Computer Simulation Research Articles

Experimental and numerical analysis of mixed mode bending of adhesive-bonded and hybrid honeycomb core sandwich structures

This study investigates the potential of a hybrid joining method, called friction stir spot welding with disc and adhesive bonding (FSSW_D_AB), for bonding honeycomb core sandwich structures, offering an alternative to traditional adhesive bonding (AB) sandwich structures. The research focuses on the manufacturing of these hybrid joints and evaluating their performance compared to conventional adhesive bonding (AB) methods. Mixed Mode Bending (MMB) tests were performed to assess the mechanical behaviour of the joints under different loading conditions. Additionally, numerical analysis using cohesive zone modeling (CZM) was performed using both a honeycomb core with a cohesive layer and the homogenized core with an equivalent cohesive layer. The study reveals that the hybrid joining method significantly enhances the performance of honeycomb sandwich structures. The good agreement between the numerical predictions and the experimental results for all types of joints showed the usefulness of the proposed numerical model. However, the FEM-based stress and damage analyses of the joints provided crucial results on normal and shear stress distributions and delamination.

Deep dehumidification characteristics of a silica gel coated cross-flow heat exchanger with a circulating blowing loop

Solid desiccant dehumidification systems offer an effective and energy-efficient alternative for deeply dehumidifying air. Desiccant coated heat exchangers (DCHEs), a type of solid desiccant dehumidification system, have garnered attention due to their ability to eliminate adsorption heat and thereby enhance dehumidification capacity, unlike desiccant wheels that perform adiabatic dehumidification. This study introduces a silica gel coated cross-flow DCHE equipped with a circulating blowing loop for deep dehumidification applications. A two-dimensional numerical model is developed to simulate deep dehumidification behavior of the DCHE. Parametric analysis is performed to explore the dehumidification characteristics under various conditions, setting different volume fractions ω of blowing loop air. Results indicate that the DCHE can effectively reduce the moisture content of humid air to a deep dehumidification threshold of 6.2 g/kg. Additionally, dehumidification capacity can be increased by incorporating a circulating blowing loop. The influence of process air velocity, cooling air velocity, process air humidity ratio, regeneration air temperature, and air channel length on the dehumidification performance are analyzed, focusing on metrics such as minimum outlet air humidity ratio Ya1,ad,out_min, effective deep dehumidification time teff, moisture removal capacity MRC and dehumidification coefficient of performance DCOP. It is determined that the regeneration air temperature should be raised to 80 °C to ensure deep dehumidification, and an air channel length of 0.2 m is optimal.

Investigation of thermal and fluid dynamics behaviors of melt pool during laser direct metal deposition on inclined substrates

The laser direct metal deposition (DMD) technique offers an efficient solution for repairing and manufacturing structures with variable curvatures, such as impeller blades. However, how the non-vertical laser irradiation on curved surfaces impacts the thermal and fluid dynamics of the melt pool still remains unclear. In the current research, a high-fidelity multi-physics numerical model is developed to explore the mechanisms of melt pool development and the effects of inclined angle and laser spot diameter on morphological evolution of deposition layers during DMD under non-vertical irradiation on inclined substrates. Results indicate that as the inclination angle increases, deposited track fluctuations become evident, with a critical angle from 40° to 42.5° identified for hump formation. A smaller laser spot diameter increases the likelihood of humps and irregularities, while a larger spot diameter expands the deposition layer and enhances melt pool wettability. This study is expected to provide significant theoretical guidance for selecting and applying process parameters for the fabrication of curved structures by DMD.

Identification and characteristic analysis of internal defects in rock-filled concrete based on deep learning method

The distribution characteristics and geometric morphology characteristics of defects within RFC are important factors affecting the strength properties and rupture morphology of RFC. However, the excessive size of commonly used aggregates for RFC leads to difficulties in conducting in-depth experimental studies indoors. Based on the improved U-Net and image processing technology, this research establishes an integrated model for the identification, classification, and extraction of defects inside the RFC, quantitatively counts and analyzes the acquired defect distribution characteristics and geometrical morphology characteristics, and establishes a defect characteristic distribution function that can be used for the numerical reconstruction of defects. In order to realize the acceleration of U-Net training using training weights, use VGG-16 with the fully connected layer removed instead of the Encoder part of the U-Net. The integrated model in this research can realize automatic identification, classification, and extraction of multiple types of defects at the same time, and the established distribution function of defect characteristics provides a data basis and new ideas for the establishment of RFC three-dimensional numerical models containing real defects.

