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的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目及 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 在这个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。材料中 科学领域，我们计划定量地研究液体的涌现性质， 晶体材料和粘土聚合物纳米复合材料， 科学和技术相关性。这项工作将进行非常大的系统 模型，使用大规模并行代码，迄今为止不可能，由于计算 资源限制。在生物分子科学领域，我们的项目涉及 通过了解基于药物结合亲和力的生物学相关过程， 计算。在这里提出的项目中，我们建立在早期工作的基础上， 开发并验证了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，这是迄今为止很难实现的。我们将重点关注六个方面 本提案中的具体项目：㈠确定不稳定周期轨道 在Navier-Stokes方程：这项工作的目的是确定不稳定 用一种新的四轨道模型描述湍流特性的周期轨道 三维时空平行化方法(ii)患者特异性全脑血 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 环境，以协助介入神经放射科医生进行神经血管手术， 提供临床相关范围内的患者特定血流动力学信息 的时间表. (iii)液晶的大尺度格子Boltzmann模拟 材料：在这个项目中，我们将研究流变响应和自组装 三元两亲性混合物中立方液晶的动力学， 测试动力学格子玻尔兹曼方法。(iv)粘土-聚合物材料性能 纳米复合材料：这项工作的目的是计算散装材料 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)HIV-1蛋白酶的耐药性和 逆转录酶：这项工作的目的是阐明和预测 HIV-1蛋白酶和逆转录酶的患者特异性突变对 药物结合亲和力这项工作将进行使用NAMD建设的小说 模拟方法在我们以前的工作中开发的TeraGrid。（六） 高效液相色谱法预测EGFR激酶结构域对药物抑制剂的亲和力 计算分子动力学：这项工作的目标是阐明和预测 癌症特异性蛋白质、表皮生长、 因子受体（EGFR）对药物结合亲和力的影响。这项工作将通过NAMD进行 和新颖的系综分子动力学模拟。我们使用可扩展代码HYPO 4D， HemeLB、LB 3D、LAMMPS和NAMD已被广泛基准化， 在我们以前的TeraGrid工作中使用，特别是在Ranger上，我们有 在多达32768个内核上实现了可扩展性。HemeLB代码已用于 在GENIUS项目中进行模拟研究， 在TeraGrid'08中获得“变革科学挑战”奖。我们还收到 HYPO 4D和LB 3D代码获得5 K俱乐部奖。我们将使用NAMD作为我们的分子 动力学研究，这是一个广泛使用的社区代码，并已在以前 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.