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.

Hierarchical synthesis of complex DSP functions on FPGAs

SoC systems are now being increasingly constructed using a hierarchy of subsystems or silicon Intellectual Property (IP) cores. The key challenge is to use these cores in a highly efficient manner which can be difficult as the internal core structure may not be known. A design methodology based on synthesizing hierarchical circuit descriptions is presented. The paper employs the MARS synthesis scheduling algorithm within the existing IRIS synthesis flow and details how it can be enhanced to allow for design exploration of IP cores. It is shown that by accessing parameterised expressions for the datapath latencies in the cores, highly efficient FPGA solutions can be achieved. Hardware sharing at both the hierarchical and flattened levels is explored for a normalized lattice filter and results are presented.

Resolving genetic functions within microbial populations: In situ analyses using rRNA and mRNA stable isotope probing coupled with single-cell raman-fluorescence in situ hybridization

Prokaryotes represent one-half of the living biomass on Earth, with the vast majority remaining elusive to culture and study within the laboratory. As a result, we lack a basic understanding of the functions that many species perform in the natural world. To address this issue, we developed complementary population and single-cell stable isotope (C-13)-linked analyses to determine microbial identity and function in situ. We demonstrated that the use of rRNA/mRNA stable isotope probing (SIP) recovered the key phylogenetic and functional RNAs. This was followed by single-cell physiological analyses of these populations to determine and quantify in situ functions within an aerobic naphthalene-degrading groundwater microbial community. Using these culture-independent approaches, we identified three prokaryote species capable of naphthalene biodegradation within the groundwater system: two taxa were isolated in the laboratory (Pseudomonas fluorescens and Pseudomonas putida), whereas the third eluded culture (an Acidovorax sp.). Using parallel population and single-cell stable isotope technologies, we were able to identify an unculturable Acidovorax sp. which played the key role in naphthalene biodegradation in situ, rather than the culturable naphthalene-biodegrading Pseudomonas sp. isolated from the same groundwater. The Pseudomonas isolates actively degraded naphthalene only at naphthalene concentrations higher than 30 mu M. This study demonstrated that unculturable microorganisms could play important roles in biodegradation in the ecosystem. It also showed that the combined RNA SIP-Raman-fluorescence in situ hybridization approach may be a significant tool in resolving ecology, functionality, and niche specialization within the unculturable fraction of organisms residing in the natural environment.

Uncertainty, learning and growth

The paper extends Blackburn and Galindev's (Economics Letters, Vol. 79 (2003), pp. 417-421) stochastic growth model in which productivity growth entails both external and internal learning behaviour with a constant relative risk aversion utility function and productivity shocks. Consequently, the relationship between long-term growth and short-term volatility depends not only on the relative importance of each learning mechanism but also on a parameter measuring individuals' attitude towards risk.