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Modeling Distributed Generation in California

In support of analysis for the biennial Integrated Energy Policy Report, the California Energy Commission and the National Renewable Energy Laboratory have partnered to study the growth of distributed energy resources in California. This study involves the use of National Renewable Energy Laboratory's Distributed Generation Market Demand model, available at https://www.nrel.gov/analysis/dgen/, to project statewide adoption of distributed photovoltaics and paired storage. Key outcomes of the collaboration include: • Improved representation of California building stock, load profiles, historical adoption, and tariffs, including the net billing tariff, in the dGen model; • Trained CEC staff members to use and adapt the dGen model for their specific needs; • Developed a methodology for representing emerging consumer segments to potentially adopt distributed energy resources, including low-income, multifamily, and renter-occupied buildings; • Forecasted solar photovoltaic and paired storage growth in California using a common set of modeling parameters. This report describes the multiyear effort, which includes a discussion of: • Methodology and data employed in adapting the Distributed Generation Market Demand model for California to forecast solar photovoltaic and storage statewide through 2040; • Steps taken to modify the base model to forecast solar photovoltaic adoption in emerging market segments such as multifamily or renter-occupied homes or both; • Future enhancements of the model.

14 SOLAR ENERGY↗

U.S. Department of Energy Collegiate Wind Competition 2025: Rules - Phases 2 and 3

The U.S. Department of Energy (DOE) Wind Energy Technologies Office's (WETO) Collegiate Wind Competition (CWC, also referred to as the "competition" in this rules document) invites interdisciplinary teams of undergraduate students from a variety of academic programs to solve complex wind energy challenges. Through the competition, WETO intends to offer students direct industry experience, valuable exposure to wind energy career pathways, and greater knowledge of wind energy's potential to contribute to a clean energy future. The competition will select up to 35 teams to start, making them eligible to compete for a cash prize pool of up to $280,000. Each year, the competition identifies a new challenge and set of activities that address real-world research questions, thus demonstrating skills that students will need to work in the wind or wider renewable energy industries. The Collegiate Wind Competition 2025 challenge requires participants to compete simultaneously in four contests: 1) Turbine Design Contest: Design, build, and present a unique, wind-driven power system. 2) Turbine Testing Contest: Test the wind turbine in a competition wind tunnel at the final event. 3) Project Development Contest: Research wind resource data, transmission infrastructure, and environmental factors to create a site plan and financial analysis for a hypothetical wind farm. 4) Connection Creation Contest: Partner with wind industry professionals, raise awareness of wind energy in your local community, and work with local media to promote your team's accomplishments. The competition does not prescribe a power system market or wind regime. It is expected that each team will participate in all four contests.

Collegiate Wind Competition↗

Power and Natural Gas Systems Interface Study

Power systems worldwide are becoming more reliant on energy from natural gas, wind, and solar, posing potential reliability and coordination challenges from the tighter coupling of these infrastructure systems. This paper proposes a framework for the market-based coordination of electricity and natural gas system operations. The proposed framework includes a power system model that accounts for flexibility in the commitment of power plants with short start-up and shut-down times, coupled with a dynamic gas model that simulates when gas cannot be delivered to generators. The capabilities of the framework are illustrated using real-world electric power and gas systems, including scenarios around wind and solar penetrations and the analysis of time-variant, “shaped flow” gas nominations. Our results indicate that coordination between power and gas systems improves total gas delivery and reduces out-of-merit order dispatch in the electricity system, and that shaped flows may reduce unserved gas in systems with high penetrations of wind and solar.

coordinated operation↗

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗

Assessing the New Home Market Opportunity: Case Study and Cost Modeling for Solar and Storage in 2030

