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At least 37 records · Page 2

Machine learning reduces soft costs for residential solar photovoltaics

Further deployment of rooftop solar photovoltaics (PV) hinges on the reduction of soft (non-hardware) costs—now larger and more resistant to reductions than hardware costs. The largest portion of these soft costs is the expenses solar companies incur to acquire new customers. In this study, we demonstrate the value of a shift from significance-based methodologies to prediction-oriented models to better identify PV adopters and reduce soft costs. We employ machine learning to predict PV adopters and non-adopters, and compare its prediction performance with logistic regression, the dominant significance-based method in technology adoption studies. Our results show that machine learning substantially enhances adoption prediction performance: The true positive rate of predicting adopters increased from 66 to 87%, and the true negative rate of predicting non-adopters increased from 75 to 88%. We attribute the enhanced performance to complex variable interactions and nonlinear effects incorporated by machine learning. With more accurate predictions, machine learning is able to reduce customer acquisition costs by 15% ($0.07/Watt) and identify new market opportunities for solar companies to expand and diversify their customer bases. Our research methods and findings provide broader implications for the adoption of similar clean energy technologies and related policy challenges such as market growth and energy inequality.

14 SOLAR ENERGY↗

Exploration Technologies for Operations

Although the International Space Station (ISS) assembly has been completed, the Operations support teams continue to seek more efficient and effective ways to prepare for and conduct the ISS operations and future exploration missions beyond low earth orbit. This search for improvement has led to a significant collaboration between the NASA research and advanced software development community at NASA Ames Research Center and the Mission Operations community at NASA Johnson Space Center. Since 2001, NASA Ames Research Center has been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for several of the unmanned Mars missions operations. Since 2006, NASA Ames Research Center has also been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for manned operations support with the Mission Operations Directorate at NASA Johnson Space Center. This paper discusses the completion of the development and deployment of a variety of intelligent and human systems technologies adopted for manned mission operations. The technologies associated with the projects include advanced software systems for operations and human-centered computing. Human-centered computing looks to the processes and procedures that people do to perform any given job, then attempts to identify opportunities to improve these processes and procedures. In particular, for mission operations, improvements are quantified by specifically identifying how a tool can increase a persons efficiency, enhance a persons functional capability, andor improve the assurance of a persons decisions. The Ames development team has collaborated with the Mission Operations team to identify areas of efficiencies through technology infusion applications in support of the Plan, Train, and Fly activities of human-spaceflight mission operations. The specific applications discussed in this paper are in the areas of mission planning systems, mission operations design modeling and workflow automation, advanced systems monitoring, mission control technologies, search tools, training management tools, spacecraft solar array management, spacecraft power management, and spacecraft attitude planning. We discuss these specific projects between the Ames Research Center and the Johnson Space Centers Mission Operations Directorate, and how these technologies and projects are enhancing the mission operations support for the International Space Station. We also discuss the challenges, problems, and successes associated with long-distance and multi-year development projects between the research team at Ames and the Mission Operations customers at Johnson Space center. Finally, we discuss how these technology infusion applications and underlying technologies might be used in the future to support on-board operations of the crew and spacecraft systems as human exploration expands beyond low earth orbit to destinations in the solar system where communications delays will require more on-board autonomy and planning by the crew. Longer communications delays will require that the ground mission operations support will be primarily strategic in nature, while the tactical level of planning, systems monitoring and control, and failure analysisisolationrecovery will be the responsibility of both the spacecraft autonomous systems and the crew. Our expectation is that the technologies

mission operations↗

Assessing the behavioral realism of energy system models in light of the consumer adoption literature

