Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Dynamic Timing Analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54

First constraints on a pixelated universe in light of DESI observations

Pixelated dark energy is a string theory scenario with a quantum mechanically stable cosmological constant. The number of pixels that make up the universe slowly increases, manifesting as a time-dependent source of dark energy. DESI has recently reported evidence for dynamical dark energy that fits within this framework. In light of this, we perform the first cosmological analysis of the pixelated model. We find that the simplest model where the pixel growth rate is constant is able to accommodate the data, providing a marginally better fit than Λ⁢ CDM; and we show that models where the pixel growth rate is increasing and of order the Hubble constant today could provide better fits. Our analysis helps to clarify the features of UV constructions of dark energy necessary to accommodate the data.

dark energy↗

Supernova-Explosion Mechanism Involving Neutrinos

A major part of the energy released upon the gravitational collapse of massive-star cores is carried away by neutrinos. Neutrinos play a crucial role in collapsing supernovae (SNe). At the present time, mathematical models of core-collapse SNe are based on multidimensional gas dynamics and thermonuclear reactions, whereas the neutrino transport is frequently treated in simplified way. An accurate analysis of neutrinos in a spherically symmetric gravitational collapse is performed on the basis of Boltzmann kinetic equations including all weak-interaction reactions with exact quantum-mechanical matrix elements. The role of multidimensional effects is studied bymeans of multidimensional gas dynamics allowing for the neutrino transport via diffusion treated by employing flux limiters. The possibility of largescale convection, which is of interest both from the point of view of explaining a type II supernova (SN) and from the point of view of implementing an experiment aimed at detecting possible energetic (≳10 MeV) neutrinos from an SN, is discussed. Thermonuclear burning leads to the explosion of a type I SN. A hot central region and the subsequent large-scale convection may also play an important role in the SN mechanism. If neutrinos and convection play a key role for a type II SN, then, in order to explain gamma radiation from product radioactive elements, convection is of importance in the case of SNe belonging to both types. In addition, convection may be important for bright type I SNe. Original methods are presented for multidimensional gas dynamics involving thermonuclear burning and for multitemperature gas dynamics involving radiative transfer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

GPU acceleration of Swendsen–Wang dynamics

When simulating a lattice system near its critical temperature, local algorithms for modeling the system’s evolution can introduce very large autocorrelation times into sampled data. Here, this critical slowing down places restrictions on the analysis that can be completed in a timely manner of the behavior of systems around the critical point. Because it is often desirable to study such systems around this point, a new algorithm must be introduced. Therefore, we turn to cluster algorithms, such as the Swendsen–Wang algorithm and the Wolff clustering algorithm. They incorporate global updates which generate new lattice configurations with little correlation to previous states, even near the critical point. We look to accelerate the rate at which these algorithm are capable of running by implementing and benchmarking a parallel implementation of each algorithm designed to run on GPUs under NVIDIA’s CUDA framework. A 17 and 90 fold increase in the computational rate was, respectively, experienced when measured against the equivalent algorithm implemented in serial code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Advancing the Adoption of High Performance Computing for Time Domain Simulation

Time domain transient stability simulation of large interconnected power systems is becoming increasingly computationally intensive. With the addition of high levels of variable generation that can aggregately ramp over many hours, both the complexity and time horizon for which power system simulations will need to be conducted are increasing. Additionally, extended-term time domain simulation is required to analyze power system security when cascading events across the system span minutes or even hours. Analysis of these occurrences requires modeling power system dynamics over tens of minutes to many hours rather than tens of seconds. Because of the required high computational intensity, there are presently no stability modeling/simulation platforms that combine the needed computational capabilities with the required power system models relevant for representing and analyzing the potential reliability implications of phenomena that occurs over both short- and extended-term dynamic timeframes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Insights into Methodologies and Stochastic Optimization of Thermal Energy Storage-Coupled Advanced Reactor Systems: A Comparison of Methods for Accessing Long-Term Sub-System Sizing Adequacy

