Performance Of Panels Research Articles

PENGARUH KECERAHAN TERHADAP ENERGI LISTRIK YANG DIHASILKAN OLEH PANEL SURYA

The reduction in fossil energy production, particularly petroleum, along with the global commitment to reducing greenhouse gas emissions, encourages the government to continuously improve the role of new and renewable energy to maintain energy security and independence. Renewable energy is a” source of energy derived from nature that can be used freely, continuously renewed, and unlimited, such as“solar energy. This study aims to analyze the performance of solar panels” in terms of battery charging and discharging duration, current, voltage, and power under sunny and cloudy conditions. The research method was conducted directly in the field, using a solar panel with a capacity of 10WP (Watt Peak) as the study object. The results showed that the performance of solar panels under sunny conditions achieved the highest average power of 4.81 Watts and the fastest battery charging time of 6 hours. Under cloudy conditions, the average power obtained was 4.34 Watts, and the battery charging time was 6 hours and 20 minutes. The battery discharging duration for a 5-watt lamp was 16 hours and 8 minutes, for a 10-watt lamp, it was 8 hours and 4 minutes, and for a 15-watt lamp, it was 5 hours and 6 minutes.

Study on the Dynamic Crushing Behaviors of Hourglass Honeycomb Sandwich Panels

In response to the problem of enclosed internal spaces in existing honeycomb sandwich panels, the concept of an hourglass honeycomb sandwich panel model is proposed for the first time, which provides a breakthrough approach for achieving the multifunctional integration of honeycomb sandwich panels. Numerical simulation methods are employed to investigate the dynamic performance of the hourglass honeycomb sandwich panels. The focus is on discussing the influences of the geometric parameters on the deformation mode, dynamic response, load uniformity, and energy absorption capacity of the hourglass honeycomb sandwich panel under different impact velocity conditions. The research results indicate that under low-velocity-impact conditions, the influence of the geometric parameters is predominant. In contrast, under high-velocity-impact conditions, the influence of the impact velocity conditions is predominant. Hourglass honeycomb sandwich panels with low density, a large inclination angle of the honeycomb wall, and small contact distances between the hourglass honeycomb cell and the panel have excellent load uniformity, and the distances between the contact points of the hourglass honeycomb cell and the panel have a great influence on the energy absorption capacity of the sandwich panels. This study provides a theoretical basis for the application of honeycombs in aerospace and other engineering areas.

Performance of photovoltaic panels with different inclinations under uniform thermal loading

Integrating photovoltaic (PV) panels with different tilt angles in building envelopes or roofs is widely employed for environmental sustainability. However, little is known about the influence of different tilt angles on the thermal failure of the photovoltaic façades or roofs in fire conditions. A total of 15 four-edge shielded PV panels (300 × 300 × 4.7 mm3), with five different inclinations of 0°, 15°, 30°, 45° and 60°, were heated to fail using a uniform radiant panel. Measurements were taken to track glass thermal breakage, surface temperatures, incident heat flux and failure characteristics. The glass fracture and pyrolysis of the internal thermoplastic materials were observed under thermal radiation. The average breakage time of glass in PV panels showed an increasing trend with increasing inclination of the PV panels. Moreover, when the PV panels were tilted beyond 30°, the time to failure increased more significantly. The maximum temperature difference and heat flux that the PV panels can withstand were primarily measured within the range of 61–84 °C and 8–15 kW/m2, respectively. Finally, the test results were simulated by a finite element method (FEM) model, calculating the heat transfer and thermal stress of PV panels: the average errors concerning temperature distributions and failure times were smaller than 15 % compared with the experimental results.

