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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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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Energy-saving potential evaluation for primary schools with occupant-centric controls

Recent studies demonstrated that there is significant energy-saving potential for primary schools, which heating, ventilation, and air-conditioning (HVAC) systems with occupant-centric control (OCC) is an excellent candidate to save energy. However, such an energy impact has yet to be evaluated for different climate zones as well as different energy code versions, but is critical for technology transfer and deployment. Therefore, this paper conducts comprehensive evaluation on the energy-saving potentials for the primary schools with two advanced OCC strategies: presence-based and counting-based. In this work, ninety-six building energy models with stochastic behavior of occupants are developed and simulated, which consist of two building energy code versions, 16 climate zones, and baseline case (without OCC) and two advanced cases (with OCC). To evaluate the energy saving potentials for OCC, primary schools in the U.S. are used as an example. The results show that there is significant energy-saving potential for primary schools by considering OCC strategies, especially the counting-based case. The energy-saving potential is up to 10.2% for presence-based OCC and 12.41% for counting-based OCC. Furthermore, both climate and code version have a significant impact on energy savings from OCC strategies. The energy-saving potentials vary from 1.79% to 12.41% for different climates and code versions. This evaluation can also contribute to quantify the nationwide energy saving potential for other countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Smooth Particle Hydrodynamics-based Wind Representation

As a result of the 2011 accident at the Fukushima Dai-ichi NPP and other operational NPP experience, there is an identified need to better characterize and evaluate the potential impacts of externally generated hazards on NPP safety. Due to the ubiquitous occurrence of high winds around the world and the possible extreme magnitude of the hazard that has been observed, the assessment of the impact of the high-winds hazard has been identified as an important activity by both NPP owner-operators and regulatory authorities. However, recent experience obtained from the conduct of high-winds risk assessments indicates that such activities have been both labor-intensive and expensive to perform. Additionally, the existing suite of methods and tools to conduct such assessments (which were developed decades ago) do not make use of modern computational architectures (e.g., parallel processing, object-oriented programming techniques, or simple user interfaces) or methods (e.g., efficient and robust numerical-solution schemes). As a result, the current suite of methods and tools will rapidly become obsolete. Physics-based 3D simulation methods can provide information to assist in the RISMC PRA methodology. This research is intended to determine what benefits SPH methods could bring to high-winds simulations for the purposes of assessing their potential impact on NPP safety. The initial investigation has determined that SPH can simulate key areas of high-wind events with reasonable accuracy, compared to other methods. Some problems, such as simulation voids, need to be addressed, but possible solutions have been identified and will be tested with continued work. This work also demonstrated that SPH simulations can provide a means for simulating debris movement; however, further investigations into the capability to determine the impact of high winds and the impacts of wind-driven debris that lead to SSC failures need to be done. SPH simulations alone would be limited in size and computation time. An advanced method of combing results from grid-based methods with SPH through a data-driven model is proposed. This method could allow for more accurate simulation of particle movement near rigid bodies even with larger SPH particle sizes. If successful, the data-driven model would eliminate the need for a SPH turbulence model and increase the simulation domain size. Continued research beyond the scope of this project will be needed in order to determine the viability of a data-driven model.

17 WIND ENERGY↗
NASA NTRS1977

Over-the-wing model thrust reverser noise tests

Static acoustic tests were conducted on a 1/12 scale model over-the-wing target type thrust reverser. The model configuration simulates a design that is applicable to the over-the-wing short-haul advanced technology engine. Aerodynamic screening tests of a variety of reverser designs identified configurations that satisfied a reverse thrust requirement of 35 percent of forward thrust at a nozzle pressure ratio of 1.29. The variations in the reverser configuration included, blocker door angle, blocker door lip angle and shape, and side skirt shape. Acoustic data are presented and compared for the various configurations. The model data scaled to a single full size engine show that peak free field perceived noise (PN) levels at a 152.4 meter sideline distance range from 98 to 104 PNdb.

Goodykoontz, J.↗
NASA NTRS1977

Over-the-wing model thrust reverser noise tests

Experimental results are presented for static acoustic tests of a 1/12 scale model over-the-wing target type thrust reverser. The model configuration simulates a design that is applicable to the over-the-wing short-haul advanced technology engine. Aerodynamic screening tests of a variety of reverser designs identified configurations that satisfied a reverse thrust requirement of 35 percent of forward thrust at a nozzle pressure ratio of 1.29. The variations in the reverser configuration included, blocker door angle, blocker door lip angle and shape, and side skirt shape. Acoustic data are presented and compared for the various configurations. The model data scaled to a single full size engine show that peak free field perceived noise levels at a 152.4 meter sideline distance range from 98 to 104 PNdB.

