Search NASA⌕ Search

SEARCH · Search NASA

Results for “Reduced Order Modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Drive Rig Mufflers for Model Scale Engine Acoustic Testing

Testing of air breathing propulsion systems in the 9x15 foot wind tunnel at NASA Glenn Research Center depends on compressed air turbines for power. The drive rig turbines exhaust directly to the wind tunnel test section, and have been found to produce significant unwanted noise that reduces the quality of the acoustic measurements of the model being tested. In order to mitigate this acoustic contamination, a muffler can be attached downstream of the drive rig turbine. The modern engine designs currently being tested produce much less noise than traditional engines, and consequently a lower noise floor is required of the facility. An acoustic test of a muffler designed to mitigate this extraneous noise is presented, and a noise reduction of 8 dB between 700 Hz and 20 kHz was documented, significantly improving the quality of acoustic measurements in the facility.

Stephens, David↗
NASA NTRS2022

Microthruster-Based Control for Precision Pointing of Next-Generation Space Telescopes

The next generation of space telescopes, such as the Habitable Exoplanet Observatory mission concept (HabEx), are expected to have milli-arcsecond-level pointing requirements at the spacecraft level. The pointing performance of such telescopes tends to be driven by internal rather than external disturbances, in particular reaction wheel jitter. This paper considers an architecture that relies on microthrusters instead of reaction wheels for spacecraft fine pointing, focusing on the HabEx mission concept as a case study. The proposed implementation uses micro-Newton-class colloidal thrusters that were tested in orbit as part of the ST7 payload on the LISA Pathfinder mission to reach Technical Readiness Level (TRL) 7. Key characteristics of these thrusters and the associated system trade-offs are first discussed. The resulting pointing control loop design is then described. Its ability to meet applicable pointing requirements is shown using three-degree-of-freedom simulations, where relevant disturbances are modelled. The control system is shown to reduce the pointing error by several orders of magnitude in about two hours, starting from coarse reaction control system (RCS) handover conditions. Once settled, the system meets the steady-state milli-arcsecond-level performance requirements with significant margin. Overall, the results show that microthruster-based pointing control architectures offer a promising alternative to traditional reaction-wheel-based designs for space telescope applications.

Ziemer, John↗
DOE OSTI2023

A variational encoder–decoder approach to precise spectroscopic age estimation for large Galactic surveys

Constraints on the formation and evolution of the Milky Way Galaxy require multidimensional measurements of kinematics, abundances, and ages for a large population of stars. Ages for luminous giants, which can be seen to large distances, are an essential component of studies of the Milky Way, but they are traditionally very difficult to estimate precisely for a large data set and often require careful analysis on a star-by-star basis in asteroseismology. Because spectra are easier to obtain for large samples, being able to determine precise ages from spectra allows for large age samples to be constructed, but spectroscopic ages are often imprecise and contaminated by abundance correlations. Here we present an application of a variational encoder–decoder on cross-domain astronomical data to solve these issues. The model is trained on pairs of observations from APOGEE and Kepler of the same star in order to reduce the dimensionality of the APOGEE spectra in a latent space while removing abundance information. The low dimensional latent representation of these spectra can then be trained to predict age with just ∼1000 precise seismic ages. We demonstrate that this model produces more precise spectroscopic ages (∼ 22 per cent overall, ∼ 11 per cent for red-clump stars) than previous data-driven spectroscopic ages while being less contaminated by abundance information (in particular, our ages do not depend on [α/M]). We create a public age catalogue for the APOGEE DR17 data set and use it to map the age distribution and the age-[Fe/H]-[α/M] distribution across the radial range of the Galactic disc.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Reinforcement learning based hybrid bond-order coarse-grained interatomic potentials for exploring mesoscale aggregation in liquid–liquid mixtures

Exploring mesoscopic physical phenomena has always been a challenge for brute-force all-atom molecular dynamics simulations. Although recent advances in computing hardware have improved the accessible length scales, reaching mesoscopic timescales is still a significant bottleneck. Coarse-graining of all-atom models allows robust investigation of mesoscale physics with a reduced spatial and temporal resolution but preserves desired structural features of molecules, unlike continuum-based methods. Here, we present a hybrid bond-order coarse-grained forcefield (HyCG) for modeling mesoscale aggregation phenomena in liquid–liquid mixtures. The intuitive hybrid functional form of the potential offers interpretability to our model, unlike many machine learning based interatomic potentials. We parameterize the potential with the continuous action Monte Carlo Tree Search (cMCTS) algorithm, a reinforcement learning (RL) based global optimizing scheme, using training data from all-atom simulations. The resulting RL-HyCG correctly describes mesoscale critical fluctuations in binary liquid–liquid extraction systems. cMCTS, the RL algorithm, accurately captures the mean behavior of various geometrical properties of the molecule of interest, which were excluded from the training set. The developed potential model along with the RL-based training workflow could be applied to explore a variety of other mesoscale physical phenomena that are typically inaccessible to all-atom molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Normal mode energetics and error analysis of GLA GCM simulations with different horizontal resolutions during a winter month

