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NASA NTRS2019

Global Cloud Cover: Comparison of Satellite, Model, and Volunteer Data

Observing and better understanding clouds and aerosols are priorities in the NASA Earth Science Decadal Survey, US National Climate Assessment, and Intergovernmental Panel on Climate Change Report. The Global Learning & Observations to Benefit the Environment (GLOBE) Program is NASA's largest and longest running citizen science program in the Earth Sciences that collects cloud observations. Since January 2017, NASA GLOBE students and citizen scientists have submitted over 800,000 cloud observations worldwide using both paper-based and smartphone app platforms. In this presentation, we compare satellite, model, and volunteer-reported total cloud cover. The comparison reveals a systematic misreporting of obscured skies (sky not visible due to smoke, dust, haze, etc.) versus overcast skies (100% total cloud cover) by GLOBE participants. We discuss implications for improving procedures for volunteer reporting under overcast and obscured sky conditions, and relevance for reporting extreme air pollution events in areas with little or no formal institutional monitoring networks.

Starke, Matthew↗

NASA NTRS2019

Citizen Science Data Quality: The GLOBE Program

The Global Learning and Observations to Benefit the Environment (GLOBE) Program is an international program that provides a way for students and the public to contribute Earth system observations. Currently 122 countries, more than 40,000 schools, and 200,000 citizen scientists are participating in GLOBE. Since 1995, participants have contributed 195 million observations. Modes of data collection and data entry have evolved with technology over the lifetime of the program, including the launch of the GLOBE Observer mobile app in 2016 to broaden access and public participation in data collection. GLOBE must meet the data needs of a diverse range of stakeholders, from elementary school classrooms to scientists across the globe, including NASA scientists. Operational quality assurance measures include participant training, adherence to standardized data collection protocols, range and logic checks, and an approval process for photos submitted with an observation. In this presentation, we will discuss the current state of operational data QA/QC, as well as additional QA/QC processes recently explored and future directions.

Amos, Helen↗

NASA NTRS2019

Orbital Debris Ontology, Terminology, and Knowledge Modeling

The looming threat orbital debris poses to assets in orbit demands solutions. As the orbital population grows, so does this hazard, but so does the sea of data. The problem is also an opportunity for interdisciplinary innovation and cooperation. This paper focuses on the data and information management aspect of developing solutions for a sustainable and safe orbital space environment. The corresponding author’s in-progress work to develop an orbital debris domain ontology is summarized in order to discuss knowledge modeling for this domain. Methodological approaches of this effort can also contribute to standards efforts and address terminological and policy questions. Leveraging the growing volumes of orbital debris and space situational awareness (SSA) data will create a more complete picture of the orbital space environment. Part of the solution will be: consistent and correct data interpretation, sharing orbital debris and SSA data in one form or another, terminology development & harmonization, and knowledge or domain modeling. To facilitate this, [Rovetto, 2015/16] discussed ontology development for the orbital debris domain. This paper lists concepts from that paper, and subsequently developed concepts [2-9]. Ontology engineering is an interdisciplinary field related to knowledge representation and reasoning in artificial intelligence, semantic technologies and the so-called semantic web. An ontology is effectively a computable and semantically rich terminology that presents a knowledge or domain model for a topic area. Expressions of knowledge or assertions are stored using formally defined term. This knowledge base is reasoned over to yield answers to queries, among other things. Ontologies have been developed in knowledge-based projects across various disciplines, and used for such things as search engines, chatbots, enterprise knowledge graphs, etc. Ontologies support: interoperability, automated reasoning, data sharing and integration, data search and retrieval, and communicating the meaning of data. The Orbital Debris Ontology (ODO), and related ontologies [Rovetto & Kelso 2016] [Rovetto 2016, 2017], were proposed to help achieve this. ODO, for instance, is intended as a domain ontology that can be used across federated databases, offering an explicitly specified set of concepts describing the orbital debris domain. Its meaning-rich taxonomy will provide a sharable semantics for orbital debris data to, in part, consistently communicate the meaning of data to both humans and machines, and tag data elements in space object catalogs to help afford inference tasks, decision support, knowledge discovery, and information integration. ODO and the SSA ontology (SSAO) is part of the overall Orbital Space Domain Ontology concept, which is conceived as a broader domain reference ontology. It aims to provide a knowledge representation structure of the orbital space environment, a common semantic model, and develop a sharable terminology. Collectively this will provide common meaning for datasets, a high-level taxonomy or classification for orbital space objects, and thus means to characterize space objects. Ongoing efforts have included using visualizations, R, JSON-LD, and contemporary semantic technologies. Potential applications and interdisciplinary partnerships include web-based platforms, web apps, visualizations, and academia projects. Community input and participation may yield a more widely understood domain model as well as facilitate terminological standards. For example, the proposed conceptual, terminological and ontological analysis may contribute to such efforts as the Space Debris Mitigation Requirements in the International Standards Organization by developing more precise, consistent and coherent terms and definitions. Projects that seek to develop in-house ontologies can use ODO and related ontologies as domain reference ontologies. This paper was developed independent of author affiliations. Readers are encouraged to contact corresponding author(1) with general interest and potential opportunities to support or realize the described project.

