Multi-Criteria Wildfire Risk Hazard Assessment in GIS Environment: Projection for the Future and Impact on RES Projects Installation Planning

It is alarming for the fact that Wildfires number, severity and consequently impact have significantly increased during the last years, an aftermath of the Climate Change. One of the most affected areas worldwide is Mediterranean, due to the unique combination of its type of vegetation and demanding climatic conditions. This research is focused on the Region of Epirus in Greece, an area with significant natural vegetation and a range of geomorphological aspects. In order to estimate the Wildfire Risk Hazard, several factors have been used: geomorphological (slope, aspect, elevation, TWI, Hydrographic network), social (Settlements and landfils, roads, overhead lines and substations), environmental (land cover) and climatic (Fire Weather Index). Through a multi-criteria decision analysis (MCDA) and an analytic hierarchy process (AHP) in a GIS environment, the Wildfire Risk Hazard has been estimated not only for current conditions but also for future projections for the near future (2031-2060) and the far future (2071-2100). The selected case study includes the potential impact of the Wildfires to the installed (or targeted to be installed) RES projects in the studied region.

MULTI-PERIODIC COLLISIONAL PROCESS BETWEEN INDIAN AND ASIAN CONTINENTS:A CASE OF EASTERN HIMALAYAN SYNTAXIS AND HENGDUAN MOUNTAINS

Our study area covered the Eastern Himalayan Syntaxis (EHS) and its southern extension (Hengduan Mountain or western Sichuan and Yunnan (WSY)) which is located at the orthogonal and oblique collisional front between Indian and Asian continents during Cenozoic.Based on geometric and kinematic mapping of the major boundary or regional faults (Dongjug—Mainling(1), Anigiao(2) and Jali(3), Guyu(4) faults in EHS, Ailaoshan—Red River(5), Lancangjiang(6), Gaoligong(7), Binlangjiang(8) and Magok(9) faults in WSY) (see Fig.1), especially on abundant geochronological dating of the mylonitic rocks along these faults, and coupled with magmato\|metamorphic sequences of this region, we try to deal with the temporal and spatial relationships of collisional process to answer questions such as: (1) when did collision start ? (2) is thrusting as a initial and dominant deformation mode to absorb the crustal shortening after suturing, or earlier thrusting usually followed by large\|scale strike\|slip faults? (3) are the two structural patterns coeval at times, or do they occur alternatively during deformation history? (4) are the collisional and associate uplift processes a continuous one or periodic? Insight into such questions is crucial for better understanding of the continental deformation and testing the models available or constraining a new one.

Training of Multi-layered Neural Network for Data Enlargement Processing Using an Activity Function

In this paper, we present a study on activity functions for an MLNN (multi-layered neural network) and propose a suitable activity function for data enlargement processing. We have carefully studied the training performance of Sigmoid, ReLu, Leaky-ReLu and L & exp. activity functions for few inputs to multiple output training patterns. Our MLNNs model has L hidden layers with two or three inputs to four or six outputs data variations by BP (backpropagation) NN (neural network) training. We focused on the multi teacher training signals to investigate and evaluate the training performance in MLNNs to select the best and good activity function for data enlargement and hence could be applicable for image and signal processing (synaptic divergence) along with the proposed methods with convolution networks. We specifically used four activity functions from which we found out that L & exp. activity function can suite DENN (data enlargement neural network) training since it could give the highest percentage training abilities compared to the other activity functions of Sigmoid, ReLu and Leaky-ReLu during simulation and training of data in the network. And finally, we recommend L & exp. function to be good for MLNNs and may be applicable for signal processing of data and information enlargement because of its performance training characteristics with multiple teacher training patterns using original generated data and hence can be tried with CNN (convolution neural networks) of image processing.

MULTI-AGENT BASED DISTRIBUTED PROCESS PLANNING MANAGEMENT

A distributed process planning system based on autonomous multi agent system to solve a distributed process plan task in a manufacturing environment was presented. A distributed agent based process plan structure was shown to be a viable alternative to hierarchical systems providing real time response to shop floor condition. An outline was done to show how to structure a distributed process plan and how its management may be achieved among manufacturers of parts that form a product. Communication between the agents involved in a distributed process planning was also shown to be important, with the controlling agent having an overall supervision of the plans. Based on the reference model a software tool was developed to realize it.

