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At least 1,171 records · Page 65

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Goetz, Scott J.↗

A Parametric Geometry Computational Fluid Dynamics (CFD) Study Utilizing Design of Experiments (DOE)

Design of Experiments (DOE) techniques were applied to the Launch Abort System (LAS) of the NASA Crew Exploration Vehicle (CEV) parametric geometry Computational Fluid Dynamics (CFD) study to efficiently identify and rank the primary contributors to the integrated drag over the vehicles ascent trajectory. Typical approaches to these types of activities involve developing all possible combinations of geometries changing one variable at a time, analyzing them with CFD, and predicting the main effects on an aerodynamic parameter, which in this application is integrated drag. The original plan for the LAS study team was to generate and analyze more than1000 geometry configurations to study 7 geometric parameters. By utilizing DOE techniques the number of geometries was strategically reduced to 84. In addition, critical information on interaction effects among the geometric factors were identified that would not have been possible with the traditional technique. Therefore, the study was performed in less time and provided more information on the geometric main effects and interactions impacting drag generated by the LAS. This paper discusses the methods utilized to develop the experimental design, execution, and data analysis.

Rhew, Ray D.↗

An LED Approach for Measuring the Photocatalytic Breakdown of Crystal Violet Dye

A simple technique to assess the reactivity of photocatalytic coatings sprayed onto transmissive glass surfaces was developed. This new method uses ultraviolet (UV) gallium nitride (GaN) light-emitting diodes (LEDs) to drive a photocatalytic reaction (the photocatalytic breakdown of a UV-resistant dye applied to a surface coated with the semiconductor titanium dioxide); and then a combination of a stabilized white light LED and a spectrometer to track the dye degradation as a function of time. Simple, standardized evaluation techniques that assess photocatalytic materials over a variety of environmental conditions, including illumination level, are not generally available and are greatly needed prior to in situ application of photocatalytic technologies. To date, much research pertaining to this aspect of photocatalysis has been limited and has focused primarily on laboratory experiments using mercury lamps. Mercury lamp illumination levels are difficult to control over large ranges and are temporally modulated by line power, limiting their use in helping to understand and predict how photocatalytic materials will behave in natural environmental settings and conditions. The methodology described here, using steady-state LEDs and time series spectroradiometric techniques, is a novel approach to explore the effect of UV light on the photocatalytic degradation of a UV resistant dye (crystal violet). GaN UV LED arrays, centered around 365 nm with an adjustable DC power supply, are used to create a small, spatially uniform light field where the steady state light level can be varied over three to four orders of magnitude. For this study, a set of glass microscope slides was custom coated with a thinly sprayed layer of photocatalytic titanium dioxide. Crystal violet was then applied to these titanium-dioxide coated slides and to uncoated control slides. The slides were then illuminated at various light levels from the dye side of the slide by the UV LED array. To monitor dye degradation on the slides over time, a temperature-stabilized white light LED was used to illuminate the opposite side of the slides. As the dye degraded, the amount of light from the white light LED transmitted through the slide was monitored with a spectrometer and subsequently analyzed to determine and compare the rate of dye degradation for photocatalytically coated versus uncoated slide surfaces. The long-term stability of the spectrometer/white light LED combination, which required only a single reference spectra to be taken for a time series sequence of several hours, enabled accurate measurements of transmitted light over time. Time series transmission curves were generated and results demonstrated that over time the transmission increased much more rapidly on the coated slides than on the control slides. This experimental configuration and methodology for photocatalytic activity measurement minimizes many external variable effects and allows low light level studies to be performed. This study also compares the advantages of this novel LED light source design to traditional mercury lamp systems and non-LED lamp approaches that have conventionally been used. The methodology and experimental design research summarized in this abstract is partly funded by the Department of Homeland Security, Science and Technology Directorate, and by the NASA Stennis Space Center Innovative Partnerships Program.

