Collaborative Research: Calibration of Thermochemical Models using Bayesian Methods--Building MELTS 2.0.

协作研究：使用贝叶斯方法校准热化学模型 - 构建 MELTS 2.0。

• 批准号: 1725425
• 负责人: Mark Ghiorso
• 金额: $ 7.13万
• 依托单位: OFM Research
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1725425&HistoricalAwards=false
• 关键词: Collaborative; Research; Calibration; Thermochemical; Models

Molten rocks are essential to the structure and long-term evolution of the Earth and other planets. The properties of rocks when heated above their melting point (including composition, density, heat content, and thermal expansion) all play important roles in a vast array of geologic processes. These range widely from the creation of deep magma oceans during the earliest stages of planet formation all the way to the steady progress of plate tectonics, responsible for creating, shaping, and destroying the Earth's oceans and continents. Unfortunately, these geologic processes occur over planetary length-scales and time-scales, playing out over thousands of kilometers and billions of years. Due to this complexity, it is not possible to perform experiments that directly probe the evolution of planetary interiors. Instead, scientist rely upon thermodynamic models, which can predict the physical and energetic properties of rocks, melts, and fluids based on the results of laboratory experiments performed under controlled conditions. The usefulness of these models thus depends entirely upon how well they are calibrated, including the amount and variety of experimental data as well as the statistical methods used to extract the thermodynamic modeling parameters. In this proposal, the team will develop new modeling techniques needed to improve and extend the geologic thermodynamic models used to predict the properties of solid and molten rocks at planetary conditions, relevant to our understanding of rocky planets both within and outside our solar system.To accomplish these overarching goals, the collaborators will design the analytic tools needed to construct flexible and robust self-consistent thermodynamic models for the geologic community using Bayesian statistical methods. Currently, the calibration procedure for thermodynamic databases (like the popular MELTS model) is an unfortunately onerous task. Updating these models is time-consuming and restricted to the very few experts with the skills required to integrate new information without breaking the accuracy and self-consistency of the model. The purpose of this proposal is to dramatically reduce the challenges associated with recalibration, enabling simple and rapid incorporation of new experimental data into the database by a wide variety of users. The proposal objectives are: (1) Design and create statistical calibration tools (using novel Bayesian techniques) to simplify thermochemical model building; (2) Expand and augment the calibration database with the large quantity of previously ignored data, including solid phase-absent constraints, melt-free sub-solidus experiments, and observations of melt coexisting with solid phases of unmeasured-composition; (3) Use the new methods and data to produce MELTS 2.0, a new tunable silicate melts model that provides model prediction uncertainties, enabling users to rapidly pinpoint and address model weaknesses. The resulting calibration tool will thus be able to generate and visualize model prediction distributions - useful for geologic process modeling, teaching, and future experimental planning -and help to close the large gap that still exists between model-use and model-design.

熔融岩石对于地球和其他行星的结构和长期演变至关重要。 当岩石在其熔点上方加热时（包括成分，密度，热含量和热膨胀）时，岩石的性质都在各种地质过程中起着重要作用。这些范围广泛，范围从行星形成的最早阶段的深岩浆海洋一直到板块构造的稳定进步，负责创造，塑造和破坏地球的海洋和大陆。 不幸的是，这些地质过程发生在行星长度和时间尺度上，播放了数千公里和数十亿年。 由于这种复杂性，无法执行直接探测行星内部演化的实验。取而代之的是，科学家依靠热力学模型，这些模型可以根据受控条件下进行的实验室实验的结果来预测岩石，熔体和流体的物理和能量性能。 因此，这些模型的有用性完全取决于它们的校准程度，包括实验数据的数量和种类以及用于提取热力学建模参数的统计方法。 在这项建议中，团队将开发需要改进和扩展用于预测行星条件下固体和熔融岩石的地质热力学模型所需的新建模技术，这与我们对太阳系内外的岩石行星的理解相关。要实现这些总体目标，该目标将使用这些统计学的稳定性自我模型来设计，以实现这些总体构建的稳定性自我模型。 方法。 当前，热力学数据库的校准程序（如流行融化模型）是不幸的繁重的任务。 更新这些模型是耗时的，并且仅限于很少有专家，而没有破坏该模型的准确性和自我矛盾所需的技能。 该建议的目的是大大减少与重新校准相关的挑战，从而使各种用户可以简单而快速地将新的实验数据纳入数据库。 提案目标是：（1）设计和创建统计校准工具（使用新颖的贝叶斯技术）来简化热化学模型构建； （2）使用大量先前被忽略的数据扩展和增强校准数据库，包括固体相位的约束，无融化的无融合亚果酚实验，以及与未经测量复合的固体相交的熔体共存的观察结果； （3）使用新方法和数据生产熔体2.0，这是一种新的可调硅酸盐融化模型，可提供模型预测不确定性，使用户能够快速查明并解决模型弱点。 因此，所得的校准工具将能够生成和可视化模型预测分布 - 对地质过程建模，教学和未来的实验计划有用 - 并有助于缩小模型使用和模型设计之间仍然存在的较大差距。