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At least 955 records · Page 53

Few-cycle optical field breakdown and damage of gallium oxide and gallium nitride

Both gallium oxide and gallium nitride have great potential for use as high power transparent conducting oxide materials for a wide range of optoelectronic applications. It is, therefore, important to determine the dynamic optical field breakdown for these materials. Here, we report laser damage thresholds for Ga 2 O 3 and GaN using 9 fs few-cycle pulses with a center wavelength near 760 nm. We determine laser-induced damage thresholds (LIDTs) for both single pulse and multi-pulse exposures, with multi-pulse LIDT showing significant reduction compared to single pulse LIDT (in some cases, >50%), possibly due to laser-induced defects. We show that Ga 2 O 3 and GaN have an ultrafast optical field breakdown of 23 and 18 GV/m when nearly polarized along their [010] and [111] planes, respectively, extending their suitability for high power applications to the ultrashort pulse regime. To accurately characterize the excited carrier density criteria in which apparent laser damage occurs, carrier excitation dynamics for the entire laser pulse interaction were simulated using a modified Keldysh ionization model. For the measured single-shot threshold fluences, the plasma critical density was surpassed by 2 orders of magnitude and 2D finite-difference time-domain simulations were employed to understand the pulse interaction near the surface.

Tripepi, Michael↗

Experimental Characterization of Gas Turbine Emissions at Simulated Flight Altitude Conditions

NASA's Atmospheric Effects of Aviation Project (AEAP) is developing a scientific basis for assessment of the atmospheric impact of subsonic and supersonic aviation. A primary goal is to assist assessments of United Nations scientific organizations and hence, consideration of emissions standards by the International Civil Aviation Organization (ICAO). Engine tests have been conducted at AEDC to fulfill the need of AEAP. The purpose of these tests is to obtain a comprehensive database to be used for supplying critical information to the atmospheric research community. It includes: (1) simulated sea-level-static test data as well as simulated altitude data; and (2) intrusive (extractive probe) data as well as non-intrusive (optical techniques) data. A commercial-type bypass engine with aviation fuel was used in this test series. The test matrix was set by parametrically selecting the temperature, pressure, and flow rate at sea-level-static and different altitudes to obtain a parametric set of data.

GAS TURBINES↗

Simulating regional workforce impacts of decarbonizing integrated steelmaking

Global efforts to mitigate climate change are increasing pressure on heavy manufacturing industries to decarbonize production. The iron and steel industry is responsible for 7% of CO 2 emissions globally (2% in the United States) and is often a major employer in the regions where iron and steel is produced. Understanding the future prospects for workers in regions with high CO 2 emitting industries—including impacts of phasing out or evolving such industries—will be critical for informing regional economic and clean energy strategies. We simulate the impact of an “in-place” transition that replaces today’s integrated production with direct reduced iron (DRI) used in electric arc furnaces (EAFs), using Southwest Pennsylvania as an application of our generalizable approach. Our results suggest that the integrated steelmaking workforce today has the skills, knowledge, and abilities (SKAs) to fill over 95% of all jobs required by DRI/EAF facilities, but the number of jobs is only 25% of those at integrated plants. We also find that some occupational groups have greater general transferability into the broader job market, while other groups, such as production workers, are ill-equipped today based on current SKAs to transition out of the iron and steel industry. Our methodology further suggests factors that limit transitions: Around 85% of occupations are more limited by missing skills, while 15% are more limited by insufficient wages. These results may help to improve the design of social policy and the targeting of retraining programs, while the simulation approach can be readily adapted for other regions and industries.

decarbonization↗

End-to-End Simulations of a 3.4-Meter Detector Wall for Neutron-Diagnosed Subcritical Experiments

