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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-C-207-01: Four-Dimensional Inverse Geometry Computed Tomography: Concept and Its Validation

Purpose: In past few years, the inverse geometry computed tomography (IGCT) system has been developed to overcome shortcomings of a conventional computed tomography (CT) system such as scatter problem induced from large detector size and cone-beam artifact. In this study, we intend to present a concept of a four-dimensional (4D) IGCT system that has positive aspects above all with temporal resolution for dynamic studies and reduction of motion artifact. Methods: Contrary to conventional CT system, projection data at a certain angle in IGCT was a group of fractionated narrow cone-beam projection data, projection group (PG), acquired from multi-source array which have extremely short time gap of sequential operation between each of sources. At this, for 4D IGCT imaging, time-related data acquisition parameters were determined by combining multi-source scanning time for collecting one PG with conventional 4D CBCT data acquisition sequence. Over a gantry rotation, acquired PGs from multi-source array were tagged time and angle for 4D image reconstruction. Acquired PGs were sorted into 10 phase and image reconstructions were independently performed at each phase. Image reconstruction algorithm based upon filtered-backprojection was used in this study. Results: The 4D IGCT had uniform image without cone-beam artifact on the contrary to 4D CBCT image. In addition, the 4D IGCT images of each phase had no significant artifact induced from motion compared with 3D CT. Conclusion: The 4D IGCT image seems to give relatively accurate dynamic information of patient anatomy based on the results were more endurable than 3D CT about motion artifact. From this, it will be useful for dynamic study and respiratory-correlated radiation therapy. This work was supported by the Industrial R&D program of MOTIE/KEIT [10048997, Development of the core technology for integrated therapy devices based on real-time MRI guided tumor tracking] and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Ab initio metadynamics calculations reveal complex interfacial effects in acetic acid deprotonation dynamics

Acid-base reactions play a central role in solution chemistry, with carboxylic acids being particularly important in atmospheric chemical processes. In this work, we harness metadynamics calculations with Born-Oppenheimer molecular dynamics (BOMD) simulations to understand deprotonation dynamics of acetic acid (CH 3 COOH) in both bulk and air-water interfacial environments. Collective variables are carefully chosen in our well-tempered metadynamics simulations to capture the deprotonation process in various aqueous configurations. Herein, our findings show that the free energy barrier for deprotonation of acetic acid at the air-water interface is lower than in the bulk, in accordance with the available experimental data. Furthermore, our well-tempered metadynamics calculations suggest that the variations in free energy are primarily due to intricate solvation shell effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Dynamic Non-Hierarchical File Systems for Exascale Storage

This constitutes the final report for “Dynamic Non-Hierarchical File Systems for Exascale Storage”. The ultimate goal of this project was to improve data management in scientific computing and high-end computing (HEC) applications, and to achieve this goal we proposed: to develop the first, HEC-targeted, file system featuring rich metadata and provenance collection, extreme scalability, and future storage hardware integration as core design goals, and to evaluate and develop a flexible non-hierarchical file system interface suitable for providing more powerful and intuitive data management interfaces to HEC and scientific computing users. Data management is swiftly becoming a serious problem in the scientific community – while copious amounts of data are good for obtaining results, finding the right data is often daunting and sometimes impossible. Scientists participating in a Department of Energy workshop noted that most of their time was spent “...finding, processing, organizing, and moving data and it’s going to get much worse”. Scientists should not be forced to become data mining experts in order to retrieve the data they want, nor should they be expected to remember the naming convention they used several years ago for a set of experiments they now wish to revisit. Ideally, locating the data you need would be as easy as browsing the web. Unfortunately, existing data management approaches are usually based on hierarchical naming, a 40 year-old technology designed to manage thousands of files, not exabytes of data. Today’s systems do not take advantage of the rich array of metadata that current high-end computing (HEC) file systems can gather, including content-based metadata and provenance1 information. As a result, current metadata search approaches are typically ad hoc and often work by providing a parallel management system to the “main” file system, as is done in Linux (the locate utility), personal computers, and enterprise search appliances. These search applications are often optimized for a single file system, making it difficult to move files and their metadata between file systems. Users have tried to solve this problem in several ways, including the use of separate databases to index file properties, the encoding of file properties into file names, and separately gathering and managing provenance data, but none of these approaches has worked well, either due to limited usefulness or scalability, or both. Our research addressed several key issues: High-performance, real-time metadata harvesting: extracting important attributes from files dynamically and immediately updating indexes used to improve search; Transparent, automatic, and secure provenance capture: recording the data inputs and processing steps used in the production of each file in the system; Scalable indexing: indexes that are optimized for integration with the file system; Dynamic file system structure: our approach provides dynamic directories similar to those in semantic file systems, but these are the native organization rather than a feature grafted onto a conventional system. In addition to these goals, our research effort will include evaluating the impact of new storage technologies on the file system design and performance. In particular, the indexing and metadata harvesting functions can potentially benefit from the performance improvements promised by new storage class memories.