Effective policymaking to achieve net zero greenhouse gas emissions demands an understanding of the complex drivers of, and barriers to, consumer adoption behavior via behaviorally realistic energy system models. Existing models tend to oversimplify by focusing on homogenized financial factors while neglecting consumer heterogeneity and non-monetary influences. This study develops and applies a comprehensive framework for evaluating the behavioral realism of consumer adoption models, informed by the adoption literature. It introduces a typology for factors influencing low-carbon technology adoption decisions: monetary and non-monetary factors relating to household characteristics, psychology, technological attributes, and contextual conditions. Next, reviews of the consumer adoption and decision-making literature identify the most influential adoption factor categories for distributed solar photovoltaics, electric vehicles, and air-source heat pumps. Finally, the extent to which a selection of energy system models accounts for these adoption factors is assessed. Existing models predominantly emphasize the economic aspects of technology, which are generally identified as the most important factors. Where the models fall short — in considering moderately important factor categories — sector-specific and agent-based models can offer more behaviorally realistic insights. This study sheds light on which types of factors are most important for consumer adoption decisions and investigates how well current models rise to the challenge of behavioral realism. The end-to-end analysis presented enables internally consistent comparisons across models and energy technologies. This research advances timely conversations on consumer adoption. It could inform more behaviorally realistic energy system modeling, and thereby more effective decarbonization policymaking.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗

High Temperature Devices for Aerospace Applications

This presentation will overview important new capabilities and benefits that next-generation higher temperature electronics promise for a variety of aerospace systems and missions. Initial aerospace infusions of higher temperature electronics to be discussed include jet engines and the prolonged robotic exploration of the Venus surface. Complete redesign of systems compared to prior conventional electronics practices would yield the most revolutionary benefits. However, the inherent higher risk and expense associated with new technology adoption will likely drive a more evolutionary technology infusion process, especially since flight qualification demands large safety margins and testing that ensures reliable operation for far longer than actual mission duration. SiC pn-junction based devices are inherently capable of the most durable operation at the highest application temperatures compared other transistor technologies, but such integrated circuits (ICs) will never achieve integration levels near today’s silicon ICs. Extreme temperature high-power devices will also be de-rated compared to room-temperature performance. While the high temperature market will always be small compared to the conventional temperature mass-market, compatibility and leveraging of existing foundry manufacturing is vital to the establishment of a sustainable high temperature electronics ecosystem sufficient to significantly improve aerospace systems.

High Temperature↗

Energy Storage Grand Challenge: Energy Storage Market Report

As part of the Department of Energy's (DOE) Energy Storage Grand Challenge (ESGC), DOE intends to synthesize and disseminate best available energy storage data, information, and analysis to inform decision-making and accelerate technology adoption. The ESGC Roadmap provides options for addressing technology development, commercialization, manufacturing, valuation, and workforce challenges to position the United States for global leadership in the energy storage technologies of the future. This report provides a baseline understanding of the numerous, dynamic energy storage markets that fall within the scope of the ESGC via an integrated presentation of deployment, investment, and manufacturing data from the best, publicly-available sources. This report covers the following energy storage technologies: lithium ion batteries, lead acid batteries, pumped storage hydropower, comrpessed air energy storage, redox flow batteries, hydrogen, building thermal energy storage, and select long duration energy storage technologies. Not all energy storage technologies and markets could be addressed in this report. Due to the wide array of energy technologies, market niches, and data availability issues, this market report only included a select group of technologies. For example, thermal energy storage technologies are very broadly defined and cover a wide range of potential markets, technology readiness levels, and primary energy sources. In other areas, data scarcity necessitates a greater understanding of future applications and emerging science. Future efforts will update data presented in this report and be expanded to include other energy storage technologies. This data-driven assessment of the current status of energy storage markets is essential to track progress toward the goals described in the Energy Storage Grand Challenge and inform the decision-making of a broad range of stakeholders. At the same time, gaps identified through the development of this report can point to areas where further data collection and analysis could provide an even greater level of understanding of the full range of markets and technologies. Finally, numerous complementary analyses are planned, underway, or completed that will provide a deeper understanding of the specific technologies and markets covered at a high-level in this report.

