Design Of Simulation Experiments Research Articles

Simulation Experiment Design and Control Strategy Analysis in Teaching of Hydrogen-Electric Coupling System

Hydrogen energy, as a clean and green energy medium, is characterized by large capacity, extended lifespan, convenient storage, and seamless transmission. On the one hand, in the power system, hydrogen can be prepared by the electrolysis of water using the surplus power from intermittent new energy generation, such as photovoltaic and wind power, to increase the space for new energy consumption. On the other hand, it can be used to generate electricity from the chemical reaction between hydrogen and oxygen through the fuel cell and be used as a backup power source when there is a shortage of power supply. In this paper, based on the teaching practice, the conversion mechanism and coupling relationship between various forms of energy, such as photovoltaic energy, hydrogen energy, and electric energy, were deeply analyzed. Further, a hydrogen-electricity coupling digital simulation experimental system, including photovoltaic power generation, fuel cell, and electrolysis hydrogen system, was formed. Simultaneously, considering the synergy between hydrogen production and electricity generation businesses, as well as the demand for the efficient utilization and flexible regulation of multiple energy sources, eight sets of simulation experimental scenarios were designed. A cooperative control strategy for the hydrogen-electric coupling system was proposed and validated through simulation on the MATLAB/SIMULINK-R2023a platform. This study shows that the simulation system has rich experimental scenarios and control strategies, and can comprehensively and accurately demonstrate the multi-energy complementary and cooperative control characteristics of the hydrogen-electric coupling system.

The Simulated Experimental Design and Study of the Synergistic Treatment of Chicken Manure and Traditional Chinese Medicine Residues on Earthworm Growth and Soil Quality

Annelids conspicuously exert influence upon soil physicochemical attributes through their alimen-tary, burrowing, and excretion endeavors, thereby imparting ramifications upon soil erosion phenomena. Nev-ertheless, comprehension of the particular repercussions stemming from annelid activities vis-à-is soil erosion remains circumscribed. The primary objective of this investigation was to scrutinize the synergistic ramifica-tions of gallinaceous fecal matter and remnants of traditional Chinese medicinal substances on annelid prolif-eration and soil characteristics within a simulated experiment. In order to gauge the impact of annelid activities upon soil hydric distribution, runoff velocity, and soil erosion, a laboratory-simulated precipitation experiment was executed across three incline gradients (5 degrees, 10 degrees, and 15 degrees), featuring a uniform pre-cipitation intensity of 80 mm/h and a 60-minute precipitation duration post-runoff initiation. Findings evinced that annelids significantly heightened soil hydric infiltration and retention. In tanks inhabited by annelids, the increments in soil hydric retention were 93%, 51%, and 70% more elevated than those in control plots at incline gradients of 5 degrees, 10 degrees, and 15 degrees, respectively. Comparatively, earthworm activities led to a 70% reduction in runoff rate at a 5-degree slope, a 13% reduction at 10 degrees, and a 39% reduction at 15 degrees. However, soil erosion rates increased by 42% and 46% at slope gradients of 10 degrees and 15 degrees, respectively. Earthworms, through their feeding and burrowing activities, not only enhanced soil water infil-tration but also mitigated surface runoff while contributing to increased soil erosion. This research proffers invaluable perspicacity regarding the influence of subterranean fauna on the vicissitudes of soil erosion pro-cesses, furnishing empirical evidence amenable for assimilation into extant soil erosion simulation paradigms or as a substratum for the construction of nascent models.

Storyline attribution of human influence on a record-breaking spatially compounding flood-heat event.

Attribution of compound events informs preparedness for emerging hazards with disproportionate impacts. However, the task remains challenging because space-time interactions among extremes and uncertain dynamic changes are not satisfactorily addressed in the well-established attribution framework. For attributing the 2020 record-breaking spatially compounding flood-heat event in China, we conduct a storyline attribution analysis by designing simulation experiments via a weather forecast model, quantifying component-based attributable changes, and comparing with historical flow analogs. We quantify that given the large-scale circulation, anthropogenic influence to date has exacerbated the extreme Mei-yu rainfall in the mid-lower reaches of the Yangtze River during June-July 2020 by ~6.5% and warmed the co-occurring seasonal extreme heat in South China by ~1°C. Our projections show a further intensification of the compound event by the end of this century, with moderate emissions making the rainfall totals ~14% larger and the season ~2.1°C warmer in South China than the 2020 status.

