Effect of Sweptback Angle of a Delta Wing on Surface Pressure Distribution at Supersonic Mach Numbers

The purpose of this work is to shed light on the effect of the pivot position on the surface pressure distribution over a 3D wing in different flight conditions.The study is intended to support the design and development of aerospace vehicles where stability analysis,performance optimization,and aircraft design are of primary importance.The following parameters are considered:Mach numbers(M)of 1.3,1.8,2.3,2.8,3.3,and 3.8,angle of incidence(θ)in the range from 5°to 25°,pivot position from h=0.2 to 1.The results of the CFD numerical simulations match available analytical data,thereby providing evidence for the reliability of the used approach.The findings provide valuable insights into the relationship between the surface pressure distribution,the Mach number and the angle of incidence.

Application of Evolution Sequential Number Theoretic Optimization in Global Optimization

Synthesis of chemical processes is of non-convex and multi-modal. Deterministic strategies often fail to find global optimum within reasonable time scales. Stochastic methodologies generally approach global solution in probability. In recogniting the state of art status in the discipline, a new approach for global optimization of processes, based on sequential number theoretic optimization (SNTO), is proposed. In this approach, subspaces and feasible points are derived from uniformly scattered points, and iterations over passing the corner of local optimum are enhanced via parallel strategy. The efficiency of the approach proposed is verified by results obtained from various case studies.

Alternative Method of Constructing Granular Neural Networks

Utilizing granular computing to enhance artificial neural network architecture, a newtype of network emerges—thegranular neural network (GNN). GNNs offer distinct advantages over their traditional counterparts: The ability toprocess both numerical and granular data, leading to improved interpretability. This paper proposes a novel designmethod for constructing GNNs, drawing inspiration from existing interval-valued neural networks built uponNNNs. However, unlike the proposed algorithm in this work, which employs interval values or triangular fuzzynumbers for connections, existing methods rely on a pre-defined numerical network. This new method utilizesa uniform distribution of information granularity to granulate connections with unknown parameters, resultingin independent GNN structures. To quantify the granularity output of the network, the product of two commonperformance indices is adopted: The coverage of numerical data and the specificity of information granules.Optimizing this combined performance index helps determine the optimal parameters for the network. Finally,the paper presents the complete model construction and validates its feasibility through experiments on datasetsfrom the UCIMachine Learning Repository. The results demonstrate the proposed algorithm’s effectiveness andpromising performance.

OPTIMAL BIRKHOFF INTERPOLATION AND BIRKHOFF NUMBERS IN SOME FUNCTION SPACES

This paper investigates the optimal Birkhoff interpolation and Birkhoff numbers of some function spaces in space L∞[-1,1]and weighted spaces Lp,ω[-1,1],1≤p<∞,with w being a continuous integrable weight function in(-1,1).We proved that the Lagrange interpolation algorithms based on the zeros of some polynomials are optimal.We also show that the Lagrange interpolation algorithms based on the zeros of some polynomials are optimal when the function values of the two endpoints are included in the interpolation systems.

An Adaptive Parameter-Free Optimal Number of Market Segments Estimation Algorithm Based on a New Internal Validity Index

An appropriate optimal number of market segments(ONS)estimation is essential for an enterprise to achieve successful market segmentation,but at present,there is a serious lack of attention to this issue in market segmentation.In our study,an independent adaptive ONS estimation method BWCON-NSDK-means++is proposed by integrating a newinternal validity index(IVI)Between-Within-Connectivity(BWCON)and a newstable clustering algorithmNatural-SDK-means++(NSDK-means++)in a novel way.First,to complete the evaluation dimensions of the existing IVIs,we designed a connectivity formula based on the neighbor relationship and proposed the BWCON by integrating the connectivity with other two commonly considered measures of compactness and separation.Then,considering the stability,number of parameters and clustering performance,we proposed the NSDK-means++to participate in the integrationwhere the natural neighbor was used to optimize the initial cluster centers(ICCs)determination strategy in the SDK-means++.At last,to ensure the objectivity of the estimatedONS,we designed a BWCON-based ONS estimation framework that does not require the user to set any parameters in advance and integrated the NSDK-means++into this framework forming a practical ONS estimation tool BWCON-NSDK-means++.The final experimental results showthat the proposed BWCONand NSDK-means++are significantlymore suitable than their respective existing models to participate in the integration for determining theONS,and the proposed BWCON-NSDK-means++is demonstrably superior to the BWCON-KMA,BWCONMBK,BWCON-KM++,BWCON-RKM++,BWCON-SDKM++,BWCON-Single linkage,BWCON-Complete linkage,BWCON-Average linkage and BWCON-Ward linkage in terms of the ONS estimation.Moreover,as an independentmarket segmentation tool,the BWCON-NSDK-means++also outperforms the existing models with respect to the inter-market differentiation and sub-market size.

