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DOE OSTI2012

Use of an Accurate DNS Particulate Flow Method to Supply and Validate Boundary Conditions for the MFIX Code (Final Report)

The simulation of particulate flows for industrial applications often requires the use of two-fluid models, where the solid particles are considered as a separate continuous phase. One of the underlining uncertainties in the use of the two-fluid models in multiphase computations comes from the boundary condition of the solid phase. Typically, the gas or liquid fluid boundary condition at a solid wall is the so called no-slip condition, which has been widely accepted to be valid for single-phase fluid dynamics provided that the Knudsen number is low. However, the boundary condition for the solid phase is not well understood. The no-slip condition at a solid boundary is not a valid assumption for the solid phase. Instead, several researchers advocate a slip condition as a more appropriate boundary condition. However, the question on the selection of an exact slip length or a slip velocity coefficient is still unanswered. Experimental or numerical simulation data are needed in order to determinate the slip boundary condition that is applicable to a two-fluid model. The goal of this project is to improve the performance and accuracy of the boundary conditions used in two-fluid models such as the MFIX code, which is frequently used in multiphase flow simulations. The specific objectives of the project are to use first principles embedded in a validated Direct Numerical Simulation particulate flow numerical program, which uses the Immersed Boundary method (DNS-IB) and the Direct Forcing scheme in order to establish, modify and validate needed energy and momentum boundary conditions for the MFIX code. To achieve these objectives, we have developed a highly efficient DNS code and conducted numerical simulations to investigate the particle-wall and particle-particle interactions in particulate flows. Most of our research findings have been reported in major conferences and archived journals, which are listed in Section 7 of this report. In this report, we will present a brief description of these results.

42 ENGINEERING↗

DOE OSTI2024

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part II: Enforcing the Lorenz Gauge Condition

In a previous paper Christlieb et al. (A particle-in-cell method for plasmas with a generalized momentum formulation, part I: Model formulation, 2024), we developed a new particle-in-cell (PIC) method for the relativistic Vlasov–Maxwell system in which the electromagnetic fields and the equations of motion for the particles were cast in terms of scalar and vector potentials through a Hamiltonian formulation. This new method evolved the potentials under the Lorenz gauge using integral equation methods. New methods to construct spatial derivatives of the potentials that converge at the same rates as the fields were also presented. The new particle method was compared against standard explicit discretizations, including the well-known FDTD-PIC method, for a range of applications involving sheaths and particle beams. Here, this paper extends this new class of methods by focusing on the enforcement the Lorenz gauge condition in both exact and approximate forms using co-located meshes. A time-consistency property of the proposed field solver for the vector potential form of Maxwell’s equations is established, which is shown to preserve the equivalence between the semi-discrete Lorenz gauge condition and the analogous semi-discrete continuity equation. Using this property, we present three methods to enforce a semi-discrete gauge condition. The first method introduces an update for the continuity equation that is consistent with the discretization of the Lorenz gauge condition. Both the finite difference and spectral implementations satisfy this discrete gauge condition to machine precision. The second approach we propose enforces a semi-discrete continuity equation using the boundary integral solution to the field equations. The potential benefit of this approach is that it eliminates spatial derivatives that appear on the particle data, namely the current density, which is often calculated by linear combinations of low-order spline basis functions. This method is ideally suited to boundary integral equation methods that invert multi-dimensional operators without dimensional splitting techniques and will be the subject of future work. The third approach introduces a gauge correcting method that makes direct use of the gauge condition to modify the scalar potential and uses local maps for both the charge and current densities. This results in a gauge error, as the maps do not enforce the continuity equation. The vector potential coming from the current density is taken to be exact, and using the Lorenz gauge, we compute a correction to the scalar potential that makes the two potentials satisfy the gauge condition. This method also enforces the gauge condition to machine precision. We demonstrate two of the proposed methods in the context of periodic domains. Problems defined on bounded domains, including those with complex geometric features remain an ongoing effort. However, this work shows that it is possible to design computationally efficient methods that can effectively enforce the Lorenz gauge condition in a non-staggered PIC formulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

