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Multiphysics modeling and statistical process optimization of the scanning laser epitaxy process applied to additive manufacturing of turbine engine hot-section superalloy componentsAcharya, Ranadip 07 January 2016 (has links)
Scanning Laser Epitaxy (SLE) is a new laser-based layer-by-layer generative manufacturing technology being developed in the Direct Digital Manufacturing Laboratory at Georgia Tech. SLE allows creation of geometrically complex three-dimensional components with as-desired microstructure through controlled melting and solidification of stationary metal-alloy powder placed on top of like-chemistry substrates. The proposed research seeks to garner knowledge about the fundamental physics of SLE through simulation-based studies and apply this knowledge for hot section turbine component repair and ultimately extend the process capability to enable one-step manufacture of complex gas turbine components. Prior methods of repair specifically for hot-section Ni-base superalloys have shown limited success, failed to consistently maintain epitaxy in the repaired part and suffered from several mechanical and metallurgical defects. The use of a fine focused laser beam, close thermal control and overlapping raster scan pattern allows SLE to perform significantly better on a range of so-called “non-weldable” Ni-base superalloys. The process capability is expanded further through closed-loop feedback control of melt pool temperature using an infra-red thermal camera. The process produces dense, crack-free and epitaxial deposit for single-crystal (SX) (CMSX4), equiaxed (René-80, IN 100) and directionally solidified (DS) (René-142) Ni-based superalloys.
However, to enable consistent and repeatable production of defect-free parts and future commercial implementation of the technology several concerns related to process capabilities and fundamental physics need to be addressed. To explore the process capability, the fabricated components are characterized in terms of several geometrical, mechanical and metallurgical parameters. An active-contour based image analysis technique has been developed to obtain several microstructural responses from the optical metallography of sample cross-sections and the process goes through continuous improvement through optimization of the process parameters through subsequent design of experiments. The simulation-based study is aimed at developing a multiphysics model that captures the fundamental physics of the fabrication process and allows the generation of constitutive equations for microstructural transitions and properties. For this purpose, a computational fluid dynamics (CFD) finite-volume solver is used to model the melting and solidification process. The development work also focuses on studying process response to different superalloy materials and implementing a multivariate statistical process control that allows efficient management and optimization of the design parameter space. In contrast to the prior work on single-bead laser scan, the model incorporates the raster scan pattern in SLE and the temperature dependent local property variations. The model is validated through thermal imaging data. The flow-thermal model is further tied to an empirical microstructural model through the active-contour based optical image analysis technique, which enables the identification of several microstructural transitions for laser beam describing a raster scan pattern.
The CFD model can effectively be coupled with finite element solver to assess the stress and deformation and can be coupled with meso-scale models (Cellular Automata) to predict different microstructural evolutions. The research thus allows extending the SLE process to different superalloy materials, performs statistical monitoring of the process, and studies the fundamental physics of the process to enable formulation of constitutive relations for use in closed-loop feedback control; thus imparting ground breaking capability to SLE to fabricate superalloy components with as-desired microstructures.
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Remote sensing of salt-affected soilsMashimbye, Zama Eric 03 1900 (has links)
Thesis (PhD)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Concrete evidence of dryland salinity was observed in the Berg River catchment in the Western
Cape Province of South Africa. Soil salinization is a global land degradation hazard that
negatively affects the productivity of soils. Timely and accurate detection of soil salinity is
crucial for soil salinity monitoring and mitigation. It would be restrictive in terms of costs to use
traditional wet chemistry methods to detect and monitor soil salinity in the entire Berg River
catchment. The goal of this study was to investigate less tedious, accurate and cost effective
techniques for better monitoring.
Firstly, hyperspectral remote sensing (HRS) techniques that can best predict electrical
conductivity (EC) in the soil using individual bands, a unique normalized difference soil salinity
index (NDSI), partial least squares regression (PLSR) and bagging PLSR were investigated.
