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NASA NTRS2022

Hybrid Model Based Approaches for Systems Health Management and Prognostics

This is a previously approved and published presentation. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Present achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. In principle, data-driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data-driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety-critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Prognostics↗

DOE OSTI2021

New Orthophoto Generation Strategies from UAV and Ground Remote Sensing Platforms for High-Throughput Phenotyping

Remote sensing platforms have become an effective data acquisition tool for digital agriculture. Imaging sensors onboard unmanned aerial vehicles (UAVs) and tractors are providing unprecedented high-geometric-resolution data for several crop phenotyping activities (e.g., canopy cover estimation, plant localization, and flowering date identification). Among potential products, orthophotos play an important role in agricultural management. Traditional orthophoto generation strategies suffer from several artifacts (e.g., double mapping, excessive pixilation, and seamline distortions). The above problems are more pronounced when dealing with mid- to late-season imagery, which is often used for establishing flowering date (e.g., tassel and panicle detection for maize and sorghum crops, respectively). In response to these challenges, this paper introduces new strategies for generating orthophotos that are conducive to the straightforward detection of tassels and panicles. The orthophoto generation strategies are valid for both frame and push-broom imaging systems. The target function of these strategies is striking a balance between the improved visual appearance of tassels/panicles and their geolocation accuracy. The new strategies are based on generating a smooth digital surface model (DSM) that maintains the geolocation quality along the plant rows while reducing double mapping and pixilation artifacts. Moreover, seamline control strategies are applied to avoid having seamline distortions at locations where the tassels and panicles are expected. The quality of generated orthophotos is evaluated through visual inspection as well as quantitative assessment of the degree of similarity between the generated orthophotos and original images. Several experimental results from both UAV and ground platforms show that the proposed strategies do improve the visual quality of derived orthophotos while maintaining the geolocation accuracy at tassel/panicle locations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

Design and Preliminary Thermal Performance of the Mars Science Laboratory Rover Heat Exchangers

The challenging range of proposed landing sites for the Mars Science Laboratory Rover requires a rover thermal management system that is capable of keeping temperatures controlled across a wide variety of environmental conditions. On the Martian surface where temperatures can be as cold as -123 degrees Centigrade and as warm as 38 degrees Centigrade, the Rover relies upon a Mechanically Pumped Fluid Loop (MPFL) and external radiators to maintain the temperature of sensitive electronics and science instruments within a -40 degrees Centigrade to 50 degrees Centigrade range. The MPFL also manages significant waste heat generated from the Rover power source, known as the Multi Mission Radioisotope Thermoelectric Generator (MMRTG). The MMRTG produces 110 Watts of electrical power while generating waste heat equivalent to approximately 2000 Watts. Two similar Heat Exchanger (HX) assemblies were designed to both acquire the heat from the MMRTG and radiate waste heat from the onboard electronics to the surrounding Martian environment. Heat acquisition is accomplished on the interior surface of each HX while heat rejection is accomplished on the exterior surface of each HX. Since these two surfaces need to be at very different temperatures in order for the MPFL to perform efficiently, they need to be thermally isolated from one another. The HXs were therefore designed for high in-plane thermal conductivity and extremely low through-thickness thermal conductivity by using aerogel as an insulator inside composite honeycomb sandwich panels. A complex assembly of hand welded and uniquely bent aluminum tubes are bonded onto the HX panels and were specifically designed to be easily mated and demated to the rest of the Rover Heat Recovery and Rejection System (RHRS) in order to ease the integration effort. During the cruise phase to Mars, the HX assemblies serve the additional function of transferring heat from the Rover MPFL to the separate Cruise Stage MPFL so that heat generated deep inside the Rover can be dissipated via the Cruise Stage radiators. Significant fabrication challenges had to be overcome in order to make the HX design a reality. The cruise phase thermal performance of the Rover HXs was verified in the cruise phase system level thermal vacuum test that was performed at JPL in January of 2009. The Rover HXs were modeled in I-DEAS TMG and predictions are compared to actual data from the test.