Flexural tensile behaviour of alkali-activated slag-based concrete and Portland cement-based concrete incorporating single and multiple hooked-end steel fibres

In this study, three-point bending tests on notched beams according to EN 14651 have been performed to evaluate the flexural post-cracking behaviour of alkali-activated slag-based concrete (AASC) and Portland cement-based concrete (PCC) incorporating single (3D) and multiple (4D, 5D) hooked-end steel fibres in different volume fractions up to 0.75%. According to the experimental results, the post-cracking residual flexural strength increases with the increase in the fibre volume fraction for each fibre and concrete matrix type. AASC mixes incorporating 3D and 4D fibres show higher values of residual flexural strength for the same crack opening than PCC mixes with the same fibre type and dosage. Only for the mixes incorporating 5D fibres, steel fibre-reinforced PCC (SFRPCC) mixes outperform steel fibre-reinforced AASC (SFRAASC) mixes in terms of post-cracking behaviour. According to EN 14651, the values of the residual strengths and , corresponding to a crack mouth opening displacement (CMOD) of 0.5 mm and 2.5 mm, respectively, and their corresponding characteristic values and , respectively, can be derived from the experimental load-CMOD curves. Following the fib Model Code 2020, each mix can then be classified according to the values of and the ratio. As a result, empirical models have been developed for SFRPCC to predict the values of and and the applicability of such models to SFRAASC is evaluated in this study. Once the values of and are known, tensile constitutive models can be derived according to the fib Model Code 2020 and used as input parameters for finite element modelling. In this study, the accuracy of the code-based constitutive model to predict the flexural behaviour of SFRAASC and SFRPCC is evaluated using the concrete damage plasticity (CDP) model available in ABAQUS. The numerical model based on the tensile stress-strain curve in the fib Model Code 2020 can qualitatively capture the post-cracking behaviour of SFRAASC and SFRPCC incorporating 3D, 4D and 5D at 0.25% fibre volume fraction, despite overestimating their tensile strength. For higher fibre volume fractions, the CDP model, in conjunction with the mode I parameters derived from the fib Model Code 2020, is unable to adequately describe the post-hardening behaviour exhibited by the composites.

Modeling condensation of Methane-Water vapor mixtures in the Hedbäck Nozzle: A comparative study of 2D and 3D geometries

This study investigated the condensation behavior of a binary mixture of methane (CH4) and water vapor (H2O) within the Hedbäck nozzle, employing both 2D and 3D modeling approaches. The 2D model was initially developed to analyze the effects of inlet parameters and mixture’s condensation characteristics. However, the inherent limitations of the 2D model in capturing the full complexity of the flow dynamics prompted a transition to a 3D modeling approach. The research explored two distinct 3D geometries: one created by extruding the 2D section and another by rotating the 2D cross-section around its axis. The latter, which more accurately represented real-world nozzle conditions, revealed differences in flow patterns, condensation behavior, and entropy generation, emphasizing the crucial role of 3D effects in the condensation process. The sensitivity of the numerical simulation results to various nucleation theories and droplet growth models was acknowledged, and the most appropriate theory and model were meticulously selected. This approach minimized discrepancies between numerical modeling outcomes and experimental data, enhancing the accuracy and reliability of the findings. The 2D results indicate a 40.5% increase in the inlet partial pressure with a constant temperature and mass fraction, resulting in a 56% rise in maximum liquid mass fraction. Similarly, a 3.6% decrease in inlet temperature under constant pressure and mass fraction increases the average radius of outlet droplets by more than 13%. In addition, entropy generation analysis revealed that less than 1% of entropy generation is attributed to mean flow, whereas 99% is linked to turbulent fluctuations. Moreover, the 3D models demonstrated markedly different entropy generation rates compared to the 2D model, highlighting the importance of 3D approach for a comprehensive understanding of thermodynamic irreversibility within the system.

Maximum waves in the Black Sea based on the results of numerical modeling

In this paper, a comparison of the wind waves parameters calculations in the Black and Azov seas, using two common spectral wave models: DHI MIKE 21 SW and SWAN was made. The fields of the wind waves main parameters (wave heights, periods, directions of propagation) were obtained for a climatic period of time from 1979 to 2018. Comparison of the calculation results shows that with the accepted model settings, the SWAN model, compared with MIKE, overestimates the values of wave heights with weak and moderate waves and underestimates with the extreme ones. Estimation of the maximum wave heights on the Black Sea, possible once in a given number of years, performed on two different models, was made. It showed that for the conditions of the Black Sea the difference between the calculated values of significant wave heights of rare frequency for the MIKE and SWAN models does not exceed 12%. The maximum significant wave heights, possible once in a hundred years, in the Black Sea can reach 11-12 m.

