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This viewgraph presentation reviews the motivation for the study, the numerical method used, the numerical simulations of the vaneless diffuser and vaned diffuser. It also reviews the conclusions from the study
Drought can cause immense agricultural and ecological damage resulting in high mitigation and compensation costs. Climate variability in future decades is expected to cause severe drought conditions and threaten necessary water resources. Stakeholders seek to implement effective drought assessments in preparation for potential economic and environmental damage invoked by drought. Although in-situ measurements are accurate, the current infrastructure is spatially limited and costly to maintain. A framework was created to compare modeled, satellite and in-situ data in drought monitoring. Here we show that the comparison of in-situ and remotely sensed soil moisture (SM) measurements can increase the spatiotemporal range of SM assessments. Data collected between 2003 and 2021 by NASA’s SPoRT Land Information System (SPoRT-LIS) and Soil Moisture Active Passive (SMAP) mission were standardized and compared with in-situ data provided through the Illinois Climate Network (WARM). Statistical analysis results including the Pearson correlation coefficient (r), root mean squared error, mean absolute error and others were calculated to compare the WARM measurements to the SMAP and SPoRT-LIS products. Results indicate that both satellite products demonstrate seasonally variable bias that is not present in the in-situ measurements. Bias was highest in the winter months and lowest in the late summer and early fall months in both satellite datasets. Overall, WARM-SPoRT comparisons resulted in lower seasonal variability. However, on average, the SMAP comparison demonstrated higher correlation values and lower error values. The WARM-SMAP average correlation (r) was 0.61 compared to the WARM-SPoRT average correlation (r) value of 0.54. Average mean absolute error values calculated for the SMAP and SPoRT comparisons were 0.07 and 0.08 percent soil moisture by volume, respectively. These analyses suggest integrating in-situ measurements and those provided by NASA Earth observations can be utilized in a multi-faceted SM evaluation, a valuable contribution to drought monitoring and water resource decision making.
Here, we study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs). The algorithm decomposes the time domain into a set of overlapping subdomains, and solves all subproblems defined over subdomains in parallel. The convergence is attained by updating primal-dual information at the boundaries of overlapping subdomains. We show that the algorithm exhibits local linear convergence, and that the convergence rate improves exponentially with the overlap size. We also establish global convergence results for a general quadratic programming, which enables the application of the Schwarz scheme inside second-order optimization algorithms (e.g., sequential quadratic programming). The theoretical foundation of our convergence analysis is a sensitivity result of nonlinear OCPs, which we call "exponential decay of sensitivity" (EDS). Intuitively, EDS states that the impact of perturbations at domain boundaries (i.e., initial and terminal time) on the solution decays exponentially as one moves into the domain. Here, we expand a previous analysis available in the literature by showing that EDS holds for both primal and dual solutions of nonlinear OCPs, under uniform second-order sufficient condition, controllability condition, and boundedness condition. We conduct experiments with a quadrotor motion planning problem and a partial differential equations (PDE) control problem to validate our theory, and show that the approach is significantly more efficient than alternating direction method of multipliers and as efficient as the centralized interior-point solver.
Humans experience widespread exposure to anthropogenic per- and polyfluoroalkyl substances (PFAS) through various media, which can lead to a wide range of negative health impacts. Tap water is an important source of exposure in communities with any degree of contamination but routine or large-scale PFAS monitoring often depends on targeted analytical methods limited to measuring specific PFAS. We analyzed 680 tap water samples from the American Healthy Homes Survey II for PFAS using non-targeted analysis (NTA) to expand the range of detectable PFAS. Based on detection frequency and relative abundance, about half of the identified PFAS were found only by NTA. We identified (with varying degrees of confidence) 75 distinct PFAS, including 57 exclusively detected by NTA. The identified PFAS are members of seven structural subclasses differentiated by their head groups and degree of fluorination. Clustering analysis categorized the PFAS into four coabundance groups dominated by specific PFAS subclasses. One group uniquely identified by NTA contains zwitterionic PFAS and other PFAS transformation products which are likely associated with aqueous firefighting foam contaminants in a small number of spatially correlated samples. These results help further characterize the scope of exposure to emerging PFAS experienced by the U.S. population via tap water and augment nationwide targeted-PFAS monitoring programs.
