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At least 19 records

Timing measurement apparatus

Methods, devices and systems for providing accurate measurements of timing errors using optical techniques are described. An example timing measurement device includes an optical hybrid that receives two optical pulse trains and produces two or more phase shifted optical outputs. The timing measurement device further includes two or more optical filters that receive the outputs of the optical hybrid to produce multiple pulse signals with distinctive frequency bands. The device also includes one or more photodetectors and analog-to-digital converters to receive to produce electrical signals in the digital domain corresponding to the optical outputs of the hybrid. A timing error associated with the optical pulse trains can be determined using the electrical signals in digital domain based on a computed phase difference between a first frequency band signal and a second frequency band signal and a computed frequency difference between the first frequency band signal and the second frequency band.

DeVore, Peter Thomas Setsuda↗

A Catalog of Temporally Localized Systematic Deviations in Global Body Wave Travel-Time Measurements

Accurate measurements of the arrival times of seismic waves are crucial for seismological analyses such as robust locations of earthquakes, characterization of seismic sources, and high-fidelity imaging of the Earth’s interior. However, these travel-time measurements can sometimes be contaminated by timing errors at the stations which record this data. In this study, we apply a classical approach, based on identifying time-dependence in measured body wave arrival times, to identify these timing errors in a dataset on the order of 107 individual measurements. We find timing deviations at a subset of the stations in our dataset and document the temporal location, extent, and severity of these errors, finding errors at 83 stations, and impacting ~100,000 measurements. This catalog of deviations may enable future investigators to obtain a more accurate dataset through the implementation of quality control measures to eliminate the contaminated data we have identified.

58 GEOSCIENCES↗

Real-Time Measurements of Gas-Phase Medium-Chain Chlorinated Paraffins Reveal Daily Changes in Gas-Particle Partitioning Controlled by Ambient Temperature

Chlorinated paraffins (CPs) are synthetic polychlorinated n-alkanes produced as mixtures of a range of C x Cl y H 2x–y+2 formulas. CPs have numerous industrial applications but are toxic, long-lived, and environmentally ubiquitous with environmental releases occurring throughout their production, use, and disposal. Short-chain chlorinated paraffins (SCCPs, C 10–13 ) have been regulated by the United States Environmental Protection Agency since 2009 and by the Stockholm Convention since 2017. SCCP regulation is expected to cause increased production of medium-chain chlorinated paraffins (MCCPs; C 14–17 ), which are currently under consideration for Stockholm Convention regulations. Thus, there is a need to improve the understanding of MCCP environmental transport, distribution, and fate. Existing measurements are limited in their spatial and temporal coverage. Measurements of CP atmospheric loading are particularly scarce. Historically, these measurements have required long sampling times, obscuring the temporal behavior of atmospheric CPs. We report real-time in situ measurements of 18 gas-phase MCCPs. These measurements were made in the United States Southern Great Plains with nitrate ion chemical ionization mass spectrometry (NO 3 –CIMS). Here, the estimated average lower-limit concentration of MCCPs is on the order of single-digit ng/m 3 . MCCP diel behavior is partially explained by gas-particle partitioning with implications for MCCP transport and lifetimes.

54 ENVIRONMENTAL SCIENCES↗

Optimal Traffic Signal Control Using Priority Metric Based on Real-Time Measured Traffic Information

Optimizing traffic control systems at traffic intersections can reduce network-wide fuel consumption as well as improve traffic flow. While traffic signals have conventionally been controlled based on predetermined schedules, various adaptive control systems have been developed recently using advanced sensors such as cameras, radars, and LiDARs. By utilizing rich traffic information enabled by the advanced sensors, more efficient or optimal traffic signal control is possible in response to varying traffic conditions. This paper proposes an optimal traffic signal control method to minimize network-wide fuel consumption utilizing real-time traffic information provided by advanced sensors. This new method employs a priority metric calculated by a weighted sum of various factors, including the total number of vehicles, total vehicle speed, vehicle waiting time, and road preference. Genetic Algorithm (GA) is used as a global optimization method to determine the optimal weights in the priority metric. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in a high-fidelity traffic simulation environment called SUMO, based on a real-world traffic network. The traffic flow within this model is simulated using actual measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed priority metric-based real-time traffic signal control algorithm can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control and coordinated actuated control methods that are currently used in the modeled network. Additionally, incorporating truck priority in the priority metric leads to further improvements in fuel consumption reduction.

