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System utilizing new type hydrogen sensor has overall detection sensitivity and response speed higher than conventional hot-wire or hot-thermistor detectors. System measures concentrations of from 2 parts per million to 30 percent and is adaptable as leak detector and hazard alarm wherever hydrogen is used.
To provide useful precipitation measurements from space, two requirements must be met: adequate spatial and temporal sampling of the storm and sufficient accuracy in the estimate of precipitation intensity. Although presently no single instrument or method completely satisfies both requirements, the visible/IR, microwave radiometer and radar methods can be used in a complementary manner. Visible/IR instruments provide good temporal sampling and rain area depiction, but recourse must be made to microwave measurements for quantitative rainfall estimates. The inadequacy of microwave radiometer measurements over land suggests, in turn, the use of radar. Several recently developed attenuating-wavelength radar methods are discussed in terms of their accuracy, dynamic range and system implementation. Traditionally, the requirements of high resolution and adequate dynamic range led to fairly costly and complex radar systems. Some simplications and cost reduction can be made; however, by using K-band wavelengths which have the advantages of greater sensitivity at the low rain rates and higher resolution capabilities. Several recently proposed methods of this kind are reviewed in terms of accuracy and system implementation. Finally, an adaptive-pointing multi-sensor instrument is described that would exploit certain advantages of the IR, radiometric and radar methods.
The purpose of this research was to develop an optical method of leak detection. Various modifications of schlieren optics were explored with initial emphasis on leak detection of the plumbing within the orbital maneuvering system of the space shuttle (OMS pod). The schlieren scheme envisioned for OMS pod leak detection was that of a high contrast pattern on flexible reflecting material imaged onto a negative of the same pattern. We find that the OMS pod geometry constrains the characteristic length scale of the pattern to the order of 0.001 inch. Our experiments suggest that optical modulation transfer efficiency will be very low for such patterns, which will limit the sensitivity of the technique. Optical elements which allow a negative of the scene to be reversibly recorded using light from the scene itself were explored for their potential in adaptive single-ended schlieren systems. Elements studied include photochromic glass, bacteriorhodopsin, and a transmissive liquid crystal display. The dynamics of writing and reading patterns were studied using intensity profiles from recorded images. Schlieren detection of index gradients in air was demonstrated.
Miniature gas chromatography (GC) and miniature mass spectrometry (MS) instrumentation has been developed to identify and quantify the chemical compounds present in complex mixtures of gases. The design approach utilizes micro-GC components coupled with a Paul quadrupole ion trap (QIT) mass spectrometer. Inherent to the system are high sensitivity, good dynamic range, good QIT resolution, low GC flow-rates to minimize vacuum requirements and the need for consumables; and the use of a modular approach to adapt to volatile organic compounds dissolved in water or present in sediment. Measurements are reported on system response to gaseous species at concentrations varying over four orders of magnitude. The ability of the system to deal with complicated mixtures is demonstrated, and future improvements are discussed. The GC/QIT system described herein has a mass, volume and power that are, conservatively, one-twentieth of those of commercial off-the-shelf systems. Potential applications are to spacecraft cabin-air monitoring, robotic planetary exploration and trace-species detection for residual gas analysis and environmental monitoring.
In the inverse radiation transport problem, a radiation signal emanating from an unknown object is used to reconstruct geometric and material parameters of the object , e.g., the mass of special nuclear material (SNM), the isotopic composition of the SNM (e.g., the enrichment of 235U), the thickness of shielding, etc. The inverse radiation transport problem is one of the most fundamental and important in the emergency response mission, and has been addressed in previous NA-22 and NA-42/84 investments by using derivative-free optimization methods. Our project was aimed at (i) consolidating previous work by applying polynomial chaos expansion (PCE) for reducing significantly the number of forward model simulations required by derivative-free optimization methods; (ii) developing a general-purpose framework and stand-alone software for solving the inverse radiation transport problem by applying a new “predictive modeling” methodology (predictive modeling of coupled multi-physics systems, PM_CMPS) which enables the fusing of experimental and computational information; and (iii) developing several benchmarks (for unscattered gamma rays) for demonstrating the quantification of non-Gaussian features (e.g., skewness and kurtosis, which characterize asymmetries and long tails) of response distributions by deterministically and efficiently propagating parameter uncertainties (covariances and higher-order moments, where available) using high-order sensitivities computed by the recently developed comprehensive adjoint sensitivity analysis methodology (C-ASAM). With regard to (i), application of PCE, the most significant accomplishment of this project was an implementation of PCE into INVERSE that significantly reduced computation time for the DiffeRential Evolution Adaptive Metropolis (DREAM) and Differential Evolution (DE) methods. For inverse transport problems with measurements of neutron leakage, neutron multiplication, and neutron-induced gamma-rays, the solution times for the DREAM and DE methods were reduced by factors of 30-300, reducing run times from hours to minutes while maintaining the same accuracy as the standard (non-PCE) DREAM and DE. Speedups were further improved by exploring sparse grid quadrature sets using the Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN (Tasmanian) toolset. An initial exploration of sparse grids indicated that further speedups factors of 5-10 are obtainable. The implementation of PCE in INVERSE is not in a form that users can easily access. With regard to (ii), solving the inverse problem using a predictive modeling paradigm, the most significant accomplishment of this project were the derivation and implementation of adjoint-based second derivatives in neutron and photon transport theory. There are two codes that compute these derivatives. SENSPG computes them for uncollided gamma rays and SENSMG computes them for neutron leakage. SENSMG is open-source code available on github. Other significant accomplishments included a stand-alone code, MULTI-PRED, that implements the predictive modeling paradigm, along with a detailed manual. The code was implemented in the existing INVERSE code for inverse problems, but a head-to-head comparison of inverse methods was not achieved. We also derived and implemented the capability to compute sensitivities for multiplicity measurements into the SENSMG code, and this capability was used in a data assimilation application, but it was not used for solving inverse problems. With regard to (iii), developing benchmarks to demonstrate the importance of high-order sensitivity and uncertainty analysis, the most significant accomplishment of this project were two test problems that showed how important second-order sensitivities are.
We present a combination of neutron powder-diffraction measurements demonstrating negative linear compressibility and irregular thermal expansion in 7 Li 2 CO 3 . This is shown to be due to an interplay between the tilting of the rigid carbonate group and the shear strain in the unit cell, which leads to a first-order transition from monoclinic to hexagonal symmetry. The phase evolution is shown to be highly sensitive to the level of hydrostaticity in the sample. Under hydrostatic conditions, the sample begins transformation at 8.5 GPa leading to a change from tetrahedral to octahedral Li coordination. Symmetry adapted basis mode analysis, combined with density functional theoretical (DFT) calculations and Raman spectroscopy, is used to show that this transition is reverse proper ferroelastic in nature.
Reduction of the earth's ozone layer, with a resultant increase in transmission of solar ultraviolet radiation in the 290 to 320nm waveband (UV-B), via space shuttle operations through the stratosphere is considered. It is shown that simulated solar ultraviolet radiation can, under experimental conditions, detrimentally affect the marine organisms that form the base of the food web of oceanic and estuarine ecosystems. Whether a small increase in biologically harmful ultraviolet radiation might overwhelm these mechanisms and produce changes that will have damaging consequences to the biosphere is discussed. The potential for irreversible damage to the productivity, structure and/or functioning of a model estuarine ecosystem by increased UV-B radiation and whether these ecosystems are highly stable or amenable to adaptive change is studied. Data are provided to assess the potential impact upon marine ecosystems if space shuttle operations contribute to a reduction of the stratospheric ozone layer and the sensitivity of key community components to increased UV-B radiation is examined.
In the present design methodology for nonlinear systems containing parameter uncertainty, a generalized sensitivity analysis is incorporated which employs parameter space sampling and statistical inference. For the case of a system with j adjustable and k nonadjustable parameters, this methodology (which includes an adaptive random search strategy) is used to determine the combination of j adjustable parameter values which maximize the probability of those performance indices which simultaneously satisfy design criteria in spite of the uncertainty due to k nonadjustable parameters.
Hair cells in the bullfrog sacculus are specifically adapted to sense small-amplitude, high-frequency linear accelerations. These hair cells display many properties that are undesirable or inappropriate for hair cells that must provide static gravity sensitivity. This study resulted in part due to an interest in seeing how the transduction mechanisms of hair cells in a gravity-sensing otolith endorgan would differ from those in the bullfrog sacculus. The bullfrog utriculus is an appropriate model for these studies, because its structure is representative of higher vertebrates in general and its function as a sensor of static gravity and dynamic linear acceleration is well known. Hair cells in the bullfrog utriculus, classifiable as Type 2 by cell body and synapse morphology, differ markedly in hair bundle morphology from those in the bullfrog sacculus. Moreover, the hair bundle morphologies of utricular hair cells, unlike those in the sacculus, differ in different membrane regions.
