Process and Supply-Chain Optimization for Testing and Verification of Formation Tester/Pressure-While- Drilling Tools

Applying a rigorous process to optimize the elements of a supply-chain network resulted in reduction of the waiting time for a service provider and customer. Different sources of downtime of hydraulic pressure controller/calibrator (HPC) were causing interruptions in the operations. The process examined all the issues to drive greater efficiencies. The issues included inherent design issues with HPC pump, contamination of the HPC with impurities, and the lead time required for annual calibration in the USA. HPC is used for mandatory testing/verification of formation tester/pressure measurement/logging-while drilling tools by oilfield service providers, including Halliburton. After market study andanalysis, it was concluded that the current HPC model is best suited in the oilfield industry. To use theexisting HPC model effectively, design andcontamination issues were addressed through design and process improvements. An optimum network is proposed after comparing different supply-chain models for calibration lead-time reduction.

Application of Nano Cutting Fluid under Minimum Quantity Lubrication (MQL) Technique to Improve Grinding of Ti – 6Al – 4V Alloy

Minimum Quantity Lubrication (MQL) technique obtained a significant attention in machining processes to reduce environmental loads caused by usage of conventional cutting fluids. Recently nanofluids are finding an extensive application in the field of mechanical engineering because of their superior lubrication and heat dissipation characteristics. This paper investigates the use of a nanofluid under MQL mode to improve grinding characteristics of Ti-6Al-4V alloy. Taguchi-s experimental design technique has been used in the present investigation and a second order model has been established to predict grinding forces and surface roughness. Different concentrations of water based Al2O3 nanofluids were applied in the grinding operation through MQL setup developed in house and the results have been compared with those of conventional coolant and pure water. Experimental results showed that grinding forces reduced significantly when nano cutting fluid was used even at low concentration of the nano particles and surface finish has been found to improve with higher concentration of the nano particles.

Stress Relaxation of Date at Different Temperature and Moisture Content of Product: A New Approach

Iran is one of the greatest producers of date in the world. However due to lack of information about its viscoelastic properties, much of the production downgraded during harvesting and postharvesting processes. In this study the effect of temperature and moisture content of product were investigated on stress relaxation characteristics. Therefore, the freshly harvested date (kabkab) at tamar stage were put in controlled environment chamber to obtain different temperature levels (25, 35, 45, and 55 0C) and moisture contents (8.5, 8.7, 9.2, 15.3, 20, 32.2 %d.b.). A texture analyzer TAXT2 (Stable Microsystems, UK) was used to apply uniaxial compression tests. A chamber capable to control temperature was designed and fabricated around the plunger of texture analyzer to control the temperature during the experiment. As a new approach a CCD camera (A4tech, 30 fps) was mounted on a cylindrical glass probe to scan and record contact area between date and disk. Afterwards, pictures were analyzed using image processing toolbox of Matlab software. Individual date fruit was uniaxially compressed at speed of 1 mm/s. The constant strain of 30% of thickness of date was applied to the horizontally oriented fruit. To select a suitable model for describing stress relaxation of date, experimental data were fitted with three famous stress relaxation models including the generalized Maxwell, Nussinovitch, and Pelege. The constant in mentioned model were determined and correlated with temperature and moisture content of product using non-linear regression analysis. It was found that Generalized Maxwell and Nussinovitch models appropriately describe viscoelastic characteristics of date fruits as compared to Peleg mode.

Neural Network Based Icing Identification and Fault Tolerant Control of a 340 Aircraft

This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.

Enriching Egg Yolk with Carotenoids and Phenols

Dried tomato peel (DTP) was tested in vivo (n=10) in 42 week-old laying hens at rates of 0, 40, 70, 100 and 130g/kg DM feed. Laying hens were fed in group 120 g DM/day/animal for 26 days. After 21 days, feed intake was not affected after DTP incorporation (97% of the offered feed in the five groups). Laying rate was not significantly different after DTP incorporation at 4 and 10% from the control group. Egg yolk resulting from DTP-enriched diets, contained lower amounts of cholesterol (14 to 17mg/g) and triglyceride (188mg/g) compared to the control group (22 and 241 mg/g, respectively) (P

Capacity Enhancement in Wireless Networks using Directional Antennas

One of the biggest drawbacks of the wireless environment is the limited bandwidth. However, the users sharing this limited bandwidth have been increasing considerably. SDMA technique which entails using directional antennas allows to increase the capacity of a wireless network by separating users in the medium. In this paper, it has been presented how the capacity can be enhanced while the mean delay is reduced by using directional antennas in wireless networks employing TDMA/FDD MAC. Computer modeling and simulation of the wireless system studied are realized using OPNET Modeler. Preliminary simulation results are presented and the performance of the model using directional antennas is evaluated and compared consistently with the one using omnidirectional antennas.

