MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Initializing the DSSAT-Century model: inverse calibration of carbon pools from apparent soil N mineralization

The CENTURY soil organic matter model was adapted for the DSSAT (Decision Support System for Agrotechnology Transfer), modular format in order to better simulate the dynamics of soil organic nutrient processes (Gijsman et al., 2002). The CENTURY model divides the soil organic carbon (SOC) into three hypothetical pools: microbial or active material (SOC1), intermediate (SOC2) and the largely inert and stable material (SOC3) (Jones et al., 2003). At the beginning of the simulation, CENTURY model needs a value of SOC3 per soil layer which can be estimated by the model (based on soil texture and management history) or given as an input. Then, the model assigns about 5% and 95% of the remaining SOC to SOC1 and SOC2, respectively. The model performance when simulating SOC and nitrogen (N) dynamics strongly depends on the initialization process. The common methods (e.g. Basso et al., 2011) to initialize SOC pools deal mostly with carbon (C) mineralization processes and less with N. Dynamics of SOM, SOC, and soil organic N are linked in the CENTURY-DSSAT model through the C/N ratio of decomposing material that determines either mineralization or immobilization of N (Gijsman et al., 2002). The aim of this study was to evaluate an alternative method to initialize the SOC pools in the DSSAT-CENTURY model from apparent soil N mineralization (Napmin) field measurements by using automatic inverse calibration (simulated annealing). The results were compared with the ones obtained by the iterative initialization procedure developed by Basso et al., 2011.

Cross-validated maximum likelihood enhances crystallographic simulated annealing refinement

Recently, the target function for crystallographic refinement has been improved through a maximum likelihood analysis, which makes proper allowance for the effects of data quality, model errors, and incompleteness. The maximum likelihood target reduces the significance of false local minima during the refinement process, but it does not completely eliminate them, necessitating the use of stochastic optimization methods such as simulated annealing for poor initial models. It is shown that the combination of maximum likelihood with cross-validation, which reduces overfitting, and simulated annealing by torsion angle molecular dynamics, which simplifies the conformational search problem, results in a major improvement of the radius of convergence of refinement and the accuracy of the refined structure. Torsion angle molecular dynamics and the maximum likelihood target function interact synergistically, the combination of both methods being significantly more powerful than each method individually. This is demonstrated in realistic test cases at two typical minimum Bragg spacings (dmin = 2.0 and 2.8 Å, respectively), illustrating the broad applicability of the combined method. In an application to the refinement of a new crystal structure, the combined method automatically corrected a mistraced loop in a poor initial model, moving the backbone by 4 Å.

DNA annealing by Rad52 Protein is stimulated by specific interaction with the complex of replication protein A and single-stranded DNA

Homologous recombination in Saccharomyces cerevisiae depends critically on RAD52 function. In vitro, Rad52 protein preferentially binds single-stranded DNA (ssDNA), mediates annealing of complementary ssDNA, and stimulates Rad51 protein-mediated DNA strand exchange. Replication protein A (RPA) is a ssDNA-binding protein that is also crucial to the recombination process. Herein we report that Rad52 protein effects the annealing of RPA–ssDNA complexes, complexes that are otherwise unable to anneal. The ability of Rad52 protein to promote annealing depends on both the type of ssDNA substrate and ssDNA binding protein. RPA allows, but slows, Rad52 protein-mediated annealing of oligonucleotides. In contrast, RPA is almost essential for annealing of longer plasmid-sized DNA but has little effect on the annealing of poly(dT) and poly(dA), which are relatively long DNA molecules free of secondary structure. These results suggest that one role of RPA in Rad52 protein-mediated annealing is the elimination of DNA secondary structure. However, neither Escherichia coli ssDNA binding protein nor human RPA can substitute in this reaction, indicating that RPA has a second role in this process, a role that requires specific RPA–Rad52 protein interactions. This idea is confirmed by the finding that RPA, which is complexed with nonhomologous ssDNA, inhibits annealing but the human RPA–ssDNA complex does not. Finally, we present a model for the early steps of the repair of double-strand DNA breaks in yeast.

Rescue of stalled replication forks by RecG: Simultaneous translocation on the leading and lagging strand templates supports an active DNA unwinding model of fork reversal and Holliday junction formation

Modification of damaged replication forks is emerging as a crucial factor for efficient chromosomal duplication and the avoidance of genetic instability. The RecG helicase of Escherichia coli, which is involved in recombination and DNA repair, has been postulated to act on stalled replication forks to promote replication restart via the formation of a four-stranded (Holliday) junction. Here we show that RecG can actively unwind the leading and lagging strand arms of model replication fork structures in vitro. Unwinding is achieved in each case by simultaneous interaction with and translocation along both the leading and lagging strand templates at a fork. Disruption of either of these interactions dramatically inhibits unwinding of the opposing duplex arm. Thus, RecG translocates simultaneously along two DNA strands, one with 5′-3′ and the other with 3′-5′ polarity. The unwinding of both nascent strands at a damaged fork, and their subsequent annealing to form a Holliday junction, may explain the ability of RecG to promote replication restart. Moreover, the preferential binding of partial forks lacking a leading strand suggests that RecG may have the ability to target stalled replication intermediates in vivo in which lagging strand synthesis has continued beyond the leading strand.

