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NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗

NASA NTRS2003

On the Scaling Laws for Jet Noise in Subsonic and Supersonic Flow

The scaling laws for the simulation of noise from subsonic and ideally expanded supersonic jets are examined with regard to their applicability to deduce full scale conditions from small-scale model testing. Important parameters of scale model testing for the simulation of jet noise are identified, and the methods of estimating full-scale noise levels from simulated scale model data are addressed. The limitations of cold-jet data in estimating high-temperature supersonic jet noise levels are discussed. It is shown that the jet Mach number (jet exit velocity/sound speed at jet exit) is a more general and convenient parameter for noise scaling purposes than the ratio of jet exit velocity to ambient speed of sound. A similarity spectrum is also proposed, which accounts for jet Mach number, angle to the jet axis, and jet density ratio. The proposed spectrum reduces nearly to the well-known similarity spectra proposed by Tam for the large-scale and the fine-scale turbulence noise in the appropriate limit.

Vu, Bruce↗

NASA NTRS2005

Scaling the Non-linear Impact Response of Flat and Curved Composite Panels

The application of scaling laws to thin flat and curved composite panels exhibiting nonlinear response when subjected to low-velocity transverse impact is investigated. Previous research has shown that the elastic impact response of structural configurations exhibiting geometrically linear response can be effectively scaled. In the present paper, a preliminary experimental study is presented to assess the applicability of the scaling laws to structural configurations exhibiting geometrically nonlinear deformations. The effect of damage on the scalability of the structural response characteristics, and the effect of scale on damage development are also investigated. Damage is evaluated using conventional methods including C-scan, specimen de-plying and visual inspection of the impacted panels. Coefficient of restitution and normalized contact duration are also used to assess the extent of damage. The results confirm the validity of the scaling parameters for elastic impacts. However, for the panels considered in the study, the extent and manifestation of damage do not scale according to the scaling laws. Furthermore, the results indicate that even though the damage does not scale, the overall panel response characteristics, as indicated by contact force profiles, do scale for some levels of damage.

Ambur, Damodar R.↗

NASA NTRS2005

Geometry and Reynolds-Number Scaling on an Iced Business-Jet Wing

A study was conducted to develop a method to scale the effect of ice accretion on a full-scale business jet wing model to a 1/12-scale model at greatly reduced Reynolds number. Full-scale, 5/12-scale, and 1/12-scale models of identical airfoil section were used in this study. Three types of ice accretion were studied: 22.5-minute ice protection system failure shape, 2-minute initial ice roughness, and a runback shape that forms downstream of a thermal anti-ice system. The results showed that the 22.5-minute failure shape could be scaled from full-scale to 1/12-scale through simple geometric scaling. The 2-minute roughness shape could be scaled by choosing an appropriate grit size. The runback ice shape exhibited greater Reynolds number effects and could not be scaled by simple geometric scaling of the ice shape.

Lee, Sam↗

NASA NTRS2006

Large-Scale Hybrid Motor Testing

Hybrid rocket motors can be successfully demonstrated at a small scale virtually anywhere. There have been many suitcase sized portable test stands assembled for demonstration of hybrids. They show the safety of hybrid rockets to the audiences. These small show motors and small laboratory scale motors can give comparative burn rate data for development of different fuel/oxidizer combinations, however questions that are always asked when hybrids are mentioned for large scale applications are - how do they scale and has it been shown in a large motor? To answer those questions, large scale motor testing is required to verify the hybrid motor at its true size. The necessity to conduct large-scale hybrid rocket motor tests to validate the burn rate from the small motors to application size has been documented in several place^'^^.^. Comparison of small scale hybrid data to that of larger scale data indicates that the fuel burn rate goes down with increasing port size, even with the same oxidizer flux. This trend holds for conventional hybrid motors with forward oxidizer injection and HTPB based fuels. While the reason this is occurring would make a great paper or study or thesis, it is not thoroughly understood at this time. Potential causes include the fact that since hybrid combustion is boundary layer driven, the larger port sizes reduce the interaction (radiation, mixing and heat transfer) from the core region of the port. This chapter focuses on some of the large, prototype sized testing of hybrid motors. The largest motors tested have been AMROC s 250K-lbf thrust motor at Edwards Air Force Base and the Hybrid Propulsion Demonstration Program s 250K-lbf thrust motor at Stennis Space Center. Numerous smaller tests were performed to support the burn rate, stability and scaling concepts that went into the development of those large motors.