This paper investigates the potential of coupling Thermal Energy Storage (TES) with Advanced Reactors (ARs) to address uncertainties posed by climate change in deep decarbonized power systems. The TES Use-case Team at Idaho National Laboratory (INL) has examined the potential of storing thermal energy from ARs during low demand periods and optimizing discharge during peak-priced hours, in both steady-state and transient conditions. Building on this groundwork, this study bridges the gaps in optimal sizing of the sub-system of TES-coupled AR systems using Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON), INL?s framework for grid optimization. By applying this framework, we present statistically-robust optimal charge, discharge including balance of plant (BOP), and storage sizing for the High-Temperature Gas-Cooled Reactor (HTGR) with 203 MWth output. To this end, we generated synthetic price samples for 30 years using 2018 ? 2021 real-time market data from ERCOT, PJM and MISO. Our results reveals that the TES-coupled HTGR system is highly effective in maximizing revenue from electricity sales. We observed a substantial increase of 40 % in ERCOT and a noteworthy 15 % increase in PJM and MISO when compared to the conventional BOP without TES. This improvement is achieved through regionally-tailored sub-system sizing, which ranges from 398 to 416 MWth for the discharge system and 610 to 1029 MWth for the TES. We find that the average electricity price directly impacts the overall economics, while price volatility influences storage size. Additional sensitivity analyses were performed to access the impact of key assumptions on system economics and sizing, differentiating the optimization window (i.e., 24 ? 219 hours of chronological observations) and by imposing storage continuity condition in tracking TES cycles. We observed that at the 120-hour of the optimization window, a reasonable balance between computation time and accuracy was achieved. Our analysis also highlights the significance of conducting multi-day cycle analysis (> 120-hour) for TES to capture interaction between electricity prices and storage dynamics, providing a comprehensive understanding of TES behavior that AR developers should integrate into their plant designs.

25 ENERGY STORAGE↗

Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling

Abstract. Major multi-reservoir cascades represent a primary mechanism for dealing with hydrologic variability and extremes within institutionally complex river basins worldwide. These coordinated management processes fundamentally reshape water balance dynamics. Yet, multi-reservoir coordination processes have been largely ignored in the increasingly sophisticated representations of reservoir operations within large-scale hydrological models. The aim of this paper is twofold, namely (i) to provide evidence that the common modeling practice of parameterizing each reservoir in a cascade independently from the others is a significant approximation and (ii) to demonstrate potential unintended consequences of this independence approximation when simulating the dynamics of hydrological extremes in complex reservoir cascades. We explore these questions using the Water Balance Model, which features detailed representations of the human infrastructure coupled to the natural processes that shape water balance dynamics. It is applied to the Upper Snake River basin in the western US and its heavily regulated multi-reservoir cascade. We employ a time-varying sensitivity analysis that utilizes the method of Morris factor screening to explicitly track how the dominant release rule parameters evolve both along the cascade and in time according to seasonal high- and low-flow events. This enables us to address aim (i) by demonstrating how the progressive and cumulative dominance of upstream releases significantly dampens the ability of downstream reservoir rules' parameters to influence flow conditions. We address aim (ii) by comparing simulation results with observed reservoir operations during critical low-flow and high-flow events in the basin. Our time-varying parameter sensitivity analysis with the method of Morris clarifies how independent single-reservoir parameterizations and their tacit assumption of independence leads to reservoir release behaviors that generate artificial water shortages and flooding, whereas the observed coordinated cascade operations avoided these outcomes for the same events. To further explore the role of (non-)coordination in the large deviations from the observed operations, we use an offline multi-reservoir water balance model in which adding basic coordination mechanisms drawn from the observed emergency operations is sufficient to correct the deficiencies of the independently parameterized reservoir rules from the hydrological model. These results demonstrate the importance of understanding the state–space context in which reservoir releases occur and where operational coordination plays a crucial role in avoiding or mitigating water-related extremes. Understanding how major infrastructure is coordinated and controlled in major river basins is essential for properly assessing future flood and drought hazards in a changing world.

