Review of Scientific Instruments最新文献

The in-vessel silicon diode arrays that are used for soft x-ray detection in many tokamaks are sensitive to neutron damage, making them unsuitable for burning plasma devices such as SPARC. In such a device, the silicon diodes would need to be placed far from the plasma-limiting their field of view-or an alternative detector could be used. Here, we present the design of a camera containing an array of chemical vapor deposition single-crystal diamonds, which will be placed in the upper and lower port plugs of the SPARC tokamak with a large enough view of the poloidal cross section to enable tomographic inversion. The camera design presented here is optimized to provide a wide field of view of the poloidal cross section. Simulated plasma conditions are used to estimate the x-ray signal that this detector array will receive and to fine-tune the camera placement within the tokamak.

Understanding fast pedestal dynamics and turbulent transport in the edge and scrape-off layer (SOL) plasma of spherical tokamaks is crucial for the design and operation of future fusion reactors. The alkali beam emission spectroscopy diagnostic technique offers a means to measure the absolute electron density radial profile and fluctuation amplitude in these regions. In this study, we demonstrate that injecting a sodium neutral beam radially into the plasma and analyzing the light emission from its 3p-3s atomic transition using near-orthogonal viewing angles allows for accurate measurement of the electron density profile and fluctuations in the National Spherical Torus Experiment (NSTX) Upgrade spherical tokamak. Our findings indicate a peak signal-to-noise ratio of 118 in the pedestal and 12 in the SOL under typical NSTX plasma conditions. The spatial resolution for the electron density profile is estimated to be between 2 and 8 mm, while for fluctuation measurements, it ranges from 12 to 15 mm.

Here, we present a novel spectroscopy approach to investigate impurity transport by analyzing line-radiation following high-n Rydberg transitions. While high-n Rydberg states of impurity ions are unlikely to be populated via impact excitation, they can be accessed by charge exchange (CX) reactions along the neutral beams in high-temperature plasmas. Hence, localized radiation of highly ionized impurities, free of passive contributions, can be observed at multiple wavelengths in the visible range. For the analysis and modeling of the observed Rydberg transitions, a technique for calculating effective emission coefficients is presented that can well reproduce the energy dependence seen in datasets available on the OPEN-ADAS database. By using the rate coefficients and comparing modeling results with the new high-n Rydberg CX measurements, impurity transport coefficients are determined with well-documented 2σ confidence intervals for the first time. This demonstrates that high-n Rydberg spectroscopy provides important constraints on the determination of impurity transport coefficients. By additionally considering Bolometer measurements, which provide constraints on the overall impurity emissivity and, therefore, impurity densities, error bars can be reduced even further.

Opacity measurements are being carried out at the Z-facility at Sandia National Laboratories and at the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory. The current soft x-ray Opacity Spectrometer (OpSpec) used on the NIF uses two elliptically bent crystals in time-integrated mode on either an image plate or a film. Plans are under way to expand these opacity measurements into a mode of time-resolved detection, called OpSpecTR. Previously, considerations for the available hCMOS detector size and photometrics led to a crystal geometry redesign and the use of a grazing angle x-ray mirror. The mirror acts as a low-pass x-ray energy filter, reducing the contribution of higher energy x rays. The first tests of the mirror and the crystal for OpSpecTR are presented here. The size of the mirror reflection and the reflectivity is tested using a Manson x-ray source. The mirror coupled with the new elliptical crystal shape demonstrates OpSpecTR's spectral coverage. The results from the x-ray optics performance testing are shown along with the intended design.

In the production process of high-end PP-R pipes, mixing different colored raw material particles can result in uneven color in the final product, affecting its appearance quality. in addition, color mixing can reduce the physical properties of the pipes, impacting their durability and safety. To address this issue, we propose a visual, non-destructive inspection solution based on image processing technology. The solution aims to enhance detection efficiency and accuracy by reducing background interference and enabling adaptive adjustments in various environments. Initially, the K-Means image segmentation algorithm is employed to eliminate complex background factors from the original image, significantly improving image segmentation accuracy. Subsequently, the Gaussian mixture model algorithm is utilized to automatically extract the color threshold of the foreground image after background removal, facilitating adaptive algorithm adjustments. Finally, the mean value algorithm is introduced to swiftly and accurately identify plastic particles of different colors using the automatically obtained color thresholds. Experimental results demonstrate that this method can quickly and accurately identify different color particles and effectively support the rejection of impurity particles. Through this approach, the algorithm achieves an average detection accuracy of 99.3%.

