Dissertations / Theses on the topic 'Response surface'

Objective: Topography, chemistry, and energy of titanium (Ti) implants alter cell response through variations in protein adsorption, integrin expression, and downstream cell signaling. However, the contribution of surface energy on cell response is difficult to isolate because altered hydrophilicity can result from changes in surface chemistry or microstructure. Our aim was to examine a unique system of wettability gradients created on microstructured Ti on osteoblast maturation and phenotype. Method: A surface energy gradient was created on sand-blasted/acid-etched (SLA) Ti surfaces. Surfaces were treated with oxygen plasma for 2 minutes, and then allowed to age for 1, 12, 80, or 116 hours to generate a wettability gradient. Surfaces were characterized by contact angle and SEM. MG63 cells were cultured on SLA or experimental SLA surfaces to confluence on TCPS. Osteoblast differentiation (IBSP, RUNX2, ALP, OCN, OPG) and integrin subunits (ITG2, ITGA5, ITGAV, ITGB1) measured by real-time PCR (n=6 surfaces per variable analyzed by ANOVA/Bonferroni’s modified Student’s t-test). Result: After plasma treatment, SLA surface topography was retained. A gradient of wettability was obtained, with contact angles of 32.0° (SLA116), 23.3° (SLA80), 12.5° (SLA12), 7.9° (SLA1). All surfaces were significantly more hydrophilic than the original SLA surface (126.8°). Integrin expression was affected by wettability. ITGA2 was higher on wettable surfaces than on SLA, but was highest on SLA1. ITGAV and ITGB1 were decreased on hydrophilic surfaces, but ITGA5 was not affected. IBSP, RUNX2, and ALP increased and OPG decreased with increasing wettability. OCN decreased with increasing wettability, but levels on the most wettable surface were similar to SLA. Conclusion: Here we elucidated the role of surface energy on cell response using surfaces with the same topography and chemistry. The results show that osteoblastic maturation was regulated in a wettability-dependent manner and suggest that the effects are mediated by integrins.

Building fragility describes the likelihood of damage to a building due to random ground motions. Conventional methods for computing building fragilities are either based on statistical extrapolation of detailed analyses on one or two specific buildings or make use of Monte Carlo simulation with these models. However, the Monte Carlo technique usually requires a relatively large number of simulations in order to obtain a sufficiently reliable estimate of the fragilities, and it quickly becomes impractical to simulate the required thousands of dynamic time-history structural analyses for physics-based analytical models. An alternative approach for carrying out the structural simulation is explored in this work. The use of Response Surface Methodology in connection with the Monte Carlo simulations simplifies the process of fragility computation. More specifically, a response surface is sought to predict the structural response calculated from complex dynamic analyses. Computational cost required in a Monte Carlo simulation will be significantly reduced since the simulation is performed on a polynomial response surface function, rather than a complex dynamic model. The methodology is applied to the fragility computation of an unreinforced masonry (URM) building located in the New Madrid Seismic Zone. Different rehabilitation schemes for this structure are proposed and evaluated through fragility curves. Response surface equations for predicting peak drift are generated and used in the Monte Carlo simulation. Resulting fragility curves show that the URM building is less likely to be damaged from future earthquakes when rehabilitation is properly incorporated. The thesis concludes with a discussion of an extension of the methodology to the problem of computing fragilities for a collection of buildings of interest. Previous approaches have considered uncertainties in material properties, but this research incorporates building parameters such as geometry, stiffness, and strength variabilities as well as nonstructural parameters (age, design code) over an aggregation of buildings in the response surface models. Simulation on the response surface yields the likelihood of damage to a group of buildings under various earthquake intensity levels. This aspect is of interest to governmental agencies or building owners who are responsible for planning proper mitigation measures for collections of buildings.

