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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

High-accuracy computation of Delta V magnitude probability densities - Preliminary remarks

This paper describes an algorithm for the high accuracy computation of some statistical quantities of the magnitude of a random trajectory correction maneuver (TCM). The trajectory correction velocity increment Delta V is assumed to be a three-component random vector with each component being a normally distributed random scalar having a possibly nonzero mean. Knowledge of the statitiscal properties of the magnitude of a random TCM is important in the planning and execution of maneuver strategies for deep-space missions such as Galileo. The current algorithm involves the numerical integration of a set of differential equations. This approach allows the computation of density functions for specific Delta V magnitude distributions to high accuracy without first having to generate large numbers of random samples. Possible applications of the algorithm to maneuver planning, planetary quarantine evaluation, and guidance success probability calculations are described.

Chadwick, C.↗
DOE OSTI2025

Adaptive PID Gain Scheduling Control for Hydropower Turbine Using Neural CDE and Stochastic Distribution Shaping

This paper introduces a gain-scheduling PID controller design strategy for hydroturbine frequency control mode. This scheme first uses real data to learn the nonlinear dynamics of the hydroturbine using neural controlled differential equations and then perturbs the obtained nonlinear system at different equilibrium points, based on which a static output feedback adaptive dynamic programming algorithm is then used to optimize the PID gains for each equilibrium point. Moreover, a continuous-time version of stochastic distribution control is proposed to further fine-tune the optimized PID gains. Finally, the controller is obtained by implementing linear interpolation between the optimized PID control gains. The simulation results show that the proposed gain-scheduling PID controller can control a larger range of operation points compared with the given fixed PID controller and the baseline method. Compared with the given fixed PID controller, the proposed gain-scheduling PID controller can regulate hydroturbine frequency against disturbances induced by power-load variation with over 50% less overshoot for some operation points.

13 HYDRO ENERGY↗
NASA NTRS2024

A Multi‐Probe Automated Classification of Ice Crystal Habits During the IMPACTS Campaign

Although all ice crystals are unique, many can be grouped together by shape or habit, with members of a habit class sharing similar representations of properties such as fall velocity and growth rate. A decision tree algorithm designed to be adaptable to any particle imaging probe, thus enabling the creation of habit size distributions over a size range larger than that of any probe on its own, is used to classify ice crystals imaged by three airborne cloud probes in mid-latitude winter cyclones during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Crystals are sorted into seven habit classes based on their morphological properties: sphere, column/needle, plate, graupel, dendrite, aggregate, and irregular. Although adaptability was its primary goal, the algorithm was found to be moderately skillful for identifying idealized habit images. Quantitative tests of the algorithm’s adaptability displayed mixed results, as Two-Dimensional Stereo Probe (2DS) classifications showed moderate correlation with Particle Habit Imaging and Polar Scattering Probe (PHIPS) classifications, but only weak correlation with High Volume Precipitation Spectrometer (HVPS) classifications. The algorithm was applied to random sets of images from each probe in a case study of a mesoscale snow band sampled on 7 February 2020. In the case study, qualitative analysis of particle images revealed general agreement on classifications among the probes, supporting the algorithm’s applicability to multiple cloud probes. Most classifications appeared correct upon manual inspection, suggesting that in practical use, the algorithm is reasonably able to classify non-idealized images.

Julian Schima↗
NASA NTRS2000

Active Structural Acoustic Control of Interior Noise on a Raytheon 1900D

An active structural acoustic control system has been demonstrated on a Raytheon Aircraft Company 1900D turboprop airliner. Both single frequency and multi-frequency control of the blade passage frequency and its harmonics was accomplished. The control algorithm was a variant of the popular filtered-x LMS implemented in the principal component domain. The control system consisted of 21 inertial actuators and 32 microphones. The actuators were mounted to the aircraft's ring frames. The microphones were distributed uniformly throughout the interior at head height, both seated and standing. Actuator locations were selected using a combinatorial search optimization algorithm. The control system achieved a 14 dB noise reduction of the blade passage frequency during single frequency tests. Multi-frequency control of the first 1st, 2nd and 3rd harmonics resulted in 10.2 dB, 3.3 dB and 1.6 dB noise reductions respectively. These results fall short of the predictions which were produced by the optimization algorithm (13.5 dB, 8.6 dB and 6.3 dB). The optimization was based on actuator transfer functions taken on the ground and it is postulated that cabin pressurization at flight altitude was a factor in this discrepancy.

