19 research outputs found
Six-degrees-of-freedom test mass readout via optical phase-locking heterodyne interferometry
Accurate position and posture measurements of the freely-falling test mass
are crucial for the success of spaceborne gravitational wave detection
missions. This paper presents a novel laboratory-developed test mass motion
readout that utilizes quadrant photodetectors to measure the translation and
tilt of a test mass. Departing from conventional methods like Zeeman effect or
AOM frequency shift modulation, the readout system employs the phase locking of
two lasers to generate the dual-frequency heterodyne source. Notably, the
out-of-loop sensitivity of the phase locking reaches below 30 pm/Hz1/2 within
the frequency band of 1 mHz and 10 Hz. The system comprises three measurement
interferometers and one reference interferometer, featuring a symmetric design
that enables measurements of up to six degrees of freedom based on
polarization-multiplexing and differential wavefront sensing. Ground-simulated
experimental results demonstrate that the proposed system has achieved a
measurement sensitivity of 4 pm/Hz1/2 and 2 nrad/Hz1/2 at 1 Hz, a resolution of
5 nm and 0.1 urad, a range of 200 um and 600 urad, respectively. These findings
showcase the system's potential as an alternative method for precisely
monitoring the motion of test masses in spaceborne gravitational wave detection
missions and other applications requiring accurate positioning and
multi-degrees-of-freedom sensing.Comment: 7 pages, 10 figures. arXiv admin note: substantial text overlap with
arXiv:2207.0642
Application of an Artificial Neural Network for Predicting the Texture of Whey Protein Gel Induced by High Hydrostatic Pressure
International audienceThe effects of high hydrostatic pressure (HP), protein concentration, and sugar concentration on the gelation of a whey protein isolate (WPI) were investigated. Differing concentrations of WPI solution in the presence or absence of lactose (0-20%, w/v) were pressurized at 200-1000 MPa and incubated at 30°C for 10 min. The hardness and breaking stress of the HP-induced gels increased with increasing concentration of WPI (12-20%) and pressure. Lactose decreased the hardness and breaking stress of the gel. Furthermore, these results were used to establish an artificial neural network (ANN). A multiple layer feed-forward ANN was also established to predict the physical properties of the gel based on the inputs of pressure, protein concentration, and sugar concentration. A useful prediction was possible, as measured by a low mean square error (MSE 0.99) between true and predicted data in all cases