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DOE OSTI2020

Enabling human–infrastructure interfaces for inspection using augmented reality

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.

Maharjan, D.↗
DOE OSTI2025

A simplified approach for creep damage and remaining life calculation for materials surveillance in advanced reactors

High temperature reactor materials will experience a combination of mechanical degradation caused by creep and fatigue and environmental degradation caused by neutron irradiation and, in some cases, exposure to corrosive coolants. A materials surveillance program is one option for ensuring the safe, reliable operation of key reactor components under these conditions. Such a program would monitor the degradation in key material properties over time, using this data to predict how changes in the material properties affect components performance. This could then be used to make plant operational decisions and support eventual plant license extensions. Past work de-scribes such a material surveillance program based on passively actuated mechanical test articles that impose creep-fatigue type loading on test materials driven only by changes in temperature, for example those experienced by components under standard operating cycles. This report focuses on two aspects of the proposed material surveillance program: how to design the test articles to mimic the mechanical response of the corresponding component and how to use ex-situ test data to deter-mine the amount of damaged experienced by the test article (and hence the corresponding compo-nent) in service. Specifically, this report derives and validated simplified methods for both tasks, replacing earlier, more complicated approaches based on simulating the test article response and finding the best specimen design or current damage via complex numerical optimization. The sim-plified methods for each task developed here can be implemented in spreadsheet software and are simple enough for practical use in future operating plants. This report derives the methods (one for sizing and two options for damage inference), verifies the simplified approaches versus more so-phisticated methods, and compares the results of applying the simplified methods to previous re-sults using the complex numerical optimization approach. The report also provides a worked sam-pled problem applying the simplified techniques to a realistic high temperature reactor component.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

TH-D-16A-01: Medical Physics Workshop: Editorial Vision and Guidance On Writing and Reviewing Papers

On January 1, 2014, editorial leadership of Medical Physics passed from esteemed long-time Editor Bill Hendee to a collective editorial group composed of the three presenters listed above. In this presentation, we would like to outline our vision for the future of Medical Physics and review recent work-in-progress initiatives to implement this vision. Finally, we will close with guidance to authors on how to write a good Medical Physics paper. Vision for Medical Physics and current initiatives: Jeff Williamson, Editor-in-Chief We cannot improve on Dr. Hendee's succinct vision statement “to continue the Journal's tradition of publishing the very best science that propels our discipline forward and improves our contribution to patient care.” More concretely, the Journal should be s the preeminent forum for electronic exchange of cutting edge medical physics science. We seek to identify the best contributions in (a) high impact clinical physics innovations; (b) clinical translation and validation of basic science innovations; or (c) cutting edge basic science developments with potential for patient care improvements. Among the challenges and opportunities we face are: are electronic-only and open access publishing; trends towards more interactive, social-media based scientific communities; and diversification of the medical physics research, authorship, and readership domains, including clinical applications quite foreign to core ABR clinical competencies. To address these issues over the next 3 years, we have reduced the size of our Editorial Board and focused its efforts on improving the Journal's impact through 4 working groups (WGs): WG-1: Review process quality and selectivity Creation of 120 member Board of Associate Editors to improve review uniformity by placing Ms. management in fewer hands New reviewer guidelines and templates Answer: “what is the scope of medical physics research?” Recursive taxonomy for tagging review expertise and article contents WG-2 Improving reader experience Redesigning http://MedPhys.org to host interactive features and gateway to electronic issue archive Experimentation with interactive features beginning with “Point/Counterpoint” Data mining and Journal quality evaluation Find out who are audiences are Identify characteristics of high impact articles Measure effectiveness of innovations Outreach to related communities Special issues presenting high-impact work in designated subcommunities Addressing the needs of new research constituencies: engineers, biophysicists, clinicians Guidelines and templates for reviewers and associate editors: Shiva Das, Therapy Physics Editor We will discuss the Med. Phys. review process and a new initiative to create review templates that attempts to address current shortcomings. Template design is informed by the literature on of the review process effectiveness and practices of other journals. Its goals are to provide authors more constructive criticism to improve the manuscript; quantifying perceived importance and potential impact; and providing structured sections that prompt the reviewer to addresses important technical and editorial elements. While the template is recommended to be used, reviewers could alternatively enter their comments in the older free-form style. The expectations of the template are that it will enable consistently thorough, high quality reviews that accurately separate acceptable vs. substandard submissions but continue our tradition of helping authors to enhance papers with high potential. Ultimately, the goal is to reduce variability and subjectivity in the peer-review process, in turn leading to articles with higher research and clinical impact. We will also discuss interesting perspectives from several journals on aspects of the peer-review process such as public input via comments, influence of author-suggested reviewers, and bias in reviewer selection. Writing good scientific papers and responding to critiques: Mitch Goodsitt, Imaging Physics Editor The essential components of the abstract, introduction, methods, discussion and conclusion sections, as well as the desired writing style and style of the figures and tables will be reviewed. Publishable Medical Physics Ms. must include a clear and concise statement of the novelty and clinical and/or scientific importance of their work. Examples of novelty include: new technical solution to an important clinical problem; new generalizable knowledge; or first demonstration that an existing engineering solution solves a clinical problem. Authors must also include: sufficient background information and rationale; enough detail that the work can be reproduced by others; sufficient statistical analysis to refute or validate their hypothesis, how it compares to; is distinct from, and improves upon others' work; and the limitations of their study. When the authors receive critiques from the referees and associate editor, the authors should provide a detailed point-bypoint response to each comment. We now ask that the authors' rebuttal include the text of the original criticism, the authors' response, and the modified text along with the line numbers in the revised article. We also ask that the new text be highlighted in a different font color in the revised submission. These changes and others will be discussed. Their purpose is to facilitate the review process.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2022

Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature: Supporting Data

This dataset was used to assess the potential of a Soil Deformation and Temperature Monitoring System developed and presented in the article named "Low-Power, Flexible Sensor Arrays with Solderless Board-to-Board Connectors for Monitoring Soil Deformation and Temperature" and published in Sensors. There are 21 comma-delimited data files (.csv). 14 files contain current measurements performed in a lab setting, enabling the electrical evaluation of the sensor probe. These files are generated by the Keithley DMM6500 multimeter, and list the measured supply current (first column) as a function of time (3rd column). Another set of 6 files is also acquired in lab experiments, but contain soil temperature an deformation measurements, enabling an assessment of the developed device's accuracy. In these files, the first column contains the time (UTC), followed by the sensor's battery voltage and temperature and acceleration values (X, Y, Z) in subsequent columns. The measurements were acquired every 5 seconds. Another .csv file contains field data in a similar format (time, temperature, acceleration) collected at the Teller road (mile 27) site near Nome, Alaska with one probe. 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 OSTI2011

FINAL REPORT: DOE CONTRACT NUMBER FG0205ER64026 Biological Neutron Scattering: A Collaboration with the Oak Ridge Center for Structural Molecular Biology

The overarching goal of this project was to promote applications of small-angle scattering in structural molecular biology by providing model examples of cutting edge applications that demonstrate the unique capabilities and potential of the DOE national user facilities at Oak Ridge, especially the newly commissioned BioSANS. The approach taken was three-fold: (1) to engage in high impact collaborative research projects that would benefit from small-angle neutron scattering to both demonstrate the power of the technique while expanding the potential user community; (2) to provide access to scattering facilities established at the University of Utah to as broad a set of researchers as possible to increase the expertise in small-angle scattering generally; and (3) to develop new methods and tools for small-angle scattering. To these ends, three major research collaborations were pursued that resulted in a significant body of published work where neutron scattering and contrast variation played a major role. These major collaborations involved studies of protein complexes involved in (1) bacterial transcription regulation and adaptive response (a DOE/BER priority area); (2) regulation of cardiac muscle; and (3) neuronal disorders. In addition, to broaden the impact of the project, smaller collaborative efforts were supported that used either small-angle X-ray or neutron scattering. Finally, the DOE supported facilities at the University of Utah were made available to researchers on a service basis and a number of independent groups took advantage of this opportunity. In all of this work, there was an emphasis on the training of students and post docs in scattering techniques, and a set of publications (a book chapter, a review, and an encyclopedia article) were produced to guide the non-specialist potential user of scattering techniques in successful applications of the techniques. We also developed a suite of user friendly web-based computational tools currently being accessed world-wide by researchers as an aid in neutron scattering data interpretation. In all, these collaborative projects and resulted in 29 original refereed journal articles published between 2005 and 2010 and engaged groups from at least 14 Universities (10 US, 4 international) and 3 National Laboratories (2 US, 1 international). An important final initiative from this project was to begin a process for international community agreement on a set of standards for the publication of biomolecular small-angle scattering data. This initiative is being championed with the International Union of Crystallography and has engaged a number of Journal Editors and is a very important step in the maturing of this now burgeoning field.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Multi-phenomenology Yield Characterization

