Frequency Response Analysis of the Molten Salt Demonstration Reactor Dynamic Simulation Model in Transient Simulation Framework of Reconfigurable Models (TRANSFORM)
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Integration of advanced nuclear reactors to industrial processes in an integrated energy system (IES) has many potential advantages. The coupling of nuclear power to varied industrial processes introduces additional accident scenarios unique to the specific systems included in the IES. Similarly, noise in one system of the IES could potentially create negative effects in the other systems. Because of the limited amount of comparable nuclear IES operating experience, there is added value in scoping the inherent behavior of these systems in response to these transients. Here, this paper investigates the safety-related behavior of an open-source IES dynamic model of a fast spectrum molten salt reactor (MSR) powering a regenerative Rankine cycle for electricity production and a hybrid sulfur (HyS) cycle for hydrogen production. The simulations include a loss of cooling water to the Rankine cycle, a loss of sulfur in the HyS cycle, and the frequency characteristics of the entire IES across six orders of magnitude of frequency. The results show safe behavior in response to the two accident scenarios, wherein a disruption in heat transfer leads to increased salt temperatures and a decrease in reactor power. The frequency analysis shows that at higher frequencies, temperature changes propagating through an IES are increasingly damped to the point of negligibility.
New capabilities of fast-sweep frequency-modulated profile reflectometry are explored to measure electron density ne perturbation magnitudes and radial profiles due to plasma coherent modes in DIII-D. The first approach is based on the frequency analysis of phase perturbations associated with high frequency (~MHz) Alfvén eigenmodes (AEs). The measurement of ~5.5 MHz fast-ion-driven global Alfvén eigenmodes (GAEs) is demonstrated in a neutral beam-heated DIII-D plasma. The GAE induced a broad radial distribution of phase perturbations in the profile reflectometer data. Analysis of these data determined the effective cutoff location displacement and the estimated ne fluctuation profile. In the second approach, high resolution ne profiles are used directly to determine the radial structure of ne perturbations due to a neo-classical tearing mode. These new measurements broaden the application of profile reflectometry and advance the development of AE spectroscopy as a tool for non-invasive diagnosis of fast-ion-driven modes in DIII-D and burning plasmas such as ITER.
Abstract Low-level jets (LLJs), in which the wind speed attains a local maximum at low altitudes, have been found to occur in the U.S. mid-Atlantic offshore, a region of active wind energy deployment as of 2023. In contrast to widely studied regions such as the U.S. southern Great Plains and the California coastline, the mechanisms that underlie LLJs in the U.S. mid-Atlantic are poorly understood. This work analyzes floating lidar data from buoys deployed in the New York Bight to understand the characteristics and causes of coastal LLJs in the region. Application of the Hilbert–Huang transform, a frequency analysis technique, to LLJ case studies reveals that mid-Atlantic jets frequently occur during times of adjustment in synoptic-scale motions, such as large-scale temperature and pressure gradients or frontal passages, and that they do not coincide with motions at the native inertial oscillation frequency. Subsequent analysis with theoretical models of inertial oscillation and thermal winds further reveals that these jets can form in the stationary geostrophic wind profile from horizontal temperature gradients alone—in contrast to canonical LLJs, which arise from low-level inertial motions. Here, inertial oscillation can further modulate the intensity and altitude of the wind speed maximum. Statistical evidence indicates that these oscillations arise from stable stratification and the associated frictional decoupling due to warmer air flowing over a cold sea surface during the springtime land–sea breeze. These results improve our conceptual understanding of mid-Atlantic jets and may be used to better predict low-level wind speed maxima. Significance Statement The purpose of this work is to identify and characterize the atmospheric mechanisms that result in an occasional low-level maximum in the wind speed off the U.S. mid-Atlantic coastline. Our findings show that these low-level jets form due to horizontal temperature gradients arising from fronts and synoptic systems, as well as from the land–sea breeze that forces warmer air over the cold ocean surface. This work aids predictability of such jets, improves our understanding of this coastal environment, and has implications for future deployment of offshore wind energy in this region.