A diamond nitrogen-vacancy (NV) ensemble has been developed as a vector magnetometry platform for sensing external time-varying magnetic fields. However, due to the complexity of manipulating electron spins along different directions, a current vector NV magnetometer often needs a large amount of supporting equipment, preventing its applications in a compact circumstance. Here, we develop a hardware-level protocol to realize a multi-axis NV magnetometer using only a single channel of microwave generation and signal detection resources. This mechanism is to monitor each resonance serialized in a sequence and measure the electron-spin frequency shifts concurrently in real time. The functionality is realized by a home-made control system with an on-chip direct digital synthesis generator and signal processor. We finally achieve a vector sensitivity of around 14 nT/Hz on four different axes at the same time. We also analyze the phase delay of the sensing signal between different axes induced by the protocol. This protocol is compatible with other schemes to further improve the performance, such as hyperfine driving, balanced detection, and high-efficiency photon collection methods.

Acoustic levitation is frequently used for non-contact manipulation of objects and to study the impact of microgravity on physical and biological processes. While the force field produced by sound pressure lifts particles against gravity (primary acoustic force), multiple levitating objects in the same acoustic cavity interact via forces that arise from scattered sound (secondary acoustic forces). Current experimental techniques for obtaining these force fields are not well-suited for mapping the primary force field at high spatial resolution and cannot directly measure the secondary scattering force. Here, we introduce a method that can measure both acoustic forces in situ, including secondary forces in the near-field limit between arbitrarily shaped, closely spaced objects. Operating similarly to an atomic force microscope, the method inserts into the acoustic cavity a suitably shaped probe tip at the end of a long, flexible cantilever and optically detects its deflection. This makes it possible to measure forces with a resolution better than 50 nN and also to apply stress or strain in a controlled manner to manipulate levitated objects. We demonstrate this by extracting the acoustic potential present in a levitation cavity, directly measuring the acoustic scattering force between two objects, and applying tension to a levitated granular raft of acoustically bound particles in order to obtain the force-displacement curve for its deformation.

In contemporary industrial systems, the prediction of remaining useful life (RUL) is recognized as a valuable maintenance strategy for health management due to its ability to monitor equipment operational status in real time and ensure the safety of industrial production. Current studies have largely concentrated on deep learning (DL) techniques, leading to a shortage of RUL prediction methods that utilize deep reinforcement learning (DRL). To further enhance application and research, this paper introduces a novel approach to RUL prediction based on DRL, specifically using a combination of Convolutional Neural Network-Bidirectional Long Short-Term Memory Network (CNN-BiLSTM) and the Deep Deterministic Policy Gradient (DDPG) algorithm. The proposed method reframes the conventional task of estimating RUL as a Markov decision process (MDP), effectively integrating the feature extraction capabilities of DL with the decision-making abilities of DRL. Initially, a hybrid CNN-BiLSTM is employed to establish an agent that can extract degradation features from raw signals. Subsequently, the DDPG algorithm within DRL is leveraged to develop the RUL prediction mechanism, completing the MDP by defining appropriate action spaces and reward functions. The agent, through repeated trials and optimization, learns to map the current operational state of the rolling bearing to its remaining service life. Validation analysis was performed on the intelligent maintenance systems (IMS) bearing dataset. The findings suggest that the DRL-based approach outperforms the current methodologies, demonstrating a superior performance in root mean square error (MSE) and MSE metrics. The predicted outcomes align more closely with the actual lifespan values.

Depositing diamond-like carbon (DLC) film is considered to be more promising for surface modification of microparticles. The development of reliable and precise measurement techniques for DLC coatings on microparticles is crucial for advancing research in this field. This paper introduces a methodological approach for quantifying the thickness of the film on microparticles. The thickness of the film is obtained by establishing the quantitative relationship between the energy lost when electrons pass through the film and the thickness of the film. The proposed method allows for the estimation of film thickness by assessing solely the elemental abundance on the particle surfaces.

We present a simple method to evaluate the curved surface of a plano-convex aspheric lens using an incoherent light source. We implement an exact ray trace to obtain analytical expressions for designing a set of geometric objects, placed within a plane, to produce by refraction a regular array of either circles or straight lines in the plane of detection when the optical system under test works in accordance with the nominal design. An innovative geometrical test is implemented to calibrate the position of each element involved in the measurement system. As part of the calibration process, we considered that the camera lens can be affected by the distortion aberration; therefore, we proposed a straightforward method to compensate for the defects introduced in the experimental images. Finally, we used the measured values of the slopes to recover the shape of the surface under test using an iterative algorithm; as a result, we obtained the geometric parameters describing the surface with a percentage error less than 1.7%.