Palumbo, Dan↗
NASA NTRS2013

Constraints on Saturn's Tropospheric General Circulation from Cassini ISS Images

An automated cloud tracking algorithm is applied to Cassini Imaging Science Subsystem high-resolution apoapsis images of Saturn from 2005 and 2007 and moderate resolution images from 2011 and 2012 to define the near-global distribution of zonal winds and eddy momentum fluxes at the middle troposphere cloud level and in the upper troposphere haze. Improvements in the tracking algorithm combined with the greater feature contrast in the northern hemisphere during the approach to spring equinox allow for better rejection of erroneous wind vectors, a more objective assessment at any latitude of the quality of the mean zonal wind, and a population of winds comparable in size to that available for the much higher contrast atmosphere of Jupiter. Zonal winds at cloud level changed little between 2005 and 2007 at all latitudes sampled. Upper troposphere zonal winds derived from methane band images are approx. 10 m/s weaker than cloud level winds in the cores of eastward jets and approx. 5 m/s stronger on either side of the jet core, i.e., eastward jets appear to broaden with increasing altitude. In westward jet regions winds are approximately the same at both altitudes. Lateral eddy momentum fluxes are directed into eastward jet cores, including the strong equatorial jet, and away from westward jet cores and weaken with increasing altitude on the flanks of the eastward jets, consistent with the upward broadening of these jets. The conversion rate of eddy to mean zonal kinetic energy at the visible cloud level is larger in eastward jet regions (5.2x10(exp -5) sq m/s) and smaller in westward jet regions (1.6x10(exp -5) sqm/s) than the global mean value (4.1x10(ep -5) sq m/s). Overall the results are consistent with theories that suggest that the jets and the overturning meridional circulation at cloud level on Saturn are maintained at least in part by eddies due to instabilities of the large-scale flow near and/or below the cloud level.

DelGenio, Anthony D.↗
NASA NTRS2016

The Microwave Radiative Properties of Falling Snow Derived from Nonspherical Ice Particle Models. Part II: Initial Testing Using Radar, Radiometer and In Situ Observations

In this study, two different particle models describing the structure and electromagnetic properties of snow are developed and evaluated for potential use in satellite combined radar-radiometer precipitation estimation algorithms. In the first model, snow particles are assumed to be homogeneous ice-air spheres with single-scattering properties derived from Mie theory. In the second model, snow particles are created by simulating the self-collection of pristine ice crystals into aggregate particles of different sizes, using different numbers and habits of the collected component crystals. Single-scattering properties of the resulting nonspherical snow particles are determined using the discrete dipole approximation. The size-distribution-integrated scattering properties of the spherical and nonspherical snow particles are incorporated into a dual-wavelength radar profiling algorithm that is applied to 14- and 34-GHz observations of stratiform precipitation from the ER-2 aircraft-borne High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) radar. The retrieved ice precipitation profiles are then input to a forward radiative transfer calculation in an attempt to simulate coincident radiance observations from the Conical Scanning Millimeter-Wave Imaging Radiometer (CoSMIR). Much greater consistency between the simulated and observed CoSMIR radiances is obtained using estimated profiles that are based upon the nonspherical crystal/aggregate snow particle model. Despite this greater consistency, there remain some discrepancies between the higher moments of the HIWRAP-retrieved precipitation size distributions and in situ distributions derived from microphysics probe observations obtained from Citation aircraft underflights of the ER-2. These discrepancies can only be eliminated if a subset of lower-density crystal/aggregate snow particles is assumed in the radar algorithm and in the interpretation of the in situ data.

