Hybrid device for acoustic noise reduction and energy harvesting based on a silicon micro-perforated panel structure

A kind of hybrid device for acoustic noise reduction and vibration energy harvesting based on the silicon micro- perforated panel （MPP） resonant structure is investigated in the article. The critical parts of the device include MPP and energy harvesting membranes. They are all fabricated by means of silicon micro-electro-mechanical systems （MEMS） tech- nology. The silicon MPP has dense and accurate micro-holes. This noise reduction structure has the advantages of wide band and higher absorption coefficients. The vibration energy harvesting part is formed by square piezoelectric membranes arranged in rows. ZnO material is used as it has a good compatibility with the fabrication process. The MPP, piezo- electric membranes, and metal bracket are assembled into a hybrid device with multifunctions. The device exhibits good performances of acoustic noise absorption and acoustic-electric conversion. Its maximum open circuit voltage achieves 69.41 mV.

Acoustic Properties of Micro-Perforated Panels Made from Oil Palm Empty Fruit Bunch Fiber Reinforced Polylactic Acid

This paper presents the development and performance of micro-perforated panels(MPP)from natural fiber reinforced composites.The MPP is made of Polylactic Acid(PLA)reinforced with Oil Palm Empty Fruit Bunch Fiber(OPEFBF).The investigation was made by varying the fiber density,air gap,and perforation ratio to observe the effect on the Sound Absorption Coefficient(SAC)through the experiment in an impedance tube.It is found that the peak level of SAC is not affected,but the peak frequency shifts to lower frequency when the fiber density is increased.This phenomenon might be due to the presence of porosity in the inner wall of the holes.Increasing or decreasing the air gap and perforation ratio shifts the peaks of acoustic absorption either way.

Enhancing Sound Absorption in Micro-Perforated Panel and Porous Material Composite in Low Frequencies:A Numerical Study Using FEM

Mitigating low-frequency noise poses a significant challenge for acoustic engineers,due to their long wavelength,with conventional porous sound absorbers showing limitations in attenuating such noise.An effective strategy involves combining porous materials with micro-perforated plates(MPP)to address this issue.Given the significant impact of structural variables like panel thickness,hole diameter,and air gap on the acoustic characteristics of MPP,achieving the optimal condition demands numerous sample iterations.The impedance tube’s considerable expense for sound absorption measurement and the substantial cost involved in fabricating each sample using a 3D printer underscore the advantage of utilizing simulation methods to attain the optimal state.This study focuses on optimizing low-frequency enhancement by investigating key parameters.Using the Finite Element Numerical Method(FEM)in COMSOL software,a composite panel was constructed comprising date palm fiber layers,an intervening air layer,and MPP.The study explored the arrangement of these layers and the impact of parameters like hole diameter,plate thickness,and perforation ratio on acoustic behavior.The selected optimal parameter at each stage was consistently maintained for subsequent steps.Results revealed that layer arrangement significantly influenced acoustic characteristics.Placing the MPP layer before the porous material yielded superior low-frequency performance.Optimizing low-frequency behavior involved reducing hole diameter and perforation ratio while increasing plate thickness.Elevating the porous material’s thickness relative to the air layer behind the MPP enhanced absorption peak and resonance frequency.In conclusion,halving the porous layer’s thickness while incorporating an air layer and single MPP proved more effective than using a thick porous material.This approach not only reduces costs and space requirements but also enhances low-frequency performance.The study highlights the precision of numerical methods like FEM,reducing the need for resource-intensive direct methods and associated laboratory expenses.

Estimation of geometric parameters for micro-perforated panels and their effects on sound absorption performance

The geometric parameters of micro-perforated panels with irregular holes cannot be directly known,making it difficult to calculate the sound absorption performance.Therefore,we propose a method of estimating the geometric parameters of micro-perforated panels.The irregular holes are treated as equivalent circular ones,and the model of estimating the geometric parameters is established by using Maa's theory about the panel with circular holes.The result of the parameter estimation of a type of micro-perforated panel is used to predict the absorption performance,resulting in good agreement with experiments.According to the influences of the geometric parameters of the panel on the high absorption region,we discuss the relationship between the application limit of Maa's theory and the geometric parameters,and investigate the evolution law of the sound absorption performance when the panel is polluted by dust.If the parameters of the panel are designed near the center of the high absorption region,large value of the application limit of Maa's theory can be obtained;and if the parameters are located in the upper right part of the high absorption region,a certain degree of dust pollution of the panel does not decrease the sound absorption performance.

