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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

H2S data reduction

Calculating microwave opacity from a weakly absorbing gas mixture using a resonator requires measuring the quality factor of that resonator which necessitates accurately determining the center frequency (f(sub O)) and the half power bandwidth (Delta-f) of a noisy resonant line. The center frequency can be determined very accurately and varies very little over many measurements (a few kHz at GHz frequencies or a few hundredths of a percent). The greater source of error in estimating the Q of a resonator come from the bandwidth measurements. The half power bandwidth is determined essentially by eye-fitting a curve over a noisy resonant line and measuring with a spectrum analyzer.

Deboer, David↗
NASA NTRS1994

TDRSS Onboard Navigation System (TONS) flight qualification experiment

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is currently developing an operational Tracking and Data Relay Satellite (TDRS) System (TDRSS) Onboard Navigation System (TONS) to provide realtime, autonomous, high-accuracy navigation products to users of TDRSS. A TONS experiment was implemented on the Explorer Platform/Extreme Ultraviolet Explorer (EP/EUVE) spacecraft, launched June 7, 1992, to flight qualify the TONS operational system using TDRSS forward-link communications services. This paper provides a detailed evaluation of the flight hardware, an ultrastable oscillator (USO) and Doppler extractor (DE) card in one of the TDRSS user transponders and the ground-based prototype flight software performance, based on the 1 year of TONS experiment operation. The TONS experiment results are used to project the expected performance of the TONS 1 operational system. TONS 1 processes Doppler data derived from scheduled forward-link S-band services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination and time maintenance. TONS 1 will be the prime navigation system on the Earth Observing System (EOS)-AM1 spacecraft, currently scheduled for launch in 1998. Inflight evaluation of the USO and DE short-term and long-term stability indicates that the performance is excellent. Analysis of the TONS prototype flight software performance indicates that realtime onboard position accuracies of better than 25 meters root-mean-square are achievable with one tracking contact every one to two orbits for the EP/EUVE 525-kilometer altitude, 28.5 degree inclination orbit. The success of the TONS experiment demonstrates the flight readiness of TONS to support the EOS-AM1 mission.

Gramling, C. J.↗
NASA NTRS1996

Autonomous Navigation With Ground Station One-Way Forward-Link Doppler Data

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has spent several years developing operational onboard navigation systems (ONS's) to provide real time autonomous, highly accurate navigation products for spacecraft using NASA's space and ground communication systems. The highly successful Tracking and Data Relay Satellite (TDRSS) ONS (TONS) experiment on the Explorer Platform/Extreme Ultraviolet (EP/EUV) spacecraft, launched on June 7, 1992, flight demonstrated the ONS for high accuracy navigation using TDRSS forward link communication services. In late 1994, a similar ONS experiment was performed using EP/EUV flight hardware (the ultrastable oscillator and Doppler extractor card in one of the TDRSS transponders) and ground system software to demonstrate the feasibility of using an ONS with ground station forward link communication services. This paper provides a detailed evaluation of ground station-based ONS performance of data collected over a 20 day period. The ground station ONS (GONS) experiment results are used to project the expected performance of an operational system. The GONS processes Doppler data derived from scheduled ground station forward link services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination. Analysis of the GONS experiment performance indicates that real time onboard position accuracies of better than 125 meters (1 sigma) are achievable with two or more 5-minute contacts per day for the EP/EUV 525 kilometer altitude, 28.5 degree inclination orbit. GONS accuracy is shown to be a function of the fidelity of the onboard propagation model, the frequency/geometry of the tracking contacts, and the quality of the tracking measurements. GONS provides a viable option for using autonomous navigation to reduce operational costs for upcoming spacecraft missions with moderate position accuracy requirements.

Horstkamp, G. M.↗
NASA NTRS2002

Critical Spacecraft-to-Earth Communications for Mars Exploration Rover (MER) entry, descent and landing

