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Using the EB approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.
Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval (IR): semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pre-trained sBERT model performs well out-of-the-box, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over a keyword search. Our use case throughout the paper is to use queries related to specific requirements from a NASA project. Fine tuning the sBERT model on LLIS data yields a mean average precision (MAP) of 0.807 on queries based on information needs from a real NASA project. Results indicate that applying state-of-the-art natural language processing techniques, especially when finetuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.
Running realistic simulations and developing algorithms for decision support tools usually require weather data access. This document describes the weather data service capability implemented in the Air Traffic Management (ATM) TestBed. The capability provides ways for querying weather data from the weather products provided by the National Aeronautics and Space Administration’s (NASA) Sherlock ATM Data Warehouse. Depending on use cases, weather data can be queried using a Java application programming interface, web data access, and map tile image access. Map tile images are generated using triangular meshes obtained using the Matching Squares contour algorithm. An analysis determines a grid size that will produce both high image quality and fast image rendering. In addition, the visualization of weather data as map tiles on a TestBed visualization tool called Traffic Viewer is presented.
To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.
As an extension of NETL's Fossil Energy Baseline for Electricity Generating Units Volume 1: Coal and Natural Gas to Electricity (FEB Rev 4a, this study develops cost and performance estimates for analogous NGCC cases using a state-of-the-art 2023 vintage H-Class CT in a 1×1 configuration, where a single combustion turbine and heat recovery steam generator are coupled to a single steam turbine on a common shaft. These 1×1 H-Class cases are used to develop cost and performance estimates of X-Class 1×1 NGCC cases with advanced performance characteristics, analogous to NETL’s cost and performance projections report.
A systematic approach is presented to constructing a radiation assurance case using Goal Structured Notation (GSN) for spacecraft containing COTS parts. The GSN paradigm is applied to an SRAM single-event upset experiment board designed to fly on a CubeSat November 2016. Construction of a radiation assurance case without use of hardened parts or extensive radiation testing is discussed.
The shipping industry contributes to a substantial quantity of global carbon emissions. Reaching a “Net-Zero World” will ultimately require complete decarbonization of the existing fleet. Nuclear energy may provide a viable solution toward this end goal. To better understand the economic dynamics of relying on nuclear energy to power maritime fleets, cost targets were identified in this study. Two use cases were considered: (1) nuclear energy is used to generate synthetic fuel (termed synfuel) to power maritime propulsion, and (2) nuclear reactors for vessel propulsion. The study found that in both cases realistic cost targets for nuclear reactor costs could be reached. However, option 2 was deemed to be much more competitive overall but with higher technical risks.
A systematic approach is presented to constructing a radiation assurance case using Goal Structuring Notation (GSN) for spacecraft containing commercial-off-the-shelf (COTS) parts. The GSN paradigm is applied to an SRAM single-event upset experiment board designed to fly on a CubeSat November 2016. Construction of a radiation assurance case without use of hardened parts or extensive radiation testing is discussed.
Reducing energy consumption and greenhouse gas emissions in the built environment is a critical step in achieving emission goals to mitigate climate change impacts. Local, federal, and international jurisdictions are deploying several methods to reduce energy and emissions such as voluntary and mandatory benchmarking and building performance standards, requiring building owners to reach energy and emission targets. Jurisdictions leveraging benchmarking and building performance standards require knowledge of the buildings covered; which is a large task due to staffing constraints, limited information on building characteristics and tax parcel data, and the need for advanced data management techniques to align datasets. This paper describes an open-source platform's recent advances to create consistent taxonomies, identify erroneous data, enable auditability, and track building performance. The paper concludes with two use cases on how the platform has been used by jurisdictions.
A systematic approach is presented to constructing a radiation assurance case using Goal Structuring Notation (GSN) for spacecraft containing COTS parts. The GSN paradigm is applied to an SRAM single-event upset experiment board designed to fly on a CubeSat in January 2017. A custom software language for development of a GSN assurance case is under development at Vanderbilt. Construction of a radiation assurance case without use of hardened parts or extensive radiation testing is discussed.
This paper presents the application of a new design of a multiport, modular, medium-voltage power electronics hub (M3PE-HUB) in a microgrid setting. The M3PE-HUB system was modeled in a digital real-time simulator (DRTS) and integrated into the Banshee microgrid test system. This paper presents the preliminary DRTS simulation-based results of the M3PE-HUB system connected in a test microgrid system. Verification and validation of the M3PE-HUB architecture and controls in the test microgrid setting are the primary contributions of this work. The results of the operation during the islanding and resynchronization process indicate the feasibility of the proposed architecture in a microgrid setting. This paper also presents results for a system reconfiguration use case where the M3PE-HUB was used to reconfigure the system under a fault condition.
Additive manufacturing (AM) is a rapidly growing technology space, not only for prototyping, but is also becoming more feasible at larger scales and increasing component quantities. There are a large variety of AM processes and materials available to users and effectively applying those processes and materials to a specific use case can be challenging. One specific area where AM could be particularly beneficial is marine renewable energy (MRE). Not only is MRE a relatively nascent industry with a near-term need for rapid deployments and prototype testing, but developers could also see long-term benefits from the broad variety of environmentally resistant materials available and the ability to manufacture complex geometries that AM technologies offer. Over the past 4 years, AM materials have played an increasing role in the Advanced Materials project; a multi-year, multi-laboratory research project funded by the U.S. Department of Energy's Water Power Technologies Office, with the main goal of reducing barriers to the adoption of complex materials in the MRE industry. The primary focus of this project is to develop test methods and generate datasets to understand the long-term performance of advanced materials in marine environmental and address specific material challenges as they arise. This report provides an extensive overview of the research that has been performed specific to AM polymers as part of the Advanced Materials project. The intention of this document is to provide recommendations of best practices with regards to material selection, mechanical test method development, and design practices, lessons learned along the way, current research trends, and ongoing challenges with regards to AM polymers in marine environments. In particular, this report focuses on several key aspects: Material and process selection, Environmental conditioning and subsequent degradation quantification through mechanical characterization, Composite reinforcements on AM polymer substrates, Adhesion of instrumentation for mechanical characterization and loads measurements, Protective coatings for preventing biofouling and water ingress, Other MRE case studies where AM has proved particularly useful. Ultimately, we hope that the test methods that have been developed, data generated, and lessons learned from this research will be valuable to the MRE community (researchers and developers alike), as well as other industries, and can be used as a reference point as the respective MRE and AM industries continue to grow and mature.
Presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24, 2024. The presentation majorly demonstrates a use case of how the meshgraphnets can be used for subsurface evaluation for real-time decision support for CO2 storage.
A conventional practice for spaceflight projects is to document scenarios in a monolithic Operations Concept document. Such documents can be hundreds of pages long and may require laborious updates. Software development practice utilizes scenarios in the form of smaller, individual use cases, which are often structured and managed using UML. We have developed a process and a web-based scenario tool that utilizes a similar philosophy of smaller, more compact scenarios (but avoids the formality of UML). The need for a scenario process and tool became apparent during the authors' work on a large astrophysics mission. It was noted that every phase of the Mission (e.g., formulation, design, verification and validation, and operations) looked back to scenarios to assess completeness of requirements and design. It was also noted that terminology needed to be clarified and structured to assure communication across all levels of the project. Attempts to manage, communicate, and evolve scenarios at all levels of a project using conventional tools (e.g., Excel) and methods (Scenario Working Group meetings) were not effective given limitations on budget and staffing. The objective of this paper is to document the scenario process and tool created to offer projects a low-cost capability to create, communicate, manage, and evolve scenarios throughout project development. The process and tool have the further benefit of allowing the association of requirements with particular scenarios, establishing and viewing relationships between higher- and lower-level scenarios, and the ability to place all scenarios in a shared context. The resulting structured set of scenarios is widely visible (using a web browser), easily updated, and can be searched according to various criteria including the level (e.g., Project, System, and Team) and Mission Phase. Scenarios are maintained in a web-accessible environment that provides a structured set of scenario fields and allows for maximum visibility across the project. One key aspect is that the tool was built for a scenario process that accounts for stakeholder input, review, comment, and concurrence. By creating well-designed opportunities for stakeholder input and concurrence and by making the scenario content easily accessible to all project personnel, we maximize the opportunities for stakeholders to both understand and agree on the concepts for how their mission is to be carried out.
Climate change and degradation of ecosystem services functioning may threaten the ability of current agricultural systems to keep up with demand for adequate and inexpensive food and for clean water, waste disposal and other broader ecosystem services. Human health is likely to be affected by changes occurring across multiple geographic and time scales. Impacts range from increasing transmissibility and the range of vector-borne diseases, such as malaria and yellow fever, to undermining nutrition through deleterious impacts on food production and concomitant increases in food prices. This paper uses case studies to describe methods that make use of satellite remote sensing and Demographic and Health Survey data to better understand individual-level human health and nutrition outcomes. By bringing these diverse datasets together, the connection between environmental change and human health outcomes can be described through new research and analysis.
Science outfitting is often given insufficient treatment in the development of early conceptual studies for lunar surface habitats. In some cases, only control masses and volumes are used as placeholders. In others, one science discipline may be given detailed treatment while others are largely ignored. It is not unheard of for science outfitting to be entirely forgotten in initial concept layouts. This is exacerbated by the reality that spacecraft design studies are often initiated long before science objectives have been established for any given human spaceflight destination. When those objectives later emerge, they can be difficult to accommodate if sizing studies did not allocate sufficient resources for them. A notional science outfitting can be created for virtually any human exploration habitat, however, utilizing data created by the International Space Station and Constellation programs. Biology, human research, physics, and geology science laboratories and a general-purpose work area for a lunar surface habitat will be derived using equipment identified by the Constellation-era Optimizing Science and Exploration Working Group (OSEWG) or flown on the International Space Station. Early science outfitting definition and inclusion in surface habitat sizing is critical for developing an exploration architecture that meets science needs. The mass, volume, power, and use cases associated with these notional laboratories impacts all of the habitat subsystems, habitat dimensions, hatch dimensions, logistics operations, launch vehicles and landers.
The NISAR mission will provide data covering nearly all the Earth's land areas and sea ice designed specifically to meet requirements of the NISAR science disciplines. However, for each science use case, the same data could potentially be used by one or more applications, often with little or no change in the core observables. Here we describe NISAR's capabilities for supporting a wide range of applications and the activities undertaken to inform, engage, and train the community that will increase the mission's societal impact.
Trajectory-Based Operations in the National Airspace System is a key aspect of advanced air traffic management research. Trajectory-Based Operations focuses on modernizing the current operating paradigm to increase efficiency, predictability, resilience, and flexibility while migrating toward greater operational autonomy across the airspace. Research conducted at the National Aeronautics and Space Administration supports the transition from current airspace operations to Trajectory-Based Operations targeting a 2035-2045 implementation timeframe. Simulation scenarios that demonstrate a representative Trajectory-Based Operations environment in that timeframe, and enable the evaluation of advanced airborne tools such as strategic airborne trajectory management services, are necessary to support this research effort. This report describes characteristics and assumptions made about the future operating environment that were applied to a scenario development methodology to study a representative 2040 Trajectory-Based Operations environment in a simulation use case. This report also includes descriptions of the study design and analysis approach, discussion of the simulation results, and application of these scenarios to future research activities.