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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Optimal design and dispatch of a system of diesel generators, photovoltaics and batteries for remote locations

Renewable energy technologies, specifically, solar photovoltaic cells, combined with battery storage and diesel generators, form a hybrid system capable of independently powering remote locations, i.e., those isolated from larger grids. If sized correctly, hybrid systems reduce fuel consumption compared to diesel generator-only alternatives. We present an optimization model for establishing a hybrid power design and dispatch strategy for remote locations, such as a military forward operating base, that models the acquisition of different power technologies as integer variables and their operation using nonlinear expressions. Our cost-minimizing, nonconvex, mixed-integer, nonlinear program contains a detailed battery model. Due to its complexities, we present linearizations, which include exact and convex under-estimation techniques, and a heuristic, which determines an initial feasible solution to serve as a “warm start” for the solver. We determine, in a few hours at most, solutions within 5% of optimality for a candidate set of technologies; these solutions closely resemble those from the nonlinear model. Lastly, our instances contain real data spanning a yearly horizon at hour fidelity and demonstrate that a hybrid system could reduce fuel consumption by as much as 50% compared to a generator-only solution.

14 SOLAR ENERGY↗
DOE OSTI2018

Numerical integration method for triple integrals using the second kind Chebyshev wavelets and Gauss–Legendre quadrature

In this paper, a computational method combining the second kind Chebyshev wavelets and Gauss–Legendre quadrature is proposed for numerical integrations of arbitrary functions over regions like cuboid, tetrahedron, cylinder, cone, paraboloid and ellipsoid. Gauss–Legendre quadrature is used to convert a triple integral into a double integral and integral regions are transformed to the standard integration region by linear and nonlinear transformation. Moreover, convergence and accuracy estimation of the second kind Chebyshev wavelets expansion of two dimensions is given. Illustrative examples have been demonstrated to show the applicability and accuracy of the present method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Trunk muscle forces and spinal loads while walking in persons with lower limb amputation: Influences of chronic low back pain

Persons with lower limb amputation (LLA) are at high risk for developing chronic low back pain (LBP), often with biomechanical factors considered as likely contributors. Here, trunk and pelvis kinematics, muscle forces, and resultant spinal loads were characterized in persons with LLA, with and without chronic LBP. Thirty-five persons with unilateral LLA – 19 with chronic LBP (“LLA-cLBP”), 16 without LBP (“LLA-nLBP”) – and 15 (uninjured) persons without LBP (“CTR-nLBP”) walked overground (1.3 m/s) while thorax and pelvis kinematics were tracked (and ranges of motion [ROM] computed), and used as inputs for a non-linear finite element model of the spine to estimate global and local muscle forces, and resultant spinal loads. In the frontal and transverse planes, thorax ROM were up to 66.6% smaller in LLA-nLBP versus LLA-cLBP (P < 0.001) and CTR-nLBP (P < 0.001). In the sagittal plane, pelvis ROM was 50.4% smaller in LLA-nLBP versus LLA-cLBP (P = 0.014). LLA-cLBP exhibited 45.5% and 34.2% greater peak local and global muscle forces, respectively, versus CTR-nLBP (P < 0.011). Up to 48.1% greater spinal loads were observed in LLA-cLBP versus CTR-nLBP (P < 0.013); peak compression and local muscle forces were respectively 20.2% and 41.0% larger in LLA-nLBP versus CTR-nLBP (P < 0.005). Despite differences in trunk and pelvis kinematics between LLA-cLBP and LLA-nLBP, trunk muscle forces and spinal loads were similar (P > 0.101) between these groups. Similar loading parameters regardless of LBP presence, while highly dependent on trunk muscle activation strategies, may mitigate further accumulation of mechanical fatigue. Finally, it remains important to understand the temporality of loading with respect to LBP onset following LLA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Numerical Analysis of Experiments on Thermally Induced Dissociation of Methane Hydrates in Porous Media

