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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High-Precision Calculation of Nanoparticle (Nanocrystal) Potentials of Mean Force and Internal Energies

Thermodynamic stability assessment of nanocrystal systems requires precise free energy calculations. This study highlights the importance of meticulous control over various factors, including the thermostat, time step, potential cutoff, initial configuration, sampling method, and overall simulation duration. Free energy computations in dry (solvent-free) systems are on the order of several hundred $k_BT$ but can be obtained with consistent accuracy. However, calculation of internal energies becomes challenging, as they are typically much larger in magnitude than free energies and exhibit significant noise and reduced reliability. To address this limitation, we propose a new internal energy estimate that drastically reduces the noise. Here, we also present formulas that enable the optimization of the parameters of the harmonic bias potential for optimal convergence. Finally, we discuss the implications of these findings for the computation of free energies in nanocrystal clusters and superlattices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Low thermal budget photonic processing of highly conductive Cu interconnects based on CuO nanoinks. Potential for flexible printed electronics

The developing field of printed electronics nanoparticle based inks such as CuO show great promise as a low-cost alternative to other metal-based counterparts (e.g., silver). In particular, CuO inks significantly eliminate the issue of particle oxidation, before and during the sintering process, that is prevalent in Cu-based formulations. We report here the scalable and low-thermal budget photonic fabrication of Cu interconnects employing a roll-to-roll compatible pulse-thermal-processing (PTP) technique that enables phase reduction and subsequent sintering of inkjet-printed CuO patterns onto flexible polymer templates. Detailed investigations of curing and sintering conditions were performed to understand the impact of PTP system conditions on the electrical performance of the Cu patterns. Specifically, the impact of energy and power of photonic pulses on print conductivity was systematically studied by varying the following key processing parameters: pulse intensity, duration and sequence. Through optimization of such parameters, highly conductive prints in < 1 s with resistivity values as low as 100 n m has been achieved. We also observed that the introduction of an initial ink-drying step in ambient atmosphere, after the printing and before sintering, leads to significant improvements in mechanical integrity and electrical performance of the printed Cu patterns. Moreover, the viability of CuO reactive inks, coupled with the PTP technology and pre ink-drying protocols, has also been demonstrated for the additive integration of a low-cost Cu temperature sensor onto a flexible polymer substrate.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization

Large wind turbines yield more energy but demand careful aeroelastic blade design. Coupled multiphysics design strategies can reduce wind energy costs by exploiting fluid-structure interactions. This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor. We use blade-resolved fluid dynamics and structural solvers in a monolithic gradient-based optimization framework to explore steady-state torque and blade mass tradeoffs. The coupled-adjoint approach computes gradients efficiently, enabling the optimization of over 100 structural and geometric parameters simultaneously. Our optimization study modifies a DTU 10 MW benchmark with a simplified structure and isotropic material properties. The tightly coupled optimizations increase torque by 14% while reducing rotor mass by 9% or reduce blade mass by 27% while maintaining torque. Blade-resolved models provide greater design freedom, enabling 5% higher mass reductions than conventional parameterizations at equal torque. This framework paves the way for more detailed high-fidelity optimization studies to complement conventional design approaches.

17 WIND ENERGY↗
DOE OSTI2025

Automated shaker placement and regularized input estimation for MIMO testing.

Multi-input, multi-output (MIMO) testing is used in component qualification to reproduce operational responses in the laboratory. It is often preferred to single-input and base-shake testing because of the potential for equivalent or better tests using smaller actuators and shorter test suites. Given a target response, two key steps in MIMO test design are selecting actuator locations and solving for input loads. Actuator locations are often manually selected using expert judgment. If an automatic method is used, locations are usually determined by simulating the vibration control problem and minimizing a combination of the input energy and control residuals. To select a configuration, the relative importance of input energy and residuals must be specified. Specifying relative weights is, in general, a manual and subjective process. This paper develops an objective function that compares actuator configurations based on control accuracy and required input energy without any manual parameter tuning. The objective function uses an optimally selected tradeoff parameter for each candidate configuration. To choose actuator locations using the new objective function, a pivoting algorithm for integer programming problems is developed. Starting with an initial configuration (such as the one generated by a greedy algorithm), the pivoting algorithm guarantees an objective function decrease in each iteration until convergence is reached. In a simulation featuring a structure excited by a diffuse acoustic field, electrodynamic shaker locations and regularized inputs are solved for without any analyst-specified parameters. Simulations are performed in MIMO configurations where the number of target responses is less than, equal to, and greater than the number of actuators.

