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At least 1,063 records · Page 59

RACE and Calculations of Three-dimensional Distributed Cavity Phase Shifts

The design for RACE, a Rb-clock flight experiment for the ISS, is described. The cold collision shift and multiple launching (juggling) have important implications for the design and the resulting clock accuracy and stability. We present and discuss the double clock design for RACE. This design reduces the noise contributions of the local oscillator and simplifies and enhances an accuracy evaluation of the clock. As we try to push beyond the current accuracies of clocks, new systematic errors become important. The best fountain clocks are using cylindrical TE(sub 011) microwave cavities. We recently pointed out that many atoms pass through a node of the standing wave microwave field in these cavities. Previous studies have shown potentially large frequency shifts for atoms passing through nodes in a TE(sub 013) cavity. The shift occurs because there is a small traveling wave component due to the absorption of the copper cavity walls. The small traveling wave component leads to position dependent phase shifts. To study these effects, we perform Finite Element calculations. Three-dimensional Finite Element calculations require significant computer resources. Here we show that the cylindrical boundary condition can be Fourier decomposed to a short series of two-dimensional problems. This dramatically reduces the time and memory required and we obtain (3D) phase distributions for a variety of cavities. With these results, we will be able to analyze this frequency shift in fountain and future space clocks.

Li, Ruoxin↗

Using Apex To Construct CPM-GOMS Models

process for automatically generating computational models of human/computer interactions as well as graphical and textual representations of the models has been built on the conceptual foundation of a method known in the art as CPM-GOMS. This method is so named because it combines (1) the task decomposition of analysis according to an underlying method known in the art as the goals, operators, methods, and selection (GOMS) method with (2) a model of human resource usage at the level of cognitive, perceptual, and motor (CPM) operations. CPM-GOMS models have made accurate predictions about behaviors of skilled computer users in routine tasks, but heretofore, such models have been generated in a tedious, error-prone manual process. In the present process, CPM-GOMS models are generated automatically from a hierarchical task decomposition expressed by use of a computer program, known as Apex, designed previously to be used to model human behavior in complex, dynamic tasks. An inherent capability of Apex for scheduling of resources automates the difficult task of interleaving the cognitive, perceptual, and motor resources that underlie common task operators (e.g., move and click mouse). The user interface of Apex automatically generates Program Evaluation Review Technique (PERT) charts, which enable modelers to visualize the complex parallel behavior represented by a model. Because interleaving and the generation of displays to aid visualization are automated, it is now feasible to construct arbitrarily long sequences of behaviors. The process was tested by using Apex to create a CPM-GOMS model of a relatively simple human/computer-interaction task and comparing the time predictions of the model and measurements of the times taken by human users in performing the various steps of the task. The task was to withdraw $80 in cash from an automated teller machine (ATM). For the test, a Visual Basic mockup of an ATM was created, with a provision for input from (and measurement of the performance of) the user via a mouse. The times predicted by the automatically generated model turned out to approximate the measured times fairly well (see figure). While these results are promising, there is need for further development of the process. Moreover, it will also be necessary to test other, more complex models: The actions required of the user in the ATM task are too sequential to involve substantial parallelism and interleaving and, hence, do not serve as an adequate test of the unique strength of CPM-GOMS models to accommodate parallelism and interleaving.

John, Bonnie↗

Validation, Comparison, and Integration of GOCI, AHI, MODIS, MISR, and VIIRS Aerosol Optical Depth Over East Asia During the 2016 KORUS-AQ Campaign

Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Myungje Choi↗

Helicopter approach capability using the differential global positioning system

The results of flight tests to determine the feasibility of using the Global Positioning System (GPS) in the differential mode (DGPS) to provide high accuracy, precision navigation, and guidance for helicopter approaches to landing are presented. The airborne DGPS receiver and associated equipment is installed in a NASA UH-60 Black Hawk helicopter. The ground-based DGPS reference receiver is located at a surveyed test site and is equipped with a real-time VHF data link to transmit correction information to the airborne DGPS receiver. The corrected airborne DGPS information, together with the preset approach geometry, is used to calculate guidance commands which are sent to the aircraft's approach guidance instruments. The use of DGPS derived guidance for helicopter approaches to landing is evaluated by comparing the DGPS data with the laser tracker truth data. Both standard (3 deg) and steep (6 deg and 9 deg) glideslope straight-in approaches were flown. DGPS positioning accuracy based on a time history analysis of the entire approach was 0.2 m (mean) +/- 1.8 m (2 sigma) laterally and -2.0 m (mean) +/- 3.5 m (2 sigma) vertically for 3 deg glideslope approaches, -0.1 m (mean) +/- 1.5 m (2 sigma) laterally and -1.1 m (mean) +/- 3.5 m (2 sigma) vertically for 6 deg glideslope approaches and 0.2 m (mean) +/- 1.3 m (2 sigma) laterally and -1.0 m (mean) +/- 2.8 m (2 sigma) vertically for 9 deg glideslope approaches. DGPS positioning accuracy at the 200 ft decision height (DH) on a standard 3 deg slideslope approach was 0.3 m (mean) +/- 1.5 m (2 sigma) laterally and -2.3 m (mean) +/- 1.6 m (2 sigma) vertically. These errors indicate that the helicopter position based on DGPS guidance satisfies the International Civil Aviation Organization (ICAO) Category 1 (CAT 1) lateral and vertical navigational accuracy requirements.

Kaufmann, David N.↗

Injecting Artificial Memory Errors Into a Running Computer Program

Single-event upsets (SEUs) or bitflips are computer memory errors caused by radiation. BITFLIPS (Basic Instrumentation Tool for Fault Localized Injection of Probabilistic SEUs) is a computer program that deliberately injects SEUs into another computer program, while the latter is running, for the purpose of evaluating the fault tolerance of that program. BITFLIPS was written as a plug-in extension of the open-source Valgrind debugging and profiling software. BITFLIPS can inject SEUs into any program that can be run on the Linux operating system, without needing to modify the program s source code. Further, if access to the original program source code is available, BITFLIPS offers fine-grained control over exactly when and which areas of memory (as specified via program variables) will be subjected to SEUs. The rate of injection of SEUs is controlled by specifying either a fault probability or a fault rate based on memory size and radiation exposure time, in units of SEUs per byte per second. BITFLIPS can also log each SEU that it injects and, if program source code is available, report the magnitude of effect of the SEU on a floating-point value or other program variable.

Bornstein, Benjamin J.↗

Evaluation of an Airborne Spacing Concept, On-Board Spacing Tool, and Pilot Interface

The number of commercial aircraft operations is predicted to increase in the next ten years, creating a need for improved operational efficiency. Two areas believed to offer significant increases in efficiency are optimized profile descents and dependent parallel runway operations. It is envisioned that during both of these types of operations, flight crews will precisely space their aircraft behind preceding aircraft at air traffic control assigned intervals to increase runway throughput and maximize the use of existing infrastructure. This paper describes a human-in-the-loop experiment designed to study the performance of an onboard spacing algorithm and pilots ratings of the usability and acceptability of an airborne spacing concept that supports dependent parallel arrivals. Pilot participants flew arrivals into the Dallas Fort-Worth terminal environment using one of three different simulators located at the National Aeronautics and Space Administration s (NASA) Langley Research Center. Scenarios were flown using Interval Management with Spacing (IM-S) and Required Time of Arrival (RTA) control methods during conditions of no error, error in the forecast wind, and offset (disturbance) to the arrival flow. Results indicate that pilots delivered their aircraft to the runway threshold within +/- 3.5 seconds of their assigned arrival time and reported that both the IM-S and RTA procedures were associated with low workload levels. In general, pilots found the IM-S concept, procedures, speeds, and interface acceptable; with 92% of pilots rating the procedures as complete and logical, 218 out of 240 responses agreeing that the IM-S speeds were acceptable, and 63% of pilots reporting that the displays were easy to understand and displayed in appropriate locations. The 22 (out of 240) responses, indicating that the commanded speeds were not acceptable and appropriate occurred during scenarios containing wind error and offset error. Concerns cited included the occurrence of multiple speed changes within a short time period, speed changes required within twenty miles of the runway, and an increase in airspeed followed shortly by a decrease in airspeed. Within this paper, appropriate design recommendations are provided, and the need for continued, iterative human-centered design is discussed.

