The neural network, a prediction method for the estimation of the TCC, was constructed and trained using 124 experi- mental data obtained by previous studies (Kim et al. 2003; Morabito 1989; Harmathy 1983; Yamazaki et al. 1995; Lie and Kodur 1996; Van Geem et al. 1997; Khan et al. 1998; Khan 2002; Kodur and Sultan 2003). Based on their data sets, the developed neural network model was trained with regard to eleven parameters: nine parameters representing the composition of concrete constituents, which were the water–cement ratio, the ﬁne aggregate percentage, the coarse aggregate percentage, the unit water weight, the unit cement weight, the unit ﬁne aggregate weight, the unit coarse aggregate weight, the unit ﬂy ash weight, and the unit silica fume weight, and two parameters representing the state of concrete, which were the temperature of the concrete and the water content in the concrete. Finally, the TCC estimated by the neural network model was compared with 28 randomly- selected measured data not included in the neural network training. As a result, the neural network model, trained by the eleven parameters, accurately estimated the values of the TCC. Therefore, this study demonstrated that the proposed prediction method based on a neural network algorithm could be used as a reliable and effective technique for determining thermal conductivity in the thermal design and analysis of concrete structures.
electric machines, the situation is more complex since these are filled with different materials, including randomly placed enameled wire, insulation varnish, insulation paper, and air. If the real structure with different materials is considered when establishing the thermal resistance network or FEA model of slot, it will be very complicated, or in many cases impossible due to the aforesaid random-nature in wire placement. Therefore, in existing literature, homogenization methods are applied, by which the slot section is usually treated as an equivalent homogenous material. Various approaches have been adopted in literature, including homogenization by Milton’s method, , by using equivalent square thermal conductor models, parallel models or using an area weighted average approach –, –. More recently the Gasar porous metal material (GPMM) model has been also used in . Compared with traditional mainstream motors using randomly placed strands, the thermalanalysis of machines with Litz wire in slots is less common, and the thermal behavior and properties of Litz wire have not received detailed attention in literature. The following two main methods for calculating the thermal resistance of Litz wire are given in literature:
At architecture design level, RLCTN will contribute to the development of mathematical algorithm to study the thermal characteristics of oil distribution transformers base on the Resistance-Inductance-Capacitance network . The thermal fault model for transformers includes abnormal thermal gradient caused by failures of capaci- tance of dielectric property in the form of transformer oil, cellulose paper and other insulators. The second impact is in showing the application of RLCTN as a base foun- dation for extensive projects. To achieve the desired re- sult and bring the proposition of this work to a logical conclusion, this model is implemented into a simulator to study the effect of thermal events on the design of abnor- mal thermal detection mechanism in a soft-real-time en- vironment such as electrical power distribution substation. Common methods of fault localization are reviewed such as digital control and advanced signal analysis algo- rithms-based; this concentrates on the incorporation of digital control, communications, and intelligent algo- rithms into power electronic devices such as direct-cur- rent-to-direct-current converters and protective switch- gears. These, enables revolutionary changes in the way electrical power systems are designed, developed, con- figured, and integrated in aerospace vehicles and satel- lites , an active “collaboration” among modular com- ponents to improve performance and enable the use of common modules, thereby reducing costs was developed. The performance improvement goals include active cur- rent sharing, load efficiency optimization, and active power quality control. Artificial Intelligence (AI) was another method developed to monitor, predict and detect faults at an early stage in a particular section of power system. Here the detector only takes external measure- ments from input and output of the power system that was simulated using Artificial Neural Networks equiva- lent circuit developed to predict and detect fault . Every electrical thermographic examination aimed at
In this study, first, and thermal analyzes are being investigated in the traditional diesel piston (uncut) Made design silicon aluminum alloy 1 and 2 design parameters. Second, the thermalanalysis Made in the piston, coated with zirconium through the use of commercial law, namely ANSYS. And I investigated the effects of coating on the thermal behavior of the pistons. Finite element analysis is Programs using computer-aided design. The main objective is to achieve and analysisThermal stress distribution of the piston in the event of an actual engine during the combustion process. To illustrate this thesis network optimization technique using the finite element analysis to predict the sensitive region of high pressure On race. In this work, the focus is on the study of the thermal behavior of functionally Classified coatings obtained through the use of commercial laws, aluminum and zirconium ANSYS Piston coated aluminum surfaces. This analysis is to reduce the pressure of the
Abstract: Network traffic anomalies stand for a large fraction of the Internet traffic and compromise the performance of the network resources. Detecting and diagnosing these threats is a laborious and time consuming task that network operators face daily. During the last decade researchers have concentrated their efforts on this problem and proposed several tools to automate this task. Thereby, recent advances in anomaly detection have permitted to detect new or unknown anomalies by taking advantage of statistical analysis of the traffic. In spite of the advantages of these detection methods, researchers have reported several common drawbacks discrediting their use in practice. Indeed, the challenge of understanding the relation between the theory underlying these methods and the actual Internet traffic raises several issues. This paper discusses a statistical approach to analysis the distribution of network traffic to recognize the normal network traffic behavior also discusses a method to recognize anomalies in network traffic, based on a non-restricted α-stable first -order model and statistical hypothesis testing.