42 ENGINEERING↗
NASA NTRS1999

A New Compendium of Unsteady Aerodynamic Test Cases for CFD: Summary of AVT WG-003 Activities

With the continuous progress in hardware and numerical schemes, Computational Unsteady Aerodynamics (CUA), that is, the application of Computational Fluid Dynamics (CFD) to unsteady flowfields, is slowly finding its way as a useful and reliable tool (turbulence and transition modeling permitting) in the aircraft, helicopter, engine and missile design and development process. Before a specific code may be used with confidence it is essential to validate its capability to describe the physics of the flow correctly, or at least to the level of approximation required, for which purpose a comparison with accurate experimental data is needed. Unsteady wind tunnel testing is difficult and expensive; two factors which dramatically limit the number of organizations with the capability and/or resources to perform it. Thus, unsteady experimental data is scarce, often classified and scattered in diverse documents. Additionally, access to the reports does not necessarily assure access to the data itself. The collaborative effort described in this paper was conceived with the aim of collecting into a single easily accessible document as much quality data as possible. The idea is not new. In the early 80's NATO's AGARD (Advisory Group for Aerospace Research & Development) Structures and Material Panel (SMP) produced AGARD Report No. 702 "Compendium of Unsteady Aerodynamic Measurements", which has found and continues to find extensive use within the CUA Community. In 1995 AGARD's Fluid Dynamics Panel (FDP) decided to update and expand the former database with new geometries and physical phenomena, and launched Working Group WG-22 on "Validation Data for Computational Unsteady Aerodynamic Codes". Shortly afterwards AGARD was reorganized as the RTO (Research and Technology Organization) and the WG was renamed as AVT (Applied Vehicle Technolology) WG-003. Contributions were received from AEDC, BAe, DLR, DERA, Glasgow University, IAR, NAL, NASA, NLR, and ONERA. The final publication with the results of the exercise is expected in the second part of 1999. The aim of the present paper is to announce and present the new database to the Aeroelasticity community. It is also intended to identify, together with one of the groups of end users it targets, deficiencies in the compendium that should be addressed by means of new wind tunnel tests or by obtaining access to additionally existing data.

Ruiz-Calavera, Luis P.↗
DOE OSTI2019

A deep learning approach to anomaly detection in geological carbon sequestration sites using pressure measurements

Carbon capture and storage (CCS) has been extensively investigated as a potential engineering measure to reduce anthropogenic carbon emission to the atmosphere. Real-time monitoring of the safety and integrity of carbon storage reservoirs is a critical aspect of any commercial-scale CCS deployment. Pressure-based sensing is cost effective, suitable for real-time monitoring, and scalable to large monitoring networks. However, questions remain on how to best harness intelligent information from the high-frequency pressure monitoring sensors to support real-time decisions. Here this work presents a deep-learning-based framework for analyzing and detecting anomalies in pressure data streams by using a convolutional long short-term memory (ConvLSTM) neural network model, which allows for the fusion of both static and dynamic reservoir data. In ConvLSTM, the convolutional neural network (CNN) is used for spatial pattern mining and the LSTM is used for temporal pattern recognition. The performance of the ConvLSTM model for real-time anomaly detection is demonstrated using a set of pressure monitoring data collected from Cranfield, Mississippi, an active enhanced-oil-recovery field. The anomaly detection model is trained using bottom-hole pressure data acquired from the base experiment (without leak event) and then tested on pressure data collected during a series of controlled CO 2 release experiments (with artificially created leak events). Results show that the ConvLSTM neural network model successfully detected anomalies in the pressure time series obtained from the controlled release experiments. Inclusion of static information into the model further improves the robustness of ConvLSTM.

