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At least 487 records · Page 27

Analyses of circular solutions for advanced plastics waste recycling

A circular plastics economy can leverage the lightweight, strong and durable characteristics of macromolecular materials, while simultaneously reducing the negative environmental impacts associated with polymer waste. Advanced recycling technologies provide an opportunity to valorize plastics waste and extend the lifespan of these materials by converting waste into new monomers, polymers or specialty chemicals. Although many advanced technologies appear promising, assessments of economic and environmental sustainability are often not conducted in a standardized fashion and neglect factors such as plastics waste transportation, sorting and pretreatment. These shortcomings can lead to inaccurate or misleading predictions, reduce opportunities for optimization and limit industrial relevance. In this Review, we highlight select industrial case studies to underscore the notable consequences of underestimating the complexity of real-life consumer plastics waste. In addition, the current challenges associated with the assessment of the industrial viability of laboratory-scale processes are explored. Here, by discussing relevant analysis frameworks and system boundaries, along with potential analytical pitfalls, future research will be guided beyond chemical considerations and toward impactful circular solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗

Microbial inoculants for soil restoration: A Risk-Proportional Stewardship Framework Integrating Strain-Resolved Genomics and Adaptive Governance

Global soil degradation and increasing reliance on chemical inputs threaten agricultural sustainability, driving interest in microbial inoculants as tools for soil restoration. These biological products have the potential to enhance nutrient cycling, improve soil structure, and support plant resilience, but their environmental release raises important safety and stewardship considerations. Here, we propose a risk-proportional framework for the responsible deployment of microbial inoculants grounded in release-based stewardship. The framework integrates genome-resolved strain identification, exclusionary hazard screening, bioassay-based risk triage, ecological testing under realistic conditions, and monitored field deployment. Drawing on evidence from microbial ecology and invasion biology, we highlight how inoculants can alter resident microbial communities, influence ecosystem function, and, in some cases, facilitate gene flow, underscoring the need for risk assessment. We further outline a federated, genome-informed data infrastructure to support traceability, cross-jurisdiction learning, and adaptive management. Together, this approach provides a scalable and scientifically grounded pathway to balance innovation and safety, enabling microbial technologies to contribute to soil restoration and climate-resilient agriculture.

Edlund, Anna [OATH Inc]↗

GridSTIX

SF-25-112 Grid-STIX is a comprehensive extension of the STIX (Structured Threat Information Expression) 2.1 ontology specifically designed for electrical grid cybersecurity applications. This ontology provides a standardized, machine-readable framework for modeling grid assets, operational technology devices, threats, vulnerabilities, supply chain risks, and security relationships in electrical power systems. ## Key Features - **Comprehensive Grid Coverage**: Physical assets, OT devices, grid components, sensors, and energy storage systems - **Zero Trust Architecture**: Policy decision points, enforcement points, trust brokers, and continuous monitoring - **AMI Infrastructure**: Advanced metering networks, head-end systems, mesh gateways, and MDM systems - **Advanced Security Modeling**: Attack patterns, vulnerabilities, mitigations, and supply chain risks - **Critical Grid Relationships**: Power flow, protection, control, and synchronization relationships - **Supply Chain Security**: Supplier modeling, country of origin tracking, and risk assessment - **Protocol Support**: DNP3, Modbus, IEC 61850, IEC 60870-5-104, OPC-UA, and IEEE standards - **Python Code Generation**: Automated STIX-compliant Python class generation from ontologies - **Interactive Visualization**: Enhanced HTML network graphs with grid-specific categorization - **STIX 2.1 Compliance**: Full compatibility with STIX threat intelligence ecosystem

Blakely, Benjamin [Argonne National Laboratory (AN↗

Dynamic life-cycle carbon analysis for fast pyrolysis biofuel produced from pine residues: implications of carbon temporal effects

