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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Accelerating technology development to monitor and minimize effects from land‐based wind energy on birds and bats

While wind energy is a key sector of domestic energy production for the United States, operation of wind turbines directly and indirectly adversely affects certain species of birds and bats. The cumulative effect of wind turbine strikes can have both biological and regulatory consequences, and, in some cases, delay permitting and construction or affect ongoing operations. Technology can help quantify and minimize these effects, but the pace of development, acceptance, and adoption of technological solutions is slow. Although adopting cost‐effective technologies may reduce negative effects on wildlife and help achieve both energy production and conservation goals, consensus is lacking among developers, regulators, and the conservation community regarding how to define technology effectiveness and acceptance and how to develop a standardized process for doing so. Removing barriers to technology advancement requires deviating from the status quo. Changes include 1) creating incentives to mitigate impacts, 2) establishing options for research as mitigation, 3) rethinking how research is funded, 4) increasing stakeholder coordination, and 5) increasing the efficiency of research and development. We recommend the creation of a national framework to establish clear criteria and protocols for technology evaluation and adoption.

17 WIND ENERGY↗
DOE OSTI2017

Hydrothermal Conditioning of Physical Hydrogels Prepared from a Midblock-Sulfonated Multiblock Copolymer

Since nanostructured amphiphilic macromolecules capable of affording high ion and water transport are becoming increasingly important in a wide range of contemporary energy and environmental technologies, the swelling kinetics and temperature dependence of water uptake are investigated in a series of midblock-sulfonated thermoplastic elastomers. Upon self-assembly, these materials maintain a stable hydrogel network in the presence of a polar liquid. In this study, real-time water-sorption kinetics in copolymer films prepared by different casting solvents are elucidated by synchrotron small-angle X-ray scattering and gravimetric measurements, which directly correlate nanostructural changes with macroscopic swelling to establish fundamental structure-property behavior. By monitoring the equilibrium swelling capacity of these materials over a range of temperatures, an unexpected transition in the vicinity of 50 degrees C has been discovered. Furthermore, depending on copolymer morphology and degree of sulfonation, hydrothermal conditioning of specimens to temperatures above this transition permits retention of superabsorbent swelling at ambient temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Quantitative impact of changes in marrow cellularity, skeletal size, and bone mineral density on active marrow dosimetry based upon a reference model

Purpose The hematopoietically active tissues of skeletal bone marrow are a prime target for computational dosimetry given potential risks of leukemia and, at higher dose levels, acute marrow toxicity. The complex three‐dimensional geometry of trabecular spongiosa, however, complicates schema for dose assessment in such a way that only a few reference skeletal models have been developed to date, and which are based upon microimaging of a limited number of cadaveric bone spongiosa cores. The question then arises as to what degree of accuracy is achievable from reference skeletal dose models when applied to individual patients or specific exposed populations? Methods Patient variability in marrow dosimetry were quantified for three skeletal sites — the ribs, lumbar vertebrae, and cranium — for the beta‐emitters 45 Ca, 153 Sm, and 90 Y, and the alpha‐particle emitters 223 Ra, 219 Rn, and 215 Po, the latter two being the immediate progeny of the former. For each radionuclide and bone site, three patient parameters were altered from their values in the reference model: (1) bone size as a surrogate for patient stature, (2) marrow cellularity as a surrogate for age‐ or disease‐related changes in marrow adiposity, and (3) the trabecular bone volume fraction as a surrogate for bone mineral density. Marrow dose variability is expressed as percent differences in the radionuclide S value given by the reference model and the patient‐parameterized model. The impact of radionuclide biokinetics on marrow dosimetry was not considered. Results Variations in overall bone size play a very minor role in active marrow dose variability. Marrow cellularity is a significant factor in dose variability for active marrow self‐irradiation, but it plays no role for radionuclides localized to the trabecular bone matrix. Variations in trabecular bone volume fractions impact the active marrow dose variability for short‐range particle emitters 45 Ca, 223 Ra, 219 Rn, and 215 Po in the vertebrae and ribs, skeletal sites with small spongiosa proportions of trabecular bone. In the cranium, with its relative high proportion of trabecular bone, significant differences in marrow dosimetry from the reference model were noted for all radionuclides. Conclusions Skeletal models of active marrow dosimetry should be more fully parameterized to permit closer matching to patient bone density and marrow cellularity, particularly when considering short‐range particle emitters localized to either the bone trabeculae or active marrow, respectively.