The Nevada National Security Site, together with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, is developing a novel diagnostic to measure the reactivity of subcritical experiments. This capability is known as neutron-diagnosed subcritical experiments. The decay of the fission gamma rays from the neutron-interrogated subcritical experiment is measured as a function of time with a large (~3-meter diameter) detector wall consisting of 151 individual detector pixels. The data from this current mode measurement inform the neutron multiplication factor, keff, and thus the relative reactivity of the subcritical experiment. The Nevada National Security Site developed the Gamma Array Simulation Toolkit initially to help inform the design of the individual detector pixels and the 3.4-meter diameter detector wall to be fielded as part of neutron-diagnosed subcritical experiments. This toolkit is now being used to simulate and predict the performance of the final design of the individual detector pixels and the aggregate detector wall. Additionally, key detector characteristics evaluated from these simulations include impulse response, pulse height spectrum, number of photoelectrons per MeV, detector efficiency, and cross talk between detector pixels. Collectively, the results of these simulations inform how well the fission gamma ray die-off distribution from a neutron-diagnosed subcritical experiment measurement can be resolved. This is critical to determining the relative reactivity of the experiment. Furthermore, the Gamma Array Simulation Toolkit can be used to aid in the analysis of the experimental data from a neutron-diagnosed subcritical experiment measurement once the simulation has been benchmarked.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Low Earth Orbit satellite traffic simulator

This paper describes a significant tool for Low Earth Orbit (LEO) capacity analysis, needed to support marketing, economic, and design analysis, known as a Satellite Traffic Simulator (STS). LEO satellites typically use multiple beams to help achieve the desired communication capacity, but the traffic demand in these beams in usually not uniform. Simulations of dynamic, average, and peak expected demand per beam is a very critical part of the marketing, economic, and design analysis necessary to field a viable LEO system. An STS is described in this paper which can simulate voice, data and FAX traffic carried by LEO satellite beams and Earth Station Gateways. It is applicable world-wide for any LEO satellite constellations operating over any regions. For aeronautical applications to LEO satellites. the anticipates aeronautical traffic (Erlangs for each hour of the day to be simulated) is prepared for geographically defined 'area targets' (each major operational region for the respective aircraft), and used as input to the STS. The STS was designed by Constellations Communications Inc. (CCI) and E-Systems for usage in Brazil in accordance with an ESCA/INPE Statement Of Work, and developed by Analytical Graphics Inc. (AGI) to execute on top of its Satellite Tool Kit (STK) commercial software. The STS simulates constellations of LEO satellite orbits, with input of traffic intensity (Erlangs) for each hour of the day generated from area targets (such as Brazilian States). accumulated in custom LEO satellite beams, and then accumulated in Earth Station Gateways. The STS is a very general simulator which can accommodate: many forms of orbital element and Walker Constellation input; simple beams or any user defined custom beams; and any location of Gateways. The paper describes some of these features, including Manual Mode dynamic graphical display of communication links, to illustrate which Gateway links are accessible and which links are not, at each 'step' of the satellite orbit. In the two Performance Modes, either Channel capacity or Grade Of Service (GOS) for objects (Satellite beams, Gateways, and an entire satellite) are computed respectively by standard traffic table capacity lookup and blocking probability equations. GOS can be input, with number of channels calculated, or number of channels can be input, with GOS calculated. Also described are some of the STS Test Procedure approach and results. AGI plans to make the STS features available through their normal commercial STK products. E-Systems is a co-developer, tester, and user of the STS. The Test Procedure for the STS was prepared by E-Systems, as an independent tester for CCI, to support the CCI delivery of the STS to ESCA, for their customer INPE.

