High-performance Computing and Data-driven Modeling of Aircraft Contrails
High-performance Computing and Data-driven Modeling of Aircraft Contrails
批准号:
1854815
负责人:
Georgeta-Elisab Marai
金额:
$44.64万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-01 至 2023-06-30
中文摘要
该项目旨在模拟凝结尾迹(“尾迹”)的早期形成,凝结尾迹是由飞机发动机排出的水产生的冰云。尽管这些轨迹最初看起来是线性的,但它们可以在有利的大气条件下扩散,形成可以持续数小时的卷云,最终几乎无法与自然卷云区分开来。尾迹和尾迹卷云确实是航空对地球辐射预算(即进入地球、反射、吸收和发射的能量的平衡)最不确定的贡献。对这一复杂的多物理问题进行建模具有挑战性,因为不同的物理过程在不同的时间和空间尺度上相互作用。该项目使用高分辨率数值模拟来应对这一挑战,高分辨率数值模拟广泛依赖高性能计算和先进的可视化技术来帮助识别、捕获和模拟轨迹特征。模拟的主要焦点是在轨迹演化的早期阶段,由飞机尾迹涡产生的大范围运动的存在与由射流和尾迹湍流引起的小尺度扰动相互作用。轨迹参数化结果将支持将排放纳入全球大气模式。尾迹特性对初始颗粒排放的敏感性可能会提出潜在的缓解策略。来自伊利诺伊大学芝加哥分校、西班牙裔服务机构和少数民族服务机构的少数族裔学生将参与计算研究。研究的具体目标是:(1)进行包括整个飞机几何形状的第一个全三维空间大涡模拟(LES),并开发准确的喷流和涡区轨迹演变数据集;(2)通过使用先进的可视化技术记录模拟工作流程,识别三维轨迹特征和拟合参数;(3)使用基于高保真数据训练的人工神经网络来降低生成的数据集的大维度,并提供喷流区域末期轨迹结构的通用而准确的模型;以及(4)使用统计启发方法(如多项式-混沌展开等)重建整个时间演化过程中的轨迹全局特性,以将其参数化为全局模型。通过这项工作开发的技术将使轨迹参数化与全球大气模型中使用的物理假设和守恒方程一致。这些技术将进一步处理冰粒的微物理和光学/辐射特性方面的巨大不确定性。这些技术还将处理大气条件中的大变异性,这些条件决定了尾迹的背景和边界条件。可视化分析框架将实现对流动特征的检测和分析,以及对多个模拟和参数的多尺度和多运行分析。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
This project aims to model the early-phase formation of condensation trails ("contrails"), which are ice clouds generated by water exhaust from aircraft engines. Although the contrails initially appear to be linear, they can spread under favorable atmospheric conditions and form cirrus clouds that can persist for hours and eventually become almost indistinguishable with natural cirrus. Contrails and contrail-cirrus are indeed the most uncertain aviation contributions to the Earth-radiation budget (that is, the balance of energy entering, reflected, absorbed, and emitted by the Earth). Modeling this complex multi-physics problem is challenging because the different physical processes interact at different time and spatial scales. This project addresses this challenge using high-resolution numerical simulations that rely extensively on high-performance computing and advanced visualization techniques to help identify, capture and model contrail features. The primary focus of the modeling is on the early phase of contrail evolution where the presence of large-scale motions generated by the aircraft wake vortices and the small-scale perturbations induced by the jet and wake turbulence interact. The contrail parameterization results will support the integration of emissions into global atmospheric models. The sensitivity of contrail properties to the initial particle emissions may suggest potential mitigation strategies. Underrepresented minority students from the University of Illinois at Chicago, a Hispanic Serving Institution and a Minority Serving Institution, will be engaged in the computational research.The specific goals of the research are: (1) to carry out the first fully three-dimensional spatial large-eddy simulations (LES) of contrail formation that include the full aircraft geometry and to develop an accurate data-set of contrail evolution in the jet and vortex regime; (2) to identify the three-dimensional contrail features and fit parameters by journaling the simulation workflow