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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Development of a compact E ? B microchannel plate detector for beam imaging

A beam imaging detector was developed by coupling a multi-strip anode with delay line readout to an E×B microchannel plate (MCP) detector. This detector is capable of measuring the incident position of the beam particles in one-dimension. To assess the spatial resolution, the detector was illuminated by an α-source with an intervening mask that consists of a series of precisely-machined slits. The measured spatial resolution was 520 um source FWHM, which was improved to 413 um FWHM by performing an FFT of the signals, rejecting spurious signals on the delay line, and requiring a minimum signal amplitude. This measured spatial resolution of 413 um FWHM corresponds to an intrinsic resolution of 334 um FWHM when the effect of the finite slit width is de-convoluted. To understand the measured resolution, the performance of the detector is simulated with the ion-trajectory code SIMION.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Space Charge Driven Emittance Growth and the Effect of Octupoles in IOTA

The Integrable Optics Test Accelerator (IOTA) at Fermilab is a small machine dedicated to a broad frontier accelerator physics program. An important aspect of this program is to investigate the potential benefits of the resonance free tune spread achievable with integrable optics to store and accelerate high intensity proton beams for which space charge is significant. In this context, a good understanding of proton beam emittance growth and particle loss mechanisms is essential. Assuming nominal design parameters, simulations show that for a bunched beam, the bulk of emittance growth takes place immediately following injection, typically within tens of turns. We attempt to account for this growth using a simplified RMS mismatch theory; some of its limitations and possible improvements are briefly discussed. We then compare theoretical predictions to simulations performed using the PIC code pyORBIT. Further exploring ways to mitigate emittance growth and reduce particle loss, we compare two beam matching strategies: (1) matching at the injection point (2) matching at the center of the nonlinear (octupole) insertion region where $\beta_x = \beta_y$. To observe how nonlinearity affects emittance growth and whether it dominates growth due to mismatch, we track two different distributions. Finally, we explore the potential of using octupoles in a quasi-integrable configuration to mitigate growth using a variety of initial distributions both at reduced and full intensities.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Report on Aging and Irradiation Theoretical Model Development for Alloy 690 in Grizzly

This report describes the current efforts to implement a model to predict the engineering scale behavior of irradiated and aged Ni 2 Cr model alloy and Alloy 690 into the Grizzly software. Grizzly is a multiphysics simulation code under development at Idaho National Laboratory to simulate aging mechanisms and their effects on the integrity of critical LWR components. Engineering scale behavior of materials are strongly impacted by the underlying microstructure: the distribution and interaction of dislocations and defects within the individual grains dictates how the material will respond to loading. The evolution of these dislocations and defects determines how the engineering scale material will perform under different loading and environmental conditions. Mesoscale models can function as a bridge to connect microstructure evolution models to engineering models of the ductile-brittle transition temperature (DBTT) curve and fracture. The toughness of a material, which governs the engineering scale fracture behavior, is a function of both elastic deformation and plastic deformation. While the yield stress measurements capture the elastic contribution to a material’s toughness, information about the dislocation movement is required to understand the plastic component of toughness. Crystal plasticity models predict dislocation density evolution and thereby connect microstructure evolution to engineering scale behavior predictions. These models calculate the plastic strain within a metal as a function of dislocations and other crystal defects, including precipitates and interstitial loops, among others, by tracking dislocation movement and the interaction of these dislocations with the crystal defects. Within NiCr alloys, long-range ordered (LRO) precipitates form under aging conditions. These precipitates act as barriers to dislocation motion and are either sheared by dislocations or pin dislocations. Additional defects, such as stacking fault tetrahedra (SFTs) from irradiation damage, also impede dislocation motion in these alloys. A crystal plasticity mode for Ni 2 Cr model alloy and Alloy 690 is being currently implemented in the Grizzly code at INL. This report includes a description of the theoretical models incorporated into the Grizzly crystal plasticity code. These theoretical models include mechanisms for dislocation glade and twinning as well as dislocation-defect interaction relationship for both LRO precipitates and SFTs. We have selected these dislocation models based on the deformation mechanisms observed in experimental micropillar compression tests conducted on the Ni 2 Cr model alloy. The models are then extended to Alloy 690 with ongoing parameter fitting.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Assessment of the MAMMOTH and PRONGHORN Pebble Bed Reactor Modeling Capabilities for the HTR-PM Design