Goodykoontz, J.↗
DOE OSTI2017

Two-Step Analysis of Watts Bar Nuclear 1 Cycle 1 with SCALE/PARCS

A two-step approach to reactor core analysis was performed using SCALE and PARCS. Polaris is a new lattice physics module in SCALE 6.2 that provides light water reactor (LWR) modelling capabilities. The VERA (Virtual Environment for Reactor Applications) benchmark problems have been established by the Consortium of Advanced Simulation of Light Water Reactors (CASL). These benchmark problems were chosen to assess the performance of Polaris and PARCS. Homogenized few-group assembly cross sections were generated using Polaris and used in the United States Nuclear Regulatory Commission (NRC) core simulator PARCS. This paper will provide descriptions of the benchmark problems modelled, discuss the impact of transport cross section approximations in SCALE 6.2.0 and 6.2.1, and present the results obtained from the SCALE/PARCS benchmark calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Proxy-based Bayesian inversion of strain tensor data measured during well tests

Recent instrument developments have made it possible to measure the strain tensor caused by injecting or pumping fluid from aquifers or reservoirs, but the full value of these data is limited because the long runtimes of poroelastic forward models makes it impractical to use many inversion schemes. This limits the interpretation of strain data for managing the recovery of resources or storage of wastes in the subsurface. This paper describes a method of inverting deformation data using a poroelastic numerical simulator so the results can be used to manage reservoirs or aquifers. We developed a workflow designed to reduce the number of simulations sufficiently to make it feasible to use DREAMzs, an advanced Bayesian inversion method that translates the uncertainties from different sources into unbiased posterior parameter distributions and uncertainty envelopes around the field data. Using a KNN proxy model for the poroelastic simulator is key to reducing the overall computations, and the workflow includes a strategy for ensuring the proxy model results converge on the results from the simulator. The workflow is tested using an idealized example that verifies the ability to correctly identify parameters and characterize noise used to perturb the data. Field data from an injection test at an oil reservoir near Tulsa, Oklahoma, are also used to evaluate the efficacy of the workflow with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), where the results were used to characterize posterior parameter distribution and evaluate the prediction uncertainty. Furthermore, this workflow is significant because it enables strain tensor, or other geomechanical measurements to be interpreted to guide decision-making during energy and environmental processes in the subsurface.

42 ENGINEERING↗
DOE OSTI2021

Science & Technology Review: Climate Change Comes into Focus

At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world. The cover image shows a simulation run on the Department of Energy’s (DOE’s) state-of-the-science Energy Exascale Earth Systems Model (E3SM), which leverages DOE’s advanced supercomputers for climate and earth science research. As the article beginning on p. 4 describes, the newly released version 2 will be used to simulate aspects of Earth’s variability at weather-scale resolution and investigate decadal changes in climate that will critically impact the United States in coming years.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

High-order continuum kinetic method for modeling plasma dynamics in phase space

Continuum methods offer a high-fidelity means of simulating plasma kinetics. While computationally intensive, these methods are advantageous because they can be cast in conservation-law form, are not susceptible to noise, and can be implemented using high-order numerical methods. Advances in continuum method capabilities for modeling kinetic phenomena in plasmas require the development of validation tools in higher dimensional phase space and an ability to handle non-cartesian geometries. To that end, a new benchmark for validating Vlasov-Poisson simulations in 3D (x,v x ,v y ) is presented. The benchmark is based on the Dory-Guest-Harris instability and is successfully used to validate a continuum finite volume algorithm. To address challenges associated with non-cartesian geometries, unique features of cylindrical phase space coordinates are described. Preliminary results of continuum kinetic simulations in 4D (r,z,v r ,v z ) phase space are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Sensitivity Analysis of Passive Heat Removal Capability of FHR Based on Efficient Surrogate Model and GenFlow

