菲涅尔透镜聚光光伏光热耦合系统性能模拟研究

建立带有嵌入式流道结构的低倍菲涅尔透镜聚光的光伏光热耦合系统数学模型,分别从聚光比、换热流体质量流量、几何和环境参数角度研究了耦合系统的光热光电性能。结果表明:随着聚光比增加,系统的热性能提升而电性能降低,且低Re数下聚光比对系统性能影响显著;系统各性能参数在小流量阶段变化剧烈,但变化速率逐渐减缓,直至趋于稳定;流道宽度w_1的不同造成系统性能随流道深度h变化特征的差异,根据Re数与换热面积所占比重可分为4个不同阶段;当太阳电池覆盖率Pa相同时,随着风速的增加,系统热性能参数缓慢降低,而电性能几乎不变。     

A Management Perspective on Risk of Security Threats to Information Systems

Electronic commerce and the Internet have enabled businesses to reduce costs, attain greater market reach, and develop closer partner and customer relationships. However, using the Internet has led to new risks and concerns. This paper provides a management perspective on the issues confronting CIOs and IT managers: it outlines the current state of the art for security in e-commerce, the important issues confronting managers, security enforcement measure/techniques, and potential threats and attacks. It develops a scheme for probabilistic evaluation of the impact of security threats with some illustrative examples. This methodology may be used to assess the probability of success of attacks on information assets in organizations, and to evaluate the expected damages of these attacks. The paper also outlines some possible remedies, suggested controls and countermeasures. Finally, it proposes the development of cost models which quantify damages of these attacks and the effort of confronting these attacks. The construction of one such cost model for security risk assessment is also outlined. It helps decision makers to select the appropriate choice of countermeasure(s) to minimize damages/losses due to security incidents. Finally, some recommendations for future work are provided to improve the management of security in organizations on the whole.     

Mathematical modeling of onset of convection in a porous layer with viscosity variation

IntroduthenIn a novel EOR (Enhanced Oil Recovery) method,diffusion-convechon may be employed as a drive toforce heavy, viscous oil to move. A ~ of gas isexpanded beneath oil, and gas is allowed tO diffuseupward. As oil dissolves gas, it becomes lighter.Therefore, an inverse density gradient is develOPed in oillayer gradually. When this density gradient exceeds acritical value, convechon is started. It may be concjudedthat develOPing a theory, which predictS the onset ofconvection, should…     

Water—ethanol—gasoline blends as spark ignition engine fuels

The miscibility characteristics of hydrated ethanol with gasoline is investigated as a means of reducing the cost of ethanol/gasoline blends for use as a spark ignition engine fuel. For a given percentage of water in the ethanol, the experimental data shows that a limited volume of gasoline can be added to form a stable mixture. Engine experiments indicate that, at normal ambient temperatures, a water/ethanol/gasoline mixture containing up to 6 vol% of water in the ethanol constitutes a desirable motor fuel with power characteristics similar to those of the base gasoline. As a means of reducing the smog causing components of the exhaust gases, such as the oxides of nitrogen and the unburnt hydrocarbons, the water/ethanol/gasoline mixture is superior to the base gasoline.     

Effect of structural uncertainty on seismic response of steel moment-resisting frames equipped with tuned mass dampers

Tuned mass dampers (TMDs) can be used to absorb the input energy of the applied loads, and reduce the response of building frames. However, inherited uncertainties in structural characteristics of building frames can significantly affect their response and counteract the effectiveness of vibration absorbing devices such as TMDs. In this study, by calculating cumulative damage indices for stories of the structure, failure probability of two steel moment-resisting frames equipped with TMDs has been studied in presence of uncertainty in characteristics of the structure. Cumulative inelastic deformation of structural elements in each story has been used to calculate the damage representative of that story, based on weighted average approach. Even though the cumulative response of the deterministic model of the structures is reduced by installing TMDs, the results of the numerical simulations on the probabilistic response of the sample structures indicate that for the records that cause excessive damage in the lower stories of the structures, the effect of TMDs on failure probability of the structure can be detrimental.     

Nonlinear dynamic response of tall buildings considering structure–soil–structure effects

Numerous studies have shown that the interaction between adjacent buildings can result in changes in nonlinear dynamic response of structures, damage, and performance level, depending on the dynamic specifications of structures involved and the frequency content of the input motion. To study these effects, finite element method is used for the analytical investigations, and total soil–foundation–structure system is modeled all together. For modeling purposes and in order to realize the effects of the adjacent buildings on the dynamic response, two buildings, namely, 15‐story and 30‐story tall buildings, which were separated by distances of 1/4 and 1/8 of the width of the foundation and were located on hard and soft soil profiles, were considered. It was concluded that in the case where the soil and structure's periods were near to each other, the interaction of adjacent structures on increasing nonlinear responses (displacement and interstory drift) and structural damage indexes was noticeable and therefore was not negligible. Whereas in the case where periods are distant from each other, the interaction of adjacent buildings has a decreasing effect on damage indexes and nonlinear responses and therefore was negligible. Copyright © 2011 John Wiley & Sons, Ltd.     

