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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.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Visualizations to Aid Decision-Making in the ACCP Value Framework

NASA’s priorities for Earth Science are informed by the 2017-2027 Decadal Survey for Earth Science and Applications from Space of the National Academies of Sciences, Engineering and Medicine. In that document, five Designated Observables are identified as priorities for research, two of which are Aerosols, and Clouds, Convection, and Precipitation. NASA is addressing these two Designated Observables by a combined study (the Aerosols, Clouds, Convection, and Precipitation, or ACCP, study). In this context of the ACCP study’s multiple objectives and multiple stakeholders, heuristic-based approaches are insufficient to assess candidate observing system concepts due to the complexity of the decision problem. For the ACCP study, this complexity in assessment is such that absent a structured approach that permits understanding of the steps leading to a decision, the decision risks being made on an incomplete basis. While prose and numeric data both have their place in effective communication, visualizations play an important part not only in presenting information, but also in structuring conversations around that information. Each of the visualizations developed for the ACCP Value Framework serve at least one of several functions: it structures communication about a method or process, it facilitates the elicitation and aggregation of data, or it summarizes complex information to enable analysis. Thus, these visualizations can present information, structure conversations, or do both.

Christopher A Jones↗
NASA NTRS1987

Pilot interaction with automated airborne decision making systems

The current research is focused on detection of human error and protection from its consequences. A program for monitoring pilot error by comparing pilot actions to a script was described. It dealt primarily with routine errors (slips) that occurred during checklist activity. The model to which operator actions were compared was a script. Current research is an extension along these two dimensions. The ORS fault detection aid uses a sophisticated device model rather than a script. The newer initiative, the model-based and constraint-based warning system, uses an even more sophisticated device model and is to prevent all types of error, not just slips or bad decision.

Hammer, John M.↗
NASA NTRS2001

Using Neural Networks in Decision Making for a Reconfigurable Electro Mechanical Actuator (EMA)

The objectives of this project were to demonstrate applicability and advantages of a neural network approach for evaluating the performance of an electro-mechanical actuator (EMA). The EMA in question was intended for the X-37 Advanced Technology Vehicle. It will have redundant components for safety and reliability. The neural networks for this application are to monitor the operation of the redundant electronics that control the actuator in real time and decide on the operating configuration. The system we proposed consists of the actuator, sensors, control circuitry and dedicated (embedded) processors. The main purpose of the study was to develop suitable hardware and neural network capable of allowing real time reconfiguration decisions to be made. This approach was to be compared to other methods such as fuzzy logic and knowledge based systems considered for the same application. Over the course of the project a more general objective was the identification of the other neural network applications and the education of interested NASA personnel on the topic of Neural Networks.

Latino, Carl D.↗
NASA NTRS2013

Improved Targeting Through Collaborative Decision-Making and Brain Computer Interfaces

This paper reports a first step toward a brain-computer interface (BCI) for collaborative targeting. Specifically, we explore, from a broad perspective, how the collaboration of a group of people can increase the performance on a simple target identification task. To this end, we requested a group of people to identify the location and color of a sequence of targets appearing on the screen and measured the time and accuracy of the response. The individual results are compared to a collective identification result determined by simple majority voting, with random choice in case of drawn. The results are promising, as the identification becomes significantly more reliable even with this simple voting and a small number of people (either odd or even number) involved in the decision. In addition, the paper briefly analyzes the role of brain-computer interfaces in collaborative targeting, extending the targeting task by using a BCI instead of a mechanical response.