This thesis is about the optimization of physical systems (or processes) characterized by a high number of input variables (e.g., operations, machines, methods, people, and materials) and multiple responses (output characteristics). These systems are of interest because they are common scenarios in real-world studies and they present many challenges for practitioners in a wide range of applicative fields (e.g., science, engineering). The first objective of the study was to develop a model-based approach to support the practitioners in planning the experiments and optimizing the system responses. Of interest was the creation of a methodology capable of providing a feedback to the practitioner while taking into account his/her point of view. The second objective was to identify a procedure to select the most promising model, to be combined with the model-based approach, on the basis of the features of the applicative problem of interest. To cope with the first objective, experimental design, modeling and optimization techniques have been combined in a sequential procedure that interacts with the practitioner at each stage. The developed approach has roots in nonparametric and semiparametric response surface ethodology (NPRSM), design and analysis of computer experiments (DACE), multi-objective optimization and swarm intelligence computation. It consists of augmenting an initial experimental design (set of experiments) by sequentially identifying additional design points (experiments) with expected improved performance. The identification of new experimental points is guided by a particle swarm optimization (PSO) algorithm that minimizes a distance-based function. In particular, the distance between the measured response values and a target is minimized. The target is composed of ideal values of the responses and is selected using a multivariate adaptive regression splines (MARS) model, which is updated as soon as new experiments are implemented and the corresponding response values are measured. The developed approach resulted in a sequential procedure named Evolutionary Model-based Multiresponse Approach (EMMA). When tested on a set of benchmark functions, EMMA was shown to overcome the potential problem of premature convergence to a local optimum and to correctly identify the true global optimum. Furthermore, EMMA is distribution-free and it allows the automatic selection of the target, in contrast to the trial-and-error procedures usually employed for this purpose. Finally, EMMA was applied to a real-world chemical problem devoted to the functionalization of a substrate for possible biomedical studies. With respect to the method typically employed by the scientists, improvements of the responses of up to 380% were detected. The proposed approach was thus shown to hold much promise for the optimization of multiresponse high dimensional systems. Moreover, EMMA turned out to be a valuable methodology for industrial research. Indeed, by means of a preliminary simulation study, it gave an initial estimate of the number of experiments and time necessary to achieve a specific goal, thus providing an indication of the budget required for the research. To deal with the second objective of the research, a meta-learning approach for model selection was adopted. Interest in model selection strategies arose from questions such as ‘Is MARS the best model we could have used?’ and ‘Given an applicative problem, how can we select the most promising modeling technique to be combined with EMMA?’. Indeed, it is now generally accepted that no single model can outperform some other models over all possible regression problems. Furthermore, the model performance ‘... may depend on the detailed nature of the problem at hand in terms of the number of observations, the number of response variables, their correlation structure, signal-to-noise ratio, collinearity of the predictor variables, etc.’ (Breiman & Friedman 1997). The meta-learning approach was adopted to select the most promising model on the basis of measurable characteristics of the investigated problem. The basic idea was to study a set of multiresponse regression models and evaluate their performance on a broad class of problems, that were characterized by various degrees of complexity. By matching the problem characteristics and the models’ performance, the aim was to discover the conditions under which a model outperforms others as well as to acquire some rules to be used as a guidance when faced with a new application. The procedures to simulate the datasets were developed, the metrics to measure the problems characteristics were identified, and the R code to evaluate the models’ performances was generated. The foundations for a large computational study was therefore established. Implementation of such study is part of ongoing research, and future works will aim to examine the obtained empirical rules from a theoretical perspective with a view to confirm their validity, as well as generating insights into each model’s behaviour.
La tesi riguarda l’ottimizzazione di sistemi (o processi) fisici caratterizzati da un elevato numero di variabili in ingresso (operazioni, macchine, metodi, persone, materiali) e da più variabili risposta, impiegate per misurare le proprietà del prodotto finale. Questa tipologia di sistemi è molto frequente in un ampio spettro di campi applicativi, che spaziano dalla scienza all’ingegneria, e pone lo sperimentatore di fronte a delle problematiche di non sempre facile risoluzione. Il primo obiettivo di questo studio era di sviluppare un approcio, basato su un modello statistico, che fosse in grado di supportare lo sperimentatore nella pianificazione degli esperimenti e nell’ottimizzazione delle risposte del sistema. Fondamentale era lo sviluppo di una procedura capace di tenere in considerazione il punto di vista dello sperimentatore e fornirgli continuamente un feedback. Il secondo obiettivo della ricerca era l’identificazione di un metodo volto a selezionare il miglior modello statistico, da integrare all’approcio proposto, sulla base delle caratteristiche del problema applicativo investigato. Il primo obiettivo ha portato allo sviluppo di una procedura sequenziale che impiega tecniche di disegno sperimentale, modellazione e ottimizzazione, e che interagisce, ad ogni passo, con lo sperimentatore. La metodologia proposta è stata denominata EMMA e coinvolge varie aree di ricerca scientifica e computazionale, quali superfici di risposta nonparametriche e semiparametriche, disegno e analisi di esperimenti a computer, ottimizzazione multiobiettivo e computazione ispirata al comportamento degli sciami in natura. EMMA prevede l’identificazione di un disegno sperimentale (insieme di esperimenti) che viene successivamente integrato con dei punti sperimentali (esperimenti), identificati in modo sequentiale. Il processo di identificazione dei nuovi punti sperimentali è guidato da un algoritmo di ottimizzazione particle swarm, che minimizza la distanza fra i valori di risposta osservati e un target. Il target è un insieme di valori ottimali, uno per ogni risposta, che vengono selezionati usando un modello di regressione multivariata basato su spline (MARS). Tale target viene aggiornato non appena i nuovi esperimenti vengono implementati e le corrispondenti risposte vengono misurate. Quando testato su un insieme di funzioni standard, EMMA ha dimostrato di poter superare il potenziale problema di convergenza prematura verso un ottimo locale e di poter identificare correttamente il vero ottimo globale. Inoltre, EMMA non richiede nessuna assunzione sulla distribuzione dei dati e, diversamente da altre procedure, permette di selezionare automaticamente il target. Infine, EMMA è stata applicata ad un problema chimico volto alla funzionalizzazione di un substrato per possibili applicazioni biomediche. Rispetto al metodo generalmente usato dagli scienziati, EMMA ha permesso di migliorare le risposte del sistema di vari punti percentuali, e incrementi fino al 380% sono stati osservati. L’approccio proposto costituisce pertanto un metodologia con elevate potenzialità per l’ottimizzazione di sistemi multirisposta ad alta dimensionalità. Inoltre, grazie a degli studi di simulazione, EMMA permette di ottenere una stima iniziale del numero di esperimenti e del tempo necessario per raggiungere il miglioramento desiderato. Di conseguenza, potendo fornire un’indicazione del budget richiesto per lo studio di interesse, la metodologia risulta essere di interesse specialmente nel settore della ricerca industriale. Il secondo obiettivo ha portato allo sviluppo di un approcio di meta-apprendimento per la selezione del modello. L’interesse nella selezione del modello deriva da domande quali ‘E’ MARS il miglior modello che avremmo potuto usare?’ e ‘Dato un problema applicativo, come possiamo selezionare la tecnica di modellazione più promettente da combinare con EMMA?’. Infatti, `e ormai riconosciuto che non esiste un modello le cui performance sono migliori, rispetto ad altre tecniche di modellazione, per tutti i possibili problemi di regressione. Inoltre, le performance di un modello ‘... possono dipendere dalla natura del problema investigato in termini di numero di osservazioni, numero di variabili risposta, struttura di correlazione delle variabili, rapporto segnale-rumore, grado di collinearity dei predittori, etc.’ (Breiman & Friedman 1997). L’approcio di meta-apprendimento è stato adottato per identificare il modello statistico più promettente, sulla base delle caratteristiche del problema investigato. L’idea consisteva nello studiare un insieme di modelli di regressione multirisposta e valutare la loro performance su un’ampia classe di problemi caratterizzati da diversi gradi di complessità. Studiando la relazione fra le caratteristiche del problema e la performance dei modelli, lo scopo è di scoprire sotto quali condizioni un modello è migliore di altri e simultaneamente acquisire alcune regole da poter usare come linee guida nello studio di nuove applicazioni. A tale scopo sono state sviluppate le procedure per simulare i dati, le metriche per misurare le caratteristiche dei problemi, e il codice R necessario per la valutazione delle performance dei modelli. Questo ha permesso di gettare le fondamenta di un ampio studio di simulazione, la cui implementazione fa parte della ricerca attualmente in corso. Lo scopo della ricerca futura è di esaminare, da un punto di vista teorico, le regole empiriche ottenute in modo da poterne confermare la validità, oltre che favorire una migliore comprensione del comportamento delle tecniche di modellazione investigate.