Geyer, Amy M.↗
DOE OSTI2019

Parallel beamlet dose calculation via beamlet contexts in a distributed multi‐GPU framework

Purpose Dose calculation is one of the most computationally intensive, yet essential tasks in the treatment planning process. With the recent interest in automatic beam orientation and arc trajectory optimization techniques, there is a great need for more efficient model‐based dose calculation algorithms that can accommodate hundreds to thousands of beam candidates at once. Foundational work has shown the translation of dose calculation algorithms to graphical processing units ( GPU s), lending to remarkable gains in processing efficiency. But these methods provide parallelization of dose for only a single beamlet, serializing the calculation of multiple beamlets and under‐utilizing the potential of modern GPU s. In this paper, the authors propose a framework enabling parallel computation of many beamlet doses using a novel beamlet context transformation and further embed this approach in a scalable network of multi‐ GPU computational nodes. Methods The proposed context‐based transformation separates beamlet‐local density and TERMA into distinct beamlet contexts that independently provide sufficient data for beamlet dose calculation. Beamlet contexts are arranged in a composite context array with dosimetric isolation, and the context array is subjected to a GPU collapsed‐cone convolution superposition procedure, producing the set of beamlet‐specific dose distributions in a single pass. Dose from each context is converted to a sparse representation for efficient storage and retrieval during treatment plan optimization. The context radius is a new parameter permitting flexibility between the speed and fidelity of the dose calculation process. A distributed manager‐worker architecture is constructed around the context‐based GPU dose calculation approach supporting an arbitrary number of worker nodes and resident GPU s. Phantom experiments were executed to verify the accuracy of the context‐based approach compared to Monte Carlo and a reference CPU ‐ CCCS implementation for single beamlets and broad beams composed by addition of beamlets. Dose for representative 4 π beam sets was calculated in lung and prostate cases to compare its efficiency with that of an existing beamlet‐sequential GPU ‐ CCCS implementation. Code profiling was also performed to evaluate the scalability of the framework across many networked GPU s. Results The dosimetric accuracy of the context‐based method displays <1.35% and 2.35% average error from the existing serialized CPU ‐ CCCS algorithm and Monte Carlo simulation for beamlet‐specific PDD s in water and slab phantoms, respectively. The context‐based method demonstrates substantial speedup of up to two orders of magnitude over the beamlet‐sequential GPU ‐ CCCS method in the tested configurations. The context‐based framework demonstrates near linear scaling in the number of distributed compute nodes and GPU s employed, indicating that it is flexible enough to meet the performance requirements of most users by simply increasing the hardware utilization. Conclusions The context‐based approach demonstrates a new expectation of performance for beamlet‐based dose calculation methods. This approach has been successful in accelerating the dose calculation process for very large‐scale treatment planning problems ‐ such as automatic 4 π IMRT beam orientation and VMAT arc trajectory selection, with hundreds of thousands of beamlets ‐ in clinically feasible timeframes. The flexibility of this framework makes it as a strong candidate for use in a variety of other very large‐scale treatment planning tasks and clinical workflows.

