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Results for “dynamic parameter estimation”

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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

On the effect of conductivity of a shock-compressed gas on interferometric recording of parameters of motion of a liner

We report on the results of a study of the acceleration dynamics of an aluminum liner to a velocity of 5.5 km/s using continuous recording of velocity (velocity interferometer system for any reflector (VISAR) and Fabry-Perot interferometer) and motion trajectory (radiointerferometer and resistive transducer) in air and in a helium atmosphere. It is found that for liner velocities exceeding 4.0 and 5.0 km/s, the displacement of the shock wave front is recorded by the radiointerferometer in air and helium, respectively. At these velocities, the conductivities of air and helium behind the shock wave front are estimated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

SU-E-J-77: Dose Tracking On An MR-Linac for Online QA and Plan Adaptation in Abdominal Organs

Recent developments made MRI-guided radiotherapy feasible. Simultaneously performed imaging during dose delivery reveals the influence of changes in anatomy not yet known at the planning stage. When targeting highly motile abdominal organs, respiratory gating is commonly employed in MRI and investigated in external beam radiotherapy to mitigate malicious motion effects. The purpose of the presented work is to investigate anatomy-adaptive dose reconstruction in the treatment of abdominalorgans using concurrent (duplex) gating of an integrated MRlinac modality.Using navigators, 3D-MR images were sampled during exhale phase, requiring 3s per axial volume (360×260×100mm{sup 3}, waterselective T1w-FFE). Deformation vector fields (DVF) were calculated for all imaging dynamics with respect to initial anatomy, yielding an estimation of anatomy changes over the time of a fraction. A pseudo-CT was generated from the outline of a reference MR image, assuming a water-filled body. Consecutively, a treatment was planned on a fictional kidney lesion and optimized simulating a 6MV linac in a 1.5T magnetic field. After delivery, using the DVF, the pseudo-CT was deformed and dose accumulated for every individual gating interval yielding the true accumulated dose on the dynamic anatomy during beam-on.Dose-volume parameters on the PTV show only moderate changes when incorporating motion, i.e. ΔD{sub 99} (GTV)=0.3Gy with D{sub 99} (GTV)=20Gy constraints. However, local differences in the PTV region showed underdosages as high as 2.7Gy and overdosages up to 1.4Gy as compared to the optimized dose on static anatomy.A dose reconstruction toolchain was successfully implemented and proved its potential in the duplex gated treatment of abdominal organs by means of an MR-linac modality. While primary dose constraints were not violated on the fictional test data, large deviations could be found locally, which are left unaccounted for in conventional treatments. Dose-tracking of both target structures and organs at risk using 3D MRI during treatment enables truly adaptive hypofractionated radiotherapy. This work was funded by the SoRTS consortium, which includes the industry partners Elekta, Philips and Technolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Spark-Assisted HCCI Residential CHP

A transformative small spark ignition (SI) internal combustion (IC) engine fueled with natural gas was developed for combined heat and power (CHP) applications using a combination of cycle simulations, computational fluid dynamics (CFD) modeling, and engine experiments. The resulting 1 kW CHP engine was demonstrated to achieve 36.1% brake thermal efficiency (BTE) while meeting aggressive exhaust emissions targets using a low-cost three-way catalyst. Starting from a “clean-sheet” design, modeling tools were used to select the optimal engine parameters and operating characteristics. The disruptive technologies developed for the CHP system have a target lifetime of at least 10 years. The engine cost at volume of 10,000 units was estimated to be $\$$1,050. A combination of experimental and simulation results were used to identify a path to the program target of 38.6% BTE. Base engine design parameters (i.e., displacement, speed, bore, stroke, valve timings, and compression ratio) were optimized to reduce friction, heat transfer, and exhaust losses. The base clean sheet prototype engine achieved 32% BTE. Optimization of the lube oil and coolant temperatures added 1.8% BTE. The addition of exhaust gas recirculation added 1.1% BTE. Novel thermal barrier coatings (TBCs) developed over the course of the project added 1.2% BTE. Further improvements in engine friction reduction (1.3% BTE) and improved combustion (1.2% BTE) are estimated to meet the program target 38.6% BTE, while also meeting the stringent criteria pollutant emissions targets.

