Transparency: from tractability to model explanations

As artificial intelligence (AI) and machine learning (ML) models get increasingly incorporated into critical applications, ranging from medical diagnosis to loan approval, they show a tremendous potential to impact society in a beneficial way, however, this is predicated on establishing a transparent relationship between humans and automation. In particular, transparency requirements span across multiple dimensions, incorporating both technical and societal aspects, in order to promote the responsible use of AI/ML. In this thesis we present contributions along both of these axes, starting with the technical side and model transparency, where we study ways to enhance tractable probabilistic models (TPMs) with properties that enable acquiring an in-depth understanding of their decision-making process. Following this, we expand the scope of our work, studying how providing explanations about a model’s predictions influences the extent to which humans understand and collaborate with it, and finally we design an introductory course into the emerging field of explanations in AI to foster the competent use of the developed tools and methodologies. In more detail, the complex design of TPMs makes it very challenging to extract information that conveys meaningful insights, despite the fact that they are closely related to Bayesian networks (BNs), which readily provide such information. This has led to TPMs being viewed as black-boxes, in the sense that their internal representations are elusive, in contrast to BNs. The first part of this thesis challenges this view, focusing on the question of whether it is feasible to extend certain transparent features of BNs to TPMs. We start with considering the problem of transforming TPMs into alternative graphical models in a way that makes their internal representations easy to inspect. Furthermore, we study the utility of existing algorithms in causal applications, where we identify some significant limitations. To remedy this situation, we propose a set of algorithms that result in transformations that accurately uncover the internal representations of TPMs. Following this result, we look into the problem of incorporating probabilistic constraints into TPMs. Although it is well known that BNs satisfy this property, the complex structure of TPMs impedes applying the same arguments, thus advances on this problem have been very limited. Having said that, in this thesis we provide formal proofs that TPMs can be made to satisfy both probabilistic and causal constraints through parameter manipulation, showing that incorporating a constraint corresponds to solving a system of multilinear equations. We conclude the technical contributions studying the problem of generating counterfactual instances for classifiers based on TPMs, motivated by the fact that BNs are the building blocks of most standard approaches to perform this task. In this thesis we propose a novel algorithm that we prove is guaranteed to generate valid counterfactuals. The resulting algorithm takes advantage of the multilinear structure of TPMs, generalizing existing approaches, while also allowing for incorporating a priori constraints that should be respected by the final counterfactuals. In the second part of this thesis we go beyond model transparency, looking into the role of explanations in achieving an effective collaboration between human users and AI. To study this we design a behavioural experiment where we show that explanations provide unique insights, which cannot be obtained by looking at more traditional uncertainty measures. The findings of this experiment provide evidence supporting the view that explanations and uncertainty estimates have complementary functions, advocating in favour of incorporating elements of both in order to promote a synergistic relationship between humans and AI. Finally, building on our findings, in this thesis we design a course on explanations in AI, where we focus on both the technical details of state-of-the-art algorithms as well as the overarching goals, limitations, and methodological approaches in the field. This contribution aims at ensuring that users can make competent use of explanations, a need that has also been highlighted by recent large scale social initiatives. The resulting course was offered by the University of Edinburgh, at an MSc level, where student evaluations, as well as their performance, showcased the course’s effectiveness in achieving its primary goals

Principles and Practice of Explainable Machine Learning

Artificial intelligence (AI) provides many opportunities to improve private and public life. Discovering patterns and structures in large troves of data in an automated manner is a core component of data science, and currently drives applications in diverse areas such as computational biology, law and finance. However, such a highly positive impact is coupled with significant challenges: how do we understand the decisions suggested by these systems in order that we can trust them? In this report, we focus specifically on data-driven methods -- machine learning (ML) and pattern recognition models in particular -- so as to survey and distill the results and observations from the literature. The purpose of this report can be especially appreciated by noting that ML models are increasingly deployed in a wide range of businesses. However, with the increasing prevalence and complexity of methods, business stakeholders in the very least have a growing number of concerns about the drawbacks of models, data-specific biases, and so on. Analogously, data science practitioners are often not aware about approaches emerging from the academic literature, or may struggle to appreciate the differences between different methods, so end up using industry standards such as SHAP. Here, we have undertaken a survey to help industry practitioners (but also data scientists more broadly) understand the field of explainable machine learning better and apply the right tools. Our latter sections build a narrative around a putative data scientist, and discuss how she might go about explaining her models by asking the right questions