General Response Surface Methodology involves the exploration of some response variable which is a function of other controllable variables. Many criteria exist for selecting an experimental design for the controllable variables. A good choice of a design is one that may not be optimal in a single sense, but rather near optimal with respect to several criteria. This robust approach can lend well to strategies that involve sequential or two stage experimental designs. An experimenter that fits a first order regression model for the response often fears the presence of curvature in the system. Experimental designs can be chosen such that the experimenter who fits a first order model will have a high degree of protection against potential model bias from the presence of curvature. In addition, designs can also be selected such that the experimenter will have a high chance for detection of curvature in the system. A lack of fit test is usually performed for detection of curvature in the system. Ideally, an experimenter desires good detection capabilities along with good protection capabilities. An experimental design criterion that incorporates both detection and protection capabilities is the A₂* criterion. This criterion is used to select the designs which maximize the average noncentrality parameter of the lack of fit test among designs with a fixed bias. The first order rotated design class is a new class of designs that offers an improvement in terms of the A₂* criterion over standard first order factorial designs. In conjunction with a sequential experimental strategy, a class of second order rotated designs are easily constructed by augmenting the first order rotated designs. These designs allow for estimation of second order model terms when a significant lack of fit is observed. Two other design criteria, that are closely related, and incorporate both detection and protection capabilities are the J_PCA, and J_PCMAX criterion. J_PCA, considers the average mean squared error of prediction for a first order model over a region where the detection capabilities of the lack of fit test are not strong. J_PCMAX considers the maximum mean squared error of prediction over the region where the detection capabilities are not strong. The J_PCA and J_PCMAX criteria are used within a sequential strategy to select first order experimental designs that perform well in terms of the mean squared error of prediction when it is likely that a first order model will be employed. These two criteria are also adopted for nonsequential experiments for the evaluation of first order model prediction performance. For these nonsequential experiments, second order designs are used and constructed based upon J_PCA and J_PCMAX for first order model properties and D₂ -efficiency and D-efficiency for second order model properties.
Ph. D.

Central Composite Designs (CCDs) with cuboidal and spherical regions are among the most popular experimental designs for studying response surfaces. Cuboidal regions are typically used when the experimenter believes the levels of one or more of the factors are bounded while a spherical region is employed when there are no restrictions on the levels of any of the factors. We propose what we call a cylindrical design in which the levels of some factors are restricted while the other factors' levels need not be. Assuming the use of a second-order model, we give the general form for the model matrix X of such a design and give a closed form for the determinant of the X 0X matrix as well as its inverse. We use the results for the determinant and inverse of X 0X to compare designs using the alphabetic design optimality criteria. D-efficiencies, A-efficiencies, G-efficiencies, and IV-efficiencies for CCDs will be compared with those of the cylindrical design. Graphical assessment of the maximum spherical prediction variance will also be done. It will be shown that the cylindrical design is an excellent alternative when some but not all factors have restricted levels.

Many industrial statisticians employ the techniques of Response Surface Methodology (RSM) to study and optimize products and processes. A second-order Taylor series approximation is commonly utilized to model the data; however, parametric models are not always adequate. In these situations, any degree of model misspecification may result in serious bias of the estimated response. Nonparametric methods have been suggested as an alternative as they can capture structure in the data that a misspecified parametric model cannot. Yet nonparametric fits may be highly variable especially in small sample settings which are common in RSM. Therefore, semiparametric regression techniques are proposed for use in the RSM setting. These methods will be applied to an elementary RSM problem as well as the robust parameter design problem.
Ph. D.

Statistical research can be more difficult to plan than other kinds of projects, since the research must adapt as knowledge is gained. This dissertation establishes a formal language and methodology for designing experimental research strategies with limited resources. It is a mathematically rigorous extension of a sequential and adaptive form of statistical research called response surface methodology. It uses sponsor-given information, conditions, and resource constraints to decompose an overall project into individual stages. At each stage, a "parent" decision-maker determines what design of experimentation to do for its stage of research, and adapts to the feedback from that research's potential "children", each of whom deal with a different possible state of knowledge resulting from the experimentation of the "parent". The research of this dissertation extends the real-world rigor of the statistical field of design of experiments to develop an deterministic, adaptive algorithm that produces deterministically generated, reproducible, testable, defendable, adaptive, resource-constrained multi-stage experimental schedules without having to spend physical resource.

Quartz particles of various discrete particle size ranges have been methylated to varying known mounts using trimethylchlorosilane and their flotation behaviour has been assessed in a modification of the Hallimond tube. For each particle size there is a definite degree of. surface coverage below which the particles do not float. A 'flotation domain' is identified which shorvs that both coarse (-100pm) and fine (-10pm) particles require a greater degree of surface coverage to initiate flotation than do intermediate (-40pm) particles. Water contact angles have been measured on quartz plates and powders which have been methylated (under the same conditions) with trimethylchlorosilane. Both advancing and receding water contact angles measured on quartz plates as a function of degree of surface methylationare in good agreement with the angles predicted by the Cassie equation. Advancing water contact angles measured on quartz particles as a function of degree of surface methylation are also in good agreement with angles predicted by the Cassie equation up to surface coverages of'about 70%. The angles measured at higher surface coverages are less than those anticipated by the Cassie equation. The flotation behaviour of the particles has been compared with that predicted by existing flotation theories. It has been shown that coarse particle behaviour is predicted by the kinetic theory of flotation proposed by Schulze. Fine particle behaviour, however, only qualitatively agrees with Scheludko's theory of fine particle behaviour. Calculated induction times, in conjunction with observed flotation behaviour, indicate that the bubble-particle attachment process is most efficient for particles of about 38pm in diameter ander the set experimental conditions used in this study. Flotation rate trials were performed for three particle size ranges and rate constants were evaluated for the various degrees of surface coverage. It was found that the dependence of rate constant on particle size is essentially linear.

Thesis (M.S. in Mechanical Engineering) Naval Postgraduate School, September 1996.
"September 1996." Thesis advisor(s): F.A. Papoulias. Includes bibliographical references (p. 73). Also available online.

