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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Execute BEE workflows on private cloud infrastructure-2.3.6.01 - LANL ATDM ST / STNS01-22 Milestone Completion Documentation (BEE-FY21 P6-2) [Slides]

This work involves the creation of the Cloud Launcher, a new subcomponent of BEE, and the extension of the BEETaskManager to run on Cloud systems. BEE will be able to interact with the Google Compute Engine and OpenStack cloud APIs to set up simple Cloud clusters for launching HPC job scripts. BEE will use existing functionality to launch jobs that previously could only be launched on HPC systems. The BEETaskManager will handle launching tasks on the Cloud cluster.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Multi-element flow-driven spectral chaos (ME-FSC) method for uncertainty quantification of dynamical systems

The flow-driven spectral chaos (FSC) is a recently developed method for tracking and quantifying uncertainties in the long-time response of stochastic dynamical systems using the spectral approach. The method uses a novel concept called enriched stochastic flow maps as a means to construct an evolving finite-dimensional random function space that is both accurate and computationally efficient in time. In this paper, we present a multi-element version of the FSC method (the ME-FSC method for short) to tackle (mainly) those dynamical systems that are inherently discontinuous over the probability space. In ME-FSC, the random domain is partitioned into several elements, and then the problem is solved separately on each random element using the FSC method. Subsequently, results are aggregated to compute the probability moments of interest using the law of total probability. To demonstrate the effectiveness of the ME-FSC method in dealing with discontinuities and long-time integration of stochastic dynamical systems, four representative numerical examples are presented in this paper, including the Van-der-Pol oscillator problem and the Kraichnan-Orszag three-mode problem. Results show that the ME-FSC method is capable of solving problems that have strong nonlinear dependencies over the probability space, both reliably and at low computational cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts

Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. The results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Improved parallel performance of the CICE model in CESM1

The Los Alamos sea ice model, CICE, is a sophisticated finite difference grid point model. It has been a part of the National Science Foundation and Department of Energy community climate models (Community Climate System Model (CCSM) and Community Earth System Model (CESM)) for over a decade. It includes various physical and dynamical processes and is parallelized to run on large-scale computer systems. The CICE model was assessed in the CESM at different resolutions and target processor counts to better understand and optimize the performance. Several new decompositions and a new feature to reduce the halo cost were added to the model. The new decompositions better leverage land block elimination and take advantage of scaling opportunities in different computational kernels. As a result of these new features, the CICE model performance has been improved by up to 45% and has more flexibility to be run efficiently at arbitrary Message Passing Interface (MPI) task counts

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Theory and numerics of subspace approximation of eigenvalue problems

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to mitigate the computational burden associated with high-fidelity systems. Furthermore, we provide general error estimates under non-simple eigenvalue conditions, establishing some theoretical foundations for understanding the convergence behavior of subspace approximations. Numerical examples, including problems with one-dimensional to three-dimensional spatial domain and one-dimensional to two-dimensional parameter domain, are presented to demonstrate the efficacy of reduced basis method in handling parametric variations in boundary conditions and coefficient fields to achieve significant computational savings while maintaining high accuracy, making them promising tools for practical applications in large-scale eigenvalue computations.

Eigenvalue problems↗
DOE OSTI2016

Bayesian analysis of rare events

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Bridging microscopy with molecular dynamics and quantum simulations: an atomAI based pipeline

Recent advances in (scanning) transmission electron microscopy have enabled a routine generation of large volumes of high-veracity structural data on 2D and 3D materials, naturally offering the challenge of using these as starting inputs for atomistic simulations. In this fashion, the theory will address experimentally emerging structures, as opposed to the full range of theoretically possible atomic configurations. However, this challenge is highly nontrivial due to the extreme disparity between intrinsic timescales accessible to modern simulations and microscopy, as well as latencies of microscopy and simulations per se. Addressing this issue requires as a first step bridging the instrumental data flow and physics-based simulation environment, to enable the selection of regions of interest and exploring them using physical simulations. Here we report the development of the machine learning workflow that directly bridges the instrument data stream into Python-based molecular dynamics and density functional theory environments using pre-trained neural networks to convert imaging data to physical descriptors. Additionally, the pathways to ensure structural stability and compensate for the observational biases universally present in the data are identified in the workflow. This approach is used for a graphene system to reconstruct optimized geometry and simulate temperature-dependent dynamics including adsorption of Cr as an ad-atom and graphene healing effects. However, it is universal and can be used for other material systems.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Preclinical assessment of dopaminergic system in rats by MicroPET using three positron-emitting radiopharmaceuticals

