Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

African Bison Optimization Algorithm:A New Bio-Inspired Optimizer with Engineering Applications

This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological population.ABO is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and eliminating.The foraging behavior prompts the bison to seek a richer food source for survival.When bison find a food source,they stick around for a while by bathing behavior.The jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating behavior.The eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent individuals.The above behaviors are translated into ABO by mathematical modeling.To assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with constraints.The findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer Problem

Artificial rabbits optimization(ARO)is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in nature.However,for solving optimization problems,the ARO algorithm shows slow convergence speed and can fall into local minima.To overcome these drawbacks,this paper proposes chaotic opposition-based learning ARO(COARO),an improved version of the ARO algorithm that incorporates opposition-based learning(OBL)and chaotic local search(CLS)techniques.By adding OBL to ARO,the convergence speed of the algorithm increases and it explores the search space better.Chaotic maps in CLS provide rapid convergence by scanning the search space efficiently,since their ergodicity and non-repetitive properties.The proposed COARO algorithm has been tested using thirty-three distinct benchmark functions.The outcomes have been compared with the most recent optimization algorithms.Additionally,the COARO algorithm’s problem-solving capabilities have been evaluated using six different engineering design problems and compared with various other algorithms.This study also introduces a binary variant of the continuous COARO algorithm,named BCOARO.The performance of BCOARO was evaluated on the breast cancer dataset.The effectiveness of BCOARO has been compared with different feature selection algorithms.The proposed BCOARO outperforms alternative algorithms,according to the findings obtained for real applications in terms of accuracy performance,and fitness value.Extensive experiments show that the COARO and BCOARO algorithms achieve promising results compared to other metaheuristic algorithms.

An Improved Bald Eagle Search Algorithm with Cauchy Mutation and Adaptive Weight Factor for Engineering Optimization

The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search stage and swooping stage.However,BES tends to drop-in local optimization and the maximum value of search space needs to be improved.To fill this research gap,we propose an improved bald eagle algorithm(CABES)that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima.Firstly,CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage,to select a better search range.Secondly,in the search stage,CABES updates the search position update formula by an adaptive weight factor to further promote the local optimization capability of BES.To verify the performance of CABES,the benchmark function of CEC2017 is used to simulate the algorithm.The findings of the tests are compared to those of the Particle Swarm Optimization algorithm(PSO),Whale Optimization Algorithm(WOA)and Archimedes Algorithm(AOA).The experimental results show that CABES can provide good exploration and development capabilities,and it has strong competitiveness in testing algorithms.Finally,CABES is applied to four constrained engineering problems and a groundwater engineeringmodel,which further verifies the effectiveness and efficiency of CABES in practical engineering problems.

Research on Coordinated Development and Optimization of Distribution Networks at All Levels in Distributed Power Energy Engineering

The uncertainty of distributed generation energy has dramatically challenged the coordinated development of distribution networks at all levels.This paper focuses on the multi-time-scale regulation model of distributed generation energy under normal conditions.The simulation results of the example verify the self-optimization characteristics and the effectiveness of real-time dispatching of the distribution network control technology at all levels under multiple time scales.

Strategies for Improving the Effectiveness of Professional Practice for Full-Time Professional Master Degree Postgraduate in Mineral Processing Engineering

In order to gain practical experience and hands-on skills,full-time professional master degree postgraduate in mineral processing engineering should engage in professional practices.Nonetheless,a series of problems,including insufficient time for practice,low management level,inadequate implementation of the double-supervisor system,and poor results of professional practice,has reduced the effectiveness of professional practice.In view of the aforementioned problems and the characteristics of the discipline,this paper proposes several strategies for improving the effectiveness of professional practice for postgraduates in mineral processing engineering.

The fabrication of hydroxyapatite mineralized hydrogels for bone tissue engineering

Bone is a complex but orderly mineralized tissue with hydroxyapatite(HA)as the inorganic phase and collagen as the organic phase.Inspired by natural bone tissues,HA-mineralized hydrogels have been widely designed and used in bone tissue engineering.HA is majorly utilized for the treatment of bone defects because of its excellent osteoconduction and bone inductivity.Hydrogel is a three-dimensional hydrophilic network structure with similar properties to the extracellular matrix(ECM).The combination of HA and hydrogels produces a new hybrid material that could effectively promote osteointegration and accelerate the healing of bone defects.In this review,the structure and growth of bone and the common strategies used to prepare HA were briefly introduced.Importantly,we discussed the fabrication of HA mineralized hydrogels from simple blending to in situ mineralization.We hope this review can provide a reference for the development of bone repair hydrogels.