Thesis (M.S. in Naval Architecture and Marine Engineering and M.S. in Mechanical Engineering) Massachusetts Institute of Technology, Sept. 2001.
Includes bibliographical references (leafs 89). Also Available online.

The control of pest populations by using insect pathogens has been an attractive alternative to the application of chemical pesticides employed for the same purpose. As these chemicals not only damage the environment, but also trigger development of resistance by the pests and can harm other organisms together with the target pest, biological control is preferable and Bacillus thuringiensis (Bt) subspecies have been the most widely used bioinsecticides in forestry, agriculture and mosquito/ black fly control. The most important property of Bt subspecies is the synthesis of protoxins named as delta-endotoxins (crystal proteins). In this study, response surface optimization of Bt subsp. israelensis HD500 batch fermentation for high level production of its toxin proteins Cry4Ba and Cry11Aa was performed. As the interaction of the medium components as well as cultivation conditions are expected to influence the production of the toxin proteins, an experimental chart was prepared by accepting the previously reported optimal values for the most important parameters as zero points: [Mn], 10-6 M
[K2HPO4], 50 mM
C:N ratio, 20:1 and incubation temperature
30°
C. When the combinations of these variables at different levels were studied at 30 batch cultures and analysed for the optimum toxin protein concentrations, temperature: 28.3&
#61616
C, [Mn]: 3.3x10-7M, C:N ratio: 22.2 and [K2HPO4]: 66.1mM yielded the highest concentrations of both Cry4Ba and Cry11Aa toxin proteins.

Research concerning the surface of technical ceramics is carried out from the viewpoint of their mechanical performance subjected to relevant operating conditions. The selected materials are silicon nitride, zirconia and alumina. They are subjected to cavitation erosion and other wear processes. When polished ceramics are subjected to cavitation, a pseudoplastic deformation pit is discovered, as well as a delayed phase transformation or ageing of the zirconia stored at room temperature. Measured ageing times recorded are of the order of one month. These two discoveries are novel and a full explanation is explored. The creation of cracks that release the slip planes of ceramic grains allowing plastic deformation is proposed to be the main mechanism. In order to understand the relationship of the zirconia surface degradation with its oxides (yttria or magnesia), several material compositions are tested. It is concluded that the delay of phase transformation relies on the existence of partially stabilized tetragonal zirconia regardless of the oxide used to stabilize it. Part of this research consists of understanding the effects of the experimental procedure that is utilised on the behaviour of the material. An unexpected non homogeneous cavitation erosion shape is obtained when an ultrasonic horn of small diameter is used to produce the bubbles. This non homogeneous region, referred to as ring region for this research, affects the erosion pattern of the material and it differs from the typical ones obtained when following the standard test. The acoustic theory does not explain this phenomenon. Therefore, a new approach is followed. This approach consists of using fluid mechanics equations combined with analytical mechanics principles. It is concluded that the location of cavitation clusters fulfils a condition of minimum energy. On the other hand, there are important differences between this experimental set up and the set up suggested by the published standards. These differences are discussed and a criterion for cavitation erosion resistance is developed. The comparison of cavitation resistance of materials is achieved by means of surface loss as criterion instead of volume loss.

Polyetheretherketone (PEEK) is a thermoplastic polymer that has been successfully used in a range of cardiovascular, orthopaedic and dental applications. This study investigates the surface modification of PEEK with calcium phosphate coatings; alone and in conjunction with topographical modifications. Calcium phosphate thin films of 200-400 nm thickness were produced on PEEK using magnetron sputter deposition. The films were applied to unmodified (injection moulded) PEEK surfaces and PEEK surfaces with grooved features. The grooves were produced by hot embossing using nickel stamps with features 20 or 60 μm wide and 30 μm deep. Furthermore, electrohydrodynamic spray deposition was used to deposit calcium phosphate relics onto unmodified PEEK, and PEEK with a sputter deposited calcium phosphate coating. The cellular response to these surfaces was investigated using MG63 osteosarcoma cells. The sputter deposited coatings were shown to have a negative effect on MG63 cell attachment, measured after one day in culture, but a positive effect on MG63 cell proliferation over seven days in culture. The presence of grooved features on the surface appeared to marginally encourage cell attachment. The highest MG63 cell attachment levels were observed on PEEK with electrohydrodynamically sprayed relics. Although no single surface studied offered both the highest cell attachment and most enhanced cell proliferation, the combination of a calcium phosphate coating with topographical modification has the potential to provide an effective surface for enhancing the cell response to PEEK. The simultaneous use of both topographical and chemical surface modification techniques may also have the potential to encourage a mechanically solid interface with bone in-vivo.

Approved for public release; distribution is unlimited
Vertical plane response of submersible vehicles in the proximity of a free surface in deep water is evaluated using a potential flow, strip theory solver. Two criteria, that are periscope submergence, and sail broaching are used to quantify the response. These criteria combined with the vehicle's response amplitude operators in regular sinusoidal waves along with a statistical description of the seaway lead to an assessment of an overall operability index for the vehicle. This thesis presents a systematic parametric study of the effects of body geometry on near surface response. Two cases, namely limited diameter and limited length are considered. The total volume of the vehicle is kept constant, and certain shape factors are changed, while either the overall diameter or the overall length remains the same. The operability index is calculated for each case within a given range for sea states and sea directions and for various shape factors, vehicle speeds and operating depths. The results indicate that certain changes of shape factors can improve vehicle operations in various depth and speed combinations

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.
Includes bibliographical references (leaf 89).
It is estimated that 70 to 85 percent of a naval ship's life-cycle cost is determined during the concept exploration phase which places an importance in the methodology used by the designer to select the concept design. But trade-off studies are guided primarily by past experience, rules-of-thumb, and designer preference. This approach is ad hoc, not efficient and may not lead to an optimum concept design. Even worse, once the designer has a "good" concept design, he has no process or methodology to determine whether a better concept design is possible or not. A methodology is required to search the design space for an optimal solution based on the specified preferences from the customer. But the difficultly is the design space, which is non-linear, discontinuous, and bounded by a variety of constraints, goals, and thresholds. Then the design process itself is difficult to optimize because of the coupling among decomposed engineering disciplines and sub-system interactions. These attributes prevent application of mature optimization techniques including Lagrange multipliers, steepest ascent methods, linear programming, non-linear programming, and dynamic programming. To further improve submarine concept exploration, this thesis examines a statistical technique called Response Surface Methods (RSM). The purpose of RSM is to lead to an understanding of the relationship between the input (factors) and output (response) variables, often to further the optimization of the underlying process. The RSM approach allows the designers to find a local optimal and examine how the design factors affect the response in the region around the generated optimal point. RSM can be applied to submarine concept exploration and provide a methodology to: determine the optimal concept design based on customer preference, efficiently perform trade-off studies, determine the feasible design space, and the ability to determine in advance if a specified concept design is feasible and meets all the customer thresholds and constraints.
by David A. Goggins.
S.M.

