Sperimentazione di metodi per la previsione della domanda termica in applicazioni legate al teleriscaldamento

Con il presente lavoro di tesi si è fornita un'attenta analisi dei dati ed elaborazione di modelli predittivi per la stima della domanda termica in applicazioni legate al teleriscaldamento urbano.

Valutazione in opera ed in laboratorio della trasmissione laterale nelle tipologie edilizie italiane

L’attività di ricerca del dottorando è stata rivolta allo studio della trasmissione del rumore per via strutturale negli edifici. Questo argomento e' di notevole interesse sia fondamentale che applicativo. Il fenomeno e le problematiche ad essa connesse contribuiscono alla diminuzione delle prestazioni fonoisolanti, sia per le strutture verticali (usualmente valutate rispetto al rumore aereo), sia per quelle orizzontali (valutate anche rispetto al rumore impattivo) ed è tipico degli edifici con struttura portante a telaio e tamponatura in laterizi. Si tratta delle tipiche tipologie edilizie italiane, per le quali il problema risulta amplificato rispetto ad altre tipologie. La metodologia di studio è stata di tipo sperimentale. La scelta è dettata sia dall’insufficiente avanzamento dello stato dell’arte dei metodi di calcolo teorici, o delle loro versioni numeriche, sia dalla necessità di disporre di dati certi da confrontare con i valori forniti dai metodi previsionali semplificati indicati nelle norme UNI (modello CEN); infatti queste ultime sono un recepimento letterale di quelle europee, sebbene esse si basino su tipologie costruttive, materiali e tecniche di realizzazione differenti da quelle comunemente in uso in Italia; da qui la difformità di risultati tra formule previsionali e misurazioni sperimentali. Al fine di realizzare uno studio completo delle principali casistiche della trasmissione laterale sono state utilizzate 6 configurazioni in scala reale, con elementi edilizi diversamente collegati fra loro in modo da simulare i nodi strutturali comunemente realizzati negli edifici. La parte sperimentale della ricerca è stata svolta presso le “Camere Acustiche di Prova” del Laboratorio del Lazzaretto “R. Alessi” del DIENCA. Oltre alle usuali misurazioni di isolamento acustico, sono state eseguite numerose misurazioni di vibrazione. Infatti, dal confronto dei livelli di velocità di vibrazione dei diversi elementi di una struttura, rigidamente connessi, è possibile determinare l’indice di riduzione delle vibrazioni Kij che è la grandezza chiave per modellizzare il fenomeno della trasmissione laterale. La possibilità di determinare sperimentalmente tali valori nel contesto di un lavoro di ricerca finalizzato a determinare i meccanismi di propagazione delle vibrazioni nelle strutture, permette di valutare la precisione delle formule previsionali del modello CEN e di proporne varianti e integrazioni. I valori di Kij così determinati assumono grande importanza anche in fase di progetto, fornendo dati attendibili da utilizzare per la progettazione acustica degli edifici.

Studio dell'innesco di frane rapide in un'area campione dell'Appennino Bolognese

Il lavoro di tesi ha preso spunto da un fenomeno franoso avvenuto a Porretta Terme (provincia di Bologna), nell’autunno 2008, a causa di abbondanti precipitazioni, in tale occasione si innescò una colata rapida di detriti che invase la strada statale n. 64 e lambì la ferrovia che collega l’Emilia Romagna e la Toscana. I detriti colpirono anche un’abitazione, senza per fortuna causare perdite umane ne danni ingenti, ma l’evento riscosse numerose attenzioni da parte della popolazione locale, preoccupata che fenomeni del genere potessero ripetersi anche in altre zone e senza alcun preavviso. L’evento allertò anche la Protezione Civile regionale che da subito si interessò all’applicazione di metodi in grado di prevedere la suscettività areale da frane di questo tipo. Metodi previsionali per colate rapide sono stati sviluppati negli ultimi anni in diverse università sia in Europa sia negli Stati Uniti d’America. Lo scopo è quello di prevedere le possibili zone di innesco e individuare le soglie di precipitazione critica in modo da realizzare carte di suscettività a scopo di pianificazione territoriale e mitigazione del rischio. Il lavoro, durato diversi mesi, è passato attraverso diverse fasi. In primis si è proceduto a sopralluoghi di campo al fine di inquadrare l’area oggetto di studio dal punto di vista geologico e geomorfologico. Successivamente è stata svolta una fase di campionamento sul terreno; tramite una trivella manuale sono stati effettuati numerosi carotaggi (circa 60) sparsi sull’intero versante oggetto di studio, al fine di ricavare un dato relativo allo spessore del suolo. Inoltre sono stati raccolti dei campioni di terreno, analizzati successivamente in laboratorio al fine di ricavarne le curve granulometriche e alcuni dati caratterizzanti. Terminata la fase sul terreno, si è provveduto ad effettuare le prove di laboratorio (curve granulometriche, limiti di Attemberg, etc). Grazie ai dati raccolti, è stato possibile applicare un modello previsionale di stabilità superficiale, TRIGRS 2.0 basato sull’infiltrazione in un mezzo non saturo di una precipitazione di durata finita. Particolare attenzione è stata rivolta ai metodi per la previsione dello spessore del suolo (Z Model, S Model, Sexp Model) e alla loro influenza nella suscettività da frana superficiale.