Abstract Background Woody biomass has been considered as a promising feedstock for biofuel production via thermochemical conversion technologies such as fast pyrolysis. Extensive Life Cycle Assessment studies have been completed to evaluate the carbon intensity of woody biomass-derived biofuels via fast pyrolysis. However, most studies assumed that woody biomass such as forest residues is a carbon–neutral feedstock like annual crops, despite a distinctive timeframe it takes to grow woody biomass. Besides, few studies have investigated the impacts of forest dynamics and the temporal effects of carbon on the overall carbon intensity of woody-derived biofuels. This study addressed such gaps by developing a life-cycle carbon analysis framework integrating dynamic modeling for forest and biorefinery systems with a time-based discounted Global Warming Potential (GWP) method developed in this work. The framework analyzed dynamic carbon and energy flows of a supply chain for biofuel production from pine residues via fast pyrolysis. Results The mean carbon intensity of biofuel given by Monte Carlo simulation across three pine growth cases ranges from 40.8–41.2 g CO 2 e MJ −1 (static method) to 51.0–65.2 g CO 2 e MJ −1 (using the time-based discounted GWP method) when combusting biochar for energy recovery. If biochar is utilized as soil amendment, the carbon intensity reduces to 19.0–19.7 g CO 2 e MJ −1 (static method) and 29.6–43.4 g CO 2 e MJ −1 in the time-based method. Forest growth and yields (controlled by forest management strategies) show more significant impacts on biofuel carbon intensity when the temporal effect of carbon is taken into consideration. Variation in forest operations and management (e.g., energy consumption of thinning and harvesting), on the other hand, has little impact on the biofuel carbon intensity. Conclusions The carbon temporal effect, particularly the time lag of carbon sequestration during pine growth, has direct impacts on the carbon intensity of biofuels produced from pine residues from a stand-level pine growth and management point of view. The carbon implications are also significantly impacted by the assumptions of biochar end-of-life cases and forest management strategies.

09 BIOMASS FUELS↗

Acoustic Tomography of the Atmosphere: A Large-Eddy Simulation Sensitivity Study

Accurate measurement of atmospheric turbulent fluctuations is critical for understanding environmental dynamics and improving models in applications such as wind energy. Advanced remote sensing technologies are essential for capturing instantaneous velocity and temperature fluctuations. Acoustic tomography (AT) offers a promising approach that utilizes sound travel times between an array of transducers to reconstruct turbulence fields. This study presents a systematic evaluation of the time-dependent stochastic inversion (TDSI) algorithm for AT using synthetic travel-time measurements derived from large-eddy simulation (LES) fields under both neutral and convective atmospheric boundary-layer conditions. Unlike prior work that relied on field observations or idealized fields, the LES framework provides a ground-truth atmospheric state, enabling quantitative assessment of TDSI retrieval reliability, sensitivity to travel-time measurement noise, and dependence on covariance model parameters and temporal data integration. A detailed sensitivity analysis was conducted to determine the best-fit model parameters, identify the tolerance thresholds for parameter mismatch, and establish a maximum spatial resolution. The TDSI algorithm successfully reconstructed large-scale velocity and temperature fluctuations with root mean square errors ( RMSE s) below 0.35 m/s and 0.12 K, respectively. Spectral analysis established a maximum spatial resolution of approximately 1.4 m, and reconstructions remained robust for travel-time measurement uncertainties up to 0.002 s. These findings provide critical insights into the operational limits of TDSI and inform future applications of AT for atmospheric turbulence characterization and system design.