Comparative energetics is presented for a series of four general circulation model simulations for January 1979 conducted by the Goddard Laboratory for Atmospheres. The simulations include cases of coarse and fine horizontal model resolutions with two slightly different initial conditions. Using a three-dimensional normal mode expansion, it is found that the gravity-mode energy levels are significantly reduced in the higher wavenumbers and in the higher-order internal vertical modes by the increase of horizontal model resolution.

Tanaka, H. L.↗
DOE OSTI2019

Viscosity of Iron Oxide Aluminosilicate Melts

A structure-based viscosity model has been developed for the CaO-MgO-FeO-SiO{sub 2}-Al{sub 2}O{sub 3} system and its subsystems. A critical analysis of the experimental data for iron oxide aluminosilicate systems has been conducted and used in the optimization of a model, which provides a link between the viscosity and the structures of the melts. The structural characteristics of aluminosilicate melt can be described by four types of oxygen: bridging oxygen O{sub i}{sup 0}, non-bridging oxygen O{sub j}{sup −}, free oxygen O{sup 2−}, and excess bridging oxygen O{sup *}. The present model is capable of predicting the viscosities in the CaO-MgO-FeO-SiO{sub 2}-Al{sub 2}O{sub 3} system and its subsystems over wide ranges of composition and temperature above the liquidus within experimental uncertainties, and the average of relative errors for this model was found to be 19.94 pct. This model includes FeO-SiO{sub 2}, CaO-SiO{sub 2}-FeO, Al{sub 2}O{sub 3}-SiO{sub 2}-FeO, MgO-SiO{sub 2}-FeO, CaO-SiO{sub 2}-MgO-FeO, CaO-SiO{sub 2}-Al{sub 2}O{sub 3}-FeO, and CaO-MgO-SiO{sub 2}-Al{sub 2}O{sub 3}-FeO. It was found that the effects of different metal cations on the viscosity can be determined, and the ability to reduce viscosity in the silicate melts follows the order: FeO > CaO > MgO. In the present model, the predicted viscosity decreased when CaO was initially initial added to the Al{sub 2}O{sub 3}-MgO-FeO-SiO{sub 2} system at a fixed SiO{sub 2} content because Ca{sup 2+} has the highest priority for charge compensation and FeO is the strongest modifier for this slag.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Adaptive Reweighted Variance Estimation for Monte Carlo Eigenvalue Simulations

Monte Carlo (MC) simulation is used to solve the eigenvalue form of the Boltzmann transport equation to estimate various parameters such as fuel pin flux distributions that are crucial for the safe and efficient operation of nuclear systems (e.g., a nuclear reactor). Monte Carlo eigenvalue simulation uses a sample mean over many stationary cycles (iterations) to estimate various parameters important to nuclear systems. A variance estimate of the sample mean is often used for calculating the confidence intervals. However, MC eigenvalue simulation variance estimators that ignore the intercycle correlation underestimate the true variance of the estimated quantity. This paper presents novel data-adaptive approaches based on a simple autoregressive (AR) model and sigmoid functions to improve MC variance estimation. The standard MC sample-based variance estimator (or naïve estimator) and the spectral density–based MC variance estimator are enhanced by adding data-adaptive components that reduce their bias and improve performance. By investigating the frequency pattern of the AR(1) (order 1) model, two adaptive spectral estimators and one adaptive naïve estimator are proposed. The proposed estimators manifest superior performance when applied to three test problems compared to the standard spectral density–based estimator previously introduced by the authors. In conclusion, these new estimators are straightforward, as they use online algorithms and do not require storage of tallies from all active cycles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1993

Failure modes of reduced-order orbit determination filters and their remedies

Ways in which failure can occur in reduced-order, orbit determination filter, error covariance calculations are discussed. In the context of this article, reduced-order filters denote nonoptimal filters which include fixed levels of uncertainty in some parameters of the measurement models or in the spacecraft dynamical model which are not explicitly estimated in the filter equations. Failure is defined as an increase in the orbit determination covariance with the addition of data or as an unreasonable growth in the covariance with time, i.e., nonasymptotic behavior of the covariance. Some simple, known cases of failure are discussed along with their traditional remedies. In addition, more modern remedies are discussed which are currently under development at the Jet Propulsion Laboratory. The article first describes the known problems of reduced-order filters when they are employed for orbit determination, and their traditional remedies. Then, having defined these, the relevancy and desirability of the more modern remedies are made apparent.