Heat Rejection System↗

NASA NTRS1983

Creep testing of foil-gage metals at elevated temperature using an automated data acquisition system

A method is being developed to obtain creep data on foil gage metals at elevated temperatures using an automated data acquisition system in conjunction with a mechanically counter balanced extensometer. The automated system components include the Hewlett-Packard (HP) 9845A desktop computer, the HP 3455A digital voltmeter and the HP 3495A scanner. Software for test monitoring and data collection was developed; data manipulation, including curve plotting was done with a HP regression analysis software package. Initial creep tests were conducted on .003 in. thick foil specimens of Ti-6A1-4V at temperatures of 800 F and 1000 F and at stress levels of 25 ksi and 45 ksi. For comparison, duplicate tests were run on .049 in. thick specimens sheet of the same alloy. During testing, the furnace and specimen temperature, bridge voltage, strain and load output were automatically monitored and recorded at predetermined intervals. Using the HP regression analysis program, recorded strain output was plotted as a function of time. These resultant creep curves indicate that, under similar conditions of temperature and stress, foil gage specimens exhibit a higher creep rate than sheet specimens.

Blackburn, L. B.↗

NASA NTRS2005

Porous media matric potential and water content measurements during parabolic flight

Control of water and air in the root zone of plants remains a challenge in the microgravity environment of space. Due to limited flight opportunities, research aimed at resolving microgravity porous media fluid dynamics must often be conducted on Earth. The NASA KC-135 reduced gravity flight program offers an opportunity for Earth-based researchers to study physical processes in a variable gravity environment. The objectives of this study were to obtain measurements of water content and matric potential during the parabolic profile flown by the KC-135 aircraft. The flight profile provided 20-25 s of microgravity at the top of the parabola, while pulling 1.8 g at the bottom. The soil moisture sensors (Temperature and Moisture Acquisition System: Orbital Technologies, Madison, WI) used a heat-pulse method to indirectly estimate water content from heat dissipation. Tensiometers were constructed using a stainless steel porous cup with a pressure transducer and were used to measure the matric potential of the medium. The two types of sensors were placed at different depths in a substrate compartment filled with 1-2 mm Turface (calcined clay). The ability of the heat-pulse sensors to monitor overall changes in water content in the substrate compartment decreased with water content. Differences in measured water content data recorded at 0, 1, and 1.8 g were not significant. Tensiometer readings tracked pressure differences due to the hydrostatic force changes with variable gravity. The readings may have been affected by changes in cabin air pressure that occurred during each parabola. Tensiometer porous membrane conductivity (function of pore size) and fluid volume both influence response time. Porous media sample height and water content influence time-to-equilibrium, where shorter samples and higher water content achieve faster equilibrium. Further testing is needed to develop these sensors for space flight applications.

Parabolic Flight↗

DOE OSTI2022

Earned Value Management Systems for Operations Activities

An earned value management system (EVMS), which monitors contractor performance, is a requirement for program and project management for all major acquisitions by the United States Federal Government with development effort: (i.e., an asset requiring management attention because of its importance to an agency’s mission; high development, operating, or maintenance costs; high risk and/or high return). As an area less explored in earned value management (EVM) practices, this paper will survey the application of an EVMS for operations activities defined as: (1) Non-capital asset activities that are projects (or project - like) with definable start and end dates, with discrete scopes of work, and measurable accomplishments; as well as (2) Routine or recurring facility or environmental operations. This paper will examine the use of an EVMS to evaluate performance of operations and maintenance activities required once construction of a capital asset is complete and being used as intended. Such activities include upgrades and maintenance in order for capital assets to meet their mission function over a life-cycle (through repair, replacement, etc.). This paper will provide background on this topic from the perspective of the Department of Energy (DOE) Environmental Management (EM) Program. In addition, it will provide material from a panel discussion provided by a group of experts from the October 2019 Office of Environmental Management Project Management Workshop, as well as material from subsequent research on this topic.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

CCD data acquisition systems at Lick and Keck Observatories

This paper will describe and compare two distinct but related CCD data acquisition systems (DAS) currently under development at Lick and Keck Observatories. Although these two systems have a number of major architectural differences, they share a considerable amount of common hardware and software. Both of these new systems build on a large body of proven software that is the foundation of the existing CCD DAS currently in use at Lick Observatory. Both will provide support for reading up to four on-chip amplifiers per CCD and/or reading out mosaics of CCD chips. In addition, they will provide the capability for interactive, real-time adjustment of CCD waveforms for engineering purposes. Each of these two systems is composed of three major subsystems: (1) an instrument computer and its software; (2) a data capture computer and its software; and (3) a CCD/dewar controller and its software. The instrument computer is a Unix workstation, and the functions it provides include user interfaces, the interactive real-time display of CCD images, and the recording of image and FITS header data to disk and/or tape. The data capture computer is responsible for the packaging and high-speed transfer of the CCD pixel data stream into a bulk RAM, and the subsequent transfer of this data to the instrument computer. The CCD/dewar controller generates the waveforms for clocking the CCD, digitizes the pixel data, and transmits it via high-speed link to the data capture computer. It is also responsible for monitoring and controlling the dewar temperature and cryogen levels. Given the number of different types of processors and high-speed data links employed in both systems, a major emphasis of this paper will be on the various forms of interprocessor communications utilized for data transfer and distributed process synchronization.