Hoelzel, John↗

End-to-End Simulations of a 3.4-Meter Detector Wall for Neutron-Diagnosed Subcritical Experiments

The Nevada National Security Site, together with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, is developing a novel diagnostic to measure the reactivity of subcritical experiments. This capability is known as neutron-diagnosed subcritical experiments. The decay of the fission gamma rays from the neutron-interrogated subcritical experiment is measured as a function of time with a large (~3-meter diameter) detector wall consisting of 151 individual detector pixels. The data from this current mode measurement inform the neutron multiplication factor, keff, and thus the relative reactivity of the subcritical experiment. The Nevada National Security Site developed the Gamma Array Simulation Toolkit initially to help inform the design of the individual detector pixels and the 3.4-meter diameter detector wall to be fielded as part of neutron-diagnosed subcritical experiments. This toolkit is now being used to simulate and predict the performance of the final design of the individual detector pixels and the aggregate detector wall. Key detector characteristics evaluated from these simulations include impulse response, pulse height spectrum, number of photoelectrons per MeV, detector efficiency, and cross talk between detector pixels. Collectively, the results of these simulations inform how well the fission gamma ray die-off distribution from a neutron-diagnosed subcritical experiment measurement can be resolved. This is critical to determining the relative reactivity of the experiment. Furthermore, the Gamma Array Simulation Toolkit can be used to aid in the analysis of the experimental data from a neutron-diagnosed subcritical experiment measurement once the simulation has been benchmarked.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

End-to-End Simulations of a 3.4-Meter Detector Wall for Neutron-Diagnosed Subcritical Experiments

The Nevada National Security Site, together with Los Alamos National Laboratory and Lawrence Livermore National Laboratory, is developing a novel diagnostic to measure the reactivity of subcritical experiments. This capability is known as neutron-diagnosed subcritical experiments. The decay of the fission gamma rays from the neutron-interrogated subcritical experiment is measured as a function of time with a large (~3-meter diameter) detector wall consisting of 151 individual detector pixels. The data from this current mode measurement inform the neutron multiplication factor, keff, and thus the relative reactivity of the subcritical experiment. The Nevada National Security Site developed the Gamma Array Simulation Toolkit initially to help inform the design of the individual detector pixels and the 3.4-meter diameter detector wall to be fielded as part of neutron-diagnosed subcritical experiments. This toolkit is now being used to simulate and predict the performance of the final design of the individual detector pixels and the aggregate detector wall. Key detector characteristics evaluated from these simulations include impulse response, pulse height spectrum, number of photoelectrons per MeV, detector efficiency, and cross talk between detector pixels. Collectively, the results of these simulations inform how well the fission gamma ray die-off distribution from a neutron-diagnosed subcritical experiment measurement can be resolved. This is critical to determining the relative reactivity of the experiment. Furthermore, the Gamma Array Simulation Toolkit can be used to aid in the analysis of the experimental data from a neutrondiagnosed subcritical experiment measurement once the simulation has been benchmarked.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Future North Atlantic tropical cyclone intensities in thermodynamically modified historical environments

Tropical cyclones (TCs) rank as the deadliest and most financially crippling natural disasters in the United States for the last half-century. It is imperative to assess potential shifts in TC intensity within the paradigm of an evolving climate. In this study, we have modeled the intensities of 620 historical TC events in the North Atlantic Basin using the Risk Analysis Framework for Tropical Cyclones (RAFT)'s deep learning intensity model. By applying a thermodynamic warming signal extrapolated from Global Climate Models, we rerun historical events under eight different future climate scenarios, providing a spectrum of potential TC intensity outcomes. One of the future simulations indicates a staggering 43% increase in the number of major hurricanes, underscoring the critical impact of climate change on TC intensity. Additionally, an interactive dashboard has been created to enable users to explore individual storm simulations and understand the influence of future climate signals on environmental conditions of TC development and resulting TC intensities. This dataset and the user-friendly tool offer invaluable resources for systematic exploration of the discrete effects that changes in the air-sea thermodynamic state have on the intensities of TCs.

