Performance Simulation Research Articles

A fuel cell performance simulation method based on pore-scale gas diffusion layer models obtained from X-ray computed tomography under different assembly pressures

The assembly pressure significantly influences the performance of proton exchange membrane fuel cells. In earlier studies, performance simulations based on volume-averaged formulae tended to smooth out the inherent non-uniformity of the gas diffusion layer (GDL) and this needs to be improved. In this study, an innovative simulation method is proposed for high-temperature proton exchange membrane fuel cells (HT-PEMFCs), which can directly couple pore-scale GDLs with fuel cells when examining fuel cell performance. We used X-ray CT to reconstruct a carbon fiber paper sample (TGP-H-060) under different pressures. These reconstructions were then directly coupled with volume-averaged components to form multiscale models of HT-PEMFCs. Governing equations of mass, momentum, species and charge were directly solved in the microstructure and fluid channels to obtain the polarization curve of the HT-PEMFC. The proposed model combines studies of fuel cell performance with evaluation of the properties of pore-scale GDLs. The results show that using the proposed method, not only can the influence of assembly pressure on the overall performance (i.e. polarization curves) of fuel cells be obtained, but also the influence of assembly pressure on the gas distribution in pore-scale channels of GDLs can be clearly revealed, which can guide the optimization of GDL structure.

Integrating discrete event simulation and data envelopment analysis for system performance and efficiency evaluation

ABSTRACT Healthcare facilities, particularly outpatient clinics, are crucial for local communities’ medical needs. To enhance their performance, these facilities need to optimize their operations. Key system performance metrics, such as patient throughput, waiting times and cycle times, can quantitatively be measured using discrete event simulation (DES). DES replicates facility structures and behaviours, offering a valuable platform for assessing the configuration effects of resources on system performance. However, current DES tools cannot identify the best resource configurations for future performance improvement. To address this issue, this paper develops a DES model for an outpatient clinic and improves its performance through data envelopment analysis (DEA). The case study involves a clinic in Northern Malaysia, where relevant data were observed and collected. The analysed data were then input into the DES model. The model measured the clinic’s current performance and assessed the impact of its resource configurations. 37 different resource configurations were tested, and their relative efficiencies were evaluated using DEA. The analysis revealed room for improvement in resource allocation.

Numerical simulation and analysis of fatigue performance for the humeral stem

Background and objectiveFatigue failure of the humeral stem is a severe long-term failure after shoulder arthroplasty, causing harm to patients and resulting in complex revision surgeries. However, there are few studies on humeral stem fatigue testing, and corresponding testing standards have not been established. Therefore, this study aims to investigate the fatigue performance of the humeral stem by establishing an efficient numerical simulation method. MethodsMaterial properties are obtained by uniaxial tensile and fatigue tests. A parameterized static analysis program was written, and an automated fatigue numerical simulation platform was established using Abaqus, Fe-safe, and Isight in combination, enabling the establishment of a numerical simulation method for the fatigue performance of the humeral stem. ResultStandard testing conditions include an 8 mm diameter humeral stem, a 40-21B humeral head, an 8° tilt angle, and a 2 mm fillet radius. Further research found that the fatigue life of the humeral stem decreases with increasing patient weight, and patients should control their weight after surgery. ConclusionsThe established automated fatigue numerical simulation platform avoids repetitive operations and efficiently completes large-scale calculations, guiding preoperative humeral stem selection and testing.

Reinforcement Learning for Jointly Optimal Coding and Control Policies for a Markovian System Controlled over a Communication Channel

This paper develops approximation and optimality results for the optimal control of a networked system. In this system, a Markovian process is managed over a finite-rate, noiseless communication channel. Solving this problem involves determining joint optimal coding and control policies that minimize cost over time. While theoretical results on optimal coding and control structures exist, practical implementation has remained largely infeasible for non-linear systems due to the computational complexities and uncountable state spaces. This research introduces an approach that combines structural results with reinforcement learning (RL) techniques. The method uses regularity properties of the system to approximate the uncountable state space with a countable one, which allows reinforcement learning algorithms to achieve near-optimal solutions. Specifically, we establish that finite model approximations (where infinite state spaces are quantized to finite ones) and sliding finite window approximations (where a finite memory "window" of past control actions is maintained at each time step) can be employed to develop near-optimality. These approximations allow the system to be reformulated as a Markov Decision Problem (MDP) with a finite state space, making RL algorithms implementable. The convergence of the reinforcement learning algorithm to a near-optimal policy (under both the previous approximations) is supported by theoretical analysis and performance simulations. We ensure that the solutions obtained are not only computationally feasible but also nearly optimal with respect to the original problem. The applications of this work extend to many networked control systems, especially those with zero-delay coding and partially observable Markov decision processes (POMDPs). By integrating structural results with learning algorithms, this paper provides a practical framework for implementing optimal control in finite-rate environments.