17 WIND ENERGY↗

DOE OSTI2022

The Quantum Condition Space

Abstract The fundamental properties of quantum physics are exploited to evaluate event probabilities with projection measurements. Next, to study what events can be specified by quantum methods, the concept of the condition space is introduced, which is found to be the dual space of the classical outcome space of bit strings. Like the classical outcome space generates the quantum state space, the condition space generates the quantum condition space being the central idea of this work. The quantum condition space permits the existence of entangled conditions having no classical equivalent. In addition, the quantum condition space is related to the quantum state space by a Fourier transform guaranteed by the Pontryagin duality, and therefore an entropic uncertainty principle can be defined. The quantum condition space offers a novel perspective of understanding quantum states with the duality picture. Furthermore, the quantum conditions have physical meanings and realizations of their own and thus may be studied for purposes beyond the original motivation of characterizing events for probability evaluation. Finally, the relation between the condition space and quantum circuits provides insights into how quantum states are collectively modified by quantum gates, which may lead to deeper understanding of the complexity of quantum circuits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Importance of turbulence-chemistry interactions at low temperature engine conditions

The role of turbulence-chemistry interaction in autoignition and flame stabilization is investigated for spray flames at low temperature combustion (LTC) conditions by performing high-fidelity three-dimensional computational fluid dynamics (CFD) simulations. A recently developed Tabulated Flamelet Model (TFM) is coupled with a large eddy simulation (LES) framework and validated across a range of Engine Combustion Network (ECN) ambient temperature conditions for n-dodecane fuel. High resolution grids with 0.0625 mm minimum cell size and 25 million total cell count are implemented using adaptive mesh refinement over the spray and combustion regions. Simulations with these grids and multiple LES realizations, with a 103 species n-dodecane mechanism show good agreement with experimental data for all the ambient conditions investigated. This modeling approach with the computational cost advantage of tabulated chemistry is then extended towards understanding the auto-ignition and flame stabilization at an ambient temperature of 750 K. These low temperature conditions lead to substantially higher ignition delays and flame liftoff lengths, and significantly leaner combustion compared to conventional high temperature diesel combustion. These conditions also require the simulations to span significantly larger temporal and spatial dimensions thereby increasing the computational cost. The TFM approach is able to capture autoignition and flame liftoff length at the low temperature conditions. Significant differences with respect to mixing, species formation and flame stabilization are observed under low temperature compared to conventional diesel combustion. At higher ambient temperatures, formation of formaldehyde is observed in the rich region (phi > 1) followed by the formation of OH in the stoichiometric regions. Under low temperature conditions, formaldehyde is observed to form at leaner regions followed by the onset of OH formation in significantly lean regions of the flame. Qualitative differences between species formation and transient flame development for the high and low temperature conditions are presented. The two stage ignition process is further investigated by studying the species formation in mixture fraction space by solving 1D flamelet equations for different scalar dissipation rates and homogeneous reactor assumption. Results show that scalar dissipation causes these radicals to diffuse within the mixture fraction space. As a result, this significantly enhances ignition and plays a dominant role at such low temperature conditions which cannot be captured by the homogeneous reaction assumption based model.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2014

Smoothed Particle Hydrodynamics Continuous Boundary Force method for Navier-Stokes equations subject to Robin boundary condition

Robin boundary condition for the Navier-Stokes equations is used to model slip conditions at the fluid-solid boundaries. A novel Continuous Boundary Force (CBF) method is proposed for solving the Navier-Stokes equations subject to Robin boundary condition. In the CBF method, the Robin boundary condition at boundary is replaced by the homogeneous Neumann boundary condition at the boundary and a volumetric force term added to the momentum conservation equation. Smoothed Particle Hydrodynamics (SPH) method is used to solve the resulting Navier-Stokes equations. We present solutions for two-dimensional and three-dimensional flows in domains bounded by flat and curved boundaries subject to various forms of the Robin boundary condition. The numerical accuracy and convergence are examined through comparison of the SPH-CBF results with the solutions of finite difference or finite element method. Taken the no-slip boundary condition as a special case of slip boundary condition, we demonstrate that the SPH-CBF method describes accurately both no-slip and slip conditions.

