Surface Reflectance Research Articles

Robust optimization of a novel ultraviolet (UV) photoreactor for water disinfection: A neural network approach

To optimize the ultraviolet (UV) water disinfection process, it is crucial to determine the ideal geometric dimensions of a corresponding model that enhance performance while minimizing the impact of uncertain photoreactor inputs. As water treatment directly affects people’s lives, it is crucial to eliminate the risks associated with the non-ideal performance of disinfection photoreactors. Input uncertainties greatly affect photoreactor performance, making it essential to develop a robust optimization algorithm in advance to mitigate these effects and minimize the physical and financial resources required for constructing the photoreactors. In the suggested algorithm, a two-objective genetic algorithm is integrated with a non-intrusive polynomial chaos expansion (PCE) technique. Additionally, the Sobol sampling method is employed to select the necessary samples for understanding the system's behavior. An artificial neural network surrogate model is trained using sufficient data points derived from computational fluid dynamics (CFD) simulations. A novel type of UV photoreactors working based on exterior reflectors is chosen to optimize the process with three uncertain input parameters, including UV lamp power, UV transmittance of water, and diffusive fraction of the reflective surface. In addition, four geometrical design variables are considered to find the optimal configuration of the photoreactor. The standard deviation (SD) and the reciprocal of log reduction value (LRV) are set as the objective functions, calculated using PCE. The optimal design provides a LRV of 3.95 with SD of 0.2. The coefficient of variation (CoV) of the model significantly declines up to 7%, indicating the decreased sensitivity of the photoreactor to the input uncertainties. Additionally, it is discovered that the robust model exhibits minimal sensitivity to changes in reflectivity in various flow rates, and its output variability aligns with the SD obtained through robust optimization.

Fabrication of broadband HgCdTe photodetectors with biomimetic insect corneal arrays

Broadband photodetectors are of great significance in a wide variety of technologically important areas. Inspired by bionics, insect cornea-mimicking microstructures could reduce surface reflection, thus enabling broadband detection. Here, we fabricate a broadband large-area (1280 × 1024) HgCdTe focal plane array photodetector based on biomimetic ZnS microarrays, which achieves high external quantum efficiency (> 60%, averaging 79%) across the broad wavelength range of 400 nm - 5000 nm. These results demonstrate that implementing biomimetic ZnS microstructures has effectively broadened the operational wavelength range of conventional HgCdTe infrared photodetectors to encompass the visible light spectrum. Our work achieves continuous visible-to-infrared spectral imaging and provides a beneficial route to fabricate broadband, large-area, high-performance photodetectors.

A segmented conformal surface for ultrawideband monostatic and bistatic RCS reductions

In this paper, a segmented cylindrical metal surface based on an optimal arrangement is proposed to achieve ultrawideband and wide-angle radar cross section (RCS) reduction. Firstly, a multi-stage semi-cylindrical surface that uses the difference in radius between each cylinder to achieve phase cancellation is designed. The PSO algorithm is used to obtain the best length of each cylinder. Then, each semi-cylinder is equally divided into a certain number of sub-surfaces. Subsequently, in the axial direction, the sequence of these sub-surfaces with different radii is disrupted according to the optimal arrangement to form discontinuous surface reflection phases. A 10-dB RCS reduction under normal incidence is achieved from 4.36 to 20.6 GHz, and the bandwidth ratio reaches 4.72:1. The theoretical analysis and simulated results are in good agreement with the measured results, and the design has an important reference value for ultrawideband monostatic and bistatic RCS reductions for cylinder-like targets.

