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DOE OSTI2024

An Evaluation of The Dynamic Physical Security Risk Assessment Methodology for Fleet-Wide Applications

The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1983

Investigation, Development, and Evaluation of Performance Proving for Fault-tolerant Computers

A number of methodologies for verifying systems and computer based tools that assist users in verifying their systems were developed. These tools were applied to verify in part the SIFT ultrareliable aircraft computer. Topics covered included: STP theorem prover; design verification of SIFT; high level language code verification; assembly language level verification; numerical algorithm verification; verification of flight control programs; and verification of hardware logic.

Levitt, K. N.↗

NASA NTRS1991

Plotting Orbital Trajectories For Maneuvers

Interactive Orbital Trajectory Planning Tool (EIVAN) computer program is forward-looking interactive orbit-trajectory-plotting software tool for use with proximity operations (operations occurring within 1-km sphere of space station) and other maneuvers. Developed to plot resulting trajectories, to provide better comprehension of effects of orbital mechanics, and to help user develop heuristics for planning missions on orbit. Program runs with Microsoft's Excel for execution on MacIntosh computer running MacIntosh OS.

Brody, Adam R.↗

DOE OSTI2023

Plant-specific Model and Data Analysis using Dynamic Security Modeling and Simulation

The requirements for U.S. nuclear power plants to maintain a large on-site physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an update on the progress in applying a dynamic computational framework that links results from a commercially available force-on-force simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework or MASS-DEF. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report does not contain any plant's sensitive information and/or Safeguards Information. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2010

Spinoff 2010

Topics covered include: Burnishing Techniques Strengthen Hip Implants; Signal Processing Methods Monitor Cranial Pressure; Ultraviolet-Blocking Lenses Protect, Enhance Vision; Hyperspectral Systems Increase Imaging Capabilities; Programs Model the Future of Air Traffic Management; Tail Rotor Airfoils Stabilize Helicopters, Reduce Noise; Personal Aircraft Point to the Future of Transportation; Ducted Fan Designs Lead to Potential New Vehicles; Winglets Save Billions of Dollars in Fuel Costs; Sensor Systems Collect Critical Aerodynamics Data; Coatings Extend Life of Engines and Infrastructure; Radiometers Optimize Local Weather Prediction; Energy-Efficient Systems Eliminate Icing Danger for UAVs; Rocket-Powered Parachutes Rescue Entire Planes; Technologies Advance UAVs for Science, Military; Inflatable Antennas Support Emergency Communication; Smart Sensors Assess Structural Health; Hand-Held Devices Detect Explosives and Chemical Agents; Terahertz Tools Advance Imaging for Security, Industry; LED Systems Target Plant Growth; Aerogels Insulate Against Extreme Temperatures; Image Sensors Enhance Camera Technologies; Lightweight Material Patches Allow for Quick Repairs; Nanomaterials Transform Hairstyling Tools; Do-It-Yourself Additives Recharge Auto Air Conditioning; Systems Analyze Water Quality in Real Time; Compact Radiometers Expand Climate Knowledge; Energy Servers Deliver Clean, Affordable Power; Solutions Remediate Contaminated Groundwater; Bacteria Provide Cleanup of Oil Spills, Wastewater; Reflective Coatings Protect People and Animals; Innovative Techniques Simplify Vibration Analysis; Modeling Tools Predict Flow in Fluid Dynamics; Verification Tools Secure Online Shopping, Banking; Toolsets Maintain Health of Complex Systems; Framework Resources Multiply Computing Power; Tools Automate Spacecraft Testing, Operation; GPS Software Packages Deliver Positioning Solutions; Solid-State Recorders Enhance Scientific Data Collection; Computer Models Simulate Fine Particle Dispersion; Composite Sandwich Technologies Lighten Components; Cameras Reveal Elements in the Short Wave Infrared; Deformable Mirrors Correct Optical Distortions; Stitching Techniques Advance Optics Manufacturing; Compact, Robust Chips Integrate Optical Functions; Fuel Cell Stations Automate Processes, Catalyst Testing; Onboard Systems Record Unique Videos of Space Missions; Space Research Results Purify Semiconductor Materials; and Toolkits Control Motion of Complex Robotics.