Multi-input multi-output↗
DOE OSTI2016

Can we detect the color-density relation with photometric redshifts?

A variety of methods have been proposed to define and to quantify galaxy environments. While these techniques work well in general with spectroscopic redshift samples, their application to photometric redshift surveys remains uncertain. To investigate whether galaxy environments can be robustly measured with photo-z samples, we quantify how the density measured with the nearest-neighbor approach is affected by photo-z uncertainties by using the Durham mock galaxy catalogs in which the 3D real-space environments and the properties of galaxies are known exactly. Furthermore, we present an optimization scheme in the choice of parameters used in the 2D projected measurements that yield the tightest correlation with respect to the 3D real-space environments. By adopting the optimized parameters in the density measurements, we show that the correlation between the 2D projected optimized density and the real-space density can still be revealed, and the color–density relation is also visible out to z ∼ 0.8 even for a photo-z uncertainty (σ{sub Δ{sub z/(1+z)}}) up to 0.06. We find that at redshifts 0.3 < z < 0.5 a deep (i ∼ 25) photometric redshift survey with σ{sub Δ{sub z/(1+z)}} = 0.02 yields a performance in small-scale density measurement that is comparable to a shallower i ∼ 22.5 spectroscopic sample with ∼10% sampling rate. Finally, we discuss the application of the local density measurements to the Pan-STARRS1 Medium Deep Survey (PS-MDS), one of the largest deep optical imaging surveys. Using data from ∼5 square degrees of survey area, our results show that it is possible to measure local density and to probe the color–density relation with 3σ confidence level out to z ∼ 0.8 in the PS-MDS. The color–density relation, however, quickly degrades for data covering smaller areas.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1971

Designing the brawny gas bearing.

Discussion of a graphic technique for matching specific groove parameters to operating conditions in order to optimize the load carrying capacity of a herringbone-grooved bearing. Details are given on the optimization of the film thickness ratio, the groove width ratio, the groove angle, and the groove length ratio to obtain a maximum radial load capacity. The effect of the dimensionless bearing number on optimal groove configuration parameters is shown in diagrams. Curves are also plotted to compare the capacities of a herringbone-grooved bearing and a plain bearing, showing the former has a higher load capacity than the latter when the dimensionless bearing number is large.

Hamrock, B. J.↗
NASA NTRS1985

Sensitivity of optimized control systems to minor structural modifications

A procedure for checking whether small changes in a structure have the potential for significant enhancements of its optimized vibration control system is described. The first step in the procedure consists of the calculation of the sensitivity of the parameters of the optimized control system to small changes in the structural parameters. Theh second step consists of the optimization of the structural parameters to produce maximal increase in the performance of the control system with minimal change in the structure. The procedure has been demonstrated for a flexible laboratory structure controlled by several rate-feedback colocated force-actuator velocity-sensor pairs. Significant improvements in the performance of the control system were obtained with small structural modifications. Analytical predictions of such effects have also been validated experimentally.

Haftka, R. T.↗
DOE OSTI2021

Co-Optimization Scheme for Hybrid Electric Vehicles Powertrain and Exhaust Emission Control System Using Future Speed Prediction

Hybrid electric vehicles (HEVs) have been an effective solution for improved vehicle fuel efficiency and reduced emission pollution. In this paper, a co-optimization scheme is proposed to optimize fuel efficiency for HEVs. Here, the proposed optimization scheme uses obtainable future speed prediction as the basis to optimally tune control parameters for the existing powertrain control system. The ramp-up time of the catalyst temperature to reach its light-off level in the exhaust emission system is also considered as an additional optimization constraint to reduce emission. The Toyota Prius Hybrid Simulink model which is an integrated model for a powertrain and exhaust emission system is validated using real data from several real driving cycle scenarios. Then, to simplify the formulation of the proposed algorithm, the model for the optimization for powertrain and exhaust emission systems is represented by a set of equivalent neural network (NN) models learned using the data generated from the well-validated Toyota Prius Hybrid Simulink model. Using NN models, a co-optimization algorithm is established that provides an optimal tuning of some fuel-sensitive powertrain control parameters using future speed prediction, leading to a novel co-optimization algorithm, achieving on average a further 9.22% fuel savings for the Toyota Prius Hybrid Simulink model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Long-range energy transport in photosystem II