Story, George↗

NASA NTRS2008

Ice Shape Scaling for Aircraft in SLD Conditions

This paper has summarized recent NASA research into scaling of SLD conditions with data from both SLD and Appendix C tests. Scaling results obtained by applying existing scaling methods for size and test-condition scaling will be reviewed. Large feather growth issues, including scaling approaches, will be discussed briefly. The material included applies only to unprotected, unswept geometries. Within the limits of the conditions tested to date, the results show that the similarity parameters needed for Appendix C scaling also can be used for SLD scaling, and no additional parameters are required. These results were based on visual comparisons of reference and scale ice shapes. Nearly all of the experimental results presented have been obtained in sea-level tunnels. The currently recommended methods to scale model size, icing limit and test conditions are described.

Anderson, David N.↗

NASA NTRS2012

The Scaling of Broadband Shock-Associated Noise with Increasing Temperature

A physical explanation for the saturation of broadband shock-associated noise (BBSAN) intensity with increasing jet stagnation temperature has eluded investigators. An explanation is proposed for this phenomenon with the use of an acoustic analogy. For this purpose the acoustic analogy of Morris and Miller is examined. To isolate the relevant physics, the scaling of BBSAN at the peak intensity level at the sideline ( = 90 degrees) observer location is examined. Scaling terms are isolated from the acoustic analogy and the result is compared using a convergent nozzle with the experiments of Bridges and Brown and using a convergent-divergent nozzle with the experiments of Kuo, McLaughlin, and Morris at four nozzle pressure ratios in increments of total temperature ratios from one to four. The equivalent source within the framework of the acoustic analogy for BBSAN is based on local field quantities at shock wave shear layer interactions. The equivalent source combined with accurate calculations of the propagation of sound through the jet shear layer, using an adjoint vector Green s function solver of the linearized Euler equations, allows for predictions that retain the scaling with respect to stagnation pressure and allows for the accurate saturation of BBSAN with increasing stagnation temperature. This is a minor change to the source model relative to the previously developed models. The full development of the scaling term is shown. The sources and vector Green s function solver are informed by steady Reynolds-Averaged Navier-Stokes solutions. These solutions are examined as a function of stagnation temperature at the first shock wave shear layer interaction. It is discovered that saturation of BBSAN with increasing jet stagnation temperature occurs due to a balance between the amplification of the sound propagation through the shear layer and the source term scaling.A physical explanation for the saturation of broadband shock-associated noise (BBSAN) intensity with increasing jet stagnation temperature has eluded investigators. An explanation is proposed for this phenomenon with the use of an acoustic analogy. For this purpose the acoustic analogy of Morris and Miller is examined. To isolate the relevant physics, the scaling of BBSAN at the peak intensity level at the sideline psi = 90 degrees) observer location is examined. Scaling terms are isolated from the acoustic analogy and the result is compared using a convergent nozzle with the experiments of Bridges and Brown and using a convergent-divergent nozzle with the experiments of Kuo, McLaughlin, and Morris at four nozzle pressure ratios in increments of total temperature ratios from one to four. The equivalent source within the framework of the acoustic analogy for BBSAN is based on local field quantities at shock wave shear layer interactions. The equivalent source combined with accurate calculations of the propagation of sound through the jet shear layer, using an adjoint vector Green s function solver of the linearized Euler equations, allows for predictions that retain the scaling with respect to stagnation pressure and allows for the accurate saturation of BBSAN with increasing stagnation temperature. This is a minor change to the source model relative to the previously developed models. The full development of the scaling term is shown. The sources and vector Green s function solver are informed by steady Reynolds-Averaged Navier-Stokes solutions. These solutions are examined as a function of stagnation temperature at the first shock wave shear layer interaction. It is discovered that saturation of BBSAN with increasing jet stagnation temperature occurs due to a balance between the amplification of the sound propagation through the shear layer and the source term scaling.

