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At least 217 records · Page 12

State of the Art in Large-Scale Soil Moisture Monitoring

Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.

Review↗

Forest Structure Characterization Using JPL's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

This paper concerns forest remote sensing using JPL's multi-baseline polarimetric interferometric UAVSAR data. It presents exemplary results and analyzes the possibilities and limitations of using SAR Tomography and Polarimetric SAR Interferometry (PolInSAR) techniques for the estimation of forest structure. Performance and error indicators for the applicability and reliability of the used multi-baseline (MB) multi-temporal (MT) PolInSAR random volume over ground (RVoG) model are discussed. Experimental results are presented based on JPL's L-band repeat-pass polarimetric interferometric UAVSAR data over temperate and tropical forest biomes in the Harvard Forest, Massachusetts, and in the La Amistad Park, Panama and Costa Rica. The results are partially compared with ground field measurements and with air-borne LVIS lidar data.

UAVSAR (Uninhabited Aerial Vehicle SAR)↗

Forest Structure Characterization Using Jpl's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

This paper concerns forest remote sensing using JPL's multi-baseline polarimetric interferometric UAVSAR data. It presents exemplary results and analyzes the possibilities and limitations of using SAR Tomography and Polarimetric SAR Interferometry (PolInSAR) techniques for the estimation of forest structure. Performance and error indicators for the applicability and reliability of the used multi-baseline (MB) multi-temporal (MT) PolInSAR random volume over ground (RVoG) model are discussed. Experimental results are presented based on JPL's L-band repeat-pass polarimetric interferometric UAVSAR data over temperate and tropical forest biomes in the Harvard Forest, Massachusetts, and in the La Amistad Park, Panama and Costa Rica. The results are partially compared with ground field measurements and with air-borne LVIS lidar data.

remote sensing↗

A statistical study of radio-source structure effects on astrometric very long baseline interferometry observations

Errors from a number of sources in astrometric very long baseline interferometry (VLBI) have been reduced in recent years through a variety of methods of calibration and modeling. Such reductions have led to a situation in which the extended structure of the natural radio sources used in VLBI is a significant error source in the effort to improve the accuracy of the radio reference frame. In the past, work has been done on individual radio sources to establish the magnitude of the errors caused by their particular structures. The results of calculations on 26 radio sources are reported in which an effort is made to determine the typical delay and delay-rate errors for a number of sources having different types of structure. It is found that for single observations of the types of radio sources present in astrometric catalogs, group-delay and phase-delay scatter in the 50 to 100 psec range due to source structure can be expected at 8.4 GHz on the intercontinental baselines available in the Deep Space Network (DSN). Delay-rate scatter of approx. 5 x 10(exp -15) sec sec(exp -1) (or approx. 0.002 mm sec (exp -1) is also expected. If such errors mapped directly into source position errors, they would correspond to position uncertainties of approx. 2 to 5 nrad, similar to the best position determinations in the current JPL VLBI catalog. With the advent of wider bandwidth VLBI systems on the large DSN antennas, the system noise will be low enough so that the structure-induced errors will be a significant part of the error budget. Several possibilities for reducing the structure errors are discussed briefly, although it is likely that considerable effort will have to be devoted to the structure problem in order to reduce the typical error by a factor of two or more.

Ulvestad, J. S.↗

Structure and evolution of the large scale solar and heliospheric magnetic fields

Structure and evolution of large scale photospheric and coronal magnetic fields in the interval 1976-1983 were studied using observations from the Stanford Solar Observatory and a potential field model. The solar wind in the heliosphere is organized into large regions in which the magnetic field has a componenet either toward or away from the sun. The model predicts the location of the current sheet separating these regions. Near solar minimum, in 1976, the current sheet lay within a few degrees of the solar equator having two extensions north and south of the equator. Soon after minimum the latitudinal extent began to increase. The sheet reached to at least 50 deg from 1978 through 1983. The complex structure near maximum occasionally included multiple current sheets. Large scale structures persist for up to two years during the entire interval. To minimize errors in determining the structure of the heliospheric field particular attention was paid to decreasing the distorting effects of rapid field evolution, finding the optimum source surface radius, determining the correction to the sun's polar field, and handling missing data. The predicted structure agrees with direct interplanetary field measurements taken near the ecliptic and with coronameter and interplanetary scintillation measurements which infer the three dimensional interplanetary magnetic structure. During most of the solar cycle the heliospheric field cannot be adequately described as a dipole.

