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At least 1,045 records · Page 58

Characterizing Signatures of Geothermal Exploration Data with Machine Learning Techniques: An Application to the Nevada Play Fairway Analysis

We are introducing machine learning methods to the play fairway analysis to generate geothermal potential maps to support the evaluation of geothermal resource potential and the exploration for undiscovered blind geothermal systems in the Nevada Great Basin region. Our project aims to identify new ways to combine the play fairway data and empirically organize relationships between feature weights and labels in an improved workflow. As a means of doing this, we introduce machine learning methods to evaluate the influence of certain geological and geophysical features/feature sets in predicting geothermal favorability. This report highlights promising approaches based on supervised and unsupervised learning methods. First, we demonstrate a filter method applied to supervised classification modeling. The supervised filter method is based on permutation analysis to evaluate every possible feature combination/drop out scenario and rank feature influence based on the performance variance of supervised classification models. Additionally, we present an unsupervised factor analysis based on principal component analysis coupled with a semi-supervised kmeans clustering algorithm. This analysis allows us to identify the optimal number of groups/clusters for training sites and structural settings to identify feature patterns including correlation, variance, and latent and dominant feature relationships. The results from these methods offer a promising avenue for identifying favorable sources of predictive information to identify the locations of blind geothermal systems and furthering our understanding of complex geothermal feature and label relationships in the Great Basin region and beyond.

15 GEOTHERMAL ENERGY↗

Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction

Abstract Developing prediction models for emerging infectious diseases from relatively small numbers of cases is a critical need for improving pandemic preparedness. Using COVID-19 as an exemplar, we propose a transfer learning methodology for developing predictive models from multi-modal electronic healthcare records by leveraging information from more prevalent diseases with shared clinical characteristics. Our novel hierarchical, multi-modal model ( $${\textsc {TransMED}}$$ T R A N S MED ) integrates baseline risk factors from the natural language processing of clinical notes at admission, time-series measurements of biomarkers obtained from laboratory tests, and discrete diagnostic, procedure and drug codes. We demonstrate the alignment of $${\textsc {TransMED}}$$ T R A N S MED ’s predictions with well-established clinical knowledge about COVID-19 through univariate and multivariate risk factor driven sub-cohort analysis. $${\textsc {TransMED}}$$ T R A N S MED ’s superior performance over state-of-the-art methods shows that leveraging patient data across modalities and transferring prior knowledge from similar disorders is critical for accurate prediction of patient outcomes, and this approach may serve as an important tool in the early response to future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling Aerial Gamma-Ray Backgrounds Using Non-negative Matrix Factorization

Airborne gamma-ray surveys are useful for many applications, ranging from geology and mining to public health and nuclear security. In all these contexts, the ability to decompose a measured spectrum into a linear combination of background source terms can provide useful insights into the data and lead to improvements in the techniques that use spectral energy windows. Multiple methods for the linear decomposition of spectra exist but are subject to various drawbacks, such as allowing negative photon fluxes or requiring detailed Monte Carlo modeling. In this work, we propose using non-negative matrix factorization (NMF) as a data-driven approach to spectral decomposition. Using aerial surveys that include flights over water, we demonstrate that the mathematical approach of NMF finds physically relevant structure in the aerial gamma-ray background, namely, that measured spectra can be expressed as the sum of nearby terrestrial emission, distant terrestrial emission, and radon and cosmic emission. Furthermore, these NMF background components are compared with the background components obtained by noise-adjusted singular value decomposition (NASVD), which contain negative photon fluxes and, thus, do not represent the emission spectra in as straightforward a way. Finally, we comment on the potential areas of research that are enabled by NMF decompositions, such as new approaches to spectral anomaly detection and data fusion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Two-Phase Fluid Flow Properties of Rough Fractures With Heterogeneous Wettability: Analysis With Lattice Boltzmann Simulations