Performance simulation and energy efficiency analysis of multi-energy complementary HVAC system based on TRNSYS

The failure rate and operating cost of the C-B (chiller-gas boiler) system, which has been in use for a long time, are increasing year by year, but there is a lack of reasonable programs and effective measures on how to retrofit the C-B system. In order to explore the prospect of ground-source heat pumps applied to the retrofit of C-B systems in HSCW (hot summer and cold winter) zone, this study designed a G-C-B (GSHP-Chiller-Boiler) system in a partial retrofit context and constructed a TRNSYS numerical simulation model of the retrofit system. Secondly, the performance and energy efficiency of the system is analyzed as well as different control strategies for the ground source heat pump cooling tower are discussed. Finally, the energy conversion efficiency of the chiller is compared based on the energy flow of the system. Studies have shown that the G-C-B system can achieve a seasonal performance factor of 5.3 during the cooling season and 4.1 during the heating season. Compared to the existing C-B system, year-round electricity consumption was reduced by 21 %, gas consumption by 92 %, and combined energy demand by 49.6 %. With the addition of GSHP, the energy conversion efficiency of the chiller has also increased by 21 %. The soil temperature of the G-C-B system increased by less than 0.5 °C after ten years of continuous operation. This paper can provide a valuable theoretical basis for the energy form modification of the C-B system in the HSCW zone.

Impact of Spatial Layout Design on Energy Consumption of Ice Rinks in Cold Regions

The differentiated physical environment requirements within the internal space of ice rinks in cold regions result in a complex heat exchange process, which becomes the primary cause of high energy consumption. Therefore, analyzing the impact mechanisms of spatial layout parameters on the energy consumption of ice rinks is crucial during the early design stages. This study employed the Delphi method to identify the key parameters affecting the total energy consumption of ice rinks. It conducted single-factor experiments using building performance simulations to quantify the relationship between each layout parameter and the energy consumption. Based on the single-factor experiment results, orthogonal experiments were conducted to develop an energy-efficient spatial layout combination. The study indicates that the height-to-width ratio and the mixed area width are the most significant parameters. By adjusting the values of these parameters, the total energy consumption can be reduced by approximately 18% to 31%. The spatial layout strategy for ice rinks in cold regions proposed in this study will help architects make more effective decisions during the early design stages.

Analysis and Simulation of Permanent Magnet Adsorption Performance of Wall-Climbing Robot

In response to problems such as insufficient adhesion, difficulty in adjustment, and weak obstacle-crossing capabilities in traditional robots, an innovative design has been developed for a five-wheeled climbing robot equipped with a pendulum-style magnetic control adsorption module. This design effectively reduces the weight of the robot, and sensors on the magnetic adsorption module enable real-time monitoring of magnetic force. Intelligent control adjusts the pendulum angle to modify the magnetic force according to different wall conditions. The magnetic adsorption module, using a Halbach array, enhances the concentration effect of the magnetic field, ensuring excellent performance in high-load tasks such as building maintenance, bridge inspection, and ship cleaning. The five-wheel structural design enhances the stability and obstacle-crossing capability, making it suitable for all-terrain environments. Simulation experiments using Maxwell analyzed the effects of the magnetic gap and the angle between the adsorption module and the wall, and mechanical performance analysis confirmed the robot’s ability to adhere safely and operate stably.

