SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Objects detected at beam axis intersections. Group of light sources or detectors is mounted in box at focal plane of lens. Box can therefore illuminate or view several axes, each corresponding to source or detector of group. Proximity sensing system developed to trigger braking system of automatically controlled car.
The Parking Garage Automation System (PGAS) is based on a technology developed by a NASA-sponsored project called Robot sensorSkin(TM). Merritt Systems, Inc., of Orlando, Florida, teamed up with NASA to improve robots working with critical flight hardware at Kennedy Space Center in Florida. The system, containing smart sensor modules and flexible printed circuit board skin, help robots to steer clear of obstacles using a proximity sensing system. Advancements in the sensor designs are being applied to various commercial applications, including the PGAS. The system includes a smartSensor(TM) network installed around and within public parking garages to autonomously guide motorists to open facilities, and once within, to free parking spaces. The sensors use non-invasive reflective-ultrasonic technology for high accuracy, high reliability, and low maintenance. The system is remotely programmable: it can be tuned to site-specific requirements, has variable range capability, and allows remote configuration, monitoring, and diagnostics. The sensors are immune to interference from metallic construction materials, such as rebar and steel beams. Inside the garage, smart routing signs mounted overhead or on poles in front of each row of parking spots guide the motorist precisely to free spaces.
A capacitive proximity sensing element, backed by a reflector driven at the same voltage as and in phase with the sensor, is used to reflect the field lines away from a grounded robot arm towards an intruding object, thus dramatically increasing the sensor's range and sensitivity.
Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.
Fundamental to many of NASA's in-space transportation missions is the capture and handling of various objects and vehicles in various orbits for servicing, debris disposal, sample retrieval, and assembly without the benefit of sufficient grapple fixtures and docking ports. To perform similar material handling tasks on Earth, pincher grippers, suction grippers, or magnetic chucks are used, but are unable to reliably grip aluminum and composite spacecraft, insulation, radiators, solar arrays, or extra-terrestrial objects in the vacuum of outer space without dedicated handles in the right places. The electronic Flexible Electrostatic Technologies for space Capture and Handling (FETCH) will enable reliable and compliant gripping (soft dock) of practically any object in various orbits or surfaces without dedicated mechanical features, very low impact capture, and built-in proximity sensing without any conventional actuators. Originally developed to handle semiconductor and glass wafers during vacuum chamber processing without contamination, the normal rigid wafer handling chucks are replaced with thin metal foil segments laminated in flexible insulation driven by commercial off-the-shelf solid state, high-voltage power supplies. Preliminary testing in NASA Marshall Space Flight Center's (MSFC's) Flat Floor Robotics Lab demonstrated compliant alignment and gripping with a full-sized, 150-lb microsat mockup and translation before a clean release with a flip of a switch. The flexible electrostatic gripper pads can be adapted to various space applications with different sizes, shapes, and foil electrode layouts even with openings through the gripper pads for addition of guidance sensors or injection of permanent adhesives. With gripping forces estimated between 0.5 and 2.5 lb/in2 or 70-300 lb/ft2 of surface contact, the FETCH can turn on and off rapidly and repeatedly to enable sample handling, soft docking, in-space assembly, precision relocation, and surface translation for accurate anchoring.
This paper presents as a proof-of-concept (POC) the design, integration, and performance of a novel reconfigurable S-/X-band Gallium Nitride (GaN) based fully solid-state microwave power module (SSMPM) for the role as the transmit module in a cognitive radio (CR). The SSMPM synergistically integrates multiple amplifiers through diplexing and high power switches to enable a single SSMPM capable of functioning as both S-/X-band amplifiers for telemetry, tracking, and command (TT&C), telecommunications, and science data downlink or as X-band radar for proximity sensing onboard a planetary exploration spacecraft. Integration of an electric field shaping field plate (FP) onto the GaN high electron mobility transistors (HEMTs) in this SSMPM provides increased performance and reliability for operation in the harsh conditions of space. This SSMPM is capable of delivering saturated power (Psat) of 39 dBm (8 W continuous wave (CW)) at S-band, P(sub sat) of 43 dBm (20 W CW) at X-band, and P(sub sat) of >50 dBm (>100 W Pulsed) at X-band.
