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In smart energy systems, load curve refers to the time series reported by smart meters, which indicate the energy consumption of customers over a certain period of time. The widespread use of load curve (data) in demand side management and demand response programs makes it one of the most important resources. To capture the load behavior or energy consumption patterns, load curve modeling is widely applied to help the utilities and residents make better plans and decisions. In this dissertation, with the help of load curve modeling, we focus on data-driven solutions to three load monitoring problems in different scenarios of smart energy systems, including residential power systems and datacenter power systems and covering the research fields of i) data cleansing, ii) energy disaggregation, and iii) fine-grained power monitoring. First, to improve the data quality for load curve modeling on the supply side, we challenge the regression-based approaches as an efficient way to load curve data cleansing and propose a new approach to analyzing and organizing load curve data. Our approach adopts a new view, termed portrait, on the load curve data by analyzing the inherent periodic patterns and re-organizing the data for ease of analysis. Furthermore, we introduce strategies to build virtual portrait datasets and demonstrate how this technique can be used for outlier detection in load curve. To identify the corrupted load curve data, we propose an appliance-driven approach that particularly takes advantage of information available on the demand side. It identifies corrupted data from the smart meter readings by solving a carefully-designed optimization problem. To solve the problem efficiently, we further develop a sequential local optimization algorithm that tackles the original NP-hard problem by solving an approximate problem in polynomial time. Second, to separate the aggregated energy consumption of a residential house into that of individual appliances, we propose a practical and universal energy disaggregation solution, only referring to the readily available information of appliances. Based on the sparsity of appliances' switching events, we first build a sparse switching event recovering (SSER) model. Then, by making use of the active epochs of switching events, we develop an efficient parallel local optimization algorithm to solve our model and obtain individual appliances' energy consumption. To explore the benefit of introducing low-cost energy meters for energy disaggregation, we propose a semi-intrusive appliance load monitoring (SIALM) approach for large-scale appliances situation. Instead of using only one meter, multiple meters are distributed in the power network to collect the aggregated load data from sub-groups of appliances. The proposed SSER model and parallel optimization algorithm are used for energy disaggregation within each sub-group of appliances. We further provide the sufficient conditions for unambiguous state recovery of multiple appliances, under which a minimum number of meters is obtained via a greedy clique-covering algorithm. Third, to achieve fine-grained power monitoring at server level in legacy datacenters, we present a zero-cost, purely software-based solution. With our solution, no power monitoring hardware is needed any more, leading to much reduced operating cost and hardware complexity. In detail, we establish power mapping functions (PMFs) between the states of servers and their power consumption, and infer the power consumption of each server with the aggregated power of the entire datacenter. We implement and evaluate our solution over a real-world datacenter with 326 servers. The results show that our solution can provide high precision power estimation at both the rack level and the server level. In specific, with PMFs including only two nonlinear terms, our power estimation i) at the rack level has mean relative error of 2.18%, and ii) at the server level has mean relative errors of 9.61% and 7.53% corresponding to the idle and peak power, respectively. / Graduate / 0984 / 0791 / 0800 / tangguo1999@gmail.com

Nesta dissertação são analisadas 34 provas de carga estática realizadas em estacas pré-moldadas de concreto, cravadas em diferentes locais da cidade de Curitiba e região metropolitana, sendo a maioria delas na Formação Guabirotuba. Três métodos de previsão da capacidade foram analisados: Aoki – Velloso (1975), Décourt – Quaresma (1978) e Amaral (1982, 1999). Para cada método foram propostos fatores de correção global e/ou parcial que tornam o valor da capacidade de carga mais próximo do valor da carga última obtida pelo critério de Van der Veen (1953). Com base em quatro provas de carga conduzidas até a ruptura, estudou-se a aplicabilidade do método de Van der Veen (1953) e determinou-se um critério para avaliar a extrapolação da curva carga x recalque em ensaios encerrados sem atingir a ruptura. Finalmente fez-se uma análise dos recalques comparando-se os valores medidos com os calculados, para três níveis de carregamento, além da comparação das curvas carga x recalque ajustadas com as experimentais. / This thesis presents the analysis of 34 static loading tests in concrete drive pile, located at different places of the Curitiba city and metropolitan area, in Guabirotuba Formation. Three methods of the bearing capacity prediction were assessed: Aoki – Velloso (1975), Décourt – Quaresma (1978) and Amaral (1982, 1999). For each method is proposed global correction factors and/or partial that turned the bearing capacity value close to the ultimate load obtained for the Van der Veen criteria (1953). Based on four static loading test carried out to failure, the applicability of the Van der Veen criteria was assessed and was determined a rule to evaluate the extrapolation of the load - settlement curve in tests stopped before of the failure. Finally, it was made an analysis of the settlements, where it was compared the observed values and the predicted values, for three loading level, and also a comparison between the experimental load-settlement curve and the predicted load-settlement curve.

PANTS (PANTS Application Node Transparency System) is a suite of programs designed to add transparent load balancing to a Beowulf cluster so that processes are transfered among the nodes of the cluster to improve performance. PANTS provides the option of using one of several different load balancing policies, each having a different approach. This paper studies the scalability and performance of these policies on large clusters and under various workloads. We measure the performance of our policies on our current cluster, and use that performance data to build simulations to test the performance of the policies in larger clusters and under differing workloads. Two policies, one deterministic and one non-deterministic, are presented which offer optimal steady-state performance. We also present best practices and discuss the major challenges of load balancing policy design.

