| 61. |
- Abdalmoaty, Mohamed, 1986-
(author)
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Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions
- 2019
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Doctoral thesis (other academic/artistic)abstract
- Data-driven modeling of stochastic nonlinear systems is recognized as a very challenging problem, even when reduced to a parameter estimation problem. A main difficulty is the intractability of the likelihood function, which renders favored estimation methods, such as the maximum likelihood method, analytically intractable. During the last decade, several numerical methods have been developed to approximately solve the maximum likelihood problem. A class of algorithms that attracted considerable attention is based on sequential Monte Carlo algorithms (also known as particle filters/smoothers) and particle Markov chain Monte Carlo algorithms. These algorithms were able to obtain impressive results on several challenging benchmark problems; however, their application is so far limited to cases where fundamental limitations, such as the sample impoverishment and path degeneracy problems, can be avoided.This thesis introduces relatively simple alternative parameter estimation methods that may be used for fairly general stochastic nonlinear dynamical models. They are based on one-step-ahead predictors that are linear in the observed outputs and do not require the computations of the likelihood function. Therefore, the resulting estimators are relatively easy to compute and may be highly competitive in this regard: they are in fact defined by analytically tractable objective functions in several relevant cases. In cases where the predictors are analytically intractable due to the complexity of the model, it is possible to resort to {plain} Monte Carlo approximations. Under certain assumptions on the data and some conditions on the model, the convergence and consistency of the estimators can be established. Several numerical simulation examples and a recent real-data benchmark problem demonstrate a good performance of the proposed method, in several cases that are considered challenging, with a considerable reduction in computational time in comparison with state-of-the-art sequential Monte Carlo implementations of the ML estimator.Moreover, we provide some insight into the asymptotic properties of the proposed methods. We show that the accuracy of the estimators depends on the model parameterization and the shape of the unknown distribution of the outputs (via the third and fourth moments). In particular, it is shown that when the model is non-Gaussian, a prediction error method based on the Gaussian assumption is not necessarily more accurate than one based on an optimally weighted parameter-independent quadratic norm. Therefore, it is generally not obvious which method should be used. This result comes in contrast to a current belief in some of the literature on the subject. Furthermore, we introduce the estimating functions approach, which was mainly developed in the statistics literature, as a generalization of the maximum likelihood and prediction error methods. We show how it may be used to systematically define optimal estimators, within a predefined class, using only a partial specification of the probabilistic model. Unless the model is Gaussian, this leads to estimators that are asymptotically uniformly more accurate than linear prediction error methods when quadratic criteria are used. Convergence and consistency are established under standard regularity and identifiability assumptions akin to those of prediction error methods.Finally, we consider the problem of closed-loop identification when the system is stochastic and nonlinear. A couple of scenarios given by the assumptions on the disturbances, the measurement noise and the knowledge of the feedback mechanism are considered. They include a challenging case where the feedback mechanism is completely unknown to the user. Our methods can be regarded as generalizations of some classical closed-loop identification approaches for the linear time-invariant case. We provide an asymptotic analysis of the methods, and demonstrate their properties in a simulation example.
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| 62. |
- Abdalmoaty, Mohamed, 1986-
(author)
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Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors
- 2017
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Licentiate thesis (other academic/artistic)abstract
- The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.
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| 63. |
- Abdelmotteleb, Ibtihal, 1988-
(author)
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Designing Electricity Distribution Network Charges for an Efficient Integration of Distributed Energy Resources and Customer Response
- 2018
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Doctoral thesis (other academic/artistic)abstract
- A significant transformation has been gradually taking place within the energy sector, mainly as a result of energy policies targeting environmental objectives. Consequently, the penetration of Distributed Energy Resources (DERs) has been escalating, including self-generation, demand side management, storage, and electrical vehicles. Although the integration of DERs may create technical challenges in the operation of distribution networks, it may also provide opportunities to more efficiently manage the network and defer network reinforcements. These opportunities and challenges impose the necessity of redesigning distribution network charges to incentivize efficient customer response.This PhD thesis focuses on the design of distribution network charges that send correct economic signals and trigger optimal responses within the context of active customers. First, a cost-reflective network charge is proposed that consists of a forward-looking locational component based on the network’s utilization level, which transmits the long-term incremental cost of network upgrades. Then, a residual cost component that recovers the remaining part of the regulated network revenues is proposed. The objective of the proposed network charge is to increase the system’s efficiency by incentivizing efficient short- and long-term customers’ reaction while ensuring network cost recovery. The Thesis presents an optimization model that simulates customers’ response to the proposed network charge in comparison to other traditional network charge designs. The model considers the operational and DER investment decisions that customers take rationally to minimize their total costs.Secondly, an evaluation methodology based on the Analytical Hierarchy Process technique is proposed in order to assess and compare different designs of network charges with respect to four attributes: network cost recovery, deferral of network costs, efficient customer response and recognition of side-effects on customers.Finally, a framework for Local Flexibility Mechanisms (LFM) is presented, complementing the proposed cost-reflective network charge. It aims to provide distribution-level coordination to mitigate unintended customer responses to network charges, by allowing customers to reveal their preferences and offer their flexibility services. It consists of a short-term LFM that utilizes customers’ flexibility in day-to-day network operation, and a long-term LFM that procures customers’ long-term flexibility to replace partially or fully network investments in network planning.