Multi-Objective Optimization of Traffic Signal Timing at Typical Junctions Based on Genetic Algorithms

With the rapid development of urban road traffic and the increasing number of vehicles,how to alleviate traffic congestion is one of the hot issues that need to be urgently addressed in building smart cities.Therefore,in this paper,a nonlinear multi-objective optimization model of urban intersection signal timing based on a Genetic Algorithm was constructed.Specifically,a typical urban intersection was selected as the research object,and drivers’acceleration habits were taken into account.What’s more,the shortest average delay time,the least average number of stops,and the maximum capacity of the intersection were regarded as the optimization objectives.The optimization results show that compared with the Webster method when the vehicle speed is 60 km/h and the acceleration is 2.5 m/s^(2),the signal intersection timing scheme based on the proposed Genetic Algorithm multi-objective optimization reduces the intersection signal cycle time by 14.6%,the average vehicle delay time by 12.9%,the capacity by 16.2%,and the average number of vehicles stop by 0.4%.To verify the simulation results,the authors imported the optimized timing scheme into the constructed Simulation of the Urban Mobility model.The experimental results show that the authors optimized timing scheme is superior to Webster’s in terms of vehicle average loss time reduction,carbon monoxide emission,particulate matter emission,and vehicle fuel consumption.The research in this paper provides a basis for Genetic algorithms in traffic signal control.

Optimization of Crude Distillation Unit Case Study of the Port Harcourt Refining Company

An HYSYS model for the crude distillation unit of the Port Harcourt Refining Company has been developed. The HYSYS model developed includes 3 mixers, 3 heaters, 1 heat exchanger, 1 desalter (3-phase separator), 2-phase separator and the main fractionating column. The raw crude was characterized using Aspen HYSYS version 8.8 and the developed model was simulated with the industrial plant data from the Port Harcourt Refining Company. The HYSYS model gave component mole fractions of 0.2677, 0.1572, 0.2687, 0.0547, 0.2517 for Naphtha, Kerosene, Light Diesel Oil (LDO), Heavy Diesel Oil (HDO) and Atmospheric Residue and when compared to plant mole fractions of 0.2710, 0.1560, 0.2650, 0.0530, 0.2550 gave a maximum deviation of 3.2%. The HYSYS model was also able to predict the temperature and the tray of withdrawal for Naphtha, Kerosene, Light Diesel Oil (LDO), Heavy Diesel Oil (HDO) and Atmospheric Residue as follows: tray 1 (120°C), tray 12 (206°C), tray 25 (215°C), tray 35 (310°C) and tray 48 (320°C) which was also compared with plant data and gave a maximum deviation 23.2%. The HYSYS model was then optimized using Sequential Quadratic Programming (SQP) with the industrial plant data as starting values of operating conditions. The optimization increased the mass flow rate of Naphtha product from 7.512E+004 kg/hr to 7.656E+004 kg/hr, Kerosene product from 5.183E+004 kg/hr to 5.239E+004 kg/hr, Light Diesel Oil (LDO) product from 1.105E+005 kg/hr to 1.112E+005 kg/hr, Heavy Diesel Oil (HDO) from 2.969E+004 kg/hr to 2.977E+004 kg/hr while the last product being Atm Residue remained at 3.157E+005 kg/hr. The new optimum mole fraction values for the five products were as follows: 0.2713, 0.1540, 0.2635, 0.0528, and 0.2584 while corresponding optimum temperature values were as follows: 129°C, 221°C, 257°C, 317°C and 327°C.

