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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Data Driven Commercial Building Energy Code Compliance and Technology Inventory for New York City

Building Performance Standards (BPS) are gaining national traction. A BPS will require new processes in the design, construction, and operation of buildings that take the occupants into account and enable predictive analysis to ensure compliance with current and future GHG emissions caps. In New York City, most buildings over 25,000 square feet will be regulated by a BPS starting in 2024, regardless of whether it is new construction permitted under current energy codes or an existing building. This research is one of the first to begin the evaluation of a long-term series of building policies in the context of an open data ecosystem, in cooperation with city agencies. Existing building policies enacted in NYC have ranged from building energy benchmarking and labeling to energy audits to the regulation of GHG emission in buildings. Through the development of a dataset related to building technologies and energy consumption, this project can help to evaluate if meaningful conclusions can be drawn for the data that has been largely self-reported in compliance with city regulations. This project will also provide lessons learned from a deep dive into these types of datasets to provide best practices for municipalities or states seeking to embark on policies like those enacted in NYC. In addition, a Building Automation System (BAS) Stretch Standard of Care (SSOC) for owners, designers, and building operators will enable the measurement and predictive analysis of energy consumption and GHG emissions at the plant, system, or component level, in anticipation of regulated GHG limits on buildings based on energy use. The SSOC is expected to be suitable for use on a national level. The primary feature of an SSOC is a standardized format for a set of BAS points that can be used to control and to gather data from individual plants, systems, or components that are related to building energy consumption. This project examined how measurements compare to prescriptive or simulation-based energy code targets, finding little correlation between predictive 8760-hour energy modeling and actual energy consumption for a small sample (n=27) of buildings constructed after 2015. Other analysis found that, while large multifamily housing (MFH) buildings showed a general trend similar to predicted reductions in energy use from the implementation of model commercial energy codes, this trend was not evident in the office, K-12 school, and hotel use groups in NYC. No upward or downward trends in energy consumption were found when buildings were grouped by size. Energy audit data were analyzed and it appears that there is bias by audit company on measures recommended to clients. Further research should be performed to cross-analyze this with other attributes, such as building size, vintage, and number of stories. Analysis found that for 281 buildings that were permitted and completed after 2015 and had submitted benchmarking data in 2022, between 81% and 96% (by use group) were found to be in compliance with the 2024 to 2029 NYC BPS emission caps, and between 55% and 89% were in compliance with the 2030-2034 caps. This work is beneficial to the public in helping policymakers and building stakeholders better understand the wide-ranging implications of a BPS.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Neutral Pion Electroproduction and development of a Neutral Particle Spectrometer

