Boundary Wind Research Articles

Degree of Burn: A Digital Tool for Burn Area Assessment and Fluid Requirement Calculation Using Wound Image Analysis

Burns are tissue damage due to contact with a heat source, such as fire, hot water, chemicals, electricity, or radiation. Burns are a type of trauma with high morbidity and mortality rates and require high treatment costs. In Indonesia, burns are still a serious problem that requires special care, high costs, and skilled personnel. Currently, burn assessments are carried out manually, which is time-consuming and the results are subjective. Treatment efforts include preventing infection and encouraging epithelial cell regeneration to close the wound. Therefore, innovation is needed in the form of a system that helps assess burns more effectively, including classifying wound tissue, measuring wound area, and monitoring wound development. The use of an Android-based system can provide more accurate measurements through a digital planimetry approach or image segmentation, which can identify wound boundaries and tissue types. Technology-based health applications, such as the "Degree of Burn" application, allow for more efficient calculation of burn area and fluid requirements. This study uses a literature review method from international journals, national journals, books, and conference results related to burn assessment to support the development of this system.

Interplay of geometry and mechanics in epithelial wound healing.

Wound healing is a complex biological process critical for maintaining an organism's structural integrity and tissue repair following an infection or injury. Recent studies have unveiled the mechanisms involving the coordination of biochemical and mechanical responses in the tissue in wound healing. In this article, we focus on the healing property of an epithelial tissue as a material while the effects of biological mechanisms such as cell proliferation, tissue intercalation, cellular migration, cell crawling, and filopodia protrusion is minimal. We present a mathematical framework that predicts the fate of a wounded tissue based on the wound's geometrical features and the tissue's mechanical properties. Precisely, adapting the vertex model of tissue mechanics, we predict whether a wound of a specific size in an epithelial monolayer characterized by certain levels of actomyosin contractility and cell-cell adhesion will heal (i.e., close), shrink in size, or rupture the tissue further. Moreover, we show how tissue-mediated mechanisms such as purse-string tension at the wound boundary facilitate wound healing. Finally, we validate the predictions of our model by designing an experimental setup that enables us to create wounds of specific sizes in kidney epithelial cells (MDCK) monolayers. Altogether, this work sets up a basis for interpreting the interplay of mechanical and geometrical features of a tissue in the process of wound healing.

CD74+ fibroblasts proliferate upon mechanical stretching to promote angiogenesis in keloids.

The healing of human skin wounds is susceptible to perturbation caused by excessive mechanical stretching, resulting in enlarged scars, hypertrophic scars, or even keloids in predisposed individuals. Keloids are fibro-proliferative scar tissues that extend beyond the initial wound boundary, consisting of the actively progressing periphery and the quiescent center. The stretch-associated outgrowth and enhanced angiogenesis are two features of the periphery of keloids. However, which cell population is responsible for transducing the mechanical stimulation to the progression of keloids remains unclear. Herein, through integrative analysis of single-cell RNA sequencing of keloids, we identified CD74+ fibroblasts, a previously unappreciated subset of fibroblasts with pro-angiogenic and stretch-induced proliferative capacities, as a key player in stretch-induced progression of keloids. Immunostaining of keloid cryosections depicted a predominant distribution of CD74+ fibroblasts in the periphery, interacting with the vasculature. Invitro tube formation assays on purified CD74+ fibroblasts ascertained their pro-angiogenic function. BrdU assays revealed that these cells proliferate upon stretching, through PIEZO1-mediated calcium influx and the downstream ERK and AKT signaling. Collectively, our findings propose a model wherein CD74+ fibroblasts serve as pivotal drivers of stretch-induced keloid progression, fueled by their proliferative and pro-angiogenic activities. Targeting the attributes of CD74+ fibroblasts holds promise as a therapeutic strategy for the management of keloids.