High dynamic range structured illumination microscopy based on per-pixel coding

Abstract Structured illumination microscopy (SIM) can achieve optical sectioning with high resolution, and have aroused extensive research interest. In SIM, a set of high-contrast illumination patterns are projected onto the sample to modulate the surface height information, and then, a decoding algorithm is applied to the modulated pattern images for high-quality optical sectioning. Applied to samples with large dynamic range of reflectivity, however, SIM may fail to achieve high quality sectioning for accurate surface reconstruction. Herein, an active digital micromirror device (DMD) based illumination method using per-pixel coded strategy is proposed in SIM to realize high-quality measurement for surface with complex reflection characteristics. In this method, the mapping relationship between DMD and the camera is established pixels by pixels, which enables the illumination intensity on the sample surface can be flexibly modulated by DMD pixel-level modulation corresponding to reflectivity distribution of the surface, and allows the camera pixels always to have reasonable exposure intensity for high precision measurement. More importantly, we put forward an adaptive light intensity control algorithm to improves the signal-to-noise ratio of acquired images without compromising modulation depth of pattern and measurement efficiency. Extensive comparative experiments were conducted and demonstrated that the proposed method can retrieve the surface morphology information of micro-scale complex reflectivity surfaces with high accuracy.

The Active Compensation Technique for Large Reflector Antennas Based on Quadratic Curve Fitting

Active reflectors are often used to compensate the surface distortion caused by environmental factors that degrade the electromagnetic performance of large high-frequency reflector antennas. This is crucial for maintaining high gain operation in antennas. A distortion compensation method for the active reflector of a large dual-reflector antenna is proposed. A relationship is established between the surface deformation and the optical path difference for the primary reflector by geometric optics. Subsequently, employing finite element analysis, a polynomial fitting approach is used to describe the impact of adjusting points on the reflector surface based on the coordinates of each node. By standardizing the positions of various panels on the reflector, the fitting ns can be applied to the reflector panels of similar shapes. Then, based on the distribution characteristics of the primary reflector panels, the adjustment equation for the actuators is derived by the influence matrix method. It can be used to determine the adjustment amount of actuators to reduce the rms of the optical path difference. And, the least squares method is employed to resolve the matrix equation. The example of a 110 m aperture dual-reflector antenna is carried out by finite element analysis and the proposed method. The results show that the optical path difference is reduced significantly at various elevation cases, which indicates that the proposed method is effective.

A dataset of trophic state index for nation-scale lakes in China from 40-year Landsat observations

Trophic state index (TSI) serves as a key indicator for quantifying and understanding the lake eutrophication, which has not been fully explored for long-term water quality monitoring, especially for small and medium inland waters. Landsat satellites offer an effective complement to facilitate the temporal and spatial monitoring of multi-scale lakes. Landsat surface reflectance products were utilized to retrieve the annual average TSI for 2693 lakes over 1 km2 in China from 1984 to 2023. Our method first distinguishes lake types by pixels with a decision tree and then derives relationships between trophic state and algal biomass index. Validation with public reports and existing datasets confirmed the good consistency and reliability. The dataset provides reliable annual TSI results and credible trends for lakes under different area scales, which can serve as a reference for further research and provide convenience for lake sustainable management.

Long-term analysis of Sentinel-6A orbit determination: Insights from three years of flight data

The Sentinel-6A mission extends the set of satellites dedicated to continuous ocean altimetry measurements, which started with TOPEX/Poseidon in 1992. To utilize these measurements, high-accuracy orbit solutions with radial position errors of less than 1.5cm (RMS) are required. For precise orbit determination (POD), a dedicated GPS/Galileo triple-frequency receiver (PODRIX) is available. Complementary to this, the TriG receiver provides GPS-only observations for POD and radio occultations. Previous research has shown that reduced-dynamic orbit solutions with PODRIX GPS/Galileo measurements meet the mission requirement for radial position accuracy of 1.5 cm (RMS). However, baseline estimation between the PODRIX and TriG antennas still reveals obvious inconsistencies in the along- and cross-track directions. In this study, we present a comprehensive reprocessing of orbit solutions using three years of Sentinel-6A flight data from both receivers covering January 2021 to December 2023. Cross-comparison between both receivers shows that inconsistencies can be removed by applying a yaw bias and a timing error correction. A comparative analysis of macro-models demonstrates strong correlation of cross-track empirical accelerations with the Sun elevation above the orbital plane when using nominal surface properties reported by the manufacturer. Adjusted macro-models improve performance at the expense of requiring increased surface areas or reflectivity coefficients. In addition to improved radiation pressure models, newly estimated antenna patterns and a time-varying gravity field were used in the analysis. The reprocessed data confirm good agreement of the results of both receivers except for a relative timing error of 1.3 μs, and the yaw bias correction of −0.43° removes previously-observed systematic differences in the estimated empirical accelerations. Satellite laser ranging results based on SLRF2020 station coordinates demonstrate a 5—6 mm (1D RMS) accuracy of the GNSS-based POD solutions across the IGb14/IGS20 reference frame transition in November 2022.

