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NASA NTRSDate not supplied

Simulation of Radiation-Induced DNA Damage With the Code RITRACKS

INTRODUCTION DNA damage is one of the most physiologically important effects of ionizing radiation. Clustered DNA damage events, like double-strand breaks (DSBs), have the most notable biological consequences. DNA damage types depend on both the track structure of the radiation and the spatial organization of the DNA. High linear energy transfer (LET) charged nuclei, found in galactic cosmic rays (GCR), are known to produce large numbers of complex DNA damage events. The human genome is packaged into chromatin, which can take on locus-dependent and cell type-dependent spatial conformations that correspond to epigenetic states, such as more open, extended structures in transcriptionally active chromatin. These epigenetic differences can affect DNA break patterns in response to ionizing radiation, potentially creating distinct DNA repair and signaling outcomes across the genome in different cells. MATERIAL AND METHODS The code RITRACKS (Relativistic Ion Tracks), which simulates stochastic radiation track structures and radiation chemistry, was used to model damage on isolated and histone-bound DNA by various types of ions and photons. The changes made to the code to perform radiation-induced DNA damage, and simulation results on single nucleosomes are given in our recent paper. In this work, the DNA building capabilities of RITRACKS have been extended to simulate more complex DNA structures build on the coarse-grain simulation framework meso-WLCsim. This code can sample generic chromatin fiber conformation ensembles based on the geometry of nucleosomes and mechanical properties of DNA. Using RITRACKS, we simulated the fragment length distributions (FLD) of irradiated DNA structures built using the chromatin conformations of WLCsim and obtained results representative of those obtained with Radiation-Induced Correlated Cleavage with sequencing (RICC-Seq) experiments [6]. We have also performed Fe ion and photon irradiations of K562, IMR90, BJ and RPE-1 cells at NSRL to experimentally validate results. Sample processing and data analysis are in progress and any available preliminary results will be discussed. DISCUSSION The recent updates in the code RITRACKS allow the calculation of several quantities such as the DNA damage yield and the FLD. This approach can be used to model epigenetic state-specific chromatin structure parameters to leverage the epigenetic state data available for many human cell types to infer relative DNA damage sensitivity among genomic loci.

I Plante↗

NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

NASA NTRS2016

Cloud-Based Orchestration of a Model-Based Power and Data Analysis Toolchain

The proposed Europa Mission concept contains many engineering and scientific instruments that consume varying amounts of power and produce varying amounts of data throughout the mission. System-level power and data usage must be well understood and analyzed to verify design requirements. Numerous cross-disciplinary tools and analysis models are used to simulate the system-level spacecraft power and data behavior. This paper addresses the problem of orchestrating a consistent set of models, tools, and data in a unified analysis toolchain when ownership is distributed among numerous domain experts. An analysis and simulation environment was developed as a way to manage the complexity of the power and data analysis toolchain and to reduce the simulation turnaround time. A system model data repository is used as the trusted store of high-level inputs and results while other remote servers are used for archival of larger data sets and for analysis tool execution. Simulation data passes through numerous domain-specific analysis tools and end-to-end simulation execution is enabled through a web-based tool. The use of a cloud-based service facilitates coordination among distributed developers and enables scalable computation and storage needs, and ensures a consistent execution environment. Configuration management is emphasized to maintain traceability between current and historical simulation runs and their corresponding versions of models, tools and data.

Post, Ethan↗

NASA NTRS1989

Enhanced rotor modeling tailored for rub dynamic stability analysis and simulation

New methods are presented that allow straightforward application of complex nonlinearities to finite element based rotor dynamic analyses. The key features are: (1) the methods can be implemented with existing finite element or dynamic simulation programs, (2) formulation is general for simple application to a wide range of problems, and (3) implementation is simplified because nonlinear aspects are separated from the linear part of the model. The new techniques are illustrated with examples of inertial nonlinearity and torquewhirl which can be important in rubbing turbomachinery. The sample analyses provide new understanding of these nonlinearities which are discussed.

Davis, R. R.↗

NASA NTRS1992

Unsteady flowfield simulation of ducted prop-fan configurations

A technique for the simulation of unsteady flows in and around complex rotating machinery is presented. Additional domain decomposition mechanisms are introduced which extend the range of applicability of software developed for the time-accurate simulation of rotating machinery flowfields. The flow models uses the unsteady 3D Euler equations, discretized as a finite-volume method, utilizing a high-resolution approximate Riemann solver for cell interface flux definitions. Multiblock domain decomposition is used to partition the field radially, axially, as well as circumferentially into an ordered arrangement of blocks which exhibit varying degrees of similarity. A general high-order numerical scheme is applied to satisfy the geometric conservation law. Two configurations are presented - ducted single rotation prop-fan and a rotor-deswirl vane combination which form a single stage fan. Comparisons are made to other numerical solutions for these geometries and to available experimental data.

