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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Designing A Lunar Terrain Vehicle: Thermal Challenges

The Lunar Terrain Vehicle (LTV) is an unpressurized rover that will be used to transport astronauts on the South Pole of the moon under the Artemis Program. The National Aeronautics and Space Administration (NASA) will be partnering with an American industry partner to develop the LTV. This paper discusses the thermal challenges faced when designing a crewed lunar vehicle concept and shares a concept that addresses these constraints. One of the most difficult aspects of the design is surviving the cold lunar night on the South Pole which includes permanently shadowed regions (PSR) that can have an extended lunar night duration of 125 hours. Other challenges are critical component temperature limits and programmatic constraints.

Zaida Y. Hernandez↗
NASA NTRS2022

SWOT and NISAR Boom Ground Deployment Test Challenges & Resolution

NASA’s Jet Propulsion Laboratory is developing two new spacecraft that use radar instruments to characterize temporal changes in the Earth’s surface with unprecedented precision (Figure 1). Both the Surface Water Ocean Topography (SWOT) and the NASA-ISRO Synthetic Aperture Radar (NISAR) spacecraft utilize large, precision flight deployable booms to properly position and support their instrument reflectors. The SWOT spacecraft includes two nearly identical reflector booms, each of which have similar flight deployable hinge designs. The NISAR spacecraft has a single reflector boom, with four unique hinge designs. These booms each undergo a multi-staged flight deployment sequence on orbit to transition from the launch stowed configuration to the science configuration within days of launch (Figure 2). The SWOT and NISAR Projects faced significant challenges relevant to requirement verification as well as hardware safety in their approach to ground testing these large flight deployables. This report summarizes flight deployable system design decisions that contributed to ground testing challenges. The report also summarizes the architecture trade study conducted for ground deployment testing. A summary of key issues encountered during flight deployable ground testing with the chosen common gravity offload system ensues, with discussion of the issues and mitigation measures implemented by both Projects that ultimately enabled successful flight subsystem-level full range of motion ground tests. Recommendations and lessons learned are offered to facilitate ground testability of future analogous large scale flight deployables.

Waters, Kyle C.↗
NASA NTRS2020

Clouds Around the World: How a Simple Citizen Science Data Challenge Became a Worldwide Success

Citizen science is often recognized for its potential to directly engage the public in science, and is uniquely positioned to support and extend participants’ learning in science. In March 2018, the Global Learning and Observations to Benefit the Environment (GLOBE) Program, NASA’s largest and longest-lasting citizen science program about Earth, organized a month-long event that asked people around the world to contribute daily cloud observations and photographs of the sky (15 March–15 April 2018). What was considered a simple engagement activity turned into an unprecedented worldwide event that garnered major public interest and media recognition, collecting over 55,000 observations from 99 different countries, in more than 15,000 locations, on every continent including Antarctica. The event was called the “Spring Cloud Challenge” and was created to 1) engage the general public in the scientific process and promote the use of the GLOBE Observer app, 2) collect ground-based visual observations of varying cloud types during boreal spring, and 3) increase the number and locations of ground-based visual cloud observations collocated with cloud-observing satellites. The event resulted in roughly 3 times more observations than during the historic and highly publicized 2017 North American total solar eclipse. The dataset also includes observations over the Drake Passage in Antarctica and reports from intense Saharan dust events. This article describes how the challenge was crafted, outreach to volunteer scientists around the world, details of the data collected, and impact of the data.