Fractures are conduits for fluid flow in low-permeability geological formations. Multiphase flow properties of fractures are important in natural processes and in engineering applications such as the evaluation of the sealing capacity of caprocks and productivity of hydrocarbon-bearing tight rocks. Investigations of flow and transport through fractures typically focus on the effects of fracture geometric and mechanical factors such as aperture, roughness, and compressibility. The wettability of the fracture surfaces and its influence on microscale interfacial phenomena and macroscale effective transport properties are seldom studied. In this study, we investigated the effect of heterogeneous wetting properties on the displacement of water by supercritical CO2 through a series of lattice Boltzmann method simulations. The results show the evolution of the CO2 plume within a fracture is controlled by both the roughness of the aperture field and the wetting distribution. We combined these factors into a capillary pressure map that can be related to the macroscopic flow behavior of the fracture. We observed that heterogeneous wetting distributions promote the residual trapping of water where lower capillary pressures allowed for isolated water pockets in higher capillary pressure zones. Analysis of fracture unsteady relative permeability shows the effect of wetting on permeability evolution and provides support for the viscous-coupling relative permeability model. Finally, analysis of the steady-state relative permeability and saturation demonstrates a strong correlation between permeability and the standard deviation of the capillary pressure field. Thus, characterizing the distribution of wetting properties of fractures is crucial to understanding multiphase fracture flow and transport properties.

58 GEOSCIENCES↗

Factors that Impact the Redox Kinetics Associated with Sr1-xAxFeO3 (A = Ca, Ba) in Air Separations Technologies

Perovskite oxides, including SrFeO3-δ, have garnered significant interest for their impressive oxygen storage thermodynamics and kinetics. While traditional oxygen production is performed through cryogenic separation methods at the industrial scale, oxygen carrier-based separations have offered an attractive alternative at the modular scale. Perovskites are considered ideal oxygen carriers, with their structural flexibility minimizing both the thermodynamic barrier and the structural strain related to the oxygen uptake/release cycle. Our latest work has identified a few major factors that directly impact the oxygen release thermodynamics and kinetics for Sr1-xAxFeO3-δ (A = Ca, Ba) materials including elemental composition, crystallographic symmetry, surface area, and pretreatment conditions. This presentation will discuss these factors using Sr1¬-xCaxFeO3 and Ba1-xSrxFeO3 to illustrate their individual and collective impacts on the design of high-performance oxygen carriers when operating at 300-700 °C. Additionally, we will discuss how each of these factors can be leveraged for the numerous catalytic applications also dependent on the redox properties of mixed metal oxides.

Popczun, Eric↗

Synergistic data analytics for electromechanical oscillation in electric power systems

Accurate real-time estimation of the four electromechanical oscillation properties, i.e., dominant oscillation modes, mode shapes, participation factors, and coherent groups, is of great importance to assess and mitigate potential electromechanical oscillations in interconnected power systems. While eigenvalue analysis can realize such estimation, it requires precise linearized dynamic models and accurate parameters, which are highly difficult to obtain in practice. Data fusion-based modal estimation methods can extract the properties of electromechanical oscillations from measurement data without the power system model and parameters, but most of the time only one or two property assessments can be accomplished each time. To overcome this challenge, this paper presents a synergistic data analytics solution to characterize the dynamic behaviors of electromechanical oscillations from real-time measurement data. Here, the proposed method uses optimized variable projection, and it is capable of estimating all four electromechanical oscillation behavior properties from measured responses. Case studies are performed using the simulated measurement data of a 16-generator 68-bus test system and the field measurements collected by the PMUs deployed in the Yunnan Power Grid. The results demonstrate that the proposed synergistic data analytics solution can achieve satisfactory performance in capturing the properties of electromechanical oscillations from measurement data and exhibit strong robustness against measurement noise when compared with existing measurement-based methods.

42 ENGINEERING↗

Peanut allergy burden survey: Factors associated with health‐related quality of life in adolescents

Abstract Background Patients with peanut allergy (PA) experience significant burden of illness, which impacts health‐related quality of life (HRQoL), particularly in adolescence. There is a paucity of research evaluating drivers of HRQoL scores. Methods A prospective, online survey of adolescents with self‐reported, provider‐diagnosed PA completed from November 2018 to January 2019 was used to explore drivers of the real‐world impact of PA on HRQoL using the Pediatric Quality of Life Inventory 4.0 (PedsQL) and other measures. Univariate and multivariate analyses were used to identify potential factors associated with PedsQL scores and to understand the level of association. Results A total of 102 adolescents were included. The final model included 10 variables: race, reported strict peanut avoidance, satisfaction with prophylaxis, moderate‐to‐severe reaction within the past 12 months, touching peanut as cause of most severe reaction, fear of reaction, age, gender, comorbidities, and daily life limitations. In total, three items were shown to be strong predictors of the PedsQL total score including cause of severe reaction was touching peanut (yes), level of agreement with avoiding peanut (completely agree), and satisfaction with prophylaxis (not very much/not at all). Conclusions There is substantial heterogeneity in the impact of the burden of PA on PedsQL scores across patients. This indicates the importance of shared and individualized decision making for PA management to optimize outcomes and improve HRQoL.

