie ad un’elaborazione dei dati aggregati disponibili, è stato possibile effettuare una modellazione energetica dell’intera città di Roma. Ciò ha permesso di individuare i “punti deboli” energetici e selezionare gli interventi di riqualificazione maggiormente efficaci ed economicamente sostenibili. L’aggiunta di logiche evolutive, basate sulle statistiche di accrescimento della città nonché di intervento sul patrimonio esistente, ha permesso anche di prevedere i possibili sviluppi futuri dei fabbisogni energetici e delle relative emissioni di CO2. E’ stato dunque possibile mettere in relazione l’evoluzione dell’impatto ecologico della città con l’entità degli interventi di efficienza energetica che verranno realizzati e quindi, indirettamente, con l’orientamento politico in fatto di incentivazione. In base a tali valutazioni si è arrivati ad individuare le azioni necessarie per il raggiungimento dell’obiettivo di riduzione dell’emissione di gas serra del 20% entro il 2020 a cui si è impegnata la città di Roma il 4 Maggio 2010 aderendo al Patto dei Sindaci. Le azioni individuate non solo permettono il raggiungimento di tale impegno, ma determinano anche il minor aggravio economico per la collettività, poiché sono frutto di uno studio di ottimizzazione energetico/economica degli interventi. In base a quanto detto si ritiene che il lavoro di ricerca svolto possa essere di ausilio sia alle amministrazioni pubbliche per individuare le modalità di raggiungimento degli obiettivi energetici prefissati, sia a ricercatori, professionisti o semplici privati per valutare le prestazioni energetiche degli edifici confrontando diverse soluzioni, anche innovative, dal punto di vista non solo energetico ma anche economic

A neural network model for explaining the asymmetries between linguistic production and linguistic comprehension

Several kinds of empirical evidence point to the existence of an asymmetry between linguistic production and linguistic comprehension: in general, understanding words seems to be easier than producing them. In this contribution we propose a neural model of the relationships between the semantic and the lexical systems. Our model explains the asymmetry between language comprehension and production as an effect of the difference between the dimensions of the brain areas which process semantic and lexical information. In fact, the model\u27s performance in lexical recall is worse than the performance in semantic recall due to the fact that the semantic network is constituted of more computational units (neurons) then the lexical network

Extracting causation from millennial-scale climate fluctuations in the last 800 kyr

The detection of cause-effect relationships from the analysis of paleoclimatic records is a crucial step to disentangle the main mechanisms at work in the climate system. Here, we show that the approach based on the generalized Fluctuation-Dissipation Relation, complemented by the analysis of the Transfer Entropy, allows the causal links to be identified between temperature, CO2 concentration and astronomical forcing during the glacial cycles of the last 800 kyr based on Antarctic ice core records. When considering the whole spectrum of time scales, the results of the analysis suggest that temperature drives CO2 concentration, or that are both driven by the common astronomical forcing. However, considering only millennial-scale fluctuations, the results reveal the presence of more complex causal links, indicating that CO2 variations contribute to driving the changes of temperature on such time scales. The results also evidence a slow temporal variability in the strength of the millennial-scale causal links between temperature and CO2 concentration.Comment: 13 pages, 5 figures + Supplemental material (10 pages, 7 figures

What Do Agent-Based and Equation-Based Modelling Tell Us About Social Conventions: The Clash Between ABM and EBM in a Congestion Game Framework

In this work simulation-based and analytical results on the emergence steady states in traffic-like interactions are presented and discussed. The objective of the paper is twofold: i) investigating the role of social conventions in coordination problem situations, and more specifically in congestion games; ii) comparing simulation-based and analytical results to figure out what these methodologies can tell us on the subject matter. Our main issue is that Agent-Based Modelling (ABM) and the Equation-Based Modelling (EBM) are not alternative, but in some circumstances complementary, and suggest some features distinguishing these two ways of modeling that go beyond the practical considerations provided by Parunak H.V.D., Robert Savit and Rick L. Riolo. Our model is based on the interaction of strategies of heterogeneous agents who have to cross a junction. In each junction there are only four inputs, each of which is passable only in the direction of the intersection and can be occupied only by an agent one at a time. The results generated by ABM simulations provide structured data for developing the analytical model through which generalizing the simulation results and make predictions. ABM simulations are artifacts that generate empirical data on the basis of the variables, properties, local rules and critical factors the modeler decides to implement into the model; in this way simulations allow generating controlled data, useful to test the theory and reduce the complexity, while EBM allows to close them, making thus possible to falsify them.Agent-Based Modelling, Equation-Based Modelling, Congestion Game, Model of Social Phenomena

Khirbet Al-Batrawy in North-Central Jordan: New discoveries in the Early Bronze Age Palace, 2018-2020

After 16 seasons (2005-2020) of excavations and restorations at Khirbet al-Batrawy in north-central Jordan, a clear picture of the history of the site and its major monuments has been obtained. In the last three seasons, works by Sapienza University of Rome and the Department of Antiquities of the Hashemite Kingdom of Jordan resumed the exploration of the “Palace of the Copper Axes”, leading to the discovery of a monumental entrance hall and a further western wing. Many finds, including several imports from Egypt, Syria, Anatolia and farther east, allow us to understand the functioning and socio-economic role of the palace in the southern Levantine scenario of the Early Bronze Age, and contribute to a better definition of urbanism in this region of the ancient Near East