Environmental Sustainability Assessment of Cold Storage Panel Production

Today's ever-increasing environmental sustainability concerns have led to a major shift in construction sites and industrial sectors. In this context, the choice of construction materials for important structures such as cold storages plays an important role in terms of both environmental impacts and energy efficiency. The aim of this study is to evaluate the environmental loads of cold storage panels with thicknesses of 80 mm, 100 mm, 120 mm, 150 mm, 180 mm and 200 mm. In order to reveal the production inputs that cause these loads, the environmental effects were examined specifically for the 100 mm thick cold storage panel. Environmental impacts were analyzed using the Life Cycle Assessment (LCA) method in accordance with the ISO 14040/44 methodology as a system boundary "cradle to gate". This study focused on three different environmental impact categories of cold storage panels produced in Türkiye: global warming potential (GWP), cumulative energy demand (CED) and water footprint. In the evaluation of environmental impacts, production inventory information obtained from the panel manufacturer was used. For analyses, Simapro v. 8.5 LCA software was used. Analysis results show that the use of galvanized sheet metal in cold storage panel production is a hot spot in terms of global warming effect. It has been determined that the largest share in the water footprint belongs to polyurethane used as insulation material. Additionally, according to the CED, non-renewable fossil and non-renewable nuclear were determined to be the most affected categories, and the use of galvanized sheet metal and polyurethane were determined to be the most important hot spots in terms of non-renewable and renewable resources. To help improve the environmental performance of the cold storage panel, it is recommended to use bio-based and less environmentally impactful raw materials in production and to measure their environmental impact on a life cycle basis from cradle to grave.

Improving solar panel performance using MPPT optimization algorithms

One of the primary challenges faced by solar energy systems is the issue of inconsistent lighting and uneven distribution of sunlight across the surface of solar panels. These conditions can result in a substantial reduction in the power output of the panels and, in some cases, the complete failure of certain solar cells. This paper examines the effects of shading on solar panel performance, focusing on how partial shading impacts energy production and efficiency through both experimental analysis and simulation. The findings emphasize the critical influence of shading patterns and configurations on the overall efficiency of photovoltaic systems. The study highlights the necessity of implementing shading mitigation strategies and optimization algorithms to enhance energy production and ensure the reliability of solar systems operating in environments with varying light conditions. This study showed that the use of optimization algorithms in photovoltaic systems exposed to shading increases their efficiency in terms of energy saving as well as performance stability. The simulation results shows that the GWO algorithm gives a higher performance than the other algorithms in the same partial shading conditions.

Performance Comparison of Bio-Inspired Algorithms for Optimizing an ANN-Based MPPT Forecast for PV Systems.

This study compares bio-inspired optimization algorithms for enhancing an ANN-based Maximum Power Point Tracking (MPPT) forecast system under partial shading conditions in photovoltaic systems. Four algorithms-grey wolf optimizer (GWO), particle swarm optimization (PSO), squirrel search algorithm (SSA), and cuckoo search (CS)-were evaluated, with the dataset augmented by perturbations to simulate shading. The standard ANN performed poorly, with 64 neurons in Layer 1 and 32 in Layer 2 (MSE of 159.9437, MAE of 8.0781). Among the optimized approaches, GWO, with 66 neurons in Layer 1 and 100 in Layer 2, achieved the best prediction accuracy (MSE of 11.9487, MAE of 2.4552) and was computationally efficient (execution time of 1198.99 s). PSO, using 98 neurons in Layer 1 and 100 in Layer 2, minimized MAE (2.1679) but had a slightly longer execution time (1417.80 s). SSA, with the same neuron count as GWO, also performed well (MSE 12.1500, MAE 2.7003) and was the fastest (987.45 s). CS, with 84 neurons in Layer 1 and 74 in Layer 2, was less reliable (MSE 33.7767, MAE 3.8547) and slower (1904.01 s). GWO proved to be the best overall, balancing accuracy and speed. Future real-world applications of this methodology include improving energy efficiency in solar farms under variable weather conditions and optimizing the performance of residential solar panels to reduce energy costs. Further optimization developments could address more complex and larger-scale datasets in real-time, such as integrating renewable energy sources into smart grid systems for better energy distribution.

