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Photometer detects motion for measuring response speed and acceleration of servocontrol system. Instrument senses selected output movement shortly after operator activates hand-controlled input. Time delay is measured on X/T recorder and response calculated. With suitable motion targets, photometer measures any open- or closed-loop servoresponse and servorate or computer lag without system disturbance.
The method of particle analysis by mass spectrometry has been applied to the quantitative measurement of sodium chloride in individual particles on a real-time basis. Particles of known masses are individually introduced, in the form of a beam, into a miniature Knudsen cell oven (1600 K). The oven is fabricated from rhenium metal sheet (0.018 mm thick) and is situated in the ion source of a quadrupole mass spectrometer. A particle once inside the oven is trapped and completely volatilized; this overcomes the problem of partial volatilization due to particles bouncing from the filament surface. Individual particles are thermally volatilized and ionized inside the rhenium oven, and produce discrete sodium ion pulses whose intensities are measured with the quadrupole mass spectrometer. An ion pulse width of several milliseconds (4-12 ms) is found for particles in the mass range 1.3 x 10 to the -13th to 5.4 x 10 to the -11th g. The sodium ion intensity is found to be proportional to the particle mass to the 0.86-power. The intensity distribution for monodisperse aerosol particles possesses a geometric standard deviation of 1.09, showing that the method can be used for the determination of the mass distribution function with good resolution in a polydisperse aerosol.
An instrumentation system was developed for reciprocating engines. Among the parameters measured are the indicated mean effective pressure, or theoretical work per cycle, and the mass fraction burn rate, a measure of the combustion rate in the cylinder. These computations are performed from measured cylinder pressure and crankshaft angle and are available in real time for the experimenter. A 100 or 200 consecutive-cycle sample is analyzed to reduce the effect of cyclic variations in the engine. Data are displayed in bargraph form, and the mean and standard deviation are computed. Other instruments are also described.
Carrier transit time in selenium. liumogen, sodium salicylate, alkali halides, electron multiplication
In this paper the relativistic transformations that are necessary to transform the results of earth-based astronomical timing observations from the terrestrial frame in which the observations are made to the proper frame of the astronomical object being observed are derived. Two coordinate systems are considered, the first being the parametrized post-Newtonian coordinate system and the second being a coordinate system based on the use of temps dynamique barycentrique as a time coordinate. Effects due to propagation of signals through curved spacetime and due to the relativistic gravitational time dilation for the earth are derived in each system. The results are then applied to three modern accurate data types spacecraft ranging, pulsar timing, and VLBI. A new effect is found in the analysis of VLBI data, amounting to a rescaling of VLBI-determined baselines produced by the curvature of space in the neighborhood of the sun.
The variation of solar p-mode travel times with cyclic frequency nu is shown to provide information on both the radial variation of the acoustic potential and the depth of the effective source of the oscillations. Observed travel-time data for waves with frequency lower than the acoustic cutoff frequency for the solar atmosphere (approximately equals 5.5 mHz) are inverted to yield the local acoustic cutoff frequency nu(sub c) as a function of depth in the outer convection zone and lower atmosphere of the Sun. The data for waves with nu greater than 5.5 mHz are used to show that the source of the p-mode oscillations lies approximately 100 km beneath the base of the photosphere. This depth is deeper than that determined using a standard mixing-length calculation.
The ion temperature varying during inertial confinement fusion implosions changes the amount of Doppler broadening of the fusion products, creating subtle changes in the fusion neutron pulse as it moves away from the implosion. A diagnostic design to try to measure these subtle effects is introduced—leveraging the fast time resolution of gas Cherenkov detectors along with a multi-puck array that converts a small amount of the neutron pulse into gamma-rays, one can measure multiple snapshots of the neutron pulse at intermediate distances. Further, precise measurements of the propagating neutron pulse, specifically the variation in the peak location and the skew, could be used to infer time-evolved ion temperature evolved during peak compression.