Purpose: Y-90 Selective Internal Radiation Therapy (SIRT) is used to treat liver tumors, and by nature has variability in the percent of the intended dose that is actually delivered. To determine the quality of the administration, pre and post activity measurements are taken, and used to infer percent delivered. Vendor specifications indicate the use of an ion chamber to take these measurements. In our work, we investigated the accuracy of ion chambers, and compared them to other detector systems. Methods: We have built phantoms, phantom holders, and protocols, which allow us to measure our Y90 doses with varying apparatuses: a dose calibrator, a Geiger-counter, an ion chamber, a crystal based thyroid probe, and a gamma camera. We have set up a system that has enabled us to gather data by measuring clinical Y90 doses as they are used in the clinic using all of the instrumental methods. Five initial doses (25 measurements/acquisitions) have been taken at the time of this abstract submission. Results: Our initial results show that measurements acquired using scintillation based detectors (thyroid probe and gamma camera) correlate better with the gold standard (i.e. the dose calibrator). Pearson correlations between the dose calibrator measurements and the GM counter, Ion chamber, thyroid probe, and gamma camera were found to be 0.88, 0.83, 0.98, 0.99, respectively. More acquisitions and analysis are planned to determine the precision of the systems, as well as optimal energy window settings. Conclusion: It is likely that current standard practice can be improved using scintillation crystal based detectors. Such systems are more sensitive, can integrate signal, and can use energy discrimination. Furthermore, phantoms can be built to integrate with probe and gamma camera systems that are robust and provide reproducibility. Future work will include expanded acquisition and analysis.
The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.
We present abundances of globular clusters (GCs) in the Milky Way and Fornax from integrated-light (IL) spectra. Our goal is to evaluate the consistency of the IL analysis relative to standard abundance analysis for individual stars in those same clusters. This sample includes an updated analysis of seven clusters from our previous publications and results for five new clusters that expand the metallicity range over which our technique has been tested. We find that the [Fe/H] measured from IL spectra agrees to ∼0.1 dex for GCs with metallicities as high as [Fe/H] = −0.3, but the abundances measured for more metal-rich clusters may be underestimated. In addition we systematically evaluate the accuracy of abundance ratios, [X/Fe], for Na i, Mg i, Al i, Si i, Ca i, Ti i, Ti ii, Sc ii, V i, Cr i, Mn i, Co i, Ni i, Cu i, Y ii, Zr i, Ba ii, La ii, Nd ii, and Eu ii. The elements for which the IL analysis gives results that are most similar to analysis of individual stellar spectra are Fe i, Ca i, Si i, Ni i, and Ba ii. The elements that show the greatest differences include Mg i and Zr i. Some elements show good agreement only over a limited range in metallicity. More stellar abundance data in these clusters would enable more complete evaluation of the IL results for other important elements.
The methods used to analyze the aerothermodynamic data gathered from the Shuttle protoflights are reviewed. Trajectory and atmospheric reconstruction allow an accurate definition of the freestream environment through which the Shuttle has flown. The reconstructions, combined with aerodynamic coefficient and convective heating rate determinations, provide predictive capability for comparison with future flights. Data are acquired by operational instrumentation (12,000 parameters), development flight instrumentation (4500 measurements), and Orbiter experiments instrumentation; tracking and meteorological data are also included in the analyses. The aerothermodynamic and aerodynamic technology base for large, winged, lifting body entry vehicles is being expanded by the analysis efforts. Sensor locations on the Shuttle and data management techniques are described.
As integral components of any power plant, transformers supply the generated electricity to the grid. However, a transformer’s cellulose-based paper insulation and the mineral oil in which it is immersed break down over time under standard operating conditions—or more rapidly due to potential faults within the system. As the transformer’s mineral oil breaks down, gases are released that can be measured and monitored. This technical brief exhibits a collection of diagnostic and prognostic techniques that utilities can adopt in lieu of labor-intensive periodic preventive maintenance routines. Furthermore, prognostic models have been incorporated using the latest version of the Institute of Electrical and Electronics Engineers (IEEE) standard (IEEE, 2019) for dissolved gas analysis (DGA), thus expanding it to include estimation of the time to maintenance. Overall, four different methodologies are explained, each of which aids in determining a transformer’s state of health. These methodologies include the Chendong model, the IEEE thermal life consumption model (IEEE, 2012), a diagnostic model for DGA, and a prognostic model for DGA that uses an autoregressive integrated moving average (ARIMA) model. An additional improvement for estimating missing system parameters by using monitoring data (i.e., a tool for parameter estimation utilizing Powell’s method) is presented, enabling the IEEE thermal life consumption model to benefit not only the collaborating power plant, but also the power industry at large.