Theoretical analysis of the sound absorption characteristics of periodically stiffened micro-perforated plates

The vibro-acoustic responses and sound absorption characteristics of two kinds of periodically stiffened micro-perforated plates are analyzed theoretically. The connected periodical structures of the stiffened plates can be ribs or block-like structures. Based on fundamental acoustic formulas of the micro-perforated plate of Maa and Takahashi, semi-analytical models of the vibrating stiffened plates are developed in this paper. Approaches like the space harmonic method, Fourier transforms and finite element method （FEM） are adopted to investigate both kinds of the stiffened plates. In the present work, the vibro-acoustic responses of micro-perforated stiffened plates in the wavenumber space are expressed as functions of plate displacement amplitudes. After approximate numerical solutions of the amplitudes, the vibration equations and sound absorption coefficients of the two kinds of stiffened plates in the physical space are then derived by employing the Fourier inverse transform. In numerical examples, the effects of some physical parameters, such as the perforation ratio, incident angles and periodical distances etc., on the sound absorption performance are examined. The proposed approaches are also validated by comparing the present results with solutions of Takahashi and previous studies of stiffened plates. Numerical results indicate that the flexural vibration of the plate has a signif- icant effect on the sound absorption coefficient in the water but has little influence in the air.

基因panel在新生儿疑似遗传代谢疾病中的应用

目的探讨基因panel在患有疑似遗传代谢疾病新生儿中的应用。方法对华中科技大学同济医学院附属同济医院2023年1月—2024年3月收治的有遗传代谢高危临床表型的新生儿,采用基因panel检测,同时搜集其临床资料并进行随访观察,分析致病基因的检出情况、患儿基因型与表型的一致性等。结果该研究共纳入53例有遗传代谢高危征象的新生儿,其中致病基因阳性的总体检出率为17.0%(9/53),常见检出的致病基因有氯离子通道基因(CLCN1)、双氧化酶2基因(DUOX2)、间隙连接蛋白β2基因(GJB2)、酪氨酸蛋白磷酸酶非受体11型基因(PTPN11)、钠通道α亚基基因(SCN1A)、痉挛截瘫基因11(SPG11)等,其中DUOX2和GJB2检出比例最高,分别为33.3%(3/9)和22.2%(2/9)。将致病基因阳性组患儿与阴性组患儿进行对比分析,阳性组患儿临床表型个数可能更多,预后相较于基因阴性组也更严重。在致病基因阳性组患儿中,除了病例1和病例9因相关疾病发病较晚导致临床表型与致病基因暂时不相符,其余病例致病基因与临床表型均符合。结论基因panel具有耗时短、检测成本及技术难度低等特点,适用于发展中国家及经济水平相对落后地区疑似遗传代谢疾病患儿的早期筛查。

Health diagnosis of ultrahigh arch dam performance using heterogeneous spatial panel vector model

Currently,more than ten ultrahigh arch dams have been constructed or are being constructed in China.Safety control is essential to long-term operation of these dams.This study employed the flexibility coefficient and plastic complementary energy norm to assess the structural safety of arch dams.A comprehensive analysis was conducted,focusing on differences among conventional methods in characterizing the structural behavior of the Xiaowan arch dam in China.Subsequently,the spatiotemporal characteristics of the measured performance of the Xiaowan dam were explored,including periodicity,convergence,and time-effect characteristics.These findings revealed the governing mechanism of main factors.Furthermore,a heterogeneous spatial panel vector model was developed,considering both common factors and specific factors affecting the safety and performance of arch dams.This model aims to comprehensively illustrate spatial heterogeneity between the entire structure and local regions,introducing a specific effect quantity to characterize local deformation differences.Ultimately,the proposed model was applied to the Xiaowan arch dam,accurately quantifying the spatiotemporal heterogeneity of dam performance.Additionally,the spatiotemporal distri-bution characteristics of environmental load effects on different parts of the dam were reasonably interpreted.Validation of the model prediction enhances its credibility,leading to the formulation of health diagnosis criteria for future long-term operation of the Xiaowan dam.The findings not only enhance the predictive ability and timely control of ultrahigh arch dams'performance but also provide a crucial basis for assessing the effectiveness of engineering treatment measures.