Numerical simulation is essential for the prediction and evaluation of hydrocarbon reservoir performance. Numerical simulators developed for the description of the behavior of hydrates under production and the corresponding flow of fluids and heat accounting for all known processes are powerful, but they need validation through comparison to field or experimental data in order to instill confidence in their predictions. In this study, we analyze by means of numerical simulation the results of an experiment of methane hydrate dissociation by thermal stimulation in unconsolidated porous media heated through the vessel walls. The physics captured by the model include multicomponent heat and mass transfer, multiphase flow through porous media, and the phase behavior of the CH 4 + H 2 O system involved in methane hydrate formation and dissociation. The set of governing equations consists of the mass and energy conservation equations coupled with constitutive relationships, i.e., the dissolution of gas in H 2 O, relative permeability and capillary pressure models, composite thermal conductivity models, and methane hydrate phase equilibria. The model geometry describes accurately the hydrate reactor used in a recent experimental study investigating methane hydrate dissociation behavior [Chong et. al. Appl. Energy 2016, 177, 409-421]. The cumulative gas production is estimated and validated against three tests of experimental data involving different boundary temperatures, showing a good agreement between observations and numerical predictions. The predicted evolution of the spatial distributions of different phases over time shows that hydrate dissociation progresses inward from the reactor boundary to the center, methane gas accumulates to the top of the reactor because of buoyancy, and water migrates down to the bottom of the reactor because of gravity. A sharp hydrate dissociation front is predicted, and the estimated location of hydrate dissociation front suggests a linear relationship with the square root of time. A sensitivity analysis on the thermal conductivity of sand under fully saturated conditions is conducted to elucidate its effect on the gas production behavior. In addition, the energy efficiency ratio computed from the simulation of this boundary-wall heating technique varies from 14.0 to 16.2. Deviations between observations and predictions of the evolution of the temperature profile are attributed to initial heterogeneous distribution of the hydrate phase in the hydrate reactor.

42 ENGINEERING↗
DOE OSTI2014

Tuning the local temperature during feedback controlled electromigration in gold nanowires

Feedback controlled electromigration (FCE) in metallic nanowires has been widely used for various purposes. However, the control of the local temperature during FCE remains a challenge. Here, we report that the environment temperature can be used as a knob to tune the local temperature during FCE in gold nanowires. FCE was performed in gold nanowires at various environment temperatures ranging from 4.2 K to 300 K. We find that the dissipated power normalized by the cross section area of the nano constriction is linearly proportional to the environment temperature. Interestingly, the estimated local maximum temperature parabolically depends on the environment temperature. A minimum in the local temperature can be reached if an appropriate environment temperature is chosen. Our findings are well supported by the finite element simulation. Moreover, the data indicates the coupling between FCE triggering current density and local temperature.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Impact of post-Born lensing on the CMB

Lensing of the CMB is affected by post-Born lensing, producing corrections to the convergence power spectrum and introducing field rotation. We show numerically that the lensing convergence power spectrum is affected at the ∼< 0.2% level on accessible scales, and that this correction and the field rotation are negligible for observations with arcminute beam and noise levels ∼> 1 μK arcmin. The field rotation generates ∼ 2.5% of the total lensing B-mode polarization amplitude (0.2% in power on small scales), but has a blue spectrum on large scales, making it highly subdominant to the convergence B modes on scales where they are a source of confusion for the signal from primordial gravitational waves. Since the post-Born signal is non-linear, it also generates a bispectrum with the convergence. We show that the post-Born contributions to the bispectrum substantially change the shape predicted from large-scale structure non-linearities alone, and hence must be included to estimate the expected total signal and impact of bispectrum biases on CMB lensing reconstruction quadratic estimators and other observables. The field-rotation power spectrum only becomes potentially detectable for noise levels || 1 μK arcmin, but its bispectrum with the convergence may be observable at ∼ 3σ with Stage IV observations. Rotation-induced and convergence-induced B modes are slightly correlated by the bispectrum, and the bispectrum also produces additional contributions to the lensed BB power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Study of ion-gyroscale fluctuations in low-density L-mode plasmas heated by NBI on KSTAR

Broadband density fluctuations with peak frequency ranging from 150 to 400 kHz were measured using a multichannel microwave imaging reflectometer in core region of the low-density L-mode plasmas heated by neutral beam injection on KSTAR. These fluctuations have been studied by comparing the dominant mode scales estimated from the measurement with those predicted from linear gyrokinetic simulation. The measured poloidal wavenumbers are qualitatively comparable to those of the 'fastest growing modes' from simulations, whereas they are larger than those of the 'transport-dominant modes' by about a factor of three. The agreement on wavenumbers between the measurement and linear simulation (for the fastest growing modes) is probably due to sufficiently weak $E \times B$ flow shear compared to the maximum linear growth rate. Meanwhile, the transport-dominant modes seem to be related to the fluctuations in lower frequencies (~80–150 kHz) observed in some of the measurement.