In this study, the effect of a passive trapped-vortex cell on lift to drag (L/D) ratio of an FFA-W3-301 airfoil is studied. The upper surface of the airfoil was modified to incorporate a cavity defined by seven parameters. The L/D ratio of the airfoil is modeled using a radial basis function metamodel. This model is used to find the optimal design parameter values that give the highest L/D. The numerical results indicate that the L/D ratio is most sensitive to the position on an airfoil’s upper surface at which the cavity starts, the position of the end point of the cavity, and the vertical distance of the cavity end point relative to the airfoil surface. The L/D ratio can be improved by locating the cavity start point at the point of separation for a particular angle of attack. The optimal cavity shape (o19_aXX) is also tested for a NACA0024 airfoil.

The estimation of a particular matrix of coefficients of a second-order polynomial model was shown to be important in Response Surface Methodology (RSM). This led naturally to designing RSM experiments for best estimation of these coefficients as a primary goal. A design criterion, D_S-optimality, was applied to several classes of RSM designs to find optimal choices of design parameters. Further, previous results on D-optimal RSM designs were extended. The designs resulting from the use of the two criteria were compared. Two other design criteria were also studied. These were IV, the prediction variance of ŷ integrated over a region R, and IV*, sum of the variances of ∂ŷ/∂α again integrated over R. Three different choices of the region R were used. The object of the study was not only to identify optimal choices of design parameters, but also to compare the resulting designs with those obtained using the determinantal criteria. An extension of a method for constructing D-optimal designs was used to construct D_S-optimal central composite designs. This involved viewing the design points as having continuous weights. D_S-best central composite designs were constructed either analytically or numerically for a fixed axial point distance. The results of previous work by other authors were extended for D-optimality by varying the axial point distance. Other design classes studied were Box-Behnken, equiradial, and some small composite designs. The novel study of IV and the extended IV, called IV*, was done for each of the four design classes mentioned previously. The results of the study were presented graphically, or tabularly. The best designs according to IV and IV* were compared with the D_S-best designs. Composite designs performed well in all criteria, with the central composite designs performing best. The Box-Behnken and equiradial seemed to suffer from a lack of flexibility. The D_S-best designs agreed well with the designs suggested by the IV* criteria.
Ph. D.
incomplete_metadata

The aim of this thesis is to investigate surface waves supported on a variety of metallic metasurfaces at microwave frequencies. The goal is to characterise the propagation of these surface waves in the plane of the structure and in some cases study how their presence gives rise to features in the scattering parameters of radiation incident on the metasurface.

The objective of the present research was to develop a system reliability-based bridge assessment method for damaged composite bridges. A response surface method was adopted in combination with the nonlinear finite element analyses, which provided a powerful tool for the evaluation of the reliability of a bridge system. Using the method, investigation was made into the effects of corrosion on the reliability of a bridge system. A numerical bridge model used for the present study was developed using an actual composite bridge in the UK. Commercial FE programmes such as ABAQUS and DIANA were used for the development of the model. In order to validate the use of these FE programmes in the present study, simulations on the full-scale bridge test were carried out. Of the three, 40-tonne vehicle loading given in BD 21, the vehicle loading which caused the worst resistance was selected as a reference loading model. In the present study, the failure of the load redistribution system due to punching shear was addressed in detail. It was found that punching shear in the concrete slab may prevent the total collapse of a whole bridge system taking place. This is because the system cannot reach the ultimate state in such a case. It was proposed that such cases be excluded from the evaluation of the failure probability of a whole system. This approach is expected to provide a more rational basis for the evaluation of the reliability of a global bridge system than simply suppressing such failure. The system reliability-based assessment was developed based on the response surface method in combination with the nonlinear finite element analyses. In the present study, reliability analyses were carried out for both intact and damaged bridges. Corrosion on steel girders was simulated by reducing the thickness of the web and the flange. The present study shows that the two-lane loading case governs the total failure probability (reliability) of the present bridge model. In addition, it was found that the traffic loading for the evaluation of load effects has a significant influence on the results. It was also found that the failure of a bridge is most likely to take place due to extremely heavy trucks for the intact state. It seems that this has a close connection to the high uncertainty of the traffic loading. However, the failure is likely to be governed by reduced dimension for severely damaged model. This is because the uncertainty related to the dimension and ultimately the resistance becomes bigger as corrosion proceeds. Results of this research revealed that this assessment methodology is less conservative. This may lead to rational use of a limited resources. It was clearly demonstrated through the reliability analyses that a system reliability-based bridge assessment methodology developed in this research may provide a tool for more rational bridge assessment.

