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At least 1,027 records · Page 57

WE-AB-204-08: Uncertainties in Kinetic Modeling of Shortened Dynamic 18F-FMISO PET Due to Image Noise

Purpose: To assess uncertainties in voxel-wise kinetic modeling (KM) of dynamic 18F-FMISO PET (dPET) due to image noise for different lengths of dPET acquisitions. Methods: 12 tumor time activity curves (TACs) deduced from 6 head and neck cancer patient dPET datasets (45min dPET + 10min frames at ∼95min and ∼160min respectively) were modeled using an irreversible two-tissue compartment model to estimate kinetic rate constants (KRCs) k3, vB, K1, and K1/k2 (reference standard). For each modeled TAC, 1000 noisy TACs were simulated by adding Gaussian noise with standard deviation equivalent to that observed on a voxel level in GE DSTE PET-CT. KM was conducted for each set of noisy TACs using (i) full dataset (170min), and repeated using (ii) 105min and (iii) 45min shortened subsets, with an input function that was image-derived from the dPET dataset of matching length. Absolute value of percent difference between KRCs from noisy TACs as estimated from either of 3 datasets and reference standard KRCs was used to represent bias. Results: For all KRCs, bias was higher for shortened datasets. For k3, bias was lower when actual k3 was higher: from 7%±5% (170min), 9%±7% (105min), and 14%±11% (45min) (actual k3=0.0098), to 32%±25% (170min), 45%±34% (95min), and 79%±48% (45min) (actual k3=0.0008). Similar relationship was observed for vB, with bias being between ∼7% (actual vB=0.28) and ∼26–34% (actual vB=0.08). For K1 [K1/k2], bias was ∼6–10% [∼2–3%] (dependence on actual value of K1 [K1/k2] was not observed). Conclusion: Uncertainties in voxel-wise KM of shortened 18F-FMISO dPET due to image noisy only are larger for shorter acquisitions and, for k3 [vB], the bias was found to be inversely correlated with the actual values of k3 [vB]. Using 45min subset, k3, vB, K1, and K1/k2 could be estimated to within ∼15–80%, ∼10–35%, ∼10%, and ∼3%, respectively.

60 APPLIED LIFE SCIENCES↗

Dislocation model of nucleation and development of slip bands and their effect on service life of structural materials subject to cyclic loading

Most of the destructions of machine parts are of fatigue character. Under cyclic loading, the surface layer, in which hardening–softening processes rapidly occur, is formed almost at once after its beginning. The interaction of plastic-deformation traces with each other and with other structural elements, such as grains, results in the formation of a characteristic microstructure of the machine-part surface subject to cyclic loadings. The character of accumulation of slip bands and their shape (narrow, wide, twisting, and broken) depends on the conditions under which (under what factors) the cyclic loading occurs. The fatigue-resistance index expressed in terms of the slope of left portion of the fatigue curve linearized in logarithmic coordinates also depends on the set of relevant factors. The dependence of the surface damageability on the fatigue resistance index makes it possible to implement the method of predicting the fatigue curve by the description of the factors acting on a detail or construction. The position of the inflection point on the curve in the highcycle fatigue region (the endurance limit and the number of loading cycles, the ordinate and abscissa of the inflection point on the fatigue curve, respectively) also depends on the set of relevant factors. In combination with the previously obtained value of the slope of the left portion of the curve in the high-cycle fatigue region, this makes it possible to construct an a priori fatigue curve, thus reducing the scope of required fatigue tests and, hence, high expenses because of their long duration and high cost. The scope of tests upon using the developed method of prediction may be reduced to a minimum of one or two samples at the predicted level of the endurance limit.

36 MATERIALS SCIENCE↗

Multi-Split Variable Refrigerant Flow (VRF) System Building Energy Simulations Using Performance Maps

Multi-split variable refrigerant flow (VRF) systems are highly energy-efficient HVAC (heating, ventilation and air conditioning) technologies that connect a single outdoor unit to multiple independent indoor terminal units using a common refrigerant circuit and a variable-speed compressor. Building energy simulations that incorporate VRF systems help model their unique operational characteristics and predict energy consumption in specific building designs. Traditionally, EnergyPlus models these systems by employing multiple sets of performance curves to characterize both individual terminal units and the outdoor unit. However, producing these curves is labor intensive and error prone, and they often do not capture all the key input and output variables. This paper introduces a novel approach that uses multi-dimensional performance maps to model VRF systems in building environments for space cooling. In this approach, performance maps are developed at the component level—separately for the outdoor unit and for each indoor terminal. The new modeling method is validated within EnergyPlus via a Python plug-in that contains a simple solver loop to coordinate the component-level, indoor, and outdoor unit maps. Furthermore, because performance maps can span more variables than traditional performance curves, they offer the opportunity to implement advanced controls, such as enhanced dehumidification and compressor modulation. A VRF air conditioner’s hardware system was modeled using the DOE/ORNL Heat Pump Design Model, which was automated to produce extensive performance maps for both the indoor and outdoor units.

