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At least 1,135 records · Page 63

PyCBC Inference: A Python-based Parameter Estimation Toolkit for Compact Binary Coalescence Signals

We introduce new modules in the open-source PyCBC gravitational-wave astronomy toolkit that implement Bayesian inference for compact-object binary mergers. We review the Bayesian inference methods implemented and describe the structure of the modules. Here, we demonstrate that the PyCBC Inference modules produce unbiased estimates of the parameters of a simulated population of binary black hole mergers. We show that the parameters' posterior distributions obtained using our new code agree well with the published estimates for binary black holes in the first Advanced LIGO–Virgo observing run.

79 ASTRONOMY AND ASTROPHYSICS↗

Validating induced seismicity forecast models—Induced Seismicity Test Bench

Abstract Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward‐looking, and updated as new data arrive. In this study, we propose an Induced Seismicity Test Bench to test and rank such models; this test bench can be used for model development, model selection, and ensemble model building. We apply the test bench to data from the Basel 2006 and Soultz‐sous‐Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models: Shapiro and Smoothed Seismicity (SaSS) and Hydraulics and Seismics (HySei). These models incorporate a different mix of physics‐based elements and stochastic representation of the induced sequences. Our results show that neither model is fully superior to the other. Generally, HySei forecasts the seismicity rate better after shut‐in but is only mediocre at forecasting the spatial distribution. On the other hand, SaSS forecasts the spatial distribution better and gives better seismicity rate estimates before shut‐in. The shut‐in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut‐in.

Király‐Proag, Eszter↗

Stochastic Fault Detection

This entry describes the state-of-the-art and future perspectives on stochastic fault detection, namely, stochastic fault detection and diagnosis (FDD). Both model-based and data-driven FDD methods for stochastic signals and systems have been included, where the use of hypothesis testing, Kalman filtering, system estimation, principal component analysis (PCA), and stochastic distribution control has been discussed for the construction of effective FDD algorithms. Indeed, stochastic FDD constitute an important and integrated part in developing fault-tolerant controls (FTC) for guaranteed safe operation of control systems, of which increased penetration of random factors is inevitable nowadays.

Wang, Aiping↗

Active and passive cooling approaches for a Southern California residential community

This study assesses cooling strategies in a low-income community in Southern California that lacks air conditioning and struggles with heat and air pollution. We used an urban building energy model and an electric distribution system model to evaluate active and passive cooling measures. The most effective space cooling measures were high-performance air-source heat pumps, cool coatings, window films, and harnessing the space cooling effect from heat pump water heaters. The results show that combining heat pump water heaters with window films and cool coatings reduces heat index hazard hours within buildings by 95 % to 99 % but increases total energy costs (equipment costs plus changes in utility bills) by 20 % to 60 % where the higher end includes building electrical upgrades. These measures also led to increased space heater use during colder months to avoid overcooling. Replacing conventional heaters with air source heat pumps eliminated unsafe indoor temperatures and reduced total energy use, but increased cost by 125 % to 150 %. In total, using heat pumps for space and water heating could reduce primary energy use by up to 57 %. The higher cost of active and passive cooling measures can be mitigated by existing and emerging incentive programs, especially those that support heat pumps. Electric distribution upgrades to support community electrification are estimated to increase utility costs by $\$$25 to $\$$40 per ratepayer per year. The results underscore the potential and challenges of adapting building infrastructure in communities at risk from climate and environmental stressors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modelling the ejection of primary aerosols during the fast pyrolysis of biomass anisotropic particles

A model for the fast pyrolysis of anisotropic biomass particles is presented which considers bubbling dynamics within the liquid intermediate phase (metaplast) and aerosol ejection from this phase. The model employs the population balance equation and the method of moments to estimate the production rate and resultant size distribution of aerosol ejections, incorporating a detailed CRECK reaction mechanism, and considers the effect of anisotropic biomass microstructure on the intraparticle transport of mass and energy. Here, this study investigates the impact of particle size, heating rate (heat transfer coefficient), and lignocellulosic composition on aerosol ejection. The model predicts that, at high heating rates (convective heat transfer coefficient of 359 W/m 2 .K), aerosols can contribute over 20% to the heavy fraction yield in bio-oil for small particles (1 mm diameter, 4 mm length). The model can predict aerosol size distribution and surface area, indicating an average size of 20 μm for bubbles and 5 μm for aerosols during increased bubble production and aerosol ejection rates. These findings are consistent with prior experimental results and provide essential information for future modeling of extra-particle reactions of the aerosols as they progress through the reactor.