Protons and neutrons, i.e. nucleons, are the basic building blocks of the matter in the visible universe. The strong force binds the nucleons to form nuclei. The electromagnetic force forms the atoms by binding the electrons with the nuclei. The electromagnetic interaction is well understood by Quantum Electrodynamics (QED), which shows the most precise predictability amongst all the theories in physics. In QED, charges interact with each other by exchanging photons. The Quantum Chromodynamics (QCD) describes the strong interaction. Its degrees of freedom are quarks and gluons, the fundamental constituents of the nucleons. The quarks interact with each other by exchanging gluons. However, unlike QED, the gluons interact amongst themselves. This feature of self bindings of the gluons confines the quarks and gluons in the nucleons/hadrons, never to be seen as free. In order to study some of the features of QCD, such as confinement or the structure of the nucleon, one usually needs to rely on experiments. Electromagnetic probes, governed by the well-understood QED, are excellent tools to probe the nucleon. In general, different scales, e.g. electron beam energies, probe different regions of the nucleon. At low energy, of the order of a few GeV, the electron probes the nucleon in the valence quark region. As its energy increases, the electron probes the sea quark and gluon regions. The study of the nucleon structure in all these regions is needed to fully understand QCD. Form factors and parton distribution functions measured from elastic scattering and deep inelastic scattering of leptons off nucleons have provided a partial view of the internal structure of the nucleon. In the mid-1990s, Generalized Parton Distributions (GPDs) were developed. These new objects are a generalization of the form factors and parton distribution functions, but contain richer information on the nucleon internal structure. GPDs are accessible experimentally by deep exclusive reactions. Deeply virtual Compton scattering (DVCS) and deeply virtual meson production (DVMP) are some examples. The first dedicated DVCS/DVMP experiment took place in 2004 in Hall A at The Thomas Jefferson National Accelerator Facility, i.e. Jefferson Lab, in Virginia, U.S.A. A new DVCS/DVMP experiment, after the beam energy upgrade of Jefferson Lab, was carried out in Hall A in a wider kinematic range. Its data were taken from 2014 to 2016. In Hall C at Jefferson Lab, the next DVCS/DVMP experiment will take place. The Hall C experiment will further exploit the kinematic range with higher precision. A Neutral Particle Spectrometer (NPS) is in development to measure DVCS/DVMP events under high background conditions. Jefferson Lab will provide the highest precision data in the valence quark region for various exclusive reactions. The Electron-Ion Collider (EIC) is a future experimental facility currently planned to start operations around 2030 in the U.S.A. Its high energy and high luminosity will probe the sea quark and gluon regions providing answers to the outstanding questions of QCD, in particular in the region where matter is dominated by gluons. First of all, this document describes the data analysis and results of the Hall A neutral pion electroproduction off the proton, from the data taken in 2014-2016. Later, some of the developments towards the construction of the electromagnetic calorimeter of the NPS for the upcoming DVCS/DVMP experiment in Hall C are presented. Finally, one of the candidate materials for the EIC calorimeter, a glass scintillator, will be briefly introduced. I have participated to all these projects, in collaboration with many colleagues. I present in this thesis my contributions to each of these projects. My contributions to the neutral pion data analysis were focused on background subtractions on the calorimeter, acceptance calculations, and the estimation of the systematic uncertainty associated to the event selection cuts. Some necessary information on calibrations of the detectors and data analysis methods are also described. In the NPS project, I performed background dose calculations and energy and position resolution studies of the calorimeter, all using Monte Carlo simulations, with realistic geometries of the experimental apparatus. Characterization of the crystals of the calorimeter was also done. Additionally, I measured the radiation hardness of some glass scintillator in its early stage of development. In order to have a future reference when the glass calorimeter prototype will be tested, I simulated the energy resolution of the prototype.

Ko, Ho-San↗
NASA NTRS1992

Intercomparison and interpretation of surface energy fluxes in atmospheric general circulation models

Responses of the surface energy budgets and hydrologic cycles of 19 atmospheric general circulation models to an imposed, globally uniform sea surface temperature perturbation of 4 K were analyzed. The responses of the simulated surface energy budgets are extremely diverse and are closely linked to the responses of the simulated hydrologic cycles. The response of the net surface energy flux is not controlled by cloud effects; instead, it is determined primarily by the response of the latent heat flux. The prescribed warming of the oceans leads to major increases in the atmospheric water vapor content and the rates of evaporation and precipitation. The increased water vapor amount drastically increases the downwelling IR radiation at the earth's surface, but the amount of the change varies dramatically from one model to another.

Randall, D. A.↗
DOE OSTI2023

Advances in the Co-Simulation of Detailed Electrical and Whole-Building Energy Performance

This article describes recent co-simulation advances for the simultaneous modeling of detailed building electrical distribution systems and whole-building energy performance. The co-simulation architecture combines the EnergyPlus® engine for whole-building energy modeling with a new Modelica library for building an electrical distribution system model that is based on harmonic power flow. This new library allows for a higher-fidelity modeling of electrical power flows and losses within buildings than is available with current building electrical modeling software. We demonstrate the feasibility of the architecture by modeling a simple, two-zone thermal chamber with internal power electronics converters and resistive loads, and we validate the model using experimental data. The proposed co-simulation capability significantly expands the capabilities of building electrical distribution system models in the context of whole-building energy modeling, thus enabling more complex analyses than would have been possible with individual building performance simulation tools that are used to date.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