Swieringa, Kurt↗

Bell Helicopter Advanced Rotocraft Transmission (ART) program

Future rotorcraft transmissions require key emerging material and component technologies using advanced and innovative design practices in order to meet the requirements for a reduced weight to power ratio, a decreased noise level, and a substantially increased reliability. The specific goals for the future rotorcraft transmission when compared with a current state-of-the-art transmission (SOAT) are: (1) a 25 percent weight reduction; (2) a 10 dB reduction in the transmitted noise level; and (3) a system reliability of 5000 hours mean-time-between-removal (MTBR) for the transmission. This report summarizes the work conducted by Bell Helicopter Textron, Inc. to achieve these goals under the Advanced Rotorcraft Transmission (ART) program from 1988 to 1995. The reference aircraft selected by BHTI for the ART program was the Tactical Tiltrotor which is a 17,000 lb gross weight aircraft. A tradeoff study was conducted comparing the ART with a Selected SOAT. The results showed the ART to be 29 percent lighter and up to 13 dB quieter with a calculated MTBR in excess of 5000 hours. The results of the following high risk component and material tests are also presented: (1) sequential meshing high contact ratio planetary with cantilevered support posts; (2) thin dense chrome plated M50 NiL double row spherical roller planetary bearings; (3) reduced kinematic error and increased bending strength spiral bevel gears; (4) high temperature WE43 magnesium housing evaluation and coupon corrosion tests; (5) flexure fatigue tests of precision forged coupons simulating precision forged gear teeth; and (6) flexure fatigue tests of plasma carburized coupons simulating plasma carburized gear teeth.

Henry, Zachary S.↗

General Solution for Theoretical Packet Data Loss Rate

Communications systems which transfer blocks ("frames") of data must use a marker ("frame synchronization pattern") for identifying where a block begins. A technique ("frame synchronization strategy") is used to locate the start of each frame and maintain synchronization as additional blocks are processed. A device which strips out the frame synchronization pattern [FSP] and provides an "end of frame" pulse is called a frame synchronizer. As clock and data errors are introduced into the system, the start-of-block marker becomes displaced and/or corrupted. The capability of the frame synchronizer to stay locked to the pattern under these conditions is a figure of merit for the frame synchronization strategy. It is important to select a strategy which will stay locked nearly all the time at bit error rates where the data is usable. ("Bit error rate" [BER] is the fraction of binary bits which are inverted by passage through a communication system.) The fraction of frames that are discarded because the frame synchronizer is not locked is called "Percent Data Loss" or "Packet Data Loss rate" [PDL]. A general approach for accurately predicting PDL given BER was developed in Theoretical Percent Data Loss Calculation and Measurement Accuracy, T. P. Kelly, LESC-30554, December 1992. Kelly gave a solution in terms of matrix equations, and only addressed "level" channel encoding. This paper goes on to give a closed-form polynomial solution for the most common class of frame synchronizer strategies, and will also address "mark" and "space" (differential) channel encoding, and burst error environments. The paper is divided into four sections and follows a logically ordered presentation, with results developed before they are evaluated. However, most readers will derive the greatest benefit from this paper by treating the results as reference material. The result developed for differential encoding can be extended to other applications (like block codes) where the probability is needed that a block contains only a certain number of errors.

Lansdowne, Chatwin↗

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗

Improving Solar and Solar+Storage Screening Techniques to Reduce Utility Interconnection Time and Costs (Final Technical Report)

Residential PV installations have increased rapidly over the last decade, and the increased application volume has caused permitting delays and lower overall adoption rates. In this project, we developed and evaluated whether data-driven secondary modeling and screening techniques can help utilities assess customer applications more accurately than traditional screening shortcuts. Secondary topologies are predicted using decision trees and commonly available information, such as service transformer, customer, and street locations. Conductors were predicted using a logistic regression method based on real world object (RWO) types, service transformer ratings, conductor length, and distance to transformer. After developing the combined primary and secondary distribution network model, hosting capacity results were used to train a random forest model to predict the pass/fail likelihood of a customer application. Powerflow based models with predicted secondaries and data-driven methods both increased the screening success rate, relative to common utility heuristics, by as much as 55 percentage points. Data-driven screening techniques were described by one utility as a "right-sized" approach for residential customers given the low-risk of small errors and the high-cost of accurate modeling.