This paper presents information regarding the nosecap Flush Airdata Sensing (FADS) system on Orion’s Pad Abort 1 (PA-1) vehicle. The purpose of the nosecap FADS system was to test whether or not useful data could be obtained from a FADS system if it was placed in close proximity to firing rocket nozzles like the Attitude Control Motor (ACM) nozzles on the PA-1 Launch Abort System. The nosecap FADS system used pressure measurements from a series of pressure ports which were arranged in a cruciform pattern and flush with the surface of the vehicle to estimate values of angle of attack, angle of sideslip, Mach number, impact pressure, and freestream static pressure. This paper will present the algorithms employed by the FADS system along with the development of the calibration datasets and a comparison of the final results to the Best Estimated Trajectory (BET) data for PA-1. Also presented in this paper is a Computational Fluid Dynamics (CFD) study to explore the impact of the ACM on the nosecap FADS system. The comparison of the nosecap FADS system results to the BET and the CFD study showed that more investigation is needed to quantify the impact of the firing rocket motors on the FADS system.
Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.
An algorithm is presented for the recognition and localization of thre-dimensional polyhedral objects based on an optical proximity sensor system capable of measuring the depth and orientation of a local area of an object surface. Emphasis is given to the determination of an optimal sensor trajectory or an optimal probing, for efficient discrimination among all the possible interpretations. The determination of an optimal sensor trajectory for the next probing consists of the selection of optimal beam orientations based on the surface normal vector distribution of the multiple interpretation image (MII) and the selection of an optimal probing plane by projecting the MII onto the projection plane perpendicular to a selected beam orientation and deriving the optimal path on the projection plane. The selection of optimal beam orientation and probing plane is based on the measure of discrimination power of a cluster of surfaces of an MII. Simulation results are shown.
This presentation presents information regarding the nose-cap flush airdata sensing (FADS) system on Orion's Pad Abort 1 (PA-1) vehicle. The purpose of the nose-cap FADS system was to test whether or not useful data could be obtained from a FADS system if it was placed in close proximity to firing rockets nozzles like the attitude control motor (ACM) nozzles on the PA-1 launch abort system (LAS). The nose-cap FADS systems use pressure measurements from a series of pressure ports which are arranged in a cruciform pattern and flush with the surface of the vehicle to estimate values of angle of attack, angle of side-slip, Mach number, impact pressure and free-stream static pressure.
Electronic spins of nitrogen–vacancy centres in diamond constitute a promising system for micro- and nanoscale magnetic sensing, because of their operation under ambient conditions, ease of placement in close proximity to sensing targets and biological compatibility. At high densities, the electronic spins interact through dipolar coupling, which typically limits but can also potentially enhance sensing performance. Here we report the experimental demonstration of many-body signal amplification in a solid-state, room-temperature quantum sensor. Our approach uses time-reversed two-axis-twisting interactions, engineered through dynamical control of the quantization axis and Floquet engineering in a two-dimensional ensemble of nitrogen–vacancy centres. We observe that optimal amplification occurs when the backward evolution time equals twice the forward evolution time, in sharp contrast to the conventional Loschmidt echo. These observations can be understood as resulting from an underlying time-reversed mirror symmetry of the microscopic dynamics, providing key insights into signal amplification and opportunities for practical entanglement-enhanced quantum sensing.
A mobile ground survey application that employs remote sensing as a primary means of area coverage is highlighted. It is distinguished from mobile robotic area coverage problems that employ contact or proximity-based sensing. The focus is on a specific concept for performing mobile surveys in search of biogenic gases on planetary surfaces using a distributed spectrometer -- a rover-based instrument designed for wide measurement coverage of promising search areas. Navigation algorithms for executing circular and spiral survey trajectories are presented for widearea distributed spectroscopy and evaluated based on area covered and distance traveled.
Several general guidelines should be kept in mind when considering the selection of field sites for teaching remote sensing fundamentals. Proximity and vantage point are two very practical considerations. Only through viewing a broad enough area to place the site in context can one make efficient use of a site. The effects of inclement weather when selecting sites should be considered. If field work is to be an effective tool to illustrate remote sensing principles, the following criteria are critical: (1) the site must represent the range of class interest; (2) the site must have a theme or add something no other site offers; (3) there should be intrasite variation within the theme; (4) ground resolution and spectral signature distinction should be illustrated; and (5) the sites should not be ordered sequentially.