Miller, Steven A.↗

NASA NTRS2021

Satellite Remote Sensing to Assess Cyanobacterial Bloom Frequency Across the United States at Multiple Spatial Scales

Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Imager for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.

remote sensing↗

NASA NTRSDate not supplied

Towards Energy Scale Calibration and Drift Correction of TES Detectors for Athena X-IFU

The Athena X-Ray Integral Field Unit (X-IFU) comprises a 2376-pixel array of transition edge sensors (TES) read out with time-division multiplexing (TDM). X-IFU will provide spatially resolved, high-resolution spectroscopy (2.5 eV full-width-half-maximum up to 7 keV) over the energy range 0.2 to 12 keV, with an absolute energy scale accuracy of 0.4 eV. The energy scale function maps the optimally filtered pulse height, in arbitrary engineering units, to real calibrated energy. Uncertainties in the calibration can result from imperfect fitting of the energy scale between the known calibration points. Furthermore, temporal changes in the TES operating environment, such as heat-sink temperature, magnetic field and bias voltage, can cause significant variations in the detector gain function over time. If not properly corrected, this can result in degradation of the energy resolution, and systematic errors in the absolute energy scale. The non-linear nature of TES detectors, coupled with the possibility of multiple simultaneously occurring sources of drift, can make effective corrections over the full bandpass of the instrument extremely challenging. Athena X-IFU will employ an on-board calibration source that provides known reference x-ray lines. This provides real-time monitoring of the gain stability of the detector system and information that can be used to correct for gain drifts. For X-IFU the baseline approach is to measure a series of calibration curves under different environmental conditions, which bound the expected drifts the instrument is predicted to see over the course of the mission. Using the information from the in-flight calibration source, these energy scale functions can be interpolated to generate a new corrected energy scale as a function of time. In this paper we discuss progress towards demonstrating that the X-IFU energy scale requirements can be met. We present measurements on ~ 200 pixels in a prototype X-IFU array read out with 8-column x 32-row TDM. We use a rotating target source containing 12 fluorescent targets to generate x-ray lines covering the energy range 4 keV (Sc-Kα) to 12 keV (Br-Kα). We present measurements of the non-linear energy scale function and show how variations in heat-sink temperature, TES bias voltage and magnetic field affect the shape of TES energy scale differently and introduce different residual gain errors over the bandpass. We explore different drift correction algorithms that use either a single or multiple referential lines to track and correct the gain from these various sources of drift. In addition to the pulse-height, the DC ‘baseline’ level of the TES can contain information about its bias conditions. Thus, we test a multi-parameter gain correction algorithm that attempts to incorporate both the pulse height and the additional baseline information into the algorithm.

Stephen J Smith↗

DOE OSTI2020

Multi-scale integration of satellite remote sensing improves characterization of dry-season green-up in an Amazon tropical evergreen forest

In tropical forests, leaf phenology-particularly the pronounced dry-season green-up-strongly regulates biogeochemical cycles of carbon and water fluxes. However, uncertainties remain in the understanding of tropical forest leaf phenology at different spatial scales. Phenocams accurately characterize leaf phenology at the crown and ecosystem scales but are limited to a few sites and time spans of a few years. Time-series satellite observations might fill this gap, but the commonly used satellites (e.g. MODIS, Landsat and Sentinel-2) have resolutions too coarse to characterize single crowns. To resolve this observational challenge, we used the PlanetScope constellation with a 3m resolution and near daily nadir-view coverage. We first developed a rigorous method to cross-calibrate PlanetScope surface reflectance using daily BRDF-adjusted MODIS as the reference. We then used linear spectral unmixing of calibrated PlanetScope to obtain dry-season change in the fractional cover of green vegetation (GV) and non-photosynthetic vegetation (NPV) at the PlanetScope pixel level. We used the Central Amazon Tapajos National Forest k67 site, as all necessary data (from field to phenocam and satellite observations) was available. For this proof of concept, we chose a set of 22 dates of PlanetScope measurements in 2018 and 16 in 2019, all from the six drier months of the year to provide the highest possible cloud-free temporal resolution. Our results show that MODIS-calibrated dry-season PlanetScope data (1) accurately assessed seasonal changes in ecosystem-scale and crown-scale spectral reflectance; (2) detected an increase in ecosystem-scale GV fraction (and a decrease in NPV fraction) from June to November of both years, consistent with local phenocam observations with R 2 around 0.8; and (3) monitored large seasonal trend variability in crown-scale NPV fraction. Finally, our results highlight the potential of integrating multi-scale satellite observations to extend fine-scale leaf phenology monitoring beyond the spatial limits of phenocams.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Wafer-Scale Synthesis of 2D Materials by an Amorphous Phase-Mediated Crystallization Approach