McCann, William A.↗

Topological Effects Near Order–Disorder Transitions in Symmetric Diblock Copolymer Melts

The effects of polymer chain topology on the order–disorder transition of symmetric AB diblock copolymer melts are studied using coarse-grained molecular dynamics simulations. Specifically, we compared chain conformations near the lamellar-disordered transition in melts of symmetric (i.e., 50–50) AB diblock copolymers of linear chains, rings, and trefoil knots at the same chain lengths. The order (lamellar)–disorder transition temperature and the domain sizes both shifted to lower values with the introduction of topological constraints, leading to the following sequence: linear chains > rings > trefoil knots. Furthermore, investigation of the polymer chain conformations in terms of their radii of gyration, their writhe values (a measure for the degree of intertwining of a chain around itself), and their Jones polynomials (a method to measure entanglement of curves) showed that linear chains and rings remained stretched, while knots were stretched and tightened in disordered melts close to the lamellar-disorder transition. This work highlights chain topology as an important factor in affecting microphase separation in block copolymers.

36 MATERIALS SCIENCE↗

Targeted seed EMS mutagenesis reveals a basic helix–loop–helix transcription factor underlying male sterility in sorghum

Abstract Forward genetic screens of mutant populations are fundamental for functional genomics studies. However, isolating independent mutant alleles to molecularly identify causal genes is challenging in species recalcitrant to genetic manipulation. Here, we demonstrate that classic seed ethyl methanesulfonate (EMS) mutagenesis coupled with genome sequencing can overcome this limitation in sorghum. We used this method to generate new mutant alleles of sorghum MALE STERILE 8 (MS8) and identified the causal locus for the ms8 phenotype as Sobic.004G270900, which encodes the sorghum ortholog of maize bhlh122, a basic helix–loop–helix (bHLH) transcription factor required for male fertility in maize. Bulked segregant analysis mapped ms8-1 to a region on chromosome 4 containing Sobic.004G270900. Seeds from heterozygous MS8/ms8-1 plants were mutagenized and screened for chimeric inflorescences containing sectors with white, sterile anthers resembling the ms8-1 homozygous phenotype. DNA sequencing of sterile and fertile sectors from a single chimeric inflorescence revealed two mutations in Sobic.004G270900 within the sterile sector, but not the fertile sector. Isolation of this loss-of-function allele (ms8-2) established Sobic.004G270900 as the causative locus for male sterility in the ms8 mutant. We generated additional alleles of MS8 in a different genetic background using CRISPR/Cas9-based gene editing, where deletions in Sobic.004G270900 also resulted in male sterility. Our work identified a gene underlying male sterility in sorghum and provides a novel and straightforward genetic tool for researchers who lack access to advanced transformation facilities to validate gene candidates. Unlike gene editing, no prior knowledge of candidate genes is required for targeted seed EMS mutagenesis to aid identification of causal loci.

Genetics & Heredity↗

CRADA Number NFE-21-08827 with DayLyte, Inc. (CRADA Final Report)

DayLyte Batteries is developing an aqueous Sodium-Air battery made with abundant materials while being half to a third the weight of Li-ion to power electric aircraft, electric vehicles and provide renewable energy on demand. To make this battery practical, DayLyte is developing a thin film ceramic Nasicon solid electrolyte amenable to rapid scaleup as well as a protective coating that will protect the solid electrolyte from 50wt% NaOH during the battery’s end-of-discharge while still allowing Na-ions to pass back and forth. If the thin film solid electrolyte and stable coating can be developed it will open the world to step change in battery performance all while not sacrificing the environment on the way. The project was designed to first focus on making and characterizing the Nasicon membrane followed by measuring its electrochemical performance, then assembling a full cell, optimizing its NaOH stability and then optimize the overall prototype design. Over the past two years, we have significantly improved the Nasicon film uniformity, demonstrated protective ligands that are stable in 50wt% NaOH by measuring no mass change with a quartz crystal microbalance, tested different heating methods like tube furnace and rapid heating and developed glassy carbon coatings on the current collector to prevent Nasicon-current collector alloying. We have found that getting film uniformity as measured by electrochemical impedance spectroscopy (EIS) is difficult because of different factors like surface roughness, deposition uniformity and heat treatment time and uniformity. The glassy carbon coating should significantly reduce the surface roughness and by tuning the coating conditions the film deposition uniformity improves and using an automated heating method should lead to much improved film uniformity.