Scheeres, D. J.↗
DOE OSTI2024

Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Data-driven operator inference for nonintrusive projection-based model reduction

We presenta a nonintrusive projection-based model reduction method for full models based on time-dependent partial differential equations. Projection-based model reduction constructs the operators of a reduced model by projecting the equations of the full model onto a reduced space. Traditionally, this projection is intrusive, which means that the full-model operators are required either explicitly in an assembled form or implicitly through a routine that returns the action of the operators on a given vector; however, in many situations the full model is given as a black box that computes trajectories of the full-model states and outputs for given initial conditions and inputs, but does not provide the full-model operators. Our nonintrusive operator inference approach infers approximations of the reduced operators from the initial conditions, inputs, trajectories of the states, and outputs of the full model, without requiring the full-model operators. Our operator inference is applicable to full models that are linear in the state or have a low-order polynomial nonlinear term. The inferred operators are the solution of a least-squares problem and converge, with sufficient state trajectory data, in the Frobenius norm to the reduced operators that would be obtained via an intrusive projection of the full-model operators. Our numerical results reflect operator inference on a linear climate model and on a tubular reactor model with a polynomial nonlinear term of third order.

42 ENGINEERING↗
DOE OSTI2018

Efficient modeling of optically-complex, non-coplanar exterior shading: Validation of matrix algebraic methods

It has long been established that shading windows with overhangs, fins, and other types of non-coplanar systems (NCS) is one of the most effective ways of controlling solar heat gains in buildings because they intercept solar radiation prior to entry into the building. Designers however often specify non-opaque materials (e.g., louvers, fritted glass, expanded metal mesh) for these systems in order to admit daylight, reduce lighting energy use, and improve indoor environmental quality. Most simulation tools rely on geometric calculations and radiosity methods to model the solar heat gain impacts of NCS and cannot model optically-complex materials or geometries. For daylighting analysis, optically-complex NCS can be modeled using matrix algebraic methods, although time-efficient parametric analysis has not yet been implemented. Determining the best design and/or material for static or operable NCS that minimize cooling, heating, and lighting energy use and peak demand requires an iterative process. This study describes and validates a matrix algebraic method that enables parametric energy analysis of NCS. Such capabilities would be useful not only for design but also for development of prescriptive energy-efficiency standards, rating and labeling systems for commercial products, development of design guidelines, and development of more optimal NCS technologies. A facade or “F” matrix, which maps the transfer of flux from the NCS to the surface of the window, is introduced and its use is explained. A field study was conducted in a full-scale outdoor testbed to measure the daylight performance of an operable drop-arm awning. Simulated data were compared to measured data in order to validate the models. Results demonstrated model accuracy: simulated workplane illuminance was within 11–13%, surface luminance was within 16–18%, and the daylight glare probability was within 6–9% of measured results. Methods used to achieve accurate results are discussed. Results of the validation of daylighting performance are applicable to solar heat gain performance. Since exterior shading can also significantly reduce peak demand, these models enable stakeholders to more accurately assess HVAC and lighting impacts in support of grid management and resiliency goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Seasonality of isoprenoid emissions from a primary rainforest in central Amazonia