Source record↗

DOE OSTI2026

Phenomenological opportunities at the EIC

This review presents a comprehensive overview of key phenomenological opportunities at the future Electron–Ion Collider (EIC), synthesizing discussions and collaborative research efforts developed within the Korean EIC community and the EICφ collaboration. We explore a diverse range of physics topics central to the EIC scientific program, including the multidimensional tomography of nucleon and nuclear structure, precision Quantum Chromodynamics studies through jet physics and event-shape observables, heavy quarkonium production as a probe of partonic dynamics, and the spectroscopy of exotic hadrons. Furthermore, we discuss the transformative potential of emerging technologies—specifically Machine Learning and Quantum Computing—as essential tools for addressing the computational challenges and maximizing the scientific discovery potential of the EIC era.

Electron–Ion collider↗

DOE OSTI2024

Establishing capabilities for quantum computing and simulations for energy applications

Quantum information science (QIS) is creating potential transformative opportunities to exploit intricate quantum mechanical phenomena in new ways for obtaining and processing information to advance many areas of science and engineering. Since the National Quantum Initiative Act was signed into law in 2018, developing QIS capability and competency is one of the most urgent tasks of DOE to make sure the US win the quantum race. The QIS contains four pillars: quantum computing, quantum simulations, quantum sensing, and quantum networking. To apply QIS in energy related applications, the key is to develop the capability of quantum computing & simulation tools. In this project, we propose to develop the capability of quantum computing and simulations at NETL to target fossil energy related problems. We will install a simulator (e. g. IBM qiskit) on the NETL supercomputer to simulate the environments of quantum computer. Based on the current available quantum algorithms for quantum chemistry, we will develop quantum computing codes to perform simulation which will focus on fossil energy sector challenges, including CO2 capture & conversion, sensing, and fuel conversion. We then will seek opportunities to run our codes on real quantum computers (such as IBM-Q, google Sycamore, etc.). Through this project, the new capability of quantum computing and simulations will be established at NETL. In addition, the NETL workforce in this area will be trained ready to conduct more complicated tasks in line with NETL missions to enhance the nation’s energy foundation.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

Surface generation and editing operations applied to structural support of aerospace vehicle fuselages

The Solid Modeling Aerospace Research Tool (SMART) is a computer aided design tool used in aerospace vehicle design. Modeling of structural components using SMART includes the representation of the transverse or cross-wise elements of a vehicle's fuselage, ringframes, and bulkheads. Ringframes are placed along a vehicle's fuselage to provide structural support and maintain the shape of the fuselage. Bulkheads are also used to maintain shape, but are placed at locations where substantial structural support is required. Given a Bezier curve representation of a cross sectional cut through a vehicle's fuselage and/or an internal tank, this project produces a first-guess Bezier patch representation of a ringframe or bulkhead at the cross-sectional position. The grid produced is later used in the structural analysis of the vehicle. The graphical display of the generated patches allows the user to edit patch control points in real time. Constraints considered in the patch generation include maintaining 'square-like' patches and placement of longitudinal, or lengthwise along the fuselage, structural elements called longerons.

Schwartz, Susan K.↗

NASA NTRS2005

Space Shuttle Underside Astronaut Communications Performance Evaluation

The Space Shuttle Ultra High Frequency (UHF) communications system is planned to provide Radio Frequency (RF) coverage for astronauts working underside of the Space Shuttle Orbiter (SSO) for thermal tile inspection and repairing. This study is to assess the Space Shuttle UHF communication performance for astronauts in the shadow region without line-of-sight (LOS) to the Space Shuttle and Space Station UHF antennas. To insure the RF coverage performance at anticipated astronaut worksites, the link margin between the UHF antennas and Extravehicular Activity (EVA) Astronauts with significant vehicle structure blockage was analyzed. A series of near-field measurements were performed using the NASA/JSC Anechoic Chamber Antenna test facilities. Computational investigations were also performed using the electromagnetic modeling techniques. The computer simulation tool based on the Geometrical Theory of Diffraction (GTD) was used to compute the signal strengths. The signal strength was obtained by computing the reflected and diffracted fields along the propagation paths between the transmitting and receiving antennas. Based on the results obtained in this study, RF coverage for UHF communication links was determined for the anticipated astronaut worksite in the shadow region underneath the Space Shuttle.

