Development of High Performance Molecular Dynamics with Application to Multimillion-Atom Biomass Simulations

An understanding of the recalcitrance of plant biomass is important for efficient economic production of biofuel. Lignins are hydrophobic, branched polymers and form a residual barrier to effective hydrolysis of lignocellulosic biomass. Understanding lignin\u27s structure, dynamics and its interaction and binding to cellulose will help with finding more efficient ways to reduce its contribution to the recalcitrance. Molecular dynamics (MD) using the GROMACS software is employed to study these properties in atomic detail. Studying complex, realistic models of pretreated plant cell walls, requires simulations significantly larger than was possible before. The most challenging part of such large simulations is the computation of the electrostatic interaction. As a solution, the reaction-field (RF) method has been shown to give accurate results for lignocellulose systems, as well as good computational efficiency on leadership class supercomputers. The particle-mesh Ewald method has been improved by implementing 2D decomposition and thread level parallelization for molecules not accurately modeled by RF. Other scaling limiting computational components, such as the load balancing and memory requirements, were identified and addressed to allow such large scale simulations for the first time. This work was done with the help of modern software engineering principles, including code-review, continuous integration, and integrated development environments. These methods were adapted to the special requirements for scientific codes. Multiple simulations of lignocellulose were performed. The simulation presented primarily, explains the temperature-dependent structure and dynamics of individual softwood lignin polymers in aqueous solution. With decreasing temperature, the lignins are found to transition from mobile, extended to glassy, compact states. The low-temperature collapse is thermodynamically driven by the increase of the translational entropy and density fluctuations of water molecules removed from the hydration shell

Poster Session

Posters presented by: P01: Adam S. Abbott, University of Georgia P02: Yasmeen Abdo, University of Mississippi P03: Vibin Abraham, Virginia Tech P04: Asim Alenaizan, Georgia Institute of Technology P05: Isuru R. Ariyanthna, Auburn University P06: Brandon W. Bakr, Georgia Institute of Technology P07: [Matthew Bassett, Georgia Southern University] P08: Alexandre P. Bazanté, University of Florida P09: Andrea N. Becker, University of Tennessee P10: Randi Beil, University of Tennessee P11: Andrea N. Bootsma, University of Georgia/Texas A&M University P12: Adam Bruner, Louisiana State University P13: Lori A. Burns, Georgia Institute of Technology P14: Chanxi Cai, Emory University P15: Katherine A. Charbonnet, University of Memphis P16: Marjory C. Clement, Virginia Tech P17: Wallace D. Derricotte, Emory University P18: Harkiran Dhah, University of Tennessee P19: Manuel Díaz-Tinoco, Auburn University P20: Vivek Dixit: Mississippi State University P21: Eric Van Dornshuld, Mississippi State University P22: Katelyn M. Dreux, University of Mississippi P23: Narendra Nath Dutta, Auburn University P24: William Earwood, University of Mississippi P25: Thomas L. Ellington, University of Mississippi P26: Marissa L. Estep, University of Georgia P27: Yanfei Guan, Texas A&M University P28: Andrew M. James, Virginia Tech P29: Yifan Jin, University of Florida P30: Dwayne John, Middle Tennessee State University P31: Sarah N. Johnson, University of Mississippi P32: Noor Md Shahriar Khan, Auburn University P33: Monika Kodrycka, Auburn University P34: Ashutosh Kumar, Virginia Tech P35: Elliot Lakner, University of Alabama P36: Robert W. Lamb, Mississippi State University P37: S. Paul Lee, University of Mississippi P38: Zachary Lee, University of Alabama P39: Conrad D. Lewis, Middle Tennessee State University P40: Guangchao Liang, Mississippi State University P41: Chenyang Li, Emory University P42: Hannah C. Lozano, University of Memphis P43: SharathChandra Mallojjala, University of Georgia/Texas A&M University P44: Zheng Ma, Duke University P45: Elvis Maradzike, Florida State University P46: Ashley S. McNeill, University of Alabama P47: Stephen R. Miller, University of Georgia P48: W. J. Morgan, University of Georgia P49: Apurba Nandi, Emory University P50: Daniel R. Nascimento, Florida State University P51: Brooke N. Nash, Mississippi College P52: Carlie M. Novak, Georgia Southern University P53: Young Choon Park, University of Florida P54: Kirk C. Pearce, Virginia Tech P55: Rudradatt (Randy) Persaud, University of Alabama P56: Karl Pierce, Virginia Tech P57: Kimberley N. Poland, University of Mississippi P58: Chen Qu, Emory University P59: Duminda S. Ranasinghe, University of Florida P60: Hailey B. Reed, University of Mississippi P61: Matthew Schieber, Georgia Institute of Technology P62: Jeffrey B. Schriber, Emory University P63: Thomas Sexton, University of Mississippi P64: Holden T. Smith, Louisiana State University P65: Aubrey Smyly, Mississippi College P66: B. T. Soto, University of Georgia P67: Trent H. Stein, University of Alabama P68: Cody J. Stephan, Georgia Southern University P69: Thomas Summers, University of Memphis P70: Zhi Sun, University of Georgia P71: Monica Vasiliu, University of Alabama P72: Jonathan M. Waldrop, Auburn University P73: Tommy Walls, Southern Louisiana University P74: Qingfeng (Kee) Wang, Emory University P75: Constance E. Warden, Georgia Institute of Technology P76: Jared D. Weidman, University of Georgia P77: Melody Williams, University of Memphis P78: Donna Xia, University of Alabama P79: Qi Yu, Emory University P80: Boyi Zhang, University of Georgia P81: Tianyuan Zhang, Emory University P82: Michael Zott, Georgia Institute of Technolog

