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

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At least 523 records · Page 29

An Evaluation of Performance Metrics for High Efficiency Tube-and-Wing Aircraft Entering Service in 2030 to 2035

An analysis of basic vehicle characteristics required to meet the Fundamental Aeronautics Program s 70 percent energy consumption reduction goal for commercial airliners in the 2030 to 2035 timeframe was conducted. A total of 29 combinations of vehicle parasitic drag coefficient, vehicle induced drag coefficient, vehicle empty weight and engine Specific Fuel Consumption were used to create sized tube-and-wing vehicle models. The mission fuel burn for each of these sized vehicles was then compared to a baseline current technology vehicle. A response surface equation was generated of fuel burn reduction as a function of the four basic vehicle performance metrics, so that any values of the performance metrics up to a 50 percent reduction could be used to estimate fuel burn reduction of tube-and-wing aircraft for future studies.

Perkins, H. Douglas↗

Demonstration of a High-Efficiency Free-Space Optical Communications Link

In this paper we discuss recent progress on the implementation of a hardware free-space optical communications test-bed. The test-bed implements an end-to-end communications system comprising a data encoder, modulator, laser-transmitter, telescope, detector, receiver and error-correction-code decoder. Implementation of each of the component systems is discussed, with an emphasis on 'real-world' system performance degradation and limitations. We have demonstrated real-time data rates of 44 Mbps and photon efficiencies of approximately 1.8 bits/photon over a 100m free-space optical link.

pulse-position-modulation↗

High Efficiency Submillimeter-Wave Imaging Array

The period of a focal array is limited by the angular sampling and the f number of the system. This fact will limit the efficiency of imaging array systems to around 50%. Recently it been demonstrated that the use of a dielectric layer on top of an array of apertures can improve this efficiency limit. In this paper, we describe a similar structure that improves the efficiency in imaging applications and that it is easy to manufacture due to its compatibility with planar lithographic techniques.

Llombart, Nuria↗

Selenium Interlayer for High-Efficiency Multijunction Solar Cell

A multi junction solar cell is provided and includes multiple semiconducting layers and an interface layer disposed between the multiple semiconducting layers. The interface layer is made from an interface bonding material that has a refractive index such that a ratio of a refractive index of each of the multiple semiconducting layers to the refractive index of the interface bonding material is less than or equal to 1.5.

Landis, Geoffrey A↗

Planar Field Emitters and High Efficiency Photocathodes Based on Ultrananocrystalline Diamond

A method of forming a field emitter comprises disposing a first layer on a substrate. The first layer is seeded with nanodiamond particles. The substrate with the first layer disposed thereon is maintained at a first temperature and a first pressure in a mixture of gases which includes nitrogen. The first layer is exposed to a microwave plasma to form a nitrogen doped ultrananocrystalline diamond film on the first layer, which has a percentage of nitrogen in the range of about 0.05 atom % to about 0.5 atom %. The field emitter has about 10.sup.12 to about 10.sup.14 emitting sites per cm.sup.2. A photocathode can also be formed similarly by forming a nitrogen doped ultrananocrystalline diamond film on a substrate similar to the field emitter, and then hydrogen terminating the film. The photocathode is responsive to near ultraviolet light as well as to visible light.

Sumant, Anirudha V.↗

Selenium Interlayer for High-Efficiency Multijunction Solar Cell

A multi-junction solar cell is provided and includes multiple semiconducting layers and an interface layer disposed between the multiple semiconducting layers. The interface layer is made from an interface bonding material that has a refractive index such that a ratio of a refractive index of each of the multiple semiconducting layers to the refractive index of the interface bonding material is less than or equal to 1.5.

Landis, Geoffrey A.↗

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning of historical and existing engine data could provide insights that help drive for better engine design. This work explored the application of machine learning to engine preliminary design. Engine core-size prediction was chosen for the first study because of its relative simplicity in terms of number of input variables required (only three). Specifically, machine-learning predictive tools were developed for turbofan engine core-size prediction, using publicly available data of two hundred manufactured engines and engines that were studied previously in NASA aeronautics projects. The prediction results of these models show that, by bringing together big data, robust machine-learning algorithms and automation, a machine learning-based predictive model can be an effective tool for turbofan engine core-size prediction. The promising results of this first study paves the way for further exploration of the use of machine learning for aircraft engine preliminary design.

Tong, Michael T.↗

Using Machine Learning to Predict Core Sizes of High-Efficiency Turbofan Engines

With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning of historical and existing engine data could provide insights that help drive for better engine design. This work explored the application of machine learning to engine preliminary design. Engine core-size prediction was chosen for the first study because of its relative simplicity in terms of number of input variables required (only three). Specifically, machine-learning predictive tools were developed for turbofan engine core-size prediction, using publicly available data of two hundred manufactured engines and engines that were studied previously in NASA aeronautics projects. The prediction results of these models show that, by bringing together big data, robust machine-learning algorithms and data science, a machine learning-based predictive model can be an effective tool for turbofan engine core-size prediction. The promising results of this first study paves the way for further exploration of the use of machine learning for aircraft engine preliminary design.

Core Size↗

High Speed Testing of a High Efficiency Concentric Magnetic Gear

This presentation presents measurements of the efficiency of NASA's 2nd magnetic gear prototype. A detailed discussion of the test rig used to make these measurements was presented, including a thorough uncertainty analysis. The reported uncertainties are 95% confidence intervals that include the effects of temperature and parasitic loads. The prototype's response was measured at output speeds between 124 rpm and 744 rpm for a controlled output torque of 10 Nm (8% of the prototype's maximum torque). After correcting for tare losses, the prototype's efficiency was found to decrease from 90.0% to 83.0% as speed increased. If the efficiency is extrapolated to a typical operating condition (85% of maximum torque) using the good assumption that energy loss is approximately independent of the transmitted torque,the expected efficiency would be 99.0% to 98.4%, which exceeds the state of the art for these speeds.

Scheidler, Justin↗