This paper assesses wind resource characteristics and energy yield for micro wind turbines integrated on noise barriers. An experimental set-up with sonic anemometers placed on top of the barrier in reference positions is realized. The effect on wind speed magnitude, inflow angle and turbulence intensity is analysed. The annual energy yield of a micro wind turbine is estimated and compared using data from a micro-wind turbine wind tunnel experiment and field data. Electrical energy costs are discussed as well as structural integration cost reduction and the potential energy yield could decrease costs. It was found that instantaneous wind direction towards the barrier and the height of observation play an influential role for the results. Wind speed increases in perpendicular flows while decreases in parallel flow, by +35% down to −20% from the reference. The azimuth of the noise barrier expressed in wind field rotation angles was found to be influential resulted in 50%–130% changes with respect to annual energy yield. A micro wind turbine (0.375 kW) would produce between 100 and 600 kWh annually. Finally, cost analysis with cost reductions due to integration and the energy yield changes due to the barrier, show a LCOE reduction at 60%–90% of the reference value. https://doi.org/10.1016/j.jweia.2020.104206
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This paper presents a report of some of the activities of the International Energy Agency's (IEA) Wind TCP Task 39. By identifying best practices in an international collaboration, Task 39 hopes to provide the scientific evidence to inform improved regulations and standards, increasing the effectiveness of quiet wind turbine technology. Task 39 is divided into five separate work packages, which address the broad wind turbine noise topic in successive steps; from wind turbine noise generation (WP2), to airborne noise propagation over large distances (WP3). The assessment of wind turbine noise and its impact on humans is addressed in WP4, while WP5 is dealing with other aspects of perception and acceptance, which may be related to noise. All WPs contribute to a dedicated Work Package on dissemination (WP1). This paper provides an update of activities primarily associated with the socio-psychological aspects of wind turbine noise (WP4 and WP5). Through the consideration of a wide variety of factors, including measurement technologies, auralisation and psychology, the effects on noise perception, annoyance and its impact on wellbeing and health is being further investigated. This paper presents a discussion of the activities of each member country and highlights some of the key research questions that need to be further considered.
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tract Micro wind turbines can be structurally integrated on top of the solid base of noise barriers near highways. A number of performance factors were assessed with holistic experiments in wind tunnel and in the field. The wind turbines underperformed when exposed in yawed flow conditions. The theoretical cosθ theories for yaw misalignment did not always predict power correctly. Inverter losses turned out to be crucial especially in standby mode. Combination of standby losses with yawed flow losses and low wind speed regime may even result in a net power consuming turbine. The micro wind turbine control system for maintaining optimal power production underperformed in the field when comparing tip speed ratios and performance coefficients with the values recorded in the wind tunnel. The turbine was idling between 20%–30% of time as it was assessed for sites with annual average wind speeds of three to five meters per second without any power production. Finally, the field test analysis showed that inadequate yaw response could potentially lead to 18% of the losses, the inverter related losses to 8%, and control related losses to 33%. The totalized loss led to a 48% efficiency drop when compared with the ideal power production measured before the inverter. Micro wind turbine’s performance has room for optimization for application in turbulent wind conditions on top of noise barriers. https://doi.org/10.3390/en14051288
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Manual crack inspection is labor-intensive and impractical at scale, prompting a shift toward AI-based segmentation methods. We present a novel crack segmentation model that leverages the Segment Anything Model 2 (SAM 2) through transfer learning to detect cracks on masonry surfaces. Unlike prior approaches that rely on encoders pretrained for image classification, we fine-tune SAM 2, originally trained for segmentation tasks, by freezing its Hiera encoder and FPN neck, while adapting its prompt encoder, LoRA matrices, and mask decoder for the crack segmentation task. No prompt input is used during training to avoid detection overhead. Our aim is to increase robustness to noise and enhance generalizability across different surface types. This work demonstrates the potential of foundational segmentation models in enabling more reliable and field-ready AI-based crack detection tools.