We found that the human gastrointestinal (GI) tract is a complex, dynamic ecosystem that consists of a carefully tuned balance of human host and microbiota membership. The microbiome component is not insignificant, but rather provides important functions that are absolutely critical to many aspects of human health, including nutrient transformation and absorption, drug metabolism, pathogen defense, and immune system development. Microbial community proteomics (sometimes referred to as metaproteomics) provides a powerful approach to measure the range and details of human gut microbiota functions and metabolic activities, revealing information about microbiome development and stability especially with regard to human health vs. disease states. In most cases, both microbial and human proteins are extracted from fecal samples and then measured by the high performance MS-based proteomics technology. We review the field of human gut microbiome community proteomics, with a focus on the experimental and informatics considerations involved in characterizing systems that range from low complexity defined model gut microbiota in gnotobiotic mice, to the simple gut microbiota in the GI tract of newborn infants, and finally to the complex gut microbiota in adults. Moreover, the current state-of-the-art in experimental and bioinformatics capabilities for community proteomics enable a detailed measurement of the gut microbiota, yielding valuable insights into the broad functional profiles of even complex microbiota. Future developments are likely to expand into improved analysis throughput and coverage depth, as well as post-translational modification characterizations.
There has been an increasing interest in exploring quantities associated with quantum information at colliders. We perform a detailed analysis describing how to measure the quantum discord in the top anti-top quantum state at the Large Hadron Collider (LHC). While for pure states, quantum discord, entanglement, and Bell nonlocality all probe the same correlations, for mixed states they probe different aspects of quantum correlations. The quantum discord, in particular, is interesting because it aims to encapsulate all correlations between systems that cannot have a classical origin. We employ two complementary approaches for the study of the top anti-top system, namely the decay method and the kinematic method. We highlight subtleties associated with measuring discord for reconstructed quantum states at colliders. Usually quantum discord is difficult to compute due to an extremization that must be performed. We show, however, that for the $t\bar{t}$ system this extremization can be performed analytically and we provide closed-form formulas for the quantum discord. We demonstrate that with current LHC datasets, quantum discord can be observed at 3.6 – 5.7σ, depending on the signal region, with the decay method and can be measured at a precision of 0.1 – 0.2% with the kinematic method. At the high luminosity LHC, the observation of quantum discord is expected to be > 5σ using both the decay and kinematic methods and can be measured with a precision of 5% with the decay method and 0.05% with the kinematic method. Additionally, we identify the kinematic cuts at the LHC to isolate the $t\bar{t}$ state that is separable but has non-zero discord. By systematically investigating quantum discord for the first time through a detailed collider analysis, this work expands the toolkit for quantum information studies in particle physics and lays the groundwork for deeper insights into the quantum properties in high-energy collisions.
LiMn x Fe 1-x PO 4 /C is considered a promising next-generation cathode material with significant commercial potential, inheriting the safety of LiFePO 4 while offering higher energy densities. However, the extremely low conductivity and the Jahn-Teller effect induced by Mn 3+ limit its practical capacity and rate performance. Effective modifications can be achieved through particle nanonization and uniform carbon coating. Here, in this work, we synthesized microspherical LiMn 0.6 Fe 0.4 PO 4 /C cathode materials using a hydrothermal method combined with spray drying carbon coating. The cathode material exhibits a microsphere structure composed of aggregated nanorods with a uniform 3 nm carbon coating, showing good dispersibility, small specific surface area and high tap density. In-situ diffraction analysis showed that expanding the single-phase solid solution region during (de)lithiation can reduce the energy barrier for electron transport, improve the kinetics of the (dis)charge process, and enhance both cycling and rate performance. The initial capacity at 0.1C can reach 155 mAh/g, and the capacity remains at 133.5 mAh/g with a retention rate of 97.1 % after 300 cycles. The synergistic effect of particle nanonization and uniform carbon coating endows the LiMn x Fe 1-x PO 4 /C material with excellent electrochemical performance.