Synergistic Swarm Optimization Algorithm

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm(SSOA).The SSOA combines the principles of swarmintelligence and synergistic cooperation to search for optimal solutions efficiently.A synergistic cooperation mechanism is employed,where particles exchange information and learn from each other to improve their search behaviors.This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities.Furthermore,adaptive mechanisms,such as dynamic parameter adjustment and diversification strategies,are incorporated to balance exploration and exploitation.By leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation,the SSOAmethod aims to achieve superior convergence speed and solution quality performance compared to other optimization algorithms.The effectiveness of the proposed SSOA is investigated in solving the 23 benchmark functions and various engineering design problems.The experimental results highlight the effectiveness and potential of the SSOA method in addressing challenging optimization problems,making it a promising tool for a wide range of applications in engineering and beyond.Matlab codes of SSOA are available at:https://www.mathworks.com/matlabcentral/fileexchange/153466-synergistic-swarm-optimization-algorithm.

Geology and mineralization of the Dongping supergiant alkalic-hosted Au-Te deposit(>100 t Au)in Northern Hebei Province,China:A review

The Dongping deposit is the largest alkalic-hosted gold deposit in China containing>100 t of Au.This paper presents a new understanding for Dongping ore system,based on the previous studies.The mineralization originally occurred at 400-380 Ma,simultaneous with emplacement of the Shuiquangou alkaline complex,and was overprinted by the hydrothermal activity in the Yanshanian.Isotope compositions of ores indicate metals of the deposit are mainly provided by the Shuiquangou complex.Ore-forming fluids are characterized by increasing oxygen fugacity and decreasing sulfur fugacity,while tellurium fugacity increased in the Stage II-2 and decreased in Stage II-3.These systematic changes are closely related to the processes of mineral precipitation and fluid evolution.Sulfide precipitation from Stage Ⅰ to Stage Ⅱ was triggered by fluid boiling,which leads to the precipitation of Pb-Bi-Te,due to decrement of sulfur fugacity.Condensation of gas phase containing high concentration of H_2Te leads to precipitation of Te-Au-Ag minerals and native tellurium.Based on these hypotheses,this paper present a polyphase metallogenic model as follow.During the Devonian,fluids were released from alkaline magmas,which carried ore-forming materials form the surrounding rocks and precipitate the early ores.During the Jurassic-Cretaceous,fluorine-rich fluids exsolved from highly factionated Shangshuiquan granite,which extracted and concentrated Au from the Shuiquangou complex and the Sanggan Group metamorphic rocks,and finally formed the Dongping gold deposit.

Wind-sand flow simulation and radius optimization of highway embankment under different vertical curve radius

It is of great practical value to explore the correlation between the vertical curve radius of desert highway and the increase of sand accumulation in local lines,and to select the appropriate vertical curve radius for reducing the risk of sand accumulation.In this study,three-dimensional models of desert highway embankments with different vertical curve radii were constructed,and Fluent software was used to simulate the wind-sand flow field and sand accumulation distribution of vertical curve embankments.The results show that:(1)Along the direction of the road,the concave and the convex vertical curve embankments have the effect of collecting and diverging the wind-sand flow,respectively.When the radius of the concave vertical curve is 3000 m,5000 m,8000 m,10000 m and 20000 m,the wind velocity in the middle of the vertical curve is 31.76%,22.58%,10.78%,10.53%and 10.44%,higher than that at both ends.When the radius of the convex vertical curve is 6500 m,8000 m,10000 m,20000 m and 30000 m,the wind velocity at both ends of the vertical curve is 14.06%,9.99%,6.14%,3.22%and 2.41%,higher than that in the middle.The diversion effect also decreases with the increase of the radius.(2)The conductivity of the concave and convex vertical curve embankments with different radii is greater than 1,which is the sediment transport roadbed.The conductivity increases with the increase of radius and gradually tends to be stable.When the radius of the concave and convex vertical curves reaches 8000 m and 20000 m respectively,the phenomenon of sand accumulation is no longer serious.Under the same radius condition,the concave vertical curve embankment is more prone to sand accumulation than the convex one.(3)Considering the strength of the collection and diversion of the vertical curve embankment with different radii,and the sand accumulation of the vertical curve embankment in the desert section of Wuma Expressway,the radius of the concave vertical curve is not less than 8000 m,and the radius of the convex vertical curve is not less than 20000 m,which can effectively reduce the sand accumulation of the vertical curve embankment.In the desert highway area,the research results of this paper can provide reference for the design of vertical curve to ensure the safe operation of desert highway.

