Data-Flow analysis of prolog programs with extra-logical features

Abstract interpretation-based data-flow analysis of logic programs is at this point relatively well understood from the point of view of general frameworks and abstract domains. On the other hand, comparatively little attention has been given to the problems which arise when analysis of a full, practical dialect of the Prolog language is attempted, and only few solutions to these problems have been proposed to date. Such problems relate to dealing correctly with all builtins, including meta-logical and extra-logical predicates, with dynamic predicates (where the program is modified during execution), and with the absence of certain program text during compilation. Existing proposals for dealing with such issues generally restrict in one way or another the classes of programs which can be analyzed if the information from analysis is to be used for program optimization. This paper attempts to fill this gap by considering a full dialect of Prolog, essentially following the recently proposed ISO standard, pointing out the problems that may arise in the analysis of such a dialect, and proposing a combination of known and novel solutions that together allow the correct analysis of arbitrary programs using the full power of the language.

A review on probabilistic graphical models in evolutionary computation

Thanks to their inherent properties, probabilistic graphical models are one of the prime candidates for machine learning and decision making tasks especially in uncertain domains. Their capabilities, like representation, inference and learning, if used effectively, can greatly help to build intelligent systems that are able to act accordingly in different problem domains. Evolutionary algorithms is one such discipline that has employed probabilistic graphical models to improve the search for optimal solutions in complex problems. This paper shows how probabilistic graphical models have been used in evolutionary algorithms to improve their performance in solving complex problems. Specifically, we give a survey of probabilistic model building-based evolutionary algorithms, called estimation of distribution algorithms, and compare different methods for probabilistic modeling in these algorithms.

Low-dimensional modeling of streaks in a wedge flow boundary layer

This paper is concerned with the low dimensional structure of optimal streaks in a wedge flow boundary layer, which have been recently shown to consist of a unique (up to a constant factor) three-dimensional streamwise evolving mode, known as the most unstable streaky mode. Optimal streaks exhibit a still unexplored/unexploited approximate self-similarity (not associated with the boundary layer self-similarity), namely the streamwise velocity re-scaled with their maximum remains almost independent of both the spanwise wavenumber and the streamwise coordinate; the remaining two velocity components instead do not satisfy this property. The approximate self-similar behavior is analyzed here and exploited to further simplify the description of optimal streaks. In particular, it is shown that streaks can be approximately described in terms of the streamwise evolution of the scalar amplitudes of just three one-dimensional modes, providing the wall normal profiles of the streamwise velocity and two combinations of the cross flow velocity components; the scalar amplitudes obey a singular system of three ordinary differential equations (involving only two degrees of freedom), which approximates well the streamwise evolution of the general streaks.

Optimal Design of Envelope Amplifier Based on Linear Assisted Buck Converter

Envelope Tracking (ET) and Envelope Elimination and Restoration (EER) are two techniques that have been used as a solution for highly efficient linear RF Power Amplifiers (PA). In both techniques the most important part is a dc-dc converter called envelope amplifier that has to supply the RF PA with variable voltage. Besides high efficiency, its bandwidth is very important as well. Envelope amplifier based on parallel combination of a switching dc-dc converter and a linear regulator is an architecture that is widely used due to its simplicity. In this paper we discuss about theoretical limitations of this architecture regarding its efficiency and we demonstrate two possible way of its implementation. In order to derive the presented conclusions, a theoretical model of envelope amplifier's efficiency has been presented. Additionally, the benefits of the new emerging GaN technology for this application have been shown as well.

Flow and wakes in large wind farms in complex terrain and offshore

Power losses due to wind turbine wakes are of the order of 10 and 20% of total power output in large wind farms. The focus of this research carried out within the EC funded UPWIND project is wind speed and turbulence modelling for large wind farms/wind turbines in complex terrain and offshore in order to optimise wind farm layouts to reduce wake losses and loads.

Flow and wakes in complex terrain and offshore. Model development and verification in UPWIND

The paper presents research conducted in the Flow workpackage of the EU funded UPWIND project which focuses on improving models for flow within and downwind of large wind farms in complex terrain and offshore. The main activity is modelling the behaviour of wind turbine wakes in order to improve power output predictions.

Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Efficient algorithms for dynamic probabilistic safety assessment. An application to convex damage domain.

The design of nuclear power plant has to follow a number of regulations aimed at limiting the risks inherent in this type of installation. The goal is to prevent and to limit the consequences of any possible incident that might threaten the public or the environment. To verify that the safety requirements are met a safety assessment process is followed. Safety analysis is as key component of a safety assessment, which incorporates both probabilistic and deterministic approaches. The deterministic approach attempts to ensure that the various situations, and in particular accidents, that are considered to be plausible, have been taken into account, and that the monitoring systems and engineered safety and safeguard systems will be capable of ensuring the safety goals. On the other hand, probabilistic safety analysis tries to demonstrate that the safety requirements are met for potential accidents both within and beyond the design basis, thus identifying vulnerabilities not necessarily accessible through deterministic safety analysis alone. Probabilistic safety assessment (PSA) methodology is widely used in the nuclear industry and is especially effective in comprehensive assessment of the measures needed to prevent accidents with small probability but severe consequences. Still, the trend towards a risk informed regulation (RIR) demanded a more extended use of risk assessment techniques with a significant need to further extend PSA’s scope and quality. Here is where the theory of stimulated dynamics (TSD) intervenes, as it is the mathematical foundation of the integrated safety assessment (ISA) methodology developed by the CSN(Consejo de Seguridad Nuclear) branch of Modelling and Simulation (MOSI). Such methodology attempts to extend classical PSA including accident dynamic analysis, an assessment of the damage associated to the transients and a computation of the damage frequency. The application of this ISA methodology requires a computational framework called SCAIS (Simulation Code System for Integrated Safety Assessment). SCAIS provides accident dynamic analysis support through simulation of nuclear accident sequences and operating procedures. Furthermore, it includes probabilistic quantification of fault trees and sequences; and integration and statistic treatment of risk metrics. SCAIS comprehensively implies an intensive use of code coupling techniques to join typical thermal hydraulic analysis, severe accident and probability calculation codes. The integration of accident simulation in the risk assessment process and thus requiring the use of complex nuclear plant models is what makes it so powerful, yet at the cost of an enormous increase in complexity. As the complexity of the process is primarily focused on such accident simulation codes, the question of whether it is possible to reduce the number of required simulation arises, which will be the focus of the present work. This document presents the work done on the investigation of more efficient techniques applied to the process of risk assessment inside the mentioned ISA methodology. Therefore such techniques will have the primary goal of decreasing the number of simulation needed for an adequate estimation of the damage probability. As the methodology and tools are relatively recent, there is not much work done inside this line of investigation, making it a quite difficult but necessary task, and because of time limitations the scope of the work had to be reduced. Therefore, some assumptions were made to work in simplified scenarios best suited for an initial approximation to the problem. The following section tries to explain in detail the process followed to design and test the developed techniques. Then, the next section introduces the general concepts and formulae of the TSD theory which are at the core of the risk assessment process. Afterwards a description of the simulation framework requirements and design is given. Followed by an introduction to the developed techniques, giving full detail of its mathematical background and its procedures. Later, the test case used is described and result from the application of the techniques is shown. Finally the conclusions are presented and future lines of work are exposed.

Steady-state thermal analysis of an innovative receiver for linear Fresnel reflectors

The study of the performance of an innovative receiver for linear Fresnel reflectors is carried out in this paper, and the results are analyzed with a physics perspective of the process. The receiver consists of a bundle of tubes parallel to the mirror arrays, resulting on a smaller cross section for the same receiver width as the number of tubes increases, due to the diminution of their diameter. This implies higher heat carrier fluid speeds, and thus, a more effective heat transfer process, although it conveys higher pumping power as well. Mass flow is optimized for different tubes diameters, different impinging radiation intensities and different fluid inlet temperatures. It is found that the best receiver design, namely the tubes diameter that maximizes the exergetic efficiency for given working conditions, is similar for the cases studied. There is a range of tubes diameters that imply similar efficiencies, which can drive to capital cost reduction thanks to the flexibility of design. In addition, the length of the receiver is also optimized, and it is observed that the optimal length is similar for the working conditions considered. As a result of this study, it is found that this innovative receiver provides an optimum design for the whole day, even though impinging radiation intensity varies notably. Thermal features of this type of receiver could be the base of a new generation of concentrated solar power plants with a great potential for cost reduction, because of the simplicity of the system and the lower weigh of the components, plus the flexibility of using the receiver tubes for different streams of the heat carrier fluid.