A Study on the Impact of Vertical Grid Parameter Perturbations in the Regional Ocean Modeling System

In this study, the Regional Ocean Modeling System (ROMS) is employed to construct a three-dimensional barotropic ocean model with a monodirectional upper boundary and homogeneous and steady wind covering the entire computation area. Eight perturbation experiments are designed to determine the vertical grid distribution difference with high resolution at the surface and bottom. Two types are considered in the model, including removing the Coriolis force (type 1) and employing a different Coriolis force (type 2). According to the experiments, the velocity of the current in type 1 yields uncertainty, and wind energy could penetrate the upper ocean and reach the abyss. The surface velocity in type 2 is fundamentally compatible with the empirical relationship constructed by Ekman, and the curved lines of the vertical distribution of horizontal currents nearly match. For type 1, the velocity is very strong from the sea surface to the bottom. When comparing type 1 and type 2 cases, the Coriolis force obstructs the wind energy transfer into the deep ocean. In addition, the European Centre for Medium-Range Weather Forecasts (ECMWF)’s global surface wind distribution indicates that the realistic ocean upper wind boundary is similar to the numerical experiment in the Pacific and Atlantic oceans, where the wind direction is along the latitude line at the equator. In order to make the experimental situation as close as possible to the real ocean, validation experiments are conducted in this study to consider the uncertainty in the current profile at the equator. The simulation results of type 1 differ significantly from the data obtained from the real ocean. This uncertainty may transfer the signal to higher latitudes, causing incorrect simulation results, especially in the critical region. Overall, this research not only makes discoveries in physical ocean theory but also guides predictive and forecasting techniques for ocean modeling.

AURKA Activates FOXO3a to Form a Positive Feedback Loop in the Proliferation and Migration of Keloid Fibroblasts.

Objective: Keloids are benign fibroproliferative disorders with invasive growth exceeding the wound boundary. Aurora kinase A (AURKA) is a serine/threonine kinase highly expressed in various tumors, facilitating tumor growth and invasion. Currently, the role of AURKA in keloid remains unclear. Approach: Fibroblasts were isolated from keloid and normal skin samples. AURKA was evaluated by qPCR, Western blot, and immunohistochemistry. Transcriptome sequencing and dual-luciferase reporter assays were applied to figure out targets of AURKA. Following expression alteration and MLN8237 (an AURKA kinase inhibitor, AKI) treatment, phenotypical experiments were conducted to clarify biological functions of AURKA along with its target, and to probe into the clinical potential of AURKA inhibition. Results: AURKA was upregulated in keloid tissues and fibroblasts. Forkhead box O 3a (FOXO3a) was verified as a downstream of AURKA. Further experiments demonstrated that AURKA transactivated FOXO3a by binding to FOXO3a, while FOXO3a directly transactivated AURKA. Functionally, AURKA and FOXO3a cooperated in enhancing the proliferation and migration of keloid fibroblasts via protein kinase B (AKT) phosphorylation. Although MLN8237 weakened the proliferation and migration in keloid fibroblasts, the transactivation of AURKA on FOXO3a was independent of kinase activity. Innovation: This study reveals that AURKA and FOXO3a compose a transactivation loop in enhancing the proliferative and migrative properties of keloid fibroblasts, and proposes AURKA as a promising target. Conclusion: AURKA/FOXO3a loop promotes the proliferation and migration of keloid fibroblasts via AKT signaling. Despite the anti-keloid effects of AKIs, AURKA acts as a transcription factor independently of kinase activity, deepening our understanding on AKI insensitivity.

Wound Tissue Segmentation and Classification Using U-Net and Random Forest

Analysing wound tissue is a crucial research field for assessing the progression of wound healing. Wounds exhibit certain attributes concerning colour and texture, although these features can vary among different wound images. Research in this field serves multiple purposes, including confirming the presence of chronic wounds, identifying infected wounds, determining the origin of the wound and addressing other factors that classify and characterise various types of wounds. Wounds pose a substantial health concern. Currently, clinicians and nurses mainly evaluate the healing status of wounds based on visual examination. This paper presents an outline of digital image processing and traditional machine learning methods for the tissue analysis of chronic wound images. Here, we propose a novel wound tissue analysis system that consists of wound image pre-processing, wound area segmentation and wound analysis by tissue segmentation. The wound area is extracted using a simple U-Net segmentation model. Granulation, slough and necrotic tissues are the three primary forms of wound tissues. The [Formula: see text]-means clustering technique is employed to assign labels to tissues. Within the wound boundary, the tissue classification is performed by applying the Random Forest classification algorithm. Both segmentation (U-Net) and classification (Random Forest) models are trained, and the segmentation gives 99% accuracy, and the classification model gives 99.21% accuracy.