The focus of this dissertation is on improving decision-maker trade-offs and the development of a new constrained methodology for multiple response surface optimization. There are three key components of the research: development of the necessary conditions and assumptions associated with constrained multiple response surface optimization methodologies; development of a new constrained multiple response surface methodology; and demonstration of the new method. The necessary conditions for and assumptions associated with constrained multiple response surface optimization methods were identified and found to be less restrictive than requirements previously described in the literature. The conditions and assumptions required for a constrained method to find the most preferred non-dominated solution are to generate non-dominated solutions and to generate solutions consistent with decision-maker preferences among the response objectives. Additionally, if a Lagrangian constrained method is used, the preservation of convexity is required in order to be able to generate all non-dominated solutions. The conditions required for constrained methods are significantly fewer than those required for combined methods. Most of the existing constrained methodologies do not incorporate any provision for a decision-maker to explicitly determine the relative importance of the multiple objectives. Research into the larger area of multi-criteria decision-making identified the interactive surrogate worth trade-off algorithm as a potential methodology that would provide that capability in multiple response surface optimization problems. The ISWT algorithm uses an ε-constraint formulation to guarantee a non-dominated solution, and then interacts with the decision-maker after each iteration to determine the preference of the decision-maker in trading-off the value of the primary response for an increase in value of a secondary response. The current research modified the ISWT algorithm to develop a new constrained multiple response surface methodology that explicitly accounts for decision-maker preferences. The new Modified ISWT (MISWT) method maintains the essence of the original method while taking advantage of the specific properties of multiple response surface problems to simplify the application of the method. The MISWT is an accessible computer-based implementation of the ISWT. Five test problems from the multiple response surface optimization literature were used to demonstrate the new methodology. It was shown that this methodology can handle a variety of types and numbers of responses and independent variables. Furthermore, it was demonstrated that the methodology can be successful using a priori information from the decision-maker about bounds or targets or can use the extreme values obtained from the region of operability. In all cases, the methodology explicitly considered decision-maker preferences and provided non-dominated solutions. The contribution of this method is the removal of implicit assumptions and includes the decision-maker in explicit trade-offs among multiple objectives or responses.
Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering PhD

Simulation software has become an essential tool in the design and development of integrated circuits. The key to the rapid and efficient designs required in the competitive industry lies with the use of these simulators with statistical optimisation methods. This is necessary if companies are to survive in the aggressive IC marketplace. The linking of simulation and statistics not only results in rapid development times, but also in robust, highly manufacturable products. In this work an automated software system is presented where the benefits of simulation and statistical techniques can be readily made available. The efficiency of the system is increased further by utilising parallel processing techniques. Using one system built round the INMOS transputer and one using Intel 1860 processors, the time taken to obtain simulation results is greatly reduced. Two statistical methods are investigated, namely Response Surface Methodology (RSM) and Taguchi analysis. In order to illustrate how these approaches can be utilised in the field of semiconductors, part of a 1.5 μm nMOS process is optimised in relation to some specified device parameters. A comparison is made between both techniques, with good agreement being obtained. Finally devices have also been fabricated using the same experimental design as for the RSM simulation analysis. This facilitated a verification of the simulation optimisation with reality. Both simulated and fabricated devices suggested the same improved optimised conditions when compared to the existing process parameters.

This study is concerned with a methodology for the aerodynamic analysis and preliminary design of a novel configuration for high subsonic civil transport, based on the flying wing concept, known a Blended Wing Body (BWB). A response surface based optimisation method is developed, enabling the designer to monitor the effect of shape modification on the controllability of the aircraft in both longitudinal and lateral/directional motion and on the Wing structural weight, while maximising the aerodynamic efficiency. The design aspects considered included high- speed aerodynamics, flight static-stability and trim characteristics. The response surface Scheme employs a space filling design of experiment technique to build least square fitting quadratic polynomials, used in place of the original computational modules in a gradient based search. A optimisation test indicated that the present method is more effective in leading the design near to the global optimum as opposed to a conventional gradient method with direct search, despite that the constructed approximation may not represent accurately the actual surface. With this system, multiple constrained optimisation problems are successfully solved in the favourable case of smooth objective/constraint function. Where these functions may exhibit high non-linear trends, an iterative response surface method refining both approximation and bounds of the design space is proposed. The capabilities of such a technique are shown for transonic aerofoil optimisation problems, demonstrating that the proposed method is more efficient and more effective than some other state-of- the-art methods. As a result of these studies, the aerodynamic efficiency of a large capacity BWB configuration has been considerably improved by re-designing the external shape to generate a spanwise loading intermediate between triangular and elliptic. The longitudinal static stability analysis revealed that the aircraft is stable except at low- weights with zero-payload. The lateral/directional analyses showed that the aircraft is stable in roll, but unstable in yaw. Despite that the winglets are found to stabilise the aircraft, it is directionally unstable without additional vertical stabilisers. I

Retaining walls (RW) are among the most common geotechnical structures. They have been widely used in railways, bridges (e.g. bridges abutment), buildings, hydraulic and harbor engineering. Once built, the RW can be exposed to dynamic loads, such as those produced by earthquakes, machines, vehicles and explosions. They must remain operational in aftermath of the natural or human-induced dynamic events. Hence, the understanding of the geotechnical response of RW to these dynamic loads is critical for the safe design of several civil engineering structures such as railways, highways, bridges, and buildings. Although fairly reliable methods have been developed for assessing and predicting the response of RW to dynamic loads induced by earthquakes, there is very little information to guide engineers in the design of RW that are exposed to surface explosions (surface blast loadings). These methods for assessing RW response to earthquake loads cannot directly be applied to the design of RW subjected to surface blast loads. Indeed, blast loads are short duration dynamic loads and their durations are very much shorter than those of earthquakes. The predominant frequencies of a blast wave are usually 2-3 orders of magnitudes higher than those of earthquake wave, and the same can be said for blast wave acceleration as compared to the peak acceleration that results from an earthquake. Thus, RW response under blast loading could be significantly different from that under a loading with much longer duration such as an earthquake. There is a need to increase our understanding of the response of RW to surface explosion loadings since there is a significant increase of terrorist threat on important buildings and some lifeline infrastructures. Transportation structures (bridges, highway, and railway) are unquestionably being regarded as potential targets for terrorist attacks. The purpose of this PhD research is to investigate the geotechnical response of reinforced concrete retaining wall (RCRW) with sand as a backfill material to surface blast loads. The soil-RW model was subjected to a simulated blast load using a shock tube. The influence of the backfill relative density, backfill saturation, blast load intensity, and live load surcharge on the behaviour of RCRW with sand backfill was studied. The dimensions of the stem and heel of the retaining wall in this study were 650 mm (height) x 500 mm (width) x 60 mm (thickness) and 400 mm (width) x 500 mm (length) x 60 mm (thickness), respectively. Soil-RW model was placed inside a wooden box. The overall height of the box was 1565 mm. The retained backfill extended behind the wall for 1300 mm. Based on the results, it is found that the maximum dynamic earth pressures were recorded at a time greater than the positive phase duration regardless of the backfill condition. The total earth pressure distribution along the height of the wall showed that the magnitude of total earth pressure for loose and medium backfill at the mid-height of the wall slightly exceeded the dense backfill. In addition, the lateral earth pressures increased with the increase in the blast load intensities. On the other hand, under the same load conditions, an increase in the wall movement was noticed in loose backfill, and a translation response mode was evident in this condition. The mobilized passive resistance of the RW backfill induced by blast load was used to determine the force-displacement relationship. Finally, the susceptibility of the RW with saturated dense sand to liquefaction was examined, and it was ascertained that liquefaction was not triggered when the RW was subjected to a blast load of 50 kPa. The results and findings of this PhD research will provide valuable information that can be used to evaluate the vulnerability of transportation structures to surface blast events as well as to develop guidance for their design.