Code Scaling, Applicability and Uncertainty Evaluation Methodology (CSAU) is used for quantifying reactor safety margins and works as an alternative method for licensing nuclear power plant. In the framework of CSAU, sensitivity and uncertainty analysis (SA and UA) should be performed. However, for large-scale complicated thermal hydraulics analysis simulated by code (e.g. RELAP5, CFD and subchannel analysis, the sensitivity and uncertainty analysis is really time-consuming. Furthermore, sometimes it is not feasible to perform SA and UA. Specifically, the computation time for Monte Carlo sampling or advanced LHS sampling can be neglected, but the computation time for thermal hydraulics code makes up main part of time during SA and UA process. In order to accelerate the speed of SA and UA, thermal hydraulics code can be improved based on advanced mathematic algorithm or using parallel method. However, the development for new mathematic method needs long time and strict verification and validation process is needed for a new code, which usually takes a couple of years or even longer time to have an approved code that can be used in nuclear industry. An alternative way to improve the speed of SA and UA is using surrogate model. The surrogate model is derived from the input as well as output data of the original code, assuming the code as a black box. The most common method is using response surface method (RSM) as a surrogate for the code, the input parameters are then sampled from their assumed distribution and the corresponding value of the response surface function is calculated. However, a couple of input parameters need hundreds or even thousands of original code calculations. The large number of runs is an obvious disadvantage of this method. Besides, the second disadvantage is an appropriate response surface function must be selected (e.g. quadratic, cubic, quartic, with or without cross product terms, or using a non-polynomial form) to avoid the overfit and underfit problem. This process is time consuming and expensive. Polynomial chaos expansion method is a reasonably fast and attractive alternative, stochastic model. The chaos expansion provides an efficient high-order method of including non-linear effects in stochastic analysis. Usually, the information about the model parameters and their probability distribution is limited and the dependence between them is not known. However, if arbitrary polynomial chaos is used, instead of assuming probability distribution for input parameters which may introduces additional subjectivity into the analysis, the available information can directly and most purely be used in stochastic analysis based on arbitrary data distribution. Thus, it is not necessary to know the exact probability density functions to perform SA and UA based on arbitrary polynomial chaos (aPC). The aPC has been applied for uncertainty quantification in many fields (e.g. in solid mechanics, fluid flows, thermal sciences), and become widely used in nuclear industry recently. Mk1 PB-FHR is a small modular fluoride-salt-cooled, high-temperature reactors (FHRs) that is a concept design by University of California, Berkeley (UCB). It has inherently safe features like natural-circulation-driven systems (e.g. direct reactor auxiliary cooling system (DRACS)) to passively remove decay heat from the reactor core during design basis and beyond design. It is necessary to perform SA and UA, since the licensing process of this new kind of reactor is under way and there are many design parameters that have not been fixed. Current nuclear commercial codes, such as RELAP5, have mainly been developed for light water reactors, which require the use of comprehensive two-phase flow models. This capability is not required to simulate single-phase flow phenomena in FHRs, whose baseline coolant, flibe, remains liquid up to 1430 deg. C at atmospheric pressure. The FHR advanced natural circulation analysis (FANCY) code has been developed specifically for FHR technology modeling and validation work has been performed by using CIET data in UCB. The code has been renamed General Flow (GenFlow) because it has been further developed to have the capability to model complicated pipework system based on object-oriented concept for user friendly purpose. Besides, it can be used to simulate both the force circulation as well as natural circulation. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Position Papers for Inverse Methods for Complex Systems under Uncertainty Workshop

The ability to solve inverse problems – inferring unknown parameters, structures, or states of a system from observed data – is essential for advancing scientific discovery and innovation capabilities for the DOE mission. Basic research needs and challenges are particularly acute in emerging areas such as the interactive, data-driven, modeling and simulation of digital twins; decision support for experiments at DOE scientific user facilities; and for other complex systems and workflows. Inverse problems are at the heart of understanding and controlling complex systems due to factors such as observational data with varying modalities and fidelities, inherent uncertainties in physical measurements and numerical models, and the computational demands of rapid and high-fidelity simulations. The convergence of recent scientific computing trends – scientific machine learning, artificial intelligence, and computing advances such as exascale computing – is creating unprecedented opportunities. These advancements offer the potential to revolutionize how we approach inverse problems to extract actionable insights with the required level of accuracy and computational efficiency. This workshop and the Call for Position Papers are vital steps in bringing together experts to collectively explore and identify the new computational and mathematical directions needed in inverse methods for complex systems under uncertainty.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Current CFD Practices in Launch Vehicle Applications