Neph, Ryan↗
DOE OSTI2018

Passage Route and Upstream Migration Success: A Case Study of Snake River Salmonids Ascending Lower Granite Dam

Abstract Lower Granite Dam is the last dam that federally protected Snake River salmonids Oncorhynchus spp. must ascend during their spawning migration. The dam has an adult fish ladder equipped with a trapping system to facilitate fisheries research and hatchery broodstock collection. There are three possible passage routes through the adult ladder: trapped, shunted, and free passage. During the adult trapping season, all fish must swim through 0.305-m shunt pipes outfitted with PIT tag arrays that allow the selection of fish for trapping. Selected fish use the “trapped” route and are kept in a holding area for up to 20 h before being sampled and returned to the ladder. Unselected fish use the “shunted” route and immediately resume upstream migration after swimming through the pipes. When the trap is not in operation, the shunted route is inaccessible, and all fish use the “free passage” route to ascend the ladder without additional impediment. In 2016, a temporary change in ladder operations permitted free passage for a portion of the trapping season. Our study used this rare opportunity to evaluate how different passage routes affect in-ladder transit time and upstream homing success for five salmonid stocks: Sockeye Salmon Oncorhynchus nerka; steelhead O. mykiss; and spring-, summer-, and fall-run Chinook Salmon O. tshawytscha. In 2016, only Sockeye Salmon and spring- and summer-run Chinook Salmon were given access to free passage, and we found evidence that free passage increased subsequent detection at natal sites upstream. An expanded analysis of shunted versus trapped fish during the years 2012–2016 found no difference in rates of detection to home tributaries by route of passage for any of the five fish stocks examined.

Morrisett, Christina N.↗
DOE OSTI2025

A Scalable Interior‐Point Gauss–Newton Method for PDE‐Constrained Optimization With Bound Constraints

Here, we present a scalable approach to solve a class of partial differential equation (PDE)‐constrained optimization problems with bound constraints. This approach utilizes a robust full‐space interior‐point (IP)‐Gauss–Newton optimization method. To cope with the poorly‐conditioned IP‐Gauss–Newton saddle‐point linear systems that need to be solved approximately, once per optimization step, we propose two spectrally related preconditioners. These preconditioners leverage the limited informativeness of data in regularized PDE‐constrained optimization problems. A block Gauss–Seidel preconditioner is proposed for the GMRES‐based solution of the IP‐Gauss–Newton linear systems. It is shown, for a large‐class of PDE‐ and bound‐constrained optimization problems, that the spectrum of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix is asymptotically independent of discretization and is not impacted by the ill‐conditioning that notoriously plagues interior‐point methods. We exploit symmetry of the IP‐Gauss–Newton linear systems and propose a regularization and log‐barrier Hessian preconditioner for the preconditioned conjugate gradient (PCG)‐based solution of the equivalent IP‐Gauss–Newton–Schur complement linear systems. The eigenvalues of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix, that are not equal to one, are identical to the eigenvalues of the regularization and log‐barrier Hessian preconditioned Schur complement matrix. The scalability of the approach is demonstrated on two example problems. The numerical solution of these optimization problems is shown to require a discretization independent number of IP‐Gauss–Newton linear solves. Furthermore, the linear systems are solved in a discretization and IP ill‐conditioning independent number of preconditioned Krylov subspace iterations. The parallel scalability of the preconditioner, achieved via algebraic multigrid component solvers when applicable, and the aforementioned algorithmic scalability permits a parallel scalable means to compute solutions of a large class of PDE‐ and bound‐constrained problems.

PDE-constrained optimization↗
DOE OSTI2014

Cyclic steady states of treaded rolling bodies

The analysis of spinning axisymmetric bodies undergoing finite deformation is useful for understanding the behavior of a wide variety of engineering systems - for example, rolling tires. Furthermore, progress beyond the axisymmetric case has been lacking. In this work, we present a methodology for the treatment of treaded rolling bodies by devising a Newton-Krylov shooting scheme for the computation of cyclic steady states of motion. The scheme advocated permits one to determine the entire transient (cyclically steady) motion of a spinning treaded body with consideration of viscoelasticity as well as contact. We demonstrate the viability of the method through three examples, (1) a viscoelastic cylinder with eight sinusoidal tread blocks, (2) a viscoelastic cylinder with 16 square tread blocks, and (3) a viscoelastic oval in which repeated contact and separation from a rigid plane excites distinct transient vibrational modes in the body during each cycle. For practical values of the viscoelastic relaxation time, the new approach is found to converge faster than the naïve approach of evolving an initial guess over many cycles until a cyclic steady state is reached.

