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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The reaction between the bromine atom and the water trimer: high level theoretical studies

Three different reaction pathways are found for the reaction of bromine atom (Br) with the lowest-energy structure of the water trimer [uud-(H 2 O) 3 ], initially using the MPW1K-DFT method. The three bromine pathways have closely related geometries and energetics, analogous to those found for the fluorine and chlorine reactions. Here, the lowest-energy pathway of the Br + uud-(H 2 O) 3 reaction was further investigated using the “gold standard” CCSD(T) method and the correlation-consistent basis sets up to cc-pVQZ(-PP). Based on the CCSD(T)/cc-pVQZ(-PP)//CCSD(T)/cc-pVTZ(-PP) results, the Br + (H 2 O) 3 reaction is endothermic by 33.3 kcal mol -1 . The classical barrier height is 29.0 kcal mol -1 between the reactants and the exit complex, and there is no barrier for the reverse reaction. The Br···(H 2 O) 3 entrance complex is found to lie 4.7 kcal mol -1 below the separated reactants, and the HBr···(H 2 O) 2 OH exit complex is bound by 6.4 kcal mol -1 relative to the separated products. This potential energy profile is further corrected by the zero point energies and spin–orbit coupling effects. Structurally, the Br + (H 2 O) 3 stationary points can be derived from those of the simpler Br + (H 2 O) 2 reaction by judiciously appending a H 2 O molecule. The Br + (H 2 O) 3 potential energy profile is compared with the Br + (H 2 O) 2 and Br + H 2 O reactions, as well as to the valence isoelectronic Cl + (H 2 O) 3 and F + (H 2 O) 3 systems. It is reasonable to expect that the reactions between the bromine atom and larger water clusters would be similar to the Br + (H 2 O) 3 reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Automated Approach to Accurate, Precise, and Fast Detector Simulation and Reconstruction

Detector simulation and reconstruction are a significant computational bottleneck in particle physics. Here, we develop particle-flow neural-assisted simulations (parnassus) to address this challenge. Our deep learning model takes as input a point cloud (particles impinging on a detector) and produces a point cloud (reconstructed particles). By combining detector simulations and reconstruction into one step, we aim to minimize resource utilization and enable fast surrogate models suitable for application both inside and outside large collaborations. We demonstrate this approach using a publicly available dataset of jets passed through the full simulation and reconstruction pipeline of the Compact Muon Solenoid (CMS) experiment. We show that parnassus accurately mimics the CMS particle flow algorithm on the (statistically) same events it was trained on and can generalize to jet momentum and type outside of the training distribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2017

Object and Facial Recognition in Augmented and Virtual Reality: Investigation into Software, Hardware and Potential Uses

As augmented and virtual reality grows in popularity, and more researchers focus on its development, other fields of technology have grown in the hopes of integrating with the up-and-coming hardware currently on the market. Namely, there has been a focus on how to make an intuitive, hands-free human-computer interaction (HCI) utilizing AR and VR that allows users to control their technology with little to no physical interaction with hardware. Computer vision, which is utilized in devices such as the Microsoft Kinect, webcams and other similar hardware has shown potential in assisting with the development of a HCI system that requires next to no human interaction with computing hardware and software. Object and facial recognition are two subsets of computer vision, both of which can be applied to HCI systems in the fields of medicine, security, industrial development and other similar areas.

object recognition↗
NASA NTRSDate not supplied

Computational Models of Trustworthiness and Trust in Autonomous Cyber-Physical-Human Systems

In this paper, we propose an approach to developing a concept of actionable trust in multi-agent,cyber-physical-human systems in safety-critical and time-critical environment of air transportation. Actionable trust requires computational models of trustworthiness and trust, for use during system design and in real time, during operations. We describe the models, examine their computability and scalability, as well as what remains to be done.

