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At least 289 records · Page 16

Production of Heavy α -Elements and 44 Ti in Cas A: Comparison to Abundances from 1D Core-collapse Supernova Models and Evidence for Carbon–Oxygen Shell Mergers

The merger between the carbon (C) and oxygen (O) shells hours to days before the collapse of a massive star significantly changes its nucleosynthesis, which is reflected in the elemental ratios observed in supernova remnants (SNRs). We present a nucleosynthesis study of 44 Ti production in core-collapse supernovae (CCSNe), highlighting large silicon (Si), sulfur (S), calcium (Ca), and, most importantly, argon (Ar) to neon (Ne) ratios as diagnostics for carbon–oxygen (C–O) shell mergers. We compare yields from eight different sets of CCSNe models to observations of Cassiopeia A (Cas A), and show that C–O shell mergers are consistently the models that best match X-ray and infrared observations. These models produce high Ar/Ne ratios (≳0.1), due to 20 Ne depletion and production of 36 Ar and 38 Ar, while lower ratios are obtained from nonmerger cases. Based on the Ar/Ne diagnostic, we compare the range of expected 44 Ti produced by C–O shell mergers, which is up to ∼20%–30% of the overall 44 Ti, but expected to be located outside the reverse shock. Based on the sets of models considered, the photon flux expected from the 44 Ti synthesized in the C–O shell merger in Cas A is below the NuSTAR and COSI detection limits, compatible with current limits locating most of the 44 Ti interior to the reverse shock, but might be detectable from proposed missions like ASCENT. Finally, for the SNR of 1987A, a dominant C–O merger origin of the observed 44 Ti is unlikely based on the observed redshift in its 44 Ti line.

79 ASTRONOMY AND ASTROPHYSICS↗

Synergistic effect of microstructure and defects on the initiation of fatigue cracks in additively manufactured Inconel 718

Fatigue cracks in additively manufactured (AMed) Inconel 718 (IN-718) in machined surface condition often initiate from persistent slip bands (PSBs) unlike other popular AM alloys such as 17-4 PH stainless steel or Ti-6Al-4V, where fatigue crack initiation is exclusively from volumetric defects; therefore, a competition between PSB- vs. defect- mediated crack initiation clearly exists. To shed light on the factors governing the competition, this study investigates the characteristics of cyclic strain localization, PSB formation, and crack initiation via crystal plasticity (CP) modeling of cyclic loading on polycrystalline aggregates which are then validated by experiments. In this work, a physics-based, free slip distance (FSD) dependent slip strength evolution law is proposed, which is shown to enable the CP model to simulate the heterogeneous strain distribution in IN-718. Implementing a crack initiation criterion based on strain contrast, the locations and lives for crack initiation can also be calculated. It is shown that both FSD and resolve shear stress influence the strain localization and crack initiation behaviors. The distribution of a localization parameter calculated based on the multiplication of FSD and Schmid factor within a grain is found to correlate well with the locations of PSBs. The maximum values of the localization parameters within a microstructure are shown to correlate well with the experimentally obtained crack initiation lives. The presence of volumetric defects in IN-718 generally do not impact strain localization behavior unless their size is large compared to the grain size.

42 ENGINEERING↗

Locating Seismic Events with Local-Distance Data

As the seismic monitoring community advances toward detecting, identifying, and locating ever-smaller natural and anthropogenic events, the need is constantly increasing for higher resolution, higher fidelity data, models, and methods for accurately characterizing events. Local-distance seismic data provide robust constraints on event locations, but also introduce complexity due to the significant geologic heterogeneity of the Earth’s crust and upper mantle, and the relative sparsity of data that often occurs with small events recorded on regional seismic networks. Identifying the critical characteristics for improving local-scale event locations and the factors that impact location accuracy and reliability is an ongoing challenge for the seismic community. Using Utah as a test case, we examine three data sets of varying duration, finesse, and magnitude to investigate the effects of local earth structure and modeling parameters on local-distance event location precision and accuracy. We observe that the most critical elements controlling relocation precision are azimuthal coverage and local-scale velocity structure, with tradeoffs based on event depth, type, location, and range.