Experimental Study and 3D CFD Analysis on the Optimization of Throttle Angle for a Convergent Vortex Tube

Seven adjustments of convergent-type Vortex Tube （VT） with different throttle angles were applied. The adjustments were made to analyze the influences of such angles on cold and hot temperature drops as well as flow structures inside the VTs. An experimental setup was designed, and tests were performed on different convergent VT configurations at injection pressures ranging from 0.45 to 0.65 MPa. The angles of the throttle valve were arranged between 30° to 90°, and the numbers of injection nozzles ranged between 2 and 6. Laboratory results indicated that the maximum hot and cold temperature drops ranged from 23.24 to 35 K and from 22.87 to 32.88 K, respectively, at four injection nozzles. Results also showed that temperature drop is a function of hot throttle valve angle with the maximum hot and cold temperature drops depending on the angle applied. We used graphs to demonstrate the changes in the cold and hot temperature drops with respect to hot throttle angle values. These values were interpreted and evaluated to determine the optimum angle, which was 60°. The CFD outputs agreed very well with the laboratory results. The proposed CFD results can help future researchers gain good insights into the complicated separation process taking place inside the VTs.

Designing optimal number of receiving traces based on simulation model

Currently, the selection of receiving traces in geometry design is mostly based on the horizontal layered medium hypothesis, which is unable to meet survey requirements in a complex area. This paper estimates the optimal number of receiving traces in field geometry using a numerical simulation based on a field test conducted in previous research （Zhu et al., 2011）. A mathematical model is established for total energy and average efficiency energy using fixed trace spacing and optimal receiving traces are estimated. Seismic data acquired in a complex work area are used to verify the correctness of the proposed method. Results of model data calculations and actual data processing show that results are in agreement. This indicates that the proposed method is reasonable, correct, sufficiently scientific, and can be regarded as a novel method for use in seismic geometry design in complex geological regions.

Study on the extending multi-attribute decision model of grey target

Based on the distance of interval numbers and the two-stage decision methods, this paper expands the decision model of grey target into some situation under which the decision information and target weights are the interval numbers at the same time. It also gives the optimization method of weights in the grey target. We get the optimum coordinated vector utilizing the combination assigning method, based on the local optimization of various schemes. So it can shift the weights of interval number into real number form and sequence it according to the weighted off-target distance. Finally the effectiveness and practicality of the model is proved by a real project.

Modeling and optimization of unbalanced multi-stage logistic system

To decompose an unbalanced multi-stage logistic system to multipleindependent single-stage logistic systems, a new notion of parameterized interface distribution ispresented. For encoding the logistic pattern on each stage, the Pruefer number is used. With theimproved decoding procedure, any Pruefer number produced stochastically can be decoded to a feasiblelogistic pattern, which can match with the capacities of the nodes of the logistic system. Withthese two innovations, a new modeling method based on parameterized interface distribution and thePriifer number coding is put forward. The corresponding genetic algorithm, named as PIP-GA, can findbetter solutions and require less computational time than st-GA. Although requiring a little moreconsumption of memory, PIP-GA is still an efficient and robust method in the modeling andoptimization of unbalanced multi-stage logistic systems.

Lectotype Optimization of Offshore Platforms by Use of Three-Scale Fuzzy Analytical Hierarchy Process

A Three-Scale Fuzzy Analytical Hierarchy Process (T-FAHP) is proposed by introducing the Three-Scale Analytical Hierarchy Process (T-AHP) and the trapezoid fuzzy number. A multi-objective optimization model based on the T-FAHP is presented subsequently, in which many factors influencing the lectotype of offshore platform are taken into account synthetically, such as the original investment, the maintenance, cost, the ability of resisting fatigue and corrosion, the construction period, the threat to the environment, and so on. With this method, the experts can give the relatively precise ranking weight of each index and at the same time the requirement of consistence checking can be met, The result of a calculation example shows that the T-FAHP is practical.