17 WIND ENERGY↗

Overview of NASA ISRU Plans, Priorites, and Activities

Introduction:The National Aeronautics andSpace Administration (NASA) of the United States ofAmerica (US) has initiated the Artemis Moon to Marsprogram to send astronauts (the first woman andperson of color) back to the lunar surface, create asustainable human lunar exploration program, andlead the first human exploration mission to the Marssurface in the 2030’s [1]. A major objective of thisprogram is to characterize the resources that exist onthe Moon and Mars, and learn how to utilize them forsustained and affordable exploration. Commonlyknown as In Situ Resource Utilization (ISRU), thesearch for, acquisition, and processing of resources inspace has the potential to greatly reduce thedependency on transporting mission consumables andinfrastructure from Earth, thereby reducing missioncosts, risks, and dependency on Earth.ISRU is Enabling: Through the extraction andprocessing of resources into mission commoditiessuch as rocket propellants, life support consumables,and fuel cell reactants, ISRU enhances and evolvesthe cis-lunar, lander, and surface transportationsystems required for human exploration; expandingand enhancing HOW humans can explore and returnfrom the Moon. Through the extraction andprocessing of resources into metals, silicon, and othermanufacturing and construction feedstock, ISRUenhances and allows for the expansion of criticalinfrastructure using in situ manufacturing andconstruction capabilities that influence WHAT humanscan do on the Moon and in cis-lunar space. Becauseof this, ISRU supports and enables commercialinvolvement beyond NASA and governmentalagencies by both lowering the cost of sustainedtransportation to/from/on the Moon as well assupporting the market required for needing thesetransportation systems. Strategic Framework:To achieve this vision,NASA’s Space Technology Mission Directorate(STMD) ensures the coordinated development ofISRU and other critical space and surfaceinfrastructure elements such as propulsion, power,manufacturing, construction, and robotics through theStrategic Technology Architecture Roundtable(STAR) process. Through STAR, an integratedframework and process has been created allowing forcapabilities and technologies to be linked andassessed, gaps to be identified, specifications andmetrics to be established, and provide a means toprioritize and implement technology development andmissions. A critical part of the STAR effort has beenthe establishment of the Strategic Framework thatorganizes all work under four major Thrusts (Go,Land, Live, and Explore) and identifies the drivingOutcomes for each of these Thrusts. From the Thrustsand Outcomes, all work can be categorized and linkedbetween Capability Areas, and Technology Gaps canbe identified and addressed (Figure 1.)Figure 1. Strategic Framework and STAR FrameworkISRU Envisioned Future: To drive thedevelopment of technologies and capabilities, theSTAR process starts with establishing a ‘grand vision’of where each Outcome and Capability is aiming tobe considered complete. For ISRU, the EnvisionedFuture is “Scalable ISRU production/utilizationcapabilities including sustainable commodities on thelunar and Mars Surface”. This involves starting with10’s of metric tons of products, but evolves into 100’sto 1000’s of metric tons of water, oxygen, propellants,construction and manufacturing feedstock, andcommodities for habitat and food production andoperations. For ISRU, the ‘Prospect to Product’philosophy starts with Destination Reconnaissance &Resource Assessment, followed by ResourceAcquisition, Isolation, and Preparation, leading intoResource Processing (which is further subdivided intomission consumables and feedstocks for constructionand manufacturing). The ISRU Envisioned Futurealso considers what resources are available andattempts to address what and when these resourceswill be evaluated and harnessed, as well asconsidering which products/commodities can beobtained for early use and which ones require moretime and/or users of refined products.It Takes an Architecture: ISRU does not existon its own. By definition, it requires customers/users SHORT TITLE HERE: A. B. Author and C. D. Authorto use the products/commodities produced by ISRUsystems. Also, for an ISRU capability to exist, itmust obtain products and services from other systemsand infrastructure. An important aspect of the STARprocess and the ISRU Envisioned Futures Prioritiesstrategy is to identify and link all of these systems andcapabilities to achieve the desired end state (Figure2).Figure 2. ISRU as Part of a Larger ArchitectureISRU Capability Drivers: The guidingprinciples for NASA’s Space TechnologyDevelopment for Artemis are to develop criticaltechnologies and capabilities that enable (i) asustainable Lunar surface presence, (ii) the future goalof sending humans to Mars, and (iii) promotingcritical technologies to enable future science andcommercial missions. It is a major goal of theArtemis campaign to establish some sort of base campat the lunar South Pole by approximately the end ofthe decade. The ISRU Envisioned Futures Prioritiesstrategy is aligned with the Artemis campaign todevelop and demonstrate ISRU capabilities in thistimeframe that could lead to sustained surfaceoperations, infrastructure growth, and commercialoperations in the next decade (Figure 3).Figure 3. ISRU Dual Path to Full Implementation and CommercializationState of the Art and Gaps: To achieve theenvisioned future, an extensive effort was performedto understand the State of the Art (SOA) for ISRUgoing back decades, and to assess the SOA against thenear and long-term goals and objectives of the ISRUStrategic Outcome objectives. While the releasedISRU Envisioned Futures Priorities only includes atop-level definition of both the SOA and Gaps, furtherinformation on these for ISRU can be found in theISRU Gap Assessment Study performed for theInternational Space Exploration Coordination Group(ISECG) [2]. To provide further guidance to industryand academia, a top level assessment was performedand provide that divides critical areas of ISRUcapabilities and technologies into 3 categories:Significant Funding, Partially Covered/MoreRequired, and Limited/No Funded Activities.Envisioned Future Priorities- Next Steps forISRU: While a significant amount of work over abroad range of technology areas has been performedover the last several years for lunar ISRU, to reach theenvisioned future for ISRU, a lot more work isrequired at the technology level leading to bothsystems and technology demonstrations in the nearfuture. To guide investments within NASA, industry,and academia, 5 specific areas of high priority wereidentified. These are:1.Complete development of the Water and Oxygen Mining Paths and close technology gaps, with emphasis on oxygen extraction from Highland regolith and parallel paths for polar water mining.2.Expand development of metal extraction and feedstock for manufacturing and construction, with emphasis on aluminum and initial/easy to obtain/make construction feedstocks leading to more refined metals and other regolith resources. Also, evaluate biologically inspired/derived technologies in bio-mining, bio-plastic, and other feedstock commodities.3.Ensure the resource assessment needed for future ISRU commercial operations is coordinated with both near/long-term science objectives as well as Artemis mission locations of interest.4.Initiate NASA and industry-led system-level analyses, integration, and testing activities for ISRU capabilities. While significant work has been performed at the technology and subsystemlevel, it is now important to understand how these technology investments can be leveraged and utilized in actual systems and applications5.Initiate lunar ISRU technology flight demonstrations leading to initial ‘Pilot Plant’ end-to-end production capability demonstrations, led by industry

