Metrics Analysis Framework of Control and Management System for Resilient Connected Community Microgrids
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Energy & Fuels↗
SEARCH · Engineering Papers
Results for “Engineering science”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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How Sampling and Averaging Historical Solar and Wind Data Can Distort Resource Adequacy
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Energy & Fuels↗
Hierarchical Intelligent Operation of Energy Storage Systems in Power Distribution Grids
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Energy & Fuels↗
Small Signal Stability of Phase Locked Loop Based Current-Controlled Inverter in 100% Inverter-Based System
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Energy & Fuels↗
On Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars
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Computer Science↗
Compute-in-Memory Technologies and Architectures for Deep Learning Workloads
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Computer Science↗
Analytical Sensitivity Analysis of a Spent Nuclear Fuel Cask
Here, we report nuclear science and engineering is a field increasingly dominated by computational studies resulting from increasingly powerful computational tools. As a result, analytical studies, which previously pioneered nuclear engineering, are increasingly viewed as secondary or unnecessary. However, analytical solutions to reduced-fidelity models can provide important information concerning the underlying physics of a problem and aid in guiding computational studies. Similarly, there is increased interest in sensitivity analysis studies. These studies commonly use computational tools. However, providing a complementary sensitivity study of relevant analytical models can lead to a deeper analysis of a problem. This work provides the analytical sensitivity analysis of the one-dimensional (1D) cylindrical mono-energetic neutron diffusion equation using the forward sensitivity analysis procedure (FSAP) developed by Cacuci. Further, these results are applied to a reduced-fidelity model of a spent nuclear fuel cask, demonstrating how computational analysis might be improved with a complementary analytic sensitivity analysis.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Scalability Testing Approach for Internet of Things for Manufacturing SQL and NoSQL Database Latency and Throughput
The proliferation of low-cost sensors and industrial data solutions has continued to push the frontier of manufacturing technology. Machine learning and other advanced statistical techniques stand to provide tremendous advantages in production capabilities, optimization, monitoring, and efficiency. The tremendous volume of data gathered continues to grow, and the methods for storing the data are critical underpinnings for advancing manufacturing technology. This work aims to investigate the ramifications and design tradeoffs within a decoupled architecture of two prominent database management systems (DBMS): sql and NoSQL. A representative comparison is carried out with Amazon Web Services (AWS) DynamoDB and AWS Aurora MySQL. The technologies and accompanying design constraints are investigated, and a side-by-side comparison is carried out through high-fidelity industrial data simulated load tests using metrics from a major US manufacturer. The results support the use of simulated client load testing for comparing the latency of database management systems as a system scales up from the prototype stage into production. As a result of complex query support, MySQL is favored for higher-order insights, while NoSQL can reduce system latency for known access patterns at the expense of integrated query flexibility. Here, by reviewing this work, a manufacturer can observe that the use of high-fidelity load testing can reveal tradeoffs in IoTfM write/ingestion performance in terms of latency that are not observable through prototype-scale testing of commercially available cloud DB solutions.
AWS↗
Methods for the Automated Determination of Sustained Maximum Amplitudes in Oscillating Signals
Machine condition monitoring has been proven to reduce machine downtime and increase productivity. The state-of-the-art research uses vibration monitoring for tasks such as maintenance and tool wear prediction. A less explored aspect is how vibration monitoring might be used to monitor equipment sensitive to vibration. In a manufacturing environment, one example of where this might be needed is in monitoring the vibration of optical linear encoders used in high-precision machine tools and coordinate measuring machines. Monitoring the vibration of sensitive equipment presents a unique case for vibration monitoring because an accurate calculation of the maximum sustained vibration is needed, as opposed to extracting trends from the data. To do this, techniques for determining sustained peaks in vibration signals are needed. Here, this work fills this gap by formalizing and testing methods for determining sustained vibration amplitudes. The methods are tested on simulated signals based on experimental data. Results show that processing the signal directly with the novel Expire Timer method produces the smallest amounts of error on average under various test conditions. Additionally, this method can operate in real-time on streaming vibration data.
Industrial Internet of Things↗
Critical Shear Stresses for Erosion from Yield Stresses
The critical shear stress for erosion is important in many fields of engineering and science that involve suspension of particles from settled particle beds. However, determining the critical shear stress for erosion remains intricate, particularly where interparticle forces play a key role. Because these forces vary widely (Pease, et al., 2019), a more convenient means of estimating the critical shear stress for erosion would be advantageous. Here we evaluate the assertion that critical shear stresses for erosion may be derived from yield stresses for nominally cohesive particle beds across the full range of particle Reynolds numbers. The critical shear stress for erosion for non-cohesive particle beds may be estimated from the Shields diagrams or the analytical expressions from conservation of force about a particle at the interface. However, equivalent diagrams for cohesive particle beds have remained elusive. In 1992, pioneering analysis by Dade included the influence of the van der Waals force in particle forces balances to show that the critical shear stresses for erosion may be related to yield stresses subject to the limitations of small particle Reynolds numbers, flat particle beds, uniform particle diameters, and negligible electrostatic forces. Here we relax these restrictions. We find that the critical shear stress for erosion does relate to the yield stresses in a linear fashion for sufficiently large yield stresses. A criterion is developed to determine when the yield stresses may be important. Pease LF, AJ Fuher, JA Bamberger, and MJ Minette. 2024. Shields Diagrams for Cohesive Particle Beds. Manuscript. Dade WB, ARM Nowell and PA Jumars. 1992. “Predicting erosion resistance of muds.” Marine Geology, 105 (1992) 285-297.