Heat conduction applied in ‘River Pollutant Diffusion’

Environment problems are a highly valued topic in today’s society, where water pollution issue is one of the most significant that could threaten human’s safety. Sources such as industrial wastewater and agricultural runoff are affecting the water quality. Rivers around the world suffer from varying degrees of pollution. In this paper, we investigate river heat pollution and employ a numerical model to investigate its evolution and impacts downstream by adapting the heat advection-diffusion equation. We explore the stability of our numerical solutions using von Neumann stability analysis of the forward and backward differencing method of discretization of the analytical equations. We further consider a setting where there are multiple sources of pollutant in the river to explore interaction of the two pollution sources. We use python to develop the model and plot temperature diffusion in the river as a function of time and location. Our model reflects the relationship between the speed of diffusion and thermal diffusivity, and how advection enhances pollutant. Our results show that heat pollution is very quickly transported to other locations and can affect water and food quality in many locations along the river. Additionally, pollution in rivers with fast currents will be more readily transported downstream, therefore both proximity to cities and speed of river water needs to be taken into account when addressing the problem of heat pollution in rivers near cities.

The Influence of a Sudden Impact Loading on the Creep, Damage, and Fracture of Beams Made From Functionally Graded Materials

ABSTRACTAn approach to the analysis of the influence of impact loading on creep, accumulation of hidden damage and fracture of structural elements made of functionally graded materials (FGM) is proposed. The approach is based on the analysis of additional damage caused by the impact loading and the stress redistribution caused by it. For the numerical modeling, finite element analysis was applied using algorithms for determining the size and direction of motion of macroscopic defects by means of the analysis of the time‐varying damage field. The fracture after an impact on a beam made from FGM is considered. The nature of fracture of a beam made of two‐layer metal‐ceramic material was studied. The advantages of using FGM to ensure a better long‐term response of a structural element to a non‐destructive impact loading are shown. An approach to determine the time until the complete fracture of the FGM beam by the simultaneous description of the motion of two cracks is proposed.

Performance prediction of flame-retardant clothing using correlations and artificial neural networks: Optimizing firefighter safety

Flame-Retardant Clothing serves as a protective shield for firefighters that safeguards them from exposure to heat, flames and other thermal hazards. To achieve an optimal design for the clothing, it is essential to simultaneously account for all the factors affecting the performance of the clothing. The present study employs data from a numerical model to explore heat and moisture transport through clothing subjected to flame exposure. Seventeen non-dimensionless parameters associated with the heat and moisture transport in flame-retardant clothing are obtained. A correlation is developed to link the dimensionless second-degree burn time with other non-dimensional parameters. This correlation provides a means to predict the thermal protective performance (TPP) of the clothing. Additionally, an Artificial Neural Network (ANN) method is employed to determine the TPP of the clothing. Multi-layer feedforward backpropagation networks are utilized to predict the TPP under specified exposure conditions. The findings indicate that both the correlations and the ANN approach adopted in the present study demonstrated promising results. However, the ANN model predictions show better agreement with model data in comparison to the results derived from the developed correlations. The maximum percentage error in the predicted non-dimensional second degree burn time using ANN is limited to 10 %.

Physics-based time-of-failure determination of rainfall-induced instability in lateritic soil slopes