ISRU↗

A Multi-Dimensional Benefit Assessment of Automated Mobility Platforms (AMP) for Large Facilities: Mobility, Energy, Equity, and Facility Management & Design

The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability - both of which are important metrics often overlooked during the engineering design process. Therefore, to evaluate systems and inform critical near- and long-term decisions more effectively, a holistic evaluation framework is proposed focused on four key areas: (1) mobility, with emphasis on travel time and accessibility within an airport, (2) environment, focused on energy consumption and greenhouse gas (GHG) emissions associated with intra-airport mobility, (3) equity, specifically to the PRM community, but with an eye to the whole of society, and (4) built environment, or the fundamental changes in building design enabled by different mobility systems for larger and more flexible, functional, and energy-efficient structures. Below, AMPs are defined, and each metric is discussed further, all with a focus on airport mobility.

ADVANCED PROPULSION SYSTEMS↗

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis

Solar photovoltaics (PV) are the fastest growing renewable energy technology for clean, inexpensive, and sustainable electricity generation. Along with numerous technical roadmaps to improve system cost, performance and reliability, the PV industry should also plan to handle large volumes of silicon panel waste, which is initially estimated to be ~13 million metric tons (MT) by 2050 in the U.S. alone. Understanding the magnitude of material needs and how material flows throughout the PV panel life cycle could respond to design, operational and different end-of-life (EOL) circular pathways will help transition into a circular, resource-conserving economy. Herein, we introduce a dynamic material flow analysis (DMFA) framework based on electricity generation to quantify time-series stocks and flows of bulk PV materials (e.g., solar glass and aluminum frames) throughout the life cycles of utility-scale silicon PV systems in the U.S. in the period 2000-2100. We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacial, frameless). We found that float glass and aluminum in PV installations would likely reach 100 million MT and 12 million MT by 2100, respectively, in the baseline scenario. The most influential parameters for PV installation and subsequent waste reduction are found to be module lifetime, module efficiency, annual degradation, and material reduction. Module recycling and component remanufacturing were found to be the most effective material circularity strategies for waste minimization. Panel reuse has negligible savings on waste under current module efficiencies compared to replacements with newer generations with higher efficiency. Ongoing trends to produce larger power frameless modules could save 10 million MT of glass and ~9 million MT of aluminum. Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize waste.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploring acute weather resilience: Meeting resilience and renewable goals

