Window Width Research Articles

Achieving Exceptional Cochlea Delineation in Radiotherapy Scans: The Impact of Optimal Window Width and Level Settings.

Introduction Radiation therapy (RT) aims to maximize the dose to the target volume while minimizing the dose to organs at risk (OAR), which is crucial for optimal treatment outcomes and minimal side effects. The complex anatomy of the head and neck regions, including the cochlea, presents challenges in radiotherapy. Accurate delineation of the cochlea is essential to prevent toxicities such as sensorineural hearing loss. Educational interventions, including seminars, atlases, and multidisciplinary discussions, can improve accuracy and interobserver agreement in contouring. This study seeks to provide radiation oncology practitioners with the necessary window width and window level settings in computed tomography (CT) scans to accurately and precisely delineate the cochlea, using a pre-and post-learning phase approach to assess the change in accuracy. Methods and materials The study used the ProKnow Contouring Accuracy Program (ProKnow, LLC,Florida, United States), which employs the StructSure method and the Dice coefficient to assess the precision of a user's contour compared to an expert contour. The StructSure method offers superior sensitivity and accuracy, while the Dice coefficient is a more rudimentary and less sensitive approach. Two datasets of CT scans, one for each left and right cochlea, were used. The author delineated the cochlea before and after applying the proposed technique for window width and window level, comparing the results with those of the expert and general population. The study included a step-by-step method for cochlea delineation using window width and window level settings. Data analysis was performed using IBMSPSSStatistics for Windows, Version 26.0 (Released 2019; IBM Corp., Armonk, New York, United States). Results The implementation of the proposed step-by-step method for adjusting window width and window level led to significant improvements in contouring accuracy and delineation quality in radiation therapy planning. Comparing pre- and post-intervention scenarios, the author exhibited increased StructSure scores (right cochlea: 88.81 to 99.15; left cochlea: 88.45 to 99.85) and Dice coefficient scores (right cochlea: 0.62 to 0.80; left cochlea: 0.73 to 0.86). The author consistently demonstrated higher contouring accuracy and greater similarity to expert contours compared to the group's mean scores both before and after the intervention. These results suggest that the proposed method enhances the precision of cochlea delineation in radiotherapy planning. Conclusion In conclusion, this study demonstrated that a step-by-step instructional approach for adjusting window width and window level significantly improved cochlea delineation accuracy in radiotherapy contouring. The findings hold potential clinical implications for reducing radiation-related side effects and improving patient outcomes. This study supports the integration of the instructional technique into radiation oncology training and encourages further exploration of advanced imaging processing and artificial intelligence applications in radiotherapy contouring.

Adaptive Time-Reassigned Synchrosqueezing Transform for Bearing Fault Diagnosis

In this paper, we propose an adaptive time-reassigned synchrosqueezing transform (ATSST) to characterize the signals with strongly time-varying feature. A time-varying window function is used to deduce the ATSST, which achieves a highly concentrated time-frequency representation (TFR) compared with the conventional time-reassigned synchrosqueezing transform (TSST). Meanwhile, the ATSST allows for mode reconstruction with the high accuracy. In this method, we make full use of the Rényi entropy and conduct a time-varying optimal window width selection scheme to evaluate the local window width by an iterative procedure for each time instant. By applying the optimal window width, the TFR can be greatly enhanced. Numerical results of two simulated signals demonstrate the effectiveness of the ATSST in improving the readability of TFR. Additionally, two sets of experimental datasets are employed to further evaluate the performance of the ATSST by comparing with some classical and advanced methods. Results indicate the superiority and robustness of the proposed ATSST in the analysis of strongly time-varying signals.