Conventional time-of-failure estimated from slope surface displacement over time, ignores the crucial geotechnical and environmental causative factors that lead to slope instability. The instrumentation and monitoring are expensive, labour-intensive, and often not feasible for large number of hill slopes. This paper focuses on the physics-based determination of time-of-failure charts for laterite soil slopes prevalent in the Western Ghats of India, under rainfall infiltration. The finite element model was first validated by performing coupled flow deformation analysis of Kondavi soil cutting situated in the Ratnagiri district of Maharashtra, India. The soil samples were collected from the site for basic geotechnical characterisation in the laboratory. In addition, the soil water characteristics curve (SWCC) was determined using the filter paper method, and the unsaturated parameters were obtained using the van Genuchten model. Following the validation of numerical model with the failed Kondavi cutting, the factor of safety (FOS) and time-of-failure (TOF) were studied for varying rainfall intensity, and permeability of the soil. The FOS and TOF charts were then established for varying slope angles (30°, 45°, 60°), effective cohesion (10 kPa, 18 kPa, 25 kPa), effective friction angle (22°, 25°, 28°), water table depth (25 m, 28 m, 30 m, 35 m) and height of slope (15 m, 25 m, 35 m). Results indicate that if rainfall intensity is lower than soil permeability, TOF depends on both the intensity and duration of the rainfall. Higher rainfall intensity leads to a shorter time of failure, and vice versa. Conversely, when rainfall intensity exceeds soil permeability, TOF is determined by the duration of rainfall and the permeability of soil, as the rainfall infiltrates at the saturated permeability rate regardless of its intensity. It is also observed that friction is the dominant parameter for initial FOS, while cohesion is the dominant parameter for the TOF of a rainfall-induced landslide. Finally, charts are proposed that shall serve as a preliminary guide for the determination of the TOF for rainfall-induced instability in the lateritic soil slopes of India. The performance of the charts is further evaluated by comparing the observed and predicted TOF of two other failed laterite cuttings. The implications of these findings are profound, as the proposed TOF charts can be integrated into early warning systems, contributing towards improved disaster mitigation and preparedness with timely decision making for adequate management of landslide associated risks.

Experimental Study of Turbulent Premixed Flames of Gas-to-Liquids (GTL) Fuel in a Fan-Stirred Combustion Bomb

This study experimentally investigates the turbulent flame speeds (St) of Gas-to-Liquids (GTL) fuel and a 50/50 blend with diesel across turbulence intensities (u') ranging from 0.5 to 3.0 m/s and equivalence ratios (Φ) from 0.7 to 1.3. Experiments were conducted using a cylindrical fan-stirred combustion bomb at an initial temperature (Ti) of 463 K and atmospheric pressure under near homogeneous and isotropic turbulence (HIT) conditions. A pressure transducer measured the St of the propagating GTL flame. High-speed imaging reveals that changes in flame brightness are associated with variations in flame temperature and soot incandescence. Compared to diesel, stoichiometric GTL and the 50/50 diesel-GTL blend showed peak combustion pressure reductions of 8.9% and 4.9%, respectively. Rich diesel fuel and lean GTL exhibited higher pressure rise rates, flame propagation, and St due to their Lewis numbers (Le) being less than one, enhancing flame-turbulence interaction. At u` of 0.5, 1.5, and 3.0 m/s, St for GTL increased by approximately 3.6%, 5.3%, and 2.8%, respectively, when compared to diesel, with these increases observed at Φ < 1.1. Transition from wrinkled to corrugated flamelets with increasing u` supports models predicting flame stability and potential industrial combustion efficiency improvements. Comparisons with numerical St results using the Zimont Turbulent Flame Speed Closure (Zimont TFC) model showed good agreement at lower (u' = 0.5 m/s) and mid-range (u' = 2.0 m/s) turbulence intensities but discrepancies at higher intensities (u' = 3.0 m/s), highlighting the need to refine numerical models for more accurate predictions across all turbulence levels.

Constitutive modelling of deformation rate dependent response of steel timber shear connections

This paper presents experimental and numerical investigations into the deformation rate-dependent constitutive response of steel-timber shear connections with screws. After describing the test specimens and experimental arrangement, a detailed account of the complete deformation response and main mechanical parameters of the tested shear connections under three applied displacement rate levels are given. Specimens with small screw diameters had a relatively brittle response, failing shortly after yielding, whilst those with higher diameters showed ductile failure modes, with plastic hinges forming in the screws and concurrent extensive timber crushing. It was observed that the stiffness increases with the deformation rate due to the viscoelastic response of wood materials, whilst the peak load is largely constant. Nonlinear finite element simulations were carried out to validate the main numerical parameters for steel, timber, and interaction characteristics. After gaining confidence in the ability of the numerical models to predict closely the stiffness and peak load, numerical investigations were carried out to examine the influence of key material and geometric parameters on the stiffness, load resistance and deformation response. The studies showed that higher timber strength increases the initial stiffness and the peak load, while higher screw grades improved both stiffness and strength. Based on the results and observations, code-modified expressions for evaluating the stiffness and load resistance, as a function of the deformation rate, are proposed within the ranges considered, and validated against a collated database. Comparative assessments with existing literature indicate that the proposed equations provide improved estimates. Suggested closed-form relationships enable the characterisation of the full constitutive response of steel-timber shear connections, that can be adopted for discrete nonlinear modelling of connectors.