Different diseases associated with dysfunction of dopaminergic system such as Parkinson, Alzheimer, and Schizophrenia are being widely studied with positron emission tomography (PET) which is a noninvasive method useful to assess the stage of these illnesses. In our facility we have recently implemented the production of [{sup 11}C]-DTBZ, [{sup 11}C]-RAC, and [{sup 18}F]-FDOPA, which are among the most common PET radiopharmaceuticals used in neurology applications to get information about the dopamine pathways. In this study two healthy rats were imaged with each of those radiotracers in order to confirm selective striatum uptake as a proof of principle before to release them for human use.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Efficient Preparation of Dicke States

Here, we present an algorithm utilizing midcircuit measurement and feedback that prepares Dicke states with polylogarithmically many ancillae and polylogarithmic depth. Our algorithm uses only global midcircuit projective measurements and adaptively chosen global rotations. This improves over prior work that was only efficient for Dicke states of low weight or was not efficient in both depth and width. Our algorithm can also naturally be implemented in a cavity QED context using logarithmic time, zero ancillae, and atom-photon coupling scaling with the square root of the system size.

cavity methods↗
DOE OSTI2017

Building near-real-time processing pipelines with the spark-MPI platform

Advances in detectors and computational technologies provide new opportunities for applied research and the fundamental sciences. Concurrently, dramatic increases in the three V's (Volume, Velocity, and Variety) of experimental data and the scale of computational tasks produced the demand for new real-time processing systems at experimental facilities. Recently, this demand was addressed by the Spark-MPI approach connecting the Spark data-intensive platform with the MPI high-performance framework. In contrast with existing data management and analytics systems, Spark introduced a new middleware based on resilient distributed datasets (RDDs), which decoupled various data sources from high-level processing algorithms. The RDD middleware significantly advanced the scope of data-intensive applications, spreading from SQL queries to machine learning to graph processing. Spark-MPI further extended the Spark ecosystem with the MPI applications using the Process Management Interface. The paper explores this integrated platform within the context of online ptychographic and tomographic reconstruction pipelines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

TU-D-202-03: Gating Is the Best ITV Killer

Respiratory motion has long been recognized as an important factor affecting the precision of radiotherapy. After the introduction of the 4D CT to visualize the respiratory motion in 3D, the internal target volume (ITV) has been widely adopted as simple method to take the motion into account in treatment planning and delivery. The ITV is generated as the union of the CTVs as the patient goes through the respiratory cycle. Many issues have been identified with the ITV. In this session three alternatives for the ITV will be discussed: 1) An alternative motion-inclusive approach with better imaging and smaller margins, called mid-position CT. 2) The tracking approach and 3) The gating approach. The following topics will be addressed by Marcel van Herk (“Is ITV the correct motion encompassing strategy”): Magnitude of respiratory motion, effect of motion on radiotherapy, motion encompassing strategies, and software solutions to assist in motion encompassing strategies. Then Paul Keall (“Make margins simple: Use real-time target tracking”) will discuss tracking with: clinical drivers for tracking, current clinical status of tumor tracking, future tumor tracking technology, and margin margin challenges with and without tracking. Finally Daniel Low will discuss gating (“Gating is the best ITV killer”): why ITV in the first place, requirements for planning, requirements at the machine, benefits and costs. The session will end with a discussion and live demo of motion simulation software to illustrate the issues and explain the relative benefit and appropriate uses for the three methods. Learning Objectives: Explain the 4D imaging and treatment planning process. Summarize the various approaches to deal with respiratory motion during radiotherapy Discuss the tradeoffs involved when choosing one of the three discussed approaches. Explain in which situation each method is the best choice Research is partly funded by Elekta Oncology Systems and the Dutch Cancer Foundation; M. van Herk, Part of the research was funded by Elekta Oncology Systems and the Dutch Cancer Foundation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Mesoscale Connections Summer 2017