25 ENERGY STORAGE↗

The Transportation Energy and Mobility Pathway Options (TEMPO) Model: Overview and Validation of V1.0 [Slides]

This presentation documents the approaches and methods used in the Transportation Energy & Mobility Pathway Options™ (TEMPO) model to evaluate passenger and freight demand for transportation and mobility services, project vehicle ownership and technology adoption decisions, and determine transport mode choices to derive scenarios of future energy use and emissions. TEMPO is an all-inclusive transportation demand model that covers the entire United States, with an implicit spatial resolution and an hourly temporal resolution that allows for generating time-resolved energy use profiles to assess multisectoral integration aspects. Key features of the TEMPO model include the ability to perform endogenous out-of-sample forecasting to extrapolate recent emerging trends and analyze impacts of disruptive technological breakthroughs and behavioral changes. TEMPO employs an innovative representation of passenger mobility demand stemming from household-level decisions that determine vehicle adoption, ownership, and use based on sociodemographics (e.g., income, household composition), technology attributes (e.g., travel cost, time), geography (e.g., urban, suburban, rural) and population-specific multiday mobility and travel requirements. This representation enables a more forward-looking perspective on the use of new mobility options and the adoption of alternative fuel vehicles, as well as a more accurate representation of their energy usage profiles than previous modeling approaches. A comparison with the U.S. Energy Information Administration’s Annual Energy Outlook showcases the ability of TEMPO to accurately replicate widely accepted projections by representing the key elements of the entire transportation sector at the appropriate level of resolution. TEMPO is intended to generate future scenarios of technology adoption, energy use, and emissions in the transportation sector to compare alternatives, inform decision makers, and assess integration with energy infrastructure and supply systems at an appropriate spatiotemporal resolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Inducing the adoption of emerging technologies for sustainable intensification of food and renewable energy production: insights from applied economics

Emerging advances in sustainable intensification technologies have the potential to transform land use and crop management approaches in ways that can increase resource productivity and reduce adverse environmental impacts of agricultural production. This paper describes emerging technologies that can sustainably intensify food and renewable energy production. We apply the findings from studies examining the adoption of technologies with similar stylized features to provide insights about the incentives and barriers for the adoption of these emerging technologies. We also present a landscape-based systems approach, based on welfare economics, to go beyond relying on a positive approach to explain observed adoption decisions to examining normative questions about the optimal mix, level, and location of adoption of these technologies to achieve desired societal outcomes. Here, we conclude with a discussion of the insights from applied economics for the design of policy incentives to achieve these outcomes.

54 ENVIRONMENTAL SCIENCES↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Roadmap to reach global net-zero emissions for developing regions by 2085

As climate change intensifies, determining a developing region’s role in achieving net-zero emissions worldwide is crucial. However, regional efforts, considering historical emissions, remain underexplored. Here, we assess energy system changes, technology adoption, and investments needed for developing regions, including five major- and minor-emitting nations. Our analysis, using an integrated assessment model, shows a large gap in regional efforts toward global net-zero emissions, stemming from the necessary shift of energy systems to low-carbon resources. The use of new technologies, like electric vehicles, hydrogen, and carbon capture, varies by region, with the highest adoption required between 2020 and 2030. Financing this shift needs an average gross domestic product (GDP) investment rise of 0.464% in minor-emitting regions and up to 2.1% in major-emitting regions by 2085. Our results could guide policies and support setting quantifiable targets for developing nations. The findings are key to facilitating strategic technology use and finance mobilization to achieve a carbon-neutral future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A demonstrator for a real-time AI-FPGA-based triggering system for sPHENIX at RHIC

The RHIC interaction rate at sPHENIX will reach around 3 MHz in pp collisions and requires the detector readout to reject events by a factor of over 200 to fit the DAQ bandwidth of 15 kHz. Some critical measurements, such as heavy flavor production in pp collisions, often require the analysis of particles produced at low momentum. This prohibits adopting the traditional approach, where data rates are reduced through triggering on rare high momentum probes. We explore a new approach based on real-time AI technology, adopt an FPGA-based implementation using a custom designed FELIX-712 board with the Xilinx Kintex Ultrascale FPGA, and deploy the system in the detector readout electronics loop for real-time trigger decision.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Handbook for Designing, Implementing, and Evaluating Successful Electric Utility Pilots