Leaf Chlorophyll of Corn, Sweet basil and Borage under Intercropping System in Weed Interference

Intercropping is one of the sustainable agricultural factors. The SPAD meter can be used to predict nitrogen index reliably, it may also be a useful tool for assessing the relative impact of weeds on crops. In order to study the effect of weeds on SPAD in corn (Zea mays L.), sweet basil (Ocimum basilicum L.) and borage (Borago officinalis L.) in intercropping system, a factorial experiment was conducted in three replications in 2011. Experimental factors were included intercropping of corn with sweet basil and borage in different ratios (100:0, 75:25, 50:50, 25:75 and 0:100 corn: borage or sweet basil) and weed infestation (weed control and weed interference). The results showed that intercropping of corn with sweet basil and borage increased the SPAD value of corn compare to monoculture in weed interference condition. Sweet basil SPAD value in weed control treatments (43.66) was more than weed interference treatments (40.17). Corn could increase the borage SPAD value compare to monoculture in weed interference treatments.

Evolutionary Approach for Automated Discovery of Censored Production Rules

In the recent past, there has been an increasing interest in applying evolutionary methods to Knowledge Discovery in Databases (KDD) and a number of successful applications of Genetic Algorithms (GA) and Genetic Programming (GP) to KDD have been demonstrated. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski & Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations, in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the 'If P Then D' part of the CPR expresses important information, while the Unless C part acts only as a switch and changes the polarity of D to ~D. This paper presents a classification algorithm based on evolutionary approach that discovers comprehensible rules with exceptions in the form of CPRs. The proposed approach has flexible chromosome encoding, where each chromosome corresponds to a CPR. Appropriate genetic operators are suggested and a fitness function is proposed that incorporates the basic constraints on CPRs. Experimental results are presented to demonstrate the performance of the proposed algorithm.

Blind Channel Estimation Based on URV Decomposition Technique for Uplink of MC-CDMA

In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity.

The Analysis of the Software Industry in Thailand

The software industry has been considered a critical infrastructure for any nation. Several studies have indicated that national competitiveness increasingly depends upon Information and Communication Technology (ICT), and software is one of the major components of ICT, important for both large and small enterprises. Even though there has been strong growth in the software industry in Thailand, the industry has faced many challenges and problems that need to be resolved. For example, the amount of pirated software has been rising, and Thailand still has a large gap in the digital divide. Additionally, the adoption among SMEs has been slow. This paper investigates various issues in the software industry in Thailand, using information acquired through analysis of secondary sources, observation, and focus groups. The results of this study can be used as “lessons learned" for the development of the software industry in any developing country.

Investigation on Adjustable Mirror Bender Using Light Beam Size

In this research, the use of light beam size to design the adjustable mirror bender is presented. The focused beam line characterized by its size towards the synchrotron light beam line is investigated. The COSMOSWorks is used in all simulation components of curvature adjustment system to analyze in finite element method. The results based on simulation covers the use of applied forces during adjustment of the mirror radius are presented.

A High Performance Technique in Harmonic Omitting Based on Predictive Current Control of a Shunt Active Power Filter

The perfect operation of common Active Filters is depended on accuracy of identification system distortion. Also, using a suitable method in current injection and reactive power compensation, leads to increased filter performance. Due to this fact, this paper presents a method based on predictive current control theory in shunt active filter applications. The harmonics of the load current is identified by using o–d–q reference frame on load current and eliminating the DC part of d–q components. Then, the rest of these components deliver to predictive current controller as a Threephase reference current by using Park inverse transformation. System is modeled in discreet time domain. The proposed method has been tested using MATLAB model for a nonlinear load (with Total Harmonic Distortion=20%). The simulation results indicate that the proposed filter leads to flowing a sinusoidal current (THD=0.15%) through the source. In addition, the results show that the filter tracks the reference current accurately.

A Microscopic Simulation Model for Earthmoving Operations

Earthmoving operations are a major part of many construction projects. Because of the complexity and fast-changing environment of such operations, the planning and estimating are crucial on both planning and operational levels. This paper presents the framework ofa microscopic discrete-event simulation system for modeling earthmoving operations and conducting productivity estimations on an operational level.A prototype has been developed to demonstrate the applicability of the proposed framework, and this simulation system is presented via a case study based on an actual earthmoving project. The case study shows that the proposed simulation model is capable of evaluating alternative operating strategies and resource utilization at a very detailed level.

Solving Part Type Selection and Loading Problem in Flexible Manufacturing System Using Real Coded Genetic Algorithms – Part I: Modeling

This paper and its companion (Part 2) deal with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system-s efficiency and productivity. The complexity of the problems is harder when flexibilities of operations such as the possibility of operation processed on alternative machines with alternative tools are considered. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. These real numbers can be converted into part type sequence and machines that are used to process the part types. This first part of the papers focuses on the modeling of the problems and discussing how the novel chromosome representation can be applied to solve the problems. The second part will discuss the effectiveness of the RCGA to solve various test bed problems.

