Optimal scheduling of a township integrated-energy system using the adjustable heat-electricity ratio model

With the expansion and implementation of rural revitalization strategies,there is a constant need for new energy sources for the construction of new townships.Consequently,integrated energy systems with the interconnection and interaction of multiple energy sources are developing rapidly.Biomass energy,a renewable green energy source with low pollution and wide distribution,has significant application potential in integrated energy systems.Considering the application of biomass energy in townships,this study established an integrated biomass energy system and proposed a model to optimize its operation.Lowest economic cost and highest clean energy utilization rate were considered as the objective functions.In addition,a plan was suggested to adjust the heat-electricity ratio based on the characteristics of the combined heat and power of the biomass.Finally,a simulation analysis conducted for a town in China was discussed,demonstrating that the construction of a township integrated-energy system and the use of biomass can significantly reduce operating costs and improve the energy utilization rate.Moreover,by adjusting the heat-electricity ratio,the economic cost was further reduced by 6.70%,whereas the clean energy utilization rate was increased by 5.14%.

Topology Optimization of Metamaterial Microstructures for Negative Poisson’s Ratio under Large Deformation Using a Gradient-Free Method

Negative Poisson’s ratio(NPR)metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy absorption.However,when subjected to significant stretching,NPR metamaterials designed under small strain assumption may experience a rapid degradation in NPR performance.To address this issue,this study aims to design metamaterials maintaining a targeted NPR under large deformation by taking advantage of the geometry nonlinearity mechanism.A representative periodic unit cell is modeled considering geometry nonlinearity,and its topology is designed using a gradient-free method.The unit cell microstructural topologies are described with the material-field series-expansion(MFSE)method.The MFSE method assumes spatial correlation of the material distribution,which greatly reduces the number of required design variables.To conveniently design metamaterials with desired NPR under large deformation,we propose a two-stage gradient-free metamaterial topology optimization method,which fully takes advantage of the dimension reduction benefits of the MFSE method and the Kriging surrogate model technique.Initially,we use homogenization to find a preliminary NPR design under a small deformation assumption.In the second stage,we begin with this preliminary design and minimize deviations in NPR from a targeted value under large deformation.Using this strategy and solution technique,we successfully obtain a group of NPR metamaterials that can sustain different desired NPRs in the range of[−0.8,−0.1]under uniaxial stretching up to 20% strain.Furthermore,typical microstructure designs are fabricated and tested through experiments.The experimental results show good consistency with our numerical results,demonstrating the effectiveness of the present gradientfree NPR metamaterial design strategy.

Optimal Insurance with Background Risk under the Ambiguity and Belief Heterogeneity Structure

In this paper, we discuss the optimal insurance in the presence of background risk while the insured is ambiguity averse and there exists belief heterogeneity between the insured and the insurer. We give the optimal insurance contract when maxing the insured’s expected utility of his/her remaining wealth under the smooth ambiguity model and the heterogeneous belief form satisfying the MHR condition. We calculate the insurance premium by using generalized Wang’s premium and also introduce a series of stochastic orders proposed by [1] to describe the relationships among the insurable risk, background risk and ambiguity parameter. We obtain the deductible insurance is the optimal insurance while they meet specific dependence structures.

Methodology for Obtaining Optimal Sleeve Friction and Friction Ratio Estimates from CPT Data

Cone penetration testing (CPT) is a cost effective and popular tool for geotechnical site characterization. CPT consists of pushing at a constant rate an electronic penetrometer into penetrable soils and recording cone bearing (qc), sleeve friction (fc) and dynamic pore pressure (u) with depth. The measured qc, fs and u values are utilized to estimate soil type and associated soil properties. A popular method to estimate soil type from CPT measurements is the Soil Behavior Type (SBT) chart. The SBT plots cone resistance vs friction ratio, Rf [where: Rf = (fs/qc)100%]. There are distortions in the CPT measurements which can result in erroneous SBT plots. Cone bearing measurements at a specific depth are blurred or averaged due to qc values being strongly influenced by soils within 10 to 30 cone diameters from the cone tip. The qcHMM algorithm was developed to address the qc blurring/averaging limitation. This paper describes the distortions which occur when obtaining sleeve friction measurements which can in association with qc blurring result in significant errors in the calculated Rf values. This paper outlines a novel and highly effective algorithm for obtaining accurate sleeve friction and friction ratio estimates. The fc optimal filter estimation technique is referred to as the OSFE-IFM algorithm. The mathematical details of the OSFE-IFM algorithm are outlined in this paper along with the results from a challenging test bed simulation. The test bed simulation demonstrates that the OSFE-IFM algorithm derives accurate estimates of sleeve friction from measured values. Optimal estimates of cone bearing and sleeve friction result in accurate Rf values and subsequent accurate estimates of soil behavior type.