42 ENGINEERING↗

Adaptive Determination of the Optimal Exchange Location in Wall-Modeled Large-Eddy Simulation

Wall-modeled large-eddy simulation introduces a modeling interface (or exchange location) separating the wall-modeled layer from the rest of the domain. The current state-of-the-art is to rely on user expertise when choosing where to place this modeling interface, whether this choice is tied to the grid or not. This paper presents a postprocessing algorithm that determines the exchange location systematically. The algorithm is based on a model for the error in the predicted wall shear stress and a model for the computational cost, and then finds the exchange location that minimizes a combination of the two. Here, the algorithm is tested both a priori and a posteriori using an equilibrium wall model for the flow over a wall-mounted hump, a boundary layer in an adverse pressure gradient, and a shock/boundary-layer interaction. The algorithm produces exchange locations that mostly agree with what an experienced user would suggest, with thinner wall-modeled layers in nonequilibrium flow regions and thicker wall-modeled layers where the boundary layer is closer to equilibrium. This suggests that the algorithm should be useful in simulations of realistic and highly complex geometries.

42 ENGINEERING↗

A taxonomy of systems that combine utility-scale renewable energy and energy storage technologies

Interest in renewable energy-based hybrid systems—which combine multiple renewable energy and/or energy storage technologies—is apparent and growing. Such systems could play an important role in the grid of the future, but our ability to quantify their potential impacts is hindered by (a) the inconsistent treatment of hybrid systems and (b) an incomplete understanding of which aspects of hybridization will have the greatest influence. In this article, we review the literature and propose an organization scheme for utility-scale hybrid systems in which electricity is generated from commercially available, renewable energy technologies, and electricity is the only output. Based on this literature review, we propose three categories for delineating systems that link multiple renewable energy and/or energy storage technologies: co-located resources (locational linkage only), virtual power plants (operational linkage only), and full hybrids (location and operational linkages). Proposing a categorization based on whether the systems involve locational and/or operational linkages reflects the fact that technology combinations do not represent a meaningful delineation. In addition, the categories are ideal for informing model development efforts, by identifying the unique characteristics that must be captured in adequate representations of systems that fall under each category. Our categories can also help inform policy considerations, as they delineate system characteristics that would introduce distinct permitting, siting, interconnection, and policy challenges. Therefore, we believe that our proposed taxonomy will help organize thinking and research efforts in a way that will enable consistent evaluation of the costs, values, and potential of renewable energy-based hybrids.

25 ENERGY STORAGE↗

Examination of Humidity and Ice Supersaturation Profiles Over West Antarctica Using Ground-Based G-Band Radiometer Retrievals

Humidity profiles retrieved from a ground-based millimeter-wave radiometer located at McMurdo Station, Antarctica and the West Antarctica Ice Sheet Divide are presented and their suitability to study the humidity of the polar climate is assessed. The dry conditions of the Antarctic winter and spring are ideal for ground-based millimeter-wave measurements and the retrievals appear to realistically reproduce the spatial and temporal variability of humidity at both sites. Furthermore, the radiometer has the ability to capture daily variability of very low humidity (0.5 to 4 g/kg) in the low-to-mid troposphere with an uncertainty of 10-20% during the Antarctic winter, spring, and summer. Despite the coarse vertical resolution (200-600 m in the first 4 km), the retrievals provide additional information with respect to the European Centre for Medium Range Weather Forecasts (ECMWF) profiles used as background information. The radiometer is also able to realistically identify the location and frequency of supersaturated layers with respect to ice in the mid troposphere. The occurrence of supersaturated layers is correlated with the occurrence of ice clouds identified by a cloud mask. Overall, results show that ground-based microwave and millimeter-wave radiometry is a viable complement to satellite observations to provide continuous information on the thermodynamic state of the low-to-mid troposphere at high latitudes.

54 ENVIRONMENTAL SCIENCES↗

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Impulse Noise Sampling at 9965 - 300-pound energetic experimant

On October 1, 2022, sound level measurements were taken at various locations throughout Kirtland Air Force Base (KAFB) and Southeastern Albuquerque. The purpose was to support sound propagation modeling predictions and sound regulations for public exposure during the detonation of an approximately 300-pound energetic experiment. Ground Zero was located on Range 7 of Sandia Thunder Range (06647). A total of 8 measurement locations were identified (e.g., 5 on KAFB and 3 in the Southeastern Albuquerque neighborhoods).

