SEARCH · Engineering Papers

Results for “Decision support tools”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 811 records · Page 45

All sources NASA NTRS DOE OSTI

NASA NTRS1988

Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

Szatkowski, Gerard P.↗

NASA NTRSDate not supplied

Game Based Learning For Earth Science Applications Training

Current NASA Earth capacity development programs employ mechanisms ranging from online resource sharing, and virtual and in-person trainings to share knowledge. While these programs are highly successful at engaging individuals around the world – in 2018, over 8000 individuals and over 2000 institutions from all 50 US states and over 140 countries were engaged through over 150 projects and trainings – user feedback has highlighted the desire for expanded hands-on, practical experiences in incorporating NASA EO insights with localized data and actions. We aim to address this gap by leveraging the benefits of game-based learning to build user skills in integrating NASA and local EO data to guide decisions for climate resiliency and hazard planning. This project is being executed as a two-phase crowdsourced challenge: 1) Phase 1 will require a well-researched product concept that reflects an understanding of NASA’s Earth data and tools and user needs, and proposes an innovative and interactive game or extended reality experience to train users in identifying relevant NASA data and applying insights to their climate resiliency decisions; 2) Winners of Phase 1 will be provided seed funding to develop a working prototype of the product. We aim to award 1-3 final winners to support the development of more than one game, thereby ensuring that NASA's diverse audiences around the world can access training games that best suit their needs and capabilities. This EO training game project fits in the NASA Earth Science Applied Sciences Program’s Capacity Development Program, contributing to the program mission of “helping people around the world better understand [NASA’s Earth] data and find ways to use them” (https://appliedsciences.nasa.gov/what-we-do/capacity-building). The final training game will complement existing programmatic activities of workforce development, trainings, and collaborative projects, while providing the unique value of providing interactive experiences to users and collecting real-time data and feedback to improve NASA’s Earth applications’ products and services related to climate resilience.

Human centered design↗

NASA NTRS1974

A computer simulation of Skylab dynamics and attitude control for performance verification and operational support

A simulation of the Skylab attitude and pointing control system (APCS) is outlined and discussed. Implementation is via a large hybrid computer and includes those factors affecting system momentum management, propellant consumption, and overall vehicle performance. The important features of the flight system are discussed; the mathematical models necessary for this treatment are outlined; and the decisions involved in implementation are discussed. A brief summary of the goals and capabilities of this tool is also included.

Buchanan, H.↗

DOE OSTI2025

CO 2 Transport Infrastructure Outlook in the United States

Carbon capture and storage (CCS) represents one of the most important methods to mitigate anthropogenic carbon emissions at a large scale, playing a key role in meeting climate change targets (Bui et al., 2018) and for net-zero CO 2 by 2050 scenarios in the United States (Browning et al., 2023). This technology involves capturing CO 2 emissions from industrial processes, transporting them via pipelines, trucks, rails, or ships, and ultimately storing them in underground geological sites, such as saline aquifers or depleted oil reservoirs. Thus, to encourage carbon reduction initiatives, the U.S. Congress enacted the Bipartisan Budget Act in 2018, reforming the 45Q tax credit to benefit operators storing CO 2 in geologic formations (Jones and Sherlock, 2021). Additionally, the 2022 Inflation Reduction Act further expanded these incentives, providing additional support for CCS initiatives (Hackett and Kuehn, 2023). Although numerous studies describe the importance of optimal CO 2 transportation to support the decision-making of CCS projects aligned with the objective of net-zero emissions by 2050 (Abramson and Christensen, 2021; Chen and Pawar, 2023; Greig and Pascale, 2021), further efforts are required to optimize the transport infrastructure for national-scale CCS deployment. Therefore, in this study, we examine three nationwide scenarios with the SimCCS 3.0 tool (Ma et al., 2022, 2023, 2024) along with a novel geospatial splitting approach developed by Velasco-Lozano et al. (Velasco- Lozano et al., 2024a, 2024b). We present optimized pipeline networks that meet the dynamic evolution of annual capture amounts, describing the required total pipeline lengths at each stage as a function of the pipeline diameters. Thus, the cases presented demonstrate the feasibility of CO 2 pipeline infrastructure for large-scale CCS projects.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Advanced Capabilities for Emergency Response Operations (ACERO)