Residential solar and storage markets are growing in the United States. With approximately 1 million new homes constructed every year, this represents a significant opportunity for solar and storage installations. Some homebuilders have begun to build new homes with solar and storage included as a standard offering. It is not clear how solar and storage is incorporated into the new construction process and at what cost. Further, it is unclear what barriers or opportunities exist to scale this model nationwide. To fill this gap in the literature, this research conducts a case study of Mandalay Homes' new solar and storage community in Arizona to gather lessons learned. From this foundation, we further generate a set of pathways to reduce install costs and expand solar and storage market penetration in this sector. To model existing and 2030 solar and storage costs, we use the National Renewable Energy Laboratory's (NREL's) bottom-up cost model. This modeling is further informed by 12 interviews conducted with new home builders, solar contractors, and other subject matter expert organizations. Our case study analysis generated three key considerations for other homebuilders including: 1. Educating local permitting, inspection, and in some cases utility officials on solar and storage products, designs, and code compliant building practices may be required. The need for education may decline as more local governments and utilities review and approve solar and storage projects. 2. Incorporating solar and storage systems into the homebuilding process can add complexity and related coordination challenges. This does not need to result in home construction delays, but can result in costly contractor "dry runs" to construction sites. 3. Deploying solar and storage at the time of new construction has significant economies of scale, which can improve the value proposition of the systems. The case study, extant literature, and interviews were used to model both existing and future solar and storage installation costs at time of new construction. Here, we find three key cost reduction opportunities relating to solar and battery storage hardware, customer acquisition, and overhead. If future contractors can maximize the cost reduction opportunities outlined here, residential new construction costs could decline by 8 - 25% by 2030, depending on the modeled scenario. Though we expect costs to decline through 2030, it is unclear which of these scenarios may ultimately appear. Interviewees further identified a variety of barriers across each cost category that could temper the savings shown here. At the same time, interviewees described several pathways to scale the new construction solar and storage market, beyond installation cost savings. Interviewees confirmed that changes in finance, rate design, resilience policies, deployment mandates, and DER aggregation could all support more market adoption than seen today. These findings suggest that there are significant opportunities to expand new construction markets and this research can serve as a baseline to assess progress in this segment through 2030.

14 SOLAR ENERGY↗

Parametric analysis on optimized design of hybrid solar power plants

There is increasing interest in utility-scale solar power plants with storage which can flexibly dispatch renewable energy to the grid. However, plant design possesses many degrees of freedom and non-obvious trade-offs in performance. Software tools can estimate or optimize the performance of a specific plant configuration under market and weather conditions of interest; the associated cost parameters and operating assumptions strongly influence estimates of plant performance and decisions regarding optimal sizing. We employ the National Renewable Energy Laboratory's Hybrid Optimization and Performance Platform, which incorporates optimal dispatch when evaluating plant performance, and investigate the sensitivity to weather and market conditions, operating limitations, and the presence of a capacity-based incentive. We demonstrate changes in plant performance and optimal sizing with respect to these inputs and discuss implications. Here results show that PV-with-battery designs are more profitable under our assumptions, but that designs including a concentrated solar power (CSP) system produce significantly greater annual energy; and that CSP-with-thermal energy storage designs maximizing the benefit-to-cost ratio have an input-dependent linear relationship between the CSP field solar multiple and the hours of storage as the project budget varies.

14 SOLAR ENERGY↗

Decarbonizing Medium- & Heavy-Duty On-Road Vehicles: Zero-Emission Vehicles Cost Analysis

We simulate adoption and energy consumption of zero-emission vehicles (ZEVs) in the medium and heavy duty (MD/HD) sector. With continued improvement in ZEV technologies, total-cost-of-driving parity with conventional vehicles is achievable by 2035 for all MD/HD vehicle classes. Two technological solutions – battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs) are viable in multiple market segments, offering alternative pathways for decarbonization. In this scenario, ZEV sales reach 99+% by 2045 and 42% by 2030. 80% of the MD/HD stock transitions to ZEVs by 2050, reducing CO2 emissions by 69% from 2019. Disparities in adoption rate and vehicle usage between vehicle classes and between short and long-haul applications highlight opportunities for targeted policies (to reduce emissions it is critical to understand what vehicles transition to ZEV, not just how many vehicles). Results are highly sensitive to assumed fuel prices, technology improvement trajectories, adoption decision-making, and assumptions about future freight demand and vehicle use.

