Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data Intensive Computing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Big Data Ecosystems Enable Scientific Discovery

Over the past 5 years, advances in experimental, sensor and computational technologies have driven the exponential growth in the volumes, acquisition rates, variety and complexity of scientific data. As noted by Hey et al in their 2009 e-book The Fourth Paradigm, this availability of large-quantities of scientifically meaningful data has given rise to a new scientific methodology - data intensive science. Data intensive science is the ability to formulate and evaluate hypotheses using data and analysis to extend, complement and, at times, replace experimentation, theory, or simulation. This new approach to science no longer requires scientists to interact directly with the objects of their research; instead they can utilize digitally captured, reduced, calibrated, analyzed, synthesized and visualized results - allowing them carry out 'experiments' in data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

FrESCO: Framework for Exploring Scalable Computational Oncology

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information from electronic health records. This data is then used to create summary statistics about cancer incidence and mortality to facilitate population health monitoring. Extracting phenotypic information from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating the information extraction process from cancer pathology reports has the potential to improve data quality by extracting information in a consistent manner across registries. It can also improve patient outcomes by reducing the time from diagnosis, enabling rapid case ascertainment for clinical trials. Here we present FrESCO, a modular deep-learning natural language processing (NLP) library initially designed for extracting pathology information from clinical text documents. This repository is not solely limited to clinical medical text, but may also be used by researchers just getting started with NLP methods and those looking for a robust solution for their classification problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Metal hydride differential scanning calorimetry as an approach to compositional determination of mixtures of hydrogen isotopologues and helium

Gaseous mixtures of diatomic hydrogen isotopologues and helium are often encountered in the nuclear energy industry and in analytical chemistry. Compositions of stored mixtures can vary due to interactions with storage and handling materials. When tritium is present, it decays to form ions and helium-3, both of which can lead to further compositional variation. Monitoring of composition is typically achieved by mass spectrometry, a method that is bulky and energy-intensive. Mass spectrometers disperse sample material through vacuum pumps, which is especially troublesome if tritium is present. Moreover, our ultimate goal is to create a compact, fast, low-power sensor that can determine composition with minimal gas consumption and waste generation, as a complement to mass spectrometry that can be instantiated more widely. We propose calorimetry of metal hydrides as an approach to this, due to the strong isotope effect on gas absorption, and demonstrate the sensitivity of measured heat flow to atomic composition of the gas. Peak shifts are discernible when mole fractions change by at least 1%. A mass flow restriction results in a unique dependence of the measurement on helium concentration. We present a mathematical model as a first step toward prediction of the peak shapes and positions. The model includes a useful method to compute estimates of phase diagrams for palladium in the presence of arbitrary mixtures of hydrogen isotopologues. As a result, we expect that this approach can be used to deduce unknown atomic compositions from measured calorimetric data over a useful range of partial pressures of each component.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Theoretical level energies, radiative lifetimes and transitions in W IX

The atomic states of the W IX (W{sup 8+}) tungsten ion lying below the W{sup 9+} ionisation threshold have been studied theoretically, employing the multiconfiguration Dirac–Hartree–Fock method with configuration interaction. The level electronic structures and their energies are presented. The electric dipole (E1), magnetic dipole (M1), electric quadrupole (E2), and magnetic quadrupole (M2) radiative transitions have been computed in order to calculate the radiative lifetimes of given states. Transition wavelengths, energies, and decay rates are also presented for selected high-intensity E1 transitions. The configuration interaction method was applied to estimate electron correlation effects. The aim of the present research was to fill a lack of atomic data for low-charged tungsten ions, which may be useful in low-temperature plasma diagnostics and may form the base for collisional–radiative modelling of spectra for low-charged tungsten ions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Sparse modeling of space- and time-varying diffraction response of a progressively loaded aluminum alloy

