Uncertainty and Sensitivity Analysis in Aircraft Operating Costs in Structural Design Optimization

The paper focuses on the development of an aircraft design optimization methodology that models uncertainty and sensitivity analysis in the tradeoff between manufacturing cost, structural requirements, andaircraft direct operating cost.Specifically,ratherthanonlylooking atmanufacturingcost, direct operatingcost is also consideredintermsof the impact of weight on fuel burn, in addition to the acquisition cost to be borne by the operator. Ultimately, there is a tradeoff between driving design according to minimal weight and driving it according to reduced manufacturing cost. Theanalysis of cost is facilitated withagenetic-causal cost-modeling methodology,andthe structural analysis is driven by numerical expressions of appropriate failure modes that use ESDU International reference data. However, a key contribution of the paper is to investigate the modeling of uncertainty and to perform a sensitivity analysis to investigate the robustness of the optimization methodology. Stochastic distributions are used to characterize manufacturing cost distributions, andMonteCarlo analysis is performed in modeling the impact of uncertainty on the cost modeling. The results are then used in a sensitivity analysis that incorporates the optimization methodology. In addition to investigating manufacturing cost variance, the sensitivity of the optimization to fuel burn cost and structural loading are also investigated. It is found that the consideration of manufacturing cost does make an impact and results in a different optimal design configuration from that delivered by the minimal-weight method. However, it was shown that at lower applied loads there is a threshold fuel burn cost at which the optimization process needs to reduce weight, and this threshold decreases with increasing load. The new optimal solution results in lower direct operating cost with a predicted savings of 640=m2 of fuselage skin over the life, relating to a rough order-of-magnitude direct operating cost savings of $500,000 for the fuselage alone of a small regional jet. Moreover, it was found through the uncertainty analysis that the principle was not sensitive to cost variance, although the margins do change.

Design, Manufacture and Performance of Germanium Bipolar Transistors

Germanium NPN bipolar transistors have been manufactured using phosphorus and boron ion implantation processes. Implantation and subsequent activation processes have been investigated for both dopants. Full activation of phosphorus implants has been achieved with RTA schedules at 535?C without significant junction diffusion. However, boron implant activation was limited and diffusion from a polysilicon source was not practical for base contact formation. Transistors with good output characteristics were achieved with an Early voltage of 55V and common emitter current gain of 30. Both Silvaco process and device simulation tools have been successfully adapted to model the Ge BJT(bipolar junction transistor) performance.

Design, optimization and characterisation of polymeric microneedle arrays prepared by a novel laser-based micromoulding technique

Design and evaluation of a novel laser-based method for micromoulding of microneedle arrays from polymeric materials under ambient conditions. The aim of this study was to optimise polymeric composition and assess the performance of microneedle devices that possess different geometries.

Building information modeling based building design optimization for sustainability

Environmental problems, especially climate change, have become a serious global issue waiting for people to solve. In the construction industry, the concept of sustainable building is developing to reduce greenhouse gas emissions. In this study, a building information modeling (BIM) based building design optimization method is proposed to facilitate designers to optimize their designs and improve buildings’ sustainability. A revised particle swarm optimization (PSO) algorithm is applied to search for the trade-off between life cycle costs (LCC) and life cycle carbon emissions (LCCE) of building designs. In order tovalidate the effectiveness and efficiency of this method, a case study of an office building is conducted in Hong Kong. The result of the case study shows that this method can enlarge the searching space for optimal design solutions and shorten the processing time for optimal design results, which is really helpful for designers to deliver an economic and environmental friendly design scheme.

Uncertainty propagation in inverse reliability-based design of composite structures

An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.

Design thinking and the precautionary principle : development of a theoretical model complementing preventive judgment for design for sustainability enriched through a study of architectural competitions adopting LEED