The 1985 and 1986 Cotton Reports have the same publication and P-Series numbers.
Fertilizer nitrogen rates and the addition of phosphorus, potassium and zinc were studied in a drip irrigated field at Eloy. Response to nitrogen was found with the optimum rate being about 170 lbs/acre although higher rates tended to increase yields. Significant response to P and K were not found, but there appeared to be a response to zinc. Yields were below desired levels because of problems with obtaining a good stand and infestations of cotton rust and root rot.

An attempt to minimize interference drag in a wing-fuselage junction by means of inserting a fillet is presented in this thesis. The case of a low-wing com- mercial transport aicraft at cruise conditions is examined. Due to the highly three dimensional behaviour of the flow field around the junction, a thin-layer Navier-Stokes code was implemented to estimate the drag forces at the junc- tion. Carefully selected design variable combinations based on-the theory of Design of Experiments constituted the initial group of feasible cases for which the flow solver had to be run. The drag values of these feasible cases were then used to create a second order response surface which could predict with rea- sonable accuracy the interference drag given the value of the design variables within the feasible region. A further optimization isolated the minimum in- terference drag combination of design variable values within the design space. The minimurn interference drag combination of design variable values was eval- uated numerically by the flow solver. The prediction of the response surface and the numerical value obtained by the flow solver for the interference drag of the optimal wing-fuselage combination differed by less than five percent. To demonstrate the ability of the method to be used in an interdisciplinary analysis and optimization program, a landing gear design module is included which provides volume constraints on the fillet geometry during the fillet sur- face definition phase. The Navier Stokes flow analyses were performed on the Cranfield Cray su- percomputer. Each analysis required between eight to twelve CPU hours, and the total CPU time required for the optimization of the six variable model described in the thesis required thirty Navier Stokes runs implementing the Design of Experimens and Surface Response Methodology implementation. For comparison, a typical optimization implementing a classical conjugate di- rections optimizer with no derivative information available would probably require more than forty iterations. Both the optimization and the flow solver results are discussed and some recommendations for improving the efficiency of the code and for further ap- plications of the method are given.

Thesis (Ph.D)--Materials Science and Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Barbara Boyan; Committee Member: Andres Garcia; Committee Member: Anthony Norman; Committee Member: Nael McCarty; Committee Member: Zvi Schwartz. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Almost all sediment transport equations incorporate the Shields parameter, which is a ratio of the total boundary shear stress as a driving force and the particle weight as a resisting force. Shields (1936) equated particle resistance to entrainment with particle weight, which is proportional to particle diameter, or bed texture. The present work analyses the particle resistance term in the Shields parameter. As the bed material adjusts to a given flow condition, bed stability increases. The arrangement of particles into more stable configurations is here termed geometric structure, and includes the formation of pebble clusters, and imbrication. After an initial surface coarsening, here termed textural structure, particle resistance to movement is a function primarily of geometric structure. The Shields number for entrainment is thus a measure of particle resistance due to both types of bed structure rather than the conventional notion of particle resistance due to particle weight. The response of a mobile bed surface composed of < 8 mm diameter gravels to flowing water was explored in a 6 meter by 0.5 meter flume using four different slopes and various water depths. Corrected bed shear stresses varied between 0.05 and 2.79 Pa. Step increases in discharge with a constant slope caused the bed surface to develop a structure which was more stable at the end of a run than at the beginning. Under these conditions, the Shields number for incipient motion was found to vary between 0.001 and 0.066. This variability can be explained by the degree of geometric structure present. Previous studies, including Shields' work (1936), have implicitly included the effects of geometric structure on incipient motion. Surface coarsening develops with very low flows, but subsequent coarsening in higher flows is minor, with less than 5% increase in median diameter following a 50% increase in bed shear stress. Calculations of Manning's n based on depth, slope, and velocity measurements show an increase in flow resistance as structure develops. The development of a coarse surface layer appears to be limited by flow characteristics near the bed which are in turn modified by the development of structure. Measurements of the area occupied by the largest stones show that they do not cover more than 14% of the surface during maximum coarsening. Froude scaling of the flume data indicates that the time necessary for development of maximum strength is on the order of a month for natural rivers under steady flow conditions. This suggests that gravel river beds are rarely in equilibrium with natural flow conditions.
Arts, Faculty of
Geography, Department of
Graduate

The work presented within this thesis concerns the optimization of finite element models of engine structures to reduce radiated noise. For many engineering problems, current methods of structural optimization provide an efficient means by which to identify an optimum design, subject to a set of imposed bounds and constraints. They do not, however, have the flexibility to carry out efficient investigation of a range of different constraint criteria, and this is often a requirement of a noise optimization study. In order to address this restriction, an alternative method of noise optimization is developed, which is based on the techniques of experimental design theory and response, surface methodology. The main feature of this approach is that values of the response functions of interest are calculated at a number of selected points Within the design variable space, from which an approximating mathematical model is generated. It is this analytical model of the original responses which is used as the basis of the optimization procedure. Experimental design theory is employed in order to ensure that a sufficiently accurate model can be generated With the minimum number of function evaluations. A number of competing experimental designs and mathematical models are considered, and numerical trials are carried out to evaluate their performance in representing the noise function. A quadratic model is found to perform well throughout the design region, and can be estimated efficiently using a particular class of economic second-order designs. A number of detailed noise optimization studies are presented, involving up to seven design variables, which illustrate the ways in which the requirements of the noise optimization problem can be met using the response surface approach.