Chaperonin-facilitated protein folding: optimization of rate and yield by an iterative annealing mechanism.

We develop a heuristic model for chaperonin-facilitated protein folding, the iterative annealing mechanism, based on theoretical descriptions of "rugged" conformational free energy landscapes for protein folding, and on experimental evidence that (i) folding proceeds by a nucleation mechanism whereby correct and incorrect nucleation lead to fast and slow folding kinetics, respectively, and (ii) chaperonins optimize the rate and yield of protein folding by an active ATP-dependent process. The chaperonins GroEL and GroES catalyze the folding of ribulose bisphosphate carboxylase at a rate proportional to the GroEL concentration. Kinetically trapped folding-incompetent conformers of ribulose bisphosphate carboxylase are converted to the native state in a reaction involving multiple rounds of quantized ATP hydrolysis by GroEL. We propose that chaperonins optimize protein folding by an iterative annealing mechanism; they repeatedly bind kinetically trapped conformers, randomly disrupt their structure, and release them in less folded states, allowing substrate proteins multiple opportunities to find pathways leading to the most thermodynamically stable state. By this mechanism, chaperonins greatly expand the range of environmental conditions in which folding to the native state is possible. We suggest that the development of this device for optimizing protein folding was an early and significant evolutionary event.

Modelling of transient heat transfer in annealing furnaces

This is a study of heat transfer in a lift-off furnace which is employed in the batch annealing of a stack of coils of steel strip. The objective of the project is to investigate the various factors which govern the furnace design and the heat transfer resistances, so as to reduce the time of the annealing cycle, and hence minimize the operating costs. The work involved mathematical modelling of patterns of gas flow and modes of heat transfer. These models are: Heat conduction and its conjectures in the steel coils;Convective heat transfer in the plates separating the coils in the stack and in other parts of the furnace; and Radiative and convective heat transfer in the furnace by using the long furnace model. An important part of the project is the development of numerical methods and computations to solve the transient models. A limited number of temperature measurements was available from experiments on a test coil in an industrial furnace. The mathematical model agreed well with these data. The model has been used to show the following characteristics of annealing furnaces, and to suggest further developments which would lead to significant savings: - The location of the limiting temperature in a coil is nearer to the hollow core than to the outer periphery. - Thermal expansion of the steel tends to open the coils, reduces their thermal conductivity in the radial direction, and hence prolongs the annealing cycle. Increasing the tension in the coils and/or heating from the core would overcome this heat transfer resistance. - The shape and dimensions of the convective channels in the plates have significant effect on heat convection in the stack. An optimal design of a channel is shown to be of a width-to-height ratio equal to 9. - Increasing the cooling rate, by using a fluidized bed instead of the normal shell and tube exchanger, would shorten the cooling time by about 15%, but increase the temperature differential in the stack. - For a specific charge weight, a stack of different-sized coils will have a shorter annealing cycle than one of equally-sized coils, provided that production constraints allow the stacking order to be optimal. - Recycle of hot flue gases to the firing zone of the furnace would produce a. decrease in the thermal efficiency up to 30% but decreases the heating time by about 26%.

