Design Optimization Research Articles

Wind turbine dynamic wake flow estimation (DWFE) from sparse data via reduced-order modeling-based machine learning approach

Wind turbine wake poses a significant challenge in wind farm operations, affecting power generation efficiency. This study introduces a Dynamic Wake Flow Estimation (DWFE) framework designed to predict wind turbine wake evolution from sparse measurement data. The framework integrates Gaussian Process Regression (GPR), Proper Orthogonal Decomposition (POD), and Long Short-Term Memory (LSTM) networks. Specifically, GPR plays a pivotal role in DWFE by enabling the transformation of flow fields discrete sensor signals into coherent, low-dimensional flow fields which is crucial for accurate flow field predictions, while POD aids in dimensionality reduction and LSTM forecasts temporal wake dynamics, improving both predictive accuracy and computational efficiency. Parametric analysis demonstrates that the robustness and adaptability of the framework improve prediction accuracy with increased sensor density and flexible POD modes. The DWFE framework demonstrates high accuracy in wake flow estimation even with limited data, effectively capturing dynamic wake behavior. Future work will extend this approach to various topographic and climatic conditions, optimizing computational efficiency, and improving interpretability. These advancements will expand the framework's applicability in wind energy and other engineering fields requiring precise flow prediction, emphasizing DWFE's potential in advancing wind farm design, operation and renewable energy optimization.

EURAD state-of-the-art report: development and improvement of numerical methods and tools for modeling coupled processes in the field of nuclear waste disposal

The Strategic Research Agenda (SRA; https://www.ejp-eurad.eu/publications/eurad-sra) of the European Joint Programme on Radioactive Waste Management (EURAD; https://www.ejp-eurad.eu/) describes the scientific and technical domains and sub-domains and knowledge management needs of common interest between EURAD participant organizations. Theme number 7 is entitled “Performance assessment, safety case development and safety analyses.” A list of research and development priorities and activities of common interest to be addressed within EURAD for theme 7 have been established. Amongst others, the Understanding and modelling of multi-physical Thermo-Hydro-Mechanical-Chemical coupled processes (THMC) occurring in radioactive waste disposal is a major and permanent issue to support optimization of design and safety case abstraction. To tackle this challenge a research work package entitled “DONUT: Development and improvement of numerical methods and tools for modelling coupled processes” has been conducted within the EURAD join programming initiative. The purpose of this work package is to improve/develop methods or numerical tools in order to go a step further in development of (i) relevant, performant and cutting-edge numerical methods that can easily be implemented in existing or new tools, in order to carry out high-performance computing to facilitate the study of highly coupled processes in large systems, (ii) numerical scale transition schemes for coupled processes, (iii) innovative numerical methods to carry out uncertainty and sensitivity analyses. In this paper the work carried out within the DONUT work package is put in perspective regarding the existing concept and literature on the field. It does not pretend to be exhaustive but rather to put emphasis on particular issues tackled during the project.

Energy-based design optimization of Adept test trajectory for SCARA robots using clothoid curve

Energy-based design optimization of Adept test trajectory for SCARA robots using clothoid curve

Relieving postherpetic neuralgia pain via gabapentin-loaded bigels as an auspicious topical drug delivery system.

Over the past decades, a substantial portion of the population worldwide has been infected with varicella zoster and most cases developed shingles. Unfortunately, shingles is usually accompanied by postherpetic neuralgia, which may persist for months to years after the resolution of the viral infection. Gabapentin is an orallygamma-aminobutyric acid analogue approved by the Food and Drug Administration to manage shingles postherpetic neuralgia. However, gabapentin shows nonlinear pharmacokinetics, with variable absorption and bioavailability along with its short half-life and long side effects that may include dizziness and somnolence, which calls for an appropriate topical dosage form. Bigels are unique semisolid dosage forms with boosted penetrability and satisfactory hydrophilic texture. The current work pointed to formulating gabapentin-loaded bigels for the treatment of postherpetic neuralgia, where the analysis and optimization of design were performed via Design-Expert®. The selected bigel (F5), incorporating 400mg Span 60, 1000mg Tween 80, and 1000mg Transcutol, displayed spherical nanosized particles with acceptable viscosity and spreadability. Subsequent topical application of the selected bigel on the skin of Wistar rats, F5, demonstrated a boosted accumulation of gabapentin in the skin similar to PLO gel but superior to the drug solution. Furthermore, a histopathological study demonstrated the biosafety of the selected bigel when applied topically. Accordingly, gabapentin-loaded bigel would be considered a potentially topical dosage form for the delivery of gabapentin for the management of postherpetic neuralgia.

