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At least 757 records · Page 42

2HOT: an improved parallel hashed oct-tree n-body algorithm for cosmological simulation

We report on improvements made over the past two decades to our adaptive treecode N-body method (HOT). A mathematical and computational approach to the cosmological N-body problem is described, with performance and scalability measured up to 256k (2 18 ) processors. We present error analysis and scientific application results from a series of more than ten 69 billion (4096 3 ) particle cosmological simulations, accounting for 4 × 10 20 floating point operations. These results include the first simulations using the new constraints on the standard model of cosmology from the Planck satellite. Our simulations set a new standard for accuracy and scientific throughput, while meeting or exceeding the computational efficiency of the latest generation of hybrid TreePM N-body methods.

Computer Science↗

2HOT: An Improved Parallel Hashed Oct-Tree N-Body Algorithm for Cosmological Simulation

We report on improvements made over the past two decades to our adaptive treecode N-body method (HOT). A mathematical and computational approach to the cosmological N-body problem is described, with performance and scalability measured up to 256k (2 18 ) processors. We present error analysis and scientific application results from a series of more than ten 69 billion (4096 3 ) particle cosmological simulations, accounting for 4×10 20 floating point operations. These results include the first simulations using the new constraints on the standard model of cosmology from the Planck satellite. Our simulations set a new standard for accuracy and scientific throughput, while meeting or exceeding the computational efficiency of the latest generation of hybrid TreePM N-body methods.

Warren, Michael S.↗

Evaluation of KDP Estimation Algorithm Performance in Rain Using a Known-Truth Framework

Accurate estimation of specific differential phase ( K DP ) is necessary for rain rate estimation, attenuation correction, and hydrometeor classification algorithms. There are numerous published methods to process polarimetric radar observations of propagation differential phase shift (Φ DP ) and estimate K DP , but the corresponding K DP estimate uncertainty is unquantified. This study provides guidance on how commonly used K DP estimation algorithms perform in various environments. Here, we create numerous synthetic (“true”) K DP profiles, integrate over them to obtain “smoothed” Φ DP , and then add noise typical of S-band operational weather radar measurements. Each algorithm is applied to our noisy Φ DP profiles and compared to the true K DP profile such that the errors and uncertainty are quantified. The synthetic K DP profiles are Gaussian in shape, which allows systematic variations in their magnitude and width to determine how each algorithm performs in smooth, slowly changing K DP profiles, as well as steep profiles. Results demonstrate that algorithm performance is dependent on the Φ DP field received. These results are further supported by an error analysis of each algorithm for two more complicated synthetic K DP profiles. Some K DP algorithms allow users to change various tuning parameters; a subset of these tuning parameters is tested to provide guidance on how changing these parameters impacts algorithm performance. We then provide evidence that our known-truth framework provides insight into algorithm performance in observed data through two case studies.

54 ENVIRONMENTAL SCIENCES↗

Dataset for "Evaluating Deep Learning Approaches for Predictions in Unmonitored Basins with Continental-scale Stream Temperature Models" Willard et al. (2024)

This data release provides all data and code used in the paper " "Evaluating Deep Learning Approaches for Predictions in Unmonitored Basins with Continental-scale Stream Temperature Models" Willard et al. (2024)" to model stream temperature, evaluate, and assess results. The associated manuscript explores current open questions in prediction in ungauged and unmonitored basins concerning top-down versus bottom-up approaches, tradeoffs between data available and input requirements, and the appropriate representation of catchment attributes as inputs to deep learning models. Modeling was done primarily with long short-term memory (LSTM) models, and stream site coverage spans 1362 locations across the conterminous United States. The data is organized into these items items:Code repository and data for the paper " "Evaluating Deep Learning Approaches for Predictions in Unmonitored Basins with Continental-scale Stream Temperature Models" Willard et al. (2024)".Code: stream_temp_ml_regionalization.zip contains the code repositoryData to run the code: - data_dir.zip -- contains all files that should be moved to the "DATA_DIR" variable defined in the "set_env_vars.sh" script in the code repository- metadata_dir.zip -- contains all files that should be moved to the "METADATA_DIR" variable defined in the "set_env_vars.sh" script in the code repository- error_analysis_attribute_and_groundwater_dir.zip - workflows for the extended error analysis by stream attribute and groundwater influenceData produced by the code and used in the paper:- outputs_dir.zip - contains model output and results (outputs_dir/results), model weights (outputs_dir/models), and all other outputs used for the paper including feature importances.To cite this code, please use the following BibTeX or MLA entries:bibtex:@misc{willard2024streamdata, author = {Jared Willard and Fabio Ciulla and Helen Weierbach and Vipin Kumar and Charuleka Varadharajan}, title = {Dataset for "Evaluating Deep Learning Approaches for Predictions in Unmonitored Basins with Continental-scale Stream Temperature Models"}, year = {2024}, doi = {10.15485/2448016}, publisher = {ESS-DIVE Repository}, url = {https://doi.org/10.15485/2448016}}MLA: Willard, Jared, et al. Dataset for "Evaluating Deep Learning Approaches for Predictions in Unmonitored Basins with Continental-scale Stream Temperature Models". 2024. ESS-DIVE Repository, doi:10.15485/2448016.