09 BIOMASS FUELS↗

Predicting the proximity to macroscopic failure using local strain populations from dynamic in situ X-ray tomography triaxial compression experiments on rocks

Predicting the proximity of large-scale dynamic failure is a critical concern in the engineering and geophysical sciences. Here we use evolving contractive, dilatational, and shear strain deformation preceding failure in dynamic X-ray tomography experiments to examine which strain components best predict the proximity to failure. We develop machine learning models to predict the proximity to failure using time series of three-dimensional local incremental strain tensor fields acquired in rock deformation experiments under stress conditions of the upper crust. Three-dimensional scans acquired in situ throughout triaxial compression experiments provide a distribution of density contrasts from which we estimate the three-dimensional incremental strain that accumulates between each scan acquisition. Training machine learning models on multiple experiments of six rock types provides suites of feature importance that indicate the predictive power of each feature. Comparing the average importance of groups of features that include information about each strain component quantifies the ability of the contractive, dilatational and shear strain to predict the proximity of macroscopic failure. A total of 24 models of four machine learning algorithms with six rock types indicate that 1) the dilatational strain provides the best predictive power of the strain components, and 2) the intermediate values (25th-75th percentile) of the strain population provide the best predictive power of the statistics of the strain populations. In addition, the success of the predictions of models trained on one rock type and tested on other rock types quantifies the similarities and differences of the precursory strain accumulation process in the six rock types. These similarities suggest the potential existence of a unified theory of brittle rock deformation for a range of rock types.

58 GEOSCIENCES↗

Steady RANS methodology for calculating pressure drop in an in-line molten salt compact crossflow heat exchanger

We report the development of molten salt cooled reactors (MSR) and fluoride-salt cooled high temperature reactors (FHR) requires the use of advanced design tools for the primary heat exchanger design. Due to geometric and flow characteristics, compact (pitch to diameter ratios equal to or less than 1.25) heat exchangers with a crossflow flow arrangement can become desirable for these reactors. Unfortunately, the available experimental data is limited for compact tube bundles or banks in crossflow. Computational Fluid Dynamics can be used to alleviate the lack of experimental data in these tube banks. Previous computational efforts have been primarily focused on large S/D ratios (larger than 1.4) using unsteady Reynolds averaged Navier-Stokes and Large Eddy Simulation frameworks. These approaches are useful, but have large computational requirements that make comprehensive design studies impractical. A CFD study was conducted with steady RANS in an effort to provide a starting point for future design work. The study was performed for an in-line tube bank geometry with FLiBe (LiF-BeF2), a frequently selected molten salt, as the working fluid. Based on the estimated pressure drops, the pressure and velocity distributions in the domain, an appropriate meshing strategy was determined and presented. Periodic boundaries in the spanwise direction transverse flow were determined to be an appropriate boundary condition for reduced computational domains. The domain size was investigated and a minimum of 2-flow channels for a domain is recommended to ensure the behavior is accounted for. Finally, the standard low Re κ-ε (Lien) turbulence model was determined to be the most appropriate for steady RANS of this case at the time of writing.

42 ENGINEERING↗

Analysis of incentive policies for phosphorus recovery at livestock facilities in the Great Lakes area

Livestock operations have been highly intensified over the last decades, resulting in the advent of large concentrated animal feeding operations (CAFOs). Intensification decreases production costs but also leads to substantial environmental impacts. Specifically, nutrient runoff from livestock waste results in eutrophication, harmful algal blooms, and hypoxia. The implementation of nutrient recovery systems in CAFOs can abate nutrient releases and negative ecosystem responses, although they might negatively affect the economic performance of CAFOs. We design and analyze potential incentive policies for the deployment of phosphorus recovery technologies at CAFOs considering the geospatial vulnerability to nutrient pollution. The case study demonstration consists of 2217 CAFOs in the U.S. Great Lakes area. The results reveal that phosphorus recovery is more economically viable in the largest CAFOs due to economies of scale, although they also represent the largest eutrophication threats. For small and medium-scale CAFOs, phosphorus credits progressively improve the profitability of nutrient management systems. The integration of biogas production does not improve the economic performance of phosphorus recovery systems at most of CAFOs, as they lack enough size to be cost-effective. Furthermore, phosphorus recovery proves to be economically beneficial by comparing the net costs of nutrient management systems with the negative economic impact derived from phosphorus releases. The incentives necessary for avoiding up to 20.7.10 3 ton/year phosphorus releases and achieve economic neutrality in the Great Lakes area are estimated at $223 million/year. Additionally, the fair distribution of limited incentives is studied using a Nash allocation scheme, determining the break-even point for allocating monetary resources.