Robert J. Rovetto↗

NASA NTRS2016

Economic Readiness Level Considerations for a Robust LEO Economy

The reduced gravity environment of space provides a unique opportunity to further our understanding of various materials phenomena involving the molten, fluidic and gaseous states as well as life science applications where, contrary to earlier beliefs, microgravity induces changes in single cells and simple organisms; not only in large organisms with a complex overall response to gravity (or lack thereof). The potential breadth of commercial opportunities in microgravity thus spans over many verticals of the private sector with applications ranging from fiber optics, high-resolution crystals, microencapsulation, 3D organs to perfume and color dyes. Overall, products manufactured in microgravity hold the promise to have key properties surpassing their best terrestrial counterparts. Commercialization, also known as taking a new technology to market, is a journey in itself where the business, economic, market and technological components must align to generate a successful outcome. A business perspective is very different than technology maturation, which can be measured with the usual Technology Readiness Level (TRL) approach. In order for a technology to be ready for commercialization, it must not only be mature (high TRL), but it must also have a compelling business case, and the means to scale up production must be identified and practical. Creating a sustainable economy in an emerging market such as microgravity is especially challenging because of the complexity (high risks, lack of standardization) involved in predicting future growth. This complexity can easily overwhelm the fact that many of the products have an attractive touch of space which aids with branding and marketing.This paper builds upon the concept of the verticals of microgravity, capturing not only new lines of investigations but also promising killer apps originating from microgravity to discuss and define the notion of Economic Readiness Level (ERL). To advance in ERL, the technology itself may not necessarily need to mature at all, but the understanding of its economic potential does. Building upon ERL, a model that ultimately leads to the creation of pathways for infusion of private capital and a sustainable commercial microgravity LEO-Earth economy will be discussed.

Cozmuta, Ioana↗

NASA NTRS2017

Exotic Optical Fibers and Glasses: Innovative Material Processing Opportunities in Earth's Orbit