Highlights: • Plasticity induces crystal orientation and lattice spacing heterogeneity. • High energy x-ray diffraction spot broadening typically accompanies plasticity. • Method quantifies spot broadening in difficult, mixed microstructure data. • Algorithm finds sparse combination of entries from dictionary of peak functions. • Approach showed asymmetric plastic response in preprocessed AA7075 T651 sample. - Abstract: High energy X-ray diffraction data collected in situ during loading experiments permits probing of the crystal structure of a plastically deforming material sample. An elastoplastic deformation is associated with heterogeneity in both crystal orientation and lattice spacing—each manifesting as azimuthal broadening and radial broadening of diffraction peaks respectively. Quantifying the spreading effect is challenging, especially in cases where the sample has a granularity between that of a single crystal and fine grain or powder material. The approach developed in this paper begins by modeling the intensity signal in the vicinity of a Debye-Scherrer ring as a sparse, nonnegative superposition of Gaussian basis functions drawn from an over-complete dictionary. Processing automatically selects from the dictionary basis functions whose widths and amplitudes are representative of the data. The chosen basis functions are used to compute scalar measures of radial and azimuthal broadening for the set of diffraction peaks composing a Debye-Scherrer ring. To demonstrate the utility of the approach, we show that analysis of diffraction peak shape information from an aluminum alloy 7075 T651 (AA7075 T651) sample provides insight into the origin of material state that would have otherwise have been difficult if not impossible to extract using conventional methods. Furthermore, the extracted information revealed a deformation response linked to the processing history of the sample.

36 MATERIALS SCIENCE↗
DOE OSTI2014

SU-E-T-63: Carotid Sparing Tomohelical Three Dimensional Conformal Radiotherapy for T1N0 Glottic Cancer

Purpose: We investigated the dosimetric benefit and treatment efficiency of carotid-sparing TomoHelical (TH) three-dimensional conformal radiotherapy (3DCRT) for early glottic cancer. Methods: Computed tomography (CT) simulation was performed for 10 patients with early-stage (T1N0M0) glottic squamous cell carcinoma. The clinical target volume, planning target volume (PTV), carotid artery (CA), and spinal cord (SP) were delineated for each CT data set. Two-field 3DCRT (2F-3DCRT), three-field intensity-modulated radiation therapy (IMRT) (3F-IMRT), TomoHelical-IMRT (TH-IMRT), and TH-3DCRT plans were generated, with a total prescribed dose of 67.5 Gy in 30 fractions to the PTV for each patient. In order to evaluate plan quality, dosimetric characteristics were compared in terms of the conformity index (CI) and homogeneity index (HI) for the PTV, V35, V50, and V63 for the CAs and in terms of the maximum dose for the SP. Additionally, treatment planning and delivery times were compared to evaluate treatment efficiency. Results: The CIs for 3F-IMRT (0.650±0.05), TH-IMRT (0.643±0.03), and TH-3DCRT (0.631±0.03) were much better than that for 2F-3DCRT (0.318±0.03). The HIs for TH-IMRT (1.053±0.01) and TH-3DCRT (1.055±0.01) were slightly better than those for 2F-3DCRT (1.062±0.01) and 3F-IMRT (1.091±0.007). 2F-3DCRT showed poor CA sparing in terms of the V35, V50, and V63 compared to 3F-IMRT, TH-IMRT, and TH-3DCRT (p<0.05), whereas there was no significant dose difference between 3F-IMRT, TH-IMRT, and TH-3DCRT (p>0.05). The maximum dose to the SP with all plans was below 45 Gy. The treatment planning times for 2F-3DCRT (5.9±0.66 min) and TH-3DCRT (7.32±0.94 min) were much lower than those for 3F-IMRT (45.51±2.76 min) and TH-IMRT (35.58±4.41 min), whereas the delivery times with all plans was below 3 minutes. Conclusion: TH-3DCRT showed excellent carotid sparing capability, comparable to that with TH-IMRT, with high treatment efficiency and short planning and treatment times, comparable to those for 2F-3DCRT, while maintaining good PTV coverage. This work was supported by the Technology Innovation Program, 10040362, Development of an integrated management solution for radiation therapy funded by the Ministry of Knowledge Economy (MKE, Korea)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2010

Center for Advanced Modeling and Simulation Intern

Some interns just copy papers and seal envelopes. Not at INL! Check out how Vanessa Gertman, an INL intern working at the Center for Advanced Modeling and Simulation, spent her summer working with some intense visualization software. Lots more content like this is available at INL's facebook page http://www.facebook.com/idahonationallaboratory.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Oncentra brachytherapy planning system