Study on Optimization of Urban Architectural Design Based on Public Demands

As the material standard of living continues to improve, people's needs at a higher level have triggered a new craze. The change of view on architecture has become an intuitive perception of this boom in people's lives, and the call for architectural design to respond to public demands is increasing. This paper compares the design and practical effects of the Amsterdam Library and the Tencent Building in Chengdu for public demands, combines the new demands of the public for modern architecture to conduct a literature analysis of relevant cases, and then explores the direction and strategy of modern architectural design and optimization oriented by public demands. It is found that the physiological, psychological, and health values provided by buildings are desired by the public but not fully satisfied, and that multifunctionality, aesthetic experience, green intelligence, and humanization are the mainstream of future buildings desired by people. Refining and grasping the information of public demands and using it as a reference is an important part of reaching the transformation of architectural design. In urban building construction, the use of the cycle is generally longer, the current reality is to minimize the misalignment of supply and demand, which means that must do a good job of mastering the information of public demands and have a certain prediction of its future direction, reserved for the transformation of the elastic space, with the times.

Size-Dependent Mechanical Properties and Excavation Responses of Basalt with Hidden Cracks at Baihetan Hydropower Station through DFN–FDEM Modeling

Basalt is an important geotechnical material for engineering construction in Southwest China. However, it has complicated structural features due to its special origin, particularly the widespread occurrence of hidden cracks. Such discontinuities significantly affect the mechanical properties and engineering stability of basalt, and related research is lacking and unsystematic. In this work, taking the underground caverns in the Baihetan Hydropower Station as the engineering background, the size-dependent mechanical behaviors and excavation responses of basalt with hidden cracks were systematically explored based on a synthetic rock mass (SRM) model combining the finite-discrete element method (FDEM) and discrete fracture network (DFN) method. The results showed that: (1) The DFN–FDEM model generated based on the statistical characteristics of the geometric parameters of hidden cracks can consider the real structural characteristics of basalt, whereby the mechanical behaviors found in laboratory tests and at the engineering site could be exactly reproduced. (2) The representative elementary volume (REV) size of basalt blocks containing hidden cracks was 0.5 m, and the mechanical properties obtained at this size were considered equivalent continuum properties. With an increase in the sample dimensions, the mechanical properties reflected in the stress–strain curves changed from elastic–brittle to elastic–plastic or ductile, the strength failure criterion changed from linear to nonlinear, and the failure modes changed from fragmentation failure to local structure-controlled failure and then to splitting failure. (3) The surrounding rock mass near the excavation face of underground caverns typically showed a spalling failure mode, mainly affected by the complex structural characteristics and high in situ stresses, i.e., a tensile fracture mechanism characterized by stress–structure coupling. The research findings not only shed new light on the failure mechanisms and size-dependent mechanical behaviors of hard brittle rocks represented by basalt but also further enrich the basic theory and technical methods for multi-scale analyses in geotechnical engineering, which could provide a reference for the design optimization, construction scheme formulation, and disaster prevention of deep engineering projects.

Application of B-spline basis functions as harmonic functions for the concurrent shape and mesh morphing of airfoils

The automatic deformation of the computational mesh along with the deformed geometry in design optimization cycles is a valuable procedure, as it reduces the required time for the construction of new meshes. The introduction of harmonic coordinates for the deformation of objects included within a closed mesh (cage) has been introduced in computer graphics. Harmonic coordinates result from solutions to the Laplace’s equation (harmonic functions) using a numerical solver. In this work, a modification to the classical harmonic coordinates’ concept is introduced for the deformation of 2D geometries (and the corresponding computational mesh) which are defined as B-spline curves. The B-spline basis functions are used as harmonic functions along the mesh boundary, being also the geometry to be deformed. Thus, any deformation of the B-spline boundary, through the movement of the curve’s control points, can be successfully propagated to the interior of the computational domain, resulting in the concurrent and conformable modification of the B-spline boundary and the entire computational mesh. For the computation of harmonic coordinates a node-centered Finite-Volume based Laplace solver for unstructured meshes is used, enhanced with an agglomeration multigrid scheme. The proposed method is applied and assessed for the shape and mesh morphing of airfoils.