SOC estimation and fault diagnosis framework of battery based on multi-model fusion modeling

Accurate estimation of the battery state characteristics can ensure the safe driving of electric vehicles(EVs). This paper aims to propose a new method for state of charge (SOC) estimation and fault diagnosis based on multiple equivalent circuit models(ECMs) fusion approach. This paper improves the accuracy of SOC estimation and fault diagnosis from the following four aspects. Firstly, the Thevenin model and second-order ECM are selected to describe the dynamic characteristics of the battery and the least square method is then used to determine the model parameters. Besides, the unscented Kalman filter(UKF) is employed to estimate the SOC from the two models and the Bayesian theorem is employed to determine the optimal weights for synthesizing the SOCs estimated from the two models. Moreover, the voltage residual innovation sequence(RIS) is introduced to adaptively adjust the size of the window width in real-time, which can promote the iterative performance of traditional UKF and the prediction ability of the models. Finally, an adaptive fault diagnosis framework based on multiple ECMs fusion is constructed to determine the current battery operation status based on the probability weight of each model, and also to achieve accurate early warning of the current sensor fault. The experimental results show that the SOC estimation errors are controlled within 1 %, and the battery status and current sensor fault can also be accurately diagnosed.

Integrated optimization of order splitting and distribution routing for the front warehouse mode e-retailing

Along with the rapid growth of online purchasing, more and more e-retailers tend to adopt the front warehouse mode to improve the performance of customer service by locating multiple front warehouses with limited space and storage capacity closer to consumers. In this context, order splitting and distribution become increasingly crucial decisions that might impact the efficiency of order fulfillment. These two issues are investigated in the related works commonly as two independent problems, although they are inherently coupled with each other. This study established an integrated optimization model for order splitting and distribution routing for the front warehouse mode e-retailing. The model considers practical features, including order splitting constraints based on product type and quantity, finite inventory, heterogeneous vehicle routing constraints, and time windows. A branch-price-and-cut algorithm is proposed to solve the problem. Two logic-based Benders cuts are designed to deal with the infeasible distribution routes. The efficiency of the proposed algorithm is verified in an experimental study by considering CPLEX and two heuristic algorithms as benchmark methods. The dominance of our proposed algorithm is observed, especially for large-scale cases. The impacts of overlapping inventory levels, the combination of heterogeneous vehicles, and the width of time windows are also examined.

Pulse Lidar imaging algorithm based on adaptive triangle window-width centroid discrimination

The pulse light detecting and ranging (Lidar) can obtain rich environmental information of the target, and the centroid algorithm can obtain the distance and intensity information of the target from the echo pulse. However, there are problems of sensitivity to noise and fixed window width. Therefore, this paper proposes an adaptive triangle window-width centroid algorithm (ATWC) to improve the ranging accuracy and robustness of Lidar. This algorithm combines the characteristics of the steep front and slow back of the pulse echo waveform. The centroid calculation point is selected by an isosceles triangle envelope in the time domain and a non-isosceles triangle envelope in the intensity domain with a longer front and a shorter back. Further combined with intensity weighting, the distance and intensity values of ATWC are obtained. On the one hand, the simulation verifies the influence of window width selection on the accuracy of the centroid algorithm. On the other hand, real environment comparison experiments are conducted with traditional waveform centroid (TWC), peak ranging (PR), and adaptive threshold methods (ATM) under a pulse Lidar system constructed by our method, and our method achieves significant improvements. At different distances, when the peak signal-to-noise ratio (PSNR) is above 20 dB, the ranging error of ATWC is below 0.3 ns, which is much better than the compared algorithms. When the target is at a distance of 25 m, which is a weak echo signal environment with a PSNR of 15.6 dB, our algorithm can still achieve a ranging error of 0.56 ns, and the detection success rate can still reach 88.8%. In addition, our method can obtain a clearer intensity image, which further demonstrates the research potential and practical utility of the proposed method.

