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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.
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Height of flight-simulator probe above model of terrain measured by automatic laser triangulation system. Airplane simulated by probe that moves over model of terrain. Altitude of airplane scaled from height of probe above model. Height measured by triangulation of laser beam aimed at intersection of model surface with plumb line of probe.
Molecular flow velocity (one component), translational temperature, and static pressure of N2 are measured in a supersonic wind tunnel using inverse Raman spectroscopy. For velocity, the technique employs the large Doppler shift exhibited by the molecules when the pump and probe laser beams are counterpropagating (backward scattering). A retrometer system is employed to yield an optical configuration insensitive to mechanical vibration, which has the additional advantage of simultaneously obtaining both the forward and backward scattered spectra. The forward and backward line breadths and their relative Doppler shift can be used to determine the static pressure, translational temperature, and molecular flow velocity. A demonstration of the technique was performed in a continuous airflow supersonic wind tunnel in which data were obtained under the following conditions: (1) free-stream operation at five set Mach number levels over the 2.50-4.63 range; (2) free-stream operation over a range of Reynolds number (at a fixed Mach number) to vary systematically the static pressure; and (3) operation in the flow field of a simple aerodynamic model to assess beam steering effects in traversing the attached shock layer.
Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts.
Detecting helium leakage is important in many applications, such as in dry cask nuclear waste storage systems. This work develops a helium detection system based on the relative permittivity (dielectric constant) difference between air and helium. This difference changes the status of an electrostatic microelectromechanical system (MEMS) switch. The switch is a capacitive-based device and requires a very negligible amount of power. Exciting the switch’s electrical resonance enhances the MEMS switch sensitivity to detect low helium concentration. This work simulates two different MEMS switch configurations: a cantilever-based MEMS modeled as a single-degree-freedom model and a clamped-clamped beam MEMS molded using the COMSOL Multiphysics finite-element software. While both configurations demonstrate the switch’s simple operation concept, the clamped-clamped beam was selected for detailed parametric characterization due to its comprehensive modeling approach. The beam detects at least 5% helium concentration levels when excited at 3.8 MHz, near electrical resonance. The switch performance decreases at lower excitation frequencies or increases the circuit resistance. The MEMS sensor detection level was relatively immune to beam thickness and parasitic capacitance changes. However, higher parasitic capacitance increases the switch’s susceptibility to errors, fluctuations, and uncertainties.
A very-high resolution multispectral television camera system is being developed for use on the earth resources technology satellite (ERTS) program. There are three cameras in the system, each viewing the same area but operating in the blue-green, red, and near-infrared spectral bands. In the laboratory the cameras' limiting resolution is 4500 TV lines over the 25 + 25-mm image format of the return beam vidicon (RBV). A model was developed to predict the resolving power performance of the RBV camera under realistic conditions. To verify the model, tests were conducted using the RBV camera, a laser-beam image reproducer and a series of AF tribar test patterns of known values of contrast. As a more graphic demonstration, simulated multispectral images were generated using color-IR photographs from Apollo 9. The measured signal-to-noise, resolution, and spectral characteristics of the ERTS Flight A and Flight B three-camera systems are presented in conclusion.
Particle accelerators operate under dynamically changing conditions, which often lead to data distribution drifts. These drifts pose significant challenges for Machine Learning (ML) models, which typically fail to maintain performance when faced with such non-stationary data. In particle accelerators, the primary sources of these data drifts include changes in accelerator settings and non-measured parameters such as machine degradation and environmental factors. Previous research has proposed conditional models to handle multiple beam configurations effectively; however, it is challenging to train the ML models on all possible configuration settings. Additionally, conditional models alone can not address performance degradation caused by drifts due to non-measured factors. These limitations contribute to a significant gap between ML development and its deployment in real-world operational settings. To bridge this gap, in this paper, we identify some of the key areas within particle accelerators where continual learning can help mitigate drift-induced performance degradation. In addition, we present a practical use case where a conditional Auto-Encoder model coupled with memory-based continual learning has been employed to demonstrate stable performance even when underlying data drifts
The MicroBooNE detector is a liquid argon time projection chamber (LArTPC) that produces three-dimensional images of particle interactions using ionization charge collected by anode wire plane arrays and scintillation light collected by a light detection system. In addition to testing long-standing experimental neutrino anomalies and performing measurements of neutrino interactions with argon nuclei using the Fermilab Booster Neutrino Beam, MicroBooNE aims to develop methodologies for rare beyond the Standard Model and off-beam physics searches. Looking ahead to the upcoming Deep Underground Neutrino Experiment (DUNE), with MicroBooNE serving as a valuable testbed, achieving high sensitivity and livetime for off-beam physics while satisfying data processing and storage constraints will require data-driven, intelligent, and online or real-time data selection techniques. These techniques are essential for reducing data rates and preserving rare signals with high accuracy. In this paper, we describe a fast data selection algorithm suitable for online execution to identify electrons from stopping cosmic ray muons in the MicroBooNE detector utilizing ionization charge information, and present its performance. This represents the first demonstration of online data selection in a LArTPC using real data and charge information exclusively and provides an important proof-of-principle for applying such techniques to other LArTPC experiments such as the Short-Baseline Near Detector and DUNE.