Shen, Bo [ORNL] (ORCID:0000000336600393)↗

Materials informatics: From the atomic-level to the continuum

We report that in recent years materials informatics, which is the application of data science to problems in materials science and engineering, has emerged as a powerful tool for materials discovery and design. This relatively new field is already having a significant impact on the interpretation of data for a variety of materials systems, including those used in thermoelectrics, ferroelectrics, battery anodes and cathodes, hydrogen storage materials, polymer dielectrics, etc. Its practitioners employ the methods of multivariate statistics and machine learning in conjunction with standard computational tools (e.g., density-functional theory) to, for example, visualize and dimensionally reduce large data sets, identify patterns in hyperspectral data, parse microstructural images of polycrystals, characterize vortex structures in ferroelectrics, design batteries and, in general, establish correlations to extract important physics and infer structure-property-processing relationships. In this Overview, we critically examine the role of informatics in several important materials subfields, highlighting significant contributions to date and identifying known shortcomings. We specifically focus attention on the difference between the correlative approach of classical data science and the causative approach of physical sciences. From this perspective, we also outline some potential opportunities and challenges for informatics in the materials realm in this era of big data.

36 MATERIALS SCIENCE↗

Hybrid gausslet/Gaussian basis sets

We introduce hybrid gausslet/Gaussian basis sets, where a standard Gaussian basis is added to a gausslet basis in order to increase accuracy near the nuclei while keeping the spacing of the grid of gausslets relatively large. The Gaussians are orthogonalized to the gausslets, which are already orthonormal, and approximations are introduced to maintain the diagonal property of the two electron part of the Hamiltonian so that it continues to scale as the second power of the number of basis functions rather than the fourth. We introduce several corrections to the Hamiltonian designed to enforce certain exact properties, such as the values of certain two-electron integrals. We also introduce a simple universal energy correction that compensates for the incompleteness of the basis stemming from the electron–electron cusps based on the measured double occupancy of each basis function. We perform a number of Hartree Fock and full configuration interaction (full-CI) test calculations on two electron systems and Hartree Fock on a ten-atom hydrogen chain to benchmark these techniques. The inclusion of the cusp correction allows us to obtain complete basis set full-CI results for the two electron cases at the level of several micro-Hartrees, and we see similar apparent accuracy for Hartree Fock on the ten-atom hydrogen chain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics.

The standard model of cosmology has provided a good phenomenological description of a wide range of observations both at astrophysical and cosmological scales for several decades. This concordance model is constructed by a universal cosmological constant and supported by a matter sector described by the standard model of particle physics and a cold dark matter contribution, as well as very early-time inflationary physics, and underpinned by gravitation through general relativity. There have always been open questions about the soundness of the foundations of the standard model. However, recent years have shown that there may also be questions from the observational sector with the emergence of differences between certain cosmological probes. In this White Paper, we identify the key objectives that need to be addressed over the coming decade together with the core science projects that aim to meet these challenges. These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model. After reviewing the principal probes used in the measurement of cosmological parameters, as well as potential systematics, we discuss the most promising array of potential new physics that may be observable in upcoming surveys. We also discuss the growing set of novel data analysis approaches that go beyond traditional methods to test physical models. These new methods will become increasingly important in the coming years as the volume of survey data continues to increase, and as the degeneracy between predictions of different physical models grows. There are several perspectives on the divergences between the values of cosmological parameters, such as the model-independent probes in the late Universe and model-dependent measurements in the early Universe, which we cover at length. The White Paper closes with a number of recommendations for the community to focus on for the upcoming decade of observational cosmology, statistical data analysis, and fundamental physics developments.