Since at least the late 1970s, electric utilities and their regulators have recognized the value of experimentation to motivate innovation. The industry has a long history of using pilots to help inform future decision making about electric utility rates, customer technology adoption and integration, and even changes to the utility’s regulatory or business model. Although utility pilots have become almost ubiquitous proving grounds for new rates, technologies, and alterations to the traditional utility regulatory and business model, some regulators are beginning to raise questions about what constitutes a “good” pilot. Much has been written about utility pilots over the years; however, what is missing from the literature is the identification of a comprehensive process for not only designing and evaluating a pilot, but also implementing, successful utility pilots that provide actionable outcomes upon which more informed decisions can be made. This report provides a step-by-step process that regulators, policymakers, and utilities can follow to help promote a more successful pilot, even if whatever is being tested fails to produce the intended or expected result(s). It is worth noting that this report is not intended to serve as a technical resource for those designing, implementing, and evaluating pilots. However, there are myriad references provided for those wishing to delve deeper into the technical details.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A demonstrator for a real-time AI-FPGA-based triggering system for sPHENIX at RHIC

The RHIC interaction rate at sPHENIX will reach around 3 MHz in pp collisions and requires the detector readout to reject events by a factor of over 200 to fit the DAQ bandwidth of 15 kHz. Some critical measurements, such as heavy flavor production in pp collisions, often require the analysis of particles produced at low momentum. This prohibits adopting the traditional approach, where data rates are reduced through triggering on rare high momentum probes. We explore a new approach based on real-time AI technology, adopt an FPGA-based implementation using a custom designed FELIX-712 board with the Xilinx Kintex Ultrascale FPGA, and deploy the system in the detector readout electronics loop for real-time trigger decision.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

2023 Critical Materials Strategy

The global effort to curb carbon emissions is accelerating demand for clean energy technologies and the materials they rely on. Demand for these materials will only continue to grow, especially as some nations aim to achieve net zero emissions by 2050. While some major materials like steel, copper, and aluminum are already powering the fossil fuel economy, others are more minor materials with potential supply risks. These risks could jeopardize the ability to reduce greenhouse gas emissions within the desirable timeframe to avoid significant climate change. In some cases, it may be necessary to take action to improve the resilience of material supply chains and mitigate supply risks. Understanding the importance of individual materials to clean energy and the supply risks associated with them is necessary to identify which materials may serve as potential roadblocks to a clean energy future. The U.S. Department of Energy (DOE) issued a series of 13 supply chain deep dive assessment reports on various energy technologies in 2022 in response to President Biden’s Executive Order on America’s Supply Chains (E.O. 14017). These reports emphasized that supply chain bottlenecks can occur at any stage of the value chain from mining and refining to component and even sub-system manufacturing. The bottlenecks are a combination of factors such as material availability, equipment availability, work force availability and quality, logistics, regulatory framework, and market conditions. These bottlenecks were worsened during the global Covid-19 pandemic. Its lingering impacts have hindered capacity expansion for material supply chains and prevented product lead-time recovery. One approach to reduce supply chain risks for the United States is to have a strong domestic manufacturing sector with a diverse set of producers. Boosting responsible domestic production would require leveraging the latest science not only in material extraction but also in developing substitutes, recycling, reuse, and remanufacturing. This report is an updated analysis of previous Critical Materials Strategy (CMS) reports published by the DOE in 2010, 2011, and 2019 based on national and global priorities, technology advancement, and technology adoption trends. Like the CMS reports, this analysis presents the results of a formal material criticality assessment to identify which materials are critical to the continued deployment of clean energy technologies globally. The analysis in this report leveraged the DOE supply chain deep dive assessments to develop the initial list of materials to evaluate. This DOE Critical Materials Assessment (CMA) is conducted independently of criticality assessments performed by other U.S. government agencies, such as that conducted by the U.S. Geological Survey (USGS). This analysis complements the USGS critical minerals determination in three aspects. First, the DOE assessment is performed from a global perspective, while the USGS analysis focusses on the importance of minerals to the U.S. economy. Second, this report focuses on the importance of materials to clean energy technologies, rather than to the economy in general. Lastly, this study is forward looking to 2035 based on clean energy deployment scenarios, whereas the USGS assessment is retrospective. Materials evaluated in this report that do not appear in the USGS Critical Minerals List include copper, uranium, electrical steel, and SiC. A draft version of this report received ~80 public comments related to supporting data and methodological improvement. Those comments have been incorporated as much as possible where appropriate. Highlights of findings from this 2023 CMA include: Rare earth materials (neodymium, praseodymium, dysprosium, and terbium) used in magnets in electric vehicle (EV) motors and wind turbine generators continue to be critical. While dysprosium (Dy) and terbium (Tb) are both heavy rare earth elements that serve the same function in magnets, the criticality of Tb is slightly lower than that for Dy in the short term due to the widespread use of Dy in high-grade magnets and Tb’s present role as a substitute. Similarly, praseodymium (Pr) is critical in the medium term but only near critical in the short term because it is more substitutable in magnets than neodymium (Nd); Materials used in batteries for EVs and stationary storage are now considered to be critical. While cobalt (Co) was found to be critical in this and previous reports, lithium (Li) becomes critical in the medium term due to its broader use in various battery chemistries and the rampant growth of the EV industry. Natural graphite is a new addition in this assessment and is also found to be critical; Platinum group metals used in hydrogen electrolyzers, such as platinum (Pr) and iridium (Ir), are critical due to an increased focus on hydrogen technologies to achieve net zero carbon emissions, while those used in catalytic converters, such as rhodium (Rh) and palladium (Pd), were screened out due to the decreased importance of catalytic converters in the medium term; Gallium (Ga) continues to be critical due to its use in light-emitting diodes (LEDs). In addition, the use of Ga has increased in magnet manufacturing and in semiconductor in forms such as gallium arsenide (GaAs) or gallium nitride (GaN); Major materials like Aluminum (Al), copper (Cu), nickel (Ni), and silicon (Si) move from noncritical in the short term to near critical in the medium term due to their importance in electrification; Electrical steel is near critical due to its use in transformers for the grid and electric motors in EVs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

