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ABSTRACT Traditional commercial aircraft design attempts to achieve improved performance and reduced operating costs by minimizing maximum takeoff weight. From the point of view of an aircraft manufacturer, however, this method does not guarantee the financial viability of an aircraft program. To assess the long-term financial impact of an aircraft program, a value-based approach is recommended. Such an approach might still account for performance while also incorporating the following elements to assess predicted cash flows into and out of the program: manufacturing and development costs. A valuation methodology has been proposed that draws on financial options theory and uses dynamic programming to estimate the costs, price, and demand associated with a previously optimized aircraft design. PROGRAM VALUATION By choosing maximum program value as a design objective, many of the above factors – performance, cost, demand – can be considered by modeling their effects on overall cost and revenue. A properly chosen value calculation based on these cash flows can effectively capture the entire program design in a single number. SIMULATION MODEL The dynamic programming problem above requires annual cost and revenue estimates for the aircraft program. These values are derived from models that take both the design vector and resulting aircraft design parameters as inputs. Physical Model. Physical Model. Inputs were the overall design vector – number of passengers and aircraft range – in addition to a number of used-specified parameters. Wing shape, cruise conditions, engine configuration, and takeoff and landing performance were fixed to values approximating a 777-class aircraft before optimization runs were begun. The cash flow in a given period was the sum of sales profits, less the design and production costs incurred and cost of switching modes. Cash flows were further adjusted for inflation and discounted by the risk-free rate. OPTIMIZATION FRAMEWORK. A design optimization framework coupled the performance and financial models with an optimization routine as illustrated in Figure 2. An initial design vector (number of passengers, range) was provided to the physical model to estimate aircraft sizing and performance characteristics.
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