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Results for “ACCURACY”
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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Modeling protein structures from predicted contacts with modern molecular dynamics potentials: accuracy, sensitivity, and refinement
Protein structure prediction has become increasingly popular and successful in recent years. An essential step for fragment-free, template-free methods is the generation of a final three-dimensional protein model from a set of predicted amino acid contacts that are often described by interresidue pairwise atomic distances. Here we explore the use of modern, open-source molecular dynamics (MD) engines, which have been continually developed over the last three decades with all-atom Hamiltonians to model biomolecular structure and dynamics, to generate accurate protein structures starting from a set of inferred pairwise distances. Additionally, the ability of MD empirical physical potentials to correct inaccuracies in the predicted geometries is tested. We rigorously characterize the effect of modeling parameters on results, the effect of different amounts of error in the predicted distances on the final structures, and test the ability of post-processing analysis to sort the best models out of a set of statistical replicas. We find that with exact distances and with noisy distances, the method can produce excellent structural models, and that the molecular dynamics force field seems to help correct errors in distance predictions, resisting the effects of applied noise.
RAPIDS: Reconciling Availability, Accuracy, and Performance in Managing Geo-Distributed Scientific Data
In modern science, big data plays an increasingly important role. Many scientific applications, such as running simulations on supercomputers or conducting experiments on advanced instruments, produce huge amount of data at unprecedented speed. Analyzing and understanding such big data is the key for scientists to make scientific breakthroughs. However, data might become unavailable for scientists to access when outages or maintenance of the storage system occur, which severely hinders scientific discovery. To improve the data availability, data duplication and erasure coding (EC) are often used. But as the scientific data gets larger, using these two methods can cause considerable storage and network overhead.In this paper, we propose RAPIDS, a hybrid approach that combines the multigrid-based error-bounded lossy compression with erasure coding, to significantly reduce the storage and network overhead required for maintaining high data availability. Our experiments show that RAPIDS reduces the storage overhead by up to 7.5x and network overhead by up to 3x to achieve the same level of availability compared to the regular EC method. We improve RAPIDS by building two models to optimize the fault tolerance configurations and data gathering strategy. We demonstrate that RAPIDS significantly improves performance when running on many CPU cores in parallel or on GPUs.
Improved accuracy of S-value-based dosimetry: a guide to transition from Cristy–Eckerman to ICRP adult phantoms
Background: In 2016, the International Commission on Radiological Protection (ICRP) published the results of Monte Carlo simulations performed using updated and anatomically realistic voxelized phantoms. The resulting specific absorbed fractions are based on more realistic human anatomy than those computed in the stylized, geometrical Cristy–Eckerman (CE) phantom. Despite this development, the ICRP-absorbed fractions have not been widely adopted for radiopharmaceutical dosimetry. To help make the transition, we have established a correspondence between source and target tissues defined in the CE phantom and those defined in the ICRP phantoms. Results: The ICRP phantom has 79 source regions and 43 target regions in comparison with the 23 source and 18 target tissue regions defined in the CE phantom. The ICRP phantom provides tissue regions with greater anatomical detail. Some of this additional detail is focused on radiation protection and dosimetry of inhaled/ingested radioactivity. Some, but not all, of this detail is useful and appropriate for radiopharmaceutical therapy. We have established the correspondence between CE and ICRP phantom source and target regions and attempted to highlight the ICRP source tissues relevant to radiopharmaceutical therapy (RPT). This paper provides tables and figures highlighting the correspondences established. Conclusion: The results provide assistance in transitioning from CE-stylized phantoms to the anatomically accurate voxelized ICRP phantoms. It provides specific guidance for porting the total absorbed activity for regions as defined in the CE phantom to regions within the ICRP phantoms.
