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At least 1,693 records · Page 94

Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

synthetic aperture radars (SARs)↗

Sampling Biases in MODIS and SeaWiFS Ocean Chlorophyll Data

Although modem ocean color sensors, such as MODIS and SeaWiFS are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data assimilation to create a "truth field", which we then sub-sampled using the observational patterns of MODIS and SeaWiFS. Monthly and annual mean chlorophyll estimates from these sub-sampled, incomplete daily fields were constructed and compared to monthly and annual means from the complete daily fields of the assimilation model, at a spatial resolution of 1.25deg longitude by 0.67deg latitude. The results showed that global annual mean biases were positive, reaching nearly 8% (MODIS) and >5% (SeaWiFS). For perspective the maximum interannual variability in the SeaWiFS chlorophyll record was about 3%. Annual mean sampling biases were low (<3%) in the midlatitudes (between -40deg and 40deg). Low interannual variability in the global annual mean sampling biases suggested that global scale trend analyses were valid. High latitude biases were much higher than the global annual means, up to 20% as a basin annual mean, and over 80% in some months. This was the result of the high solar zenith angle exclusion in the processing algorithms. Only data where the solar angle is <75deg are permitted, in contrast to the assimilation which samples regularly over the entire area and month. High solar zenith angles do not facilitate phytoplankton photosynthesis and consequently low chlorophyll concentrations occurring here are missed by the data sets. Ocean color sensors selectively sample in locations and times of favorable phytoplankton growth, producing overestimates of chlorophyll. The biases derived from lack of sampling in the high latitudes varied monthly, leading to artifacts in the apparent seasonal cycle from ocean color sensors. A false secondary peak in chlorophyll occurred in May-August, which resulted from lack of sampling in the Antarctic.

Gregg, Watson W.↗

Wing Shape Sensing from Measured Strain

A new two step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to extrapolate the deflection and slope of the entire structure through the use of System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular wing. It is then applied to test data from a cantilevered swept wing model.

system equivalent reduction and expansion process↗

Coastal zone color scanner 'system calibration': A retrospective examination

During its lifetime the Coastal Zone Color Scanner (CZCS) produced approximately 66,000 images. These have been placed in an archive of 'raw' radiance (sensor counts) in a subsampled format that is easily accessible. They have also been processed to form global fields, at reduced resolution, of normalized water-leaving radiance, phytoplankton pigments, and diffuse attenuation coefficient. Using this archive, we have tried to characterize some aspects of the 'system calibration' for the 8-year lifetime of CZCS. Specifically, we have assumed that the sensitivity of the red band decayed in a simple manner similar to the well-known long-term degradation of the shorter-wavelength bands, and we examined the sensitivity of the green and yellow bands by computing the globally averaged water-leaving radiance, over 10-day periods, for all of the imagery. The results provided evidence that in addition to the long-term degradation, short-term (2 weeks to 1 month) variations in the radiometric sensitivity of these bands started in early fall 1981 and continued for the rest of the mission. In contrast, the data suggested the absence of such variations prior to August 1981. It is reasonable to believe that the sensitivity of the blue (and probably the red) band underwent such variations as well; however our methodology cannot be used to study the other bands. Thus, after these fluctuations began, the actual values of CZCS - estimated pigment concentrations at a given location should be viewed with skepticism; however, the global patterns of derived pigment concentrations should be valid. Had an extensive set of surface measurements of water-leaving radiance, e.r., from moored buoyes or drifters, had been available during the CZCS mission, these fluctuations could have been removed from the data set, and this would have greatly increased its value. The lessons learned from CZCS that is, the requirement of good radiometric calibration and stability and the necessity of 'sea truth' stations to monitor the performance of the system (sensor plus algorithms), are being applied to the sea-viewing wide-field-of-view senso (Sea WiFS) scheduled for launch in August 1993.

Evans, Robert H.↗

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dominant balance-based adaptive mesh refinement for incompressible fluid flows

This work introduces a novel adaptive mesh refinement (AMR) method that utilizes dominant balance analysis (DBA) for efficient and accurate grid adaptation in computational fluid dynamics (CFD) simulations. The proposed method leverages a Gaussian mixture model (GMM) to classify grid cells into active and passive regions based on the dominant physical interactions within the equation space. By modeling truncation error probabilistically from discretized terms, the method identifies regions of high interaction where numerical accuracy is most sensitive to resolution. Unlike traditional AMR strategies, this approach does not rely on heuristic-based sensors or user-defined thresholds, providing a fully automated and problem-independent framework for AMR. Applied to the incompressible Navier-Stokes equations for steady and unsteady flow past a cylinder, the DBA-based AMR method achieves comparable accuracy to high-resolution grids while reducing computational costs by up to 70 %. The validation highlights the method’s effectiveness in capturing complex flow features while minimizing grid cells, directing computational resources toward regions with the most critical dynamics. This modular and scalable strategy is adaptable to a wide range of applications, presenting a promising tool for efficient high-fidelity simulations in CFD and other multiphysics domains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Dissolved Oxygen and Temperature Data from the Hyporheic Zone of the East River Watershed July 2017 to October 2018