The Advanced Capabilities for Emergency Response Operations (ACERO) project is expected to develop, integrate, demonstrate, and transition to operations, evolving aviation technologies from NASA and industry to identify, monitor, and suppress wildland fires as a means to enhance safety, improve operational efficiency, and prevent economic loss. Some of the concepts ACERO explores are: wildfire airspace mangement to improve safety and resource utilization during a disaster, applying new aviation technologies to improve safety and demonstrate new mission-support capabilities, second-shift operations to enable progress towards 24/7 aerial response, and the integration of capabilities across NASA's Aeronautics Research, Science, and Space Technology mission directorates to enable expanded and scalable operations. Realizing this vision is expected to bring positive impact to such areas as: consistency of technology adoption through a unified concept of operations, airspace coordination and deconfliction that integrates portable solutions and enables diverse operations, remote sensing and data fusion for modeling and predictions that support in-time decision making, aircraft technologies for hazard avoidance and state management, and increased response capabilities through persistent communications and surveillance. ACERO continues the research begun under the Scalable Traffic Management for Emergency Response Operations (STEReO) activity, which brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the ACERO and STEReO projects to the Council of Western State Foresters (CWSF) Western State Fire Managers (WSFM) Committee.

emergency response operations↗

DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗

DOE OSTI2025

Navigating Uncertainty: Challenges in Visualizing Ensemble Data and Surrogate Models for Decision Systems

Uncertainty visualization plays a critical role in transforming ensemble simulation data into actionable insights by effectively communicating various dimensions of uncertainty within a system. The emergence of artificial intelligence-driven surrogate models trained on multirun ensemble data offers a transformative opportunity to replace computationally intensive simulations with fast estimates, enabling users to explore data spaces with unprecedented depth and interactivity. However, integrating ensemble data and surrogate models into decision-making workflows and tools introduces novel challenges for uncertainty visualization. These include reconciling and clearly communicating the unique uncertainties associated with ensembles and their surrogate model estimates, and leveraging these approximations to inform actionable decisions. This work explores these challenges in the context of high-dimensional data visualization, bridging discrete datasets with their continuous representations and addressing the complexities of systems that support iterative navigation between input and output spaces. We evaluate the role of uncertainty visualization in fostering intuitive, actionable interactions and identify critical hurdles in advancing this frontier of computational simulation.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

Distributed environmental control

We present an architecture of distributed, independent control agents designed to work with the Computer Aided System Engineering and Analysis (CASE/A) simulation tool. CASE/A simulates behavior of Environmental Control and Life Support Systems (ECLSS). We describe a lattice of agents capable of distributed sensing and overcoming certain sensor and effector failures. We address how the architecture can achieve the coordinating functions of a hierarchical command structure while maintaining the robustness and flexibility of independent agents. These agents work between the time steps of the CASE/A simulation tool to arrive at command decisions based on the state variables maintained by CASE/A. Control is evaluated according to both effectiveness (e.g., how well temperature was maintained) and resource utilization (the amount of power and materials used).

Cleveland, Gary A.↗

DOE OSTI2023

Building the Case for Hybrid Energy Developments: Webinar Recording Day 2

INL, PNNL, and NREL, with support from our academic and industry partners, hosted a 2-day webinar to learn more about the benefits of hybrid energy systems, considerations for designing the right system for communities, and practical tools that can help with the design and development process. In Day 2 of this webinar, the focus was on tools that can be used to help inform design decisions for hybrid systems, including resource analysis, siting, resilience, valuation, and resource optimization. Day 2 also highlighted funding opportunities for hybrid systems.

14 SOLAR ENERGY↗

DOE OSTI2023

Building the Case for Hybrid Energy Developments: Webinar Recording Day 2

14 SOLAR ENERGY↗

DOE OSTI2024

Decision support for United States—Canada energy integration is impaired by fragmentary environmental and electricity system modeling capacity

