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At least 55 records · Page 3

Using dorsal surface for individual identification of dairy calves through 3D deep learning algorithms

Advances in machine learning techniques have allowed the development of computer vision systems (CVS) that can accurately predict several phenotypes of interest for livestock operations. In this context, 3D images taken from a top-down view are particularly useful for estimating body condition score, growth development, and body biometrics in cattle. Frequently, such CVS rely on identification (ID) systems, such as electronic tags, as a way to match animal ID and the predicted phenotype. However, the same 3D images used to predict body weight and other animal biometrics could be adopted for animal recognition as well. Such alternative would optimize CVS to recognize animal ID and monitor growth development simultaneously while leveraging the same hardware infrastructure. Furthermore, this strategy could be used to recognize animals with similar color patterns. Nonetheless, growing animals are continuously changing body shape, which could limit its use as an invariant feature for pattern recognition. Thus, the objectives of this study were: (1) to compare algorithms for different 3D object representations to identify individual animals; and (2) to evaluate how short-term changes in body shape due to animal growth affect the predictive performance of these algorithms. For objective 1, the algorithms were trained (n = 4,558) and tested (n = 1,139) using images from 38 Holstein calves. For objective 2, we designed three different experiments using images (n = 2,347) from five Holstein calves taken over six weeks during their growing period, always training and testing on different weeks. Each experiment evaluated how changing a different parameter of the image capturing procedure affected the predictive ability of the trained algorithms. In the first experiment, we varied the total number of images per animal in the training set; in the second experiment, we varied the number of weeks while keeping a fixed number of images in the training set; and in the third experiment, we skipped weeks between images in the training and test sets. The F 1 score for objective (1) was up to 0.804 when testing with the last frames of each video, and up to 0.959 when using random frames for testing. For objective (2), the F 1 score was up to 0.947 for the first experiment when using 130 images per animal; up to 0.979 for the second experiment when using all five weeks; and up to 0.917 when not skipping weeks between training and testing. In conclusion, these results show that deep learning algorithms can be used to identify individual animals through their dorsal area 3D surfaces, and, from our experiments using calves in their growing period, that they are robust enough to account for changes in body shape and size, making them a promising tool for animal recognition during growth.

3D neural networks↗

The Hydrosphere State (Hydros) Satellite Mission: An Earth System Pathfinder for Global Mapping of Soil Moisture and Land Freeze/Thaw

The Hydrosphere State Mission (Hydros) is a pathfinder mission in the National Aeronautics and Space Administration (NASA) Earth System Science Pathfinder Program (ESSP). The objective of the mission is to provide exploratory global measurements of the earth's soil moisture at 10-km resolution with two- to three-days revisit and land-surface freeze/thaw conditions at 3-km resolution with one- to two-days revisit. The mission builds on the heritage of ground-based and airborne passive and active low-frequency microwave measurements that have demonstrated and validated the effectiveness of the measurements and associated algorithms for estimating the amount and phase (frozen or thawed) of surface soil moisture. The mission data will enable advances in weather and climate prediction and in mapping processes that link the water, energy, and carbon cycles. The Hydros instrument is a combined radar and radiometer system operating at 1.26 GHz (with VV, HH, and HV polarizations) and 1.41 GHz (with H, V, and U polarizations), respectively. The radar and the radiometer share the aperture of a 6-m antenna with a look-angle of 39 with respect to nadir. The lightweight deployable mesh antenna is rotated at 14.6 rpm to provide a constant look-angle scan across a swath width of 1000 km. The wide swath provides global coverage that meet the revisit requirements. The radiometer measurements allow retrieval of soil moisture in diverse (nonforested) landscapes with a resolution of 40 km. The radar measurements allow the retrieval of soil moisture at relatively high resolution (3 km). The mission includes combined radar/radiometer data products that will use the synergy of the two sensors to deliver enhanced-quality 10-km resolution soil moisture estimates. In this paper, the science requirements and their traceability to the instrument design are outlined. A review of the underlying measurement physics and key instrument performance parameters are also presented.

