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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Temporal Coherence Importance Sampling for Wind Turbine Extreme Loads Estimation

Estimating long return period extreme wind turbine loads is made especially difficult by the large response variability for 'the same' environmental conditions. To alleviate this, we have 'opened up the black box' of the turbulent wind generation stage of the simulations. Exploiting the notion of 'temporal coherence' allows us to manipulate the turbulent inflow to target extreme wind conditions, while at the same time quantifying 'how probable these are.' The resulting importance sampling load estimates achieve a significantly lower exceedance probability (i.e., they represent much longer return periods) than estimates using the same number of samples (i.e., the same computational resources) but only a standard Monte Carlo estimate.

17 WIND ENERGY↗
DOE OSTI2015

Including the temporal change in PM{sub 2.5} concentration in the assessment of human health impact: Illustration with renewable energy scenarios to 2050

This article proposes a new method to assess the health impact of populations exposed to fine particles (PM{sub 2.5}) during their whole lifetime, which is suitable for comparative analysis of energy scenarios. The method takes into account the variation of particle concentrations over time as well as the evolution of population cohorts. Its capabilities are demonstrated for two pathways of European energy system development up to 2050: the Baseline (BL) and the Low Carbon, Maximum Renewable Power (LC-MRP). These pathways were combined with three sets of assumptions about emission control measures: Current Legislation (CLE), Fixed Emission Factors (FEFs), and the Maximum Technically Feasible Reductions (MTFRs). Analysis was carried out for 45 European countries. Average PM{sub 2.5} concentration over Europe in the LC-MRP/CLE scenario is reduced by 58% compared with the BL/FEF case. Health impacts (expressed in days of loss of life expectancy) decrease by 21%. For the LC-MRP/MTFR scenario the average PM{sub 2.5} concentration is reduced by 85% and the health impact by 34%. The methodology was developed within the framework of the EU's FP7 EnerGEO project and was implemented in the Platform of Integrated Assessment (PIA). The Platform enables performing health impact assessments for various energy scenarios. - Highlights: • A new method to assess health impact of PM{sub 2.5} for energy scenarios is proposed. • An algorithm to compute Loss of Life Expectancy attributable to exposure to PM{sub 2.5} is depicted. • Its capabilities are demonstrated for two pathways of European energy system development up to 2050. • Integrating the temporal evolution of PM{sub 2.5} is of great interest for assessing the potential impacts of energy scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Validation of the National Solar Radiation Database (NSRDB) (2005-2012): Preprint

Publicly accessible, high-quality, long-term, satellite-based solar resource data is foundational and critical to solar technologies to quantify system output predictions and deploy solar energy technologies in grid-tied systems. Solar radiation models have been in development for more than three decades. For many years, the National Renewable Energy Laboratory (NREL) developed and/or updated such models through the National Solar Radiation Data Base (NSRDB). There are two widely used approaches to derive solar resource data from models: (a) an empirical approach that relates ground-based observations to satellite measurements and (b) a physics-based approach that considers the radiation received at the satellite and creates retrievals to estimate clouds and surface radiation. Although empirical methods have been traditionally used for computing surface radiation, the advent of faster computing has made operational physical models viable. The Global Solar Insolation Project (GSIP) is an operational physical model from the National Oceanic and Atmospheric Administration (NOAA) that computes global horizontal irradiance (GHI) using the visible and infrared channel measurements from the Geostationary Operational Environmental Satellites (GOES) system. GSIP uses a two-stage scheme that first retrieves cloud properties and then uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. NREL, the University of Wisconsin, and NOAA have recently collaborated to adapt GSIP to create a high temporal and spatial resolution data set. The product initially generates the cloud properties using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms [3], whereas the GHI is calculated using SASRAB. Then NREL implements accurate and high-resolution input parameters such as aerosol optical depth (AOD) and precipitable water vapor (PWV) to compute direct normal irradiance (DNI) using the DISC model. The AOD and PWV, temperature, and pressure data are also combined with the MMAC model to simulate solar radiation under clear-sky conditions. The current NSRDB update is based on a 4-km x 4-km resolution at a 30-minute time interval, which has a higher temporal and spatial resolution. This paper demonstrates the evaluation of the data set using ground-measured data and detailed evaluation statistics. The result of the comparison shows a good correlation to the NSRDB data set. Further, an outline of the new version of the NSRDB and future plans for enhancement and improvement are provided.