Pan, Wenxiao↗

DOE OSTI2012

The effect of chemical composition and austenite conditioning on the transformation behavior of microalloyed steels

In this investigation, by using continuous cooling torsion (CCT) testing, the transformation behavior of four microalloyed steels under two circumstances of austenite conditioning and non-conditioning was studied. A full scale hot-rolling schedule containing a 13-pass deformation was employed for the conditioning of the austenite. The CCT tests were then employed till temperature of {approx} 540 Degree-Sign C and the flow curves obtained from this process were analyzed. The initial and final microstructures of the steels were studied by optical and electron microscopes. Results show that alloying elements would decrease the transformation temperature. This effect intensifies with the gradual increase of Mo, Nb and Cu as alloying elements added to the microalloyed steels. As well, austenite conditioning increased the transformation start temperature due mainly to the promotion of polygonal ferrite formation that resulted from a pancaked austenite. The final microstructures also show that CCT alone would decrease the amount of bainite by inducing ferrite transformation in the two phase region. In addition, after the transformation begins, the deformation might result in the occurrence of dynamic recrystallization in the ferrite region. This could lead to two different ferrite grain sizes at the end of the CCT. Moreover, the Nb bearing steels show no sign of decreasing the strength level after the transformation begins in the non-conditioned situation and their microstructure is a mix of polygonal ferrite and bainite indicating an absence of probable dynamic recrystallization in this condition. In the conditioned cases, however, these steels show a rapid decrease of the strength level and their final microstructures insinuate that ferrite could have undergone a dynamic recrystallization due to deformation. Consequently, no bainite was seen in the austenite conditioned Nb bearing steels. The pancaking of austenite in the latest cases produced fully polygonal ferrite structures. - Highlights: Black-Right-Pointing-Pointer Adding alloying elements would decrease the transformation temperatures. Black-Right-Pointing-Pointer Austenite conditioning increases the transformation start temperature. Black-Right-Pointing-Pointer Deformation could induce the occurrence of dynamic recrystallization in ferrite region.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Bullying among children with heart conditions, National Survey of Children’s Health, 2018–2020

Abstract Children with chronic illnesses report being bullied by peers, yet little is known about bullying among children with heart conditions. Using 2018–2020 National Survey of Children’s Health data, the prevalence and frequency of being bullied in the past year (never; annually or monthly; weekly or daily) were compared between children aged 6–17 years with and without heart conditions. Among children with heart conditions, associations between demographic and health characteristics and being bullied, and prevalence of diagnosed anxiety or depression by bullying status were examined. Differences were assessed with chi-square tests and multivariable logistic regression using predicted marginals to produce adjusted prevalence ratios and 95% confidence intervals. Weights yielded national estimates. Of 69,428 children, 2.2% had heart conditions. Children with heart conditions, compared to those without, were more likely to be bullied (56.3% and 43.3% respectively; adjusted prevalence ratio [95% confidence interval] = 1.3 [1.2, 1.4]) and bullied more frequently (weekly or daily = 11.2% and 5.3%; p < 0.001). Among children with heart conditions, characteristics associated with greater odds of weekly or daily bullying included ages 9–11 years compared to 15–17 years (3.4 [2.0, 5.7]), other genetic or inherited condition (1.7 [1.0, 3.0]), ever overweight (1.7 [1.0, 2.8]), and a functional limitation (4.8 [2.7, 8.5]). Children with heart conditions who were bullied, compared to never, more commonly had anxiety (40.1%, 25.9%, and 12.8%, respectively) and depression (18.0%, 9.3%, and 4.7%; p < 0.01 for both). Findings highlight the social and psychological needs of children with heart conditions.