In situ U-Pb dating and trace elements of magmatic rutile from Mujicun Cu-Mo deposit,North China Craton:Insights into porphyry mineralization

Porphyry Cu(Mo-Au)deposit is one of the most important types of copper deposit and usually formed under magmatic arc-related settings,whilst the Mujicun porphyry Cu-Mo deposit in North China Craton uncommonly generated within intra-continental settings.Although previous studies have focused on the age,origin and ore genesis of the Mujicun deposit,the ore-forming age,magma source and tectonic evolution remain controversial.Here,this study targeted rutile(TiO_(2))in the ore-hosting diorite porphyry from the Mujicun Cu-Mo deposit to conduct in situ U-Pb dating and trace element composition studies,with major views to determine the timing and magma evolution and to provide new insights into porphyry Cu-Mo metallogeny.Rutile trace element data show flat-like REE patterns characterized by relatively enrichment LREEs and depleted HREEs,which could be identified as magmatic rutile.Rutile U-Pb dating yields lower intercept ages of 139.3–138.4 Ma,interpreted as post magmatic cooling timing below about 500℃,which are consistent or slightly postdate with the published zircon U-Pb ages of diorite porphyry(144.1–141.7 Ma)and skarn(146.2 Ma;139.9 Ma)as well as the molybdenite Re-Os ages of molybdenum ores(144.8–140.0 Ma).Given that the overlap between the closure temperature of rutile U-Pb system and ore-forming temperature of the Mujicun deposit,this study suggests that the ore-forming ages of the Mujicun deposit can be constrained at 139.3–138.4 Ma,with temporal links to the late large-scale granitic magmatism at 138–126 Ma in the Taihang Orogen.Based on the Mg and Al contents in rutile,the magma of ore-hosting diorite porphyry was suggested to be derived from crust-mantle mixing components.In conjunction with previous studies in Taihang Orogen,this study proposes that the far-field effect and the rollback of the subducting Paleo-Pacific slab triggered lithospheric extension,asthenosphere upwelling,crust-mantle interaction and thermo-mechanical erosion,which jointly facilitated the formation of dioritic magmas during the Early Cretaceous.Subsequently,the dioritic magmas carrying crust-mantle mixing metallic materials were emplaced and precipitated at shallow positions along NNE-trending ore-controlling faults,eventually resulting in the formation of the Mujicun Cu-Mo deposit within an intracontinental extensional setting.

Geology and mineralization of the Hongqiling large magmatic nickel-copper-cobalt deposit(22×10^(4)t)in Jilin Province,China:A review