Entekhabi, D.↗

The Atmosphere-Space Transition Region Explorer (ASTRE) – A Low Perigee Satellite to Investigate the Coupling of the Earth’s Upper Atmosphere and Magnetosphere

The Atmosphere-Space Transition Region Explorer (ASTRE) is a mission concept designed to carry out an unprecedented study of the interaction between the Earth’s atmosphere and the ionized gases of space within the atmosphere-space transition region. By gathering direct measurements of the coupling of ion and neutral gases in this region, ASTRE provides the critical missing link in our knowledge of the transfer, dissipation, and regulation of energy and momentum between the sun and the upper atmosphere. ASTRE provides the first detailed, systematic investigation of this important unexplored region, vastly improves and constrains models of the upper atmosphere, and fills a critical gap in our understanding of how the coupled lower ionosphere/upper atmosphere “works” as a system. To achieve its science objectives, ASTRE gathers accurate measurements of plasma and neutral gases, electric and magnetic fields, and energetic particles using well-proven, in situ instruments with excellent flight heritage. Furthermore, as described herein, all the instruments have been designed to perform well in the low perigee environment, including altitudes of 150 km and lower. ASTRE utilizes a three-axis stabilized satellite that uses on-board propulsion to carry out systematic, low perigee measurements at high latitudes. The satellite design incorporates a “form follows function” approach with a cylindrical shape and conductive body-mounted solar arrays to minimize drag and perturbations to the space environment. Atomic-oxygen resistant materials are utilized and a passive thermal design with heat pipes and radiator panels minimizes the impact of aero-heating. ASTRE launches into a 250 km × 1500 km elliptical insertion orbit with an inclination of 83°. Perigee precesses from its highest northern latitude to its highest southern latitude every ~60 days. Hydrazine propulsion provides over 2000 orbits with perigee below 200 km, with a significant fraction as low as 150 km, during high latitude, two-week campaigns when perigee precesses to either the northern or southern high latitude region. At mid and low latitudes, the perigee is near 225 km. Because very conservative assumptions were made with respect to the orbital analysis and drag, including continuous 3-sigma “worst-case” solar flux and atmospheric density, when additional propellant is included (accommodated in the current design) and some of the stringent assumptions are relaxed, the ASTRE mission described herein may be expected to include repeated excursions to altitudes of ~130 km or even lower. This paper presents an overview of the ASTRE mission, its science motivation, and objectives. It includes a discussion of the science-driven requirements and traceability, followed by a “proof-of concept” implementation that includes notional instruments and a straightforward spacecraft design. Three key points are demonstrated: 1) There is a critical knowledge gap in the high latitude, atmosphere-space transition region below 250 km; 2) The instrument and measurement techniques needed to obtain the ASTRE measurements are well-proven and function well in the low-altitude environment; and 3) A mature spacecraft design, flight dynamics analysis, and concept of operations have been developed that demonstrate that the ASTRE mission can be achieved in a straightforward manner using current technologies.

Ionosphere↗

Advancing Open Science in Atmospheric Research: Integrating Data Usability and Machine Learning

In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences." "In the dynamic realm of atmospheric sciences, the convergence of data science methodologies and open data marks a transformative era, driving research advancements and nurturing aspiring scientists. This abstract highlights two pivotal projects that epitomize open science principles, aligning seamlessly with the session's objective of interdisciplinary synergy and the cultivation of emerging talent. As a NASA-certified data center, our foremost endeavor focuses on enhancing the visibility and traceability of NASA datasets within atmospheric science research. This initiative not only elevates these datasets' prominence but also establishes a robust framework ensuring their credibility in scholarly discourse. By bridging the gap between data sources and research publications, this project serves as an educational catalyst, nurturing a new generation of scholars in open collaboration and dataset authenticity. Concurrently, our second project pioneers an early warning system for flooding events, utilizing machine learning algorithms to predict flooded fractions. Through multi-source data fusion and predictive modeling, this initiative goes beyond forecasting; it embodies the core of open science by enabling proactive risk mitigation strategies. This project not only advances atmospheric sciences but also fosters an environment where young scholars engage in practical, data-driven solutions. These intertwined projects exemplify the fusion of data science with open data solutions, ensuring both the usability of quality datasets and the cultivation of scientific knowledge among emerging scholars. By spotlighting these impactful use cases, our aim is to foster discussions emphasizing the importance of open collaboration, data integrity, and the nurturing of scientific talent in atmospheric sciences.