We simulate the long-range inter-complex electronic energy transfer in photosystem II—from the antenna complex, via a core complex, to the reaction center—using a non-Markovian (ZOFE) quantum master equation description that allows the electronic coherence involved in the energy transfer to be explicitly included at all length scales. This allows us to identify all locations where coherence is manifested and to further identify the pathways of the energy transfer in the full network of coupled chromophores using a description based on excitation probability currents. We investigate how the energy transfer depends on the initial excitation—localized, coherent initial excitation versus delocalized, incoherent initial excitation—and find that the overall energy transfer is remarkably robust with respect to such strong variations of the initial condition. To explore the importance of vibrationally enhanced transfer and to address the question of optimization in the system parameters, we systematically vary the strength of the coupling between the electronic and the vibrational degrees of freedom. We find that the natural parameters lie in a (broad) region that enables optimal transfer efficiency and that the overall long-range energy transfer on a ns time scale appears to be very robust with respect to variations in the vibronic coupling of up to an order of magnitude. Nevertheless, vibrationally enhanced transfer appears to be crucial to obtain a high transfer efficiency, with the latter falling sharply for couplings outside the optimal range. Comparison of our full quantum simulations to results obtained with a “classical” rate equation based on a modified-Redfield/generalized-Förster description previously used to simulate energy transfer dynamics in the entire photosystem II complex shows good agreement for the overall time scales of excitation energy transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Floating Wind Turbine Control Optimization

We present a framework for optimizing the control parameters of floating offshore wind turbines (FOWTs). The framework combines aeroelastic simulations with a systems engineering model and control software. In an example of the optimization framework, we minimize tower damage equivalent loading with generator speed constraints. We also study the effect of thrust-limiting control and quantify the trade off between fatigue loading and energy capture using a set of optimal controller designs. Finally, we optimize the controller of four different FOWT models and compare their dynamic responses. Additional details and other use cases for the framework are presented, which can optimize different control problems and evaluate FOWT designs.

controls↗
DOE OSTI2022

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗
DOE OSTI2014

A Grid Intensity Map-Based Source Model for Monte Carlo Modeling of IMRT Field Irradiation - Paper 5

An accurate source model is important for TPS (Treatment Planning System) dose calculation and verification, especially for IMRT (Intensity Modulated Radiotherapy) irregular and inhomogeneous fields. Monte Carlo simulation is the most accurate way to calculate dose distributions in the heterogeneous media like human bodies. A full radiotherapy modeling generally includes Linac modeling and phantom dose calculation. Full Linac modeling is very time-consuming and requires highly detailed knowledge of the accelerator composition and structure, however, which is very difficult to obtain for commercial interests. Often all relevant parameters are not known with sufficient accuracy, and thus a time-consuming tuning of e.g. the electron beam spot size and energy must be performed. A multiple source model (MSM) regards particles coming from different parts of an accelerator as if they are coming from different virtual sources. MSM uses a set of virtual sources representing the treatment beam (e.g. primary photons, head scatter, electron contamination) by a set of analytic functions or histograms with parameters derived from dosimetric measurements or a full MC simulation. Tillikainen et al built a three sub-source model by matching with measurement data using an automatic process to optimize the free model parameters for a Varian 2100 C/D accelerator. Lin et al have built a convenient five-photon-sub-source model for Varian 2300C 6 MV-X beam based on Monte Carlo simulated Linac for ARTS (Accurate Radiotherapy System). The particle generation of MSM is very fast compared to full Linac simulation, and its sampling efficiency is not limited by the size of the phase space file (PSF). However, generally MSM is generated based on regular field PSF and needs an irregular component to form the beam shape meanwhile apt to bringing error Linac modeling and MSM producing from PSF analysis actually both are multi-freedom optimization process by adjusting several parameters (e.g. electron energy and angular divergence). Linac modeling adjusts its parameters from the beginning of electron hitting target through all components to fit the simulation to the measurement. MSM tunes its PSF-derived parameters by optimizing to minimize the deviations between the simulation and the measurement. Since the full Linac modeling and the MSM model both need to fine tune their parameters to match the simulation to the measurement, and sometimes maybe offsets the real accelerator for its multi-parameter optimization process. So, why not fine tune directly all source model parameters just behind all Linac components to fit the simulation to the measurement? A grid intensity-based surface source model was suggested here, which assumed the particle emitting from the bottom surface of Linac last beam trimmer MLC (Multi Leaf Collimator). The particle emitting position is sampled on the grid intensity map optimized by TPS, and the particle weight is adjusted by its original grid intensity. This source model not only takes advantage of the Monte Carlo method in the heterogeneous media, but also avoids effectively the transportation speed shortcoming of Monte Carlo simulation through Linac components. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

