Estimation of fouling in a plate heat exchanger through the application of neural networks

Pasteurization is an important, if not the most important, process step in the packaging of milk. It is subject to alterations stemming from the variation in the temperature, pH and raw milk quality. The variability may manifest itself in changes in the formation of the deposit (fouling) in the pasteurization unit, such that there is a need for tools, both instrumentation and computational, to help in monitoring the process and keeping it on the desired course. In this paper we describe a practical procedure based on artificial neural networks (ANN) that allows prediction of the deposit thickness, the overall heat transfer coefficient and the critical time (the time that the unit has to be stopped for cleaning) for reducing the impact of fouling on such processes. The procedure determines when the cleaning operation is required once the system is under critical conditions of operations. A combination of fundamental studies and plant measurements were used for study of the operating conditions and thus evaluation of the trades‐offs between operating conditions and longer operating life span. The results are encouraging, enough to validate current operating industrial techniques. Copyright © 2005 Society of Chemical Industry     

Coalgebra morphisms subsume open maps

We relate two abstract notions of bisimulation, induced by open maps and by coalgebra morphisms, respectively. We show that open maps correspond to coalgebra morphisms for a suitable chosen endofunctor in a category of many sorted sets. This demonstrates that the notion of open-maps bisimilarity is of essentially coalgebraic nature. A central role in our development is played by a category of presheaves, which we show as corresponding to the subcategory of consistent coalgebras with lax cohomomorphisms.     

A dynamic linear programming approach to market allocation of renewable resources in the italian energy system: The case of solar thermal and biogas technologies

In Italy solar thermal energy and energy from biogas are two possible means of reducing dependence on energy imports. Using a multiperiod LP model (MARKAL) the authors assessed the likely potential of both technologies under various circumstances. The study covered the period 1980–2005, in five segments of five years. It focused only on the subsystem of the energy end-uses which can be substituted for by solar thermal and biogas technologies. The overall non-renewable sources which can be saved in 20 years by these technologies total 450 PJ (1 PJ = 10^{1 5} J) if the fuel prices rise at 0 per cent average annual, 1450 PJ if the fuel prices rise at 4.2 per cent average annual, 1860 PJ if the fuel prices rise at 7.2 per cent average annual and 3780 PJ if the fuel prices rise at 15 per cent average annual. However the most competitive technologies appear to be solar water heaters used mainly in the private and commercial sectors and biogas systems used mainly in the agricultural sector. The study was carried out by APRE under ENEA (formerly CNEN) contract and was intended to serve as an analytical basis for establishing an overall development and demonstration strategy for end-use renewable technologies in Italy.     

Residual Stress Simulation of Injection Molding

In this study, distribution and history of residual stresses in plaque-like geometries are simulated based on linear thermoviscoelastic model, which helps to understand the mechanics and evolution of the residual stresses in the injection molding process. The numerical calculation of direction, combined with the specified boundary conditions. Results show that the stress variation across the thickness exhibits a high surface tensile value changing to a compressive peak value close to the surface, with the core region experiencing a parabolic tensile peak. Residual stress distribution throughout the thickness is almost same along the flowpath and the final residual stresses value near the gate is lower than the value near the end of flowpath.     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Identification of gaps in mangrove forests with airborne LIDAR

Mangrove forests change frequently due to disturbances from tropical storms, frost, lightning, and insects. It has been suggested that the death and regeneration of trees in small gaps due to lightning may play a critical role in mangrove forest turnover; however, the large-scale quantification of spatial pattern and areas of gaps is lacking for investigating this issue. Airborne light detection and ranging (LIDAR) technology provides an effective way for identifying gaps by remotely obtaining direct measurements of ground and canopy elevations. A method based on an alternative sequential filter and black top-hat mathematical morphological transformation was developed to extract gap features. Comparison of identified gap polygons with raw LIDAR measurements and field surveys shows that the proposed method successfully extracted gap features in mangrove forests in Everglades National Park. There are 400–500 lightning gaps per square kilometer in mangrove forests at the study sites. The distribution of gap sizes follows an exponential form and the area of gaps with sizes larger than 100 m² account for 55–61% of the total area of gaps. The area of gaps in the mangrove forest in Everglades National Park is about 4–5% of the total forest area and the average gap formation rate is about 0.3% of the total forest area per year, indicating that lightning gaps play an important role in mangrove forest dynamics.     

Performance analysis of IEEE 802.11 ad hoc networks in the presence of exposed terminals

The paper evaluates the performance effects of exposed terminals in IEEE 802.11 ad hoc networks in finite load conditions. It derives analytical models for the estimation of channel utilization and media access delay for IEEE 802.11 ad hoc networks in finite load conditions with and without exposed terminals. The simulation results show that the analytical estimated channel utilization and media access delay metrics are fairly accurate.     

雷达仿真系统中电磁干扰环境的仿真设计和实施

雷达仿真系统是为检测雷达设备的抗干扰能力以及在各种电磁环境下的工作性能而设计的，包括有源干扰和无源干扰的模拟仿真。本文阐述了无源干扰即杂波的散射模型和仿真过程；从同步脉冲干扰的基本原理出发，阐明在雷达工作环境仿真系统中距离拖引、速度拖引、虚假目标等同步脉冲有源干扰的设计和实施过程；并针对工作在搜索和跟踪交替模式下的相控阵雷达提出自适应综合干扰方式；最后分析并总结了系统仿真时为真实、有效地模拟电磁干扰环境应注意的关键问题。     

多孔挡板流化床还原UO3反应器模型的研究

针对ＵＯ＿３的Ｎ＿２还原反应建立了多孔挡板流化床反应器模型。将多孔挡板床的每一级视为具有相似的流动状态，每一级的上、下段称为稀、密相段，分别用鼓泡床和活塞流模型描述。该模型的计算值与￠６３ｍｍ的多孔挡板床Ｈ＿２还原ＵＯ＿３的热态实验值能较好的吻合。还预计了还原温度、操作气速和挡板结构参数对固相转化率的影响，为该类反应器的工业设计、放大和优化提供了依据。