Research Reports: 1997 NASA/ASEE Summer Faculty Fellowship Program

For the 33rd consecutive year, a NASA/ASEE Summer Faculty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The program was conducted by the University of Alabama in Huntsville and MSFC during the period June 2, 1997 through August 8, 1997. Operated under the auspices of the American Society for Engineering Education, the MSFC program was sponsored by the Higher Education Branch, Education Division, NASA Headquarters, Washington, D.C. The basic objectives of the program, which are in the 34th year of operation nationally, are: (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of the participants' institutions; and (4) to contribute to the research objectives of the NASA centers. The Faculty Fellows spent 10 weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This document is a compilation of Fellows' reports on their research during the summer of 1997. The University of Alabama in Huntsville presents the Co-Directors' report on the administrative operations of the program. Further information can be obtained by contacting any of the editors

NASA SBIR abstracts of 1991 phase 1 projects

The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

Evaluation of single photon avalanche diode arrays for imaging fluorescence correlation spectroscopy : FPGA-based data readout and fast correlation analysis on CPUs, GPUs and FPGAs

The metabolism of all living organisms, and specifically also of their smallest constituents, the cell, is based on chemical reactions. A key factor determining the speed of these processes is transport of reactants, energy, and information within the and between the cells of an organism. It has been shown that the relevant transport processes also depend on the spatial organization of the cells. Such transport processes are typically investigated using fluorescence correlation spectroscopy (FCS) in combination with fluorescent labeling of the molecules of interest. In FCS, one observes the fluctuating fluorescence signal from a femtoliter-sized sub-volume within the sample (e.g. a cell). The variations in the intensity arise from the particles moving in and out of this sub-volume. By means of an autocorrelation analysis of the intensity signal, conclusion can be drawn regarding the concentration and the mobility parameters, such as the diffusion coefficient. Typically, one uses the laser focus of a confocal microscope for FCS measurements. But with this microscopy technique, FCS is limited to a single spot a every time. In order to conduct parallel multi-spot measurements, i.e. to create diffusion maps, FCS can be combined with the lightsheet based selective plane illumination microscopy (SPIM). This recent widefield microscopy technique allows observing a small plane of a sample (1-3um thick), which can be positioned arbitrarily. Usually, FCS on a SPIM is done using fast electron-multiplying charge-coupled device (EMCCD) cameras, which offer a limited temporal resolution (500us). Such a temporal resolution only allows measuring the motion of intermediately sized particles within a cell reliably. The limited temporal resolution renders the detection of even smaller molecules impossible. In this thesis, arrays of single photon avalanche diodes (SPADs) were used as detectors. Although SPAD-based image sensors still lack in sensitivity, they provide a significantly better temporal resolution (1-10us for full frames) that is not achievable with sensitive cameras and seem to be the ideal sensors for SPIM-FCS. In the course of this work, two recent SPAD arrays (developed in the groups of Prof. Edoardo Charbon, TU Delft, the Netherlands, and EPFL, Switzerland) were extensively characterized with regards to their suitability for SPIM-FCS. The evaluated SPAD arrays comprise 32x32 and 512x128 pixels and allow for frame rates of up to 300000 or 150000 frames per second, respectively. With these specifications, the latter array is one of the largest and fastest sensors that is currently available. During full-frame readout, it delivers a data rate of up to 1.2 GiB/s. For both arrays, suitable readout-hardware-based on field programmable gate arrays (FPGAs) was designed. To cope with the high data rate and to allow real-time correlation analysis, correlation algorithms were implemented and characterized on the three major high performance computing platforms, namely FPGAs, CPUs, and graphics processing units (GPUs). Of all three platforms, the GPU performed best in terms of correlation analysis, and a speed of 2.6 over real time was achieved for the larger SPAD array. Beside the lack in sensitivity, which could be accounted for by microlenses, a major drawback of the evaluated SPAD arrays was their afterpulsing. It appeared that the temporal structure superimposed the signal of the diffusion. Thus, extracting diffusion properties from the autocorrelation analysis only proved impossible. By additionally performing a spatial cross-correlation analysis such influences could be significantly minimized. Furthermore, this approach allowed for the determination of absolute diffusion coefficients without prior calibration. With that, spatially resolved measurements of fluorescent proteins in living cells could be conducted successfully

Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT's hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness

New Trends in 3D Printing

A quarter century period of the 3D printing technology development affords ground for speaking about new realities or the formation of a new technological system of digital manufacture and partnership. The up-to-date 3D printing is at the top of its own overrated expectations. So the development of scalable, high-speed methods of the material 3D printing aimed to increase the productivity and operating volume of the 3D printing machines requires new original decisions. It is necessary to study the 3D printing applicability for manufacturing of the materials with multilevel hierarchical functionality on nano-, micro- and meso-scales that can find applications for medical, aerospace and/or automotive industries. Some of the above-mentioned problems and new trends are considered in this book

KINETICALLY CONSISTENT THERMAL LATTICE BOLTZMANN MODELS

The lattice Boltzmann (LB) method has developed into a numerically robust and efficient technique for simulating a wide variety of complex fluid flows. Unlike conventional CFD methods, the LB method is based on microscopic models and mesoscopic kinetic equations in which the collective long-term behavior of pseudo-particles is used to simulate the hydrodynamic limit of a system. Due to its kinetic basis, the LB method is particularly useful in applications involving interfacial dynamics and complex boundaries, such as multiphase or multicomponent flows. However, most of the LB models, both single and multiphase, do not satisfy the energy conservation principle, thus limiting their ability to provide quantitatively accurate predictions for cases with substantial heat transfer rates. To address this issue, this dissertation focuses on developing kinetically consistent and energy conserving LB models for single phase flows, in particular. Firstly, through a procedure similar to the Galerkin method, we present a mathematical formulation of the LB method based on the concept of projection of the distributions onto a Hermite-polynomial basis and their systematic truncation. This formulation is shown to be capable of approximating the near incompressible, weakly compressible, and fully compressible (thermal) limits of the continuous Boltzmann equation, thus obviating the previous low-Mach number assumption. Physically it means that this formulation allows a kinetically-accurate description of flows involving large heat transfer rates. The various higher-order discrete-velocity sets (lattices) that follow from this formulation are also compiled. The resulting higher-order thermal model is validated for benchmark thermal flows, such as Rayleigh-Benard convection and thermal Couette flow, in an off-lattice framework. Our tests indicate that the D2Q39-based thermal models are capable of modeling incompressible and weakly compressible thermal flows accurately. In the validation process, through a finite-difference-type boundary treatment, we also extend the applicability of higher-order la ttices to flow-domains with solid boundaries, which was previously restricted. Secondly, we present various off-lattice time-marching schemes for solving the discrete Boltzmann equation. Specifically, the various temporal schemes are analyzed with respect to their numerical stability as a function of the maximum allowable time-step . We show that the characteristics-based temporal schemes offer the best numerical stability among all other comparable schemes. Due to this enhanced numerical stability, we show that the usual restriction no longer applies, enabling larger time-steps, and thereby reducing the computational run-time. The off-lattice scheme were also successfully extended to higher-order LB models. Finally, we present the algorithm and single-core optimization techniques for a off-lattice, higher-order LB code. Using simple cache optimization techniques and a proper choice of the data-structure, we obtain a 5-7X improvement in performance compared to a naive, unoptimized code. Thereafter, the optimized code is parallelized using OpenMP. Scalability tests indicate a parallel efficiency of 80% on shared-memory systems with up to 50 cores (strong scaling). An analysis of the higher-order LB models also show that they are less memory-bound if the off-lattice temporal schemes are used, thus making them more scalable compared to the stream-collide type scheme