Flow modeling in Pelton turbines by an accurate Eulerian and a fast Lagrangian evaluation method

The recent development of Computational Fluids Dynamics (CFD) has allowed the flow modeling in impulse hydro turbines that includes complex phenomena like free surface flow, multi fluid interaction, and unsteady, time dependent flow. Some commercial and open-source CFD codes, which implement Eulerian solving methods, have been validated against experimental results showing satisfactory accuracy. Nevertheless, further improvement of the flow analysis accuracy is still a challenge, while the computational cost is very high and unaffordable for multi-parametric design optimization of the turbine’s runner. In the present work, a CFD Eulerian approach is applied at first, in order to simulate the flow in the runner of a Pelton turbine model installed at the laboratory. Then, a particulate method, the Fast Lagrangian Simulation (FLS), is used for the same case, which is much faster than the Eulerian approach, and hence potentially suitable for numerical design optimization, providing that it can achieve adequate accuracy. The results of both methods for various operation conditions of the turbine, as also for modified runner and bucket designs, are presented and discussed in the paper. In all examined cases the FLS method shows very good accuracy in predicting the hydraulic efficiency of the runner, although the computed flow evolution and torque curve during the jet-runner interaction exhibit some systematic differences from the Eulerian results

ΜΕΛΕΤΗ ΑΝΑΠΤΥΞΗΣ ΣΠΗΛΑΙΩΣΗΣ ΣΕ ΦΥΓΟΚΕΝΤΡΙΚΕΣ ΑΝΤΛΙΕΣ ΜΕ ΠΕΙΡΑΜΑΤΙΚΑ ΚΑΙ ΥΠΟΛΟΓΙΣΤΙΚΑ ΕΡΓΑΛΕΙΑ

Η ανάγκη μεγιστοποίησης της παραγωγικότητας στη βιομηχανία, καθώς και εξοικονόμησης ενέργειας και μείωσης του σχετικού κόστους, , οδηγεί στην ανάπτυξη εξελιγμένων συστημάτων παρακολούθησης της λειτουργίας των φυγοκεντρικών αντλιών, οι οποίες χρησιμοποιούνται για διακίνηση διαφόρων ρευστών σε πολλές βιομηχανικές διεργασίες Ένα από τα υδροδυναμικά φαινόμενα που επηρεάζει την ομαλή λειτουργία και την απόδοση των αντλιών, είναι η ανάπτυξη της σπηλαίωσης, η οποία μελετάται από πολλούς ερευνητές, με στόχο την ανάπτυξη αξιόπιστων μεθόδων διάγνωσης και ελέγχου της. Στο πλαίσιο αυτό, στην παρούσα εργασία μελετάται η έναρξη και ανάπτυξη του μηχανισμού σπηλαίωσης σε φυγοκεντρική αντλία με πτερωτή ακτινικής ροής, ανοικτού τύπου, με χρήση πειραματικών και υπολογιστικών εργαλείων. Πιο συγκεκριμένα, λαμβάνονται μετρήσεις ταλαντώσεων και ακουστικών κυμάτων σε διάφορα σημεία λειτουργίας της αντλίας, ταυτόχρονα με την οπτική παρακολούθηση του φαινομένου, ενώ παράλληλα εφαρμόζεται υπολογιστικό μοντέλο κατάλληλο για τη μελέτη των χαρακτηριστικών της ροής που ελέγχουν την εμφάνιση και την ανάπτυξή του. Με βάση τα αποτελέσματα της παρούσας μελέτης, καθίσταται δυνατή η διάγνωση της σπηλαίωσης σε μια αντλία από τις μετρήσεις ταλάντωσης και ακουστικών κυμάτων, και διαπιστώνεται ότι το αριθμητικό μοντέλο έχει τη δυνατότητα να προβλέψει επιτυχώς τόσο τη θέση εμφάνισης όσο και την έκταση της περιοχής της διφασικής ροής νερού-ατμού εντός της πτερωτής