Quantum-empowered electromagnetic transients program (QEMTP) is a promising paradigm for tackling EMTP's computational burdens. Nevertheless, no existing studies truly achieve a practical and scalable QEMTP operable on today's noisy-intermediate-scale quantum (NISQ) computers. The strong reliance on noise-free and fault-tolerant quantum devices--which appears to be decades away--hinder practical applications of current QEMTP methods. Here, we devise a NISQ-QEMTP methodology which for the first time transitions the QEMTP operations from ideal, noise-free quantum simulators to real, noisy quantum computers. The main contributions lie in: (1) a shallow-depth QEMTP quantum circuit for mitigating noises on NISQ quantum devices; (2) practical QEMTP linear solvers incorporating executable quantum state preparation and measurements for nodal voltage computations; (3) a noise-resilient QEMTP algorithm leveraging quantum resources logarithmically scaled with power system dimension; (4) a quantum shifted frequency analysis (QSFA) for accelerating QEMTP by exploiting dynamic phasor simulations with larger time steps; (5) a systematical analysis on QEMTPs performance under various noisy quantum environments. Extensive experiments systematically verify the accuracy, efficacy, universality and noise-resilience of QEMTP on both noise-free simulators and IBM real quantum computers.
We present 12 new transit light curves of the hot-Jupiter TrES-3b observed during 2012−2018 to probe the transit timing variation (TTV). By combining the midtransit times determined from these 12 transit data with those reestimated through uniform procedure from 71 transit data available in the literature, we derive new linear ephemeris and obtain the timing residuals that suggest the possibility of TTV in the TrES-3 system. However, the frequency analysis shows that the possible TTV is unlikely to be periodic, indicating the absence of an additional body in this system. To explore the other possible origins of TTV, the orbital decay and apsidal precession ephemeris models are fitted to the transit time data. We find the decay rate of TrES-3b to be P-dot {sub q}=−4.1±3.1 ms yr{sup −1}, and the corresponding estimated modified stellar tidal quality factor of Q{sub ∗}{sup ′}∼1.11×10{sup 5} is consistent with the theoretically predicted values for the stars hosting the hot-Jupiters. The shift in the transit arrival time of TrES-3b after 11 years is expected to be T {sub shift} ∼ 69.55 s, which is consistent with the rms of the timing residuals. Besides, we find that the apsidal precession ephemeris model is statistically less probable than the other considered ephemeris models. It is also discussed that despite the fact that the linear ephemeris model appears to be the most plausible model to represent the transit time data, the possibility of the orbital decay cannot be completely ruled out in the TrES-3 system. To confirm this, further high-precision and high-cadence follow-up observation of transits of TrES-3b would be important.
Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (ZDR) specific differential phase shift (K DP ) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band Z DR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed Z DR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, KDP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.
Here, this study examines the application of the recently developed next-generation intensity-duration-frequency (NG-IDF) curves in hydrological design, focusing on a small snow-dominated basin in Washington state. Four methods are used to assess the NG-IDF performance: (1) basin outlet flood frequency analysis, (2) use of standard precipitation-based intensity-duration-frequency (PREC-IDF) curves following surface water design manuals typically used in the basin, (3) utilization of locally constructed PREC-IDF curves, and (4) use of locally constructed NG-IDF curves. The standard PREC-IDF design method assumes precipitation as rainfall and neglecting snowmelt or rain-on-snow (ROS) events that can lead to significant flood underestimations in the test basin. In contrast, the NG-IDF method incorporates snow processes and shows promising improvements in accurately estimating design floods. The validation analysis demonstrates the superiority of NG-IDF over standard and local PREC-IDF in this test basin. The study highlights the necessity for adjustments in current design manuals to ensure sufficient flood protection, particularly in light of the planned substantial investments in US infrastructure.