54 ENVIRONMENTAL SCIENCES↗

A Novel Measurement of the Anomalous Muon Spin Precession Frequency in the Muon $g-2$ Experiment at Fermilab

The Muon $g-2$ Experiment operated at Fermi National Accelerator Laboratory (FNAL, or Fermilab) between 2018 and 2023 to produce the world's most precise measurement of the muon's \textit{anomalous magnetic moment}, $a_\mu = \frac{g_\mu - 2}{2}$, which expresses the relative deviation in the muon's $g$-factor from a baseline theoretical expectation that $g_\mu = 2$. In the Standard Model of particle physics, $g_\mu > 2$ and hence $a_\mu > 0$ by a calculable amount that depends on all possible interactions between the muon and all other fundamental particles, including any potentially undiscovered interactions beyond the Standard Model. For this reason, measurements of the electron anomaly $a_e$ and later the muon anomaly $a_\mu$ have helped guide the development of the Standard Model since the inception of quantum field theory, and the measured value of $a_\mu$ provides a valuable constraint for new hypotheses that extend the Standard Model. As of 2006, the leading measurement and Standard Model prediction for $a_\mu$ exhibited tension at the level of about three standard deviations, motivating an improved measurement at Fermilab that could test the tension more precisely. The experiment functions by storing a polarized beam of $\mu^+$ in a uniform magnetic field, which simultaneously induces circular motion and spin precession. As the stored muons undergo the Michel decay $\mu^+ \to e^+ + \nu_e + \bar{\nu}_\mu$, mediated by the parity-violating weak interaction, the rest-frame $e^+$ emission direction is correlated with the parent $\mu^+$ spin orientation. Boosting into the laboratory frame encodes this correlation in the decay $e^+$ energy, which is higher when the emission (i.e. $\mu^+$ spin direction) is aligned with the $\mu^+$ momentum, and lower when opposite. Detectors then count the rate of high-energy decay $e^+$, which modulates at the difference between the $\mu^+$ revolution and spin precession frequencies. This observed frequency, called the \textit{anomalous spin precession frequency} $\omega_a$, is directly proportional to $a_\mu$. The extraction of $\omega_a$ proceeds by fitting the time spectrum of detected $e^+$, which requires precise modeling of the $\omega_a$ oscillation as well as any perturbations from beam dynamics and detector acceptance. Using the $\omega_a$ analysis presented in this work, based on Runs 4 -- 6 of the Muon $g-2$ Experiment at Fermilab, we find that $a_\mu = 0.001\,165\,920\,738(162)$ with a relative uncertainty of 139 parts per billion.

Barrett, Tyler [Cornell U.]↗

Utilization of an Advanced Sensor network to determine fuel heating value and Real-Time net unit heat rate during transient operation

Coal-fired utility boilers are being increasingly used as variable electricity generation to resolve the imbalance in the energy market from the expansion of intermittent renewable energy. The frequent transient operation required to meet residual energy demand has created a challenge for coal-fired units to operate efficiently. This work utilizes an advanced sensor network (ASN) to calculate net unit heat rate (NUHR) of a coal-fired boiler in real time through combustion calculations and statistical correlations to provide the tools for optimizing dynamic operation. Real-time heating values that were necessary to determine fuel input energy to calculate accurate NUHR were found using both fundamental and data-driven methods. Real-time NUHR shows distinct shifts that reflect changes in process conditions that will improve the ability to optimize transient operation. Data-driven heating value correlations had 24% lower root mean square error (RMSE) than the fundamental combustion calculation approach when compared to daily retrospective proximate analysis. Furthermore, the data-driven method RMSE improved by 7% with the inclusion of ASN data. Future work is to validate by comparing unit performance with and without the inclusion of NUHR as a control parameter for the dynamic neural network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Characterizing The Mechanical Properties of Polyurethane Foams