The Hongqiling large nickel-copper-cobalt deposit(hereafter referred to as the Hongqiling deposit),a typical mafic-ultramafic copper-nickel deposit in China,boasts proven Ni(Ni)resources of approximately 22×10^(4)t,associated copper resources of 2×10^(4)t,and associated cobalt(Co)resources of 0.5×10^(4)t,with Ni reserves ranking 10th among China's magmatic nickel deposits.Geotectonically,the Hongqiling deposit is situated in the superimposed zone between the Xing'an-Mongolian orogenic belt and the circum-Western Pacific's active continental margin belt.Its ore-bearing plutons occur within the metamorphic rocks of the Ordovician Hulan Group,with the emplacement of plutons and the locations of orebodies governed by the deep-seated Huifahe fault and its secondary NW-trending Fujia-Hejiagou-Beixinglong-Changsheng fault zone.In the deposit,the rock assemblages of ore-bearing plutons predominantly encompass gabbro-pyroxenite-olivine pyroxenite-pyroxene peridotite(pluton No.1)and norite-orthopyroxenite-harzburgite(pluton No.7),with ore-bearing lithofacies consisting primarily of olivine pyroxenite and pyroxenite facies.The Hongqiling deposit hosts stratoid,overhanging lentoid,veined,and pure-sulfide veined orebodies.Its ores principally contain metallic minerals including pyrrhotite,pentlandite,chalcopyrite,violarite,and pyrite.Despite unidentified magma sources of ore-bearing mafic-ultramafic rocks,it is roughly accepted that the magmatic evolution in the Hongqiling deposit primarily involved fractional crystallization and crustal contamination.The ore-forming materials were primarily derived from the upper mantle,mixed with minor crustal materials.The ore-bearing mafic-ultramafic rocks in the deposit,primarily emplaced during the Indosinian(208-239 Ma),were formed in an intense extension setting followed by the collisional orogeny between the North China Plate and the Songnen-Zhangguangcai Range Block during the Middle-Late Triassic.From the perspective of the metallogenic geological setting,surrounding rocks,ore-controlling structures,and rock assemblages,this study identified one favorable condition and seven significant indicators for prospecting for Hongqiling-type nickel deposits and developed a prospecting model of the Hongqiling deposit.These serve as valuable references for exploring similar nickel deposits in the region,as well as the deep parts and margins of the Hongqiling deposit.

Optimization performance of quantum endoreversible Otto machines with dual-squeezed reservoirs

We consider a quantum endoreversible Otto engine cycle and its inverse operation-Otto refrigeration cycle,employing two-level systems as the working substance and operating in dual-squeezed reservoirs.We demonstrate that the efficiency of heat engines at maximum work output and the coefficient of performance for refrigerators at the maximum c criterion will degenerate toη-=η_(C)/(2-η_(C))andε-=(√9+8ε_(C)-3)/2 when symmetric squeezing is satisfied,respectively.We also investigated the influences of squeezing degree on the performance optimization of quantum Otto heat engines at the maximum work output and refrigerators at the maximum X criterion.These analytical results show that the efficiency of heat engines at maximum work output and the coefficient of performance for refrigerators at the maximum X criterion can be improved,reduced or even inhibited in asymmetric squeezing.Furthermore,we also find that the efficiency of quantum Otto heat engines at maximum work output is lower than that obtained from the Otto heat engines based on a single harmonic oscillator system.However,the coefficient of performance of the corresponding refrigerator is higher.

Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management

Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments,surpassing traditional inspection techniques.Building on this foundation,this paper delves into the optimization of UAV inspection routing and scheduling,addressing the complexity introduced by factors such as no-fly zones,monitoring-interval time windows,and multiple monitoring rounds.To tackle this challenging problem,we propose a mixed-integer linear programming(MILP)model that optimizes inspection task assignments,monitoring sequence schedules,and charging decisions.The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem(VRP),leading to a mathematically intractable model for commercial solvers in the case of large-scale instances.To overcome this limitation,we design a tailored variable neighborhood search(VNS)metaheuristic,customizing the algorithm to efficiently solve our model.Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm,demonstrating its scalability for both large-scale and real-scale instances.Sensitivity experiments and a case study based on an actual engineering project are also conducted,providing valuable insights for engineering managers to enhance inspection work efficiency.

Optimization of water-urban-agricultural-ecological land use pattern:A case study of Guanzhong Basin in the southern Loess Plateau of Shaanxi Province,China

Extensive land use will cause many environmental problems.It is an urgent task to improve land use efficiency and optimize land use patterns.In recent years,due to the flow decrease,the Guanzhong Basin in Shaanxi Province is confronted with the problem of insufficient water resources reserve.Based on the Coupled Ground-Water and Surface-Water Flow Model(GSFLOW),this paper evaluates the response of water resources in the basin to changes in land use patterns,optimizes the land use pattern,improves the ecological and economic benefits,and the efficiency of various spatial development,providing a reference for ecological protection and high-quality development of the Yellow River Basin.The research shows that the land use pattern in the Guanzhong Basin should be further optimized.Under the condition of considering ecological and economic development,the percentage change of the optimum area of farmland,forest,grassland,water area,and urban area compared with the current land use area ratio is+2.3,+2.4,-6.1,+0.2,and+1.6,respectively.The economic and ecological value of land increases by14.1%and 3.1%,respectively,and the number of water resources can increase by 2.5%.