14 SOLAR ENERGY↗
DOE OSTI2015

A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion

Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors’ proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors’ proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Multigrid Reduction in Time for Nonlinear Parabolic Problems

The need for parallel-in-time is being driven by changes in computer architectures, where future speed-ups will be available through greater concurrency, but not faster clock speeds, which are stagnant.This leads to a bottleneck for sequential time marching schemes, because they lack parallelism in the time dimension. Multigrid Reduction in Time (MGRIT) is an iterative procedure that allows for temporal parallelism by utilizing multigrid reduction techniques and a multilevel hierarchy of coarse time grids. MGRIT has been shown to be effective for linear problems, with speedups of up to 50 times. The goal of this work is the efficient solution of nonlinear problems with MGRIT, where efficient is defined as achieving similar performance when compared to a corresponding linear problem. As our benchmark, we use the p-Laplacian, where p = 4 corresponds to a well-known nonlinear diffusion equation and p = 2 corresponds to our benchmark linear diffusion problem. When considering linear problems and implicit methods, the use of optimal spatial solvers such as spatial multigrid imply that the cost of one time step evaluation is fixed across temporal levels, which have a large variation in time step sizes. This is not the case for nonlinear problems, where the work required increases dramatically on coarser time grids, where relatively large time steps lead to worse conditioned nonlinear solves and increased nonlinear iteration counts per time step evaluation. This is the key difficulty explored by this paper. We show that by using a variety of strategies, most importantly, spatial coarsening and an alternate initial guess to the nonlinear time-step solver, we can reduce the work per time step evaluation over all temporal levels to a range similar with the corresponding linear problem. This allows for parallel scaling behavior comparable to the corresponding linear problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Digital tomosynthesis (DTS) for verification of target position in early stage lung cancer patients

Purpose: The ability to verify intrafraction tumor position is clinically useful for hypofractionated treatments. Short arc kV digital tomosynthesis (DTS) could facilitate more frequent target verification. The authors used DTS combined with triangulation to determine the mean temporal position of small-volume lung tumor targets treated with stereotactic radiotherapy. DTS registration results were benchmarked against online clinical localization using registration between free-breathing cone-beam computed tomography (CBCT) and the average intensity projection (AvIP) of the planning 4DCT.Methods: In this retrospective study, 76 sets of kV-projection images from online CBCT scans of 13 patients were used to generate DTS image slices (CB-DTS) with nonclinical research software (DTS Toolkit, Varian Medical Systems). Three-dimensional tumor motion was 1.3–4 mm in six patients and 6.1–25.4 mm in seven patients on 4DCT (significant difference in the mean of the groups, P < 0.01). The 4DCT AvIP was used to digitally reconstruct the Reference-DTS. DTS registration and DTS registration combined with triangulation were investigated. Progressive shortening of total DTS arc lengths from 95° to 35° around 0° gantry position was evaluated for different scenarios: DTS registration using the entire arc; DTS registration plus triangulation using two nonoverlapping arcs; and for 55° and 45° total gantry rotation, DTS registration plus triangulation using two overlapping arcs. Finally, DTS registration plus triangulation performed at eight gantry angles, each separated by 45° was evaluated using full fan kV projection data for one patient with an immobile tumor and five patients with mobile tumors.Results: For DTS registration alone, shortening arc length did not influence accuracy in X- and Y-directions, but in Z-direction, mean deviations from online CBCT localization systematically increased for shorter arc length (P < 0.05). For example, using a 95° arc mean DTS-CBCT difference was 0.8 mm (1 SD = 0.6 mm) and for a 35° arc the mean was 2.4 mm (1 SD = 1.7 mm). DTS plus triangulation using nonoverlapping-arcs increased accuracy in Z-direction for tested arc lengths ≤55° (P < 0.01). Overlapping arcs increased accuracy in Y-direction for tumors with motion >4 mm (P < 0.02) but increased Z-direction accuracy was only observed with 55° total gantry rotation. The 95th percentile deviations with this overlapping technique in X-, Y-, and Z-directions were 1.3, 2.0, and 2.5 mm, respectively. For the five patients with mobile tumors where DTS + triangulation was performed with 45° intervals, the pooled deviation from online CBCT correction showed, for X-, Y-, and Z-directions, mean of 1.1 mm, standard deviations (SD) of 0.9, 1.0, and 0.9 mm, respectively. The mean + 2 SD was <3 mm for each direction.Conclusions: Short-arc DTS verification of time averaged lung tumor position is feasible using free-breathing kV projection data and the AvIP of the 4DCT as a reference. Observed differences between DTS and online CBCT registration with AvIP were ≤3 mm (mean + 2 SD), however, the increased temporal resolution of DTS + triangulation also identified short period deviations from the average target position on the CBCT. Short-arc DTS appears promising for intrafraction tumor position monitoring during stereotactic lung radiotherapy delivered with a rotational technique.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Role of scan strategies on thermal gradient and solidification rate in electron beam powder bed fusion

