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LRAC的要求中，我们建议研究湍流、血液动力学、材料研究和生物分子科学中的问题。在材料科学领域，我们计划定量研究液晶材料和粘土-聚合物纳米复合材料的紧急性质，这两种材料具有巨大的科学和技术意义。这项工作将在非常大的系统模型上进行，使用大规模并行代码，由于计算资源的限制，到目前为止还不可能。在生物分子科学领域，我们的项目关注于了解基于药物结合亲和力计算的生物相关过程。在这里提出的项目中，我们建立在早期工作的基础上，我们开发和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模拟访问物理时间尺度，这到目前为止很难实现。我们将集中于这一提议中的六个具体项目：(I)识别Navier-Stokes方程中的不稳定周期轨道：这项工作的目的是利用一种新的四维时空并行方法来识别用于描述湍流的不稳定周期轨道。(Ii)患者特定的全脑血流模拟：我们在这个项目中的目标是提供一个有效的计算环境，通过在临床相关的时间范围内提供关于患者特定的血流动力学的信息来辅助神经血管外科的介入神经放射科医生。(Iii)液晶材料的大规模格子Boltzmann模拟：在这个项目中，我们将使用我们经过验证的动力学格子Boltzmann方法来研究立方液晶在三元两亲性混合物中的流变响应和自组装动力学。粘土-聚合物纳米复合材料的材料性质：本工作的目的是利用前所未有的模型尺寸，利用分子动力学模拟计算粘土-聚合物纳米复合材料的块体材料性质。(V)HIV-1蛋白水解酶和逆转录酶的耐药性：这项工作的目的是阐明和预测患者特有的HIV-1蛋白水解酶和逆转录酶突变对药物结合亲和力的影响。这项工作将使用NAMD在我们之前的TeraGrid工作中开发的新模拟方法的基础上进行。(Vi)用高性能计算分子动力学预测EGFR激活域与药物抑制剂的亲和力：本工作的目的是阐明和预测癌症特异性蛋白--表皮生长因子受体(EGFR)的患者特异性突变对药物结合亲和力的影响。这项工作将使用NAMD和新的系综分子动力学模拟来进行。我们使用可扩展代码HYPO4D、HEMELB、LB3D、LAMPS和NAMD，这些代码已经在我们之前的TeraGrid工作中进行了广泛的基准测试和使用，特别是在Ranger上，我们已经在高达32768个内核上实现了可伸缩。该代码已被用于在我们获得TeraGrid‘08“转型科学挑战”奖的GENES项目中进行模拟研究。我们还获得了HYPO4D和LB3D代码的5K Club奖。我们将使用NAMD进行分子动力学研究，这是一种广泛使用的社区代码，以前曾在SPICE项目的获奖模拟中使用过。

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.