Energy dissipation mechanism and ballistic characteristic optimization in foam sandwich panels against spherical projectile impact

This study systematically examines the energy dissipation mechanisms and ballistic characteristics of foam sandwich panels(FSP)under high-velocity impact using the explicit non-linear finite element method.Based on the geometric topology of the FSP system,three FSP configurations with the same areal density are derived,namely multi-layer,gradient core and asymmetric face sheet,and three key structural parameters are identified:core thickness(t_(c)),face sheet thickness(t_(f))and overlap face/core number(n_(o)).The ballistic performance of the FSP system is comprehensively evaluated in terms of the ballistic limit velocity(BLV),deformation modes,energy dissipation mechanism,and specific penetration energy(SPE).The results show that the FSP system exhibits a significant configuration dependence,whose ballistic performance ranking is:asymmetric face sheet>gradient core>multi-layer.The mass distribution of the top and bottom face sheets plays a critical role in the ballistic resistance of the FSP system.Both BLV and SPE increase with tf,while the raising tcor noleads to an increase in BLV but a decrease in SPE.Further,a face-core synchronous enhancement mechanism is discovered by the energy dissipation analysis,based on which the ballistic optimization procedure is also conducted and a design chart is established.This study shed light on the anti-penetration mechanism of the FSP system and might provide a theoretical basis for its engineering application.

Mechanical Behavior of Panels Reinforced with Orthogonal Plant Fabrics: Experimental and Numerical Assessment

The construction sector is one of the main sources of pollution,due to high energy consumption and the toxic substances generated during the processing and use of traditional materials.The production of cement,steel,and other conventional materials impacts both ecosystems and human health,increasing the demand for ecological and biodegradable alternatives.In this paper,we analyze the properties of panels made from a combination of plant fibers and castor oil resin,analyzing the viability of their use as construction material.For the research,orthogonal fabrics made with waste plant fibers supplied by a company that deals with the manufacture of furniture and craft products were used.These fabrics were made with strips of plant fibers of the Calamus rotang,Bambusa vulgaris,Heteropsis flexuosa,and Salix viminalis species.To improve their compatibility with the castor oil resin,a cold argon plasma treatment was applied.The effect of the treatment on the properties of the fibers and the panels was analyzed.The density,water absorption capacity,and swelling percentage were evaluated.Tensile,compression,static bending,and linear buckling tests were carried out.The study found that panels made with treated fiber fabrics exhibited a reduction of approximately 10%in absorption capacity and up to 35%in swelling percentage values.Panels made with Bambusa vulgaris fabrics exhibited the highest strength and stiffness values.Numerical models were constructed using commercial finite element software.When comparing the numerical results with the experimental ones,differences of less than 15%were seen,demonstrating that the models allow adequately predicting the analyzed properties.On comparing the values obtained with the characteristic values of oriented strand board,the results suggest that panels made with unconventional materials could replace commercial panels traditionally made with wood-based fibers and particles and other composite materials in several applications in the construction industry.

Impact of Different Rooftop Coverings on Photovoltaic Panel Temperature

Photovoltaic(PV)panels are essential to the global transition towards sustainable energy,offering a clean,renewable source that reduces reliance on fossil fuels and mitigates climate change.High temperatures can significantly affect the performance of photovoltaic(PV)panels by reducing their efficiency and power output.This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic(PV)panels.It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels,considering the thermal performance and its implications for enhancing their overall performance and sustainability.The study compares four rooftop covering materials:wooden flakes packs(both dry and wet),polystyrene,and woolen insulation.The measurements were implemented under Iraqi weather conditions.The comparison was based on the PV panels’thermal behavior and its impact on conversion efficiency.The results revealed that covering the roof beneath the installed PV panels reduces their temperature and increases efficiency.The best performance was observedwhen placingwetwooden flakes beneath the panels,with an efficiency increase of 5%.Moreover,thewoolen insulation offered an efficiency rise of 12%near sunset.Themain outcome of thiswork is that the wet–wooden–flakes showed the best performance improvement of the PV panels.