N-IoU: better IoU-based bounding box regression loss for object detection

Object detection is one of the core tasks of computer vision, and bounding box (bbox) regression is one of the basic tasks of object detection. In recent years of related research, bbox regression is often used in the Intersection over Union (IoU) loss and its improved version. In this paper, for the first time, we introduce the Dice coefficient into the regression loss calculation and propose a new measure which is superior to and can replace the IoU. We define three properties of the new measure and prove the theory by mathematical reasoning and analysis of the existing work. This paper also proposes the N-IoU regression loss family. And the superiority of the N-IoU regression loss family is proved by designing simulation experiments and comparative experiments. The main results of this paper are: (1) The proposed new measure is better than IoU which can be used to evaluate bounding box regression, and the three properties of the new measure can be used as a broad criterion for the design of regression loss functions; and (2) we propose N-IoU loss. The parameter n of N-IOU can be debugged, which can be widely adapted to different application scenarios with higher flexibility, and the regression performance is better.

Design and implementation of fine-grained realistic 3D virtual simulation experiment

Abstract Based on the virtual simulation platform, this paper firstly builds a five-in-one comprehensive, realistic 3D virtual platform with teaching method orientation, experiment method frontier, course thinking daily, team building refinement, and assessment and evaluation comprehensiveness. Then the establishment of the UAV nonlinear mathematical model, the bit attitude calibration of the UAV model, the virtual simulation of the motion of the UAV model, and the construction of the UAV flight sky realistic model based on the UAV corner control of virtual reality technology, and also the analysis of the UAV formation keeping control research based on 3D virtual simulation. The results show that the UAV takes off from a random initial position, so the initial error is large, and then the formation holding error is less than 0.1m when flying in a straight line, and the formation error is less than 1.79 when coordinating a turn. When flying in formation for the 40s, the ground sends a formation spreading command to perform a reconnaissance mission, and this study has a catalytic effect on the development of UAV aerial photography virtual simulation.

A new control strategy of CAVs platoon for mitigating traffic oscillation in a two-lane highway

With the development of autonomous driving technology, designing connected automated vehicles (CAVs) control strategies to mitigate traffic oscillations has become a hot topic. Most current control strategies are mainly oriented to single-lane highway scenarios and do not consider vehicles' lane-changing behaviors. To address the gap, this paper proposes the Follower-Stopper-Platoon (FSP) strategy, which attempts to mitigate traffic oscillation by controlling a platoon of CAVs in a two-lane scenario. Firstly, based on the Follower-Stopper (FS) control and considering CAVs' platoon behaviors, this paper proposes the FSP strategy and compares it with two comparative strategies, the Baseline and FS strategies. Then, a two-lane mixed traffic flow cellular automata model is developed and used to verify the effectiveness of the FSP strategy. Finally, this study demonstrates the efficacy of the FSP strategy by designing simulation experiments and analyzes the effect of CAVs' platoon size on the control effect. The result shows that (1) the FSP strategy can overcome the shortcomings of the FS control and will increase traffic flow speed while mitigating traffic oscillations. (2) In a two-lane scenario, as penetration rates of CAVs and traffic densities increase, the FSP strategy's advantages in mitigating traffic oscillations, reducing energy consumption and pollutant emissions, and improving speed and passenger comfort are gradually apparent. (3) Under the FSP strategy, the larger the maximum size of the CAVs platoon, the better the performance of the mixed traffic flow in terms of traffic efficiency, stability, fuel consumption, and pollutant emission.