We report the United States is affected by an average of almost seven severe weather events a year, often resulting in billions of dollars in physical and economic damages, a subset of which are related to grid outages. There is a need for power and energy system stakeholders to better understand and implement the strategies that help reduce net-economic and societal consequences associated with grid outages by improving the resilience of their systems. In addition, there are incentives to reduce emissions and meet climate goals, several pathways of which include resilient technologies. Including resilience constraints and metrics in energy system planning models may help inform the design of more resilient systems that are also more renewable and sustainable. This paper reviews qualitative definitions of resilience, quantitative approaches to resilience, recent examples of the inclusion of resilience in energy system models with respect to acute climatological threats, and the gaps in fully articulating resilience in current modeling tools. We then outline steps to effectively improve resilience considerations against such threats into energy sector modeling tools. Based on the findings, the authors propose a novel framework for energy system resilience assessment and future areas of research to bridge the current modeling gaps.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Systems Analysis Approach to Polyethylene Terephthalate and Olefin Plastics Supply Chains in the Circular Economy: A Review of Data Sets and Models

The environmental and economic impacts of implementing a circular economy in plastic waste supply chains are not well understood. The proposed systems analysis framework assesses environmental, social, and economic impacts of plastic waste supply chains in a circular economy. The first objective of this article is to identify datasets, models and knowledge gaps associated with waste plastic supply chain processes, mainly in the U.S. Our literature review indicated that the best datasets exist for virgin plastic resin production, mechanical recycling, landfilling, and incineration, with materials recovery facility being intermediate, and with chemical recycling the lowest. The second objective of this article is to develop an illustrative application of the framework by conducting a preliminary systems analysis of PET bottles with closed-loop recycling. Here, the preliminary systems analysis of PET bottles utilized a linear programming optimization method. Our optimization model indicated that both chemical and mechanical recycling processes are needed to achieve a true circular economy of PET bottles with the least greenhouse gas emissions, specifically reductions of 24% when compared with the linear economy. Good quality and standardized life cycle assessment and techno-economic analysis studies are needed to better understand the environmental, economic, and social impacts of advanced sorting and chemical recycling technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models

Low-temperature plasmas have quickly emerged as alternative and unconventional types of radiation that offer great promise for various clinical modalities. As with other types of radiation, the therapeutic efficacy and safety of low-temperature plasmas are ubiquitous concerns, and assessing their dose rates is crucial in clinical settings. Unfortunately, assessing the dose rates by standard dosimetric techniques has been challenging. To overcome this difficulty, we proposed a dose-rate assessment framework that combined the predictive modeling of plasma-induced damage in DNA by machine learning with existing radiation dose-DNA damage correlations. Our results indicated that low-temperature plasmas have a remarkably high dose rate that can be tuned by various process parameters. This attribute is beneficial for inducing radiobiological effects in a more controllable manner.

59 BASIC BIOLOGICAL SCIENCES↗

A Circularity Assessment for Silicon Solar Panels Based on Dynamic Material Flow Analysis: Preprint

