The invention concerns a method for the non-destructive mapping of a component, in order to determine an elongation direction of the elongate microstructure of the component at at least one point of interest, characterised in that it comprises at least two successive intensity measurement steps comprising the following steps: a sub-step of rotating a linear transducer into a plurality of angular positions, said linear transducer comprising a plurality of transducer elements, a sub-step of emitting a plurality of elementary ultrasonic beams at each angular position, a sub-step of measuring a plurality of backscattered signals resulting from the backscattering of the elementary ultrasonic beams by said elongate microstructure, the intensity measurement steps making it possible to obtain two series of intensities measured according to two axes of rotation, and in that the method comprises a step of combining the measured series of intensities so as to determine the elongation direction of the microstructure at said at least one point of interest.

A compatibility prediction method includes predicting compatibility between a prediction target food and a prediction target drink using: a model for predicting the compatibility between the prediction target food and the prediction target drink, and measurements that are values related to predetermined information obtained when a measuring instrument measures aroma components of the prediction target food and the prediction target drink or calculations calculated based on the measurements.

Systems and methods are disclosed for conducting an ultrasonic-based inspection. The systems and methods perform operations comprising: receiving a plurality of scan plan parameters associated with generating an image of at least one flaw within a specimen based on acoustic echo data obtained using full matrix capture (FMC); applying the plurality of scan plan parameters to an acoustic model, the acoustic model configured to determine a two-way pressure response of a plurality of inspection modes based on specular reflection and diffraction phenomena; generating, by the acoustic model based on the plurality of scan plan parameters, an acoustic region of influence (AROI) comprising an acoustic amplitude sensitivity map for a first inspection mode amongst the plurality of inspection modes; and generating, for display, a first image comprising the AROI associated with the first inspection mode for capturing or inspecting the image of the at least one flaw.

A method of distinguishing a first physical phenomenon captured in a sensory measurement time waveform from a second physical phenomenon captured in the waveform includes: receiving the waveform on a processor from a sensor in sensory contact with an object undergoing first and second physical phenomena, wherein the first phenomenon is a comparatively fast event; deriving a first rate of change data stream from the time waveform with a processor operable on a processor, wherein each value of the first rate of change data stream is based on a difference in extreme amplitudes of the waveform during a first interval of waveform samples; and analyzing with the processor the derived first rate of change data stream to distinguish the comparatively fast first physical phenomena from the second physical phenomenon captured in the waveform.

A method and system for determining acoustic emission (AE) parameters of rock based on moment tensor analysis. The method includes: constructing, according to macroscopic mechanical parameters, a numerical model of a rock specimen to be tested; loading the numerical model through particle flow code software to simulate a failure process of the rock specimen to be tested, and identifying fracturing time and positions of microcracks when the PFC software loads the numerical model; determining, when the PFC software loads the numerical model, if rock grains of two sequentially generated microcracks include common rock grains, and an interval for generating the two microcracks is less than duration time of a present AE event, the two microcracks as a same AE event; taking geometric centers of all microcracks within a spatial range of an AE event as source positions of the corresponding AE event; and determining AE parameters of the AE event.

This disclosure relates to the monitoring and detection of corrosion and/or erosion of pipes, vessels, and other components in an industrial facility. The monitoring system may comprise of an arrangement of guided wave (GW) transducers and a longitudinal wave (LW) transducer affixed to the piping component to collectively measure for localized corrosion of the piping component without necessarily requiring a thickness map. The monitoring system may use an intelligent amplified multiplexer/switch to control the operation of the transducers that may be controlled and operated to generate waves in the kilohertz range and megahertz range with the same hardware.

A method and system are described for processing tissues according to particular processing protocols that are established based on time-of-flight measurements as a processing fluid is diffused into a tissue sample. In one embodiment, measurement of the time it takes about 70% ethanol to diffuse into a tissue sample is used to predict the time it will take to diffuse other processing fluids into the same or similar tissue samples. Advantageously, the disclosed method and system can reduce overall processing times and help ensure that only samples that require similar processing conditions are batched together.

The present disclosure provides systems and methods for estimating the strength of a concrete foundation. The disclosed systems and methods can be used to estimate compressive strength of below-grade concrete without excavation. A method of estimating compressive strength may include determining compressive strength measurements corresponding to surface wave speeds for a plurality of concrete test specimens, determining a speed of surface waves in the concrete foundation, and estimating compressive strength of the concrete foundation based on the compressive strength measurements and corresponding surface wave speeds for the plurality of concrete test specimens and the speed of surface waves in the concrete foundation.

A device for estimating a mechanical property of a sample is disclosed herein. The device may include a chamber configured to hold the sample; a transmitter configured to transmit a plurality of waveforms, including at least one forcing waveform; and a transducer assembly operatively connected to the transmitter and configured to transform the transmit waveforms into ultrasound waveforms. The transducer assembly can also transmit and receive ultrasound waveforms into and out of the chamber, as well as transform at least two received ultrasound waveforms into received electrical waveforms. The device also includes a data processor that can receive the received electrical waveforms; estimate a difference in the received electrical waveforms that results at least partially from movement of the sample; and estimate a mechanical property of the sample by comparing at least one feature of the estimated difference to at least one predicted feature, wherein the at least one predicted feature is based on a model of an effect of the chamber wall. Finally, the device can also include a controller configured to control the timing of the ultrasound transmitter and data processor.

A method for simulating an ultrasonic response of a metal part is carried out by an electronic simulating device. The method includes computing a first distribution of ultrasonic waves for the part without defect, in response to an ultrasonic excitation toward said part computing a second distribution of ultrasonic waves for a predefined zone (S.sub.3.sup.k) of the part, including a defect (20), in response to an ultrasonic excitation toward said zone (S.sub.3.sup.k), with the computation of elementary distributions, each corresponding to an ultrasonic response received by a receiver located at a border (F) of said zone; and determining a resultant distribution of ultrasonic waves for the part with defect, from the first and second computed distributions, the resultant distribution forming a simulation of an ultrasonic response received from the part including the defect (20), in response to an ultrasonic excitation toward said part.