Cette thèse contribue à une théorie générale de la conception du projet. S’inscrivant dans une demande marquée par les enjeux du développement durable, l’objectif principal de cette recherche est la contribution d’un modèle théorique de la conception permettant de mieux situer l’utilisation des outils et des normes d’évaluation de la durabilité d’un projet. Les principes fondamentaux de ces instruments normatifs sont analysés selon quatre dimensions : ontologique, méthodologique, épistémologique et téléologique. Les indicateurs de certains effets contre-productifs reliés, en particulier, à la mise en compte de ces normes confirment la nécessité d’une théorie du jugement qualitatif. Notre hypothèse principale prend appui sur le cadre conceptuel offert par la notion de « principe de précaution » dont les premières formulations remontent du début des années 1970, et qui avaient précisément pour objectif de remédier aux défaillances des outils et méthodes d’évaluation scientifique traditionnelles. La thèse est divisée en cinq parties. Commençant par une revue historique des modèles classiques des théories de la conception (design thinking) elle se concentre sur l’évolution des modalités de prise en compte de la durabilité. Dans cette perspective, on constate que les théories de la « conception verte » (green design) datant du début des années 1960 ou encore, les théories de la « conception écologique » (ecological design) datant des années 1970 et 1980, ont finalement convergé avec les récentes théories de la «conception durable» (sustainable design) à partir du début des années 1990. Les différentes approches du « principe de précaution » sont ensuite examinées sous l’angle de la question de la durabilité du projet. Les standards d’évaluation des risques sont comparés aux approches utilisant le principe de précaution, révélant certaines limites lors de la conception d’un projet. Un premier modèle théorique de la conception intégrant les principales dimensions du principe de précaution est ainsi esquissé. Ce modèle propose une vision globale permettant de juger un projet intégrant des principes de développement durable et se présente comme une alternative aux approches traditionnelles d’évaluation des risques, à la fois déterministes et instrumentales. L’hypothèse du principe de précaution est dès lors proposée et examinée dans le contexte spécifique du projet architectural. Cette exploration débute par une présentation de la notion classique de «prudence» telle qu’elle fut historiquement utilisée pour guider le jugement architectural. Qu’en est-il par conséquent des défis présentés par le jugement des projets d’architecture dans la montée en puissance des méthodes d’évaluation standardisées (ex. Leadership Energy and Environmental Design; LEED) ? La thèse propose une réinterprétation de la théorie de la conception telle que proposée par Donald A. Schön comme une façon de prendre en compte les outils d’évaluation tels que LEED. Cet exercice révèle cependant un obstacle épistémologique qui devra être pris en compte dans une reformulation du modèle. En accord avec l’épistémologie constructiviste, un nouveau modèle théorique est alors confronté à l’étude et l’illustration de trois concours d'architecture canadienne contemporains ayant adopté la méthode d'évaluation de la durabilité normalisée par LEED. Une série préliminaire de «tensions» est identifiée dans le processus de la conception et du jugement des projets. Ces tensions sont ensuite catégorisées dans leurs homologues conceptuels, construits à l’intersection du principe de précaution et des théories de la conception. Ces tensions se divisent en quatre catégories : (1) conceptualisation - analogique/logique; (2) incertitude - épistémologique/méthodologique; (3) comparabilité - interprétation/analytique, et (4) proposition - universalité/ pertinence contextuelle. Ces tensions conceptuelles sont considérées comme autant de vecteurs entrant en corrélation avec le modèle théorique qu’elles contribuent à enrichir sans pour autant constituer des validations au sens positiviste du terme. Ces confrontations au réel permettent de mieux définir l’obstacle épistémologique identifié précédemment. Cette thèse met donc en évidence les impacts généralement sous-estimés, des normalisations environnementales sur le processus de conception et de jugement des projets. Elle prend pour exemple, de façon non restrictive, l’examen de concours d'architecture canadiens pour bâtiments publics. La conclusion souligne la nécessité d'une nouvelle forme de « prudence réflexive » ainsi qu’une utilisation plus critique des outils actuels d’évaluation de la durabilité. Elle appelle une instrumentalisation fondée sur l'intégration globale, plutôt que sur l'opposition des approches environnementales.

Design and Analysis of Zero Cogging Brushless DC Motor for Spacecraft Applications

This paper presents the optimal design of a sur- face mounted permanent magnet Brushless DC mo- tor (PMBLDC) meant for spacecraft applications. The spacecraft applications requires the choice of a torques motor with high torque density, minimum cogging torque, better positional stability and high torque to inertia ratio. Performance of two types of machine con¯gurations viz Slotted PMBLDC and Slotless PMBLDC with halbach array are compared with the help of analytical and FE methods. It is found that unlike a Slotted PMBLDC motor, the Slotless type with halbach array develops zero cogging torque without reduction in the developed torque. Moreover, the machine being coreless provides high torque to inertia ratio and zero magnetic stiction

