Prediction of Threshold Sand Rates from Acoustic Monitors Using Artificial Intelligence

Solids production from oil and gas wells can cause excessive damage resulting in safety hazards and expensive repairs. To prevent the problems associated with sand influx, ultrasonic devices can be used to provide a warning when sand is being produced in pipelines. One of the most used methods for sand detection is utilizing commercially available acoustic sand monitors that clamp to the outside of pipe wall and measures the acoustic energy generated by sand grain impacts on the inner side of a pipe wall. Although the transducer used by acoustic monitors is especially sensitive to acoustic emissions due to particle impact, it also reacts to flow induced noise as well (background noise). The acoustic monitor output does not exceed the background noise level until a sufficient sand rate is entrained in the flow that causes a signal output that is higher than the background noise level. This sand rate is referred to as the threshold sand rate or TSR. A significant amount of data has been compiled over the years for TSR at the Tulsa University Sand Management Projects (TUSMP) for various flow conditions with stainless steel pipe material. However, to use this data to develop a model for different flow patterns, fluid properties, pipe, and sand sizes is challenging. The purpose of this work is to develop an artificial intelligence (AI) methodology using machine learning (ML) models to determine TSR for a broad range of operating conditions. More than 250 cases from previous literature as well as ongoing research have been used to train and test the ML models. The data utilized in this work has been generated mostly in a large-scale multiphase flow loop for sand sizes ranging from 25 to 300 μm varying sand concentrations and pipe diameters from 25.4 mm to 101.6 mm ID in vertical and horizontal directions downstream of elbows. The ML algorithms including elastic net, random forest, support vector machine and gradient boosting, are optimized using nested cross-validation and the model performance is evaluated by R-squared score. The machine learning models were used to predict TSR for various velocity combinations under different flow patterns with sand. The sensitivity to changes of input parameters on predicted TSR was also investigated. The method for TSR prediction based on ML algorithms trained on lab data is also validated on actual field conditions available in the literature. The AI method results reveal a good training performance and prediction for a variety of flow conditions and pipe sizes not tested before. This work provides a framework describing a novel methodology with an expanded database to utilize Artificial Intelligence to correlate the TSR with the most common production input parameters.

Synchrony as a measure of conversation difficulty: Movement coherence increases with background noise level and complexity in dyads and triads

When people interact, they fall into synchrony. This synchrony has been demonstrated in a range of contexts, from walking or playing music together to holding a conversation, and has been linked to prosocial outcomes such as development of rapport and efficiency of cooperation. While the basis of synchrony remains unclear, several studies have found synchrony to increase when an interaction is made challenging, potentially providing a means of facilitating interaction. Here we focus on head movement during free conversation. As verbal information is obscured when conversing over background noise, we investigate whether synchrony is greater in high vs low levels of noise, as well as addressing the effect of background noise complexity. Participants held a series of conversations with unfamiliar interlocutors while seated in a lab, and the background noise level changed every 15-30s between 54, 60, 66, 72, and 78 dB. We report measures of head movement synchrony recorded via high-resolution motion tracking at the extreme noise levels (i.e., 54 vs 78 dB) in dyads (n = 15) and triads (n = 11). In both the dyads and the triads, we report increased movement coherence in high compared to low level speech-shaped noise. Furthermore, in triads we compare behaviour in speech-shaped noise vs multi-talker babble, and find greater movement coherence in the more complex babble condition. Key synchrony differences fall in the 0.2–0.5 Hz frequency bands, and are discussed in terms of their correspondence to talkers’ average utterance durations. Additional synchrony differences occur at higher frequencies in the triads only (i.e., >5 Hz), which may relate to synchrony of backchannel cues (as multiple individuals were listening and responding to the same talker). Not only do these studies replicate prior work indicating interlocutors’ increased reliance on behavioural synchrony as task difficulty increases, but they demonstrate these effects using multiple difficulty manipulations and across different sized interaction groups.

Subjective Evaluation on the Annoyance of Environmental Noise Containing Low-Frequency Tonal Components

Recently in Japan, noises from wind turbines and domestic use heat sources sometimes cause an increase in noise annoyance owing to low-frequency tonal components. The purpose of this study was to investigate the effects of the tonal components on the annoyance of the environmental noise. The authors conducted an auditory test in the laboratory to evaluate the annoyance of tonal noise using a seven-step rating method. The stimuli were composed of a broadband noise modeling of the environmental noise (25, 30, and 35 dB) and a low-frequency tonal component. With the tonal component added to the broadband noise, the frequency and tonal audibility were varied to 40, 50, 100, 200, and 400 Hz and 0, 3, 6, 9, and 12 dB, respectively. The amount of increase in annoyance owing to the addition of the tonal component was quantitatively evaluated as a tonal adjustment by comparing it with broadband noise. As a result, tonal adjustment ranged from 0 to 7 dB, and the higher the tonal frequency, the larger the value. For the test background noise level, the lower the background noise level of the test sound, the greater the value. This trend suggests that the influence of tonal components on subjective impressions is stronger in quiet environments such as residential areas. This result may provide a basis for the evaluation method, which varies the penalty in the noise evaluation according to the frequency of the pure tones and the noise level.