An Assessment of the Effectiveness of the AGATE Program Management Model

This report describes the collaborative program model chosen to implement an aeronautics research and technology program from 1994 through 2001: the Advanced General Aviation Transport Experiments (AGATE) Program. The Program had one primary objective: to improve the ability of the General Aviation industry to adopt technology as a solution to fulfill public benefit objectives. The primary objective of this report is to assess the program s ability to meet a combination of "effectiveness measures" from multiple stakeholders. The "effectiveness" of any model forms the foundation of legitimate questions for policy makers and professional federal managers. The participants rated AGATE as achieving its primary objectives and rating well on effectiveness in most areas, with high measures for relevance, cost, speed and public benefit, but lower measures for institutional fit and flexibility at dealing with the larger NASA organizational structure. This pattern mirrors private sector surveys and represents a tradeoff between the benefits of tailoring a program using partnering, versus the changes necessary within the institutional structure to support such tailoring.

Warner, Timothy P.↗

Forecasting distributed energy resources adoption for power systems

Failing to incorporate accurate distributed energy resource penetration forecasts into long-term resource and transmission planning can lead to cost inefficiencies at best and system failures at worst. We have developed an open-source tool that employs an advanced Bass specification to calibrate and forecast technology adoption. The advanced specification includes geographic clustering, exogenously estimated market size, and dynamic time steps. Training on historical adoption of rooftop photovoltaics at the U.S. county-level and using detailed techno-economic estimates, our model achieves a two-year average mean-absolute-percentage-error of 19% in predicting system counts at the county-level, weighted by population. Model error was negatively correlated with market maturity - the error was 12% for counties in states with at least 28 W-per-capita of installed capacity. The advanced specification significantly reduces unweighted forecasting percent error compared to a conventional Bass specification: from 196% to 25% for capacity and from 226% to 22% for system count.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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↗