Cardiovascular System & Cardiology↗

DOE OSTI2012

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2017

Impact of assembly-specific conditions on BWR burnup credit

Because boiling water reactors use control blades during operation, there can be significant changes to the local axial power shape, coolant density profile, and other parameters when the blades are inserted. Previous work examined the reactor operating parameters that impact cask reactivity. These previous studies identified limiting conditions for fuel cask reactivity or the direction of trends with cask reactivity (e.g., lower coolant densities result in higher cask reactivity). However, using limiting conditions for all parameters simultaneously is unrealistic. When the control blades are inserted deeply into the reactor - a limiting condition - the power is reduced and the void fraction decreases - a less limiting condition. This paper identifies the impacts of using assembly-specific conditions for control blade history, coolant density profile, burnup profile, and fuel temperature profile. Results indicate that cask reactivity is reduced when using assembly-specific operating conditions versus combining limiting conditions for the individual parameters of interest. The magnitude of reactivity reduction for using assembly- specific conditions varies based on each assembly and its operating conditions. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2019

The role of soil redox conditions in microbial phosphorus cycling in humid tropical forests

Humid tropical forests are among the most productive ecosystems globally, yet they often occur on soils with high phosphorus (P) sorption capacity, lowering P availability to biota. Short-term anoxic events are thought to release sorbed P and enhance its acquisition by soil microbes. However, the actual effects of anoxic conditions on microbial P acquisition in humid tropical forest soils are surprisingly poorly studied. We used laboratory incubations of bulk soils, NanoSIMS analysis of single microbial cells, and landscape-scale measurements in the Luquillo Experimental Forest (LEF), Puerto Rico to test the hypothesis that anoxic conditions increase microbial P acquisition in humid tropical forests. In laboratory and field experiments, we found that microbial P uptake generally decreased under anoxic conditions, leading to high microbial carbon (C) to P ratios in anoxic soils. The decreased P acquisition under anoxic conditions was correlated with lower microbial C use efficiency (CUE), an index of microbial energy transfer in ecosystems. Phosphorus amendments to anoxic soils led to increased microbial P uptake and higher CUE suggesting that microbes were less able to access and utilize P under natural low redox conditions. Under oxic conditions, microbial C:P ratios and CUE did not respond to changes in substrate stoichiometry. These results challenge the existing paradigm by showing that anoxic conditions can decrease microbial P uptake and ultimately constrain microbial CUE. Finally, our findings indicate that soil redox conditions tightly couple soil P and C cycles and advance our understanding of controls on P cycling in humid tropical forest ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Injury severity analysis of truck-involved crashes under different weather conditions

This paper investigates truck-involved crashes to determine the statistically significant factors that contribute to injury severity under different weather conditions. The analysis uses crash data from the state of Ohio between 2011 and 2015 available from the Highway Safety Information System. To determine if weather conditions should be considered separately for truck safety analyses, parameter transferability tests are conducted; the results suggest that weather conditions should be modeled separately with a high level of statistical confidence. To this end, three separate mixed logit models are estimated for three different weather conditions: normal, rain and snow. The estimated models identify a variety of statistically significant factors influencing the injury severity. Different weather conditions are found to have different contributing effects on injury severity in truck-involved crashes. Rural, rear-end and sideswipe crash parameters were found to have significantly different levels of impact on injury severity. Based on the findings of this study, several countermeasures are suggested: 1) safety and enforcement programs should focus on female truck drivers, 2) a variable speed limit sign should be used to lower speeds of trucks during rainy condition, and 3) trucks should be restricted or prohibited on non-interstates during rainy and snowy conditions. These countermeasures could reduce the number and severity of truck-involved crashes under different weather conditions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Application of Cable Condition Monitoring Technologies to Assess Age-Related Degradation of Industrial Cables Installed in Harsh Environments

