SEARCH · Engineering Papers
Results for “statistical”
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.
Finite Bubble Statistics Constrain Late Cosmological Phase Transitions
We consider first order cosmological phase transitions (PTs) happening at late times below standard model temperatures T PT ≲ GeV. The inherently stochastic nature of bubble nucleation and the finite number of bubbles associated with a late-time PT lead to superhorizon fluctuations in the PT completion time. We compute how such fluctuations eventually source curvature fluctuations with universal properties, independent of the microphysics of the PT dynamics. Using cosmic microwave background (CMB) and large scale structure measurements, we constrain the energy released in a dark-sector PT. For 0.1 eV ≲ T PT ≲ keV this constraint is stronger than both the current bound from additional neutrino species ΔN eff , and in some cases, even CMB-S4 projections. Future measurements of CMB spectral distortions and pulsar timing arrays will also provide competitive sensitivity for keV ≲ T PT ≲ GeV.
Statistical detection of Josephson, Andreev, and single quasiparticle currents in scanning tunneling microscopy
Not Available
Dynamical quantum ergodicity from energy level statistics
Not Available
Disentangling the impact of quasiparticles and two-level systems on the statistics of superconducting-qubit lifetime
Temporal fluctuations in the superconducting qubit lifetime, T 1 , present additional challenges in the pursuit of fault-tolerant quantum computing. Although the exact mechanisms remain unclear, T 1 fluctuations are generally attributed to strong coupling between the qubit and a few near-resonant two-level systems (TLSs), which can exchange energy with an ensemble of thermally fluctuating two-level fluctuators (TLFs) at low frequencies. Here, we report T 1 measurements of qubits with varying geometrical footprints and surface dielectrics as a function of temperature. By analyzing the noise spectrum of the qubit depolarization rate, Γ 1 = 1 / T 1 , we disentangle the contributions of TLSs, nonequilibrium quasiparticles (QPs), and equilibrium (thermally excited) QPs to the variance in Γ 1 . We find that the Γ 1 variance in qubits with smaller footprints is more susceptible to QP and TLS fluctuations than that in larger-footprint qubits. Furthermore, the QP-induced variances in all qubits align with the theoretical framework of QP diffusion and fluctuation. These findings offer valuable insights for future qubit design and engineering optimization.
A Statistical Assessment of Zener Diode Behavior Using Functional Data Analysis.
Abstract not provided.
Understanding HPC Application I/O Behavior Using System Level Statistics
Explore the source record for details and available documents.
PV Hosting Capacity Estimation in Low-Voltage Secondary Networks Using Statistical Properties of AMI Data
Explore the source record for details and available documents.
Statistical Performance of Forced Oscillation Detectors in the Presence of Missing Measurements
In bulk power systems, measurement-based monitoring for large oscillations can help maintain system reliability. One of the challenges encountered in a recent field demonstration was the unavailability of measurements due to underlying measurement quality or communication problems. During the demonstration, the oscillation detector ignored a measurement location if even 10 seconds of data was missing. To extend the detector's ability to operate in these conditions, this paper evaluates the impact of three methods for addressing missing data. The strengths and weaknesses of each approach are evaluated using theoretical expressions for the probability of detection along with results from simulated data and publicly available field measurements. Based on these results, a suitable approach is identified that can extend the oscillation detector's performance when large segments of data are missing.
Statistical Performance Analysis on Approximately 320 Perovskite Single- and Two-Junction Solar Cells and Modules from >30 Global Sources
As perovskite photovoltaics (PV) advance from the laboratory to commercial prototypes, their accurate and reliable performance testing is becoming increasingly important. The well documented dynamic response of perovskite solar cells to an external applied voltage has led to the development of steady-state performance measurement methods; however, these methods have not been widely adopted by the perovskite PV community. A key reason for this is that steady-state measurement methods take tens of minutes to complete, as opposed to conventional "fast" current-voltage (I-V) measurements usually lasting a few seconds. Fast I-Vs arise from a snapshot, almost always not a steady-state condition of the device; however, given their widespread use, the question arises: how do performance parameters of perovskite PV compare when measured with fast I-V and with a steady-state method? We compile results from ca. 320 perovskite PV cells and modules, including single junction, and two-terminal perovskite-perovskite and perovskite-Si tandems, and show that fast I-Vs can provide a useful measure of the open-circuit voltage of the devices, while the short-circuit current and the overall efficiency can be widely misestimated. We discuss implications of these findings on performance testing protocols and propose possible options for fast and accurate testing of perovskite PV.