Abstract— Because of Complex design and higher demand for Printed Circuit Boards (PCB), thermal design of PCB pose challenges to any heat transfer designer for perfect design. PCB design proceeds on the strength of various assumptions in the predictions of temperatures. Generally, problems were solved for temperatures of a given PCB card without taking all factors into consideration, but the obtained results for those problems are not totally correct. So a forward step was taken by considering all factors to get the correct results. Some of the factors affecting temperature distribution in PCBs are device power dissipations, their distribution in a board, layer-wise thermal conductivity and copper (Cu) spread within a PCB, nature of drill-holes / thermal mass distribution and finally electrical heating effects affecting thermal performance of PCBs. All the above factors bring uncertainty in prediction of temperatures in devices and inferior design generally results in de-lamination of PCB layers. Likewise, Joule Heating phenomenon also impacts the thermalanalysis which normally occurs in PCB. Effects of DC drop due to passage of electric current inside Cu-traces, impacts Joule heating effects inside traces of the board and lead to trace level fusing. So in this report the trace level heating was done with different Mechanical computer Aided Engineering (MCAE) software tools by giving the required boundary conditions and results were obtained. The problems were also solved for no-joule heating case and compared.
Abstract:- The manganese ore samples from Sandur were subjected to thermal studies. The thermal study of minerals involves the Differential thermalanalysis (DTA) a method of mineral analysis that is particularly useful in the identification of the minerals which undergo transformation when heated to temperatures generally below 1200 0 c. If heat energy is absorbed the rate will decrease during the transformation and the reaction is endothermic. The temperatures at which endothermic and exothermic transformations take place are characteristic of certain substances. The DTA technique has been devised to determine these temperatures. Since it is unlikely that any two minerals have chemical bonds of identical strength, they will decompose, oxidize or change phase at different temperatures. The temperature at which the peak occurs often indicates which mineral is present. Since many minerals undergo several endothermic or exothermic changes in the temperature range studied, the aggregate peaks at the proper temperatures suffice in many instances to identify the mineral. In this study it has been the objective to define the thermal curves of the simpler manganese minerals and to study how the method can be applied to natural mixtures. Thermo gravimetric analysis (TGA) technique deals with the study of the loss in weight of a substance as it is being heated. The behavior of the minerals to the rising temperatures is studied. The studies are carried out with respect to their transformations and weight loss due to the rising temperature. The studies show the presence of Manganese minerals such as psilomelane, pyrolusite, manganite, cryptomelane and ramsdellite. The instrument used is SDT Q 600 TA instruments, Waters USA.
randomly around the stable value. We analyze that random amplitude fluctuation of per carbon emissions vary with time, in other words, it vary with gas inflow. This model take carbon emission external data of CEMS systems(gas inflow, gas turbine load and steam turbine load) and per carbon emissions as the input of abnormal data screening neural network model, which is
Heat transfer through thermal conduction over composite slabs or walls are found in many physical problems and engineering applications such as in fields of nuclear reactors, Internal combustion engines, steam turbines and boilers, refrigeration, ventilations and many other real life applications. The thermal conductivity of a material depends on so many factor the most important factors are Material structure, Density of material, Moisture content and operating conditions like pressure and temperature. Brian Y. Lattimer and Jason Ouellette conducted the Properties of composite materials for thermalanalysis involving fires. Inverse heat transfer analysis was used to determine thermal and physical properties of a coupon size glass reinforced vinyl ester composite sample from ambient to 800 °C these apparent specific heat capacities were input into a transient heat conduction model to predict the temperature profile through a sample.George S. Springer and Stephen W. Tsai (2016) reported the Thermal Conductivities of Unidirectional Materials. The composite thermal conductivities of unidirectional composites are studied and expressions are obtained for predicting these conductivities in the directions along and normal to the filaments. The results of the shear loading analogy agree reason ably well with the results of the thermal model particularly at filament contents
Surface thermodynamic properties of nanoparticles take a distinct effect on thermodynamic and kinetic parame- ters of chemical reactions (so-called size effect) in nano- dyspersed systems. However, this problem is poorly in- vestigated because of complexity of experiment and ab- sence of a database on surface thermodynamic properties of solid. The present article attempts to fill an existing gap somewhat. In the article, the new method of determi- nation of surface thermodynamic properties of nanopar- ticles by thermalanalysis is described and its influence on thermodynamic and kinetic parameters of chemical reaction is shown.
