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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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Scalable Reactive Molecular Dynamics Simulations for Computational Synthesis
Reactive molecular dynamics (MD) simulation is a powerful research tool for describing chemical reactions. We eliminate the speed-limiting charge iteration in MD with a novel extended-Lagrangian scheme. The extended-Lagrangian reactive MD (XRMD) code drastically improves energy conservation while substantially reducing time-to-solution. Furthermore, we introduce a new polarizable charge equilibration (PQEq) model to accurately predict atomic charges and polarization. The XRMD code based on hybrid message passing+multithreading achieves a weak-scaling parallel efficiency of 0.977 on 786 432 IBM Blue Gene/Q cores for a 67.6 billion-atom system. The performance is portable to the second-generation Intel Xeon Phi, Knights Landing. Blue Gene/Q simulations for the computational synthesis of materials via novel exfoliation mechanisms for synthesizing atomically thin transition metal dichalcogenide layers will dominate nanomaterials science in this century.
FY2020 Energy Efficient Mobility Systems Annual Progress Report
EEMS Program activities during FY 2020 focused on analytical research and large-scale modeling and simulation to understand the impacts that new mobility technologies and services will have at the vehicle-, traveler-, and overall transportation system-level. This research included the development of a multi-fidelity, end-to-end transportation system models and tools to evaluate the complex interactions among the various actors within the mobility landscape, analysis of empirical data to characterize which solutions may provide the largest benefits, and development of new control systems and algorithms that use vehicle connectivity and automation to improve the performance and efficiency of individual vehicles as well as the overall traffic system. This document presents a brief overview of the EEMS Program and documents progress and results from projects within each of the EEMS activity areas. The Computational Modeling and Simulation key activity area summarizes work within the sub-areas of (1) the SMART (Systems and Modeling for Accelerated Research in Transportation) Mobility Lab Consortium, (2) Artificial Intelligence, High-Performance Computing, and Data Analytics, and (3) Core Simulation and Evaluation Tools. Additionally, the program’s advanced R&D projects are summarized within (4) the Connectivity and Automation Technology key activity area. Each of the individual progress reports provide a project overview and highlights of the technical results.
Characterization of Exoplanet Atmospheres with the Optical Coronagraph on WFIRST
Wide-Field Infrared Survey Telescope (WFIRST)-CGI is a NASA technology demonstration mission that is charged with demonstrating key technologies for future exo-Earth imaging missions in space. In the process, it will obtain images and low-resolution spectra of a handful to a dozen extrasolar planets and possibly protoplanetary disks. Its unprecedented contrast levels in the optical will provide astronomers’ with their first direct look at mature, Jupiter-sized planets at moderate separations. This paper addresses the question: what science can be done with such data? An analytic noise model, which is informed by the ongoing engineering developments, is used to compute maximum achievable signal-to-noise ratios and scientifically viable integration times for hypothetical star–planet systems, as well as to investigate the constraining power of various combinations of WFIRST-CGI photometric and spectral observations. This work introduces two simple models for planetary geometric albedos, which are inspired largely by the solar system’s gas giants. The first planet model is a hybrid Jupiter–Neptune model, which separately treats the short and long wavelengths where chromophores and methane dominate absorption, respectively. The second planet model fixes cloud and haze properties in CoolTLusty to match Jupiter’s albedo spectrum, it then perturbs only the metallicity. MCMC retrievals performed on simulated observations are used to assess the precision with which planet model parameters can be measured subject to different exposure times and observing cases. Planet radius is recovered within ±15% for all observing cases with both the hybrid model and the CoolTLusty metallicity grid. Fit results for both models’ parameterizations of geometric albedo spectra demonstrate that a rough indication of the metallicity or methane content should be possible for some WFIRST-CGI targets. We conclude that real observations will likely be able to differentiate between extreme cases using these models, but will lack the precision necessary to uncover subtle trends.
MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies
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NIMBLE. A data management and visualization framework for large scale engineering and science VVUQ applications
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An Analysis of Equity and Equality Constraints on Power System Planning
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Advanced Computing Annual Report 2023
In 2023, advanced computing saw the arrival of Kestrel, the National Renewable Energy Laboratory's (NREL's) newest high-performance computing (HPC) system. Kestrel will accelerate clean energy research at a pace and scale more than five times greater than Eagle, with approximately 44 petaflops of computing power. Kestrel's heterogeneous architecture - which includes both CPU-only and GPU-accelerated nodes - is designed to bring a much greater GPU capacity to EERE workloads compared to Eagle, enabling rapidly advancing applications in artificial intelligence and expanding research in new directions for computing. In Fiscal Year (FY) 2023, 333 projects utilized NREL's HPC system, advancing the U.S. Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy (EERE) mission across 13 funding areas. Cross-disciplinary collaboration among researchers yielded more than 800 technical outputs, including 177 peer-reviewed journal articles in FY 2023. All this great work continues to advance the science of energy efficiency and renewable energy. This report highlights research that utilized HPC resources in FY 2023.
Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM
Real-time flood model plays a pivotal role in averting urban flood damage, particularly when there is minimal lead time for preparatory measures. However, urban flood modeling in real-time often contends with inherent uncertainties arising from input data uncertainty and parameter ambiguities. Here this study introduces a real-time calibration (RTC) tool called Bayes_Opt-SWMM, specifically tailored for real-time urban flood modeling and uncertainty optimization. This tool leverages the Gaussian process-based Bayesian optimization algorithm and interfaces seamlessly with the Stormwater Management Model (SWMM). It integrates real-time model forcing data and flood monitoring collected through sensors and gauges which are strategically placed within critical locations of urban drainage systems. Our approach hinges on the Surrogate Model based Uncertainty Optimization (SMUO) concept, providing an avenue for enhancing real-time flood modeling. Bayes_Opt-SWMM runs the optimization process using a surrogate model called Gaussian Process emulator with two inference methods: (1) the Gaussian Process (GP) model and (2) Markov Chain Monte Carlo (MCMC) algorithm in GP model (GP_MCMC). Furthermore, three acquisition functions, namely Expected Improvement (EI), Maximum Probability of Improvement (MPI), and Lower Confidence Bound (LCB), facilitate optimal parameter fitting within the surrogate models. The efficiency of GP-based surrogate models in learning SWMM model parameters, leads to an improved uncertainty quantification and accelerated real-time flood modeling in urban areas. Overall, Bayes_Opt-SWMM emerges as a cost-effective and valuable tool for real-time flood modeling and monitoring, with significant potential for managing intelligent storm water systems in urban environments.
SU-E-T-341: DVH-Based Comparison of True 3D Measurements to a Delta4 System
Purpose: Delta4 dosimetric software can be used to calculate DVH-based metrics for patient-specific quality assurance from measurements made by a Delta4 QA device. This study investigates the effectiveness of a novel transform method that transposes measurements made with a full-density 3D dosimeter onto patient anatomy, enabling the calculation of DVHs. This allows for DVH comparisons from the transformed dose distribution, which are based on true 3D measurements, to those from the Delta4 system, which are based on semi-3D measurements and interpolation. Methods: A double-arc VMAT treatment for a head-and-neck case was delivered to a 1kg PRESAGE 3D dosimeter inserted into a polyurethane head phantom. The dosimeter was readout using an in-house optical-CT scanner to gather full-density 3D dosimetric data. The transform method is achieved by multiplication of the measured doses with a “transformation matrix” which accounts for heterogeneities and differences in geometry between the patient and the phantom. The transformation matrix is a voxel-by-voxel division of the patient planned dose by the phantom planned dose, both calculated in the treatment planning system (Eclipse). The transformed distribution was then overlaid on the patient CT data, enabling the calculation of DVHs. The same VMAT treatment was delivered to the Delta4 phantom and DVH data was calculated using its associated software. Results: The transformed dose distribution showed good agreement with calculated patient values, determined by similarity in dose profiles between the two distributions and a 3D gamma index passing rate of 94.87% for 3%/3mm criteria. For every structure contained within the dosimeter volume, the transformed DVHs demonstrated better agreement than the Delta4 DVHs, when compared to the values calculated in the treatment planning system. Conclusion: The coupled technique of full-density 3D dose measurements and the presented transform method enables clinical patient-specific quality assurance data that is more accurate than the semi-3D Delta4 system. This work was supported by NIH R01CA100835.
