Discrete element modelling of power draw of tumbling mills

The power required to operate large mills is typically 5-10 MW. Hence, optimisation of power consumption will have a significant impact on overall economic performance and environmental impact. Power draw modelling results using the discrete element code PFC3D have been compared with results derived from the widely used empirical Model of Morrell. This is achieved by calculating the power draw for a range of operating conditions for constant mill size and fill factor using two modelling approaches. fThe discrete element modelling results show that, apart from density, selection of the appropriate material damping ratio is critical for the accuracy of modelling of the mill power draw. The relative insensitivity of the power draw to the material stiffness allows selection of moderate stiffness values, which result in acceptable computation time. The results obtained confirm that modelling of the power draw for a vertical slice of the mill, of thickness 20% of the mill length, is a reliable substitute for modelling the full mill. The power draw predictions from PFC3D show good agreement with those obtained using the empirical model. Due to its inherent flexibility, power draw modelling using PFC3D appears to be a viable and attractive alternative to empirical models where necessary code and computer power are available.

Scheduling of head-dependent cascaded reservoirs considering discharge ramping constraints and start/stop of units

This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP).

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Estudo dosimétrico comparativo do Acuros® XB: algoritmo avançado de cálculo de dose com o AAA – Anisotropic Analytical Alghorithm, em tratamentos de radioterapia externa com a técnica de RapidArc™

Mestrado em Radioterapia.

Modelo de otimização do espaço livre de armazenagem num silo de cereais

Este trabalho baseia-se num caso de estudo real de planeamento de operações de armazenagem num silo rural de cereais, e enquadra-se nos problemas de planeamento e programação de armazéns. Os programadores deparam-se diariamente com o problema de arranjar a melhor solução de transferência entre células de armazenagem, tentando maximizar o número de células vazias, por forma a ter maior capacidade para receber novos lotes, respeitando as restrições de receção e expedição, e as restrições de capacidade das linhas de transporte. Foi desenvolvido um modelo matemático de programação linear inteira mista e uma aplicação em Excel, com recurso ao VBA, para a sua implementação. Esta implementação abrangeu todo o processo relativo à atividade em causa, isto é, vai desde a recolha de dados, seu tratamento e análise, até à solução final de distribuição dos vários produtos pelas várias células. Os resultados obtidos mostram que o modelo otimiza o número de células vazias, tendo em conta os produtos que estão armazenados mais os que estão para ser rececionados e expedidos, em tempo computacional inferior a 60 segundos, constituindo, assim, uma importante mais valia para a empresa em causa.

Desenvolvimento de módulos para planeamento e controlo de execução de missões de veículos aéreos não tripulados

Com a evolução da tecnologia, os UAVs (unmanned aerial vehicles) são cada vez mais utilizados, não só em missões de risco para o ser Humano, mas também noutro tipo de missões, como é o caso de missões de inspeção, vigilância, busca e salvamento. Isto devese ao baixo custo das plataformas assim como à sua enorme fiabilidade e facilidade de operação. Esta dissertação surge da necessidade de aumentar a autonomia dos UAVs do projeto PITVANT (Projeto de Investigação e Tecnologia em Veículos Aéreos Não Tripulados), projeto de investigação colaborativa entre a AFA (Academia da Força Aérea) e a FEUP (Faculdade de Engenharia da Universidade do Porto), relativamente ao planeamento de trajetórias entre dois pontos no espaço, evitando os obstáculos que intersetem o caminho. Para executar o planeamento da trajetória mais curta entre dois pontos, foi implementado o algoritmo de pesquisa A*, por ser um algoritmo de pesquisa de soluções ótimas. A área de pesquisa é decomposta em células regulares e o centro das células são os nós de pesquisa do A*. O tamanho de cada célula é dependente da dinâmica de cada aeronave. Para que as aeronaves não colidam com os obstáculos, foi desenvolvido um método numérico baseado em relações trigonométricas para criar uma margem de segurança em torno de cada obstáculo. Estas margens de segurança são configuráveis, sendo o seu valor por defeito igual ao raio mínimo de curvatura da aeronave à velocidade de cruzeiro. De forma a avaliar a sua escalabilidade, o algoritmo foi avaliado com diferentes números de obstáculos. As métricas utilizadas para avaliação do algoritmo foram o tempo de computação do mesmo e o comprimento do trajeto obtido. Foi ainda comparado o desempenho do algoritmo desenvolvido com um algoritmo já implementado, do tipo fast marching.