Analisi critica di modelli previsionali per le frane in Emilia Romagna

Questa tesi di dottorato è inserita nell’ambito della convenzione tra ARPA_SIMC (che è l’Ente finanziatore), l’Agenzia Regionale di Protezione Civile ed il Dipartimento di Scienze della Terra e Geologico - Ambientali dell’Ateneo di Bologna. L’obiettivo principale è la determinazione di possibili soglie pluviometriche di innesco per i fenomeni franosi in Emilia Romagna che possano essere utilizzate come strumento di supporto previsionale in sala operativa di Protezione Civile. In un contesto geologico così complesso, un approccio empirico tradizionale non è sufficiente per discriminare in modo univoco tra eventi meteo innescanti e non, ed in generale la distribuzione dei dati appare troppo dispersa per poter tracciare una soglia statisticamente significativa. È stato quindi deciso di applicare il rigoroso approccio statistico Bayesiano, innovativo poiché calcola la probabilità di frana dato un certo evento di pioggia (P(A|B)) , considerando non solo le precipitazioni innescanti frane (quindi la probabilità condizionata di avere un certo evento di precipitazione data l’occorrenza di frana, P(B|A)), ma anche le precipitazioni non innescanti (quindi la probabilità a priori di un evento di pioggia, P(A)). L’approccio Bayesiano è stato applicato all’intervallo temporale compreso tra il 1939 ed il 2009. Le isolinee di probabilità ottenute minimizzano i falsi allarmi e sono facilmente implementabili in un sistema di allertamento regionale, ma possono presentare limiti previsionali per fenomeni non rappresentati nel dataset storico o che avvengono in condizioni anomale. Ne sono esempio le frane superficiali con evoluzione in debris flows, estremamente rare negli ultimi 70 anni, ma con frequenza recentemente in aumento. Si è cercato di affrontare questo problema testando la variabilità previsionale di alcuni modelli fisicamente basati appositamente sviluppati a questo scopo, tra cui X – SLIP (Montrasio et al., 1998), SHALSTAB (SHALlow STABility model, Montgomery & Dietrich, 1994), Iverson (2000), TRIGRS 1.0 (Baum et al., 2002), TRIGRS 2.0 (Baum et al., 2008).

Forecasting trends in the Brisbane central business district office market

The Queensland Department of Public Works (DPW) holds a significant interest in the Brisbane Central Business District (CBD) in controlling approximately 20 percent of the office space within its confines. This comprises a total of 333,903 square metres of space, of which 170,111 square metres is owned and 163,792 square metres is leased from the private sector. The department’s nominal ownership extends to several enduring, landmark buildings as well as several modern office towers. The portfolio includes the oldest building in the CBD, being the former Commissariat Stores building and one of the newest, a 15,000 square metre office tower under construction at 33 Charlotte Street.