Exotic optical fibers and glasses are the platform material for photonics applications, primarily due to their superior signal transmission (speed, low attenuation), with extending bandwidth deep into the infrared, exceeding that of silica fibers. Gravitational effects (convection sedimentation) have a direct impact on the phase diagram of these materials and influence melting properties, crystallization temperatures, and viscosity of the elemental mix during the manufacturing process. Such factors constitute limits to the yield, transmission quality, and strength and value of these fibers; they also constrain the range of applications. Manufacturing in a gravity-free environment such as the Earth’s Orbit also helps with other aspects of the fabrication process (i.e., improved form factor of the manufacturing unit, sustainability). In this article, revolutionary developments in the field of photonics over the past decade merge with the paradigm shift in the privatization of government-owned capabilities supporting a more diverse infrastructure (parabolic, suborbital, orbital), reduced price, and increased frequency to access space and the microgravity environment. With the increased dependence on data (demand, bandwidth, efficiency), space and the microgravity environment provide opportunities for optimized performance of these exotic optical fibers and glasses underlying the development of enabling technologies to meet future data demand. Existing terrestrial markets (Internet, telecommunications, market transactions) and emerging space markets (onorbit satellite servicing, space manufacturing, space resources, space communications, etc.) seem to converge, and this innovative material processing opportunity of exotic optical fibers and glasses might just be that ‘‘killer app’’: technologically competitive, economically viable, and with the ability to close the business case.

Ioana Cozmuta↗

NASA NTRSDate not supplied

TPSAS-NF1676L-16422-DND

The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Results from recent NAIRAS model updates and new data products are presented. In addition, current and ongoing radiation measurement campaigns and verification and validation efforts are discussed.

Christopher J Mertens↗

NASA NTRSDate not supplied

TPSAS-NF1676L-30692-DND

Objectives: transform a branch of the FUN3D mini-app into OpenCL, benchmark OpenCL routines against sequential and CUDA versions of the same routines, use Intel OpenCL SDK to run on FPGA, and compare performance and suggest opportunities for optimization.

Jason Orender↗

NASA NTRSDate not supplied

Enabling Execution of a Legacy CFD Mini Application on Accelerators Using OpenMP

We describe the process and outcome of our efforts to port a legacy Fortran benchmark code to heterogeneous GPU-accelerated computing architectures using OpenMP. The benchmark code is one of the multi-zone NAS Parallel Benchmarks (NPB-MZ) called SP-MZ. This “mini-app” mimics the computation and data movement that is found in popular legacy and modern implicit computational fluid dynamics (CFD)solvers. Our objective was to examine how efficiently legacy Fortran codes can be ported to accelerators by leveraging OpenMP directives. We describe the development and optimization process and demonstrate the performance impact of various code modifications. We show select profiling results from the Nvidia nvvp profiler to help others diagnose and overcome performance issues in their own applications. We present results for two compute systems endowed with Nvidia V100 accelerators.

Ioannis Nompelis↗

NASA NTRS2020

ATD-2 Benefits Mechanism

NASA has been developing and demonstrating a suite of decision support capabilities for integrated arrival, departure, and surface (IADS) operations in a metroplex environment. The effort is being made in three phases, under NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project, through a close partnership with the Federal Aviation Administration (FAA), air carriers, airport, and general aviation community. The Phase 1 Baseline IADS capabilities provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, tactical surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. The Phase 2 Fused IADS capabilities include the fusion of strategic and tactical surface metering, Atlanta Center airspace tactical scheduling, Electronic Flight Data (EFD) integration, Terminal Flight Data Manager (TFDM) Terminal Publication (TTP) prototype, and Mobile App for General Aviation (GA) community. In the Phase 2 field evaluation, strategic surface metering provides advance notice of metering and additional stability to the assigned gate holds. The users of the IADS system in Phases 1 and 2 include the personnel at Charlotte Douglas International Airport (CLT) air traffic control tower, American Airlines ramp tower, CLT terminal radar approach control (TRACON), and Washington and Atlanta Center. This document describes the ATD-2 benefits mechanism used to assess the Phases 1 and 2 IADS capabilities and field evaluation conducted at CLT since September 2017. The ATD-2 benefits mechanism mainly consists of surface metering and overhead stream insertion. This document provides detailed calculation methods of major benefit metrics, such as fuel savings, gas emissions savings, and engine runtime reduction, which can be obtained through surface metering, gate hold of Approval Request (APREQ) flights prior to pushback, and the renegotiation of release time while taxiing. As of March 31, 2020, it is estimated that 5,075,981 pounds of fuel savings and 15,634,022 pounds of CO2 emission reduction have been achieved so far, with a reduction of 3,832 hours in total engine runtime. The amount of CO2 savings is estimated to be equivalent to planting 116,254 urban trees. The pre- and post-metering comparison results using FAA’s Aviation System Performance Metrics (ASPM) data have also shown that the surface metering had no negative impact on the on-time arrival performance of both outbound and inbound flights at CLT.