Hwu, Shian U.↗

DOE OSTI2023

Identifying limitations in screening high-throughput photocatalytic bimetallic nanoparticles with machine-learned hydrogen adsorptions

The Sabatier principle is of fundamental importance to computational catalyst discovery, saving researchers time and expense by predicting catalytic activity in silico at scale. However, as polycrystalline and nanoscale catalysts increasingly dominate industry, computational screening tools must be adapted to these uses. In this work, we demonstrate the effectiveness of computational adsorption energy screening in nanocatalysis by comparing a multisite adsorption energy prediction workflow against a large experimental dataset of hydrogen evolution activities over bimetallic nanoparticles. Comparing 16 million hydrogen adsorption energy predictions with the hydrogen evolution activity of 5300 experiments across 84 monometallic and bimetallic systems, we discover that favorable adsorption energies are a necessary condition for experimental activity, but other factors often determine trends in practice. Finally, about half of the bimetallic search space can be excluded from experimental screens using hydrogen adsorption predictions, but this method may become significantly more powerful when combined with other screening tools.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2004

Space Shuttle UHF Communications Performance Evaluation

An extension boom is to be installed on the starboard side of the Space Shuttle Orbiter (SSO) payload bay for thermal tile inspection and repairing. As a result, the Space Shuttle payload bay Ultra High Frequency (UHF) antenna will be under the boom. This study is to evaluate the Space Shuttle UHF communication performance for antenna at a suitable new location. To insure the RF coverage performance at proposed new locations, the link margin between the UHF payload bay antenna and Extravehicular Activity (EVA) Astronauts at a range distance of 160 meters from the payload bay antenna was analyzed. The communication performance between Space Shuttle Orbiter and International Space Station (SSO-ISS) during rendezvous was also investigated. The multipath effects from payload bay structures surrounding the payload bay antenna were analyzed. The computer simulation tool based on the Geometrical Theory of Diffraction method (GTD) was used to compute the signal strengths. The total field strength was obtained by summing the direct fields from the antennas and the reflected and diffracted fields from the surrounding structures. The computed signal strengths were compared to the signal strength corresponding to the 0 dB link margin. Based on the results obtained in this study, RF coverage for SSO-EVA and SSO- ISS communication links was determined for the proposed payload bay antenna UHF locations. The RF radiation to the Orbiter Docking System (ODS) pyros, the payload bay avionics, and the Shuttle Remote Manipulator System (SRMS) from the new proposed UHF antenna location was also investigated to ensure the EMC/EMI compliances.

Hwu, Shian U.↗

NASA NTRS1991

Domain decomposition methods in computational fluid dynamics

The divide-and-conquer paradigm of iterative domain decomposition, or substructuring, has become a practical tool in computational fluid dynamic applications because of its flexibility in accommodating adaptive refinement through locally uniform (or quasi-uniform) grids, its ability to exploit multiple discretizations of the operator equations, and the modular pathway it provides towards parallelism. These features are illustrated on the classic model problem of flow over a backstep using Newton's method as the nonlinear iteration. Multiple discretizations (second-order in the operator and first-order in the preconditioner) and locally uniform mesh refinement pay dividends separately, and they can be combined synergistically. Sample performance results are included from an Intel iPSC/860 hypercube implementation.

Gropp, William D.↗

NASA NTRS1992

Domain decomposition methods in computational fluid dynamics

Gropp, William D.↗

NASA NTRS2000

A Collaborative Analysis Tool for Integrated Hypersonic Aerodynamics, Thermal Protection Systems, and RBCC Engine Performance for Single Stage to Orbit Vehicles