GLOBE↗
NASA NTRSDate not supplied

Early Artemis Surface Navigation: Challenges, Approaches, and Opportunities

The early Artemis missions represent the return of humanity to the surface of the Moon and provide opportunities for meeting early science and exploration goals. Position, Navigation, and Timing (PNT) capabilities are a fundamental element and inform operational design, flight rules, and the ability to meet these. This paper provides an overview of the needs, potential implementations, challenges, and concepts of operations in the initial human surface missions, Artemis III and IV. These early excursions are a crucial learning opportunity to gain more experience in the actual operational environment for Artemis V and beyond where exploration objectives and complexity increases. As part of the study, the team defined a threshold performance navigation requirement (including position and orientation) to meet crew safe return and assessed a breadth of navigation approaches that could be deployed to augment the crew’s baseline navigation capability. Data was collected in terms of size, mass, power, operational constraints, environment constraints, interface, and performance to define the technical metrics. Given these, the trade team conducted polling among the various Artemis Campaign elements to capture preference, integration challenges, and operational impacts. These were used to develop weightings and inform a ranked order of solutions across each of the early missions. The results of the study recommended augmenting the initial orientation capability with additional navigation sensors to provide coarse position and heading information to the crew to enable a safe contingency walk-back when out of video range. The team identified opportunities for embedding this hardware in future scenarios to provide an integrated solution. With the deployment of the LunaNet’s Lunar Augmented Navigation System, the crew will be able to maintain accurate real-time navigation knowledge with minimal physical impacts. Discussion of future testing and continued analysis is included in this paper. These forward plans and long-term architecture systems will enable a powerful navigation approach for orbiting and surface users, enabling a high level of scientific return and crew safety.

Evan Anzalone↗
NASA NTRSDate not supplied

Early Artemis Surface Navigation: Challenges, Approaches, and Opportunities

The early Artemis missions represent the return of humanity to the surface of the Moon and provide opportunities for meeting early science and exploration goals. Position, Navigation, and Timing (PNT) capabilities are a fundamental element and inform operational design, flight rules, and the ability to meet these. This paper provides an overview of the needs, potential implementations, challenges, and concepts of operations in the initial human surface missions, Artemis III and IV. These early excursions are a crucial learning opportunity to gain more experience in the actual operational environment for Artemis V and beyond where exploration objectives and complexity increases. As part of the study, the team defined a threshold performance navigation requirement (including position and orientation) to meet crew safe return and assessed a breadth of navigation approaches that could be deployed to augment the crew’s baseline navigation capability. Data was collected in terms of size, mass, power, operational constraints, environment constraints, interface, and performance to define the technical metrics. Given these, the trade team conducted polling among the various Artemis Campaign elements to capture preference, integration challenges, and operational impacts. These were used to develop weightings and inform a ranked order of solutions across each of the early missions. The results of the study recommended augmenting the initial orientation capability with additional navigation sensors to provide coarse position and heading information to the crew to enable a safe contingency walk-back when out of video range. The team identified opportunities for embedding this hardware in future scenarios to provide an integrated solution. With the deployment of the LunaNet’s Lunar Augmented Navigation System, the crew will be able to maintain accurate real-time navigation knowledge with minimal physical impacts. Discussion of future testing and continued analysis is included in this paper. These forward plans and long-term architecture systems will enable a powerful navigation approach for orbiting and surface users, enabling a high level of scientific return and crew safety.

Evan Anzalone↗
NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗
NASA NTRS2024

Mars Surface Power Generation Challenges and Considerations

Once the challenges of reaching and landing safely on Mars have been met, the first human explorers will be faced with the challenge of finding sufficient energy to power the systems they will need for a healthy and productive stay on the surface and for their ascent back to orbit.

Moon↗
NASA NTRSDate not supplied

James Webb Space Telescope Navigation Optimization Challenges

This paper details the orbit determination, solar radiation pressure (SRP) modeling, and station-keeping maneuver planning for the NASA James Webb Space Telescope during the routine science phase of the mission. The complexities of SRP modeling driven by the vehicle’s large area, attitude profile, and attitude constraints for maneuver execution entail unique challenges for spaceflight navigation. The techniques utilized to combine predictive attitude and maneuver targeting modeling were refined using the experiences and data accumulated during and following the commissioning phase. The Navigation Team at NASA Goddard Space Flight Center’s Flight Dynamics Facility responded to these challenges and implemented methods for trajectory optimization and improving maneuver efficiency.