As the US fusion materials community awaits the selection and design of a fusion prototypical neutron source (FPNS), a risk reduction exercise has been conducted to (i) provide an updated materials performance evaluation using state-of-the-art computational materials modeling, (ii) expand on legacy analysis based on pure Fe to other relevant fusion structural materials types, and (iii) ensure that materials response under FPNS operational conditions is consistent with referential fusion reactor conditions. The current paper describes the efforts undertaken to assemble a comprehensive computational methodology that includes neutronics, primary damage calculations, atomistic simulations of displacement cascades, chemical inventory evolution calculations, and a computational thermodynamic analysis of emerging phases during irradiation. Our work extends existing studies in pure Fe to reduced-activation ferritic/martensitic steels, tungsten, silicon carbide, and vanadium alloys. We focus on the single-beam deuteron/lithium-stripping neutron source behind the IFMIF-DONES concept, which we assess against ITER, two DEMO designs, and an ideal pure 14-MeV flux. Our analysis indicates that, within standard uncertainties inherent to the models employed, the DONES concept adequately captures fusion conditions in the four materials analyzed. Our work is intended as a comprehensive irradiation damage analysis of fusion-representative neutron sources, to be used for further neutron source evaluation and fusion facility operation.
As solar adoption across the United States continues to grow, so do the gaps between rural and urban communities in how they choose to embrace these technologies, leading to serious questions of social justice and equity by researchers and policymakers alike. While recent studies have examined the racial and social justice elements of solar adoption alongside institutions' role in shaping pro-solar policies, codes, and code enforcement, an opportunity exists to discuss how the place and composition of the body politic in terms of race/ethnicity and rurality exists. This paper establishes a methodology for examining location and body politic composition concerning adopting all types of solar (residential, non-residential, utility-scale), utilizing the State of Georgia as a case study. Results indicate that the approach yields useful and informative findings; namely, there is a significant difference in adopting non-residential and utility-scale solar between rural and urban counties. We conclude by discussing further opportunities to expand on this analysis and the impact of assessing solar adoption in terms of value alignment between a body politic and the policies that shape the adoption of sustainable energy technologies. Finally, combining solar adoption information for the State of Georgia with Census data, this study compares solar adoption trends across counties--grouped by urban/rural classification and racial and ethnic majority.
Urban water and energy systems are crucial for sustainably meeting basic service demands in cities. Therefore, this paper proposes and applies a technology-independent “reference resource-to-service system” framework for concurrent evaluation of urban water and energy system interventions and their ‘nexus’ or ‘interlinkages’. In a concrete application, data that approximate New York City conditions are used to evaluate a limited set of interventions in the residential sector, spanning from low-flow toilet shifts to extensive green roof installations. Results indicate that interventions motivated primarily by water management goals can considerably reduce energy use and contribute to mitigation of greenhouse gas emissions. Similarly, energy efficiency interventions can considerably reduce water use in addition to lowering emissions. However, interventions yielding the greatest reductions in energy use and emissions are not necessarily the most water conserving ones, and vice versa. Useful further research, expanding the present analysis should consider a broader set of resource interactions, towards a full climate, land, energy and water (CLEW) nexus approach. Overall, assessing the impacts, trade-offs and co-benefits from interventions in one urban resource system on others also holds promise as support for increased resource efficiency through integrated decision making.
The catalytic hydrogenation of prochiral ketones with second and third-row transition metal complexes bearing chelating chiral ligands containing at least one N–H functionality has achieved unparalleled performance, delivering, in the best cases, chiral alcohols with up to 99.9% ee using extremely small catalyst loadings (~10 -5 mol%). Hence the efficacy of this reaction has closely approached that of natural enzymatic systems and the reaction itself has become one of the most efficient artificial catalytic reactions developed to date. This paper describes the current level of understanding of the mechanism of enantioselective hydrogenation and transfer hydrogenation of aromatic ketones with pioneering prototypes of bifunctional catalysts, the Noyori and Noyori–Ikariya complexes. Finally, analysis presented herein expands the concept of “metal–ligand cooperation”, redefines the term “cooperative ligand” and introduces “H – /H + outer-sphere hydrogenation” as a novel paradigm in outer-sphere hydrogenation.