Quasi Multi-Pulse Back-to-Back Static Synchronous Compensator Employing Line Frequency Switching 2-Level GTO Inverters

Back-to-back static synchronous compensator (BtBSTATCOM) consists of two back-to-back voltage-source converters (VSC) with a common DC link in a substation. This configuration extends the capabilities of conventional STATCOM that bidirectional active power transfer from one bus to another is possible. In this paper, VSCs are designed in quasi multi-pulse form in which GTOs are triggered only once per cycle in PSCAD/EMTDC. The design details of VSCs as well as gate switching circuits and controllers are fully represented. Regulation modes of BtBSTATCOM are verified and tested on a multi-machine power system through different simulation cases. The results presented in the form of typical time responses show that practical PI controllers are almost robust and stable in case of start-up, set-point change, and line faults.

Identifying Significant Factors of Brick Laying Process through Design of Experiment and Computer Simulation: A Case Study

Improving performance measures in the construction processes has been a major concern for managers and decision makers in the industry. They seek for ways to recognize the key factors which have the largest effect on the process. Identifying such factors can guide them to focus on the right parts of the process in order to gain the best possible result. In the present study design of experiment (DOE) has been applied to a computer simulation model of brick laying process to determine significant factors while productivity has been chosen as the response of the experiment. To this end, four controllable factors and their interaction have been experimented and the best factor level has been calculated for each one. The results indicate that three factors, namely, labor of brick, labor of mortar and inter arrival time of mortar along with interaction of labor of brick and labor of mortar are significant.

The Residual Effects of Different Doses of Atrazine+Alachlor and Foramsulfuron on the Growth and Physiology of Rapeseed (Brassica napus L.)

A pot experiment was carried out under controlled conditions to evaluate the residual effects of different doses of atrazine+alachlor and foramsulfuron used in corn fields on the growth and physiology of rapeseed (Brassica napus L.). A split-plot experiment in CRD with 4 replications was used. The main plots consisted of herbicide type (atrazine+alachlor mixture and foramsulfuron) and the sub-plots were different residual doses of the herbicides (0, 1%, 5%, 10%, 20%, 40%, 50% and 100%). 7 cm diameter pots were filled with a virgin soil and seeds of rapeseed cv. Hayola were planted in them. The pots were kept under controlled conditions for 8 weeks after germination. At harvest, the growth parameters and the chlorophyll contents of the leaves were determined. The results showed that the growth of rapeseed plants was completely prevented at the highest residual doses of the herbicides (50 and 100 %). The growth parameters of rapeseed plants were affected by all doses of both types of the herbicide as compared to the controls. The residual effects of atrazine+alachlor mixture in reducing the growth parameters of rapeseed were more pronounced as compared to the residual effects of foramsulfuron alone.

Investigating Simple Multipath Compensation for Frequency Modulated Signals at Lower Frequencies

Radio propagation from point-to-point is affected by the physical channel in many ways. A signal arriving at a destination travels through a number of different paths which are referred to as multi-paths. Research in this area of wireless communications has progressed well over the years with the research taking different angles of focus. By this is meant that some researchers focus on ways of reducing or eluding Multipath effects whilst others focus on ways of mitigating the effects of Multipath through compensation schemes. Baseband processing is seen as one field of signal processing that is cardinal to the advancement of software defined radio technology. This has led to wide research into the carrying out certain algorithms at baseband. This paper considers compensating for Multipath for Frequency Modulated signals. The compensation process is carried out at Radio frequency (RF) and at Quadrature baseband (QBB) and the results are compared. Simulations are carried out using MatLab so as to show the benefits of working at lower QBB frequencies than at RF.

An Adaptive Model for Blind Image Restoration using Bayesian Approach

Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.

Characterization and Development of Anthropomorphic Phantoms Liver for Use in Nuclear Medicine

The objective this study was to characterize and develop anthropomorphic liver phantoms in tomography hepatic procedures for quality control and improvement professionals in nuclear medicine. For the conformation of the anthropomorphic phantom was used in plaster and acrylic. We constructed three phantoms representing processes with liver cirrhosis. The phantoms were filled with 99mTc diluted with water to obtain the scintigraphic images. Tomography images were analyzed anterior and posterior phantom representing a body with a greater degree cirrhotic. It was noted that the phantoms allow the acquisition of images similar to real liver with cirrhosis. Simulations of hemangiomas may contribute to continued professional education of nuclear medicine, on the question of image acquisition, allowing of the study parameters such of the matrix, energy window and count statistics.