Optimal Size for Maximal Energy Efficiency in Information Processing of Biological Systems Due to Bistability

Energy efficiency is closely related to the evolution of biological systems and is important to their information processing. In this work, we calculate the excitation probability of a simple model of a bistable biological unit in response to pulsatile inputs, and its spontaneous excitation rate due to noise perturbation. Then we analytically calculate the mutual information, energy cost, and energy efficiency of an array of these bistable units. We find that the optimal number of units could maximize this array＇s energy efficiency in encoding pulse inputs, which depends on the fixed energy cost. We conclude that demand for energy efficiency in biological systems may strongly influence the size of these systems under the pressure of natural selection.

Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization

The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.

AHP-Based Optimal Selection of Garment Sizes for Online Shopping

Garment online shopping has been accepted by more and more consumers in recent years. In online shopping, a buyer only chooses the garment size judged by his own experience without trying-on, so the selected garment may not be the fittest one for the buyer due to the variety of body's figures. Thus, we propose a method of optimal selection of garment sizes for online shopping based on Analytic Hierarchy Process (AHP). The hierarchical structure model for optimal selection of garment sizes is structured and the fittest garment for a buyer is found by calculating the matching degrees between individual's measurements and the corresponding key-part values of ready-to-wear clothing sizes. In order to demonstrate its feasibility, we provide an example of selecting the fittest sizes of men's bottom. The result shows that the proposed method is useful in online clothing sales application.

A Simple Method of Calculating the Optimal Step Size in 4DVAR Technique

In four—dimensional variational data assimilation (4DVAR) technology, how to calculate the optimal step size is always a very important and indeed difficult task. It is directly related to the computational efficiency. In this research, a new method is proposed to calculate the optimal step size more effectively. Both nonlinear one—dimensional advection equation and two—dimensional inertial wave equation are used to test and compare the influence of different methods of the optimal step size calculations on the iteration steps, as well as the simulation results of 4DVAR processes. It is in evidence that the different methods have different influences. The calculating method is very important to determining whether the iteration is convergent or not and whether the convergence rate is large or small. If the calculating method of optimal step size is properly determined as demonstrated in this paper, then it can greatly enlarge the convergence rate and further greatly decrease the iteration steps. This research is meaningful since it not only makes an important improvement on 4DVAR theory, but also has useful practical application in improving the computational efficiency and saving the computational time. Key words 4DVAR - Optimal step size - Iterative convergence rate This work was supported by the National Natural Science Foundation under grants: 49735180 and 49675259, the “973 Project? CHERES(G 1998040907), the Project of Natural Science Foundation of Jiangsu Province(BK99020), and the Project Sponsored by the Scientific Research Foundation for the Returned Overseas Chinese Scholars.

Geopolymer-based modification of blasting sealing materials and optimization of blasting block size in coal seams of open pit mines

This research proposes the utilization of a geopolymer-based blasting sealing material to improve the profitability of coal sales and reduce the rate of coal fragmentation during blasting in open pit mines.The study first focused on optimizing the strength of the sealant material and reducing curing time.This was achieved by regulating the slag doping and sodium silicate solution modulus.The findings demonstrated that increasing slag content and improving the material resulted in an early rise in strength while increasing the modulus of the sodium silicate solution extended the curing time.The slag doping level was fixed at 80 g,and the sodium silicate solution modulus was set at 1.5.To achieve a strength of 3.12 MPa,the water/gel ratio was set at 0.5.The initial setting time was determined to be 33 min,meeting the required field test duration.Secondly,the strength requirements for field implementation were assessed by simulating the action time and force destruction process of the sealing material during blasting using ANSYS/LS-DYNA software.The results indicated that the modified material meets these requirements.Finally,the Shengli Open Pit Coal Mine served as the site for the field test.It was observed that the hole-sealing material’s hydration reaction created a laminated and flocculated gel inside it.This enhanced the density of the modified material.Additionally,the pregelatinized starch,functioning as an organic binder,filled the gaps between the gels,enhancing the cohesion and bonding coefficient of the material.Upon analyzing the post-blasting shooting effect diagram using the Split-Desktop software,it was determined that the utilization of the modified blast hole plugging material resulted in a decrease in the rate of coal fragmentation from 33.2%to 21.1%.This reduction exhibited a minimal error of 1.63%when compared to the field measurement,thereby providing further confirmation of the exceptional plugging capabilities of the modified material.This study significantly contributes to establishing a solid theoretical basis for enhancing the blasting efficiency of open pit mines and,in turn,enhancing their economic advantages.

