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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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NASA NTRS2020

Molecular Simulations of Ultrafast Radiation Induced Melting at Metal-Semiconductor Interfaces

Understanding radiation induced ultrafast melting at material interfaces is essential in designing robust electronic devices for aviation/space applications and in laser machining. While it is difficult to achieve the spatial and temporal resolution required to quantify the phenomenon experimentally, simulations can provide the detailed mechanisms of the structural changes that happen during phase transition. In this work, we use molecular simulations to study the effect of radiation damage on silicon carbide (SiC) - tungsten (W) interfaces which is of interest in high power electronics. A multi-scale approach is involved wherein the reactions at the interfaces are quantified using ab-initio molecular dynamics (MD) simulations and classical MD simulations are employed to understand the structural and diffusional changes across the material interface. Finally, coarse-grained Lennard-Jones type models are used to study the larger scale mechanisms and structures obtained due to the induced damages. We show that the response of the material to radiation damage depends on factors such as energy of the incident radiation, thermal properties, and molecular structure of the material.

Ravichandran, Ashwin↗
NASA NTRS2024

Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Humidity↗
NASA NTRS1997

Low Cost Manufacturing Approach of High Temperature PMC Components

The overall objective is to develop a satisfactory sheet molding compound (SMC) of a high temperature polyimide, such as PMR-11-50, VCAP-75, or NB2-76, and to develop compression molding processing parameters for a random, chopped fiber, high temperature, sheet molding compound that will be more affordable than the traditional hand lay-up fabrication methods. Compression molding will reduce manufacturing costs of composites by: (1) minimizing the conventional machining required after fabrication due to the use of full 360 deg matched tooling, (2) reducing fabrication time by minimizing the intensive hand lay-up operations associated with individual ply fabrication techniques, such as ply orientation and ply count and (3) possibly reducing component mold time by advanced B-staging prior to molding. This program is an integral part of Allison's T406/AE engine family's growth plan, which will utilize technologies developed under NASA's Sub-sonic Transport (AST) programs, UHPTET initiatives, and internally through Allison's IR&D projects. Allison is aggressively pursuing this next generation of engines, with both commercial and military applications, by reducing the overall weight of the engine through the incorporation of advanced, lightweight, high temperature materials, such as polymer matrix composites. This infusion of new materials into the engine is also a major factor in reducing engine cost because it permits the use of physically smaller structural components to achieve the same thrust levels as the generation that it replaced. A lighter, more efficient propulsion system translates to a substantial cost and weight savings to an airframe's structure.

Kannmacher, Kevin↗
NASA NTRS2019

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗
NASA NTRS2017

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems.

context-sensitive↗
NASA NTRS1977

Design outline for a new multiman ATC simulation facility at NASA-Ames Research Center

A new and unique facility for studying human factors aspects in aeronautics is being planned for use in the Man-Vehicle Systems Research Division at the NASA-Ames Research Center. This facility will replace the existing three cockpit-single ground controller station and be expandable to include approximately seven cockpits and two ground controller stations. Unlike the previous system, each cockpit will be mini-computer centered and linked to a main CPU to effect a distributed computation facility. Each simulator will compute its own flight dynamic and flight path predictor. Mechanical flight instruments in each cockpit will be locally supported and CRT cockpit displays of (e.g.) traffic and or RNAV information will be centrally computed and distributed as a means of extending the existing computational and graphical resources. An outline of the total design is presented which addresses the technical design options and research possibilities of this unique man-machine facility and which may also serve as a model for other real time distributed simulation facilities.

