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.

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.

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.

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.

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.

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.

Structural optimization design of a bolster based on a simulation-driven design

A simulation-driven design method which uses multiple optimization methods can effectively promote innovative structural design tion analysis can enormously improve the efficiency of modelling and solving.This study establishes a general workflow of structural and reduce the product development cycle.Meanwhile,the sub-model technology which has more detailed simulation and optimizaoptimization for a stainless-steel metro bolster by combining the simulation-driven design method and sub-model technology.In the sub-model definition phase,the end underframe sub-model which contains the bolster is obtained based on the whole car body finite element(FE)model,and the effectiveness of the end underframe sub-model is also proved.In the conceptual design phase,the is determined according to manufacturing processes and design experiences.In the detailed design phase,the thickness of each topology path inside the bolster is obtained by the topology method and the optimized structure of the inner ribs inside the bolster part of the bolster is determined by size optimization.The simulation analyses indicate that the requirements of static strength and can be decreased by 17.79% compared with the original bolster structure,which means that not only the lightweight design goal fatigue strength are fulfilled by the optimized bolster structure.Besides,the weight can be reduced by 11.18% and the weld length is achicved.but also the welding auantity and manufacturing difficulty are geatly reduced.The results show the effectiveness of the simulation-driven design method based on the sub-model technology in the structural optimization for key parts of rail transit vehicles.

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.

Modeling and configuration optimization of the rooftop photovoltaic with electric-hydrogen-thermal hybrid storage system for zero-energy buildings:Consider a cumulative seasonal effect

Rooftop photovoltaic(PV)systems are represented as projected technology to achieve net-zero energy building(NEZB).In this research,a novel energy structure based on rooftop PV with electric-hydrogen-thermal hybrid energy storage is analyzed and optimized to provide electricity and heating load of residential buildings.First,the mathematical model,constraints,objective function,and evaluation indicators are given.Then,the simulation is conducted under the stand-alone condition.The annual return on investment and the levelized cost of energy of the system are 36.37%and 0.1016$/kWh,respectively.Residential building with the proposed system decreases annual carbon emission by 25.5 t.In the third part,simulation analysis under different grid-connected modes shows that building system will obtain better economics when connected to the grid,but the low-carbon performance will be reduced.Finally,the cumulative seasonal impact of the countywide rooftop PV buildings is discussed.The result indicates that the energy structure proposed in this paper can effectively reduce the grid-connected impact on the local grid.This model and optimization method developed in this paper is applicable to different climate zones and can provide management support to the investors of NZEB before the field test.

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.

Metal nanoparticles for cancer therapy:Precision targeting of DNA damage

Cancer,a complex and heterogeneous disease,arises from genomic instability.Currently,DNA damage-based cancer treatments,including radiotherapy and chemotherapy,are employed in clinical practice.However,the efficacy and safety of these therapies are constrained by various factors,limiting their ability to meet current clinical demands.Metal nanoparticles present promising avenues for enhancing each critical aspect of DNA damage-based cancer therapy.Their customizable physicochemical properties enable the development of targeted and personalized treatment platforms.In this review,we delve into the design principles and optimization strategies of metal nanoparticles.We shed light on the limitations of DNA damage-based therapy while highlighting the diverse strategies made possible by metal nanoparticles.These encompass targeted drug delivery,inhibition of DNA repair mechanisms,induction of cell death,and the cascading immune response.Moreover,we explore the pivotal role of physicochemical factors such as nanoparticle size,stimuli-responsiveness,and surface modification in shaping metal nanoparticle platforms.Finally,we present insights into the challenges and future directions of metal nanoparticles in advancing DNA damage-based cancer therapy,paving the way for novel treatment paradigms.