Jennifer Wei↗

Stakeholder-Engaged Structured Decision Making for the Los Alamos Legacy Cleanup Mission - 20501

The Los Alamos National Laboratory (LANL) environmental legacy cleanup program requires decisions to be made for environmental remediation, decommissioning and disposal or management of radioactive waste. This legacy cleanup program was established to address groundwater contamination, material disposal areas (MDAs) that have been used to dispose of radioactive and other waste material, and 'aggregate areas' that might produce radioactive or other chemical waste as a result of remediation activities. The LANL site is regulated for environmental concerns under the Resource Conservation and Recovery Act (RCRA). However, some parts of LANL, such as material disposal area G (MDA G), have disposed of radioactive waste under DOE Order 435.1, and are subject to other regulations. For example, decommissioning the remote-handled TRU material stored in 33 shafts at MDA G falls under EPA's 40 CFR 191. Collectively, the regulations are all aimed in the same direction of finding the best solution, either through constructs such as 'as low as reasonably achievable' (ALARA), considering balancing factors as opposed to only cost and human health risk, and, under EPA regulations such as RCRA and NEPA, evaluating impact from all chemicals and both human health and ecological endpoints. Despite the basic goals and objectives of the regulations or their guidance, the main challenge is in their implementation. Arguably perhaps, but really in principle, all of these (and similar) regulations are asking for a decision analysis to be performed. Implementation challenges encountered have included lack of understanding of decision analysis in the industry, lack of effective stakeholder engagement in the decision analysis process, and lack of appreciation of the need to separate value judgments from science, the latter leading to developing conservative, or protective, science-based models. Conservative models lead to poor solutions, lack of effective stakeholder engagement leads to long drawn out protracted approaches to finding a solution (which also might never be found with this approach), and lack of understanding of decision analysis and Bayesian statistics causes poor models to be built, which creates unfortunate situations of 'garbage in, garbage out' becoming the basis for decision making. Stakeholder-engaged structured decision making (SDM) is an approach to solving problems that relies on the theory of decision science to involve stakeholders in the decision-making process. This approach incorporates stakeholder values using a scientifically rigorous methodology that separates value judgments from science in a way that helps avoid the pitfalls of biased, protective, or conservative modeling. This approach has its foundation in Keeney's 1992 treatise on value-focused thinking [1]. Keeney advocated a paradigm shift in decision making based on the idea that the standard way of thinking about decisions is backwards. The standard approach of focusing first on identifying alternatives rather than on articulating values results in a reactive approach with the emphasis on mechanics and fixed choices instead of the core values that have meaning to stakeholders. This paradigm shift effectively engages all stakeholders in the decision-making process while using a values focused thinking approach that can lead to the identification of decision opportunities and the creation of better alternatives. The intent is to be proactive and generate solutions that are related directly to values and objectives as identified by stakeholders. There are, perhaps, two overarching reasons why SDM can be used to benefit LANL's environmental legacy cleanup. Some of LANL's remaining waste management and environmental management problems are challenging and complex (for example, the Cr and RDX plumes, and MDAs) and while the traditional approach has, arguably, worked well for relatively simple risk-based problems, it cannot, or should not, be applied to more complex problems if the most effective and efficient solutions are desired. The second reason is cost. This has perhaps become more critical since publication of the Government Accountability Office (GAO) reports that DoE's environmental liability is considered a high-risk concern for the nation [2]. The focus of SDM is on structuring solutions to decision risk problems by first addressing stakeholder and decision maker values and subsequently developing decision objectives and ways to measure those objectives, preference weighting across objectives, identifying decision alternatives that best achieve those values, and characterizing uncertainty in predictions of the measures. Because a complete decision model is created using SDM, it can be evaluated to find the main elements of the model that drive, or predict, the best solution. This approach creates complete decision models that are transparent, traceable, reproducible and technically defensible. The science behind SDM, or decision analysis, is well founded, yet it is not unusual to see ad hoc approaches to decision making implemented under various environmental regulations that are pertinent to the LANL site, including NEPA, RCRA and DOE Order 435.1. Such ad hoc approaches are often not transparent or traceable, and lack reproducibility and technical defensibility. The LANL legacy cleanup program has embarked on using SDM to address the complex problems that remain. Stakeholder meetings have been held, and a prototype version of the stakeholder value system has been developed. Further meetings are expected in the future to address specific project needs. This is a long-term endeavor considering the complex environmental problems faced by DOE EM in Los Alamos (EM-LA), and careful planning, consideration of stakeholder value systems, and engagement with stakeholders throughout the SDM process is expected to lead to a successful endpoint. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Reference Ocean Surface Emission and Backscatter Model from Microwaves to Infrared