Kreifeldt, J. G.↗
NASA NTRSDate not supplied

NASA GeneLab Multi-study Visualization Portal

NASA GeneLab has helped advance the field of Space Biology by providing a public repository where researchers can store, share, analyze and visualize the results of space flight related omics experiments. The GeneLab data visualization portal allows any user, regardless of bioinformatics knowledge or access to computational resources, to interact with the experimental data, draw their own conclusions, and gain insights about the effects of space on living systems. These tools help democratize scientific research and foster the NASA Open Science initiative. The new multi-study feature of the GeneLab visualization platform allows users to mine study metadata from RNA sequencing (RNA-seq) experiments to identify samples of interest by filtering datasets based on organism, tissue, assay technology type, and/or factor. Once samples are selected from multiple datasets, users can combine and normalize the sample data, then utilize the visualization displays, including Principal Component Analysis (PCA) plots, to assess sample distributions. Finally, users can perform differential gene expression analysis on the combined data and visualize the results through PCA plots, Volcano plots, Pair plots, Heatmap, Ideogram and Gene Set Enrichment Analysis. All user-generated results and visualizations will be available for download. Here, we present a biological study using samples from multiple GeneLab RNA-seq datasets and analyzed using the multi-study visualization platform to demonstrate inter- and intra-study variability, as well as commonly differentially expressed genes between spaceflight and ground control conditions across datasets. This new feature opens a wide range of possibilities and opportunities for further development including combining other assay technology types and integration with batch effect correction techniques and machine learning applications. Overall, this tool allows users to increase the statistical power of individual experiments, validate hypothesis, identify patterns, and opens the door to new and exciting research.

space biology↗
NASA NTRSDate not supplied

Global SO 2 Data Record from OMPS Instruments on the JPSS Constellation

NASA’s Earth Observing System (EOS) SO 2 climate data record (CDR) started in 2004, with the launch of the Aura/Ozone Monitoring Instrument (OMI) and is now being continued with the SNPP/Ozone Mapping and Profiler Suite (OMPS) launched in 2011. Both OMI and SNPP/OMPS SO 2 CDRs are produced with the Goddard principal component analysis (PCA) spectral fitting algorithm. An advantage of the data-driven PCA retrieval technique is that it enables highly consistent retrievals from different instruments, by inherently accounting for various instrumental factors. To further extend the EOS SO 2 CDR, we are implementing the PCA SO 2 retrieval algorithm with the L1B measurements from OMPS instruments flying on the Joint Polar Satellite System (JPSS) constellation. In this presentation, we will provide an update on our progress in NOAA-20 (launched in 2017) and NOAA-21 (launched in 2022) PCA SO2 retrievals. We will focus on our new NOAA-20/OMPS PCA SO 2 EOS continuity product, to be publicly released in fall of 2023. We will present statistical analyses on the quality of NOAA-20 PCA SO 2 product, including retrieval noise, biases over background areas, and long-term stability. We will compare our PCA SO 2 retrievals from NOAA-20 with those from OMI, SNPP/OMPS, and S5P/TROPOMI (TROPOspheric Monitoring Instrument) for anthropogenic sources as well as large volcanic plumes. We will also discuss the application of a new machine learning technique that helps to further reduce the noise of NOAA-20 SO 2 retrievals. In addition, we will present preliminary PCA SO 2 retrievals from NOAA-21/OMPS, including those from direct readout implementation for aviation disaster avoidance. Finally, we will share some first results applying the PCA algorithm to NASA’s geostationary TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument to obtain hourly, high resolution SO 2 data over North America.

SO2↗
NASA NTRS2004

Developing Glassy Magnets from Simulated Composition of Martian Soil for Exploration Applications

The long-term exploration goals of NASA include developing human habitation on Mars and conducting scientific investigations on Mars and other planetary bodies. In situ resource processing is a key objective in this area We focus OR the possibility of making magnetic glasses in situ for potential applications development. The paper will focus on ongoing work at NASA Marshall Space Flight Center on making magnetic glass h m Mars soil simulants and its characterization. Analysis of the glass morphology, strength, chemistry and resulting magnetic properties will provide a fi.mdamenta1 understanding ofthe synthesized materiai that can be used for pomtiai appiications cieveiopment. In an effort to characterize the magnetic properbes of the Mars glasses, a series of tests were performed at NASA MSFC. Preliminary tests indicated that the glasses were attracted to a magnet and also had a small amount of residual magnetism. They were opaque (almost black in color). As the first step, a sample of Mars 1 glass (-lm x lmm x 5 mm length) was machined, weighed and its hysteresis curve was measured using a Vibration Sample Magnetometer 0. Next, a small furnace was designed and built and the sample was baked in a graphite (reducing agent) crucible at 800 C in an Argon atmosphere for 3 hours in the presence of a uniform, transverse (transverse to the 5mm length of the sample) magnetic field of 0.37 Tesla. The treated sample showed reddening on the outside and showed substantially increased residual magnetism. This sample was again analyzed in the VSM. The data clearly showed that some chemical change occurred during the heat treatment (color change) and that both the glasses have useful magnetic properties. Although no orientation effects of the magnetic field were considered, the data showed the following: 1. Both glass samples are primarily soft magnets and display ferromagnetic behavior (hysteresis, saturation, etc.) 2. The treated glass has improved saturation magnetism (order of magnitude increase), retentivity (factor of 6 increase) and susceptibility (order of magnitude increase) compared to the untreated glass 3. The untreated sample has higher coercivity (-50% that of Nickel) than the treated sample