For planetary lander missions, the most challenging phase of the spacecraft to ground communications is during the entry, descent, and landing (EDL). As each 2003 Mars Exploration Rover (MER) enters the Martian atmosphere, it slows dramatically. The extreme acceleration and jerk cause extreme Doppler dynamics on the X-band signal received on Earth. When the vehicle slows sufficiently, the parachute is deployed, causing almost a step in deceleration. After parachute deployment, the lander is lowered beneath the parachute on a bridle. The swinging motion of the lander imparts high Doppler dynamics on the signal and causes the received signal strength to vary widely, due to changing antenna pointing angles. All this time, the vehicle transmits important health and status information that is especially critical if the landing is not successful. Even using the largest Deep Space Network antennas, the weak signal and high dynamics render it impossible to conduct reliable phase coherent communications. Therefore, a specialized form of frequency-shift-keying will be used. This paper describes the EDL scenario, the signal conditions, the methods used to detect and frequency-track the carrier and to detect the data modulation, and the resulting performance estimates.

entry, descent, and landing communications↗
NASA NTRS2016

Development Of VHF (240-270 MHz) Antennas For SoOp (Signal Of Opportunity) Receiver For 6u Cubesat Platforms

The main goal of this research is to design, fabricate, and test deployable VHF antennas for 6U Cubesat platforms to enable validation of root zone soil moisture (RZSM) estimation algorithms for signal of opportunity (SoOp) remote sensing over the 240-270 MHz frequency band. The proposed work provides a strong foundation for establishing a technology development path for maturing a truly global direct surface soil moisture (SM) and RZSM measurement system (Figure 1) over a variety of land covers with limited density restrictions. In SoOp methodology, signals transmitted by already existing transmitters (known as transmitters of opportunity, in this case the Military Satellite Communication (MilSatCom) System's UHF Follow-On program) are utilized to measure properties of reflecting targets by recording reflected signals using a simple passive microwave receiver.

Cubesat↗
NASA NTRS2016

Unsteady Aerodynamic Force Sensing from Measured Strain

A simple approach for computing unsteady aerodynamic forces from simulated measured strain data is proposed in this study. First, the deflection and slope of the structure are computed from the unsteady strain using the two-step approach. Velocities and accelerations of the structure are computed using the autoregressive moving average model, on-line parameter estimator, low-pass filter, and a least-squares curve fitting method together with analytical derivatives with respect to time. Finally, aerodynamic forces over the wing are computed using modal aerodynamic influence coefficient matrices, a rational function approximation, and a time-marching algorithm. A cantilevered rectangular wing built and tested at the NASA Langley Research Center (Hampton, Virginia, USA) in 1959 is used to validate the simple approach. Unsteady aerodynamic forces as well as wing deflections, velocities, accelerations, and strains are computed using the CFL3D computational fluid dynamics (CFD) code and an MSC/NASTRAN code (MSC Software Corporation, Newport Beach, California, USA), and these CFL3D-based results are assumed as measured quantities. Based on the measured strains, wing deflections, velocities, accelerations, and aerodynamic forces are computed using the proposed approach. These computed deflections, velocities, accelerations, and unsteady aerodynamic forces are compared with the CFL3D/NASTRAN-based results. In general, computed aerodynamic forces based on the lifting surface theory in subsonic speeds are in good agreement with the target aerodynamic forces generated using CFL3D code with the Euler equation. Excellent aeroelastic responses are obtained even with unsteady strain data under the signal to noise ratio of -9.8dB. The deflections, velocities, and accelerations at each sensor location are independent of structural and aerodynamic models. Therefore, the distributed strain data together with the current proposed approaches can be used as distributed deflection, velocity, and acceleration sensors. This research demonstrates the feasibility of obtaining induced drag and lift forces through the use of distributed sensor technology with measured strain data. An active induced drag control system thus can be designed using the two computed aerodynamic forces, induced drag and lift, to improve the fuel efficiency of an aircraft. Interpolation elements between structural finite element grids and the CFD grids and centroids are successfully incorporated with the unsteady aeroelastic computation scheme. The most critical technology for the success of the proposed approach is the robust on-line parameter estimator, since the least-squares curve fitting method depends heavily on aeroelastic system frequencies and damping factors.

shape sensing↗
NASA NTRS2019

The Impact of Neglecting Ice Phase on Cloud Optical Depth Retrievals from AERONET Cloud Mode Observations

Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world. Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid. This assumption has the potential to introduce errors into long term statistics of retrieved optical depth for clouds that also contain ice. Using a set of idealized cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence of ice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55% to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2– 4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10% and surface flux to about 15 %.