Advances of Nanobiomaterials for Treating Skin Pathological Fibrosis

Skin pathological fibrosis conditions, such as hypertrophic scars (HS) and keloids, where the scar tissue is raised and extends beyond the original wound boundary, are aesthetically unappealing and sometimes painful or itchy, significantly impacting the life quality of patients. In this review, the advances of nanobiomaterials in treating skin pathological fibrosis are summarized and discussed. The focus is on the therapeutic approaches to cellular and molecular targets of HS, highlighting the potential of nanotechnology in scar management. The biofunctional nanomaterials can modulate inflammation, regulate angiogenesis, and promote fibroblast apoptosis. The nanotechnology‐based drug delivery systems such as liposomes, ethosomes, and dendritic macromolecules can improve the solubility, stability, and efficacy of drugs, and enhance precise delivery, resulting in better outcomes in HS therapy. Integrating nanomaterials or nanostructures into hydrogels, nanofibers, and microneedles can enhance the biological functionality and maximize the therapeutic effect of nanoparticles (NPs) at the wound site. The important potential of nanotechnology‐based scar treatment should be further explored to overcome the current challenges and promote its application in clinical practice.

Clinical and Molecular Insights into Hypertrophic Scars and Keloids: A Literature Review

Background: Hypertrophic scars and keloids represent two distinct forms of abnormal wound healing, characterized by excessive fibrous tissue formation. Despite their prevalence, the pathophysiological mechanisms underlying their development and persistence remain incompletely understood. This literature review synthesizes current clinical and molecular insights into hypertrophic scars and keloids, aiming to highlight differences in their etiology, pathogenesis, and therapeutic responses. Methods: A comprehensive review of the literature was conducted, focusing on articles that provided significant insights into the clinical manifestations, genetic predispositions, molecular pathways, and treatment strategies related to hypertrophic scars and keloids. Experimental studies and clinical trials were included to encompass a wide range of data sources. Results: Hypertrophic scars are confined to the original wound boundary and may regress over time, whereas keloids extend beyond the wound margins and do not regress. Clinically, hypertrophic scars and keloids differ in their appearance, texture, and predilection sites. At the molecular level, these differences are underscored by distinct profiles of cytokine expression, growth factor activity, and extracellular matrix composition. Genetic studies have identified several predisposing factors, including specific gene mutations and polymorphisms. Treatment strategies vary; however, intralesional corticosteroids remain the first-line treatment for both conditions. Emerging therapies targeting specific molecular pathways offer potential for improved outcomes. Conclusion: Hypertrophic scars and keloids are complex conditions with distinct clinical and molecular characteristics. Understanding these differences is crucial for developing targeted and effective therapies. Future research should focus on unraveling the genetic basis of these conditions and exploring novel therapeutic targets. Enhanced knowledge of the pathogenic mechanisms will facilitate the advancement of personalized medicine approaches in the management of hypertrophic scars and keloids.

FUSeg: The Foot Ulcer Segmentation Challenge

Wound care professionals provide proper diagnosis and treatment with heavy reliance on images and image documentation. Segmentation of wound boundaries in images is a key component of the care and diagnosis protocol since it is important to estimate the area of the wound and provide quantitative measurement for the treatment. Unfortunately, this process is very time-consuming and requires a high level of expertise, hence the need for automatic wound measurement methods. Recently, automatic wound segmentation methods based on deep learning have shown promising performance; yet, they heavily rely on large training datasets. A few wound image datasets were published including the Diabetic Foot Ulcer Challenge dataset, the Medetec wound dataset, and WoundDB. Existing public wound image datasets suffer from small size and a lack of annotation. There is a need to build a fully annotated dataset to benchmark wound segmentation methods. To address these issues, we propose the Foot Ulcer Segmentation Challenge (FUSeg), organized in conjunction with the 2021 International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). It contains 1210 pixel-wise annotated foot ulcer images collected over 2 years from 889 patients. The submitted algorithms are reviewed in this paper and the dataset can be accessed through the Foot Ulcer Segmentation Challenge website.