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INTRODUCTION: Delirium in critically-ill patients is a common multifactorial disorder that is associated with various negative outcomes. It is assumed that sleep disturbances can result in an increased risk of delirium. This study hypothesized that implementing a protocol that reduces overall nocturnal sound levels improves quality of sleep and reduces the incidence of delirium in Intensive Care Unit (ICU) patients.METHODS: This interrupted time series study was performed in an adult mixed medical and surgical 24-bed ICU. A pre-intervention group of 211 patients was compared with a post-intervention group of 210 patients after implementation of a nocturnal sound-reduction protocol. Primary outcome measures were incidence of delirium, measured by the Intensive Care Delirium Screening Checklist (ICDSC) and quality of sleep, measured by the Richards-Campbell Sleep Questionnaire (RCSQ). Secondary outcome measures were use of sleep-inducing medication, delirium treatment medication, and patient-perceived nocturnal noise.RESULTS: A significant difference in slope in the percentage of delirium was observed between the pre- and post-intervention periods (-3.7% per time period, p=0.02). Quality of sleep was unaffected (0.3 per time period, p=0.85). The post-intervention group used significantly less sleep-inducing medication (p<0.001). Nocturnal noise rating improved after intervention (median: 65, IQR: 50-80 versus 70, IQR: 60-80, p=0.02).CONCLUSIONS: The incidence of delirium in ICU patients was significantly reduced after implementation of a nocturnal sound-reduction protocol. However, reported sleep quality did not improve.
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Over many years we’ve been looking at the emergence of “organized networks” as an alternative concept that could counter the social media platform a priori of gathering (and then exploiting) “weak links.”[1] Organized networks invent new institutional forms whose dynamics, properties, and practices are internal to the operational logic of communication media and digital technologies. Their emergence is prompted, in part, by a wider social fatigue with and increasing distrust of traditional and modern institutions such as the church, political party, firm, and labour union, which maintain hierarchical modes of organization. While not without hierarchical tendencies (founders, technical architectures, centralized infrastructures, personality cults), organized networks tend to gravitate more strongly toward horizontal modes of communication, practice, and planning.
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This paper describes the concept of a new algorithm to control an Unmanned Aerial System (UAS) for accurate autonomous indoor flight. Inside a greenhouse, Global Positioning System (GPS) signals are not reliable and not accurate enough. As an alternative, Ultra Wide Band (UWB) is used for localization. The noise is compensated by combining the UWB with the delta position signal from a novel optical flow algorithm through a Kalman Filter (KF). The end result is an accurate and stable position signal with low noise and low drift.
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Noise is a common problem in hospitals, and it is known that social behavior can influence sound levels. The aim of this naturally-occurring field experiment was to assess the influence of a non-talking rule on the actual sound level and perception of patients in an outpatient infusion center. In a quasi-randomized trial two conditions were compared in real life. In the control condition, patients (n = 137) were allowed to talk to fellow patients and visitors during the treatment. In the intervention condition patients (n = 126) were requested not to talk to fellow patients and visitors during their treatment. This study measured the actual sound levels in dB(A) as well as patients’ preferences regarding sound and their perceptions of the physical environment, anxiety, and quality of health care. A linear-mixed-model showed a statistically significant, but rather small reduction of the non-talking rule on the actual sound level with an average of 1.1 dB(A). Half of the patients preferred a talking condition (57%), around one-third of the patients had no preference (36%), and 7% of the patients preferred a non-talking condition. Our results suggest that patients who preferred non-talking, perceived the environment more negatively compared to the majority of patients and perceived higher levels of anxiety. Results showed no significant effect of the experimental conditions on patient perceptions. In conclusion, a non-talking rule of conduct only minimally reduced the actual sound level and did not influence the perception of patients.
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The 5th generation of mobile communications is designed to employ both FR1 and FR2 bands throughout the world. The higher frequency bands (i.e., FR2 n257 26.50 - 29.50 GHz) are posing several challenges to operators and national telecom agencies for performing electromagnetic fields (EMF) measurements. In this work we present the design and preliminary evaluation of an FR2 sensor node to measure EMF radiations in urban environments. The design is carried out in an RF circuit design software, i.e., Keysight ADS, where the various nonidealities (i.e., nonlinearities, noise behavior and electromagnetic response) of the various sub blocks of the systems are accounted for. The sensor concept is then implemented in a prototype board technology (i.e., X-microwave) and its response is experimentally verified in the FR2 band.
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