13 HYDRO ENERGY↗
DOE OSTI2023

Toward using collective x-ray Thomson scattering to study C–H demixing and hydrogen metallization in warm dense matter conditions

The insulator–metal transition in liquid hydrogen is an important phenomenon to understand the interiors of gas giants, such as Jupiter and Saturn, as well as the physical and chemical behavior of materials at high pressures and temperatures. Here, the path toward an experimental approach is detailed based on spectrally resolved x-ray scattering, tailored to observe and characterize hydrogen metallization in dynamically compressed hydrocarbons in the regime of carbon–hydrogen phase separation. With the help of time-dependent density functional theory calculations and scattering spectra from undriven carbon samples collected at the European x-ray Free-Electron Laser Facility (EuXFEL), we demonstrate sufficient data quality for observing C–H demixing and investigating the presence of liquid metallic hydrogen in future experiments using the reprated drive laser systems at EuXFEL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Cosmological preference for a negative neutrino mass

The most precise determination of the sum of neutrino masses from cosmological data, derived from analysis of the cosmic microwave background (CMB) and baryon acoustic acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI), favors a value below the minimum inferred from neutrino flavor oscillation experiments. We explore which data is most responsible of this puzzling aspect of the current constraints on neutrino mass and whether it is related to other anomalies in cosmology. We demonstrate conclusively that the preference for negative neutrino masses is a consequence of larger than expected lensing of the CMB in both the two- and four-point lensing statistics. Furthermore, we show that this preference is robust to changes in likelihoods of the BAO and CMB optical depth analyses given the available data. We then show that this excess clustering is not easily explained by changes to the expansion history and is likely distinct from the preference for for dynamical dark energy in DESI BAO data. Finally, we discuss how future data may impact these results, including an analysis of Planck CMB with mock DESI 5-year data. Here, we conclude that the negative neutrino mass preference is likely to persist even as more cosmological data is collected in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Abstract for CRADA between the National Energy Technology Laboratory, Ohio State University, Lawrence Berkeley National Laboratory, and Sandia National Laboratories (AGMT-0804)

This CRADA will enable cooperation between Ohio State University (OSU) and a collective led by the National Energy Technology Laboratory (NETL), with the goal of facilitating the accelerated commercialization of OSU’s iron-based chemical looping process through advanced modeling and state-of-the-art optimization techniques. OSU will provide data for model development and validation, while NETL and collaborators through the Institute for the Design of Advanced Energy Systems (IDAES) will develop advanced high-fidelity optimization-based system models. The project will use data collected primarily from OSU’s bench scale and sub pilot scale facilities and will be supplemented by data collected from the open literature. Models representative of chemical looping combustion or gasification using either coal or natural gas as fuel are considered in scope. Specific tasks will include 1) development of physical property sub-models, 2) development of steady-state and dynamic 1 st principles models of the novel gas solid contactor technologies being developed by OSU, and 3) superstructure and parametric optimization of a full chemical looping process by leveraging the large-scale optimization capabilities being developed by IDAES. This collaboration will provide a greater fundamental understanding of the OSU chemical looping process, will help to improve the overall process economics, and will thus enable a greater probability of commercial success. It will provide IDAES with the opportunity to validate, demonstrate, and further develop its toolset through a real-world practical demonstration.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

The use of seismic spatial gradients in a single layer neural network for seismic source discrimination: proof of concept

This report describes a proof-of-concept method of seismic source discrimination using seismic gradiometry and a common machine learning technique. The tests described here are purely numerical, using synthetic seismic data and well understood mathematical techniques. The primary innovation described here is the application of a richer seismic data set derived from seismic gradiometry. Seismic gradiometry is a method to estimate the time variable spatial gradient of the wavefield to compute various wavefield attributes such as slowness, dynamic strain, and rotational motions. With the addition of these wavefield attributes, we are afforded up to twenty "compo- nents" of time series data measured at a single point on, or in, the Earth. This is in direct contrast to conventional three-component seismic data collected at several locations using a seismic network. Using the gradiometrically-derived wavefield components directly in a single-layer neural network, I show that it is possible to discriminate between three common seismic source types (earthquakes, explosions, and opening fractures) for various noise conditions and gradiometry configurations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence Q - Raw Data