Research on Design Optimization of Barrier-Free Public Facilities

With the change in the development of civilization, China has paid more and more attention to the people-oriented concept, and the degree of care for special groups such as the disabled has gradually increased. However, due to the increase of the population base and the expansion of urbanization areas, the demand for infrastructure is expanding, and some facilities such as barrier-free facilities are difficult to perfect in the specific application of details. This means that it is difficult to provide proper physical and psychological services for special people, and it also lays hidden dangers for later use and maintenance. Because the existing barrier-free public facilities have a certain time lag in theoretical design, they have exposed some inconvenient problems in practical application, and there are many places that can be improved and optimized. At the same time, the development of science and technology has provided many emerging techniques that can be applied in the field of research. This paper lists some problems existing in the operation of barrier-free public facilities and puts forward some optimization and improvement schemes based on the existing technology and the expected development of technology in the near future.

Material and Parametric Design Optimization of Improved Heat Transfer Rate of AC Condenser

Air conditioner system is made up of a condenser that removes unwanted heat in an enclosure through the refrigerant and transfers the heat outside. Improving the heat transfer of air conditioning condenser is still a difficult task because of the broader set of materials and various parametric designs involved. Due to this high cost, the experimental set-up cost cannot be modified, instead, simulation analysis was introduced in the optimization process in order to achieve a near-optimal solution. The aim of this research is to improve the heat transfer rate for air conditioning condenser by material and parametric design optimization. The system was designed based on one basic parameter optimization: varying the condenser tube diameter. This variable was changed in order to improve the heat transfer of the condenser. Simulations using Computational Fluid Dynamic (CFD) analysis and thermal analysis were carried out to have a better understanding and distinct visualization of the fluid flow and materials used, and to compare the results. The materials that were used for CFD analysis are R32 and R290, and for thermal analysis are copper (C12200) and aluminum. The analysis was done using Analysis System (ANSYS) software. Different parameters were calculated from the results that were obtained and graphs were plotted between various parameters such as heat flux, static pressure, velocity, mass flow rate and total heat transfer. From the CFD analysis, the result shows that R32 has more static pressure, velocity, mass flow rate and total heat transfer than R290 at a condenser tube diameter of 7mm. In thermal analysis, the heat flux is more for copper (C12200) material at a condenser tube diameter of 7mm than aluminum.

Working Memory Capacity for Mid-Air Gestures in Human–Computer Interaction

Mid-air gesture interactions have emerged as one of the predominant modalities used in human-computer interaction (HCI). However, extant research on gestures predominantly concentrates on the design of gestures for singular functionalities, which requires a comprehensive investigation into gesture interaction design from an integrative HCI system perspective. Working memory capacity plays a pivotal role in constraining the number of gestures accommodated within an HCI system. This study adopts the change detection paradigm to conduct an empirical investigation into the working memory capacities associated with mid-air gestures, aiming to elucidate the working memory capacity for such gestures. The experimental design included two independent variables: five distinct categories of mid-air gestures (physical, symbolic, metaphorical, abstract, and mixed) and memory set sizes ranging from two to nine items. The findings revealed that working memory capacities for different types of gestures fluctuate between three and five items, with symbolic gestures presenting the most negligible cognitive load for recall and abstract gestures proving to be the most challenging. The outcomes of this research have significant implications for both the design of individual gestures and the overarching design of gesture interaction systems, serving as a valuable reference for future endeavors in HCI design optimization.

Boosting selective Cs+ uptake through the modulation of stacking modes in layered niobate-based perovskites

Selective separation of 137Cs is significant for the sustainable development of nuclear energy and environmental protection, due to its strong radioactivity and long half-life. However, selective capture of 137Cs+ from radioactive liquid waste is challenging due to strong coulomb interactions between the adsorbents and high-valency metal ions. Herein, we propose a strategy to resolve this issue and achieve specific Cs+ ion recognition and separation by modulating the stacking modes of layered perovskites. We demonstrate that among niobate-based perovskites, ALaNb2O7 (A = Cs, H, K, and Li), HLaNb2O7 shows an outstanding selectivity for Cs+ even in the presence of a large amount of competing Mn+ ions (Mn+ = K+, Ca2+, Mg2+, Sr2+, Eu3+, and Zr4+) owing to its suitable void fraction and space shape, brought by the stacking mode of layers. The Cs+ capture mechanism is directly elucidated at molecular level by single-crystal structural analyses and density functional theory calculations. This work not only provides key insights in the design and property optimization of perovskite-type materials for radiocesium separation, but also paves the way for the development of efficient inorganic materials for radionuclides remediation.