Ramachandran, Narayanan↗
NASA NTRS2004

Developing Glassy Magnets from Simulated Composition of Martian Soil for Exploration Applications

The long-term exploration goals of NASA include developing human habitation on Mars and conducting scientific investigations on Mars and other planetary bodies. In situ resource processing is a key objective in this area. We focus on the possibility of making magnetic glasses in situ for potential applications development. The paper will focus on ongoing work at NASA Marshall Space Flight Center on making magnetic glass from Mars soil simulants and its characterization. Analysis of the glass morphology, strength, chemistry and resulting magnetic properties will provide a fundamental understanding of the synthesized material that can be used for potential applications development. in an effort to characterize the magnetic properties of the Mars glasses, a series of tests were performed at NASA MSFC. Preliminary tests indicated that the glasses were attracted to a magnet and also had a small amount of residual magnetism. They were opaque (almost black in color). As the first step, a sample of Mars 1 glass (approx.1 mm x 1 mm x 5 mm length) was machined, weighed and its hysteresis curve was measured using a Vibration Sample Magnetometer (VSM). Next, a small furnace was designed and built and the sample was baked in a graphite (reducing agent) crucible at 800 C in an Argon atmosphere for 3 hours in the presence of a uniform, transverse (transverse to the 5mm length of the sample) magnetic field of 0.37 Tesla. The treated sample showed reddening on the outside and showed substantially increased residual magnetism. This sample was again analyzed in the VSM. The data clearly showed that some chemical change occurred during the heat treatment (color change) and that both the glasses have useful magnetic properties. Although no orientation effects of the magnetic field were considered, the data showed the following: 1. Both glass samples are primarily soft magnets and display ferromagnetic behavior (hysteresis, saturation, etc.) 2. The treated glass has improved saturation magnetism (order of magnitude increase), retentivity (factor of 6 increase) and susceptibility (order of magnitude increase) compared to the untreated glass 3. The untreated sample has higher coercivity (approx.50% that of Nickel) than the treated sample 4. Both samples have similar energy density. Results from a systematic study to quantify the effects of processing conditions such as heat treatment, atmosphere, containerless processing (by electrostatic levitation), and applications of external magnetic fields of different strengths will be discussed. Efforts on optimizing the magnetic properties of the product and the feasibility of using it for a couple of specific magnetic applications such as heat generation using an ac field and for electro forming will also be covered. The latter is an in situ manufacturing technique being studied for in-space fabrication applications at MSFC.

Ramachandran, N.↗
NASA NTRS2004

The Effect of Hole Quality on the Fatigue Life of 2024-T3 Aluminum Alloy Sheet

This paper presents the results of a study whose main objective was to determine which type of fabrication process would least affect the fatigue life of an open-hole structural detail. Since the open-hole detail is often the fundamental building block for determining the stress concentration of built-up structural parts, it is important to understand any factor that can affect the fatigue life of an open hole. A test program of constant-amplitude fatigue tests was conducted on five different sets of test specimens each made using a different hole fabrication process. Three of the sets used different mechanical drilling procedures while a fourth and fifth set were mechanically drilled and then chemically polished. Two sets of specimens were also tested under spectrum loading to aid in understanding the effects of residual compressive stresses on fatigue life. Three conclusions were made from this study. One, the residual compressive stresses caused by the hole-drilling process increased the fatigue life by two to three times over specimens that were chemically polished after the holes were drilled. Second, the chemical polishing process does not appear to adversely affect the fatigue life. Third, the chemical polishing process will produce a stress-state adjacent to the hole that has insignificant machining residual stresses.