Two fundamental environmental influences that have shaped the evolution of life on Earth are gravity and the cyclic changes occurring over the 24-hour day. Light levels, temperature, and humidity fluctuate over the course of a day, and organisms have adapted to cope with these variations. The primary adaptation has been the evolution of a biological timing system. Previous studies have suggested that this system, named the circadian (circa - about; dies - a day) timing system (CTS), may be sensitive to changes in gravity. The NASA Neurolab spaceflight provided a unique opportunity to evaluate the effects of microgravity on the mammalian CTS. Our experiment tested the hypotheses that microgravity would affect the period, phasing, and light sensitivity of the CTS. Twenty-four Fisher 344 rats were exposed to 16 days of microgravity on the Neurolab STS-90 mission, and 24 Fisher 344 rats were also studied on Earth as one-G controls. Rats were equipped with biotelemetry transmitters to record body temperature (T(sub b)) and heart rate (HR) continuously while the rats moved freely. In each group, 18 rats were exposed to a 24-hour light-dark (LD 12:12) cycle, and six rats were exposed to constant dim red-light (LL). The ability of light to induce a neuronal activity marker (c-fos) in the circadian pacemaker of the brain, the suprachiasmatic nucleus (SCN), was examined in rats studied on flight days two (FD2) and 14 (FD14), and postflight days two (R+1) and 14 (R+13). The flight rats in LD remained synchronized with the LD cycle. However, their T(sub b), rhythm was markedly phase-delayed relative to the LD cycle. The LD flight rats also had a decreased T(sub b) and a change in the waveform of the T(sub b) rhythm compared to controls. Rats in LL exhibited free-running rhythms of T(sub b), and HR; however, the periods were longer in microgravity. Circadian period returned to preflight values after landing. The internal phase angle between rhythms was different in flight than in one-G. Compared with control rats, the flight rats exhibited no change in HR. Finally, the LD FD2 flight rats demonstrated a reduced sensitivity to light as shown by significantly reduced c-fos expression in the SCN in comparison with controls. These findings constitute the first demonstration that microgravity affects the fundamental properties of the mammalian circadian timing system, specifically by influencing the clock's period, and its ability to maintain temporal organization and phase angle of synchronization to an external LD cycle.
A multidisciplinary design optimization methodology to directly minimize the ground-level noise generated by the sonic boom of a high altitude supersonic body is presented. A Cartesian Euler flow solver is coupled with an atmospheric propagation tool to create a ground-noise analysis capability for supersonic bodies. Adjoint formulations for both the flow solver and propagation tool are also coupled to compute sensitivities of shape variations in the body in a highly efficient manner. A gradient-based optimizer is then introduced to forge a valuable design capability. Output-based mesh adaptation that is driven directly by ground-level noise is employed to increase accuracy and provide error estimation. The design method is demonstrated first on a simple axisymmetric body with few design variables to evaluate the efficacy of the optimization scheme. Guided by the results of this initial case, the problem is then repeated with somewhat different design variables to further demonstrate the capabilities of the design method. Finally, the method is applied to a real-world problem by optimizing control surface deflection settings of a low-boom aircraft to minimize ground noise while maintaining trimmed, level flight.
By accounting for surface-based light source emissions and top-of-atmosphere (TOA) downward lunar fluxes, we adapted the spherical harmonics discrete ordinate method (SHDOM) 3-dimensional (3-D) radiative transfer model (RTM) to simulate nighttime 3-D TOA radiances as observed from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) on board the Suomi-NPP satellite platform. Used previously for daytime 3-D applications, these new SHDOM enhancements allow for the study of the impacts of various observing conditions and aerosol properties on simulated VIIRS-DNB TOA radiances. Observations over Dakar, Senegal, selected for its bright city lights and a large range of aerosol optical depth (AOD), were investigated for potential applications and opportunities for using observed radiances containing VIIRS-DNB “bright pixels” from artificial light sources to conduct aerosol retrievals. We found that using the standard deviation (SD) of such bright pixels provided a more stable quantity for nighttime AOD retrievals than direct retrievals from TOA radiances. Further, both the mean TOA radiance and SD of TOA radiances over artificial sources are significantly impacted by satellite viewing angles. Light domes, the enhanced radiances adjacent to artificial light sources, are strong functions of aerosol properties and especially aerosol vertical distribution, which may be further utilized for retrieving aerosol layer height in future studies. Through inter-comparison with both day- and nighttime Aerosol Robotic Network (AERONET) data, the feasibility of retrieving nighttime AODs using 3-D RTM SHDOM over artificial light sources was demonstrated. Our study shows strong potential for using artificial light sources for nighttime AOD retrievals, while also highlighting larger uncertainties in quantifying surface light source emissions. This study underscores the need for surface light emission source characterizations as a key boundary condition, which is a complex task that requires enhanced input data and further research. We demonstrate how quality-controlled nighttime light data from NASA’s Black Marble product suite could serve as a primary input into estimations of surface light source emissions for nighttime aerosol retrievals.
Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.