The quest for sustained space exploration will require the development of advanced launch vehicles, and efficient and reliable operating systems. Development of launch vehicles via test-fail-fix approach is very expensive and time consuming. For decision making, modeling and simulation (M&S) has played increasingly important roles in many aspects of launch vehicle development. It is therefore essential to develop and maintain most advanced M&S capability. More specifically computational fluid dynamics (CFD) has been providing critical data for developing launch vehicles complementing expensive testing. During the past three decades CFD capability has increased remarkably along with advances in computer hardware and computing technology. However, most of the fundamental CFD capability in launch vehicle applications is derived from the past advances. Specific gaps in the solution procedures are being filled primarily through "piggy backed" efforts.on various projects while solving today's problems. Therefore, some of the advanced capabilities are not readily available for various new tasks, and mission-support problems are often analyzed using ad hoc approaches. The current report is intended to present our view on state-of-the-art (SOA) in CFD and its shortcomings in support of space transport vehicle development. Best practices in solving current issues will be discussed using examples from ascending launch vehicles. Some of the pacing will be discussed in conjunction with these examples.

Kwak, Dochan↗
NASA NTRS2008

Multiscale Modeling of Damage Processes in Aluminum Alloys: Grain-Scale Mechanisms

This paper has two goals related to the development of a physically-grounded methodology for modeling the initial stages of fatigue crack growth in an aluminum alloy. The aluminum alloy, AA 7075-T651, is susceptible to fatigue cracking that nucleates from cracked second phase iron-bearing particles. Thus, the first goal of the paper is to validate an existing framework for the prediction of the conditions under which the particles crack. The observed statistics of particle cracking (defined as incubation for this alloy) must be accurately predicted to simulate the stochastic nature of microstructurally small fatigue crack (MSFC) formation. Also, only by simulating incubation of damage in a statistically accurate manner can subsequent stages of crack growth be accurately predicted. To maintain fidelity and computational efficiency, a filtering procedure was developed to eliminate particles that were unlikely to crack. The particle filter considers the distributions of particle sizes and shapes, grain texture, and the configuration of the surrounding grains. This filter helps substantially reduce the number of particles that need to be included in the microstructural models and forms the basis of the future work on the subsequent stages of MSFC, crack nucleation and microstructurally small crack propagation. A physics-based approach to simulating fracture should ultimately begin at nanometer length scale, in which atomistic simulation is used to predict the fundamental damage mechanisms of MSFC. These mechanisms include dislocation formation and interaction, interstitial void formation, and atomic diffusion. However, atomistic simulations quickly become computationally intractable as the system size increases, especially when directly linking to the already large microstructural models. Therefore, the second goal of this paper is to propose a method that will incorporate atomistic simulation and small-scale experimental characterization into the existing multiscale framework. At the microscale, the nanoscale mechanics are represented within cohesive zones where appropriate, i.e. where the mechanics observed at the nanoscale can be represented as occurring on a plane such as at grain boundaries or slip planes at a crack front. Important advancements that are yet to be made include: 1. an increased fidelity in cohesive zone modeling; 2. a means to understand how atomistic simulation scales with time; 3. a new experimental methodology for generating empirical models for CZMs and emerging materials; and 4. a validation of simulations of the damage processes at the nano-micro scale. With ever-increasing computer power, the long-term ability to employ atomistic simulation for the prognosis of structural components will not be limited by computation power, but by our lack of knowledge in incorporating atomistic models into simulations of MSFC into a multiscale framework.