In modern cancer management, treatment planning has progressed as a contemporary tool with all the advances in computing power in recent years. One of the advanced planning tools uses 3-dimensional (3D) data sets for accurate dose distributions in patient prescription. Among these planning processes, brachytherapy has been a very important part of a successful cancer management program, offering clinical benefits with specific or combined treatments with external beam therapy. In this chapter, we mainly discussed the Elekta Oncentra planning system, which is the main treatment planning tool for high-dose rate (HDR) modality in our facility and in many other facilities in the United States. HDR is a technically advanced form of brachytherapy; a high-intensity radiation source (3.6 mm in length) is delivered with step motor in submillimeter precision under computer guidance directly into the tumor areas while minimizing injury to surrounding normal healthy tissue. Oncentra planning is the key component to generate a deliverable brachytherapy procedure, which is executed on the microSelectron V3 remote afterloader treatment system. Creating a highly conformal plan can be a time-consuming task. The development of Oncentra software (version 4.5.3) offers a variety of useful tools that facilitate many of the clinical challenging tasks for planning, such as contouring and image reconstruction, as well as rapid planning calculations with dose and dose volume histogram analysis. Oncentra Brachy module creates workflow and optimizes the planning accuracy for wide varieties of clinical HDR treatments, such as skin, gynecologic (GYN), breast, prostate, and many other applications. The treatment file can also be transferred to the afterloader control station for speedy delivery. The design concept, calculation algorithms, and optimization modules presented some key characteristics to plan and treat the patients effectively and accurately. The dose distribution and accuracy of several clinical sample cases were discussed to illustrate the effectiveness and clinical efficacy. The American Association of Physicists in Medicine brachytherapy reports of TG-43 and TG-186 were also described and compared in evaluations of fundamental calculation methodologies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Toward Accelerating Discovery via Physics-Driven and Interactive Multifidelity Bayesian Optimization

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often nondifferentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or time consuming to evaluate a single instance, and hence classical approaches based on exhaustive grid or random search are too data intensive. This resulted in strong interest toward active learning methods such as Bayesian optimization (BO) where the adaptive exploration occurs based on human learning (discovery) objective. However, classical BO is based on a predefined optimization target, and policies balancing exploration and exploitation are purely data driven. In practical settings, the domain expert can pose prior knowledge of the system in the form of partially known physics laws and exploration policies often vary during the experiment. Here, we propose an interactive workflow building on multifidelity BO (MFBO), starting with classical (data-driven) MFBO, then expand to a proposed structured (physics-driven) structured MFBO (sMFBO), and finally extend it to allow human-in-the-loop interactive interactive MFBO (iMFBO) workflows for adaptive and domain expert aligned exploration. These approaches are demonstrated over highly nonsmooth multifidelity simulation data generated from an Ising model, considering spin–spin interaction as parameter space, lattice sizes as fidelity spaces, and the objective as maximizing heat capacity. Detailed analysis and comparison show the impact of physics knowledge injection and real-time human decisions for improved exploration with increased alignment to ground truth. Here, the associated notebooks allow to reproduce the reported analyses and apply them to other systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Predicting wind farm operations with machine learning and the P2D‐RANS model: A case study for an AWAKEN site

Abstract The power performance and the wind velocity field of an onshore wind farm are predicted with machine learning models and the pseudo‐2D RANS model, then assessed against SCADA data. The wind farm under investigation is one of the sites involved with the American WAKE experimeNt (AWAKEN). The performed simulations enable predictions of the power capture at the farm and turbine levels while providing insights into the effects on power capture associated with wake interactions that operating upstream turbines induce, as well as the variability caused by atmospheric stability. The machine learning models show improved accuracy compared to the pseudo‐2D RANS model in the predictions of turbine power capture and farm power capture with roughly half the normalized error. The machine learning models also entail lower computational costs upon training. Further, the machine learning models provide predictions of the wind turbulence intensity at the turbine level for different wind and atmospheric conditions with very good accuracy, which is difficult to achieve through RANS modeling. Additionally, farm‐to‐farm interactions are noted, with adverse impacts on power predictions from both models.