Back Frame Section Size Optimization of Large Aperture Telescope

The back frame structure of a large radio telescope is an important component supporting the reflecting surface,which is directly related to the surface precision.Its optimal design is of key significance for ensuring the surface precision and reducing structural weight.Two methods are constructed to optimize the cross-section size of the telescope back frame in this paper,the criterion method and the first-order optimization method.The criterion method is based on the Lagrangian multiplier method and Kuhn-Tucker condition.This method first establishes the mathematical model by taking the inner and outer radiuses of the back frame beams as the design variables,the structural weight as the constraint condition,and the structural compliance as the objective function,then derives the optimization criterion.The first-order optimization method takes the inner and outer radiuses of the beams as the design variables,the back frame RMS as the objective function,and the structural weight as the constraint condition.Comparison of RMS,structural stress uniformity and optimization efficiency shows that both algorithms can effectively reduce structural deformation and improve RMS,but the criterion method has relatively better result than the first-order method.

Optimal integration of solar home systems and appliance scheduling for residential homes under severe national load shedding

In developing countries like South Africa,users experienced more than 1030 hours of load shedding outages in just the first half of 2023 due to inadequate power supply from the national grid.Residential homes that cannot afford to take actions to mitigate the challenges of load shedding are severely inconvenienced as they have to reschedule their demand involuntarily.This study presents optimal strategies to guide households in determining suitable scheduling and sizing solutions for solar home systems to mitigate the inconvenience experienced by residents due to load shedding.To start with,we predict the load shedding stages that are used as input for the optimal strategies by using the K-Nearest Neighbour(KNN)algorithm.Based on an accurate forecast of the future load shedding patterns,we formulate the residents’inconvenience and the loss of power supply probability during load shedding as the objective function.When solving the multi-objective optimisation problem,four different strategies to fight against load shedding are identified,namely(1)optimal home appliance scheduling(HAS)under load shedding;(2)optimal HAS supported by solar panels;(3)optimal HAS supported by batteries,and(4)optimal HAS supported by the solar home system with both solar panels and batteries.Among these strategies,appliance scheduling with an optimally sized 9.6 kWh battery and a 2.74 kWp panel array of five 550 Wp panels,eliminates the loss of power supply probability and reduces the inconvenience by 92%when tested under the South African load shedding cases in 2023.

An Improved JSO and Its Application in Spreader Optimization of Large Span Corridor Bridge

In this paper,given the shortcomings of jellyfish search algorithmwith low search ability in the early stage and easy to fall into local optimal solution,this paper introduces adaptive weight function and elite strategy,improving the global search scope in the early stage and the ability to refine the local development in the later stage.In the numerical study,the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted,and the corresponding penalty method is used for constraint treatment.The test results show that the improved jellyfish search algorithm can provide better truss sections as well as weights.Because when the steel main truss of the large-span covered bridge is lifted,the site is limited and the large lifting equipment cannot enter the site,and the original structure does not meet the problem of stress concentration and large deformation of the bolt group,so the spreader is used to lift,and the improved jellyfish search algorithm is introduced into the design optimization of the spreader.The results show that the improved jellyfish algorithm can efficiently and accurately find out the optimal shape and weight of the spreader,and throughMidas Civil simulation,the spreader used canmeet the requirements of weight and safety.

THE SATELLITE STRUCTURE TOPOLOGY OPTIMIZATION BASED ON HOMOGENIZATION METHOD AND ITS SIZE SENSITIVITY ANALYSIS

With the development of satellite structure technology, more and more design parameters will affect its structural performance. It is desirable to obtain an optimal structure design with a minimum weight, including optimal configuration and sizes. The present paper aims to describe an optimization analysis for a satellite structure, including topology optimization and size optimization. Based on the homogenization method, the topology optimization is carried out for the main supporting frame of service module under given constraints and load conditions, and then the sensitivity analysis is made of 15 structural size parameters of the whole satellite and the optimal sizes are obtained. The numerical result shows that the present optimization design method is very effective.

Impacts of sample size for stomach content analysis on the estimation of ecosystem indices

This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories:(1) direct indices, like the trophic level of species, influenced by stomach sample size directly;(2)indirect indices, like ecology efficiency(EE) of invertebrates, influenced by the multiple prey-predator relationships;and(3) systemic indices, like total system throughout(TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient.The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.