Sequence Q: Dynamic Inflow (P) This sequence was designed to characterize the dynamic inflow variation using the five-hole probes that extend upwind of the leading edge of the blade. This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speeds ranged from 5 m/s to 15 m/s, and data were collected at a 0° yaw angle. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to -99999.99 Nm. The teeter link load cell was pretensioned to 40,000 N. The blade pitch angle was changed from the initial tip pitch angle to the final tip pitch angle at the maximum rate of 67°/s. This angle was maintained for the specified delay time duration. Then the blade was pitched back to the initial pitch angle and held for the specified hold time. This was repeated 20 times. The campaign at 15 m/s was aborted early due to excessive low-speed shaft torque loads. The file length varied depending on the time required to obtain 20 pitch cycles for the specified range of angles. The name convention was the standard format, except for the short campaigns collected to ascertain the functionality of the instrumentation. These points were collected at a 3° pitch angle and use the characters REF in the four digits that normally represent yaw angle.

17 WIND ENERGY↗
DOE OSTI2015

Integrating laboratory and field data to quantify the immersion freezing ice nucleation activity of mineral dust particles

Data from both laboratory studies and atmospheric measurements are used to develop an empirical parameterization for the immersion freezing activity of natural mineral dust particles. Measurements made with the Colorado State University (CSU) continuous flow diffusion chamber (CFDC) when processing mineral dust aerosols at a nominal 105% relative humidity with respect to water (RH w ) are taken as a measure of the immersion freezing nucleation activity of particles. Ice active frozen fractions vs. temperature for dusts representative of Saharan and Asian desert sources were consistent with similar measurements in atmospheric dust plumes for a limited set of comparisons available. The parameterization developed follows the form of one suggested previously for atmospheric particles of non-specific composition in quantifying ice nucleating particle concentrations as functions of temperature and the total number concentration of particles larger than 0.5 μm diameter. Such an approach does not explicitly account for surface area and time dependencies for ice nucleation, but sufficiently encapsulates the activation properties for potential use in regional and global modeling simulations, and possible application in developing remote sensing retrievals for ice nucleating particles. A calibration factor is introduced to account for the apparent underestimate (by approximately 3, on average) of the immersion freezing fraction of mineral dust particles for CSU CFDC data processed at an RH w of 105% vs. maximum fractions active at higher RH w . Instrumental factors that affect activation behavior vs. RH w in CFDC instruments remain to be fully explored in future studies. Nevertheless, the use of this calibration factor is supported by comparison to ice activation data obtained for the same aerosols from Aerosol Interactions and Dynamics of the Atmosphere (AIDA) expansion chamber cloud parcel experiments. Further comparison of the new parameterization, including calibration correction, to predictions of the immersion freezing surface active site density parameterization for mineral dust particles, developed separately from AIDA experimental data alone, shows excellent agreement for data collected in a descent through a Saharan aerosol layer. These studies support the utility of laboratory measurements to obtain atmospherically relevant data on the ice nucleation properties of dust and other particle types, and suggest the suitability of considering all mineral dust as a single type of ice nucleating particle as a useful first-order approximation in numerical modeling investigations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Barriers and Opportunities for Energy Technology Adoption in Juneau, Alaska

This report presents findings from a qualitative study examining barriers and opportunities for air source heat pump (ASHP) and electric vehicle (EV) adoption in Juneau, Alaska, with a particular focus on manufactured and multifamily housing. The analysis draws on community insights from end users and middle actors to better understand how technology adoption unfolds in contexts with distinct logistical, infrastructural, and housing constraints. The report is organized according to key barriers and opportunities identified through stakeholder input, providing a structured understanding of adoption dynamics across technologies and housing types. These insights are intended to inform program design and support more effective electrification strategies tailored to local conditions. The study team employed qualitative methods to capture both in-depth and high-level perspectives on technology adoption. Data collection included: 1) two 2-hour focus groups with a total of five end users and seven middle actors, enabling detailed and structured discussion and 2) ten semistructured interviews with manufactured home owners, multifamily landlords, and one tenant, providing complementary insights across housing contexts. Focus groups captured accounts of shared challenges and opportunities while interviews offered more concise reflections on individual experiences. Together, these methods enabled a more comprehensive understanding of both systemic barriers and lived experiences with ASHPs and EVs. The findings reveal that adoption of electrification technologies is shaped by a combination of economic, logistical, and informational factors that vary across housing types, technology characteristics, user groups, and other demographic factors. Addressing these factors requires tailored strategies that reflect local conditions and user experiences. The insights in this report can provide a foundation for organizations such as AEL&P to refine program design, support more effective outreach, and anticipate shifts in energy demand associated with increased electrification. More broadly, the study highlights the importance of incorporating community perspectives when developing electrification initiatives to ensure they are both practical and responsive to real-world constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2009