How R&D investment promotes green technology innovation in the context of digitalization?-An empirical analysis based on provincial panel data

Green technology innovation is an important driving force and source to promote my country’s high-quality development,and it is the core path to achieve sustainable development.This paper uses my country’s provincial panel data from 2016 to 2019 to study the impact mechanism of R&D investment on green technology innovation,and introduces the level of digitization,using the panel threshold model to discuss its role in the impact mechanism of R&D investment on green technology innovation.The study found that when the level of digitalization in a region is low,increasing R&D investment does not necessarily improve the ability of green technology innovation;when the level of digitalization is relatively high,R&D investment has a positive role in promoting green technology innovation.Therefore,it is necessary to improve policies to encourage enterprises to increase investment in research and development;at the same time,it is necessary to promote the coordinated development of digital foundation,digital investment,digital literacy,digital economy and digital application,and promote the deep integration of digitalization and green technology innovation.

Advancements in Photovoltaic Panel Fault Detection Techniques

This paper examines the progression and advancements in fault detection techniques for photovoltaic (PV) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of PV technology grows, the need for effective fault detection strategies becomes increasingly paramount to maximize energy output and minimize operational downtimes of solar power systems. These approaches include the use of machine learning and deep learning methodologies to be able to detect the identified faults in PV technology. Here, we delve into how machine learning models, specifically kernel-based extreme learning machines and support vector machines, trained on current-voltage characteristic (I-V curve) data, provide information on fault identification. We explore deep learning approaches by taking models like EfficientNet-B0, which looks at infrared images of solar panels to detect subtle defects not visible to the human eye. We highlight the utilization of advanced image processing techniques and algorithms to exploit aerial imagery data, from Unmanned Aerial Vehicles (UAVs), for inspecting large solar installations. Some other techniques like DeepLabV3 , Feature Pyramid Networks (FPN), and U-Net will be detailed as such tools enable effective segmentation and anomaly detection in aerial panel images. Finally, we discuss implications of these technologies on labor costs, fault detection precision, and sustainability of PV installations.

Composite Panels from the Combination of Rice Husk and Wood Chips with a Natural Resin Based on Tannins Reinforced with Sugar Cane Molasses Intended for Building Insulation: Physico-Mechanical and Thermal Properties

The objective of this work is to develop new biosourced insulating composites from rice husks and wood chips that can be used in the building sector. It appears from the properties of the precursors that rice chips and husks are materials which can have good thermal conductivity and therefore the combination of these precursors could make it possible to obtain panels with good insulating properties. With regard to environmental and climatic constraints, the composite panels formulated at various rates were tested and the physico-mechanical and thermal properties showed that it was essential to add a crosslinker in order to increase certain solicitation. an incorporation rate of 12% to 30% made it possible to obtain panels with low thermal conductivity, a low surface water absorption capacity and which gives the composite good thermal insulation and will find many applications in the construction and real estate sector. Finally, new solutions to improve the fire reaction of the insulation panels are tested which allows to identify suitable solutions for the developed composites. In view of the flame tests, the panels obtained are good and can effectively combat fire safety in public buildings.

A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.

Comprehensive Examination of Solar Panel Design: A Focus on Thermal Dynamics

In the 21st century, the deployment of ground-based Solar Photovoltaic (PV) Modules has seen exponential growth, driven by increasing demands for green, clean, and renewable energy sources. However, their usage is constrained by certain limitations. Notably, the efficiency of solar PV modules on the ground peaks at a maximum of 25%, and there are concerns regarding their long-term reliability, with an expected lifespan of approximately 25 years without failures. This study focuses on analyzing the thermal efficiency of PV Modules. We have investigated the temperature profile of PV Modules under varying environmental conditions, such as air velocity and ambient temperature, utilizing Computational Fluid Dynamics (CFD). This analysis is crucial as the efficiency of PV Modules is significantly impacted by changes in the temperature differential relative to the environment. Furthermore, the study highlights the effect of airflow over solar panels on their temperature. It is found that a decrease in the temperature of the PV Module increases Open Circuit Voltage, underlining the importance of thermal management in optimizing solar panel performance.