Cicadas are insects that belong to the order Hemiptera (i.e., true bugs). They feed on plant fluids above and below ground. Cicada species fall into two categories: periodical and annual. Seven species of periodical cicadas have been identified, emerging in 13-, 17-, and 21-year cycles [1]. The largest brood (i.e., periodical cicadas of the same cycle) of 17-year cicadas is Brood X, examples of which are shown in Fig. 1. Male cicadas produce the loudest sounds of the insect world. A single male can produce a clicking sound that exceeds 100 dB sound pressure level. This male cicada sound emanates from an organ called the tympanic membrane, which is located on both sides of the body near the base of the wing [2]. The vibrations from this organ generate the sound. Female cicadas make a similar— although less loud—clicking sound with their wings. Figure 2 shows the locations of active cicadas within the United States.
We measured the prompt neutron decay constant 𝛼 of the CROCUS zero-power reactor at the Swiss Federal Institute of Technology Lausanne using cross-power spectral density (CPSD) analysis of gamma-gamma correlations from two trans-stilbene organic scintillators positioned near the reactor core. We measured critical and subcritical states, with water levels ranging from 960 mm (critical) to 800 mm (𝜌=−1.4 $ subcritical). Our analysis used the Welch method, dividing signal segments for fast Fourier transform (FFT) frequency analysis and applying bootstrapping uncertainty quantification that uses Welch-defined segments. Results demonstrated a clear increase in the measured 𝛼 as reactor reactivity decreased, distinguishing critical from subcritical conditions. At the 960-mm critical level, 𝛼 was estimated at 155.9 ± 0.7 s −1 , and for the 800-mm subcritical level, 𝛼 increased significantly to 367.3 ± 6.9 s –1 . A linear regression of subcritical states yielded a critical estimate of 154.0 ± 3.1 s –1 , aligning with the static 𝛼 estimate at critical. The bootstrapping method produced normally distributed 𝛼 estimates, confirming data consistency. The gamma CPSD 𝛼 estimates clearly distinguish reactor states and improve monitoring of zero-power reactors. The future deployment of modular and microreactors as potential candidates for noise analysis is demonstrated in CROCUS, particularly zero-power mock-ups of new designs. The improvement of noise analysis in the subcritical domain from this work will support experimental data for reactor deployment and procedure.
The software utilizes frequency, amplitude, and phase features from sensor signals (either raw or processed) that are extracted using recursive frequency analysis, enabling (1) understanding of reactor operations under different operating conditions, (2) identifying of quiescent frequency ranges for sensor development, (3) system controls (4) predictive analytics, (5) structural health monitoring, and (6) loose part monitoring.
In this paper, finite element method simulations and frequency analysis of additively manufactured windings with a Hilbert–cross section pattern were performed over a wide frequency range. The current density distributions for the proposed winding conductor and for a square-wire winding conductor at selected frequencies were compared. An approximately 25% winding loss reduction at higher frequencies and an approximately 5% increase at low frequencies were observed for the analyzed Hilbert structure.
Dynamometer testing of full-scale wind turbine drivetrains involves subjecting integrated components to extreme static loads, fatigue loads, or dynamic loads to replicate field conditions. This paper provides a detailed evaluation of the uncertainty and errors in applied loads and measured responses, and their magnitude relative to established repeatability bounds for a drivetrain subjected to static and dynamic loads on the 7.5 MW test bench at the Clemson University Wind Turbine Drivetrain Testing Facility. An ideal drivetrain simulation model is utilized to isolate the influence of load tracking errors on test article responses. It is shown that the test article response variations are mainly driven by run out and clearances inherent to the drivetrain. For the dynamic profiles, the load tracking errors are within acceptable limits. Furthermore, a frequency analysis is used to show that the test bench controller tracking performance is acceptable for profiles with frequency content up to 1.5 Hz.
While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.