Janus, J. M.↗

NASA NTRS2005

Efficient Construction of Discrete Adjoint Operators on Unstructured Grids Using Complex Variables

A methodology is developed and implemented to mitigate the lengthy software development cycle typically associated with constructing a discrete adjoint solver for aerodynamic simulations. The approach is based on a complex-variable formulation that enables straightforward differentiation of complicated real-valued functions. An automated scripting process is used to create the complex-variable form of the set of discrete equations. An efficient method for assembling the residual and cost function linearizations is developed. The accuracy of the implementation is verified through comparisons with a discrete direct method as well as a previously developed handcoded discrete adjoint approach. Comparisons are also shown for a large-scale configuration to establish the computational efficiency of the present scheme. To ultimately demonstrate the power of the approach, the implementation is extended to high temperature gas flows in chemical nonequilibrium. Finally, several fruitful research and development avenues enabled by the current work are suggested.

Nielsen, Eric J.↗

NASA NTRS2005

Efficient Construction of Discrete Adjoint Operators on Unstructured Grids by Using Complex Variables

Nielsen, Eric J.↗

NASA NTRS2012

Overcoming the Critical Shortage of STEM - Prepared Secondary Students Through Modeling and Simulation

In developing understanding of technological systems - modeling and simulation tools aid significantly in the learning and visualization processes. In design courses we sketch , extrude, shape, refine and animate with virtual tools in 3D. Final designs are built using a 3D printer. Aspiring architects create spaces with realistic materials and lighting schemes rendered on model surfaces to create breathtaking walk-throughs of virtual spaces. Digital Electronics students design systems that address real-world needs. Designs are simulated in virtual circuits to provide proof of concept before physical construction. This vastly increases students' ability to design and build complex systems. We find students using modeling and simulation in the learning process, assimilate information at a much faster pace and engage more deeply in learning. As Pre-Engineering educators within the Career and Technical Education program at our school division's Technology Academy our task is to help learners in their quest to develop deep understanding of complex technological systems in a variety of engineering disciplines. Today's young learners have vast opportunities to learn with tools that many of us only dreamed about a decade or so ago when we were engaged in engineering and other technical studies. Today's learner paints with a virtual brush - scenes that can aid significantly in the learning and visualization processes. Modeling and simulation systems have become the new standard tool set in the technical classroom [1-5]. Modeling and simulation systems are now applied as feedback loops in the learning environment. Much of the study of behavior change through the use of feedback loops can be attributed to Stanford Psychologist Alfred Bandura. "Drawing on several education experiments involving children, Bandura observed that giving individuals a clear goal and a means to evaluate their progress toward that goal greatly increased the likelihood that they would achieve it."

Spencer, Thomas↗

NASA NTRS2008

The School of Virtual Knocks: Learning from Doing--Without Pain of Mistakes

The present day educational process, as currently practiced, is no longer necessarily synonymous with learning, and the concept of learning is becoming disassociated with knowledge acquisition. True, learning is not accidental, nor is the absence of learning normally by choice. It is the result, intended or otherwise, of decisions made by government, researchers, educators, students, parents, and the wider community. It is underpinned by the quality of teaching, the relevancy of the instruction to the student's world, and the perseverance of the student's desire to learn. It is these choices that are driving the wedge between teaching and learning. The learning outcomes are derived by curriculum developers, educational psychologists, government and industry.Yet as advances in understanding how students learn have been made, the advances in technology, specifically models and simulation, which are able to underpin complex knowledge domains, have been left behind if not ignored. While a majority of stakeholders in education agree that the current educational environment is missing the mark, it is important to underpin those impressions with a basis of knowledge. This paper reviews education in order to foster the conclusion that education must change and that the enabling methodologies and technologies already exist in the form of models and simulation.

Darby, Michael↗

NASA NTRS1981

Design and control strategies for CELSS - Integrating mechanistic paradigms and biological complexities

Systems analysis and control theory consideration are given to simulations of both individual components and total systems, in order to develop a reliable control strategy for a Controlled Ecological Life Support System (CELSS) which includes complex biological components. Because of the numerous nonlinearities and tight coupling within the biological component, classical control theory may be inadequate and the statistical analysis of factorial experiments more useful. The range in control characteristics of particular species may simplify the overall task by providing an appropriate balance of stability and controllability to match species function in the overall design. The ultimate goal of this research is the coordination of biological and mechanical subsystems in order to achieve a self-supporting environment.