Hoeksema, J. T.↗

Linear-quadratic-Gaussian synthesis with reduced parameter sensitivity

We present a method for improving the tolerance of a conventional LQG controller to parameter errors in the plant model. The improvement is achieved by introducing additional terms reflecting the structure of the parameter errors into the LQR cost function, and also the process and measurement noise models. Adjusting the sizes of these additional terms permits a trade-off between robustness and nominal performance. Manipulation of some of the additional terms leads to high gain controllers while other terms lead to low gain controllers. Conditions are developed under which the high-gain approach asymptotically recovers the robustness of the corresponding full-state feedback design, and the low-gain approach makes the closed-loop poles asymptotically insensitive to parameter errors.

Lin, J. Y.↗

A quantitative assessment of the model form error of friction models across different interface representations for jointed structures

Hysteretic models are widely used to model frictional interactions in joints to recreate experimental behavior. However, it is unclear which models are best suited for fitting or predicting the responses of structures. Here, the present study evaluates 26 friction model/interface representation combinations to quantify the model form error. A Quasi-Static Modal Analysis approach (termed Rayleigh Quotient Nonlinear Modal Analysis) is adopted to calculate the nonlinear system response, and a Multi-Objective Optimization is solved to fit experimental data of the first mode of the Brake-Reuß Beam. Optimized parameters from the first mode are applied to the second and third bending modes to quantify the predictive ability of the models. Formulations for both tracing full hysteresis loops and recreating hysteresis loops from a single loading curve (Masing assumptions) are considered. Smoothly varying models applied to a five patch representation showed the highest flexibility (for fitting mode 1) and good predictive potential (for modes 2 and 3). For a second formulation, which uses 152 frictional elements to represent the interface, the physically motivated spring in series with a Coulomb slip model (elastic dry friction) has high error for fitting mode 1 and performs near the middle for predicting higher modes. For both interface representation, the best fit models are not the most physical, but rather the ones with the most parameters (as expected); however, the more physical models perform somewhat better for predicting the higher modes.

42 ENGINEERING↗

Error analysis of finite element solutions for postbuckled cylinders

A general method of error analysis and correction is investigated for the discrete finite-element results for cylindrical shell structures. The method for error analysis is an adaptation of the method of successive approximation. When applied to the equilibrium equations of shell theory, successive approximations derive an approximate continuous solution from the discrete finite-element results. The advantage of this continuous solution is that it contains continuous partial derivatives of an order higher than the basis functions of the finite-element solution. Preliminary numerical results are presented in this paper for the error analysis of finite-element results for a postbuckled stiffened cylindrical panel modeled by a general purpose shell code. Numerical results from the method have previously been reported for postbuckled stiffened plates. A procedure for correcting the continuous approximate solution by Newton's method is outlined.

Sistla, Rajaram↗

Modeling mechanical behavior of an additively manufactured metal structure with local texture variations: a study on model form error

Here, the repetitive rapid solidification that occurs in metal additive manufacturing (AM) processes creates microstructures distinctly different from wrought materials. Local variability in AM microstructures (either by design or unintentional) raises questions as to how AM structures should be modeled at the part-scale to minimize modeling error. The key goal of this work is to demonstrate a posteriori error estimation applied to an AM part. It is assumed that the actual microstructure is unknown and an approximate, spatially uniform material model is used. Error bounds are calculated for many reference models based on AM microstructures with elongated grain morphology and localized or global fiber textures during a post-processing step. The current findings promote confidence that a posteriori model form error estimation could be used effectively in mechanical performance simulations of AM parts to quickly obtain quantitative error metrics between an approximate model result and many microstructure-based reference models. The a posteriori error estimation introduces significant time savings compared to computing the full reference model solutions. Tight bounds on model form error are obtained when texture variations in the reference models occur on large length scales. For materials with property variation at small length scales, multi-scale error estimation techniques are needed to properly account for the many interfaces present between areas with different properties.