Sequential Optimal Recovery: A Paradigm for Active Learning

In most classical frameworks for learning from examples, it is assumed that examples are randomly drawn and presented to the learner. In this paper, we consider the possibility of a more active learner who is allowed to choose his/her own examples. Our investigations are carried out in a function approximation setting. In particular, using arguments from optimal recovery (Micchelli and Rivlin, 1976), we develop an adaptive sampling strategy (equivalent to adaptive approximation) for arbitrary approximation schemes. We provide a general formulation of the problem and show how it can be regarded as sequential optimal recovery. We demonstrate the application of this general formulation to two special cases of functions on the real line 1) monotonically increasing functions and 2) functions with bounded derivative. An extensive investigation of the sample complexity of approximating these functions is conducted yielding both theoretical and empirical results on test functions. Our theoretical results (stated insPAC-style), along with the simulations demonstrate the superiority of our active scheme over both passive learning as well as classical optimal recovery. The analysis of active function approximation is conducted in a worst-case setting, in contrast with other Bayesian paradigms obtained from optimal design (Mackay, 1992).

Sparse model identification using orthogonal forward regression with basis pursuit and D-optimality

An efficient model identification algorithm for a large class of linear-in-the-parameters models is introduced that simultaneously optimises the model approximation ability, sparsity and robustness. The derived model parameters in each forward regression step are initially estimated via the orthogonal least squares (OLS), followed by being tuned with a new gradient-descent learning algorithm based on the basis pursuit that minimises the l(1) norm of the parameter estimate vector. The model subset selection cost function includes a D-optimality design criterion that maximises the determinant of the design matrix of the subset to ensure model robustness and to enable the model selection procedure to automatically terminate at a sparse model. The proposed approach is based on the forward OLS algorithm using the modified Gram-Schmidt procedure. Both the parameter tuning procedure, based on basis pursuit, and the model selection criterion, based on the D-optimality that is effective in ensuring model robustness, are integrated with the forward regression. As a consequence the inherent computational efficiency associated with the conventional forward OLS approach is maintained in the proposed algorithm. Examples demonstrate the effectiveness of the new approach.

Experimental design and model construction algorithms for radial basis function networks

New construction algorithms for radial basis function (RBF) network modelling are introduced based on the A-optimality and D-optimality experimental design criteria respectively. We utilize new cost functions, based on experimental design criteria, for model selection that simultaneously optimizes model approximation, parameter variance (A-optimality) or model robustness (D-optimality). The proposed approaches are based on the forward orthogonal least-squares (OLS) algorithm, such that the new A-optimality- and D-optimality-based cost functions are constructed on the basis of an orthogonalization process that gains computational advantages and hence maintains the inherent computational efficiency associated with the conventional forward OLS approach. The proposed approach enhances the very popular forward OLS-algorithm-based RBF model construction method since the resultant RBF models are constructed in a manner that the system dynamics approximation capability, model adequacy and robustness are optimized simultaneously. The numerical examples provided show significant improvement based on the D-optimality design criterion, demonstrating that there is significant room for improvement in modelling via the popular RBF neural network.

Spectral design and verification of HIRDLS filters and antireflection coatings using an integrated system performance approach

The HIRDLS instrument contains 21 spectral channels spanning a wavelength range from 6 to 18mm. For each of these channels the spectral bandwidth and position are isolated by an interference bandpass filter at 301K placed at an intermediate focal plane of the instrument. A second filter cooled to 65K positioned at the same wavelength but designed with a wider bandwidth is placed directly in front of each cooled detector element to reduce stray radiation from internally reflected in-band signals, and to improve the out-of-band blocking. This paper describes the process of determining the spectral requirements for the two bandpass filters and the antireflection coatings used on the lenses and dewar window of the instrument. This process uses a system throughput performance approach taking the instrument spectral specification as a target. It takes into account the spectral characteristics of the transmissive optical materials, the relative spectral response of the detectors, thermal emission from the instrument, and the predicted atmospheric signal to determine the radiance profile for each channel. Using this design approach an optimal design for the filters can be achieved, minimising the number of layers to improve the in-band transmission and to aid manufacture. The use of this design method also permits the instrument spectral performance to be verified using the measured response from manufactured components. The spectral calculations for an example channel are discussed, together with the spreadsheet calculation method. All the contributions made by the spectrally active components to the resulting instrument channel throughput are identified and presented.