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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Sensitivity Analysis of Modal Parameters of a Jacket Offshore Wind Turbine to Operational Conditions

Accurate estimation of offshore wind turbine (OWT) modal parameters has a prominent effect on the design loads, lifetime prediction, and dynamic response of the system. Modal parameters can vary during the operation of OWTs. This paper studies the variation and sensitivity analysis of an OWT’s modal parameters with respect to operational and environmental conditions. Three finite element models of a jacket-supported OWT at the Block Island Wind Farm are created within the OpenSees, SAP2000, and OpenFAST platforms and validated using experimental measurements. The OpenFAST model is used to simulate the modal parameters of the turbine under various wind speed, rotor speed, power, yaw angle, mean sea level, blade pitch angle, and soil spring values. The model-predicted modal parameters of the first fore–aft (FA) and side–side (SS) modes are compared to those identified from experimental measurements. Results from the simulations show that the first FA natural frequency and damping ratio mostly depend on the rotor speed and wind speed, respectively, while yaw angle and mean sea level do not have a visible effect. It is observed that there is about 8% stiffening in the first FA frequency and an aerodynamic damping of 7.5% during the operation of the OWT.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Hailstorm Analyses and Detection Derived from Current and Historical Satellite Data and Convective Environmental Parameters

We seek to demonstrate the extent to which hailstorms can be detected using a combination of geostationary (GEO) visible and infrared metrics of storm intensity and convective environmental parameters from reanalysis. Hailstorm identifications from low-Earth-orbiting (LEO) passive microwave sensors and maximum expected size of hail (MESH) from ground-based radar serve as a proxy for hail events. Data are analyzed for two warm seasons over the contiguous United States (CONUS). A neural network (NN) is trained to predict hailstorm detection dependent on optimal multi-variate weighting of observed and modeled input. The NN results are then applied to a 15-year Meteosat Second Generation climatology over South Africa to depict where hailstorms are most likely to occur. We also explore the impact of GEO imager resolution on our ability to discriminate hailstorms by matching GOES-13 (4 km) and GOES-16 (2 km) storm intensity metrics against hail characteristics using LEO, MESH, and spotter reports over CONUS during 2017, when both satellites were simultaneously imaging. Such analysis allows us to assess the feasibility of assembling a severe storm climate data record back to GOES-8, in the mid-1990’s. Finer spatial resolution of GOES-16 better resolves the updraft characteristics and intensities that are inherently linked to hail formation; however, GOES-13 can be normalized to achieve comparable detection capability. When intelligently combined with model-derived convective environmental parameters, GEO-derived storm intensity metrics enable high-spatial resolution hail risk assessment at hourly intervals throughout the diurnal cycle anywhere around the world and an improved understanding of hailstorms in the climate system.

Kyle F Itterly↗
NASA NTRS1988

Infinite-dimensional approach to system identification of Space Control Laboratory Experiment (SCOLE)

The identification of a unique set of system parameters in large space structures poses a significant new problem in control technology. Presented is an infinite-dimensional identification scheme to determine system parameters in large flexible structures in space. The method retains the distributed nature of the structure throughout the development of the algorithm and a finite-element approximation is used only to implement the algorithm. This approach eliminates many problems associated with model truncation used in other methods of identification. The identification is formulated in Hilbert space and an optimal control technique is used to minimize weighted least squares of error between the actual and the model data. A variational approach is used to solve the problem. A costate equation, gradients of parameter variations and conditions for optimal estimates are obtained. Computer simulation studies are conducted using a shuttle-attached antenna configuration, more popularly known as the Space Control Laboratory Experiment (SCOLE) as an example. Numerical results show a close match between the estimated and true values of the parameters.

Hossain, S. A.↗
DOE OSTI2024

Narrowing lab–to–market gaps: Device innovations in fuel generation, solar–cell, and photodetection

Academic translational research efforts to industry are often an underlying sought–after goal among various researchers. Through the interchanges of research endeavors between academia–industry, great innovations can/has been achieved that cater to the real–world application by bridging “industrially relevant” problem solving with pursuing fundamental studies. It is pertinent that most of the studies from university–level research works may not translate into demonstrable market products due to various reasons. Funding support, individual researcher goals, socioeconomic factors, and most importantly the technical know–how of generating revenue strategies for startups, are a few of the factors that have slowed the pace of collaborative efforts. However, we believe that the most crucial component is the identification of the critical parameters that solve long–standing problems that hinder the scale–up of the lab scale research into marketable products considering the techno–economic analysis. Here, to illustrate this, we take the three most relevant examples of devices for fuel generation, devices to utilize solar radiation, and devices for detection and other related applications. In this perspective, we provide an in–depth case study of each of these critical parameters to comment on the direction of research avenues that can serve as step–stones for the commercialization of university–level lab research studies.