The renewable energy transition is leading to increased electricity trade between the United States and Canada, with Canadian hydropower providing firm lower-carbon power and buffering variability of wind and solar generation in the U.S. However, long-term power purchase agreements and transborder transmission projects are controversial, with two of four proposed transmission lines between Quebec, Canada and the northeast U.S. cancelled since 2018. Here, we argue that controversies are exacerbated by a lack of open-source data and tools to understand tradeoffs of new hydropower generation and transmission infrastructure in comparison to alternatives. This gap includes impacts that incremental transmission and generation projects have on the economics of the entire system, for example, how new transmission projects affect exports to existing markets or incentivize new generation. We identify priority areas for data synthesis and model development, such as integrating linked hydropower and hydrologic interactions in energy system models and openly releasing (by utilities) or back-calculating (by researchers) hydropower generation and operational parameters. Publicly available environmental (e.g. streamflow, precipitation) and techno-economic (e.g. costs, reservoir size,) data can be used to parameterize freely usable and extensible models. Existing models have been calibrated with operational data from Canadian utilities that are not publicly available, limiting the range of scientific and commercial questions these tools have been used to answer and the range of parties that have been involved. Studies conducted using highly resolved, national-scale public data exist in other countries, notably, the United States, and demonstrate how greater transparency and extensibility can drive industry action. Improved data availability in Canada could facilitate approaches that (1) increase participation in decarbonization planning by a broader range of actors; (2) allow independent characterizations of environmental, health, and economic outcomes of interest to the public; and (3) identify decarbonization pathways consistent with community values.

13 HYDRO ENERGY↗

DOE OSTI2023

Developing an Equity Framework for State Regulatory Decision-Making

The report presents a framework for states that seek to incorporate equity into regulatory decision-making. Berkeley Lab contextualizes approaches and metrics from various states into example processes to exemplify how this may be done, including topics such as the development of equity goals and definitions, intervenor funding, community engagement, performance-based ratemaking, and utility resource planning. The report offers five takeaways and considerations, supported by these examples: 1. Equity comprises multiple tenets and stages, all of which must be considered in parallel. 2. At the start of designing new equity-related processes, it is critical to establish clear and actionable goals, definitions, roles, and responsibilities to ensure progress. 3. Once goals are established, it is critical to align tools and metrics that bridge the gap between what an intervention may do and how it may impact communities and households. 4. Processes should be stakeholder driven. It is important to not only increase education and outreach, but to actively seek out and incorporate feedback from inclusive public processes and build in accountability mechanisms. Processes should be iterative. Feedback loops between evaluations and program design provide the flexibility to better align existing interventions with community priorities and to incorporate equity into future decision-making.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2000

Improving The Discipline of Cost Estimation and Analysis

The need to improve the quality and accuracy of cost estimates of proposed new aerospace systems has been widely recognized. The industry has done the best job of maintaining related capability with improvements in estimation methods and giving appropriate priority to the hiring and training of qualified analysts. Some parts of Government, and National Aeronautics and Space Administration (NASA) in particular, continue to need major improvements in this area. Recently, NASA recognized that its cost estimation and analysis capabilities had eroded to the point that the ability to provide timely, reliable estimates was impacting the confidence in planning many program activities. As a result, this year the Agency established a lead role for cost estimation and analysis. The Independent Program Assessment Office located at the Langley Research Center was given this responsibility. This paper presents the plans for the newly established role. Described is how the Independent Program Assessment Office, working with all NASA Centers, NASA Headquarters, other Government agencies, and industry, is focused on creating cost estimation and analysis as a professional discipline that will be recognized equally with the technical disciplines needed to design new space and aeronautics activities. Investments in selected, new analysis tools, creating advanced training opportunities for analysts, and developing career paths for future analysts engaged in the discipline are all elements of the plan. Plans also include increasing the human resources available to conduct independent cost analysis of Agency programs during their formulation, to improve near-term capability to conduct economic cost-benefit assessments, to support NASA management's decision process, and to provide cost analysis results emphasizing "full-cost" and "full-life cycle" considerations. The Agency cost analysis improvement plan has been approved for implementation starting this calendar year. Adequate financial and human resources are being made available to accomplish the goals of this important effort, and all indications are that NASA's cost estimation and analysis core competencies will be substantially improved within the foreseeable future.

Piland, William M.↗

NASA NTRS2021

A Systematic Approach to Developing Paths Towards Airborne Vehicle Autonomy

Advanced Air Mobility (AAM) demands greater levels of aircraft autonomy than are currently implemented today. To enable this requirement, novel aircraft functionalities and technologies as well as supporting airworthiness and operational regulations are required. A structured method to derive a comprehensive list of aircraft level decision-making functions is defined and applied. The resulting function set is programmed into an ontology, and enables autonomous decision-making through the application of a defined decision-making process. Paths to implementing the functions are generated by applying a structured four step method. By surveying current technologies, airspace, procedures and regulations, the paths generation method defines incremental paths to autonomy that the current regulatory environment can support. Opportunities to implement novel technologies and functions are identified, and regulatory mechanisms supporting their implementation are underscored. The analysis provides the tools to further define aircraft functions and paths to their implementation, while demonstrating that for particular use cases, aircraft autonomy is attainable in the medium-term.