54 ENVIRONMENTAL SCIENCES↗

Persuasive Influence Detection: The Role of Argument Sequencing

Automatic detection of persuasion in online discussion is key to understanding how social media is used. Predicting persuasiveness is difficult, however, due to the need to model world knowledge, dialogue, and sequential reasoning. Here, we focus on modeling the sequence of arguments in social media posts using neural models with embeddings for words, discourse relations, and semantic frames. We demonstrate significant improvement over prior work in detecting successful arguments. We also present an error analysis assessing novice human performance at predicting persuasiveness.

99 GENERAL AND MISCELLANEOUS↗

CrossCheck: Rapid, Reproducible, and Interpretable Model Evaluation

Evaluation beyond aggregate performance metrics, e.g. F1-score, is crucial to both establish an appropriate level of trust in machine learning models and identify future model improvements. In this paper we demonstrate CrossCheck, an interactive visualization tool for rapid crossmodel comparison and reproducible error analysis. We describe the tool and discuss design and implementation details. We then present three use cases (named entity recognition, reading comprehension, and clickbait detection) that show the benefits of using the tool for model evaluation. CrossCheck allows data scientists to make informed decisions to choose between multiple models, identify when the models are correct and for which examples, investigate whether the models are making the same mistakes as humans, evaluate models’ generalizability and highlight models’ limitations, strengths and weaknesses. Furthermore, CrossCheck is implemented as a Jupyter widget, which allows rapid and convenient integration into data scientists’ model development workflows.

Arendt, Dustin L.↗

A biofilm microreactor system for simultaneous electrochemical and nuclear magnetic resonance techniques

In order to fully understand electrochemically active biofilms and the limitations to their scale-up in industrial biofilm reactors, a complete picture of the microenvironments inside the biofilm is needed. Nuclear magnetic resonance (NMR) techniques are ideally suited for the study of biofilms and for probing their microenvironments because these techniques allow for non-invasive interrogation and in situ monitoring with high resolution. By combining NMR with simultaneous electrochemical techniques, it is possible to sustain and study live electrochemically active biofilms. Here, we introduce a novel biofilm microreactor system that allows for simultaneous electrochemical and NMR techniques (EC-NMR) at the microscale. Microreactors were designed with custom radiofrequency resonator coils, which allowed for NMR measurements of biofilms growing on polarized gold electrodes. For an example application of this system, we grew Geobacter sulfurreducens biofilms. NMR was used to investigate growth media flow velocities, which were compared to simulated laminar flow, and electron donor concentrations inside the biofilms. We use Monte Carlo error analysis to estimate standard deviations of the electron donor concentration measurements within the biofilm. The EC-NMR biofilm microreactor system can ultimately be used to correlate extracellular electron transfer rates with metabolic reactions and explore extracellular electron transfer mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CBP Toolbox Version 2.0: Code Integration Enhancements

This report describes enhancements made to code integration aspects of the Cementitious Barriers Project (CBP) Toolbox as a result of development work performed at the Savannah River National Laboratory (SRNL) in collaboration with Vanderbilt University (VU) in the first half of fiscal year 2013. Code integration refers to the interfacing to standalone CBP partner codes, used to analyze the performance of cementitious materials, with the CBP Software Toolbox. The most significant enhancements are: 1) Improved graphical display of model results. 2) Improved error analysis and reporting. 3) Increase in the default maximum model mesh size from 301 to 501 nodes. 4) The ability to set the LeachXS/Orchestra simulation times through the GoldSim interface. These code interface enhancements have been included in a new release (Version 2.0) of the CBP Toolbox.

36 MATERIALS SCIENCE↗

A Method for the Quantification of Model Form Error Associated with Physical Systems

In the process of model validation, models are often declared valid when the differences between model predictions and experimental data sets are satisfactorily small. However, little consideration is given to the effectiveness of a model using parameters that deviate slightly from those that were fitted to data, such as a higher load level. Furthermore, few means exist to compare and choose between two or more models that reproduce data equally well. These issues can be addressed by analyzing model form error, which is the error associated with the differences between the physical phenomena captured by models and that of the real system. This report presents a new quantitative method for model form error analysis and applies it to data taken from experiments on tape joint bending vibrations. Two models for the tape joint system are compared, and suggestions for future improvements to the method are given. As the available data set is too small to draw any statistical conclusions, the focus of this paper is the development of a methodology that can be applied to general problems.