Kibrick, R. I.↗

NASA NTRS1991

A reusable knowledge acquisition shell: KASH

KASH (Knowledge Acquisition SHell) is proposed to assist a knowledge engineer by providing a set of utilities for constructing knowledge acquisition sessions based on interviewing techniques. The information elicited from domain experts during the sessions is guided by a question dependency graph (QDG). The QDG defined by the knowledge engineer, consists of a series of control questions about the domain that are used to organize the knowledge of an expert. The content information supplies by the expert, in response to the questions, is represented in the form of a concept map. These maps can be constructed in a top-down or bottom-up manner by the QDG and used by KASH to generate the rules for a large class of expert system domains. Additionally, the concept maps can support the representation of temporal knowledge. The high degree of reusability encountered in the QDG and concept maps can vastly reduce the development times and costs associated with producing intelligent decision aids, training programs, and process control functions.

Westphal, Christopher↗

NASA NTRS2002

Earth Observing-1 Advanced Land Imager: Imaging Performance On-Orbit

This report analyzes the on-orbit imaging performance of the Advanced Land Imager (ALI) on the Earth Observing-1 satellite. The pre-flight calibrations are first summarized. The methods used to reconstruct and geometrically correct the image data from this push-broom sensor are described. The method used here does not refer to the position and attitude telemetry from the spacecraft. Rather, it is assumed that the image of the scene moves across the focal plane with a constant velocity, which can be ascertained from the image data itself. Next, an assortment of the images so reconstructed is presented. Color images sharpened with the 10-m panchromatic band data are shown, and the algorithm for producing them from the 30-m multispectral data is described. The approach taken for assessing spatial resolution is to compare the sharpness of features in the on-orbit image data with profiles predicted on the basis of the pre-flight calibrations. A large assortment of bridge profiles is analyzed, and very good fits to the predicted shapes are obtained. Lunar calibration scans are analyzed to examine the sharpness of the edge-spread function at the limb of the moon. The darkness of the space beyond the limb is better for this purpose than anything that could be simulated on the ground. From these scans, we find clear evidence of scattering in the optical system, as well as some weak ghost images. Scans of planets and stars are also analyzed. Stars are useful point sources of light at all wavelengths, and delineate the point-spread functions of the system. From a quarter-speed scan over the Pleiades, we find that the ALI can detect 6th magnitude stars. The quality of the reconstructed images verifies the capability of the ALI to produce Landsat-type multi spectral data. The signal-to-noise and panchromatic spatial resolution are considerably superior to those of the existing Landsat sensors. The spatial resolution is confirmed to be as good as it was designed to be.

ALI (ADVANCED LAND IMAGER)↗

NASA NTRS2012

Thermal Vacuum Integrated System Test at B-2

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) Plum Brook Station (PBS) Space Propulsion Research Facility, commonly referred to as B-2, is NASA s third largest thermal vacuum facility. It is the largest designed to store and transfer large quantities of liquid hydrogen and liquid oxygen, and is perfectly suited to support developmental testing of chemical propulsion systems as well as fully integrated stages. The facility is also capable of providing thermal-vacuum simulation services to support testing of large lightweight structures, Cryogenic Fluid Management (CFM) systems, electric propulsion test programs, and other In-Space propulsion programs. A recently completed integrated system test demonstrated the refurbished thermal vacuum capabilities of the facility. The test used the modernized data acquisition and control system to monitor the facility during pump down of the vacuum chamber, operation of the liquid nitrogen heat sink (or cold wall) and the infrared lamp array. A vacuum level of 1.3x10(exp -4)Pa (1x10(exp -6)torr) was achieved. The heat sink provided a uniform temperature environment of approximately 77 K (140deg R) along the entire inner surface of the vacuum chamber. The recently rebuilt and modernized infrared lamp array produced a nominal heat flux of 1.4 kW/sq m at a chamber diameter of 6.7 m (22 ft) and along 11 m (36 ft) of the chamber s cylindrical vertical interior. With the lamp array and heat sink operating simultaneously, the thermal systems produced a heat flux pattern simulating radiation to space on one surface and solar exposure on the other surface. The data acquired matched pretest predictions and demonstrated system functionality.