14 SOLAR ENERGY↗

Assessing Heterogeneity of Surface Water Temperature Following Stream Restoration and a High-Intensity Fire from Thermal Imagery

Thermal heterogeneity of rivers is essential to support freshwater biodiversity. Salmon behaviorally thermoregulate by moving from patches of warm water to cold water. When implementing river restoration projects, it is essential to monitor changes in temperature and thermal heterogeneity through time to assess the impacts to a river’s thermal regime. Lightweight sensors that record both thermal infrared (TIR) and multispectral data carried via unoccupied aircraft systems (UASs) present an opportunity to monitor temperature variations at high spatial (<0.5 m) and temporal resolution, facilitating the detection of the small patches of varying temperatures salmon require. Here, we present methods to classify and filter visible wetted area, including a novel procedure to measure canopy cover, and extract and correct radiant surface water temperature to evaluate changes in the variability of stream temperature pre- and post-restoration followed by a high-intensity fire in a section of the river corridor of the South Fork McKenzie River, Oregon. We used a simple linear model to correct the TIR data by imaging a water bath where the temperature increased from 9.5 to 33.4 °C. The resulting model reduced the mean absolute error from 1.62 to 0.35 °C. We applied this correction to TIR-measured temperatures of wetted cells classified using NDWI imagery acquired in the field. We found warmer conditions (+2.6 °C) after restoration (p < 0.001) and median absolute deviation for pre-restoration (0.30) to be less than both that of post-restoration (0.85) and post-fire (0.79) orthomosaics. In addition, there was statistically significant evidence to support the hypothesis of shifts in temperature distributions pre- and post-restoration (KS test 2009 vs. 2019, p < 0.001, D = 0.99; KS test 2019 vs. 2021, p < 0.001, D = 0.10). Moreover, we used a Generalized Additive Model (GAM) that included spatial and environmental predictors (i.e., canopy cover calculated from multispectral NDVI and photogrammetrically derived digital elevation model) to model TIR temperature from a transect along the main river channel. This model explained 89% of the deviance, and the predictor variables showed statistical significance. Collectively, our study underscored the potential of a multispectral/TIR sensor to assess thermal heterogeneity in large and complex river systems.

Barker, Matthew I. (ORCID:0000000252864930)↗

QES-Plume v1.0: a Lagrangian dispersion model

Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low-computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-Plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local-mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian plume model for an elevated continuous point-source release in uniform flow, the Lagrangian scaling of dispersion in isotropic turbulence, and a non-Gaussian plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-Plume yields a maximum relative error below 6 % when compared with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasize the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.

58 GEOSCIENCES↗

Monitoring cognitive function and need with the automated neuropsychological assessment metrics in Decompression Sickness (DCS) research

Hypobaric decompression sickness (DCS) research presents the medical monitor with the difficult task of assessing the onset and progression of DCS largely on the basis of subjective symptoms. Even with the introduction of precordial Doppler ultrasound techniques for the detection of venous gas emboli (VGE), correct prediction of DCS can be made only about 65 percent of the time according to data from the Armstrong Laboratory's (AL's) hypobaric DCS database. An AL research protocol concerned with exercise and its effects on denitrogenation efficiency includes implementation of a performance assessment test battery to evaluate cognitive functioning during a 4-h simulated 30,000 ft (9144 m) exposure. Information gained from such a test battery may assist the medical monitor in identifying early signs of DCS and subtle neurologic dysfunction related to cases of asymptomatic, but advanced, DCS. This presentation concerns the selection and integration of a test battery and the timely graphic display of subject test results for the principal investigator and medical monitor. A subset of the Automated Neuropsychological Assessment Metrics (ANAM) developed through the Office of Military Performance Assessment Technology (OMPAT) was selected. The ANAM software provides a library of simple tests designed for precise measurement of processing efficiency in a variety of cognitive domains. For our application and time constraints, two tests requiring high levels of cognitive processing and memory were chosen along with one test requiring fine psychomotor performance. Accuracy, speed, and processing throughout variables as well as RMS error were collected. An automated mood survey provided 'state' information on six scales including anger, happiness, fear, depression, activity, and fatigue. An integrated and interactive LOTUS 1-2-3 macro was developed to import and display past and present task performance and mood-change information.