On Spatial Distribution Pattern of Broccoli Clubroot Disease and and the Sampling Technique

[Objective] To further improve the prediction and forecast and continuous control ability of broccoli clubroot disease. [Methods] The spatial distribution pattern of diseased or infected plants was analyzed using the least square method, fre- quency distribution, aggregation index, m＊-m regression analysis and Taylor＇s pow- er law model. [Result] The field distribution of broccoli plants with clubroot disease tended to be aggregated distribution, m＇-m regression analysis showed that the el- ementary composition of the spatial distribution of diseased or infected plants was individual colony, the individuals attracted each other; the disease had obvious dis- ease focus in the field, and the individual colony showed uniform distribution pattern in the field. Taylor＇s power law showed that the spatial pattern of individual dis- eased or infected plant with clubroot disease tended to be uniform distribution with the increase of the density. On the basis of this, Iwao optimal theoretical sampling model and sequential sampling model were established, namely N =273.954 1/m- 59.698 5, To （N）=0.368 4N±1.926 8√N, respectively, it meant that when surveying N plants, if the accumulative incidence rate exceeded upper bound, the field can be set as control object; if the accumulative incidence rate didn＇t reach lower bound, it can be set as uncontrol field; if the accumulative incidence rate was between upper bound and lower bound, it should be surveyed continuously until the maximum sample size （mo=0.368 4） appeared, that was, the disease incidence was 15%, so the sampling number should be 684 plants. [Conclusion] The research results had very important instructive meaning for disease control.

Optimization and Sizing of a Stand-Alone Photovoltaic System and Assessment of Random Load Fluctuation on Power Supply

This study presents an optimization technique and design for a stand-alone photovoltaic (PV) system to provide the required electricity for a single residential household in remote areas. From the basic solar components analysis, the irradiance on tilted surface is derived and compared to that on horizontal surface for Furu-Awa locality to infer the appropriate tilt angle (β) that maximizes the collection of solar energy. Seven optimum values of β applicable to the PV network were then derived depending of the period of the year and this simulation resulted that the panels are to be adjusted seven times a year. The optimization technique for load demand based on total apparent power of the household appliances produces an increase of 18% compared to the simple case of the PV components design using active power but leads to the optimum configuration that meets the real load demand of the household. Following the sizing of the station, reliability tests simulations were conducted for a one year corresponding period to infer the sensitivity of power supply to initial state of charge, to check the system autonomy and to evaluate the effect of random variation of the load on the smooth functioning of the PV system using a pseudo random number generator. This analysis shows that the minimum capacity of the battery for normal run of the Plan is 22.2% and that with random fluctuation of load, there will be periods of the year where the system experiences power failure depending on how important is the variation. The result of the study may imply a small increase in the cost of the entire plant but improves the stability and flexibility of such a station.

Optimization Design for Fixed Table of Gantry Machining Center Based on Sensitivity and Topology Analyses

In order to decrease the deformation and stress and increase the natural frequency of the fixed table,a method of optimization driven by the sensitivity and topology analyses is proposed.The finite element model of the fixed table is constructed and analyzed by using ANSYS software.Based on the results of static analysis and modal analysis,the maximum deformation,the maximum stress,and natural frequencies are obtained.Then,the sensitivity analysis and topology optimization are carried out to find out the parameters to be optimized.The fixed table is reconstructed according to optimal design scheme.In the comparison of the results between original model and the optimized one,the maximum deformation and stress are decreased by 71.73%and 60.27%respectively.At the same time,the natural frequencies from the first mode to the sixth mode are increased by 30.28%,29.57%,29.51%,31.52%,22.19%,and 21.80%,respectively.The method can provide technology guide for the design and optimization of machining structure.