Experimental analysis of cavitation in a centrifugal pump using acoustic emission, vibration measurements and flow visualization

The continuously increasing industrial productivity has resulted in a great breakthrough in the field of maintenance on centrifugal pumps in order to ensure their optimum operation under different operating conditions. One of the important mechanisms that affect the steady and dynamic operation of a pump is cavitation, which appears in the low static pressure zone formed at the impeller entrance region. This paper investigates the inception and development of cavitation in three different impellers of a laboratory centrifugal pump with a Plexiglas casing, using flow visualization, vibration and acoustic emission measurements. The aim of this study is the development of an experimental tool that detects cavitation in different impellers and the further understanding of the effects of blade geometry in cavitation development. The results show that the geometrical characteristics of the impeller affect cavitation development and behavior, while an acoustic emission sensor and an accelerometer can be applied for successfully detecting the onset of this mechanism

Investigating the influence of the jet from three nozzle and spear design configurations on Pelton runner performance by numerical simulation

This paper reports the initial results of three dimensional CFD simulations of the jet – runner interactions in a twin jet horizontal axis Pelton turbine. More specifically, the analysis examines the impact of the nozzle and spear valve configuration on the performance of the runner. Previous research has identified that injectors with notably steeper nozzle and spear angles attain a higher efficiency than the industry standard. However, experimental testing of the entire Pelton system suggests that there appears to be an upper limit beyond which steeper angled designs are no longer optimal. In order to investigate the apparent difference between the numerical prediction of efficiency for the injector system and the obtained experimental results, four different jet configurations are analysed and compared. In the first configuration, the interaction between the runner and an ideal axisymmetric jet profile is investigated. In the final three configurations the runner has been coupled with the jet profile from the aforementioned injectors, namely the Standard design with nozzle and spear angles of 80° & 55° and two Novel designs with angles 110° & 70° and 150° & 90° respectively. The results are compared by examining the impact the jet shape has on the runner torque profile during the bucket cycle and the influence this has on turbine efficiency. All results provided incorporate the Reynolds-averaged Navier Stokes (RANS) Shear Stress Transport (SST) turbulence model and a two-phase Volume of Fluid (VOF) model, using the ANSYS® FLUENT® code. Therefore, this paper offers new insights into the optimal jet – runner interaction

Experimental investigation and analysis of the spear valve design on the performance of Pelton turbines:3 case studies

The impact of the nozzle and spear valve configuration on the performance of a Pelton turbine is investigated both experimentally and computationally. A previously published computational fluid dynamics (CFD) study has shown that injectors with noticeably steeper nozzle and spear angles, 110° and 70° respectively, attain a higher efficiency than the industry standard 80° and 55°. As a result, three injector design cases were manufactured for experimental testing. Two of those cases were the standard (80/55) design, with nozzle and spear tip angles of 80° and 55° and the Novel 1 design (110/70) with nozzle and spear tip angles of 110° and 70° based on previously published CFD optimisation studies. These studies showed that increasing the nozzle and spear angles to the upper limit of the investigated test plan gave higher efficiencies. The response surfaces suggested that the optimum nozzle and spear angles could be even steeper. That is why, an additional case, a third design (Novel 2) with even steeper angles (150/90) was also manufactured and tested. The experimental tests were carried out in a single jet operation using the upper injector on the Gilkes Pelton runner with series Z120 buckets. The results show that two novel injector design cases produce higher efficiencies than the standard design, when tested with a Pelton runner. An important gain of about 1% in efficiency is achieved at the Best Efficiency Point of the turbine. Furthermore, the improvement is even more pronounced at lower flow rates, where the spear valve opening is smaller and the geometry of the injector has even larger effect. To discuss and analyse these experimental observations, a further 2D axisymmetric CFD analysis is performed. This analysis shows a similar trend to the experimental results. The CFD results show that the largest amount of energy is lost at the region upstream of the nozzle exit, where the static pressure is converted into the dynamic pressure. This conversion starts earlier in case 1, the Standard injector design, at about twice the distance compared to the Novel designs, cases 2 and 3. Consequently, the flow must travel in this region at an increased velocity and it is shown that this region is longer in the Standard injector. Hence, its friction losses are higher. However, the differences between the designs calculated in CFD are about a factor of 2 lower than the experimental results, indicating that the 3D secondary flow mechanisms arising from the geometry upstream of the nozzle and spear tip also affect the performance of the spear valve and the Pelton runner. The mismatch between the efficiency increase magnitude observed experimentally and modelled using the axisymmetric case suggests that the steeper angle injectors cope better with secondary velocities in the flow