42 ENGINEERING↗
DOE OSTI2012

Wildfire Risk Mapping over the State of Mississippi: Land Surface Modeling Approach

Three fire risk indexes based on soil moisture estimates were applied to simulate wildfire probability over the southern part of Mississippi using the logistic regression approach. The fire indexes were retrieved from: (1) accumulated difference between daily precipitation and potential evapotranspiration (P-E); (2) top 10 cm soil moisture content simulated by the Mosaic land surface model; and (3) the Keetch-Byram drought index (KBDI). The P-E, KBDI, and soil moisture based indexes were estimated from gridded atmospheric and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). Normalized deviations of these indexes from the 31-year mean (1980-2010) were fitted into the logistic regression model describing probability of wildfires occurrence as a function of the fire index. It was assumed that such normalization provides more robust and adequate description of temporal dynamics of soil moisture anomalies than the original (not normalized) set of indexes. The logistic model parameters were evaluated for 0.25 x0.25 latitude/longitude cells and for probability representing at least one fire event occurred during 5 consecutive days. A 23-year (1986-2008) forest fires record was used. Two periods were selected and examined (January mid June and mid September December). The application of the logistic model provides an overall good agreement between empirical/observed and model-fitted fire probabilities over the study area during both seasons. The fire risk indexes based on the top 10 cm soil moisture and KBDI have the largest impact on the wildfire odds (increasing it by almost 2 times in response to each unit change of the corresponding fire risk index during January mid June period and by nearly 1.5 times during mid September-December) observed over 0.25 x0.25 cells located along the state of Mississippi Coast line. This result suggests a rather strong control of fire risk indexes on fire occurrence probability over this region.

forest fire risk↗
DOE OSTI2025

Parameterizing empirical interatomic potentials for predicting thermophysical properties via an irreducible derivative approach: the case of ThO 2 and UO 2

The accuracy of classical physical property predictions using molecular dynamics simulations is determined by the quality of the interatomic potentials. Here we introduce a training approach for empirical interatomic potentials (EIPs) which is well suited for capturing phonons and phonon-related properties. Our approach is based on direct comparisons of the second- and third-order irreducible derivatives (IDs) between an EIP and the Born–Oppenheimer potential within density functional theory (DFT) calculations. IDs fully exploit space group symmetry and allow for training without redundant information. We demonstrate the fidelity of our approach in the context of ThO 2 and UO 2 , where we optimize parameters of an embedded-atom method potential in addition to core–shell interactions. Our EIPs provide thermophysical properties in good agreement with DFT and outperform widely utilized EIPs for phonon dispersion and thermal conductivity predictions. Reasonable estimates of thermal expansion and formation energies of Frenkel pairs are also obtained.

empirical interatomic potential↗
DOE OSTI2016

Aging kinetics of levoglucosan orientational glass as a rate dispersion process and consequences for the heterogeneous dynamics view

Aging kinetics of a glass is currently modeled in terms of slowing of its α-relaxation dynamics, whose features are interpreted in terms of dynamic heterogeneity, i.e., formation and decay of spatially and temporally distinct nm-size regions. To test the merits of this view, we studied the calorimetric effects of aging an orientational glass of levoglucosan crystal in which such regions would not form in the same way as they form in liquids, and persist in structural glasses, because there is no liquid-like molecular diffusion in the crystal. By measuring the heat capacity, C{sub p}, we determined the change in the enthalpy, H, and the entropy, S, during two aging-protocols: (a) keeping the samples isothermally at temperature, T{sub a}, and measuring the changes after different aging times, t{sub a}, and (b) keeping the samples at different T{sub a}s and measuring the changes after the same t{sub a}. A model-free analysis of the data shows that as t{sub a} is increased (procedure (a)), H and S decrease according to a dispersive rate kinetics, and as T{sub a} is increased (procedure (b)), H and S first increase, reach a local maximum at a certain T{sub a}, and then decrease. Even though there is no translational diffusion to produce (liquid-like) free volume, and no translational-rotational decoupling, the aging features are indistinguishable from those of structural glasses. We also find that the Kohlrausch parameter, originally fitted to the glass-aging data, decreases with decrease in T{sub a}, which is incompatible with the current use of the aging data for estimating the α-relaxation time. We argue that the vibrational state of a glass is naturally incompatible with its configurational state, and both change on aging until they are compatible, in the equilibrium liquid. So, dipolar fluctuations seen as the α-relaxation would not be the same motions that cause aging. We suggest that aging kinetics is intrinsically dispersive with its own characteristic rate constant and it does not yield the α-relaxation rate. In this view, thermodynamic and other properties define the fictive temperature; the real or imaginary components of a dynamic property do not define it. While particles’ overall motions may still play a crucial role in (structural) glass physics, we conclude that translational diffusion alone is not a requirement for structure stabilization on aging of a kinetically frozen state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Study the Cyclic Plasticity Behavior of 508 LAS under Constant, Variable and Grid-Load-Following Loading Cycles for Fatigue Evaluation of PWR Components