Flight Dynamics↗
NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗
NASA NTRSDate not supplied

Space Crop Production Gaps and Challenges

As astronauts venture farther from Earth, and stay for longer periods, the space food system will increase in importance. Crop production can supplement a pre-packaged space diet to provide nutrition and dietary variety for space crews. In future missions, bioregenerative approaches may be used to generate a larger percentage of the diet, as well as help to reduce life support system burdens and resupply from Earth. Plants may also provide behavioral health benefits to crew members living in the isolated, confined environment of a space habitat. A number of unique challenges exist for growth of plants in microgravity and on other reduced gravity surfaces like the moon and Mars. Testing plant growth inside the Veggie and Advanced Plant Habitat (APH) chambers on the International Space Station is allowing us to understand the impacts of gravity and spaceflight on crop growth, nutritional content, acceptability, and the importance of plants to astronauts living and working away from Earth. We are also gaining a better understanding of food safety concerns and the behavior of space plant microbiomes and plant pathogens, but major gaps in knowledge remain. As we move from research towards operational space crop production to enable exploration, there are numerous gaps in technology, knowledge, and practice related to space crop growth that must be addressed. Research and development in key focus areas such as effective water and nutrient delivery at variable gravity levels, autonomous plant health monitoring, growth system cleaning and disinfection, and selection of ideal space crops are needed to fill these gaps. Breeding or engineering custom space crops may impact areas including plant growth and development, plant physiology, produce nutrition, organoleptic acceptability, and post-harvest characteristics, and these may further enable space crop production scenarios. Space crop challenges are multifaceted and require diverse interdisciplinary teams working together to develop effective solutions. Solving these requires an array of skill sets from across the biological and physical sciences, engineering, and human social sciences. Solutions to help ensure food security off-Earth may also translate to more sustainable terrestrial crop production approaches, and regular dialog between industry, academia, and government organizations working in related fields benefit all. Additional help can come from engagement with student researchers at various levels through courses, participatory science projects, and open science activities which can provide useful data. Global coordination and integration between space agencies and partners will be essential.

Gioia Donna Massa↗
NASA NTRSDate not supplied

Boundary-Layer Cloud Modeling Challenges on the North Slope of Alaska

The accurate modeling and prediction of cloud base heights is critical for energy balance calculations and aviation operations, alike. Low-level (i.e., boundary-layer) Arctic clouds can be difficult to model, making prediction of formation and dissipation challenging. Primarily mixed-phase, these clouds typically contain low quantities of supercooled liquid water and often slowly precipitate relatively small amounts of moderately and heavily rimed snow particles. While this appears to be the predominant cloudy state on the North Slope of Alaska (NSA), the delicate balance of microphysical, dynamical, radiative, surface coupling, and advective processes can rapidly shift to heavy snow (with various degrees of riming) or to a complete dissipation of the cloud layer without any precipitation, depending on the dominant processes. Here we strive to disentangle these various processes. First, we compare the predictive performances of four different numerical weather models in forecasting the presence and base-heights of low-level clouds: the High-Resolution Rapid Refresh - Alaska (HRRR-AK) model, the Polar Weather Research and Forecasting (Polar WRF) model, the Unified Model (UM), and the European Centre for Medium-range Weather Forecasting (ECMWF) model. Initial results comparing model output at two U.S. Department of Energy Atmospheric Radiation Measurement (AMT) NSA sites, during the fall season in 2019 and 2022, show that the UM slightly outperforms the HRRR-AK in terms of accurately forecasting the presence of a low-level cloud layer (89% of the time). All models have a significant bias of 300 to 800 meters in forecasting cloud base height (lower than is observed); however, the UM and ECMWF models have the lowest biases. Finally, a case study for a particularly challenging April 2017 thin-cloud event is presented, wherein we compare the performance of four different bulk microphysical parameterization schemes using a higher-resolution large eddy simulation (LES) model, the WRF-LES. Initial results show that the Thompson scheme was the only one able to reproduce and sustain a substantial supercooled liquid layer, but it was unable to reproduce the transition from a deep, liquid-rich cloud to a thin layer with moderately and heavily rimed precipitation. This is the first step in linking simulated LES-scale riming processes with those parameterized at a coarser mesoscale model scale. This has important implications for forecasting low-level clouds in an operational environment, given the efficiency of the riming process.

cloud base heights↗
NASA NTRSDate not supplied

James Webb Space Telescope Navigation Optimization Challenges

This paper details the orbit determination, solar radiation pressure (SRP) modeling, and station-keeping maneuver planning for the NASA James Webb Space Telescope during the routine science phase of the mission. The complexities of SRP modeling driven by the vehicle’s large area, attitude profile, and attitude constraints for maneuver execution entail unique challenges for spaceflight navigation. The techniques utilized to combine predictive attitude and maneuver targeting modeling were refined using the experiences and data accumulated during and following the commissioning phase. The Navigation Team at NASA Goddard Space Flight Center’s Flight Dynamics Facility responded to these challenges and implemented methods for trajectory optimization and improving maneuver efficiency.