Local microstructure control in electron beam powder bed fusion (EB-PBF) is of great interest to the additive manufacturing community to realize complex part geometry with targeted performance. The local microstructure control relies on having a detailed understanding of local melt pool physics (e.g., 3-D melt pool shape as well as spatial and temporal variations of thermal gradient (G) and solidification rate (R)). In this research, a new scan strategy referred to as ghost beam is numerically evaluated as a candidate to achieve the targeted G and R of IN718 alloy. The boundary conditions for simulations, including the speed (490 mm/s) and spatial locations of the beam within a given layer, are obtained by using series of snapshot images, recorded at 12,000 frames per second, using a high-speed camera. The heat transfer simulations were performed using TRUCHAS an open-source software deployed within a high-performance computational infrastructure. The simulation results showed that reheating at short beam on-time and time delay decreases both G and R. Local variation of R at the center of the melt pool trailing edge showed periodic temporal fluctuations. Finally, the ghost beam scan strategy was compared to other existing raster and spot scan strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unveiling Spatial and Temporal Dynamics of Plasmon-Enhanced Localized Fields in Metallic Nanoframes through Ultrafast Electron Microscopy

Plasmonic nanomaterials, particularly noble metal nanoframes (NFs), are important for applications such as catalysis, biosensing, and energy harvesting due to their ability to enhance localized electric fields and atomic efficiency via localized surface plasmon resonance (LSPR). Yet the fundamental structure-function relationships and plasmonic dynamics of the NFS are difficult to study experimentally and thus far rely predominately on computational methodologies, limiting their utilization. This study leverages the capabilities of ultrafast electron microscopy (UEM), specifically photon-induced near-field electron microscopy (PINEM), to probe the light-matter interactions within plasmonic NF structures. Here, the effects of shape, size, and plasmonic coupling of Pt@Au core-shell NFs on spatial and temporal characteristics of plasmon-enhanced localized electric fields are explored. Importantly, time-resolved PINEM analysis reveals that the plasmonic fields around hexagonal NF prisms exhibit a spatially dependent excitation and decay rate, indicating a nuanced interplay between the spatial geometry of the NF and the temporal evolution of the localized electric field. These results and observations uncover nanophotonic energy transfer dynamics in NFs and highlight their potential for applications in biosensing and photocatalysis.

Plasmonics↗
DOE OSTI2019

Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings

This study looks at forecasted dynamic line ratings in southern Idaho by using data from the High Resolution Rapid Refresh (HRRR) model for forecasted weather conditions. The HRRR model can provide accurate 18- hour forecasts with a 15-minute temporal resolution. Typical static ratings used for over head transmission lines use overly conservative assumptions for local weather conditions, such as using the maximum solar irradiance or temperature measured during the summer combined with low wind speed for an entire season. The HRRR forecast model used here has a high spatial resolution to provide local forecast conditions along the entire length of a transmission line. The area that is of interest in this study is in southern Idaho spanning a total of 15,000 square kilometers. The forecasted weather data is coupled with a computational fluid dynamics model of the wind in the region to improve the resolution to an even finer scale for resolving local convective cooling rates on each individual transmission line midpoint span. This high fidelity approach can be used to find the minimum ampacity limit across all given midpoints of a transmission line to determine the absolute minimum to be used for the line rating. The ability to increase the line rating above the conservative static approach with the forecasted weather data provides a large potential to alleviate congestion and provide data for the utility market transactions. Furthermore, this study shows that for the region of interest, using forecasted weather data coupled with CFD modeling will calculate DLR ampacity rating above static about 90% of the time, with only a small relative error in the forecasted ampacity over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Thermomechanical conversion in metals: dislocation plasticity model evaluation of the Taylor-Quinney coefficient