An Innovative Single‐Stage Approach of High‐Tension Keloid Excision and Reconstruction Using Acellular Dermal Matrix and Epidermal Skin Grafting

The treatment of keloids, particularly in high‐tension areas, is challenging due to their extension beyond the original wound boundaries and high recurrence rates, thereby rendering traditional treatments ineffective. In this study, we investigated the effectiveness of a novel single‐stage treatment approach that combined acellular dermal matrix (ADM) with keloid‐specific epidermal skin grafting. To further prevent recurrence after neo‐skin formation, the treatment was followed by fractionated laser and radiation therapy (LCR). Seven patients with high‐tension keloids, including one with keloids at two locations, were treated and followed‐up for an average of 15.9 months. The patients showed significant improvements in wound healing and skin appearance, with a marked reduction in the Patient and Observer Scar Assessment Scale (POSAS) (scores from 91.1 ± 5.6 to 23.8 ± 6.1 (p < 0.001)). This approach effectively minimizes tension, reduces the likelihood of keloid recurrence, and serves as a viable alternative to conventional methods that often involve challenges related to donor‐site acquisition. No recurrence was observed during the follow‐up period, indicating a promising innovation in the management of extensive keloids and offering improved healing and esthetic outcomes, particularly in high‐tension areas.

Automatic foot ulcer segmentation using conditional generative adversarial network (AFSegGAN): A wound management system.

Effective wound care is essential to prevent further complications, promote healing, and reduce the risk of infection and other health issues. Chronic wounds, particularly in older adults, patients with disabilities, and those with pressure, venous, or diabetic foot ulcers, cause significant morbidity and mortality. Due to the positive trend in the number of individuals with chronic wounds, particularly among the growing elderly and diabetes populations, it is imperative to develop novel technologies and practices for the best practice clinical management of chronic wounds to minimize the potential health and economic burdens on society. As wound care is managed in hospitals and community care, it is crucial to have quantitative metrics like wound boundary and morphological features. The traditional visual inspection technique is purely subjective and error-prone, and digitization provides an appealing alternative. Various deep-learning models have earned confidence; however, their accuracy primarily relies on the image quality, the dataset size to learn the features, and experts' annotation. This work aims to develop a wound management system that automates wound segmentation using a conditional generative adversarial network (cGAN) and estimate the wound morphological parameters. AFSegGAN was developed and validated on the MICCAI 2021-foot ulcer segmentation dataset. In addition, we use adversarial loss and patch-level comparison at the discriminator network to improve the segmentation performance and balance the GAN network training. Our model outperformed state-of-the-art methods with a Dice score of 93.11% and IoU of 99.07%. The proposed wound management system demonstrates its abilities in wound segmentation and parameter estimation, thereby reducing healthcare workers' efforts to diagnose or manage wounds and facilitating remote healthcare.

Automated wound segmentation and classification of seven common injuries in forensic medicine

In forensic medical investigations, physical injuries are documented with photographs accompanied by written reports. Automatic segmentation and classification of wounds on these photographs could provide forensic pathologists with a tool to improve the assessment of injuries and accelerate the reporting process. In this pilot study, we trained and compared several preexisting deep learning architectures for image segmentation and wound classification on forensically relevant photographs in our database. The best scores were a mean pixel accuracy of 69.4% and a mean intersection over union (IoU) of 48.6% when evaluating the trained models on our test set. The models had difficulty distinguishing the background from wounded areas. As an example, image pixels showing subcutaneous hematomas or skin abrasions were assigned to the background class in 31% of cases. Stab wounds, on the other hand, were reliably classified with a pixel accuracy of 93%. These results can be partially attributed to undefined wound boundaries for some types of injuries, such as subcutaneous hematoma. However, despite the large class imbalance, we demonstrate that the best trained models could reliably distinguish among seven of the most common wounds encountered in forensic medical investigations.