Engineering optomechanically induced transparency by coupling a qubit to a spinning resonator

We theoretically study the spectral properties of a pump–probe driven hybrid spinning optomechanical ring resonator optically coupled with a two-level quantum emitter (QE or qubit). Recently, we have shown [Opt. Express 27, 25515 (2019)OPEXFF1094-408710.1364/OE.27.025515] that in the absence of the emitter, the coupled cavity version of this setup is not only capable of non-reciprocal light propagation but can also exhibit slow and fast light propagation. In this work, we investigate in what ways the presence of a single QE coupled with the optical whispering gallery modes of a spinning optomechanical resonator can alter the probe light non-reciprocity. Under the weak-excitation assumption and mean-field approximation, we find that the interplay between the rotational/spinning Sagnac effect and qubit coupling can lead to enhancement of both the optomechanically induced transparency peak value and the width of the transparency window due to the opening of a qubit-assisted backreflection channel. However, compared to the no-qubit case, we notice that such enhancement comes at the cost of degrading the group delay in probe light transmission by a factor of 1/2 for clockwise rotary directions. The target applications of these results can be in the areas of quantum circuitry and in non-reciprocal quantum communication protocols where QEs are a key component.

Advanced Online Broadband Impedance Spectrum Acquisition of Fuel Cells by S-Transform

Electrochemical impedance spectrum (EIS) applied in fuel cell characterization and diagnosis facilitates its system management in the vehicular application, but the first consideration of impedance-based management is how to obtain impedance online. The traditional laboratory method based on sine sweep is unsuitable for vehicular EIS measurement as limited by measured time and equipment price. In this article, we design an excitation device that can generate the square wave signal containing many harmonics as the excitation current. Besides, introduce S-transform (ST) for online broadband fuel cell impedance spectrum fast calculation, whose window width can be adaptively changed with frequency, and meanwhile, preserving high computational efficiency by fast Fourier transform operation. Based on this, the performance of ST and the previous method based on Morlet wavelet transform (MWT) is compared under different operating conditions. Extensive experimental results show that the ST can calculate impedance with the mean relative error of less than 3% based on appropriate excitation, while the computed time can be saved by nearly 95% as compared to MWT. Furthermore, the effectiveness and robustness of ST against different current densities, cell temperatures, fault scenarios with various fault degrees, and stable time are also verified through experimentation.

Event-by-event multiplicity fluctuations and correlations in ring-like and jet-like events in 197Au–AgBr collisions at 11.6 A GeV/c

Event-by-event (ebe) multiplicity fluctuations and correlations amongst the charged particles emitted in the forward–backward symmetric pseudorapidity ([Formula: see text]) windows of varying widths and positions are investigated by analyzing the experimental data on [Formula: see text]Au–AgBr collisions at 11.6[Formula: see text]A[Formula: see text]GeV/[Formula: see text]. The findings are compared with the predictions of relativistic transport model, urqmd and independent particle emission (or mixed event) model. It is observed that the fluctuations in ebe mean pseudorapidity values and those reflected from the fluctuations strength measure, [Formula: see text] are relatively higher as compared to those expected from the statistically independent particle emission model. The study of the variance, [Formula: see text] of a suitably defined forward–backward asymmetry variable [Formula: see text] as a function of [Formula: see text] window width and position indicates the presence of strong short-range correlations, which might arise due to isotropic decay of cluster-like objects either in forward or backward [Formula: see text] region. Furthermore, analyses of events having ring-like and jet-like substructures, carried out separately, suggest that the major contribution to the observed fluctuations in the data sample are due to ring-like events, while the contributions from the jet-like events appear to be rather small. The observed difference in the behavior of correlation strengths from the two types of events might be due to the enhanced emission of Cherenkov gluons, giving rise to the ring-like substructure. The mixed event analysis further confirms that the observed fluctuations are the distinct feature of the data, which disappear after event mixing.

Simulation Study of Improved DDSRF-PLL under Distorted Grid Voltage

When the grid voltage is distorted and harmonic and DC components are mixed, the phase locking accuracy of decoupled double synchronous reference frame for phase-locked loop (DDSRF-PLL) will be greatly reduced. This paper proposes an improved DDSRF-PLL(IDDSRF-PLL) structure based on Frequency Adaptive Sliding Discrete Fourier Transform (FASDFT) filtering. A cascade SDFT structure is adopted for FASDFT filtering. The SDFT with fixed sliding window width at the front stage extracts the fundamental wave signal of power grid voltage to eliminate the influence of harmonics and DC components. The latter SDFT detects the sliding window width of power grid frequency update in real time through a nonlinear tracking differentiator (TD) to suppress spectrum leakage. Then DDSRFT-PLL is used to separate the positive and negative sequence of the fundamental signal and lock the phase. Finally, the simulation results in Matlab/Simulink verify the correctness and effectiveness of the proposed method.