Using a partitioned-energy thermodynamic framework which assigns energy to that of atomic configurational stored energy of cold work and kinetic-vibrational, in this study we derive an important constraint on the Taylor-Quinney coefficient, which quantifies the fraction of plastic work that is converted into heat during plastic deformation. Associated with the two energy contributions are two separate temperatures – the ordinary temperature for the thermal energy and the effective temperature for the configurational energy. We show that the Taylor-Quinney coefficient is a function of the thermodynamically defined effective temperature that measures the atomic configurational disorder in the material. Finite-element analysis of recently published experiments on the aluminum alloy 6016-T4 [1], using the thermodynamic dislocation theory (TDT), shows good agreement between theory and experiment for both stress-strain behavior and temporal evolution of the temperature. The simulations include both conductive and convective thermal energy loss during the experiments, and significant thermal gradients exist within the simulation results. Computed values of the differential Taylor-Quinney coefficient are also presented and suggest a value which differs between materials and increases with increasing strain.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Framework for optimization of long-term, multi-period investment planning of integrated urban energy systems

In order to achieve stringent greenhouse gas emission reductions, a transition of our entire energy system from fossil to renewable resources needs to be designed. Such an energy transition brings two main challenges: most renewables generate variable electric energy, yet most demand is currently not electric (carrier mismatch) and does not always manifest at the same time as supply (temporal mismatch). Integrating multiple energy infrastructures can address both challenges by using the synergy between different energy carriers; building on existing infrastructure, while allowing a robust and flexible integration of the new. This paper proposes an optimization framework for long-term, multi-period investment planning of urban energy systems in an integrated manner. We formulate it as a mixed-integer linear program, combining a capacitated facility location with a multi-dimensional, capacitated network design problem. It includes generation and network expansion planning as well as interconnections between networks and storage infrastructure for each energy system. It can incorporate pathway effects like techno-economic developments, policy measures, and weather variations. The intended use is to support urban decision makers with long-term investment planning, though it can be tailored to fit other geographical or temporal scales. We demonstrate the model using two cases based on an average city in The Netherlands, which wants to reduce its CO 2 -emissions with 95% by 2050. In the first case, we include explicit carbon-emission constraints to study the effects of the carrier mismatch. In the second case, we implement interannual weather variations to analyze the temporal mismatch. The results give valuable insights into the energy transition design strategy for urban decision makers. They also show the future potential, as well as the computational challenges of the optimization framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Material point methods applied to one-dimensional shock waves and dual domain material point method with sub-points

Here, using a simple one-dimensional shock problem as an example, the present paper investigates numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the dual domain material point (DDMP) method. For a weak isothermal shock of ideal gas, the MPM cannot be used with accuracy. With a small number of particles per cell, GIMP and CPDI produce reasonable results. However, as the number of particles increases the methods fail to converge and produce pressure spikes. The DDMP method behaves in an opposite way. With a small number of particles per cell, DDMP results are unsatisfactory. As the number of particles increases, the DDMP results converge to correct solutions, but the large number of particles needed for convergence makes the method very expensive to use in these types of shock wave problems in two- or three-dimensional cases. The cause for producing the unsatisfactory DDMP results is identified. A simple improvement to the method is introduced by using sub-points. With this improvement, the DDMP method produces high quality numerical solutions with a very small number of particles. Although in the present paper, the numerical examples are one-dimensional, all derivations are for multidimensional problems. With the technique of approximately tracking particle domains of CPDI, the extension of this sub-point method to multidimensional problems is straightforward. Finally, this new method preserves the conservation properties of the DDMP method, which conserves mass and momentum exactly and conserves energy to the second order in both spatial and temporal discretizations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

An ultrahigh-resolution E3SM land model simulation framework and its first application to the Seward Peninsula in Alaska