The interest in the wafer-scale growth of two-dimensional (2D) materials, including transition metal dichalcogenides (TMDCs), has been rising for transitioning from lab-scale devices to commercial-scale systems. Among various synthesis techniques, physical vapor deposition, such as pulsed laser deposition (PLD), has shown promise for the wafer-scale growth of 2D materials. However, due to the high volatility of chalcogen atoms (e.g., S and Se), films deposited by PLD usually suffer from a lack of stoichiometry and chalcogen deficiency. To mitigate this issue, excess chalcogen is necessary during the deposition, which results in problems like uniformity or not being repeatable. This study demonstrates a condensed-phase or amorphous phase-mediated crystallization (APMC) approach for the wafer-scale synthesis of 2D materials. This method uses a room-temperature PLD process for the deposition and formation of amorphous precursors with controlled thicknesses, followed by a post-deposition crystallization process to convert the amorphous materials to crystalline structures. This approach maintains the stoichiometry of the deposited materials throughout the deposition and crystallization process and enables the large-scale synthesis of crystalline 2D materials (e.g., MoS 2 and WSe 2 ) on Si/SiO 2 substrates, which is critical for future wafer-scale electronics. We show that the thickness of the layers can be digitally controlled by the number of laser pulses during the PLD phase. Optical spectroscopy is used to monitor the crystallization dynamics of amorphous layers as a function of annealing temperature. The crystalline quality, domain sizes, and the number of layers were explored using nanoscale and atomistic characterization (e.g., AFM, STEM, and EDS) along with electrical characterization to explore process–structure–performance relationships. Finally, this growth technique is a promising method that could potentially be adopted in conventional semiconductor industries for wafer-scale manufacturing of next-generation electronic and optoelectronic devices.

2D electronics↗

DOE OSTI2022

Unexpected Changes of Aerosol Burdens With Decreased Convection in the Context of Scale-Aware Convection Schemes

Atmospheric aerosols in global climate models (GCMs) can be removed by both large-scale and convective precipitation. As the horizontal resolution of GCMs increases, it is expected that large-scale precipitation increases and convective precipitation decreases if scale-aware convection schemes are well developed. Here, to explore its impact on aerosol burdens, this study develops a novel method and applies it to the National Center for Atmospheric Research Community Atmosphere Model version 5.3 to mimic the behavior of scale-aware convective schemes. Surprisingly, it is found that aerosol burden increases globally as convective precipitation decreases and large-scale precipitation increases, which can be attributed to the reduced light rain. In the light-rain intensity category, the decreased frequency of convective precipitation is not offset by the increased frequency of large-scale precipitation. Therefore, for aerosol simulations in high-resolution GCMs using scale-aware convection schemes, subgrid convection and large-scale condensation should be coordinated to assure light rain stays the same.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Allometric Scaling of Hyporheic Respiration Across Basins in the Pacific Northwest United States

Abstract Hyporheic zones regulate biogeochemical processes in streams and rivers, but high spatiotemporal heterogeneity makes it difficult to predict how these processes scale from individual reaches to river basins. Recent work applying allometric scaling (i.e., power‐law relationships between size and function) to river networks provides a new paradigm for understanding cumulative hyporheic biogeochemical processes. We used previously published model predictions of reach‐scale hyporheic aerobic respiration to explore patterns in allometric scaling across two climatically divergent basins with differing characteristics in the Pacific Northwest, United States. In the model, hydrologic exchange fluxes (HEFs) regulate hyporheic respiration, so we examined how HEFs might influence allometric scaling of respiration. We found consistent scaling behaviors where HEFs were either very low or very high, but differences between basins when HEFs were moderate. Our findings provide initial model‐generated hypotheses for factors influencing allometric scaling of hyporheic respiration. These hypotheses can be used to optimize new data generation efforts aimed at developing predictive understanding of allometries that can, in turn, be used to scale biogeochemical dynamics across watersheds.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Empirical scaling of the L–H threshold power for metal wall tokamaks using a multi-device database