Ryan, Robert E.↗

Determining Chlamydomonas reinhardtii resistance to ionizing radiation at a genome-wide scale

Spaceflight is a complex mixture of abiotic stresses that causes a myriad of cellular responses including increased genome-wide mutation load. The impact of spaceflight on mutation load is not well understood for most organisms and is especially critical to characterize for candidate microorganisms that could be part of biological life support systems. Prior research in our laboratory revealed an unexpectedly high level of mutation during spaceflight in the eukaryotic green algae, C. reinhardtii. Based on the spectrum of base changes observed, we concluded that the mutations were generated through a molecular mechanism unique to the spaceflight environment. Spaceflight is a complex set of stresses, and we are using an Earth-based analog to test ionizing radiation as a potential causative variable for the unique mutation spectrum observed in spaceflight. C. reinhardtii was grown exposed to chronic radiation from a Cesium-137 source. Four biological replicate cultures of wild-type cells were grown in gas permeable plastic tissue culture bags in liquid media following the design used on the International Space Station (ISS) during the previous space algae experiment. Radiation levels for this experiment approximate ionizing radiation observed on the moon, in low Earth orbit (LEO), and on Earth. Cells from each replicate were passaged to inoculate the next cycle of growth, then samples were taken from each culture to characterize cell morphology, quantify biomass, and extract DNA. Whole genome sequencing from each culture will be used to identify the frequency and types of mutations in each radiation level. In growth cycles 3 and 4, there was a significant increase in biomass accumulation under lunar radiation level compared to LEO or Earth radiation levels. These results such that ionizing radiation affected growth of C. reinhardtii.

Microbiology↗

A generalizable machine learning approach to predict land surface temperature

Monitoring of land surface and atmospheric states is highly reliant on satellite data. Traditionally, data products are generated using carefully tuned and validated algorithms for low-earth orbit (LEO) sensors. However, the emerging constellation of geostationary (GEO) sensors contributes global, high temporal resolution observations which can better capture the diurnal variability of key observables like land surface temperature (LST). Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from LEO and GEO satellites to develop a deep learning-based method for sensor-to-sensor algorithm emulation. Our model is trained on GOES-16 thermal bands to predict MODIS Terra LST and achieves a validation error <2K. Further, application of the model to unseen times of day and a second GEO sensor observing an unseen spatial domain demonstrate the generalization of the deep learning model across space, time and spectra. We anticipate that the synergies between a variety of active orbit configurations can be used to accelerate application of existing algorithms to new datasets.

Kate Marie Duffy↗

Determining Chlamydomonas Reinhardtii Resistance to Ionizing Radiation at A Genome-Wide Scale

Spaceflight is a complex mixture of abiotic stresses that causes a myriad of cellular responses including increased genome-wide mutation load. The impact of spaceflight on mutation load is not well understood for most organisms and is especially critical to characterize for candidate microorganisms that could be part of biological life support systems. Prior research in our laboratory revealed an unexpectedly high level of mutation during spaceflight in the eukaryotic green algae, C. reinhardtii. Based on the spectrum of base changes observed, we concluded that the mutations were generated through a molecular mechanism unique to the spaceflight environment. Spaceflight is a complex set of stresses, and we are using an Earth-based analog to test ionizing radiation as a potential causative variable for the unique mutation spectrum observed in spaceflight. C. reinhardtii was grown exposed to chronic radiation from a Cesium-137 source. Four biological replicate cultures of wild-type cells were grown in gas permeable plastic tissue culture bags in liquid media following the design used on the International Space Station (ISS) during the previous space algae experiment. Radiation levels for this experiment approximate ionizing radiation observed on the moon, in low Earth orbit (LEO), and on Earth. Cells from each replicate were passaged to inoculate the next cycle of growth, then samples were taken from each culture to characterize cell morphology, quantify biomass, and extract DNA. Whole genome sequencing from each culture will be used to identify the frequency and types of mutations in each radiation level. In growth cycles 3 and 4, there was a significant increase in biomass accumulation under lunar radiation level compared to LEO or Earth radiation levels. These results show that ionizing radiation affected growth of C. reinhardtii.

Hope Hersh↗

Control logic to track the outputs of a command generator or randomly forced target

A procedure is presented for synthesizing time-invariant control logic to cause the outputs of a linear plant to track the outputs of an unforced (or randomly forced) linear dynamic system. The control logic uses feed-forward of the reference system state variables and feedback of the plant state variables. The feed-forward gains are obtained from the solution of a linear algebraic matrix equation of the Liapunov type. The feedback gains are the usual regulator gains, determined to stabilize (or augment the stability of) the plant, possibly including integral control. The method is applied here to the design of control logic for a second-order servomechanism to follow a linearly increasing (ramp) signal, an unstable third-order system with two controls to track two separate ramp signals, and a sixth-order system with two controls to track a constant signal and an exponentially decreasing signal (aircraft landing-flare or glide-slope-capture with constant velocity).