Everett, Richard A., Jr.↗
NASA NTRS2024

Direct Ink Write 3D Printing of Fully Dense and Functionally Graded Liquid Metal Elastomer Foams

Liquid metal (LM) elastomer composites offer promising potential in soft robotics, wearable electronics, and human-machine interfaces. Direct ink write (DIW) 3D printing offers a versatile manufacturing technique capable of precise control over LM microstructures, yet challenges such as interfilament void formation in multilayer structures impact material performance. Here, a DIW strategy is introduced to control both LM microstructure and material architecture. Investigating three key process parameters–nozzle height, extrusion rate, and nondimensionalized nozzle velocity–it is found that nozzle height and velocity predominantly influence filament geometry. The nozzle height primarily dictates the aspect ratio of the filament and the formation of voids. A threshold print height based on filament geometry is identified; below the height, significant surface roughness occurs, and above the ink fractures, which facilitates the creation of porous structures with tunable stiffness and programmable LM microstructure. These porous architectures exhibit reduced density and enhanced thermal conductivity compared to cast samples. When used as a dielectric in a soft capacitive sensor, they display high sensitivity (gauge factor = 9.0), as permittivity increases with compressive strain. These results demonstrate the capability to simultaneously manipulate LM microstructure and geometric architecture in LM elastomer composites through precise control of print parameters, while maintaining geometric fidelity in the printed design.

Spencer Pak↗
NASA NTRS2021

NASA Electric Vertical Takeoff and Landing (eVTOL) Aircraft Technology for Public Services – A White Paper