The multi-factor recombination and processes superimposition model for hydrocarbon accumulation:application to the Silurian in the Tarim Basin

The multi-factor recombination and processes superimposition model for hydrocarbon accumulation is put forward in view of the hydrocarbon geological characteristics of multiple episodes of structural evolution, multiple sets of source-reservoir-seal assemblage, multiple cycles of hydrocarbon accumulation and multiple episodes of readjustment and reconstruction in the complex superimposed basins in China. It is a system including theories and methods that can help to predict favorable exploration regions. According to this model, the basic discipline for hydrocarbon generation, evolution and distribution in the superimposed basins can be summarized in multi-factor recombination, processes superimposition, multiple stages of oil filling and latest stage preservation. With the Silurian of the Tarim basin as an example, based on the reconstruction of the evolution history of the four factors （paleo-anticline, source rock, regional cap rock and kinematic equilibrium belt） controlling hydrocarbon accumulation, this model was adopted to predict favorable hydrocarbon accumulation areas and favorable exploration regions following structural destruction in three stages of oil filling, to provide guidance for further exploration ofoil and gas in the Silurian of the Tarim basin.

MULTI-AGENT COMPUTER AIDED ASSEMBLY PROCESS PLANNING SYSTEM FOR SHIP HULL

A multi agent computer aided assembly process planning system (MCAAPP) for ship hull is presented. The system includes system framework, global facilitator, the macro agent structure, agent communication language, agent oriented programming language, knowledge representation and reasoning strategy. The system can produce the technological file and technological quota, which can satisfy the production needs of factory.

FE simulation and process analysis on forming of aluminum alloy multi-layer cylinder parts with flow control forming

The aluminum alloy parts used in airbag of car were studied with flow control forming(FCF) method, which was a good way to low forming force and better mechanical properties. The key technology of FCF was the design of control chamber to divide metal flow. So, the design method of FCF was analyzed and two type of control chamber were put forward. According to divisional principle, calculation model of forming force and approximate formula were given. Then forming process of aluminum alloy multi-layer cylinder parts was simulated. The effect of friction factor, die radius and punch velocity on metal flow and forming force was obtained. Finally, the experiment was preformed under the direction of theory and finite element(FE) simulation results. And the qualified parts were manufactured. The simulation data and experimental results show that the forming sequence of inner wall and outer wall, and then the force step, can be controlled by adjusting the process parameters. And the FCF technology proposed has very important application value in precision forging.

Multi-objective optimization of process parametersduring low-pressure die casting of AZ91Dmagnesium alloy wheel castings

Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosity, while reducing the secondary dendritic arm spacing of a wheel casting during low-pressure die casting(LPDC) process, was taken as an example of such problem. A commercial simulation software Pro CASTTM was applied to simulate the filling and solidification processes. Additionally, a program for integrating the optimization algorithm with numerical simulation was developed based on SiPESC. By setting pouring temperature and filling pressure as design variables, shrinkage porosity and secondary dendritic arm spacing as objective variables, the multi-objective optimization of minimum volume of shrinkage porosity and secondary dendritic arm spacing was achieved. The optimal combination of AZ91 D wheel casting was: pouring temperature 689 °C and filling pressure 6.5 kPa. The predicted values decreased from 4.1% to 2.1% for shrinkage porosity, and 88.5 μm to 81.2 μm for the secondary dendritic arm spacing. The optimal results proved the feasibility of the developed program in multi-objective optimization.

Pollutant mixing and transport process via diverse transverse release positions in a multi-anabranch river with three braid bars

A multi-anabranch river with three braid bars is a typical river pattern in nature, but no studies have been conducted to describe mixing characteristics of pollutants in the river. In this study, a physical model of a typical multi-anabranch river with three braid bars was established to explore the pollutant mixing characteristics in different branches. The multi-anabranch reach was separated into seven branches, B1, B2, B3, B4, B5, B6, and BT, by three braid bars. Five tracer release positions located 2.9 m upstream from the inlet section of the multi-anabranch reach were adopted, and the distances from the five positions to the left bank of the upstream main channel were 1/6B, 1/3B, 1/2B, 2/3B, and 5/6B （B is the width of the upstream main channel）, respectively. The longitudinal velocities and pollutant concentrations in the seven branches were measured. The planar flow field and mixing characteristics of pollutants from the bottom to the surface in the multi-anabranch river were obtained and analyzed. The results show that the pollutant release positions are the main influencing factors in the pollutant transport process, and the diversion points and pollutant release positions jointly influence the percentage ratios of the pollutant fluxes in branches B 1, B2, and B3 to the pollutant flux in the upstream main channel.