Panoramic Perfection: Unveiling Technical Insights from “The Henderson” in Hong Kong

The organic design and seamlessly reflective surface of “The Henderson” establish it as a landmark in Hong Kong. With its all-glass façade and a height of 210 m, the skyscraper designed by Zaha Hadid Architects offers spectacular panoramic views. Particularly noteworthy is the “Banquet Hall” on the top floor, distinguished by its fully glazed roof and engineered by Eckersley O’Callaghan. Large-format, coated and curved glass panes with the best possible technical specification in terms of thickness and minimal dimensional tolerances counterbalance architectural aesthetics and structural resilience. Engineered, manufactured and installed by seele, they serve as effective shields against solar radiation and glare, seamlessly complementing the organic architecture. Collaborative efforts focused on maximizing the transparency of the building envelope as interdisciplinary teams navigated challenges in structural engineering, design aesthetics and compliance with strict regulatory standards of the building authorities in Hong Kong. Thanks to targeted investigations, advancements in glass construction technology and engineering innovation, a procedure was developed that ensured optimum bearing of the panoramic glass panes. This project contributes to the safety and durability of high-rise glass structures to withstand extreme conditions and showcases the transformative potential of bold design concepts, rigorous testing, and international collaboration. The result is a visually stunning and structurally outstanding masterpiece.

Solar Tracking Control Algorithm Based on Artificial Intelligence Applied to Large-Scale Bifacial Photovoltaic Power Plants

The transition to a low-carbon economy is one of the main challenges of our time. In this context, solar energy, along with many other technologies, has been developed to optimize performance. For example, solar trackers follow the sun’s path to increase the generation capacity of photovoltaic plants. However, several factors need consideration to further optimize this process. Important variables include the distance between panels, surface reflectivity, bifacial panels, and climate variations throughout the day. Thus, this paper proposes an artificial intelligence-based algorithm for solar trackers that takes all these factors into account—mainly weather variations and the distance between solar panels. The methodology can be replicated anywhere in the world, and its effectiveness has been validated in a real solar plant with bifacial panels located in northeastern Brazil. The algorithm achieved gains of up to 7.83% on a cloudy day and obtained an average energy gain of approximately 1.2% when compared to a commercial solar tracker algorithm.

Modeling stochastic elastic wave diffraction by the tips of randomly rough defects

Elastic wave scattering from a randomly rough surface of a finite length includes surface reflections and diffractions from the tips. Previous research has focused upon reflection waves with applications in ultrasonic defect detection, seismic wave exploration and phonon boundary transport. However, waves diffracted from the tips/edges have been largely neglected so far for rough defects, despite their importance in engineering applications including ultrasonic defect sizing and imaging for assessment of structural integrity. Currently understanding the statistical nature of elastic wave tip diffraction and the role of roughness is limited due to the lack of theoretical studies. In this article, we develop a statistical geometrical tip diffraction (SGTD) theory to rapidly predict the stochastic properties of tip diffraction amplitude as a function of surface roughness and incident angle. By applying a small slope perturbation to the model, a simplified analytical solution of tip diffraction is obtained. It is found that for defects with small to medium roughness, the diffraction amplitude explicitly follows a Gamma distribution, and its mean and the standard deviation are both proportional to the square of the rms slope. High-fidelity Monte Carlo finite element simulations are then run to evaluate the accuracy of the theoretical model. The range of validity of the analytical solution with respect to the level of roughness and the incident angle is obtained. The SGTD method is accurate when the correlation length is approximately equivalent or larger than one wavelength, for a wide range of angles. It is also applicable for a correlation length as short as half wavelength, but only for small rms values and when the beam angle is larger than 45∘. In addition, at large angles, the tip diffraction is almost not affected by roughness, being very similar to that from a smooth crack. This is explained by the significant dependence on the beam angle factor explicitly shown in the theoretical solution.