42 ENGINEERING↗
DOE OSTI2018

In-situ investigation of Hf 6 Ta 2 O 17 anisotropic thermal expansion and topotactic, peritectic transformation

The anisotropic coefficients of thermal expansion and the peritectic transformation of orthorhombic-Hf 6 Ta 2 O 12 to tetragonal-HfO 2 plus liquid at 2250 °C have been studied by in-situ X-ray powder diffraction from room temperature to complete melting (~2450 °C) in air, using a quadrupole lamp furnace (QLF) and a conical nozzle levitator (CNL) equipped with a CO 2 laser. The topotactic, peritectic transformation has been fully described by extracting the orientation relationship, lattice variant deformation and a motif (grouping) of cations that relates the two structures at the transformation temperature. The calculation of these two important parameters as well as identification of the motif is facilitated by a knowledge of the anisotropic coefficients of thermal expansion as a function of temperature. In conclusion, symmetry decomposition has been performed to show that the orthorhombic-Hf 6 Ta 2 O 12 and tetragonal-HfO 2 structures are simply related by polyhedral rotations and loss of 1 mol of oxygen.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Correction of Q Factor Effects for Simultaneous Collection of Elemental Analysis and Relaxation Times by Nuclear Magnetic Resonance

A new method for measurement of elemental analysis by nuclear magnetic resonance (NMR) of unknown samples is discussed in this report as a quick and robust means to measure elemental ratios without the use of internal or external calibration standards. The determination of elemental ratios was done by normalizing the signal intensities by the frequency dependent quality factor (Q) and the gyromagnetic ratios (γ) for each measured nucleus. The correction for the frequency dependence was found by characterizing the output signal of the probe as a function of the quality factor (Q) and the frequency, and the correction for γ was discussed in a previous study. A Carr–Purcell–Meiboom–Gill (CPMG) pulse sequence was used for evaluation of the relative signal intensities, which allows for derivation of elemental ratios, and was correspondingly used to simultaneously measure the T 2 * of samples for an added parameter for more accurate identification of unknown samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

POLARRIS: A POLArimetric Radar Retrieval and Instrument Simulator

This paper introduces a synthetic polarimetric radar simulator and retrieval package, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), for evaluating cloud-resolving models (CRMs). POLARRIS is composed of forward (POLARRIS-f) and inverse (retrieval and diagnostic) components (iPOLARRIS) to generate not only polarimetric radar observables ($Z_h, Z_{dr}, K_{dp}, ρ_{hv})$ but also radar-consistent geophysical parameters such as hydrometeor identification, vertical velocity, and rainfall rates retrieved from CRM data. To demonstrate its application and uncertainties, POLARRIS is applied to simulations of a mesoscale convective system over the Southern Great Plains on 23 May 2011, using the Weather Research and Forecasting model with both spectral bin microphysics (SBM) and the Goddard single-moment bulk 4ICE microphysics. Statistical composites reveal a significant dependence of simulated polarimetric observables $(Z_{dr}, K_{dp})$ on the assumptions of the particle axis ratio (oblateness) and orientation angle distributions. We note the simulated polarimetric variables differ considerably between the SBM and 4ICE microphysics in part due to the differences in their ice particle size distributions as revealed by comparisons with aircraft measurements. Regardless of these uncertainties, simulated hydrometeor identification distributions overestimate graupel and hail fractions, especially from the simulation with SBM. To minimize uncertainties in forward model, the particle shape and orientation angle distributions of frozen particles should be predicted in a microphysics scheme in addition to the size distributions and particle densities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Thermal Experiments for Fractured Rock Characterization: Theoretical Analysis and Inverse Modeling

Abstract Field‐scale properties of fractured rocks play a crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross‐borehole thermal experiments data. It is based on a particle‐based heat‐transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of the heat‐transfer model runs and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to be estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding nonuniform prior information related to the DFN connectivity improves the inference of this parameter.