97 MATHEMATICS AND COMPUTING↗

Susceptibility Study of Audio Recording Devices to Electromagnetic Stimulations

Little research has been performed to study how intentional electromagnetic signals may couple into recording devices. An electromagnetic susceptibility study was performed on an analog tape recorder, a digital video camera, a wired computer microphone, and a wireless microphone system to electromagnetic interference. Devices were subjected to electromagnetic stimulations in the frequency range of 1-990 MHz and field strengths up to 4.9 V/m. Carrier and message frequencies of the stimulation signals were swept, and the impacts of device orientation and antenna polarization were explored. Message signals coupled into all devices only when amplitude modulated signals were used as stimulation signals. Test conditions that produced maximum sensitivity were highly specific to each device. Only narrow carrier frequency ranges could be used for most devices to couple messages into recordings. A basic detection technique using cross-correlation demonstrated the need for messages to be as long as possible to maximize message detection and minimize detection error. Analysis suggests that detectable signals could be coupled to these recording devices under realistic ambient conditions.

42 ENGINEERING↗

Arbitrary Dimension Convection-Diffusion Schemes for Space-Time Discretizations

This note proposes embedding a time dependent PDE into a convection-diffusion type PDE (in one space dimension higher) with singularity, for which two discretization schemes, the classical streamline-diffusion and the EAFE (edge average finite element) one, are investigated in terms of stability and error analysis. The EAFE scheme, in particular, is extended to be arbitrary order which is of interest on its own. Numerical results, in combined space-time domain demonstrate the feasibility of the proposed approach.

97 MATHEMATICS AND COMPUTING↗

Centralized Activities in Support of the Radiative Forcing Model Intercomparison Project

A new paradigm in benchmark absorption-scattering radiative transfer is presented that enables both the globally-averaged and spatially-resolved testing of climate model radiation parameterizations using a novel benchmark computational strategy to uncover persistent sources of biases in the aerosol Instantaneous Radiative Effect (IRE). A proof-of-concept is demonstrated with the GFDL AM4 and CESM 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to a highly accurate radiation solver to uncover relevant biases unique to each climate model. These diagnostic results show that the models’ aerosol IRE bias is of the same magnitude as the persistent intermodel spread (~1 W/m2), and varies spatially and with intrinsic aerosol optical properties. The findings underscore the significance of native model error analysis and its ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project (RFMIP).

58 GEOSCIENCES↗

The NSLS-II Control Network Design

The required positioning tolerances are an essential part of the survey and alignment design. The following tables show the requirement of storage ring. Table 1 provides the required global tolerances, while Table 2 outlines the relative tolerances for the NSLS-II girder-to-girder positioning. These tolerances dictate the instruments and methods necessary to obtain the positioning goals. The global tolerance is a little bit relaxed, but the ± 0.10 mm positioning requirement of adjacent girders is rather strict if the larger dimension and probable foundation settlement is considered. control network. Therefore, whether the goals can be obtained is mainly dependent on the performance of control network. The shape of control network defines the global alignment accuracy, while the relative position relationships of monuments determine the relative positioning accuracy between girders. When deciding the strategy of survey and alignment techniques, the instrumentation and approach of light sources have been built and are still in construction are investigated. State-of-the art equipment and methods will be employed. NSLS-II covers an area of about one-eighth of a square kilometer with a radius of ~126 m and a circumference of ~792 m. Depending on the size of the system to be constructed, primary and secondary control networks are required to achieve these tolerances. Primary control network will provide global control for different tunnels, and it should possess a relative point accuracy of better than ± 3 mm for all the storage ring monuments. Secondary control network will direct the alignment of girders in tunnel with the ability to ensure the final ± 0.10 mm positioning accuracy. The experiences from accomplished light source indicate that: for a dimension like NSLS2, primary control network can obtain a point accuracy of better than ± 1 mm easily, while secondary control network can obtain a relative point accuracy of ± 0.08 mm. With this expectation, the tolerance can be achieved for both the global and relative situation. Take the relative positioning requirement as an example, with 2 control network error of ± 0.08 mm, instrument tie-in error of ± 0.04 mm, and residual error of ± 0.04 mm, according to error propagation formula, the final alignment error should be better than ± 0.1 mm. Correspondingly, if a better control network accuracy can be achieved, the requirement for the residuals can be looser. The further alignment accuracy improvement will be realized by a smoothing process to assure the better position relationship between adjacent girders. The following simulation will perform error analysis to evaluate the estimated accuracy of NSLS II control network.