Forecasting time-varying value-at-risk

In this thesis we are interested in financial risk and the instrument we want to use is Value-at-Risk (VaR). VaR is the maximum loss over a given period of time at a given confidence level. Many definitions of VaR exist and some will be introduced throughout this thesis. There two main ways to measure risk and VaR: through volatility and through percentiles. Large volatility in financial returns implies greater probability of large losses, but also larger probability of large profits. Percentiles describe tail behaviour. The estimation of VaR is a complex task. It is important to know the main characteristics of financial data to choose the best model. The existing literature is very wide, maybe controversial, but helpful in drawing a picture of the problem. It is commonly recognised that financial data are characterised by heavy tails, time-varying volatility, asymmetric response to bad and good news, and skewness. Ignoring any of these features can lead to underestimating VaR with a possible ultimate consequence being the default of the protagonist (firm, bank or investor). In recent years, skewness has attracted special attention. An open problem is the detection and modelling of time-varying skewness. Is skewness constant or there is some significant variability which in turn can affect the estimation of VaR? This thesis aims to answer this question and to open the way to a new approach to model simultaneously time-varying volatility (conditional variance) and skewness. The new tools are modifications of the Generalised Lambda Distributions (GLDs). They are four-parameter distributions, which allow the first four moments to be modelled nearly independently: in particular we are interested in what we will call para-moments, i.e., mean, variance, skewness and kurtosis. The GLDs will be used in two different ways. Firstly, semi-parametrically, we consider a moving window to estimate the parameters and calculate the percentiles of the GLDs. Secondly, parametrically, we attempt to extend the GLDs to include time-varying dependence in the parameters. We used the local linear regression to estimate semi-parametrically conditional mean and conditional variance. The method is not efficient enough to capture all the dependence structure in the three indices —ASX 200, S&P 500 and FT 30—, however it provides an idea of the DGP underlying the process and helps choosing a good technique to model the data. We find that GLDs suggest that moments up to the fourth order do not always exist, there existence appears to vary over time. This is a very important finding, considering that past papers (see for example Bali et al., 2008; Hashmi and Tay, 2007; Lanne and Pentti, 2007) modelled time-varying skewness, implicitly assuming the existence of the third moment. However, the GLDs suggest that mean, variance, skewness and in general the conditional distribution vary over time, as already suggested by the existing literature. The GLDs give good results in estimating VaR on three real indices, ASX 200, S&P 500 and FT 30, with results very similar to the results provided by historical simulation.

Forecasting crashes at the planning level: Simultaneous negative binomial crash model applied in Tucson, Arizona

At least two important transportation planning activities rely on planning-level crash prediction models. One is motivated by the Transportation Equity Act for the 21st Century, which requires departments of transportation and metropolitan planning organizations to consider safety explicitly in the transportation planning process. The second could arise from a need for state agencies to establish incentive programs to reduce injuries and save lives. Both applications require a forecast of safety for a future period. Planning-level crash prediction models for the Tucson, Arizona, metropolitan region are presented to demonstrate the feasibility of such models. Data were separated into fatal, injury, and property-damage crashes. To accommodate overdispersion in the data, negative binomial regression models were applied. To accommodate the simultaneity of fatality and injury crash outcomes, simultaneous estimation of the models was conducted. All models produce crash forecasts at the traffic analysis zone level. Statistically significant (p-values < 0.05) and theoretically meaningful variables for the fatal crash model included population density, persons 17 years old or younger as a percentage of the total population, and intersection density. Significant variables for the injury and property-damage crash models were population density, number of employees, intersections density, percentage of miles of principal arterial, percentage of miles of minor arterials, and percentage of miles of urban collectors. Among several conclusions it is suggested that planning-level safety models are feasible and may play a role in future planning activities. However, caution must be exercised with such models.

Forecasting negative effects of monotony and sensation seeking on performance during a vigilance task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create hypovigilance and impair performance towards critical events. Identifying such impairment in monotonous conditions has been a major subject of research, but no research to date has attempted to predict it in real-time. This pilot study aims to show that performance decrements due to monotonous tasks can be predicted through mathematical modelling taking into account sensation seeking levels. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants‟ performance. The framework for prediction developed on this task could be extended to a monotonous driving task. A Hidden Markov Model (HMM) is proposed to predict participants‟ lapses in alertness. Driver‟s vigilance evolution is modelled as a hidden state and is correlated to a surrogate measure: the participant‟s reactions time. This experiment shows that the monotony of the task can lead to an important decline in performance in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