33 ADVANCED PROPULSION SYSTEMS↗

Economic Incentives for Agrivoltaics Systems with Commodity Crops in the Midwestern United States

Declining costs of photovoltaic (PV) technology and rising market and policy incentives are leading to the growing deployment of PV on cropland in the US Midwest, leading to concerns about the displacement of food and feed crop production. Agrivoltaic (AV) technology enables the dual use of land by co-locating PV energy and crop production, potentially reducing land-use competition with crop production. We develop a benefit-cost analysis framework to compare the net economic returns from AV to those with stand-alone PV and crop production on a representative field and show conditions under which AV can be more profitable for both a solar developer and a farmer. We integrate it with a crop and solar energy model to simulate the performance of various field designs and space and height configurations in AV systems to accommodate soybean production with conventional farm equipment under representative conditions in the US Midwest. We find that an AV system with soybean production is less profitable than PV alone for a solar developer due to the high capital costs of raising panel height, and less profitable for a farmer than leasing land for PV due to its adverse effects of shading on crop yield. We discuss the changes in technology and market prices of solar energy and soybeans that are necessary to make the AV system profitable for solar developers and farmers. We show that AV can worsen rather than mitigate the conflict between food crops and solar energy production in the Midwest.

14 SOLAR ENERGY↗

Play Fairway Analysis Retrospective GeoRePORTs

NREL, as part of the Play Fairway Analysis (PFA) Retrospective and with assistance from PFA PIs, completed GeoRePORTs for the sites identified in Phases 1&2 of the DOE PFA projects. The GeoRePORT (geothermal resource portfolio optimization and reporting technique) uses two factors to describe a specific project; grade and project readiness level. Grade describes the quality or potential of a project while project readiness level shows the progress of research and development. The categories that factor into the total grades and readiness levels are Geological, Technical, and Socio-Economic.

15 GEOTHERMAL ENERGY↗

Novel Proppant Logging Technique for Infill Drilling of Unconventional Shale Wells

Summary During the development of an unconventional play, wells are drilled and completed in batches, and depending on the development plans, current and expected energy market trends, as well as other developmental considerations, new wells are drilled and hydraulically fractured later near existing producing laterals. This creates challenges in terms of optimizing resource recovery and reducing interwell communication. A novel approach is proposed that utilizes systematic composite sampling and analysis of drilling mud returns to look for and quantitatively identify sand particles. The workflow involves cleaning, drying, and segregation of samples into sizes of interest to us (size distribution of pumped proppant in offset parent wells). These samples are imaged at a very high resolution and analyzed for grains using characteristic optical imaging properties to classify proppant sand particles using computer vision algorithms. Further analysis, such as elemental compositional analysis, is used to validate the results from the imaging workflow. We present a case study from the Permian Basin, where a new child well was used as a test case to prove this technology at the Hydraulic Fracturing Test Site (HFTS-2) in Delaware Basin. We introduce new proppant parameters that help identify sustained proppant zones vs. localized propped fractures. We have used additional diagnostics and data collected at the test site to validate observations from the proppant log and have successfully interpreted significantly propped vs. unpropped zones. A key finding from this test has been the significant proppant transport distances observed away from parent wells. Observable proppant was found at a lateral distance of approximately 425 m for one set of parent wells and more than 915 m for another set of parent wells. While a major limitation of this technique is the sampling rate, given adequate sampling, the proposed technology represents a systematic and one-of-a-kind interpretation of spatial proppant distribution while drilling infill wells. It provides us with unique opportunities to better understand the current state of the reservoir being targeted, including zones that are likely highly drained relative to others, and how the planned hydraulic fracturing of child wells can be improved.