42 ENGINEERING↗

Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction

The long-term operation (LTO) of nuclear power plants (NPP) beyond their original design life of 40 years can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition, the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Requiring frequent NDE inspections may lead to frequent NPP shutdowns which can lead to power outages and additional NDE inspection cost-related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing a more digital approach such as using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. The DT framework is based on limited experimental data, Artificial-intelligence (AI)-Machine-Learning (ML) and multiphysics-computationalmechanics such as finite element- (FE) based models. Given the real-time thermal-hydraulic process measurements from several existing plant sensors, the overall goal of the DT framework is to predict the cumulative usages factors or equivalent fatigue lives in real time and at any random 3D location of the components. This includes inaccessible locations such as inside the thickness or location of a component. This prediction can be at thousands to millions of 3D point clouds or locations like conventional FE-based models, but without running an FE model in real time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Systems and methods for evaluating electrolyte wetting and distribution

Systems and techniques for measuring process characteristics including electrolyte distribution in a battery cell. A non-destructive method for analyzing a battery cell includes determining acoustic features at two or more locations of the battery cell, the acoustic features based on one or more of acoustic signals travelling through at least one or more portions of the battery cell during one or more points in time or responses to the acoustic signals obtained during one or more points in time, wherein the one or more points in time correspond to one or more stages of electrolyte distribution in the battery cell. One or more characteristics of the battery cell are determined based on the acoustic features at the two or more locations of the battery cell.

Dou, Shan↗

Urban Parameters Washington, DC 100m

132 Urban parameters based on building physical dimensions and location were generated for Washington, District of Columbia at 100m resolution using the NATURF model. To use the binary file with WRF, the binary file and the index file must be placed in their own directory in WRF_GEOG and accessed in the same way NUDAPT44 would be accessed.

Dumas, Melissa [ORNL] (ORCID:0000000233190846)↗

Nanocomposite Materials for Radionuclide Sequestration from Groundwater Environments

The half-lives of radionuclides range from fractions of a second to billions of years. Since no practical method of altering radioactive decay exists, and since exposure to either the energy emitted from radioactive decay or chemical properties of radionuclides poses dire health risks, radioactive materials must be segregated and controlled. The capture, treatment, and disposition of radioactive materials remain an extraordinary challenge. In here, we focus our attention on the synthesis and characterization of a unique class of nanocomposite materials that have potential for removal of radionuclide contamination. Specifically, we report a simple approach to decorate the surface of iron-based (Fe/FexOy) material with various nano-catalysts. Specifically, copper (Cu), tin (Sn), and silver (Ag) nanoparticles were prepared through two different reduction approaches, namely, citrate and cetyltrimethylammonium bromide (CTAB) methods, on the iron-based material surface. All samples were characterized by a variety of analytical tools, which included scanning electron microscopy (SEM), electron-dispersive X-ray microanalysis (EDS), and EDS mapping to elucidate materials’ morphology as well as nano-catalysts’ loading and location on the iron-based structures.

Hunyadi Murph, Simona E.↗

Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach

Abstract The macroscopic fundamental diagram (MFD) captures an orderly relationship among traffic flow, density, and speed at the network level. It is a simple yet powerful tool for modeling traffic dynamics in large urban networks with broad application in traffic control and management. However, empirically derived MFDs in urban regions require high-resolution traffic data from the network. Having the network flow and vehicular density estimated at the (granular) census tract level using vehicle probe data, we apply machine learning methods to predict the MFDs across U.S. urban areas and capture the impacts of location-specific input features on the network flow–density relationships at a large scale. The results show that, among the four tested machine learning approaches (Random Forest, XGBoost, Support Vector Machine, and Neural Network), XGBoost delivers the best performance in predicting network traffic flow based on vehicular density and location attributes. Using interaction Shapley Additive explanation (SHAP) values and partial correlation analysis, we examine the factors influencing MFD shapes across different locations. Our empirical findings reveal that across U.S. urban areas, network topology, transportation infrastructure, and land use are primary factors shaping MFD curves, while demand and trip-related factors play a lesser role. Specifically, higher ranking roads, centrality, and development levels correlate positively with network capacity and critical density, whereas negative associations are observed for network connectivity, mixed-use development, and road roughness levels.