Flight Dynamics↗
NASA NTRS2023

Comparative Analysis of Empirical and Machine Learning Models for Chla Extraction Using Sentinel-2 and Landsat OLI Data: Opportunities, Limitations, and Challenges

Remote retrieval of near-surface chlorophyll-a (Chla) concentration in small inland waters is challenging due to substantial optical interferences of various water constituents and uncertainties in the atmospheric correction (AC) process. Although various algorithms have been developed to estimate Chla from moderate-resolution terrestrial missions (∼10–60 m), the production of both accurate distribution maps and time series of Chla has proven challenging, limiting the use of remote analyses for lake monitoring. Here, we develop a support vector regression (SVR) model, which uses satellite-derived remote-sensing reflectance spectra () from Sentinel-2 and Landsat-8 images as input for Chla retrieval in a representative eutrophic prairie lake, Buffalo Pound Lake (BPL), Saskatchewan, Canada. Validated against in situ Chla from seven ice-free seasons (N ∼ 200; 2014–2020), the SVR model outperformed both locally tuned, -fed empirical models (Normalized Difference Chlorophyll Index, 2- and 3-band, and OC3) and Mixture Density Networks (MDNs) by 15–65%, while exhibiting comparable performance to a locally trained MDN, with an error of ∼35%. Comparison of Chla retrieval models, AC processors (iCOR, ACOLITE), and radiometric products (Rayleigh-corrected, surface, and top-of-atmosphere reflectance) showed that the best Chla maps and optimal time series (up to 100 mg m−3) were produced using a coupled SVR-iCOR system.

algal blooms↗
NASA NTRSDate not supplied

A Call To Action To Engage The Community To Meet The Challenges That Must Be Tackled To Make Electrified Aircraft Propulsion Real

Technology risk reduction is essential, as it is necessary to demonstrate the potential of Electrified Aircraft Propulsion (EAP). However, more is needed for implementation. The industry is leading EAP by developing a diverse community of novel vehicles from short-haul, small, urban-focused electric vertical takeoff and landing (eVTOL) to regional air mobility (RAM) and hybrid-electric, single-aisle transport category airplanes. There are a variety of novel EAP technologies for each of these novel vehicles. And the industry is not only looking at novel technology to advance the state of the art. Instead, the industry is looking to certify these novel aircraft through their regulatory authorities, such as the US Federal Aviation Administration (FAA), the European Union Aviation Safety Authority (EASA), Transport Canada Civil Aviation (TCCA), and Brazil’s Agência Nacional de Aviação Civil (National Civil Aviation Agency, ANAC), as well as other regulatory authorities. The NASA Electrified Powertrain Flight Demonstration (EPFD) project has partnered with two industry partners to advance integrated MW-class powertrain system technology demonstration that includes an assessment of their regulatory and standards gaps in their technology. The EPFD has conducted a generic regulatory gap analysis of hybrid electric engines that aligns with the industry partners’ efforts. The EPFD regulations and standards team is integrated into the industry standards community. The international industry standards community is wrestling with critical key challenges to certification. While some certification elements are proprietary, several technology elements cut across company propriety in aircraft engines (US 14 CFR Part 33 and EASA CS-E, regulations that only reflect reciprocating and turbine engines). The approach that several of these regulatory authorities have taken is to collaborate to address their challenges. The Certification Management Team (CMT) consists of the EASA, FAA, TCCA, and ANAC, and they have begun to address common questions, such as the Loss of Power Control (LOPC) for electric engines. They have reached out to the standards community to seek answers. The industry standards development organizations (SDO) have also looked ahead to address current regulations and standards gaps. The ASTM has built key committees in its ASTM F44 General Aviation Committee and F39 Aircraft Systems Committee. The SAE has established the E-40 Electric Propulsion and AE-10 High Voltage committees.

