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At least 865 records · Page 48

Theoretical, experimental and numerical methods for investigating the characteristics of laser radiation scattered in the integrated-optical waveguide with three-dimensional irregularities

We consider theoretical, experimental and numerical methods which make it possible to analyse the key characteristics of laser radiation scattered in the integrated-optical waveguide with three-dimensional irregularities. The main aspects of the three-dimensional vector electrodynamic problem of waveguide scattering are studied. The waveguide light scattering method is presented and its main advantages over the methods of single scattering of laser radiation are discussed. The experimental setup and results of measurements are described. Theoretical and experimental results confirming the validity of the vector theory of three-dimensional waveguide scattering of laser radiation developed by the author are compared for the first time. (fiber and integrated optics)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental study and numerical modelling of a 3 × 100G DP-QPSK superchannel

Crosstalk effects are studied experimentally in a DWDM line with 100G DP-QPSK channels at a frequency convergence of the channels (three channels with a frequency separation of 50, 37.5 and 33 GHz) in the C-band. Spans of 100 km in length are used, with the number of spans varying from one to six. The required optical signal-to-noise ratio (OSNR{sub R}) is determined experimentally for a different number of spans, interchannel intervals and input power. We propose a theoretical model based on the numerical modelling that describes the influence of adjacent channels at a strong convergence. The model is calibrated using the obtained experimental data. Based on the proposed model, we calculate the maximal value of the spectral efficiency in systems with a dense arrangement of 100G DP-QPSK channels (∼3.2 bit s{sup −1} Hz{sup −1}). (fibre-optic communication)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Bayesian experimental design and parameter estimation for ultrafast spin dynamics

Abstract Advanced experimental measurements are crucial for driving theoretical developments and unveiling novel phenomena in condensed matter and materials physics, which often suffer from the scarcity of large-scale facility resources, such as x-ray or neutron scattering centers. To address these limitations, we introduce a methodology that leverages the Bayesian optimal experimental design paradigm to efficiently uncover key quantum spin fluctuation parameters from x-ray photon fluctuation spectroscopy (XPFS) data. Our method is compatible with existing theoretical simulation pipelines and can also be used in combination with fast machine learning surrogate models in the event that real-time simulations are unfeasible. Our numerical benchmarks demonstrate the superior performance in predicting model parameters and in delivering more informative measurements within limited experimental time. Our method can be adapted to many different types of experiments beyond XPFS and spin fluctuation studies, facilitating more efficient data collection and accelerating scientific discoveries.

97 MATHEMATICS AND COMPUTING↗

Determination of low-energy parameters of neutron-proton scattering in the the shape-parameter approximation from present-day experimental data

On the basis of the total cross sections for neutron-proton scattering in the region of laboratory energies below 150 keV, the value of {sigma}{sub 0} = 20.4288(146) b was obtained for the total cross sections for neutron-proton scattering at zero energy. This value is in very good agreement with the experimental cross sections obtained by Houke and Hurst, but it is at odds with Dilg's experimental cross section. By using the value that we found for {sigma}{sub 0} and the experimental values of the neutron-proton coherent scattering length f, the deuteron binding energy {epsilon}{sub t}, the deuteron effective radius {rho}{sub t}(-{epsilon}{sub t}, -{epsilon}{sub t}), and the total cross section in the region of energies below 5 MeV, the following values were found in the shape-parameter approximation for the low-energy parameters of neutron-proton scattering in the spin-triplet and spin-singlet states: a{sub t} = 5.4114(27) fm, r{sub 0t} = 1.7606(35) fm, v{sub 2t} = 0.157 fm{sup 3}, a{sub s} = -23.7154(80) fm, r{sub 0s} = 2.706(67) fm, and v{sub 2s} = 0.491 fm{sup 3}.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis

Implementing remote, real-time spectroscopic monitoring of radiochemical processing streams in hot cell environments requires efficiency and simplicity. The success of optical spectroscopy for the quantification of species in chemical systems highly depends on representative training sets and suitable validation sets. Selecting a training set (i.e., calibration standards) to build multivariate regression models is both time- and resource-consuming using standard one-factor-at-a-time approaches. This study describes the use of experimental design to generate spectral training sets and a validation set for the quantification of sodium nitrate (0–1 M) and nitric acid (0.1–10 M) using the near-infrared water band centered at 1440 nm. Partial least squares regression models were built from training sets generated by both D- and I-optimal experimental designs and a one-factor-at-a-time approach. The prediction performance of each model was evaluated by comparing the bias and standard error of prediction for statistical significance. D- and I-optimal designs reduced the number of samples required to build regression models compared with one-factor-at-a-time while also improving performance. Models must be confirmed against a validation sample set when minimizing the number of samples in the training set. The D-optimal design performed the best when considering both performance and efficiency by improving predictive capability and reducing number of samples in the training set by 64% compared with the one-factor-at-a-time approach. The experimental design approach objectively selects calibration and validation spectral data sets based on statistical criterion to optimize performance and minimize resources.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Experimental Testing of a Floating Oscillating Surge Wave Energy Converter at Hinsdale Wave Research Laboratory

In order to generate a public data set that can be used to validate Wave Energy Converter (WEC) numerical codes, such as WEC-Sim, Sandia National Laboratories led an experimental testing campaign of a 1:33 scale Floating Oscillating Surge Wave Energy Converter (FOSWEC) in the Directional Wave Basin at Oregon State University's Hinsdale Wave Research Laboratory. Testing was performed in two phases; Phase 1 testing was completed in November - December 2015, and Phase 2 testing was completed in May - June 2016. This experimental testing report details the selection and design of a FOSWEC, experimental setup and tests, and overview of the resulting dataset from Phase 1 and Phase 2 testing.

16 TIDAL AND WAVE POWER↗

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.

97 MATHEMATICS AND COMPUTING↗

DOE Microreactor Program: Summary of Experimental Capabilities Development and Activities

This document provides a summary of the experimental capabilities and activities developed and currently performed under the U.S. Department of Energy’s (DOE’s) Microreactor Program. These capabilities, along with other laboratory capabilities, are available to support developer and other stakeholder needs. Specific experimental capabilities described in this document include the single primary heat extraction and removal emulator (SPHERE), the microreactor agile non-nuclear experimental test bed (MAGNET), microreactor applications research validation and evaluation (MARVEL), yttrium hydride fabrication, the Hypatia critical experiment series, and a brief overview of the National Criticality Experiments Research Center (NCERC), which provides the platform to conduct experiments and training with critical assemblies and fissionable material.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

SPRUCE Bog Surface Elevation Assessments with SPRUCE Elevation Transect Instrument, Marcell Experimental Forest, Minnesota, 2013-2025

This data set reports plot-specific bog surface elevation measurements collected with the SPRUCE Elevation Transect (SET) instrument at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. The SET instrument is a modified version of the Cahoon et al. (2002) surface elevation table instrument. The device is mounted to fixed stands that are anchored in deep sediments, making it capable of identifying subtle changes in bog surface elevation over time. Measurements are reported as absolute elevation in meters above mean sea level (amsl) for two locations in each of the SPRUCE experimental treatment plots and additional ambient boardwalk plots: 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 20 and 21. Measurements were collected from June 2013 through September 2025 (2013-06-02 to 2025-09-08). Changes in bog surface elevation may indicate alterations in the carbon and water cycles due to changing environmental conditions. This data set contains one data file in comma separate (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE NDVI Data from Selected SPRUCE Experimental Plots, 2016-2018