Jin, Ling↗

Characterization of Gulf Stream energy resources: A 30-year high-resolution simulation study

The strength and proximity of the Gulf Stream (GS) along the U.S. coast offers opportunities for marine energy extraction. Leveraging high-resolution (up to 400 m) long-term (30-year) hindcasts based on an unstructured grid model, this study characterizes the energy potential of the GS in two viable locations: the Florida Straits (FS) and Cape Hatteras (CH). Results reveal distinct characteristics in the kinetic energy flux (KEF) and kinetic energy density (KED) for the two regions. The 30-year mean KEF at CH is 27.50 GW, surpassing the 19.74 GW estimated for the FS, which is attributed to the wider cross-section of the GS in CH. Additionally, CH exhibits higher KEF variability due to GS’s larger path shifts and meanders. Estimated KEDs at ADCP site locations reach up to 2,908 W/m 2 in the FS and 1,512 W/m 2 in the CH at a depth of 20 m. High-energy zones are closer to shore in the FS, whereas energy-rich areas at CH are located further offshore. A depth-based KED analysis shows significant decreases across typical energy extraction depths (20 to 100 m), with reductions up to 44%. Finally, this study provides high-resolution resource characterization, forming a foundation for optimized site selection and marine hydrokinetic system design.

16 TIDAL AND WAVE POWER↗

Thermal measurement apparatus and methods for anisotropic thermal materials

A system for characterizing thermal properties of thermally anisotropic heterogeneous samples includes a heating element, a first temperature sensing device, a second temperature sensing device, and a computing system. The heating element is positioned at a first location within a sample and heats the sample. The first temperature sensing device outputs data indicative of temperatures of the first location to the computing device. The second temperature sensing device outputs data indicative of temperatures of the second location to the computing device. The computing device computes a thermal conductivity of the sample based upon the temperatures of the first location. The computing device further outputs an indication of a portion of the sample to which the thermal conductivity pertains based upon the second temperatures.

Reyes, Karla Rosa↗

Thermal measurement apparatus and methods for anisotropic thermal materials

A system for characterizing thermal properties of thermally anisotropic heterogeneous samples includes a heating element, a first temperature sensing device, a second temperature sensing device, and a computing system. The heating element is positioned at a first location within a sample and heats the sample. The first temperature sensing device outputs data indicative of temperatures of the first location to the computing device. The second temperature sensing device outputs data indicative of temperatures of the second location to the computing device. The computing device computes a thermal conductivity of the sample based upon the temperatures of the first location. The computing device further outputs an indication of a portion of the sample to which the thermal conductivity pertains based upon the second temperatures.

Reyes, Karla Rosa↗

Modeling for a Digital Twin-Based Remote Operation System Framework

New reactor designs and technologies are being developed to grow and advance the nuclear industry. Microreactors are one of the many new concepts for advancing the industry. Microreactors are very small reactors generally designed to have an operating power of 20 MWth or less. They are ideal for many applications in which it would not be feasible to have a large-scale reactor, such as powering remote communities, military bases, and mining sites. Many of these applications currently rely on diesel generators for power, and replacing those generators with the carbon-free energy of a microreactor is a major driving factor for microreactor development. However, most of the use cases for microreactors are in isolated locations where construction and labor costs are much higher. Microreactors will need to be comparable to other energy production methods for their deployment to be successful. Remotely operating the microreactor has a great potential to benefit the economics and make it more cost competitive. With remote operations, the operation facility location could be strategically chosen based on factors such as construction costs, workforce size, etc. The benefits of remote operations could be leveraged even more if the remote operation system is semi-autonomous. If the remote operation system is semi-autonomous, more microreactors could be operated and monitored from one remote operation facility. Additionally, with the system handling some tasks for the human operator, it could reduce the number of operating staff necessary for the microreactor. Digital twins can be used to introduce a level of automation to the remote operation system. Digital twins are capable of component monitoring, system operation and control, and predictive performance [1]. All of those features are important for a successful semi-autonomous remote operation system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Time Series Classification for Locating Forced Oscillation Sources

Here, this article presents a machine learning based time-series classification method for using synchrophasor measurements to locate the source of forced oscillation (FO) for fast disturbance removal. First, multivariate time series (MTS) matrices are constructed by the most informative measurements selected by sequential feature selection from each power plant. Then, the Mahalanobis matrix is trained such that the Mahalanobis distance between the MTSs from the same class (i.e., with the same FO source location) are minimized and from different classes (i.e., with different FO source locations) are maximized. This allows MTSs to be classified by classifiers with class membership corresponding to the location of each FO source. To meet the runtime requirements of online matching, class templates are constructed to reduce data size and improve matching efficiency. To account for uncertainty in identifying the exact beginning of an FO event, dynamic time warping is used to align the out-of-sync MTSs. IEEE 39bus and WECC 179bus systems are used for algorithm development and validation. Simulation results demonstrate that the algorithm meets online operation runtime requirement with high accuracy using misaligned data sets.

42 ENGINEERING↗