42 ENGINEERING↗
DOE OSTI2016

An n -material thresholding method for improving integerness of solutions in topology optimization

It is common in solving topology optimization problems to replace an integer-valued characteristic function design field with the material volume fraction field, a real-valued approximation of the design field that permits "fictitious" mixtures of materials during intermediate iterations in the optimization process. This is reasonable so long as one can interpolate properties for such materials and so long as the final design is integer valued. For this purpose, we present a method for smoothly thresholding the volume fractions of an arbitrary number of material phases which specify the design. This method is trivial for two-material design problems, for example, the canonical topology design problem of specifying the presence or absence of a single material within a domain, but it becomes more complex when three or more materials are used, as often occurs in material design problems. We take advantage of the similarity in properties between the volume fractions and the barycentric coordinates on a simplex to derive a thresholding, method which is applicable to an arbitrary number of materials. As we show in a sensitivity analysis, this method has smooth derivatives, allowing it to be used in gradient-based optimization algorithms. Finally, we present results, which show synergistic effects when used with Solid Isotropic Material with Penalty and Rational Approximation of Material Properties material interpolation functions, popular methods of ensuring integerness of solutions.

42 ENGINEERING↗
DOE OSTI2016

Field-gradient partitioning for fracture and frictional contact in the material point method: Field-gradient partitioning for fracture and frictional contact in the material point method [Fracture and frictional contact in material point method using damage-field gradients for velocity-field partitioning]

Contact and fracture in the material point method require grid-scale enrichment or partitioning of material into distinct velocity fields to allow for displacement or velocity discontinuities at a material interface. We present a new method which a kernel-based damage field is constructed from the particle data. The gradient of this field is used to dynamically repartition the material into contact pairs at each node. Our approach avoids the need to construct and evolve explicit cracks or contact surfaces and is therefore well suited to problems involving complex 3-D fracture with crack branching and coalescence. A straightforward extension of this approach permits frictional ‘self-contact’ between surfaces that are initially part of a single velocity field, enabling more accurate simulation of granular flow, porous compaction, fragmentation, and comminution of brittle materials. Finally, numerical simulations of self contact and dynamic crack propagation are presented to demonstrate the accuracy of the approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Peridynamic bond-associated correspondence model: Stability and convergence properties

The correspondence approach is a powerful technique that permits the usage of standard constitutive models from local theory within a peridynamic formulation. However, the conventional correspondence formulation suffers from material instability, i.e. zero-energy modes, that must be controlled for it to be applied in practice. The recently-introduced correspondence reformulation based on the use of a bond-associated deformation gradient can inherently remove the material instability. In this paper, we characterize some important properties, i.e. balance of linear momentum, balance of angular momentum and material stability, of the bond-associated correspondence model. The convergence behavior is also examined. Here, the accuracy of this approach is further demonstrated by comparing model predictions against local reference solutions and results from the conventional correspondence model with penalty stabilization for both two-dimensional and three-dimensional problems.

42 ENGINEERING↗
DOE OSTI2020

Probabilistic learning and updating of a digital twin for composite material systems

This paper presents an approach for characterizing and estimating statistical dependence between a large number of observables in a composite material system. Conditional regression is carried out using the estimated joint density function, permitting a systematic exploration of interdependence between fine scale and coarse observables that can be used for both prognosis and design of complex material systems. An example demonstrates the integration of experimental data with a computational database. The statistical approach is based on the probabilistic learning on manifolds recently developed by the authors. This approach leverages intrinsic structure detected through diffusion on graphs with projected stochastic differential equations to generate samples constrained to that structure.