The purpose is to determine the mechanical properties of polyurethane foams with the intent of using PU foams to fill large void asymmetrical volumes like a glovebox to fixate transferable radiological material. Testing the resiliency of foam technologies when exposed to physicals stressors will be done. Six COTS PU foams considered will be fabricated and tested (iT 7, iT 8, iT 14, iT 23, 3M Fire Barrier, and Hilti) with and without additives at 12.5% wt (Bi, WO{sub 3}, and Na{sub 2}WO{sub 3}). Polyurethanes (PU) are a special class of polymeric materials that have great potential in many applications. Used in automotive, biomedical, construction, and textiles industries. Sought after due to its versatility and superior properties. PU foams have become one of the most prominent PU-based products. Bench-scale testing by SRNL and FIU-ARC confirmed PU foam technology's superior capabilities: Cured in various and desired volumes; No samples generated heat above 90 deg. C during curing reaction; Incorporation of additives (Bi, WO{sub 3}, BiO{sub 3}, Na{sub 2}WO{sub 3}) led to the following shielding: 98% of Am-241, 16% of Cs-137, 9.5% of Co-60. Proved foams' resistance to thermal stressors: Foams lasted 2 hours of direct flame; Excellent thermal insulation; Maintained structural integrity; No smoke or flame propagation. Experiment 1: A tensile tester (MTS Criterion Series 43) will be utilize to evaluate various properties of different PU rigid and flexible foams with and without additives (at 12.5% wt) under tension at 1 mm/s. Experiment 2: A thermogravimetric analysis (TGA) and Dynamic Mechanical Analyzer (DMA) will be employed to determine PU foams' breakdown of physical properties while under a constant heat rate (10 C/min) and strain rate (1%) under a period of time. Foams with additives showed an increase in stiffness and durability during tensile testing with WO{sub 3} producing the best results for Foam iT 7. All the other foam samples showed similar trends. Glass transition temperature (Tg) range for Foam iT 7 with Na{sub 2}WO{sub 3} ranged from 120-150 C while Foam iT 7 blank Tg range was from 90-110 C with a difference of about 30 C showing improvement with addition of additives.

36 MATERIALS SCIENCE↗

Numerical simulation of vortex-induced motion of a deep-draft paired-column semi-submersible offshore platform

Understanding and predicting vortex-induced motion (VIM) of offshore systems for deep seawater applications is crucial to improve the system safety and integrity. In this paper, we report on experimental tow-tank measurements and numerical simulations of VIM of a deep-draft offshore platform, specifically Paired-Column Semisubmersible (PC-Semi). The study is carried out in model scale (1:54), at subcritical flow regime with Re~10 4 . Motion of the floating structure has three degrees of freedom: in-line, cross-flow, and yaw. Large periodic cross-flow motion is measured for headings 0°, 11.25°, and 22.5°, for reduced velocities (U r ) between 5 and 10. Considerably smaller cross-flow amplitude is recorded at 45° heading across the U r range considered. An extensive sensitivity study is performed using computational fluid dynamics (CFD) to capture the transient displacement history of VIM (in-line, cross-flow, and yaw motion components). Amplitude and period of cross-flow (transverse) motion are obtained from statistical analysis of VIM time history and subsequently used as the validation criterion between the CFD simulation and the model tests. Satisfactory agreement between the CFD results and tow-tank measurements is achieved with a Delayed Detached Eddy Simulation – Shear Stress Transport (DDES-SST) formulation. Finally, this work provides experimental results and serves as a practical starting point to set up a CFD problem to estimate amplitude and period of cross-flow VIM motion for offshore engineering applications.