47 OTHER INSTRUMENTATION↗

DME-Propane Ignition Delay Time Measurements at Mixing Controlled Compression Ignition Engine-Relevant Conditions

The blend of dimethyl ether (DME, CH 3 OCH 3 ) and propane (C 3 H 8 ) is a potentially renewable fuel mixture that has the potential to replace diesel in compression ignition engines. The combination can potentially reduce particulate and greenhouse gas emissions compared to a conventional diesel engine operating under similar conditions. However, detailed conceptual and simulation studies must be conducted before adopting a new fuel on a compression ignition engine. For these simulations, accurate chemical kinetic models are necessary. However, the validity of chemical kinetic mechanisms in the literature is unknown for mixing controlled compression ignition (MCCI) engine operating conditions. Hence, in this work, we studied the ignition of dimethyl ether (DME) and propane blends in a shock tube at MCCI engine conditions. Ignition delay time (IDT) data was collected behind the reflected shock for DME-propane mixtures for heavy-duty compression ignition (CI) engine parameters. Undiluted experiments spanning temperatures of 700 to 1100 K and pressures of 55 to 84 bar for various blends (100% CH 3 OCH 3 / 0% C 3 H 8, 100% C 3 H 8 / 0% CH 3 OCH 3 , 60% CH 3 OCH 3 / 40% C 3 H 8 ) of DME and propane were combusted in synthetic air (21% O 2 / 79% N 2 ). Some experiments were conducted at higher pressures (90-120 bar) to understand model performance at these conditions. Comparisons of IDT were made with the predictions of recent chemical kinetic mechanisms for DME-propane mixture, including the Aramco3.0, NUIG, and Dames et al. mechanisms. All mechanisms overpredicted IDT compared to experimental values. Sensitivity analysis was conducted with Dames et al. model, and critical reactions sensitive to IDT of DME-propane mixture near 100 bar are outlined.

Mohammed, Zuhayr Pasha↗

Construction and Modeling of a Coculture Microplate for Real-Time Measurement of Microbial Interactions

The dynamic structures of microbial communities emerge from the complex network of interactions between their constituent microorganisms. Quantitative measurements of these interactions are important for understanding and engineering ecosystem structure. Here, we present the development and application of the BioMe plate, a redesigned microplate device in which pairs of wells are separated by porous membranes. BioMe facilitates the measurement of dynamic microbial interactions and integrates easily with standard laboratory equipment. We first applied BioMe to recapitulate recently characterized, natural symbiotic interactions between bacteria isolated from the Drosophila melanogaster gut microbiome. Specifically, the BioMe plate allowed us to observe the benefit provided by two Lactobacillus strains to an Acetobacter strain. We next explored the use of BioMe to gain quantitative insight into the engineered obligate syntrophic interaction between a pair of Escherichia coli amino acid auxotrophs. We integrated experimental observations with a mechanistic computational model to quantify key parameters associated with this syntrophic interaction, including metabolite secretion and diffusion rates. This model also allowed us to explain the slow growth observed for auxotrophs growing in adjacent wells by demonstrating that, under the relevant range of parameters, local exchange between auxotrophs is essential for efficient growth. The BioMe plate provides a scalable and flexible approach for the study of dynamic microbial interactions.

3D printed device↗

Autoignition Delay Time Measurements of Dimethyl Ether at 110 Bar Inside a Shock Tube

Fuel mixtures of propane and dimethyl ether have been proposed as potential diesel substitutes for use in compression-ignition engines. There is an interest in phasing out diesel fuel because its combustion byproducts are harmful to the environment. Propane and dimethyl ether burn cleaner and produce significantly less carbon dioxide than diesel. The combustion of these fuels at engine-relevant conditions must be characterized to create an engine capable of running on propane and dimethyl ether. In this work, IDT measurements of stoichiometric neat DME diluted in 75% argon were completed for temperatures spanning 800-1200K at 110 bar. A shock tube will be used for all experiments in this work. Experimental IDTs were then compared to simulated values using several well-established mechanisms in the literature.