Satellite observations are vital for the initialization of Numerical Weather Prediction models, and very important for climate monitoring and prediction, as well as other applications such as hydrology and flood awareness prediction. Knowledge of radiative contributions from the Earth's surface is needed to sound the lower troposphere from space. The lack of a reference quality ocean emission and backscatter model is a major gap in our ability to provide absolute calibration of the satellite based observing system. Uncertainty in emissivity models is not well characterized and different models are used for different spectral bands, for active and passive instruments. An International Space Science Institute (ISSI) team was put together [4] to address these issues. The objectives of the team are to provide a reference model as a community software (i.e., documented and freely available code), that is maintained and supported, has traceable uncertainty estimations, and that enables new science from microwaves to infrared with bidirectional reflectance distribution function (BRDF) capability. We will present the model and its various components, discussing the choices between various parameterizations, building on the LOCEAN model of [2]. The model predictions will be evaluated at various frequencies, including comparisons to radiometric observations by SMAP, AMSR2 and GMI (e.g., [5]). We will discuss early model evaluation in the infrared and for active microwave sensors. Areas of ongoing research include improving the foam parametrization (coverage and emissivity) to provide consistent performances across frequencies, building on [1], and the azimuthal dependence of the active and passive signals. The model will be used to generate training data for fast models e.g., Fastem, [3], that are used in operational data assimilation and climate re-analysis.

Emmanuel Dinnat↗

Measuring Broadband IR Irradiance in the Direct Solar Beam (Poster)

Solar and atmospheric science radiometers, e.g. pyranometers, pyrheliometers, and photovoltaic cells are calibrated with traceability to a consensus reference, which is maintained by Absolute Cavity Radiometers (ACRs). The ACR is an open cavity with no window, developed to measure extended broadband direct solar irradiance beyond the ultraviolet and infrared bands below and above 0.2 micrometers and 50 micrometers, respectively. On the other hand, pyranometers and pyrheliometers are developed to measure broadband shortwave irradiance from approximately 0.3 micrometers to 3 micrcometers, while the present photovoltaic cells are limited to approximately 0.3 micrometers to 1 micrometers. The broadband mismatch of ACR versus such radiometers causes discrepancy in radiometers' calibration methods that has not been discussed or addressed in the solar and atmospheric science literature. Pyrgeometers are also used for solar and atmospheric science applications and calibrated with traceability to consensus reference, yet calibrated during nighttime only, because no consensus reference has yet been established for the daytime longwave irradiance. This poster shows a method to measure the broadband IR irradiance in the direct solar beam from 3 micrometers to 50 micrometers, as first step that might be used to help develop calibration methods to address the mismatch between broadband ACR and shortwave radiometers, and the lack of a daytime reference for pyrgeometers. The irradiance was measured from sunrise to sunset for 5 days when the sun disk was cloudless; the irradiance varied from approximately 1 Wm-2 to 16 Wm-2 for solar zenith angle from 80 degres to 16 degrees respectively; estimated uncertainty is 1.5 Wm-2.

47 OTHER INSTRUMENTATION↗

A Procedure to Correct the Historical Atmospheric Longwave Irradiance Data When the World Reference Is Established with Respect to the International System of Units

Historical and traceable atmospheric longwave irradiance data sets with traceability to the International System of units (SI) are essential for renewable energy and atmospheric science research and applications. To date, all pyrgeometers used to measure the irradiance are traceable to the interim World InfraRed Standard Group (WISG) not to SI units. In 2013 the Absolute Cavity Pyrgeometer (ACP), [Reda et al., 2012] was developed at the National Renewable Energy Laboratory (NREL) to measure the atmospheric longwave irradiance. The ACP has been compared against the InfraRed Integrating Sphere (IRIS) developed by the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC) [J. Grobner, 2012]. ACP and IRIS are absolute instruments traceable to SI units through the International Temperature Scale ITS-90. Results of six comparisons between ACP and IRIS at different location have shown that the irradiance measured by WISG pyrgeometers is underestimating clear-sky atmospheric longwave irradiance by 2 to 6 W/m 2 [Grobner et al., 2014]. Therefore, once the world reference is established with traceability to SI units the WISG would be corrected then used to calibrate field pyrgeometers with traceability to SI units. The described method below is used to correct the historical atmospheric longwave irradiance data sets in anticipation of the WISG scale change.