Tropical rainforests are an important source of isoprenoid and other volatile organic compound (VOC) emissions to the atmosphere. The seasonal variation of these compounds is however still poorly understood. In this study, vertical profiles of mixing ratios of isoprene, total monoterpenes and total sesquiterpenes, were measured within and above the canopy, in a primary rainforest in central Amazonia, using a proton transfer reaction – mass spectrometer (PTR-MS). Fluxes of these compounds from the canopy into the atmosphere were estimated from PTR-MS measurements by using an inverse Lagrangian transport model. Measurements were carried out continuously from September 2010 to January 2011, encompassing the dry and wet seasons. Mixing ratios were higher during the dry (isoprene – 2.68 ± 0.9 ppbv, total monoterpenes – 0.67 ± 0.3 ppbv; total sesquiterpenes – 0.09 ± 0.07 ppbv) than the wet season (isoprene – 1.66 ± 0.9 ppbv, total monoterpenes – 0.47 ± 0.2 ppbv; total sesquiterpenes – 0.03 ± 0.02 ppbv) for all compounds. Ambient air temperature and photosynthetically active radiation (PAR) behaved similarly. Daytime isoprene and total monoterpene mixing ratios were highest within the canopy, rather than near the ground or above the canopy. By comparison, daytime total sesquiterpene mixing ratios were highest near the ground. Daytime fluxes varied significantly between seasons for all compounds. The maximums for isoprene (2.53 ± 0.5 µmol m -2 h -1 ) and total monoterpenes (1.77 ± 0.05 µmol m -2 h -1 ) were observed in the late dry season, whereas the maximum for total sesquiterpenes was found during the dry-to-wet transition season (0.77 ± 0.1 µmol m -2 h -1 ). These flux estimates suggest that the canopy is the main source of isoprenoids emitted into the atmosphere for all seasons. However, uncertainties in turbulence parameterization near the ground could affect estimates of fluxes that come from the ground. Leaf phenology seemed to be an important driver of seasonal variation of isoprenoid emissions. Although remote sensing observations of changes in leaf area index were used to estimate leaf phenology, MEGAN 2.1 did not fully capture the behavior of seasonal emissions observed in this study. This could be a result of very local effects on the observed emissions, but also suggest that other parameters need to be better determined in biogenic volatile organic compound (BVOC) models. Our results support established findings that seasonality of isoprenoids are driven by seasonal changes in light, temperature and leaf phenology. However, they suggest that leaf phenology and its role on isoprenoid production and emission from tropical plant species needs to be better understood in order to develop mechanistic explanations for seasonal variation in emissions. This also may reduce the uncertainties of model estimates associated with the responses to environmental factors. Therefore, this study strongly encourages long-term measurements of isoprenoid emissions, environmental factors and leaf phenology from leaf to ecosystem scale, with the purpose of improving BVOC model approaches that can characterize seasonality of isoprenoid emissions from tropical rainforests.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

Electromagnetic deep-probing (100-1000 KMS) of the Earth's interior from artificial satellites: Constraints on the regional emplacement of crustal resources

The two stages of analysis of MAGSAT magnetic data which are designed to evaluate electromagnetic induction effects are described. The first stage consists of comparison of data from contiguous orbit passes over large scale geologic boundaries, such as ocean-land interfaces, at several levels of magnetic disturbance. The purpose of these comparisons is to separate induction effects from effects of lithospheric magnetization. The procdure for reducing the data includes: (1) identifying and subtracting quiet time effects; (2) modelling and subtracting first order ring current effects; and (3) projecting an orbit track onto a map as a nearly straight line so it can serve as an axis on which to plot the corresponding orbit pass data in the context of geography. The second stage consists of comparison of MAGSAT data with standard hourly observatory data. The purpose is to constrain the time evolution of ionospheric and magnetospheric current systems. Qualitative features of the ground based dataset are discussed. Methods for reducing the ground based data are described.

Hermance, J. F.↗
NASA NTRS1975

Aeroacoustic performance of scale model sonic inlets

Various means can be used to vary engine inlet throat areas in order to reduce noise generated at takeoff and approach. Low-speed wind-tunnel tests were performed to evaluate the aeroacoustic performance of two takeoff geometries (cylindrical centerbody and bulb-shaped centerbody) and four approach geometries (bulb-shaped centerbody, annular ring, radial vanes, and step diffuser). The effects of inlet internal lip shape and diffuser length on sonic inlet performance were also investigated. It was found that the single-passage geometries, in particular a cylindrical centerbody takeoff geometry and a bulb-shaped centerbody approach geometry, provide the highest level of aeroacoustic performance. Increasing the inlet lip contraction ratio extends the maximum incidence angle for attached lip flow, while increasing the inlet diffuser length increases total pressure recovery for a given amount of noise suppression.

Abbott, J. M.↗
NASA NTRS1987

Scattering models for some vegetation samples

The Helmholtz integral equation is presently derived for a scatterer of arbitrary shape, and reduced in order to obtain the far zone-scattered field in terms of the field within the scatterer. Attention is given to the effect of different approaches to field estimation within the scatterer on the backscattering cross section, as illustrated numerically by the cases of a circular disk, a needle, and a finite-length cylinder. A comparison is made of the results obtained by modeling a leaf by means of a circular disk within the Shifrin approximation, and a tree branch by means of a finite-length cylinder, with measurements from a single leaf and a single branch.