The internal heat load of office buildings in Japan has increased due to the rapid automation of offices. Accordingly, the use of active air-conditioning (A/C) systems to maintain indoor thermal comfort in offices has also increased. To realize a sustainable society, however, the reduction of cooling loads (especially internal heat loads) by the effective use of outdoor air has been attempted. Recently, A/C systems that combine natural ventilation with artificial cooling (“hybrid A/C systems” hereinafter) have received increased attention . These hybrid A/C systems are considered an effective means of utilizing natural resources, and many office buildings are adopting such systems. For efficient introduction of outdoor air into buildings, flow control has been installed at ventilation inlets and outlets. Although hybrid A/C systems are expected to decrease energy consumption when cooling, the quantitative effect of a system is influenced by the building shape, site environment, weather conditions and other factors. Therefore, the estimations of natural ventilation rates and energy-saving effects of hybrid A/C systems have been difficult. Due to the significance of hybrid A/C systems, numerous research studies have been performed (e.g. , ), however little is known about the quantitative characteristics of these systems especially with flow control inlets and outlets.
The disc brake rotor is a rotating device. Braking is a process which converts the kinetic energy of the vehicle into mechanical energy which must be dissipated in the form of heat. This paper presents the analysis of the thermal stress ,deformation and heat flux at the disc interfaces using a detailed 3-dimensional finite element model of a real car disc brake rotor . Finite element (FE) models of the brake-disc rotor are created using CATIAV5R20 and simulated using ANSYS 19.2 which is based on the finite element method (FEM). It is also investigates different levels in modeling a disc brake rotor system and simulating contact pressure distributions . It covers Finite Element Method approaches in the automotive industry the contact analysis and thermalanalysis. The effect of the angular velocity and the contact pressure distribution on disc brake rotor are investigated. In our project we take different materials like Gray Cast Iron Alloy, ALSI 398, and Al6060 and Composite materials Carbon fibre. Finally comparison between these materials and carried out stresses and deformations level maximum and minimum then we have find out Carbon fiber is best materials other than materials because its light weight and durable.
Social networkanalysis deals with the interactions between individuals by considering them as nodes of a network (graph) whereas their relations are mapped as network edges. Social networks, such as Facebook and Bebo, are essentially online communities that allow users to come together, communicate and share things such as photographs, music or other files; and, most prolifically, to create short messages, often in the style of a mobile phone text message but shared among a group. People use the sites to ask their friends questions, say how they feel today and what they are up to, to comment on something they have seen on someone‟s page. A social network is the network of relationships and interactions among social entities such as individuals, groups of individuals, and organizations. Since the rise of Internet and the World Wide Web has enabled us to investigate large -scale social networks, there has been growing interest in social networkanalysis.
Clay minerals are considered the most important components of clastic reservoir rock evaluation studies. The Shurijeh gas reservoir Formation, represented by shaly sandstones of the Late Jurassic- Early Cretaceous age, is the main reservoir rock in the Eastern Kopet-Dagh sedimentary Basin, NE Iran. In this study, X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopic (SEM) studies, and thermalanalysis including differential thermalanalysis (DTA), and thermogravimetric analysis (TGA) techniques were utilized in the characterization of the Shurijeh clay minerals in ten representative samples. The XRF studies showed that silica and aluminum oxides are present quantities. The XRD test was then used to determine the mineralogical composition of bulk components, as well as the clay fraction. The XRD patterns indicated the presence of dominant amount of quartz and plagioclase, with moderate to minor amounts of alkali feldspar, anhydrite, carbonates (calcite and dolomite), hematite and clay minerals. The most common clays in the Shurijeh Formation were illite, chlorite, and kaolinite. However, in very few samples, glauconite, smectite, and mixed layer clay minerals of both illite-smectite and chlorite-smectite types were also recognized. The XRD results were quantified, using the elemental information from the XRF test, showing that each Shurijeh exhibited low to moderate amounts of clay minerals, typically up to 21%. The amount of illite, the most dominant clay mineral, reached maximum of 13.5%, while the other clay types were significantly smaller. Based on the use of SEM and thermal data, the results of the identification of clay minerals, corresponded with the powder X-ray diffraction analysis, which can be taken into account as an evidence of the effectiveness of the thermalanalysis technique in clay typing, as a complementary method besides the XRD.