Efficiency enhancement of bicycle anti-lock braking systems (ABS): Design and optimization of solenoid actuators through finite element analysis and performance simulation

The rising popularity of cycling underscores the need for enhanced safety, particularly under challenging braking conditions. This study introduces a novel high-power switch valve designed explicitly for Bicycle Hydraulic Disc Brakes (BHDBs), incorporating Hydraulic Anti-lock Braking Systems (ABS). Comprehensive Finite Element Analysis (FEA) modeling and subsequent optimization of an existing solenoid valve’s internal geometry were performed through 2D and 3D simulations to evaluate magnetic flux. The improved design achieved a maximum output force of 280 N with a linear stroke of approximately 3.5 mm. Notably, the enhanced system exhibited a 28% reduction in required current, from 5.0 to 3.6 A, a result validated through LabVIEW-equipped custom tests, which stress the credibility of the research. This study underscores significant advancements in high-power switch valves for BHDBs, promising enhanced braking efficiency and safety in high-performance, battery-powered bicycles. These findings not only promise enhanced safety for cyclists but also suggest the potential for broader application in energy-efficient and sustainable bicycle ABS technology, contributing to improved cyclist safety without compromising the environmental and health benefits of cycling. The potential impact of this research extends beyond the immediate context, offering insights that could be applied to other areas of technology and safety.

Numerical Simulations of the Prethawing Performance of Lime-Energy-Column Embankments in Warm Permafrost Regions

Numerical Simulations of the Prethawing Performance of Lime-Energy-Column Embankments in Warm Permafrost Regions

Numerical simulation study of liquid–liquid mixing of high-viscosity fluids under laminar flow in a reverse flow multi-stage Tesla valve

In this study, computational fluid dynamics was employed to conduct a numerical simulation of the mixing performance and flow characteristics of two highly viscous liquids under laminar flow conditions within a reversed Tesla valve. Scalar transport techniques are employed to analyze the efficiency of liquid–liquid mixing in high-viscosity fluids. The focus of this study is to investigate the optimal mixing behavior between different parameters. Results indicate that an increase in Reynolds number leads to intensified Dean vortices, thereby promoting liquid–liquid mixing efficiency. Additionally, the mixing coefficient shows a negative correlation with Schmidt number (Sc), with a diminishing impact on the mixing coefficient when Sc ≥ 104. This is attributed to the dominance of fluid flow in controlling mixing within the channel at higher Schmidt numbers. Furthermore, this study compares the influence of valve angles (α) and stage numbers (n) on the mixing coefficient under identical Reynolds and Schmidt number conditions. As the number of Tesla valve stages increases, fluid acceleration within the pipeline is enhanced. Moreover, larger valve angles result in increased lengths of the curved section, leading to higher mixing efficiency. Therefore, to enhance mixing efficiency, it is recommended to increase the valve angle and the number of stages in the Tesla valve.

Conversion of a small size passenger car to hydrogen fueling: simulation of full load performance

Abstract Hydrogen offers a valid choice when considering zero emissions transport. This alternative fuel is well suited for spark ignition (SI) engines and it can be implemented with relatively minor changes in terms of added components. Initial evaluations of feasibility with respect to available space for the fuel tank revealed that it is possible to convert a small size passenger car to hydrogen fueling and maintain a range comparable to the fully electric alternative. Peak power assessment showed that additional boosting was required compared to gasoline operation, close to the limit of compressor surge. As a result, the present study extended the engine speed range so as to evaluate full load performance levels that can be obtained when using hydrogen. 0D/1D simulation was applied for simulating power unit output as well as related control parameters. A dedicated laminar flame speed sub-model was implemented for including fuel chemistry effects. Predicted combustion phasing showed the required changes in ignition timing when switching fuels and revealed that the engine could be operated close to stoichiometry when using hydrogen. A reduction of torque was calculated at low engine speed, even if peak power ratings were practically the same as with gasoline fueling.

Research on reconfigurable systems in discrete manufacturing workshops

Abstract With the development of smart manufacturing, the demand for personalized production has made reconfigurable systems in the manufacturing industry a focal point of research and application in high-end manufacturing. The paper analyzes the current status of the manufacturing industry and the challenges of reconfigurable technology. Furthermore, it designs and develops a reconfigurable system for discrete manufacturing of automotive components. The paper focuses on issues such as creating reconfigurable models, designing adaptive reconfiguration algorithms, accomplishing the creation of multi-layered models, the design of rule libraries, and algorithm implementation. The reconfiguration result scheme can be input into commercial software for performance simulation, and can directly integrate with production systems to complete production planning. This demonstrates the rationality of the reconfigurable models in the system, the correctness of the reconfiguration algorithms, and the effectiveness of the system, providing a theoretical basis for reconfigurable production lines.