This report serves as the first delivery of a four-year applied science effort to transform and advance the error bounds for the yield estimate of an explosion. Each year’s delivery will be in this form, culminating in the submission of this work for peer review to a scientific journal. Importantly, the yearly progress reports can then also be viewed as expanding drafts working towards a formal journal article submission. For the first tranche of funding, we collaborated with Air Force Technical Applications Center (AFTAC) scientists to identify unclassified real-world data that demonstrate and validate our advanced error propagation methods. Collaboration includes visits to AFTAC and telecons. For this development, we illustrate the fusion of seismic, acoustic, optical, and surface effect signatures from an explosion. The mathematics and code being adapted to this specific application (Williams et al., 2021) involves physics models of multiple sensor signatures. We have also identified related physics models and have integrated them into code. Current methods of underground explosion yield estimation for the Threshold Test Ban Treaty (TTBT) have served the US treaty monitoring mission well for decades. A research objective of the Defense Nuclear Nonproliferation Research and Development (DNN R&D) office of the National Nuclear Security Administration (NNSA) has always been to provide new technical capabilities for monitoring lower thresholds. The general model and error propagation code to be developed in this project is based on significant advances in error modeling and propagation needed to analyze data at lower detection thresholds. The second tranche of funding for this project began on May 1, 2022, and planned work for the second tranche includes: i) completing the integration of physical model code into the general error model framework; this code accommodates a wide range of linear/nonlinear source models, fixed/ random effects, and frequentist/Bayesian analyses (the purpose of which is not to dictate to users how to analyze data, but instead to allow users the maximum flexibility in their work); ii) illustrative application of code to identified data, and; iii) initial planning with AFTAC researchers on delivery of code to the Common Development Environment at AFTAC, and continued writing of the planned final journal article submission (year two of this progress report), with particular emphasis on descriptions of data identified for this effort.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

Damaris: Addressing performance variability in data management for post-petascale simulations

With exascale computing on the horizon, reducing performance variability in data management tasks (storage, visualization, analysis, etc.) is becoming a key challenge in sustaining high performance. Here, this variability significantly impacts the overall application performance at scale and its predictability over time. In this article, we present Damaris, a system that leverages dedicated cores in multicore nodes to offload data management tasks, including I/O, data compression, scheduling of data movements, in situ analysis, and visualization. We evaluate Damaris with the CM1 atmospheric simulation and the Nek5000 computational fluid dynamic simulation on four platforms, including NICS’s Kraken and NCSA’s Blue Waters. Our results show that (1) Damaris fully hides the I/O variability as well as all I/O-related costs, thus making simulation performance predictable; (2) it increases the sustained write throughput by a factor of up to 15 compared with standard I/O approaches; (3) it allows almost perfect scalability of the simulation up to over 9,000 cores, as opposed to state-of-the-art approaches that fail to scale; and (4) it enables a seamless connection to the VisIt visualization software to perform in situ analysis and visualization in a way that impacts neither the performance of the simulation nor its variability. In addition, we extended our implementation of Damaris to also support the use of dedicated nodes and conducted a thorough comparison of the two approaches—dedicated cores and dedicated nodes—for I/O tasks with the aforementioned applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Unsteady Flowfield in a High-Pressure Turbine Modeled by TURBO

Forced response, or resonant vibrations, in turbomachinery components can cause blades to crack or fail because of the large vibratory blade stresses and subsequent high-cycle fatigue. Forced-response vibrations occur when turbomachinery blades are subjected to periodic excitation at a frequency close to their natural frequency. Rotor blades in a turbine are constantly subjected to periodic excitations when they pass through the spatially nonuniform flowfield created by upstream vanes. Accurate numerical prediction of the unsteady aerodynamics phenomena that cause forced-response vibrations can lead to an improved understanding of the problem and offer potential approaches to reduce or eliminate specific forced-response problems. The objective of the current work was to validate an unsteady aerodynamics code (named TURBO) for the modeling of the unsteady blade row interactions that can cause forced response vibrations. The three-dimensional, unsteady, multi-blade-row, Reynolds-averaged Navier-Stokes turbomachinery code named TURBO was used to model a high-pressure turbine stage for which benchmark data were recently acquired under a NASA contract by researchers at the Ohio State University. The test article was an initial design for a high-pressure turbine stage that experienced forced-response vibrations which were eliminated by increasing the axial gap. The data, acquired in a short duration or shock tunnel test facility, included unsteady blade surface pressures and vibratory strains.