This report provides an update of an earlier assessment of environmentally assisted fatigue for components in light water reactors. This report is a deliverable in September 2016 under the work package for environmentally assisted fatigue under DOE’s Light Water Reactor Sustainability program. In an April 2016 report, we presented a detailed thermal-mechanical stress analysis model for simulating the stress-strain state of a reactor pressure vessel and its nozzles under grid-load-following conditions. In this report, we provide stress-controlled fatigue test data for 508 LAS base metal alloy under different loading amplitudes (constant, variable, and random grid-load-following) and environmental conditions (in air or pressurized water reactor coolant water at 300°C). Also presented is a cyclic plasticity-based analytical model that can simultaneously capture the amplitude and time dependency of the component behavior under fatigue loading. Results related to both amplitude-dependent and amplitude-independent parameters are presented. The validation results for the analytical/mechanistic model are discussed. This report provides guidance for estimating time-dependent, amplitude-independent parameters related to material behavior under different service conditions. The developed mechanistic models and the reported material parameters can be used to conduct more accurate fatigue and ratcheting evaluation of reactor components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Analysis of a Li-Ion Nanobattery with Graphite Anode Using Molecular Dynamics Simulations

In this work, molecular dynamics simulations were performed of the initial charging of a Li-ion nanobattery with a graphite anode and lithium hexaflourphosphate (LiPF 6 ) salt dissolved in ethylene carbonate (CO 3 C 2 H 4 ) solvent as the electrolyte solution. The charging was achieved through the application of external electric fields simulating voltage sources. A variety of force fields were combined to simulate the materials of the nanobattery, including the solid electrolyte interphase, metal collectors, and insulator cover. Some of the force field parameters were estimated using ab initio methods and others were taken from the literature. We studied the behavior of Li-ions traveling from cathode to anode through electrolyte solutions of concentrations 1.15 and 3.36 M. Time-dependent variables such as energy, temperature, volume, polarization, and mean square displacement are reported; a few of these variables, as well as others such as current, resistance, current density, conductivity, and resistivity are reported as a function of the external field and charging voltage. A solid electrolyte interphase (SEI) layer was also added to the model to study the mechanism behind the diffusion of the Li-ions through the SEI. As the battery is charged, the depletion of Li atoms in the cathode and their accumulation in the anode follow a linear increase of the polarizability in the solvent, until reaching a saturation point after which the charging of the battery stops, i.e., the energy provided by the external source decays to very low levels. Lastly, the nanobattery model containing the most common materials of a commercial lithium-ion battery is very useful to determine atomistic information that is difficult or too expensive to obtain experimentally; available data shows consistency with our results.

25 ENERGY STORAGE↗
DOE OSTI2023

Thermal acclimation of plant photosynthesis and autotrophic respiration in a northern peatland

Peatlands contain one-third of global soil carbon (C), but the responses of peatland ecosystems to long-term warming are not well understood. Here, we pursue an emergent understanding of warming effects on ecosystem C fluxes at peatlands by constraining a process-oriented model, the terrestrial ECOsystem model, with observational data from a long-term warming experiment at the Spruce and Peatland Responses Under Changing Environments site. Model-based assessments show that ecosystem-level photosynthesis and autotrophic respiration exhibited significant thermal acclimation, with temperature sensitivities being linearly decreased with warming. Using the thermal-acclimated parameter values, simulated gross primary production, net primary production, and plant autotrophic respiration (R a ), were all lower than those simulated with non-thermal acclimated parameter values. In contrast, ecosystem respiration simulated with thermal acclimated parameter values was higher than that simulated with non-thermal acclimated parameter values. Net ecosystem CO 2 exchange was much higher after constraining model parameters with observational data from the warming treatments, releasing C at a rate of 28.3 g C m -2 yr -1 °C -1 . Our data-model integration study suggests that peatlands are likely to release more C than previously estimated. Earth system models may overestimate C uptake by peatlands under warming if physiological thermal acclimation of plants is not incorporated. Thus, it is critical to consider the long-term physiological thermal acclimation of plants in the models to better predict global C dynamics under future climate and their feedback to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

WE-AB-303-07: Computational Monitoring Framework of Four-Dimensional Dose Distributions During Treatment Time Based On a 2D/3D Registration with Adaptive Transformation Parameters in Lung Stereotactic Body Radiotherapy