Performance Loss Rate Estimation of Fielded Photovoltaic Systems Based on Statistical Change-Point Techniques .
Abstract not provided.
Statistical Behavior of Low-Amplitude Power System Point-on-Wave Measurements
The power grid is undergoing massive changes to ensure resiliency and reliability in a more decentralized world. Distributed energy resources are becoming a prominent source of generation, potentially leading to a lack of centralized generation sources. Due to these new behaviors and system topologies, it is important to install measurement devices that are 1) accurate and 2) self-aware of their measurement quality. In this paper, a residential-scale microgrid is used to generate voltage and current waveforms, captured by Verivolt and National Instruments measurement equipment. A least-squares approach is used to separate the “clean” signals from the noise. Finally, Gaussian mixture modeling is used to approximate noise distributions, and it is shown these higher-order distribution estimates are a better fit to voltage and current noise profiles than single-mode Gaussian estimates.
Uncertainty Visualization of 2D Morse Complex Ensembles Using Statistical Summary Maps
Not provided.
Comparison of the spatial statistics of random and defined-sequence photoresist films
The resolution-line edge roughness-sensitivity tradeoff has motivated the exploration of potential improvements using defined sequence polymers and polymer-bound photoacid generators and quenchers. We characterize the internal structures of positive tone photoresist polymer films formed from defined sequence polymers and compare them with random copolymers of the same composition. We model their imaging to connect initially to developable film structures. We use a polymer packing algorithm to simulate films of diverse compositions and locations of photoacid generators and quenchers, using the composition of an ESCAP photoresist. We use a simple extreme ultraviolet exposure-deprotection algorithm to model developable image formation within them. In all cases, the spatial distribution of chemical moieties in the film for defined sequence polymers is nearly indistinguishable from random copolymers. We evaluate several exposure-deprotection scenarios and find that a defined sequence copolymer has a distinctive developable image under certain circumstances. The use of defined sequence polymers within a photoresist layer does not automatically result in improved imaging; however, they do have some characteristics different from random polymers of the same composition. Further study of these characteristics may provide a route to improved control over the nanoscale imaging process.
Sensitive detection of structural dynamics using a statistical framework for comparative crystallography
Chemical and conformational changes are crucial to protein function and its pharmacological control. X-ray crystallography can reveal these changes in atomic detail, but standard analysis methods, which refine separate datasets, often overlook differences that are subtle or arise in only a subset of molecules. Direct comparison of crystallographic datasets is, in principle, more powerful, but systematic errors (“scales”) often mask changes in the crystallographic observables (“structure factors”). Machine learning algorithms that jointly estimate scales and structure factors can address this limitation. Here, we augment this approach with multivariate, structured priors derived from crystallographic theory, implemented in the variational deep learning framework Careless. Doing so strongly improves the detection of protein dynamics, element-specific anomalous signals, and the binding of drug candidates, offering a robust approach to comparative crystallography and, potentially, to detection of protein dynamics by other structure determination methods.
Nucleon-induced inelastic scattering with statistical strength functions and the ECIS direct reaction code
Modern theoretical descriptions of inelastic scattering make use of multi-step direct reaction approaches together with transition potentials obtained from sophisticated nuclear structure models. Here we demonstrate how the complexity of such calculations can be reduced to permit simpler ones, also using the ECIS code, but providing an almost equally precise alternative to a much more detailed calculation. We have studied the transition form factors within the random phase approximation (RPA), where these are obtained as linear combinations of particle–hole states. At moderate to high excitation energies, where interference effects tend to disappear, we have proposed an independent particle–hole formalism in which particle–hole states are spread in energy with an appropriate strength function obtained from the RPA. The effects of more complex modes, such as 2p–2h ones, are simulated with widths calculated in a semi-classical context. In this work, we verify the validity of our approximations for pre-equilibrium proton-induced reactions on 90 Zr target. Our calculations provide a good description of the reaction data and point toward a simplification of the description of nucleon-induced reactions based on averages of microscopic details of the projectile–target interaction.