using advanced visualization techniques; (3) to reduce the large dimensionality of the generated data-set and provide a general and accurate model of contrail structure at the end of the jet regime using Artificial Neural Networks based on high-fidelity data training; and (4) to reconstruct contrail global properties over the full time evolution using statistically inspired methods such as Polynomial-Chaos expansions for parameterization into global models. The techniques developed through this work will enable contrail parameterizations that are consistent with the physical assumptions and the conservation equations used in global atmospheric models. These techniques will further handle large uncertainties in the microphysical and optical/radiative properties of ice particles. The techniques will also handle large variability in atmospheric conditions that determine the background and boundary conditions for LES of contrails. A visual analysis framework will enable detection and analysis of flow features, as well as multi-scale and multi-run analysis of multiple simulations and parameters.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Numerical Experiments of Subsonic Jet Flow Simulations Using RANS with OpenFOAM
使用 RANS 和 OpenFOAM 进行亚音速射流模拟的数值实验
DOI:
10.4236/ojfd.2022.122011
发表时间:
2022
期刊:
Open Journal of Fluid Dynamics
影响因子:
--
作者:
[Zadeh, Negar Naghash, Paoli, Roberto]
通讯作者:
Paoli, Roberto
DOI:
10.1111/cgf.14830
发表时间:
2023-06-01
期刊:
COMPUTER GRAPHICS FORUM
影响因子:
2.5
作者:
[Wentzel,A., Floricel,C., Marai,G. E.]
通讯作者:
Marai,G. E.
DOI:
10.1109/tvcg.2023.3326939
发表时间:
2024-01-01
期刊:
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
影响因子:
5.2
作者:
[Floricel,Carla, Wentzel,Andrew, Marai,G. Elisabeta]
通讯作者:
Marai,G. Elisabeta
DOI:
10.1109/tvcg.2021.3114810
发表时间:
2022-01
期刊:
IEEE transactions on visualization and computer graphics
影响因子:
5.2
作者:
[Floricel C, Nipu N, Biggs M, Wentzel A, Canahuate G, Van Dijk L, Mohamed A, Fuller CD, Marai GE]
通讯作者:
Marai GE
Parameter Analysis and Contrail Detection of Aircraft Engine Simulations
飞机发动机仿真的参数分析和轨迹检测
DOI:
10.1109/ldav53230.2021.00016
发表时间:
2021
期刊:
2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV
影响因子:
--
作者:
[Nipu, Nafiul, Floricel, Carla, Naghashzadeh, Negar, Paoli, Roberto, Marai, G. Elisabeta]
通讯作者:
Marai, G. Elisabeta
共 7 条
WORKSHOP: Doctoral Colloquium at IEEE VIS 2016
-
批准号:1647803
-
项目类别:Standard Grant
-
资助金额:$2.09万
-
财政年份:2016
-
负责人:Georgeta-Elisab Marai
-
依托单位:
WORKSHOP: Doctoral Colloquium at IEEE VIS 2015
-
批准号:1540159
-
项目类别:Standard Grant
-
资助金额:$2.09万
-
财政年份:2015
-
负责人:Georgeta-Elisab Marai
-
依托单位:
QuBBD: Collaborative Research: SMART -- Spatial-Nonspatial Multidimensional Adaptive Radiotherapy Treatment
-
批准号:1557559
-
项目类别:Standard Grant
-
资助金额:$2.5万
-
财政年份:2015
-
负责人:Georgeta-Elisab Marai
-
依托单位:
CAREER: Data-driven Bottom-Up Humanoid Articulations
-
批准号:1541277
-
项目类别:Continuing Grant
-
资助金额:$27.25万
-
财政年份:2014
-
负责人:Georgeta-Elisab Marai
-
依托单位:
CAREER: Data-driven Bottom-Up Humanoid Articulations
-
批准号:0952720
-
项目类别:Continuing Grant
-
资助金额:$53.68万
-
财政年份:2010
-
负责人:Georgeta-Elisab Marai
-
依托单位:
海外基金