Climate Change↗

Design of passive piezoelectric damping for space structures

Passive damping of structural dynamics using piezoceramic electromechanical energy conversion and passive electrical networks is a relatively recent concept with little implementation experience base. This report describes an implementation case study, starting from conceptual design and technique selection, through detailed component design and testing to simulation on the structure to be damped. About 0.5kg. of piezoelectric material was employed to damp the ASTREX testbed, a 500kg structure. Emphasis was placed upon designing the damping to enable high bandwidth robust feedback control. Resistive piezoelectric shunting provided the necessary broadband damping. The piezoelectric element was incorporated into a mechanically-tuned vibration absorber in order to concentrate damping into the 30 to 40 Hz frequency modes at the rolloff region of the proposed compensator. A prototype of a steel flex-tensional motion amplification device was built and tested. The effective stiffness and damping of the flex-tensional device was experimentally verified. When six of these effective springs are placed in an orthogonal configuration, strain energy is absorbed from all six degrees of freedom of a 90kg. mass. A NASTRAN finite element model of the testbed was modified to include the six-spring damping system. An analytical model was developed for the spring in order to see how the flex-tensional device and piezoelectric dimensions effect the critical stress and strain energy distribution throughout the component. Simulation of the testbed demonstrated the damping levels achievable in the completed system.

Hagood, Nesbitt W., IV↗

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗

Functional Characterization and Structural Insights Into Stereoselectivity of Pulegone Reductase in Menthol Biosynthesis

Monoterpenoids are the main components of plant essential oils and the active components of some traditional Chinese medicinal herbs like Mentha haplocalyx Briq ., Nepeta tenuifolia Briq ., Perilla frutescens (L.) Britt and Pogostemin cablin (Blanco) Benth. Pulegone reductase is the key enzyme in the biosynthesis of menthol and is required for the stereoselective reduction of the Δ 2,8 double bond of pulegone to produce the major intermediate menthone, thus determining the stereochemistry of menthol. However, the structural basis and mechanism underlying the stereoselectivity of pulegone reductase remain poorly understood. In this study, we characterized a novel (-)-pulegone reductase from Nepeta tenuifolia ( Nt PR), which can catalyze (-)-pulegone to (+)-menthone and (-)-isomenthone through our RNA-seq, bioinformatic analysis in combination with in vitro enzyme activity assay, and determined the structure of (+)-pulegone reductase from ( Mp PR) by using X-ray crystallography, molecular modeling and docking, site-directed mutagenesis, molecular dynamics simulations, and biochemical analysis. We identified and validated the critical residues in the crystal structure of Mp PR involved in the binding of the substrate pulegone. We also further identified that residues Leu56, Val282, and Val284 determine the stereoselectivity of the substrate pulegone, and mainly contributes to the product stereoselectivity. This work not only provides a starting point for the understanding of stereoselectivity of pulegone reductases, but also offers a basis for the engineering of menthone/menthol biosynthetic enzymes to achieve high-titer, industrial-scale production of enantiomerically pure products.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An RL10A-3-3A rocket engine model using the rocket engine transient simulator (ROCETS) software

Steady-state and transient computer models of the RL10A-3-3A rocket engine have been created using the Rocket Engine Transient Simulation (ROCETS) code. These models were created for several purposes. The RL10 engine is a critical component of past, present, and future space missions; the model will give NASA an in-house capability to simulate the performance of the engine under various operating conditions and mission profiles. The RL10 simulation activity is also an opportunity to further validate the ROCETS program. The ROCETS code is an important tool for modeling rocket engine systems at NASA Lewis. ROCETS provides a modular and general framework for simulating the steady-state and transient behavior of any desired propulsion system. Although the ROCETS code is being used in a number of different analysis and design projects within NASA, it has not been extensively validated for any system using actual test data. The RL10A-3-3A has a ten year history of test and flight applications; it should provide sufficient data to validate the ROCETS program capability. The ROCETS models of the RL10 system were created using design information provided by Pratt & Whitney, the engine manufacturer. These models are in the process of being validated using test-stand and flight data. This paper includes a brief description of the models and comparison of preliminary simulation output against flight and test-stand data.