A Multi-Scale Study on Silicon-Oxide Etching Processes in C_4F_8/Ar Plasmas

A multi-scale numerical method coupled with the reactor,sheath and trench model is constructed to simulate dry etching of SiO_2 in inductively coupled C_4F_8 plasmas.Firstly,ion and neutral particle densities in the reactor are decided using the CFD-ACE＋ commercial software.Then,the ion energy and angular distributions（IEDs and IADs） are obtained in the sheath model with the sheath boundary conditions provided with CFD-ACE＋.Finally,the trench profile evolution is simulated in the trench model.What we principally focus on is the effects of the discharge parameters on the etching results.It is found that the discharge parameters,including discharge pressure,radio-frequency（rf） power,gas mixture ratios,bias voltage and frequency,have synergistic effects on IEDs and IADs on the etched material surface,thus further affecting the trench profiles evolution.

Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks

In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a ＂global＂ nonlinear long-range prediction model through the fuzzy conjunction of a number of ＂local＂ linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.

Coating process of multi-material composite sand mold 3D printing

Sand mold 3 D printing technology is an advanced manufacturing technology which has great flexible manufacturing ability. A multi-material composite sand mold can control the temperature field of metallic parts during the pouring process, while the current sand mold 3 D printing technology can only fabricate a single material sand mold. The casting temperature field can not be adjusted by using single sand mold material with isotropous heat exchange ability during the pouring process. In this work, a kind of novel coating device was designed. Multi-material composite sand molds could be manufactured using the coating device according to the casting process demands of the final parts. The influences of curing agent content, coating velocity and scraper shape on compactness and surface roughness of the sand layer(silica sand and zircon sand) were studied. The shapes and sizes of transition intervals of two kinds of sand granules were also tested. The results show that, with the increase of the added volume of curing agent, the compactness of sand layer reduces and the surface roughness value rises. With the increase of the velocity of the coating device, the compactness of sand layer reduces and the surface roughness value rises similarly. In addition, the scraper with a dip angle of 72 degrees could increase the compactness value of the sand layer. The criteria of quality parmeters of the coating procedure are obtained. That is, the surface roughness(δ) of sand layer should be equal to or lesser than half of main size of the sand particles(Dm). The parameter H of the coating device which is the distance between the base of hopper and the surface of sand layer impacts the size of transition zone. The width of the transition zone is in direct proportion to the parameter H, qualitatively. Through the optimization of the coating device, high quality of multi-material sand layers can be obtained. This will provide a solution in manufacturing the multi-material composite sand mold.

Integrated Building Envelope Design Process Combining Parametric Modelling and Multi-Objective Optimization

As an important element in sustainable building design, the building envelope has been witnessing a constant shift in the design approach. Integrating multi-objective optimization (MOO) into the building envelope design process is very promising, but not easy to realize in an actual project due to several factors, including the complexity of optimization model construction, lack of a dynamic-visualization capacity in the simulation tools and consideration of how to match the optimization with the actual design process. To overcome these difficulties, this study constructed an integrated building envelope design process (IBEDP) based on parametric modelling, which was implemented using Grasshopper platform and interfaces to control the simulation software and optimization algorithm. A railway station was selected as a case study for applying the proposed IBEDP, which also utilized a grid-based variable design approach to achieve flexible optimum fenestrations. To facilitate the stepwise design process, a novel strategy was proposed with a two-step optimization, which optimized various categories of variables separately. Compared with a one-step optimization, though the proposed strategy performed poorly in the diversity of solutions, the quantitative assessment of the qualities of Pareto-optimum solution sets illustrates that it is superior. © 2016, Tianjin University and Springer-Verlag Berlin Heidelberg.

Microstructure and mechanical properties of Al-Si-Ni coating on Cu-Cr substrate prepared by multi-permeation and friction stir processing

The surface of copper-chromium alloy was processed by Al-Si-Ni multi-permeation and friction stir processing,and the microstructure and mechanical properties of the surface layer were tested by scanning electron microscopy(SEM),energy dispersive spectroscopy(EDS),microhardness tester and friction testing machine.The results show that Al,Si and Ni elements are fully permeated into the surface of copper-chromium alloy after multielement co-infiltration and friction stir processing.In the observation of the microstructures,we found that the reticular structure is fragmented and distributed in the stir zone region.Microstructure becomes finer and grains refinement.The micro hardness of the copper-chromium alloy increased to 129 HV,44.9%higher than that of the original matrix.The main reasons of microhardness enhancement are solid solution strengthening,fine grains strengthening and dispersion strengthening.The friction test results show that the friction coefficient is basically stable at 0.69 and the wear mass is only 0.0017 g after 10 min of friction test.The improvement of wear resistance was attributed to the increase of microhardness of the alloy surface.