Resonant Power Frequency Converter and Application in High-Voltage and Partial Discharge Test of a Voltage Transformer

This paper presents application of a resonant power frequency converter for high-voltage (HV) and partial discharge (PD) test of a voltage transformer. The rating voltage, power, and frequency of the system are 70 kVrms, 40 kVA, and 200 Hz, respectively. The testing system utilized the converter feeding to an HV testing transformer connected to a conventional partial discharge detection system. The converter system comprising a rectifier and insulated-gate bipolar (IGBT) switches with the H-bridge configuration was applied as a low-voltage source instead of a conventional motor-generator test set which requires large space and high cost. The requirements of the test according to the standards are quality of the test voltage and the background noise level. The required voltage must have the different voltage (DV) and total harmonic distortion (THDv) in the acceptable values of less than 5%. The DV is defined as the difference of the root mean square and peak voltages in percent. The required background noise level must be lower than 2.5 pC. Simulations and experiments were performed for verification of the developed system performance in comparison with those of the previously developed system based on the pulse width modulation converter. It is found that the developed system can provide the testing voltage with the DV and the THDv of lower than 1% and the background noise level of lower than 1 pC. Considering this achievement of promising performance, the developed system is an attractive choice for the HV and PD testing of voltage transformers in real practice.

ACOUSTICALLY CHARACTERIZED 'EXPERIENCE OF TRANSCENDENCE' IN PFARKIRCHE ST MICHAEL, STEYR

Experience of Transcendence’ is acoustically characterized in Pfarrkirche St Michael, Steyr using trained participants’ feedback during live organ rendition of Johann Sebastian Bach’s ‘TOCCATA’. Transcendental experiences of ‘awe’, ‘deeper understanding’ and ‘tranquility’ were acoustically derived and termed as ‘Acoustically Transcendent Awe’ (ATAWE), ‘Acoustically Transcendent Intelligibility’ (ATINT), and ‘Acoustically Transcendent Tranquility’ (ATTRANQ). In this study, ‘Acoustically Transcendent Intelligibility’ (ATINT) and ‘Acoustically Transcendent Tranquility’ (ATTRANQ) showed significant multiregressions with subjective acoustical qualities of the space (R2=0.99; p=0.01) and (R2=0.99; p=0.04) respectively. Instantaneous, statistical and percentile sound levels during ambient noise and during live performances were recorded at different listening zones. Background Noise Levels (LA90) between 76dB-82dB indicated congregational and choir space as optimally loud (without any need for electro-acoustical support) and sanctuary (with LA90 value of 56.8dB) as needing support, for performance and listening. Acoustically ranscendent Intelligibility (ATINT) was found significantly predictable from Subjective Acoustical Quality of Silence from Background Noise (SAQSNOIS) (p=0.05) and from Background Noise Level (LA90) (p=0.05). Perception of optimal Reverberance (SAQREV) in the Choir Loft provides good ambience for choir and musicians. These significant relationships between Acoustical Transcendence Impressions, Subjective Acoustical Qualities and Sound Levels can serve as part of Pfarrkirche St Michael’s unique intangible heritage.

Safety of smartwatches and their chargers in patients with cardiac implantable electronic devices

Aims Cardiac implantable electronic devices (CIEDs) are susceptible to electromagnetic interference (EMI). Smartwatches and their chargers could be a possible source of EMI. We sought to assess whether the latest generation smartwatches and their chargers interfere with proper CIED function. Methods and results We included consecutive CIED recipients in two centres. We tested two latest generation smartwatches (Apple Watch and Samsung Galaxy Watch) and their charging cables for potential EMI. The testing was performed under continuous electrocardiogram recording and real-time device telemetry, with nominal and ‘worst-case’ settings. In vitro magnetic field measurements were performed to assess the emissions from the tested devices, initially in contact with the probe and then at a distance of 10 cm and 20 cm. In total, 171 patients with CIEDs (71.3% pacemakers–28.7% implantable cardioverter-defibrillators) from five manufacturers were enrolled (63.2% males, 74.8 ± 11.4 years), resulting in 684 EMI tests. No EMI was identified in any patient either under nominal or ‘worst-case scenario’ programming. The peak magnetic flux density emitted by the smartwatches was similar to the background noise level (0.81 μT) even when in contact with the measuring probe. The respective values for the chargers were 4.696 μΤ and 4.299 μΤ for the Samsung and Apple chargers, respectively, which fell at the background noise level when placed at 20 cm and 10 cm, respectively. Conclusion Two latest generation smartwatches and their chargers resulted in no EMI in CIED recipients. The absence of EMI in conjunction with the extremely low intensity of magnetic fields emitted by these devices support the safety of their use by CIED patients.