The aging of electrical cables has been the subject of substantial research and development (R&D) projects performed by national and international laboratories, universities, and private organizations for many years. This R&D was conducted to develop guidance, equipment, and techniques to support aging management of in-service cables in industrial facilities such as nuclear power plants, research reactors, waste facilities, and fuel fabrication plants. Through these research efforts, condition monitoring technologies have been developed that can determine the severity of age-related degradation that occurs in industrial cables and insulation polymers during service. This paper summarizes the results of aging assessments that were performed for cables installed in two U.S. nuclear power plants, one a pressurized water reactor and one a boiling water reactor. These cables had been in service for over 40 years and during plant operation were exposed to harsh environmental conditions including elevated temperatures and radiation. For these assessments, a comprehensive series of measurements was performed to assess the aged condition of the cables. These cables came from different manufacturers, were manufactured in different years, and were constructed with a variety of jacket and insulation polymers including chloro-sulfonated polyethylene (CSPE), cross-linked polyethylene (XLPE)/cross-linked polyolefin (XLPO), neoprene, and ethylene propylene rubber (EPR). The goal of these assessments was to determine the current aged condition of the cable polymers and provide an estimate of how long the cable insulation materials could remain exposed to their in-service environmental conditions before reaching their end-of-life condition. Both nuclear power plants have received license renewals to extend their operation from 40 to 60 years, and the utilities need objective evidence to show that critical components such as cables will be able to function safely and reliably during the extended operating period. Furthermore, the results of these assessments showed that the cables exhibited different aged conditions depending on the type of polymers they were constructed with and the environment they were exposed to during service. Some of the cables and insulation polymers showed signs of significant age-related degradation and were estimated to have approximately 5 years of remaining service life. Other cables exhibited no signs of significant age-related degradation and were estimated to have 50 years or more of remaining service life. Using the results of these cable aging assessments, plant personnel were able to (1) determine the overall aged condition of cables and insulation polymers using objective test results, (2) identify aged or degraded cables before they caused operability issues, and (3) avoid unnecessary and costly replacement of cables that can continue to operate safely and reliably.

36 MATERIALS SCIENCE↗

DOE OSTI2012

Technetium Sorption by Cementitious Materials Under Reducing Conditions

The objective of this study was to measure Tc sorption to cementitious materials under reducing conditions to simulate Saltstone Disposal Facility conditions. Earlier studies were conducted and the experimental conditions were found not to simulate those of the facility. Through a five month subcontract with Clemson University, sorption of 99 Tc to four cementitious materials was examined within an anaerobic glovebag targeting a 0.1% H 2 (g)/ 99.9% N 2 (g) atmosphere. Early experiments based on Tc sorption and Eh indicated that 0.1% H 2 (g) (a reductant) was necessary to preclude experimental impacts from O 2 (g) diffusion into the glovebag. Preliminary data to date (up to 56 days) indicates that sorption of 99 Tc to cementitious materials increased with increasing slag content for simulated saltstone samples. This is consistent with the conceptual model that redox active sulfide groups within the reducing slag facilitate reduction of Tc(VII) to Tc(IV). These experiments differ from previous experiments where a 2% H 2 (g) atmosphere was maintained (Kaplan et al., 2011 (SRNL-STI-2010-00668)). The impact of the 2% H 2 (g) reducing atmosphere on this data was examined and determined to cause the reduction of Tc in experimental samples without slag. In the present ongoing study, after 56 days, Tc sorption by the 50-year old cement samples (no slag) was undetectable, whereas Tc sorption in the cementitious materials containing slag continues to increase with contact time (measured after 1, 4, 8, 19 and 56 days). Sorption was not consistent with spike concentrations and steady state has not been demonstrated after 56 days. The average conditional K d value for the Vault 2 cementitious material was 6,362 mL/g (17% slag), for the TR547 Saltstone (45% slag) the conditional K d was 1258 mL/g, and for TR545 (90% slag) the conditional K d was 12,112 mL/g. It is anticipated that additional samples will be collected until steady state conditions are established to permit measuring more representative K d and solubility values under these experimental conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Operational-Condition-Independent Criteria Dedicated to Monitoring Wind Turbine Generators: Preprint

To date the existing wind turbine condition monitoring technologies and commercially available systems have not been fully accepted for improving wind turbine availability and reducing their operation and maintenance costs. One of the main reasons is that wind turbines are subject to constantly varying loads and operate at variable rotational speeds. As a consequence, the influences of turbinefaults and the effects of varying load and speed are coupled together in wind turbine condition monitoring signals. So, there is an urgent need to either introduce some operational condition de-coupling procedures into the current wind turbine condition monitoring techniques or develop a new operational condition independent wind turbine condition monitoring technique to maintain high turbineavailability and achieve the expected economic benefits from wind. The purpose of this paper is to develop such a technique. In the paper, three operational condition independent criteria are developed dedicated for monitoring the operation and health condition of wind turbine generators. All proposed criteria have been tested through both simulated and practical experiments. The experimentshave shown that these criteria provide a solution for detecting both mechanical and electrical faults occurring in wind turbine generators.