25 ENERGY STORAGE↗

Opportunities for Cost Savings with In-Transit Visualization

We analyze the opportunities for in-transit visualization to provide cost savings compared to in-line visualization. We begin by developing a cost model that includes factors related to both in-line and in-transit which allows comparisons to be made between the two methods. We then run a series of studies to create a corpus of data for our model. We run two different visualization algorithms, one that is computation heavy and one that is communication heavy with concurrencies up to 32, 768 cores. Our primary results are in exploring the cost model within the context of our corpus. Our findings show that in-transit consistently achieves significant cost efficiencies by running visualization algorithms at lower concurrency, and that in many cases these efficiencies are enough to offset other costs (transfer, blocking, and additional nodes) to be cost effective overall. Finally, this work informs future studies, which can focus on choosing ideal configurations for in-transit processing that can consistently achieve cost efficiencies.

Kress, James↗

Tropical amplitudes for colored Lagrangians

Recently a new formulation for scattering amplitudes in Tr(Φ 3 ) theory has been given based on simple combinatorial ideas in the space of kinematic data. This allows all-loop integrated amplitudes to be expressed as “curve integrals” defined using tropical building blocks — the “headlight functions”. This paper shows how the formulation extends to the amplitudes of more general Lagrangians. We will present a number of different ways of introducing tropical “numerator functions” that allow us to describe general Lagrangian interactions. The simplest family of these “tropical numerators” computes the amplitudes of interesting Lagrangians with infinitely many interactions. We also describe methods for tropically formulating the amplitudes for general Lagrangians. One uses a variant of “Wick contraction” to glue together numerator factors for general interaction vertices. Another uses a natural characterization of polygons on surfaces to give a novel combinatorial description of all possible diagrams associated with arbitrary valence interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Three-dimensional fracture continuum characterization aided by surface time-domain electromagnetics and hydrogeophysical joint inversion—proof-of-concept

Efficient and safe production of hydraulically fractured reservoirs benefits from the prediction of their geometrical attributes. Geophysical methods have the potential to provide data that are sensitive to fracture geometries, alleviating the typically sparse nature of in situ reservoir observations. Moreover, surface-based methods can be logistically and economically attractive since they avoid operational interference with the injection well infrastructure. Here, we investigate the potential of the surface-based time-domain electromagnetic (EM) method. EM methods can play an important role owing to their sensitivity to injection-induced fluid property changes. Two other advantageous factors are the EM signal-enhancing effect of vertical steel-cased wells and the fact that injected proppants can be enhanced to produce a stronger electrical conductivity contrast with the reservoir’s connate fluid. Nevertheless, an optimal fracture characterization will no doubt require the integration of EM and reservoir injection and production data. We hence carry out our investigations within a hydrogeophysical parameter estimation framework where EM data and injection flow rates are combined in a fully coupled way. Given the interdisciplinary nature of coupled hydrogeophysical inverse modeling, we dedicate one section to laying out key aspects in a didactic manner.

58 GEOSCIENCES↗

An investigation of the multi-mode Richtmyer-Meshkov instability at a gas/HE interface using Pagosa

Here, in this work, we present a hydrocode Pagosa and explore the Richtmyer-Meshkov Instability (RMI) at an air/high explosive (HE) interface for the first time that is important but has not received much attention yet in the high explosive safety field. Thus, the presented Pagosa can be expected to predict the whole deflagration-to-detonation transition (DDT) process in future. In Pagosa, spatial discretization is implemented on cubic staggered grids by computing different variables at the vertex and the cell center, respectively, a special operator-splitting technique is employed to reduce the computational cost, and an artificial viscosity is added to handle the discontinuous shock waves in our simulations. To quantitatively evaluate the capability of Pagosa to solve these kinds of instabilities, the single mode Rayleigh-Taylor instability (RTI) and the multimode RMI at an air/SF 6 interface are first performed, respectively. The Pagosa results are compared with the related numerical solutions in the existing references and the experimental result. Moreover, a theoretical derivation of growth of RTI is also provided based on our numerical method. Subsequently, we explore the multi-mode RMI at an air/HE interface as well as the effects of several factors using Pagosa. Numerical results show that Pagosa is a powerful toolset to generate the right structures and the amplitude of RTI and RMI at an air/SF 6 interface. The solid HE can be penetrated by a strong shock wave and forms RMI deformations. The RMI at an air/HE interface behaves very different than at an air/SF 6 interface, periodic, decreased oscillation is observed due to material character, and is very sensitive to the initial simulation settings, that is, a tiny change in physical quantities will lead to a remarkable RMI structure, which is also observed in a shock bubble interaction. The findings in this work are significant, and will present a new insight for the high explosive field.