54 ENVIRONMENTAL SCIENCES↗

Palladized cells as suspension catalyst and electrochemical catalyst for reductively degrading aromatics contaminants: Roles of Pd size and distribution

The palladized cell (Pd-cell) could be used as an efficient catalyst in catalyzing the degradations of a wide variety of environmental contaminants. Nevertheless, when the Pd NPs associate with the bacteria, the catalytic activity likely significantly affected by the biomass. Quantitative indicators that characterize of Pd-cell are necessary and little attention has been paid to investigate how the catalytic efficiency of Pd-cell is affected by the size and distribution of Pd NPs. To fill this gap, we explored the roles of the above-mentioned key factors on the performance of Pd-cell in catalyzing the degradations of two aromatic contaminants (nitrobenzene and p-chlorophenol) in two commonly used scenarios: (1) using Pd-cell as suspended catalyst in solution and (2) using Pd-cell as electrocatalyst directly coated on electrode. In scenario (1), the relationship of exposing area to Pd particle size and distribution factors was established. Based on theoretical estimation and catalytic performance analysis, the results indicated that adjusting the exposing area to a large value (9.3 ± 0.1 × 10 5 nm 2 mg -1 Pd) was extremely effective for improving the catalytic activity of Pd-cell used as a suspension catalyst. In scenario (2), our results showed that the best electrocatalytic performances were achieved on the electrode decorated with Pd-cells with the largest NP size (54.3 ± 16.4 nm), which exerted maximum electrochemical active surface area (10.6 m 2 g -1 ) as well as favorable conductivity. The coverage of deposited Pd NPs (>95%) on the cell surface played a crucial role in boosting the conductivity of biocatalyst, thus determining the possibility of Pd-cell as an efficient electrocatalyst. The findings of this study provide a guidance for the synthesis and application of Pd-cell, which enables the design of Pd-cell to be suitable for different catalysis systems with high catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantification of Shallow Defect Suppression in Aminosilane-Passivated Lead Halide Perovskites via Optical and Electrochemical Methods

We combine fluence-dependent photoluminescence (PL) and electrochemical characterization to estimate defect-dependent trapping rates, energetic distributions, and densities of defects, in lead halide perovskite films Cs 0.1 FA 0.9 PbI 3 and Cs 0.17 FA 0.83 Pb­(I 0.75 Br 0.25 ) 3 , before and after trap passivation with vapor-deposited (3-aminopropyl)­trimethoxysilane (APTMS). For both compositions, the PL studies show that energetically shallow subgap near-valence defect densities lead to bimolecular nonradiative recombination which is reduced by 92% after APTMS treatment. Electrochemical characterization of these same active layers shows for the first time that APTMS passivation impacts mainly on near-valence (mobile anionic) defects that decrease in density by 4 orders of magnitude, from 10 18 cm –3 to 10 14 cm –3 , as a result of silane modification. Here, the combination of PL and electrochemical characterization promises a unique approach to speciation and quantification of a broader distribution of trap states in perovskites and provides straightforward assessments of the efficacy of defect mitigation strategies.

Defects↗

Computational Framework for Machine-Learning-Enabled 13 C Fluxomics

13 C metabolic flux analysis (MFA) has emerged as a powerful tool for synthetic biology. This optimization-based approach suffers long computation time and unstable solutions depending on the initial guess. Here, we develop a machine-learning-based framework for 13 C fluxomics. Specifically, training and test data sets are generated by metabolic network decomposition and flux sampling, in which flux ratios at metabolic nodes and simulated labeling patterns of metabolites are used as training targets and features, respectively. To improve prediction accuracy and simplify the model, automated processes are developed for flux ratio selection based on solvability and feature screening based on importance. We found that predictive performance can be significantly improved using both amino acids and central carbon metabolites in comparison with amino acids alone. Together with measured external fluxes, the predicted flux ratios determine the mass balance system, yielding global flux distributions. This approach is validated by flux estimation using both simulated and experimental data in comparison with canonical 13 C MFA. The approach represents a reliable fluxomics method readily applicable to high-throughput metabolic phenotyping, which highlights the advances of intelligent learning algorithms in synthetic biology, specifically in the Test and Learn stage of the Design-Build-Test-Learn cycle.