Dissolved oxygen (DO) is critical for aquatic ecosystems. Our focus is on the long-term DO dynamics in hyporheic zone of rivers, which are a function of both transport (hydrologic exchange between river and hyporheic zone) and uptake by biogeochemical reactions or respiration. The study site is the alpine East River watershed in Colorado, USA, meander A downstream from the pump house. Opti O2 probes were deployed in the water column and directly within the river-bed at 10, 20, and 35 cm depth (38°55'23.38"N, 106°57'4.21"W, 9046.88m) to monitor DO and temperature. A continuous data stream from July 24, 2017 to Oct 24, 2018 was autonomously telemetered to the cloud. This 14-month DO and temperature time series were obtained without any servicing for maintenance or data downloads; additionally the ability to remotely verify probe performance during field deployment was essential to confirm data validity during winter freeze-in and hydrological/weather events, such as spring melt and summer monsoons. We investigate the variations in dissolved oxygen dynamics of this snow-pack dominated watershed during a comparatively low flow water year (2018) and a relatively normal water year (2017), enabled by distinctive, in-situ, high frequency (∆t = 5min) sensors that provided a continuous time-series from the undisturbed study site over multiple seasons.

54 ENVIRONMENTAL SCIENCES↗

A new era of observationally-infused E3SM: GANs for unifying imagery archives

This paper presents an idea to develop a “Rosetta Stone” for unifying observations from various satellite or remote sensors into a common format that would vastly advance our ability to exploit existing datasets for improving predictability within Earth System Models (ESMs). While the applications of such a unified archive are broad, we believe it will be a critical step toward ushering in a new generation of ESMs that are richly informed, guided by, and validated by extensive observational data. With the vast quantity of both remotely-sensed and in-situ data streams available and coming online, new approaches are needed that can harmonize and thus fully exploit these expensive datasets. While we present the broader idea, we point to examples of applications that impact the water cycle and its representation in ESMs.

58 GEOSCIENCES↗

Large space structure model reduction and control system design based upon actuator and sensor influence functions

A model reduction procedure based on aggregation with respect to sensor and actuator influences rather than modes is presented for large systems of coupled second-order differential equations. Perturbation expressions which can predict the effects of spillover on both the aggregated and residual states are derived. These expressions lead to the development of control system design constraints which are sufficient to guarantee, to within the validity of the perturbations, that the residual states are not destabilized by control systems designed from the reduced model. A numerical example is provided to illustrate the application of the aggregation and control system design method.

Yam, Y.↗

Experimental validation of flexible robot arm modeling and control

Flexibility is important for high speed, high precision operation of lightweight manipulators. Accurate dynamic modeling of flexible robot arms is needed. Previous work has mostly been based on linear elasticity with prescribed rigid body motions (i.e., no effect of flexible motion on rigid body motion). Little or no experimental validation of dynamic models for flexible arms is available. Experimental results are also limited for flexible arm control. Researchers include the effects of prismatic as well as revolute joints. They investigate the effect of full coupling between the rigid and flexible motions, and of axial shortening, and consider the control of flexible arms using only additional sensors.

Ulsoy, A. Galip↗

Operational Cloud Detection in GEOS Imagery

The bispectral spatial coherence approach for the detection and masking of clouds is revisited with modifications for operational applications to Geostationary Operational Environmental Satellite (GOES) Imager and Sounder data. The approach applies an edge detection algorithm to a "difference" image to identify the edges or contours of the clouds. The difference image is generated as the difference between the 3.9 and 11 micrometer channels of the GOES sensors. This difference image better highlights cloud edges than either image alone and draws upon the emissivity differences in the various channels. The cloud contours are "filled-in" by referencing the thermal gradients in the 11-micrometer channel or difference image associated with the cloud edge. This paper and associate poster will present a preliminary validation of the bispectral spatial coherence approach and will compare the cloud masks generated with this approach to the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service (NOAA/NESDIS) operational cloud products.