Binder, Michael↗

Chatter detection in simulated machining data: a simple refined approach to vibration data

Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification model, to predict and classify chatter—a detrimental self-excited vibration phenomenon—during machining operations. While sophisticated methods have been employed to address chatter, this research investigates the efficacy of a novel approach to an RF model. The study leverages simulated vibration data, bypassing resource-intensive real-world data collection, to develop a versatile chatter detection model applicable across diverse machining configurations. The feature extraction process combines time-series features and Fast Fourier Transform (FFT) data features, streamlining the model while addressing challenges posed by feature selection. By focusing on the RF model’s simplicity and efficiency, this research advances chatter detection techniques, offering a practical tool with improved generalizability, computational efficiency, and ease of interpretation. The study demonstrates that innovation can reside in simplicity, opening avenues for wider applicability and accelerated progress in the machining industry.

42 ENGINEERING↗

Reliability estimation of an advanced nuclear fuel using coupled active learning, multifidelity modeling, and subset simulation

Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel and determining its reliability is critical for the success of advanced nuclear technologies. However, TRISO failure probabilities are small and the associated computational models are expensive. Here we used coupled active learning, multifidelity modeling, and subset simulation to estimate the failure probabilities of TRISO fuels using several 1D and 2D models. With multifidelity modeling, we replaced expensive high-fidelity (HF) model evaluations with information fusion from two low-fidelity (LF) models. For the 1D TRISO models, we considered three multifidelity modeling strategies: only Kriging, Kriging LF prediction plus Kriging correction, and deep neural network (DNN) LF prediction plus Kriging correction. While the results across these multifidelity modeling strategies compared satisfactorily, strategies employing information fusion from two LF models called the HF model least often. Next, for the 2D TRISO model, we considered two multifidelity modeling strategies: DNN LF prediction plus Kriging correction (data-driven) and 1D TRISO LF prediction plus Kriging correction (physics-based). The physics-based strategy, as expected, consistently required the fewest calls to the HF model. However, the data-driven strategy had a lower overall simulation time since the DNN predictions are instantaneous, and the 1D TRISO model requires a non-negligible simulation time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Influence of Precipitation Forcing Uncertainty on Hydrological Simulations with the NASA South Asia Land Data Assimilation System

Accurate meteorological estimates are critical for process-based hydrological simulationand prediction. This presents a significant challenge in mountainous Asia where in situmeteorological stations are limited and major river basins cross international borders. In thiscontext, remotely sensed and model-derived meteorological estimates are often necessary inputsfor distributed hydrological analysis. However, these datasets are difficult to evaluate on accountof limited access to ground data. In this case, the implications of uncertainty associated withprecipitation forcing for hydrological simulations is explored by driving the South Asia Land DataAssimilation System (South Asia LDAS) using a range of meteorological forcing products.MERRA2, GDAS, and CHIRPS produce a wide range of estimates for rainfall, which causes awidespread simulated streamflow and evapotranspiration. A combination of satellite-derived andlimited in situ data are applied to evaluate model simulations and, by extension, to constrain theestimates of precipitation. The results show that available gridded precipitation estimates based onin situ data may systematically underestimate precipitation in mountainous regions and thatperformance of gridded satellite-derived or modeled precipitation estimates varies systematicallyacross the region. Since no station-based data or product including station data is satisfactoryeverywhere, our results suggest that the evaluation of the hydrological simulation of streamflowand ET can be used as an indirect evaluation of precipitation forcing based on ground-basedproducts or in-situ data. South Asia LDAS produces reasonable evapotranspiration and streamflowwhen forced with appropriate meteorological forcing and the choice of meteorological forcingshould be made based on the geographical location as well as on the purpose of the simulations.