Physics↗
DOE OSTI2021

Influence of inhomogeneous stochasticity on the falsifiability of mean-field theories and examples from accretion disc modelling

ABSTRACT Despite spatial and temporal fluctuations in turbulent astrophysical systems, mean-field theories can be used to describe their secular evolution. However, observations taken over time scales much shorter than dynamical time scales capture a system in a single state of its turbulence ensemble. Comparing with mean-field theory can falsify the latter only if the theory is additionally supplied with a quantified precision. The central limit theorem provides appropriate estimates to the precision only when fluctuations contribute linearly to an observable and with constant coherent scales. Here, we introduce an error propagation formula that relaxes both limitations, allowing for non-linear functional forms of observables and inhomogeneous coherent scales and amplitudes of fluctuations. The method is exemplified in the context of accretion disc theories, where inhomogeneous fluctuations in the surface temperature are propagated to the disc emission spectrum – the latter being a non-linear and non-local function of the former. The derived precision depends non-monotonically on emission frequency. Using the same method, we investigate how binned spectral fluctuations in telescope data change with the spectral resolving power. We discuss the broader implications for falsifiability of a mean-field theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Nonlinear Photovoltaic Degradation Rates: Modeling and Comparison Against Conventional Methods

Although common practice for estimating photovoltaic (PV) degradation rate (RD) assumes a linear behavior, field data have shown that degradation rates are frequently nonlinear. This article presents a new methodology to detect and calculate nonlinear RD based on PV performance time-series from nine different systems over an eight-year period. Prior to performing the analysis and in order to adjust model parameters to reflect actual PV operation, synthetic datasets were utilized for calibration purposes. A change-point analysis is then applied to detect changes in the slopes of PV trends, which are extracted from constructed performance ratio (PR) time-series. Once the number and location of change points is found, the ordinary least squares method is applied to the different segments to compute the corresponding rates. The obtained results verified that the extracted trends from the PR time-series may not always be linear and therefore, “nonconventional” models need to be applied. All thin-film technologies demonstrated nonlinear behavior whereas nonlinearity detected in the crystalline silicon systems is thought to be due to a maintenance event. A comparative analysis between the new methodology and other conventional methods demonstrated levelized cost of energy differences of up to 6.14%, highlighting the importance of considering nonlinear degradation behavior

14 SOLAR ENERGY↗
DOE OSTI2015

Predicting the Onset of Flash Sintering

Analyzing the temperature trajectory during flash sintering, this study demonstrates that Joule heating alone is responsible for thermal runaway that is the most likely cause for rapid densification. The calculated onset temperature T on is in good agreement with the literature data. As predicted by the analysis the T on data follow a 1/ T on ~log(field) linear dependence, which affords an expeditious means to estimate the activation energy of resistivity/conductivity of the sintered ceramics.

Dong, Yanhao↗
DOE OSTI2024

CONSTRAINT-INDEPENDENT CONSTANT CTOA DETERMINATION FOR DUCTILE STABLE CRACK GROWTH

Crack tip opening angle (CTOA) has been used as a reliable fracture toughness parameter for decades to characterize stable ductile crack growth for thin-walled aerospace structures in the low-constraint conditions. Recently, the CTOA parameter was also applied to the pipeline industry, and a CTOA test standard ASTM E3039 was thus developed for testing a critical constant CTOA. Research showed that the constant CTOA can reasonably describe fracture toughness required to arrest a dynamic crack propagation for a modern gas pipeline. However, the CTOA fracture criterion requires constraint-independent CTOA toughness against stable ductile crack growth. ASTM E3039 recommends a drop weight tearing test (DWTT) specimen for CTOA testing. Since a shallow crack is used, DWTT measured CTOA may depend on constraint level at the crack tip. To understand if it is the case, this paper evaluates the critical CTOA for a set of fracture toughness tests on single edge notched bend (SENB) specimens with shallow and deep cracks based on four CTOA estimation models. In which, the Ln(P)-LLD linear fit model is similar to that used by ASTM E3039 in the CTOA calculation. Fracture test data for X80 pipeline steel and HY80 structural steel are considered in the CTOA evaluation. The results show that the four CTOA models can determine a crack size-independent constant CTOA over stable ductile crack growth for the SENB specimens. As a result, CTOA determined by ASTM E3039 is constraint&#x2;independent and transferable to use for an actual crack propagating in a gas pipeline.