Optimal City Size in China:An Extended Empirical Study from the Perspective of Energy Consumption

The optimal city size has always been a heated topic for debate in China. Given the background of global warming and fossil fuel crisis, it is argued that the issue should be considered from not only the perspective of economic benefits of a city but should also consider the energy consumption efficiency of the city. On the basis of the energy consumption data of 286 cities at the prefectural level and above in Chinese mainland except Lasa, which are obtained from the EU Emission Database for Global Atmospheric Research(EDGAR), this paper carries out an empirical analysis on the relationship between the city size and the energy consumption efficiency of the city. Then based on this analysis, the paper further examines the economic benefits, social benefits, and environment quality of cities in different scales, and the findings reveal that large cities with 2 – 5 million population have the highest efficiency in all these aspects.

The infuence of window size on remote sensing-based prediction of forest structural variables

Background:Determining the appropriate window size is a critical step in the estimation process of stand structural variables based on remote sensing data.Because the value of the reference laser and image metrics that afect the quality of the prediction model depends on window size.However,suitable window sizes are usually determined by trial and error.There are a limited number of published studies evaluating appropriate window sizes for diferent remote sensing data.This research investigated the efect of window size on predicting forest structural variables using airborne LiDAR data,digital aerial image and WorldView-3 satellite image.Results:In the WorldView-3 and digital aerial image,signifcant diferences were observed in the prediction accuracies of the structural variables according to diferent window sizes.For the estimation based on WorldView-3 in black pine stands,the optimal window sizes for stem number(N),volume(V),basal area(BA)and mean height(H)were determined as 1000 m^(2),100 m^(2),100 m^(2) and 600 m^(2),respectively.In oak stands,the R^(2) values of each moving window size were almost identical for N and BA.The optimal window size was 400 m^(2) for V and 600 m^(2) for H.For the estimation based on aerial image in black pine stands,the 800 m^(2) window size was optimal for N and H,the 600 m^(2) window size was optimal for V and the 1000 m^(2) window size was optimal for BA.In the oak stands,the optimal window sizes for N,V,BA and H were determined as 1000 m^(2),100 m^(2),100 m^(2) and 600 m^(2),respectively.The optimal window sizes may need to be scaled up or down to match the stand canopy components.In the LiDAR data,the R^(2) values of each window size were almost identical for all variables of the black pine and the oak stands.Conclusion:This study illustrated that the window size has an efect on the prediction accuracy in estimating forest structural variables based on remote sensing data.Moreover,the results showed that the optimal window size for forest structural variables varies according to remote sensing data and tree species composition.

Multi-Objective Sizing of Solar-Wind-Hydro Hybrid Power System with Doubled Energy Storages Under Optimal Coordinated Operational Strategy

More and more attention has been paid to the high penetration of renewable energy in recent years.The randomness and intermittency of solar and wind energy make it an inevitable trend that renewables are coupled with energy storage technologies.Pumped hydro storage(PHS)is the most widelyused storage form in the power grid but the capacity is limited by geographic conditions.The concentrated solar power(CSP)plant with a thermal energy storage(TES)system can realize easier grid connections and effective peak shaving.Therefore,this paper proposes a solar-wind-hydro hybrid power system with PHS-TES double energy storages,and investigates the optimal coordinated operational strategy and multi-objective sizing.The optimal sizing problem which considers the minimum levelized cost of energy(LCOE)and loss of power supply probability(LPSP)as objectives is solved by multi-objective particle swarm optimization.Moreover,the seasonal uncertainties of renewables are considered by applying a scenario-based analysis using Kmeans clustering.Finally,a case study reveals the effectiveness of the coordinated operational strategy and double energy storages from the perspectives of economy and reliability.The comparisons of optimal sizing results show that the PV-WindCSP-PHS system decreases the LCOE by 19.1%compared to a PV-Wind-CSP system under the same LPSP,and reduces the LPSP compared to PV-Wind-PHS systems with limited reservoir capacity,which indicates that the proposed system with double energy storages has better economy and reliability performance compared to single storage.