Nesthus, Thomas E.↗

Rapid monitoring of fermentations: a feasibility study on biological 2,3-butanediol production

2,3-butanediol (2,3-BDO) is an economically important platform chemical that can be produced by the fermentation of sugars using an engineered strain of Zymomonas mobilis . These fermentations require continuous monitoring and modification of fermentation conditions to maximize 2,3-BDO yields and minimize the production of the undesired coproducts glycerol and acetoin. Because of the time required for sampling and off-line chromatographic measurement of fermentation samples, the ability of fermentation scientists to modify fermentation conditions in a timely manner is limited. The goal of this study was to test if near-infrared spectroscopy (NIRS) along with multivariate statistics could reduce the time needed for this analysis and enable real-time monitoring and control of the fermentation. In this work we developed partial least squares (PLS) calibration models to predict the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol in fermentations via NIRS using two different spectrometers and two different spectroscopy modalities. We first evaluated the feasibility of rapid NIRS monitoring through experiments where we measured the signals from each analyte of interest and built NIRS-based PLS models using spectra from synthetic samples containing uncorrelated concentrations of these analytes. All analytes showed unique spectral signatures, and this initial modeling showed that all analytes could be detected simultaneously. We then began work with samples from laboratory fermentation experiments and tested the feasibility of regression model development across two spectral collection modalities (at-line and on-line) and two instruments: a laboratory-grade instrument and a low-cost instrument with a more limited spectral range. All modalities showed promise in the ability to monitor Z. mobilis fermentations of glucose and xylose to 2,3-BDO. The low-cost instrument displayed a lower signal-to-noise ratio than the laboratory-grade instrument, which led to comparatively lower performance overall, but still provided sufficient accuracy to monitor fermentation trends. While the ease of use of on-line monitoring systems was favored as compared to at-line systems due to the lack of sampling required and potential for automated process control, we observed some decrease in performance due to the additional complexity of the sample matrix. We have demonstrated that NIRS combined with multivariate analysis can be used for at-line and on-line monitoring of the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol during Z. mobilis fermentations. The decrease in signal-to-noise ratio when using a low-cost spectrometer led to greater prediction error than the laboratory-grade spectrometer for at-line monitoring. The on-line monitoring modality showed great promise for real time process control via NIRS.

09 BIOMASS FUELS↗

Calibration, measurement, and characterization of soil moisture dynamics in a central Amazonian tropical forest

Soil moisture plays a key role in hydrological, biogeochemical, and energy budgets of terrestrial ecosystems. Accurate soil moisture measurements in remote ecosystems such as the Amazon are difficult and limited because of logistical constraints. Time domain reflectometry (TDR) sensors are widely used to monitor soil moisture and require calibration to convert the TDR's dielectric permittivity measurement (K a ) to volumetric water content (θ v ). In this study, our objectives were to develop a field-based calibration of TDR sensors in an old-growth upland forest in the central Amazon, to evaluate the performance of the calibration, and then to apply the calibration to determine the dynamics of soil moisture content within a 14.2 -m-deep vertical soil profile. Depth-specific TDR calibration using local soils in a controlled laboratory setting yielded a novel K a –θ v third-degree polynomial calibration. The sensors were later installed to their specific calibration depth in a 14.2-m pit. The widely used K a –θ v relationship (Topp model) underestimated the site-specific θ v by 22–42%, indicating significant error in the model when applied to these well-structured, clay-rich tropical forest soils. The calibrated wet- and dry-season θ v data showed a variety of depth and temporal variations highlighting the importance of soil textural differentiation, root uptake depths, as well as event to seasonal precipitation effects. Data such as these are greatly needed for improving our understanding of ecohydrological processes within tropical forests and for improving models of these systems in the face of changing environmental conditions.