Brain computer interfaces (BCI)↗
NASA NTRSDate not supplied

Exploration Medical Capability - Advancing Medical System Design and Risk-Informed Decision Making for Deep Space Exploration

BACKGROUND: Within NASA’s Human Research Program, the Exploration Medical Capability (ExMC) Element has three primary focus areas: clinical and scientific research, systems engineering and trade space analysis, and technology development and demonstrations. These focus areas feed into the overarching goal of enabling progressively Earth-Independent Medical Operations (EIMO), a new paradigm that will be necessary for future Artemis and Mars medical and vehicle systems. This EIMO end state aligns with NASA’s Moon to Mars Objectives, which clearly outline the need for NASA deep space exploration missions to reduce their reliance upon Earth and become increasingly autonomous, in preparation for the first human Mars mission. OVERVIEW: To advance exploration medical systems and ultimately, integrated crew health and performance systems, ExMC’s portfolio includes: funding ground development & testing of novel medical capabilities; creation of new approaches for the development of medical protocols and procedures; deployment of innovative technologies into analog environments; technology demonstrations in spaceflight; and eventual transition to operations of new capabilities for deep space exploration missions. The portfolio also includes: pharmaceutical research targeting stability, pharmacokinetics, and pharmacodynamics; integrated data architectures and clinical decision support tools; and systems engineering and trade space analysis tools to assist NASA in the development of future medical system models as well as the medical system requirements that can serve as a foundation for deep space exploration missions. All of these investments are done in a collaborative and coordinated fashion with other NASA stakeholders, such as the Environmental Control and Life Support Systems – Crew Health and Performance System Capability Leadership Team and the Health and Medical Technical Authority. DISCUSSION: In this presentation, ExMC will provide an overview of our work from across our portfolio, all of which will inform future EIMO efforts at NASA. ExMC’s research and development investments are targeted to reduce the human system risks associated with deep space exploration to the Moon and Mars.

Kris Lehnhardt↗
NASA NTRS2002

A Remote Sensing Approach for Urban Environmental Decision-Making: An Atlanta, Georgia Case Study

Unquestionably, urbanization causes tremendous changes in land cover and land use, as well as impacting a host of environmental characteristics. For example, unlike natural surfaces, urban surfaces have very different thermal energy properties whereby they store solar energy throughout the day and continue to release it as heat well after sunset. This effect, known as the 'Urban Heat Island', serves as a catalyst for chemical reactions from vehicular exhaust and industrial activities leading to the deterioration in air quality, especially exacerbating the production of ground level ozone. 'Cool Community' strategies that utilize remote sensing data, are now being implemented as a way to reduce the impacts of the urban heat island and its subsequent environmental impacts. This presentation focuses on how remote sensing data have been used to provide descriptive and quantitative data for characterizing the Atlanta, Georgia metropolitan area - particularly for measuring surface energy fluxes, such as the thermal or "heat" energy that emanates from different land cover types across the Atlanta urban landscape. In turn, this information is useful for developing a better understanding of how the thermal characteristics of the city surface affect the urban heat island phenomena and, ultimately, air quality and other environmental parameters over the Atlanta metropolitan region. Additionally, this paper also provides insight on how remote sensing, with its synoptic approach, can be used to provide urban planners, local, state, and federal government officials, and other decision-makers, as well as the general public, with information to better manage urban areas as sustainable environments.

Quattrochi, Dale A.↗
DOE OSTI2021

Commercial Vehicle Driver Behaviors and Decision Making: Lessons Learned from Urban Ridealongs

As e-commerce and urban deliveries spike, cities grapple with managing urban freight more actively. In order to effectively manage urban deliveries, city planners and policy makers need to better understand driver behaviors and the challenges they experience in performing deliveries. In this study, we collected data on commercial vehicle (CV) driver behaviors by performing ridealongs with various logistics carriers. Ridealongs were performed in Seattle, Washington, covering a range of vehicles (cars, vans, and trucks), goods (parcels, mail, beverages, and printed materials), and customer types (residential, office, large and small retail). Observers collected qualitative observations and quantitative data on trip and dwell times, while also tracking vehicles through GPS devices. The results showed that, on average, urban CVs spent 80 percent of their daily operating time parked. The study also found that, unlike the common belief, drivers (especially those operating heavier vehicles) parked in authorized parking locations, with only less than 5 percent of stops occurring in the travel lane. Dwell times associated with authorized parking locations were significantly longer than those of other parking locations, and mail and heavy goods deliveries generally had longer dwell times. We also identified three main criteria CV drivers used for choosing a parking location: avoiding unsafe maneuvers, minimizing conflicts with other users of the road, and coopetition with other commercial drivers. Here, the results provide estimates for trip times, dwell times, and parking choice types, as well as insights into why those decisions are made and the factors affecting driver choices.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Developing new pathways for energy and environmental decision-making in India: a review