Spectral reflectance of dry soil samples was measured using an analytical spectral device
FieldSpec spectrometer in a darkroom. Soil salinity predictive models were computed using a
training dataset (n = 63). An independent validation dataset (n = 32) was used to validate the
models. Also, field-based regression predictive models for EC, pH, soluble Ca, Mg, Na, Cl and
SO4 were developed using soil samples (n = 23) collected in the Sandspruit catchment. These
soil samples were not ground or sieved and the spectra were measured using the sun as a source
of energy to emulate field conditions. Secondly, the value of NIR spectroscopy for the prediction
of EC, pH, soluble Ca, Mg, Na, Cl, and SO4 was evaluated using 49 soil samples. Spectral
reflectance of dry soil samples was measured using the Bruker multipurpose analyser
spectrometer. “Leave one out” cross validation (LOOCV) was used to calibrate PLSR predictive
models for EC, pH, soluble Ca, Mg, Na, Cl, and SO4. The models were validated using R2, root
mean square error of cross validation (RMSECV), ratio of prediction to deviation (RPD) and the
ratio of prediction to interquartile distance (RPIQ). Thirdly, owing to the suitability of land
components to map soil properties, the value of digital elevation models (DEMs) to delineate
accurate land components was investigated. Land components extracted from the second version
of the 30-m advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM2), the 90-m shuttle radar topography mission DEM (SRTM DEM), two
versions of the 5-m Stellenbosch University DEMs (SUDEM L1 and L2) and a 5-m DEM
(GEOEYE DEM) derived from GeoEye stereo-images were compared. Land components were delineated using the slope gradient and aspect derivatives of each DEM. The land components
were visually inspected and quantitatively analysed using the slope gradient standard deviation
measure and the mean slope gradient local variance ratio for accuracy.
Fourthly, the spatial accuracy of hydrological parameters (streamlines and catchment
boundaries) delineated from the 5-m resolution SUDEM (L1 and L2), the 30-m ASTER GDEM2
and the 90-m SRTM was evaluated. Reference catchment boundary and streamlines were
generated from the 1.5-m GEOEYE DEM. Catchment boundaries and streamlines were extracted
from the DEMs using the Arc Hydro module for ArcGIS. Visual inspection, correctness index, a
new Euclidean distance index and figure of merit index were used to validate the results. Finally,
the value of terrain attributes to model soil salinity based on the EC of the soil and groundwater
was investigated. Soil salinity regression predictive models were developed using CurveExpert
software. In addition, stepwise multiple linear regression soil salinity predictive models based on
annual evapotranspiration, the aridity index and terrain attributes were developed using
Statgraphics software. The models were validated using R2, standard error and correlation
coefficients. The models were also independently validated using groundwater hydro-census data
covering the Sandspruit catchment. This study found that good predictions of soil salinity based on bagging PLSR using first
derivative reflectance (R2 = 0.85), PLSR using untransformed reflectance (R2 = 0.70), a unique
NDSI (R2 = 0.65) and the untransformed individual band at 2257 nm (R2 = 0.60) predictive
models were achieved. Furthermore, it was established that reliable predictions of EC, pH,
soluble Ca, Mg, Na, Cl and SO4 in the field are possible using first derivative reflectance. The R2
for EC, pH, soluble Ca, Mg, Na, Cl and SO4 predictive models are 0.85, 0.50, 0.65, 0.84, 0.79,
0.81 and 0.58 respectively. Regarding NIR spectroscopy, validation R2 for all the PLSR
predictive models ranged from 0.62 to 0.87. RPD values were greater than 1.5 for all the models
and RMSECV ranged from 0.22 to 0.51. This study affirmed that NIR spectroscopy has the
potential to be used as a quick, reliable and less expensive method for evaluating salt-affected
soils. As regards hydrological parameters, the study concluded that valuable hydrological
parameters can be derived from DEMs. A new Euclidean distance ratio was proved to be a
reliable tool to compare raster data sets. Regarding land components, it was concluded that
higher resolution DEMs are required for delineating meaningful land components. It seems probable that land components may improve salinity modelling using hydrological modelling
and that they can be integrated with other data sets to map soil salinity more accurately at
catchment level. In the case of terrain attributes, the study established that promising soil salinity
predictions could be made based on slope, elevation, evapotranspiration and terrain wetness
index (TWI). Stepwise multiple linear regressions soil salinity predictive model based on
elevation, evapotranspiration and TWI yielded slightly more accurate prediction of soil salinity.
