LATTICE-BOLTZMANN STUDIES OF TURBULENCE, BLOOD FLOW AND LIQUID CRYSTALS, AND MO

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 在这份LRAC请求中，我们建议研究湍流中的问题， 血液动力学、材料研究和生物分子科学。在材料中 科学领域，我们计划定量研究液体的突现性质 结晶材料和粘土-聚合物纳米复合材料，具有巨大的 科学和技术的相关性。这项工作将在非常大的系统中进行 使用大规模并行代码的模型，由于计算的原因，到目前为止还不可能 资源限制。在生物分子科学领域，我们的项目涉及 了解基于药物结合亲和力的生物相关过程 计算。在这里提出的项目中，我们在我们已有的早期工作的基础上 开发和验证新的计算算法和网格计算 基础设施，允许通过分子动力学访问物理时间尺度 模拟，到目前为止，这是很难实现的。我们将重点关注六个方面 本提案中的具体项目：(1)确定不稳定周期轨道(UPO) 在Navier-Stokes方程中：这项工作的目标是识别不稳定 用一种新的四轨道模型表征湍流的周期轨道 维度时空可并行化方法。(Ii)患者特有的全脑血 流动模拟：我们在这个项目中的目标是提供一个有效的计算 在神经血管手术中协助介入神经放射科医生的环境 在临床相关区域内提供特定于患者的血流动力学信息 时间框架。(Iii)液晶的大规模格子-玻耳兹曼模拟 材料：在本项目中，我们将研究流变性响应和自组装。 三元两亲混合物中立方液晶的动力学研究 测试了动力学格子-玻尔兹曼方法。(四)粘土聚合物的材料特性 纳米复合材料：这项工作的目标是计算块体材料 粘土-聚合物纳米复合材料性能的分子动力学模拟 使用前所未有的模型尺寸。(V)艾滋病毒-1蛋白水解酶和 逆转录酶：这项工作的目标是阐明和预测 HIV-1蛋白酶和逆转录酶患者特异性突变对人类免疫功能的影响 药物结合亲和力。这项工作将使用NAMD建筑在小说上进行 我们之前在TeraGrid上的工作中开发了模拟方法。(Vi) 高效预测药物抑制剂对EGFR激活域的亲和力 计算分子动力学：这项工作的目的是阐明和预测 患者特定突变对癌症特异性蛋白、表皮生长的影响 药物结合亲和力上的因子受体(EGFR)。这项工作将使用NAMD进行 和新颖的系综分子动力学模拟。我们使用可伸缩码HYPO4D， 已经过广泛基准测试的hemeLB、LB3D、LAMMPS和NAMD 在我们之前关于TeraGrid的工作中使用，特别是在Ranger上，我们在那里有 实现了多达32768个核心的可扩展性。HemeLB码已被用于 在天才项目中进行模拟研究，我们获得了 在TeraGrid‘08上颁发的“变革性科学挑战”奖。我们还收到了 HYPO4D和LB3D代码的5K俱乐部奖。我们将对我们的分子使用NAMD 动力学研究，这是一种广泛使用的社区代码，以前 用于SPICE项目的获奖模拟。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In this LRAC request, we propose to investigate problems in turbulence, haemodynamics, materials research and the biomolecular science. In the materials science domain, we plan to quantitatively study the emergent properties of liquid crystalline materials and of clay-polymer nanocomposites which have immense scientific and technological relevance. This work will be carried for very large system models, using massively parallel codes, hitherto not possible due to computational resource limitations. In the biomolecular sciences domain, our projects are concerned with understanding biologically relevant processes based on drug binding affinity calculations. In the projects proposed here, we build on earlier work where we have developed and validated novel computational algorithms and grid computing infrastructure, allowing access to physical timescales via molecular dynamics simulations, which have so far been very difficult to achieve. We shall focus on six specific projects in this proposal: (i) Identification of Unstable Periodic Orbits (UPOs) in the Navier-Stokes equations: The objective of this work is to identify Unstable Periodic Orbits for the characterisation of turbulent flows using a novel four- dimensional spacetime parallelisable approach. (ii) Patient-specific whole brain blood flow simulations: Our objective in this project is to provide an efficient computational environment to assist interventional neuroradiologists in neurovascular surgery by providing information on patient-specific haemodynamics within clinically relevant timeframes. (iii) Large-scale lattice-Boltzmann simulations of liquid crystalline materials: In this project we will study the rheological response and self-assembly dynamics of cubic liquid crystals in ternary amphiphilic mixtures using our tried and tested kinetic lattice-Boltzmann approach. (iv) Materials properties of clay-polymer nanocomposites: The objective of this work is to calculate the bulk materials properties of clay-polymer nanocomposites using molecular dynamics simulations using unprecedented model sizes. (v) Drug resistance in HIV-1 proteases and reverse transcriptases: The objective of this work is to elucidate and predict the effect of patient-specific mutations in HIV-1 Proteases and Reverse Transcriptases on drug-binding affinities. This work will be carried using NAMD building on novel simulation methodologies developed in our previous work on the TeraGrid. (vi) Predicting affinity of EGFR kinase domain for drug inhibitors using high performance computing molecular dynamics: The objective this work is to elucidate and predict the effect of patient-specific mutations in the cancer-specific protein, epidermal growth factor receptor (EGFR) on drug-binding affinities. This work will be carried using NAMD and novel ensemble molecular dynamics simulations. We use scalable codes HYPO4D, HemeLB, LB3D, LAMMPS and NAMD which have been extensively benchmarked and used in our previous work on the TeraGrid, particularly on Ranger, where we have achieved scalability on up to 32768 cores. The HemeLB code has been used to conduct simulation studies within the GENIUS project for which we received the "Transformational Science Challenge" award at TeraGrid'08. We have also received 5K Club awards for the HYPO4D and LB3D codes. We will use NAMD for our molecular dynamics studies which is a widely used community-code and has been previously used in award winning simulations of the SPICE project.