Shonk, Jonathan K. P.↗
NASA NTRSDate not supplied

Modification of Mach 6 Freestream Flow by Pitot Probe Bow Shock as Measured by Line FLDI and SAFS

Measurements of the flow in front of flat-face Pitot probes in NASA Langley ResearchCenter’s 20-Inch Mach 6 Air Tunnel were made using a 35-point line focused laser differentialinterferometer (FLDI), a two-point FLDI, and a self-aligned focusing schlieren system. Thesesystems were used to make measurements of flow unsteadiness between the bow shock andPitot probe face, while also probing the freestream region just upstream of the bow shock.Shock standoff distances from the non-intrusive measurements match closely with analyticalsolutions using the probe face diameter. Acoustic wave angles and velocities in the freestreamcompare favorably with DNS simulations of a Mach 6 freestream flow, and wave velocities in thepost-shock region slow as they approach the probe face. Peak frequencies in the post-shockregion as measured by FLDI compare favorably to the estimates computed from the shockstandoff distance for most probe diameters. With increasing unit Reynolds number, fluctuationintensities in the post-shock region were attenuated below the intensities of the freestream, witha spectral, spatial, and probe size dependence. Pitot probe power spectral density estimatesare presented from the test campaign, which can be compared with FLDI and SAFS data toevaluate the applicability of the transfer functions derived from computational simulations.

Joshua M Weisberger↗
DOE OSTI2024

Estimation of mean electron energy in helium surface ionization waves on dielectric substrates

Abstract The determination of basic plasma parameters in atmospheric pressure discharges is critical to advancing their use in applications. Atmospheric pressure plasma jets have found use in the fields of medicine, agriculture, material modification and others. Atmospheric pressure plasma jets often generate plasma surface ionization waves (SIW) which interact with and propagate over surfaces. Electrical diagnostics are challenging in SIW due to high collision frequencies and small scale of the plasma discharge. This work employs a passive optical emission line ratio technique to estimate the mean electron energy in SIW over planar dielectric substrates. The method uses an intensity ratio of two helium triplet lines: He( 3 3 S ) at 706.5 nm and He( 3 3 D ) at 587.56 nm. A collisional-radiative model is used to correlate line ratio to mean electron energy and determine dependencies on electron density and He/air gas mixture. Mean electron energies ranging from 3–8 eV are determined in He/air mixtures and are found to remain constant as the surface wave propagates radially. This work provides a 2D, time-resolved, mean electron energy diagnostic for surface ionization wave propagation and validation of numerical modeling in atmospheric pressure systems with spatially varying He/air gas mixtures. The model in question is designed for use with any He line ratio in the n = 3 excitation level.

Morsell, Joshua (ORCID:0000000331073002)↗
NASA NTRS1985

Active and passive microwave measurements in Hurricane Allen

The NASA Langley Research Center analysis of the airborne microwave remote sensing measurements of Hurricane Allen obtained on August 5 and 8, 1980 is summarized. The instruments were the C-band stepped frequency microwave radiometer and the Ku-band airborne microwave scatterometer. They were carried aboard a NOAA aircraft making storm penetrations at an altitude of 3000 m and are sensitive to rain rate, surface wind speed, and surface wind vector. The wind speed is calculated from the increase in antenna brightness temperature above the estimated calm sea value. The rain rate is obtained from the difference between antenna temperature increases measured at two frequencies, and wind vector is determined from the sea surface normalized radar cross section measured at several azimuths. Comparison wind data were provided from the inertial navigation systems aboard both the C-130 aircraft at 3000 m and a second NOAA aircraft (a P-3) operating between 500 and 1500 m. Comparison rain rate data were obtained with a rain radar aboard the P-3. Evaluation of the surface winds obtained with the two microwave instruments was limited to comparisons with each other and with the flight level winds. Two important conclusions are drawn from these comparisons: (1) the radiometer is accurate when predicting flight level wind speeds and rain; and (2) the scatterometer produces well behaved and consistent wind vectors for the rain free periods.