ABSTRACT We report the frequency analysis of a known roAp star, HD 86181 (TIC 469246567), with new inferences from Transiting Exoplanet Survey Satellite (TESS) data. We derive the rotation frequency to be νrot = 0.48753 ± 0.00001 d−1. The pulsation frequency spectrum is rich, consisting of two doublets and one quintuplet, which we interpret to be oblique pulsation multiplets from consecutive, high-overtone dipole, quadrupole, and dipole modes. The central frequency of the quintuplet is 232.7701 d−1 (2.694 mHz). The phases of the sidelobes, the pulsation phase modulation, and a spherical harmonic decomposition all show that the quadrupole mode is distorted. Following the oblique pulsator model, we calculate the rotation inclination, i, and magnetic obliquity, β, of this star, which provide detailed information about the pulsation geometry. The i and β derived from the best fit of the pulsation amplitude and phase modulation to a theoretical model, including the magnetic field effect, slightly differ from those calculated for a pure quadrupole, indicating the contributions from ℓ = 4, 6, 8,... are small. Non-adiabatic models with different envelope convection conditions and physics configurations were considered for this star. It is shown that models with envelope convection almost fully suppressed can explain the excitation at the observed pulsation frequencies.
Low-power analog filter banks provide frequency analysis with minimal power and space requirements, making them viable solutions for integrated remote audio- and vibration-sensing applications. Compared with their digital counterparts, analog filter banks are better suited to achieve the lower power consumption necessary for IoT applications, while maintaining high dynamic range and a wide operational frequency range. In this work, the design and implementation of a sub-threshold complementary metal-oxide semiconductor (CMOS) integrated low-power tunable analog filter channel for signal spectrum analysis and signal discrimination is presented. Project specifications required a programmable, high-order, monolithic bandpass filter channel with small chip area, low power consumption, high dynamic range, and wide operational frequency range. The 8th-order filter channel presented in this work provides an effective Q-factor of 4.5 and a minimum dynamic range (DR) of approximately 85 dB, while allowing for tuning across a range of center frequencies from 2 kHz to 100 kHz, with power consumption of a single 8th-order filter channel measured at 256 µW nominally at the highest center frequency. An integrated analog Gm-C filter topology was selected for this application. Functionally, the high-Q bandpass filter transfer function is implemented via four cascaded 2nd-order filter cells, resulting in a single 8th-order filter channel, fabricated in 130-nm 1.2-V CMOS technology, suitable for use in monolithic integrated spectral analysis (MISA1) applications.
This paper provides statistical analysis of the characteristics of power system outages to gain a better understanding of the impacts of the increasing severe weather conditions on the outages. 10-year historical power system outage data from the Bonneville Power Administration (BPA) were gathered together with co-located weather attributes and recorded extreme weather events in the service area, which are paired in comparable spatial and temporal scales, with a focus on each outage transmission line. Statistical frequency analysis and cross-tabular evaluation are performed to investigate the occurring frequency and duration of outages associated with extreme weather in this area of study. The study reveals that the weather-related outages can be mainly attributed to hail and thunderstorm events which correspond to up to 60% out of all failures in several transmission line types.
A recent upgrade to the Imaging Neutral Particle Analyzer (INPA) on DIII-D has allowed for the first fluctuation measurements using an INPA to be taken during a neoclassical tearing mode (NTM). The INPA signal tracked the mode over 150 ms as the mode frequency dropped to zero, capturing both the NTM with poloidal and toroidal mode numbers $m/n=2/1$ and a $3/2$ mode at double the frequency. Analysis shows that the signals originate from charge exchange events near the edge of the plasma, and relative fluctuation amplitudes are greater than 25% for the duration of the NTM. Filtered signals show frequency beating patterns that are phase-space dependent. Simulated signal is dominated by prompt transport from the neutral beams to the INPA sightline, while the contribution from the slowing down distribution is significantly lower. Simulated measurements in the range of pitches that the diagnostic is sensitive to (0.5≤|v∥/v|≤ 0.75) show the signal is dominated by trapped orbits that pass through magnetic islands near the edge of the plasma. Calculations of expected fluctuation levels show that only direct interaction with the NTM can provide the strong relative fluctuation levels seen experimentally. The prompt nature of the orbits and thin radial layer found to contribute to synthetic signals suggest INPA passive data may be used to measure the perturbations of confined orbits on a single pass through a plasma instability.