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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Improved loss functions for machine-learned atomic potentials

Machine learning (ML) has become an invaluable tool across a wide array of domains in science as researchers find new ways to leverage its predictive power. This is especially true in chemistry, where ML is used to fit chemical properties or desirable attributes to the local structure of molecules and materials. In the pursuit of greater accuracy, it is relatively simple to increase the size or complexity of such models, although this often requires simultaneously seeking larger datasets in order to both fit and interpret the larger number of parameters. However, it is equally important to assess the quality and relative importance of the data and how these factors impact the training process. We, therefore, investigate the impact of using different loss functions for training neural network potentials (NNPs), as the loss function defines the error and parameter gradients used to train the NNP. In particular, we test the mean-squared error and Huber loss functions and, using insight from these functions, derive a new loss function based on the Asinh function, which yields significant improvement in the accuracy and generality of NNPs. We show that by discounting/minimizing errors and anomalies in the optimization process, both the Huber and Asinh loss functions improve the training of NNPs, leading to a final potential with a greater effective dimensionality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Proof-of-concept studies with a computationally designed M pro inhibitor as a synergistic combination regimen alternative to Paxlovid

As the SARS-CoV-2 virus continues to spread and mutate, it remains important to focus not only on preventing spread through vaccination but also on treating infection with direct-acting antivirals (DAA). The approval of Paxlovid, a SARS-CoV-2 main protease (M pro ) DAA, has been significant for treatment of patients. A limitation of this DAA, however, is that the antiviral component, nirmatrelvir, is rapidly metabolized and requires inclusion of a CYP450 3A4 metabolic inhibitor, ritonavir, to boost levels of the active drug. Serious drug–drug interactions can occur with Paxlovid for patients who are also taking other medications metabolized by CYP4503A4, particularly transplant or otherwise immunocompromised patients who are most at risk for SARS-CoV-2 infection and the development of severe symptoms. Developing an alternative antiviral with improved pharmacological properties is critical for treatment of these patients. By using a computational and structure-guided approach, we were able to optimize a 100 to 250 μM screening hit to a potent nanomolar inhibitor and lead compound, Mpro61. In this study, we further evaluate Mpro61 as a lead compound, starting with examination of its mode of binding to SARS-CoV-2 M pro . In vitro pharmacological profiling established a lack of off-target effects, particularly CYP450 3A4 inhibition, as well as potential for synergy with the currently approved alternate antiviral, molnupiravir. Development and subsequent testing of a capsule formulation for oral dosing of Mpro61 in B6-K18-hACE2 mice demonstrated favorable pharmacological properties, efficacy, and synergy with molnupiravir, and complete recovery from subsequent challenge by SARS-CoV-2, establishing Mpro61 as a promising potential preclinical candidate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Precision Reconstruction of Rational Conformal Field Theory from Exact Fixed-Point Tensor Network

The novel concept of entanglement renormalization and its corresponding tensor network renormalization technique have been highly successful in developing a controlled real-space renormalization group (RG) scheme. Numerically approximate fixed-point (FP) tensors are widely used to extract the conformal data of the underlying conformal field theory (CFT) describing critical phenomena. In this paper, we present an explicit analytical construction of the FP tensor for 2D rational CFT. We define it as a correlation function between the “boundary-changing operators” (BCO) on triangles. Our construction fully captures all the real-space RG conditions. We also provide concrete examples, such as Ising, Yang-Lee, and tricritical Ising models, to compute the scaling dimensions explicitly based on the corresponding FP tensor. The BCO descendants turn out to be an optimal basis such that truncation in bond dimensions naturally produces comparable accuracies with the leading existing FP algorithms. Interestingly, our construction of FP tensors is closely related to a strange correlator, where the holographic picture naturally emerges. Our results also open a new door toward understanding CFT in higher dimensions. Published by the American Physical Society 2025