TU-A-304-03: Quality Assurance, Safety, and Other Practical Aspects of SBRT
Increased use of SBRT and hypo fractionation in radiation oncology practice has posted a number of challenges to medical physicist, ranging from planning, image-guided patient setup and on-treatment monitoring, to quality assurance (QA) and dose delivery. This symposium is designed to provide updated knowledge necessary for the safe and efficient implementation of SBRT in various linac platforms, including the emerging digital linacs equipped with high dose rate FFF beams. Issues related to 4D CT, PET and MRI simulations, 3D/4D CBCT guided patient setup, real-time image guidance during SBRT dose delivery using gated/un-gated VMAT or IMRT, and technical advancements in QA of SBRT (in particular, strategies dealing with high dose rate FFF beams) will be addressed. The symposium will help the attendees to gain a comprehensive understanding of the SBRT workflow and facilitate their clinical implementation of the state-of-art imaging and planning techniques. Learning Objectives: Present background knowledge of SBRT, describe essential requirements for safe implementation of SBRT, and discuss issues specific to SBRT treatment planning and QA. Update on the use of multi-dimensional (3D and 4D) and multi-modality (CT, beam-level X-ray imaging, pre- and on-treatment 3D/4D MRI, PET, robotic ultrasound, etc.) for reliable guidance of SBRT. Provide a comprehensive overview of emerging digital linacs and summarize the key geometric and dosimetric features of the new generation of linacs for substantially improved SBRT. Discuss treatment planning and quality assurance issues specific to SBRT. Research grant from Varian Medical Systems.
SU-F-T-489: 4-Years Experience of QA in TomoTherapy MVCT: What Do We Look Out For?
Purpose: To evaluate the QA results of TomoTherapy MVCT from March 2012 to February 2016, and to identify issues that may affect consistency in HU numbers and reconstructed treatment dose in MVCT. Methods: Monthly QA was performed on our TomoHD system. Phantom with rod inserts of various mass densities was imaged in MVCT and compared to baseline to evaluate HU number consistency. To evaluate treatment dose reconstructed by delivered sinogram and MVCT, a treatment plan was designed on a humanoid skull phantom. The phantom was imaged with MVCT and treatment plan was delivered to obtain the sinogram. The dose reconstructed with the Planned Adaptive software was compared to the dose in the original plan. The QA tolerance for HU numbers was ±30 HU, and ±2% for discrepancy between original plan dose and reconstructed dose. Tolerances were referenced to AAPM TG148. Results: Several technical modifications or maintenance activities to the system have been identified which affected QA Results: 1) Upgrade in console system software which added a weekly HU calibration procedure; 2) Linac or MLC replacement leading to change in Accelerator Output Machine (AOM) parameters; 3) Upgrade in planning system algorithm affecting MVCT dose reconstruction. These events caused abrupt changes in QA results especially for the reconstructed dose. In the past 9 months, when no such modifications were done to the system, reconstructed dose was consistent with maximum deviation from baseline less than 0.6%. The HU number deviated less than 5HU. Conclusion: Routine QA is essential for MVCT, especially if the MVCT is used for daily dose reconstruction to monitor delivered dose to patients. Several technical events which may affect consistency of this are software changes, linac or MLC replacement. QA results reflected changes which justify re-calibration or system adjustment. In normal circumstances, the system should be relatively stable and quarterly QA may be sufficient.
MO-D-BRB-01: Fundamental Aspects of SBRT
Increased use of SBRT and hypofractionation in radiation oncology practice has posted a number of challenges to medical physicist, ranging from planning, image-guided patient setup and on-treatment monitoring, to quality assurance (QA) and dose delivery. This symposium is designed to provide current knowledge necessary for the safe and efficient implementation of SBRT in various linac platforms, including the emerging digital linacs equipped with high dose rate FFF beams. Issues related to 4D CT, PET and MRI simulations, 3D/4D CBCT guided patient setup, real-time image guidance during SBRT dose delivery using gated/un-gated VMAT/IMRT, and technical advancements in QA of SBRT (in particular, strategies dealing with high dose rate FFF beams) will be addressed. The symposium will help the attendees to gain a comprehensive understanding of the SBRT workflow and facilitate their clinical implementation of the state-of-art imaging and planning techniques. Learning Objectives: Present background knowledge of SBRT, describe essential requirements for safe implementation of SBRT, and discuss issues specific to SBRT treatment planning and QA. Update on the use of multi-dimensional and multi-modality imaging for reliable guidance of SBRT. Discuss treatment planning and QA issues specific to SBRT. Provide a comprehensive overview of emerging digital linacs and summarize the key geometric and dosimetric features of the new generation of linacs for substantially improved SBRT. NIH/NCI; Varian Medical Systems; F. Yin, Duke University has a research agreement with Varian Medical Systems. In addition to research grant, I had a technology license agreement with Varian Medical Systems.