Solar photovoltaics (PV) are the fastest growing renewable energy technology for clean, inexpensive, and sustainable electricity generation. Along with numerous technical roadmaps to improve system cost, performance and reliability, the PV industry should also plan to handle large volumes of silicon panel waste, which is initially estimated to be ~13 million metric tons (MT) by 2050 in the U.S. alone. Understanding the magnitude of material needs and how material flows throughout the PV panel life cycle could respond to design, operational and different end-of-life (EOL) circular pathways will help transition into a circular, resource-conserving economy. Herein, we introduce a dynamic material flow analysis (DMFA) framework based on electricity generation to quantify time-series stocks and flows of bulk PV materials (e.g., solar glass and aluminum frames) throughout the life cycles of utility-scale silicon PV systems in the U.S. in the period 2000-2100. We apply the model to a range of scenarios to understand how material demands depend on selected PV-related parameters, different material circularity strategies, and recent module design trends (e.g., bifacial, frameless). We found that float glass and aluminum in PV installations would likely reach 100 million MT and 12 million MT by 2100, respectively, in the baseline scenario. The most influential parameters for PV installation and subsequent waste reduction are found to be module lifetime, module efficiency, annual degradation, and material reduction. Module recycling and component remanufacturing were found to be the most effective material circularity strategies for waste minimization. Panel reuse has negligible savings on waste under current module efficiencies compared to replacements with newer generations with higher efficiency. Ongoing trends to produce larger power frameless modules could save 10 million MT of glass and ~9 million MT of aluminum. Our results enable advanced planning for future materials needs and provide insight into potential opportunities to minimize waste.

circular economy↗

Energy storage planning for enhanced resilience of power systems against wildfires and heatwaves

Extreme weather events pose significant risks to power grid stability due to their severe consequences and potential for widespread failures. Energy storage systems hold great potential for enhancing grid resilience against such events by providing reliable power during peak demand periods. However, accurately quantifying the size, location, and investment costs of new energy storage assets is a complex task, as energy storage planning decisions depend on the investment choices of other generation technologies and the integration of new transmission projects. Here, this paper presents a novel capacity expansion planning framework that simultaneously optimizes investments in energy storage, generation, and transmission, determining their optimal size, location, and type, while incorporating extreme weather events into long-term planning. More specifically, our stress-event-informed planning framework integrates the impact of heatwaves and wildfires into the planning process, identifying least-cost investment solutions that comply with policy goals and enhance grid resilience. The proposed framework employs machine-learning-based modeling to project heatwave-induced loads and performance-based risk assessment to evaluate wildfire-driven transmission line derates. Using industry-standard datasets to accurately represent the transmission topology of the Western Interconnection (WI) system, the proposed framework is applied to the WI 40-zone system, with investment decisions reported for the years 2030, 2035, and 2040. Simulation results reveal that with just a 10% increase in investment costs, resilience against extreme events can be significantly improved, with investment decisions heavily favoring energy storage, particularly 4-hour energy storage systems.

25 ENERGY STORAGE↗

Toward a Climate OSSE Framework for Satellite Mission Design

The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here, we outline a new framework for climate OSSEs that leverages the use of machine learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA’s GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth’s planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations.

54 ENVIRONMENTAL SCIENCES↗

Safety Metrics for Human-Computer Controlled Systems

The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems.This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

Leveson, Nancy G↗

The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

tectonic processes↗

Analysis and Optimization of Baseline Single Aisle Aircraft for Future Electrified Powertrain Flight Demonstrator Comparisons

The purpose of this study is to provide baseline single-aisle vehicles for future comparisons with NASA’s Electrified Powertrain Flight Demonstration (EPFD) turbofan-powered Vision Systems. State-of-the-art single-aisle transports with varying design capacities of 100 to 150 passengers are modeled using NASA Ames Research Center’s General Aviation Synthesis Program (GASP) as well as GASPy. GASPy is a modernized Python-based version of GASP built on the OpenMDAO framework to allow for future, efficient gradient-based optimization and coupled airframe-propulsion design. In order to meet projected NASA Aeronautics goals for 2035, advanced aircraft technologies must be incorporated into these vehicle systems. Methodology to parametrically infuse baseline aircraft models with advanced technologies simulating improvements in aerodynamics, structures, and propulsion systems is detailed, along with the results of technology sensitivity studies. Comparison of the baseline and advanced configurations will allow for future analysis of the benefits of future hybrid and fully electric aircraft concepts in the EPFD project, where fuel consumption and emissions will be modeled and assessed. This study has been conducted under the EPFD project to establish benchmark turbofan models and demonstrate System Analysis capabilities in multi-disciplinary aircraft design, analysis, and optimization for advanced turbofan concepts.

Carl J. Recine↗