Cheng, Gong (ORCID:0009000891587404)↗
DOE OSTI2022

Predicting the Cetane Number, Sooting Tendency, and Energy Density of Terpene Fuel Additives

Abstract Discovering renewable fuels and fuel additives is paramount in reducing carbon emissions from internal combustion engines. Terpenes, a group of compounds that can be synthesized from plant matter and microorganisms, have gained significant interest in recent years as promising candidates for fuels/additives. Terpenes are a diverse class of compounds that contain rings and methyl branches, resulting in high energy densities and optimal cold weather behavior. Their variation in bond order, carbon chains, and functional groups lead to varying degrees of soot formation and performance in existing engines. The present work leverages predictive models, namely artificial neural networks, to predict the cetane number (CN), sooting tendency (quantified with yield sooting index, YSI), and energy density (quantified with lower heating value, LHV) of terpenes and hydrogenated terpenes whose sooting propensities were previously determined through experimental means. Predicted sooting propensities of these terpenes are compared with experimental values, and predicted cetane numbers and energy densities are used to comment on the compounds’ ability to act as fuels/additives. Expected prediction errors for CN, YSI, and LHV, defined by blind test set median absolute error, are within 5.56 cetane units, 3.63 yield sooting index units, and 0.77 MJ/kg respectively. Additionally, the present work investigates a variety of correlation/dependence metrics for property-property relationships, furthering our understanding of how combustion-relevant properties are related.

09 BIOMASS FUELS↗
DOE OSTI2025

Machine learning-driven predictive resource management in complex science workflows

Here, the collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Visualizing Vehicle Acceleration and Braking Energy at Intersections along a Major Traffic Corridor

Automobiles approaching a controlled intersection need to brake and come to a full stop when the signal transitions from green to red, and the vehicle must later accelerate to normal speeds after the signal changes back to green. These stops and starts associated with normal signal changes lead to unnecessary energy consumption and vehicle emissions. Previous studies have revealed that the optimization of traffic intersections' signal controls and coordination facilitates smoother traffic flows with reduced stop-and-go driving, which can significantly reduce traffic congestion and unnecessary fuel waste. This paper presents an interactive visual analytics dashboard that allows transportation planners to explore and analyze energy consumption patterns resulting from temporally varying traffic signal phases at multiple intersections along a major transportation corridor using traffic simulation outputs. The visual dashboard is implemented as an accessible and responsive web application and employs a combination of visualization techniques to cover multiple aspects of vehicle acceleration and braking at multiple adjacent intersections along a corridor. The paper presents a case study of a simulated traffic scenario on the Shallowford Road traffic corridor located in Chattanooga, Tennessee to demonstrate the capability of the visual dashboard.

Xu, Haowen↗
DOE OSTI2023

The Effects of Lithium Ions and pH on the Function of Polyacrylic Acid Binder for Silicon Anodes

Binder plays a critical role in the performance of silicon anodes for lithium-ion batteries, specifically by connecting particles of active material and promoting adhesion to the current collector. Recent studies have differed on the relative cycle life of silicon anodes made from water-based polyacrylic acid (PAA) vs LiOH-PAA binders. Differences between the two may be due to the pH value or the extra Li + in the binder, both of which change when LiOH is added to PAA. Here we investigate the impact of these two variables on the performance of silicon anodes. Regarding the effect of Li + , cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) results confirm our hypothesis that the extra Li + facilitates ion transport. Regarding pH, we find that high pH in binders is detrimental to the electrode mechanical integrity, as observed in peeling tests and cross-sectional imaging. However, viscosity tests reveal that increased pH benefits the coating and mixing process. Further, our cycling results show that LiOH-PAA binder maintains greater cell capacity than does PAA, and further that LiOH-PAA at pH 4.5 leads to a cell with the highest capacity. Therefore, an intermediate pH is an optimal compromise between benefits observed for the low and high pH experiments.