Zhou, Zitong↗
DOE OSTI2023

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

Abstract The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Chemistry↗
DOE OSTI2020

Nonlocal elastic metasurfaces: Enabling broadband wave control via intentional nonlocality

While elastic metasurfaces offer a remarkable and very effective approach to the subwavelength control of stress waves, their use in practical applications is severely hindered by intrinsically narrow band performance. In applications to electromagnetic and photonic metamaterials, some success in extending the operating dynamic range was obtained by using nonlocality. However, while electronic properties in natural materials can show significant nonlocal effects, even at the macroscales, in mechanics, nonlocality is a higher-order effect that becomes appreciable only at the microscales. This study introduces the concept of intentional nonlocality as a fundamental mechanism to design passive elastic metasurfaces capable of an exceptionally broadband operating range. The nonlocal behavior is achieved by exploiting nonlocal forces, conceptually akin to long-range interactions in nonlocal material microstructures, between subsets of resonant unit cells forming the metasurface. These long-range forces are obtained via carefully crafted flexible elements, whose specific geometry and local dynamics are designed to create remarkably complex transfer functions between multiple units. The resulting nonlocal coupling forces enable achieving phase-gradient profiles that are functions of the wavenumber of the incident wave. The identification of relevant design parameters and the assessment of their impact on performance are explored via a combination of semianalytical and numerical models. The nonlocal metasurface concept is tested, both numerically and experimentally, by embedding a total-internal-reflection design in a thin-plate waveguide. Results confirm the feasibility of the intentionally nonlocal design concept and its ability to achieve a fully passive and broadband wave control.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Negative Ion Drift Time Projection Chamber Development for High-Resolution Tracking

Gas Time Projection Chambers (TPCs) are used extensively in High Energy Physics. Modern micro-pattern gaseous detectors (MPGDs) have made it feasible to construct large-volume TPCs with high readout granularity, so that ionization can be imaged with spatial resolution of order 100 μm or better. A challenge with large TPCs is preserving the track geometry over large drift distances. The reduced diffusion offered by negative ion drift (NID) has long been considered a possible means to scaling up TPCs at reduced cost, but NID has up to now required toxic and often flammable multi-component gas mixtures. A number of recent breakthroughs in the field have, however, led to a resurgence of interest in NID gas TPCs: First, it was found that multiple charge carriers in NID can be utilized to measure the absolute position of primary ionization in the drift direction, yielding a powerful new handle on backgrounds, at zero additional cost. Second, work by one of the PIs has revealed SF6 gas to be a non-toxic, non-flammable, NID gas with suitable minority charge carriers present. Third, preliminary work by the PIs suggests that multiple MPGD technologies work well with SF6. This opens the door to a new generation of large, high-resolution, low-background, low-cost gas TPCs. In this work we will investigate MPGD charge multiplication and charge readout in NID TPCs with SF6 gas. The objectives are to quantify the improvement over electron drift TPCs, and to identify the optimal MPGD types, operational parameters, electronics, and vacuum technologies for future low-background experiments. We will measure low-level detector performance parameters such as gain, gain resolution, and spatial resolution, as well as the resulting higher-level performance parameters such nuclear recoil identification efficiency, gamma-ray background rejection, track angle resolution and recoil energy resolution. The proposed work also includes investigation of acrylic vacuum vessels and collaboration on dedicated charge readout chips, both required for next-generation NID MPGD TPCs. MGPD NID TPCs may prove transformative for applications which require both high readout granularity and large detector volumes, such as the reconstruction of nuclear recoils in the context of large-scale directional dark matter searches, measurements of coherent neutrino-nucleus scattering, and directional neutron detection. While the proposed work is focused on nuclear recoils, the lessons learned will be widely applicable to gas TPCs in HEP, and hence have broad impact.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Baryon Effective Theories and Phenomenology in the 1/ N C Expansion