This dataset consists of observations of Normalized Difference Vegetation Index (NDVI) observations from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Measurements were collected via stationary sensors positioned 1.5 meter above unobstructed areas of the ground layer. Sensors were installed above undisturbed community composition plots, that are not instrumented or destructively sampled in any way, in six of the ten chambered SPRUCE experimental study plots located in the S1-Bog. Spectral data (630 and 800 nanometers) were collected at 10-minute intervals over a field of view of ~53 cm in diameter beginning May 6, 2016. Data collection ended at a different time for each sensor as batteries discharged – ranging from January 1, 2018 to April 1, 2018. The spectral sensors were manufactured by Decagon Inc., (now METER) for observation of ecosystem canopies. Sensors were deployed at the beginning of the 2016 growing season in +0, +4.5, and +9.0 C temperature treatments, with one each in an ambient and elevated carbon dioxide (CO2) plot, for a total of six sensors. These data have been analyzed and reported on in McPartland et al (2018). This dataset contains one data file in comma-separate values (*.csv) format and PDF (*.pdf) file containing plot maps. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Fungal Necromass Litter Bag Decomposition Study in SPRUCE Experimental Plots, 2016-2018

This dataset provided the results of a 2-year fungal necromass litter bag decomposition study at the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Necromass from four mycorrhizal fungal species that naturally occur and associate with either the ectomycorrhizal (EM) tree hosts or ericoid mycorrhizal (ERM) shrubs in the S1 Bog site and vary in melanin content (Cenococcum geophilum Fr., Suillus grisellus, Meliniomyces bicolor, and Oideodendron griseum) were incubated in situ in SPRUCE experimental treatment chambers for 3, 12, and 24 months duration beginning in June of 2016 and ending in June of 2018. Analyses of the necromass included pre-incubation chemistry and post-incubation mass loss and Fourier transform infrared (FTIR) spectroscopy of remaining fungal necromass. These data were used in analyses in Fernandez et al (2019). This dataset contains three data files in comma-separate values (*.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE High-Resolution Minirhizotrons in an Experimentally-Warmed Peatland Provide an Unprecedented Glimpse at Fine Roots and their Fungal Partners: Supporting Data

Images were collected using first of their kind, non-destructive, high-resolution automated minirhizotrons (RhizoSystems, LLC) to assess the response of plant fine-root and fungal mycelium dynamics to elevated temperatures after 4-6 years of whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (e[CO2]) in a peat bog where the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment is located. We focused on two SPRUCE experimental plots: Plot 10 has elevated temperature (+9°C) and plot 19 is a control (+0°C). Both have elevated carbon dioxide (e[CO2]). Changes in root and fungal abundance with warming were estimated from a timeseries of landscape-level mosaiced images for each plot by measuring the proportional abundance of five belowground classes: fine roots of vascular plants, ectomycorrhizas, fungal hyphae, fungal rhizomorphs, and fungal sporocarps. To examine root and fungal phenology responses to warming, the length per individual root or fungal structure (except fungal hyphae that did not grow linearly but rather increased in areal coverage) were measured per image area of a set of timeseries patch-level mosaiced images for each plot. The experimental work was conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This ecosystem, which is located at the southern margin of the boreal forest, is considered especially vulnerable to climate change and anticipated to be near its tipping point. These data were used in analyses published in Defrenne et al (2021). This dataset contains 5 data files in comma-separate values (*.csv) format and a compressed folder (*.zip) containing 383 JPEG (*.jpg) images. Data files contain landscape-level assessment of belowground class abundance, patch-level growth phenology, and environmental variables (originally published in Hanson et al., 2016 and Hanson et al 2020). Images were collected with automated minirhizotrons and analyzed for phenology. Additional metadata are provided: 5 data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Redox-Active Subsurface Organic Matter, Marcell Experimental Forest, Minnesota, 2023