Sound environment quality in nursing units in Chinese nursing homes: A pilot study

Recent studies have investigated sound environment in nursing homes. However, there has been little research on the sound environment of nursing units. This research sought to address this gap. Subjective evaluations were gathered using questionnaire surveys of 75 elderly residents and 30 nursing staff members in five nursing units of five nursing homes in Chongqing, China. Background noise level and reverberation time were measured in five empty bedrooms, five occupied bedrooms and five occupied nursing station areas, in five nursing units. The subjective evaluation results indicate that the residents stay in the nursing units for most of their waking hours. The residents and nursing staff had strong preferences for natural sounds, with the lowest perceptions of these in the nursing units. The background noise level in all the occupied bedrooms exceeded Chinese standards for waking and sleeping hours. Only 20% of the occupied nursing station areas were below the allowable noise level for recreation and fitness room during sleeping hours. The nursing station area was identified as the main source of noise in the unit during waking hours. The average background noise level of the occupied bedrooms was 3–12 dBA higher than that of the empty bedrooms during sleeping hours. Attention should be given to the implementation of noise specifications for sleeping hours. The reverberation time of the bedrooms was within the range of 0.44–0.68 s, and in the nursing station areas it was 0.63–1.54 s.

Acceptable noise levels in Arabic-Persian bilinguals

Background and Aim: Acceptable noise level (ANL) test is a reliable measure of people’s abi­lity to tolerate background noise. Central ner­vous system is one of the determinant factors in subject’s tolerance of noise. Bilinguals’ diffe­rent central activity pattern may yield different ANL test results from monolinguals. This study aims to compare noise tolerance function in Arabic-Persian bilinguals with Persian monolin­guals via Persian version of ANL. Methods: In the present study, the Persian ver­sion of ANL was administered on 115 cases with normal hearing (56 male, 59 female) aged 18–37 years in three groups of the Persian mon­olingual, sequential Arabic-Persian bilinguals, and simultaneous Arabic-Persian bilinguals. Results: The statistical analysis revealed sig­nificant difference in most comfortable level (p = 0.002) and background noise level (p = 0.011) among three groups, i.e. between Persian monolinguals and sequential Arabic-Persian bil­inguals and between Persian monolinguals and simultaneous Arabic-Persian bilinguals. In other words, mean scores of bilingual were higher than monolingual scores. There was no signifi­cant difference among three groups with regard to ANL scores (p = 0.114). * Corresponding author: Department of Audiology, School of Rehabilitation, Tehran University of Medical Sciences, Piche-Shemiran, Enghelab Ave., Tehran, 1148965141, Iran. Tel: 009821-77530636, E-mail: [email protected] Conclusion: Despite the difference between Persian monolinguals and Arabic-Persian bilin­guals in most comfortable level and background noise level, there is no significance difference in ANL results. Therefore, auditory central proce­ssing acts similarly in normal hearing monolin­gual and bilingual subjects. As a result, Persian version of ANL can be used for Arabic-Persian bilinguals, too.

Analysis of Noise Level Generated by Stone Cutter Machine

Marble, one of natural stone, has been widely produced since the last decade. In South Aceh, Marble stone is fabricated at Marble Production Unit that is located around Polytechnic of Aceh Selatan. The using of large-scale stone-cutting machines in Marble Production process tends to be a major noise source in Polytechnic of Aceh Selatan environment. The aim of this study is to analyze the noise level generated by Marble Cutting Machine in Marble Production Unit. The noise levels were analyzed by measuring Background Noise Level (BNL) and Sound Pressure Level (SPL). Sound Level Meter Type SL-814 was employed in the measurement. The results show that Background Noise Level measured is 53.03 dB on average. The highest Sound Pressure Level measured when the marble cutting machine was operated without workpiece is 94dB. In addition, the highest sound pressure level measured when marble cutting machine was operated with the workpiece is 96 dB. The values have generally exceeded the Threshold Noise Level allowed for education area, 55 dB. The noisy condition in campus environment would have an impact on teaching and learning processes within the Polytechnic of South Aceh.