Autonomous Systems↗
DOE OSTI2013

Safeguards and security modeling for electrochemical plants

Safeguards and security design for reprocessing plants can lead to excessive costs if not incorporated early in the design process. The design for electrochemical plants is somewhat uncertain since these plants have not been built at a commercial scale in the past. The Separation and Safeguards Performance Model (SSPM), developed at Sandia National Laboratories, has been used for safeguards design and evaluation for multiple reprocessing plant types. The SSPM includes the following capabilities: -) spent fuel source term library, -) mass tracking of elements 1-99 and bulk solid/liquids, -) tracking of heat load and activity, -) customisable measurement points, -) automated calculation of ID and error propagation, -) alarm conditions and statistical tests, and -) user-defined diversion scenarios. Materials accountancy and process monitoring data can provide more timely detection of material loss specifically to protect against the insider threat. While the SSPM is capable of determining detection probabilities and examining detection times for material loss scenarios, it does not model the operations or spatial effects for a plant design. The STAGE software was chosen to model the physical protection system. STAGE provides a framework to create end-to-end scalable force-on-force combat simulations. It allows for a complete 3D model of a facility to be designed along with the design of physical protection elements. This software, then, can be used to model operations and response for various material loss scenarios. The future integration of the SSPM model data with the STAGE software will provide a more complete analysis of diversion scenarios to assist plant designers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Validation Metrics for Deterministic and Probabilistic Data

Computational modeling and simulation are paramount to modern science. Computational models often replace physical experiments that are prohibitively expensive, dangerous, or occur at extreme scales. Thus, it is critical that these models accurately represent and can be used as replacements for reality. This paper provides an analysis of metrics that may be used to determine the validity of a computational model. While some metrics have a direct physical meaning and a long history of use, others, especially those that compare probabilistic data, are more difficult to interpret. Furthermore, the process of model validation is often application-specific, making the procedure itself challenging and the results difficult to defend. We therefore provide guidance and recommendations as to which validation metric to use, as well as how to use and decipher the results. Furthermore an example is included that compares interpretations of various metrics and demonstrates the impact of model and experimental uncertainty on validation processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A software package for plasma facing component analysis and design: the Heat flux Engineering Analysis Toolkit (HEAT)

The engineering limits of plasma facing components (PFCs) constrain the allowable operational space of tokamaks. Poorly managed heat fluxes that push the PFCs beyond their limits not only degrade core plasma performance via elevated impurities, but can also result in PFC failure due to thermal stresses or melting. Simple axisymmetric assumptions fail to capture the complex interaction between 3D PFC geometry and 2D or 3D plasmas. This results in fusion systems that must either operate with increased risk or reduce PFC loads, potentially through lower core plasma performance, to maintain a nominal safety factor. High precision 3D heat flux predictions are necessary to accurately ascertain the state of a PFC given the evolution of the magnetic equilibrium. A new code, the Heat flux Engineering Analysis Toolkit (HEAT), has been developed to provide high precision 3D predictions and analysis for PFCs. HEAT couples many otherwise disparate computational tools together into a single open source python package. Magnetic equilibrium, engineering CAD, finite volume solvers, scrape off layer plasma physics, visualization, high performace computing, and more, are connected in a single web-based user interface. Linux users may use HEAT without any software prerequisites via an appImage. This manuscript introduces HEAT, discusses the software architecture, presents first HEAT results, and outlines physics modules in development.

divertor physics↗
NASA NTRS1988

A physically consistent model for artificial dissipation in transonic potential flow computations

The effect that artificial dissipation has on numerical solutions of the transonic Full Potential Equation (FPE) are investigated by comparing the artificially dissipative FPE to a Physically Dissipative Potential (PDP) equation. Analytic expressions were derived from the variables C and M sub c that are used in the artificial density formulation. It was shown that these new values generate artificial dissipation which is equivalent to the physical dissipation existing in the PDP equation. The new expression for the variables C and M sub c can easily be incorporated into the existing full potential codes which are based either on the artificial density or on the artificial viscosity formulation. A comparison of Physically Dissipative Potential (PDP), Artificial Density or Viscosity (ADV), Artificial Mass Flux (AMF), and ADV with variable C and M sub c formulation (MCC) is also presented.

Dulikravich, George S.↗
DOE OSTI2025

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom

Energy-efficient ventilation control plays an important role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representations of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO 2 prediction and deep learning–based reduced-order models, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

A Roadmap for HEP Software and Computing R&D for the 2020s

Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Physics-Based Hazard Assessment for Critical Structures Near Large Earthquake Sources