Hochhalter, J. D.↗
DOE OSTI2019

Study of Regional Climate Change Final Technical Report

Anthropogenic activity of fossil fuel and biomass burning emissions increase tropospheric aerosol concentrations causing a direct cooling effect by scattering solar radiation and thus increasing the Earth’s albedo. In addition, the aerosols can act as cloud condensation nuclei to regulate cloud droplet number and size, thereby changing both the cloud albedo, and the cloud lifetime and precipitation. Thus, the aerosol climate effect concerns intricate aerosol-cloud-radiation-precipitation interactions which are recognized to introduce the largest uncertainties in using GCMs to project future regional climate changes. The climate effects of aerosols are significant in the land regions of the Northern Hemisphere, in particular the sulfate aerosols over East Asia where significant anthropogenic SO 2 emissions have been observed and concentrations of other aerosol species are also high. The objective of the present project is to advance “modeling aerosol-cloud-climate interactions” in two areas: the aerosol-cloud microphysics interactions and model simulations of aerosol effects on regional climate with focus on East Asia. To achieve the objective, in addition to analyzing relevant observations, the project conducts and diagnoses regional and global climate model simulations. Specifically, two collaborative tasks were carried out: Task-1: Incorporating a physics-based, two-moments cloud scheme developed by J. P. Chen/National Taiwan University (NTU) into regional models (WRF and WRF-Chem) to study “aerosol-cloud microphysics interactions over eastern China and the southeast Pacific” ; for latter region, CMIP5 models exhibit distinct biases in (weaker) cloud radiative effects and (warmer) sea surface temperature. The task is conducted in collaboration with J.-P. Chen, H.-W. Xue/Peking University, and H. Liao/Institute of Atmospheric Physics; and Task-2: Diagnosis of NCAR-CESM and WRF model simulations of “aerosol climate effects” focusing on changes of circulation, precipitation and clouds over East Asia. The task is conducted in collaboration with J.-P. Chen, and I-Chun Tsai & H.-H. Hsu/Academia Sinica. For each task, several topical studies were carried out and documented in eleven (11) articles (five for Task-1 and six for Task-2), published in: J. Atmospheric Sciences (2); J. Climate (1); Climate Dynamics (3); J. Geophysical Research (2); Geophysical Research Letter (1); Int. J. Climatology (1); and Advances in Atmospheric Sciences (1). In addition, Wei-Chyung Wang (the PI) continues serving as the U. S. Chief Scientist for the joint agreement, “Climate Sciences”, between the U. S. DOE and China Ministry of Sciences and Technology (Riches et al., 2010). In this capacity, he works closely with Michael Riches/DOE (the U. S. Manager) to coordinate the scientific exchanges (visiting scientists) between the two countries. Educations (graduate students) and trainings (postdoctoral research associates) are key elements of the research project.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2026

xEMU Spacesuit Boot Lunar South Pole Thermal Vacuum Testing

The Exploration Extravehicular Mobility Unit (xEMU) spacesuit lunar boot was evaluated in the Jet Propulsion Lab (JPL) CITADEL thermal vacuum chamber at lunar South Pole conditions. The JPL CITADEL chamber provides a radiation environment and contact plate temperature of 48K, simulating the temperature of a lunar Permanently Shadowed Region (PSR) at the South Pole of the Moon. The main objectives of the test series were: to evaluate the risk lunar PSRs pose to advanced spacesuit boots, validate the xEMU lunar boot thermal model, and develop a test methodology to evaluate lunar spacesuit boots. To simulate the thermal effects of a crewmember’s foot inside the boot, a thermal manikin foot was developed to inject heat into the spacesuit boot. Thermal data was collected through a variety of sensors including thermocouples, thermistors, heat flux sensors, and infrared cameras. A test matrix was developed to investigate the variables of foot contact force, simulated skin temperature, external contact plate temperature, and ventilation flowrate. The JPL CITADEL chamber includes a loadlock (airlock) that afforded the ability to simulate the transition of the boot from a thermally neutral IVA condition to a cold EVA condition within seconds. This paper will document the test design, test objectives, success criteria, test support equipment, spacesuit boot to chamber interfaces, and configuration of the test article. Additionally, this paper will document the high-level results of the testing. More detailed test results will be presented in a different paper.

TVAC↗
DOE OSTI2026

Pattern-enhanced Resonant Soft X-ray Scattering for Operando monitoring of electrochemical solid-liquid interfaces

Unveiling interfaces at sub-nanometer scales is essential for advancing the understanding of complex chemical transformations. However, characterizing solid-liquid interfaces with high dimensional sensitivity and temporal resolution remains challenging, due to their dynamic nature and inaccessibility by conventional probes. Here we present an approach, Pattern-enhanced Resonant Soft X-ray Scattering, to overcome the challenges. Rooted in a “sample-as-optics” philosophy, this technique utilizes precisely engineered line-grating nanopatterns to modulate near-field X-ray illumination, coherently enhancing scattering signals from the line-gratings. We implement the method using Ni line-grating nanopatterns in electrochemical water oxidation. The periodic nanostructures serve as diffractive optical elements to reveal the Ni oxidation gradients and structural dynamics at the electrode-electrolyte interfaces. Finite-element simulations corroborate the observed trends by modeling variations in compositions and structures during electrocatalysis. Through integrating advanced sample design with coherent wave nature of soft X-rays, our approach opens accessible pathways to operando exploring chemical evolution and sub-nanometer dimensional variations simultaneously in electrochemical systems. This non-destructive method is efficient and element-specific, making it valuable for probing chemical and dimensional dynamics with appropriate modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Unraveling fundamental mechanisms of silicon nitride crystallization in microelectronics manufacturing