Analysis of the Multi-Pivot Quicksort Process

In this paper, we study a new version from Dual-pivot Quicksort algorithm when we have some other number of pivots. Hence, we discuss the idea of picking pivots ?by random way and splitting the list simultaneously according to these. The modified version generalizes these results for multi process. We show that the average number of swaps done by Multi-pivot Quicksort process and we present a special case. Moreover, we obtain a relationship between the average number of swaps of Multi-pivot Quicksort and Stirling numbers of the first kind.

Existence and joint continuity of local time of multi-parameter fractional Lévy processes

In this paper, we introduce the definition of a multi-parameter fractional Lévy process and its local time, and show its decomposition. Using the decomposition, we prove existence and joint continuity of its local time.

Study on Multi-enterprise Collaborative Resource Planning Based Process-oriented Decision Model

Aiming to share the information,knowledge and optimizing resource via collaborating with multiple external partners across their supply chains,the concept model and system framework of multi-enterprises collaborative resource planning (MECORP) are put forward.While there is Considerable pressure to improve the operation of MECORP system,their inherent complexity can make modelling a MECORP system a difficult task.Yet there could be considerable benefits in designing MECORP taking into account the operation of the system.In order to address the central research issue of developing of a methodology that can assist a manager in making decisions by modelling the operation of MECORP system.The methodology called process-oriented deci- sion model (PODM) is presented in the paper.This uses an abstracted network to model MECORP system.The MECORP system supported by PODM,can effective optimize the manifold resource,coordinate the relationship of multiple partners and assist deci- sion.Finally,an industry excample of MECORP system is described to illustrate the application of PODM.

Multi-Agent Deep Reinforcement Learning for Cross-Layer Scheduling in Mobile Ad-Hoc Networks

Due to the fading characteristics of wireless channels and the burstiness of data traffic,how to deal with congestion in Ad-hoc networks with effective algorithms is still open and challenging.In this paper,we focus on enabling congestion control to minimize network transmission delays through flexible power control.To effectively solve the congestion problem,we propose a distributed cross-layer scheduling algorithm,which is empowered by graph-based multi-agent deep reinforcement learning.The transmit power is adaptively adjusted in real-time by our algorithm based only on local information(i.e.,channel state information and queue length)and local communication(i.e.,information exchanged with neighbors).Moreover,the training complexity of the algorithm is low due to the regional cooperation based on the graph attention network.In the evaluation,we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states,and demonstrate the adaptability and stability in different topologies.The method is general and can be extended to various types of topologies.

MULTI-SCALES RELAXATION PROCESSES OF SHORT FIBER OF NEMATIC LIQUID CRYSTALLINE COPOLYMER IN POLYCARBONATE MATRIX

Multi-scales relaxation processes of short fiber of a nematic liquid crystalline copolymer(LCP)in polycarbonate matrix were investigated.First,the structure relaxation of LCP was studied by rheology.The relaxation spectrum of the nematic liquid crystalline copolymer at 295℃was calculated from the combined dynamic modulus.There are three kinds of relaxation mechanisms for nematic liquid crystalline copotymer:the relaxation of chain orientation,the relaxation of deformed polydomains and the coalescence of pol...

Real-time Parallel Processing System Design and Implementation for Underwater Acoustic Communication Based on Multiple Processors

ADSP-TS101 is a high performance DSP with good properties of parallel processing and high speed.According to the real-time processing requirements of underwater acoustic communication algorithms,a real-time parallel processing system with multi-channel synchronous sample,which is composed of multiple ADSP-TS101s,is designed and carried out.For the hardware design,field programmable gate array(FPGA)logical control is adopted for the design of multi-channel synchronous sample module and cluster/data flow associated pin connection mode is adopted for multiprocessing parallel processing configuration respectively.And the software is optimized by two kinds of communication ways:broadcast writing way through shared bus and point-to-point way through link ports.Through the whole system installation,connective debugging,and experiments in a lake,the results show that the real-time parallel processing system has good stability and real-time processing capability and meets the technical design requirements of real-time processing.