Identification of Maximum Road Friction Coefficient and Optimal Slip Ratio Based on Road Type Recognition

The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions.The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory.In this paper,an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio.The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model,and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time,which are updated with time progressing.The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road,and the minimum statistical error is used as the recognition principle to improve identification robustness.Once the road type is recognized,the maximum road friction coefficient and optimal slip ratio are determined.The numerical simulation tests are conducted on two typical road friction conditions（single-friction and joint-friction）by using CarSim software.The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim.The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations,and the identification results can be used for the adjustment of vehicle active safety control strategies.

A Modified Bi-Directional Evolutionary Structural Optimization Procedure with Variable Evolutionary Volume Ratio Applied to Multi-Objective Topology Optimization Problem

Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.

Production optimization in a fractured carbonate reservoir with high producing GOR

The Gas-Oil Ratio(GOR)is a crucial production parameter in oil reservoirs.An increase in GOR results in higher gas production and lower oil production,potentially leading to well shut-ins due to economic infeasibility.This study focuses on a real fractured oil field that requires urgent production operations to reduce the producing GOR.In this study,the static model for the field was developed using commercial software,involving steps such as data collection,fault modeling,meshing,and statistical analysis to prepare for dynamic simulation.The dynamic model incorporates geometry,gridding,and rock properties from the static model,utilizing a dual-porosity approach for the naturally fractured reservoir and the Peng-Robinson equation for fluid phase behavior.Initial reservoir conditions,production history,and rock-fluid interactions were defined,with relative permeability curves indicating a water-wet reservoir and low critical gas saturation affecting the GOR.To better understand the relationship between reservoir and production parameters,a detailed sensitivity analysis was performed using the Response Surface Methodology(RSM).Following the sensitivity analysis,a history matching process was conducted using the Designed Exploration and Controlled Evolution(DECE)optimizer to validate the model for future forecasts.Six operational scenarios were defined to decrease the production GOR and enhance final recovery from the field.The results indicate that the water injection scenario is effective in preventing the GOR increase by maintaining reservoir pressure,thereby sustaining production over a longer period.This scenario also improves oil recovery by approximately 6%compared to the base case.Finally,optimization was carried out using the DECE optimizer for each scenario to fine-tune the operational parameters.The goal was to maximize oil revenue for each scenario during the optimization process.This study stands out as one of the few that provides a comprehensive analysis of production behavior and development planning for a real fractured reservoir with high producing GOR.

Optimization of Open-cast Mining Procedure Based on RSR Method

To explore the optimal evaluation mechanism of open-cast mining procedure,this paper takes the actual operation status of Huolinhe No.1 Open-cast Mine as the research basis,and makes a deep analysis of the four representative mining procedures proposed by this mine.A detailed and comprehensive evaluation system is constructed using rank-sum ratio(RSR)method.The system covers 17 key indicators and aims to evaluate the advantages and disadvantages of each scheme in an all-round and multi-angle manner.Through the calculation and analysis by RSR method,the comprehensive evaluation of the four types of mining procedure schemes is carried out,and finally the secondary river improvement project is determined as the optimal mining implementation scheme,and the joint mining scheme of the south and north areas is the alternative strategy.The research results of this paper are objective,clear and definite,can not only reveal the effectiveness and feasibility of RSR method in solving the problem of open-cast mining procedure optimization,but also provide a strong technical support and decision-making basis for the future production development of Huolinhe No.1 Open-cast Mine.Thus,this study is expected to further promote the scientific and refined process of mining operations.