36 MATERIALS SCIENCE↗

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗

A two dimensional interface element for coupling of independently modeled three dimensional finite element meshes and extensions to dynamic and non-linear regimes

The work reported here pertains only to the first year of research for a three year proposal period. As a prelude to this two dimensional interface element, the one dimensional element was tested and errors were discovered in the code for built-up structures and curved interfaces. These errors were corrected and the benchmark Boeing composite crown panel was analyzed successfully. A study of various splines led to the conclusion that cubic B-splines best suit this interface element application. A least squares approach combined with cubic B-splines was constructed to make a smooth function from the noisy data obtained with random error in the coordinate data points of the Boeing crown panel analysis. Preliminary investigations for the formulation of discontinuous 2-D shell and 3-D solid elements were conducted.

Aminpour, Mohammad↗

Microwave Resonator Measurements of Atmospheric Absorption Coefficients: A Preliminary Design Study

A preliminary design study examined the feasibility of using microwave resonator measurements to improve the accuracy of atmospheric absorption coefficients and refractivity between 18 and 35 GHz. Increased accuracies would improve the capability of water vapor radiometers to correct for radio signal delays caused by Earth's atmosphere. Calibration of delays incurred by radio signals traversing the atmosphere has applications to both deep space tracking and planetary radio science experiments. Currently, the Cassini gravity wave search requires 0.8-1.0% absorption coefficient accuracy. This study examined current atmospheric absorption models and estimated that current model accuracy ranges from 5% to 7%. The refractivity of water vapor is known to 1% accuracy, while the refractivity of many dry gases (oxygen, nitrogen, etc.) are known to better than 0.1%. Improvements to the current generation of models will require that both the functional form and absolute absorption of the water vapor spectrum be calibrated and validated. Several laboratory techniques for measuring atmospheric absorption and refractivity were investigated, including absorption cells, single and multimode rectangular cavity resonators, and Fabry-Perot resonators. Semi-confocal Fabry-Perot resonators were shown to provide the most cost-effective and accurate method of measuring atmospheric gas refractivity. The need for accurate environmental measurement and control was also addressed. A preliminary design for the environmental control and measurement system was developed to aid in identifying significant design issues. The analysis indicated that overall measurement accuracy will be limited by measurement errors and imprecise control of the gas sample's thermodynamic state, thermal expansion and vibration- induced deformation of the resonator structure, and electronic measurement error. The central problem is to identify systematic errors because random errors can be reduced by averaging. Calibrating the resonator measurements by checking the refractivity of dry gases which are known to better than 0.1% provides a method of controlling the systematic errors to 0.1%. The primary source of error in absorptivity and refractivity measurements is thus the ability to measure the concentration of water vapor in the resonator path. Over the whole thermodynamic range of interest the accuracy of water vapor measurement is 1.5%. However, over the range responsible for most of the radio delay (i.e. conditions in the bottom two kilometers of the atmosphere) the accuracy of water vapor measurements ranges from 0.5% to 1.0%. Therefore the precision of the resonator measurements could be held to 0.3% and the overall absolute accuracy of resonator-based absorption and refractivity measurements will range from 0.6% to 1.

Walter, Steven J.↗

Accuracy analysis of the semi-analytical method for shape sensitivity calculation

The semianalytical method, widely used for calculating derivatives of static response with respect to design variables for structures modeled by finite elements, is studied in this paper. The paper shows that the method can have serious accuracy problems for shape design variables in structures modeled by beam, plate, truss, frame, and solid elements. The errors are shown to be associated with the structural model. An error index is developed to test the accuracy of the semianalytical method. It characterizes the difference in errors between a general finite-difference method and the semianalytical method. Moreover, a method for improving the accuracy of the semianalytical method (when possible) is provided. Examples are presented to demonstrate the use of the error index.