Experimental investigation and analysis of three spear valve designs on the performance of Turgo impulse turbines

Several numerical investigations into the impact of the spear and nozzle configuration of impulse turbine injectors can be found in the literature, however there is little or no experimental data available for the effect on Turgo impulse turbine performance. A recent 2D numerical Design of Experiments (DoE) study found that much steeper nozzle and spear angles than the industry standard produced higher efficiencies. This work was extended to compare the performance of an industry standard injector (with nozzle and spear angles of 80° and 55°) and an improved injector with much steeper angles of 110° and 70° using a full 3D simulation of the injector, guide vanes and first branch pipe. The impact of the jets produced by these injectors on the performance of a Turgo runner was also simulated. The results for both CFD tools used suggest that steeper injector nozzle and spear angles reduce the injector losses, showing an increase in efficiency of 0.76% for the Turgo 3D injector. In order to investigate the numerical results from the previous studies further, three Turgo impulse turbine injectors were manufactured by Gilbert Gilkes & Gordon Ltd for testing on the 9” Gilkes HCTI Turgo rig at the Laboratory of Hydraulic Machines, National Technical University of Athens (NTUA). The injector designs tested were the standard (80/55) design, with nozzle and spear tip angles of 80° and 55° and the Novel 1 design (110/70) with nozzle and spear tip angles of 110° and 70° based on previously published CFD optimisation studies. The optimisations in the previous studies showed that the nozzle and spear angles in the upper limit of the investigated test plan, which was much higher than current industry guidelines, gave higher efficiencies. The DoE response surfaces in that study suggested that the optimum nozzle and spear angles may be even steeper and therefore an additional, third design (Novel 2) with even steeper angles (150/90) was also manufactured and tested. This paper presents the experimental data obtained for the three injector designs which were tested in a Turgo model turbine at various rotating speeds and flow rates. The 70 kW Turgo was coupled to a 75kW DC generator which allowed continuous speed regulation. The inlet conditions into the Turgo model turbine were controlled by a high head adjustable speed multistage pump of nominal operation point Q=290 m3/h, H=130 m (coupled via a hydraulic coupler to a 200 kW induction motor) which pumped water from the 320 m3 main reservoir of the Lab. The tests were carried out in single jet and twin jet operation. Testing and calibration of all the sensors was carried out according to testing standard IEC 60193 Hydraulic turbines, storage pumps and pump-turbines – Model acceptance tests (IEC 60193:1999). The results show that the Novel 2 injector performs best overall, which is consistent with the results obtained in previous 2D injector simulations. The achieved turbine efficiency with this injector is of the order of 0.5-1% higher than the Standard design, for both single and twin jet operation. The Novel 1 injector’s performance is between the Standard and Novel 2 injectors overall. Some images of the jets were also taken at various openings and are presented to qualitatively analyse the impact of each injector design on the disturbances on the outside of the jet. A further 2D axisymmetric CFD analysis is carried out to validate the measurements and to analyse the mechanisms which lead to injector losses. The results found that the majority of the losses occur in the region just upstream of the nozzle exit, where the static pressure is converted into dynamic pressure and the flow accelerates. In the Standard design, this conversion begins sooner and the flow travels over a longer distance at higher velocities leading to an increase in the losses. The CFD results found the differences between the designs to be smaller than the experiments however the trend of the results was similar, suggesting that the steeper angle injectors achieve higher efficiencies and better jet quality. The next stage of this research is to carry out a CFD analysis of the three injector designs in 3D, including the guide vanes and branch pipes, to investigate the impact of the steeper angles on the secondary velocities within the jet and the impact this has on the runner performance