Paul Vajda↗

NASA NTRS2022

Haiti Agriculture: Utilizing NASA Earth Observations to Evaluate the Success of Reforestation Practices in Haiti

Haiti is one of the world’s most deforested and environmentally degraded countries. Over the past 30 years, the Haiti Reforestation Partnership (HRP) has provided resources, education, and expertise to support reforestation work in Haiti. The HRP has planted over 15 million trees through their partnership with Comprehensive Development Program (CODEP). However, they have yet to conduct a comprehensive analysis of forest stand survival. The NASA DEVELOP team partnered with the HRP to aid their future silvicultural decisions using satellite imagery. Through the creation of the Monitoring of Vegetation Presence (MVP) tool in Google Earth Engine, the team produced a time series showing trends in enhanced vegetation index (EVI) from 1984 to 2021, as well as a habitat suitability map using a general model for all tree species. These provided the partner with visuals to communicate their reforestation efforts and guidance on where to apply their future efforts. The team utilized Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2 and Sentinel-2 Multispectral Instrument (MSI) vegetation indices as indicators of stand success over time. The team also incorporated WorldClim bioclimatic variables such as precipitation and temperature, Centre National de L’Information Geo-Spatiale (CNIGS) Airborne Lidar elevation, and ancillary datasets areas suitable for future reforestation efforts. Overall, the time series showed that the demonstration forest increased in EVI at a greater rate than the surrounding area and the habitat model suggested there are 49,000 hectares of suitable habitat for planting using slope, aspect and temperature as predictor variables.

Kelli Roberts↗

NASA NTRSDate not supplied

Airport Runway Configuration Management with Offline Model-free Reinforcement Learning

Runway configuration management (RCM) deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction and other environmental variables. RCM is one of the most challenging tasks in air traffic management, as it relies on operational and environmental variables (e.g., weather forecast) that are highly uncertain and complex to model. In this paper, an innovative and automated approach is deployed using offline model-free reinforcement learning to provide decision-support for RCM. The proposed technology processes historical data about variables of interest, decisions made regarding RCM, and their subsequent outcome, to identify a policy that would encourage good decisions and avoid the poor ones. The policy search is guided by an appropriately chosen weighted utility function (e.g., based on minimizing delays and go-arounds). Finally, the performance of the proposed tool is validated using Charlotte Douglas International Airport as the case study, which shows that the proposed method is superior to other conventional rule-based approaches.

Milad Memarzadeh↗

NASA NTRSDate not supplied

Airport Runway Configuration Management with Offline Model-free Reinforcement Learning

Milad Memarzadeh↗

DOE OSTI2023

Supporting Risk-informed Decision-making During Reactor Accidents

Uncertainty in severe accident evolution and outcome is driven by event bifurcations that represent distinctive challenges to defensive layers and tend to promote the emergence of discrete classes of core damage and accident risk. This discrete set of "attractor" states arise from the complex networks of competing physical phenomena and conditional event cascades occurring as the overall system degrades – a process that yields increasing degrees of freedom and accident progression pathways. Characterization of these event spaces has proven elusive to more traditional data interrogation methods, but proves tractable by application of more advanced data collection and machine learning approaches. Through application of these approaches we demonstrate a conceptual framework that enables real-time/robust, risk-informed decision-making support to improve accident mitigation and encourage “graceful exits” during low probability, extreme events limiting accident consequences. In this analysis, we simulated over 8,000 short-term station blackout (STSBO) accidents with the state-of-the-art integral severe accident code, MELCOR, and demonstrate the potential for ML approaches to predict simulation outcomes. We chose to pair ML tools with interpretable and mechanistic event trees for the considered STSBO accident space to predict the likelihood of future event paths along the tree. In addition to the current state of the system, we use information from recent trajectories of temperature, pressure, and other physical features, combining both the current state and past trajectories to forecast future event paths. Finally, we simulate the random injection of variable amounts of water to quantify the efficacy of available actions at reducing risks along the many branches in the event tree. We identify scenarios and windows of opportunity to mitigate risk as well as scenarios in which such actions are unlikely to alter the accident end-state.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