The availability of supercomputers and state-of-science datasets has made it possible to conduct large-scale land simulations at an ultrahigh-resolution. This study reported a computational framework for land surface simulation using the E3SM land model (ELM) at an unprecedented resolution (1 km x 1 km gridcell). The ultrahigh-resolution ELM (uELM) simulation framework includes three parts: (1) high-resolution atmospheric forcing and surface properties dataset generation, (2) massive gridcell-based simulation, and (3) large-scale simulation results analysis. Additionally, we implemented the uELM simulation framework and completed the first 1 km x 1 km terrestrial ecosystem simulation (from 1850 to 2014) over the Seward Peninsula in Alaska (78,000 km 2 ). The experiment contained two phases: a spin-up simulation and a transient simulation, and required five weeks of calculations using 320 cores in a 44-node Linux HPC computer. It created approximately 1.3 TB of data from the transient simulation alone (1850 - present). We selected sample results (monthly and daily simulation outputs) to illustrate the temporal and spatial variations of several variables in high-latitude Arctic ecosystems’ water, energy, and carbon cycles. At last, we summarized the lessons learned and proposed new developments for full-scale uELM simulations over the entire North American continent (approximately 22,000,000 km 2 ).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

helios: An R package to process heating and cooling degrees for GCAM

helios is an open-source R package that estimates population-weighted heating and cooling degree-hours (HDH and CDH) and degree-days (HDD and CDD) at various temporal (e.g., energy dispatch segments, monthly, yearly) and spatial scales (e.g., U.S. states, global political regions, countries). The degree hour and degree day outputs from helios are used to inform electricity demand load in the Global Change Analysis Model (GCAM) as well as in GCAM-USA (which is the version of GCAM with U.S. state-level details). helios uses a workflow with four steps: processing raw data; calculating heating and cooling degrees; visualizing performance diagnostics; and outputing results in various formats. There are two sources of widely-used climate data compatible with helios: (1) hourly climate data with 12-km resolution that are dynamically downscaled with the Weather Research and Forecasting (WRF) model and projected using a thermal global warming (TGW) approach; and (2) daily climate data with 0.5-degree resolution from the Coupled Model Intercomparison Project (CMIP) that is bias-adjusted and statistical downscaled by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). In summary, helios is a model that standardizes methodology of heating and cooling degrees-hours and degree-days using publicly available data and advance the understanding of the impact of spatial and temporal temperature variability on building energy services.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

MO-AB-BRA-09: Temporally Realistic Manipulation a 4D Biomechanical Lung Phantom for Evaluation of Simultaneous Registration and Segmentation

Purpose: To produce multi-modality compatible, realistic datasets for the joint evaluation of segmentation and registration with a reliable ground truth using a 4D biomechanical lung phantom. The further development of a computer controlled air flow system for recreation of real patient breathing patterns is incorporated for additional evaluation of motion prediction algorithms. Methods: A pair of preserved porcine lungs was pneumatically manipulated using an in-house computer controlled respirator. The respirator consisted of a set of bellows actuated by a 186 W computer controlled industrial motor. Patient breathing traces were recorded using a respiratory bellows belt during CT simulation and input into a control program incorporating a proportional-integral-derivative (PID) feedback controller in LabVIEW. Mock tumors were created using dual compartment vacuum sealed sea sponges. 65% iohexol,a gadolinium-based contrast agent and 18F-FDG were used to produce contrast and thus determine a segmentation ground truth. The intensity distributions of the compartments were then digitally matched for the final dataset. A bifurcation tracking pipeline provided a registration ground truth using the bronchi of the lung. The lungs were scanned using a GE Discovery-ST PET/CT scanner and a Phillips Panorama 0.23T MRI using a T1 weighted 3D fast field echo (FFE) protocol. Results: The standard deviation of the error between the patient breathing trace and the encoder feedback from the respirator was found to be ±4.2%. Bifurcation tracking error using CT (0.97×0.97×3.27 mm{sup 3} resolution) was found to be sub-voxel up to 7.8 cm displacement for human lungs and less than 1.32 voxel widths in any axis up to 2.3 cm for the porcine lungs. Conclusion: An MRI/PET/CT compatible anatomically and temporally realistic swine lung phantom was developed for the evaluation of simultaneous registration and segmentation algorithms. With the addition of custom software and mock tumors, the entire package offers ground truths for benchmarking performance with high fidelity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities]

Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems. Here, examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures), (b) structural and nuclear engineering to model the temporal evolution of the structural damage of concrete shields exposed to continuous neutron and gamma radiations emitted by the nuclear reactor core, (c) urban sciences (e.g., transportation and smart buildings), and (d) power grid systems.

97 MATHEMATICS AND COMPUTING↗