Barthelemy, Bruno↗

Dynamics and control of a large space antenna

It is pointed out that large space antennae and other large space structures will play an important role in the coming decades as commercial applications of space become feasible. A investigation is conducted of the structural dynamics and the control properties for a 64-meter diameter center fed antenna. Attention is given to antenna configuration and structural dynamic porperties, the attitude and structural control system, disturbance assessment, hardware sizing, the construction of weighting matrices, and numerical results. It is found that structural uncertainties and model error can cause serious performance deterioration and can even destabilize the controllers. Flight test and in-orbit system identification of critical structural modes will insure performance and reduce risk for large space antenna missions.

Wang, S. J.↗

Discrete Assemblers Utilizing Conventional Motion Systems

An alternative to additive manufacturing is disclosed, introducing an end-to-end workflow in which discrete building blocks are reversibly joined to produce assemblies called digital materials. Described is the design of the bulk-material building blocks and the devices that are assembled from them. Detailed is the design and implementation of an automated assembler, which takes advantage of the digital material structure to avoid positioning errors within a large tolerance. To generate assembly sequences, a novel CAD/CAM workflow is described for designing, simulating, and assembling digital materials. The structures assembled using this process have been evaluated, showing that the joints perform well under varying conditions and that the assembled structures are functionally precise.

Langford, William Kai↗

Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction

We introduce a novel neural network, SkyReconNet, which combines the expanded receptive fields of dilated convolutional layers along with standard convolutions, to capture both the global and local features for reconstructing the missing information in an image. We implement our network to inpaint the masked regions in a full-sky cosmic microwave background (CMB) map. Inpainting CMB maps is a particularly formidable challenge when dealing with extensive and irregular masks, such as galactic masks which can obscure substantial fractions of the sky. The hybrid design of SkyReconNet leverages the strengths of standard and dilated convolutions to accurately predict CMB fluctuations in the masked regions by effectively utilizing the information from surrounding unmasked areas. During training, the network optimizes its weights by minimizing a composite loss function that combines the structural similarity index measure (SSIM) and mean squared error (MSE). SSIM preserves the essential structural features of the CMB, ensuring an accurate and coherent reconstruction of the missing CMB fluctuations, while MSE minimizes the pixelwise deviations, thus enhancing the overall accuracy of the predictions. The predicted CMB maps and their corresponding angular power spectra align closely with the targets, achieving the performance limited only by the fundamental uncertainty of cosmic variance. The network’s generic architecture enables application to other physics-based challenges involving data with missing or defective pixels, systematic artifacts, etc. In conclusion, our results demonstrate its effectiveness in addressing the challenges posed by large irregular masks, offering a significant inpainting tool not only for CMB analyses but also for image-based experiments across disciplines where such data imperfections are prevalent.

Cosmic microwave background↗

Distant Observer™ [SWR-12-09]

Distant Observer™ (DO) is an optical measurement tool, designed for parabolic trough solar collectors, that determines reflector slope error, absorber position error, and the combined errors based on images of the receiver-tube reflection taken from different angles. We have demonstrated that DO can provide a measurement accuracy of 0.25 mrad for the slope and receiver position errors. DO has two implementation versions: ground-based and drone-driven. As we pursue efforts to lower the capital and installation costs of parabolic trough solar collectors, it is essential to maintain high optical performance. The Distant Observer™ (DO) tool, developed by engineers at NREL, is a fast and highly accurate tool that provides complete characterization of the performance of the optical components which include the mirror panels and thermal receiver. This tool is very useful for testing both prototype and operational modules. The Distant Observer™ is an optical measurement tool for parabolic solar collectors that measures reflector slope error, absorber position error and the combined errors. Reflector slope errors occur for many reasons including imperfection in structural frame design, manufacturing and assembly. Absorber position error can be caused by poor structural design, poor installation, sag from the absorber weight, or change in the structure over time.

Ihas, Benjamin↗