This assessment explores the current analysis methodologies of various external and MOOSE-based tools available at the Idaho National Laboratory to model pebble bed reactor multiphysics phenomena. The study involves three MOOSE-based, coupled codes: 1) MAMMOTH for reactor physics, 2) Rattlesnake for neutron transport and 3) Pronghorn for thermal fluids and strongly coupled conjugate heat transfer. These advanced tools are being developed under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS). They currently contain a collection of advanced modeling capabilities that allow high-fidelity simulations of advanced reactor concepts including gas and fluoride-salt cooled pebble bed reactors. Software development of these tools follows NQA-1 standards ensuring software quality that many of the currently deployed legacy codes lack. In this work, the MAMMOTH Pronghorn tools are compared to the legacy codes PEBBED-THERMIX-KONVEK. The external codes in use are LAMMPS for pebble mechanics and Serpent for cross section preparation. The coupling under MOOSE enables significant flexibility for modern engineering tools since MOOSE applications can be seamlessly coupled with various levels of resolution. This report focuses on low-resolution (r-z) and midresolution (3-D) homogenized geometries. The high-resolution Pebble Tracking Transport solution is not pursued herein and is postponed to future work. The results from this assessment show that the new MOOSE-based tools compare well with the results from legacy tools (r-z) and produce reasonable accuracy limited by the methods in the legacy tools. In the 3-D studies, the PJFNK-SPH methodology available in MAMMOTH allows the reproduction of Monte Carlo results with a transport-corrected diffusion solution. This has implications for the coupled solutions since without the SPH correction the temperature coefficient of reactivity is under-predicted and leads to lower temperature feedback and a significantly higher eigenvalue showing a difference of 2000 pcm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Demonstration of a code coupling framework for modeling beam-collimator impacts in the advanced photon source

The high-brightness beams being produced in current and future accelerators present new machine protection concerns with the potential for high-energy-density (HED) conditions ( >100 J/mm 3 ) in beam-intercepting components. Simulating HED conditions in accelerators requires utilizing a suite of physics codes for particle dynamics, particle-matter interactions, and hydrodynamics. This paper describes a method of coupling the codes elegant, fluka, and flash to simulate the effects of a rapid beam loss in the advanced photon source storage ring and the resulting interaction of the beam and collimators. This paper expands previous work [J. Dooling et al., Collimator irradiation studies at the advanced photon source, in Proceedings of the IBIC-2023 (2023), pp. 245–249] by introducing a definition of the evolving geometry of the collimator surface as well as providing methods for simulating the absorption of synchrotron radiation and tracking shower particles produced during beam strikes. We demonstrate this framework by simulating machine conditions of the APS ring before and after its recent upgrade. Simulation results are compared with observed damage to collimators and test samples taken from the APS ring.

Accelerator/storage ring control systems↗
DOE OSTI2022

A Hydro-particle-mesh Code for Efficient and Rapid Simulations of the Intracluster Medium

We introduce the cosmological HYPER code based on an innovative hydro-particle-mesh (HPM) algorithm for efficient and rapid simulations of gas and dark matter. For the HPM algorithm, we update the approach of Gnedin & Hui to expand the scope of its application from the lower-density intergalactic medium (IGM) to the higher-density intracluster medium (ICM). While the original algorithm tracks only one effective particle species, the updated version separately tracks the gas and dark matter particles, as they do not exactly trace each other on small scales. For the approximate hydrodynamics solver, the pressure term in the gas equations of motion is calculated using robust physical models. In particular, we use a dark matter halo model, ICM pressure profile, and IGM temperature–density relation, all of which can be systematically varied for parameter-space studies. We show that the HYPER simulation results are in good agreement with the halo model expectations for the density, temperature, and pressure radial profiles. Simulated galaxy cluster scaling relations for Sunyaev–Zel’dovich (SZ) and X-ray observables are also in good agreement with mean predictions, with scatter comparable to that found in hydrodynamic simulations. HYPER also produces lightcone catalogs of dark matter halos and full-sky tomographic maps of the lensing convergence, SZ effect, and X-ray emission. These simulation products are useful for testing data analysis pipelines, generating training data for machine learning, understanding selection and systematic effects, and for interpreting astrophysical and cosmological constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Deep Packet/Flow Analysis using GPUs

Deep packet inspection (DPI) faces severe performance challenges in high-speed networks (40/100 GE) as it requires a large amount of raw computing power and high I/O throughputs. Recently, researchers have tentatively used GPUs to address the above issues and boost the performance of DPI. Typically, DPI applications involve highly complex operations in both per-packet and per-flow data level, often in real-time. The parallel architecture of GPUs fits exceptionally well for per-packet network traffic processing. However, for stateful network protocols such as TCP, their data stream need to be reconstructed in a per-flow level to deliver a consistent content analysis. Since the flow-centric operations are naturally antiparallel and often require large memory space for buffering out-of-sequence packets, they can be problematic for GPUs, whose memory is normally limited to several gigabytes. In this work, we present a highly efficient GPU-based deep packet/flow analysis framework. The proposed design includes a purely GPU-implemented flow tracking and TCP stream reassembly. Instead of buffering and waiting for TCP packets to become in sequence, our framework process the packets in batch and uses a deterministic finite automaton (DFA) with prefix-/suffix- tree method to detect patterns across out-of-sequence packets that happen to be located in different batches. In conclusion, evaluation shows that our code can reassemble and forward tens of millions of packets per second and conduct a stateful signature-based deep packet inspection at 55 Gbit/s using an NVIDIA K40 GPU.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Exascale-capable cellular automaton for nucleation and grain growth