shear stress, erosion, yield stress, slurry, settl↗
Comparison of Radiation Models for a Turbulent Piloted Methane/Air Jet Flame: A Frozen-Field Study
Numerical modeling of radiative transfer in nongray reacting media is a challenging problem in computational science and engineering. The choice of radiation models is important for accurate and efficient high-fidelity combustion simulations. Different applications usually involve different degrees of complexity, so there is yet no consensus in the community. In this paper, the performance of different radiative transfer equation (RTE) solvers and spectral models for a turbulent piloted methane/air jet flame are studied. The flame is scaled from the Sandia Flame D with a Reynolds number of 22,400. Three classes of RTE solvers, namely the discrete ordinates method, spherical harmonics method, and Monte Carlo method, are examined. The spectral models include the Planck-mean model, the full-spectrum k-distribution (FSK) method, and the line-by-line (LBL) calculation. The performances of different radiation models in terms of accuracy and computational cost are benchmarked. The results have shown that both RTE solvers and spectral models are critical in the prediction of radiative heat source terms for this jet flame. The trade-offs between the accuracy, the computational cost, and the implementation difficulty are discussed in detail. The results can be used as a reference for radiation model selection in combustor simulations.
David, Chloe↗
Monolithic mtesla-level magnetic induction by self-rolled-up membrane technology
Monolithic strong magnetic induction at the mtesla to tesla level provides essential functionalities to physical, chemical, and medical systems. Current design options are constrained by existing capabilities in three-dimensional (3D) structure construction, current handling, and magnetic material integration. We report here geometric transformation of large-area and relatively thick (~100 to 250 nm) 2D nanomembranes into multiturn 3D air-core microtubes by a vapor-phase self-rolled-up membrane (S-RuM) nanotechnology, combined with postrolling integration of ferrofluid magnetic materials by capillary force. Hundreds of S-RuM power inductors on sapphire are designed and tested, with maximum operating frequency exceeding 500 MHz. An inductance of 1.24 μH at 10 kHz has been achieved for a single microtube inductor, with corresponding areal and volumetric inductance densities of 3 μH/mm 2 and 23 μH/mm 3 , respectively. The simulated intensity of the magnetic induction reaches tens of mtesla in fabricated devices at 10 MHz.
42 ENGINEERING↗
Bright magnetic dipole radiation from two-dimensional lead-halide perovskites
Light-matter interactions in semiconductors are uniformly treated within the electric dipole approximation; multipolar interactions are considered “forbidden.” We experimentally demonstrate that this approximation inadequately describes light emission in two-dimensional (2D) hybrid organic-inorganic perovskites (HOIPs), solution processable semiconductors with promising optoelectronic properties. By exploiting the highly oriented crystal structure, we use energy-momentum spectroscopies to demonstrate that an exciton-like sideband in 2D HOIPs exhibits a multipolar radiation pattern with highly directed emission. Electromagnetic and quantum-mechanical analyses indicate that this emission originates from an out-of-plane magnetic dipole transition arising from the 2D character of electronic states. Symmetry arguments and temperature-dependent measurements suggest a dynamic symmetry-breaking mechanism that is active over a broad temperature range. These results challenge the paradigm of electric dipole–dominated light-matter interactions in optoelectronic materials, provide new perspectives on the origins of unexpected sideband emission in HOIPs, and tease the possibility of metamaterial-like scattering phenomena at the quantum-mechanical level.
42 ENGINEERING↗
One-component order parameter in URu 2 Si 2 uncovered by resonant ultrasound spectroscopy and machine learning
The unusual correlated state that emerges in URu 2 Si 2 below T HO = 17.5 K is known as “hidden order” because even basic characteristics of the order parameter, such as its dimensionality (whether it has one component or two), are “hidden.” We use resonant ultrasound spectroscopy to measure the symmetry-resolved elastic anomalies across T HO . We observe no anomalies in the shear elastic moduli, providing strong thermodynamic evidence for a one-component order parameter. We develop a machine learning framework that reaches this conclusion directly from the raw data, even in a crystal that is too small for traditional resonant ultrasound. Our result rules out a broad class of theories of hidden order based on two-component order parameters, and constrains the nature of the fluctuations from which unconventional superconductivity emerges at lower temperature. Our machine learning framework is a powerful new tool for classifying the ubiquitous competing orders in correlated electron systems.
42 ENGINEERING↗
A molten carbonate shell modified perovskite redox catalyst for anaerobic oxidative dehydrogenation of ethane
Acceptor-doped, redox-active perovskite oxides such as La 0.8 Sr 0.2 FeO 3 (LSF) are active for ethane oxidation to CO x but show poor selectivity to ethylene. This article reports molten Li 2 CO 3 as an effective “promoter” to modify LSF for chemical looping–oxidative dehydrogenation (CL-ODH) of ethane. Under the working state, the redox catalyst is composed of a molten Li 2 CO 3 layer covering the solid LSF substrate. The molten layer facilitates the transport of active peroxide (O 2 2- ) species formed on LSF while blocking the nonselective sites. Spectroscopy measurements and density functional theory calculations indicate that Fe 4+ →Fe 3+ transition is responsible for the peroxide formation, which results in both exothermic ODH and air reoxidation steps. With >90% ethylene selectivity, up to 59% ethylene yield, and favorable heat of reactions, the core-shell redox catalyst has an excellent potential to be effective for intensified ethane conversion. The mechanistic findings also provide a generalized approach for designing CL-ODH redox catalysts.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