The empirical scaling for the H-mode power threshold in tokamaks has been revisited using a database with threshold data from machines with a metallic first wall as part of International Tokamak Physics Activity (ITPA) task TC-26. The database contains discharges from ASDEX Upgrade (AUG) (W), JET (Be/W) and Alcator C-Mod (Mo). This was motivated by reports that in like-for-like discharges the power threshold was reduced by approximately 30% after the change from carbon based to metallic first wall materials on AUG (Ryter et al 2013 Nucl. Fusion 53 113003) and JET (Maggi et al 2014 Nucl. Fusion 54 023007). The database contains L–H transition data for all hydrogen isotopes and mixtures, including T and DT from the recent JET campaigns. Compared to the ITPA 2008 scaling (Martin et al 2008 J. Phys.: Conf. Ser. 123 012033), the metal wall scaling has a smaller magnetic field exponent but a larger density exponent. We present an additional parameter to capture the strong dependence of the L–H power threshold (approx. factor 2) on the magnetic configuration in the divertor on JET. The scaling recovers the approximate inverse isotope mass scaling of the threshold power. Alternative scalings involving the plasma current and poloidal magnetic field are explored. Despite the reduction in threshold observed earlier, the scalings based on the metal wall database do not necessarily extrapolate to a lower threshold for ITER compared to the ITPA 2008 scaling, especially at high density. The divertor configuration effect induces the largest uncertainty in the extrapolation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Non-local contribution from small scales in galaxy–galaxy lensing: comparison of mitigation schemes

ABSTRACT Recent cosmological analyses with large-scale structure and weak lensing measurements, usually referred to as 3 × 2pt, had to discard a lot of signal to noise from small scales due to our inability to accurately model non-linearities and baryonic effects. Galaxy–galaxy lensing, or the position–shear correlation between lens and source galaxies, is one of the three two-point correlation functions that are included in such analyses, usually estimated with the mean tangential shear. However, tangential shear measurements at a given angular scale θ or physical scale R carry information from all scales below that, forcing the scale cuts applied in real data to be significantly larger than the scale at which theoretical uncertainties become problematic. Recently, there have been a few independent efforts that aim to mitigate the non-locality of the galaxy–galaxy lensing signal. Here, we perform a comparison of the different methods, including the Y-transformation, the point-mass marginalization methodology, and the annular differential surface density statistic. We do the comparison at the cosmological constraints level in a combined galaxy clustering and galaxy–galaxy lensing analysis. We find that all the estimators yield equivalent cosmological results assuming a simulated Rubin Observatory Legacy Survey of Space and Time (LSST) Year 1 like set-up and also when applied to DES Y3 data. With the LSST Y1 set-up, we find that the mitigation schemes yield ∼1.3 times more constraining S8 results than applying larger scale cuts without using any mitigation scheme.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Multi-Time Scale Coordinated Control and Scheduling of Inverter-Based TCLs With Variable Wind Generation

To address microgrid tie flow errors caused by wind generation variability, here we propose and develop a multi-time scale coordinated control and scheduling strategy for inverter-based thermostatically controlled loads (TCLs). First, in hour-time scale, inverter-based TCLs with adjusting temperature set-point are modeled as virtual generators to compensate tie flow deviations in the day-ahead plan. Next, in minute-time scale, virtual batteries representing operating behaviors of inverter-based TCLs with frequency control are scheduled determined by the control of virtual generators in hour-time scale. The virtual batteries are scheduled to smooth out tie flow errors corresponding to day-ahead plan and hour-time scale schedules. The multi-time scale control methods are coordinated to employ the response potential of inverter-based TCLs and response curve-based methods are proposed to control inverter-based TCLs considering the customer privacy. The multi-time scale stochastic schedules which are based on response curves of inverter-based TCLs are coordinated to accommodate wind generation variability. Simulation results demonstrate that the microgrid tie flow errors are effectively mitigated by the proposed multi-time scale coordinated control and scheduling of inverter-based TCLs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms

Deployment and execution of machine learning tasks on extreme-scale computing platforms face several significant technical challenges: 1) High computing cost incurred by dense networks – The computing workload of deep networks with densely-connected topology increases rapidly with the network size, imposing a non-scalable computing model of extreme-scale computing platforms; 2) Non-optimized workload distribution – Many advanced deep learning algorithms, e.g., sparsification and irregular net-work topology, produce very unbalanced workload distribution on extreme-scale computing platforms. The computation efficiency is greatly hindered by the incurred data and computation redundancies as well as long tails of the node with extensive workload; 3) Constraints in data movement and I/O bottle-neck – Inter-node data movement in extreme-scale computing platforms are associated with high energy and latency costs, and subject to the constraints of I/O bandwidth; and 4) Generalization of algorithm realization and acceleration on computing platforms – The large varieties of machine learning algorithms and structures of extreme-scale computing platforms make the derivation of a generalized algorithm realization and acceleration method very challenging, which, however, is the requirement by domain scientists and interested users. We call the above challenges Smale’s Problems in Machine Learning and Understanding for High-Performance Computing Scientific Discovery. The objective of our three-year research project is to develop a holistic innovation set at structure, assembly, and acceleration layers of machine learning algorithms to address the above challenges in algorithm deployment and execution. Three tasks are particularly performed, including: At the algorithm structure level, we investigate the techniques that can structurally sparsify on the topology of deep networks for computing workload reduction. We also study clustering and pruning techniques that can optimize the workload distributions over the extreme-scale computing platforms; At the algorithm assembly level, we derive a unified learning framework for unsupervised transfer learning and dynamic growing capabilities. Novel training methods are also exploited to enhance the training efficiency of the proposed framework; At the algorithm acceleration level, we will develop a series of techniques that can accelerate the computation of sparse matrix operations, which are one of the core executions in deep learning and optimize memory access of the concerned platforms. Our proposed techniques attack the fundamental problems in machine learning algorithms running on extreme-scale computing platforms by vertically integrating the solutions at three closely entangled layers, paving the long-term scaling path of machine learning applications under DOE context. Three tasks corresponding to the above respective research orientations are performed during the three-year project period with our collaborators at ORNL. The outcome of the proposed project is anticipated to form a holistic solution set of novel algorithms and network topologies, efficient training techniques, and fast acceleration methods to promote the computing scalability of the machine learning applications of particular interest to DOE.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Calcium Sulfate and Calcium Carbonate Scaling of Thin-Film Composite Polyamide Reverse Osmosis Membranes with Surface-Tethered Polyacrylic Acid Chains

The gypsum and calcite scaling propensities of the thin-film composite polyamide (PA-TFC) reverse osmosis (RO) membrane, modified with a tethered surface layer of polyacrylic acid (PAA) chains, was evaluated and compared to the scaling of selected commercial RO membranes. The tethered PAA layer was synthesized onto a commercial polyamide membrane (i.e., base-PA) via atmospheric pressure plasma-induced graft polymerization (APPIGP). The PAA nano-structured (SNS) base-PA membrane (SNS-PAA-PA) was scaled to a lesser degree, as quantified by a lower permeate flux decline and surface imaging, relative to the tested commercial membranes (Dow SW30, Toray SWRO, and BWRO). The cleaning of gypsum-scaled membranes with D.I. water flushing achieved 100% water permeability recovery for both the SNS-PAA-PA and Dow SW30 membranes, relative to 92–98% permeability restoration for the Toray membranes. The calcium carbonate scaling of SNS-PAA-PA membranes was also lower relative to the commercial membranes, but permeability recovery after D.I. water cleaning was somewhat lower (94%) but consistent with the level of surface scale coverage. In contrast, the calcite and gypsum-scaled membrane areas of the commercial membranes post-cleaning were significantly higher than for the SNS-PAA-PA membrane but with 100% permeability recovery, suggesting the potential for membrane damage when mineral scaling is severe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