54 ENVIRONMENTAL SCIENCES↗

A Procedure to Correct the Historical Atmospheric Longwave Irradiance Data When the World Reference Is Established with Respect to the International System of Units

Historical atmospheric longwave irradiance data sets with traceability to the International System of Units (SI) are essential for renewable energy and atmospheric science research and applications. To date, all pyrgeometers used to measure the irradiance are traceable to the interim World Infrared Standard Group (WISG), not to SI units. In 2013, the Absolute Cavity Pyrgeometer (ACP) (Reda et al. 2012) was developed at the National Renewable Energy Laboratory (NREL) to measure the atmospheric longwave irradiance. The ACP has been compared against the InfraRed Integrating Sphere (IRIS), developed by the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC) (Gröbner 2012). The ACP and the IRIS are absolute instruments traceable to SI units through the International Temperature Scale of 1990. Results of six comparisons between the ACP and the IRIS at different locations have shown that the irradiance measured by WISG pyrgeometers underestimates clear-sky atmospheric longwave irradiance by 2 W/m 2 to 6 W/m 2 (Gröbner et al. 2014); therefore, once the world reference is established with traceability to SI units, the WISG would be corrected, then used to calibrate field pyrgeometers with traceability to SI units. The following described method is used to correct the historical atmospheric longwave irradiance data sets in anticipation of the WISG scale change.

54 ENVIRONMENTAL SCIENCES↗

Roadmap for In-Space Propulsion Technology

NASA has created a roadmap for the development of advanced in-space propulsion technologies for the NASA Office of the Chief Technologist (OCT). This roadmap was drafted by a team of subject matter experts from within the Agency and then independently evaluated, integrated and prioritized by a National Research Council (NRC) panel. The roadmap describes a portfolio of in-space propulsion technologies that could meet future space science and exploration needs, and shows their traceability to potential future missions. Mission applications range from small satellites and robotic deep space exploration to space stations and human missions to Mars. Development of technologies within the area of in-space propulsion will result in technical solutions with improvements in thrust, specific impulse (Isp), power, specific mass (or specific power), volume, system mass, system complexity, operational complexity, commonality with other spacecraft systems, manufacturability, durability, and of course, cost. These types of improvements will yield decreased transit times, increased payload mass, safer spacecraft, and decreased costs. In some instances, development of technologies within this area will result in mission-enabling breakthroughs that will revolutionize space exploration. There is no single propulsion technology that will benefit all missions or mission types. The requirements for in-space propulsion vary widely according to their intended application. This paper provides an updated summary of the In-Space Propulsion Systems technology area roadmap incorporating the recommendations of the NRC.

Meyer, Michael↗

Measuring Broadband IR Irradiance in the Direct Solar Beam (Presentation)

Solar and atmospheric science radiometers, e.g. pyranometers, pyrheliometers, and photovoltaic cells are calibrated with traceability to a consensus reference, which is maintained by Absolute Cavity Radiometers (ACRs). The ACR is an open cavity with no window, developed to measure extended broadband direct solar irradiance beyond the ultraviolet and infrared bands below and above 0.2 um and 50um, respectively. On the other hand, pyranometers and pyrheliometers are developed to measure broadband shortwave irradiance from approximately 0.3 um to 3 um, while the present photovoltaic cells are limited to approximately 0.3 um to 1 um. The broadband mismatch of ACR versus such radiometers causes discrepancy in radiometers' calibration methods that has not been discussed or addressed in thesolar and atmospheric science literature. Pyrgeometers are also used for solar and atmospheric science applications and are calibrated with traceability to consensus reference, yet are calibrated during nighttime only, because no consensus reference has yet been established for the daytime longwave irradiance. This poster shows a method to measure the broadband IR irradiance in the direct solarbeam from 3 um to 50 um, as a first step that might be used to help develop calibration methods to address the mismatch between broadband ACR and shortwave radiometers, and the lack of a daytime reference for pyrgeometers. The irradiance was measured from sunrise to sunset for 5 days when the sun disk was cloudless; the irradiance varied from approximately 1 Wm-2 to 16 Wm-2 for solar zenithangle from 80 degrees to 16 degrees respectively; estimated uncertainty is 1.5 Wm-2.