Computationally Efficient Adaptive Design of Experiments for Global Metamodeling through Integrated Error Approximation and Multicriteria Search Strategies

Gaussian processes (GPs) are a popular technique for global metamodeling applications. Their objective in such settings is to establish an efficient and globally accurate approximation of the response surface of computationally expensive simulation models. When developing such GPs, the design of (simulation) experiments (DoE) plays an important role in reducing the required number of model runs for obtaining accurate approximations. Sequential (adaptive) selection of experiments can provide significant advantages, especially when the response surface is characterized by localized nonlinearities. Such adaptive DoE strategies for global metamodeling applications typically focus on minimizing the predictive GP variance, representing an exploration strategy, while recent developments have additionally considered the reduction of the GP bias obtained through cross validation, representing an exploitation strategy. While significant focus has been placed on the definition of appropriate adaptive DoE criteria, computational challenges still exist that limit the widespread adoption of adaptive DoE techniques—for example, related to the additional computational demand for identifying the optimal new experiment(s) or the necessity to establish proper schemes to combine exploration and exploitation strategies. To address these specific challenges, this research investigates two new adaptive DoE formulations. The first one focuses on the approximation of the popular integrated mean square error (IMSE) DoE criterion. The computationally demanding GP predictive variance update (after addition of each candidate experiment), required in the original IMSE formulation, is replaced by an approximation based on the current predictive variance and the domain of influence that surrounds each new experiment. The approximation is established through a parametric formulation that leverages the GP kernel to describe the aforementioned domain, with characteristics that are progressively calibrated across the GP training stages, to minimize the discrepancy between the actual and the approximated IMSE. The second formulation establishes a multicriteria search for simultaneously identifying multiple Pareto optimal experiments that balance exploration and exploitation objectives, replacing conventional strategies that establish a weighted combination of these objectives to promote a single DoE selection criterion.

Aerodynamics Optimization of Multi-Blade Centrifugal Fan Based on Extreme Learning Machine Surrogate Model and Particle Swarm Optimization Algorithm

The centrifugal fan is widely used in converting mechanical energy to aerodynamic energy. To improve the pressure of the multi-blade centrifugal fan used in an air purifier, an optimization process was proposed based on extreme learning machine (ELM) combined with particle swarm optimization (PSO). The blade definition position parameter and blade definition radian parameter were designed using the full-factor simulation experimental method. The steady numerical simulation of each experimental point was carried out using ANSYS CFX software. The total pressure of the multi-blade centrifugal fan was selected as the optimization response. The optimized ELM combined with the PSO algorithm considering the total pressure response value and the two multi-blade centrifugal fan parameters were built. The PSO algorithm was used to optimize the approximation blade profile to obtain the optimum parameters of the multi-blade centrifugal fan. The total pressure was improved from 140.6 Pa to 151 Pa through simulation experiment design and improved surrogate optimization. The method used in the article is meant for improving multi-blade centrifugal total pressure. The coupling optimization of impellers, volutes, and air intakes should be comprehensively considered to further improve the performance of centrifugal fans.

Track Planning for Damage Detection on the Building Enclosure by UAV Considering Image Detection

Considering the rapid acquisition and detection task of building enclosure damage information and the natural environment characteristics of building enclosure, a new unmanned aerial vehicle (UAV) track planning framework considering image detection and UAV dynamic characteristics is proposed. Firstly, considering the position of UAV in the task space for track planning, combined with the characteristics of the sensor detection equipment carried by UAV, and the task requirements of extracting and identifying the damage edge features and texture features on the shell of the building; the detection efficiency and detection safety of UAV are improved to the maximum extent. Secondly, the Improved Circle Chaos Initialization Strategy, Adaptive Weight Strategy and Elite Perturbation Mechanism are introduced to solve the problem that the traditional honey badger algorithm (HBA) is easy to fall into local optimal solution and to ensure that the designed algorithm is more in line with the inspection planning requirements of the outer surface of the building. Furthermore, improved honey badger algorithm (IHBA) is compared with particle swarm optimization (PSO), whale optimization algorithm (WOA) and traditional badger algorithm in multi-dimensional horizontal through design simulation experiments, which shows that the design algorithm in this paper is efficient in solving the damage information collection of building enclosure.