Adaptive mesh refinement is shown to be essential in turbulence modeling. Adaptive Mesh Refinement (AMR) is a more computationally efficient means to obtain a discrete approximation to a continuous boundary value problem of a specified accuracy than classic isotropic grid refinement. Previous application of this methodology in the assessment of turbulence models suggested that the field variable solution on the interior of the domain was more sensitive to grid refinement than would be suggested by the sensitivity to grid refinement of surface quantities. Revisiting challenging high speed flow field revealed that issues believed to be fundamental turbulence model issues appear to be related to an under-resolved boundary layer edge – a flow detail previously considered unimportant.
Regions worldwide are adopting and exploring low-speed automated electric shuttle (AES) service as an on-demand shared mobility service in dense geofenced urban areas. Building on this concept, the National Renewable Energy Laboratory (NREL) recently developed the Automated Mobility District (AMD) toolkit. The AMD toolkit—comprising of a travel micro-simulation model and an energy estimation model—estimates the mobility and energy impacts of a given shuttle configuration within an AMD. Early-stage AMD deployments need to find optimal operational configurations that include: (a) passenger capacity of an AES, (b) time-dependent routes, and (c) fleet size (AES units) to satisfy the demand for the region. This research extends the AMD toolkit functionality by developing an optimization-based planning module that will assist in the operations of AES units. We developed a constrained mixed-integer program accounting for passenger waiting time, battery range, and passenger capacity of AES units. For scalability, we demonstrated the Tabu search-based solution technique for a real-world network—a proposed AMD deployment in Greenville, South Carolina, USA. Compared to rule-based operations, our developed solution yields higher travel time and energy savings for the network at different demand levels. The sensitivity analyses for waiting time thresholds indicate nonlinearity in the system performance, underscoring the need to meet shared-use mobility user-level expectations. The developed optimization framework can be adapted and extended to accommodate different categories of shared-use on-demand mobility services.
In this study, a method of producing velocity profile maps from electrical capacitance volume tomography (ECVT) measurements by reconstructing displacement from measured changes in capacitance is developed and applied to fluidized bed systems. The mapping of the reconstruction leverages the gradient of the sensitivity distribution of the ECVT sensor to circumvent the need for image cross correlation techniques. Experimental data of both bubbling and slugging fluidized beds are collected in a cold flow model. Adaptation of the technique is discussed in detail, and velocity profiles are obtained for a range of gas flow rates. The produced velocity maps are compared against the established methods of cross correlation and against empirical correlations from the literature and are found to agree well in tracking slug and bubble velocity. The exception is when the tracked object is large relative to the ECVT sensor dimensions, a scenario that can be avoided through proper sensor design. The quantities of average velocity, momentum, and solid and gas volume fraction are derived from the image and velocity profiles. The results demonstrate and extend the power of ECVT as a measurement tool for the study and monitoring of gas–solid fluidized beds by providing a computationally cheaper alternative to 3-D cross correlation for deriving velocity profiles.
Proposed hearing aid maps spectrum of speech into band of lower frequencies at which ear remains sensitive. By redirecting normal speech frequencies into frequency band from 100 to 1,500 Hz, hearing aid allows people to understand normal conversation, including telephone calls. Principle operation of hearing aid adapted to other uses such as, clearing up noisy telephone or radio communication. In addition, loud-speakers more easily understood in presence of high background noise.
The Multiple Mirror Telescope (MMT) under development at the University of Arizona takes a new approach in adaptive optics placing a large (0.65 m) force-actuated, thin facesheet deformable mirror at the secondary of an astronomical telescope, thus reducing the effects of emissivity which are important in IR astronomy. However, The large size of the mirror and low stiffness actuators used drive the natural frequencies of the mirror down into the bandwidth of the atmospheric distortion. Conventional adaptive optics takes a quasi-static approach to controlling the, deformable mirror. However, flexibility within the control bandwidth calls for a new approach to adaptive optics. Dynamic influence functions are used to characterize the influence of each actuator on the surface of the deformable mirror. A linearized model of atmospheric distortion is combined with dynamic influence functions to produce a dynamic reconstructor. This dynamic reconstructor is recognized as an optimal control problem. Solving the optimal control problem for a system with hundreds of actuators and sensors is formidable. Exploiting the circularly symmetric geometry of the mirror, and a suitable model of atmospheric distortion, the control problem is divided into a number of smaller decoupled control problems using circulant matrix theory. A hierarchic control scheme which seeks to emulate the quasi-static control approach that is generally used in adaptive optics is compared to the proposed dynamic reconstruction technique. Although dynamic reconstruction requires somewhat more computational power to implement, it achieves better performance with less power usage, and is less sensitive than the hierarchic technique.