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At least 253 records · Page 14

Enhancing Systems Engineering Education Through Case Study Writing

Developing and refining methods for teaching systems engineering is part of Systems Engineering grand challenges and agenda for research in the SE research community. Retention of systems engineering knowledge is a growing concern in the United States as the baby boom generation continues to retire and the faster pace of technology development does not allow for younger generations to gain experiential knowledge through years of practice. Government agencies, including the National Aeronautics and Space Administration (NASA), develop their own curricula and SE leadership development programs to "grow their own" systems engineers. Marshall Space Flight Center (MSFC) conducts its own Center-focused Marshall Systems Engineering Leadership Development Program (MSELDP), a competitive program consisting of coursework, a guest lecture series, and a rotational assignment into an unfamiliar organization engaged in systems engineering. Independently, MSFC developed two courses to address knowledge retention and sharing concerns: Real World Marshall Mission Success course and its Case Study Writers Workshop and Writers Experience. Teaching case study writing and leading students through a hands-on experience at writing a case study on an SE topic can enhance SE training and has the potential to accelerate the transfer of experiential knowledge. This paper is an overview of the pilot experiences with teaching case study writing, its application in case study-based learning, and identifies potential areas of research and application for case study writing in systems engineering education.

Stevens, Jennifer Stenger↗

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/Departure/Surface (IADS) System Demonstration, Technology Transfer Document Summary (ReadMe)

Airspace Technology Demonstration - 2 (ATD-2) is part of NASA's Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and the operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and key industry stakeholders. This summary document and accompanying artifacts satisfy the first of three Research Transition Products (RTPs) defined in the IADS Research Transition Team (RTT) Plan. This transfer consists of NASA's ATD-2 Phase 1 Baseline IADS System capabilities.

IADS↗

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/ Departure/Surface (IADS) System Demonstration Technology Transfer Document Summary (ReadMe) Version 2 - Phase 2 Fused IADS

Airspace Technology Demonstration 2 (ATD-2) is part of NASA's Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the second of three research transition products (RTPs) defined in the IADS research transition team (RTT) plan. This transfer consists of NASA's ATD-2 Phase 1 Baseline IADS and Phase 2 Fused IADS system capabilities

Capps, Alan↗

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/Departure/Surface (IADS) System Demonstration - Technology Transfer Document Summary (ReadMe) (Version 2.5 - Initial Phase 3 Metroplex IADS)

Airspace Technology Demonstration – 2 (ATD-2) is part of NASA’s Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the next delivery of research transition products (RTPs) defined in the IADS research transition team (RTT) plan. With the ATD-2 project extended for another year, this Tech Transfer 2.5 constitutes an interim delivery of artifacts from the Phase 3 field demonstration. The final Phase 3 tech transfer delivery is planned for August 2021.

ATD-2, IADS, Phase 3, tech transfer↗

Airspace Technology Demonstration 2 (ATD-2): Integrated Arrival/ Departure/Surface (IADS) System Demonstration - Technology Transfer Document Summary (ReadMe)Version 3 (Final Phase 3 Metroplex IADS)

Airspace Technology Demonstration – 2 (ATD-2) is part of NASA’s Airspace Technology Demonstrations (ATD) Project under its Airspace Operations and Safety Program (AOSP). ATD-2 is a multi-year research and development effort to improve the predictability and operational efficiency of the air traffic system in metroplex environments while maintaining or improving throughput by enhancing and integrating arrival, departure, and surface prediction, scheduling, and management systems. In order to ensure that the products of this knowledge and technology transfer are relevant and useful, NASA has created strong partnerships with the FAA and industry stakeholders. This summary document and accompanying artifacts satisfy the final delivery of research transition products (RTPs) defined in the IADS research transition team (RTT) plan.

ATD-2↗

Renewable electricity storage using electrolysis

Electrolysis converts electrical energy into chemical energy by storing electrons in the form of stable chemical bonds. The chemical energy can be used as a fuel or converted back to electricity when needed. Water electrolysis to hydrogen and oxygen is a well-established technology, whereas fundamental advances in CO 2 electrolysis are still needed to enable short-term and seasonal energy storage in the form of liquid fuels. This paper discusses the electrolytic reactions that can potentially enable renewable energy storage, including water, CO 2 and N 2 electrolysis. Recent progress and major obstacles associated with electrocatalysis and mass transfer management at a system level are reviewed. We conclude that knowledge and strategies are transferable between these different electrochemical technologies, although there are also unique complications that arise from the specifics of the reactions involved.