Design of simulation experiments using Central Composite Design

Design of simulation experiments using Central Composite Design

An option-based capacity control mechanism for code-sharing alliances

This study addresses capacity control problems in code-sharing alliances, which deal with the determination of member airlines' booking limits. We propose an innovative option-based capacity control mechanism to overcome the drawback of inflexibility in blocked seat allotment for a two-airline code-sharing alliance. The mechanism incorporates the concept of a straddle, an advanced option strategy in finance, to allow member airlines the flexibility to tackle not only downward but also upward demand variations during the booking process. We design simulation experiments and use a case illustration to show scenarios when the code-sharing alliance can benefit from the proposed mechanism.

Popularization of science in colleges and universities in the new network media environment based on artificial intelligence

By introducing new network media and artificial intelligence technology into the field of science popularization in colleges and universities, this research strives to solve the practical problems of science popularization websites that are large but not distinctive in the current era, and tries to improve the social impact and economic benefits of such science popularization platforms, so as to promote platform innovation and break away from the stereotyped system design form. Through the establishment of a science popularization system for colleges and universities, the mainstream content management can be achieved, and the differentiation management between the main station and the substation can be completed. The platform design is implemented by Java EE technology, carrying multi-functional module components, completing the componentized configuration of the system, which can be developed sustainably and has good security. The university science popularization system can operate stably in most environments, and the security management measures are strict. It can take multiple means to effectively protect the security of information, and it is simple and easy to implement. It can be seen from the design of simulation experiment that this promotion system, through the design of hybrid recommendation strategy, can_ UserCF and SBBRM_ Based on the advantages of Doc2Vec algorithm, the accuracy and coverage of system recommendations are improved, making it more universal. And the hybrid recommendation results can be compared with the main recall model to prove the efficiency of the system. This paper introduces artificial intelligence technology into the field of science popularization in colleges and universities, so as to realize the system design and improvement based on the new network media environment.

Optimal design research structure rollover safety universe coach follow standards European safety ECE R66

Computer applications modeling finite element universe bus seats are technicaltopics. Then, skeletal model starting stiffness was analyzed using simulation to meet theEuropean tilt safety requirement ECE R66. As a result, the skeleton's initial volume andhardness are higher. Reduce the volume of the passenger car frame by performing athickness reduction in the conventional manner until skeletal deformation reaches a safespace. continuing to improve by altering the structural skeleton's design at deformationaffecting positions. Results showed improved volumes decreased by 5%. However, this improved method is not really optimal. Conduct simulation experimental design using optimization problems with an empirical regression equation from SPSS. applying Matlab GA's genetic algorithms to the empirical regression equation. Results achieved as the total volume of the selected variables decreased 18.5% compared to the prior optimization.

Economic and environmental impact of circular business models: A case study of White Goods-as-a-Service using multi-method simulation modelling

Circular business models are gaining traction in academia and industry as an instrument to deliver environmental benefits while being economically profitable. Despite this increased interest, studies that quantitatively assess the impact of circular business models are limited. This study provides researchers and practitioners with a quantitative analysis tool to assess the dynamics of circular business models from both an economic and environmental perspective. Using the case study of white goods-as-a-service, this study employs multi-method simulation modelling in combination with statistical design and analysis of simulation experiments to investigate the effect of different factors including payment schemes (i.e., fixed fee, pay-per-use, and hybrid) and subscription contract duration (i.e., long-term, mid-term, and short-term) on the economic and environmental performance of access-based models. In addition, as the adoption of access-based models is economically challenging for manufacturers due to a discrepancy between costs and revenue streams, this study analyses the effect of different levers to improve the liquidity performance of access-based business models including deposit schemes, cancellation and collection fees, as well as partnering with financial institutions to cover the initial revenue gap.

Wind speed and direction measurement method based on intelligent optimization algorithm.

Accurate and rapid measurement of wind speed and direction is an important research topic. However, the current measurement algorithms based on ultrasonic arrays are constrained by the large computational effort caused by the spectrum peak search, which hinders the development and application of ultrasonic array wind parameter measurement technology. To overcome this problem, this study applies an intelligent optimization algorithm for measuring wind speed and direction based on a co-prime arc ultrasonic array, which avoids the problem of a large number of calculations in the spectrum peak search. First, the spatial-spectral function of the propagator method algorithm is employed as the fitness function of the particle swarm optimization algorithm. Then, the wind parameter estimation problem is formulated as a function optimization problem, which realizes the fast and accurate measurement of wind speed and direction. Then, the artificial bee colony algorithm is used to measure wind speed and direction, further reducing the calculation amount of the wind parameter measurement. The performance and speed of the proposed method are verified by the design simulation and comparison experiments, reducing the time complexity by up to 90%. In addition, the feasibility of the proposed method is validated in hardware experiments.