History has shown that our personal life is highly dependent on the technology that people have developed. A strategic scan of the aerospace environment at the beginning of the 21st century strongly suggests that the world might be approaching a new age of airpower—the era of electrified/hybrid aircraft propulsion. Undeniably, starting from the Montgolfier Brothers balloon flight in 1783, to the Wright Brothers piston engine flight in 1903, and the jet engine of the 1960s, or the space age of today, one can say that leaps in propulsion technology have marked the different ages of human flight. The technological advancements, brought at the beginning of 21st century by the revolution in data exchange, computational power, sensors, wireless communication, internet, and autonomy, contributed to the vision of this new age of propulsion we are approaching. Historically, conventional vertical takeoff and landing (VTOL) aircraft have been equipped with propulsion units relying on complex internal combustion machines (turbines, piston engines, for example), and complex mechanical arrangements (gearboxes, shafts, variable pitch propeller). By contrast, electric VTOL aircraft (eVTOL)1 rely on simpler propulsion units (electric motors and in some cases fixed-pitch propellers). This promotes redundancy and improves tolerance to failures, in turn improving safety. The use of simpler electric propulsion units should also allow significant acquisition and operating cost reductions. Whether full-electric (relying solely on batteries) or hybrid-electric (relying on a combination of batteries, fuel-powered engines, and generators.), eVTOLs are also expected to generate less noise and air pollution than conventional aircraft with similar payloads. According to the 2019 Annual Review of IATA (International Air Transport Association) [ref.1], due to an expected increase in air transport traffic by 5% every year and a doubling of air transport passenger numbers to 8.2 billion by 2037 significant challenges are posed to the aviation industry. Furthermore, this report does not factor in the expected demand for short-range (intra-city) air transportation, which is in development and yet to be operational. The increased demand to fly creates a responsibility to expand in a sustainable manner and an endeavor to develop more environmentally-friendly aircraft. eVTOL aircraft, either piloted or autonomous, is gathering considerable interest worldwide. Modern and novel full-electric or hybrid-electric eVTOL configurations enable a new paradigm shift in air transportation as the aviation industry remains committed to its goals of carbon-neutral growth from 2020 onwards and cutting CO2 emissions to half 2005 levels by 2050. While electric power has been used for decades, recent developments in mobile electric/hybrid propulsion coupled with advanced materials and autonomous systems may create the possibility to transition into the next age of air mobility propelled by electric/hybrid VTOL aircraft technology. Although eVTOL aircraft might seem like an incremental improvement or even a counterintuitive regression with regard to past VTOL development, it has in fact the potential to transform air mobility across a wide range of government applications. Previous transformations in aviation generated dramatic leaps in performance, but the cost was commensurate with performance, limiting quantity produced. This next age appears to take a different approach. Performance may not increase, but at this moment technology is poised for future urban mobility that will spawn commercial passenger drone services, that is, autonomous (pilotless) air taxis and thereby add a new dimension to the urban transportation mix of the future [ref. 2]. Advances in electric propulsion, autonomous flight technology, and 5G communication networks will enable this fast new-growing market to become a reality. It is now time to envision the introduction of electric/hybrid eVTOL aircraft for Public Services2. We believe that in the next decades eVTOL aircraft will have the potential to become an essential tool to Public Service agencies around the world in applications such as firefighting, public safety, search and rescue, disaster relief and law enforcement. This is due to several major factors. • First, with the increasing popularity of small, unmanned aircraft vehicles (UAVs) or drones, many companies today are focusing on the development of passenger UAVs designed to accommodate up to five passengers or equivalent cargo payload. Many such configurations are electric or hybrid-electric designs with VTOL capabilities. Several of these projects have started a flight test program and many more are expected to be in the experimental and development phase in 2020. Such revolutionary vehicles could be in commercial operations by 2030. These eVTOL systems could be ready for selected Public Services missions even sooner. • Second, although these advanced eVTOL vehicles under development still need access to fuel (hybrid) and/or electric charging capability, they can take off and land from almost anywhere. Therefore, such vehicles, both manned and unmanned can be successfully integrated for the critical missions of the Public Services with extra deployment flexibilities. • Third, advancement in electric propulsion systems in the automotive industry together with NASA’s leading efforts in electrification of aircraft propulsion systems, FAA’s ongoing active eVTOL certification programs, and EASA’s proposed framework for the certification of electric/hybrid small category VTOL aircraft in Europe [ref. 3] will help accelerate industry electric propulsion system development and integration. • Finally, eVTOL vehicles could be deployed for Public Services sooner than air taxi or other commercial applications, since Public Services missions may be more easily approved based on specific mission criteria, localized airworthiness authority for public-use aircraft3, and are normally operating under centralized airspace management and control by the theater command. Moreover, public perception and acceptance are generally less of a concern when operations save lives and benefit the wider community. The prioritized introduction of eVTOL aircraft in Public Services is ambitious, but we believe it is achievable in the coming decades if fundamental enablers (people and technologies) are engaged in defining the objectives and needs of these missions. The revolution that is currently taking place in eVTOL aircraft represents an unprecedented opportunity to develop a safer, more affordable, more available and more environmentally friendly future of vertical flight. To ensure that these novel aircraft meet the future expectations of Public Services, it is essential to take a collaborative and multi-disciplinary approach to their development, across engineering disciplines, policy-making, program management, business case development, manufacturing, and flight demonstrations. It should be noted that the term eVTOL (in the near term) used throughout this publication implies aircraft capable of transporting up to 5 persons which may or may not include a pilot if operated fully autonomously, assuming an average of 200 pounds (91 kg) per person or equivalent payload and a range up to 60 miles plus a suitable reserve. Hybrid or hydrogen powered eVTOLs would have greater range. For example, a “3-seat” eVTOL aircraft may only be able to carry two fully equipped firemen, and payload capacity is more relevant when used for the supply mission. Moreover, this paper concentrates on the “last-mile” solutions with a deployment time of no more than 6 hours. Although not specifically discussed in this document, it is understood that the future of Transformative Vertical Flight in general and Public Services, in particular, will also involve smaller UAVs that will undoubtedly play a crucial role in future aerial operations. For example, smaller unmanned aircraft may be used to dispatch medical supplies, portable filtration systems or perform the Search task of future Search and Rescue (SAR) operations. Close collaboration between the aircraft industry, the Civil Aviation Authorities (CAA), e.g., Federal Aviation Administration (FAA), European Aviation Safety Agency (EASA), Transport Canada Civil Aviation (TCCA) and the Department of Defense (DoD) certifiers, will help identify Public Services requirements, define expectations and limit development cost and timescales. Take the US Air Force Agility Prime as an example, the majority of the eVTOL application opportunities and mission elements identified are in line with the NASA TVF WG-4 objectives and use cases. Together, it forms a strong partnership to accelerate the development, certification, and practical deployment for public service missions. The US Air Force Agility Prime has been a collaboration partner on this white paper, and provided valuable input and recommendations. Most of the eVTOL public service mission elements discussed in this paper and additional use cases envisioned by the NASA TVF WG-4 team are shared by the Agility Prime program. The focus and efforts of the Agility Prime in product and system development, industry and government partnership, accelerated certifications as well as early test and deployment are totally in sync with the path forward recommended by this white paper. This kind of collaboration and partnership will help enable the practical use of the eVTOL for public service missions, benefit the eVTOL public acceptance, and accelerate the eVTOL industry revolution.