The land surface is important to the climate system for the exchanges of moisture, momentum and heat. Momentum, radiation, and sensible and latent heat fluxes between the atmosphere and the surface will likely affect atmospheric dynamics, temperature, precipitation and humidity fields (Sato et ai., 1989). These may subsequently feed back into the land surface processes as part of a cyclical system. Therefore it is evident that our livelihood is largely dependent on interactions and exchanges between the land surface and climate system (Henderson-Sellers et ai., 1993) and it is thus essential that we gain a better understanding of the interactive sensitivity. This is of particular relevance in the context of the portended future global climate change. In the present study the interactions between the land surface and the atmosphere are considered over the southern African region. This region has a climate showing a high degree of spatial and temporal variability, most notably with rainfall. Regional climates are characterised by summer, winter and all-year-round rainfall. There are steep vegetation gradients and a wide range of vegetation types adapted to suit the variable climate. These factors, combined with the societal implications of changes in the climate and land surface systems, make southern Africa a challenging and important study domain for examining the sensitivity between the different elements of the atmosphere and biosphere. This research makes use of a biosphere model driven by climate change data derived from a general circulation model (GCM). Regions susceptible and sensitive to changes on an annual and seasonal basis are identified and examined. The thesis comprises 8 chapters. The first chapter, Chapter 1, provides some background information on climate change, biosphereatmosphere interactions, GCMs and transient simulations, vegetation models and vegetation representation over southern Africa. This chapter also sets out the research objectives. The following chapter, Chapter 2, introduces the atmospheric GCM model data from the Hadley Centre Model (HadCM2) used in the analysis. The chapter additionally provides a detailed description of the biosphere model, the Integrated Biosphere Simulator (IBIS). Chapter 3 examines the Hadley Centre HadCM2 GCM input data used in driving the biosphere model, while Chapter 4 presents the input forcing data and configuration of the IBIS model. In Chapter 5 the results of the IBIS model simulation are examined on the annual scale and in Chapter 6 the results are examined on the seasonal scale. Some of the implications of climate change are considered in Chapter 7. This chapter also places the HadCM2 GCM model data used in driving IBIS into the context of the latest emissions scenarios. In the final chapter, Chapter 8, an overview summary is provided and conclusions are drawn.

A response surface analysis is concerned with the exploration of a system in order to determine the behavior of the response of the system as levels of certain factors which influence the response are changed. It is often of particular interest to predict the response in some region of the allowable factor values and to find the optimal operating conditions of the system. In an experiment to search for the optimum response of a surface it is advantageous to predict the response with equal, or nearly equal, precision at all combinations of the levels of the variables which represent locations which are the same distance from the center of the experimental region. Measures of the quality of prediction at locations on the surface of a hypersphere are presented in this thesis. These measures are used to form a graphical method of assessing the overall prediction capability of an experimental design throughout the region of interest. Rotatable designs give equal variances of predicted values corresponding to locations on the same sphere. In this case, the center of the sphere coincides with the center of the rotatable design. However, there is a need for a method to quantify the prediction capability on spheres for non-rotatable designs. The spherical variance is a measure of the average prediction variance at locations on the surface of a sphere. The spherical variance obtained with a design provides an assessment of how well the response is being estimated on the average at locations which are the same distance from the region center. This thesis introduces two measures which describe the dispersion in the variances of the predicted responses at aH locations on the surface of a sphere. These prediction variance dispersion (PVD) measures are used to evaluate the ability of a design to estimate the response with consistent precision at locations which are the same distance from the region center. The PVD measures are used in conjunction with the spherical variance to assess the prediction capability of a design. A plot of the spherical variance and the maximum and minimum prediction variances for locations on a sphere against the radius of the sphere gives a comprehensive picture of the behavior of the prediction variances throughout a region, and, hence, of the quality of the predicted responses, obtained with a particular design. Such plots are used to investigate and compare the prediction capabilities of certain response surface designs currently available to the researcher. The plots are also used to investigate the robustness of a design under adverse experimental conditions and to determine the effects of taking an additional experimental run on the quality of the predicted responses.
Ph. D.

Response surface methodology (RSM) provides a useful framework for the optimization of stochastic simulation models. The sequential experimentation and model fitting procedures of RSM enable prediction of the response and location of the optimum operating conditions. In a simulation environment, the experimentation phase of RSM involves selecting the input variable levels for each simulation run and assigning pseudorandom number streams to the stochastic model components. Through an appropriate assignment of random number streams to simulation runs, correlation among the simulated responses can be induced, thereby affecting reductions in the variances of certain model coefficients. Three methods of correlation induction are considered in this research: (i) no correlation induction, achieved through the use of independent streams, (ii) positive correlation induction, achieved through the use of common streams, and (iii) a combination of positive and negative correlation induction, achieved through the use of the assignment rule blocking strategy. The performance of the correlation induction strategies is evaluated in terms of two mean squared error design criteria; MSE of response and MSE of slope. The MSE of slope criteria is useful in the early stages of RSM, when the experimental objective is location of the region containing the optimum. The MSE of response criteria is useful in the latter stages of RSM, when the experimental objective is prediction of the optimum response. The correlation induction strategies are evaluated under two experimental situations; fitting a first order model while protecting against quadratic curvature in the response surface, and fitting a second order model while protecting against cubic curvature. In the case of fitting a first order model, two-level factorial designs are used to evaluate the correlation induction strategies, and in the second order case, four design classes are considered; central composite designs, Box-Behnken designs, three-level factorial designs, and small composite designs. The findings of this research indicate that the assignment rule blocking strategy generally performs the best of the three strategies under both MSE criteria, and the performance of this strategy improves as the magnitudes of the induced correlations increase. The independent streams strategy is a poor choice when the design criteria is MSE of slope and the common streams strategy is a poor choice when the design criteria is MSE of response. The central composite and Box-Behnken designs were found to perform the best of the four second order design classes. The three-level factorial designs performed poorly under MSE of response criteria and the small composite designs performed poorly under the MSE of slope criteria.
Ph. D.