Soils, like several other materials, exhibit strong time-dependent behaviour which can be evidenced in terms of creep or strain-rate effects. The degree of this rheological behaviour varies with the type of soil, its structure, and with the stress history. This effect is exacerbated in pile load testing where the procedure duration tends to be shortened under increasing time pressures. The modelling needed to interpret the results therefore becomes more and more complex, including soil viscosity, wave radiation into the soil and other significant phenomena. The objective of the research reported herein is to refine the rheological parameters characterizing the influence of the loading rate within the framework of a relevant pile/soil interaction model fed with dynamic measurements acquired during pile Dynamic Load Tests (DLTs). The final goal is to predict and simulate the quasi-static pile load settlement curve. The pile/soil interaction system is described by a non-linear mass/spring/dashpot system supposed to represent the pile and the soil, with constitutive relationships existing within and between them. These relationships account for the static and the dynamic or rheologic behaviour. A back-analysis process based on a matching procedure between measured and computed quantities allows one to characterize the pile/soil interaction in terms of constitutive and rheologic parameters based on the dynamic measurements. After optimisation of the matching procedure, the parameters obtained are used to simulate the “static” load-settlement curve. The matching procedure is based on an automatic and stochastic parameter perturbation analysis. Since the parameters influence the system response with a relative weight, they are sorted in order to optimise all the parameters by successively retrieving the most influential ones and working on the remaining ones. The back-analysis performed on real dynamic measurements in this research leads to an improved pile/soil interaction model. The slippage between pile and soil along the pile shaft must be explicitly taken into account. This refinement increases the number of degrees of freedom needed to describe the pile/soil system but brings deeper insight into the behaviour of an interfacing zone of limited thickness surrounding the pile shaft.

During the last decade, the Internet usage has been growing at an enormous rate which has beenaccompanied by the developments of network applications (e.g., video conference, audio/videostreaming, E-learning, E-Commerce and real-time applications) and allows several types ofinformation including data, voice, picture and media streaming. While end-users are demandingvery high quality of service (QoS) from their service providers, network undergoes a complex trafficwhich leads the transmission bottlenecks. Considerable effort has been made to study thecharacteristics and the behavior of the Internet. Simulation modeling of computer networkcongestion is a profitable and effective technique which fulfills the requirements to evaluate theperformance and QoS of networks. To simulate a single congested link, simulation is run with asingle load generator while for a larger simulation with complex traffic, where the nodes are spreadacross different geographical locations generating distributed artificial loads is indispensable. Onesolution is to elaborate a load generation system based on master/slave architecture.

The main objective of this research was to study the buckling and post-buckling response of axially restrained beam-columns under thermal loading. Also the effects of slenderness ratios on pre-buckling and post-buckling behavior which is neglected in AISC specification was examined. The results of this study indicate that: a) Both the deflection and end moment amplification factors are significantly smaller for the restrained beam-columns subjected to temperature increase than the corresponding unrestrained beam-columns subjected to (mechanical) axial loads. b) The deflection amplification factors tend to decrease with decreasing ratio of end moments. However, reverse seems to occur for the moment amplification factors and as the moment amplification factors tend to increase with decreasing moment ratio particularly in the pre-buckling and the initial post-buckling range (0.1 < T/Tcr < 1.5). c) The thermal amplification factors tend to be smaller than the AISC values even in the pre-buckling range with those for the slender beam-columns significantly smaller than those for the shorter beam-columns.

Nesta dissertação são analisadas 34 provas de carga estática realizadas em estacas pré-moldadas de concreto, cravadas em diferentes locais da cidade de Curitiba e região metropolitana, sendo a maioria delas na Formação Guabirotuba. Três métodos de previsão da capacidade foram analisados: Aoki – Velloso (1975), Décourt – Quaresma (1978) e Amaral (1982, 1999). Para cada método foram propostos fatores de correção global e/ou parcial que tornam o valor da capacidade de carga mais próximo do valor da carga última obtida pelo critério de Van der Veen (1953). Com base em quatro provas de carga conduzidas até a ruptura, estudou-se a aplicabilidade do método de Van der Veen (1953) e determinou-se um critério para avaliar a extrapolação da curva carga x recalque em ensaios encerrados sem atingir a ruptura. Finalmente fez-se uma análise dos recalques comparando-se os valores medidos com os calculados, para três níveis de carregamento, além da comparação das curvas carga x recalque ajustadas com as experimentais. / This thesis presents the analysis of 34 static loading tests in concrete drive pile, located at different places of the Curitiba city and metropolitan area, in Guabirotuba Formation. Three methods of the bearing capacity prediction were assessed: Aoki – Velloso (1975), Décourt – Quaresma (1978) and Amaral (1982, 1999). For each method is proposed global correction factors and/or partial that turned the bearing capacity value close to the ultimate load obtained for the Van der Veen criteria (1953). Based on four static loading test carried out to failure, the applicability of the Van der Veen criteria was assessed and was determined a rule to evaluate the extrapolation of the load - settlement curve in tests stopped before of the failure. Finally, it was made an analysis of the settlements, where it was compared the observed values and the predicted values, for three loading level, and also a comparison between the experimental load-settlement curve and the predicted load-settlement curve.