Bakhle, Milind A.↗
NASA NTRS2011

Test-Anchored Vibration Response Predictions for an Acoustically Energized Curved Orthogrid Panel with Mounted Components

A rich body of vibroacoustic test data was recently generated at Marshall Space Flight Center for a curved orthogrid panel typical of launch vehicle skin structures. Several test article configurations were produced by adding component equipment of differing weights to the flight-like vehicle panel. The test data were used to anchor computational predictions of a variety of spatially distributed responses including acceleration, strain and component interface force. Transfer functions relating the responses to the input pressure field were generated from finite element based modal solutions and test-derived damping estimates. A diffuse acoustic field model was employed to describe the assumed correlation of phased input sound pressures across the energized panel. This application demonstrates the ability to quickly and accurately predict a variety of responses to acoustically energized skin panels with mounted components. Favorable comparisons between the measured and predicted responses were established. The validated models were used to examine vibration response sensitivities to relevant modeling parameters such as pressure patch density, mesh density, weight of the mounted component and model form. Convergence metrics include spectral densities and cumulative root-mean squared (RMS) functions for acceleration, velocity, displacement, strain and interface force. Minimum frequencies for response convergence were established as well as recommendations for modeling techniques, particularly in the early stages of a component design when accurate structural vibration requirements are needed relatively quickly. The results were compared with long-established guidelines for modeling accuracy of component-loaded panels. A theoretical basis for the Response/Pressure Transfer Function (RPTF) approach provides insight into trends observed in the response predictions and confirmed in the test data. The software modules developed for the RPTF method can be easily adapted for quick replacement of the diffuse acoustic field with other pressure field models; for example a turbulent boundary layer (TBL) model suitable for vehicle ascent. Wind tunnel tests have been proposed to anchor the predictions and provide new insight into modeling approaches for this type of environment. Finally, component vibration environments for design were developed from the measured and predicted responses and compared with those derived from traditional techniques such as Barrett scaling methods for unloaded and component-loaded panels.

Frady, Gregory P.↗
DOE OSTI2016

Data-Driven, In Situ, Relative Sensor Calibration Based on Waveform Fitting Moment Tensor Inversion

This article presents a deconvolution-based methodology for the relative calibration of acoustic emission sensors. The method uses the observations from multiple acoustic emission arrivals to estimate correction functions that account for instrument response and site effects. The corrections act on the measurements reshaping the wave arrivals, in many cases allowing visible discrimination between compressional and shear phases. The methodology is illustrated with the application on a dataset obtained during the hydraulic fracturing at triaxial stress conditions of a Colton sandstone block. A workflow for the estimation of full moment tensor solutions, including the generation of quality control attributes complements the presentation. The moment tensor solutions display fracture geometries mostly aligned with the main hydraulic fracture’s plane. The style of activation can be associated with an extensive stress regime before breakdown and to a compressional stress regime after breakdown, when the pumps were reversed to withdraw fluid from the block. In conclusion, the source types commonly deviate from the pure double-couple type; however, the deviations are under 30° in the case of opening fractures, and under 20° in the case of closing fractures. Therefore, the acoustic emissions in this experiment are the result of predominantly shearing dislocations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Characteristics of Fuel Articles for Irradiation Testing in INL-TREAT and MIT-NRL

To obtain valuable data that will help in the design and commissioning of the Transformational Challenge Reactor, a series of graded, increasingly complex irradiation tests are planned that will demonstrate the feasibility of advanced manufactured reactor core components. In the first irradiation test, conventionally- fabricated uranium nitride tristructural isotropic (UN TRISO) fuel kernels will be embedded into compacts that are fabricated using advanced manufacturing methods. These compacts are to be irradiated at Massachusetts Institute of Technology’s Nuclear Reactor Laboratory and Idaho National Laboratory’s Transient Reactor Test Facility. This report presents the characteristics of the proposed samples and experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2019