42 ENGINEERING↗

Rayleigh-type parametric chemical oscillation

We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

Imaginary admittance and charge transfer resistance correlate to the physiological status of Shewanella oneidensis cultures in real time

Monitoring microbial activity is essential for industrial and environmental applications to proceed efficiently. To minimize time and labor-intensive monitoring, a new paradigm is required for in-situ, real time analysis. Since bioconversion of organics is accomplished by microorganisms through the oxidation of feedstocks linked to the reduction of electron acceptors, microorganisms can be viewed as electrochemical catalysts. In this respect, cell membranes have an electrical potential, which is analogous to a conventional capacitor and linked dynamically to cellular activity. Here, in this study, we demonstrate the use of electrochemical impedance spectrometry (EIS) and cyclic voltammetry (CV) for monitoring microbial metabolic activity in real time, in-situ. The effect of organic electron donors as a function of concentration to the physiological status of strains of Shewanella oneidensis was determined. In this study, the pyomelanin overproducer (S. oneidensis ΔhmgA) and the pyomelanin deficient mutant (S. oneidensis ΔmelA) were chosen due to different surface electrochemical characteristics along with differences in oxygen utilization efficiency. CV, relative admittance, phase shift and permittivity changed with growth status and correlated with electron flow from organic carbon sources and terminal electron acceptor availability. This work offers a novel and inexpensive approach to real time monitoring with the advantage of abundant data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-resolved biphase signatures of quadratic nonlinearity observed in coupled Alfvén eigenmodes on the DIII-D tokamak

We report the detection of nonstationary quadratic coupling between toroidicity-induced Alfvén eigenmodes (TAEs) on sub-millisecond time scales. Identification of phase coherency between multiple TAEs and nonlinearly generated modes is facilitated by wavelet-based bicoherence analysis of time-series from inductive coils, taken from a DIII-D discharge heated by neutral beam injection (NBI). Characterization of nonlinear three-wave interaction is inferred by stationary local bispectrum phase (biphase) and confirmed via bandpass filtering. Biphase dynamics associated with prominent bispectral features are well-resolved in time and consistent with transient quadratic coupling. Onset and duration of nonlinearity are correlated with enhanced amplitude of participating TAEs; coincident changes in amplitude are observed for modes at difference frequency |f TAE,1 - f TAE,2 |.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Numerical Analysis of Regular Material Point Method and its Application to Multiphase Flows

The material point method (MPM) is gaining wide popularity in engineering research to model and simulate complex multiphase flow dynamics. The method relies on solving the governing equations of motion and transport in a Lagrangian framework using particles also known as material points. The fluid and kinematic properties are stored on the material points while the spatial gradient calculation and temporal integration are performed on a background grid. This Lagrangian framework allows for large deformations, easy integration of constitutive models, and direct import of complex geometries as particles. However, despite their increasing popularity, very few studies have addressed the issues of numerical resolution and stability of MPM techniques. The presence of additional factors such as the number of material points-per-cell, the location of the material points, the CFL-like condition used in time update, and the grid shape functions also increase the complexity of the error analysis when compared to other finite element methods. In this presentation, we analyze the various forms of error incurred in the application of MPM to continuum mechanics and multiphase flows. The effect of the previously mentioned factors on the error dynamics is studied. The application of these principles to canonical and industrial problems is also presented.

high pressure reverse osmosis↗

Electromagnetic effects on dynamics of high-beta filamentary structures

The impacts of the electromagnetic effects on blob dynamics are considered. Electromagnetic BOUT++ simulations on seeded high-beta blobs demonstrate that inhomogeneity of magnetic curvature or plasma pressure along the filament leads to bending of the blob filaments and the magnetic field lines due to increased propagation time of plasma current (Alfvén time). The bending motion can enhance heat exchange between the plasma facing materials and the inner scrape-off layer (SOL) region. The effects of sheath boundary conditions on the part of the blob away from the boundary are also diminished by the increased Alfvén time. Using linear analysis and BOUT++ simulations, it is found that electromagnetic effects in high temperature and high density plasmas reduce the growth rate of resistive drift wave instability when resistivity drops below a certain value. The blobs temperature decreases in the course of its motion through the SOL and so the blob can switch from the electromagnetic to the electrostatic regime where resistive drift waves become important again.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