Purpose: The aim of this study was to develop a computational framework for monitoring four-dimensional (4D) dose distributions during treatment time based on a 2D/3D registration with adaptive transformation parameters (ATPs) in lung stereotactic body radiotherapy (SBRT). Methods: The 4D dose distributions during the SBRT were calculated by applying a pencil beam convolution (PBC) algorithm to simulated 4D-computed tomography (CT) images during treatment time (hereinafter referred to as “treatment” 4D-CT images). The “treatment” 4D-CT images were derived by deforming 3D planning CT images by using transformation parameters so that 2D planning portal dose images (PDIs) can resemble 2D dynamic clinical PDIs in each frame, which were derived from electronic portal imaging device (EPID) images. The transformation parameters were optimized by the Levenberg- Marquardt (LM) algorithm. The optimized transformation parameters in a certain frame were adaptively employed as initial transformation parameters for optimization of the parameters in the consecutive frame. Gamma pass rates (3mm/3%) between dynamic clinical PDIs and dynamic “treatment” PDIs derived from the “treatment” 4D-CT images were measured for comparing the proposed frameworks without and with the ATPs. These proposed frameworks were applied to the EPID dynamic images (40 frames) of two patients with lung cancer, who underwent the SBRT. Results: Gamma pass rates without and with the ATPs were 83.01±4.42% and 89.31±3.18% on average, respectively (p<0.05). Moreover, percentage errors between prescribed doses and estimated doses at an isocenter by the proposed frameworks without and with the ATPs were 10.67±5.66% and 6.34±0.47% on average, respectively (p<0.05). Conclusion: The proposed framework with ATPs could be useful to ensure the quality of the SBRT by monitoring 4D dose distributions during treatment time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Modeling Nonlinear Energy Dissipation of the Ministack Assembly

An assessment of two methodologies used at Sandia National Laboratories to model mechanical interfaces is performed on the Ministack finite element model. One method uses solid mechanics models to model contacting surfaces with Coulomb frictional contact to capture the physics. The other, termed the structural dynamics reduced order model, models the interface with a simplified whole joint model using four-parameter Iwan elements. The solid mechanics model resolves local kinematics at the interface while the simplified structural dynamics model is significantly faster to simulate. One of the current challenges to using the whole joint model is that it requires calibration to data. A novel approach is developed to calibrate the reduced structural dynamics model using data from the solid mechanics model to match the global dynamics of the system. This is achieved by calibrating to amplitude dependent frequency and damping of the system modes, which are estimated using three different approaches.

42 ENGINEERING↗
DOE OSTI2026

A Kinetic Model-Driven Techno-Economic Analysis of Plastic Pyrolysis: Linking Process Dynamics to Economic Viability

This study employs a kinetic model integrated into Aspen Plus to predict pyrolysis product distribution under various conditions. A techno-economic assessment calculated the minimum selling price (MSP) of pyrolysis oil under different operating conditions for the baseline capacity of 100 kta, and across eight processing capacities ranging from 30 to 150 kta. The lowest MSP under the baseline capacity is estimated at $\$$420/ton, which is 33% lower than the 2023 average US crude oil price ($\$$74.6/bbl, equivalent to $\$$634/ton based on the density of pyrolysis oil). Under Monte Carlo simulation, accounting for variability in key economic and technical parameters, the mean MSP is estimated at $\$$1137/ton. The economic viability depends on feedstock price remaining below $\$$320/ton, defining the break-even feedstock price threshold. Sensitivity analysis further identifies capital investment and transportation cost as key economic drivers. Capacities beyond 90 kta show limited economies of scale benefits. Reducing product storage time cuts capital costs by 7% but raises operational risk. Uncertainty analysis suggests the economic feasibility of pyrolysis oil is unlikely to compete with crude oil without policy incentives.

petrochemicals↗
DOE OSTI2015

A simplified, data-constrained approach to estimate the permafrost carbon–climate feedback