Extracting knowledge from building-related data — A data mining framework

Energy management systems provide an opportunity to collect vast amounts of building-related data. The data contain abundant knowledge about the interactions between a building’s energy consumption and the influencing factors. It is highly desirable that the hidden knowledge can be extracted from the data in order to help improve building energy performance. However, the data are rarely translated into useful knowledge due to their complexity and a lack of effective data analysis techniques. This paper first conducts a comprehensive review of the commonly used data analysis methods applied to building-related data. Both the strengths and weaknesses of each method are discussed. Then, the critical analysis of the previous solutions to three fundamental problems of building energy performance improvement that remain significant barriers is performed. Considering the limitations of those commonly used data analysis methods, data mining techniques are proposed as a primary tool to analyze building-related data. Moreover, a data analysis process and a data mining framework are proposed that enable building-related data to be analyzed more efficiently. The process refers to a series of sequential steps in analyzing data. The framework includes different data mining techniques and algorithms, from which a set of efficient data analysis methodologies can be developed. The applications of the process and framework to two sets of collected data demonstrate their applicability and abilities to extract useful knowledge. Particularly, four data analysis methodologies were developed to solve the three problems. For demonstration purposes, these methodologies were applied to the collected data. These methodologies are introduced in the published papers and are summarized in this paper. More extensive investigations will be performed in order to further evaluate the effectiveness of the framework.     

Thermal Properties of the Binary‐Filler Hybrid Composites with Graphene and Copper Nanoparticles

The thermal properties of epoxy‐based binary composites comprised of graphene and copper nanoparticles are reported. It is found that the “synergistic” filler effect, revealed as a strong enhancement of the thermal conductivity of composites with the size‐dissimilar fillers, has a well‐defined filler loading threshold. The thermal conductivity of composites with a moderate graphene concentration of f_g = 15 wt% exhibits an abrupt increase as the loading of copper nanoparticles approaches f_Cu ≈ 40 wt%, followed by saturation. The effect is attributed to intercalation of spherical copper nanoparticles between the large graphene flakes, resulting in formation of the highly thermally conductive percolation network. In contrast, in composites with a high graphene concentration, f_g = 40 wt%, the thermal conductivity increases linearly with addition of copper nanoparticles. A thermal conductivity of 13.5 ± 1.6 Wm^?1K^?1 is achieved in composites with binary fillers of f_g = 40 wt% and f_Cu = 35 wt%. It has also been demonstrated that the thermal percolation can occur prior to electrical percolation even in composites with electrically conductive fillers. The obtained results shed light on the interaction between graphene fillers and copper nanoparticles in the composites and demonstrate potential of such hybrid epoxy composites for practical applications in thermal interface materials and adhesives.     

The impact of surface air movement on material emissions

The effects of surface air movement on material emissions were investigated experimentally. A field study was carried out to understand the characteristics of surface air movement in real rooms, and a velocity-controlled test chamber was designed and built, based on the field study results, to provide a uniform mean airflow and boundary layer condition over the test area. An extensive experimental study on the effects of air movement on material emissions was carried out, under different mean flow velocities and turbulence fluctuations, by using the small velocity-controlled test chamber. It was found that material emission rates are a function of the surface air flow conditions: as surface air velocity increases, contaminants from materials deplete faster, the turbulent fluctuation has a lesser effect on material emissions.     

Overland Water Flow and Solute Transport: Model Development and Field-Data Analysis

The application of plant nutrients with irrigation water is an efficient and cost-effective method for fertilizer application to enhance crop production and reduce or eliminate potential environmental problems related to conventional application methods. In this study, a combined overland water flow and solute transport model for analysis and management of surface fertigation/chemigation is presented. Water flow is predicted with the well-known Saint-Venant’s equations using a control volume of moving cells, while solute transport is modeled with the advection-dispersion equation. The 1D transport equation was solved using a Crank-Nicholson finite-difference scheme. Four, large-scale, field experiments were conducted on blocked-end and free draining furrows to calibrate and verify the proposed model. The results showed that application of solute during the entire irrigation event, or during the second half of the irrigation for blocked end conditions with appropriate inflow rates, produced higher solute uniformity than application of solute during the first half of the irrigation event. Measured fertilizer distribution uniformity of the low quarter ranged from 21 to 76% while fertilizer distribution uniformity of the low half values varied between 62 to 87%. The model was subsequently applied to the experimental data; results showed good agreement with all field data. Water balance errors for the different experiments varied from 0.004 to 1.8%, whereas fertilizer mass balance errors ranged from 1.2 to 3.6%. A sensitivity analysis was also performed to assess the effects of longitudinal dispersivity parameter on overland solute concentrations. A value of 10 cm for dispersivity provided a reasonable fit to the experimental data.