Energy & Fuels↗

Liquid Air Combined Cycle TM for Power and Storage

Liquid Air Combined Cycle (LACC) is a hybrid liquid air energy storage (LAES) system combining energy storage with a combustion turbine to enable large-scale, long-duration energy storage (LDES) while reducing fuel intensity compared to the current state-of-the-art. The LACC technical approach employs proven equipment (cryogenic refrigeration, storage, tanks, pumps, gas turbines, exhaust heat recovery equipment, and turbines) to limit technical risk to a novel organic Rankine cycle (ORC), which was evaluated during this project and found to be feasible. Moreover, LACC storage is safe and relatively compact, to facilitate siting close to loads and within metropolitan regions. The air storage medium is freely available and eliminates supply chain constraints. LACC uses cryogenic air as a storage medium and a gas turbine as the source of heat to drive the discharge process. LACC is distinguished from other LAES technologies by several factors. The charge and discharge processes are decoupled so that cryogenic liquid air is the only storage medium. Other systems also store the higher temperature thermal energy from the liquefaction process in an additional medium. Subsequently, LACC focuses on maximization of the discharge energy and power. LACC also permits the use of commercially available cryogenic refrigeration and storage technologies to increase competition. This project identified product requirements to support market entry and commercialization of the LACC in modular units of approximately 117 MW, each drawing liquid air from customary cryogenic storage tanks capable of storing 75 GWh of dispatchable energy, more than pumped storage hydro or compressed air energy storage technologies. An economic analysis identified the specific liquid air consumption (quantity of liquid air per unit of discharge energy) as a critical parameter. Minimizing the air consumption reduces the specific capital cost ($\$ $/kW) for charging and discharging equipment by reducing the size of piping and turbomachinery. Likewise, the specific cost of energy capacity ($\$ $/kWh) is reduced by increasing the energy deliverable from a given size tank. The cycle was analyzed to identify the optimal equipment selection and operating conditions, which in turn were combined with quotes and cost estimates to calculate the cost of energy from an LACC system. A substantial effort was focused on the ORC, which draws low-temperature heat from the gas turbine exhaust and condenses at low temperature using the cryogenic liquid air as a heat sink. Alternative turbomachinery arrangements were evaluated for feasibility and cost. A technology maturation plan lays out a low-risk approach to development of the novel ORC components and demonstration of LACC technology at pilot scale.

25 ENERGY STORAGE↗

dGen (Distributed Generation Market Demand) Model Data: Alpha Release

Open sourced data needed to run the basic alpha release version of the dGen model. Includes a pre-generated agent file of 100,000 agents in pickle file format along with the base schema and table data in parquet format that are needed to create a postgreSQL database for the model to interact with.

14 SOLAR ENERGY↗

Aero-Mechanical Design Methodology for Subsonic Civil Transport High-Lift Systems

In today's highly competitive and economically driven commercial aviation market, the trend is to make aircraft systems simpler and to shorten their design cycle which reduces recurring, non-recurring and operating costs. One such system is the high-lift system. A methodology has been developed which merges aerodynamic data with kinematic analysis of the trailing-edge flap mechanism with minimum mechanism definition required. This methodology provides quick and accurate aerodynamic performance prediction for a given flap deployment mechanism early on in the high-lift system preliminary design stage. Sample analysis results for four different deployment mechanisms are presented as well as descriptions of the aerodynamic and mechanism data required for evaluation. Extensions to interactive design capabilities are also discussed.

vanDam, C. P.↗

Water Vapor Sensors Go Sky-High to Assure Aircraft Safety

JPL used a special tunable diode laser, which NASA scientists could tune to different wavelengths, like a radio being tuned to different frequencies, to accurately target specific molecules and detect small traces of gas. This tunable diode laser was designed to emit near-infrared light at wavelengths absorbed by the gas or gases being detected. The light energy being absorbed by the target gas is related to the molecules present. This is usually measured in parts per million or parts per billion. Multiple measurements are made every second, making the system quick to respond to variations in the target gas. NASA scientists developed this technology as part of the 1999 Mars Polar Lander mission to explore the possibility of life-giving elements on Mars. NASA has since used the tunable diode laser-based gas sensor on aircraft and on balloons to successfully study weather and climate, global warming, emissions from aircraft, and numerous other areas where chemical gas analysis is needed. SpectraSensors, Inc., was formed in 1999 as a spinoff company of JPL, to commercialize tunable diode laser-based analyzers for industrial gas-sensing applications (Spinoff 2000). Now, the San Dimas, California-based firm has come back to the market with a new product featuring the NASA-developed instrument for atmospheric monitoring. This instrument is now helping aircraft avoid hazardous weather conditions and enabling the National Weather Service to provide more accurate weather forecasts.