Overall, the study showed that it is possible to enhance soil salinity monitoring using HRS, NIR
spectroscopy, land components, hydrological parameters and terrain attributes. / AFRIKAANSE OPSOMMING: Konkrete bewyse van droëland sout is waargeneem in die Bergrivier opvanggebied in die Wes-
Kaap van Suid-Afrika. Verbrakking van grond is 'n wêreldwye probleem wat ‘n negatiewe
invloed op die produktiwiteit van grond kan hê. Tydige en akkurate herkenning van verandering
in grond soutgehalte is ‘n noodsaaklike aksie vir voorkoming. Dit sou beperkend wees in terme
van koste om konvensionele nat chemiese metodes te gebruik vir die opsporing en monitering
daarvan in die hele Bergrivier opvanggebied. Die doel van hierdie studie was om ondersoek in
te stel na minder tydsame, akkurate en koste-effektiewe tegnieke vir beter monitering.
Eerstens, is hiperspektrale afstandswaarnemings (HRS) tegnieke wat die beste in staat is
elektriese geleidingsvermoë (EG) in die grond te kan voorspel deur gebruik te maak van
individuele bande, 'n unieke genormaliseerde grond soutindeks verskil (NDSI), parsiële kleinste
kwadratiese regressie (PLSR) en afwyking in PLSR, is ondersoek. Spektrale reflektansie van
droë grondmonsters is gemeet deur gebruik te maak van 'n spektrale analitiese toestel: FieldSpec
spektrometer in 'n donkerkamer. Voorspellings modelle vir grond soutgehalte is bereken met
behulp van 'n toets datastel (n = 63). 'n onafhanklike validasie datastel (n = 32) is gebruik om die
modelle te evalueer. Daarbenewens is veld-gebaseerde regressie voorspellings modelle vir EG,
pH oplosbare Ca, Mg, Na, Cl and SO4 ontwikkel deur gebruik te maak van grondmonsters (n =
23) versamel in the Sandpruit opvangsgebied. Hierdie grondmonsters is nie gemaal of gesif nie
en die spectra is gemeet deur gebruik te maak van die son as ‘n bron van energie om veld
toestande na te boots. Tweedens, is die waarde van NIR spektroskopie vir die voorspelling van
die EG, pH, oplosbare Ca, Mg, Na, Cl, en SO4 met behulp van 49 grondmonsters geëvalueer.
Spektrale reflektansie van droë grondmonsters is gemeet deur gebruik te maak van die Bruker
NIR veeldoelige analiseerder . Kruisvalidering (LOOCV) is gebruik om PLSR voorspellings
modelle vir EG, pH, oplosbare Ca, Mg, Na, Cl, en SO4 te kalibreer. Hierdie modelle is
gevalideer: R2, wortel-gemiddelde-kwadraat fout kruisvalidering (RMSECV), verhouding van
voorspellings afwyking (RPD) en die verhouding van die voorspelling se inter-kwartiel afstand (RPIQ). Derdens is land komponente gekarteer vanweë die nut daat van tov grondeienskappe, en
die waarde van DEMs is ondersoek om akkurate land komponente af te baken. Land komponente
uit die tweede weergawe van die 30 m gevorderde ruimte termiese emissie en refleksie radio globale DEM (ASTER GDEM2), die 90-m ruimtetuig radar topografie sending DEM (SRTM
DEM), twee weergawes van die 5 m Universiteit van Stellenbosch DEMs (SUDEM L1 en L2) en
'n 5 m DEM (GEOEYE DEM) afgelei van GeoEye stereo-beelde, is vergelyk. Land komponente
is afgebaken met behulp van helling, gradiënt en aspek afgeleides van elke DEM. Die land
komponente is visueel geïnspekteer en kwantitatief ontleed met behulp van die helling gradiënt
standaardafwyking te meet en die gemiddelde helling-gradiënt-plaaslike variansie verhouding vir
akkuraatheid.