25 ENERGY STORAGE↗
DOE OSTI2020

Design, Development and Testing Plan for Energy Efficiency Algorithms Related to Building-Integrated Cooling, Heating, and Power Systems

Building-integrated cooling, heating and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. It is estimated that the total CHP technical potential in the commercial building sector is approximately 76 GW, but only a small fraction of it is actually deployed. Advanced control and monitoring systems that realize the full potential of these CHP systems can transform this capacity into an asset for both the owner and the grid and also accelerate the adoption of these systems in the building sector. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. It has been demonstrated by several studies that as much as 30% of building energy use is wasted. Much of the waste results from the inability to anticipate load variations (design day vs. non-design day operations; diurnal variation of loads), identify improper operation, and efficiently operate, control and maintain building systems. Moreover, many buildings, even those with adequate control infrastructure, lack knowledgeable staff to operate and maintain energy systems. Operators of buildings with CHP systems will constantly need to make tradeoffs (economic dispatch) between onsite power generation and purchasing power, between onsite heat production from distributed generation versus heating/cooling from conventional systems, and different passive and active load management measures. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of a clean, efficient, reliable and affordable next-generation integrated energy systems. This report lists the components for which PM, real-time CxV and AFDD algorithms will be developed, how the algorithms will be tested, and metrics that will be used to validate the algorithms and easy of deployment. Deployment of these algorithms in the field will result in savings reduction in energy consumption of between 10% and 20%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Implementation Plan for Combined Heat and Power Systems VOLTTRON Controller: Performance Monitoring and Real-Time Commissioning Algorithm Verification

Building-integrated cooling, heating, and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV, and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of clean, efficient, reliable, and affordable next-generation integrated energy system. Previous report listed the components for which PM, real-time CxV, and AFDD algorithms will be developed, how the algorithms will be tested, and the metrics that will be used to validate the algorithms and their ease of deployment. Deployment of these algorithms in the field will result in a reduction in energy consumption of between 10% and 20% (for both CHP and conventional building systems). This report builds upon the previous report by detailing the process by which PNNL will implement performance monitoring and real-time commissioning algorithms for CHP systems in conjunction with the use of the VOLTTRON CHP economic dispatch agent in host facilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1980

Orbital Transfer Vehicle (OTV) engine study. Phase A: Extension

The current Phase A-Extension of the OTV engine study program aims to provide additional expander and staged combustion cycle data that will lead to design definition of the OTV engine. The proposed program effort seeks to optimize the expander cycle engine concept (consistent with identified OTV engine requirements), investigate the feasibility of kitting the staged combustion cycle engine to provide extended thrust operation, and conduct in-depth analysis of development risk, crew safety, and reliability for both cycles. Additional tasks address the costing of a 10/K thrust expander cycle engine and support of OTV systems study contractors.

Sobin, A. J.↗
NASA NTRS1990

The NASA high temperature superconductivity program

It has been recognized from the onset that high temperature superconductivity held great promise for major advances across a broad range of NASA interests. The current effort is organized around four key areas: communications and data, sensors and cryogenics, propulsion and power, and space materials technology. Recently, laser ablated YBa2Cu3O(7-x) films on LaAIO produced far superior RF characteristics when compared to metallic films on the same substrate. This achievement has enabled a number of unique microwave device applications, such as low insertion loss phase shifters and high Q filters. Melt texturing and melt quenched techniques are being used to produce bulk materials with optimized magnetic properties. These yttrium enriched materials possess enhanced flux pinning characteristics and will lead to prototype cryocooler bearings. Significant progress has also occurred in bolometer and current lead technology. Studies are being conducted to evaluate the effect of high temperature superconducting materials on the performance and life of high power magneto-plasma-dynamic thrusters. Extended studies were also performed to evaluate the benefit of superconducting magnetic energy storage for LEO space station, lunar and Mars mission applications. The project direction and level of effort of the program are also described.