A Qualitative Review of Selected Infrared Flow Visualization Processing Techniques: Contrast Enhancement and Frequency Domain Analysis

The deployment and integration of high-sensitivity infrared cameras in a transonic wind tunnel test environment has resulted in a unique capability to image aerodynamic phenomena in real-time. Multi-camera infrared flow visualization data systems are now routinely utilized at the NASA Ames Unitary Plan Wind Tunnel. The small flow-induced temperature gradients on the surface of the wind tunnel test article coupled with the high bit-depth of the infrared camera sensor makes the processing of the image data critically important. An image processing routine must enhance features of interest with minimal artifacts. Additionally, the production wind tunnel test environment demands that these processed images are made available in a real-time, automatic fashion. Therefore, any image processing routine must be computationally economical and enhance the image data with minimal input from a human operator. The following seeks to qualitatively explore selected image processing techniques by assessing their effectiveness to resolve flow features on a wind tunnel test article. A multi-scale contrast enhancement technique is introduced as well as a new implementation of a multi-scale, non-interpolated adaptive histogram equalization. Finally, a novel method is introduced that demonstrates the ability to resolve flow features imaged on bare-steel test articles possessing low emissivity. This method merges frequency domain analysis with contrast enhancement and has the potential to extend the application of infrared flow-visualization within the wind tunnel test environment.

Infrared Imaging↗
NASA NTRS2012

Precipitation from Space: Advancing Earth System Science

Of the three primary sources of spatially contiguous precipitation observations (surface networks, ground-based radar, and satellite-based radar/radiometers), only the last is a viable source over ocean and much of the Earth's land. As recently as 15 years ago, users needing quantitative detail of precipitation on anything under a monthly time scale relied upon products derived from geostationary satellite thermal infrared (IR) indices. The Special Sensor Microwave Imager (SSMI) passive microwave (PMW) imagers originated in 1987 and continue today with the SSMI sounder (SSMIS) sensor. The fortunate longevity of the joint National Aeronautics and Space Administration (NASA) and Japan Aerospace Exploration Agency (JAXA) Tropical Rainfall Measuring Mission (TRMM) is providing the environmental science community a nearly unbroken data record (as of April 2012, over 14 years) of tropical and sub-tropical precipitation processes. TRMM was originally conceived in the mid-1980s as a climate mission with relatively modest goals, including monthly averaged precipitation. TRMM data were quickly exploited for model data assimilation and, beginning in 1999 with the availability of near real time data, for tropical cyclone warnings. To overcome the intermittently spaced revisit from these and other low Earth-orbiting satellites, many methods to merge PMW-based precipitation data and geostationary satellite observations have been developed, such as the TRMM Multisatellite Precipitation Product and the Climate Prediction Center (CPC) morphing method (CMORPH. The purpose of this article is not to provide a survey or assessment of these and other satellite-based precipitation datasets, which are well summarized in several recent articles. Rather, the intent is to demonstrate how the availability and continuity of satellite-based precipitation data records is transforming the ways that scientific and societal issues related to precipitation are addressed, in ways that would not be otherwise possible. These developments have taken place in parallel with the growth of an increasingly interconnected scientific environment. Scientists from different disciplines can easily interact with each other via information and materials they encounter online, and collaborate remotely without ever meeting each other in person. Likewise, these precipitation datasets are quickly and easily available via various data portals and are widely used. Within the framework of the NASA/JAXA Global Precipitation Measurement (GPM mission, these applications will become increasingly interconnected. We emphasize that precipitation observations by themselves provide an incomplete picture of the state of the atmosphere. For example, it is unlikely that a richer understanding of the global water cycle will be possible by standalone missions and algorithms, but must also involve some component of data, where model analyses of the physical state are constrained alongside multiple observations (e.g., precipitation, evaporation, radiation). The next section provides examples extracted from the many applications that use various high-resolution precipitation products. The final section summarizes the future system for global precipitation processing.