Table 5.7 compares the timing, clock skew, maximum temperature and runtime analyzed with different resolutions implemented in the three-tier five-metal-layer technology. These experiments were run on a Sun Ultra-Sparc3 900MHz CPU with 16G memory. The seventh column of Table 5.7 gives the density of thermal via cells (TV density) compared to the die area that was inserted with the clock buffers. The ‘-’ symbol corresponds to our first scheme in which no extra vias were inserted. From Table 5.7, we can see the trade-offs of analyzing a design with various resolutions. The two coarse analyses run two orders of magnitude faster than the fine analysis, however they fail to capture the hotspots and the hold-time violation in the case where no thermal vias are inserted. The fine analysis runs much slower and gives similar performance values, but it captures the hotspots and the hold time violation. In the FFT, the maximum error between coarse and fine simulation for delay and energy per cycle are 1.1% and 5.0%, respectively. When comparing the resolution, the clock skew varies by 10.4% without thermal vias but only varies 5% if thermal vias are inserted. In the ORPSOC, the maximum errors between the coarse and fine simulations for delay and energy per cycle are 8.2% and 4.0% respectively. The variation of clock skew simulated with different resolutions is reduced from 14.5% to 5.5% if thermal vias are inserted. The larger variation in delay and clock skew in the ORPSOC design is due to the memory. The temperature in memory regions is much lower than other regions filled with logic circuits. The coarsest analysis averages this effect and underestimates the path delay and clock skew.
ABSTRACT Thermal response testing is an in situ technique for characterising the thermal conductivity of the ground around a borehole heat exchanger. The test has seen renewed interest in recent years as an increasing number of ground heat exchangers are being constructed to provide renewable heating and cooling energy as part of ground source heat pump systems. The thermal response test involves applying a constant heating power to the ground via a circulating heat transfer fluid. Most test rigs are set up to cater for deep boreholes, with avail- able heat transfer lengths typically more than 100m, and therefore have electrical heater capacities of a corresponding size. Pile heat ex- changers are generally much shorter and the heat exchange length can be a little as 10m. This means that many standard thermal response test rigs cannot provide a low enough heating power and there is a risk of excessive temperature changes developing, especially during longer duration tests which can be recommended for larger diameter piles. One solution is to carry out the thermal response test on a group of piles, thereby increasing the effective heated length. This has the added advantage of testing a larger volume of soil. This paper exam- ines the principles behind group thermal response testing for energy piles and considers the advantages and limitations of the approach with reference to a case study.
The objective of the present work is to develop methodology to relate tool wear with mechanical properties of a material such as Hardness. Here hardness is related with the modified temperature, including the effect of strain rate, of cutting tool. Finite Element Analysis is used to depict the temperature at various points of cutting tool by changing various machining parameters such as cutting speed (V), depth of cut (d), feed rate (f).
This paper is an extension of work originally presented in CyberC 2017, “9th International Conference on Cyber-enabled distributed computing and knowledge discovery” titled ‘A Trust Evaluation Method for Active Attack Counteraction in Wireless Sensor Networks’ . Mobile robot networks are quite vulnerable to attacks both over the network and physical properties of nodes. The article  presented a threats model for the network of mobile robots. The authors also analyzed the attacks for a group of mobile robots. Based on the analysis, it was revealed that the main set of attacks that an attacker can implement for a group of mobile robots is denial of service (DoS), distributed denial-of-service (DDoS) attack, a man in the middle (MITM) and a Sybil attack, and exhaustion resources. In addition, there are a number of attacks aimed at the robot positioning system and on other elements of the sensor system, which are not considered in this study. The main purpose of this study is to detect these attacks with a minimum of resources of mobile robots. The offender, implementing an active attack, can influence any physical parameter of the mobile robot through a network or physical impact.
Many problems in science and engineering fields can be modeled by integral equation. In various branches of linear and nonlinear functional analysis, discrete Homotopy is the important method to solve them. In order to find the numerical solution of the linear and nonlinear integral equations, varies methods are applied and have been explored. Nonlinear problems are hard to be solved when compared with linear problems especially analytically. There are two criterions for a satisfactory analytic method of nonlinear problem:
ANSYS is general-purpose finite element analysis (FEA) software package. Finite Element Analysis is a numerical method of deconstructing a complex system into very small pieces (of user- designated size) called elements. The software implements equations that govern the behaviour of these elements and solves them all; creating a comprehensive explanation of how the system acts as a whole. These results then can be presented in tabulated, or graphical forms. This type of analysis is typically used for the design and optimization of a system far too complex to analyse by hand. Systems that may fit into this category are too complex due to their geometry, scale, or governing equations. The analysis is carried out in ansys fluent the solver is pressure based solver. Energy model is kept on and the viscous model is set to k- epsilon. The flow material is the mixture of gases such as nitrogen, carbon dioxide, water vapour, carbon monoxide, oxygen and methane.