17 WIND ENERGY↗
DOE OSTI2012

Effect of beam arrangement on oral cavity dose in external beam radiotherapy of nasopharyngeal carcinoma

This study compared the oral cavity dose between the routine 7-beam intensity-modulated radiotherapy (IMRT) beam arrangement and 2 other 7-beam IMRT with the conventional radiotherapy beam arrangements in the treatment of nasopharyngeal carcinoma (NPC). Ten NPC patients treated by the 7-beam routine IMRT technique (IMRT-7R) between April 2009 and June 2009 were recruited. Using the same computed tomography data, target information, and dose constraints for all the contoured structures, 2 IMRT plans with alternative beam arrangements (IMRT-7M and IMRT-7P) by avoiding the anterior facial beam and 1 conventional radiotherapy plan (CONRT) were computed using the Pinnacle treatment planning system. Dose-volume histograms were generated for the planning target volumes (PTVs) and oral cavity from which the dose parameters and the conformity index of the PTV were recorded for dosimetric comparisons among the plans with different beam arrangements. The dose distributions to the PTVs were similar among the 3 IMRT beam arrangements, whereas the differences were significant between IMRT-7R and CONRT plans. For the oral cavity dose, the 3 IMRT beam arrangements did not show significant difference. Compared with IMRT-7R, CONRT plan showed a significantly lower mean dose, V30 and V-40, whereas the V-60 was significantly higher. The 2 suggested alternative beam arrangements did not significantly reduce the oral cavity dose. The impact of varying the beam angles in IMRT of NPC did not give noticeable effect on the target and oral cavity. Compared with IMRT, the 2-D conventional radiotherapy irradiated a greater high-dose volume in the oral cavity.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Online and Scalable Data Compression Pipeline with Guarantees on Quantities of Interest

Data compression is becoming critical for data-intensive scientific applications. Scientists require compression techniques that accurately preserve derived quantities of interest (QoIs). Prior work has shown that a pipeline can be built to guarantee error on the primary data (PD) within user-defined bounds and achieve near-floating point QoI errors. In this paper, we present novel computational approaches for accelerating the pipeline and demonstrate results that enable concurrent execution of compression in parallel with the simulation nodes. This allows compression, including the writing of the required compression data, for the previous time step to be completed while the simulation proceeds with the current time step. Overall, the approach presented in this paper results in a 6–8 times improvement in computational overhead compared to previous work. These results were obtained using data generated by a large-scale fusion code called XGC, which produces hundreds of terabytes of data in a single day.

Banerjee, Tania↗
DOE OSTI2025

Block Island Noise Modeling Data

Noise propagation near Block Island was simulated to assess environmental impacts of impact pile driving during wind turbine construction. Computational models complement field-recorded acoustic data, providing insights into sound attenuation, spectral variability, and propagation dynamics. The dataset includes: 1. Propagation Models: Simulated underwater sound fields documenting sound pressure and directional variability across frequency bands and distances. 2. Spectral Analysis (LTSA): Long-term averages and processed outputs calculating acoustic intensity over time. 3. Visualization Files: Graphs, 2D/3D simulation results, and reference calculations used in sound modeling.

17 WIND ENERGY↗
DOE OSTI2014

Towards the clinical implementation of iterative low-dose cone-beam CT reconstruction in image-guided radiation therapy: Cone/ring artifact correction and multiple GPU implementation