Delnore, V. E.↗
NASA NTRS2014

A Framework for Dimensioning VDL-2 Air-Ground Networks

This paper describes a framework developed at MITRE for dimensioning a Very High Frequency (VHF) Digital Link Mode 2 (VDL-2) Air-to-Ground network. This framework was developed to support the FAA's Data Communications (Data Comm) program by providing estimates of expected capacity required for the air-ground network services that will support Controller-Pilot-Data-Link Communications (CPDLC), as well as the spectrum needed to operate the system at required levels of performance. The Data Comm program is part of the FAA's NextGen initiative to implement advanced communication capabilities in the National Airspace System (NAS). The first component of the framework is the radio-frequency (RF) coverage design for the network ground stations. Then we proceed to describe the approach used to assess the aircraft geographical distribution and the data traffic demand expected in the network. The next step is the resource allocation utilizing optimization algorithms developed in MITRE's Spectrum ProspectorTM tool to propose frequency assignment solutions, and a NASA-developed VDL-2 tool to perform simulations and determine whether a proposed plan meets the desired performance requirements. The framework presented is capable of providing quantitative estimates of multiple variables related to the air-ground network, in order to satisfy established coverage, capacity and latency performance requirements. Outputs include: coverage provided at different altitudes; data capacity required in the network, aggregated or on a per ground station basis; spectrum (pool of frequencies) needed for the system to meet a target performance; optimized frequency plan for a given scenario; expected performance given spectrum available; and, estimates of throughput distributions for a given scenario. We conclude with a discussion aimed at providing insight into the tradeoffs and challenges identified with respect to radio resource management for VDL-2 air-ground networks.

Aviation↗
DOE OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Report on Depth-Dependent Q from Frequency-Dependent Lg Q

As a phase that travels through the crustal waveguide, Lg samples the velocity and attenuation structure of the crust. We have developed methods (Pasyanos et al., 2009a; Pasyanos et al., 2009b) to estimate Qp and Qs of the crust and upper mantle from the amplitudes of regional phases, and have applied it to a number of regions around the world, and over a broad frequency band (0.5 - 10 Hz). In prior attenuation modeling, Lg phase amplitudes are able to effectively distinguish the high Q (low attenuation) of old stable cratonic crust from the low Q (high attenuation) of more recently active tectonic regions. For a variety of purposes (e.g. waveform modeling, seismic hazard, etc.), it is useful to have more information on the depth-dependence of the Q structure in the crust. One obvious candidate for doing this is using the frequency-dependence information of Lg Q, in the manner of surface waves. Unfortunately, however, Lg samples the whole of the crust without much differentiation with respect to frequency that is characteristic of fundamental mode surface waves. Lg is generally thought to be the sum of supercritically reflected S-waves trapped in the crustal waveguide (e.g. Xie and Lay, 1994). The phase can also be modeled as a superposition of surface waves. At lower frequencies, it is primarily composed of fundamental and low-order surface waves, while at higher frequencies, it is comprised purely of many high-order surface waves. The low-order surface waves that comprise Lg in low frequency bands (< 1 Hz) are preferentially sensitive to shallow earth structure, such as sedimentary basins and upper crust, while high-order surface waves have a more homogenized sensitivity to the whole crust. Furthermore, at the lower frequencies, we might expect to see some differentiation in the sensitivity between early Lg (herein referred to as Lg1) and late Lg (referred to as Lg2) where the latter is comprised of lower-order surface waves and, hence, shallower structure. Therefore, we might expect to see the signature of shallow features, primarily the lower Q of sediments as compared to crystalline crust, at lower frequencies and in later arriving Lg amplitudes.

58 GEOSCIENCES↗
NASA NTRS1975

Mission Analysis Program for Solar Electric Propulsion (MAPSEP). Volume 2: User's manual for earth orbital MAPSEP

The trajectory simulation mode (SIMSEP) requires the namelist SIMSEP to follow TRAJ. The SIMSEP contains parameters which describe the scope of the simulation, expected dynamic errors, and cumulative statistics from previous SIMSEP runs. Following SIMSEP are a set of GUID namelists, one for each guidance correction maneuver. The GUID describes the strategy, knowledge or estimation uncertainties and cumulative statistics for that particular maneuver. The trajectory display mode (REFSEP) requires only the namelist TRAJ followed by scheduling cards, similar to those used in GODSEP. The fixed field schedule cards define: types of data displayed, span of interest, and frequency of printout. For those users who can vary the amount of blank common storage in their runs, a guideline to estimate the total MAPSEP core requirements is given. Blank common length is related directly to the dimension of the dynamic state (NDIM) used in transition matrix (STM) computation, and, the total augmented (knowledge) state (NAUG). The values of program and blank common must be added to compute the total decimal core for a CDC 6500. Other operating systems must scale these requirements appropriately.