Ice particles; Radiances; Radiative transfer; Airc↗
DOE OSTI2021

Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale

Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in various graph, scientific computing and machine learning algorithms. In this paper, we consider SpGEMMs performed on hundreds of thousands of processors generating trillions of nonzeros in the output matrix. Distributed SpGEMM at this extreme scale faces two key challenges: (1) high communication cost and (2) inadequate memory to generate the output. Furthermore, we address these challenges with an integrated communication-avoiding and memory-constrained SpGEMM algorithm that scales to 262,144 cores (more than 1 million hardware threads) and can multiply sparse matrices of any size as long as inputs and a fraction of output fit in the aggregated memory. As we go from 16,384 cores to 262,144 cores on a Cray XC40 supercomputer, the new SpGEMM algorithm runs 10x faster when multiplying large-scale protein-similarity matrices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Graphene K‐Tape Meshes for Densely Distributed Human Motion Monitoring

Abstract Wearable sensors that measure parameters associated with physical activity and bodily motions have been regarded as an indispensable tool for assessing personal wellness. Recent advances in nanocomposite strain sensors have been successfully used for monitoring skin strains and other strain‐derived physiological parameters. This study complements the existing body of work and presents a flexible, self‐adhering, fabric‐based wearable sensor for measuring skin strains and human motions. Graphene nanosheet thin films are directly spray‐coated onto kinesiology tape (K‐Tape) to obtain a self‐adhering strain sensor of high sensitivity and linearity. Their stable sensing performance and high repeatability are verified, while human subject tests confirm that they adequately capture muscle engagement during functional movements. In addition, densely distributed strain monitoring can be achieved using an electrical impedance tomography measurement approach and algorithm. Spatial strain sensing is successfully demonstrated using a single strip of piezoresistive K‐Tape, as well as when a K‐Tape network or mesh pattern is formed. The results show promise for using graphene K‐Tape meshes to measure how specific major muscle groups engage during different physical activities.

Lin, Yun‐An↗
DOE OSTI2024

Data-driven nonlocal model for fragmentation in the crushing of solids

A technique is proposed for reproducing particle size distributions in three-dimensional simulations of the crushing and comminution of solid materials. The method is designed to produce realistic distributions over a wide range of loading conditions, especially for small fragments. In contrast to most existing methods, the new model does not explicitly treat the small-scale process of fracture. Instead, it uses measured fragment distributions from laboratory tests as the basic material property that is incorporated into the algorithm, providing a data-driven approach. The algorithm is implemented within a nonlocal peridynamic solver, which simulates the underlying continuum mechanics and contact interactions between fragments after they are formed. Finally, the technique is illustrated in reproducing fragmentation data from drop weight testing on sandstone samples.

58 GEOSCIENCES↗
DOE OSTI2023

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗
DOE OSTI2025

Medium-induced modification of groomed and ungroomed jet mass and angularities in Pb–Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

The ALICE Collaboration presents a new suite of jet substructure measurements in Pb–Pb and pp collisions at a center-of-mass energy per nucleon pair $\sqrt{s_{NN}}$ = 5.02 TeV. These measurements provide access to the internal structure of jets via the momentum and angle of their constituents, probing how the quark–gluon plasma modifies jets, an effect known as jet quenching. Jet grooming additionally removes soft wide-angle radiation to enhance perturbative accuracy and reduce experimental uncertainties. We report the groomed and ungroomed jet mass m jet and jet angularities λ$^{κ}_{α}$ using κ = 1 and α > 0. Charged-particle jets are reconstructed at midrapidity using the anti-k T algorithm with resolution parameter R = 0.2. A narrowing of the jet mass and angularity distributions in Pb–Pb collisions with respect to pp is observed and is enhanced for groomed results, confirming modification of the jet core. By using consistent jet definitions and kinematic cuts between the mass and angularities for the first time, previous inconsistencies in the interpretation of quenching measurements are resolved, rectifying a hurdle for understanding how jet quenching arises from first principles and highlighting the importance of a well-controlled baseline. These results are compared with a variety of theoretical models of jet quenching, providing constraints on jet energy-loss mechanisms in the quark–gluon plasma.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Arctic Cloud‐Base Ice Precipitation Properties Retrieved Using Bayesian Inference

Abstract Cloud‐climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long‐lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud‐base properties a more appealing target for inference and evaluation of model simulations. Here I describe an inverse model for the estimation of cloud base ice precipitation properties over Utqiagvik, North Slope of Alaska, using the synthesis of ground‐based radar and lidar measurements. By leveraging a Markov Chain Monte Carlo algorithm as the core of the inverse model, a wide range of particle size distributions are sampled, and different combinations of ice habit models are examined, both of which are typically fixed in other retrieval methods. Results show intriguing links between different cloud base thermodynamic and ice precipitation properties. Apparent ice number concentration enhancements at temperatures of −5 and −15°C suggest possible secondary ice production (SIP). The analysis alludes to an overestimation of SIP occurrence and intensity, especially in studies relying only on radar or lidar measurements. Finally, reflectivity‐dependent ice precipitation rate and ice water content parameterizations are presented.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