Karam, M. A.↗
DOE OSTI2022

Implementation of a Model Predictive Control Strategy to Regulate Temperature Inside Plug-Flow Solar Reactor With Countercurrent Flow

Abstract Solar-driven thermochemical energy storage systems are proven to be promising energy carriers (solar fuels) to utilize solar energy by using reactive solid-state pellets. However, the production of solar fuel requires a quasi-steady-state process temperature, which represents the main challenge due to the transient nature of solar power. In this work, an adaptive model predictive controller (MPC) is presented to regulate the temperature inside a tubular solar reactor to produce solid-state solar fuel for long-term thermal storage systems. The solar reactor system consists of a vertical tube heated circumferentially over a segment of its length by concentrated solar power, and the reactive pellets (MgMn2O4) are fed from the top end and flow downwards through the heated tube. A countercurrent flowing gas supplied from the lower end interacts with flowing pellets to reduce it thermochemically at a temperature range of 1000—1500 °C. A low-order physical model was developed to simulate the dynamics of the solar reactor including the reaction kinetics, and the proposed model was validated numerically by using a 7-kW electric furnace. The numerical model then was utilized to design the MPC controller, where the control system consists of an MPC code linked to an adaptive system identification code that updates system parameters online to ensure system robustness against external disturbances (sudden change in the flow inside the reactor), model mismatches, and uncertainty. The MPC controller parameters are tuned to enhance the system performance with minimum steady-state error and overshoot. The controller is tested to track different temperature ranges between 500 °C and 1400 °C with different particles/gas mass flowrates and ramping temperature profiles. Results show that the MPC controller successfully regulated the reactor temperature within ± 1 °C of its setpoint and maintained robust performance with minimum input effort when subjected to sudden changes in the amount of flowing media and the presence of chemical reaction.

Engineering↗
DOE OSTI2017

A multiphase three-dimensional multi-relaxation time (MRT) lattice Boltzmann model with surface tension adjustment

The interdependence of surface tension and density ratio is a weakness of pseudo-potential based lattice Boltzmann models (LB). In this paper, we propose a 3D multi-relaxation time (MRT) model for multiphase flows at large density ratios. The proposed model is capable of adjusting the surface tension independently of the density ratio. We also present the 3D macroscopic equations recovered by the proposed forcing scheme. A high order of isotropy for the interaction force is used to reduce the amplitude of spurious currents. The proposed 3D-MRT model is validated by verifying Laplace's law and by analyzing its thermodynamic consistency and the oscillation period of a deformed droplet. The model is then applied to the simulation of the impact of a droplet on a dry surface. Impact dynamics are determined and the maximum spread factor calculated for different Reynolds and Weber numbers. The numerical results are in agreement with data published in the literature. The influence of surface wettability on the spread factor is also investigated. Finally, our 3D-MRT model is applied to the simulation of the impact of a droplet on a wet surface. The propagation of transverse waves is observed on the liquid surface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Stem Inc. SunShot Incubator Program Final Technical Report

In this Energy Storage Control Algorithms project, Stem sought to develop tools and control algorithms to increase the value and reduce balance-of-system and grid integration costs associated with adding distributed solar generation to the grid. These advances fell under the headings SolarScope and SolarController. Stem sought to create initial market traction with a fully commercialized product for the solar industry to size storage systems (SolarScope) as well as a solar intermittency-mitigation framework for utilities (SolarController) in the course of the project. The company sought to align strategic growth plans and enable the rollout of the products to broader audiences in multiple geographic regions by leveraging the major solar companies in the national market as partners. Both final products were both intended to be commercialized. They are: SolarScope: Analysis tool to identify viable PV + storage projects and thereby expedite the sales and interconnection processes. SolarScope combines customer load data, PV production estimates, utility rate tariff, and simulated storage into a simple user interface for PV developers. Developers can easily identify viable solar + storage sites without the need for complex and time consuming, site-by-site spreadsheet modeling. SolarContoller: Tool to autonomously dispatch distributed storage in order to mitigate voltage fluctuation and reduce curtailment. SolarController co-optimizes, in real time, storage dispatch for circuit stability and curtailment reduction, enabling higher penetrations of PV. SolarController is automated, not requiring utility dispatch or management, as Stem hardware senses grid voltage, frequency, customer load, PV production, and power factor. In the end the two products met with different outcomes. SolarScope was tested by potential users, and continues to be used as a foundational platform for partnership with key solar industry partners. SolarController, on the other hand, was successful in lab testing but was not commercialized due to a lack of marketability and lack of interested customer base. Together the development of these two products marked a material step forward for Stem; and a new milestone along the pathway of integration for the solar and storage industries. SolarScope is leading to real, out-of-the-lab project development in storage + solar for the commercial customer sector. Meanwhile SolarController has opened the eyes of regulators and utility executives alike to the potential of distributed solar and by doing so, has moved the conversation forward for the integration of distributed energy resources more broadly on the grid.

25 ENERGY STORAGE↗