Vierdens, is die ruimtelike akkuraatheid van hidrologiese parameters (stroomlyn en
opvanggebied grense) geëvalueer soos afgelei vanaf die 5 m resolusie SUDEM (L1 en L2), die
30 m ASTER GDEM2 en die 90 m SRTM . Die verwysings opvanggebied grens en stroomlyn is
gegenereer vanaf die 1,5-m GEOEYE DEM. Opvanggebied grense en stroomlyn uit die DEMs is
bepaal deur gebruik te maak van die Arc Hydro module in ArcGIS. Visuele inspeksie,
korrektheid indeks, 'n nuwe Euklidiese afstand indeks en die indikasie-van-meriete indeks is
gebruik om die resultate te valideer. Laastens is die waarde van die terrein eienskappe om grond
southalte te modeleer ondersoek, gebaseer op die EG van die grond en grondwater. Grond
soutgehalte regressie voorspellings modelle is ontwikkel met behulp van CurveExpert sagteware.
Verder, stapsgewyse meervoudige lineêre regressie grond soutgehalte voorspellings modelle
gebaseer op jaarlikse evapotranspirasie, die dorheids indeks en terrein eienskappe is ontwikkel
met behulp van Statgraphics sagteware. Die modelle is gevalideer deur gebruik te maak van R2,
standaardfout en korrelasiekoëffisiënte. Die modelle is ook onafhanklik bekragtig deur die
gebruik van grondwater hidro-sensus-data wat die Sandspruit opvanggebied insluit. Hierdie studie het bevind dat 'n goeie voorspelling van grond soutgehalte gebaseer op uitsak
PLSR met behulp van eerste orde afgeleide reflektansie (R2 = 0,85), PLSR deur gebruik te maak
van ongetransformeerde reflektansie (R2 = 0,70), 'n unieke NDSI (R2 = 0,65) en die
ongetransformeerde individuele band op 2257 nm (R2 = 0,60) voorspellings modelle verkry is.
Verder is vasgestel dat betroubare voorspellings van die EG, pH, oplosbare Ca, Mg, Na, Cl en
SO4 in die veld moontlik is met behulp van eerste afgeleide reflektansie. Die R2 van EG, pH,
oplosbare Ca, Mg, Na, Cl en SO4 is 0.85, 0.50, 0.65, 0.84, 0.79, 0.81 en 0.58 onderskeidelik. Ten
opsigte van NIR spektroskopie het die validasie van R2 vir al die PLSR voorspellings modelle gewissel tussen 0,62-0,87. Die RPD waardes was groter as 1,5 vir al die modelle en RMSECV
het gewissel tussen 0,22-0,51. Hierdie studie het bevestig dat NIR spektroskopie die potensiaal
het om gebruik te word as 'n vinnige, betroubare en goedkoper metode vir die analise van soutgeaffekteerde
gronde. T.o.v. hidrologiese parameters, het die studie tot die gevolgtrekking
gekom dat waardevolle hidrologiese parameters afgelei kan word uit DEMs. 'n nuwe Euklidiese
afstand verhouding is bevestig as 'n betroubare hulpmiddel om raster datastelle te vergelyk. Ten
opsigte van grond komponente, is daar tot die gevolgtrekking gekom dat hoër resolusie DEMs
nodig is vir die bepaling van sinvolle land komponente. Dit lyk waarskynlik dat die land
komponent soutgehalte modellering hidrologiese modellering verbeter en dat hulle geïntegreer
kan word met ander datastelle vir meer akkurate kaarte op opvangsgebied skaal. In die geval van
die terrein eienskappe het, die studie vasgestel dat belowende grond soutgehalte voorspellings
gemaak kan word gebaseer op helling, elevasie, evapotranspirasie en terrein natheid indeks
(TWI). 'n stapsgewyse meervoudige lineêre regressie grond soutgehalte voorspellings model wat
gebaseer is op elevasie, evapotranspirasie en TWI het effens meer akkurate voorspellings van die
grond soutgehalte gelewer. In geheel gesien, het die studie getoon dat dit moontlik is om grond
soutgehalte monitering te verbeter met behulp van HRS, NIR spektroskopie, land komponente,
hidrologiese parameters en terrein eienskappe. / The Agricultural Research Council (ARC), Water Research Commission and the National
Research Foundation for funding.