Design optimization of automotive carbon fiber composite material floor laminate based on PSO-BFO algorithm

In response to the current challenges of low precision and efficiency in the optimization of composite material layups, the insufficient lightweight of automotive body floors, and the high cost of carbon fiber composites, this study introduces an optimized design method for carbon fiber composite flooring layups. Based on implicit parametric technology, a hybrid PSO-BFO (Particle Swarm Optimization-Bacterial Foraging Optimization) algorithm is employed. This approach achieves an integrated optimization of materials, processes, and structures, thereby balancing and reducing costs. The SFE-CONCEPT is utilized to establish an implicit parameterization model for the body floor, which is validated through experiments and finite element simulation analysis. Concept design and modeling of the carbon fiber composite material floor laminate are performed. Continuous variable optimization is employed to determine the thickness, tile shape, and number of layers for the front, middle, and rear floors. A continuous variable discretization rounding strategy is used to obtain the discrete layer numbers for each laminate orientation of the composite material floor. The continuous fiber lamination strategy is applied to create different shared lamination regions. The PSO-BFO hybrid optimization method is proposed to optimize the lamination sequence as a multi-objective optimization, addressing the challenges of discrete lamination sequence, explosive combinations, and multiple variables in the optimization design of carbon fiber composite material floor laminates. The optimization results demonstrate improvements of 34.4% in floor quality M, 6.0% in static bending stiffness BS, and 5.3% in lightweight coefficient QLX using the proposed PSO-BFO method. PSO-BFO and PSO-GA (Particle Swarm Optimization-Genetic Algorithm) methods are more capable of obtaining global optimal solutions for complex optimization problems than single optimization algorithms. Still, the results obtained by the PSO-BFO method are more balanced.

Heat transfer performance optimization of turbine blade internal cooling channel with pin-fins and recessed-extruded endwalls

This paper involves implementing and optimizing a novel recessed-extruded endwall design for a rectangular cooling channel equipped with pin-fins. The study encompasses an in-depth exploration of the flow dynamics, pondering the generation and sustenance of vortices within the channel, using Reynolds-averaged Navier-Stokes analysis. The study delves into the evaluation of heat transfer characteristics, considering crucial parameters such as Nusselt number, friction factor, and overall heat transfer performance. These attributes are contrasted with the corresponding values observed in cases featuring flat endwalls, concerning Reynolds numbers spanning from 7400 to 36,000. A parametric study of the channel with recessed-extruded endwalls is conducted, aiming to comprehend the influence of geometric factors on channel heat transfer. A single-objective optimization process focusing on enhancing heat transfer effectiveness, quantified through the heat transfer efficiency index (HTEI), is conducted with three design variables. The results indicate that the new endwall configuration significantly enlarges the high heat transfer areas near the pin-fins compared to the flat endwall across all Reynolds numbers. This novel endwall design substantially elevates the heat transfer levels adjacent to the pin-fins, showcasing an impressive 62.4% increase in HTEI at Re = 21,500 compared to the flat endwall, with a protrusion height of 2.5% of the channel height. Furthermore, by increasing the height, the recessed-extruded endwall configuration can achieve a remarkable 91.1% increase in HTEI compared to the flat endwall. This achievement is reached with a protrusion height equivalent to 5% of the channel height at Re = 7400. Through design optimization using the radial basis neural network (RBNN) surrogate model and particle swarm optimization (PSO) technique, the HTEI of the recessed-extruded endwall design shows enhancements of 91.7% and 18.0% compared with the flat endwall and reference designs, respectively, at a Reynolds number of 21,500. The present work demonstrates the potential for enhancing the heat transfer of pin-fins channels by improving endwall design.