Kudlac, Maureen T.↗

DOE OSTI2023

Fusion of Multiple Models for Improving Gross Primary Production Estimation With Eddy Covariance Data Based on Machine Learning

Abstract Terrestrial gross primary production (GPP) represents the magnitude of CO 2 uptake through vegetation photosynthesis, and is a key variable for carbon cycles between the biosphere and atmosphere. Light use efficiency (LUE) models have been widely used to estimate GPP for its physiological mechanisms and availability of data acquisition and implementation, yet each individual GPP model has exhibited large uncertainties due to input errors and model structure, and further studies of systematic validation, comparison, and fusion of those models with eddy covariance (EC) site data across diverse ecosystem types are still needed in order to further improve GPP estimation. We here compared and fused five GPP models (VPM, EC‐LUE, GOL‐PEM, CHJ, and C‐Fix) across eight ecosystems based on FLUXNET2015 data set using the ensemble methods of Bayesian Model Averaging (BMA), Support Vector Machine (SVM), and Random Forest (RF) separately. Our results showed that for individual models, EC‐LUE gave a better performance to capture interannual variability of GPP than other models, followed by VPM and GLO‐PEM, while CHJ and C‐Fix were more limited in their estimation performance. We found RF and SVM were superior to BMA on merging individual models at various plant functional types (PFTs) and at the scale of individual sites. On the basis of individual models, the fusion methods of BMA, SVM, and RF were examined by a five‐fold cross validation for each ecosystem type, and each method successfully improved the average accuracy of estimation by 8%, 18%, and 19%, respectively.

Environmental Sciences & Ecology↗

NASA NTRS1983

Optimization methods applied to hybrid vehicle design

The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.

Donoghue, J. F.↗

NASA NTRS2019

NASA GIBS and Worldview: Bringing 20 Years of Terra Data into View

For nearly 10 years, the NASA Global Imagery Browse Services (GIBS) and Worldview interactive mapping site have provided users full resolution visualizations of Terra land, cryosphere, ocean, and atmosphere science parameters available within hours of acquisition. Over that time, GIBS and Worldview have expanded their Terra visualization suite to include even more parameters covering the entire mission of science data. Users can now view daily visualizations of nearly 50 near-real time and over 125 science quality science parameters from Terra instruments. These visualizations provide a unique capability for a broad user base to interact and discover the wealth of information sense by instruments on the Terra platform. By viewing Terra-based visualizations in a single location, users can correlate retrievals across instruments. Additionally, GIBS and Worldview include visualizations from many other platforms, allowing for an even greater data discovery capability.The GIBS and Worldview teams continue to work with Terra instrument science teams to add more visualized layers, as well as supporting visualization updates as the data is continually improved. Additionally, the GIBS interfaces and Worldview site are actively working on improved visualization functionality, including vector- and granule/swath-based products, to better address the expanding needs of its user community. This presentation will focus on an overview of existing and future visualization products and capabilities that have supported, and will support, a broad use of Terra data in science, media, and application communities.

Cechini, Matthew↗

DOE OSTI2021

DNA Viral Diversity, Abundance, and Functional Potential Vary across Grassland Soils with a Range of Historical Moisture Regimes

Soil viruses are abundant, but the influence of the environment and climate on soil viruses remains poorly understood. Here, we addressed this gap by comparing the diversity, abundance, lifestyle, and metabolic potential of DNA viruses in three grassland soils with historical differences in average annual precipitation, low in eastern Washington (WA), high in Iowa (IA), and intermediate in Kansas (KS). Bioinformatics analyses were applied to identify a total of 2,631 viral contigs, including 14 complete viral genomes from three deep metagenomes (1 terabase [Tb] each) that were sequenced from bulk soil DNA. An additional three replicate metagenomes (~0.5 Tb each) were obtained from each location for statistical comparisons. Identified viruses were primarily bacteriophages targeting dominant bacterial taxa. Both viral and host diversity were higher in soil with lower precipitation. Viral abundance was also significantly higher in the arid WA location than in IA and KS. More lysogenic markers and fewer clustered regularly interspaced short palindromic repeats (CRISPR) spacer hits were found in WA, reflecting more lysogeny in historically drier soil. More putative auxiliary metabolic genes (AMGs) were also detected in WA than in the historically wetter locations. The AMGs occurring in 18 pathways could potentially contribute to carbon metabolism and energy acquisition in their hosts. Structural equation modeling (SEM) suggested that historical precipitation influenced viral life cycle and selection of AMGs. The observed and predicted relationships between soil viruses and various biotic and abiotic variables have value for predicting viral responses to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2005