Dienes, Keith [Univ. of Arizona, Tucson, AZ (Unite↗

Fast ion generation and bulk plasma heating with three-ion ICRF scenarios

Launching electromagnetic waves in the ion cyclotron range of frequencies (ICRF) is an efficient method of plasma heating, actively employed in most of fusion machines. ICRF has a number of important supplementary applications, including the generation of high-energy ions. In this paper, we discuss a new set of three-ion ICRF scenarios and the prospect of their use as a dedicated tool for fast ion generation in tokamaks and stellarators. A distinct feature of these scenarios is a strong absorption efficiency possible at very low concentrations of resonant minority ions (∼ 1% or even below). Such concentration levels are typical for impurities contaminating fusion plasmas. An alternative ICRF scenario for maximizing the efficiency of bulk D-T ion heating is suggested for JET and ITER tokamaks, which is based on three-ion ICRF heating of intrinsic Beryllium impurities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Towards Resiliency Evaluation of Vector Programs

The systems resilience research community has developed methods to manually insert additional source-program level assertions to trap errors, and also devised tools to conduct fault injection studies for scalar program codes. In this work, we contribute the first vector oriented LLVM-level fault injector VULFI to help study the effects of faults in vector architectures that are of growing importance, especially for vectorizing loops. Using VULFI, we conduct a resiliency study of nine real-world vector benchmarks using Intel’s AVX and SSE extensions as the target vector instruction sets, and offer the first reported understanding of how faults affect vector instruction sets. We take this work further toward automating the insertion of resilience assertions during compilation. This is based on our observation that during intermediate (e.g., LLVM-level) code generation to handle full and partial vectorization, modern compilers exploit (and explicate in their code-documentation) critical invariants. These invariants are turned into error-checking code. We confirm the efficacy of these automatically inserted low-overhead error detectors for vectorized for-loops.

fault injection↗

A Comprehensive Set of Impact Data for Common Aerospace Metals

Our results for the two sets of impact experiments are reported here. In order to assist with model development using the impact data reported, the materials are mechanically characterized using a series of standard experiments. The first set of impact data comes from a series of coefficient of restitution experiments, in which a 2 meter long pendulum is used to study "in context" measurements of the coefficient of restitution for eight different materials (6061-T6 Aluminum, Phosphor Bronze alloy 510, Hiperco, Nitronic 60A, Stainless Steel 304, Titanium, Copper, and Annealed Copper). The coefficient of restitution is measured via two different techniques: digital image correlation and laser Doppler vibrometry. Due to the strong agreement of the two different methods, only results from the digital image correlation are reported. The coefficient of restitution experiments are "in context" as the scales of the geometry and impact velocities are representative of common features in the motivating application for this research. Finally, a series of compliance measurements are detailed for the same set of materials. Furthermore, the compliance measurements are conducted using both nano-indentation and micro-indentation machines, providing sub-nm displacement resolution and uN force resolution. Good agreement is seen for load levels spanned by both machines. As the transition from elastic to plastic behavior occurs at contact displacements on the order of 30 nm, this data set provides a unique insight into the transitionary region.

36 MATERIALS SCIENCE↗

Enrichable consortia of microbial symbionts degrade macroalgal polysaccharides in Kyphosus fish

ABSTRACT Coastal herbivorous fishes consume macroalgae, which is then degraded by microbes along their digestive tract. However, there is scarce genomic information about the microbiota that perform this degradation. This study explores the potential of Kyphosus gastrointestinal microbial symbionts to collaboratively degrade and ferment polysaccharides from red, green, and brown macroalgae through in silico study of carbohydrate-active enzyme and sulfatase sequences. Recovery of metagenome-assembled genomes (MAGs) from previously described Kyphosus gut metagenomes and newly sequenced bioreactor enrichments reveals differences in enzymatic capabilities between the major microbial taxa in Kyphosus guts. The most versatile of the recovered MAGs were from the Bacteroidota phylum, whose MAGs house enzyme collections able to decompose a variety of algal polysaccharides. Unique enzymes and predicted degradative capacities of genomes from the Bacillota (genus Vallitalea ) and Verrucomicrobiota (order Kiritimatiellales ) highlight the importance of metabolic contributions from multiple phyla to broaden polysaccharide degradation capabilities. Few genomes contain the required enzymes to fully degrade any complex sulfated algal polysaccharide alone. The distribution of suitable enzymes between MAGs originating from different taxa, along with the widespread detection of signal peptides in candidate enzymes, is consistent with cooperative extracellular degradation of these carbohydrates. This study leverages genomic evidence to reveal an untapped diversity at the enzyme and strain level among Kyphosus symbionts and their contributions to macroalgae decomposition. Bioreactor enrichments provide a genomic foundation for degradative and fermentative processes central to translating the knowledge gained from this system to the aquaculture and bioenergy sectors. IMPORTANCE Seaweed has long been considered a promising source of sustainable biomass for bioenergy and aquaculture feed, but scalable industrial methods for decomposing terrestrial compounds can struggle to break down seaweed polysaccharides efficiently due to their unique sulfated structures. Fish of the genus Kyphosus feed on seaweed by leveraging gastrointestinal bacteria to degrade algal polysaccharides into simple sugars. This study reconstructs metagenome-assembled genomes for these gastrointestinal bacteria to enhance our understanding of herbivorous fish digestion and fermentation of algal sugars. Investigations at the gene level identify Kyphosus guts as an untapped source of seaweed-degrading enzymes ripe for further characterization. These discoveries set the stage for future work incorporating marine enzymes and microbial communities in the industrial degradation of algal polysaccharides.