Creation of a Walloon Pasture Monitoring Platform Based on Machine Learning Models and Remote Sensing

The use of remote sensing data and the implementation of machine learning (ML) algorithms is growing in pasture management. In this study, ML models predicting the available compressed sward height (CSH) in Walloon pastures based on Sentinel-1, Sentinel-2, and meteorological data were developed to be integrated into a decision support system (DSS). Given the area covered (>4000 km2 of pastures of 100 m2 pixels), the consequent challenge of computation time and power requirements was overcome by the development of a platform predicting CSH throughout Wallonia. Four grazing seasons were covered in the current study (between April and October from 2018 to 2021, the mean predicted CSH per parcel per date ranged from 48.6 to 67.2 mm, and the coefficient of variation from 0 to 312%, suggesting a strong heterogeneity of variability of CSH between parcels. Further exploration included the number of predictions expected per grazing season and the search for temporal and spatial patterns and consistency. The second challenge tackled is the poor data availability for concurrent acquisition, which was overcome through the inclusion of up to 4-day-old data to fill data gaps up to the present time point. For this gap filling methodology, relevancy decreased as the time window width increased, although data with 4-day time lag values represented less than 4% of the total data. Overall, two models stood out, and further studies should either be based on the random forest model if they need prediction quality or on the cubist model if they need continuity. Further studies should focus on developing the DSS and on the conversion of CSH to actual forage allowance.

Kolokteral karsinomda histopatolojik düşük ve yüksek dereceli tümörlerin ayrımı için bilgisayarlı tomografi histogram analizinin tanısal etkinliği

Aim: Colorectal adenocarcinoma (CA) is the most common type of cancer worldwide and the third leading cause of cancer-related deaths. Primary pathological grade bears importance in the course of the disease. The possibility of non-invasive grading through radiology modalities is still an important issue. The present study aims to reveal whether a non-invasive grading similar to pathological grading can be performed using histogram analysis on computed tomography (CT) scan images.
 Material and Method: 58 patients operated and diagnosed with CA pathologically were included in the present study. As for medical protocol, abdominal intravenous contrast CT scan images obtained from TOSHIBA Alexion and TOSHIBA Aquilion ONE (Toshiba Medical Systems, Nasu, Japan) devices with 120 kVp tube voltage were set to a window width of 400 and a window level of 40. Patient images from retrospective scanning were evaluated on a workstation. For the evalution of mass, intraluminal air, necrotic areas, pericolonic fat tissue or intra-mass large feeding vessels were not included in the measurement range. Mass size was measured on the largest axis according to the longest axis. For histogram analysis, regions of interest were positioned. Parameters included in the histogram analysis were pixels, mean, standard deviation, minimum, maximum, median, variance, entropy, size L%, size U%, size M%, kurtosis, skewness, uniformity, percent01, percent03, percent05, percent10, percent25, percent75, percent90, percent95, percent97 and percentile 99.
 Results: Histogram analysis results obtained from three different measurements for each of 58 patients were not found to be statistically significant in the differentation of pathologically defined histological grading system. 
 Conclusion: Although the use of a non-invasive method instead of an invasive one may offer an advantage, was not statistically significant in the prediction of histological grade.