Recent advances in leaf fluorescence measurements and canopy proximal remote sensing currently enable the non-destructive collection of rich diurnal and seasonal time series, which are required for monitoring vegetation function at the temporal and spatial scales relevant to the natural dynamics of photosynthesis. Remote sensing assessments of vegetation function have traditionally used actively excited foliar chlorophyll fluorescence measurements, canopy optical reflectance data and vegetation indices (VIs), and only recently passive solar induced chlorophyll fluorescence (SIF) measurements. In general, reflectance data are more sensitive to the seasonal variations in canopy chlorophyll content and foliar biomass, while fluorescence observations more closely relate to the dynamic changes in plant photosynthetic function. With this dataset we link leaf level actively excited chlorophyll fluorescence, canopy proximal reflectance and SIF, with eddy covariance measurements of gross ecosystem productivity (GEP). The dataset was collected during the 2017 growing season on maize, using three automated systems (i.e., Monitoring Pulse-Amplitude-Modulation fluorimeter, Moni-PAM; Fluorescence Box, FloX; and from eddy covariance tower). The data were quality checked, filtered and collated to a common 30 minutes timestep. We derived vegetation indices related to canopy functioning (e.g., Photochemical Reflectance Index, PRI; Normalized Difference Vegetation Index, NDVI; Chlorophyll Red-edge, Clre) to investigate how SIF and VIs can be coupled for monitoring vegetation photosynthesis. The raw datasets and the filtered and collated data are provided to enable new processing and analyses.
Abstract Photosynthesis is currently measured using time-laborious and/or destructive methods which slows research and breeding efforts to identify crop germplasm with higher photosynthetic capacities. We present a plot-level screening tool for quantification of photosynthetic parameters and pigment contents that utilizes hyperspectral reflectance from sunlit leaf pixels collected from a plot (~2 m×2 m) in <1 min. Using field-grown Nicotiana tabacum with genetically altered photosynthetic pathways over two growing seasons (2017 and 2018), we built predictive models for eight photosynthetic parameters and pigment traits. Using partial least squares regression (PLSR) analysis of plot-level sunlit vegetative reflectance pixels from a single visible near infra-red (VNIR) (400–900 nm) hyperspectral camera, we predict maximum carboxylation rate of Rubisco (Vc,max, R2=0.79) maximum electron transport rate in given conditions (J1800, R2=0.59), maximal light-saturated photosynthesis (Pmax, R2=0.54), chlorophyll content (R2=0.87), the Chl a/b ratio (R2=0.63), carbon content (R2=0.47), and nitrogen content (R2=0.49). Model predictions did not improve when using two cameras spanning 400–1800 nm, suggesting a robust, widely applicable and more ‘cost-effective’ pipeline requiring only a single VNIR camera. The analysis pipeline and methods can be used in any cropping system with modified species-specific PLSR analysis to offer a high-throughput field phenotyping screening for germplasm with improved photosynthetic performance in field trials.
Vibration and stability of a primary seal ring is controlled by a secondary seal system. An inflatable bladder which forms a portion of the secondary seal varies the damping applied to this seal ring. The amplitude of vibration of the primary seal ring is sensed with a proximity probe that is connected to a microprocessor in a control system. The bladder pressure is changed by the control system to mitigate any sensed instability or vibration.
Isolation of volatile analytes from environmental or biological fluids is a rate-determining step that can delay the response time for continuous sensing. In this paper, we demonstrate a colorimetric sensing system that enables the rapid detection of gas-phase analytes released from a flowing micro-volume fluid sample. The sensor platform is an analyte-responsive metal-insulator-metal (MIM) thin-film structure integrated with a large area quartz micropillar array. This allows precise planar alignment and microscale separation (310 μm) of the optical and fluidic structures. This configuration offers rapid and homogeneous color changes over large areas that permits detection by low-resolution optics or eye, which is well-suited to portable/wearable devices. For our proof-of-principle demonstration, we utilized a poly(methyl methacrylate) (PMMA) spacer and evaluated the sensor's response (color change) to ethanol vapor. We show that the RGB color value is quantitatively linked to the spacer swelling, which is reversible and repeatable. The optofluidic platform reduces the sensor response time from minutes to seconds compared with experiments using a conventional chamber. The sensor's concentration-dependent response was examined, confirming the potential of the reported sensing platform for continuous, compact, and quantitative colorimetric analysis of volatile analytes in low-volume samples, such as biofluids.
ABSTRACT Currently, the breeding programs focus their efforts on identifying and developing tolerant genotypes to adverse conditions, such as drought and high temperatures. In this context, the physiological approach, which involves phenotyping several traits, is useful for breeding programs. Leaf photosynthetic traits have become one of the main objectives to be evaluated for breeders due to their relationship with improving grain yield and biomass production. Gas exchange ( Ge ) and chlorophyll “a” fluorescence ( Chf ) are the main tools to characterize the photosynthetic activity in real time at the leaf level. Consequently, several association studies using proximal and nonproximal sensing (e.g., RGB, thermography) have been developed. However, for the correct application of this breeding approach, it is essential to have a basic knowledge of both the physiological principles involved in the readings and the limitations of phenotyping due to the characteristics of the devices available on the market. This revision also covers other traits, such as the morphological and anatomical characteristics of leaves and roots, and the use of isotopes complementing Ge and Chf measurements.