59 BASIC BIOLOGICAL SCIENCES↗

Non-residential Electricity Prices: A Review of Data Sources and Estimation Methods

This paper presents a review of electricity price data sources and estimation methods for non-residential consumers, including a detailed empirical study of tariff-based prices collected as part of Lawrence Berkeley Lab's Tariff Analysis Project (TAP). We compare the TAP data to two other data sources: utility-level annual sales, revenues and consumer counts published by the Energy Information Administration (EIA), and the Typical Bills reports published by the Edison Electric Institute. A brief overview of the types of rate structures included in the TAP database illustrates the often complex relationship between the consumer's energy use and the costs they see on their electricity bills. We provide mathematical definitions of the different types of electricity price that are useful in cost-benefit analysis, construct estimation methods appropriate to each data set, compare the results, and evaluate the relative strengths and weaknesses of each approach. We also examine how price variation is driven by differences in season, region, industry business model, and variables characterizing consumer energy use. Tables of regional price estimates for each data source, based on 2015 data, are included in the Appendix to this paper.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Status Report: Design and Fabricate Installation-Ready Test Capsule for the In-Situ Measurement of Elastic Properties Using an Optical Fiber-Based Measurement Technique

Microstructure evolution due to irradiation in a nuclear reactor can have a dramatic effect on material properties. A better understanding of this evolution is necessary for developing improved nuclear fuels and materials. The ability to measure such changes in real time is extremely limited due to the harsh conditions, high radiation fields, and limited access of the reactor environment. Through carefully designed experiments, measurement of elastic properties can be tied directly to microstructure. We present the methodology, design, and deployment plan for an instrument that has been developed to monitor grain microstructural changes during irradiation. Our measurement approach involves exciting and measuring the resonant frequency of a thin cantilever beam. Excitation and detection of the flexural vibrations of the beam are accomplished using optical methods that require only an optical fiber connection between the instrumentation and the sample. This technique has been demonstrated in a laboratory setting to monitor the recrystallization of highly textured copper during high temperature annealing. A test capsule incorporating this technique has been developed for in reactor testing. The capsule has been designed to be compatible with a reusable test module that allows simplified insertion in the TREAT reactor at INL. An exact replica of the instrument described in this Status Report, constructed from Quality Level 3 materials, is slated to be inserted into the TREAT reactor in FY19.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SU-D-202-02: Quantitative Imaging: Correlation Between Image Feature Analysis and the Accuracy of Manually Drawn Contours On PET Images

Purpose: To evaluate the correlation between image features and the accuracy of manually drawn target contours on synthetic PET images Methods: A digital PET phantom was used in combination with Monte Carlo simulation to create a set of 26 simulated PET images featuring a variety of tumor shapes and activity heterogeneity. These tumor volumes were used as a gold standard in comparisons with manual contours delineated by 10 radiation oncologist on the simulated PET images. Metrics used to evaluate segmentation accuracy included the dice coefficient, false positive dice, false negative dice, symmetric mean absolute surface distance, and absolute volumetric difference. Image features extracted from the simulated tumors consisted of volume, shape complexity, mean curvature, and intensity contrast along with five texture features derived from the gray-level neighborhood difference matrices including contrast, coarseness, busyness, strength, and complexity. Correlation between these features and contouring accuracy were examined. Results: Contour accuracy was reasonably well correlated with a variety of image features. Dice coefficient ranged from 0.7 to 0.90 and was correlated closely with contrast (r=0.43, p=0.02) and complexity (r=0.5, p<0.001). False negative dice ranged from 0.10 to 0.50 and was correlated closely with contrast (r=0.68, p<0.001) and complexity (r=0.66, p<0.001). Absolute volumetric difference ranged from 0.0002 to 0.67 and was correlated closely with coarseness (r=0.46, p=0.02) and complexity (r=0.49, p=0.008). Symmetric mean absolute difference ranged from 0.02 to 1 and was correlated closely with mean curvature (r=0.57, p=0.02) and contrast (r=0.6, p=0.001). Conclusion: The long term goal of this study is to assess whether contouring variability can be reduced by providing feedback to the practitioner based on image feature analysis. The results are encouraging and will be used to develop a statistical model which will enable a prediction of contour accuracy based purely on image feature analysis.