Standards↗
NASA NTRSDate not supplied

Space Crop Production Gaps and Challenges

As astronauts venture farther from Earth, and stay for longer periods, the space food system will increase in importance. Crop production can supplement a pre-packaged space diet to provide nutrition and dietary variety for space crews. In future missions, bioregenerative approaches may be used to generate a larger percentage of the diet, as well as help to reduce life support system burdens and resupply from Earth. Plants may also provide behavioral health benefits to crew members living in the isolated, confined environment of a space habitat. A number of unique challenges exist for growth of plants in microgravity and on other reduced gravity surfaces like the moon and Mars. Testing plant growth inside the Veggie and Advanced Plant Habitat (APH) chambers on the International Space Station is allowing us to understand the impacts of gravity and spaceflight on crop growth, nutritional content, acceptability, and the importance of plants to astronauts living and working away from Earth. We are also gaining a better understanding of food safety concerns and the behavior of space plant microbiomes and plant pathogens, but major gaps in knowledge remain. As we move from research towards operational space crop production to enable exploration, there are numerous gaps in technology, knowledge, and practice related to space crop growth that must be addressed. Research and development in key focus areas such as effective water and nutrient delivery at variable gravity levels, autonomous plant health monitoring, growth system cleaning and disinfection, and selection of ideal space crops are needed to fill these gaps. Breeding or engineering custom space crops may impact areas including plant growth and development, plant physiology, produce nutrition, organoleptic acceptability, and post-harvest characteristics, and these may further enable space crop production scenarios. Space crop challenges are multifaceted and require diverse interdisciplinary teams working together to develop effective solutions. Solving these requires an array of skill sets from across the biological and physical sciences, engineering, and human social sciences. Solutions to help ensure food security off-Earth may also translate to more sustainable terrestrial crop production approaches, and regular dialog between industry, academia, and government organizations working in related fields benefit all. Additional help can come from engagement with student researchers at various levels through courses, participatory science projects, and open science activities which can provide useful data. Global coordination and integration between space agencies and partners will be essential.

Gioia Massa↗
NASA NTRSDate not supplied

A Call To Action To Engage The Community To Meet The Challenges That Must Be Tackled To Make Electrified Aircraft Propulsion Real

Technology risk reduction is essential, as it is necessary to demonstrate the potential of Electrified Aircraft Propulsion (EAP). However, more is needed for implementation. The industry is leading EAP by developing a diverse community of novel vehicles from short-haul, small, urban-focused electric vertical takeoff and landing (eVTOL) to regional air mobility (RAM) and hybrid-electric, single-aisle transport category airplanes. There are a variety of novel EAP technologies for each of these novel vehicles. And the industry is not only looking at novel technology to advance the state of the art. Instead, the industry is looking to certify these novel aircraft through their regulatory authorities, such as the US Federal Aviation Administration (FAA), the European Union Aviation Safety Authority (EASA), Transport Canada Civil Aviation (TCCA), and Brazil’s Agência Nacional de Aviação Civil (National Civil Aviation Agency, ANAC), as well as other regulatory authorities. The NASA Electrified Powertrain Flight Demonstration (EPFD) project has partnered with two industry partners to advance integrated MW-class powertrain system technology demonstration that includes an assessment of their regulatory and standards gaps in their technology. The EPFD has conducted a generic regulatory gap analysis of hybrid electric engines that aligns with the industry partners’ efforts. The EPFD regulations and standards team is integrated into the industry standards community. The international industry standards community is wrestling with critical key challenges to certification. While some certification elements are proprietary, several technology elements cut across company propriety in aircraft engines (US 14 CFR Part 33 and EASA CS-E, regulations that only reflect reciprocating and turbine engines). The approach that several of these regulatory authorities have taken is to collaborate to address their challenges. The Certification Management Team (CMT) consists of the EASA, FAA, TCCA, and ANAC, and they have begun to address common questions, such as the Loss of Power Control (LOPC) for electric engines. They have reached out to the standards community to seek answers. The industry standards development organizations (SDO) have also looked ahead to address current regulations and standards gaps. The ASTM has built key committees in its ASTM F44 General Aviation Committee and F39 Aircraft Systems Committee. The SAE has established the E-40 Electric Propulsion and AE-10 High Voltage committees.

Standards↗