Trankle, T. L.↗

Creating Aerosol Types Form CHemistry (CATCH): a New Algorithm to Extend the Link Between Remote Sensing and Models

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH-derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first-generation airborne High Spectral Resolution Lidar (HSRL-1) retrievals during the Ship-Aircraft Bio-Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH-derived aerosol types are determined by multivariate clustering of model-calculated variables that have been trained using retrievals of aerosol types from HSRL-1. CATCH-derived aerosol types (with the exception of smoke) compare well with HSRL-1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System- with Chemistry (GEOS-Chem) model. Spatial distributions of CATCH-derived aerosol types for the North American model domain during July/August 2014 show that aerosol type-specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model-generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL-1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

K W Dawson↗

Test results of six-month test of two water electrolysis systems

The two water electrolysis systems used in the NASA space station simulation 90-day manned test of a regenerative life support system were refurbished as required and subjected to 26-weeks of testing. The two electrolysis units are both promising systems for oxygen and hydrogen generation and both needed extensive long-term testing to evaluate the performance of the respective cell design and provide guidance for further development. Testing was conducted to evaluate performance in terms of current, pressure, variable oxygen demands, and orbital simulation. An automatic monitoring system was used to record, monitor and printout performance data at one minute, ten minute or one-hour intervals. Performance data is presented for each day of system operation for each module used during the day. Failures are analyzed, remedial action taken to eliminate problems is discussed and recommendations for redesign for future space applications are stated.

Mills, E. S.↗

Control for nuclear thermionic power source

A control for a power source which includes nuclear fuel interspersed with thermionic converters, is described. A power regulator maintains a substantially constant output voltage to a variable load, and a control circuit drives a neutron flux regulator in accordance with the current supplied to the power regulator and the neutron flux density in the region of the converters. The control circuit generates a control signal which is the difference between the neutron flux density and a linear function of the current, and drives the neutron regulator in a direction to decrease or increase the neutron flux according to the polarity of the control signal.

Sawyer, C. D.↗

Prediction of radio frequency power generation of Neptune's magnetosphere from generalized radiometric Bode's law

Magnetospheric radio frequency emission power has been shown to vary as a function of both solar wind and planetary values such as magnetic field by Kaiser and Desch (1984). Planetary magnetic fields have been shown to scale with planetary variables such as density and angular momentum by numerous researchers. This paper combines two magnetic scaling laws with the radiometric law to yield 'Bode's'-type laws governing planetary radio emissions. Further analysis allows the reduction of variables to planetary mass and orbital distance. These generalized laws are then used to predict the power otuput of Neptune to be about 1.6 x 10 to the 7th W; with the intensity peaking at about 3 MHz.

Million, M. A.↗

The effects of leading edge and downstream film cooling on turbine vane heat transfer

The progress under contract NAS3-24619 toward the goal of establishing a relevant data base for use in improving the predictive design capabilities for external heat transfer to turbine vanes, including the effect of downstream film cooling with and without leading edge showerhead film cooling. Experimental measurements were made in a two-dimensional cascade previously used to obtain vane surface heat transfer distributions on nonfilm cooled airfoils under contract NAS3-22761 and leading edge showerhead film cooled airfoils under contract NAS3-23695. The principal independent parameters (Mach number, Reynolds number, turbulence, wall-to-gas temperature ratio, coolant-to-gas temperature ratio, and coolant-to-gas pressure ratio) were maintained over ranges consistent with actual engine conditions and the test matrix was structured to provide an assessment of the independent influence of parameters of interest, namely, exit Mach number, exit Reynolds number, coolant-to-gas temperature ratio, and coolant-to-gas pressure ratio. Data provide a data base for downstream film cooled turbine vanes and extends the data bases generated in the two previous studies. The vane external heat transfer obtained indicate that considerable cooling benefits can be achieved by utilizing downstream film cooling. The data obtained and presented illustrate the interaction of the variables and should provide the airfoil designer and computational analyst the information required to improve heat transfer design capabilities for film cooled turbine airfoils.