Analyzing TDMA with slot skipping

Distributed real-time systems, such as factory automation systems, require that computer nodes communicate with a known and low bound on the communication delay. This can be achieved with traditional time division multiple access (TDMA). But improved flexibility and simpler upgrades are possible through the use of TDMA with slot-skipping (TDMA/SS), meaning that a slot is skipped whenever it is not used and consequently the slot after the skipped slot starts earlier. We propose a schedulability analysis for TDMA/SS. We assume knowledge of all message streams in the system, and that each node schedules messages in its output queue according to deadline monotonic. Firstly, we present a non-exact (but fast) analysis and then, at the cost of computation time, we also present an algorithm that computes exact queuing times.

Short-term electricity prices forecasting in a competetive market by a hybrid Pso-Anfis approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn.

Uma metaheurística para a programação de projectos com multi-modos e recursos limitados

Este artigo apresenta uma nova abordagem (MM-GAV-FBI), aplicável ao problema da programação de projectos com restrições de recursos e vários modos de execução por actividade, problema conhecido na literatura anglo-saxónica por MRCPSP. Cada projecto tem um conjunto de actividades com precedências tecnológicas definidas e um conjunto de recursos limitados, sendo que cada actividade pode ter mais do que um modo de realização. A programação dos projectos é realizada com recurso a um esquema de geração de planos (do inglês Schedule Generation Scheme - SGS) integrado com uma metaheurística. A metaheurística é baseada no paradigma dos algoritmos genéticos. As prioridades das actividades são obtidas a partir de um algoritmo genético. A representação cromossómica utilizada baseia-se em chaves aleatórias. O SGS gera planos não-atrasados. Após a obtenção de uma solução é aplicada uma melhoria local. O objectivo da abordagem é encontrar o melhor plano (planning), ou seja, o plano que tenha a menor duração temporal possível, satisfazendo as precedências das actividades e as restrições de recursos. A abordagem proposta é testada num conjunto de problemas retirados da literatura da especialidade e os resultados computacionais são comparados com outras abordagens. Os resultados computacionais validam o bom desempenho da abordagem, não apenas em termos de qualidade da solução, mas também em termos de tempo útil.

Non emergency patients transport - a mixed integer linear programming

This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.

The non-emergency patient transport modelled as a team orienteering problem

This work presents an improved model to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving Orienteering Problems is presented, and this heuristic provides good results in terms of accuracy and computation time. Euclidean instances as well as asymmetric real data gathered from Google maps were used, and the model has a promising performance mainly with asymmetric cost matrices.

ADSNARK: Nearly practical and privacy-preserving proofs on authenticated data

We study the problem of privacy-preserving proofs on authenticated data, where a party receives data from a trusted source and is requested to prove computations over the data to third parties in a correct and private way, i.e., the third party learns no information on the data but is still assured that the claimed proof is valid. Our work particularly focuses on the challenging requirement that the third party should be able to verify the validity with respect to the specific data authenticated by the source — even without having access to that source. This problem is motivated by various scenarios emerging from several application areas such as wearable computing, smart metering, or general business-to-business interactions. Furthermore, these applications also demand any meaningful solution to satisfy additional properties related to usability and scalability. In this paper, we formalize the above three-party model, discuss concrete application scenarios, and then we design, build, and evaluate ADSNARK, a nearly practical system for proving arbitrary computations over authenticated data in a privacy-preserving manner. ADSNARK improves significantly over state-of-the-art solutions for this model. For instance, compared to corresponding solutions based on Pinocchio (Oakland’13), ADSNARK achieves up to 25× improvement in proof-computation time and a 20× reduction in prover storage space.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

Alineamiento de secuencias genéticas en procesadores multicore

Este trabajo analiza el rendimiento del algoritmo de alineamiento de secuencias conocido como Needleman-Wunsch, sobre 3 sistemas de cómputo multiprocesador diferentes. Se analiza y se codifica el algoritmo serie usando el lenguaje de programación C y se plantean una serie de optimizaciones con la finalidad de minimizar el volumen y el tiempo de cómputo. Posteriormente, se realiza un análisis de las prestaciones del programa sobre los diferentes sistemas de cómputo. En la segunda parte del trabajo, se paraleliza el algoritmo serie y se codifica ayudándonos de OpenMP. El resultado son dos variantes del programa que difieren en la relación entre la cantidad de cómputo y la de comunicación. En la primera variante, la comunicación entre procesadores es poco frecuente y se realiza tras largos periodos de ejecución (granularidad gruesa). En cambio, en la segunda variante las tareas individuales son relativamente pequeñas en término de tiempo de ejecución y la comunicación entre los procesadores es frecuente (granularidad fina). Ambas variantes se ejecutan y analizan en arquitecturas multicore que explotan el paralelismo a nivel de thread. Los resultados obtenidos muestran la importancia de entender y saber analizar el efecto del multicore y multithreading en el rendimiento.