13C metabolic flux analysis↗

A Decision-Relevant Factor-Fixing Framework: Application to Uncertainty Analysis of a High-Dimensional Water Quality Model

Factor Fixing (FF) is a common method for reducing the number of model parameters to lower computational cost. FF typically starts with distinguishing the insensitive parameters from the sensitive and pursues uncertainty quantification (UQ) on the resulting reduced-order model, fixing each insensitive parameter at a fixed value. There is a need, however, to expand such a common approach to consider the effects of decision choices in the FF-UQ procedure on metrics of interest. Therefore, to guide the use of FF and increase confidence in the resulting dimension-reduced model, we propose a new adaptive framework consisting of four principles: (a) re-parameterize the model first to reduce obvious non-identifiable parameter combinations, (b) focus on decision relevance especially with respect to errors in quantities of interest (QoI), (c) conduct adaptive evaluation and robustness assessment of errors in the QoI across FF choices as sample size increases, and (d) reconsider whether fixing is warranted. The framework is demonstrated on a spatially-distributed water quality model. The error in estimates of QoI caused by FF can be estimated using a Polynomial Chaos Expansion (PCE) surrogate model. Built with 70 model runs, the surrogate is computationally inexpensive to evaluate and can provide global sensitivity indices for free. For the selected catchment, just two factors may provide an acceptably accurate estimate of model uncertainty in the average annual load of Total Suspended Solids (TSS), suggesting that reducing the uncertainty in these two parameters is a priority for future work before undertaking further formal uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗

Compositional heterogeneity in Cs y FA 1- y Pb(Br x I 1- x ) 3 perovskite films and its impact on phase behavior

Hybrid organic inorganic lead halide perovskite semiconductors of the form Cs y FA 1-y Pb(Br x I 1-x ) 3 are promising candidate materials for high-efficiency photovoltaics. Notably, cation and anion substitution can be used to tune the band gaps to optimize performance and improve stability. However, multi-component materials can be prone to compositional and structural inhomogeneity and the extent, length scale and impact of this heterogeneity on lead halide perovskite properties are not well understood. Here we use synchrotron X-ray diffraction to probe the evolution of crystal structure across the tetragonal-to-cubic phase transition for a series of Cs y FA 1-y Pb(Br x I 1-x ) 3 thin films with x = 0.05 to 0.3 and y = 0.17 to 0.40. We find that the transition occurs across a broad temperature range of approximately 40 °C, much larger than for pure compounds such as MAPbI 3 and MAPbBr 3 . Finally, we hypothesize that this smearing of the phase transition is due to compositional inhomogeneities that give rise to a distribution of local transition temperatures and we estimate the composition varies by about 10% to 15% with likely greater heterogeneity for the halide anion than the cation. This approach of mapping the transition is a simple and effective method of assessing heterogeneity, enabling evaluation of its impact.

36 MATERIALS SCIENCE↗

Dielectric relaxation in 0-3 PVDF-Ba(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} composites

(1-x)PVDF-xBa(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} ceramic-polymer composites with x = 0.025, 0.05, 0.10, 0.15 were prepared using melt-mixing technique. The crystal symmetry, space group and unit cell dimensions were determined from the XRD data of Ba(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} using FullProf software, whereas crystallite size and lattice strain were estimated using Williamson-Hall approach. The distribution of Ba(Fe{sub 1/2}Nb{sub 1/2})O{sub 3} particles in the PVDF matrix were examined on the cryo-fractured surfaces using a scanning electron microscope. Cole-Cole and pseudo Cole-Cole analysis suggested the dielectric relaxation in this system to be of non-Debye type. Filler concentration dependent real and imaginary parts of dielectric constant as well as ac conductivity data followed definite trends of exponential growth types of variation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Environment of the submillimeter-bright massive starburst HFLS3 at z ∼ 6.34

We describe the search for Lyman break galaxies (LBGs) near the submillimeter-bright starburst galaxy HFLS3 at z = 6.34 and a study on the environment of this massive galaxy during the end of reionization. We performed two independent selections of LBGs on images obtained with the Gran Telescopio Canarias (GTC) and the Hubble Space Telescope (HST) by combining nondetections in bands blueward of the Lyman break and color selection. A total of 10 objects fulfilling the LBG selection criteria at z>5.5 were selected over the 4.54 and 55.5 arcmin{sup 2} covered by our HST and GTC images, respectively. The photometric redshift, UV luminosity, and star formation rate of these sources were estimated with models of their spectral energy distribution. These z∼6 candidates have physical properties and number densities in agreement with previous results. The UV luminosity function at z ∼ 6 and a Voronoi tessellation analysis of this field show no strong evidence for an overdensity of relatively bright objects (m{sub F105W} < 25.9) associated with HFLS3. However, the overdensity parameter deduced from this field and the surface density of objects cannot exclude definitively the LBG overdensity hypothesis. Moreover, we identified three faint objects at less than 3″ from HFLS3 with color consistent with those expected for z ∼ 6 galaxies. Deeper data are needed to confirm their redshifts and to study their association with HFLS3 and the galaxy merger that may be responsible for the massive starburst.