Εργασίες στη μοντελοποίηση και πρόβλεψη της διακύμανσης

This thesis consists of essays on modelling and forecasting asset price volatility. The common motivation behind these essays is twofold: firstly, to exploit the rich informational content of volatility by integrating observable estimators of variance dynamics into parametric GARCH-type models and, secondly, to investigate the ability of these augmented GARCH representations to explain and forecast the observable variance dynamics at multiple horizons ahead. We start by considering a GARCH specification, which we augment to incorporate information from high-frequency data related to measurable characteristics of Realized Variance (RV). The choice of these exogenous features is well-motivated by the recent and ongoing stream of empirical studies on Heterogeneous Auto-Regressive (HAR) models. We find our ``augmented'' Realized-GARCH and Realized-EGARCH specifications to perform significantly better than other already-existing models in fitting the data (in-sample) and forecasting Realized Variance (out-of-sample). The enhanced performance of our models is primarily due to the inclusion of: (i) realized upside/downside semi-variances (indicating prevalent asymmetric effects in intra-day variance), (ii) heterogeneous terms of RV (exogenously approximating long-memory patterns in volatility), and (iii) realized jump or variance-of-variance indicators (capturing discontinuities in the RV process or attenuation biases in RV projections, respectively). Next, we introduce a risk-neutral variance proxy within a flexible parametric framework that is described by affine-GARCH dynamics and a variance-dependent pricing kernel.We find evidence of a sizeable priced volatility risk premium (of approximately -3%), that can be recovered in a robust and parsimonious way from the VIX dynamics through a joint estimation approach. We analyze the transmission mechanism of innovations from physical to risk-neutral dynamics, as well as the impact of volatility risk on the news impact curves and impulse response functions of risk-neutral variance. Our approach reveals that accounting for volatility risk in this GARCH-based framework is of utmost importance for establishing a consistent link between the physical and risk-neutral probability measures. Finally, we provide an extension to the EGARCH and Realized-EGARCH that allows capturing long-run and short-run dynamics of log-variance. We find that decomposing variance into long/short-run dynamics, significantly improves the ability of the model to jointly explain the observable dynamics of returns and RV. Our preliminary results indicate the presence of a long-run component that is highly persistent and not very responsive to past shocks, as well as a short-run component that is less persistent and transmits most of the impact of past shocks on variance. Interestingly, we find shocks to RV to have an equally strong impact on both long- and short-run components (more pronounced for the short-run component), which implies that shocks to returns impact mainly the short-run volatility, whereas shocks to volatility itself may have a more long-run effect. As we discuss, the model extensions that we present in this thesis have direct and important economic implications for asset-pricing, volatility forecasting and risk-management.