Data-Driven Models for Significant Wave Height Forecasting: Comparative Analysis of Machine Learning Techniques

Accurate prediction of significant wave height (SWH) is critical for coastal safety, marine operations, and disaster management. Traditional numerical models for wave prediction are computationally intensive and often lack accuracy, prompting a shift towards data-driven methods. This study explores the efficacy of machine learning (ML) models in forecasting SWH in the coastline of North Stradbroke Island, Queensland, Australia. Using a dataset spanning 2010 to 2022, the study employs wave characteristics such as maximum wave height (Hmax), wave periods (Tz, Tp), peak direction, and sea surface temperature (SST) as predictors. Three ML models—Linear Regression, Decision Tree, and Random Forest—were trained and evaluated using performance metrics like Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²). The Random Forest model demonstrated the best predictive accuracy with the lowest MSE (0.0074) and highest R² (0.958), outperforming both Linear Regression and Decision Tree models. This improvement in prediction accuracy supports the model's application for coastal management, ensuring better forecasting of wave conditions. The proposed approach shows significant advantages, including better handling of non-linearities and reduced computational costs compared to conventional numerical methods, such as SWAN and WAM, making it highly applicable for real-time wave forecasting, particularly for regions with complex coastal dynamics such as North Stradbroke Island.

Improving subsurface structural interpretation in complex geological settings through geophysical imaging and machine learning

This study employs seismic refraction tomography (SRT) and electrical resistivity tomography (ERT) to assess subsurface geological conditions along the proposed Porsgrunn Highway in Norway. The primary objective is to analyze SRT and ERT tomograms to identify subsurface geological structures. However, interpreting tomograms is often limited by smoothed boundaries and reduced resolution. To address these challenges, we apply k-means clustering, a machine learning technique that groups data based on similarities in physical properties, to post-process the geophysical tomograms. This study pioneers the use of k-means clustering to interpret tomograms from SRT and ERT data in complex geological settings. We first evaluate the effectiveness of clustering techniques using numerical modeling for two geological scenarios: a horizontally layered case and a layered case with undulation and a fault structure. Utilizing automated methods (Elbow and Silhouette), we objectively determine the optimal number of clusters for each geophysical tomogram. Subsequently, we compare the performance of the k-means clustering algorithm with subjective expert interpretations and the Laplacian edge detection method. Borehole data validate the clustering results and confirm the effectiveness of optimal cluster selection techniques. The findings of this study demonstrate that k-means clustering significantly enhances the detection of geological structures by establishing clearer boundaries and minimizing noise interference, enabling more accurate fault zone delineation. Compared to traditional edge detection and subjective interpretation methods, k-means clustering offers a systematic and objective approach that improves consistency and reliability across diverse geological settings. Moreover, its automated classification of geophysical data into meaningful clusters enables efficient analysis of large datasets. This study underscores the value of integrating machine learning techniques with geophysical methods such as SRT and ERT to improve interpretability and accurately identify subsurface geological structures, particularly in fault zone identification.

Numerical Modeling for 250 nm DUV LEDs With Discrete p-type Functional Layers to Manage Both Carrier and Photon Transport

Numerical Modeling for 250 nm DUV LEDs With Discrete p-type Functional Layers to Manage Both Carrier and Photon Transport

Experimental and Numerical Simulation on the Generation and Development of Cumulative Plastic Strain of Cement Sheath in Salt Cavern Gas Storage Well

ABSTRACTSalt cavern gas storage is an important technical means to balance the demand for staggered energy supply. Due to the repeated injection and extraction of natural gas in gas storage facilities, sealing integrity failure in the wellbore of gas storage facilities frequently occurs. In response to this, considering the cyclic loading and unloading of the pressure load inside the casing, mechanical tests of set cement were carried out under alternating loads, quantifying the cumulative plastic strain change law of set cement and revealing the deterioration characteristics of its mechanical properties. A numerical model of cumulative plastic strain of casing cement sheath formation under alternating load was established based on the obtained experimental parameters. Comparative verification was conducted using experimental data, and the variation law of cumulative plastic strain of cement sheath was analyzed. The distribution of cumulative plastic strain on the cement sheath bonding surface of the entire wellbore was quantified. The research results indicate that the higher the internal pressure value of the casing, the earlier the plastic strain appears, and with the increase in the number of alternating loads, the cumulative plastic strain increases approximately linearly. After the internal pressure increased by 30 MPa, the cumulative plastic strain increased by a maximum of 46.75%. When the number of loading and unloading cycles under alternating loads is small, reducing the elastic modulus (6 GPa) of the cement sheath can effectively reduce its cumulative plastic strain. However, as the number of loading and unloading cycles under alternating loads exceeds a specific value, the cumulative plastic strain produced by high elastic modulus (15 GPa) cement sheaths decreases. Finally, the distribution pattern of cumulative plastic strain along the wellbore under different gas injection times and complex formation conditions was analyzed. Suggestions for establishing well barriers in salt cavern gas storage during cementing were proposed. The research results can provide theoretical and engineering references for evaluating the sealing integrity of gas storage wells.