Integration of an Autopilot for a Micro Air Vehicle

Two autopilots providing autonomous flight capabilities are presented herein. The first is the Pico-Pilot, demonstrated for the 12-inch size class of micro air vehicles. The second is the MicroPilot MP2028(sup g), where its integration into a 36-inch Zagi airframe (tailless, elevons only configuration) is investigated and is the main focus of the report. Analytical methods, which include the use of the Advanced Aircraft Analysis software from DARCorp, were used to determine the stability and control derivatives, which were then validated through wind tunnel experiments. From the aerodynamic data, the linear, perturbed equations of motion from steady-state flight conditions may be cast in terms of these derivatives. Using these linear equations, transfer functions for the control and navigation systems were developed and feedback control laws based on Proportional, Integral, and Derivative (PID) control design were developed to control the aircraft. The PID gains may then be programmed into the autopilot software and uploaded to the microprocessor of the autopilot. The Pico-Pilot system was flight tested and shown to be successful in navigating a 12-inch MAV through a course defined by a number of waypoints with a high degree of accuracy, and in 20 mph winds. The system, though, showed problems with control authority in the roll and pitch motion of the aircraft: causing oscillations in these directions, but the aircraft maintained its heading while following the prescribed course. Flight tests were performed in remote control mode to evaluate handling, adjust trim, and test data logging for the Zagi with integrated MP2028(sup g). Ground testing was performed to test GPS acquisition, data logging, and control response in autonomous mode. Technical difficulties and integration limitations with the autopilot prevented fully autonomous flight from taking place, but the integration methodologies developed for this autopilot are, in general, applicable for unmanned air vehicles within the 36-inch size class or larger that use a PID control based autopilot.

Platanitis, George↗

NASA NTRS2011

Lunar Wormbot: Design and Development of a Ground Base Robotic Tunneling Worm for Operation in Harsh Environments

From 1969 to 1972, the National Aeronautics and Space Administration (NASA) sent Apollo missions to the moon to conduct various exploration experiment. A few of the missions were directed to the study and sampling of moon soil, otherwise known as lunar regolith. The extent of the sample acquisition was limited due to the astronauts' limited ability to penetrate the moon's surface to a depth greater than three meters. However. the samples obtained were sufficient enough to provide key information pertaining to lunar regolith material properties that would further assist in future exploration endeavors. Analysis of the collected samples showed that the properties of lunar regolith may lead to knowledge of processed materials that will be beneficial for future human exploration or colonization. However, almost 40 years after the last Apollo mission, limited infonnation is known about regions underneath the moon's surface. Future lunar missions will require hardware that possesses the ability to burrow to greater depths in order to collect samples for subsequent analysis. During the summer of 2010, a team (Dr. Jessica Gaskin, Michael Kuhlman. Blaze Sanders, and Lafe Zabowski) from the NASA Robotics Academy at Marshall Space Flight Center (MSFC) was given the task of designing a robot to function as a soil collection and analysis device. Working with the National Space Science and Technology Center (NSSTC), the team was able to propose an initial design, build a prototype, and test the various subsystems of the prototype to be known as the "Lunar Wormbot" (LW). The NASA/NSSTC team then transferred the project to a University of Alabama in Huntsville (UAH) Mechanical and Aerospace Engineering (MAE) senior design class for further development. The UAH team was to utilize the NASA Systems Engineering Engine Design Process in the continuance of the Lunar Wormbot project. This process was implemented in order to coordinate the efforts of the team and guide the design of the project to ensure a high quality product that met requirements within the academic year timeframe. When the transition from the NASA NSSTC team to the UAH team occurred in August 2010, the scope and requirements were provided to the UAH team. The main objective for the UAH team was to design and fabricate a robotic burrowing prototype using peristaltic or earthworm-like motion with the purpose of collecting soil samples. The team was tasked with the design of a sub-system of the LW called the locomotive, or active, segment. Through the design process, the team extensively reviewed the requirements and functions to be performed of the LW, which led to the proposal of a final design. The present paper provides the details of the development of the design up to and including the Critical Design Review (CDR) of the Lunar Wormbot. This document briefly describes thc overall system and its function but primarily focuses on the design and implementation of the locomotive segment. Content presented includes: general design and system functionality, technical drawings, system analysis, manufacturing methods, and general project costs.