25 ENERGY STORAGE↗

Spatial Transferability of Machine Learning Based Volume Estimation Models

High-quality traffic volume data is essential for efficient transportation planning and operations. However, such high-quality data is expensive to collect, owing primarily to the high capital cost of installing and maintaining continuous counting stations (CCSs). Recent availability of probe-based vehicle data offers a cost-effective solution for increasing the observability of traffic volumes. However, having ample ground truth traffic data is a prerequisite for developing robust volume estimation models. Though this might not be a big issue in many states, states with scarce CCS data might be able to benefit from robust volume estimation models developed in (adjacent) data-rich states. While there is a reasonable amount of spatial transferability research in the transportation domain, there is a dearth of knowledge on the spatial transferability of probe-based volume estimation models. To address this gap, this paper explores spatial transferability of volume estimation models developed from data in three states (Colorado, North Carolina, and Pennsylvania). Results indicate that it is extremely important to maintain temporal consistency when attempting spatial transferability of volume estimation models. It was also found that models trained on regions with lower peak traffic volumes will limit the performance of models transferred to states with higher peak hourly traffic volumes. Corroborating findings from existing spatial transferability research on other topics, it was found that a meta-model (developed using data from multiple states) performs better than volume estimation models developed within any one of the states.

ADVANCED PROPULSION SYSTEMS↗

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 river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

Abstract A unified conceptual framework for river corridors requires synthesis of diverse site‐, method‐ and discipline‐specific findings. The river research community has developed a substantial body of observations and process‐specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site‐, scale‐, and mechanism‐specific observations begins the process of synthesis. Machine learning is particularly well‐suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a fifth order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively‐generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favour the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery.

54 ENVIRONMENTAL SCIENCES↗

Temporal evolution of Pu and Cs sediment contamination in a seasonally stratified pond

There remains a lack of knowledge regarding ecosystem transfer, transport processes, and mechanisms, which influence the long-term mobility of Pu-239 and Cs-137 in natural environments. Monitoring the distribution and migration of trace radioisotopes as ecosystem tracers has the potential to provide insight into the underlying mechanisms of geochemical cycles. This study investigated the distribution of anthropogenic radionuclides Pu-239 and Cs-137 along with total organic carbon, iron, and trace element in contaminated sediments of Pond B at the Savannah River Site (SRS). Pond B received reactor cooling water from 1961 to 1964, and trace amounts of Pu-239 and Cs-137 during operations. Our study collected sediment cores to determine concentrations of Pu-239, Cs-137, and major and minor elements in solid phase, pore water and an electrochemical method was used on wet cores to determine dissolved elemental concentrations. More than 50 years after deposition, Pu-239 and Cs-137 in sediments are primarily located in the upper 5 cm in area where deposition of particulate-bound contaminants was prevalent and located between 5 and 10 cm in areas of high sedimentation, showing a limited migration of Pu-239 and Cs-137. A Factor analysis demonstrated different sediment facies across the pond resulting in a range of geochemical processes controlling accumulation of Pu and Cs. Highest concentrations appear to be controlled by particulate input from the influent canal, dominated by clay, silt, and sand minerals bearing Fe. Elevated Pu-239 in the sediments were observed in areas with high organic matter and higher deposition rate relative to the Pond B system near the outlet indicating strong association of Pu with OM and particulates. Therefore, organic matter cycling likely plays a role in Pu redistribution between sediment and overlying pond water, and deposition in organic rich sediments accumulating near the outlet. Though Pu appears to have been distributed throughout the pond, Cs-137 concentrations remained the highest near the influent canal.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Round Robin Measurements of Molten Salt Properties for LiF-NaF-KF (FLiNaK) and NaCl-KCl Mixtures

The development, operation, and regulation of nuclear reactors that utilize molten salts as fuel or as heat transfer media require knowledge of the thermal properties of the salt systems and quantification of the corresponding uncertainties. Knowledge of molten salt properties is also necessary for applications in material synthesis, processing, separations, solar thermal power generation, and energy storage. A round robin was conducted with national laboratory and university participants from twenty-one laboratories in five countries to compare property measurements, to better understand uncertainties, and to identify possible best practices. Two salt mixtures, each from a common batch, were distributed to participants for evaluation: equimolar NaCl-KCl and 45.0LiF-13.7NaF-41.3KF mol % (FLiNaK). Measurements were performed to determine the major constituent composition, oxygen content, density, thermal expansivity, melting point, and thermal conductivity. Error analysis was performed on each measurement for uncertainty quantification for each type of property that was explored. Finally, the resulting discussion of the methodologies used in this work is meant to lay the groundwork for the development of standard methods and reference materials for future high-temperature property measurements on halide melts.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

LAN: A Materials Notation for Two-Dimensional Layered Assemblies

Two-dimensional (2D) layered materials offer intriguing possibilities for novel physics and applications. Before any attempt at exploring the materials space in a systematic fashion, or combining insights from theory, computation, and experiment, a formal description of information about an assembly of arbitrary composition is required. Here, we introduce a domain-generic notation that is used to describe the space of 2D layered materials from monolayers to twisted assemblies of arbitrary composition, existent or not yet fabricated. The notation corresponds to a theoretical materials concept of stepwise assembly of layered structures using a sequence of rotation, vertical stacking, and other operations on individual 2D layers. Its scope is demonstrated with several example structures using common single-layer materials as building blocks. This work overall aims to contribute to the systematic codification, capture, and transfer of materials knowledge in the area of 2D layered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomically dispersed metal–nitrogen–carbon catalysts for fuel cells: advances in catalyst design, electrode performance, and durability improvement