60 APPLIED LIFE SCIENCES↗

Current Efforts in Immobilized Low-Activity Waste Glass Testing to Support the Hanford Site Integrated Disposal Facility - 17119

Cleanup plans for Hanford site high-level radioactive mixed tank waste calls for separating the waste into high-level waste (HLW) and low-activity waste (LAW) fractions. The fractions will be vitrified separately at the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The HLW glass will be sent to an offsite geological disposal facility while the immobilized low-activity waste (ILAW) glass will be disposed at the onsite Integrated Disposal Facility (IDF). In order to inform models used to predict the performance of ILAW glass at IDF, it is necessary to understand the corrosion behavior of the glass. In this paper, we discuss tests that account for the effects of 1) solution chemistry, 2) the ion exchange reaction, and 3) secondary phase formation on the glass dissolution rate. To quantify the effects of solution chemistry, specifically changes in pH, T, and Si concentration, the single-pass flow-through (SPFT) test method is applied. A designed set of these tests results in a set of kinetic rate law parameters that are used in a glass dissolution rate law based on transition-state theory. Furthermore, for SPFT tests with relatively high concentrations of Si, an ion exchange rate is provided. Additionally, through tests such as the pressurized unsaturated flow (PUF) test method, a suite of secondary phases can be compiled. The collection of kinetic rate law parameters, the ion exchange term, and the suite of secondary phases are provided to IDF performance assessment (PA) modelers. Lastly, we present a description of the efforts made to verify and validate the use of these parameters and secondary phases through the use of a field lysimeter present at the Hanford site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Weak Lensing by Galaxy Clusters: from Pixels to Cosmology

The story of the origin and evolution of our Universe is told, equivalently, by space-time itself and by the structures that grow inside of it. Clusters of galaxies are the frontier of bottom-up structure formation. They are the most massive objects to have collapsed at the present epoch. By that virtue, their abundance and structural parameters are highly sensitive to the composition and evolution of the Universe. The most common probe of cluster cosmology, abundance, uses samples of clusters selected by some observable. Applying a mass-observable relation (MOR), cosmological parameters can be constrained by comparing the sample to predicted cluster abundances as a function of observable and redshift. Arguably, however, cluster probes have not yet entered the era of per cent level precision cosmology. The primary reason for this is our imperfect understanding of the MORs. The overall normalization, the slope of mass vs. observable, the redshift evolution, and the degree and correlation of intrinsic scatters of observables at fixed mass have to be constrained for interpreting abundances correctly. Mass measurement of clusters by means of the differential deflection of light from background sources in their gravitational field, i.e. weak lensing, is a powerful approach for achieving this. This thesis presents new methods for and scientific results of weak lensing measurements of clusters of galaxies. The former include, on the data reduction side, (i) the correction of CCD images for non-linear effects due to the electric fields of accumulated charges and (ii) a method for masking artifact features in sets of overlapping images of the sky by comparison to the median image. Also, (iii) I develop a method for the selection of background galaxy samples based on their color and apparent magnitude that includes a new correction for contamination with cluster member galaxies. The main scientific results are the following. (i) For the Hubble Frontier Field cluster RXC J2248.7--4431 our lensing analysis constrains mass and concentration of the cluster halo and we confirm the large mass predicted by X-ray and Sunyaev-Zel’dovich (SZ) observations. The study of cluster members shows the relation of galaxy morphology to luminosity and environment. (ii) Our lensing mass measurements for 12 clusters are consistent with X-ray masses derived under the assumption of hydrostatic equilibrium of the intra-cluster gas. We confirm the MORs derived by the South Pole Telescope collaboration for the detection significance of the cluster SZ signal in their survey. We find discrepancies, however, with the Planck SZ MOR. We hypothesize that these are related either to a shallower slope of the MOR or a size-, redshift- or noise-dependent bias in SZ signal extraction. (iii) Finally, using a combination of simulations and theoretical models for the variation of cluster profiles at fixed mass, we find that the latter is a significant contribution to the uncertainty of cluster lensing mass measurements. A cosmic variance model, such as the one we develop, is necessary for MOR constraints to be accurate at the level required for future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks

Abstract Streamflow forecasting over gauged and ungauged basins play a vital role in water resources planning, especially under the changing climate. Increased availability of large sample hydrology data sets, together with recent advances in deep learning techniques, has presented new opportunities to explore temporal and spatial patterns in hydrological signatures for improving streamflow forecasting. The purpose of this study is to adapt and benchmark several state‐of‐the‐art graph neural network (GNN) architectures, including ChebNet, Graph Convolutional Network (GCN), and GraphWaveNet, for end‐to‐end graph learning. We explicitly represent river basins as nodes in a graph, learn the spatiotemporal nodal dependencies, and then use the learned relations to predict streamflow simultaneously across all nodes in the graph. The efficacy of the developed GNN models is investigated using the Catchment Attributes and MEteorology for Large‐sample Studies (CAMELS) data set under two settings, fixed graph topology (transductive learning), and variable graph topology (inductive learning), with the latter applicable to prediction in ungauged basins (PUB). Results indicate that GNNs are generally robust and computationally efficient, achieving similar or better performance than a baseline model trained using the long short‐term memory (LSTM) network. Further analyses are conducted to interpret the graph learning process at the edge and node levels and to investigate the effect of different model configurations. We conclude that graph learning constitutes a viable machine learning‐based method for aggregating spatiotemporal information from a multitude of sources for streamflow forecasting

Sun, Alexander Y.↗

Analytical Large-Signal Modeling of Inverter-Based Microgrids With Koopman Operator Theory for Autonomous Control

The microgrid (MG) plays a crucial role in the energy transition, but its nonlinearity presents a significant challenge for large-signal power systems studies in the electromagnetic transient (EMT) time scale. In this paper, we develop a large-signal linear MG model that considers the detailed dynamics of the primary and zero-control levels based on the Koopman operator (KO) theory. Firstly, a set of observable functions is carefully designed to capture the nonlinear dynamics of the MG. The corresponding linear KO is then analytically derived based on these observables, resulting in the linear representation of the original nonlinear MG with observables as the new coordinate. The influence of external input on the system dynamics is also considered during the derivation, enabling control of the MG. We solve the voltage control problem using the traditional linear quadratic integrator (LQI) method to demonstrate that textbook linear control techniques can accurately control the original nonlinear MG via the developed KO-linearized MG model. Our proposed KO linearization method is generic and can be easily extended for different control objectives and MG structures using our analytical derivation procedure. Here, we validate the effectiveness of our methodology through various case studies.

25 ENERGY STORAGE↗

Near-surface Density Currents Observed in the Southeast Pacific Stratocumulus-topped Marine Boundary Layer

Density currents (i.e. cold pools or outflows) beneath marine stratocumulus clouds are characterized using a 30-d data set of ship-based observations obtained during the 2008 Variability of American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) in the southeast Pacific. An objective method identifies 71 density current fronts using an air density criterion and isolates each density current’s core (peak density) and tail (dissipating) zone. Compared to front and core zones, most density current tails exhibited weaker density gradients and wind anomalies elongated about the axis of the mean wind. The mean cloud-level advection relative to the surface layer wind (1.9 m s-1) nearly matches the mean density current propagation speed (1.8 m s-1). The similarity in speeds allows drizzle cells to deposit tails in their wakes. Based on high-resolution scanning Doppler lidar data, prefrontal updrafts had a mean intensity of 0.91 m s-1, reached an average altitude of 800 m, and were often surmounted by low-lying shelf clouds not connected to the overlying stratocumulus cloud. Nearly 90% of density currents were identified when C-band radar estimated 30-km diameter areal average rain rates exceeded 1 mm d-1. Rather than peaking when rain rates are highest overnight, density current occurrence peaks between 0600 and 0800 local solar time when enhanced local drizzle co-occurs with shallow subcloud dry and stable layers. The dry layers may contribute to density current formation by enhancing subcloud evaporation of drizzle. Density currents preferentially occur in regions of open cells but also occur in regions of closed cells.

density currents↗