Boyles, Charles↗

DOE OSTI2021

Drought legacies mediated by trait trade‐offs in soil microbiomes

Abstract Soil microbiomes play a key role in driving biogeochemical cycles of the Earth system. As drought frequency and intensity increase due to climate change, soil microbes and the processes they control will be impacted. Even after a drought ends, microbiomes and other systems take time to recover and may display a memory of previous climate conditions. Still, the mechanisms involved in these legacy effects remain unclear, making it difficult to predict climate and biogeochemical rates in the future. Here, we used a trait‐based microbiome model (DEMENTpy) to implement trade‐off‐mediated mechanisms that may lead to drought legacy effects on litter decomposition. Trade‐offs were assumed to follow the Y‐A‐S framework that defines three primary life‐history strategies of microorganisms: high growth Yield, resource Acquisition, and Stress tolerance. We represented cellular trade‐offs between osmolytes required for drought tolerance and investment in enzymes involved in litter decomposition. Simulations were run under varying levels of drought severity and dispersal. With high levels of dispersal, no legacy effects were predicted by DEMENTpy following drought. With limited dispersal, severe drought resulted in a persistent legacy of altered community‐level traits and reduced litter decomposition. Moderate drought resulted in a transient legacy that disappeared after two years, consistent with recent empirical observations in Southern California ecosystems. These results imply that greater movement along the trade‐off between enzyme investment and osmolyte production resulted in stronger legacy effects. More generally, factors that shift the position of a microbiome in YAS space may alter the legacy outcome following drought. Our trait‐based modeling study motivates additional empirical measurements to quantify YAS traits and trade‐offs that are needed to make accurate predictions of soil microbiome resilience and functioning. Also, our study illustrates an emerging approach for representing trait trade‐offs in microbiomes and vegetation that dictate ecosystem responses to drought and other environmental perturbations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1999

Cloud Thickness from Diffusion of Lidar Pulses in Clouds

Measurements of the distribution of reflected light from a laser beam incident on an aqueous suspension of particles or "cloud" with known thickness and particle size distribution are reported. The distribution is referred to as the "cloud radiative Green's function", G. In the diffusion domain, G is sensitive to cloud thickness, allowing that important quantity to be retrieved. The goal of the laboratory simulation is to provide preliminary estimates of sensitivity of G to cloud thickness,for use in the optimal design of an offbeam Lidar instrument for remote sensing of cloud thickness (THOR, Thickness from Offbeam Returns). These clouds of polystyrene microspheres suspended in water are analogous to real clouds of water droplets suspended in air. The microsphere size distribution is roughly lognormal, from 0.5 microns to 25 microns, similar to real clouds. Density of suspended spheres is adjusted so mean-free-path of visible photons is about 10 cm, approximately 1000 times smaller than in real clouds. The light source is a ND:YAG laser at 530 nm. Detectors are flux and photon-counting Photomultiplier Tube (PMTS), with a glass probe for precise positioning. A Labview 5 VI controls positioning, and data acquisition, via an NI Motion Control board connected to a stepper motor driving an Edmund linear slider, and a 16-channel 16-bit NI-DAQ board. The stepper motor is accurate to 10 microns, and step size is selectable from the VI software. Far from the incident beam, the rate of exponential increase as the direction of the incident beam is approached scales as expected from diffusion theory, linearly with the cloud thickness, and inversely as the square root of the reduced optical thickness, and is independent of particle size. Near the beam the signal begins to increase faster than exponential, due to single and low-order scattering near the backward direction, and here the distribution depends on particle size. Results are being used to verify 3D Monte Carlo radiative transfer simulations, used to estimate signal-to-noise ratios for remotely sensed off beam returns, for both homogeneous and inhomogeneous clouds. Signal-to-noise estimates show that unfiltered observations are straight forward at night, while narrow band pass filters are being studied for day.

Cahalan, Robert F.↗