Optimal Classification of Minerals by Microscopic Image Analysis Based on Seven-State “Deep Learning” Combined with Optimizers

The development of artificial intelligence (AI), particularly deep learning, has made it possible to accelerate and improve the processing of data collected in different fields (commerce, medicine, surveillance or security, agriculture, etc.). Most related works use open source consistent image databases. This is the case for ImageNet reference data such as coco data, IP102, CIFAR-10, STL-10 and many others with variability representatives. The consistency of its images contributes to the spectacular results observed in its fields with deep learning. The application of deep learning which is making its debut in geology does not, to our knowledge, include a database of microscopic images of thin sections of open source rock minerals. In this paper, we evaluate three optimizers under the AlexNet architecture to check whether our acquired mineral images have object features or patterns that are clear and distinct to be extracted by a neural network. These are thin sections of magmatic rocks (biotite and 2-mica granite, granodiorite, simple granite, dolerite, charnokite and gabbros, etc.) which served as support. We use two hyper-parameters: the number of epochs to perform complete rounds on the entire data set and the “learning rate” to indicate how quickly the weights in the network will be modified during optimization. Using Transfer Learning, the three (3) optimizers all based on the gradient descent methods of Stochastic Momentum Gradient Descent (sgdm), Root Mean Square Propagation (RMSprop) algorithm and Adaptive Estimation of moment (Adam) achieved better performance. The recorded results indicate that the Momentum optimizer achieved the best scores respectively of 96.2% with a learning step set to 10−3 for a fixed choice of 350 epochs during this variation and 96, 7% over 300 epochs for the same value of the learning step. This performance is expected to provide excellent insight into image quality for future studies. Then they participate in the development of an intelligent system for the identification and classification of minerals, seven (7) in total (quartz, biotite, amphibole, plagioclase, feldspar, muscovite, pyroxene) and rocks.

DYNAMIC RESPONSE OPTIMIZATION DESIGN FOR ENGINEERING STRUCTURES BASED ON RELIABILITY

In many practical structures, physical parameters of material and applied loads have random property.To optimize this kind of structures,an optimum mathematical model was built.This model has reliability constraints on dynamic stress and displacement and upper & lower limits of the design variables. The numerical characteristic of dynamic response and sensitivity of dynamic response based on probability of structure were deduced respectively. By equivalent disposing, the reliability constraints were changed into conventional forms. The SUMT method was used in the optimization process.Two examples illustrate the correctness and practicability of the optimum model and solving approach.

Scientific and Engineering Progress in CO_2 Minerali zation Using Industrial Waste and Natural Minerals

The issues of reducing CO_2 levels in the atmo-sphere, sustainably utilizing natural mineral resources,and dealing with indus trial waste offer challenging opportunities for sustainable development in energy and the environment. The latest advances in CO_2 mineralization technology involving natural minerals and industrial waste are summarized in this paper, with great emphasis on the advancement of fundamental science, economic evaluation, and engineering applications. We discuss several lead-ing large-scale CO_2 mineralization methodologies from a techn ical and engineering-science perspective. For each technology option, we give an overview of the technical parameters, reaction pathway, reactivity, procedural scheme, and laboratorial and pilot devices. Furthermore, we present a discussion of each technology based on experimental results and the literature. Finally, current gaps in knowledge are identified in the conclusion, and an overview of the challenges and opportunities for future research in this field is provided.

Optimization of Vehicle Side Curtain Airbag Module Based on Computer Aided Engineering

Compared with other kinds of airbags, curtain airbag（CAB） has more complex structures and larger coverage area. The product development process depends on many module tests, sled tests and full size vehicle tests. Computer aided engineering（CAE） technology can replace tests to a great extent, also save test costs and product development time. This paper introduces the way of setting up simulation models and application of static deployment tests and free motion headform（FMH） tests to verify simulation models. In the CAB simulation, uniform pressure airbag models and computational fluid dynamics（CFD） models are all used. The uniform pressure airbag models are not able to simulate the pressure difference among different parts inside the cushion during inflating process. CFD-based CAB models are used to help the curtain airbag optimization design. Based on effective CAE simulation, the optimization analyses related to diffuser tube parameters, inflator mass flow rate and cushion folding patterns are discussed and performed in different cases. The optimization result shows that the proposed techniques are helpful to the parametric optimization design of side curtain airbag module in curtain airbag development process.