A generic tool for cost estimating in aircraft design

A methodology to estimate the cost implications of design decisions by integrating cost as a design parameter at an early design stage is presented. The model is developed on a hierarchical basis, the manufacturing cost of aircraft fuselage panels being analysed in this paper. The manufacturing cost modelling is original and relies on a genetic-causal method where the drivers of each element of cost are identified relative to the process capability. The cost model is then extended to life cycle costing by computing the Direct Operating Cost as a function of acquisition cost and fuel burn, and coupled with a semi-empirical numerical analysis using Engineering Sciences Data Unit reference data to model the structural integrity of the fuselage shell with regard to material failure and various modes of buckling. The main finding of the paper is that the traditional minimum weight condition is a dated and sub-optimal approach to airframe structural design.

Economic cost of age-related macular degeneration: a review of recent research

As the population of most developed countries ages so the prevalence of diseases such as age-related macular degeneration (AMD) are likely to increase. To facilitate planning and informed debate regarding making provisions for this disease it is important that we have a clear understanding of the economic impact of visual impairment associated with AMD. In this paper we assess the state of current knowledge based on a review of published evidence in scientific journals. Based on our assessment of the evidence we argue that the paucity of research studies on the subject and wide variation in estimates produced from the few studies available make it difficult to assess with confidence the likely average direct cost-of-illness associated with AMD. We further argue that significant gaps in our understanding of the costs of AMD (particularly in respect of indirect costs) also exist. Current research should be augmented by more comprehensive studies.

Query cost estimation through remote system contention states analysis over the Internet

Query processing over the Internet involving autonomous data sources is a major task in data integration. It requires the estimated costs of possible queries in order to select the best one that has the minimum cost. In this context, the cost of a query is affected by three factors: network congestion, server contention state, and complexity of the query. In this paper, we study the effects of both the network congestion and server contention state on the cost of a query. We refer to these two factors together as system contention states. We present a new approach to determining the system contention states by clustering the costs of a sample query. For each system contention state, we construct two cost formulas for unary and join queries respectively using the multiple regression process. When a new query is submitted, its system contention state is estimated first using either the time slides method or the statistical method. The cost of the query is then calculated using the corresponding cost formulas. The estimated cost of the query is further adjusted to improve its accuracy. Our experiments show that our methods can produce quite accurate cost estimates of the submitted queries to remote data sources over the Internet.