Presented is a computer-based tool that connects several disciplines that are needed in the complex and integrated design of high performance reusable single stage to orbit (SSTO) vehicles. Every system is linked to every other system, as is the case of SSTO vehicles with air breathing propulsion, which is currently being studied by NASA. An RBCC propulsion system integrates airbreathing and rocket propulsion into a single engine assembly enclosed within a cowl or duct. A typical RBCC propulsion system operates as a ducted rocket up to approximately Mach 3. Then there is a transition to a ramjet mode for supersonic-to-hypersonic acceleration. Around Mach 8 the engine transitions to a scramjet mode. During the ramjet and scramjet modes, the integral rockets operate as fuel injectors. Around Mach 10-12 (the actual value depends on vehicle and mission requirements), the inlet is physically closed and the engine transitions to an integral rocket mode for orbit insertion. A common feature of RBCC propelled vehicles is the high degree of integration between the propulsion system and airframe. At high speeds the vehicle forebody is fundamentally part of the engine inlet, providing a compression surface for air flowing into the engine. The compressed air is mixed with fuel and burned. The combusted mixture must be expanded to an area larger than the incoming stream to provide thrust. Since a conventional nozzle would be too large, the entire lower after body of the vehicle is used as an expansion surface. Because of the high external temperatures seen during atmospheric flight, the design of an airbreathing SSTO vehicle requires delicate tradeoffs between engine design, vehicle shape, and thermal protection system (TPS) sizing in order to produce an optimum system in terms of weight (and cost) and maximum performance. To adequately determine the performance of the engine/vehicle, the Hypersonic Flight Inlet Model (HYFIM) module was designed to interface with the RBCC engine model. HYFIM performs the aerodynamic analysis of forebodies and inlet characteristics of RBCC powered SSTO launch vehicles. HYFIM is applicable to the analysis of the ramjet/scramjet engine operations modes (Mach 3-12), and provides estimates of parameters such as air capture area, shock-on-lip Mach number, design Mach number, compression ratio, etc., based on a basic geometry routine for modeling axisymmetric cones, 2-D wedge geometries. HYFIM also estimates the variation of shock layer properties normal to the forebody surface. The thermal protection system (TPS) is directly linked to determination of the vehicle moldline and the shaping of the trajectory. Thermal protection systems to maintain the structural integrity of the vehicle must be able to mitigate the heat transfer to the structure and be lightweight. Herein lies the interdependency, in that as the vehicle's speed increases, the TPS requirements are increased. And as TPS masses increase the effect on the propulsion system and all other systems is compounded. The need to analyze vehicle forebody and engine inlet is critical to be able to design the RBCC vehicle. To adequately determine insulation masses for an RBCC vehicle, the hypersonic aerodynamic environment and aeroheating loads must be calculated and the TPS thicknesses must be calculated for the entire vehicle. To accomplish this an ascent or reentry trajectory is obtained using the computer code Program to Optimize Simulated Trajectories (POST). The trajectory is then used to calculate the convective heat rates on several locations on the vehicles using the Miniature Version of the JA70 Aerodynamic Heating Computer Program (MINIVER). Once the heat rates are defined for each body point on the vehicle, then insulation thicknesses that are required to maintain the vehicle within structural limits are calculated using Systems Improved Numerical Differencing Analyzer (SINDA) models. If the TPS masses are too heavy for the performance of the vehicle the process may be repeated altering the trajectory or some other input to reduce the TPS mass. E-PSURBCC is an "engine performance" model and requires the specification of inlet air static temperature and pressure as well as Mach number (which it pulls from the HYFIM and POST trajectory files), and calculates the corresponding stagnation properties. The engine air flow path geometry includes inlet, a constant area section where the rocket is positioned, a subsonic diffuser, a constant area afterburner, and either a converging nozzle or a converging-diverging nozzle. The current capabilities of E-PSURBCC ejector and ramjet mode treatment indicated that various complex flow phenomena including multiple choking and internal shocks can occur for combinations of geometry/flow conditions. For a given input deck defining geometry/flow conditions, the program first goes through a series of checks to establish whether the input parameters are sound in terms of a solution path. If the vehicle/engine performance fails mission goals, the engineer is able to collaboratively alter the vehicle moldline to change aerodynamics, or trajectory, or some other input to achieve orbit. The problem described is an example of the need for collaborative design and analysis. RECIPE is a cross-platform application capable of hosting a number of engineers and designers across the Internet for distributed and collaborative engineering environments. Such integrated system design environments allow for collaborative team design analysis for performing individual or reduced team studies. To facilitate the larger number of potential runs that may need to be made, RECIPE connects the computer codes that calculate the trajectory data, aerodynamic data based on vehicle geometry, heat rate data, TPS masses, and vehicle and engine performance, so that the output from each tool is easily transferred to the model input files that need it.