Source record↗
DOE OSTI2023

Calibrating radar wind profiler reflectivity factor using surface disdrometer observations

Abstract. This study uses surface disdrometer reflectivity factor estimates to calibrate the vertical and off-vertical pointing radar beams produced by an ultra high frequency (UHF) band radar wind profiler (RWP) deployed at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) Central Facility in northern Oklahoma from April 2011 through July 2019. The methodology consists of five steps. First, the recorded Doppler velocity power spectra are adjusted to account for Nyquist velocity aliasing and coherent integration filtering effects. Second, the spectrum moments are calculated. The third step increases the signal-to-noise ratio (SNR) due to inflated noise power estimates during convective rain events that cause SNR to be biased low. The fourth step determines the RWP calibration constant for one radar beam (called the “reference” beam) by comparing uncalibrated RWP reflectivity factors at 500 m above the ground to 1 min resolution surface disdrometer reflectivity factors. The last step uses the calibrated reference beam reflectivity factor to calibrate the other radar beams during precipitation. There are two key findings. The RWP sensitivity decreased by approximately 3 to 4 dB yr−1 as the hardware aged. This drift was slow enough that the reference calibration constant can be estimated over 3-month intervals using episodic rain events. The calibrated moments are available on the DOE ARM data archive, and the Python processing code is available on public repositories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Alcohol consumption and breast cancer risk in Japan: A pooled analysis of eight population‐based cohort studies

Abstract Although alcohol consumption is reported to increase the incidence of breast cancer in European studies, evidence for an association between alcohol and breast cancer in Asian populations is insufficient. We conducted a pooled analysis of eight large‐scale population‐based prospective cohort studies in Japan to evaluate the association between alcohol (both frequency and amount) and breast cancer risk with categorization by menopausal status at baseline and at diagnosis. Estimated hazard ratios (HR) and 95% confidence intervals were calculated in the individual cohorts and combined using random‐effects models. Among 158 164 subjects with 2 369 252 person‐years of follow‐up, 2208 breast cancer cases were newly diagnosed. Alcohol consumption had a significant association with a higher risk of breast cancer in both women who were premenopausal at baseline (regular drinker compared to nondrinker: HR 1.37, 1.04‐1.81, ≥23 g/d compared to 0 g/d: HR 1.74, 1.25‐2.43, P for trend per frequency category: P = .017) and those who were premenopausal at diagnosis (≥23 g/d compared to 0 g/d: HR 1.89, 1.04‐3.43, P for trend per frequency category: P = .032). In contrast, no significant association was seen in women who were postmenopausal at baseline or at diagnosis, despite a substantial number of subjects and long follow‐up period. Our results revealed that frequent and high alcohol consumption are both risk factors for Asian premenopausal breast cancer, similarly to previous studies in Western countries. The lack of a clear association in postmenopausal women in our study warrants larger investigation in Asia.

Iwase, Madoka↗
DOE OSTI2026

Neural Network‐Based Methods for Ocean Surface Wave Measurement Using Submarine Distributed Acoustic Sensing (DAS)

Two new data-driven models for estimating ocean surface waves from distributed acoustic sensing (DAS) submarine cable strain rate are developed using supervised machine learning on a 10-day data set collected offshore of Oliktok Point, Alaska. The new models were trained on target data from seafloor pressure moorings at three sites spaced evenly along 27.1 km of cable and were benchmarked against an empirical transfer function method previously used to estimate waves from DAS. A model which uses convolutional neural networks to transform 2-km frequency-wavenumber strain spectra to seafloor pressure spectra outperforms the benchmark in wave height prediction (RMSE of 0.15 vs. 0.41 m) and period prediction (0.29 vs. 0.37 s) when evaluated on a held-out test data set. When applied to a DAS data set collected on the same cable 2 years prior, the CNN-based model maintained similar significant wave height performance (RMSE = 0.23 m) relative to available satellite altimetry data. A two-hidden-layer, fully connected neural network which transforms 1-D strain spectra to seafloor pressure spectra also outperforms the benchmark in wave height prediction (RMSE of 0.19 vs. 0.41 m), but does not generalize as well to the prior data. Regression-based machine learning is useful for estimating waves from DAS data when the pressure-strain relationship varies temporally and spatially across different wave conditions. Models can be applied to DAS data to measure waves with higher spatial resolution and longer temporal coverage than traditional methods, which often measure waves only at a single point.

Davis, Jacob R. [Univ. of Washington, Seattle, WA ↗