Analysis and experimental evaluation framework for buckling and post-buckling of composite stiffened panels

The composite thin-walled stiffened panel exhibits considerable potential for post-buckling bearing capacity. However, due to the limitations in post-buckling analysis and experimental evaluation capabilities, local buckling under limited loads is not permissible for current aircraft composite panels, significantly diminishing the weight reduction effect of composite panels. In this paper, experimental research on composite fuselage curved panels under combined compression and shear loads was conducted with an experimental system. The buckling analysis and failure prediction of composite fuselage curved panels were performed by the finite element method, using the interlaminar failure criterion and an improved Tsai-Wu failure criterion. Meanwhile, interaction formulaes were utilized to predict buckling correlation curves and failure envelopes. The results show that the finite element model with improved criteria and the rapid analysis method based on interaction formulaes exhibit high accuracy, which are available for properties analysis of composite panels. The experimental techniques and analytical methods proposed in this paper can provide a way to evaluate the buckling and post-buckling performance of composite stiffened panels.

Integrated analysis of microbiota and gut microbial metabolites in blood for breast cancer.

Gut microbiota and associated metabolites have been linked to breast carcinogenesis. Evidences demonstrate blood microbiota primarily originates from the gut and may act as a biomarker for breast cancer. We aimed to characterize the microbiota-gut microbial metabolites cross-talk in blood and develop a composite diagnostic panel for breast cancer. We performed 16S rRNA gene sequencing and metabolomics profiling on blood samples from 107 breast cancer cases and 107 age-paired controls. We found that the alpha diversity of the blood microbiota was decreased in breast cancer compared to controls. There were significantly different profiles of microbiota and gut microbial metabolites in blood between these two groups, with nine bacterial genera and four gut microbial metabolites increased in patients, while thirty-nine bacterial genera and two gut microbial metabolites increased in controls. Some breast cancer-associated gut microbial metabolites were linked to differential blood microbiota, and a composite microbiota-metabolite diagnostic panel was further developed with an area under the curve of 0.963 for breast cancer. This study underscored the pivotal role of microbiota and gut microbial metabolites in blood and their interactions for breast carcinogenesis, as well as the potential of a composite diagnostic panel as a non-invasive biomarker for breast cancer.IMPORTANCEOur integrated analysis demonstrated altered profiles of microbiota and gut microbial metabolites in blood for breast cancer patients. The extensive correlation between microbiota and gut microbial metabolites in blood assisted the understanding of the pathogenesis of breast cancer. The good performance of a composite microbiota-gut microbial metabolites panel in blood suggested a non-invasive approach for breast cancer detection and a novel strategy for better diagnosis and prevention of breast cancer in the future.

Research on thermal insulation performance and application simulation of high-temperature vacuum insulation panel

Research on thermal insulation performance and application simulation of high-temperature vacuum insulation panel

Validation of a blood biomarker panel for machine learning-based radiation biodosimetry in juvenile and adult C57BL/6 mice

Following a large-scale radiological event, timely collection of samples from all potentially exposed individuals may be precluded, and high-throughput bioassays capable of rapid and individualized dose assessment several days post-exposure will be essential for population triage and efficient implementation of medical treatment. The objective of this work was to validate the performance of a biomarker panel of radiosensitive intracellular leukocyte proteins (ACTN1, DDB2, and FDXR) and blood cell counts (CD19+ B-cells and CD3+ T-cells) for retrospective classification of exposure and dose estimation up to 7 days post-exposure in an in-vivo C57BL/6 mouse model. Juvenile and adult C57BL/6 mice of both sexes were total body irradiated with 0, 1, 2, 3, or 4 Gy, peripheral blood was collected 1, 4, and 7-days post-exposure, and individual blood biomarkers were quantified by imaging flow cytometry. An ensemble machine learning platform was used to identify the strongest predictor variables and combine them for biodosimetry outputs. This approach generated successful exposure classification (ROC AUC = 0.94, 95% CI: 0.90–0.97) and quantitative dose reconstruction (R2 = 0.79, RMSE = 0.68 Gy, MAE = 0.53 Gy), supporting the potential utility of the proposed biomarker assay for determining exposure and received dose in an individual.