Stanley, Thomas Troy↗

DOE OSTI2020

1st Computational Physics School for Fusion Research (2019 CPS-FR)

The rising number of applications of machine learning and computational statistics in fusion energy research requires flexibility in adopting a growing variety of tools. The Computational Physics School for Fusion Research (CPS-FR) aims at providing young researchers with critical skill sets to deal with modern fusion energy research challenges. The School aims at covering essentials of: Computational Statistics, Machine Learning, Deep Learning and optimization methods, Parallel Programming and HPC. As the first edition of the CPS-FR just concluded, this report highlights its main results and summarizes its contents.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

End-to-end optimization for battery materials and molecules by combining graph neural networks and reinforcement learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to design new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗

DOE OSTI2022

End-to-End Optimization for Battery Materials and Molecules by Combining Graph Neural Networks and Reinforcement Learning

The National Renewable Energy Laboratory (NREL), together with the Colorado School of Mines (CSM) and Colorado State University (CSU), has developed a machine learning-enhanced approach to the design of new battery materials. Currently, such materials are designed in part via numerous expensive high-fidelity computational simulations that predict the performance of a given composition. Even with computational screening tools, the vast landscape of possible molecular or crystal structures exceeds current and future computational capacity. Improving the efficiency by which new materials can be optimized will therefore disrupt the cost, risk, and time required to bring new energy solutions to the marketplace. Predicting the properties of an organic molecule or periodic crystalline material given its structure has grown increasingly common. These approaches leverage large-scale computational and experimental databases and ML approaches such as graph neural networks. The inverse design problem of finding a material that possesses desired properties is substantially more challenging, since enumerating all valid material structures is not feasible. In this project, we leveraged recent success in reinforcement learning to efficiently navigate this high-dimensional search space. Just as algorithms can find the optimal chess moves from nearly limitless options, we train an approach to evolve a simple starting structure into a complex structure that possess the desired properties. Our solution has been demonstrated by applying it to two related design application tasks for short- and long-term energy storage, respectively: (1) the design of solid-state ion conductors and (2) the design of organic redox-active materials. The project has resulted an open-source software library for material design, documented examples of applying the library to both organic and inorganic material optimization, and peer-reviewed publications detailing the data, computational models, and resulting candidate materials.

25 ENERGY STORAGE↗

NASA NTRS2024

Comparison of Geant4-DNA and RITRACKS/RITCARD: Microdosimetry, Nanodosimetry and DNA Damage Predictions for Low to High LET Ions

Low linear energy transfer (LET) ionizing radiations induce homogeneously distributed DNA damage at the cellular scale, while high LET ionizing radiations are well known to create complex biological damage including clustered double strand breaks (DSB). Clustered DSB are critical events that are difficult to repair, leading to increased biological outcomes compared to low LET radiation exposure. Recent studies have shown that DNA compaction, which can be actively modified by the cell to allow DNA repair, influences the yield of DSB [1]. The goal of this work is to determine the impact of DNA compaction on chromosome aberration formation, a biomarker of radiation-induced cancer risk. The RITRACKS track structure code [2], together with the RITCARD code [3], allow one to simulate the transport of high LET ions, calculate DNA damage and repair, and chromosome aberration formation, but does not include detailed geometrical models of DNA. The Geant4-DNA toolkit provides such detailed models with different levels of DNA compaction [1,4], but does not model chromosome aberration formation. In this work, these highly detailed DNA geometries are used to compute DNA breaks with Geant4-DNA and combine the results with the RITCARD tool to compute chromosome aberrations. As a first step, we compared the transport models used in RITRACKS and Geant4-DNA and newly released heavy ion model transport (G4DNARuddIonisationExtendedModel Geant4 v11.2) to ensure consistency between the physical stage of the two radiation transport codes. We compared energy deposition at the micrometric and nanometric scales for different ions (H 250 MeV, H 150 Me, He 250 MeV/n, C 290 MeV/n, O 350 MeV/n, O 55 MeV/n, Si 170MeV/n, Ti 300 MeV/n, Ti 300 MeV/n, Fe 600 MeV/n, Fe 450 MeV/n and Fe 300 MeV/n) with LET ranging from ~0.4 keV/μm up to 235 keV/μm. Excellent agreement is found for both microdosimetric and nanodosimetric spectra for all ion types and energies. The calculation of DNA breaks and their complexity with the Geant4-DNA is an ongoing work, and comparison with RITCARD will be presented based on result availability at the time of the conference. [1] Tang et al. (2019). Med. Phys., 46(3), 1501-1511. [2] Plante et al. (2008). NJP, 10(12), 125020. [3] Plante et al. (2019). Rad. Res., 192(3), 282-298. [4] Incerti et al. (2018). Med. Phys., 45(8), e722-e739.

Floriane Poignant↗