High Spectral Resolution Lidar – generation 2 (HSRL-2) retrievals of ocean surface wind speed: methodology and evaluation

Abstract. Ocean surface wind speed (i.e., wind speed 10 m above sea level) is a critical parameter used by atmospheric models to estimate the state of the marine atmospheric boundary layer (MABL). Accurate surface wind speed measurements in diverse locations are required to improve characterization of MABL dynamics and assess how models simulate large-scale phenomena related to climate change and global weather patterns. To provide these measurements, this study introduces and evaluates a new surface wind speed data product from the NASA Langley Research Center nadir-viewing High Spectral Resolution Lidar – generation 2 (HSRL-2) using data collected as part of the NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) mission. The HSRL-2 can directly measure vertically resolved aerosol backscatter and extinction profiles without additional constraints or assumptions, enabling the instrument to accurately derive atmospheric attenuation and directly determine surface reflectance (i.e., surface backscatter). Also, the high horizontal spatial resolution of the HSRL-2 retrievals (0.5 s or ∼ 75 m along track) allows the instrument to probe the fine-scale spatial variability in surface wind speeds over time along the flight track and over breaks in broken cloud fields. A rigorous evaluation of these retrievals is performed by comparing coincident HSRL-2 and National Center for Atmospheric Research (NCAR) Airborne Vertical Atmosphere Profiling System (AVAPS) dropsonde data, owing to the joint deployment of these two instruments on the ACTIVATE King Air aircraft. These comparisons show correlations of 0.89, slopes of 1.04 and 1.17, and y intercepts of −0.13 and −1.05 m s−1 for linear and bisector regressions, respectively, and the overall accuracy is calculated to be 0.15 ± 1.80 m s−1. It is also shown that the dropsonde surface wind speed data most closely follow the HSRL-2 distribution of wave slope variance using the distribution proposed by Hu et al. (2008) rather than the ones proposed by Cox and Munk (1954) and Wu (1990) for surface wind speeds below 7 m s−1, with this category comprising most of the ACTIVATE data set. The retrievals are then evaluated separately for surface wind speeds below 7 m s−1 and between 7 and 13.3 m s−1 and show that the HSRL-2 retrieves surface wind speeds with a bias of ∼ 0.5 m s−1 and an error of ∼ 1.5 m s−1, a finding not apparent in the cumulative comparisons. Also, it is shown that the HSRL-2 retrievals are more accurate in the summer (−0.18 ± 1.52 m s−1) than in the winter (0.63 ± 2.07 m s−1), but the HSRL-2 is still able to make numerous (N=236) accurate retrievals in the winter. Overall, this study highlights the abilities and assesses the performance of the HSRL-2 surface wind speed retrievals, and it is hoped that further evaluation of these retrievals will be performed using other airborne and satellite data sets.