Our challenge derives from the fact that in metals or explosives grains, interfaces and defects control engineering performance in ways that are neither amenable to continuum codes (which fail to rigorously describe the heterogeneities derived from microstructure) nor computationally tractable to first principles atomistic calculations. This is a region called the mesoscale, which stands at the frontier of our desire to translate fundamental science insights into confidence in aging system performance over the range of extreme conditions relevant in a nuclear weapon. For dynamic problems, the phenomena of interest can require extremely good temporal resolutions. A shock wave traveling at 1000 m/s (or 1 mm/μs) passes through a grain with a diameter of 1 micron in a nanosecond (10-9 sec). Thus, to observe the mesoscale phenomena—such as dislocations or phase transformations—as the shock passes, temporal resolution better than picoseconds (10-12 sec) may be needed. As we anticipate the science challenges over the next decade, experimental insights on material performance at the micron spatial scale with picosecond temporal resolution—at the mesoscale— are a clear challenge. This is a challenge fit for Los Alamos in partnership with our sister labs and academia. Mesoscale Connections will draw attention to our progress as we tackle the mesoscale challenge. We hope you like it and encourage suggestions of content you are interested in.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Spatiotemporal Sequence Forecasting Platform to Advance the Prediction of Changing Spatiotemporal Patterns of CO 2 Concentration by Incorporating Human Activity and Hydrological Extremes

Focal Areas (2): Predictive modeling using AI techniques and AI-derived model components. It describes the use of AI and other tools to design a prediction system comprising a hierarchy of models. Specifically, this white paper focuses on the development of a collaborative deep learning platform for evaluating and predicting spatiotemporal relationships between the hydrological and carbon cycles and includes capabilities for considering biogenic and anthropogenic inputs to these systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

An evaluation of the E3SMv1 Arctic ocean and sea-ice regionally refined model

The Energy Exascale Earth System Model (E3SM) is a state-of-the-science Earth system model (ESM) with the ability to focus horizontal resolution of its multiple components in specific areas. Regionally refined global ESMs are motivated by the need to explicitly resolve, rather than parameterize, relevant physics within the regions of refined resolution, while offering significant computational cost savings relative to the respective cost of configurations with high-resolution (HR) everywhere on the globe. In this paper, we document results from the first Arctic regionally refined E3SM configuration for the ocean and sea-ice components (E3SM-Arctic-OSI), while employing data-based atmosphere, land, and hydrology components. Our aim is an improved representation of the Arctic coupled ocean and sea-ice state, its variability and trends, and the exchanges of mass and property fluxes between the Arctic and the sub-Arctic. We find that E3SM-Arctic-OSI increases the realism of simulated Arctic ocean and sea-ice conditions compared to a similar low-resolution E3SM simulation without the Arctic regional refinement in ocean and sea-ice components (E3SM-LR-OSI). In particular, exchanges through the main Arctic gateways are greatly improved with respect to E3SM-LR-OSI. Other aspects, such as the Arctic freshwater content variability and sea-ice trends, are also satisfactorily simulated. Yet, other features, such as the upper-ocean stratification and the sea-ice thickness distribution, need further improvements, involving either more advanced parameterizations, model tuning, or additional grid refinements. Overall, E3SM-Arctic-OSI offers an improved representation of the Arctic system relative to E3SM-LR-OSI, at a fraction (15 %) of the computational cost of comparable global high-resolution configurations, while permitting exchanges with the lower-latitude oceans that cannot be directly accounted for in Arctic regional models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Molecular Electronic Level Alignment at Weakly Coupled Organic Film/Metal Interfaces

Electronic level alignment at interfaces of molecular materials with inorganic semiconductors and metals controls many interfacial phenomena. How the intrinsic properties of the interacting systems define the electronic structure of their interface remains one of the most important problems in molecular electronics and nanotechnology that can be solved through a combination of surface science experimental techniques and theoretical modeling. In this article, we address this fundamental problem through experimental and computational studies of molecular electronic level alignment of thin films of C6F6 on noble metal surfaces. The unoccupied electronic structure of C6F6 is characterized with single molecule resolution using low-temperature scanning tunneling microscopy-based constant-current distance-voltage spectroscopy. The experiments are performed on several noble metal surfaces with different work functions and distinct surface-normal projected band structures. In parallel, the electronic structures of the quantum wells (QWs) formed by the lowest unoccupied molecular orbital state of the C6F6 monolayer and multilayer films and their alignment with respect to the vacuum level of the metallic substrates are calculated by solving the Schrödinger equation for a semiempirical one-dimensional (1D) potential of the combined system using input from density functional theory. Our analysis shows that the level alignment for C6F6 molecules bound through weak van der Waals interactions to noble metal surfaces is primarily defined by the image potential of metal, the electron affinity of the molecule, and the molecule surface distance. We expect the same factors to determine the interfacial electronic structure for a broad range of molecule/metal interfaces.

Environmental Molecular Sciences Laboratory↗