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| 64. |
- Abdi, Adel
(author)
-
Efficient Winter Road Maintenance : A Study of Technical and Contractual Issues
- 2014
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Doctoral thesis (other academic/artistic)abstract
- Since ancient times, roads have tied people and cultures together. Roads have been createdwith the aim of facilitating trade and cultural exchange among different regions in the world. After the technologic development in vehicle industry and dramatically increase of motoring in the world during the past century road communication has gained a great importance for transporting people and goods. Thus, good safety and accessibility on roads all year round is now a vital necessity for a healthy economy in all modern societies. In order to keep roads safe, available for use with high transport quality they need to be maintained in real time. One of the most difficult tasks in this context is to keep the roads in good condition and accessible even during winter. The main objective of this doctoral thesis is to attempt to specify the most efficient ways of executing winter road maintenance. The preliminary issue in this context is whether it is the use of current assistive tools, that is, technical aspects that should be optimized and developed or whether it is the way in which winter maintenance services are procured and outsourced, that is, contractual aspects that should be improved which could give the optimal impact for both clients and contractors and make winter road maintenance more effective, or both issues. In order to define the outline of the research project a comprehensive state of the art survey was initiated with the intention of collecting and gaining insights into the earlier studies in the research area. Three basic areas associated with the performance of winter road maintenance were considered to be most relevant for review due to the anchorage between the areas. The selected areas were climatological, technical and contractual aspects. The literature review was followed by an electronic questionnaire survey. The results of the study in this stage showed that current technical methods almost functioned in a reasonable manner but there was an imprecise dissatisfaction with the current maintenance contract. The second stage of the research consisted of a number of additional empirical investigations in order to identify contractual problematic issues behind the current winter road maintenance in Sweden. Generally, those factors that are rarely considered as potential underlying causes to costly performance of winter road maintenance in Sweden were studied in this research project for example improper use of related technical assistive tools, procurement of improper bundled winter services and inappropriate contract structure. This thesis consists of six papers, five of which are related to each other, and the first one is completely independent but within research area. Findings in the thesis contributes to extend understanding about; how designing appropriate contracts can improve winter road maintenance, how proper use of assistive tools can reduce unnecessary winter road maintenance costs and minimize road traffic disruptions and delays, how a partnering structure in contracts can create confidence and trust between clients and contractors that in turn leads to minimizing or eliminating conflicts and disputes between parties involved, how choice of appropriate procurement methods through proper bundling of winter road services can contribute to shorten the procurement process and create incentives for contractors, and how selection of proper payment mechanisms can contribute to higher service quality of performed winter road measures. Additionally, an adequate knowledge and understanding of climate, proper knowledge of road weather and its impact on winter road traffic is essential for contribution of better planning of how to maintain the road network during winter. Since understanding about winter issues and its effect on winter road traffic is far from complete and winter road maintenance in the cold regions is a similar challenge, broad and complex, the results of this research may even contribute to improving winter maintenance problems in the countries with severe winters like Sweden.