An integrated adaptive Kalman filter for improving the reliability of navigation systems

Abstract Integrated GPS/INS using Kalman filter is the best technique for improving navigation accuracy. Assuming that the covariance matrices are known and constant, a conventional Kalman filter (CKF) is usually used, however, when they are unknown and time-varying, several adaptive estimation approaches have to be developed to estimate the statistical information of the measurement (R), process (Q), and state (P) covariance matrices. In many situations, blunders/faults in the measurement model and/or sudden changes in the dynamic model may occur during the navigation period. Therefore, the CKF, as well as the adaptive Kalman filter (AKF) will exhibit abnormal behavior and may lead the filter to be suboptimal or even diverge. In this study, the Sage-Husa adaptive Kalman filter (SHAKF) and innovation-based adaptive Kalman filter (IAKF) approaches are employed for adapting the measurement covariance matrix(R). In the case of abrupt changes in the dynamic model, the state covariance matrix (P) is adapted using the strong tracking filter (STF). The performance of these adaptive approaches is evaluated before and after simulating a fault of different sizes in the measurement and dynamic models. The results show that with a large window width, the SHAKF outperforms the CKF and IAKF. However, when the system encounters any fault either in the measurement or dynamic model, the SHAKF loses its optimality and diverges. The sensitivity of the SHAKF to the fault is because the R matrix accumulates with the propagation of the recursive noise estimator. On the other hand, the IAKF and STF provide better performance than both the CKF and SHAKF because the gain matrix is adaptively adjusted to mitigate the influence of the fault, and therefore, they behave normally when a fault of any size occurs in the measurement and/or dynamic model.

Effects of stochastic forces on the nonlinear behaviour of a silicon nitride membrane nanoelectromechanical resonator

In this work, we present the effects of stochastic force generated by white noise on the nonlinear dynamics of a circular silicon nitride membrane. By tuning the membrane to the Duffing nonlinear region, detected signals switching between low- and high-amplitudes have been observed. They are generated by noise-assisted random jumps between bistable states at room temperature and exhibit high sensitivity to the driving frequency. Through artificially heating different mechanical vibration modes by external input of white noise, the switching rate exhibits exponential dependence on the effective temperature and follows with Kramer‘s law. Furthermore, both the measured switching rate and activation energy exhibit sensitivity to the width of the hysteresis window in nonlinear response and the driving force, which is in qualitative agreement with the theoretical descriptions. Besides, white noise-induced hysteresis window squeezing and bifurcation point shifting have also been observed, which are attributed to the stochastic force modulation of the spring constant of the membrane. These studies are carried out in an all-electric operating scheme at room temperature, paving the way for the exploration of probability distribution-based functional elements that can be massively integrated on-chip.

Seismometer Orientation Correction via Teleseismic Receiver Function Measurements in West Africa and Adjacent Islands

AbstractTo establish a robust method of determining and correcting the misorientation of seismometers with radial and tangential components of the teleseismic receiver function (RF), we assess the measurement of the amplitude of P-wave phase arrivals at zero seconds (PRFamp method) and the energy of the width of the time window around the P-wave phase arrival (PRFenergy method) using varying Gaussian factors, ranging from 0.5 to 5.0 with equivalent cutoff frequencies. To understand the efficacy and discrepancies in these methods, and their results across different geological terrains, we conduct an assessment of their performance on 26 permanent seismic stations located in West Africa and adjacent islands. We conduct several tests to examine the effect of varying Gaussian factors on the estimates of misorientation. These effects are more noticeable in results from stations for which RFs are indicative of 3D or complex structures and islandic stations. Statistical analyses reveal good correlation between the results obtained from both the methods, although results from PRFamp method proves to be more stable due to their proximity to the statistical mean and standard deviation results. In comparison with the PRFenergy results, there is a smaller error difference and uncertainty, a higher correlation coefficient, a relatively lower standard deviation, and better convergence around the mean misorientation obtained using PRFamp. From both the methods, estimates from continental stations reveal similar trends, results from coastal stations tend to be consistent, whereas some island stations show a reverse trend in sensor misorientation classification. We propose that the PRFamp yields more consistent results and is less sensitive to subsurface heterogeneities. Gaussian filtering with an alpha value (α) of 1.5 is recommended as a trade-off between oversimplification and complications due to subsurface structures. However, we suggest that multiple approaches be adopted to provide robust bases for the estimation and comparison of sensor orientation correction calculations.

Assessment of the distribution and volume of air chambers around the inner auditory canal on high-resolution computed tomography scans of the temporal bone.