An NLMS algorithm with optimized preparatory step-size parameters for SQUID-based MCG data processing

We present a new least-mean-square algorithm of adaptive filtering to improve the signal to noise ratio for magneto-cardiography data collected with high-temperature SQUID-based magnetometers. By frequently adjusting the adaptive parameter a go systematic optimum values in the course of the programmed procedure, the convergence is accelerated with a highest speed and the minimum steady-state error is obtained simultaneously. This algorithm may be applied to eliminate other non-steady relevant noises as well.

Optimal Placement and Sizing of Distributed Generation Using Metaheuristic Algorithm

Power loss and voltage uncertainty are the major issues prevalently faced in the design of distribution systems.But such issues can be resolved through effective usage of networking reconfiguration that has a combination of Distributed Generation(DG)units from distribution networks.In this point of view,optimal placement and sizing of DGs are effective ways to boost the performance of power systems.The optimum allocation of DGs resolves various problems namely,power loss,voltage profile improvement,enhanced reliability,system stability,and performance.Several research works have been conducted to address the distribution system problems in terms of power loss,energy loss,voltage profile,and voltage stability depending upon optimal DG distribution.With this motivation,the current study designs a Chaotic Artificial Flora Optimization based on Optimal Placement and Sizing of DGs(CAFO-OPSDG)to enhance the voltage profiles and mitigate the power loss.Besides,the CAFO algorithm is derived from the incorporation of chaos theory concept into conventional artificial flora optimization AFO algorithm with an aim to enhance the global optimization abilities.The fitness function of CAFO-OPSDG algorithm involves voltage regulation,power loss minimization,and penalty cost.To consider the actual power system scenario,the penalty factor acts as an important element not only to minimize the total power loss but to increase the voltage profiles as well.The experimental validation of the CAFO-OPSDG algorithm was conducted against IEEE 33 Bus system and IEEE 69 Bus system.The outcomes were examined under various test scenarios.The results of the experiment established that the presented CAFO-OPSDG model is effective in terms of reducing the power loss and voltage deviation and boost-up the voltage profile for the specified system.

Dielectric size optimization for high power density in large-scale triboelectric nanogenerators

Triboelectric nanogenerators(TENGs)have emerged as a promising technology to harvest electrical energy from natural motions such as human movement,wind,and water flow.Although TENGs show significant potential in small-scale applications,developing large-scale TENGs capable of generating high power remains a significant challenge.Several factors that can affect the performance of large-scale TENGs are being investigated to overcome this challenge,including the size and configuration of dielectric materials.This study optimizes dielectrics regarding surface area,thickness,and multicell configuration to improve harvested electrical power density in large-scale TENGs.In the studies,glass fiber was used as the positive dielectric,and multipurpose white silicone was used as the negative dielectric because of their high tribo-potential,durability,and easy accessibility.In the size optimization phase,dielectric thicknesses and surface areas that provide the maximum power density were determined.Subsequently,horizontal and vertical multicell configurations were examined to efficiently integrate size-optimized dielectrics.The results reveal that large-scale TENGs with vertical multicell configurations can achieve high and usable energy density for electronics.The findings provide valuable insight into the development of large-scale TENGs with advanced power generation capabilities.

Sensitivity of optimal double-layer grid designs to geometrical imperfections and geometric nonlinearity conditions in the analysis phase

This study focuses on exploring the effects of geometrical imperfections and different analysis methods on the optimum design of Double-Layer Grids(DLGs),as used in the construction industry.A total of 12 notable metaheuristics are assessed and contrasted,and as a result,the Slime Mold Algorithm is identified as the most effective approach for size optimization of DLGs.To evaluate the influence of geometric imperfections and nonlinearity on the optimal design of real-size DLGs,the optimization process is carried out by considering and disregarding geometric nonlinearity while incorporating three distinct forms of geometrical imperfections,namely local imperfections,global imperfections,and combinations of both.In light of the uncertain nature of geometrical imperfections,probabilistic distributions are used to define these imperfections randomly in direction and magnitude.The results demonstrate that it is necessary to account for these imperfections to obtain an optimal solution.It’s worth noting that structural imperfections can increase the maximum stress ratio by up to 70%.The analysis also reveals that the initial curvature of members has a more significant impact on the optimal design of structures than the nodal installation error,indicating the need for greater attention to local imperfection issues in space structure construction.