Investigation of Optimal Split Ratio of 6-Slot/2-pole High Speed Permanent Magnet Motor with Toroidal Winding

Split ratio,i.e.the ratio of stator inner diameter to outer diameter,has a closed relationship with electromagnetic performance of permanent magnet(PM)motors.In this paper,the toroidal windings with short end-winding axial length are employed in the 6-slot/2-pole(6s/2p)PM motor for high speed applications.The split ratio is optimized together with the ratio of inner slot to outer slot area,i.e.slot ratio,considering stator total loss(stator iron loss and copper loss).In addition,the influence of maximum stator iron flux density and tooth-tip on the optimal split ratio,slot ratio,and average torque is investigated.The analytical predictions show that when the slot ratio is 0.5,the maximum torque can be achieved,and the optimal split ratio increases with the decrease of slot ratio,as confirmed by the finite element(FE)analyses.Finally,some of predicted results are verified by the measured results of 6s/2p prototype motor with 0.5 slot ratio.

Optimal Designs of Wound Field Switched Flux Machines with Different DC Windings Configurations

Wound field switched flux(WFSF)machines exhibits characteristics of the simple robust rotor,flexible flux-adjustable capability,and no risk of demagnetization.However,they suffer from a poor torque density compared with permanent magnet machines due to the saturation.Therefore,in this paper,two WFSF machines with single-and double-layer DC windings,respectively,are optimized for the maximum torque.The end-winding(EW)lengths differ in these two machines,which can affect the optimal design.Design parameters including the DC to armature winding copper loss ratio,slot area ratio and split ratio are optimized when two machines have the same copper loss and overall sizes.In addition,the influence of the flux density ratio,total copper loss,air-gap length and aspect ratio on the optimal split ratio is investigated using the finite element method and results are explained through the analytical model accounting for the saturation.It is discovered that the EWs have no effect on the optimal copper loss ratio,which is unity.In terms of the slot area ratio,the machine with single-layer DC windings prefers smaller DC slot areas than armature slot areas.In the WFSF machine with longer EWs,the optimal split ratio becomes smaller.Moreover,compared with other parameters,the flux density ratio can significantly affect the optimal split ratio.

Optimizing the frequency ratio method for landslide susceptibility assessment: A case study of the Caiyuan Basin in the southeast mountainous area of China

Bivariate statistical analysis of data-driven approaches is widely used for landslide susceptibility assessment, and the frequency ratio(FR) method is one of the most popular. However, the results of such assessments are dominated by the number of classes and bounds of landslide-related causative factors, and the optimal assessment is unknown. This paper optimizes the frequency ratio method as an example of bivariate statistical analysis for landslide susceptibility mapping based on a case study of the Caiyuan Basin, a region with frequent landslides, which is located in the southeast coastal mountainous area of China. A landslide inventory map containing a total of 1425 landslides(polygons) was produced, in which 70% of the landslides were selected for training purposes, and the remaining were used for validationpurposes. All datasets were resampled to the same 5 m × 5 m/pixel resolution. The receiver operating characteristic(ROC) curves of the susceptibility maps were obtained based on different combinations of dominating parameters, and the maximum value of the areas under the ROC curves(AUCs) as well as the corresponding optimal parameter was identified with an automatic searching algorithm. The results showed that the landslide susceptibility maps obtained using optimal parameters displayed a significant increase in the prediction AUC compared with those values obtained using stochastic parameters. The results also showed that one parameter named bin width has a dominant influence on the optimum. In practice, this paper is expected to benefit the assessment of landslide susceptibility by providing an easy-to-use tool. The proposed automatic approach provides a way to optimize the frequency ratio method or other bivariate statistical methods, which can furtherfacilitate comparisons and choices between different methods for landslide susceptibility assessment.

Optimal decision fusion given sensor rules

When all the rules of sensor decision are known, the optimal distributeddecision fusion, which relies only on the joint conditional probability densities, can be derivedfor very general decision systems. They include those systems with interdependent sensorobservations and any network structure. It is also valid for m-ary Bayesian decision problems andbinary problems under the Neyman-Pearson criterion. Local decision rules of a sensor withcommunication from other sensors that are optimal for the sensor itself are also presented, whichtake the form of a generalized likelihood ratio test. Numerical examples are given to reveal someinteresting phenomena that communication between sensors can improve performance of a senordecision, but cannot guarantee to improve the global fusion performance when sensor rules were givenbefore fusing.