A Markov chain location-allocation meta-model for hurricane relief

An emergency is a deviation from a planned course of events that endangers people, properties, or the environment. It can be described as an unexpected event that causes economic damage, destruction, and human suffering. When a disaster happens, Emergency Managers are expected to have a response plan to most likely disaster scenarios. Unlike earthquakes and terrorist attacks, a hurricane response plan can be activated ahead of time, since a hurricane is predicted at least five days before it makes landfall. This research looked into the logistics aspects of the problem, in an attempt to develop a hurricane relief distribution network model. We addressed the problem of how to efficiently and effectively deliver basic relief goods to victims of a hurricane disaster. Specifically, where to preposition State Staging Areas (SSA), which Points of Distributions (PODs) to activate, and the allocation of commodities to each POD. Previous research has addressed several of these issues, but not with the incorporation of the random behavior of the hurricane's intensity and path. This research presents a stochastic meta-model that deals with the location of SSAs and the allocation of commodities. The novelty of the model is that it treats the strength and path of the hurricane as stochastic processes, and models them as Discrete Markov Chains. The demand is also treated as stochastic parameter because it depends on the stochastic behavior of the hurricane. However, for the meta-model, the demand is an input that is determined using Hazards United States (HAZUS), a software developed by the Federal Emergency Management Agency (FEMA) that estimates losses due to hurricanes and floods. A solution heuristic has been developed based on simulated annealing. Since the meta-model is a multi-objective problem, the heuristic is a multi-objective simulated annealing (MOSA), in which the initial solution and the cooling rate were determined via a Design of Experiments. The experiment showed that the initial temperature (T0) is irrelevant, but temperature reduction (δ) must be very gradual. Assessment of the meta-model indicates that the Markov Chains performed as well or better than forecasts made by the National Hurricane Center (NHC). Tests of the MOSA showed that it provides solutions in an efficient manner. Thus, an illustrative example shows that the meta-model is practical.

O problema de alocação de berços: um estudo das heurísticas simulated annealing e algoritmo genético

Este trabalho apresenta um estudo de caso das heurísticas Simulated Annealing e Algoritmo Genético para um problema de grande relevância encontrado no sistema portuário, o Problema de Alocação em Berços. Esse problema aborda a programação e a alocação de navios às áreas de atracação ao longo de um cais. A modelagem utilizada nesta pesquisa é apresentada por Mauri (2008) [28] que trata do problema como uma Problema de Roteamento de Veículos com Múltiplas Garagens e sem Janelas de Tempo. Foi desenvolvido um ambiente apropriado para testes de simulação, onde o cenário de análise foi constituido a partir de situações reais encontradas na programação de navios de um terminal de contêineres. Os testes computacionais realizados mostram a performance das heurísticas em relação a função objetivo e o tempo computacional, a m de avaliar qual das técnicas apresenta melhores resultados.

In situ transmission electron microscopy ion irradiations of model iron-chromium alloys

Iron-chromium alloys are used as a model to study the microstructural evolution of defects in irradiated structural steel components of a nuclear reactor. We examine the effects of temperature and chromium concentration on the defect evolution and segregation behavior in the early stages of damage. In situ irradiations are conducted in a transmission electron microscope (TEM) at 300°C and 450°C with 150keV iron ions in single crystal Fe14Cr and Fe19Cr bicrystal to doses of 2E15 ions/cm^2. The microstructures resulting from annealing and irradiation of the alloy are characterized by analysis of TEM micrographs and diffraction patterns and compared with those of irradiated pure iron. We found the irradiation temperature to have little effect on the microstructural development. We also found that the presence of chromium in the sample leads to defect populations with small average loop size and no extended or nested loop structures, in contrast to the populations of large extended loops seen in irradiated pure iron. A very weak dependence was found on the specific chromium content of the alloy. Chromium was shown to suppress defect growth by inhibiting defect mobility in the alloy. While defects in pure iron are highly mobile and able to grow, those in the FeCr alloys remained small and relatively motionless due to the pinning effect of the chromium.

A space-time hybrid hourly rainfall model for derived flood frequency analysis

For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.

Search for Higgs Boson Production Beyond the Standard Model Using the Razor Kinematic Variables in pp Collisions at √s=8 TeV and Optimization of Higgs Boson Identification Using a Quantum Annealer

In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy √s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb^-1.

In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at √s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state.

The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson.

We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 ± 0.28, which observation has a p-value of 10^-3 and a local significance of 3.35σ. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5σ deviation from the Standard Model hypothesis over a broader range of the razor plane.

In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.

Raman spectroscopy study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the thermal annealing pathway

We report a multi-wavelength Raman spectroscopy study of the structural changes along the thermal annealing pathway of a poly(furfuryl alcohol) (PFA) derived nanoporous carbon (NPC). The Raman spectra were deconvoluted utilizing G, D, D′, A and TPA bands. The appropriateness of these deconvolutions was confirmed via recovery of the correct dispersive behaviours of these bands. It is proposed that the ID/IG ratio is composed of two parts: one associated with the extent of graphitic crystallites (the Tuinstra–Koenig relationship), and a second related to the inter-defect distance. This model was used to successfully determine the variation of the in-plane size and intra-plane defect density along the annealing pathway. It is proposed that the NPC skeleton evolves along the annealing pathway in two stages: below 1600 °C it was dominated by a reduction of in-plane defects with a minor crystallite growth, and above this temperature growth of the crystallites accelerates as the in-plane defect density approaches zero. A significant amount of transpolyacetylene (TPA)-like structures was found to be remaining even at 2400 °C. These may be responsible for resistance to further graphitization of the PFA-based carbon at higher temperatures.