We argue that for critical structures near large earthquake sources: (1) the ergodic assumption, recent history, and simplified descriptions of the hazard are not appropriate to rely on for earthquake ground motion prediction and can lead to a mis-estimation of the hazard and risk to structures; (2) a physics-based approach can address these issues; (3) a physics-based source model must be provided to generate realistic phasing effects from finite rupture and model near-source ground motion correctly; (4) wave propagations and site response should be site specific; (5) a much wider search of possible sources of ground motion can be achieved computationally with a physics-based approach; (6) unless one utilizes a physics-based approach, the hazard and risk to structures has unknown uncertainties; (7) uncertainties can be reduced with a physics-based approach, but not with an ergodic approach; (8) computational power and computer codes have advanced to the point that risk to structures can be calculated directly from source and site-specific ground motions. Spanning the variability of potential ground motion in a predictive situation is especially difficult for near-source areas, but that is the distance at which the hazard is the greatest. The basis of a “physical-based” approach is ground-motion syntheses derived from physics and an understanding of the earthquake process. This is an overview paper and results from previous studies are used to make the case for these conclusions. Our premise is that 50 years of strong motion records is insufficient to capture all possible ranges of site and propagation path conditions, rupture processes, and spatial geometric relationships between source and site. Predicting future earthquake scenarios is necessary; models that have little or no physical basis but have been tested and adjusted to fit available observations can only “predict” what happened in the past, which should be considered description as opposed to prediction. Finally, we have developed a methodology for synthesizing physics-based broadband ground motion that incorporates the effects of realistic earthquake rupture along specific faults and the actual geology between the source and site.

58 GEOSCIENCES↗
NASA NTRS2013

Time-Accurate Local Time Stepping and High-Order Time CESE Methods for Multi-Dimensional Flows Using Unstructured Meshes

With the wide availability of affordable multiple-core parallel supercomputers, next generation numerical simulations of flow physics are being focused on unsteady computations for problems involving multiple time scales and multiple physics. These simulations require higher solution accuracy than most algorithms and computational fluid dynamics codes currently available. This paper focuses on the developmental effort for high-fidelity multi-dimensional, unstructured-mesh flow solvers using the space-time conservation element, solution element (CESE) framework. Two approaches have been investigated in this research in order to provide high-accuracy, cross-cutting numerical simulations for a variety of flow regimes: 1) time-accurate local time stepping and 2) highorder CESE method. The first approach utilizes consistent numerical formulations in the space-time flux integration to preserve temporal conservation across the cells with different marching time steps. Such approach relieves the stringent time step constraint associated with the smallest time step in the computational domain while preserving temporal accuracy for all the cells. For flows involving multiple scales, both numerical accuracy and efficiency can be significantly enhanced. The second approach extends the current CESE solver to higher-order accuracy. Unlike other existing explicit high-order methods for unstructured meshes, the CESE framework maintains a CFL condition of one for arbitrarily high-order formulations while retaining the same compact stencil as its second-order counterpart. For large-scale unsteady computations, this feature substantially enhances numerical efficiency. Numerical formulations and validations using benchmark problems are discussed in this paper along with realistic examples.

Chang, Chau-Lyan↗
DOE OSTI2019

Entropy and Gravitation—From Black Hole Computers to Dark Energy and Dark Matter

We show that the concept of entropy and the dynamics of gravitation provide the linchpin in a unified scheme to understand the physics of black hole computers, spacetime foam, dark energy, dark matter and the phenomenon of turbulence. We use three different methods to estimate the foaminess of spacetime, which, in turn, provides a back-door way to derive the Bekenstein-Hawking formula for black hole entropy and the holographic principle. Generalizing the discussion for a static spacetime region to the cosmos, we find a component of dark energy (resembling an effective positive cosmological constant of the correct magnitude) in the current epoch of the universe. The conjunction of entropy and gravitation is shown to give rise to a phenomenological model of dark matter, revealing the natural emergence, in galactic and cluster dynamics, of a critical acceleration parameter related to the cosmological constant; the resulting mass profiles are consistent with observations. Unlike ordinary matter, the quanta of the dark sector are shown to obey infinite statistics. This property of dark matter may lead to some non-particle phenomenology and may explain why dark matter particles have not been detected in dark matter search experiments. We also show that there are deep similarities between the problem of “quantum gravity” (more specifically, the holographic spacetime foam) and turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Navy Enhanced Sierra Mechanics (NESM): Toolbox for predicting Navy shock and damage

Here, the US Navy is developing a new suite of computational mechanics tools (Navy Enhanced Sierra Mechanics) for the prediction of ship response, damage, and shock environments transmitted to vital systems during threat weapon encounters. NESM includes fully coupled Euler-Lagrange solvers tailored to ship shock/damage predictions. NESM is optimized to support high-performance computing architectures, providing the physics-based ship response/threat weapon damage predictions needed to support the design and assessment of highly survivable ships. NESM is being employed to support current Navy ship design and acquisition programs while being further developed for future Navy fleet needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Information criteria for quantifying loss of reversibility in parallelized KMC