17 WIND ENERGY↗

DOE OSTI2022

Research needs targeting direct air capture of carbon dioxide: Material & process performance characteristics under realistic environmental conditions

The extraction of CO 2 from ambient air, or direct air capture (DAC), is a crucial negative CO 2 emissions technology with great potential for contributing to the mitigation of global warming and climate change. Furthermore, nearly all published research on DAC has been conducted under indoor temperature conditions, i.e. 20 to 30 °C. In contrast, the future global implementation of DAC requires it to be operational across a wide expanse of geographical areas, of which the local temperatures can vary between -30 to 50 °C. Similarly, the absolute humidity can vary from ~0 to 84 g/m 3 in various locations. Due to the massive amount of air that would be processed, it may be impractical to preheat or dehumidify the air before the CO 2 separation. Therefore, it is important to develop DAC materials with good performance at realistic outdoor conditions, especially at sub-ambient conditions, i.e. -30 to 20 °C. In addition to material development, system-level studies at sub-ambient conditions are also needed for the DAC processes to reach optimal designs, which may be very different from those at ambient conditions. In this perspective article, we first assess the literature to identify the technical gaps that need to be filled for DAC to be applicable at realistic outdoor conditions. We then suggest additional research directions needed for DAC to be viable under varied conditions from the perspectives of materials and system designs. For materials, we discuss the expected physical and chemical property changes for the sorbents when the temperature or humidity reaches extremes within their range, and how that will impact performance. Similarly, for system design, we indicate how varied conditions will impact performance and how these changes will impact process optimization.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Adversarial sampling of unknown and high-dimensional conditional distributions

Many engineering problems require the prediction of realization-to-realization variability or a refined description of modeled quantities. In that case, it is necessary to sample elements from unknown high-dimensional spaces with possibly millions of degrees of freedom. While there exist methods able to sample elements from probability density functions (PDF) with known shapes, several approximations need to be made when the distribution is unknown. In this paper the sampling method, as well as the inference of the underlying distribution, are both handled with a data-driven method known as generative adversarial networks (GAN), which trains two competing neural networks to produce a network that can effectively generate samples from the training set distribution. In practice, it is often necessary to draw samples from conditional distributions. When the conditional variables are continuous, only one (if any) data point corresponding to a particular value of a conditioning variable may be available, which is not sufficient to estimate the conditional distribution. This work handles this problem using an a priori estimation of the conditional moments of a PDF. Herein, two approaches, stochastic estimation, and an external neural network are compared for computing these moments; however, any preferred method can be used. The algorithm is demonstrated in the case of the deconvolution of a filtered turbulent flow field. It is shown that all the versions of the proposed algorithm effectively sample the target conditional distribution with minimal impact on the quality of the samples compared to state-of-the-art methods. Additionally, the procedure can be used as a metric for the diversity of samples generated by a conditional GAN (cGAN) conditioned with continuous variables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

A framework for characterizing the ambient conditions experienced by light duty vehicles in the United States

The relationship between ambient conditions and light-duty vehicle energy consumption has been widely researched. Relatively little effort, however, has been dedicated to understanding representative ambient conditions a light-duty vehicle may experience. As such, the framework introduced in this article provides a means of quantifying ambient conditions specific to light-duty vehicle operation by incorporating both when and where vehicles are driven. The analysis presented expands the literature beyond solely focusing on temperature; distributions for humidity, solar irradiance, and air density are also included. A procedure is presented that calculates the ambient condition distributions for each metric by relating open-source data sets describing representative vehicle utilization and representative ambient conditions. While this study explores ambient conditions related to light-duty vehicle utilization, the framework may also be applied to separate vocations. Finally, the article concludes with an example use case of the ambient condition weighting process. A binning methodology is introduced that facilitates insight into vehicle energy consumption in response to ambient conditions at the national and local levels while minimizing the number of tests or simulations required.

33 ADVANCED PROPULSION SYSTEMS↗