MO-D-BRB-03: Quality Assurance of SBRT
Increased use of SBRT and hypofractionation in radiation oncology practice has posted a number of challenges to medical physicist, ranging from planning, image-guided patient setup and on-treatment monitoring, to quality assurance (QA) and dose delivery. This symposium is designed to provide current knowledge necessary for the safe and efficient implementation of SBRT in various linac platforms, including the emerging digital linacs equipped with high dose rate FFF beams. Issues related to 4D CT, PET and MRI simulations, 3D/4D CBCT guided patient setup, real-time image guidance during SBRT dose delivery using gated/un-gated VMAT/IMRT, and technical advancements in QA of SBRT (in particular, strategies dealing with high dose rate FFF beams) will be addressed. The symposium will help the attendees to gain a comprehensive understanding of the SBRT workflow and facilitate their clinical implementation of the state-of-art imaging and planning techniques. Learning Objectives: Present background knowledge of SBRT, describe essential requirements for safe implementation of SBRT, and discuss issues specific to SBRT treatment planning and QA. Update on the use of multi-dimensional and multi-modality imaging for reliable guidance of SBRT. Discuss treatment planning and QA issues specific to SBRT. Provide a comprehensive overview of emerging digital linacs and summarize the key geometric and dosimetric features of the new generation of linacs for substantially improved SBRT. NIH/NCI; Varian Medical Systems; F. Yin, Duke University has a research agreement with Varian Medical Systems. In addition to research grant, I had a technology license agreement with Varian Medical Systems.
Towards Auto-Generated Data Systems
After decades of progress, database management systems (DBMSs) are now the backbones of many data applications that we interact with on a daily basis. Yet, with the emergence of new data types and hardware, building and optimizing new data systems remain as difficult as the heyday of relational databases. In this paper, we summarize our work towards automating the building and optimization of data systems. Drawing from our own experience, we further argue that any automation technique must address three aspects: user specification, code generation, and result validation. We conclude by discussing a case study using videos data processing, along with opportunities for future research towards designing data systems that are automatically generated.
Jaynesian Analysis of Environmental Chemistry: Systems Model Component Integration via the Arctic Aquatic Carbon Cycle
Focal Areas: All three are touched upon from the OBER call. We will consider formal logical inference and entropic information analysis for sparse but intensive chemical measurements, as optimal drivers for managing process complexity. As a centerpiece for the discussion we take soil-to-sea organic structural evolution within the Arctic hydro-geochemosphere, assessing detrital negentropy then algorithmic greed to generate ranked, reduced mechanisms for system integration.
Preferential flow in subsurface hydrology: From a century of denial to a decade of addressing it via ML?
This white paper highlights the potential of using machine learning (ML) to gain new insights from large, high-frequency Earth science observatory network datasets (focal area 3) and better represent complex subsurface processes via ML in Earth System Models (ESMs, focal area 2).
NETL CO2U openLCA LCI Database Version 2.1
The NETL CO2U openLCA LCI Database Version 2 is part of the NETL CO2U LCA Guidance Toolkit for Carbon Utilization funding recipients to meet their LCA requirements. The toolkit includes the following files: NETL CO2U LCA Guidance Document, NETL CO2U openLCA LCI Database, NETL CO2U openLCA Results Contribution Tool, NETL CO2U LCA Documentation Spreadsheet, and NETL CO2U LCA Report Template. The NETL CO2U openLCA LCI Database is an openLCA software files that contains data and an example system for funding recipients using openLCA to complete their LCA requirements.