ATD-2↗

NASA NTRS2020

ATD-2 Benefits Mechanism

NASA has been developing and demonstrating a suite of decision support capabilities for integrated arrival, departure, and surface (IADS) operations in a metroplex environment. The effort is being made in three phases, under NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project, through a close partnership with the Federal Aviation Administration (FAA), air carriers, airport, and general aviation community. The Phase 1 Baseline IADS capabilities provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, tactical surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. The Phase 2 Fused IADS capabilities include the fusion of strategic and tactical surface metering, Atlanta Center airspace tactical scheduling, Electronic Flight Data (EFD) integration, Terminal Flight Data Manager (TFDM) Terminal Publication (TTP) prototype, and Mobile App for General Aviation (GA) community. In the Phase 2 field evaluation, strategic surface metering provides advance notice of metering and additional stability to the assigned gate holds. The users of the IADS system in Phases 1 and 2 include the personnel at Charlotte Douglas International Airport (CLT) air traffic control tower, American Airlines ramp tower, CLT terminal radar approach control (TRACON), and Washington and Atlanta Center. This document describes the ATD-2 benefits mechanism used to assess the Phases 1 and 2 IADS capabilities and field evaluation conducted at CLT since September 2017. The ATD-2 benefits mechanism mainly consists of surface metering and overhead stream insertion. This document provides detailed calculation methods of major benefit metrics, such as fuel savings, gas emissions savings, and engine runtime reduction, which can be obtained through surface metering, gate hold of Approval Request (APREQ) flights prior to pushback, and the renegotiation of release time while taxiing. As of April 30, 2020, it is estimated that 5,097,173 pounds of fuel savings and 15,699,292 pounds of CO2 emission reduction have been achieved so far, with a reduction of 3,831 hours in total engine runtime. The amount of CO2 savings is estimated to be equivalent to planting 116,739 urban trees. The pre- and post-metering comparison results using FAA’s Aviation System Performance Metrics (ASPM) data have also shown that the surface metering had no negative impact on the on-time arrival performance of both outbound and inbound flights at CLT.

ATD-2↗

NASA NTRSDate not supplied

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗

NASA NTRSDate not supplied

NASA GLOBE Clouds: Matching your sky observations to multiple satellite data

Have you ever wondered how your view of the sky compares to satellite data? The NASA GLOBE Clouds team at NASA Langley Research Center in Hampton, VA, matches ground-cloud observations taken by citizen scientists through the GLOBE Program to geostationary satellites as well as to Terra, Aqua, and CALIPSO satellites. The result is the NASA GLOBE Clouds satellite match table sent in a NASA personalized email summarizing both ground-cloud and satellite observations. The table contains ground-cloud and satellite values of total cloud cover and cloud cover by height (low, mid, high), cloud opacity and cloud phase. The satellite match table also includes images from the respective satellites centered on the latitude and longitude of the ground-cloud report entered through the GLOBE Program. Participants can receive satellite flyover notifications for their location through the GLOBE Observer app or through the satellite flyover schedule. This presentation will engage the audience through a live demonstration showing how to access GLOBE Clouds data visualization tools and view corresponding satellite imagery and data. We will also discuss best practices suggested by classroom teachers and undergraduate professors in incorporating active learning and satellite data analysis.