Sokoloski, Martin M.↗
NASA NTRS1996

Mixing of Multiple Jets with a Confined Subsonic Crossflow in a Cylindrical Duct

This paper summarizes NASA-supported experimental and computational results on the mixing of a row of jets with a confined subsonic crossflow in a cylindrical duct. The studies from which these results were derived investigated flow and geometric variations typical of the complex 3-D flowfield in the combustion chambers in gas turbine engines. The principal observations were that the momentum-flux ratio and the number of orifices were significant variables. Jet penetration was critical, and jet penetration decreased as either the number of orifices increased or the momentum-flux ratio decreased. It also appeared that jet penetration remained similar with variations in orifice size, shape, spacing, and momentum-flux ratio when the number of orifices was proportional to the square-root of the momentum-flux ratio. In the cylindrical geometry, planar variances are very sensitive to events in the near wall region, so planar averages must be considered in context with the distributions. The mass-flow ratios and orifices investigated were often very large (mass-flow ratio greater than 1 and ratio of orifice area-to-mainstream cross-sectional area up to 0.5), and the axial planes of interest were sometimes near the orifice trailing edge. Three-dimensional flow was a key part of efficient mixing and was observed for all configurations. The results shown also seem to indicate that non-reacting dimensionless scalar profiles can emulate the reacting flow equivalence ratio distribution reasonably well. The results cited suggest that further study may not necessarily lead to a universal 'rule of thumb' for mixer design for lowest emissions, because optimization will likely require an assessment for a specific application.

Holdeman, James D.↗
NASA NTRS1997

An Introduction to Rotorcraft Research at NASA Ames

NASA Ames Research Center, Moffett Field, CA is the NASA lead Center for rotorcraft research. Rotorcraft research at Ames includes system analysis and configuration optimization, aeromechanics, and flight control and cockpit integration. Research in other areas such as composite structure and material, and rotor acoustics are conducted mainly at Langley Research Center, and rotorcraft propulsion and drivetrain are conducted at Lewis Research Center. This seminar will discuss Ames' rotorcraft research goals and some sample research projects and results. The talk will also briefly describe the newly fanned Army/NASA Rotorcraft Division, which combines the resources of rotorcraft branches in NASA Ames Aeronautics Directorate with Army's Aeroflightdynamics Directorate to better achieve the missions of the two previous rotorcraft research organizations at Ames. Rotorcraft research activities at NASA Ames are funded by two main program categories: Research and Technology (RUTH Base program and the Short Haul (Civil Tiltrotor) program. Work in the R&T program is carried out by the research staff in the Army/NASA Rotorcraft Division, and the work on SH(CT) program is carried out jointly by the SH(CT) program office and the Army/NASA Rotorcraft Division. Sample research projects and results in REST base program, such as conceptual assessment of several high-speed rotorcraft, rotorcraft CFD, individual blade control for reduction of external noise and vibration, noise-abatement flight procedures, engine inoperative procedures, handling qualities, and advanced flight control laws are broadly reviewed. High-speed rotorcraft research related to SH(CT) technology development conducted at Ames in the areas of low-noise proprotor, and low-noise terminal-area operations is also discussed.

Chen, Robert T. N.↗
NASA NTRS2004

Uncertainties in estimates of the risks of late effects from space radiation

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits. Published by Elsevier Ltd on behalf of COSPAR.

Non-NASA Center↗
NASA NTRS2005

A Program to Improve the Triangulated Surface Mesh Quality Along Aircraft Component Intersections

A computer program has been developed for improving the quality of unstructured triangulated surface meshes in the vicinity of component intersections. The method relies solely on point removal and edge swapping for improving the triangulations. It can be applied to any lifting surface component such as a wing, canard or horizontal tail component intersected with a fuselage, or it can be applied to a pylon that is intersected with a wing, fuselage or nacelle. The lifting surfaces or pylon are assumed to be aligned in the axial direction with closed trailing edges. The method currently maintains salient edges only at leading and trailing edges of the wing or pylon component. This method should work well for any shape of fuselage that is free of salient edges at the intersection. The method has been successfully demonstrated on a total of 125 different test cases that include both blunt and sharp wing leading edges. The code is targeted for use in the automated environment of numerical optimization where geometric perturbations to individual components can be critical to the aerodynamic performance of a vehicle. Histograms of triangle aspect ratios are reported to assess the quality of the triangles attached to the intersection curves before and after application of the program. Large improvements to the quality of the triangulations were obtained for the 125 test cases; the quality was sufficient for use with an automated tetrahedral mesh generation program that is used as part of an aerodynamic shape optimization method.