Abstract India faces a dual challenge of economic development and responding to climate change. Although India’s per capita emissions are well below global average, the country is one of the world’s largest greenhouse gas emitters. Indian policymakers and stakeholders require high-quality data and research to assess low-emissions, sustainable development strategies. Peer-reviewed literature is a key source of this information and also a key venue for conversation amongst research leaders. This paper examines the recent peer-reviewed literature on India’s 2030 and 2050 pathways. We conducted a systematic literature review to identify key quantitative national modeling studies. From the 34 studies identified, we synthesized scenario data to draw common conclusions and identify critical research gaps. The main focus was on examining the coverage and the state of information available on low-carbon pathways. Overall, we find a few scenarios that are potentially consistent with a 2070 net-zero goal, but more limited assessment of pathways to reach net-zero emissions before this date. Mitigation pathways with greater ambition are required across all energy sectors to ensure a smooth transition to net-zero emissions by or before 2070. The scenarios confirm that reducing emissions to below 2 GtCO 2 yr −1 by mid-century would necessitate significant transformations of the Indian energy sector, such as, a decrease in unabated coal power capacity, transportation modal shift, and industrial process switching. The assessment also finds substantial differences in final energy estimates reported across studies, particularly in transportation. The lack of consistency in, and transparency about underlying drivers, assumptions, and even outputs across studies points to the critical need for the sorts of coordinated, multi-model studies that have proven exceptionally valuable for decision makers in other major emitting countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Design space exploration and decision‐making for a segmented ultralight morphing 50‐MW wind turbine

Abstract Wind turbine design encompasses many different aspects including aerodynamic, structural, electrical, and control system design. To achieve optimal plant performance, a system design approach is utilized in which the performance of the whole wind turbine is evaluated and quantified during operational scenarios with subsystem interactions. In this paper, the design for a Segmented Ultralight Morphing Rotor (SUMR) 50‐MW wind turbine is presented utilizing levelized cost of energy (LCOE) for design choices, with additional quantification of simulated performance shortcomings at the 50‐MW scale. The multi‐disciplinary design process results in a final ultra‐scale turbine configuration that outperforms other existing offshore wind farms regarding the LCOE.

Kianbakht, Sepideh↗
DOE OSTI2023

Reliability-informed end-of-use decision making for product sustainability using two-stage stochastic optimization

The concept of circular economy has been diffused in recent decades to promote economic growth that does not add to the burden on natural resource extraction. Re-X options (e.g., reuse, repair, refurbish, remanufacture, recycle) have been gradually adopted in the product development process and optimized to reduce or eliminate waste and pollution. Although manufacturing incorporating Re-X options can be more environmentally friendly, it involves more sources of uncertainty than traditional manufacturing since the end-of-use products can be collected from multiple origins with various quantities and qualities, and the market demand for both new and remanufactured products cannot be forecasted perfectly. Thus, there is a need to optimize the Re-X policy to alleviate the negative impacts of the higher uncertainty. One option is using the reliability information of new products to estimate the end-of-use conditions and applying multi-stage stochastic optimization to capture multiple demand scenarios. This paper develops a two-stage stochastic optimization model to optimize the quality thresholds for reuse, recycling, and remanufacturing options. Our objective is to minimize the total cost, energy consumption, and environmental impact of producing and providing warranty service for a product family. The model employs reliability information of product components to estimate the warranty service cost and the end-of-use conditions of the returned resources. A case study on a general product family is implemented to illustrate the efficacy of the optimization model. Finally, results show that the two-stage optimization can achieve cost and environmental impact reduction for a hybrid manufacturing and remanufacturing process.

97 MATHEMATICS AND COMPUTING↗