This model is a cellular automata-based algorithm used to predict grain-scale microstructure development. Nucleation and growth of existing grains are considered in an initially liquid domain, where the temperature field evolution is either driven through heat transport simulation data or a frozen temperature approximation (i.e., a constant cooling rate and a fixed thermal gradient). The growth of grains is based on the decentered octahedron algorithm published by Gandin and Rappaz (https://doi.org/10.1016/S1359-6454(96)00303-5), where the grain envelopes are tracked as approximations of the evolving dendritic growth front. The input heat transport data, which can come from simulation of an arbitrary processing technique, consists of coordinates and times at which said coordinates fall below the liquidus and solidus temperatures for the final time. As a result, only the final solidification of a given region is modeled (no remelting). The code is designed to be compatible with pre-Exascale architectures, and uses MPI and the Kokkos library to decompose the computational domain and offload solidification calculations to GPUs.

Rolchigo, MatthewR.↗
DOE OSTI2019

l3d2vtk: An MCNPTools Utility to Enable LNK3DNT File Visualization & Post-Processing

This paper describes recent work to develop and incorporate a utility program into the MCNPTools package that enables LNK3DNT file visualization & post-processing. A LNK3DNT file is a binary Cartesian, cylindrical, or spherical structured mesh file that describes material and material relative density distributions by mesh voxel. This mesh file format is principally used by the PARTISN discrete-ordinates radiation-transport code. However, the MCNP ® Monte Carlo radiation-transport code can use LNK3DNT files to specify geometry, and the MCNP code can produce LNK3DNT files representing a user-defined region of the MCNP constructive solid geometry (CSG). Because of the use of LNK3DNT files as MCNP input and output and with other computer codes, improving the ability to visualize and/or quantitatively post-process LNK3DNT files benefits end users. In particular, it is helpful to visually verify that the material and density distributions are as expected. Also, an analyst can orient viewers with respect to other in formation, e.g., by co-plotting a voxelized representation of MCNP CSG with mesh tally and/or particle track results. However, until now, the only capability to interactively interrogate LNK3DNT files is through a 2-D slice plotter provided by the Monte Carlo Application ToolKit (MCATK), which is not currently distributed outside of Los Alamos National Laboratory. The utility created as part of this work converts LNK3DNT binary files to an ASCII XML-based StructuredMesh VTK (.vts) file. The geometries supported are 1-D spherical and cylindrical ( r ), 1-D Cartesian ( x ), 2-D cylindrical ( r-z and r-θ ) and Cartesian ( x-y ), and 3-D cylindrical ( r-z-θ ) and Cartesian ( x-y-z ). This file format is chosen to minimize external dependencies (e.g., on an HDF5 library) and to provide a file that can be interrogated by the user in a text editor or standard visualization applications (e.g., ParaView or VisIt). However, other file formats may provide more utility such as XDMF, which can use HDF5 and is discussed further as something to explore as future work. This paper is organized as follows: a brief introduc tion to the MCNPTools library and utility programs is given, the LNK3DNT-to-VTK (l3d2vtk) utility functionality is de scribed, and then an example post-processing workflow using the ParaView application is given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

H2Fills™ [SWR-19-67]

H2FillS: Hydrogen Filling Simulation The Hydrogen Filling Simulation (H2FillS) software is a thermodynamic model designed to track and report on the transient change in hydrogen temperature, pressure, and mass flow when filling a fuel cell electric vehicle (FCEV). H2FillS simulates gas flow from the hydrogen station to the FCEV storage system. Using empirical fueling data sets, the model has been validated over a range of fueling conditions to match common light-duty FCEV fill profiles. Overall, it provides significant benefits to the light-duty fueling market and fill knowledge gaps of the interaction between a hydrogen station and an FCEV. Capabilities Use the comprehensive H2FillS model to: Safely design and operate a hydrogen fueling station Support code refinement with readily available data Develop system and operational improvements to reduce capital or operating costs at hydrogen stations or on-board FCEVs. How It Works H2FillS uses a "drag-and-drop" graphical user interface to simulate station and vehicle systems with preset parameters for common hydrogen station components as default values. When needed, users can define their own parameters to create their own station or vehicle components. Download H2FillS in Two Steps Read the terms of the end user software license agreement. Register to download the software. There are two versions of the model: A full-station model starts the simulation at high-pressure ground storage, runs through a dispenser, and ends at a vehicle storage system. A partial-station model starts at the dispenser breakaway and consists solely of the dispenser components and the vehicle storage system. H2FillS will automatically output fill performance data from the vehicle by tracking pressure and temperature throughout the fill. Users can input their own fill profiles into the model to run a variety of simulations.