Jedlovec, Gary J.↗

Remote Observations of Reentering Spacecraft Including the Space Shuttle Orbiter

Flight measurement is a critical phase in development, validation and certification processes of technologies destined for future civilian and military operational capabilities. This paper focuses on several recent NASA-sponsored remote observations that have provided unique engineering and scientific insights of reentry vehicle flight phenomenology and performance that could not necessarily be obtained with more traditional instrumentation methods such as onboard discrete surface sensors. The missions highlighted include multiple spatially-resolved infrared observations of the NASA Space Shuttle Orbiter during hypersonic reentry from 2009 to 2011, and emission spectroscopy of comparatively small-sized sample return capsules returning from exploration missions. Emphasis has been placed upon identifying the challenges associated with these remote sensing missions with focus on end-to-end aspects that include the initial science objective, selection of the appropriate imaging platform and instrumentation suite, target flight path analysis and acquisition strategy, pre-mission simulations to optimize sensor configuration, logistics and communications during the actual observation. Explored are collaborative opportunities and technology investments required to develop a next-generation quantitative imaging system (i.e., an intelligent sensor and platform) with greater capability, which could more affordably support cross cutting civilian and military flight test needs.

Horvath, Thomas J.↗

On-Orbit Calibration and Performance of S-NPP VIIRS DNB

The S-NPP VIIRS instrument has successfully operated since its launch in October 2011. The VIIRS Day-Night Band (DNB) is a panchromatic channel covering wavelengths from 0.5 to 0.9 m that is capable of observing Earth scenes during both day and nighttime orbits at a spatial resolution of 750 m. To cover the large dynamic range, the DNB operates at low, mid, or high gain stages, and it uses an onboard solar diffuser (SD) for its low gain stage calibration. The SD observations also provide a means to compute gain ratios of low-to-mid and mid-to-high gain stages. This paper describes the DNB on-orbit calibration methodologies used by the VIIRS Characterization Support Team (VCST) in supporting the NASA earth science community with consistent VIIRS sensor data records (SDRs) made available by the Land Science Investigator-led Processing Systems (SIPS). It provides an assessment and update of DNB on-orbit performance, including the SD degradation in the DNB spectral range, detector gain and gain ratio trending, stray light contamination and its correction. Also presented in this paper are performance validations based on earth scenes and lunar observations.

Chen, H.↗

Passive/active Microwave Soil Moisture Change Disaggregation Using Smapvex12 Data

The SMAPVEX12 (Soil Moisture Active Passive (SMAP) Validation Experiment 2012) experiment was conducted during June-July 2012 in Manitoba, Canada with the goal of collecting remote sensing data and ground measurements for the development and testing of soil moisture retrieval algorithms under varying vegetation and soil conditions for the SMAP satellite. The aircraft based soil moisture data provided by the passive/active microwave sensor PALS (Passive and Active L-band System) has a nominal spatial resolution of 1600 m. However, this resolution is not compatible with agricultural, meteorological and hydrological studies that require high spatial resolutions and this issue can be solved by soil moisture disaggregation. The soil moisture disaggregation algorithm integrates radiometer soil moisture retrievals and high-resolution radar observations and it can provide soil moisture estimates at a finer scale than the radiometer data alone. In this study, a change detection algorithm was used for disaggregation of coarse resolution passive microwave soil moisture retrievals with radar backscatter coefficients obtained from the higher spatial resolution UAVSAR (Unmanned Air Vehicle Synthetic Aperture Radar) at crop field scale. The accuracy of the disaggregated change in soil moisture was evaluated using ground based soil moisture measurements collected during SMAPVEX12 campaign. The results showed that soil moisture spatial variabilities were better characterized by the disaggregated change in soil moisture estimates at 5 m / 800 m resolution as well as good agreement with in situ measurements. It also showed that VWC (Vegetation Water Content) did not have a big impact on disaggregation algorithm performance, with R2 of the disaggregated results ranging 0.628-0.794. The 5 m and 800m resolution disaggregated soil moisture did no show significant difference in statistical performance variables.

Radar Backscatter↗

Tunable diode laser absorption spectroscopy-based tomography system for on-line monitoring of two-dimensional distributions of temperature and H{sub 2}O mole fraction

To monitor two-dimensional (2D) distributions of temperature and H{sub 2}O mole fraction, an on-line tomography system based on tunable diode laser absorption spectroscopy (TDLAS) was developed. To the best of the authors’ knowledge, this is the first report on a multi-view TDLAS-based system for simultaneous tomographic visualization of temperature and H{sub 2}O mole fraction in real time. The system consists of two distributed feedback (DFB) laser diodes, a tomographic sensor, electronic circuits, and a computer. The central frequencies of the two DFB laser diodes are at 7444.36 cm{sup −1} (1343.3 nm) and 7185.6 cm{sup −1} (1391.67 nm), respectively. The tomographic sensor is used to generate fan-beam illumination from five views and to produce 60 ray measurements. The electronic circuits not only provide stable temperature and precise current controlling signals for the laser diodes but also can accurately sample the transmitted laser intensities and extract integrated absorbances in real time. Finally, the integrated absorbances are transferred to the computer, in which the 2D distributions of temperature and H{sub 2}O mole fraction are reconstructed by using a modified Landweber algorithm. In the experiments, the TDLAS-based tomography system was validated by using asymmetric premixed flames with fixed and time-varying equivalent ratios, respectively. The results demonstrate that the system is able to reconstruct the profiles of the 2D distributions of temperature and H{sub 2}O mole fraction of the flame and effectively capture the dynamics of the combustion process, which exhibits good potential for flame monitoring and on-line combustion diagnosis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Continuous Water Quality Sensing for FGD Wastewater