A quantum energy transport model for semiconductor device simulation

This paper describes numerical methods for a quantum energy transport (QET) model in semiconductors, which is derived by using a diffusion scaling in the quantum hydrodynamic (QHD) model. We newly drive a four-moments QET model similar with a classical ET model. Space discretization is performed by a new set of unknown variables. Numerical stability and convergence are obtained by developing numerical schemes and an iterative solution method with a relaxation method. Numerical simulations of electron transport in a scaled MOSFET device are discussed. The QET model allows simulations of quantum confinement transport, and nonlocal and hot-carrier effects in scaled MOSFETs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL’s Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1983

Energy consumption analysis of the Venus Deep Space Station (DSS-13)

This report continues the energy consumption analysis and verification study of the tracking stations of the Goldstone Deep Space Communications Complex, and presents an audit of the Venus Deep Space Station (DSS 13). Due to the non-continuous radioastronomy research and development operations at the station, estimations of energy usage were employed in the energy consumption simulation of both the 9-meter and 26-meter antenna buildings. A 17.9% decrease in station energy consumption was experienced over the 1979-1981 years under study. A comparison of the ECP computer simulations and the station's main watt-hour meter readings showed good agreement.

Hayes, N. V.↗
DOE OSTI2014

Statistical investigations on nitrogen-vacancy center creation

Quantum information technologies require networks of interacting defect bits. Color centers, especially the nitrogen vacancy (NV{sup −}) center in diamond, represent one promising avenue, toward the realisation of such devices. The most successful technique for creating NV{sup −} in diamond is ion implantation followed by annealing. Previous experiments have shown that shallow nitrogen implantation (<10 keV) results in NV{sup −} centers with a yield of 0.01%–0.1%. We investigate the influence of channeling effects during shallow implantation and statistical diffusion of vacancies using molecular dynamics and Monte Carlo simulation techniques. Energy barriers for the diffusion process were calculated using density functional theory. Our simulations show that 25% of the implanted nitrogens form a NV center, which is in good agreement with our experimental findings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Small Hydropower Plant Response Improvement Using Energy Storage

Small hydropower plants contribute significantly to global power generation. However, due to limited storage, these can have low ramping capacity and poor load-frequency regulation. These can prevent small hydropower plants from being used in isolated grids as backup power to critical loads and rural areas. In this paper, a control architecture for frequency control is proposed that facilitates the use of energy storage to improve the response of standalone small hydropower plants. The frequency controller generates power commands using proportional control on frequency deviation and a user-defined power setpoint, and this incorporates with a current controller that facilitates power injection. The distinctive feature of the controller design is that it takes into account frequency thresholds and storage constraints to enable power injections, and it provides the capability to perform automated and manual recharge of the energy storage. Simulations using detailed nonlinear models demonstrate the improved performance of the hydropower with energy storage using the proposed controller. Automated and manual recharge and the impact of the energy storage constraints on the performance of the hydropower plant are demonstrated.

13 HYDRO ENERGY↗
DOE OSTI2016

The evolution of star formation histories of quiescent galaxies

Although there has been much progress in understanding how galaxies evolve, we still do not understand how and when they stop forming stars and become quiescent. We address this by applying our galaxy spectral energy distribution models, which incorporate physically motivated star formation histories (SFHs) from cosmological simulations, to a sample of quiescent galaxies at 0.2<z<2.1. A total of 845 quiescent galaxies with multi-band photometry spanning rest-frame ultraviolet through near-infrared wavelengths are selected from the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey (CANDELS) data set. We compute median SFHs of these galaxies in bins of stellar mass and redshift. At all redshifts and stellar masses, the median SFHs rise, reach a peak, and then decline to reach quiescence. At high redshift, we find that the rise and decline are fast, as expected, because the universe is young. At low redshift, the duration of these phases depends strongly on stellar mass. Low-mass galaxies (log(M{sub ∗}/M{sub ⊙})∼9.5) grow on average slowly, take a long time to reach their peak of star formation (≳4 Gyr), and then the declining phase is fast (≲2 Gyr). Conversely, high-mass galaxies (log(M{sub ∗}/M{sub ⊙})∼11) grow on average fast (≲2 Gyr), and, after reaching their peak, decrease the star formation slowly (≳3). These findings are consistent with galaxy stellar mass being a driving factor in determining how evolved galaxies are, with high-mass galaxies being the most evolved at any time (i.e., downsizing). The different durations we observe in the declining phases also suggest that low- and high-mass galaxies experience different quenching mechanisms, which operate on different timescales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A review of tidal energy—Resource, feedbacks, and environmental interactions