$N$=5, 6, 7, 8: Nested hypothesis tests and truncation dependence of $|V_{cb}|$ |Vcb|

The determination of | V c b | from exclusive semileptonic B → D * ℓ ν decays is sensitive to the choice of form factor parametrization. Larger | V c b | values are obtained by fitting the Boyd-Grinstein-Lebed (BGL) versus the Caprini-Lellouch-Neubert (CLN) parametrization to recent Belle measurements. For the BGL parametrization, published fits use different numbers of parameters. We propose a method based on nested hypothesis tests to determine the optimal number of BGL parameters to fit the data, and find that six parameters are optimal to fit the Belle tagged and unfolded measurement. We further explore the differences between fits that use different numbers of parameters. The fits which yield | V c b | values in better agreement with determinations from inclusive semileptonic decays tend to exhibit tensions with heavy quark symmetry expectations. These have to be resolved before the determinations of | V c b | from exclusive and inclusive decays can be considered understood.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Evaluation of LPBF Steels for Nuclear Applications

This report provides an update on the prioritization of existing reactor materials for advanced manufacturing. This report is a Milestone 3 deliverable in FY2023, under work package CT-23AN130401 to support research and qualification activities supported by the Advanced Materials and Manufacturing Technologies (AMMT) program here at Argonne National Laboratory (ANL). The focus of FY23 for ANL included the determination of a decision criteria matrix for the prioritization of existing materials, the literature review of a select few Fe-based alloys, and working with vendors to obtain customized powders. The work package also includes fabricating test samples in a Renishaw AM400 Laser Powder Bed Fusion (LPBF) system and optimizing the process parameters. The major outcomes of this work package are: With collaborations from PNNL, ORNL, and INL, we were able to establish a decision criteria matrix containing a total of 6 categories and 31 different criteria. These will be used to downselect alloys for further evaluation; As part of that, 6 different Fe-based alloys were selected, 3 austenitic stainless steels (A709, D9, AFA) and 3 ferritic/martensitic steels (HT9, Grade 91, Grade 92). Customized powders were obtained from vendors in small quantities to fabricate initial prints to check printability of these specific alloys; A total of 72 single track experiments were performed on two alloy systems, 1 austenitic stainless steel (A709) and 1 ferritic/martensitic steel (Grade 91) in order to optimize the process parameters for the full 3d prints. The optimization led to the selection of 20 different processing conditions, 10 for each class of alloys; D9 and AFA alloys showed extensive cracking and porosity in the samples. This was due to less-than-ideal conditions present in the chamber during the deposition. A709 printed using the same process parameters showed almost fully dense samples with no noticeable porosity or any other defects. SEM and EBSD analysis revealed single phase FCC microstructure with cellular structure within the grains; HT9, Grade 91, Grade 92 alloys also showed no noticeable signs of cracking and ImageJ analysis showed porosity <0.5% in all conditions. While Grade 91 and Grade 92 showed single phase BCC microstructures, the presence of martensite laths was noted in HT9 alloy; Future work will include further characterization of these alloys to better understand the microstructural evolution during the 3d printing process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Exploring the effects of data quality, data worth, and redundancy of CO2 gas pressure and saturation data on reservoir characterization through PEST Inversion