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| 65. |
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| 66. |
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| 67. |
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| 68. |
- Abdi, Amir, 1987-
(author)
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Heat Transfer Enhancement of Latent Thermal Energy Storage in Rectangular Components
- 2022
-
Doctoral thesis (other academic/artistic)abstract
- Latent Thermal Energy Storage (LTES) is an interesting choice to storethermal energy in a sustainable energy system. The primary benefit of LTESis the relatively high latent heat of fusion of the materials, known as PhaseChange Materials (PCM), used in such a system as the storage medium.However, as the thermal conductivity of PCMs is often very low, there is aneed to enhance the rate of heat transfer within the charging/dischargingprocess and to improve the thermal performance of the LTES systems.This thesis addresses the enhancing effect of extending heat transfer area inrectangular LTES enclosures. A key contribution of this thesis is acomprehensive visualization of the phase change processes for an organicPCM, including solidification and melting, constrained as well asunconstrained, known as Close-Contact Melting (CCM), in a cavity with andwithout fins. Observations have been carried out for fins of different lengthsand numbers with a varying angle of inclination, and a comprehensive analysisin terms of phase change time and thermal power is conducted.The observations show fins are more influential in solidification than inmelting, reducing the solidification time by 80% and increasing the meanpower by 395%, at a cost of 10% loss in the extracted energy. In contrast, inmelting, fins have a modest effect in enhancing the process. The relativeenhancement effect of fin is higher in constrained melting than inunconstrained melting. In a case with maximum enhancement, a reduction by52% in the constrained melting time and a relative enhancement in the meanpower by 90% is achieved at a cost of 9% loss in the stored energy. As thevolume fraction of fin increases, the discrepancies in melting time betweenthe constrained and unconstrained melting diminishes.A numerical model for solidification and constrained melting is validatedbased on the experiments, and a more inclusive sensitivity analysis of finparameters is performed. The enhancing effect of different parameters on thephase change time and the thermal power is analyzed and the relatively moreeffective measures are identified. Analyzing the simulation data withdimensionless parameters for a cavity oriented horizontally and enhancedwith vertical fins, overall dimensionless groups for solidification and constrained melting have been obtained. The dimensionless groupscontribute in general to achieving a better understanding of fins parametersand to facilitating the LTES designs.In addition, this thesis investigates a novel idea of extending the surface areavia incorporating mini-channels into LTES enclosures, used as passages forair as a low thermal conductive Heat Transfer Fluid (HTF). The mini-scaleinternal hydraulic diameter of the mini-channels and their high external areato-volume ratios make a potential for dual enhancement on both the PCMside and the HTF side. An existing design and a conceptual one with thepossibility of adding fins on the PCM side, capable of being manufactured viaproduction methods of extrusion and Additive Manufacturing (AM),respectively, have been simulated and studied.The two mini-channel types provide considerable enhancements in the rateof heat transfer for a PCM heat exchanger working with air. The degree ofenhancement increases as the air flow rate increases, at the cost of anincreasingly higher pressure drop. Regarding this, increasing the number ofchannels is identified as a more effective enhancing measure than adding finsto the PCM side. In addition, the conceptual design with a higher internalhydraulic diameter and considerably a higher aspect ratio has a lower pressuredrop than the existing design, charging/discharging the thermal energy at asimilar rate but with a lower fan power. More optimized designs withminimization of pressure drop, contribute to paving the way in facilitation ofthe utilization of the enhanced air-PCM heat exchanger in variousapplications.
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| 69. |
- Abdul Abas, Riad
(author)
-
Experimental Studies of Thermal Diffusivities concerning some Industrially Important Systems
- 2006
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Doctoral thesis (other academic/artistic)abstract
- The main objective of this industrially important work was to gain an increasing understanding of the properties of some industrially important materials such as CMSX-4 nickel base super alloy, 90Ti.6Al.4V alloy, 25Cr:6Ni stainless steel, 0.7% carbon steel, AISI 304 stainless steel-alumina composites, mould powder used in continuous casting of steel as well as coke used in blast furnace with special reference to the thermal diffusivities. The measurements were carried out in a wide temperature range covering solid, liquid, glassy and crystalline states. For CMSX-4 alloy, the thermal conductivities were calculated from the experimental thermal diffusivities. Both the diffusivities and conductivities were found to increase with increasing temperature. Microscopic analysis showed the presence of intermetallic phases γ´ such as Ni3Al below 1253 K. In this region, the mean free path of the electrons and phonons is likely to be limited by scattering against lattice defects. Between 1253 K and solidus temperature, these phases dissolved in the alloy adding to the impurities in the matrix, which, in turn, caused a decrease in the thermal diffusivity. This effect was confirmed by annealing the samples at 1573 K. The thermal diffusivities of the annealed samples measured at 1277, 1403 and 1531 K were found to be lower than the thermal diffusivities of non-annealed samples and the values did not show any noticeable change with time. It could be related to the attainment of equilibrium with the completion of the dissolution of γ´ phase during the annealing process. Liquid CMSX-4 does not show any change of thermal diffusivity with temperature. It may be attributed to the decrease of the mean free path being shorter than characteristic distance between two neighbouring atoms. Same tendency could be observed in the case of 90Ti.6Al.4V alloy. Since the thermal diffusivity increases with increasing temperature below 1225 K and shows slight decrease or constancy at higher temperature. For 25Cr:6Ni stainless steel, the thermal diffusivity is nearly constant up to about 700 K. Beyond that, there is an increase with temperature both during heating as well as cooling cycle. On the other hand, the slope of the curve increases above 950 K, which can be due to the increase of bcc phase in the structure. 