Marilé Colón Robles↗

NASA NTRSDate not supplied

Adaptive Pressure Profile Method to Locate the Isolator Shock Train Leading Edge Given Limited Pressure Information

To maximize the performance of high-speed air-breathing engines, such as dual-mode scramjets, the streamwise location of the shock train leading edge (STLE) is ideally placed as far upstream in the isolator as possible while avoiding engine unstart. Thus, it is of interest to quantify and control the STLE location as the vehicle travels along its flight trajectory. The STLE location is typically quantified using wall static pressure measurements but there are often restrictions on the number and placement of transducers, thus reducing the accuracy and overall capability of STLE detection methods. In this work, the Adaptive Pressure Profile (APP) method is introduced to address such sparsity concerns. This method is data driven and does not heavily rely on prior information about the flow regime or engine model. Instead, the \mname method uses real-time pressure measurements from a small number of transducers to adaptively learn the isolator pressure profile. This adaptively-learned profile is fit to the pressure data at each time instance to estimate STLE location. The \mname method produces accurate estimates even when (1) the STLE location is not bounded by two or more transducers or (2) when the STLE location is between two transducers that are situated several duct heights apart. Data from two direct-connect isolator models are used to evaluate the accuracy of the \mname method and demonstrate its robustness for different back-pressure scenarios and transducer configurations.

Robin L Hunt↗

NASA NTRSDate not supplied

Adaptive Pressure Profile Method to Locate the Isolator Shock Train Leading Edge Given Limited Pressure Information

Robin Hunt↗

NASA NTRS2021

VESIcal Part I: An open-source thermodynamic model engine for mixed volatile (H2O-CO2) solubility in silicate melts

Thermodynamics has been fundamental to the interpretation of geologic data and modeling of geologic systems for decades. However, more recent advancements in computational capabilities and a marked increase in researchers’ accessibility to computing tools has outpaced the functionality and extensibility of currently available modeling tools. Here we present VESIcal (Volatile Equilibria and Saturation Identification calculator): the first comprehensive modeling tool for H 2 O, CO 2 , and mixed (H 2 O-CO 2 ) solubility in silicate melts that: a) allows users access to seven commonly used models, plus easy inter-comparison between models; b) provides universal functionality for all models (e.g., functions for calculating saturation pressures, degassing paths, etc.); c) can process large datasets (1,000’s of samples) automatically; d) can output computed data into an excel spreadsheet for simple post-modeling analysis; e) integrates advanced plotting capabilities directly within the tool; and f) provides all of these within the framework of a python library, making the tool extensible by the user and allowing any of the model functions to be incorporated into any other code capable of calling python. The tool is presented within this manuscript, which is a Jupyter notebook containing worked examples accessible to python users with a range of skill levels. The basic functions of VESIcal can also be access via a web app (https://vesical.anvil.app). The VESIcal python library is open-source and available for download at https://github.com/kaylai/VESIcal.

K. Iacovino↗

NASA NTRSDate not supplied

Splashdown Visualization of Spent Stages

The state of the art for many Earth-to-orbit trajectory analysis toolsets used at NASA is somewhat dated in terms of the languages they are written in and their user interfaces. Many of these programs are written in languages like Fortran or C that are no longer considered modern in the technology industry, and are command-line based without any means of interpreting the data outputs. This presentation is meant to demonstrate a specific use case for a newly developed web app that visualizes the output data for one of these tools. Specifically, one key usage is to investigate and validate launches for notional multi-stage vehicle concepts to various non-standard high-inclination orbits. Some NASA requirements dictate that trajectories be designed such that no surviving debris lands closer than 200 nautical miles (nm) from foreign landmasses or 27 nm from the continental United States, therefore validating re-entry locations of spent stages is an integral part of the launch planning process. In addition, at programmatic levels it can prove insightful and clarifying for the decision-making process to enhance the technical results of numerical simulations with visualizations. The intent with this tool is to provide the mission analyst and program level management with an intuitive and clear grasp of key information on possible mission scenarios either departing from or arriving at Earth, and in the future, the moon or Mars as well. The software tool was developed with an agile development approach and utilizes the latest frameworks and technologies. The front end uses the React JavaScript library for making a state of the art frontend and a backend based on the Django Python framework for handling data using Python’s powerful and free scientific libraries. In addition, the CesiumJS open-source library is key for visualizing these end-to-end trajectories on a high-resolution Earth model. The presentation will demonstrate the current capability and tested use cases.