Cliff, Susan E.↗
NASA NTRS2009

Extravehicular Activity Testing in Analog Environments: Evaluating the Effects of Center of Gravity and Environment on Human Performance

The EVA Physiology, Systems and Performance (EPSP) Project is performing tests in different analog environments to understand human performance during Extravehicular Activity (EVA) with the aim of developing more safe and efficient systems for lunar exploration missions and the Constellation Program. The project is characterizing human EVA performance in studies using several test beds, including the underwater NASA Extreme Environment Mission Operations (NEEMO) and Neutral Buoyancy Laboratory (NBL) facilities, JSC fs Partial Gravity Simulator (POGO), and the NASA Reduced Gravity Office (RGO) parabolic flight aircraft. Using these varied testing environments, NASA can gain a more complete understanding of human performance issues related to EVA and the limitations of each testing environment. Tests are focused on identifying and understanding the EVA system factors that affect human performance such as center of gravity (CG), inertial mass, ground reaction forces (GRF), suit weight, and suit pressure. The test results will lead to the development of lunar EVA systems operations concepts and design requirements that optimize human performance and exploration capabilities. METHODS: Tests were conducted in the NBL and during NEEMO missions in the NOAA Aquarius Habitat. A reconfigurable back pack with repositionable mass was used to simulate Perfect, Low, Forward, High, Aft and NASA Baseline CG locations. Subjects performed simulated exploration tasks that included ambulation, kneel and recovery, rock pick-up, and shoveling. Testing using POGO, that simulates partial gravity via pneumatic weight offload system and a similar reconfigurable rig, is underway for a subset of the same tasks. Additionally, test trials are being performed on the RGO parabolic flight aircraft. Subject performance was assessed using a modified Cooper-Harper scale to assess operator compensation required to achieve desired performance. All CG locations are based on the assumption of a standardized 6 ft 180 lb subject. RESULTS: The modified Cooper-Harper Scale assesses desired task performance described as performance in a reduced gravity environment as compared to a 1G environment. Modified Cooper-Harper ratings of . 3 indicate no improvements are needed, ratings of 4-6 indicate improvements are desirable, and ratings . 7 indicate improvements are mandatory. DISCUSSION: Differences were noted in suited CH results based on environment at the same CG and suit pressure. Additionally, results suggest that CG location affects unsuited human performance. Subjects preferred locations near their natural CG over those that are high, aft, or a combination of high and aft. Further testing and analyses are planned to compare these unsuited results to suited performance.

Gernhardt, M.L.↗
NASA NTRS2002

Uncertainties in Estimates of the Risks of Late Effects from Space Radiation

The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.

Cucinotta, F. A.↗
NASA NTRS2015

Aircraft Electric Propulsion Systems Applied Research at NASA

Researchers at NASA are investigating the potential for electric propulsion systems to revolutionize the design of aircraft from the small-scale general aviation sector to commuter and transport-class vehicles. Electric propulsion provides new degrees of design freedom that may enable opportunities for tightly coupled design and optimization of the propulsion system with the aircraft structure and control systems. This could lead to extraordinary reductions in ownership and operating costs, greenhouse gas emissions, and noise annoyance levels. We are building testbeds, high-fidelity aircraft simulations, and the first highly distributed electric inhabited flight test vehicle to begin to explore these opportunities.

Clarke, Sean↗