54 ENVIRONMENTAL SCIENCES↗

Predeployment validation of fault-tolerant systems through software-implemented fault insertion

Fault injection-based automated testing (FIAT) environment, which can be used to experimentally characterize and evaluate distributed realtime systems under fault-free and faulted conditions is described. A survey is presented of validation methodologies. The need for fault insertion based on validation methodologies is demonstrated. The origins and models of faults, and motivation for the FIAT concept are reviewed. FIAT employs a validation methodology which builds confidence in the system through first providing a baseline of fault-free performance data and then characterizing the behavior of the system with faults present. Fault insertion is accomplished through software and allows faults or the manifestation of faults to be inserted by either seeding faults into memory or triggering error detection mechanisms. FIAT is capable of emulating a variety of fault-tolerant strategies and architectures, can monitor system activity, and can automatically orchestrate experiments involving insertion of faults. There is a common system interface which allows ease of use to decrease experiment development and run time. Fault models chosen for experiments on FIAT have generated system responses which parallel those observed in real systems under faulty conditions. These capabilities are shown by two example experiments each using a different fault-tolerance strategy.

Czeck, Edward W.↗

Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system

This paper evaluates the performance of a multirotor uncrewed aircraft and AirCore system (UAAS) for measuring vertical profiles of wind velocity (speed and direction) and the mole fractions of methane (CH 4 ) and carbon dioxide (CO 2 ), and it presents a use case that combines UAAS measurements and dispersion modeling to quantify CH 4 emissions from a dairy farm. To evaluate the atmospheric sensing performance of the UAAS, four field deployments were performed at three locations in the San Joaquin Valley of California where CH 4 hotspots were observed downwind of dairy farms. A comparison of the observations collected on board the UAAS and an 11 m meteorological tower show that the UAAS can measure wind velocity trends with a root mean squared error varying between 0.4 and 1.1 m s -1 when the wind magnitude is less than 3.5 m s -1 . Findings from UAAS flight deployments and a calibration experiment also show that the UAAS can reliably resolve temporal variations in the mole fractions of CH 4 and CO 2 occurring over periods of 10 s or longer. Results from the UAAS and dispersion modeling use case further demonstrate that UAASs have great potential as low-cost tools for detecting and quantifying CH 4 emissions in near real time.

54 ENVIRONMENTAL SCIENCES↗

Prediction of annual soil respiration from its flux at mean annual temperature

Accurately scaling soil respiration (SR, the soil-to-atmosphere flow of CO2) across time and space is important to constrain and understand ecosystem to global scale SR, a major terrestrial carbon flux to the atmosphere. Year-round SR measurements are however expensive and sometimes impossible to perform. Bahn et al. (2010) developed an approach to estimate annual SR (SRannual) from the flux measured at mean soil temperature (SRMAST), but the robustness of this approach needs to be evaluated in diverse ecosystem types and climatic conditions globally. We used a global soil respiration database (SRDB-V4, with 823 SR observations worldwide) to test the capability of SRMAST to predict SRannual. SRMAST estimated using a variety of methods all showed clear relationships with annual SRannual. Two single-rate methods (i.e., using the single SR rate most close to mean annual soil temperature, or the single SR rate most close to mean annual air temperature) showed the most pronounced divergence from the true SRannual, but errors significantly decreased when using multiple SR rates within 1 ? of the mean annual soil temperature to estimate SRMAST. SRannual was most closely correlated with SRMAST estimated via a Q10 relationship, but this method has a potential autocorrelation issue that we explore and discuss. Air temperature data are much more widely available than is soil temperature, and we found that SR at mean annual air temperature (SRMAAT) can be used to predict SRannual as well. This study builds on Bahn et al. (2010) to demonstrate that SR measured at both annual mean soil and air temperature can be used to predict annual SR, with well-quantified errors. This capability could be used to reduce SR measurement frequency required for estimating SRannual and greatly decrease cost, factors that are generally important but especially in lower-income countries and cold, inaccessible regions.

Soil respiration, temperature, modeling↗