Η διατριβή αυτή απαρτίζεται από εργασίες στη μοντελοποίηση και πρόβλεψη της διακύμανσης. Ο κοινός στόχος πίσω από τις εργασίες αυτές είναι διττός: πρώτον, η αξιοποίηση της πληροφορίας της διακύμανσης μέσω ενσωμάτωσης παρατηρήσιμων εκτιμητών της διακύμανσης σε παραμετρικά γενικευμένα αυτοπαλίνδρομα υποδείγματα δεσμευμένης ετεροσκεδαστικότητας (GARCH-type models) και, δεύτερον, η μελέτη και αξιολόγηση της ικανότητας αυτών των “επαυξημένων” υποδειγμάτων να εξηγήσουν και να προβλέψουν την παρατηρήσιμη διακύμανση σε διάφορες χρονικές περιόδους στο μέλλον. Συγκεκριμένα, βασιζόμαστε σε ένα παραμετρικό GARCH υπόδειγμα, στο οποίο ενσωματώνουμε εξωγενή πληροφορία από δεδομένα υψηλής συχνότητας τα οποία σχετίζονται με μετρήσιμα χαρακτηριστικά της πραγματικής διακύμανσης (Realized Variance, RV). Η επιλογή αυτών των μέτρων στηρίζεται σε αποτελέσματα διάφορων εμπειρικών ερευνών της σύγχρονης αρθρογραφίας σε Ετερογενή αυτοπαλίνδρομα υποδείγματα (Heterogeneous Auto-Regressive, HAR). Τα αποτελέσματά μας υποδεικνύουν ότι τα “επαυξημένα" υποδείγματα που μελετάμε εμφανίζουν βελτιωμένη επίδοση (σε σχέση με άλλα μοντέλα που έχουν ήδη παρουσιαστεί στη βιβλιογραφία), τόσο ως προς την ικανότητά τους να εξηγήσουν τα δεδομένα του δείγματος, όσο και την ακριβέστερη πρόβλεψη της πραγματικής διακύμανσης εκτός δείγματος. Η βελτιωμένη επίδοση των υποδειγμάτων οφείλεται κυρίως στην ενσωμάτωση πληροφορίας: 1) μέσω της θετικής/αρνητικής ημι-διακύμανσης (positive/negative semi-variance), 2) από ετερογενείς όρους πραγματικής διακύμανσης (heterogeneous terms of RV) και 3) από δείκτες αλμάτων (jumps) ή διακύμανσης-της-διακύμανσης (variance-of-variance). Στη συνέχεια εισάγουμε σε ένα affine-GARCH υπόδειγμα ένα προσεγγιστικό μέτρο της ουδέτερης από κίνδυνο διακύμανσης (risk-neutral variance proxy). Βρίσκουμε ενδείξεις για ένα σημαντικό και τιμολογημένο πριμ κινδύνου για τη διακύμανση (της τάξης του -3%) το οποίο μπορούμε να εκτιμήσουμε μέσω του υποδείγματός μας με έναν πιο απλό και αποτελεσματικό τρόπο, βασιζόμενοι σε μια συνδυαστική προσέγγιση της εκτίμησης των αποδόσεων της αγοράς και του δείκτη VIX. Επίσης, αναλύουμε την επίδραση του πριμ κινδύνου της διακύμανσης στο μηχανισμό μετάδοσης της πληροφορίας από τη φυσική κατανομή στην ουδέτερη από κίνδυνο κατανομή. Τελος, παρουσιάζουμε μία επέκταση του υποδείγματος (EGARCH and Realized-EGARCH) που επιτρέπει τη μοντελοποίηση της μακροχρόνιας και βραχυχρόνιας διακύμανσης. Παρατηρούμε ότι ο διαχωρισμός της διακύμανσης σε μακροχρόνια και βραχυχρόνια μπορεί να οδηγήσει σε σημαντική βελτίωση της ικανότητας του μοντέλου να εξηγεί ταυτόχρονα τις αποδόσεις και την πραγματική διακύμανση. Τα αποτελέσματά μας υποδεικνύουν ότι η μακροχρόνια διακύμανση κινείται αργά/ομαλά και δεν έχει μεγάλο βαθμό απόκρισης στα πρόσφατα σοκ. Αντίστροφα, η βραχυχρόνια διακύμανση κινείται γύρω από τη μακροχρόνια διακύμανση και παρουσιάζει πολύ έντονο βαθμό απόκρισης σε σοκ στις αποδόσεις και τη διακύμανση. Όπως εξηγούμε, η μεθοδολογία και τα αποτελέσματα αυτής της διατριβής μπορούν να έχουν άμεση χρησιμότητα και εφαρμογή σε πολύ σημαντικά προβλήματα τιμολόγησης, πρόβλεψης της διακύμανσης αλλά και διαχείρισης χρηματοοικονομικού κινδύνου