Modelling the Optimal Control of Transmission Dynamics of <i>Mycobacterium ulceran</i>Infection

This paper examines optimal control of transmission dynamics of Mycobacterium ulceran (MU) infection. A nonlinear mathematical model for the problem is proposed and analysed qualitatively using the stability theory of the differential equations, optimal control and computer simulation. The basic reproduction number of the reduced model system is obtained by using the next generation operator method. It is found that by using Ruth Hurwitz criteria, the disease free equilibrium point is locally asymptotically stable and using centre manifold theory, the model shows the transcritical (forward) bifurcation. Optimal control is applied to the model seeking to minimize the transmission dynamics of MU infection on human and water-bugs. Pontryagin’s maximum principle is used to characterize the optimal levels of the controls. The results of optimality are solved numerically using MATLAB software and the results show that optimal combination of two controls (environmental and health education for prevention) and (water and environmental purification) minimizes the MU infection in the population.

Stability and Optimal Control of Tuberculosis Spread with an Imperfect Vaccine in the Case of Co-Infection with HIV

This paper focuses on the study and control of a non-linear mathematical epidemic model ( SSvihVELI ) based on a system of ordinary differential equation modeling the spread of tuberculosis infectious with HIV/AIDS coinfection. Existence of both disease free equilibrium and endemic equilibrium is discussed. Reproduction number R0 is determined. Using Lyapunov-Lasalle methods, we analyze the stability of epidemic system around the equilibriums (disease free and endemic equilibrium). The global asymptotic stability of the disease free equilibrium whenever Rvac is proved, where R0 is the reproduction number. We prove also that when R0 is less than one, tuberculosis can be eradicated. Numerical simulations are conducted to approve analytic results. To achieve control of the disease, seeking to reduce the infectious group by the minimum vaccine coverage, a control problem is formulated. The Pontryagin’s maximum principle is used to characterize the optimal control. The optimality system is derived and solved numerically using the Runge Kutta fourth procedure.

A NEW TECHNIQUE FOR COMPAIRING FUZZY NUMBERS USING AN INDEX OF OPTIMISM

Fuzzy numbers are convenient for representing imprecise numerical quantities in a vague environment, and their comparison or ranking is very important for application purposes. Despite many methods suggested in the literature, there is no single measure that is universally applicable to a wide variety of situations. This paper suggested a new method for comparing fuzzy numbers based on the combination of maximizing possibility and minimizing possibility using an index of optimism in [0,1] reflecting the decision makers’ risk taking attitude. The method is simple, but has many comparative advantages.

Robust Topology Optimization of Vehicle Suspension Control Arm

A robust topology optimization design framework is developed to solve lightweight structural design problems under uncertain conditions. To enhance the calculation accuracy and flexibility of the statistical moments of robust analysis, number theory integral method is applied to sample point selection and weight assignment. Both the structure topology optimization and number theory integral methods are combined to form a new robust topology optimization method. A suspension control arm problem is provided as a demonstration of robust topology optimization methods under loading uncertainties. Based on the results of deterministic and robust topology optimization, it is demonstrated that the proposed robust topology optimization method can produce a more robust design than that obtained by deterministic topology optimization. It is also found that this new approach is easy to apply in the existing commercial topology optimization software and thus feasible in practical engineering problems.

Particle swarm optimization computer simulation of Ni clusters

The stable structures and energies of Ni clusters were investigated using particle swarm optimization(PSO)combined with simulated annealing(SA).Sutton-Chen many-body potential was used in describing the interatomic interactions.The simulation results indicate that the structures of Ni clusters are icosahedral-like and binding energy per atom tends to approach that of bulk materials when the atoms number increases.The stability of Ni clusters depends not only on size but also on symmetrical characterization.The structure stability of Nin clusters increases with the increase of total atom number n.It is also found that there exists direct correlation between stability and geometrical structures of the clusters,and relatively higher symmetry clusters are more stable.From the results of the second difference in the binding energy,the clusters at n=3 is more stable than others,and the magic numbers effect is also found.