Chiral perturbation theory (ChPT) and the 1/ N C expansion provide systematic frameworks to investigate the strong interaction at low energy. There are two main focuses of this dissertation. First, analyzing the masses of baryons in the framework of the 1/ N C expansion, using the available physical masses and masses calculated in lattice QCD. Second, combining both ChPT and the 1/ N C expansion into a single framework and applying it to the phenomenology of baryons with three light-quark flavors. In the first focus, the baryon states are organized into irreducible representations of SU(6)×O(3), where the [56,ℓ P = 0 + ] contains the ground state and radially excited baryons, and the [56,2 + ] and [70,1 - ] contain orbitally excited states are analyzed. The analyses are carried out to O(1/ N C ) and first order in the quark masses. The issue of state identifications is discussed. Numerous parameter independent mass relations and the famous Gell-Mann-Okubo (GMO) and Equal-Spacing (ES) relations are tested. Also, the quark mass dependence of the operator coefficients for baryon mass is discussed. In the second focus, a small scale expansion of the combined approach is defined as the ξ-expansion, in which the power counting of 1/ N C and chiral expansions are linked as O(p) = O(1/ N C ) = O(ξ). A calculation of one-loop corrections to the ground state baryon masses, vector and axial-vector currents up to O(x&i; 3 ) is presented. Moreover, the physical and lattice QCD masses are considered in order to understand the quark mass dependence, along with an analysis of the violations to GMO, ES and Gürsey-Radicati (GR) mass relations, and their dependence on N C .

Fernando, Madappuli Arachchige Ishara↗
DOE OSTI2019

A Data-Driven Workflow Approach to Optimization of Fracture Spacing in Multi-Fractured Shale Oil Wells

A data-driven workflow approach is presented in this study for optimizing fracture spacing of multifractured horizontal wells (MFHW) in shale oil reservoirs. The workflow employs a simple well productivity model for the initial design of hydraulic fracturing well completions. This provides a transparent approach to the identification of key fracturing parameters affecting well productivity. The workflow uses transient pressure or production data to identify fracture interference. This offers a reliable and cost-effective means for assessment of well production potential in terms of optimization of fracture spacing in the MFHW. Result of a field case study indicated that three wells were drilled in an area with dense natural fractures, and the fracture spacing of MFHW in this area was short enough to effectively drain the stimulated reservoir volume (SRV), while the other three wells were drilled in an area with less natural fractures, and the fracture spacing of MFHW in this area could be shortened to double well productivity.

58 GEOSCIENCES↗
NASA NTRS1972

Identification of boiler inlet transfer functions and estimation of system parameters

An iterative computer method is described for identifying boiler transfer functions using frequency response data. An objective penalized performance measure and a nonlinear minimization technique are used to cause the locus of points generated by a transfer function to resemble the locus of points obtained from frequency response measurements. Different transfer functions can be tried until a satisfactory empirical transfer function of the system is found. To illustrate the method, some examples and some results from a study of a set of data consisting of measurements of the inlet impedance of a single tube forced flow boiler with inserts are given.

Miles, J. H.↗
NASA NTRS1975

Analytical simulation of the far-field jet noise and the unsteady jet flow-field by a model of periodic shedding of vortex ring from the jet exit

The construction of a theoretical flow field due to shedding of vortex rings, the identification of the controlling parameters, and the determination of whether the theoretical model successfully simulated the unsteady pressure field near jet (and consequently the far field noise) was studied. The basic parameters contained in the analytic solutions were the epoch at which a vortex ring was shed near the jet exit and the eddy viscosity coefficient. These parameters were identified from the experimental data for the real-time pressure and from the spread of the mixing layer of the jet. Results of the theoretical analysis show good qualitative agreement with the experimental data.

Liu, C. H.↗
NASA NTRS1974

Preliminary results of fisheries investigation associated with Skylab-3

The purpose of the 15-month investigation now in the analysis phase is to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. Data from the test area, jointly acquired by private and professional fishermen and NASA and NOAA/NMFS elements, in the northeastern Gulf of Mexico has made possible the identification of significant environmental parameters for white marlin. Predictive models based on catch data and surface truth information have been developed and have demonstrated potential for reducing search significantly by identifying areas which have a high probability of being productive. Three of the parameters utilized by the model, chlorophyll-a, sea surface temperature and turbidity have been inferred from aircraft sensor data.

Savastano, K.↗
NASA NTRS1975

HAL/SM system functional design specification

The functional design of a preprocessor, and subsystems is described. A structure chart and a data flow diagram are included for each subsystem. Also a group of intermodule interface definitions (one definition per module) is included immediately following the structure chart and data flow for a particular subsystem. Each of these intermodule interface definitions consists of the identification of the module, the function the module is to perform, the identification and definition of parameter interfaces to the module, and any design notes associated with the module. Also described are compilers and computer libraries.

Ross, C.↗