42 ENGINEERING↗
DOE OSTI2022

A neural network‐enhanced reproducing kernel particle method for modeling strain localization

Abstract Modeling the localized intensive deformation in a damaged solid requires highly refined discretization for accurate prediction, which significantly increases the computational cost. Although adaptive model refinement can be employed for enhanced effectiveness, it is cumbersome for the traditional mesh‐based methods to perform while modeling the evolving localizations. In this work, neural network‐enhanced reproducing kernel particle method (NN‐RKPM) is proposed, where the location, orientation, and shape of the solution transition near a localization is automatically captured by the NN approximation via a block‐level neural network (NN) optimization. The weights and biases in the blocked parameterization network control the location and orientation of the localization. The designed basic four‐kernel NN block is capable of capturing a triple junction or a quadruple junction topological pattern, while more complicated localization topological patters are captured by the superposition of multiple four‐kernel NN blocks. The standard RK approximation is then utilized to approximate the smooth part of the solution, which permits a much coarser discretization than the high‐resolution discretization needed to capture sharp solution transitions with the conventional methods. A regularization of the NN approximation is additionally introduced for discretization‐independent material responses. The effectiveness of the proposed NN‐RKPM is verified by a series of numerical verifications.

Baek, Jonghyuk↗
DOE OSTI2021

Improve durability and surface quality of additively manufactured molds using carbon fiber prepreg

Hybrid tooling is an emerging concept introduced in the aerospace industries to reduce weight and cost of traditional tools. A hybrid tool features a skin, which provides desired surface quality, durability, and a low-density substrate to reduce the weight of the mold. The big area additive manufacturing (BAAM) technology permits rapid production of thermoplastic polymer intensive large-scale structures. The present study features a carbon fiber reinforced polyphenylene sulfide (CF-PPS) substrate fabricated using Oak Ridge National Laboratory's BAAM system. Carbon fiber-bismaleimide (CF-BMI) prepreg skin was then bonded to the BAAM tool through high-pressure autoclave molding. Process optimization was conducted to improve the bonding between CF-PPS and CF-BMI (transverse tensile strength increased from 0.54 to 4.8 MPa). Durability of the mold was demonstrated from fabricating seven (7) carbon fiber-Huntsman epoxy hand lay-up parts utilizing the mold.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Registration of the sorghum carbon–partitioning nested association mapping (CP–NAM) population

The sorghum [ Sorghum bicolor (L.) Moench] carbon-partitioning nested association mapping (CP_NAM) (Reg. no. MP-4, NSL 542189 MAP) population was developed at Clemson University, SC, using 11 diverse, male founder accessions, each crossed with a recurrent female parent ‘Grassl’. The male parents represent all five major botanical races and the four major agronomic types: cellulosic (5), sweet (3), grain (2) and forage (1). A set of 11 recombinant inbred line (RIL) families CP_NAM01 to CP_NAM011 were maintained, which consisted of 2,484 (F 6 ) individuals. Each RIL family contained a minimum of 193 individuals (CP_NAM01) and a maximum of 287 individuals (CP_NAM06). For the development of this population, the founder lines were judiciously selected from the sorghum Bioenergy Association Panel based on carbon-partitioning phenotypes that make this population an ideal genetic resource for dissecting a wide range of agronomic and compositional traits for basic and applied research. The founder accessions of the CP_NAM were phenotypically characterized for various traits, including agronomic, biomass and related components, and additional compositional components. Each of the 11 F 6 RIL families of the CP_NAM were genotyped using genotyping-by-sequencing analysis, and 144,087 single nucleotide polymorphisms were generated for each individual. Genotypic information along with phenotypic data were used for the characterization of this population and to explore the range of phenotypes that permits the understanding of carbon-partitioning dynamics. This population is a unique resource for researchers to study a wide range of contrasting carbon-partitioning characteristics in sorghum to understand the genetic architecture underlying whole-plant carbon partitioning and allocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Morpheus Spectral Counter: A computational tool for label-free quantitative mass spectrometry using the Morpheus search engine