This dataset contains measurements that report on the effects of the SPRUCE experimental treatments on redox-active organic matter (RAOM) reduction (Valenzuela and Cervantes, 2021). Measurements occurred at the SPRUCE Experiment site in the Marcell Experimental Forest in northern Minnesota, USA. This work is also a follow-up to Rush et al. (2021a) which investigated effects of temperature on RAOM reduction after two years of experimental warming (Rush et al. 2021b). This follow-up dataset addresses two main questions; (i) How does warming and elevated carbon dioxide (CO2) directly affect in situ RAOM reduction, and subsequent methane (CH4) and CO2 production, across the peat depth profile? and (ii) How has long-term warming and elevated CO2 changed the total RAOM pool, and subsequent CH4 and CO2 production, across the peat depth profile? This dataset reports electron shuttling capacity (a proxy for RAOM reduction; Keller, and Takagi, 2013) and carbon dioxide (CO2) and methane (CH4) concentrations both in one-week in situ incubations (2023-05-31 to 2023-08-01) and 42-day laboratory incubations from peat collected in 2023 (2023-05-31 to 2023-06-26). Laboratory incubations also measured acetate concentrations. The 2023 laboratory incubations were also compared with laboratory incubations conducted on peat collected in 2016 (Rush et al. 2021b). This dataset contains three data files in comma-separate (.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

Experimental and Computational Sonic Boom Assessment of Boeing N+2 Low Boom Models

Near-field pressure signatures were measured and computational predictions made for several sonic boom models representing Boeing's Quiet Experimental Validation Concept (QEVC) supersonic transport, as well as three axisymmetric calibration models. Boeing developed the QEVC under a NASA Research Announcement (NRA) contract for Experimental Systems Validations for N+2 Supersonic Commercial Transport Aircraft, which was led by the NASA High Speed Project under the Fundamental Aeronautics Program. The concept was designed to address environmental and performance goals given in the NRA, specifically for low sonic boom loudness levels and high cruise efficiency, for an aircraft anticipated to enter service in the 2020 timeframe. Wind tunnel tests were conducted on the aircraft and calibration models during Phases I and II of the NRA contract from 2011 to 2013 in the NASA Ames 9- by 7-Foot and NASA Glenn 8- by 6-Foot Supersonic Wind Tunnels. Sonic boom pressure signatures were acquired primarily at Mach 1.6 and 1.8, and force and moment data were acquired from Mach 0.8 to 1.8. The sonic boom test data were obtained using a 2-in. flat-top pressure rail and a 14-in. round-top tapered "reflection factor 1" (RF1) pressure rail. Both rails capture an entire pressure signature in one data point, and successive signatures at varying positions along or above the rail were used to improve data quality through spatial averaging. The sonic boom data obtained by the rails were validated with high-fidelity numerical simulations of off-body pressures using the CFD codes USM3D, Cart3D, and OVERFLOW. The test results from the RF1 rail showed good agreement between the computational and experimental data when a variety of testing techniques including spatial averaging of a series of pressure signatures were employed, however, reflections off the 2-in. flat-top rail caused distortions in the signatures that did not agree with the CFD predictions. The 9 x 7 and 8 x 6 wind tunnels generally produced comparable data.

pressure signature↗

Experimental Validation of Pulse Phase Tracking for X-Ray Pulsar Based

Pulsars are a form of variable celestial source that have shown to be usable as aids for autonomous, deep space navigation. Particularly those sources emitting in the X-ray band are ideal for navigation due to smaller detector sizes. In this paper X-ray photons arriving from a pulsar are modeled as a non-homogeneous Poisson process. The method of pulse phase tracking is then investigated as a technique to measure the radial distance traveled by a spacecraft over an observation interval. A maximum-likelihood phase estimator (MLE) is used for the case where the observed frequency signal is constant. For the varying signal frequency case, an algorithm is used in which the observation window is broken up into smaller blocks over which an MLE is used. The outputs of this phase estimation process were then looped through a digital phase-locked loop (DPLL) in order to reduce the errors and produce estimates of the doppler frequency. These phase tracking algorithms were tested both in a computer simulation environment and using the NASA Goddard Space flight Center X-ray Navigation Laboratory Testbed (GXLT). This provided an experimental validation with photons being emitted by a modulated X-ray source and detected by a silicon-drift detector. Models of the Crab pulsar and the pulsar B1821-24 were used in order to generate test scenarios. Three different simulated detector trajectories were used to be tracked by the phase tracking algorithm: a stationary case, one with constant velocity, and one with constant acceleration. All three were performed in one-dimension along the line of sight to the pulsar. The first two had a constant signal frequency and the third had a time varying frequency. All of the constant frequency cases were processed using the MLE, and it was shown that they tracked the initial phase within 0.15% for the simulations and 2.5% in the experiments, based on an average of ten runs. The MLE-DPLL cascade version of the phase tracking algorithm was used in the varying frequency case. This resulted in tracking of the phase and frequency by the DPLL outputs in both the simulation and experimental environments. The crab pulsar was experimentally tested with a trajectory with a higher acceleration. In this case the phase error tended toward zero as the observation extended to 250 seconds and the doppler frequency error tended to zero in under 100 seconds.