The impact of regulatory reforms on the earnings forecasting behaviour of IPO firms

Purpose – The purpose of this paper is to jointly assess the impact of regulatory reform for corporate fundraising in Australia (CLERP Act 1999) and the relaxation of ASX admission rules in 1999, on the accuracy of management earnings forecasts in initial public offer (IPO) prospectuses. The relaxation of ASX listing rules permitted a new category of new economy firms (commitments test entities (CTEs))to list without a prior history of profitability, while the CLERP Act (introduced in 2000) was accompanied by tighter disclosure obligations and stronger enforcement action by the corporate regulator (ASIC). Design/methodology/approach – All IPO earnings forecasts in prospectuses lodged between 1998 and 2003 are examined to assess the pre- and post-CLERP Act impact. Based on active ASIC enforcement action in the post-reform period, IPO firms are hypothesised to provide more accurate forecasts, particularly CTE firms, which are less likely to have a reasonable basis for forecasting. Research models are developed to empirically test the impact of the reforms on CTE and non-CTE IPO firms. Findings – The new regulatory environment has had a positive impact on management forecasting behaviour. In the post-CLERP Act period, the accuracy of prospectus forecasts and their revisions significantly improved and, as expected, the results are primarily driven by CTE firms. However, the majority of prospectus forecasts continue to be materially inaccurate. Originality/value – The results highlight the need to control for both the changing nature of listed firms and the level of enforcement action when examining responses to regulatory changes to corporate fundraising activities.

Semi-parametric forecasting of realized volatility

Forecasts generated by time series models traditionally place greater weight on more recent observations. This paper develops an alternative semi-parametric method for forecasting that does not rely on this convention and applies it to the problem of forecasting asset return volatility. In this approach, a forecast is a weighted average of historical volatility, with the greatest weight given to periods that exhibit similar market conditions to the time at which the forecast is being formed. Weighting is determined by comparing short-term trends in volatility across time (as a measure of market conditions) by means of a multivariate kernel scheme. It is found that the semi-parametric method produces forecasts that are significantly more accurate than a number of competing approaches at both short and long forecast horizons.

Forecasting volatility and correlation : the role of option implied measures

Forecasts of volatility and correlation are important inputs into many practical financial problems. Broadly speaking, there are two ways of generating forecasts of these variables. Firstly, time-series models apply a statistical weighting scheme to historical measurements of the variable of interest. The alternative methodology extracts forecasts from the market traded value of option contracts. An efficient options market should be able to produce superior forecasts as it utilises a larger information set of not only historical information but also the market equilibrium expectation of options market participants. While much research has been conducted into the relative merits of these approaches, this thesis extends the literature along several lines through three empirical studies. Firstly, it is demonstrated that there exist statistically significant benefits to taking the volatility risk premium into account for the implied volatility for the purposes of univariate volatility forecasting. Secondly, high-frequency option implied measures are shown to lead to superior forecasts of the intraday stochastic component of intraday volatility and that these then lead on to superior forecasts of intraday total volatility. Finally, the use of realised and option implied measures of equicorrelation are shown to dominate measures based on daily returns.

Forecasting success on large projects : developing reliable scales to predict multiple perspectives by multiple stakeholders over multiple time frames

Our aim is to develop a set of leading performance indicators to enable managers of large projects to forecast during project execution how various stakeholders will perceive success months or even years into the operation of the output. Large projects have many stakeholders who have different objectives for the project, its output, and the business objectives they will deliver. The output of a large project may have a lifetime that lasts for years, or even decades, and ultimate impacts that go beyond its immediate operation. How different stakeholders perceive success can change with time, and so the project manager needs leading performance indicators that go beyond the traditional triple constraint to forecast how key stakeholders will perceive success months or even years later. In this article, we develop a model for project success that identifies how project stakeholders might perceive success in the months and years following a project. We identify success or failure factors that will facilitate or mitigate against achievement of those success criteria, and a set of potential leading performance indicators that forecast how stakeholders will perceive success during the life of the project's output. We conducted a scale development study with 152 managers of large projects and identified two project success factor scales and seven stakeholder satisfaction scales that can be used by project managers to predict stakeholder satisfaction on projects and so may be used by the managers of large projects for the basis of project control.