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Μελέτη των ατμοσφαιρικών ρύπων στην πόλη της Πάτρας με τη μέθοδο της ανάλυσης σε κύριες συνιστώσεςΣούφλα, Ευαγγελία 04 September 2013 (has links)
Μελέτη των ατμοσφαιρικών ρύπων στην πόλη της Πάτρας για το έτος 2010 με τη μέθοδο της ανάλυσης σε κύριες συνιστώσες και κάνοντας χρήση του στατιστικού πακέτου Minitab16 / Research on air pollutants in the city of Patras for the year 2010 using the method of Principal Components Analysis. The results are elaborated using the statistical program minitab16.
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Analysts’ use of earnings components in predicting future earningsBratten, Brian Michael 16 October 2009 (has links)
This dissertation examines the general research issue of whether the components of earnings are informative and specifically 1) how analysts consider earnings components when predicting future earnings and 2) whether the information content in, and analysts’ use of, earnings components have changed through time. Although earnings components have predictive value for future earnings based on each component’s persistence, extant research provides only a limited understanding of whether and how analysts consider this when forecasting. Using an integrated income statement and balance sheet framework to estimate the persistence of earnings components, I first establish that disaggregation based on the earnings components framework in this study is helpful to predict future earnings and helps explains contemporaneous returns. I then find evidence suggesting that although analysts consider the persistence of various earnings components, they do not fully integrate this information into their forecasts. Interestingly, analysts appear to be selective in their incorporation of the information in earnings components, seeming to ignore information from components indicating lower persistence, which results in higher forecast errors. Conversely, when a firm’s income is concentrated in high persistence items, analysts appear to incorporate the information into their forecasts, reducing their forecast errors. I also report that the usefulness of components relative to aggregate earnings has dramatically and continuously increased over the past several decades, and contemporaneous returns appear to be much better explained by earnings components than aggregate earnings (than historically). Finally, the relation between analyst forecast errors and the differential persistence of earnings components has also declined over time, indicating that analysts appear to recognize the increasing importance of earnings components through time. / text
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流動性與買賣價差因子分解:興櫃轉上市櫃之實證研究吳佩玟, Wu,Pei-wen Unknown Date (has links)
The purpose of this paper is to compare the liquidity and the components of the bid-ask spread for thinly traded firms switching from a dealer market (Emerging Stock Market (ESM)) to an order driven market (Taiwan Stock Exchanges (TSE) or GreTai Securities Market (GTSM)). Firstly, we follow Christie and Huang’s (1994) method to measure the liquidity performance. Our finding shows that thinly traded firms could improve their liquidity by switching from a dealer market to an order driven market. Secondly, we apply Huang and Stoll’s (1997) and Lin et al.’s (1995) model to estimate the bid-ask spread components. Our results show that the adverse selection cost is significantly smaller on ESM than TSE or GTSM using both Huang and Stoll’s (1997) and Lin et al.’s (1995) model. The inventory holding cost is lower on ESM than TSE or GTSM estimated by Huang and Stoll’s (1997) model. However, the estimates of order processing cost and the probability of trade reversal do not produce consistent results by applying Huang and Stoll’s (1997) and Lin et al.’s (1995) model.