Guenther, Aaron C. [University of Central Florida]↗

Integration of a real-time orientation measurement system for a real-time evaluator (RTE) to measure the position and orientation of crane-lifted components

Prefabrication of building components holds the potential to revolutionize the construction industry. Prefabrication consists of manufacturing building components, modules, and other elements in a factory to be shipped and installed on a construction site. Prefabricated components have been produced for various applications including precast concrete panels for new construction and exterior wall retrofits. The manufacturing process has seen much innovation in recent years; however, the installation process has seen minimal advancements. A real-time evaluator (RTE) was developed to reduce the installation cost of prefabricated components by reducing installation time, decreasing rework, and improving accuracy. The RTE uses off-the-shelf hardware and novel algorithms to assist erectors with component installation by measuring the real-time positions of connections and prefabricated components, providing installation guidance through a graphical user interface, and monitoring the accumulated installation errors. An overview of the RTE and the proposed workflow is presented. Previous on-site demonstrations provided valuable feedback from users on the potential areas for improvement of the system. One common request was real-time measurement of component orientation during lifting, a process that previously required that the component remain stationary while the laser tracker cycled through target prisms. This paper will present the incorporation and testing of a real-time orientation measurement system as it was implemented into the RTE, allowing for measurement of component orientation during movement.

Selvakumar, Balaji [ORNL]↗

Numerical quantum clock simulations for measuring tunneling times

Here, we numerically study two methods of measuring tunneling times using a quantum clock. In the conventional method using the Larmor clock, we show that the Larmor tunneling time can be shorter for higher tunneling barriers. In the second method, we study the probability of a spin-flip of a particle when it is transmitted through a potential barrier including a spatially rotating field interacting with its spin. According to the adiabatic theorem, the probability depends on the velocity of the particle inside the barrier. It is numerically observed that the probability increases for higher barriers, which is consistent with the result obtained by the Larmor clock. By comparing outcomes for different initial spin states, we suggest that one of the main causes of the apparent decrease in the tunneling time can be the filtering effect occurring at the end of the barrier.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

PickerXL, A Large Deep Learning Model to Measure Arrival Times from Noisy Seismic Signals

Precisely measuring seismic arrival times is a labor-intensive task but is critical for both earthquake monitoring and subsurface imaging. Recently published deep learning models have demonstrated superior performance compared to traditional automatic approaches for picking arrival times. Although existing deep learning models have shown promising results, further advancements are necessary as their performance is not yet satisfactory especially when applied to new regions and station networks. Increasing model size has led to improved performance in other machine learning applications. Here, we aimed to investigate whether enlarging deep learning models can increase performance on accepted benchmarks. We trained three models of varying sizes, small (1X), medium (4X), and large (16X), using globally distributed local and regional earthquake signals and background noise waveforms from a benchmark dataset, Stanford Earthquake Dataset. Our results indicate that the largest model (PickerXL) outperforms both the smaller models and Seisbench implementation of the PhaseNet model, which has the same number of parameters as our small model. The PickerXL model’s enhanced capacity to extract complex patterns from seismograms contributes to its superior arrival picking abilities compared to the smaller model.

Chai, Chengping [Oak Ridge National Laboratory (OR↗

Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Unlike transmission systems, distribution systems do not typically contain sufficient metering to enable real-time state estimation. The lack of sufficient real-time measurements prohibits accurate and timely monitoring of the state of distribution systems. As a result, control and optimal operation of distribution systems, especially those containing large numbers of renewable generation units are not possible without proper data and information about the current state of the system. The main motivation of this project is to address this shortcoming by developing an approach which provides “predicted” real-time measurements so that they can be used to execute a distribution system state estimator. Thus, the objective of the project is to make the distribution systems fully observable, such that the hosting capacity for solar generation can be accurately estimated, and unnecessary solar curtailments can be avoided. In order to accomplish this goal, the project investigated the use of a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams obtained from AMI meters, SCADA as well as PMU measurements and created synchronous measurement snapshots for the state estimator (SE); and developed a hybrid robust SE which provides not only accurate state estimates but also real-time feedback for the ML model refinement.

14 SOLAR ENERGY↗

Prospects for measuring the time variation of astrophysical neutrino sources at dark matter detectors