Power density of a bare electrodynamic tether generator

The maximum performance of bare electrodynamic tethers as power generating systems under OML-theory is analyzed. Results show that best performance in terms of power density is achieved by designing the tether in such a way to increase ohmic impedance with respect to plasma contact impedance, hence favoring longer and thinner tethers. In such condition the corresponding optimal value of the load impedance is seen to approach the ohmic impedance of the conducting tether. At the other extreme, when plasma contact impedance dominates (which is not optimal but can be relevant for some applications) optimum power generation is found by matching the load impedance with an effective tether-plasma contact impedance whose expression is derived.

Co2 capture in power plants-using the oxy-combustion principle

In the C02 capture from power generation, the energy penalties for the capture are one of the main challenges. Nowadays, the post-combustion methods have energy penalties 10wer than the oxy combustion and pre-combustion technologies. One of the main disadvantages of the post combustion method is the fact that the capture ofC02at atmospheric pressure requires quite big equipment for the high flow rates of flue gas, and the 10w partial pressure of the CO2generates an important 10ss of energy. The A1lam cyc1e presented for NETPOWER gives high efficiencies in the power production and 10w energy penalties. A simulation of this cyc1e is made together with a simulation of power plants with pre-combustion and post-combustion capture and without capture for natural gas and forcoa1. The simulations give 10wer efficiencies than the proposed for NETPOWER For natural gas the efficiency is 52% instead of the 59% presented, and 33% instead of51% in the case of using coal as fuel. Are brought to light problems in the CO2compressor due the high flow ofC02that is compressed unti1300 bar to be recyc1ed into the combustor.

Approximate Relational Reasoning for Probabilistic Programs

La seguridad verificada es una metodología para demostrar propiedades de seguridad de los sistemas informáticos que se destaca por las altas garantías de corrección que provee. Los sistemas informáticos se modelan como programas probabilísticos y para probar que verifican una determinada propiedad de seguridad se utilizan técnicas rigurosas basadas en modelos matemáticos de los programas. En particular, la seguridad verificada promueve el uso de demostradores de teoremas interactivos o automáticos para construir demostraciones completamente formales cuya corrección es certificada mecánicamente (por ordenador). La seguridad verificada demostró ser una técnica muy efectiva para razonar sobre diversas nociones de seguridad en el área de criptografía. Sin embargo, no ha podido cubrir un importante conjunto de nociones de seguridad “aproximada”. La característica distintiva de estas nociones de seguridad es que se expresan como una condición de “similitud” entre las distribuciones de salida de dos programas probabilísticos y esta similitud se cuantifica usando alguna noción de distancia entre distribuciones de probabilidad. Este conjunto incluye destacadas nociones de seguridad de diversas áreas como la minería de datos privados, el análisis de flujo de información y la criptografía. Ejemplos representativos de estas nociones de seguridad son la indiferenciabilidad, que permite reemplazar un componente idealizado de un sistema por una implementación concreta (sin alterar significativamente sus propiedades de seguridad), o la privacidad diferencial, una noción de privacidad que ha recibido mucha atención en los últimos años y tiene como objetivo evitar la publicación datos confidenciales en la minería de datos. La falta de técnicas rigurosas que permitan verificar formalmente este tipo de propiedades constituye un notable problema abierto que tiene que ser abordado. En esta tesis introducimos varias lógicas de programa quantitativas para razonar sobre esta clase de propiedades de seguridad. Nuestra principal contribución teórica es una versión quantitativa de una lógica de Hoare relacional para programas probabilísticos. Las pruebas de correción de estas lógicas son completamente formalizadas en el asistente de pruebas Coq. Desarrollamos, además, una herramienta para razonar sobre propiedades de programas a través de estas lógicas extendiendo CertiCrypt, un framework para verificar pruebas de criptografía en Coq. Confirmamos la efectividad y aplicabilidad de nuestra metodología construyendo pruebas certificadas por ordendor de varios sistemas cuyo análisis estaba fuera del alcance de la seguridad verificada. Esto incluye, entre otros, una meta-construcción para diseñar funciones de hash “seguras” sobre curvas elípticas y algoritmos diferencialmente privados para varios problemas de optimización combinatoria de la literatura reciente. ABSTRACT The verified security methodology is an emerging approach to build high assurance proofs about security properties of computer systems. Computer systems are modeled as probabilistic programs and one relies on rigorous program semantics techniques to prove that they comply with a given security goal. In particular, it advocates the use of interactive theorem provers or automated provers to build fully formal machine-checked versions of these security proofs. The verified security methodology has proved successful in modeling and reasoning about several standard security notions in the area of cryptography. However, it has fallen short of covering an important class of approximate, quantitative security notions. The distinguishing characteristic of this class of security notions is that they are stated as a “similarity” condition between the output distributions of two probabilistic programs, and this similarity is quantified using some notion of distance between probability distributions. This class comprises prominent security notions from multiple areas such as private data analysis, information flow analysis and cryptography. These include, for instance, indifferentiability, which enables securely replacing an idealized component of system with a concrete implementation, and differential privacy, a notion of privacy-preserving data mining that has received a great deal of attention in the last few years. The lack of rigorous techniques for verifying these properties is thus an important problem that needs to be addressed. In this dissertation we introduce several quantitative program logics to reason about this class of security notions. Our main theoretical contribution is, in particular, a quantitative variant of a full-fledged relational Hoare logic for probabilistic programs. The soundness of these logics is fully formalized in the Coq proof-assistant and tool support is also available through an extension of CertiCrypt, a framework to verify cryptographic proofs in Coq. We validate the applicability of our approach by building fully machine-checked proofs for several systems that were out of the reach of the verified security methodology. These comprise, among others, a construction to build “safe” hash functions into elliptic curves and differentially private algorithms for several combinatorial optimization problems from the recent literature.