Research on infiltration clogging effect and its application prospect in anti-seepage project

Clogging effect,as a new concept in geological engineering,is a phenomenon of permeability decreasing under seeping in reservoir dam foundation of the alluvial and diluvial deposits with deep and thick layer,coarse particle and high permeability in mountains-gully rivers of Tibetan Plateau.A clogging infiltration instrument has been designed successfully and a series of simulation tests have been done.Based on large amounts of data,it is confirmed that the existence of the clogging effect and the law of infiltration clogging is found out.Three indexes are proposed such as "optimal size of particle","optimal size range of particle" and "characteristic pore",which are closely related with effect of infiltration clogging.The concept and results can offer a new idea to solve problems on anti-seepage of dam foundation in mountains-gully rivers environment and to study artificial clogging,meanwhile supplement of the concept of seepage deformation.

INTEGRATION SHAPE AND SIZING OPTIMIZATION OF COMPOSITE WING STRUCTURE BASED ON RESPONSE SURFACE METHOD

An effective optimization method for the shape/sizing design of composite wing structures is presented with satisfying weight-cutting results. After decoupling, a kind of two-layer cycled optimization strategy suitable for these integrated shape/sizing optimization is obtained. The uniform design method is used to provide sample points, and approximation models for shape design variables. And the results of sizing optimization are construct- ed with the quadratic response surface method （QRSM）. The complex method based on QRSM is used to opti- mize the shape design variables and the criteria method is adopted to optimize the sizing design variables. Compared with the conventional method, the proposed algorithm is more effective and feasible for solving complex composite optimization problems and has good efficiency in weight cutting.

Investigation of Connecting Wind Turbine to Radial Distribution System on Voltage Stability Using SI Index and λ - V Curves

The growth of wind energy penetration level in distribution system raises the concern about its impact on the operation of the power system, especially voltage stability and power loss. Among the major concerns, this paper studied the impact of connecting wind Turbine (WT) in radial distribution system with different penetration levels and different power factor (lead and lag) on power system voltage stability and power loss reduction. Load flow calculation was carried out using forward-backward sweep method. The analysis proceeds on 9- and 33-bus radial distribution systems. Results show that voltage stability enhancement and power loss reduction should be considered as WT installation objective.

Light-Weight Design Method for Force-Performance-Structure of Complex Structural Part Based Co-operative Optimization

A light?weight design method of integrated structural topology and size co?optimization for the force?performance?structure of complex structural parts is presented in this paper. Firstly, the supporting function of a complex structural part is built to map the force transmission, where the force exerted areas and constraints are considered as connecting structure and the structural configuration, to determine the part performance as well as the force routines. Then the connecting structure design model, aiming to optimize the static and dynamic performances on connection configuration, is developed, and the optimum design of the characteristic parameters is carried out by means of the collaborative optimization method, namely, the integrated structural topology optimization and size optimization. In this design model, the objective is to maximize the connecting stiffness. Based on the relationship between the force and the structural configuration of a part, the optimal force transmission routine that can meet the performance requirements is obtained using the structural topology optimization technology. Accordingly, the light?weight design of conceptual configuration for complex parts under multi?objective and multi?condition can be realized. Finally, based on the proposed collaborative optimization design method, the optimal performance and optimal structure of the complex parts with light weight are realized, and the reasonable structural unit configuration and size charac?teristic parameters are obtained. A bed structure of gantry?type machining center is designed by using the proposed light?weight structure design method in this paper, as an illustrative example. The bed after the design optimization is lighter 8% than original one, and the rail deformation is reduced by 5%. Moreover, the lightweight design of the bed is achieved with enhanced performance to show the effectiveness of the proposed method.

Modeling of nano piezoelectric actuator based on block matching algorithm with optimal block size

In order to model the hysteresis behavior of a nano piezoelectric actuator(PA)on nano scale in a real time system,a new hysteresis modeling method based on an improved sub-pixel blocking matching algorithm with an optimal block size is proposed in this paper.First,Preisach model is introduced to model the hysteresis behavior of a piezoelectric actuator.Then,a real time block matching algorithm is researched and its block size is optimized with a standard object.Finally,experiments are performed with respect to a nanometer movement platform system,and the results show the feasibility and validity of the sub-pixel estimation based block matching algorithm and its application in modeling the hysteresis behavior of PA.