36 MATERIALS SCIENCE↗

Pressurizing Hagan and SAVY containers to 30-psig (air) to measure the release of analytical cerium oxide test powder

The need to pressure-test known nuclear material storage containers has been made apparent by the CSE (cognizant systems engineer) assigned to containers at TA-55. The main goal of the current study is to understand the behavior of the SAVY-4000 and Hagan containers during an internal pressurization (30 psig) event. The experiments incorporated a nominal mass of 100 g of CeO 2 (cerium oxide) powder to simulate MAR (material at risk) conditions. For the experimental results with mass losses of 0.0±0.1 g mass loss), using ASME error analysis, there is a total expanded uncertainty in a 95% confidence interval (±0.25 g) for the tested SAVY-4000 and Hagan containers. For purposes of conservatism, this has been rounded upward to yield a bounding value for the damage ratio DR = 0.003 = 0.3%.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Quarter 4 Report: Report on Final Findings and Opportunities for Future Work in the Use of Mixed Precision in Iterative Solvers

The fourth quarter of the project was spent developing an error analysis of the s-step Lanczos and CG algorithms. Our theoretical bounds and numerical experiments show that the numerical behavior of the algorithm can be significantly improved by using extra precision in a small part of the computation related to the computation and application of the Gram matrix. We have published a technical report which includes all steps of the analysis [8]; a shortened version for journal submission is in preparation. We plan to submit this paper in the following weeks. Activities related to this also include a collaboration with Ichitaro Yamazaki on gathering performance results for these new mixed precision s-step Krylov subspace methods using single/double precision on GPUs. Namely, we would like to obtain performance results that show that the performance overhead of using double the working precision in these select computations is minimal. Other activities include attending biweekly xSDK meetings and presenting a pitch talk on this work to the group on February 25, 2021. In the remainder of the document, we summarize our findings on the potential for mixed precision in classical Krylov subspace methods and s-step Krylov subspace methods, as well as key opportunities for future work.

97 MATHEMATICS AND COMPUTING↗

ASCEND: Asymptotically compatible strong form foundations for nonlocal discretization

Nonlocal models naturally handle a range of physics of interest to SNL, but discretization of their underlying integral operators poses mathematical challenges to realize the accuracy and robustness commonplace in discretization of local counterparts. This project focuses on the concept of asymptotic compatibility, namely preservation of the limit of the discrete nonlocal model to a corresponding well-understood local solution. We address challenges that have traditionally troubled nonlocal mechanics models primarily related to consistency guarantees and boundary conditions. For simple problems such as diffusion and linear elasticity we have developed complete error analysis theory providing consistency guarantees. We then take these foundational tools to develop new state-of-the-art capabilities for: lithiation-induced failure in batteries, ductile failure of problems driven by contact, blast-on-structure induced failure, brittle/ductile failure of thin structures. We also summarize ongoing efforts using these frameworks in data-driven modeling contexts. This report provides a high-level summary of all publications which followed from these efforts.

97 MATHEMATICS AND COMPUTING↗

GraphAlign: Graph-Enabled Machine Learning for Seismic Event Filtering

This report summarizes results from a 2 year effort to improve the current automated seismic event processing system by leveraging machine learning models that can operated over the inherent graph data structure of a seismic sensor network. Specifically, the GraphAlign project seeks to utilize prior information on which stations are more likely to detect signals originating from particular geographic regions to inform event filtering. To date, the GraphAlign team has developed a Graphical Neural Network (GNN) model to filter out false events generated by the Global Associator (GA) algorithm. The algorithm operates directly on waveform data that has been associated to an event by building a variable sized graph of station waveforms nodes with edge relations to an event location node. This builds off of previous work where random forest models were used to do the same task using hand crafted features. The GNN model performance was analyzed using an 8 week IMS/IDC dataset, and it was demonstrated that the GNN outperforms the random forest baseline. We provide additional error analysis of which events the GNN model performs well and poorly against concluded by future directions for improvements.

58 GEOSCIENCES↗

Doppler-Free Saturation Spectroscopy (DFSS) for Magnetic and Electric Field Measurements in an FRC plasma

The Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and TAE Technologies (TAE) focused on a feasibility study of Doppler-free saturation spectroscopy (DFSS) as a diagnostic strategy to measure the internal magnetic and electric fields of TAE’s C-2W field-reversed configuration (FRC) fusion device. Non-perturbative measurements of magnetic and electric fields in the core of FRCs can provide critical information needed to constrain equilibrium models and for the continued advancement of the fusion research program at TAE. DFSS is a well-established, laser-based absorption spectroscopy technique used to suppress inhomogeneous (Doppler) broadening linewidths and reveal Zeeman/Stark split hyperfine structures of target emission lines. The collaboration involved the use of ORNL’s suite of experimentally validated quantum mechanical modelling codes to simulate theoretical atomic spectra for a variety of machine parameters and laser beam configurations. TAE’s expertise was heavily used to provide measurements/models of the required machine parameters needed as inputs to the simulations. Results of an all-encompassing error analysis demonstrate the favourable capabilities of the diagnostic and provided invaluable insights as to how DFSS can be best used to accurately measure internal B/E-fields in C-2W.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