0.7% carbon steel shows a decrease in the thermal diffusivity at temperature below Curie point, where the structure contains bcc+ fcc phases. Above this point the thermal diffusivity increases, where the structure contains only fcc phase. The experimental thermal conductivity values of these alloys show good agreement with the calculated values using Mills model. Thermal diffusivity measurements as a function of temperature of sintered AISI 304 stainless steel-alumina composites having various composition, viz, 0.001, 0.01, 0.1, 1, 2, 3, 5, 7, 8 and 10 wt% Al2O3 were carried out in the present work. The thermal diffusivity as well as the thermal conductivity were found to increase with temperature for all composite specimens. The thermal diffusivity/conductivity decreases with increasing weight fraction of alumina in the composites. The experimental results are in good agreement with simple rule of mixture, Eucken equation and developed Ohm´s law model at weight fraction of alumina below 5 wt%. Beyond this, the thermal diffusivity/ conductivity exhibits a high discrepancy probably due to the agglomeration of alumina particles during cold pressing and sintering. On the other hand, thermal diffusivities of industrial mould flux having glassy and crystalline states decrease with increasing temperature at lower temperature and are constant at higher temperature except for one glassy sample. The thermal diffusivity is increased with increasing crystallisation degree of mould flux, which is expected from theoretical considerations. Analogously, the thermal diffusivity measurements of mould flux do not show any significant change with temperature in liquid state. It is likely to be due to the silicate network being largely broken down. In the case of coke, the sample taken from deeper level of the pilot blast furnace is found to have larger thermal diffusivity. This can be correlated to the average crystallite size along the structural c-axis, Lc, which is indicative of the higher degree of graphitisation. This was also confirmed by XRD measurements of the different coke samples. The degree of graphitisation was found to increase with increasing temperature. Further, XRD and heat capacity measurements of coke samples taken from different levels in the shaft of the pilot blast furnace show that the graphitisation of coke was instantaneous between 973 and 1473 K.
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| 70. |
- Abdul Khader, Shahbaz
(author)
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Data-Driven Methods for Contact-Rich Manipulation: Control Stability and Data-Efficiency
- 2021
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Doctoral thesis (other academic/artistic)abstract
- Autonomous robots are expected to make a greater presence in the homes and workplaces of human beings. Unlike their industrial counterparts, autonomous robots have to deal with a great deal of uncertainty and lack of structure in their environment. A remarkable aspect of performing manipulation in such a scenario is the possibility of physical contact between the robot and the environment. Therefore, not unlike human manipulation, robotic manipulation has to manage contacts, both expected and unexpected, that are often characterized by complex interaction dynamics.Skill learning has emerged as a promising approach for robots to acquire rich motion generation capabilities. In skill learning, data driven methods are used to learn reactive control policies that map states to actions. Such an approach is appealing because a sufficiently expressive policy can almost instantaneously generate appropriate control actions without the need for computationally expensive search operations. Although reinforcement learning (RL) is a natural framework for skill learning, its practical application is limited for a number of reasons. Arguably, the two main reasons are the lack of guaranteed control stability and poor data-efficiency. While control stability is necessary for ensuring safety and predictability, data-efficiency is required for achieving realistic training times. In this thesis, solutions are sought for these two issues in the context of contact-rich manipulation.First, this thesis addresses the problem of control stability. Despite unknown interaction dynamics during contact, skill learning with stability guarantee is formulated as a model-free RL problem. The thesis proposes multiple solutions for parameterizing stability-aware policies. Some policy parameterizations are partly or almost wholly deep neural networks. This is followed by policy search solutions that preserve stability during random exploration, if required. In one case, a novel evolution strategies-based policy search method is introduced. It is shown, with the help of real robot experiments, that Lyapunov stability is both possible and beneficial for RL-based skill learning.Second, this thesis addresses the issue of data-efficiency. Although data-efficiency is targeted by formulating skill learning as a model-based RL problem, only the model learning part is addressed. In addition to benefiting from the data-efficiency and uncertainty representation of the Gaussian process, this thesis further investigates the benefits of adopting the structure of hybrid automata for learning forward dynamics models. The method also includes an algorithm for predicting long-term trajectory distributions that can represent discontinuities and multiple modes. The proposed method is shown to be more data-efficient than some state-of-the-art methods.
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