Optimization of clay material mixture ratio and filling process in gypsum mine goaf

Because there is neither waste rock nor mill tailings in the gypsum mine, and the buildings on the goaf of gypsum mine are needed to be protected, the research proposed the scheme of the clay filling technology. Gypsum, cement, lime and water glass were used as adhesive, and the strength of different material ratios were investigated in this study. The influence factors of clay strength were obtained in the order of cement, gypsum, water glass and lime. The results show that the cement content is the determinant influence factor, and gypsum has positive effects, while the water glass can enhance both clay strength and the fluidity of the filing slurry. Furthermore, combining chaotic optimization method with neural network, the optimal ratio of composite cementing agent was obtained. The results show that the optimal ratio of water glass, cement, lime and clay (in quality) is 1.17:6.74:4.17:87.92 in the process of bottom self-flow filling, while the optimal ratio is 1.78:9.58:4.71:83.93 for roof-contacted filling. A novel filling process to fill in gypsum mine goaf with clay is established. The engineering practice shows that the filling cost is low, thus, notable economic benefit is achieved.

Optimization of the reflux ratio of benzene-toluene stage distillation columns by the Cuckoo algorithm

In this study, an enthalpy-concentration method was applied in order to model a steady state continuous benzene-toluene mixture distillation column. For a distillation tower such as the benzene- toluene splitter, there are relatively few degrees of freedom that can be manipulated in order to minimize the total annualized cost. The reflux ratio can influence the steady-state operating point and therefore influence the total annualized cost. The trade-offs between reflux ratios and total annualized cost were discussed. The Cuckoo optimization algorithm was applied to obtain a correlation for the optimum value of the reflux ratio as a power function of the economic parameters of energy price and capital cost. The results show that, at low energy price or high capital cost, the optimum reflux factor is high.

Investigation of the optimum differential gear ratio for real driving cycles by experiment design and genetic algorithm

Experiment statistical method and genetic algorithms based optimization method are used to obtain the optimum differential gear ratio for heavy truck that provides best fuel consumption when changing the working condition that affects its torque and speed range. The aim of the study is to obtain the optimum differential gear ratio with fast and accurate optimization calculation without affecting drivability characteristics of the vehicle according to certain driving cycles that represent the new working conditions of the truck. The study is carried on a mining dump truck YT3621 with 9 for- ward shift manual transmission. Two loading conditions, no load and 40 t, and four on road real driving cycles have been discussed. The truck powertrain is modeled using GT-drive, and DOE -post processing tool of the GT-suite is used for DOE analysis and genetic algorithm optimization.

Optimal INR level in elderly and non-elderly patients with atrial fibrillation receiving warfarin: a report from the COOL-AF nationwide registry in Thailand

Background Asian population are at increased risk of bleeding during the warfarin treatment,so the recommended optimal international normalized ratio(INR)level may be lower in Asians than in Westerners.The aim of this prospective multicenter study was to determine the optimal INR level in Thai patients with non-valvular atrial fibrillation(NVAF).Methods Patients with NVAF who were on warfarin for stroke prevention were recruited from 27 hospitals in the nationwide COOL-AF registry in Thailand.We collected demographic data,medical history,risk factors for stroke and bleeding,concomitant disease,electrocardiogram and laboratory data including INR and antithrombotic medications.Outcome measurements included ischemic stroke/transient ischemic attack(TIA)and major bleeding.Optimal INR level was assessed by the calculation of incidence density for six INR ranges(<1.5,1.5–1.99,2–2.49,2.5–2.99,3–3.49,and≥3.5).Results A total of 2,232 patients were included.The mean age of patients was 68.5±10.6 years.The mean follow-up duration was 25.7±10.6 months.There were 63 ischemic stroke/TIA and 112 major bleeding events.The lowest prevalence of ischemic stroke/TIA and major bleeding events occurred within the INR range of 2.0–2.99 for patients<70 years and 1.5–2.99 for patients≥70 years.Conclusions The INR range associated with the lowest risk of ischemic stroke/TIA and bleeding in the Thai population was 2.0–2.99 for patients<70 years and 1.5–2.99 for patients≥70 years.The rates of major bleeding and ischemic stroke/TIA were both higher than the rates reported in Western population.