Investigation on mechanical properties and stealth characteristics of a novel gradient-stitched composite structure

Based on the far field function of electric field, a new glass carbon fiber gradient-stitched structure is proposed and designed in the paper. In the frequency range of 8–28 GHz, the electric field distribution of transverse electric and magnetic field (TEM) waves incident obliquely on the surface of the structure by optimizing the glass fiber fabric units. It is confirmed that the surface has the function of suppressing electromagnetic wave reflection. The electrical performance simulation and testing results of the structure show that the radar cross section (RCS) is reduced by 90% in the frequency range of 12.3–26.5 GHz. In addition, a multi-scale analysis model is established to quickly predict the tensile modulus and strength of the composite material. The strength and modulus reached 26.9 GPa and 403 MPa, respectively. The simulating and testing results of mechanical properties are in good agreement.

A Review of Experimentation Numerical Simulation of Low-Velocity Impact Performances and Damages of Fiber-Reinforced Composites

Fiber-reinforced composites (FRCs) are extensively utilized in various industries due to their lightweight and high-strength properties, making the understanding of their response to low-velocity impact (LVI) crucial for ensuring structural integrity, performance and invisible internal damages that can compromise performance and safety. This paper critically examines the current state of research on the low-velocity impact behavior of FRCs, focusing on both experimental and numerical simulation approaches. The review comprehensively surveys on characterizing and modeling the response of FRCs to low-velocity impacts leading to damages. The effects of parameters including composites preparation; impact mechanics; testing methods; induced damages including assessment methods; different performance parameters including impact energy, force, load, impact resistance; post-impact damages and their resistance; performance and damage affecting different factors; numerical and simulation modeling are discussed. Current challenges and future prospects regarding the subject matter is highlighted. The comprehensive analysis presented in this review goals to consolidate current knowledge, identify research gaps, and guide future endeavors in enhancing the understanding of low-velocity impact (LVI) behavior in fiber-reinforced composites (FRCs).

Quantifying Uncertainty with Conformal Prediction for Heating and Cooling Load Forecasting in Building Performance Simulation

Quantifying Uncertainty with Conformal Prediction for Heating and Cooling Load Forecasting in Building Performance Simulation

An efficient multi-fidelity simulation approach for performance prediction of adaptive cycle engines

Adaptive cycle engine (ACE) with multi-stream, modulated bypass ratio, and high-thrust/high-efficiency mode provides the capability of multiple mission adaptation for the next-generation aviation propulsion system. The low-fidelity zero-dimensional (0D) performance simulation method is commonly adopted in conventional engines such as turbofan and turbojet. However, it is hard to accommodate well to ACE with complex variable geometry schemes and strong interaction between components. This paper presents an efficient multi-fidelity simulation approach, often referred to as component zooming, for predicting the performance of ACE with the three-stream configuration. The one-dimensional (1D) mean-line models of the adaptive fan and low-pressure turbine (LPT) are integrated into the 0D ACE model by the iteratively-coupled method. The performance predicted by the multi-fidelity ACE models with different component zooming strategies is compared. The maximum deviations of thrust, specific fuel consumption, turbine inlet temperature, and bypass ratio between the 0D/1D Adaptive Fan/1D LPT coupled model and 0D ACE model are −10.8%, −4.4%, −5.4% (−75 K), and 1.6%, respectively, which are considerable and non-negligible for the application in the design stage of ACE. The computing time of all the multi-fidelity models is less than 2 minutes. The effects of the key aerodynamic parameters of the adaptive fan and LPT on the engine performance are also evaluated. The proposed approach provides a generic and efficient solution for multi-fidelity ACE performance prediction with acceptable computing resource requirements and time cost, which is applicable in the engine conceptual and preliminary design stage.

Rural heat island effect of centralized residences in China: Mitigation through localized measures