The ocean contains a variety of renewable energy resources, little of which has been exploited. Here, we review both tidal range and tidal stream energy, with a focus on the resource, feedbacks, and environmental interactions. The review covers a wide range of timescales of relevance to tidal energy, from fortnightly (spring-neap) and semi-diurnal variability, down to array, and device-scale turbulence. When simulating the regional tidal energy resource, and to assess environmental impacts, it is necessary to account for feedbacks between the tidal array and the resource itself. We critically review various methods for simulating energy extraction, from insights gained through theoretical studies of “tidal fences” in idealized channels, to realistic three-dimensional model studies with complex geometry and arrays of turbines represented by momentum sinks and additional turbulence due to the presence of rotors and support structures. We discuss how variability can be reduced by developing multiple (aggregated) sites with a consideration of the enhanced phase diversity offered by exploiting less energetic tidal currents. This leads to future research questions that have not yet been explored in depth at first-generation tidal sites in relatively sheltered channels (e.g., the interaction of waves with currents). Such enhanced understanding of real sea conditions, including the effects of wind and waves, leads to our other identified primary future research direction—reduced uncertainties in turbulence predictions, including the development of realistic models that simulate the interaction between ambient turbulence and the turbulence resulting from multiple wakes, and changes to system-wide hydrodynamics, water quality, and sedimentation.

Environmental impacts↗
DOE OSTI2020

Towards isolated attosecond electron bunches using ultrashort-pulse laser-solid interactions

We investigate MeV-level attosecond electron bunches from ultrashort-pulse laser-solid interactions through similarities between experimental and simulated electron energy spectra. We show measurements of the bunch duration and temporal structure from particle-in-cell simulations. The experimental observation of such bunches favors specular reflection direction when focusing the laser pulse onto a subwavelength boundary of thick overdense plasmas at grazing incidence. Particle-in-cell simulation further reveals that the attosecond duration is a result of ultra-thin (~tenth of a micron) gaps of zero electromagnetic energy density in the modulated reflected radiation, while the bunching (locally peaked electron concentration) comes from the highly-directional electron angular distribution acquired by the electrons in a grazing incidence setup. To isolate a single electron bunch, we perform simulations using 1-cycle laser pulses and analyze the effect of carrier-envelop phase with particle tracking. The duration of the electron bunch can be further decreased by increasing the laser intensity and the focal spot size, while its direction can be changed by tuning the preplasma density gradient.

High-harmonic generation↗
DOE OSTI2015

SU-E-T-30: A Factor for Converting Dose to a Gold Nanoparticle Mixture to a Biologically-Relevant Dose

Purpose: Monte Carlo studies of gold nanoparticle (GNP) dose enhancement on macroscopic scales in radiotherapy have modeled GNPs in tissue as a homogeneous mixture of gold and tissue. Using an explicit model of GNPs randomly positioned in a small volume (1 µm{sup 3}) of tissue, this study aims to quantify the dose to the biologically relevant component of a goldtissue mixture, enabling a conversion from macroscopically-scored dose. Methods: Using the PENELOPE Monte Carlo code with the penEasy package, we modeled a 1 µm{sup 3} volume containing either a tissue-gold mixture or GNPs suspended in ICRU 4-component tissue at various gold concentrations (0, 5, 10, and 15 mg Au/g tissue) and GNP diameters (20, 30, 40, 50 nm). The volume was irradiated with monoenergetic photon and electron beams, ranging from 110 eV to 6 MeV. Interaction forcing was utilized to increase simulation efficiency. Energy deposition was scored in the tissue for each case and was converted to dose. For each scenario, we calculated a conversion factor, the ratio of dose-to-tissue to dose-to-mixture as a function of energy. Results: The conversion factor was plotted as a function of energy for both photons and electrons. For electrons, the conversion factor was relatively unaffected by any of the parameters, including energy, ranging between 0.98–1.02. For photons, the factor was very energy dependent, with a range of 0.49–1.02. The factor was lowest for 10–100 keV photons. The conversion factor generally decreased with increasing GNP concentration and increasing GNP size. Conclusion: With a large variation in the conversion factor with incident energy, dose deposition is dependent on the spectrum incident on a volume. By scoring the energy spectrum in a given volume, one can provide a scenario-specific conversion factor, allowing fast, detailed Monte Carlo simulations without the need for explicit GNP-definition.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Strategy and gaps for modeling, simulation, and control of hybrid systems