Source record↗

Prediction-Based Approaches for Generation of Noise-Power-Distance Data with Application to Urban Air Mobility Vehicles

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise-power-distance (NPD) data for use within AEDT. One utilizes AEDT’s fixed-wing aircraft modeling approach and the other utilizes the rotary-wing aircraft modeling approach.

noise-power-distance↗

Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem

The International Space Station National Lab (ISSNL) was established through Congressional authority in 2005 and has been managed by a nonprofit called the Center for the Advancement of Science in Space (CASIS) since 2011 to support research, development, education, and commercial activities in low-Earth orbit (LEO). NASA leadership is considering next steps for microgravity and orbital activities in LEO in preparation for the retirement of the International Space Station (ISS) and transition to Commercial LEO Destinations (CLDs) in the 2030 timeframe. Specifically, our study team within the NASA Office of Technology, Policy, and Strategy addressed the question: What are potential models for an ISS National Lab facilitating government-funded or subsidized activities on a commercial LEO platform after the transition of the ISS to one or more private platforms? To inform the trade space of potential models, we conducted over 40 discussions with stakeholders internal and external to NASA and reviewed over 35 documents related to LEO legislation, commercialization, models, and activities. Following the extensive literature review and discussions with diverse stakeholders, we defined and evaluated six models, in addition to the current ISSNL model. We assessed each model across three possible future scenarios (dynamic, steady, and limited growth of the commercial LEO market and activities) and across five stakeholder-driven model evaluation criteria (ability to meet NASA’s needs, adaptability, opportunity for collaboration, market sustainability, and equity and accessibility). The six models in the future trade space were: • Government Research Broker: Customizable research efforts on transport vehicles and CLDs • Innovation Campus: Modern terrestrial campus with workforce focus • Anchor Tenant: Long-term, substantial agreement for leasing space on a single CLD • Fee for Service: Free market approach with NASA-sponsored grants and service/data buys • Matchmaker: Neutral third-party connecting users to platforms • Institute Network: Network of separate but related efforts to enable commercial scaling The Government Research Broker model performed best across the scenarios, followed by Innovation Campus, Anchor Tenant, and Fee for Service. While Matchmaker and Institute Network exhibited positive aspects, the two models performed most favorably in future scenarios with well-established communities and markets. The six models presented in this study are representative of the potential trade space and are illustrative examples. NASA leadership can adjust models as desired to align to their priorities more closely by using combinations of the unique model features provided in our analysis. The optimal model is likely a combination of features from multiple models. Building upon this work to best position NASA and the diverse stakeholders of LEO activities for success post-ISS, further work will explore the near-term impact of preparing for the transition of the ISS to CLDs by identifying opportunities for modifying the current ISSNL-CASIS partnership. ACKNOWLEDGEMENTS We thank the many reviewers and discussants, internal and external to NASA, that contributed to the work.

Erica Rodgers↗

Prediction of Noise-Power-Distance Data for Urban Air Mobility Vehicles

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise-power-distance (NPD) data for use within AEDT. One utilizes the AEDT fixed-wing aircraft modeling approach and the other utilizes the AEDT rotary-wing aircraft modeling approach.

noise-power-distance↗

On the Modeling of UAM Aircraft Community Noise in AEDT Helicopter Mode

In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations. Prior work focused on modeling UAM aircraft within AEDT under fixed-wing mode. This paper addresses the modeling of UAM aircraft under helicopter mode, using requisite noise-power-distance data generated through analysis. Results are compared with those from the fixed-wing approach and a hybrid approach. The latter models some flight segments in fixed-wing mode and others in helicopter mode.

aircraft community noise↗