Label-free quantitative MS based on the Normalized Spectral Abundance Factor (NSAF) has emerged as a straightforward and robust method to determine the relative abundance of individual proteins within complex mixtures. Here, we present Morpheus Spectral Counter (MSpC) as the first computational tool that directly calculates NSAF values from output obtained from Morpheus, a fast, open-source, peptide-MS/MS matching engine compatible with high-resolution accurate-mass instruments. NSAF has distinct advantages over other MS-based quantification methods, including a higher dynamic range as compared to isobaric tags, no requirement to align and re-extract MS1 peaks, and increased speed. MSpC features an easy to use graphic user interface that additionally calculates both distributed and unique NSAF values to permit analyses of both protein families and isoforms/proteoforms. MSpC determinations of protein concentration were linear over several orders of magnitude based on the analysis of several high-mass accuracy datasets either obtained from PRIDE or generated with total cell extracts spiked with purified Arabidopsis 20S proteasomes. Lastly, the MSpC software was developed in C# and is open sourced under a permissive license with the code made available at http://dcgemperline.github.io/Morpheus_SpC/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Building and testing correlations for the estimation of one‐electron reduction potentials of a diverse set of organic molecules

We describe and evaluate a method for computationally predicting reduction potentials of a diverse group of organic molecules by linearly correlating calculated lowest unoccupied molecular orbital energies with ground state reduction potentials measured in acetonitrile. The approach is shown to provide a unique combination of extreme computational simplicity and excellent accuracy across a diverse range of organic structures and a wide window of reduction potentials. A disparate set of molecules (74 compounds belonging to six distinct structural families, comprised of molecules containing C, H, N, O, F, Cl, and Br, with functional groups including esters, ketones, halides, nitriles, quinones, alkenes, arenes, heteroarenes, and pyridinium and higher benzologs, all containing conjugated pi systems, spanning a 3.5‐V range of reduction potentials) was used to build the correlations. This methodology was found to be computationally inexpensive compared with other approaches and to permit the useful prediction of reduction potentials of additional molecules of diverse structural types not included in the families used to determine the correlation parameters. The effects of varying the basis set used in the B3LYP electronic structure calculations and including solvent (compared with calculations in gas phase) were also examined. It was found that the inclusion of a continuum solvent model in the calculations was required for accurate results, particularly when including cationic species in the correlations (although when only neutral molecules were examined, reasonable results could even be obtained in vacuo ). Several of the best correlations were used to predict the reduction potentials of seven much larger and structurally diverse chromophores that were not included in the correlation data set. Strong correlations ( r 2 values > 0.99) with very good predictive abilities (root mean square deviation < 60 mV) were found. This extremely simple and computationally efficient entirely closed‐shell methodology is proven robust and useful for the design of new molecules capable of participating in redox processes, including electron transfer reactions. Copyright © 2015 John Wiley & Sons, Ltd.

Méndez‐Hernández, Dalvin D.↗
DOE OSTI2019

Ultra-High Fidelity Laser-Induced Air Shock from Energetic Materials

Recent interest in the implementation of the Laser-induced Air Shock from Energetic Materials (LASEM) technique prompted an investigation using ultra-high-speed imaging diagnostics to provide early-time (sub-μs) shock-wave-radius-versus-time data necessary to accurately determine the characteristic laser-induced-shock velocity (y-intercept) for high explosives (HE) of interest. Ultra-high-speed focused-shadowgraphy images were collected from nanosecond-pulsed laser-ablated samples of HE similar to those in the published literature. Shadowgraphy images were collected using interframe times ranging from 50–750 ns, with exposure times of 5 ns. Acquired shock-wave-radius-versus-time data permitted a high-fidelity assessment of the shock wave velocity produced at the characteristic radius of the generated laser-plasma pulse. The resulting data from eight different HE indicated that early-time energy contributions and the resulting laser-induced shock velocity profiles produced from ablation of the HE material were indistinguishable amongst the explosives tested for the majority of the time domain characterized (0–12 μs).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