The linear elastic response is determined for an internally pressurized, long circular cylindrical shell stiffened on the inside by a regular arrangement of identical stringers and identical rings. Periodicity of this configuration permits the analysis of a portion of the shell wall centered over a generic stringer-ring joint; i.e., a unit cell model. The stiffeners are modeled as discrete beams, and the stringer is assumed to have a symmetrical cross section and the ring an asymmetrical section. Asymmetery causes out-of-plane bending and torsion of the ring. Displacements are assumed as truncated double Fourier series plus simple terms in the axial coordinate to account for the closed and pressure vessel effect (a non-periodic effect). The interacting line loads between the stiffeners and the inside shell wall are Lagrange multipliers in the formulation, and they are also assumed as truncated Fourier series. Displacement continuity constraints between the stiffeners and shell along the contact lines are satisfied point-wise. Equilibrium is imposed by the principle of virtual work. A composite material crown panel from the fuselage of a large transport aircraft is the numerical example. The distributions of the interacting line loads, and the out-of-plane bending moment and torque in the ring, are strongly dependent on modeling the deformations due to transverse shear and cross-sectional warping of the ring in torsion. This paper contains the results from the semiannual report on research on 'Pressure Pillowing of an Orthogonally Stiffened Cylindrical Shell'. The results of the new work are illustrated in the included appendix.
A steady-state carrier computer code, PECK (Parker Enhanced Carrier Kinetics), that predicts the radiation-induced conductivity (RIC) produced in a dielectric by an electron beam was developed. The model, which assumes instantly-trapped holes, was then applied to experimental measurements on thin Kapton samples penetrated by an electron beam. Measurements at high bias were matched in the model by an appropriate choice for the trap-modulated electron mobility. A fractional split between front and rear currents measured at zone bias is explained on the basis of beam-scattering. The effects of carrier-enhanced conductivity (CEC) on data obtained for thick, free-surface Kapton samples is described by using an analytical model that incorporates field injection of carriers from the RIC region. The computer code, LWPCHARGE, modified for carrier transport, is also used to predict partial penetration effects associated with CEC in the unirradiated region. Experimental currents and surface voltages, when incorporated in the appropriate models, provide a value for the trap modulated mobility that is in essential agreement with the RIC results.
For nearly 60 years, cold field emitters have been the source of choice for electron microscopy due to their high brightness and relatively low energy spread. In this paper, we have examined an alternative: nanoscale electron sources based on near-threshold photoemission. While these sources have not yet been realized, they hold the potential to produce significantly brighter beams than cold field emitters. We model electron–electron Coulomb interactions in beams emitted from such sources to calculate the impact of these interactions on the brightness and the energy spread. Our results show that these sources can theoretically deliver more than an order of magnitude brighter electron beams compared to cold field emitters along with more than an order of magnitude smaller energy spread, before being limited by the Coulomb interactions. Electron sources with such high brightness and low energy spread would be transformational for electron microscopy, enabling electron energy loss-based vibrational spectroscopy at the sub-nanometer scale.
Determining the toroidal rotation for future tokamaks like ITER is a challenging and important problem. By combining empirical scalings for the intrinsic rotation at the top of the pedestal with the expected neutral beam torque and modeling of momentum transport, the toroidal rotation profile for ITER is predicted with TGYRO using TGLF (SAT0 and SAT1). On axis rotation exceeds 20 krad s –1 and the E x B shear is significant enough to reduce turbulent transport and significantly increase confinement and fusion power when comparing to cases that ignore the effect of rotation. Here, the prediction of the rotation at the top of the pedestal is made with increased confidence due to experiments and modeling in DIII-D that have determined the importance of fast-ion and neutral particle transport effects on intrinsic rotation at this location. In particular, the effect of neutral particles on momentum transport in the pedestal region is found to be insignificant.