This research project investigates the fundamental mechanisms of silicon nitride (SiN) crystallization, aiming to enhance the understanding of this critical material in microelectronics manufacturing. Through a collaborative effort between Sandia National Laboratories, the University of Tennessee, and the University of Florida, we developed a comprehensive framework that integrates experimental techniques, atomistic modeling, meso-scale simulations, and an integrated multi-scale model to capture this physical phenomenon on multiple time and length scales . The project developed a new machine learning based atomistic potential and utilized advanced phase field modeling to capture the complexities of polycrystalline growth and the influence of mechanical stresses on crystallization dynamics. By employing a grain tracker algorithm, the meso-scale model effectively identified and tracked individual crystal grains, enabling the simulation of anisotropic growth behaviors reflective of SiN’s physical properties. The integration of atomistic simulations with meso-scale modeling created a powerful multi-scale framework that validated atomistic inputs and enhanced predictive accuracy for crystallization dynamics at larger scales, validated experimentally. This adaptable modeling capability not only accelerates development times by informing manufacturing processes but also serves as a valuable starting point for understanding crystallization physics in similar materials. The insights gained from this research unlock new opportunities for the development of advanced materials tailored for future microelectronics and photonics applications. Overall, this project represents a significant advancement in understanding of fundamental physics of SiN and establishes a foundation for future research in material science, bridging the gap between atomic-level phenomena and macroscopic material behaviors for practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Backend-agnostic, Quantum-classical Framework for Simulations of Chemistry in C ++

As quantum computing hardware systems continue to advance, the research and development of performant, scalable, and extensible software architectures, languages, models, and compilers is equally as important to bring this novel coprocessing capability to a diverse group of domain computational scientists. For the field of quantum chemistry, applications and frameworks exist for modeling and simulation tasks that scale on heterogeneous classical architectures, and we envision the need for similar frameworks on heterogeneous quantum-classical platforms. Furthermore, we present the XACC system-level quantum computing framework as a platform for prototyping, developing, and deploying quantum-classical software that specifically targets chemistry applications. We review the fundamental design features in XACC, with special attention to its extensibility and modularity for key quantum programming workflow interfaces and provide an overview of the interfaces most relevant to simulations of chemistry. A series of examples demonstrating some of the state-of-the-art chemistry algorithms currently implemented in XACC are presented, while also illustrating the various APIs that would enable the community to extend, modify, and devise new algorithms and applications in the realm of chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

WE-DE-BRA-05: Monte Carlo Simulation of a Novel Multi-Layer MV Imager

Purpose: To develop and validate a Monte Carlo (MC) model of a novel multi-layer imager (MLI) for megavolt (MV) energy beams. The MC model will enable performance optimization of the MLI design for clinical applications including patient setup verification, tumor tracking and MVCBCT. Methods: The MLI is composed of four layers of converter, scintillator and light detector, each layer similar to the current clinical AS1200 detector (Varian Medical Systems, Inc). The MLI model was constructed using the Geant4 Application for Tomographic Emission (GATE v7.1) and includes interactions for x-ray photons, charged particles and optical photons. Computational experiments were performed to assess Modulation Transfer Function (MTF), Detective Quantum Efficiency (DQE) and Noise Power Spectrum normalized by photon fluence and average detector signal (qNNPS). Results were compared with experimental measurements. The current work incorporates, in one model, the complete chain of events occurring in the imager; i.e. starting from x-ray interaction to charged particle transport and energy deposition to subsequent generation, interactions and detection of optical photons. Results: There is good agreement between measured and simulated MTF, qNNPS and DQE values. Normalized root mean squared error (NRMSE) between measured and simulated values over all four layers was 2.18%, 2.43% and 6.05% for MTF, qNNPS and DQE respectively. The relative difference between simulated and measured values for qNNPS(0) was 1.68% and 1.57% for DQE(0). Current results were obtained using a 6MV Varian Truebeam™ spectrum. Conclusion: A comprehensive Monte Carlo model of the MLI prototype was developed to allow optimization of detector components. The model was assessed in terms of imaging performance using standard metrics (i.e. MTF, qNNPS, DQE). Good agreement was found between simulated and measured values. The model will be used to assess alternative detector constructions to facilitate advanced clinical imaging applications including MV-CBCT and tumor tracking. The project was supported, partially, by a grant from Varian Medical Systems, Inc., and Award No. R01CA188446-01 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

60 APPLIED LIFE SCIENCES↗