Physiological Factors Contributing to Postflight Changes in Functional Performance

Astronauts experience alterations in multiple physiological systems due to exposure to the microgravity conditions of space flight. These physiological changes include sensorimotor disturbances, cardiovascular deconditioning and loss of muscle mass and strength. These changes might affect the ability of crewmembers to perform critical mission tasks immediately after landing on lunar and Martian surfaces. To date, changes in functional performance have not been systematically studied or correlated with physiological changes. To understand how changes in physiological function impact functional performance an interdisciplinary pre/postflight testing regimen (Functional Task Test, FTT) has been developed that systematically evaluates both astronaut postflight functional performance and related physiological changes. The overall objectives of the FTT are to: Develop a set of functional tasks that represent critical mission tasks for Constellation. Determine the ability to perform these tasks after flight. Identify the key physiological factors that contribute to functional decrements. Use this information to develop targeted countermeasures. The functional test battery was designed to address high priority tasks identified by the Constellation program as critical for mission success. The set of functional tests making up the FTT include the: 1) Seat Egress and Walk Test, 2) Ladder Climb Test, 3) Recovery from Fall/Stand Test, 4) Rock Translation Test, 5) Jump Down Test, 6) Torque Generation Test, and 7) Construction Activity Board Test. Corresponding physiological measures include assessments of postural and gait control, dynamic visual acuity, fine motor control, plasma volume, orthostatic intolerance, upper and lower body muscle strength, power, fatigue, control and neuromuscular drive. Crewmembers will perform both functional and physiological tests before and after short (Shuttle) and long-duration (ISS) space flight. Data will be collected on R+0 (Shuttle only), R+1, R+6 and R+30. Using a multivariate regression model we will identify which physiological systems contribute the most to impaired performance on each functional test. This will allow us to identify the physiological systems that play the largest role in decrement in functional performance. Using this information we can then design and implement countermeasures that specifically target the physiological systems most responsible for the altered functional performance associated with space flight.

Bloomberg, J. J.↗
NASA NTRS2012

A l% and 1cm Perspective Leads to a Novel CDOM Absorption Algorithm

A next-generation in-water profiler designed to measure the apparent optical properties of seawater was developed and validated across a wide dynamic range of water properties. This new Compact-Optical Profiling System (C-OPS) design uses a novel, kite-shaped, free-falling backplane with adjustable buoyancy and is based on 19 state-of-the-art microradiometers, spanning 320-780 nm. Data collected as part of the field commissioning were of a previously unachievable quality and showed that systematic uncertainties in the sampling protocols were discernible at the 1% optical and 1cm depth resolution levels. A sensitivity analysis as a function of three water types, established by the peak in the remote sensing reflectance spectra, revealed which water types and spectral domains were the most indicative of data acquisition uncertainties. The unprecedented vertical resolution of C-OPS measurements provided near-surface data products at the spectral endpoints with a quality level that has not been obtainable. The improved data allowed development of an algorithm for predicting the spectral absorption due to chromophoric dissolved organic matter (CDOM) using ratios of diffuse attenuation coefficients with over 99% of the variance in the data explained.

Morrow, J. H.↗
NASA NTRS2012

Performance Evaluation of a High Bandwidth Liquid Fuel Modulation Valve for Active Combustion Control

At the NASA Glenn Research Center, a characterization rig was designed and constructed for the purpose of evaluating high bandwidth liquid fuel modulation devices to determine their suitability for active combustion control research. Incorporated into the rig s design are features that approximate conditions similar to those that would be encountered by a candidate device if it were installed on an actual combustion research rig. The characterized dynamic performance measures obtained through testing in the rig are planned to be accurate indicators of expected performance in an actual combustion testing environment. To evaluate how well the characterization rig predicts fuel modulator dynamic performance, characterization rig data was compared with performance data for a fuel modulator candidate when the candidate was in operation during combustion testing. Specifically, the nominal and off-nominal performance data for a magnetostrictive-actuated proportional fuel modulation valve is described. Valve performance data were collected with the characterization rig configured to emulate two different combustion rig fuel feed systems. Fuel mass flows and pressures, fuel feed line lengths, and fuel injector orifice size was approximated in the characterization rig. Valve performance data were also collected with the valve modulating the fuel into the two combustor rigs. Comparison of the predicted and actual valve performance data show that when the valve is operated near its design condition the characterization rig can appropriately predict the installed performance of the valve. Improvements to the characterization rig and accompanying modeling activities are underway to more accurately predict performance, especially for the devices under development to modulate fuel into the much smaller fuel injectors anticipated in future lean-burning low-emissions aircraft engine combustors.