Peters, Michael↗
DOE OSTI2023

DeepSurveySim: Simulation Software and Benchmark Challenges for Astronomical Observation Scheduling

Modern astronomical surveys have multiple competing scientific goals. Optimizing the observation schedule for these goals presents significant computational and theoretical challenges, and state-of-the-art methods rely on expensive human inspection of simulated telescope schedules. Automated methods, such as reinforcement learning, have recently been explored to accelerate scheduling. However, there do not yet exist benchmark data sets or user-friendly software frameworks for testing and comparing these methods. We present DeepSurveySim -- a high-fidelity and flexible simulation tool for use in telescope scheduling. DeepSurveySim provides methods for tracking and approximating sky conditions for a set of observations from a user-supplied telescope configuration. We envision this tool being used to produce benchmark data sets and for evaluating the efficacy of ground-based telescope scheduling algorithms, particularly for machine learning algorithms that would suffer in efficacy if limited to real data for training.We introduce three example survey configurations and related code implementations as benchmark problems that can be simulated with DeepSurveySim.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Capability Demonstration of a 3D CdZnTe Detector on a High-Altitude Balloon Flight

In collaboration between the University of Michigan and Los Alamos National Laboratory, a 3D position-sensing CdZnTe (CZT) detector prototype was built and integrated into a high-altitude balloon platform to evaluate its performance in a space-like mixed-radiation environment. The detector prototype, Orion Eagle, was designed to operate in near-vacuum environments without any temperature regulation. Orion Eagle was hand-launched from NASA’s Columbia Scientific Balloon Facility (CSBF) at Fort Sumner, NM on September 26, 2021, and successfully operated throughout a 9-hour flight, which reached 38.5 km in altitude. The flight met its objectives, successfully detecting atmospheric gamma rays and galactic cosmic rays, and raising the Technical Readiness Level from 4 to 6 for large-volume 3D CZT detector technology for space applications. Ionization tracks produced by charged particles create spatial signatures in the detector that are distinguishable from discrete gamma-ray interactions. Therefore, the 3D position-sensing capabilities using pixelated electrodes on a CZT detector can help enable discrimination of background charged particles from gamma-ray events without an anticoincidence shield. The potential for background rejection capability, ambient-temperature operation, gamma-ray coded-aperture and Compton imaging, and near High Purity Germanium (HPGe) energy resolution motivate the use of large-volume 3D CZT imaging spectrometers in future space missions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Reconstruction and analysis of exploding wire particle trajectories via automatic calibration of stereo images

Quantitative understanding of the physics of dust or granular matter transport significantly impacts several aspects of burning plasma science and technology. Here, this work takes machine vision techniques popular in robotics and self-driving cars and applies them to identification and analysis of microparticles generated from exploding wires. Using only the image frames and knowledge of the intrinsic properties of the cameras, a Python code was written to identify the particles, automatically calibrate the relative image positions, and extract trajectory data. After identifying approximately 50 particles based on the timing of secondary particle explosions, the eight point and random sample consensus algorithms were used to determine the geometric correlation between the cameras. Over 100 particle matches were found between the two camera views. These correlated trajectories were used in subsequent 3D track reconstruction and analysis of the physics behind the particle motion. The 3D reconstruction resulted in accurate positioning of the particles with respect to the experimental setup. The particle motion was consistent with the effects of a 1 g gravitational field modified by drag forces. Lastly, the methods and analyses presented here can be used in many facets of high temperature plasma diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Energy Exascale Computational Fluid Dynamics Simulations With the Spectral Element Method

Development and application of the open-source GPU-based fluid-thermal simulation code, NekRS, are described. Time advancement is based on an efficient kth-order accurate timesplit formulation coupled with scalable iterative solvers. Spatial discretization is based on the high-order spectral element method (SEM), which affords the use of fast, low-memory, matrix-free operator evaluation. Further, recent developments include support for nonconforming meshes using overset grids and for GPU-based Lagrangian particle tracking. Results of large-eddy simulations of atmospheric boundary layers for wind-energy applications as well as extensive nuclear energy applications are presented.

42 ENGINEERING↗
DOE OSTI2018

A New Standard DNA Damage (SDD) Data Format

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called “indirect” damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates intermodel comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to significantly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