Purpose: Compressed sensing (CS)-based iterative reconstruction (IR) techniques are able to reconstruct cone-beam CT (CBCT) images from undersampled noisy data, allowing for imaging dose reduction. However, there are a few practical concerns preventing the clinical implementation of these techniques. On the image quality side, data truncation along the superior–inferior direction under the cone-beam geometry produces severe cone artifacts in the reconstructed images. Ring artifacts are also seen in the half-fan scan mode. On the reconstruction efficiency side, the long computation time hinders clinical use in image-guided radiation therapy (IGRT). Methods: Image quality improvement methods are proposed to mitigate the cone and ring image artifacts in IR. The basic idea is to use weighting factors in the IR data fidelity term to improve projection data consistency with the reconstructed volume. In order to improve the computational efficiency, a multiple graphics processing units (GPUs)-based CS-IR system was developed. The parallelization scheme, detailed analyses of computation time at each step, their relationship with image resolution, and the acceleration factors were studied. The whole system was evaluated in various phantom and patient cases. Results: Ring artifacts can be mitigated by properly designing a weighting factor as a function of the spatial location on the detector. As for the cone artifact, without applying a correction method, it contaminated 13 out of 80 slices in a head-neck case (full-fan). Contamination was even more severe in a pelvis case under half-fan mode, where 36 out of 80 slices were affected, leading to poorer soft tissue delineation and reduced superior–inferior coverage. The proposed method effectively corrects those contaminated slices with mean intensity differences compared to FDK results decreasing from ∼497 and ∼293 HU to ∼39 and ∼27 HU for the full-fan and half-fan cases, respectively. In terms of efficiency boost, an overall 3.1 × speedup factor has been achieved with four GPU cards compared to a single GPU-based reconstruction. The total computation time is ∼30 s for typical clinical cases. Conclusions: The authors have developed a low-dose CBCT IR system for IGRT. By incorporating data consistency-based weighting factors in the IR model, cone/ring artifacts can be mitigated. A boost in computational efficiency is achieved by multi-GPU implementation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

MODELING ATMOSPHERIC EMISSION FOR CMB GROUND-BASED OBSERVATIONS

Atmosphere is one of the most important noise sources for ground-based cosmic microwave background (CMB) experiments. By increasing optical loading on the detectors, it amplifies their effective noise, while its fluctuations introduce spatial and temporal correlations between detected signals. We present a physically motivated 3D-model of the atmosphere total intensity emission in the millimeter and sub-millimeter wavelengths. We derive a new analytical estimate for the correlation between detectors time-ordered data as a function of the instrument and survey design, as well as several atmospheric parameters such as wind, relative humidity, temperature and turbulence characteristics. Using an original numerical computation, we examine the effect of each physical parameter on the correlations in the time series of a given experiment. We then use a parametric-likelihood approach to validate the modeling and estimate atmosphere parameters from the polarbear-i project first season data set. We derive a new 1.0% upper limit on the linear polarization fraction of atmospheric emission. We also compare our results to previous studies and weather station measurements. The proposed model can be used for realistic simulations of future ground-based CMB observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Mass Spectrometry Imaging Quick View

MSI QuickView is a software designed to provide a graphical user interface (GUI) for greatly speeding up experimental feedback (visualization and analysis) of mass spectrometry imaging (MSI or IMS) data during data acquisition. Often different software loads the entire data set, i.e., all lines of data into computer memory (RAM). This causes out of memory errors for larger datasets. We solved this in MSI QuickView by reading in the data one line at a time. Only the required information (e.g. the final pixel values for that line of heat map) is maintained in RAM. Interim analysis options include the mean intensity vs. m/z spectrum, intensity vs. time spectrums for up to 6 different m/z values or ranges chosen by the user and heat maps for each line. This assists in validating the usefulness of the particular experiment after scanning the first few lines. In addition, the tool facilitates further processing and analysis of the massive datasets. The user can manually pick different m/z values, time ranges, scroll through the spectra for any line in the data without having to load it in manually, save multiple images, change aspect ratios for the heat maps, and process the heat maps in multiple ways including overlaying images at different m/z values, displaying up to 9 different heat maps, alignment of scans along each line etc. There is no manipulation of the data required by the user to visualize the data.

Carson, JamesP.↗
DOE OSTI2012

Software System Design for Large Scale, Spatially-explicit Agroecosystem Modeling

Recently, site-based agroecosystem model has been applied at regional and state level to enable comprehensive analyses of environmental sustainability of food and biofuel production. Those large-scale, spatially-explicit simulations present computational challenges in software systems design. Herein, we describe our software system design for large-scale, spatially-explicit agroecosystem modeling and data analysis. First, we describe the software design principles in three major phases: data preparation, high performance simulation, and data management and analysis. Then, we use a case study at a regional intensive modeling area (RIMA) to demonstrate our system implementation and capability.

Wang, Dali↗