Composite Panels from Wood Waste: A Detailed Review of Processes, Standards, and Applications

The global demand for sustainable building materials has fuelled research into composite panels from wood waste. Despite their potential, the widespread adoption of this practice is hindered by the absence of quality standards, inconsistent material properties, and uncertainties about durability and strength. This paper critically reviews existing standards, manufacturing processes, and the suitability of panels from wood waste. A systematic review is conducted to identify the influencing processes and parameters affecting panel performance, from waste collection to the finishing stages. The findings indicate that incorporating 10–30% of wood waste can enhance the mechanical and physical properties, with particularly improved hygroscopic properties and greater dimensional stability. By establishing comprehensive standards and optimizing manufacturing processes, wood waste-based panels can emerge as a viable and eco-friendly alternative. Furthermore, the potential for repeated recycling in a closed-loop process offers promising environmental benefits, though it necessitates balancing resource conservation with product quality. By addressing these challenges, wood waste-based panels can significantly contribute to environmental conservation and resource management.

Innovative cooling for PV panels: Energy and exergy assessments of water-induced V-shaped channels

Panel temperature is one of the important parameters that influences the output from a solar photovoltaic (PV) panel. Higher panel surface temperature leads to deterioration of the electrical output of the panel. Many researchers have tried to improve the panel's cooling performance using various active and passive techniques. The present experimental investigation aims to estimate the panel performance of a PV panel fitted with V-shaped aluminium cooling channels at its back surface as a passive technique. Water is made to flow in these channels to cool the panel. The volume flow rate in the cooling channels varies between 0.3LPM and 0.6LPM in steps of 0.1LPM. All the chosen flow rates used in the study tend to improve the panel's output in terms of electrical efficiency through a drop in the panel temperature. For the volume flow rate corresponding to 0.3 LPM, a temperature drop of about 12.7 °C is seen, contributing to a decrement of about 21.6 % compared to the plain PV panel without cooling arrangements. The modified panel also yields about a 2.26 % improvement in electrical efficiency for the volume flow rate of 0.5 LPM, despite being a cloudy day. Therefore, the PV module equipped with V-shaped water-cooled channels is recommended for the enhanced performance of PV installations.

Seismic Performance of Cellular Lightweight Concrete Block Panels as Infilled Wall in RC Frames Due to Cyclic Lateral Loading

Seismic Performance of Cellular Lightweight Concrete Block Panels as Infilled Wall in RC Frames Due to Cyclic Lateral Loading

Objective and subjective assessment of PET felt recycled panels as an acoustic treatment in the meeting rooms

This study presents the performance of the PET-felt recycled panels for the room acoustic treatment. As the objective parameters, Reverberation Time (RT) and Speech Transmission Index (STI) were measured with B&K DIRAC, an omnidirectional loudspeaker, and power amplifier in the meeting room at the Department of Interior Design, Bilkent University, Ankara, Turkey, before the acoustic treatment. Following ISO 12913-2 Method A, Perceived Affective Quality (PQA), Appropriateness, and Assessment of the Acoustic Environment were measured. Fifteen participants who were occupants of the meeting room were selected for the questionnaire survey to be conducted using the snowball method. The findings showed that the reverberation time was five seconds at 1 kHz, which is insufficient, and the acoustic quality could have been better for the speech-purpose room. PET-felt recycled acoustic panels were applied to the ceiling and walls as a solution. After the acoustic treatments, all procedures were repeated with the same. The results showed that significant improvements have been provided in both objective and subjective assessments. RT was in the optimum range. The participants found the meeting room with PET-felt recycled panels more pleasant and eventful after the acoustic treatment.

B-262 Validation of a point-of-care lateral flow immunoassay for urine drug testing prior to application in an outpatient rapid access addiction medicine clinic