South Asia land data assimilation system (South As↗

Implementation and testing of physics-based pulverization model in BISON

This report summarizes lower length scale computational research conducted to improve the pulverization criterion for high-burnup UO 2 fuel in the BISON fuel performance code. This research was sponsored by the NEAMS program during FY22. Efforts to improve the model primarily focus on calculating the current pressure of bubbles in the high-burnup structure (HBS) region, as well as the critical bubble pressure at which pulverization occurs in the HBS. The phase-field model for predicting initial bubble pressure in the HBS was improved by implementing a more realistic model for defect production, and by coupling the phase-field model for inter-granular bubble evolution with the spatially-resolved cluster dynamics code Xolotl to simulate intra-granular fission gas evolution. An evolution equation for current bubble pressure was added to BISON, an improvement over the previous model that assumed that bubble pressure was static following HBS formation. To improve calculations of critical bubble pressure for pulverization, 3-D phase-field fracture simulations were performed, and a function for critical bubble pressure was fit—based on the simulation results—to replace the previous function, which had been determined using 2-D simulations. The impacts of these modifications to the existing pulverization assessment cases will be reported in the forthcoming engineering scale milestone on high-burnup UO 2 pulverization. A poromechanics-based approach was used to include the effect of bubble over pressurization on the stress state of the pellet at the engineering scale, and the initial strategy for integration of the pulverization criterion with pellet-scale mechanical degradation using a smeared cracking model was developed. This report also describes the initial research that was conducted to inform a forthcoming transient fission gas release (tFGR) model in BISON. Focusing on the fission gas release caused by pulverization of the outer pellet rim, a model for the amount of fission gas release was developed as a function of fuel porosity, bubble size, and fragment size. Implementation of this model in BISON and its impact of engineering-scale predictions will also be described in the aforementioned engineering-scale milestone on high-burnup UO 2 pulverization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Phase behavior of continuous-space systems: A supervised machine learning approach

The phase behavior of complex fluids is a challenging problem for molecular simulations. Supervised machine learning (ML) methods have shown potential for identifying the phase boundaries of lattice models. In this work, we extend these ML methods to continuous-space systems. We propose a convolutional neural network model that utilizes grid-interpolated coordinates of molecules as input data of ML and optimizes the search for phase transitions with different filter sizes. We test the method for the phase diagram of two off-lattice models, namely, the Widom–Rowlinson model and a symmetric freely jointed polymer blend, for which results are available from standard molecular simulations techniques. The ML results show good agreement with results of previous simulation studies with the added advantage that there is no critical slowing down. We find that understanding intermediate structures near a phase transition and including them in the training set is important to obtain the phase boundary near the critical point. The method is quite general and easy to implement and could find wide application to study the phase behavior of complex fluids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A phase-field model of quasi-brittle fracture for pressurized cracks: Application to UO 2 high-burnup microstructure fragmentation

Here, in this paper, we present a phase-field model of quasi-brittle fracture with pressurized cracks, with dedicated applications for polycrystalline materials. The model is formulated as a minimization problem within the variational framework. The external work done by pressure on the crack surfaces is included in the objective function. Several careful modeling choices lead to a regularization-length-independent critical strength. The model is constructed to give a softening response with an underlying linear traction-separation law. The pressure-dependent softening response and the regularization of the prescribed pressure are demonstrated with a (quasi) one-dimensional numerical analysis. In a two-dimensional numerical analysis under plane strain assumptions, the critical stress corresponding to crack propagation (as predicted by our quasi-brittle fracture model) is compared with linear elastic fracture mechanics (LEFM) analytical solutions. Our model is further utilized to simulate fission-gas-induced fragmentation of the UO 2 high-burnup structure (HBS). Simulation results show that pressurized bubbles can cause crack nucleation and propagation, and that the bubble size and the surrounding external pressure affect the critical pressure corresponding to crack nucleation. Simulations of a partial HBS at different recrystallization stages show that different grain structures (due to recrystallization) also influence crack paths and fragmentation morphology.

36 MATERIALS SCIENCE↗