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Future of Thai Electronic Component Industry under ACFTABoonumpaichaikul, Tossapon, Mongkoltada, Unnada January 2010 (has links)
<p>Explore factors that influence investors interested in investing in the electronic components sector in Thailand, with a focus on the consequences of Thailand‟s membership in the ASEAN-China Free Trade Agreement.</p>
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COMPARISON OF VARIABILITY MODELING TECHNIQUESAkram, Asif, Abbas, Qammer January 2009 (has links)
<p>Variability in complex systems offering rich set of features is a seriouschallenge to their users in term of flexibility with many possible variants fordifferent application contexts and maintainability. During the long period oftime, much effort has been made to deal with these issues. An effort in thisregard is developing and implementing different variability modelingtechniques.This thesis argues the explanation of three modeling techniques namedconfigurable components, feature models and function-means trees. The maincontribution to the research includes:• A comparison of above mentioned variability modeling techniques in asystematic way,• An attempt to find the integration possibilities of these modelingtechniques based on literature review, case studies, comparison,discussions, and brainstorming.The comparison is based on three case studies each of which is implemented inall above mentioned three modeling techniques and a set of generic aspects ofthese techniques which are further divided into characteristics. At the end, acomprehensive discussion on the comparison is presented and in final sectionsome integration possibility are proposed on the basis of case studies,characteristics, commonalities and experience gained through theimplementation of case studies and literature review.</p>
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EVALUATING THE PERFORMANCE AND WATER CHEMISTRY DYNAMICS OF PASSIVE SYSTEMS TREATING MUNICIPAL WASTEWATER AND LANDFILL LEACHATEWallace, JACK 29 October 2013 (has links)
This thesis consists of work conducted in two separate studies, evaluating the performance of passive systems for treating wastewater effluents. The first study involved the characterization of three wastewater stabilization ponds (WSPs) providing secondary and tertiary treatment for municipal wastewater at a facility in Amherstview, Ontario, Canada. Since 2003, the WSPs have experienced excessive algae growth and high pH levels during the summer months. A full range of parameters consisting of: pH, chlorophyll-a (chl-a), dissolved oxygen (DO), temperature, alkalinity, oxidation-reduction potential (ORP), conductivity, nutrient species, and organic matter measures; were monitored for the system and the chemical dynamics in the three WSPs were assessed through multivariate statistical analysis. Supplementary continuous monitoring of pH, chl-a, and DO was performed to identify time-series dependencies. The analyses showed strong correlations between chl-a and sunlight, temperature, organic matter, and nutrients, and strong time dependent correlations between chl-a and DO and between chl-a and pH. Additionally, algae samples were collected and analyzed using metagenomics methods to determine the distribution and speciation of algae growth in the WSPs. A strong shift from the dominance of a major class of green algae, chlorophyceae, in the first WSP, to the dominance of land plants, embryophyta – including aquatic macrophytes – in the third WSP, was observed and corresponded to field observations during the study period. The second study involved the evaluation of the performance and chemical dynamics of a hybrid-passive system treating leachate from a municipal solid waste (MSW) landfill in North Bay, Ontario, Canada. Over a three year period, monitoring of a full range of parameters consisting of: pH, DO, temperature, alkalinity, ORP, conductivity, sulfate, chloride, phenols, solids fractions, nutrient species, organic matter measures, and metals; was conducted bi-weekly and the dataset was analyzed with time series and multivariate statistical techniques. Regression analyses identified 8 parameters that were most frequently retained for modelling the five criteria parameters (alkalinity, ammonia, chemical oxygen demand, iron, and heavy metals), on a statistically significant level (p < 0.05): conductivity, DO, nitrite, organic nitrogen, ORP, pH, sulfate, and total volatile solids. / Thesis (Master, Civil Engineering) -- Queen's University, 2013-10-27 05:29:20.564
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Evaluating the Use of Ridge Regression and Principal Components in Propensity Score Estimators under MulticollinearityGripencrantz, Sarah January 2014 (has links)
Multicollinearity can be present in the propensity score model when estimating average treatment effects (ATEs). In this thesis, logistic ridge regression (LRR) and principal components logistic regression (PCLR) are evaluated as an alternative to ML estimation of the propensity score model. ATE estimators based on weighting (IPW), matching and stratification are assessed in a Monte Carlo simulation study to evaluate LRR and PCLR. Further, an empirical example of using LRR and PCLR on real data under multicollinearity is provided. Results from the simulation study reveal that under multicollinearity and in small samples, the use of LRR reduces bias in the matching estimator, compared to ML. In large samples PCLR yields lowest bias, and typically was found to have the lowest MSE in all estimators. PCLR matched ML in bias under IPW estimation and in some cases had lower bias. The stratification estimator was heavily biased compared to matching and IPW but both bias and MSE improved as PCLR was applied, and for some cases under LRR. The specification with PCLR in the empirical example was usually most sensitive as a strongly correlated covariate was included in the propensity score model.
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Damage assessment by Acoustic Emission (AE) during landing gear fatigue testingBaxter, Matt January 2007 (has links)
No description available.
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