Three-dimensional, Time-dependent MHD Simulation of Disk–Magnetosphere–Stellar Wind Interaction in a T Tauri, Protoplanetary System

We present a three-dimensional, time-dependent MHD simulation of the short-term interaction between a protoplanetary disk and the stellar corona in a T Tauri system. The simulation includes the stellar magnetic field, self-consistent coronal heating and stellar wind acceleration, and a disk rotating at sub-Keplerian velocity to induce accretion. We find that, initially, as the system relaxes from the assumed initial conditions, the inner part of the disk winds around and moves inward and close to the star as expected. However, the self-consistent coronal heating and stellar wind acceleration build up the original state after some time, significantly pushing the disk out beyond 10R ⋆. After this initial relaxation period, we do not find clear evidence of a strong, steady accretion flow funneled along coronal field lines, but only weak, sporadic accretion. We produce synthetic coronal X-ray line emission light curves, which show flare-like increases that are not correlated with accretion events nor with heating events. These variations in the line emission flux are the result of compression and expansion due to disk–corona pressure variations. Vertical disk evaporation evolves above and below the disk. However, the disk–stellar wind boundary stays quite stable, and any disk material that reaches the stellar wind region is advected out by the stellar wind.

Impact of Image Compression on In Vitro Cell Migration Analysis

Collective cell movement is an indication of phenomena such as wound healing, embryonic morphogenesis, cancer invasion, and metastasis. Wound healing is a complicated cellular and biochemical procedure in which skin cells migrate from the wound boundaries into the wound area to reconstruct the injured skin layer(s). In vitro analysis of cell migration is an effective assay for measuring changes in cell migratory complement in response to experimental inspections. Open-source segmentation software (e.g., an ImageJ plug-in) is available to analyze images of in vitro scratch wound healing assays; however, often, these tools are error-prone when applied to, e.g., low-contrast, out-of-focus, and noisy images, and require manual tuning of various parameters, which is imprecise, tedious, and time-consuming. We propose two algorithmic methods (namely log gradient segmentation and entropy filter segmentation) for cell segmentation and the subsequent measurement of the collective cell migration in the corresponding microscopic imagery. We further investigate the effects of image compression on the algorithms’ measurement accuracy, applying lossy compression algorithms (the current ISO standards JPEG2000, JPEG, JPEG-XL and AV1, BPG, and WEBP). We aim to identify the most suitable compression algorithm that can be used for this purpose, relating rate–distortion performance as measured in terms of peak signal-to-noise ratio (PSNR) and the multiscale structural similarity index (MS-SSIM) to the segmentation accuracy obtained by the segmentation algorithms. The experimental results show that the log gradient segmentationalgorithm provides robust performance for segmenting the wound area, whereas the entropy filter segmentation algorithm is unstable for this purpose under certain circumstances. Additionally, the best-suited compression strategy is observed to be dependent on (i) the segmentation algorithm used and (ii) the actual data sequence being processed.

Reliability of an AI-Powered Application Across Different Mobile Devices for Assessment of Chronic Wounds.