Study on Functional Mechanical Performance of Honeycomb Array Structures Inspired by Gideon Beetle

To obtain bio-inspired structures with superior biological function,four bio-inspired structures named regular arrangement honeycomb structure(RAHS),staggered arrangement honeycomb structure(SAHS),floral arrangement honeycomb structure(FLAHS)and functional arrangement honeycomb structure(FUAHS)are designed by observing the microstructure of the Gideon beetle,based on the optimal size bio-inspired cells by response surface method(RSM)and particle swarm optimization(PSO)algorithm.According to Euler theory and buckling failure theory,compression deformation properties of bio-inspired structures are explained.Experiments and simulations further verify the accuracy of theoretical analysis results.The results show that energy absorption of FLAHS is,respectively,increased by 26.95%,22.85%,and 121.45%,compared with RAHS,SAHS,and FUAHS.Elastic modulus of FLAHS is 110.37%,110.37%,and 230.56% of RAHS,SAHS,and FUAHS,respectively.FLAHS perfectly inherits crashworthiness and energy absorption properties of the Gideon beetle,and FLAHS has the most stable force.Similarly,RAHS,SAHS,and FUAHS,respectively,inherit mechanical properties of the Gideon beetle top horn,the Gideon beetle middle horn,and the abdomen of the beetle.This method,designing bio-inspired structures with biological functions,can be introduced into the engineering field requiring the special function.

Design and experiment on atomizer parameter of impinging low-speed centrifugal atomization sprayer

Atomizers were designed with different atomization parameters to obtain droplets that satisfy optimal particle size requirements for an impinging-type low-speed centrifugal atomizing sprayer.The main factors affecting droplet size are turntable speed,the number of teeth and the tooth shape of the toothed disc.Winner318 software was used to evaluate droplet sizes for different structures and the working parameters of the atomizer.The response surface method and Design-Expert were used to analyze the effect of each factor.The response surface analysis of the effect of structural and working parameters of the atomizer on the interaction between the volume medium diameter of the droplet and the spectral width of the droplet size was used to establish the atomizer droplet Granular spectrum prediction model.Optimal design fitting formulas are obtained,and the droplet sizes required for pesticides to control flying insect pests,to control the growth of reptile larvae,and the use of spraying fungicides to prevent crop damage were determined.This research provides a product not only similar to those in the market,but also the theoretical basis and references for innovation,development,and optimization of centrifugal atomization technology.

Levy-flight moth-flame optimisation algorithm-based micro-grid equipment sizing:An integrated investment and operational planning approach

Bridging the gap between simulation and reality for successful micro-grid(MG)implementation requires accu-rate mathematical modelling of the underlying energy infrastructure and extensive optimisation of the design space defined by all possible combinations of the size of the equipment.While exact mathematical optimisa-tion approaches to the MG capacity planning are highly computationally efficient,they often fail to preserve the associated problem nonlinearities and non-convexities.This translates into the fact that the available MG sizing tools potentially return a sub-optimal(inferior)MG design.This brings to light the importance of nature-inspired,swarm-based meta-heuristic optimisation algorithms that are able to effectively handle the nonlinear and non-convex nature of the MG design optimisation problem–and better approximate the globally optimum solution–though at the expense of increased computational complexity.Accordingly,this paper introduces a robust MG capacity planning optimisation framework based on a state-of-the-art meta-heuristic,namely the Lévy-flight moth-flame optimisation algorithm(MFOA).An intelligent linear programming-based day-ahead en-ergy scheduling design is,additionally,integrated into the proposed model.A case study is presented for a real grid-tied community MG in rural New Zealand.A comparison of the modelling results with those of the most popular tool in the literature and industry,HOMER Pro,verifies the superiority of the proposed meta-heuristic-based MG sizing model.Additionally,the efficiency of the Lévy-flight MFOA is compared to nine well-established meta-heuristics in the MG capacity planning literature.The comparative analyses have revealed the statistically significant outperformance of the Lévy-flight MFOA to the examined meta-heuristics.Notably,its superiority to the original MFOA,the hybrid genetic algorithm-particle swarm optimisation,and the ant colony optimiser,by at least~6.5%,~8.4%,and~12.8%,is demonstrated.Moreover,comprehensive capital budgeting analyses have confirmed the financial viability of the test-case system optimised by the proposed model.