The coal fired plant power industry requires new solutions for on-line monitoring of flue gas desulfurization (FGD) wastewaters for regulated trace metals to reduce recurring operating and off-site laboratory analysis costs and provide a high level of confidence of compliance with state and federal discharge guidelines. The University of Alabama at Birmingham (UAB) developed an integrated water sensor package for continuous water quality monitoring of flue gas desulfurization (FGD) wastewaters for concentration measurements of Selenium (Se). UAB utilized a diverse team of University Professors/Staff Members/Student(s) (Engineering and Innovative Technology Development Group), a University Affiliated Research Institution from the local area (Southern Research), and a cost sharing Industry Partner (Metrohm). The team developed and validated a proprietary wet chemistry batch process for water sample preparation; and implemented this process as a fully automated on-line monitor prototype system. This prototype system’s performance was evaluated in both the laboratory and during in-field deployment to a coal fired power plant. In both environments it was found that the prototype system was unable to recreate the batch process’s success at preparing FGD water samples for total Se measurements with a commercial-off-the-shelf (COTS) cyclic anodic stripping voltammetry (CSV) system. Through this experience, UAB has provided insight into a number of specific areas where improvements can be made with respect to the COTS systems used in this project to yield a more complete and competitive industry solution for on-line monitoring of total Se in industrial wastewater.

20 FOSSIL-FUELED POWER PLANTS↗

Continuous Water Quality Sensing for FGD Wastewater

The coal fired plant power industry requires new solutions for on-line monitoring of flue gas desulfurization (FGD) wastewaters for regulated trace metals to reduce recurring operating and off-site laboratory analysis costs and provide a high level of confidence of compliance with state and federal discharge guidelines. The University of Alabama at Birmingham (UAB) developed an integrated water sensor package for continuous water quality monitoring of flue gas desulfurization (FGD) wastewaters for concentration measurements of Selenium (Se). UAB utilized a diverse team of University Professors/Staff Members/Student(s) (Engineering and Innovative Technology Development Group), a University Affiliated Research Institution from the local area (Southern Research), and a cost sharing Industry Partner (Metrohm). The team developed and validated a proprietary wet chemistry batch process for water sample preparation; and implemented this process as a fully automated on-line monitor prototype system. This prototype system’s performance was evaluated in both the laboratory and during in-field deployment to a coal fired power plant. In both environments it was found that the prototype system was unable to recreate the batch process’s success at preparing FGD water samples for total Se measurements with a commercial-off-the-shelf (COTS) cyclic anodic stripping voltammetry (CSV) system. Through this experience, UAB has provided insight into a number of specific areas where improvements can be made with respect to the COTS systems used in this project to yield a more complete and competitive industry solution for on-line monitoring of total Se in industrial wastewater.

01 COAL, LIGNITE, AND PEAT↗

Out of the Lab: 3D Printing on Non-Ideal Surfaces

In this work, coaxial direct ink writing is utilized to print sensitive or encapsulated materials onto heterogeneous and rough substrates. By enclosing the core fluid within a rigid ceramic shell, continuity is maintained even when printing on substrates traditionally considered challenging. This work presents the development of a coaxial ceramic direct ink writing system and investigates co-flow dynamics through microfluidic principles. A specially designed coaxial nozzle enables the co-extrusion of an alumina shell, with indium-tin-oxide inks serving as the core material. This approach allows the fabrication of core-shell ceramic structures suitable for future high-temperature applications on rough surfaces. The colloidal inks are tailored to achieve the necessary rheological properties and sintering performance. Additionally, flow simulations, guided by microfluidic co-flow principles, are employed to define the processing parameters for coaxial printing, ensuring precise control over the core-shell architectures. Physical modeling is further applied to study core deformation and eccentricity. These simulations are experimentally validated, supporting the successful deposition of coaxial ceramic features on heterogeneous, high-temperature ceramic substrates.

20 FOSSIL-FUELED POWER PLANTS↗