Assessment of the distribution and volume of air chambers around the inner auditory canal on high-resolution computed tomography scans of the temporal bone.

Reproducibility and stability of spirometer-guided deep inspiration breath-hold in left-breast treatments using an optical surface monitoring system.

The aim of this study was to evaluate the reproducibility and stability of left breast positioning during spirometer-guided deep-inspiration breath-hold (DIBH) radiotherapy using an optical surface imaging system (AlignRT). The AlignRT optical tracking system was used to monitor five left-sided breast cancer patients treated using the Active Breathing Coordinator spirometer with DIBH technique. Treatment plans were created using an automated hybrid-VMAT technique on DIBH CTs. A prescribed dose of 60Gy to the tumor bed and 50Gy to the breast in 25 fractions was planned. During each treatment session, the antero-posterior (VRT), superior-inferior (LNG), and lateral (LAT) motion of patients was continuously recorded by AlignRT. The intra-breath-hold stability and the intra- and inter-fraction reproducibility were analyzed for all breath-holds and treatment fractions. The dosimetric impact of the residual motion during DIBH was evaluated from the isocenter shifts amplitudes obtained from the 50%, 90%, and 100% cumulative distribution functions of intra-fractional reproducibility. The positional variations of 590 breath-holds as measured by AlignRT were evaluated. The mean intra-breath-hold stability during DIBH was 1.0±0.4mm, 2.1±1.9mm, and 0.7±0.5mm in the VRT, LNG, and LAT directions, with a maximal value of 8.8mm in LNG direction. Similarly, the mean intra-breath-hold reproducibility was 1.4±0.8mm, 1.7±1.0mm, and 0.8±0.5mm in the VRT, LNG, and LAT directions, with a maximal value of 4.1mm in LNG direction. Inter-fractional reproducibility showed better reliability, with difference in breathing levels in all fractions of 0.3mm on average. Based on tolerance limits corresponding to the 90% cumulative distribution level, gating window widths of 1mm, 2mm, and 5mm in the LAT, VRT, and LNG directions were considered an appropriate choice. In conclusion, despite the use of a dedicated spirometer at constant tidal volume, a non-negligible variability of the breast surface position has been reported during breath-holds. The real-time monitoring of breast surface using surface-guided optical technology is strongly recommended.

Effect of Interior Space and Window Geometry on Daylighting Performance for Terrace Classrooms of Universities in Severe Cold Regions: A Case Study of Shenyang, China

Good daylighting performance positively affects students’ physical and mental health, learning efficiency, and the building’s energy-saving capability. Due to the terrace classroom having ample space, large capacity, the ability to avoid obstructing sight, and the ability to meet various use needs, it is the most important place in university buildings. However, research on the daylighting performance of university terrace classrooms is limited, leading to a lack of quantitative guidance in early design stages. This study aims to explore the effects of interior space and window geometry of terrace classrooms in universities in severe cold regions on daylighting performance. This research took Shenyang as an example; spatial daylight autonomy (sDA300,50%) and useful daylight illuminance (UDI100–2000) were selected as daylighting performance evaluation indices. Based on the Grasshopper parametric platform, the simulation was carried out using Ladybug and Honeybee plugins. Correlation and regression analyses revealed the relationship between interior space and window geometry parameters and the evaluation indices. The results showed the following: window-to-floor ratio (WFR), classroom height (Htc), window height (Hw), window-to-wall ratio (WWR), classroom width (Wtc), and window width (Ww) have positive effects on improving the daylight sufficiency of the terrace classrooms facing each orientation, and the degree of the effect decreases in order. To ensure the overall daylighting performance, the Wtc can be maximized. The width of walls between windows for south-facing and west-facing classrooms should be 0.9 m. The WWR and WFR for south-facing classrooms should be 0.3–0.5 and 0.11–0.14, respectively. The WWR and WFR for north-facing classrooms should be 0.6–0.7 and 0.14–0.20, respectively. Prediction models are established for the sDA300,50% and UDI100–2000 of the terrace classrooms facing each orientation.