Zhu, Xian-Kui↗
DOE OSTI2015

TU-F-CAMPUS-T-01: Potential of Using Cerium Oxide Nanoparticles (CONP) for Protecting Healthy Tissue During Accelerated Partial Breast Irradiation (APBI)

Purpose: The purpose of this research is to investigate the feasibility of using targeted cerium oxide nanoparticles (CONP) during APBI to protect healthy cells. Methods: In one approach, CONP are assumed to be incorporated in a micrometer-thick polymer film on the surface of routinely used mammosite balloon applicators for sustained in-situ release of the CONP. In case two, CONPs are administered directly into the lumpectomy cavity. The concentration of H{sub 2}O{sub 2} produced by ionizing radiation was estimated from previously published work using short range linear extrapolation. The assessment of CONPs concentration required to absorb corresponding H{sub 2}O{sub 2} to protect healthy tissue was calculated. Fick’s Second law of diffusion was employed to determine the initial concentration of CONP needed to achieve the minimum concentration for radioprotection at distance 1 cm and 2 cm from the lumpectomy cavity during APBI. The study was carried out for different nanoparticle sizes. Results: The initial concentration of CONPs required to get desired radioprotection concentration at 1 cm and 2 cm after 7 days was found to be 0.4089 mg per Kg and 59.7605 g per Kg respectively for 2 nm size nanoparticles. Using concentrations of 5 mg per kg of CONP that have been shown to be used to confer radioprotection (for about 7.97 Gy) in experiments it was observed that 4.5631, 8.5286, 10.9247, 22.0408, 43.6796 and 65.5618 number of days are required to achieve radioprotection at 1 cm for CONP of sizes 2 nm, 3.8 nm, 5 nm, 10 nm, 20 nm, 30 nm, respectively. Conclusion: Our preliminary results show that smaller size (2 nm and 3.8 nm) CONP would be suitable as radio protectant during APBI because they took a reasonable number of days, i.e. less than 10 days to reach tissues of 1 cm or 2 cm thickness.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-D-204-06: An Open Source ImageJ CatPhan Analysis Tool

Purpose: The CatPhan is a popular QA device for assessing CT image quality. There are a number of software options which perform analysis of the CatPhan. However, there is often little ability for the user to adjust the analysis if it isn’t running properly, and these are all expensive options. An open source tool is an effective solution. Methods: To use the software, the user imports the CT as an image sequence in ImageJ. The user then scrolls to the slice with the lateral dots. The user then runs the plugin. If tolerance constraints are not already created, the user is prompted to enter them or to use generic tolerances. Upon completion of the analysis, the plugin calls pdfLaTex to compile the pdf report. There is a csv version of the report as well. A log of the results from all CatPhan scans is kept as a csv file. The user can use this to baseline the machine. Results: The tool is capable of detecting the orientation of the phantom. If the CatPhan was scanned backwards, one can simply flip the stack of images horizontally and proceed with the analysis. The analysis includes Sensitometry (estimating the effective beam energy), HU values and linearity, Low Contrast Visibility (using LDPE & Polystyrene), Contrast Scale, Geometric Accuracy, Slice Thickness Accuracy, Spatial resolution (giving the MTF using the line pairs as well as the point spread function), CNR, Low Contrast Detectability (including the raw data), Uniformity (including the Cupping Effect). Conclusion: This is a robust tool that analyzes more components of the CatPhan than other software options (with the exception of ImageOwl). It produces an elegant pdf and keeps a log of analyses for long-term tracking of the system. Because it is open source, users are able to customize any component of it.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Scaled Vecchia Approximation for Fast Computer-Model Emulation

Many scientific phenomena are studied using computer experiments consisting of multiple runs of a computer model while varying the input settings. Gaussian processes (GPs) are a popular tool for the analysis of computer experiments, enabling interpolation between input settings, but direct GP inference is computationally infeasible for large datasets. We adapt and extend a powerful class of GP methods from spatial statistics to enable the scalable analysis and emulation of large computer experiments. Specifically, we apply Vecchia’s ordered conditional approximation in a transformed input space, with each input scaled according to how strongly it relates to the computer-model response. The scaling is learned from the data by estimating parameters in the GP covariance function using Fisher scoring. Our methods are highly scalable, enabling estimation, joint prediction, and simulation in near-linear time in the number of model runs. In several numerical examples, our approach substantially outperformed existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects

Abstract Of great relevance to climate engineering is the systematic relationship between the radiative forcing to the climate system and the response of the system, a relationship often represented by the linear response function (LRF) of the system. However, estimating the LRF often becomes an ill-posed inverse problem due to high-dimensionality and nonunique relationships between the forcing and response. Recent advances in machine learning make it possible to address the ill-posed inverse problem through regularization and sparse system fitting. Here, we develop a convolutional neural network (CNN) for regularized inversion. The CNN is trained using the surface temperature responses from a set of Green’s function perturbation experiments as imagery input data together with data sample densification. The resulting CNN model can infer the forcing pattern responsible for the temperature response from out-of-sample forcing scenarios. This promising proof of concept suggests a possible strategy for estimating the optimal forcing to negate certain undesirable effects of climate change. The limited success of this effort underscores the challenges of solving an inverse problem for a climate system with inherent nonlinearity. Significance Statement Predicting the climate response for a given climate forcing is a direct problem, while inferring the forcing for a given desired climate response is often an inverse, ill-posed, problem, posing a new challenge to the climate community. This study makes the first attempt to infer the radiative forcing for a given target pattern of global surface temperature response using a deep learning approach. The resulting deeply trained convolutional neural network inversion model shows promise in capturing the forcing pattern corresponding to a given surface temperature response, with a significant implication on the design of an optimal solar radiation management strategy for curbing global warming. This study also highlights the technical challenges that future research should prioritize in seeking feasible solutions to the inverse climate problem.

Ren, Huiying↗
DOE OSTI2018

Non-Linear Langevin and Fractional Fokker–Planck Equations for Anomalous Diffusion by Lévy Stable Processes

The numerical solutions to a non-linear Fractional Fokker–Planck (FFP) equation are studied estimating the generalized diffusion coefficients. The aim is to model anomalous diffusion using an FFP description with fractional velocity derivatives and Langevin dynamics where Lévy fluctuations are introduced to model the effect of non-local transport due to fractional diffusion in velocity space. Distribution functions are found using numerical means for varying degrees of fractionality of the stable Lévy distribution as solutions to the FFP equation. The statistical properties of the distribution functions are assessed by a generalized normalized expectation measure and entropy and modified transport coefficient. The transport coefficient significantly increases with decreasing fractality which is corroborated by analysis of experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Determination of Constraint-Independent Crack Tip Opening Angle for Stable Crack Growth in High-Strength Ductile Steels

The crack tip opening angle (CTOA) is one of fracture toughness parameters that has been used for decades in describing large stable crack growth in thin-walled aerospace structures under the low-constraint conditions. Recently, the pipeline industry has developed a growing interest in using the CTOA parameter to serve as the minimum required fracture toughness to arrest dynamic crack propagation in modern gas transmission pipelines made of high-strength ductile steel. To meet this industrial need, the CTOA test standard ASTM E3039 was therefore developed for measuring the constant critical CTOA. ASTM E3039 recommends a drop weight tearing test (DWTT) specimen with a shallow crack for standard CTOA testing, but its CTOA may depend on the low constraint condition of the DWTT specimen at the crack tip. Verifying the constraint independence of the DWTT-measured CTOA thus becomes indispensable for applying CTOA toughness to the running fracture control in the pipeline design. For this purpose, the present paper evaluates critical CTOA values in a set of fracture toughness tests on single-edge notched bend (SENB) specimens with shallow and deep cracks, based on four CTOA estimation models. Among these, the Ln(P)-LLD linear fit model is similar to that recommended by ASTM E3039 for CTOA calculation. Fracture test data for X80 pipeline steel and HY80 structural steel were considered in the CTOA evaluation. The results showed that the four CTOA models were able to determine a constraint independent CTOA value for stable crack growth in the SENB specimens. As a result, a single, reliable, constant CTOA value could be determined regardless of the specimen geometry or the crack-tip constraint conditions. Therefore, the CTOA measured using ASTM E3039 is constraint-independent and transferable to use in cases of actual cracks propagating in gas transmission pipelines.

36 MATERIALS SCIENCE↗