Yield performance and optimal nitrogen and phosphorus application rates in wheat and faba bean intercropping

Yield performance in cereal and legume intercropping is related to nutrient management,however,the yield response of companion crops to nitrogen(N)input is inconclusive and only limited efforts have focused on rationed phosphorous(P)fertilization.In this study,two multi-year field experiments were implemented from 2014-2019 under identical conditions.Two factors in a randomized complete block design were adopted in both experiments.In field experiment 1,the two factors included three planting patterns(mono-cropped wheat(MW),mono-cropped faba bean(MF),and wheat and faba bean intercropping(W//F))and four N application rates(N0,0 kg N ha^(-1);N1,90 and 45 kg N ha^(-1) for wheat and faba beans,respectively;N2,180 and 90 kg N ha^(-1) for wheat and faba beans,respectively;and N3,270 and 135 kg N ha^(-1) for wheat and faba beans,respectively).In field experiment 2,the two factors included three P application rates(P0,0 kg P_(2)O_(5) ha^(-1);P1,45 kg P_(2)O_(5) ha^(-1);and P2,90 kg P_(2)O_(5) ha^(-1))and the same three planting patterns(MW,MF,and W//F).The yield performances of inter-and mono-cropped wheat and faba beans under different N and P application rates were analyzed and the optimal N and P rates for intercropped wheat(IW)and MW were estimated.The results revealed that intercropping favored wheat yield and was adverse to faba bean yield.Wheat yield increased by 18-26%,but faba bean yield decreased by 5-21% in W//F compared to MW and MF,respectively.The stimulated IW yield drove the yield advantage in W//F with an average land equivalent ratio(LER)of 1.12.N and P fertilization benefited IW yield,but reduced intercropped faba bean(IF)yield.Nevertheless,the partial LER of wheat(pLER_(wheat))decreased with increasing N application rates,and the partial LER of faba bean(pLER_(faba bean))decreased with increasing P application rates.Thus,LER decreased as N input increased and tended to decline as P rates increased.IW maintained a similar yield as MW,even under reduced 40-50% N fertilizer and 30-40% P fertilizer conditions.The estimated optimum N application rates for IW and MW were 150 and 168 kg ha^(-1),respectively,and 63 and 62 kg ha^(-1) for P_(2)O_(5),respectively.In conclusion,W//F exhibited yield advantages due to stimulated IW yield,but the intercropping yield benefit decreased as N and P inputs increased.Thus,it was concluded that modulated N and P rates could maximize the economic and ecological functions of intercropping.Based on the results,rates of 150 kg N ha^(-1) and 60 kg P_(2)O_(5) ha^(-1) are recommended for IW production in southwestern China and places with similar conditions.

Multidisciplinary Design Optimization of Crash Box with Negative Poisson’s Ratio Structure

To improve the crashworthiness and energy absorption performance,a novel crash box negative Poisson’s ratio(NPR)structure is proposed according to the characteristics of low speed collision of bumper system.Taking the peak collision force and the average collision force as two subsystems,a multidisciplinary collaborative optimization design is carried out,and its optimization results are compared with the ones optimized by NSGA-II algorithm.Simulation results show that the crashworthiness and energy absorption performance of the novel crash box is improved effectively based on the multidisciplinary optimization method.

Aeroelastic Analysis and Optimization of High-aspect-ratio Composite Forward-swept Wings

In order to analyze the effects of forward-swept angle and skin ply-orientation on the static and dynamic aeroelastic characteristics, the aeroelastic modeling and calculation for high-aspect-ratio composite wings with different forward-swept angles and skin ply-orientation are performed. This paper presents the results of a design study aiming to optimize wings with typical forward-swept angles and skin ply-orientation in an aeroelastic way by using the genetic/sensitivity-based hybrid algorithm. Under the conditions of satiated multiple constraints including strength, displacements, divergence speeds and flutter speeds, the studies are carried out in a bid to minimize the structural weight of a wing with the lay-up thicknesses of wing components as design variabies. In addition, the effects of the power of spanwise variation function of lay-up thicknesses of skins and iugs on the optimized weights are also analyzed.

OPERATION AND OPTIMIZATION OF BATCH DISTILLATION FOR A BINARY SYSTEM

Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.