Probabilistic analysis of water availability for agriculture and associated crop net margins.

Rising water demands are difficult to meet in many regions of the world. In consequence, under meteorological adverse conditions, big economic losses in agriculture can take place. This paper aims to analyze the variability of water shortage in an irrigation district and the effect on farmer?s income. A probabilistic analysis of water availability for agriculture in the irrigation district is performed, through a supply-system simulation approach, considering stochastically generated series of stream-flows. Net margins associated to crop production are as well estimated depending on final water allocations. Net margins are calculated considering either single-crop farming, either a polyculture system. In a polyculture system, crop distribution and water redistribution are calculated through an optimization approach using the General Algebraic Modeling System (GAMS) for several scenarios of irrigation water availability. Expected net margins are obtained by crop and for the optimal crop and water distribution. The maximum expected margins are obtained for the optimal crop combination, followed by the alfalfa monoculture, maize, rice, wheat and finally barley. Water is distributed as follows, from biggest to smallest allocation: rice, alfalfa, maize, wheat and barley.

Optimal water allocation in shortage situations as applied to an irrigation community.

This work studies the most beneficial way of allocating water in an irrigation community in water shortage situations. Therefore, it proposes that the irrigation surface area be divided into homogeneous zones, each with a beneficial relationship with respect to the water applied. The mathematical formula that enables one to obtain the optimal quota for the users or irrigation community as a whole has been found for individual relations of a quadratic or power type, and these have yielded different and complementary characteristics. Dimensionless variables have been used to display the results, and to compare with other alternative allocation rules such as the proportional rule, referencing the situation without water restrictions. As a result, for each water shortage situation, the water that is allocated to each user is obtained, together with the losses in individual income and the losses for the community as a whole. Furthermore, a proposal is put forth for establishing the marginal benefit from the water available, which could be of interest in enabling each community to analyze whether it is in its best interest to invest in increasing the resource, or to sell the resource to other users. Finally, an example is given to demonstrate how the method works and to show that, when the differences between the production schemes are considered, the differences in benefit reduction between the proportional allocation and the optimal allocation are also sizeable. Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)IR.1943-4774.0000667