Abstract The injection of electron cyclotron (EC) waves fulfills a number of important tasks in nuclear fusion devices for which detailed knowledge of the spatial power deposition profile is critical. This deposition profile is commonly determined using forward models such as beam or ray tracing. Recent numerical and experimental studies have shown that small-angle scattering of the EC beam as it passes through the turbulent plasma edge can cause significant broadening of the effective deposition profile, leading to considerable underestimation of the deposition width by forward methods. However, traditional inverse methods to determine the deposition profile from measurements overestimate the deposition profile width due to transport broadening. In this work, we implement three novel methods to resolve the EC power deposition profile from measurements that counteract transport broadening by simultaneously resolving transport and power deposition. We validate their assumptions and compare the results from these methods to the traditional break-in-slope method as well as to the TORAY ray-tracing code in a set of DIII-D discharges spanning five different confinement modes. We show that the four different inverse methods, novel and established, paint a consistent picture of deposition broadening. Specifically, we show that the measured power deposition profile is between 1.6 and 3.6 times wider than the TORAY profiles. Moreover, we show the considerable consequences that this level of broadening can have for ITER.
Bosonic pure-loss channel, which represents the process of photons decaying into a vacuum environment, has zero quantum capacity when the channel’s transmissivity is less than 50%. Modeled as a beam splitter interaction between the system and its environment, the performance of bosonic pure-loss channel can be enhanced by controlling the environment state. We show that by choosing the ideal Gottesman-Kitaev-Preskill (GKP) states for the system and its environment, perfect transmission of quantum information through a beam splitter is achievable at arbitrarily low transmissivities. Our explicit constructions allow for experimental demonstration of the improved performance of a quantum channel through passive environment assistance, which is potentially useful for quantum transduction where the environment state can be naturally controlled. In practice, it is crucial to consider finite-energy constraints, and high-fidelity quantum communication through a beam splitter remains achievable with GKP states at the few-photon level.
The ITS venue provides the first opportunity to fully assemble and test the performance of the injector; integrate, assemble and test four modules; measure the severity of the Beam Break-Up instability and perform the first set of beam measurements. Figure 1 shows a high level configuration of the ITS without the system of overhead cable management trays. The final configuration will integrate the injector, 4 modules (12 accelerator cells), 264 SSPP Line Replaceable Units (LRUs), global controls, data acquisition, and a subset of the downstream transport, Table 1. This was chosen because it provides the minimum accelerator cells required to measure the Beam Break-Up (BBU) instability and perform measurements required to validate the ASD beam transport computer models, which are priority measurements for commissioning.
Ongoing work in air-vehicle design illustrates the potential of advanced concepts to provide significant improvements in efficiency; but with their incorporation of lightweight flexible structures, such configurations may require active control systems to ensure reliability and safety. However, many contemporary analysis methods are inefficient for aeroelastic analysis and design of such configurations. This paper describes the development of a new approach that automates the geometry setup, mesh generation, and assembly of fluid–structural coupling interfaces to enable efficient aeroelastic and aeroservoelastic analysis of advanced concepts. The core elements for this approach are a cut-cell Cartesian grid-based computational fluid dynamics solver, a nonlinear beam element structural model, a conservative fluid–structural interface treatment, and the formulation and implementation of a new deforming grid capability within the cut-cell Cartesian grid solver. In this paper, emphasis is on this latter component with detailed description given of the mesh motion strategy, evaluation of fluxes and structural loads at the surface, and computation of geometrical properties such as cell volume, directed face areas, centroids, and motion-induced fluxes for deforming Cartesian grids required to advance the flow states. Aeroelastic simulations exercising the capability show favorable agreement with data and predictions in the literature for subsonic and supersonic applications.
This dataset provides continuous near ground-level in situ ozone and meteorological data at the TBS site (S7) during the CoURAGE summer IOP. The ozone inlet and the weather station were approximately 5 meters above the surface. In situ ozone (ppbv) was collected with a 2BTech Model 205 dual beam ozone monitor. The meteorological data (temperature, pressure, relative humidity, wind speed, and wind direction) was collected with an AIRMAR 220WX WeatherStation Instrument with relative humidity (RH) module. The data has 2-second temporal resolution.
Flight model cesium ion beam source for electric field strength measuring instrument
Numerical analysis of buckling of continuously infinite beams using Winkler model, Pasternak model, and elastic continuum