Johnny T. Doo↗
NASA NTRS2021

Passive Microwave Brightness Temperature Assimilation to Improve Snow Mass Estimation across Complex Terrain in Pakistan, Afghanistan, and Tajikistan

An ensemble Kalman filter is used to assimilate Advanced Microwave Scanning Radiometer-2 (AMSR2) observations of passive microwave (PMW) brightness temperatures (spectral differences, ΔT b ) into land surface model estimates of snow mass over northwestern high mountain Asia (HMA). Trained support vector machines serve as the observation operator and map the geophysical modeled variables into ΔT b space within the assimilation framework. Evaluation of the assimilation routine is carried out through comparison of assimilated snow mass estimates with an in situ dataset. The assimilation framework helps improve the land surface model estimates through PMW ΔT b assimilation, particularly in terms of decreasing the domain-wide bias. The assimilation framework proved more effective during the (dry) snow accumulation season and decreased the bias and root-mean-square error (RMSE) in snow mass estimates at 76% and 58% of the comparative pixels, respectively. During the snow ablation season, the PMW brightness temperature signal contained less information related to snow mass due to the presence of other concurrent geophysical features that effectively serve as noise during the snow mass update. The utilization of PMW ΔT b for accurate snow mass estimation in complex terrain such as HMA is dependent on a multitude of factors for optimal results; however, it does add utility to the land surface model if the relevant pitfalls are taken into consideration prior to the state variable update.

Jawairia Ahmad↗
NASA NTRS1994

Test results for rotordynamic coefficients of anti-swirl self-injection seals

Test results are presented for rotordynamic coefficients and leakage for three annular seals which use anti-swirl self-injection concept to yield significant improvement in whirl frequency ratios as compared to smooth and damper seals. A new anti-swirl self-inection mechanism is achieved by deliberately machining self-injection holes inside the seal stator mechanism which is used to achieve effective reduction of the tangential flow which is considered as a prime cause of rotor instability in high performance turbomachinery. Test results show that the self-injection mechanism significantly improves whirl frequency ratios; however, the leakage performance degrades due to the introduction of the self-injection mechanism. Through a series of the test program, an optimum anti-swirl self-injection seal which uses a labyrinth stator surface with anti-axial flow injections is selected to obtain a significant improvement in the whirl frequency ratio as compared to a damper seal, while showing moderate leakage performance. Best whirl frequency ratio is achieved by an anti-swirl self-injection seal of 12 holes anti-swirl and 6 degree anti-leakage injection with a labyrinth surface configuration. When compared to a damper seal, the optimum configuration outperforms the whirl frequency ratio by a factor of 2.