We study the prospects for measuring the time variation of solar and atmospheric neutrino fluxes at future large-scale xenon and argon dark matter detectors. For solar neutrinos, a yearly time variation arises from the eccentricity of Earth’s orbit and, for charged current interactions, from a smaller energy-dependent day-night variation due to flavor regeneration as neutrinos travel through Earth. For a 100-ton xenon detector running for ten years with a xenon-136 fraction of ≲ 0.1 % , in the electron recoil channel a time-variation amplitude of about 0.8% is detectable with a power of 90% and the level of significance of 10%. This is sufficient to detect time variation due to eccentricity, which has amplitude of ∼ 3 % . In the nuclear recoil channel, the detectable amplitude is about 10% under current detector resolution and efficiency conditions, and this generally reduces to about 1% for improved detector resolution and efficiency, the latter of which is sufficient to detect time variation due to eccentricity. Our analysis assumes both known and unknown periods. We provide scalings to determine the sensitivity to an arbitrary time-varying amplitude as a function of detector parameters. Identifying the time variation of the neutrino fluxes will be important for distinguishing neutrinos from dark matter signals and other detector-related backgrounds and extracting properties of neutrinos that can be uniquely studied in dark matter experiments. Published by the American Physical Society 2024

Zhuang, Yi (ORCID:0000000277138724)↗

Time-resolved measurement of neutron energy isotropy in a sheared-flow-stabilized Z pinch

Previous measurements of neutron energy using fast plastic scintillators while operating the Fusion Z Pinch Experiment (FuZE) constrained the energy of any yield-producing deuteron beams to less than 4.65 keV. FuZE has since been operated at increasingly higher input power, resulting in increased plasma current and larger fusion neutron yields. A detailed experimental study of the neutron energy isotropy in these regimes applies more stringent limits to possible contributions from beam-target fusion. The FuZE device operated at -25 kV charge voltage has resulted in average plasma currents of 370 kA and D–D fusion neutron yields of $4\times10^7 \pm 4\times10^6$ neutrons per discharge. Measurements of the neutron energy isotropy under these operating conditions demonstrates the energy of deuteron beams is less than $7.4 \pm 5.6^\mathrm{(stat)} \pm 3.7^\mathrm{(syst)}$ keV. Characterization of the detector response has reduced the number of free parameters in the fit of the neutron energy distribution, improving the confidence in the forward-fit method. Gamma backgrounds have been measured and the impact of these contributions on the isotropy results have been studied. Additionally, a time dependent measurement of the isotropy has been resolved for the first time, indicating increases to possible deuteron beam energies at late times. This suggests the possible growth of m = 0 instabilities at the end of the main radiation event but confirms that the majority of the neutron production exhibits isotropy consistent with thermonuclear origin.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fluorescence time profile measurement of LAB based liquid scintillator in response to medium relativistic ion particles

Liquid scintillator is widely used in particle physics experiments due to its high light yield, good timing resolution, scalability and low cost. Certain liquid scintillators exhibit pulse shape discrimination capabilities because of difference in fluorescence timing properties induced by different particles. Its fluoresence timing properties have been measured mostly for radioactive decay sources at MeV energies. Here, we present a novel measurement of fluorescence time properties of Linear Alkyl Benzene (LAB) based liquid scintillator in response to high-energy ions of hydrogen (Z = 1), helium (Z = 2) and krypton at around 200–300 MeV/u for the first time. We compared the results to those from radioactive sources and observed a distinct dE / dX dependence, regardless of the particle type. These findings are essential for physics searches such as the diffuse supernova neutrino background in large liquid scintillator detectors like JUNO, and are also critical towards understanding the underlying scintillation timing mechanism.

Ion identification systems↗

Fast data-driven spectrometer with direct measurement of time and frequency for multiple single photons

We present a single-photon-sensitive spectrometer based on a linear array of 512 single-photon avalanche diode detectors with 0.04 nm spectral and 40 ps temporal resolutions. We employ a fast data-driven operation that allows direct measurement of time and frequency for simultaneous single photons, time- and frequency-stamping each single-photon detection. Our results combine excellent temporal and spectral resolution. This work opens numerous applications in quantum photonics, especially when both spectral and temporal properties of single photons can be exploited.

79 ASTRONOMY AND ASTROPHYSICS↗

A diagnostic to measure time-resolved atom column density and Doppler temperature in atomic vapors produced by laser ablation

We report on the development of a diagnostic to measure the time-resolved column density and Doppler temperature of atomic vapors produced by laser ablation. The diagnostic is based on the strong frequency dependence of the atomic susceptibility near an electronic transition in the interrogated atomic species. Interference on the face of a fast photodetector between the several frequency components present in a sinusoidally phase-modulated probe beam will produce a time signature uniquely determined by the column density of atoms in the probed atomic state and the Doppler temperature of the atomic vapor. With the extensive, high precision atomic spectroscopy data available in the literature, it is possible to model the vapor and extract the desired parameters through comparison of the model result with the experimental data.

47 OTHER INSTRUMENTATION↗