Kucera, Paul A.↗
NASA NTRS2017

Exploration Mission Particulate Matter Filtration Technology Performance Testing in a Simulated Spacecraft Cabin Ventilation System

Human deep space exploration missions will require advances in long-life, low maintenance airborne particulate matter filtration technology. As one of the National Aeronautics and Space Administrations (NASA) developments in this area, a prototype of a new regenerable, multi-stage particulate matter filtration technology was tested in an International Space Station (ISS) module simulation facility. As previously reported, the key features of the filter system include inertial and media filtration with regeneration and in-place media replacement techniques. The testing facility can simulate aspects of the cabin environment aboard the ISS and contains flight-like cabin ventilation system components. The filtration technology test article was installed at the inlet of the central ventilation system duct and instrumented to provide performance data under nominal flow conditions. In-place regeneration operations were also evaluated. The real-time data included pressure drop across the filter stages, process air flow rate, ambient pressure, humidity and temperature. In addition, two video cameras positioned at the filtration technology test articles inlet and outlet were used to capture the mechanical performance of the filter media indexing operation under varying air flow rates. Recent test results are presented and future design recommendations are discussed.

particulate matter filtration↗
NASA NTRS2017

Next Generation Agricultural System Models and Knowledge Products: Synthesis and Strategy

The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. In the Introduction to this Special Issue, we described a vision for accelerating the rate of agricultural innovation and meeting the growing global need for food and fiber. In this concluding article of the NextGen Special Issue we synthesize insights and formulate a strategy to advance data, models, and knowledge products that are consistent with this vision. This strategy is designed to facilitate a transition from the current, primarily supply-driven approach toward a more demand-driven approach that would address key Use Cases where better data, models and knowledge products are seen by end-users as essential to meet their needs.

Next generation↗
NASA NTRS2023

Machine Intelligence for Radiation Science: Summary of the Radiation Research Society 67th Annual Meeting Symposium

The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. The 67 th Annual Meeting of the Radiation Research Society featured a symposium on MI approaches to highlight recent advancements in the radiation sciences and their clinical applications. This article summarizes three of those presentations regarding recent developments for metadata processing and ontological formalization, data mining for radiation outcomes in pediatric oncology, and imaging in lung cancer.

radiation↗
NASA NTRS1993

Failure monitoring in dynamic systems: Model construction without fault training data

Advances in the use of autoregressive models, pattern recognition methods, and hidden Markov models for on-line health monitoring of dynamic systems (such as DSN antennas) have recently been reported. However, the algorithms described in previous work have the significant drawback that data acquired under fault conditions are assumed to be available in order to train the model used for monitoring the system under observation. This article reports that this assumption can be relaxed and that hidden Markov monitoring models can be constructed using only data acquired under normal conditions and prior knowledge of the system characteristics being measured. The method is described and evaluated on data from the DSS 13 34-m beam wave guide antenna. The primary conclusion from the experimental results is that the method is indeed practical and holds considerable promise for application at the 70-m antenna sites where acquisition of fault data under controlled conditions is not realistic.

Smyth, P.↗
DOE OSTI2024

A Data-Driven Methodology for Contextual Unit Commitment Using Regression Residuals

Day after day, system operators are faced with the challenge of taking unit commitment (UC) decisions under uncertain net load conditions. The standard operating procedure for taking UC decisions begins by leveraging auxiliary data on covariates (such as the day of the week or latest weather information) to generate a point prediction for net load, which is used in solving a deterministic UC problem. Such an approach, however, is known to deliver a notoriously poor out-of-sample (OOS) performance, as it completely disregards the stochastic nature of net load. While stochastic programming models explicitly represent uncertainty, they mostly do so using a generic set of scenarios that neglect covariate observations, squandering useful auxiliary data that could be harnessed to glean insights into uncertainty. In this article, we discuss a contextual stochastic optimization approach to UC, which effectively exploits covariate observations while explicitly assessing uncertainty so as to boost the OOS performance of UC decisions. The key thrust of our approach is to leverage regression models, along with their empirical residuals, to set up and solve sample average approximation problems. Not only do we prove that our approach satisfies the requisite conditions for asymptotic optimality and consistency laid out in (Kannan et al., 2022), but we also assess its performance on several case studies conducted using real-world data collected in California ISO and New York ISO grids. In conclusion, results show that the proposed approach can significantly improve OOS performance compared to alternative methods proposed in the literature under varying dataset sizes.

Yurdakul, Ogun↗