Kim, C. H.↗
NASA NTRS2012

Fabrication of an Absorber-Coupled MKID Detector

Absorber-coupled microwave kinetic inductance detector (MKID) arrays were developed for submillimeter and far-infrared astronomy. These sensors comprise arrays of lambda/2 stepped microwave impedance resonators patterned on a 1.5-mm-thick silicon membrane, which is optimized for optical coupling. The detector elements are supported on a 380-mm-thick micro-machined silicon wafer. The resonators consist of parallel plate aluminum transmission lines coupled to low-impedance Nb microstrip traces of variable length, which set the resonant frequency of each resonator. This allows for multiplexed microwave readout and, consequently, good spatial discrimination between pixels in the array. The transmission lines simultaneously act to absorb optical power and employ an appropriate surface impedance and effective filling fraction. The fabrication techniques demonstrate high-fabrication yield of MKID arrays on large, single-crystal membranes and sub-micron front-to-back alignment of the micro strip circuit. An MKID is a detector that operates upon the principle that a superconducting material s kinetic inductance and surface resistance will change in response to being exposed to radiation with a power density sufficient to break its Cooper pairs. When integrated as part of a resonant circuit, the change in surface impedance will result in a shift in its resonance frequency and a decrease of its quality factor. In this approach, incident power creates quasiparticles inside a superconducting resonator, which is configured to match the impedance of free space in order to absorb the radiation being detected. For this reason MKIDs are attractive for use in large-format focal plane arrays, because they are easily multiplexed in the frequency domain and their fabrication is straightforward. The fabrication process can be summarized in seven steps: (1) Alignment marks are lithographically patterned and etched all the way through a silicon on insulator (SOI) wafer, which consists of a thin silicon membrane bonded to a thick silicon handle wafer. (2) The metal microwave circuitry on the front of the membrane is patterned and etched. (3) The wafer is then temporarily bonded with wafer wax to a Pyrex wafer, with the SOI side abutting the Pyrex. (4) The silicon handle component of the SOI wafer is subsequently etched away so as to expose the membrane backside. (5) The wafer is flipped over, and metal microwave circuitry is patterned and etched on the membrane backside. Furthermore, cuts in the membrane are made so as to define the individual detector array chips. (6) Silicon frames are micromachined and glued to the silicon membrane. (7) The membranes, which are now attached to the frames, are released from the Pyrex wafer via dissolution of the wafer wax in acetone.

Brown, Ari↗
NASA NTRS1994

Seventh Annual Workshop on Space Operations Applications and Research (SOAR 1993), volume 2

This document contains papers presented at the Space Operations, Applications and Research Symposium (SOAR) Symposium hosted by NASA/Johnson Space Center (JSC) on August 3-5, 1993, and held at JSC Gilruth Recreation Center. The symposium was cosponsored by NASA/JSC and U.S. Air Force Materiel Command. SOAR included NASA and USAF programmatic overviews, plenary session, panel discussions, panel sessions, and exhibits. It invited technical papers in support of U.S. Army, U.S. Navy, Department of Energy, NASA, and USAF programs in the following areas: robotics and telepresence, automation and intelligent systems, human factors, life support, and space maintenance and servicing. SOAR was concerned with Government-sponsored research and development relevant to aerospace operations. More than 100 technical papers, 17 exhibits, a plenary session, several panel discussions, and several keynote speeches were included in SOAR '93. These proceedings, along with comments and suggestions made by panelists and keynote speakers, will be used to assess progress made in joint USAF/NASA projects and activities to identify future collaborative/jolnt programs. SOAR '93 was the responsibility of the USAF NASA Space Technology Interdependency Group Operations Committee. Symposium proceedings include papers presented by experts from NASA, the USAF, USA, and USN, U.S. Department of Energy, universities, and industry.

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CERES FluxByCldTyp NB2BB Fluxes Improvement based on Deep Neural Network

The NASA Clouds and the Earth's Radiant Energy System (CERES) product provides over 20 years of accurately observed top-of-the-atmosphere (TOA) and surface flux data record for climate monitoring and diagnostic studies. The interaction between clouds and radiation interaction is a key factor that dominate climate feedbacks but is not well understood. To further advance our understanding of the cloud-radiation interaction, a new CERES FluxByCldTyp (FBCT) product has been developed that contains radiative fluxes by cloud-type, which can provide more stringent constraints when validating models and reveal more insight into the interactions between clouds and climate. For CERES partly cloudy and multiple cloud-type footprints, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) narrow-band (NB) imager channel radiances partitioned by cloud-type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multi-channel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. This study takes advantage of recent progress in machine learning (ML) field by applying deep neural network algorithm to improve fluxes based on MODIS NB radiances. The preliminary study shows ML produce are an improvement over the current FBCT Edition 4 NB2BB algorithm. Furthermore, unlike Ed4 NB2BB, the new ML method convert NB radiances directly to broadband fluxes. For future Ed5, new NB radiances are proposed and used by ML to improve fluxes calculation. Prelimary results show significant LW improvement.

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