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A preliminary experimental study has been conducted to gain insight into the temporal and spatial contents of largescale structures in a convective Mach number = 0.51 high Reynolds number planar two-dimensional compressible free shear layer. Power spectra, coherence, and space-time correlations were obtained using single- and two-point pressure measurements. Both developing and fully developed regions of the flow were investigated. The passage frequency of structures were found to be 10-15 kHz in the developing region and 4-8 kHz in the fully developed region. The convective velocity obtained from the space-time correlation in the middle of the shear layer was close to the theoretical value but varied toward the edge of the shear layer. The structures were shown to be surprisingly three-dimensional even in this low compressibility level shear layer. The structures size and spacing were also determined and discussed.
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.
In recent years, hydrogen-carrying compounds have accrued interest as an alternative to traditional fossil fuels due to their function as zero-emission fuels. As such, there is interest in investigating hydrogen-carrying compounds to improve understanding of the fuels' characteristics for use in high pressure systems. In the current study, the oxidation of ammonia/natural gas/hydrogen mixtures was carried out to study carbon monoxide (CO) formation profiles as well as the ignition delay times (IDTs) behind reflected shock waves in order to refine chemical kinetic models. Experiments were carried out in the University of Central Florida's shock tube facility by utilizing chemiluminescence to obtain OH* emission and laser absorption spectroscopy to obtain CO profiles over a temperature range between 1200 K and 1800 K with an average pressure of 2.2 atm. Experimental mixtures included both neat and combination natural gas/hydrogen with ammonia addition, with all mixtures except one having an equivalence ratio of 1. Results were then compared with the GRI 3.0 mechanism, as well as the newly developed UCF 2022 mechanism utilizing chemkin-pro software. In general, both models were able to capture the trend in auto-ignition delay times and CO time histories for natural gas and ammonia mixtures. However, for ammonia–hydrogen mixtures, GRI 3.0 failed to predict ignition delay times, whereas the UCF 2022 mechanism was able to capture the IDTs within the uncertainty limits of the experiments. A sensitivity analysis was conducted for different mixtures to understand the important reactions at the experimental conditions. Lastly, a reaction pathway analysis was carried out to understand important ammonia decomposition pathways in the presence of hydrogen and natural gas.
Abstract In recent years, hydrogen-carrying compounds have accrued interest as an alternative to traditional fossil fuels due to their function as zero-emission fuels. As such, there is interest in investigating hydrogen-carrying compounds to improve understanding of the fuels’ characteristics for use in high-pressure systems. In the current study, the oxidation of ammonia/natural gas/hydrogen mixtures was carried out to study CO formation profiles as well as the ignition delay times behind reflected shock waves in order to refine chemical kinetic models. Experiments were carried out in the University of Central Florida’s shock tube facility by utilizing chemiluminescence to obtain OH* emission and laser absorption spectroscopy to obtain CO profiles. Experimental results were then compared with the GRI 3.0 mechanism, as well as the proprietary UCF 2022 mechanism utilizing CHEMKIN-Pro software. In general, both models were able to capture the trend in autoignition delay times and CO time histories for natural gas and ammonia mixtures. However, for ammonia-hydrogen mixtures, GRI 3.0 failed to predict ignition delay times whereas the UCF 2022 mechanism was able to capture the IDTs within the uncertainty limits of the experiments. A sensitivity analysis was conducted for different mixtures to understand the important reactions at the experimental conditions. Finally, a reaction pathway analysis was carried out to understand important ammonia decomposition pathways in the presence of hydrogen and natural gas.
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.
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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.
The project, a collaboration between the Ross Lab at MIT and the Filler Lab at Georgia Tech, aimed to combine in situ microscopy and spectroscopy measurements to answer fundamental questions about the physics and chemistry governing the bottom-up vapor-solid-liquid (VLS) growth of one-dimensional (1-D) functional oxides. This work supported one PhD student and 1 postdoc. One paper has been published and 5 others are in preparation. To date, this work has been presented at 5 conferences.