The urgent need to address the high-cost issue of proton-exchange membrane fuel cell (PEMFC) technologies, particularly for transportation applications, drives the development of simultaneously highly active and durable platinum group metal-free (PGM-free) catalysts and electrodes. The past decade has witnessed remarkable progress in exploring PGM-free cathode catalysts for the oxygen reduction reaction (ORR) to overcome sluggish kinetics and catalyst instability in acids. Among others, scientists have identified the newly emerging atomically dispersed transition metal (M: Fe, Co, or/and Mn) and nitrogen co-doped carbon (M–N–C) catalysts as the most promising alternative to PGM catalysts. Here, we provide a comprehensive review of significant breakthroughs, remaining challenges, and perspectives regarding the M–N–C catalysts in terms of catalyst activity, stability, and membrane electrode assembly (MEA) performance. A variety of novel synthetic strategies demonstrated effectiveness in improving intrinsic activity, increasing active site density, and attaining optimal porous structures of catalysts. Rationally designing and engineering the coordination environment of single metal MN x sites and their local structures are crucial for enhancing intrinsic activity. Increasing the site density relies on the innovative strategies of restricting the migration and agglomeration of single metal sites into metallic clusters. Relevant understandings provide the correlations among the nature of active sites, nanostructures, and catalytic activity of M–N–C catalysts at the atomic scale through a combination of experimentation and theory. Current knowledge of the transferring catalytic properties of M–N–C catalysts to MEA performance is limited. Rationally designing morphologic features of M–N–C catalysts play a vital role in boosting electrode performance through exposing more accessible active sites, realizing uniform ionomer distribution, and facilitating mass/proton transports. We outline future research directions concerning the comprehensive evaluation of M–N–C catalysts in MEAs. The most considerable challenge of current M–N–C catalysts is the unsatisfied stability and rapid performance degradation in MEAs. Therefore, we further discuss practical methods and strategies to mitigate catalyst and electrode degradation, which is fundamentally essential to make M–N–C catalysts viable in PEMFC technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exascale Storage Systems the SIRIUS Way

As the exascale computing age emerges, data related issues are becoming critical factors that determine how and where we do computing. Popular approaches used by traditional I/O solution and storage libraries become increasingly bottlenecked due to their assumptions about data movement, re-organization, and storage. While, new technologies, such as "burst buffers", can help address some of the short-term performance issues, it is essential that we reexamine the underlying storage and I/O infrastructure to effectively support requirements and challenges at exascale and beyond. In this paper we present a new approach to the exascale Storage System and I/O (SSIO), which is based on allowing users to inject application knowledge into the system and leverage this knowledge to better manage, store, and access large data volumes so as to minimize the time to scientific insights. Central to our approach is the distinction between the data, metadata, and the knowledge contained therein, transferred from the user to the system by describing "utility" of data as it ages.

97 MATHEMATICS AND COMPUTING↗

Transformer quantum state: A multipurpose model for quantum many-body problems

Here, inspired by the advancements in large language models based on transformers, we introduce the transformer quantum state (TQS): a versatile machine learning model for quantum many-body problems. In sharp contrast to Hamiltonian/task specific models, TQS can generate the entire phase diagram, predict field strengths with experimental measurements, and transfer such a knowledge to new systems it has never been trained on before, all within a single model. With specific tasks, fine-tuning the TQS produces accurate results with small computational cost. Versatile by design, TQS can be easily adapted to new tasks, thereby pointing towards a general-purpose model for various challenging quantum problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DAWN: Dashboard for Agricultural Water Use and Nutrient Management—A Predictive Decision Support System to Improve Crop Production in a Changing Climate

Abstract Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Meteorology & Atmospheric Sciences↗

Phase Transformation Kinetics and Alloy Microsegregation in High Pressure Die Cast Magnesium Alloys (Final Report)

The primary objective of this project is to conduct a systematic, quantitative study of phase transformation kinetics and microsegregation in HPDC Mg alloys in both as-cast and heat treated conditions. These results will be used to develop and validate physics-based phase transformation kinetics micro-models that quantitatively capture microstructural evolution and microsegregation during HPDC and heat treatment of Mg alloys. Finally, this knowledge will be transferred to industry and the wider research community through these micro-models and the experimental data that will be stored in the National Institute of Standards and Technology (NIST)-DOE Energy Efficiency and Renewable Energy Advanced Automotive Cast Magnesium Alloys Repository, as well as a new repository, the University of Michigan Department of Energy Predictive Integrated Structural Materials Science (UM DOE PRISMS) Materials Commons. To accomplish these goals, a systematic and comprehensive experimental study is being combined with computational modeling and simulation.

36 MATERIALS SCIENCE↗