Retrieval of sea ice thickness using FY-3E/GNOS-II data

Sea ice, a significant component in polar regions, plays a crucial role in climate change through its varying conditions. In Global Navigation Satellite System-Reflectometry (GNSS-R) studies, the observed surface reflectivity Γ serves as a tool to examine the physical characteristics of sea ice covers. This facilitates the large-scale estimation of first-year ice thickness using a two-layer sea ice-seawater medium model. However, it is important to note that when Sea Ice Thickness (SIT) becomes thicker, the accuracy of SIT retrieval via this two-layer model begins to decline. In this paper, we present a novel application of a spaceborne GNSS-R technique to retrieve SIT based on a three-layer model using the data from Fengyun-3E (FY-3E). Soil Moisture Ocean Salinity (SMOS) data are treated as the reference. The performance of the proposed three-layer model is evaluated against a previously established two-layer model for SIT retrieval. The analysis used the sea ice data from 2022 and 2023 with SITs less than 1.1 m. By comparing the retrieved SITs against reference values, the three-layer model achieved a Root Mean Square Error (RMSE) of 0.149 m and Correlation Coefficient (r) of 0.830, while the two-layer model reported the RMSE of 0.162 m and r value of 0.789. A scheme incorporating both models yielded superior results than either individual model, with the RMSE of 0.137 m and r reaching up to 0.852. This study is the first application of FY-3E for GNSS-R SIT retrieval, combining the advantages of a two-layer model and a three-layer model and extending the precision of GNSS-R retrieval for SIT to within 1.1 m. This provides a good reference for the future studies on GNSS-R SIT retrieval.

Critical evaluation of the spatiotemporal behavior of UHI, through correlation analyses based on multi-city heterogeneous dataset

This study utilizes year-round temperature data observed in 15 cities around the United States (U.S.) to investigate the relationships between UHI and urban design attributes, and answer the following questions: (1) Whether and to what extent these relationships vary with the diurnal cycle and across seasons?, (2) What is the spatial extent within which UHI is affected by different urban variables?, and (3) Which climatic factors determine the correlations between UHI and urban variables? Our analysis revealed that while surface reflectance, vegetation and building height are more influential on winter UHI, the effect of anthropogenic heat and building density is independent of the season. Also, tree canopy cover, impervious area and built-up area were more dominant on nighttime UHI, and albedo, surface reflectance, vegetation and building height had stronger influence on daytime UHI. With regards to the spatial extent, while the effect of 3D urban variables and imperviousness was prominent in the immediate vicinity (250 m–1 km), the effect of vegetation, surface reflectance and anthropogenic factors extend to a larger surrounding area (4 km–8 km). Lastly, the relationships between UHI and urban variables were noted to be strongly driven by humidity in each location.

Research on Response Characteristics of GPR Method for Detecting Phreatic Lines in Embankments

The excessive elevation of the phreatic lines under continuous high-water levels is the cause of many dangerous situations in embankments. Therefore, accurately understanding the dynamic changes in the infiltration characteristics of embankments is of great significance for judging and evaluating the stability of engineering. This study conducted indoor model experiments and used ground penetrating radar to detect the phreatic lines of soil. By comparing the radar detection results with the measured position of the phreatic lines, it was determined that the phreatic lines appeared as a continuous strong reflection surface with similar shapes in the radargram, and the reflection below the reflection surface became weaker. Through time-domain analysis of the single waveform at different time points, it was found that the amplitude of the reflected wave at the saturation line was larger, and the energy attenuation below the saturation line was faster, resulting in a rapid decrease in amplitude; perform Fourier transform on a single channel signal to obtain a spectrogram, and perform frequency domain analysis on it. The main frequency is around 600MHz, and the second main frequency is around 900MHz. As the saturation line rises, the main frequency gradually shifts towards lower frequencies.

In Vitro Analysis of the Accuracy of the Use of Waste Zirconia Dust Compared With Optical Scanning Spray on Implant Abutment Models in Extraoral Scanning Protocol.