Abstract Background Point-of-care (POC) urine drug testing is a useful adjunct to self-reporting in rapid access addiction medicine settings to immediately guide patient management. However, available POC immunoassays have limitations including cross-reactivity with unrelated compounds or low sensitivity that may cause false results. Here, we assessed the performance of a multi-drug test panel by comparing against gold-standard liquid chromatography tandem mass spectrometry (LC-MS/MS) testing. Methods 102 residual urine specimens were assayed using a competitive lateral flow immunoassay (LFA) for 10 drugs: 2-ethylene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP, methadone metabolite), buprenorphine, morphine, hydromorphone, oxycodone, fentanyl, cocaine, methamphetamine, amphetamine, and benzodiazepines (BTNX Rapid ResponseTM Multi-Drug Panel). Results were compared to those obtained by LC-MS/MS (n=67, 66%) or kinetic interaction of microparticles in solution automated immunoassay (KIMS) (Roche Diagnostics, n=35, 33%). Broad spectrum LC-MS/MS results were reviewed in entirety for discordant cases, particularly in false positives to identify the presence of any known cross-reacting compounds. Results Of 10 drugs evaluated, four demonstrated ≥95% agreement with LC-MS/MS or KIMS immunoassay (EDDP, buprenorphine, oxycodone, methamphetamine). Fentanyl demonstrated the highest false negative rate of 44% (LFA cut-off: 10 ng/mL) followed by amphetamines (22%, cut-off: 1000 ng/mL). Morphine and hydromorphone demonstrated false positive rates of 14% and 18%, respectively, with most cases likely due to cross-reacting opiate or opioid metabolites. Benzodiazepines (target: Oxazepam) demonstrated false positive and negative rates of 13% and 24%, respectively. Conclusions To our knowledge, this is the first study to evaluate the performance of the BTNX multi-drug test panel against definitive testing in urine samples. While good concordance was observed for most drugs, high rates of discordant results for fentanyl and others emphasize the need for confirmatory testing by methods with higher sensitivity and specificity. Careful consideration prior to implementation would be essential, including physician education, interpretative comments, and training resources.

B-202 Clinical and analytical performance evaluation of Savanna RVP4 panel versus three methodologies

Abstract Background Rapid molecular diagnosis became a key solution for healthcare institutions across the world, after COVID-19 pandemic. It has enabled diagnosis based on improved quality, accuracy, analytical sensitivity, and turnaround times for laboratory services. It also has positioned this methodology as a trusted technology for point-of-care settings. These solutions also allow to consolidate combinations of different pathogen detection in panels. This study assessed the analytical and clinical performance of the novel Savanna RVP4 panel against other available methodologies. Methods A prospective study was performed, considering 84 patient samples obtained from nasopharyngeal swabs. Samples were processed in parallel after collection, using Savanna RVP4, and either QIAstat-Dx Respiratory SARS-CoV Panel (59 samples), Sansure iPonatic (10 samples) and BioFire® Respiratory 2.1 (RP2.1) Panel (15 samples). Samples were collected in either MTU, commercial or homemade PBS. Results Overall clinical sensitivity and specificity were 96.43% and 99.64%, respectively for the aggregated panels (Table 1). By technology, the overall clinical sensitivity and specificity were 93.75% and 99.51% versus QIAstat, 100% and 100% versus Biofire, respectively. For iPonatic comparisons, no positive samples were processed and 100% of specificity was obtained. Cycle threshold (Ct) values for positive samples were compared using box plots. Ct values also showed slighlty differences, where means were lower for RSV and Flu A in Savanna (22 and 22.9 respectively) versus other PCR assays (22.5 and 24.5 respectively). For SARS-CoV-2, Ct values were higher versus other methods (19.8 vs 13.6). Conclusions Results obtained with Savanna RVP4 were comparable to those obtained with other methodologies, correlating with patient clinical symptoms. Samples showing disagreement for QIAstat comparison panel, in Flu A and RSV assays, corresponded to the same patient samples for the two methodologies, where Ct obtained in QIAstat were above 33. This evaluation also provides strong evidence supporting PBS usage for samples processed in Savanna RVP.

Study on factors affecting slip resistance performance of floor panels

Abstract In order to improve the slip resistence performance of floor panels used in escalators and moving walkways, as well as ensure the safety, the paper analyzes the impact of different factors on the slip resistence performance of floor panels through experiments. The test results reveal that the surface treatment degree of floor panels, environmental temperature and humidity, and passengers’ footwear all exert varying degress of impact on the slip resistence performance.

Hydrodynamic frictional performance of fouled panels: a comparative study of different coating types.