Micro-Sized Pinhole Inspection with Segmented Time Reversal and High-Order Modes Cluster Lamb Waves Based on EMATs

Pinhole corrosion is difficult to discover through conventional ultrasonic guided waves inspection, particularly for micro-sized pinholes less than 1 mm in diameter. This study proposes a new micro-sized pinhole inspection method based on segmented time reversal (STR) and high-order modes cluster (HOMC) Lamb waves. First, the principle of defect echo enhancement using STR is introduced. Conventional and STR inspection experiments were conducted on aluminum plates with a thickness of 3 mm and defects with different diameters and depths. The parameters of the segment window are discussed in detail. The results indicate that the proposed method had an amplitude four times larger than of conventional ultrasonic guided waves inspection method for pinhole defect detection and could detect micro-sized pinhole defects as small as 0.5 mm in diameter and 0.5 mm in depth. Moreover, the segment window location and width (5−10 times width of the conventional excitation signal) did not affect the detection sensitivity. The combination of low-power and STR is more conducive to detection in different environments, indicating the robustness of the proposed method. Compared with conventional ultrasonic guided wave inspection methods, the proposed method can detect much smaller defect echoes usually obscured by noise that are difficult to detect with a lower excitation power and thus this study would be a good reference for pinhole defect detection.

Study on Optimization of Copper to Aluminum for Locomotive Finned Tube Radiator

The influence of the improvement of the finned tube radiator unit structure on the fluid flow and heat transfer effect of the locomotive was studied. A saw-toothed fin structure with aluminum instead of copper was proposed to keep the position and size of the flat copper hot water pipe unchanged. CFD simulation analysis was carried out by ICEPAK17.0, under the conditions of an ambient temperature of 24.6 °C, atmospheric pressure of 85,040 Pa and air density ρ = 0.94 kg/m3, to compare the changes of velocity field, temperature field, turbulence field and field synergy angle. The sawtooth structure of the new heat sink increases the turbulence effect of the fluid, reduces the thickness of the outer boundary layer of the water pipe, and strengthens the heat transfer effect of the radiator. Finally, the baffle height, wing window width and sawtooth angle of the sawtooth structure were selected, and the heat transfer coefficient and pressure under three conditions of low, medium and high were used as indexes to analyze the influence of each parameter on the performance of the radiator. The results show that the heat dissipation effect of the serrated aluminum sheet is higher than that of the copper sheet, the heat transfer coefficient is increased by about 1.3%, the average pressure is reduced, the turbulence performance is improved, the synergy angle is reduced by about 2.3°, and the new radiator has better performance. The fin factor has the greatest influence on the heat transfer coefficient and the least influence on the pressure. When the baffle is about 0.15 mm high, the heat transfer coefficient is the largest, and the height change has the highest effect on the pressure. The included Angle factor has the least influence on the heat transfer effect, and the influence on the pressure is higher. By changing the fin window structure, the thermal performance of the finned tube radiator can be improved.

Patio Design Optimization for Huizhou Traditional Dwellings Aimed at Daylighting Performance Improvements

Hui-style architecture is a mature architectural school in the late period of ancient Chinese society with distinct regional cultural characteristics. Especially as the most direct carrier of Huizhou people’s living culture, Hui-style architecture is the witness of ancient Huizhou society, history, and culture. However, with the continuous development of society, residents gradually put forward higher requirements for the living environment. In this paper, the indoor light environment of Huizhou dwellings is measured and found to have problems such as poor indoor light environment and low light quality. In order to improve the indoor lighting quality, this study extracts the key design parameters (window edge height, window width, patio length, and patio width) that affect the indoor lighting quality through field research and literature analysis, and then uses Honeybee to carry out multi-factor orthogonal experiments and single factor quantitative comparative analyses on the key design parameters to determine the degree of influence. The results show that reducing the window edge height can improve the lighting effect near the window, and increasing the window width and patio width can improve the overall lighting quality of the room, thus providing a reference for optimizing the lighting effect of Huizhou traditional dwellings.