Hylton, L. D.↗

Thermal modeling of a Ni-H2 battery cell

The nickel-hydrogen secondary battery has many desirable features which make it attractive for satellite power systems. It can provide a significant improvement over the energy density of present spacecraft nickel-cadnium batteries, combined with longer life, tolerance to overcharge and possibility of state-of-charge indication. However, to realize these advantages, accurate thermal modeling of nickel-hydrogen cells is required in order to properly design the battery pack so that it operates within a specified temperature range during the operation. Maintenance of a low operating temperature and a uniform temperature profile within the cell will yield better reliability, improved cycle life and better charge/discharge efficiencies. This research has the objective of developing and testing a thermal model which can be used to characterize battery operation. Primarily, temperature distribution with the heat generation rates as a function of position and time will be evaluated for a Ni-H2 cell in the three operating modes: (1) charge cycle, (2) discharge cycle, and (3) overcharge condition, if applicable. Variables to be examined include charging current, discharge rates, state of charge, pressure and temperature. Once the thermal model has been developed, this resulting model will predict the actual operating temperature and temperature gradient for the specific cell geometry to be used.

Ryu, Si-Ok↗

Advance finite element modeling of rotor blade aeroelasticity

An advanced beam finite element has been developed for modeling rotor blade dynamics and aeroelasticity. This element is part of the Element Library of the Second Generation Comprehensive Helicopter Analysis System (2GCHAS). The element allows modeling of arbitrary rotor systems, including bearingless rotors. It accounts for moderately large elastic deflections, anisotropic properties, large frame motion for maneuver simulation, and allows for variable order shape functions. The effects of gravity, mechanically applied and aerodynamic loads are included. All kinematic quantities required to compute airloads are provided. In this paper, the fundamental assumptions and derivation of the element matrices are presented. Numerical results are shown to verify the formulation and illustrate several features of the element.

Straub, F. K.↗

Using Artificial Life to Assess the Typicality of Terrestrial Life: Implications for Human Mission Planetary Protection

The extent to which extraterrestrial life questions can be addressed, in the absence of an actual example, rests in some measure on the extent to which terrestrial life is representative of life in general since we will likely have to draw heavily, if not completely, from terrestrial life research. One example of a practical question involving extraterrestrial life that arises in preparing for a human mission to another planet such as Mars, is trying to assess and minimize the possible adverse effects of the presence of humans on possible indigenous extraterrestrial life-forms. This paper will present some key planetary protection challenges for a human Mars mission and then focus on one possible approach for assessing the extent to which terrestrial life is representative of biological phenomena in general, informing perhaps, the level of confidence we might have in applying terrestrial research - to extraterrestrial life issues. The approach involves appealing to the relatively new field of Artificial Life (A-Life) to: (1) use what might be the most basic minimal set of life-defining characteristics in (2) a large number of open-ended Artificial Life simulations to generate a "life possibility space" (3) the products of which can be examined for their plausibility within the context of relevant constraining knowledge, so that (4) the remaining possibility space can be examined for its variability relative to terrestrial life, where low variability might suggest that terrestrial life is representative of life in general, and high variability would indicate otherwise.

Lupisella, Mark↗

The Effects of Implementing TopModel Concepts in the Noah Model

Topographic effects on runoff generation have been documented observationally (e.g., Dunne and Black, 1970) and are the subject of the physically based rainfall-runoff model TOPMODEL (Beven and Kirkby, 1979; Beven, 1986a;b) and its extensions, which incorporate variable soil transmissivity effects (Sivapalan et al, 1987, Wood et al., 1988; 1990). These effects have been shown to exert significant control over the spatial distribution of runoff, soil moisture and evapotranspiration, and by extension, the latent and sensible heat fluxes

Peters-Lidard, C. D.↗

The Modular Aero-Propulsion System Simulation (MAPSS) Users' Guide

The Modular Aero-Propulsion System Simulation is a flexible turbofan engine simulation environment that provides the user a platform to develop advanced control algorithms. It is capable of testing the performance of control designs on a validated and verified generic engine model. In addition, it is able to generate state-space linear models of the engine model to aid in controller design. The engine model used in MAPSS is a generic high-pressure ratio, dual-spool, lowbypass, military-type, variable cycle turbofan engine with a digital controller. MAPSS is controlled by a graphical user interface (GUI) and this guide explains how to use it to take advantage of the capabilities of MAPSS.

Parker, Khary I.↗

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