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Computationally guided discovery of thermoelectric materials

The potential for advances in thermoelectric materials, and thus solid-state refrigeration and power generation, is immense. Progress so far has been limited by both the breadth and diversity of the chemical space and the serial nature of experimental work. In this Review, we discuss how recent computational advances are revolutionizing our ability to predict electron and phonon transport and scattering, as well as materials dopability, and we examine efficient approaches to calculating critical transport properties across large chemical spaces. When coupled with experimental feedback, these high-throughput approaches can stimulate the discovery of new classes of thermoelectric materials. Within smaller materials subsets, computations can guide the optimal chemical and structural tailoring to enhance materials performance and provide insight into the underlying transport physics. Beyond perfect materials, computations can be used for the rational design of structural and chemical modifications (such as defects, interfaces, dopants and alloys) to provide additional control on transport properties to optimize performance. Through computational predictions for both materials searches and design, a new paradigm in thermoelectric materials discovery is emerging.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Baryon–antibaryon photoproduction cross sections off the proton

The GlueX experiment at Jefferson Lab has observed 𝑝⁢$\overline{p}$ and, for the first time, Λ$\overlineΛ$ and 𝑝$\overlineΛ$ photoproduction from a proton target at photon energies up to 11.6 GeV. The angular distributions are forward peaked for all produced pairs, consistent with Regge-like 𝑡-channel exchange. Asymmetric wide-angle antibaryon distributions show the presence of additional processes. In a phenomenological model, we find consistency with a double-𝑡-channel exchange process where antibaryons are created only at the middle vertex. The model matches all observed distributions with a small number of free parameters. In the hyperon channels, we observe a clear distinction between photoproduction of the Λ$\overlineΛ$ and 𝑝$\overlineΛ$ systems but general similarity to the 𝑝$\overline{p}$ system. We report both total cross sections and cross sections differential with respect to momentum transfer and the invariant masses of the created particle pairs. No narrow resonant structures were found in these reaction channels. The suppression of 𝑠$\overline{s}$ quark pairs relative to 𝑑$\overline{d}$ quark pairs is similar to what has been seen in other reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

SU-E-T-521: Investigation of the Uncertainties Involved in Secondary Neutron/gamma Production in Geant4/MCNP6 Monte Carlo Codes for Proton Therapy Application

Purpose: A major concern in proton therapy is the production of secondary neutrons causing secondary cancers, especially in young adults and children. Most utilized Monte Carlo codes in proton therapy are Geant4 and MCNP. However, the default versions of Geant4 and MCNP6 do not have suitable cross sections or physical models to properly handle secondary particle production in proton energy ranges used for therapy. In this study, default versions of Geant4 and MCNP6 were modified to better handle production of secondaries by adding the TENDL-2012 cross-section library. Methods: In-water proton depth-dose was measured at the “The Svedberg Laboratory” in Uppsala (Sweden). The proton beam was mono-energetic with mean energy of 178.25±0.2 MeV. The measurement set-up was simulated by Geant4 version 10.00 (default and modified version) and MCNP6. Proton depth-dose, primary and secondary particle fluence and neutron equivalent dose were calculated. In case of Geant4, the secondary particle fluence was filtered by all the physics processes to identify the main process responsible for the difference between the default and modified version. Results: The proton depth-dose curves and primary proton fluence show a good agreement between both Geant4 versions and MCNP6. With respect to the modified version, default Geant4 underestimates the production of secondary neutrons while overestimates that of gammas. The “ProtonInElastic” process was identified as the main responsible process for the difference between the two versions. MCNP6 shows higher neutron production and lower gamma production than both Geant4 versions. Conclusion: Despite the good agreement on the proton depth dose curve and primary proton fluence, there is a significant discrepancy on secondary neutron production between MCNP6 and both versions of Geant4. Further studies are thus in order to find the possible cause of this discrepancy or more accurate cross-sections/models to handle the nuclear interactions of protons with energy ranges used for therapy. NSERC-CRSNG’ CREATE Medical Physics Research Training Network compute calcul CANADA; McGill University health center research institute the fast foundation; LM acknowledges partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering; Research Council Grant number 432290.

60 APPLIED LIFE SCIENCES↗