A panel data model to predict airline passenger volume

Airline passenger volume is an important reference for the implementation of aviation capacity and route adjustment plans.This paper explores the determinants of airline passenger volume and proposes a comprehensive panel data model for predicting volume.First,potential factors influencing airline passenger volume are analyzed from Geo-economic and service-related aspects.Second,the principal component analysis(PCA)is applied to identify key factors that impact the airline passenger volume of city pairs.Then the panel data model is estimated using 120 sets of data,which are a collection of observations for multiple subjects at multiple instances.Finally,the airline data from Chongqing to Shanghai,from 2003 to 2012,was used as a test case to verify the validity of the prediction model.Results show that railway and highway transportation assumed a certain proportion of passenger volumes,and total retail sales of consumer goods in the departure and arrival cities are significantly associated with airline passenger volume.According to the validity test results,the prediction accuracies of the model for 10 sets of data are all greater than 90%.The model performs better than a multivariate regression model,thus assisting airport operators decide which routes to adjust and which new routes to introduce.

供应链金融对中小企业R&D投资效率的影响:基于融资约束视角

创新是中小企业保持竞争力、适应市场变化和实现可持续发展的关键。基于2016-2022年创业板中小企业相关数据,运用三阶段DEA分析、面板Tobit模型回归、二元Logistic回归等方法,探究供应链金融对中小企业R&D投资效率的影响。结果表明,供应链金融能够显著提高中小企业R&D投资效率,融资约束在二者间发挥遮掩效应。进一步分析发现,上述效应对供应链集中度较高的企业更为显著。结论可为发挥供应链金融筹资优势,促进供应链生态系统资源互补、信息共享的协同创新网络形成,进而支持中小企业创新活动提供理论支持。

虚拟仪器平台下旋转机械振动应用研究

利用LabVIEW软件图形化程序和可视化前面板,基于旋转机械结构和运动特点构建虚拟仪器仿真平台基本框架,设计了与真实仪器功能相当的旋转机械齿轮振动虚拟仿真研究平台。通过仿真验证,齿轮振动虚拟仿真平台能够有效采集振动信号,并对振动信号特征进行提取和分析,测试结果与旋转机械齿轮实际振动情况一致。开发的虚拟仿真平台达到了预期功能目标,为旋转机械关键部件振动检测和故障诊断提供了可视化技术支持,降低了旋转机械故障检测成本。

基于改进YOLOv8的汽车门板紧固件检测算法

针对汽车门板紧固件在复杂场景下存在的检测准确度较低和实时性较差的问题,提出一种小目标改进算法YOLOv8-SOD(small object detection)。在主干网络引入SPD(space-to-depth)模块和自适应权重分配模块,在算法的颈部网络输出位置增加选择性注意力模块,将CIOU损失函数替换为MPDIOU损失函数。实验结果表明,YOLOv8-SOD算法平均检测精度为99.1%,比模板匹配方法和YOLOv8算法分别提高了9.4%、2%,达到了工厂生产流水线的检测标准,具有实用价值。

科学、技术的互动及其对经济发展的影响:基于panel data的实证研究

进入知识经济社会,发展中国家的追赶和发展过程,更加依赖于科学、技术及其二者之间的相互作用。本文在前人研究的基础上,选择了中国30个省(市、自治区)的板面数据进行初步实证分析。研究发现,中国的基础科学研究、技术进步对经济发展存在显著的促进作用,技术进步对经济发展的直接贡献要远大于基础科学研究的贡献;然而基础科学研究与技术进步之间的相互作用机制不甚理想,致使科学研究的作用未能很好发挥。最后在实证研究的基础上对科技和经济发展提供了若干对策建议,并提出进一步研究的建议。