The purpose of this report is to establish a strategy for modeling and simulation of candidate hybrid energy systems. Modeling and simulation is necessary to design, evaluate, and optimize the system technical and economic performance. Accordingly, this report first establishes the simulation requirements to analysis candidate hybrid systems. Simulation fidelity levels are established based on the temporal scale, real and synthetic data availability or needs, solution accuracy, and output parameters needed to evaluate case-specific figures of merit. Accordingly, the associated computational and co-simulation resources needed are established; including physical models when needed, code assembly and integrated solutions platforms, mathematical solvers, and data processing. This report first attempts to describe the figures of merit, systems requirements, and constraints that are necessary and sufficient to characterize the grid and hybrid systems behavior and market interactions. Loss of Load Probability (LOLP) and effective cost of Effective Cost of Energy (ECE), as opposed to the standard Levelized Cost of Electricty (LCOE), are introduced as technical and economical indices for integrated energy system evaluations. Financial assessment methods are subsequently introduced for evaluation of non-traditional, hybrid energy systems. Algorithms for coupled and iterative evaluation of the technical and economic performance are subsequently discussed. This report further defines modeling objectives, computational tools, solution approaches, and real-time data collection and processing (in some cases using real test units) that will be required to model, co-simulate, and optimize; (a) an energy system components (e.g., power generation unit, chemical process, electricity management unit), (b) system domains (e.g., thermal, electrical or chemical energy generation, conversion, and transport), and (c) systems control modules. Co-simulation of complex, tightly coupled, dynamic energy systems requires multiple simulation tools, potentially developed in several programming languages and resolved on separate time scales. Whereas further investigation and development of hybrid concepts will provide a more complete understanding of the joint computational and physical modeling needs, this report highlights areas in which co-simulation capabilities are warranted. The current development status, quality assurance, availability and maintainability of simulation tools that are currently available for hybrid systems modeling is presented. Existing gaps in the modeling and simulation toolsets and development needs are subsequently discussed. This effort will feed into a broader Roadmap activity for designing, developing, and demonstrating hybrid energy systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

THE STORAGE AND DISSIPATION OF MAGNETIC ENERGY IN THE QUIET SUN CORONA DETERMINED FROM SDO/HMI MAGNETOGRAMS

In recent years, higher cadence, higher resolution observations have revealed the quiet-Sun photosphere to be complex and rapidly evolving. Since magnetic fields anchored in the photosphere extend up into the solar corona, it is expected that the small-scale coronal magnetic field exhibits similar complexity. For the first time, the quiet-Sun coronal magnetic field is continuously evolved through a series of non-potential, quasi-static equilibria, deduced from magnetograms observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory, where the photospheric boundary condition which drives the coronal evolution exactly reproduces the observed magnetograms. The build-up, storage, and dissipation of magnetic energy within the simulations is studied. We find that the free magnetic energy built up and stored within the field is sufficient to explain small-scale, impulsive events such as nanoflares. On comparing with coronal images of the same region, the energy storage and dissipation visually reproduces many of the observed features. The results indicate that the complex small-scale magnetic evolution of a large number of magnetic features is a key element in explaining the nature of the solar corona.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Numerical challenges for energy conservation in N -body simulations of collapsing self-interacting dark matter halos