Introduction The evolution of computer-aided design/computer-aided manufacturing(CAD/CAM) systems has heightened the significance of digital models in dentistry, particularly for fabricating prostheses like inlays, crowns, and bridges. While digital dentistry offers enhanced speed and precision, the initial investment in intraoral scanners may pose a barrier for some clinicians. Extraoral or lab scanners, however, offer a viable alternative, reducing laboratory time and providing accurate prostheses fit, though challenges such as reflective surfaces and availability of scanning sprays persist, impacting scanning quality and operator technique. Optical scanning using laboratory scanners is a routine practice in today's age of digital dentistry. Often these require powder opacification to record fine details. There arenumbered studies on the accuracy of scanning sprays. Materials and methods Tencasts, poured with type 4 dental stone (Elite Rock, Zhermack, Italy) with single implants, were used for the purpose of this study. Each cast was scanned by two different operators, using both mediums. It was scanned using an extraoral scanner (E4, 3Shape, Copenhagen,Denmark). Operator A used easy scan (Alphadent, Korea), followed by zirconia dust (Upcera, Guangdong, China), whereas operator B used zirconia dust first. Digital models within each group were superimposed individually to measure precision. Results Easy scan operator 1 and zirconia dust operator 1 differ by 0.16000 (p = 0.0802). In scenario 2, easy scan operator 2 and zirconia dust operator 2 differ by 0.21900 (p = 0.0212) . Operator type significantly affects performance, emphasizing the need to account for operator variability in relevant contexts. The trueness values obtained for zirconia dust and easy scan among both operators were statistically insignificant. Conclusion Zirconia dust can be reliably used for extraoral scanning of abutments in place of optical scanning sprays.

Utilizing Deep Learning for Defect Inspection in Hand Tool Assembly.

The integrity of product assembly in the precision assembly industry significantly influences the quality of the final products. During the assembly process, products may acquire assembly defects due to personnel oversight. A severe assembly defect could impair the product's normal function and potentially cause loss of life or property for the user. For workpiece defect inspection, there is limited discussion on the simultaneous detection of the primary kinds of assembly anomaly (missing parts, misplaced parts, foreign objects, and extra parts). However, these assembly anomalies account for most customer complaints in the traditional hand tool industry. This is because no equipment can comprehensively inspect major assembly defects, and inspections rely solely on professionals using simple tools and their own experience. Thus, this study proposes an automated visual inspection system to achieve defect inspection in hand tool assembly. This study samples the work-in-process from three assembly stations in the ratchet wrench assembly process; an investigation of 28 common assembly defect types is presented, covering the 4 kinds of assembly anomaly in the assembly operation; also, this study captures sample images of various assembly defects for the experiments. First, the captured images are filtered to eliminate surface reflection noise from the workpiece; then, a circular mask is given at the assembly position to extract the ROI area; next, the filtered ROI images are used to create a defect-type label set using manual annotation; after this, the R-CNN series network models are applied to object feature extraction and classification; finally, they are compared with other object detection models to identify which inspection model has the better performance. The experimental results show that, if each station uses the best model for defect inspection, it can effectively detect and classify defects. The average defect detection rate (1-β) of each station is 92.64%, the average misjudgment rate (α) is 6.68%, and the average correct classification rate (CR) is 88.03%.

A DRL-based resource allocation for IRS-enhanced semantic spectrum sharing networks

Semantic communication and spectrum sharing are pivotal technologies in addressing the perennial challenge of scarce spectrum resources for the sixth-generation (6G) communication networks. Notably, scant attention has been devoted to investigating semantic resource allocation within spectrum sharing semantic communication networks, thereby constraining the full exploitation of spectrum efficiency. To mitigate interference issues between primary users and secondary users while augmenting legitimate signal strength, the introduction of Intelligent Reflective Surfaces (IRS) emerges as a salient solution. In this study, we delve into the intricacies of resource allocation for IRS-enhanced semantic spectrum sharing networks. Our focal point is the maximization of semantic spectral efficiency (S-SE) for the secondary semantic network while upholding the minimum quality of service standards for the primary semantic network. This entails the joint optimization of parameters such as semantic symbol allocation, subchannel allocation, reflective coefficients of IRS elements, and beamforming adjustment of secondary base station. Recognizing computational intricacies and interdependence of variables in the non-convex optimization problem formulated, we present a judicious approach: a hybrid intelligent resource allocation approach leveraging dueling double-deep Q networks coupled with the twin-delayed deep deterministic policy. Simulation results unequivocally affirm the efficacy of our proposed resource allocation approach, showcasing its superior performance relative to baseline schemes. Our approach markedly enhances the S-SE of the secondary network, thereby establishing its prowess in advancing the frontiers of semantic spectrum sharing (S-SE).