Design and Application of Virtual Flexible Simulation Experiment Teaching Platform for Relay Protection

Abstract: Power system relay protection (PSRP) is a comprehensive course in electrical engineering undergraduate stage, which has a very strong engineering application. However, due to the influence of many factors, such as the power system security, high experimental cost, limited course hours, insufficient open conditions, and so on, traditional experimental teaching combined with hardware is difficult to meet the needs of students in various scenarios anytime and anywhere. Therefore, a low-cost virtual flexible simulation experiment teaching platform (VFSETP) is developed. The platform uses Simulink to build the simulation model of power system primary system and uses graphical user interface (GUI) to design the human-computer interaction interface. Through the communication between GUI and Simulink model, the protection experiments in various scenarios are successfully simulated. The VFSETP has many advantages such as simple interface, good visualization effect, and simple operation. The teachers can easily use it for classroom demonstration, and the students can use it for verification, analysis, expansion, and exploration of experiments in a variety of application scenarios without relying on the laboratory environment. This experimental mode is very conducive to the understanding of knowledge and the cultivation of practical innovation ability. The results of the student survey show that the design method and application mode of the platform can provide a reference for similar courses.

The Impact of Marking Itemized Prices in the Package on Consumers' Spending Pain and Satisfaction

In the shopping scenario, price is undoubtedly a very important factor for consumers. From the psychological level, how price affects consumers' judgment is a constantly updated topic. A further study is that the way prices are presented will subconsciously affect consumers' judgments and ultimately affect the trading volume. For enterprises, under the same cost, different presentation methods of prices can affect consumers' consumption behavior. Therefore, research on the presentation methods of commodity prices is conducive to revealing consumers' preferences, and ultimately, under the same conditions, different presentation methods of prices can directly affect the final trading volume, and to a certain extent, affect consumers' experience. To examine the impact of itemized prices on spending pain and consumer satisfaction, this study was based on the manner of the questionnaire survey, design of simulation experiments with relevant scenarios, and then analysis by the experimental results. In analyzing the realistic situation in which the total par price has been determined, the sum of prices is significantly higher than the total price, impact on consumer spending pain and consumer satisfaction, and it follows that, in this context, itemized price labeling can reduce consumer’s spending pain.At the same time, the conclusion of improving consumer’s consumption satisfaction, According to the present study, This conclusion can provide guidance for the price labeling of business sites.

How Temperature Measurement Impacts Pressure Drop and Heat Transport in Slender Fixed Beds of Raschig Rings

The axial temperature profile of a packed bed is often measured by thermocouples placed either directly in the bed or inside a thermowell centered in the reactor tube. Quantifying the impact of the thermocouple well on fluid flow, heat transport, and consequently on the measured temperatures is still an unresolved challenge for lab-scale reactors but especially, and even more so for multitubular reactors in industry. Particle-resolved computational fluid dynamics (PRCFD) simulations are a suitable approach to investigate the changes in transport phenomena exerted by inserting thermocouple wells into packed beds because they take into account the local packed bed structures. In this study, PRCFD simulations are performed based on design of simulation experiments (DoSE). The effect of the thermowell diameter and its thermal conductivity on the deviations between packed beds with and without thermowells is statistically quantified for characteristic integral quantities like pressure drop and tube wall-bed Nusselt number. The axial temperature profiles inside the thermowells can be computed efficiently with reasonably accuracy applying the Nusselt number correction as derived in this study from the DoSE in a one-dimensional pseudo-homogeneous energy balance.