Dark matter (DM) halos can be subject to gravothermal collapse if the DM is not collisionless, but engaged in strong self-interactions instead. When the scattering is able to efficiently transfer heat from the centre to the outskirts, the central region of the halo collapses and reaches densities much higher than those for collisionless DM. This phenomenon is potentially observable in studies of strong lensing. Current theoretical efforts are motivated by observations of surprisingly dense substructures. However, a comparison with observations requires accurate predictions. One method to obtain such predictions is to use N-body simulations. Collapsed halos are extreme systems that pose severe challenges when applying state-of-the-art codes to model self-interacting dark matter (SIDM). In this work, we investigate the root of such problems, with a focus on energy non-conservation. Moreover, we discuss possible strategies to avoid them. We ran N-body simulations, both with and without SIDM, of an isolated DM-only halo and we adjusted the numerical parameters to check the accuracy of the simulation. We find that not only the numerical scheme for SIDM can lead to energy non-conservation, but also the modelling of gravitational interaction and the time integration are problematic. The main issues we find are: (a) particles changing their time step in a non-time-reversible manner; (b) the asymmetry in the tree-based gravitational force evaluation; and (c) SIDM velocity kicks breaking the time symmetry. Tuning the parameters of the simulation to achieve a high level of accuracy allows us to conserve energy not only at early stages of the evolution, but also later on. However, the cost of the simulations becomes prohibitively large as a result. Some of the problems that make the simulations of the gravothermal collapse phase inaccurate can be overcome by choosing appropriate numerical schemes. However, other issues still pose a challenge. Our findings motivate further works on addressing the challenges in simulating strong DM self-interactions.

dark matter↗
DOE OSTI2018

TOPAS-nBio: An Extension to the TOPAS Simulation Toolkit for Cellular and Sub-cellular Radiobiology

The TOPAS Monte Carlo (MC) system is used in radiation therapy and medical imaging research, having played a significant role in making Monte Carlo simulations widely available for proton therapy related research. While TOPAS provides detailed simulations of patient scale properties, the fundamental unit of the biological response to radiation is a cell. Thus, our goal was to develop TOPAS-nBio, an extension of TOPAS dedicated to advance understanding of radiobiological effects at the (sub-)cellular, (i.e., the cellular and sub-cellular) scale. TOPAS-nBio was designed as a set of open source classes that extends TOPAS to model radiobiological experiments. TOPAS-nBio is based on and extends Geant4-DNA, which extends the Geant4 toolkit, the basis of TOPAS, to include very low-energy interactions of particles down to vibrational energies, explicitly simulates every particle interaction (i.e., without using condensed histories) and propagates radiolysis products. To further facilitate the use of TOPAS-nBio, a graphical user interface was developed. TOPAS-nBio offers full track-structure Monte Carlo simulations, integration of chemical reactions within the first millisecond, an extensive catalogue of specialized cell geometries as well as sub-cellular structures such as DNA and mitochondria, and interfaces to mechanistic models of DNA repair kinetics. We compared TOPAS-nBio simulations to measured and published data of energy deposition patterns and chemical reaction rates (G values). Our simulations agreed well within the experimental uncertainties. Additionally, we expanded the chemical reactions and species provided in Geant4-DNA and developed a new method based on independent reaction times (IRT), including a total of 72 reactions classified into 6 types between neutral and charged species. Chemical stage simulations using IRT were a factor of 145 faster than with step-by-step tracking. Finally, we applied the geometric/chemical modeling to obtain initial yields of double-strand breaks (DSBs) in DNA fibers for proton irradiations of 3 and 50 MeV and compared the effect of including chemical reactions on the number and complexity of DSB induction. Over half of the DSBs were found to include chemical reactions with approximately 5% of DSBs caused only by chemical reactions. In conclusion, the TOPAS-nBio extension to the TOPAS MC application offers access to accurate and detailed multiscale simulations, from a macroscopic description of the radiation field to microscopic description of biological outcome for selected cells. TOPAS-nBio offers detailed physics and chemistry simulations of radiobiological experiments on cells simulating the initially induced damage and links to models of DNA repair kinetics.

62 RADIOLOGY AND NUCLEAR MEDICINE↗