Experimental↗

Experimental Setup for Mechanically Testing Subscale Triangular, Rollable, and Collapsible Deployable Composite Booms

High-strain composite deployable space structures are used for space infrastructure and science applications such as solar array supports, antennae, camera masts, and lightweight structures supporting solar sailing propulsion ele-ments. Triangular, Rollable, and Collapsible (TRAC) deployable composite booms are one example of a high-strain composite deployable structure and were studied using novel experimental test and characterization methods developed under the Gravity Offloading and Analysis of Long Imperfection-sensitive Ele-ments (GOALIE) project. In the present work, a subscale 7-m-long TRAC boom was suspended vertically to orient gravity along the length of the boom. By ori-enting vertically, highly nonlinear and unstable behavior often encountered dur-ing horizontally oriented gravity offload testing of similar structures was reduced. Pretest analytical predictions of TRAC booms indicated three unique failure modes, loads, and locations for three unique loading cases of in-plane bending, out-of-plane bending, and axial compression. To investigate the predicted behav-ior, an experimental test was set up to impart mechanical loads to a subscale TRAC boom. The experimental setup, loading cases, and instrumentation used to characterize the mechanical response of a subscale TRAC boom are described in this paper.

High-strain composites↗

Experimental Setup for Mechanically Testing Subscale Triangular, Rollable, and Collapsible Deployable Composite Booms

High-strain composite deployable space structures are used for space infrastructure and science applications such as solar array supports, antennae, camera masts, and lightweight structures supporting solar sailing propulsion elements. Triangular, Rollable, and Collapsible (TRAC) deployable composite booms are one example of a high-strain composite deployable structure and were studied using novel experimental test and characterization methods developed under the Gravity Offloading and Analysis of Long Imperfection-sensitive Elements (GOALIE) project. In the present work, a subscale 7-m-long TRAC boom was suspended vertically to orient gravity along the length of the boom. By orienting vertically, highly nonlinear and unstable behavior often encountered during horizontally oriented gravity offload testing of similar structures was reduced. Pretest analytical predictions of TRAC booms indicated three unique failure modes, loads, and locations for three unique loading cases of in-plane bending, out-of-plane bending, and axial compression. To investigate the predicted behavior, an experimental test was set up to impart mechanical loads to a subscale TRAC boom. The experimental setup, loading cases, and instrumentation used to characterize the mechanical response of a subscale TRAC boom are described in this paper.

Experimental testing↗

Perspectives on Prediction Variance and Bias in Developing, Assessing, and Comparing Experimental Designs

The vast majority of response surface methods used in practice to develop, assess, and compare experimental designs focus on variance properties of designs. Because response surface models only approximate the true unknown relationships, models are subject to bias errors as well as variance errors. Beginning with the seminal paper of Box and Draper (1959) and over the subsequent 50 years, methods that consider bias and mean-squared-error (variance and bias) properties of designs have been presented in the literature. However, these methods are not widely implemented in software and are not routinely used to develop, assess, and compare experimental designs in practice. Methods for developing, assessing, and comparing response surface designs that account for variance properties are reviewed. Brief synopses of publications that consider bias or mean-squared-error properties are provided. The difficulties and approaches for addressing bias properties of designs are summarized. Perspectives on experimental design methods that account for bias and/or variance properties and on future needs are presented.

97 MATHEMATICS AND COMPUTING↗