This study examined the impacts of reservoir properties on CO2 migration after subsurface injection and evaluated the possibility of characterizing reservoir properties using CO2 monitoring data such as saturation distribution. The injection reservoir was assumed to be located 1400-1500 m below the ground surface such that CO2 remained in the supercritical state. The reservoir was assumed to contain layers with alternating conductive and resistive properties, which is analogous to actual geological formations such as the Mount Simon Sandstone unit. The CO2 injection simulation used a cylindrical grid setting in which the injection well was situated at the center of the domain, which extended up to 8000 m from the injection well. The CO2 migration was simulated using the PNNL-developed simulator STOMP-CO2e (the water-salt-CO2 module). We adopted a nonlinear parameter estimation and optimization modeling software package, PEST, for automated reservoir parameter estimation. We explored the effects of data quality, data worth, and data redundancy on the detectability of reservoir parameters using CO2 saturation monitoring data, by comparing PEST inversion results using data with different levels of noises, various numbers of monitoring wells and locations, and different data collection spacing and temporal sampling intervals. This study yielded insight into the use of CO2 saturation monitoring data for reservoir characterization and how to design the monitoring system to optimize data worth and reduce data redundancy.

Carbon sequestration↗
NASA NTRS2003

Optimization of Brayton Cycle Power Generation for In-Space Electric Propulsion Application

A Brayton cycle was analyzed and optimized over the power range 60 - 140 kWe, for application to electric propulsion systems. A gas-cooled reactor heat source with exit temperature 1150 K was assumed. Power generation system specific masses (alpha) from 36 kg/kWe at 60 kWe to 22 kg/kWe at 140 kWe were obtained. These masses do not include the thrust production system, which is predicted to add 6 to 8 kg/kWe. Cycle efficiencies varied from 32% at 60 kWe to 36% at 140 kWe. Cycle minimum temperature, cycle pressure ratio, and heat exchanger design parameters were varied for the optimization. Optimization parameters and methods are described.

Woodcock, Gordon↗
NASA NTRSDate not supplied

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗
DOE OSTI2017

Hippocampal dose from stereotactic radiosurgery for 4 to 10 brain metastases: Risk factors, feasibility of dose reduction via re-optimization, and patient outcomes

This study aimed to report hippocampal dose from single-fraction stereotactic radiosurgery (SRS) for 4 to 10 brain metastases and determine feasibility of hippocampal-sparing SRS. Patients with 4 to 10 brain metastases receiving single-isocenter, multi-target single-fraction SRS were identified. Hippocampi were contoured using the Radiation Therapy Oncology Group (RTOG) 0933 atlas. RTOG 0933 dose constraints were converted to a biologically effective dose using an alpha/beta of 2 (D{sub 100} 421 cGy, D{sub max} 665 cGy). Number of metastases, total target volume, prescribed dose, and distance of nearest metastasis (dmin) were analyzed as risk factors for exceeding hippocampal constraints. If hippocampi exceeded constraints, the SRS plan was re-optimized. Key dosimetric parameters were compared between original and re-optimized plans. To determine if a single target can exceed constraints, all targets but the closest metastasis were removed from the plan, and dosimetry was compared. Forty plans were identified. Fifteen hippocampi (19%) exceeded constraints in 12 SRS plans. Hippocampal sparing was achieved in 10 of 12 replanned cases (83%). Risk factors associated with exceeding hippocampal constraints were decreasing dmin (24.0 vs 8.0 mm, p = 0.002; odds ratio [OR] 1.14, 95% confidence interval [CI] 1.04 to 1.26) and total target volume (5.46 cm{sup 3}vs 1.98 cm{sup 3}, p = 0.03; OR 1.14, 95% CI 1.00 to 1.32). There was no difference in exceeding constraints for 4 to 5 vs 6 to 10 metastases (27% vs 21%, p = 0.409) or prescribed dose (18 Gy, p = 0.58). For re-optimized plans, there were no significant differences in planning target volume (PTV) coverage (99.6% vs 99.0%, p = 0.17) or conformality index (1.47 vs 1.4, p = 0.78). Six (50%) plans exceeded constraints with a single target. A substantial minority of hippocampi receive high radiation dose from SRS for 4 to 10 brain metastases. Decreasing distance of the closest metastasis and total target volume are associated with exceeding hippocampal constraints. Re-optimizing these plans yielded hippocampal-sparing SRS plans with acceptable dosimetry. Prospective evaluation of the impact of hippocampal dose from SRS on neurocognition merits consideration.

62 RADIOLOGY AND NUCLEAR MEDICINE↗