Jack Agolli↗

NASA NTRS2021

GLOBE Observer and the GO on a Trail Data Challenge: A Citizen Science Approach to Generating a Global Land Cover Land Use Reference Dataset

Land cover and land use are highly visible indicators of climate change and human disruption to natural processes. While land cover is frequently monitored over a large area using satellite data, ground-based reference data is valuable as a comparison point. The NASA-funded GLOBE Observer (GO) program provides volunteer-collected land cover photos tagged with location, date and time, and, in some cases, land cover type. When making a full land cover observation, volunteers take six photos of the site, one facing north, south, east, and west (N-S-E-W) respectively, one pointing straight up to capture canopy and sky, and one pointing down to document ground cover. Together, the photos document a 100 meter square of land. Volunteers may then optionally tag each N-S-E-W photo with the land cover types present. Volunteers collect the data through a smartphone app, also called GLOBE Observer, resulting in consistent data. While land cover data collected through GLOBE Observer is ongoing, this paper presents the results of a data challenge held between June 1 and October 15, 2019. Called “GO on a Trail,” the challenge focused on collecting land cover observations at designated points along the Lewis and Clark National Historic Trail (LCNHT), which transects approximately 7,900 kilometers of the United States from east to west. The challenge also included an international component in which participants were recognized for the most data collected during the period. The challenge resulted in more than 2800 land cover data points from around the world with just over 900 land cover data points along the LCNHT. The data collected along the LCNHT is largely within a 1,000 meter corridor along the historic route. Internationally, the challenge had strong participation in Australia, where a Scouts Australia team-based competition was conducted in conjunction with GO on a Trail. GLOBE Observer collections can serve as reference data, ground truthing satellite imagery for the improvement and verification of broad land cover maps. Continued collection using this protocol will build a database documenting climate-related land cover and land use change into the future.

land cover↗

NASA NTRSDate not supplied

Towards Accurate and Efficient Predictions of Martensitic Transition Temperatures for Shape Memory Alloys from First Principles

Recent rapid progresses in physics theory and computational power have made it possible to predict the martensitic transition temperatures (MTTs) in shape memory alloys (SMAs) from first principles [1-3]. In particular, rigorous while time-consuming thermodynamic integration has been employed to compute the anharmonic phonon free energies, which play a crucial role in determining martensitic phase transitions in SMAs. However, this approach has only been applied to simple binaries, and its accuracy is unsatisfying for certain SMAs such as the most commonly used NiTi. In this work, we report on several new developments to our method that bring first-principles theory and experiment much closer into agreement including the MTT of NiTi, and that improve the computational efficiency significantly. We have applied our refined approach to investigate the Ni0.5Ti0.5-xHfx and PdxNi0.5-xTi0.5 ternaries, and the predicted MTT for each composition is within 100K compared with experiment. We will address various techniques to overcome the difficulty encountered in studying ternaries. Our theoretical approach is expected to be a broadly applicable and predictive theory for designing complex SMAs with desirable properties. [1] J.B. Haskins, A.E. Thompson,and J.W. Lawson, Phys. Rev B 94, 214110 (2016). [2] J.B. HaskinsandJ.W. Lawson, J. App. Phys. 121, 205103 (2017). [3] J.B. Haskins, H. Malmir, S. J. Honrao, L. A. Sandoval, and J.W. Lawson, Acta Materialia 212, 116872 (2017).

Zhigang Wu↗