14 SOLAR ENERGY↗

Measuring Broadband IR Irradiance in the Direct Solar Beam and Recent Developments

Solar and atmospheric science radiometers such as pyranometers, pyrheliometers, and photovoltaic cells are calibrated with traceability to a consensus reference which is maintained by Absolute Cavity Radiometers (ACRs). An ACR is an open cavity with no window, developed to measure the extended broadband spectrum of the terrestrial direct solar beam irradiance that extends beyond the ultraviolet and infrared bands; i.e. below 0.2 um and above 50 um, respectively. On the other hand, the pyranometers and pyrheliometers were developed to measure broadband shortwave irradiance from approximately 0.3 um to 3 um, while the present photovoltaic cells are limited to the spectral range of approximately 0.3 um to 1 um. The broadband mismatch of ACR versus such radiometers causes discrepancy in radiometers' calibration methods that has not been discussed or addressed in the solar and atmospheric science literature. Pyrgeometers, which measure the atmospheric longwave irradiance, are also used for solar and atmospheric science applications and calibrated with traceability to a consensus reference, yet they are calibrated during nighttime only, because no consensus reference has been established for the daytime longwave irradiance. This poster describes a method to measure the broadband longwave irradiance in the terrestrial direct solar beam from 3 um to 50 um, as a first step that might be used to help develop calibration methods to address the mismatch between broadband ACR and shortwave radiometers, and the lack of a daytime reference for pyrgeometers. The described method is used to measure the irradiance from sunrise to sunset; the irradiance varied from approximately 1 Wm-2 to 16 Wm-2 with an estimated uncertainty of 1.5 Wm-2, for a solar zenith angle range from 80 degrees to 16 degrees, respectively. Recent development shows that there is greater than 1.1 percent bias in measuring shortwave solar irradiance.

14 SOLAR ENERGY↗

A Procedure to Correct the Historical Atmospheric Longwave Irradiance Data When the World Reference Is Established with Respect to the International System of Units

Historical atmospheric longwave irradiance data sets with traceability to the International System of Units (SI) are essential for renewable energy and atmospheric science research and applications. To date, all pyrgeometers used to measure the irradiance are traceable to the interim World Infrared Standard Group (WISG), not to SI units. In 2013, the Absolute Cavity Pyrgeometer (ACP) (Reda et al. 2012) was developed at the National Renewable Energy Laboratory (NREL) to measure the atmospheric longwave irradiance. The ACP has been compared against the InfraRed Integrating Sphere (IRIS), developed by the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center (PMOD/WRC) (Grobner 2012). The ACP and the IRIS are absolute instruments traceable to SI units through the International Temperature Scale of 1990. Results of six comparisons between the ACP and the IRIS at different locations have shown that the irradiance measured by WISG pyrgeometers underestimates clear-sky atmospheric longwave irradiance by 2 W/m 2 to 6 W/m 2 (Grobner et al. 2014); therefore, once the world reference is established with traceability to SI units, the WISG would be corrected, then used to calibrate field pyrgeometers with traceability to SI units. The following described method is used to correct the historical atmospheric longwave irradiance data sets in anticipation of the WISG scale change.

47 OTHER INSTRUMENTATION↗

MO-FG-CAMPUS-IeP3-01: Evaluation of Specific Absorption Rate and Temperature Increase Induced by Artificial Medical Implants During MRI Scan

Purpose: Heating of patients or burning of biological tissues around medical implants by RF power during MRI scan is a significant patient safety concern. The purpose of this study is to not only measure SAR values, but also RF-induced temperature elevation due to artificial hip joints during MRI scans. Methods: SAR measurement experiment was performed on three discrete manufacturers at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T2w inversion recovery, and T2w TSE) with imaging parameters were selected. A gelled saline phantom mimicking human body tissue was made (Fig.1). FDTD method was utilized to calculate the SAR distribution using Sim4Life software. Based on the results of the simulation, 4 electrical field (E-field) sensors were located around two artificial hip joints inside the phantom. 56 Fiber Bragg Grating (FBG) temperature sensors (28 sensors on each artificial hip joint) were located on both left and right artificial hip joints to measure temperature change during MRI scan (Fig.1). Both E-field and FBG temperature sensors were calibrated with traceability at Korea Research Institute of Standards and Science (KRISS). Results: Simulation shows that high SAR values occur in the head and tail of the implanted artificial hip joints (Fig.1 lower right). 3T MRI scanner shows that the local averaged-SAR values measured by probe 1, 2, and 3 are 2.30, 2.77, and 1.68 W/kg, compared to MRI scanner-reported whole body SAR value (≤1.5 W/kg) for T1w TSE and T2w-IR (Table 1). The maximum temperature elevation measured by FBG sensors is 1.49°C at 1.5 T, 2.0°C at 3 T, and 2.56°C at 3 T for T1w TSE, respectively (Table 2). Conclusion: It is essential to assess the safety of MRI system for patient with medical implant by measuring not only accurate SAR deposited in the body, but also temperature elevation due to the deposited SAR during clinical MRI.