Study on combined thermal protection scheme integrating supercritical CO2 regenerative cooling and fuel film cooling used for scramjet engines

Supercritical CO2 closed-Brayton-cycle demonstrates considerable application potential on hypersonic vehicles, effectively addressing power supply issues during prolonged flights. However, the CO2 flow rate is strictly limited by the cycle’s cooling source (aviation kerosene), rendering traditional regenerative cooling inadequate for sufficiently cooling the scramjet engine. To address this challenge, this study proposes an integrated cooling scheme that combines regenerative cooling, ceramic thermal-protective layer, and fuel film cooling. A two-dimensional coupled numerical model was developed, simultaneously considering the convective heat transfer of supercritical CO2 and the shear mixing of supersonic fuel film. The results indicate that the high-enthalpy gas imposes an extreme aerodynamic heat load on the regenerative cooling channel wall, resulting in a notable deterioration in heat transfer for supercritical CO2. Implementing kerosene film cooling within the combustor can effectively mitigate the abnormal heat transfer behavior of supercritical CO2 and significantly reduce viscous dissipation heat within the gas boundary layer. By optimizing the fuel film injection layout, this combined cooling scheme reduced wall heat flux by 43% and temperature by over 400 K compared to traditional regenerative cooling, thus providing effective thermal protection for the scramjet engine.

Protocol of investigations for the preliminary assessment of the structural safety of highway overpasses

This paper presents the results of a protocol of investigations that have been carried out on 15 overpasses, located along the highway A18 in Sicily (south of Italy) and built about fifty years ago, with the aim of achieving a preliminary evaluation of the structural safety of these overpasses. The investigated overpasses are characterized by a three-span deck consisting of a reinforced concrete slab and prestressed concrete girders. The girders of the central span are simply supported by two Gerber saddles located on cantilever girders at the two ends of the same span. The safety level of the overpasses is investigated by means of different activities that include visual inspection and computation of the class of attention of the overpasses according to the Italian Bridge Guidelines for the classification and the risk management, safety evaluation and monitoring of existing bridges, laboratory and in situ tests on materials, pachometric, georadar and video-endoscopic tests on structural details, and static load tests of the overpasses. The results of the static load tests have also been used to assess the accuracy of two numerical models of the overpasses. These models are elastic but characterised by different levels of accuracy and computational burden: while the first model is the well-established and simple Courbon-Albenga method, the second is a finite element model characterised by a more refined simulation of the response of slabs, longitudinal girders and crossbeams. The results of the investigations have been critically analysed and discussed to underline the ability of the protocol to reveal possible deficiencies of the overpasses and thus identify overpasses that are liable to structural interventions or more accurate and expensive investigations.

Design and operation of a demonstration plant for fluidized bed low-temperature gasification of alternative fuels applied to cement production

A fluidized bed low-temperature gasification technology for solid waste treatment is proposed, which provides an effective solution for energy saving and carbon reduction in the cement industry. A demonstration plant was designed and constructed, which is a fluidized bed low-temperature gasifier coupled to the calciner, capable of treating more than 4,000 kg/h of solid waste. The project involved detailed equipment configuration to ensure stable operation. Commissioning tests for rice husk and textile waste gasification assessed system reliability and gasification performance, with a thermal substitution rate (TSR) of 53.10 % for the calciner. At the same time, targeting a clinker production capacity of 2500 t/d, the gasification plant could achieve an annual net profit of at least 753,100 USD. The fluidized bed low-temperature gasification technology not only has a good economic and environmental value for the use of alternative fuels in the cement production process, but also is important for the design and operation of industrial-scale gasifiers and for numerical modeling.