79 ASTRONOMY AND ASTROPHYSICS↗

Changes in site-specific shape resonances in nitrogen K-shell photoionization of N 2 O induced by vibrational excitation

The central (Nc) and terminal (Nt) nitrogen K-shell photoelectron spectra (PESs) of N 2 O molecules have been measured in the σ shape resonance energy region at temperatures of ~300 and ~630 K. Estimating vibrational populations based on the Boltzmann distribution at these temperatures, PESs of vibrationally ground and bending-excited levels in the initial electronic ground state were extracted. Vibrationally integrated partial cross sections and asymmetry parameters for ionization from vibrationally ground and bending-excited levels were obtained as a function of the incident photon energy by integrating PESs over the vibrational levels of the core-hole states. In N c photoionization, the shape resonance from the bending-excited level was found to be shifted to the lower photon energy side and to become narrower than that from the ground vibrational level. In N t photoionization from the bending-excited level, the downward shift of the resonance is more significant than that in N c ionization. These experimental findings are qualitatively consistent with theoretical predictions and suggest that the shape resonance associated with the N t core hole is more sensitive to the bending angle of the initial state than is the shape resonance associated with the N c core hole. Finally, the asymmetry parameters for photoionization from the bending-excited level, however, showed almost the same behavior as those from the ground vibrational level for both K-shell photoionization channels and in the photon energy range studied here.

74 ATOMIC AND MOLECULAR PHYSICS↗

A biokinetic model for trivalent or hexavalent chromium in adult humans

Chromium exists in several oxidation states, with the trivalent state (Cr(III)) being the dominant naturally occurring form. Chromium in other oxidation states tends to be converted to the trivalent oxide in the natural environment and in biological systems. Chromium(III) has been shown to be an essential nutrient for humans and several non-human species. Chromium(VI), the second most stable form of chromium, is an important environmental contaminant that is mostly of industrial origin and is associated with lung cancer and nose tumours in chromium workers. This paper proposes a biokinetic model for chromium that addresses the distinctive behaviours of Cr(III) and Cr(VI) following uptake to blood of an adult human. Additionally, the model is based on biokinetic data derived from relatively short-term studies involving administration of chromium tracers to adult human subjects or laboratory animals, supplemented with data on the long-term distribution of chromium in adult humans as estimated from autopsy measurements. The model is part of a comprehensive update of biokinetic models of the International Commission on Radiological Protection, used to project or evaluate radiation doses from occupational intake of radionuclides.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Emergency department visits in California associated with wildfire PM 2.5 : differing risk across individuals and communities

The threats to human health from wildfires and wildfire smoke (WFS) in the United States (US) are increasing due to continued climate change. A growing body of literature has documented important adverse health effects of WFS exposure, but there is insufficient evidence regarding how risk related to WFS exposure varies across individual or community level characteristics. To address this evidence gap, we utilized a large nationwide database of healthcare utilization claims for emergency department (ED) visits in California across multiple wildfire seasons (May through November, 2012–2019) and quantified the health impacts of fine particulate matter <2.5 μm (PM 2.5 ) air pollution attributable to WFS, overall and among subgroups of the population. We aggregated daily counts of ED visits to the level of the Zip Code Tabulation Area (ZCTA) and used a time-stratified case-crossover design and distributed lag non-linear models to estimate the association between WFS and relative risk of ED visits. We further assessed how the association with WFS varied across subgroups defined by age, race, social vulnerability, and residential air conditioning (AC) prevalence. Over a 7 day period, PM 2.5 from WFS was associated with elevated risk of ED visits for all causes (1.04% (0.32%, 1.71%)), non-accidental causes (2.93% (2.16%, 3.70%)), and respiratory disease (15.17% (12.86%, 17.52%)), but not with ED visits for cardiovascular diseases (1.06% (–1.88%, 4.08%)). Analysis across subgroups revealed potential differences in susceptibility by age, race, and AC prevalence, but not across subgroups defined by ZCTA-level Social Vulnerability Index scores. These results suggest that PM 2.5 from WFS is associated with higher rates of all cause, non-accidental, and respiratory ED visits with important heterogeneity across certain subgroups. Notably, lower availability of residential AC was associated with higher health risks related to wildfire activity.

54 ENVIRONMENTAL SCIENCES↗