This research study delves into the hydrodynamic frictional characteristics of fouled panels coated with different types of coatings, investigating how fouling coverage and surface roughness influence drag. The investigation incorporates data on the overall percentage coverage of fouling, as well as roughness measurements obtained through a 3D profilometer. Drag data collected from a flowcell simulation of real-world flow conditions complements these measurements. Notably, the determination of the level of fouling leverages the capabilities of CIE L*a*b as an image analysis method, focusing on the overall coverage rather than individual fouling species. The objective is to illustrate how fouled panels perform under varying flow and coating conditions compared to their clean counterparts. Furthermore, the paper proposes a roughness scaling approach that considers both the percentage coverage and measured areal roughness for each coating type, encompassing both fouled and unfouled areas. This approach provides valuable insights into the combined effects of fouling and surface roughness on hydrodynamic performance, enhancing our understanding of the intricate interplay between these factors.

Serum metabolite biomarkers for the early diagnosis and monitoring of age-related macular degeneration

IntroductionAge-related macular degeneration (AMD) is a leading cause of irreversible blindness worldwide, with significant challenges for early diagnosis and treatment. ObjectivesTo identify new biomarkers that are important for the early diagnosis and monitoring of the severity/progression of AMD. MethodsWe investigated the diagnostic and monitoring potential of blood metabolites in a cohort of 547 individuals (167 healthy controls, 240 individuals with other eye diseases as eye disease controls, and 140 individuals with AMD) from 2 centers over three phases: discovery phase 1, discovery phase 2, and an external validation phase. The samples were analyzed via a mass spectrometry-based, widely targeted metabolomic workflow. In discovery phases 1 and 2, we built a machine learning algorithm to predict the probability of AMD. In the external validation phase, we further confirmed the performance of the biomarker panel identified by the algorithm. We subsequently evaluated the performance of the identified biomarker panel in monitoring the progression and severity of AMD. ResultsWe developed a clinically specific three-metabolite panel (hypoxanthine, 2-furoylglycine, and 1-hexadecyl-2-azelaoyl-sn-glycero-3-phosphocholine) via five machine learning models. The random forest model effectively discriminated patients with AMD from patents in the other two groups and showed acceptable calibration (area under the curve (AUC) = 1.0; accuracy = 1.0) in both discovery phases 1 and 2. An independent validation phase confirmed the diagnostic model’s efficacy (AUC = 0.962; accuracy = 0.88). The three-biomarker panel model demonstrated an AUC of 1.0 in differentiating the severity of AMD via RF machine learning, which was consistent across both the discovery and external validation phases. Additionally, the biomarker concentrations remained stable under repeated freeze–thaw cycles (P > 0.05). ConclusionsThis study reveals distinct metabolite variations in the serum of AMD patients, paving the way for the development of the first routine laboratory test for AMD.

Assessing the performance of multi-InDel panels for human identification among admixed Brazilians

Insertion/deletion polymorphisms, or InDels, are widely present in the human genome. They have been considered as potential markers for forensic analysis because they can be genotyped using the CE platform and compatible typing techniques used in forensic laboratories. Additionally, InDels have lower mutation rates and often short amplicon sizes, making them ideal for detecting degraded samples. However, most InDels are bi-allelic; therefore, their discrimination power is relatively low. A new set of genetic marker called multi-InDels was reported to improve InDel's informativeness. Multi-InDel markers are generally designated as microhaplotypes encompassing two or more InDels within a short distance, usually less than 200bp. In this study, we evaluated the applicability of three previously proposed panels of multi-InDel markers, designed for Asian populations, for human identification in Brazil. We assessed all the multi-InDel markers using high-coverage whole-genome sequencing data from a census-based cohort of 1,171 Brazilians residing in São Paulo, the largest Brazilian capital. The results showed that most markers are informative for Brazilian individuals since they present more than three frequent haplotypes with different sizes. However, most markers are prone to amplification/sequencing errors due to repetitive or low-complexity regions. Among the tested panels, the one from Huang et al. (2014) is the most promising for forensic use in Brazil, with a combined match probability and cumulative power of exclusion of 4.92 ×10-14 and 0.9991, respectively. Nevertheless, these values are low compared to the ones obtained with CODIS STRs (short tandem repeats) and larger SNP (single nucleotide polymorphisms) panels. Therefore, new attempts to scan the human genome for highly polymorphic multi-InDel markers are still necessary to obtain a suitable panel of multi-InDels for worldwide populations.