We present an approach to estimate the feedback from large-scale thawing of permafrost soils using a simplified, data-constrained model that combines three elements: soil carbon (C) maps and profiles to identify the distribution and type of C in permafrost soils; incubation experiments to quantify the rates of C lost after thaw; and models of soil thermal dynamics in response to climate warming. We call the approach the Permafrost Carbon Network Incubation–Panarctic Thermal scaling approach (PInc-PanTher). The approach assumes that C stocks do not decompose at all when frozen, but once thawed follow set decomposition trajectories as a function of soil temperature. The trajectories are determined according to a three-pool decomposition model fitted to incubation data using parameters specific to soil horizon types. We calculate litterfall C inputs required to maintain steady-state C balance for the current climate, and hold those inputs constant. Soil temperatures are taken from the soil thermal modules of ecosystem model simulations forced by a common set of future climate change anomalies under two warming scenarios over the period 2010 to 2100. Under a medium warming scenario (RCP4.5), the approach projects permafrost soil C losses of 12.2–33.4 Pg C; under a high warming scenario (RCP8.5), the approach projects C losses of 27.9–112.6 Pg C. Projected C losses are roughly linearly proportional to global temperature changes across the two scenarios. These results indicate a global sensitivity of frozen soil C to climate change (γ sensitivity) of –14 to –19 Pg C °C–1 on a 100 year time scale. For CH 4 emissions, our approach assumes a fixed saturated area and that increases in CH 4 emissions are related to increased heterotrophic respiration in anoxic soil, yielding CH 4 emission increases of 7% and 35% for the RCP4.5 and RCP8.5 scenarios, respectively, which add an additional greenhouse gas forcing of approximately 10–18%. In conclusion, the simplified approach presented here neglects many important processes that may amplify or mitigate C release from permafrost soils, but serves as a data-constrained estimate on the forced, large-scale permafrost C response to warming.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Median statistics estimate of the galactic rotational velocity

We compile a complete collection of 18 recent (from 2000 to 2017) measurements of Θ 0 , the rotational velocity of the Milky Way at R 0 (the radial distance of the Sun from the Galactic center). These measurements use tracers that are believed to more accurately reflect the systematic rotation of the Milky Way. Unlike other recent compilations of Θ 0 , our collection includes only independent measurements. We find that these 18 measurements are distributed in a mildly non-Gaussian fashion and a median statistics estimate indicates Θ 0 = 220 ± 10 kms –1 (2σ error) as the most reliable summary, at R 0 = 8.0 ± 0.3 kpc (2σ error).

(cosmology:) cosmological parameters↗
DOE OSTI2021

Identification and Online Updating of Dynamic Models for Demand Response of an Industrial Air Separation Unit

Demand-response operation of air separation units requires frequent changes in production rate(s), and scheduling calculations must explicitly consider process dynamics to ensure feasibility of the solutions. To this end, scale-bridging models (SBMs) approximate the scheduling-relevant dynamics of a process and its controller in a low-order representation. In contrast to previous works that have employed nonlinear SBMs, this paper proposes linear SBMs, developed using time-series analysis, to facilitate online scheduling computations. Using a year-long industrial dataset, we nd that compact linear SBMs are suitable approximations over typical scheduling horizons, but that their accuracies are unpredictable over time. We introduce a strategy for online updating of the SBMs, based on Kalman ltering schemes for online parameter estimation. The approach greatly improves the accuracy of SBM predictions and will enable the use of linear SBM-based demand-response scheduling in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Laser ablated copper plasmas in liquid and gas ambient

The dynamics of copper ablated plasma plumes generated using laser ablation of copper targets in both liquid (de-ionized water) and gas (air) ambients is reported. Using time and space resolved visible emission spectroscopy (450-650 nm), the plasma plumes parameters are investigated. The electron density (n{sub e}) determined using Stark broadening of the Cu I (3d{sup 10}4d{sup 1} {sup 2}D{sub 3/2}-3d{sup 10}4p{sup 1} {sup 2}P{sub 3/2} at 521.8 nm) line is estimated and compared for both plasma plumes. The electron temperature (T{sub e}) was estimated using the relative line emission intensities of the neutral copper transitions. Field emission scanning electron microscopy and energy dispersive x-ray spectral analysis of the ablated copper surface indicated abundance of spherical nanoparticles in liquid while those in air are amalgamates of irregular shapes. The nanoparticles suspended in the confining liquid form aggregates and exhibit a surface plasmon resonance at ∼590 nm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Greybox Thermal Parameter Identification of Electric Machine Stators

The parameters of electric machine thermal equivalent circuit networks are difficult to predict due to material and manufacturing uncertainties. In this paper, a Greybox system identification approach is used to identify parameters of electric machine stator lumped parameter thermal networks (LPTNs). LPTNs provide a low order, computationally efficient, dynamic model of temperatures at specific locations. Second and third order LPTN model structures are defined as state space equations with stator thermal parameters to be identified. To test the Greybox electric machine stator thermal system identification, five stator motorette prototypes were constructed with controlled variations in slot fill and slot liner thickness. The variation in the motorette thermal parameters and thermal time constants are detected using the Greybox identification. Special attention is given to the impact of sampling rate and Greybox data record length on parameter estimation accuracy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with intractable likelihoods, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in nonconvex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.

Bayesian inference↗