Objective: Evaluate the inter- and intrarater reliability of a wound assessment tool in iPhone 12 and 13 mini modalities against a validated iPad mini/Structure Sensor configuration. Approach: We assessed a wound measurement application (eKare inSight®) for result consistency in patients presenting with wounds. Assessments were analyzed using a two-way analysis of variance. Intraclass correlation coefficient (ICC) was computed for intrarater (ICC1,1) and inter-rater (ICC2,1) analysis using a two-way random effects model. Paired t-test assessed the statistical difference between measurement methods. Results: Forty-two lesions were analyzed with surface areas ranging from 0.2 to 23 cm2 (average 4.33 ± 5.44 cm2). A high level of reliability was observed for repeat wound area measurements by the same examiner (ICC1,1 = 0.997) and between examiners with iPhone 13 mini (ICC2,1 = 0.998). There was no significant difference between iPhone 12 and iPad mini/Structure Sensor (p = 0.78) or between iPhone 13 mini and iPhone 12 (p = 0.22). Minimal difference existed between iPhone 13 mini and iPad mini/Structure Sensor (p = 0.049, Cohen's d = 0.01). Innovation: Increased pervasiveness of smartphones in clinical care, coupled with advances in smartphone imaging and machine learning, allows for a potential solution to the problem of fast and accurate wound measurements. The application investigated produces wound measurement results quickly and with demonstrated accuracy. It does not require a calibration sticker or reference marker and allows for automatic wound boundary delineation. Conclusion: The results of this study suggest that a digital planimetry mobile application may offer high levels of reliability across devices and users.

Nonprecipitating Shallow Cumulus Convection Is Intrinsically Unstable to Length Scale Growth

Abstract Condensation in cumulus clouds plays a key role in structuring the mean, nonprecipitating trade wind boundary layer. Here, we summarize how this role also explains the spontaneous growth of mesoscale [>O(10) km] fluctuations in clouds and moisture around the mean state in a minimal-physics, large-eddy simulation of the undisturbed period during BOMEX on a large [O(100) km] domain. Small, spatial anomalies in condensation in cumulus clouds, which form on top of small moisture fluctuations, power circulations that transport moisture, but not heat, from dry to moist regions, and thus reinforce the condensation anomaly. We frame this positive feedback as a linear instability in mesoscale moisture fluctuations, whose time scale depends only on (i) a vertical velocity scale and (ii) the mean environment’s vertical structure. In our minimal-physics setting, we show both ingredients are provided by the shallow cumulus convection itself: it is intrinsically unstable to length scale growth. The upshot is that energy released by clouds at kilometer scales may play a more profound and direct role in shaping the mesoscale trade wind environment than is generally appreciated, motivating further research into the mechanism’s relevance.

Trade Wind Boundary Layer Turbulence and Shallow Precipitating Convection: New Insights Combining SAR Images, Satellite Brightness Temperature, and Airborne In Situ Measurements

AbstractThe imprint of marine atmospheric boundary layer (MABL) dynamical structures on sea surface roughness, as seen from Sentinel‐1 synthetic aperture radar (SAR) acquisitions, is investigated. We focus on 13 February 2020, a case study of the elucidating the role of clouds‐circulation coupling in climate field campaign. For suppressed conditions, convective rolls imprint on sea surface roughness is confirmed through the intercomparison with MABL turbulent organization deduced from airborne measurements. A discretization of the SAR wide swath into 25 × 25 km2 tiles then allows us to capture the spatial variability of the turbulence organization varying from rolls to cells. Second, we objectively detect cold pools within the SAR image and combine them with geostationary brightness temperature. The geometrical or physically‐based metrics of cold pools are correlated to cloud properties. This provides a promising methodology to analyze the dynamics of convective systems as seen from below and above.

New Actuator Disk Model for the Analysis of Wind Turbines Wake Interaction with the Ground