BEYONDPLANCK XIII. Intensity foreground sampling, degeneracies, and priors

We present the intensity foreground algorithms and model employed within the BEYONDPLANCK analysis framework. The BEYONDPLANCK analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the Planck Low Frequency Instrument (LFI) data analysis. Given the scope of the BEYONDPLANCK analysis, a limited set of data is included in the component separation process, leading to foreground parameter degeneracies. In order to properly constrain the Galactic foreground parameters, we improve upon the previous Commander component separation implementation by adding a suite of algorithmic techniques. These algorithms are designed to improve the stability and computational efficiency for weakly constrained posterior distributions. These are: (1) joint foreground spectral parameter and amplitude sampling, building on ideas from MIRAMARE; (2) component-based monopole determination; (3) joint spectral parameter and monopole sampling; and (4) application of informative spatial priors for component amplitude maps. We find that the only spectral parameter with a significant signal-to-noise ratio using the current BEYONDPLANCK data set is the peak frequency of the anomalous microwave emission component, for which we find $ν$ p = 25.3 ± 0.5 GHz; all others must be constrained through external priors. Future works will be aimed at integrating many more data sets into this analysis, both map and time-ordered based, thereby gradually eliminating the currently observed degeneracies in a controlled manner with respect to both instrumental systematic effects and astrophysical degeneracies. When this happens, the simple LFI-oriented data model employed in the current work will need to be generalized to account for both a richer astrophysical model and additional instrumental effects. This work will be organized within the Open Science-based COSMOGLOBE community effort.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Computing Nonequilibrium Responses with Score-Shifted Stochastic Differential Equations

Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used to interpret experiments and shed light on microscopic dynamics. For nonequilibrium systems, perturbations cannot be interpreted simply by monitoring fluctuations in a conjugate observable and general response results rely on path ensemble averaging. Furthermore, these techniques do not apply to perturbations that affect the diffusion tensor in a stochastic system. Here, we introduce an “effective” physical process that represents the diffusion perturbed dynamics and enables accurate calculations of responses to a change in the diffusion. Interestingly, the effective dynamics contain an additional drift involving the instantaneous “score” of the system, and we leverage score matching algorithms to carry out nonequilibrium response calculations on systems for which the exact stationary distribution is unknown.

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

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗
DOE OSTI2025

Linear Solver for Electromagnetic Simulation of General Distribution Feeders

High-fidelity electromagnetic transient (EMT) modeling is required for accurate simulation and analysis of power system dynamics in modern distribution feeders. However, the high-fidelity of EMT models often leads to significant computational challenges, particularly in terms of computational resources and simulation time. This paper investigates the development and application of a detailed EMT model for general distribution feeders, with a focus on improving computational efficiency. A direct linear solver is proposed for a bordered block diagonal (BBD) matrix structure commonly encountered in a EMT model of distribution feeders. The solver integrates the Schur complement method with the block tridiagonal matrix algorithm to enhance the computational performance. The proposed solver is validated using the primary feeder of the IEEE 342-node test system, demonstrating its accuracy and efficiency in EMT simulations. Furthermore, the solver’s performance is benchmarked against MATLAB’s built-in linear solvers, showing significant improvements in computation time while maintaining high fidelity and accuracy in simulation results.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗
DOE OSTI2021

RAPID

Parallel computer code for the simulator for dynamics of power systems which has the capability to initiate the system and create different faults for the dynamic analysis. The code is based on time-parallel method (Parareal) with Adaptive Method Reduction (AMR). The coarse solvers for the Parareal algorithm include several Semi Analytical Solution methods. Also, Integrated simulation of coupled transmission and distribution systems can be studied.

Simunovic, Srdjan [Oak Ridge National Lab. (ORNL),↗
DOE OSTI2020

Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

54 ENVIRONMENTAL SCIENCES↗