China has implemented a Centralized Rural Policy since 2004 to enhance energy efficiency. However, this has led to the potential creation of a Rural Heat Island (RHI) effect, which could diminish outdoor thermal comfort and increase building energy consumption during hot summers. While most studies on heat island effect focus on spatiotemporal variations and heat mitigation measures, there is limited research on rural areas, particularly the special layout of rural residences. Additionally, most studies only consider the outdoor environment, overlooking indoor thermal comfort and building energy consumption. Therefore, in order to investigate the RHI effect and assess the efficacy of localized heat mitigation measures, this study analyzed 22 types of courtyard layout patterns in a typical centralized village in northern China through detailed field measurements and performance simulations. The results show an obvious heat island effect in the rural centralized residences, where residential zones recorded average temperatures of 1.6 °C higher than those of rural boundaries. Courtyards featuring a south wing significantly alleviated outdoor thermal stress, reducing the discomfort time of extreme Physiological Equivalent Temperature (PET) by 1.5 h compared to those courtyards with a wall. Among the four localized heat mitigation measures examined, the featured black fabric shade performs best for its effectiveness in mitigating outdoor thermal stress, capable of reducing the courtyard's maximum Mean Radiant Temperature (Tmrt) by 21.5 °C and decreasing the duration of extreme PET by 2 h. Photovoltaic modules installed on the roof not only generate energy but also alleviate outdoor thermal stress, reducing the maximum Tmrt by 12.9 °C and lowering 23 % to 28 % daily energy demand, making them highly suitable for deployment in rural areas with high rates of energy poverty. The simulated results indicate that these localized heat mitigation measures mutually reinforce each other in reducing the RHI effect. The combination of four heat mitigation measures can reduce PET by up to 20 % and EUI by up to 44 % compared to the original courtyard. Incorporating these localized strategies into planning practice enables rural planners and policymakers to develop effective interventions against the RHI effect.

IDA-Based Seismic Fragility Analysis of a Concrete-Filled Square Tubular Frame

Based on the incremental dynamic analysis (IDA) method, this paper conducts seismic fragility analysis of a CFST plane frame, a CFST spatial frame under 1D (one-dimensional) ground motions, and a CFST spatial frame under 2D (two-dimensional) ground motions, with different attacking angles. Firstly, nine-story, three-span CFST frame structures (including the plane frame and spatial frame) were modeled in OpenSees, based on the accurate simulation of the hysteresis performance of the test CFST frames. Then, twenty-five groups of ground motions were employed to analyze the seismic response. Lastly, the IDA curve clusters, probabilistic demand models, and seismic fragility curves of frame structures were researched, respectively. The analytical results showed that the exceeding probability of the spatial frame under 2D ground motions was successively greater than that under 1D ground motions, and greater than the plane frame, and the maximum difference at each performance level was up to 6% and 16%, respectively. The fragility analysis result of the spatial frame was sensitive to the attacking angle of ground motion, and the exceeding probability of the 135°, 150°, and 165° fragility curves was larger than that of the 0° (original attacking angle) fragility curve at each performance level. The research results provide a reference for seismic fragility analysis of CFST frame structures employing the IDA method.

Simulation and Optimization of Hole Transport Layer Performance of Lead‐Free Perovskite Solar Cells

AbstractThis article employs a combined approach using SCAPS and MS software to screen the cell structure combinations of various cell materials such as MASnI3, FASnI3, TiO2, C60, spiro‐OMeTAD, PTAA, CuI, CuSCN, Cu2O, and NiO. The structure of lead‐free perovskite solar cells (PSCs): FTO/TiO2/MASnI3/Cu2O/Au is identified as having the best cell performance. Based on Molecular Dynamics theory, in combination with physical experimental preparation and characterization results, it is found that Cu2O thin films treated with annealing at 388 °C, as the hole transport layer material, can significantly enhance the performance of PSCs. This optimization led to power conversion efficiency (PCE) and fill factor (FF) performance indicators reaching 29.2% and 87.32%, achieving excellent cell performance.

Advanced cyclic constitutive model and parameter calibration method for austenitic stainless steel

Austenitic stainless steel is recognized for its potential in improving structural seismic resistance due to its exceptional ductility. This study seeks to analyse the material characteristics and cyclic constitutive model of austenitic stainless steel under cyclic loading using a combination of experiments and numerical studies. The primary goal is to enhance the precision of numerical simulations predicting the seismic performance of stainless steel and to minimize the costs associated with calibrating the parameters of the cyclic constitutive model. By conducting cyclic loading experiments on stainless steel with different plate thicknesses, the hysteresis curves under different loading protocols were obtained. The loading protocol significantly influences the cyclic hardening behaviour of stainless steel. To calibrate material parameters in the Chaboche model more effectively, a new parameter calibration method based on genetic algorithm optimization is proposed. Additionally, a method is proposed to calibrate the material parameters of the Hu model by utilizing the monotonic tensile stress-strain curve of austenitic stainless steel, which provides a new material model option for the numerical simulation of stainless steel seismic performance. The applicability of the Chaboche model and the Hu model in numerical simulations of stainless steel members is then verified and compared using existing seismic performance test results. The findings indicate that the Hu model offers more accurate numerical simulations of cyclic loading on austenitic stainless steel members compared to the Chaboche model.