Influencing Factors of Virtual Simulation Experiment Teaching Effect Based on SEM

Virtual simulation experiment teaching has been extensively applied to higher education. Recognizing the influencing factors of virtual simulation experiment teaching effect and analyzing the influencing strength of each factor has become a highly concerning problem in the education circle. To improve the virtual simulation experiment teaching effect effectively and make feasible optimization measures, influencing factors were first reviewed and analyzed in this study based on previous research from four perspectives of engagement of students, the academic basis of students, virtual simulation experiment design, and teachers’ guiding. Second, the conceptual model and structural equation model (SEM) to analyze the virtual simulation experiment teaching effect were constructed by the SEM analytical method. On this basis, nine hypotheses of the model were designed. Finally, a case study based on the three built virtual simulation teaching projects was conducted. The significance of the influencing factors on the teaching effect was verified through questionnaires, SPSS analysis, and AMOS software. The acting path and influencing the strength of influencing factors were analyzed. Some strategies and measures to improve the virtual simulation teaching effect were proposed. Results demonstrated that virtual simulation experiment design is the primary influencing factor of the teaching effect, followed by engagement of students, teachers’ guiding and academic basis of students successively. Conclusions can provide theoretical support and decision-making references to formulate strategies for improving virtual simulation experiment teaching.

CURRICULUM DESIGN OF VIRTUAL SIMULATION EXPERIMENT OF THERMISTOR TEMPERATURE MEASUREMENT CHARACTERISTICS BASED ON EDUCATIONAL PSYCHOLOGY

Abstract Background In order to meet the social demand for applied and innovative talents and meet the “advanced, innovative and challenging” university education standard of the Ministry of education, colleges and universities continue to explore new training modes and teaching forms. High quality experimental teaching plays an important role in cultivating students' practical ability and innovative ability. Thermistor is an important category of sensors. Through experimental operation, students can effectively understand and master its physical structure, working principle and application characteristics. Subject and Method In order to overcome the disadvantage of limited resources of traditional thermistor equipment, the design of this virtual simulation experiment follows the principle of “maximum authenticity, combination of virtualization and authenticity”. From the perspective of educational psychology, taking the temperature control link of central heating and air supply system as the background, the experimental steps are designed around the thermistor, and the students are guided to carry out the temperature measurement characteristic experiment of thermistor in combination with the knowledge points such as PID control algorithm and single chip microcomputer data processing. Each step of the experiment is designed to test students' mastery of corresponding knowledge and skills. In addition, by scientifically simplifying and virtualizing each link of the gas supply system, on the premise of ensuring the integrity of the process and the authenticity of the experience, the experimental steps outside the scope of the “sensor” course are still “achievable” for the experimenter. Form the whole process of communication before, during and after the experiment to effectively explain knowledge to students. Before the experiment, students should learn the theoretical knowledge, precautions and operation skills required by the experiment; During the experiment, students should understand information, make plans and collect data; After the experiment, students and teachers make full use of the scattered time segments to communicate on the problems in the experiment. Results Students can query the technical data, choose the design scheme, observe the experimental results, deepen the understanding of thermistor knowledge, improve the engineering practice ability, and get rid of the limitations of time and space in the process of repeatedly “making mistakes” and “correcting mistakes”. The project can completely copy a system through virtual instrument. No physical heat source, no equipment performance degradation, no special safety control requirements, and no restrictions on equipment resources, site and time. It can effectively solve the problems that thermistor is easy to cause performance attenuation, precision decline and affect the effect of experimental teaching. Conclusion After long-term use, the experimental design will not lead to the decline of component performance and material consumption. The experimenter can remotely complete the experimental operation anytime and anywhere through the computer connected to the network, so as to obtain the sensory experience close to the actual operation of the experimental equipment. In short, we should carry out relevant combination of industry and education according to our own advantages and characteristics. Make clear the goal of motivation by example, and regularly hold activities such as successful model sharing, experience introduction and project display, so as to set a successful example for positive emotions, clarify the specific objectives of the activities, form a strong psychological momentum, stimulate internal potential and help the realization of positive behavior. We should strengthen professional guidance, give full play to the concentration of professionals, high intelligence, professional knowledge in business fields, and give full play to the advantages of talents and intelligence. We can organize experts and scholars to establish a professional bid winning guidance team, give full play to the business projects of experts and scholars in their respective fields, and carry out scientific research on relevant projects. Acknowledgements Supported by a project grant from Ministry of Education Collaborative Education Project (202102343015).