Saus, Joseph R.↗
NASA NTRS2015

Chug and Dynamics of the RS-84 Subscale Preburner

The development of the RS-84 engine began in 2002 as part of the Space Launch Initiative. It was intended to be a reusable liquid oxygen/RP-1 booster engine of approximately 1 Mlbf thrust. Part of the test campaign consisted of testing subscale components to study key technologies such as oxygenrich, liquid oxygen/RP-1 combustion. In late 2003, the subscale preburner completed 4 hot-fire tests at Stennis Space Center with various hardware configurations and operating conditions, but before all planned tests could be completed the RS-84 engine development program was canceled in 2004. Recently, there has been a renewed interest in the development of an oxygen-rich, liquid oxygen/RP-1 combustion engine. Aerojet Rocketdyne and NASA completed testing of the subscale preburner in 2014 at Marshall Space Flight Center in an effort to better understand the chug encountered during the 2003 testing and to collect performance information over a wider range of operating conditions. The 2003 and 2014 data sets included extreme chug oscillations that reached nearly 200% of the chamber pressure and were reduced to well below 10% of the chamber pressure by incorporating a fuel orifice upstream of the fuel manifold. Depending on the hardware configuration and operating condition, a wide range of chug oscillation amplitudes were encountered. The dynamics for both test series were characterized and the data were used in the development of a chug model.

Casiano, M. J↗
DOE OSTI2023

Wind Turbine Drivetrain Reliability Research - Gearbox Bearing Axial Cracking Failure Mode Example

The U.S. Department of Energy's National Renewable Energy Laboratory and Argonne National Laboratory have been conducting wind turbine drivetrain (formerly gearbox) reliability research for many years. Although the drivetrain focus has not changed, detailed projects are adjusted every few years based on dynamic needs seen in the field across the wind industry. This webinar will walk through the research methodology by using wind turbine gearbox bearing axial cracking failure mode as an example. The detailed steps include: 1) top failure mode identification based on actual failure data collected from project partners, 2) bench-top testing to identify possible contributing factors and formulate a damage metric, 3) physics domain modeling and validation through testing, 4) reliability assessment and prognosis based on the physics domain model and data domain inputs, and further enhancement through machine learning algorithms, using actual wind plant operational and failure event data. Hopefully, the presented work is of interest to the IISE community, and some members can apply their expertise to wind turbine and plant applications, helping enhance wind power generation technology advancement and its broader deployment.

axial cracking↗
DOE OSTI2021

Monitoring agroecosystem productivity and phenology at a national scale: A metric assessment framework

Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, GCC) from tower-mounted PhenoCams for 2017 and 2018. Overall, our analysis compared production dynamics estimated from three independent ground and remote platforms using data for 34 agricultural sites constituting 51 site-years of co-located time series. Pairwise sensor comparisons across all four metrics revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazing land sites where estimating SOS can be challenging. Growing season length estimates derived from 16-day satellite GPP (179.1 days) were significantly longer than those from PhenoCam G CC (70.4 days, p adj < 0.0001) and EC GPP (79.6 days, p adj < 0.0001). Landscape heterogeneity did not explain differences in SOS and EOS estimates. Annual integrated estimates of productivity from EC GPP and PhenoCam G CC diverged from those estimated by Landsat GPP and NDVI at sites where annual production exceeds 1000 gC/m –2 yr –1 . Based on our results, we developed a “metric assessment framework” that articulates where and how metrics from satellite, eddy covariance and PhenoCams complement, diverge from, or are redundant with one another. The framework was designed to optimize instrumentation selection for monitoring, modeling, and forecasting ecosystem functioning with the ultimate goal of informing decision-making by land managers, policy-makers, and industry leaders working at multiple scales.

54 ENVIRONMENTAL SCIENCES↗