The Kepler mission was a National Aeronautics and Space Agency (NASA) Discovery-class mission designed to continuously monitor the brightness of at least 100,000 stars to determine the frequency of Earth-size and larger planets orbiting other stars. Once the Kepler proposal was chosen for a flight opportunity, it was necessary to optimize the design to accomplish the ambitious goals specified in the proposal and still stay within the available resources. To maximize the science return from the mission, a merit function (MF) was constructed that relates the science value (as determined by the PI and the Science Team) to the chosen mission characteristics and to models of the planetary and stellar systems. This MF served several purposes; predicting possible science results of the proposed mission, evaluating the effects of varying the values of the mission parameters to increase the science return or to reduce the mission costs, and supporting quantitative risk assessments. The MF was also valuable for the purposes of advocating the mission by illustrating its expected capability. During later stages of implementation, it was used to keep management informed of the changing mission capability and support rapid design tradeoffs when mission down-sizing was necessary. The MF consisted of models of the stellar environment, assumed exoplanet characteristics and distributions, detection sensitivity to key design parameters, and equations that related the science value to the predicted number and distributions of detected exoplanet. A description of the MF model and representative results are presented. Examples of sensitivity analyses that supported design decisions and risk assessments are provided to illustrate the potential broader utility of this approach to other complex science-driven space missions.

中文翻译：

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开普勒任务的科学价值功能

开普勒任务是美国国家航空航天局（NASA）发现级任务，旨在连续监测至少100,000个恒星的亮度，以确定地球大小和绕其他恒星运行的较大行星的频率。一旦选择开普勒提案作为飞行机会，就必须优化设计以实现提案中指定的雄心勃勃的目标，并且仍要在可用资源范围内。为了使任务的科学回报最大化，构建了一项价值函数（MF），该函数将科学价值（由PI和科学团队确定）与选定的任务特征以及行星和恒星系统模型相关联。该MF有多个目的；预测拟议任务的可能科学结果，评估改变任务参数值的效果，以增加科学回报或降低任务成本，并支持定量风险评估。MF通过说明其预期能力来倡导任务也很有价值。在实施的后期阶段，它用于使管理层随时了解任务能力的变化，并在需要缩小任务规模时支持快速的设计权衡。MF由恒星环境模型，假定的系外行星特征和分布，对关键设计参数的探测灵敏度以及将科学价值与探测到的系外行星的预测数量和分布相关的方程组成。给出了MF模型的描述和代表性的结果。