Soil sampling design matters - Enhancing the efficiency of digital soil mapping at the field scale

Optimisation of sampling design (methods chosen to select the samples) and sample size (number of samples) remains a key challenge in digital soil mapping, especially in the area of precision farming with the expected economic benefits from the introduction of new technologies. As the existing information is available in the form of relevant environmental covariates, its combination with non-parametric machine learning techniques requires careful planning from the initial field sampling to the final production of digital soil maps. The aim of this study is to compare widely used covariate-wise sampling designs combined with variable sample sizes for supervised prediction of common soil drivers of agricultural productivity (pH, soil organic carbon, soil macronutrients) in a real case study of a field (35 ha) with heterogeneous soil properties. From a total of 200 samples, we evaluated different sample sets where 10, 30 and 60 field samples were selected by conditioned Latin Hypercube Sampling (cLHS) and Feature Space Coverage Sampling (FSCS) to calibrate random forest (RF) models. The evaluation was performed on independently in-situ sampled test points. In addition to these datasets, we also compared the investigated methods with Simple Random Sampling (SRS) in a numerical benchmark experiment with increasing sample size, comparing the global accuracies of the predicted maps on the test points, but using interpolated maps as the artificial true population for each soil characteristic. The results of the study in both the field experiment and the numerical experiment showed slightly better results for the FSCS method, especially when the number of samples was small. At smaller training sample sizes, the risk of insufficiently accurate prediction models was slightly lower for FSCS and the difference decreased as the sample size increased. Nevertheless, sample size proved to be the most important factor in the accuracy of RF models, regardless of the sampling technique. The results suggest that a sample size between 18 and 30 training samples (0.6 to 1 sample ha−1) seems plausible for covariate-wise predictions using RF at field scale in our case study. The relative importance of each auxiliary variable for each RF calibration was also assessed for the field experiment. The results showed that the additional introduction of spatial proxies overshadowed the importance of other covariates, but only significantly improved the model calibration at larger sample sizes. The calibrated models without spatial proxies showed the strongest effect of remotely sensed surface characteristics.

A multi-objective approach to optimizing the geometry and envelope of rural dwellings for energy demand, thermal comfort, and daylight in cold regions of China: A case study of Shandong province

Rural dwellings in China’s cold regions face significant challenges related to energy consumption, thermal comfort, and daylight, with a projected substantial increase in energy demand in the future. Scientifically optimized design during the early planning stages can significantly enhance indoor thermal and daylight conditions, effectively reducing energy consumption. This study focuses on Shandong Province to comprehensively analyze the optimization of geometry and envelope design of rural dwellings in China’s cold regions. It employs a multi-objective optimization method, integrating genetic algorithms with dynamic energy simulations, to minimize total energy demand while ensuring thermal comfort and sufficient daylight. Utilizing the Octopus plugin in Grasshopper, in conjunction with EnergyPlus, Ladybug, and Honeybee, this research optimizes and analyzes the impact of various design variables on energy consumption, thermal comfort and daylight, including room depth, window-to-wall ratio in different orientations, thermal performance of the envelope, and related glass material parameters. The results indicate that the selected variables have significant energy-saving potential. Compared to the case study building, the optimized solutions can reduce total energy demand by over 62.41%, with the highest savings rate reaching 88.75%. This study emphasizes the importance of integrated design and optimization strategies in enhancing the sustainability of rural dwellings. It proposes both cost-free and cost-included optimization schemes: the former maximizes the energy-saving, thermal comfort and daylight potential of the selected variables, while the latter is more practically feasible considering the economic constraints of rural areas. The proposed optimization schemes provide multiple reference solutions and theoretical foundations for users of rural dwellings in China’s cold regions.

Study on seismic performance and restoring force model of framed CFST column-composite box beam joints

Quasi-static tests are conducted on framed concrete-filled steel tubular (CFST) column-composite box beam joints to study the deformation characteristics and restoring force performance under seismic loads. The joints' seismic performance is evaluated. This study shows that the joints with three different connection forms (single-limbed diagonal brace, cross brace, and diaphragm) in the core area have good bearing and energy dissipation capacities. As a result, the joints exhibit excellent seismic performance. The theoretical and fitting analyses of test results reveal the stiffness degradation law for this type of joint. Additionally, a fixed-point directional degradation trilinear restoring force model is established and compared with the test results. The research results indicate that the proposed restoring force model accurately predicts the nonlinear recovery behavior of the joint under seismic loads. This model is in good agreement with the hysteretic curve of the test, providing a theoretical basis for the seismic design and performance evaluation of the joint and for the seismic design and toughness optimization of a structure.