Threshold Analysis of Modelling and Measurement Accuracies in Muon Scattering Tomography
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Multi-pitch self-calibration measurement using a nano-accuracy surface profiler for X-ray mirror metrology
Not Available
Accuracy of High Explosive Data used for Reactive Burn Model Calibration
Reactive burn models for a high explosive (HE) have three components: an equation of state (EOS) for the products, an EOS for the reactants and a reaction rate. For the products, we discuss the uncertainty in data for the planar detonation state and its release isentrope. For the reactants, the uncertainty in the principal shock locus data is discussed. For the reaction rate, we discuss uncertainties in shock initiation data (distance-of-run to detonation as a function of shock pressure), and curvature effect data (detonation speed as a function of front curvature). An important source of uncertainty for calibrating the reaction rate for a plastic-bonded explosive (PBX) results from variations in heterogeneities; that is the mesoscale structure of HE grains, binder and porosity. This shows up in the scatter of both shock initiation data and curvature effect data with small changes in initial density and initial temperature, and systematic changes with PBX lot. As illustrative examples, we use data for the conventional HMX based PBX 9501 and the insensitive TATB based PBX 9502 since these explosives have been extensively studied and high quality data are readily available in the literature.
AI-Improved Resolution Projections of Population Characteristics and Imperviousness Can Improve Resolution and Accuracy of Urban Flood Predictions
Focal Area: (2) Predictive modeling through the use of AI techniques and AI-derived model components. Specifically, we call for the use of deep generative models from ML for providing high-resolution projections of impervious surface area, as well as neural network solvers for fast approximation of urban hydrodynamics to provide greatly enhanced forecasts of future urban flood dynamics.
LUNA Condition-Based Monitoring Update: Random Forest and Mahalanobis Ensemble Accuracy Crossover Point [Slides]
Abstract not provided.
LUNA Condition-Based Monitoring Update: Random Forest and Mahalanobis Ensemble Accuracy Crossover Point
Abstract not provided.
High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace
The US manufacturing industry produces about 1.3 million tons of refined lead each year using secondary sources consisting mainly of lead batteries. ORNL is partnering with Gopher resource, the second largest lead recycling company in the United States, and GTI, to develop a high-fidelity CFD model of a directly fired, reverberatory-style, secondary lead furnace. These High Performance Computing (HPC) simulations are aimed to use first principles modeling for combustion and melting processes of the secondary lead feed while accounting for complex interphase interactions between the gas, solid charge (lead) material, slag, and metal phases. Through validation against operating plant data, this effort will enable significant improvements in design, operational parameters, and energy efficiency, thus improving productivity and refractory lifetime of secondary lead melting furnaces. Estimated savings/reduction of, at least, 1 trillion BTU, 1 million ton/year of greenhouse gas emissions, and $\$50$ million/year to the US lead industry can be expected. ORNL resources and expertise in high-performance computing and multicomponent, multiphase flows were utilized to realize this goal while advancing the understanding of the smelting and melting processes occurring within the furnace.
Using machine learning to improve efficiency and accuracy of burnup measurements at PBR reactors [Slides]
The outline of the slides include: Motivations of the work; Modeling and simulation; Machine learning model; Results and comparison study with linear regression; and Conclusions. This work was done to help PBR designers and operators understand the burnup measurement better. We look forward to discussing the results in detail with industrial collaborators.
Increasing the accuracy of cold Fe opacity measurements to help resolve the Fe solar opacity puzzle.
Abstract not provided.
A High-Accuracy Technique to Measure the Phase-Space of a Dispersive Particle Beam
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Increasing the accuracy of cold Fe opacity measurements to help resolve the Fe solar.
Abstract not provided.
Improving accuracy and reducing computational cost in ab initio simulations of aqueous-interfaces for photocatalysis and electrochemistry (Final Report)
Our outcome in the past cycle are detailed in the papers [1–8]. Here we discuss the developments which are most relevant to the proposed work below.
Assessing the Accuracy of a Borehole-Controlled Velocity Model of Yucca Flat Nevada Using Large-N Seismic Data.
Abstract not provided.
Improving the Accuracy of Modeling/Simulation Solvers to Better Understand the Impact of Inverter-Based Resources and other Fast Dynamics on Power Grids.
Abstract not provided.