Low-loss vanadium dioxide-enabled mmWave tunable reflective electromagnetic surface with complementary unit cells for wave manipulation

This study presents a novel implementation of vanadium dioxide (VO2) phase change material in an electromagnetic (EM) surface with beam steering capabilities. For the first time, we present the design, fabrication, and measurement of a globally actuated, VO2-based beamforming reflective EM surface. We propose a design featuring complementary unit cells that enable beam steering with a single excitation, marking a pioneering use of low-loss VO2 in creating a complementary EM surface for the mmWave band. The unit cells incorporating VO2 exhibit low-loss characteristics, with −0.92 and −1.9 dB in the hot state and −0.49 and −0.25 dB in the cold state, respectively. We incorporate both positive and negative phase variants alongside two temperature-independent phase unit cells. The complementary design enables us to utilize two beam operating states, effectively exploiting the otherwise unused cold state. We experimentally demonstrated beamforming at ±5° and ±10° from the broadside. In the case of ±10°, the measured gains at 35 GHz in the cold and hot states were 19.4 and 20.3 dB, respectively, which aligned well with the simulated gains of 20.9 and 21.5 dB. Manipulation of the electromagnetic wave direction with a single excitation has the potential for imaging, sensing, and communication applications. The complementary unit cell design methodology can be further adapted for mmWave beamforming, absorbing, and cloaking reconfigurable EM surfaces. Furthermore, the use of VO2 can be extended up to sub-THz frequencies due to the wideband, low-loss characteristics compared with conventional reconfigurable devices, such as PIN diodes or MEMS switches.

Three-dimensional surface reconstruction from reflectance direction fields with orthogonal multicolor filters

A three-dimensional (3D) freeform surface reconstruction method is proposed, specifically designed to handle complex surfaces, even those with steep inclinations. This method utilizes a one-shot color mapping imaging system to obtain reflectance direction fields using a stripe multicolor filter positioned in two orthogonal orientations. This imaging system can capture reflectance directions that are identifiable by corresponding colors. The multicolor filter consists of multiple stripe regions, each with a different transmission spectrum. Theoretically, an equation that describes the relationship between reflectance direction fields and the reflective 3D surface can be derived based on geometrical optics. By solving this equation using a deep neural network (DNN) as a gradient descent method without any training data, the 3D surface can be accurately reconstructed, even for surfaces with steep inclinations. The effectiveness of this method is validated through numerical demonstrations on several 3D surfaces, including complex ones with concave and convex areas, as well as steep inclinations.

Experimental investigation of BIPV/T application in winter season under Şanlıurfa's meteorological conditions

AbstractConsidering that nearly 39% of the total CO2 emission released into the atmosphere today are thought to be due to the energy consumed by buildings, the importance of taking measures through buildings to combat global warming is evident. Therefore, the concept of nearly zero‐energy buildings (NZEB) is come to the forefront. Building integrated photovoltaic thermal (BIPV/T) systems are used to enable buildings to generate their own energy. However, buildings have limited facade and roof areas required for BIPV/T systems. Therefore, in this study, various configurations of bifacial (double‐sided) and monofacial (single‐sided) panels were compared to investigate ways to enhance the efficiency of BIPV/T systems. Different air flow velocities and varying air gap distances were tested for both panel types. By placing a reflective surface on the wall behind the bifacial panel, the electrical efficiency of the bifacial panel was increased and proven through PVsyst analysis. Both panels provided maximum heat efficiency at the shortest air gap distance under high air flow conditions. In addition, it was shown in both the experimental setup and Comsol CFD analysis that it provides significant benefit in the thermal energy load of the building when heating the interior environment in winter. In terms of electrical power production surplus, the bifacial panel outperformed the monofacial panel in all configurations, with a minimum advantage of 8.33% and a maximum of 12.73%. Additionally, the maximum electrical efficiency was obtained from the bifacial panel in configurations with the longest air gap distance. Using the bifacial panel in the BIPV/T system with the shortest air gap distance during the heating season and the longest air gap distance during other seasons can provide the highest efficiency for the building throughout the year.