Optimal design of vibration resistance of fiber-reinforced composite sandwich plates embedded in a viscoelastic square honeycomb core

This work focuses on investigating the optimal design of composite sandwich plates (FCSPs) with a viscoelastic square honeycomb core (VSHC). Firstly, using the cross-fill theory, the complex modulus technique, the first-order shear deformation theory, the minimum strain energy principle, and the Newmark-β method, a theoretical model of the VSHC-FCSPs under half-sine pulse excitation is formulated to calculate the inherent frequencies, the peak and vibration decay time of the transient response in time domain. The peak and vibration decay time are taken as the indexes of the anti-vibration performance. Considering an index of structural stiffness performance, the average value of the inherent frequencies is adopted to calculate the overall stiffness. After a set of literature validations and optimization validations, the multi-objective genetic algorithm is employed to study the optimization issue of VSHC-FCSPs. The optimization objectives are to minimize the three design variables of the transient response peak, vibration decay time, and reciprocal of overall stiffness. Then, the fiber laying angle of each layer, the core thickness ratio and the modulus ratio are assumed as optimization variables. Finally, the results with good vibration resistance and structural stiffness in the Pareto front are chosen as references, and these corresponding variations of the design variables and optimization objectives are obtained. The optimization results have revealed that the optimization variables corresponding to the intermediate points should be selected as references to improve the anti-vibration capacity and ensure the structural stiffness performance.

Ferroelectric tungsten bronze-based ceramics with high-energy storage performance via weakly coupled relaxor design and grain boundary optimization

A multiscale regulation strategy has been demonstrated for synthetic energy storage enhancement in a tetragonal tungsten bronze structure ferroelectric. Grain refining and second-phase precipitation (perovskite phase) are introduced in the BaSrTiNb2-xTaxO9 ceramics by regulating the composition and sintering process. Disordered polarization and distribution, chemical inhomogeneity, and insulating boundary layers are achieved to provide the fundamental structural origin of the relaxation characteristic, high breakdown strength, and superior energy storage performance. Thus, an ultrahigh energy storage density of 12.2 J cm−3 with an low energy consumption was achieved at an electric field of 950 kV cm−1. This is the highest known energy storage performance in tetragonal tungsten bronze-based ferroelectric. Notably, this ceramic shows remarkable stability over frequency, temperature, and cycling electric fields. This work brings new material candidates and structure design for developing of energy storage capacitors apart from the predominant perovskite ferroelectric ceramics.

Multi-segmented tube design and multi-objective optimization of deep coaxial borehole heat exchanger

Deep coaxial borehole heat exchanger (DCBHE) is a key component to extract medium-deep geothermal energy for low-carbon building heating. It is a convention that both center tube and annuals tube are respectively using a single material. However, a basic idea behind this study is using non-linear design to ask for performance improvement. It is assumed that non-uniform tube design pattern can meet different heat exchanger demand at different depth under a geothermal gradient dominated underground environment. The whole study is to prove this conjecture and make it useful for engineering application. A new numerical model is put forward to considered multi-segmented structure in heat transfer computation and a nondominated sorting genetic algorithm (NSGA-Ⅱ) is adopted in optimization process. The results of this study show that the optimized designed case can increase outlet temperature by 3 °C while reducing investment of 10000RMB. In addition, a home-made software is developed to perform the thermal and economic evaluation of DCBHE as well as automatically optimization of this multi-segmented structure. This study can provide a new model, algorithm, results and software tool for better utilizations of deep geothermal energy.

Experimental study of the design and performance optimisation of a self-heating methanol on-board reforming reactor for hydrogen production

There is an increasing research on efficient and compact on-board reformer, based on which a serpentine plate type self-heating reformer integrating preheating, reforming and combustion has been designed and fabricated, which can be disassembled and assembled flexibly. In this paper, experiments on the self-heating reformer have been carried out to optimise the differential structure of different chambers. It can be found that: the combustion chamber needs to be partitioned and the resistance loss is small and stable for a long time when the number of partitions is 3. The combustion chamber with O2/CH3OH = 1.5 has the highest wall temperature of 240 °C. Hydrogen yield can be increased to more than two times after optimising the evaporation chamber. The catalyst in the reforming chamber must be uniformly distributed, and the methanol conversion rate is stable at 75 % with a mass of 110 g and Weight Hourly Space Velocity (WHSV) = 8 h−1. The optimum operating conditions of the reactor is WHSV = 8 h−1 with air flow rate of 25 L/min, at which the reactor starts up within 20 min, the hydrogen yield stabilises within 40 min, and the hydrogen yield is 9.8 L/min and remains stable for 120 min.