Moore, B., III↗

NASA NTRS2011

The Challenge of Grounding Planning in Simulation with an Interactive Model Development Environment

A principal obstacle to fielding automated planning systems is the difficulty of modeling. Physical systems are modeled conventionally based on specification documents and the modeler's understanding of the system. Thus, the model is developed in a way that is disconnected from the system's actual behavior and is vulnerable to manual error. Another obstacle to fielding planners is testing and validation. For a space mission, generated plans must be validated often by translating them into command sequences that are run in a simulation testbed. Testing in this way is complex and onerous because of the large number of possible plans and states of the spacecraft. Though, if used as a source of domain knowledge, the simulator can ease validation. This paper poses a challenge: to ground planning models in the system physics represented by simulation. A proposed, interactive model development environment illustrates the integration of planning and simulation to meet the challenge. This integration reveals research paths for automated model construction and validation.

radio occultation↗

NASA NTRS1987

Attention theory and training research

This study used elements of attention theory as a methodological basis to decompose a complex training task in order to improve training efficiency. The complex task was a microcomputer flight simulation where subjects were required to control the stability of their own helicopter while acquiring and engaging enemy helicopers in a threat enviroment. Subjects were divided into whole-task, part-task, and part/open loop adaptive task groups in a transfer of training paradigm. The effect of reducing mental workload at the early stages of learning was examined with respect to the degree that subordinate elements of the complex task could be automated through practice of consistent, learnable stimulus-response relationships. Results revealed trends suggesting the benefit of isolating consistently mapped sub-tasks for part-task training and the presence of a time-sharing skill over and above the skill required for the separate subtasks.

Connelly, James G., Jr.↗

NASA NTRS2005

Three Dimensional Multi-Fluid Simulation of Comet Halley

The Cometary Atmosphere Simulator (CASIM) is designed to simulate in 2-D and 3-D the complex interaction between the cometary atmosphere and the hypersonic solar wind using a multi-fluid approach. Our simulator is based on the solution of multi-fluid equations using an efficient adaptive Cartesian mesh. It is designed to use the capabilities of highly parallel super-cluster computers.

Benna, M.↗

NASA NTRS1983

Numerical investigation of unsteady flow development in a nozzle-duct configuration

A computational approach has been used to resolve the transient phenomena caused by a rocket engine starting up and exhausting into a short duct. The results are obtained from the finite-difference Navier-Stokes, continuity, and energy equations for a single component gas. Using a recently developed numerical technique to account for the time-varying boundary conditions at the nozzle throat and the duct openings, the numerical simulation of the idealized ignition flow model has yielded some insight into the complex interactions between the wave patterns and the vortical flow. The present findings verify the hypothesis that a lateral expansion of the jetstream outside the nozzle will generate an over-pressure pulse on the duct wall if the jetstream is restricted within the nozzle by flow separation. The numerical simulations of this complex flow problem should be useful for improving simple correlation techniques used for engineering purposes.

Li, C. P.↗

NASA NTRS2003

Monte Carlo Methodology Serves Up a Software Success

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Source record↗

NASA NTRS1985

Simplified Worst-Case Analysis of Complex Systems

Statistical method avoids excessive computer time. Technique involves simplified Monte Carlo simulation of system with randomly chosen parameters and comparison of tolerance extremes of several of worst-case situations found. Resulting combination of tolerance extremes then used in detailed analysis - one that makes use of full complex nonlinear model capable of accurate simulations.

Pond, C. L.↗

NASA NTRS1963

Integrated Mission Simulation for Long Term Space Flight

The problems of evaluating pilot performance, pilot training, and the integration of the man-machine system for proper functioning become increasingly difficult as the length of projected space flights increases. Further, actual in-flight experience becomes harder to obtain and the major means for training and evaluation becomes simulation. The first major source of difficulty in any simulation stems from a basic requirement of leaning theory: that for increased proficiency of performance to occur within any biologically capable system, the stimuli which are the bases for the expected behavior must be presented in an amenable form to the learner. Further, the sequence of presentation of the pertinent stimuli must be such that the learner can form the appropriate concepts and interactions required for the ultimate use of the learned material. It can then be seen that two basic factors of learning complex skills are: 1) Fidelity of simulation of pertinent stimuli. 2) Appropriate sequencing of stimuli during learning for proper concept formation.

SPACE FLIGHT↗

NASA NTRS1998

The Identification of Complex Organic Molecules in the Interstellar Medium: Using Lasers and Matrix Isolation Spectroscopy to Simulate the Interstellar Environment

The Astrochemistry Group at NASA Ames Research Center is interested in the identification of large organic molecules in the interstellar medium Many smaller organic species (e.g. hydrocarbons, alcohols, etc.) have been previously identified by their radiofrequency signature due to molecular rotations. However, this becomes increasingly difficult to observe as the size of the molecule increases. Our group in interested in the identification of the carriers of the Diffuse Interstellar Bands (absorption features observed throughout the visible and near-infrared in the spectra of stars, due to species in the interstellar medium). Polycyclic Aromatic Hydrocarbons (PAHs) and related molecules are thought to be good candidates for these carriers. Laboratory experiments am performed at Ames to simulate the interstellar environment, and to compare spectra obtained from molecules in the laboratory to those derived astronomically. We are also interested in PAHs with respect to their possible connection to the UIR (Unidentified infrared) and ERE (Extended Red Emission) bands - emission features found to emanate from particular regions of our galaxy (e.g. Orion nebula, Red Rectangle, etc.). An old, "tried and proven spectroscopic technique, matrix isolation spectroscopy creates molecular conditions ideal for performing laboratory astrophysics.

Stone, Bradley M.↗