60 APPLIED LIFE SCIENCES↗

Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA

In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Failure Mechanism Traceability and Application in Human System Interface of Nuclear Power Plants using RESHA

In recent years, there has been considerable effort to modernize existing and new nuclear power plants with digital instrumentation and control systems (DI&C). However, there has also been considerable concern both by industry and regulatory bodies for the risk and consequence analysis of these systems. Of particular concern are digital common cause failures (CCFs) specifically related to software defects. These “misbehaviors” by the software can occur in both the control and monitoring of a system. While many new methods have been proposed to identify potential software failure modes, such as Systems-theoretic Process Analysis (STPA), Hazard and Consequence Analysis for Digital Systems (HAZCADS), etc., these methods are focused primarily on the control action pathway of a system. In contrast, the information feedback pathway lacks unsafe control actions (UCAs), which are typically related to software basic events; thus, assessment of software basic events in such systems is unclear. In this work, we present the idea of intermediate processors and unsafe information flow (UIF) to help safety analysts trace failure mechanisms in the feedback pathway and how they can be integrated into a fault tree for improved assessment capability. The concepts presented are demonstrated in two comprehensive case studies, a smart sensor integrated platform for unmanned autonomous vehicles and another on a representative advanced human system interface (HSI) for safety critical plant monitoring. The qualitative software basic events are identified, and a fault tree analysis is conducted based on a modified Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) methodology. The case studies demonstrate the use of UIF and intermediate processors in the fault tree to improve traceability of software failures in highly complex digital instrumentation feedback. The improved method can also clarify fault tree construction when multiple component dependencies are present in the system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Sensitivity of the ACCP Value Framework Science Benefit Score

NASA’s priorities for Earth Science are informed by the 2017-2027 Decadal Survey for Earth Science and Applications from Space of the National Academies of Sciences, Engineering and Medicine. In that document, five Designated Observables are identified as priorities for implementation: Aerosols, Cloud-Convection-Precipitation, Surface Biology, Mass Change, and Surface Deformation Change. In 2019, NASA initiated four multi-year studies to formulate, assess, and recommend potential Observing System concepts that are responsive to the recommendations of the Earth Science Decadal Survey. The Aerosols, Clouds, Convection, and Precipitation (ACCP) study investigates opportunities for synergistic science resulting from implementations that combine both Aerosols science objectives and Clouds, Convection, and Precipitation science objectives. For the ACCP study, a Value Framework was designed to introduce structure, transparency, and traceability in the mission down-select decision process. This paper presents a sensitivity analysis that was conducted to characterize the behavior of the science benefit score of the ACCP Value Framework. it includes derivations of the sensitivity analysis equations, numerical analyses of the behavior of the combined benefit score, and the conclusions drawn from the results of the work that was conducted. The results of this analysis were key to ensuring that the aggregated science benefit scores would enable the team to differentiate and contrast across concepts.

John McLaughlan↗

Persistent Identifiers Implementation in EOSDIS

This presentation provides the motivation for and status of implementation of persistent identifiers in NASA's Earth Observation System Data and Information System (EOSDIS). The motivation is provided from the point of view of long-term preservation of datasets such that a number of questions raised by current and future users can be answered easily and precisely. A number of artifacts need to be preserved along with datasets to make this possible, especially when the authors of datasets are no longer available to address users questions. The artifacts and datasets need to be uniquely and persistently identified and linked with each other for full traceability, understandability and scientific reproducibility. Current work in the Earth Science Data and Information System (ESDIS) Project and the Distributed Active Archive Centers (DAACs) in assigning Digital Object Identifiers (DOI) is discussed as well as challenges that remain to be addressed in the future.

persistent identifiers↗