97 MATHEMATICS AND COMPUTING↗

Tuning successive linear programming to solve AC optimal power flow problem for large networks

Successive linear programming (SLP) is a practical approach for solving large-scale nonlinear optimization problems. Alternating current optimal power flow (ACOPF) is no exception, particularly the large size of real-world networks. However, in order to achieve tractability, it is essential to tune the SLP algorithm presented in the literature. This paper presents a modified SLP algorithm to solve the ACOPF problem, specified by the U.S. Department of Energy’s (DOE) Grid Optimization (GO) Competition Challenge 1, within strict time limits. The algorithm first finds a near-optimal solution for the relaxed problem (i.e., Stage 1). Then, it finds a feasible solution in the proximity of the near-optimal solution (i.e., Stage 2 and Stage 3). The numerical experiments on test cases ranging from 500-bus to 30,000-bus systems show that the algorithm is tractable. Here the results show that our proposed algorithm is tractable and can solve more than 80% of test cases faster than the well-known Interior Point Method while significantly reduce the number of iterations required to solve ACOPF. The number of iterations is considered an important factor in the examination of tractability which can drastically reduce the computational time required within each iteration.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Experimental investigation of fuel temperature effects on transient needle motion and injection velocity of solenoid type diesel injector

Real driving emission (RDE) test conducted in sub-zero temperature conditions has been acting as a severe emission regulation over the existing test methods for diesel engines. In order to cope with this tightened regulation, many studies have been conducted to interpret the factors causing the deteriorated diesel engine combustion in cold operation conditions. The deteriorated fuel injection performance has been regarded as one of the key contributing factors but the governing mechanisms are not thoroughly understood so far. This study aims to provide a comprehensive understanding of the effects of fuel temperature including sub-zero conditions on fuel injection performance by measuring the transient needle motion and injection velocity of a diesel injector using synchrotron X-ray imaging techniques. Here, the factors causing the deteriorated injector performance and their contributions are discussed thoroughly based on the results. The results showed that the injection duration was shortened as the fuel temperature decreased as a result of decreased needle opening speed and increased needle closing speed. The increase of fuel viscosity and bulk modulus was discussed as the main factors associated with these results. The total injection mass was reduced by lowering the fuel temperature not only by the shortened injection duration but also by the decreased injection velocity. These factors exerted near equivalent contribution to the reduced injection mass at low fuel temperatures.

42 ENGINEERING↗

Enhanced internal condensation of R1233zd(E) on micro- and nanostructured copper and aluminum surfaces

In-tube condensation of refrigerants is an important process which affects thermal efficiency in many applications, ranging from refrigeration and air conditioning to electronics thermal management. In-tube heat transfer and pressure drop are important to heat exchanger sizing and design. Here, in this work, micro- and nanostructured surfaces are applied to the internal wetted areas of copper and aluminum mini-channels to enhance the condensation heat transfer coefficient of hydrofluorocarbon R1233zd(E) refrigerant. To achieve scalable nanomanufacturing, surfaces were uniformly structured by relying on hydrochloric acid etching of aluminum and chemical oxidation of copper. The etched aluminum surfaces exhibited a 150% increase in heat transfer coefficient compared to smooth aluminum channels at specific qualities, with a 66% heat transfer coefficient improvement for complete phase change from saturated vapor to saturated liquid. Copper oxide structures showed no discernable difference in thermal-hydraulic performance when compared to smooth copper channels. Critical dimensionless parameters governing the heat transfer enhancement were identified by varying the tube internal diameter (2.3 mm to 4.7 mm), refrigerant mass flux (50 to 300 kg/(m 2 ·s)), and refrigerant quality (0 to 1). The dimensionless parameters include the Bond number normalized to the condensate film thickness, and the Weber number modified by the vapor friction factor. The relatively small increase in pressure drop (< 10%) associated with these surface enhancements further supports the promise of this method. The scalable and cost-effective techniques used to create these aluminum microstructures may reduce manufacturing cost when compared with current enhancement approaches such as extrusion, drawing, and welding.

42 ENGINEERING↗