Wake models based on Actuator Disk theory are usually applied to optimize the wind farm layouts and improve their overall efficiency and expected AEP. Despite the effectiveness of the existing models, most Actuator Disk approaches are based on the flow axisymmetric assumption, without considering the ground effect on the wake behavior. However, it has been shown that the mast’s height, or distance from the wind turbine to the ground, has an influence on the wake expansion on both hub’s side and at downstream of the wind turbine. Therefore, in this study, a hybrid CFD-BEM-Actuator Disk approach is developed to address the lack of the existing models. In the proposed model, the 3D wind rotor is modeled by a set of blade elements. Then, the local lift and drag forces acting on each blade element are calculated using BEM theory and incorporated into the momentum equation. This BEM-AD model is implemented in a User Defined Function (UDF) that is loaded into the CFD software. Thereby, ground effects are considered to be a wall boundary and defining a wind boundary layer profile at the inlet boundary, which describes the Atmospheric Boundary Layer (ABL). For the validation of this new Actuator Disk model, an enhanced experimental study is conducted at the Dynfluid Laboratory wind tunnel (ENSAM School Paris Tech). The Particle Image Velocimetry (PIV) measurements are used for the experimental wake explorations applied to a miniature two-bladed wind turbine. The wake developments are analyzed at two different hub heights ratio, h/D = 0.7 and 1.0 (where h is the hub height, and D is the wind rotor diameter). The analysis of the outcomes showed that the numerical simulations are in good correlation with the experimental measurements of the ENSAM wind tunnel. The numerical results show that for h/D=0.7, the upper half of the rotor operates within the boundary layer whereas the lower tip vortices are mainly developed in the horizontal direction with lower intensity compared to the upper tip vortices. This effect was not observed for the case h/D=1.0 where the rotor operates outside of the boundary layer; however, the wake centerline is upward deflected at about 0.3D. The main conclusion is that a distance above 7D must be observed between wind turbines to optimize the wind farm performance and over 1D hub height be required to limit the influence of the ground boundary layer effect.

Experimental Examination for the Electric Power Generation of a Commercial Small-scale Wind Turbine with Modified Aerodynamic Design

Small-scale horizontal axis wind turbines (SSHAWT) have recently gained more interest due to fuel shortages and environmental issues. Generally, they are installed close to the ground in the wind boundary layer, where the velocity is relatively small. This study aims to evaluate the performance of a commercial SSHAWT and to modify rotor design based on wind velocity in the field. The experimental measurements are performed to examine a commercial 1.5 m radius rotor of 1 kW SSHAWT, which was designed at a rated velocity of about 8 m/s. The CFD calculations are performed as well to understand flow characteristics and to verify the experimental measurements. In the experimental procedure, the test of the wind turbine with a permanent magnet synchronous generator showed that at a wind velocity of 5 and 6 m/s, the highest generated power is 163.9 and 306 W corresponding to power coefficients of 0.255 and 0.28 when AC voltage of the generator is 24.4 and 37.76 V, the DC voltage after rectified 22 and 34 V, and the load current 7.45 and 9 A, respectively. Then the available wind velocity was measured in the field, and the average velocity was 4 m/s. Therefore, a more appropriate rotor is designed based on field velocity. The CFD calculations are used to test the new rotor. The results clarify that for the new rotor, the maximum blade's power coefficient is enhanced by more than 60 % compared to the commercial rotor.

Organization Development in Precipitating Shallow Cumulus Convection: Evolution of Turbulence Characteristics

Abstract Horizontal organization or mesoscale variability is an important mechanism in the interaction of the boundary layer with the large-scale conditions. The development of organization in a precipitating cumulus trade wind boundary layer is studied using large-eddy simulations with extensive horizontal domains, up to 160 × 160 km2 and fine grid resolution (40 m). The cloud fields vary between different computational domain sizes. Mean profiles and vertical velocity statistics do not vary significantly, both with respect to the domain size and when large-scale organization develops. Turbulent kinetic energy (TKE) rapidly increases when organization develops. The increase of TKE is attributed to the horizontal component, whereas the vertical velocity variance does not change significantly. The large computational domains blend the boundary between local convective circulations and mesoscale horizontal motions leading to the dependence of horizontal TKE on the LES domain size. Energy-containing horizontal length scales are defined based on the premultiplied spectra. When large-scale organization develops, the premultiplied spectra develop multiple peaks corresponding to the characteristic horizontal scales in the boundary layer. All flow variables have a small length scale of 1–2 km, which corresponds to local convective motions, e.g., updrafts and cumulus clouds. Organization development creates additional larger length scales. The growth rate of the large length scale is linear and it is about 3–4 km h−1, which agrees well with the growth rate of the cold pool radii. A single energy containing length scale is observed for vertical velocity for the entire run (even after organized convection develops) that is fairly constant with height.