Search Results (12,505)

This study employs CFD simulations carried on ANSYS Fluent 2022 R1 (ANSYS Inc., Canonsburg, PA, USA), to address the design, development, and thermodynamic analysis of a biomass burner, based on mass and energy balances, combustion efficiency, flame temperature, and thermodynamic properties. The prototype incorporates a flow deflector located before the combustion chamber. This component improves the air-fuel mixture to maximise thermal efficiency and minimise pollutant emissions. The burner is specifically designed to use sawdust as fuel and is intended for industrial applications such as heating or drying processes. The integration of the flow deflector results in uniform, complete combustion, achieving 90% thermal efficiency and an adjustable thermal power output of 0–100 kW. Compared to conventional burners, this design reduces CO emissions by 20% and NO_x emissions by 15%, demonstrating significant environmental improvements. The design methodology is based on mass and energy balance equations to evaluate combustion efficiency as a function of the stoichiometric ratio, along with experimental testing. These experimental tests were conducted using an ECOM (America Ltd., Nashua, NH, USA) gas analyser and anemometer. The internal temperature was monitored with a K-type thermocouple (Omega Engineering Inc., Norwalk, CT, USA). The results confirmed the positive influence of the structural design on thermal performance. The proposed burner aims to maximise heat generation in the combustion chamber, offering an innovative alternative for biomass combustion systems. Full article

Hydrogen-based direct reduction (H-DR) represents an environmentally benign and energy-efficient alternative in ironmaking that has significant industrial potential. This study reviews the current status of H-DR shaft furnaces and accompanying hydrogen-rich reforming technologies (steam and autothermal reforming), assessing the three dominant numerical frameworks used to analyze these processes: (i) porous medium continuum models, (ii) the Eulerian two-fluid model (TFMs), and (iii) coupled computational fluid dynamics (CFD)–discrete element method (DEM) models. The respective trade-offs in terms of computational cost and model accuracy are critically compared. Recent progress is evaluated from an engineering standpoint in four key areas: optimization of the pellet bed structure and gas distribution, thermal control of the reduction zone, sensitivity analysis of operating parameters, and industrial-scale model validation. Current limitations in predictive accuracy, computational efficiency, and plant-level transferability are identified, and possible mitigation strategies are discussed. Looking forward, high-fidelity multi-physics coupling, advanced mesoscale descriptions, AI-accelerated surrogate models, and rigorous uncertainty quantification can facilitate effective scalable and intelligent application of hydrogen-based shaft furnace simulations. Full article

This study comprehensively analyzes the free vibration and transient response for a sandwich piezoelectric laminated beam with elastic boundaries in a thermal environment. Quasi-3D shear deformation beam theory (Q3DBT) and Hamilton’s principle are used to obtain the thermo-electro-mechanical coupling equations, and the method of reverberation-ray matrix (MRRM) is utilized to integrate the phase and scattering relationship of the structure in a unified approach. Specifically, the scattering relationship established by the Mixed Rigid-Rod Model (MRRM) via dual coordinate systems describes the general dynamic model of the beam using generalized displacements and generalized forces at the two endpoints. This analytical solution is compared with the finite element numerical results based on Solid5 and Solid45 elements. The similarity of this approach lies in the fact that solid elements can account for the Poisson effect of thick beams, while the difference is that solid elements have a certain width; here, the error is minimized by adopting a single-element division in the width direction. Comparison of the numerical results under different geometric parameters and boundary conditions with the simulation software proves that MRRM has good accuracy and stability in analyzing the dynamic performance of sandwich piezoelectric laminated beams. On this basis, a spring-supported boundary technology is introduced to expand the flexibility of classical boundary conditions, and a detailed parameterization study is conducted on the material properties of the base layer, including the material parameters, geometric property, and the external temperature. The study in this article provides many new results for sandwich-type piezoelectric laminated structures to help further research. Full article

The reliability of mechanical systems hinges on analyzing the actual surface-to-surface contact area, which critically influences dynamic behavior, friction, material performance, and thermal dissipation. Uneven surfaces lead to incomplete contact, where only a fraction of asperities touch, creating a nominal contact area. This study proposes a novel fractal contact model for various mechanical behaviors between mechanical contact surfaces, integrating the Weierstrass–Mandelbrot fractal function and nonuniform rational B-spline interpolation (NURBS) to model material-dependent actual contact conditions. Furthermore, this research delved into the changes in thermal conductivity across the surfaces of metal materials within a simulated setting. It maintained a contact ratio ranging from 0.038% to 15.2%, a factor that remained unaffected by contact pressure. Both experimental and simulated findings unveiled an actual contact rate spanning from 0.44% to 1.06%, thereby underscoring the distinctive interface behaviors specific to different materials. The proposed approach provides fresh perspectives for investigating material–contact interactions and tackling associated engineering hurdles. Full article

This study provides a comprehensive three-dimensional Computational Fluid Dynamics analysis of airflow distribution in a surgical operating room under realistic occupancy and equipment conditions. Using integrated modelling in SolidWorks and a subsequent analysis in ANSYS Fluent, a full-scale Operating Room geometry was simulated to assess the effectiveness of a laminar airflow system. The model includes surgical staff mannequins, thermal loads from surgical lights, and medical equipment that commonly disrupt unidirectional flow patterns. A polyhedral mesh with over 2.8 million nodes was employed, and a grid independence study confirmed solution reliability. The realisable k–ε turbulence model with enhanced wall treatment was used to simulate steady-state airflow, thermal stratification, and pressure variation due to door opening. Results highlight significant flow disturbances and recirculation zones caused by the shear zone created by supply air, overhead lights and heat plumes, particularly outside the core laminar air flow zone. The most important area, 10 cm above the surgical site, shows a maximum velocity gradient of 0.09 s⁻¹ while the temperature gradient shows 6.7 K.m⁻¹ and the pressure gradient, 0.0167 Pa.m⁻¹. Streamline analysis reveals potential re-entrainment of contaminated air into the sterile field. Full article

Buildings account for nearly 32% of global energy consumption and serve as key demand-side flexibility resources in power systems with high renewable penetration. However, their utilization is constrained by the lack of an integrated framework that can jointly quantify energy-adjustable margin (BAM) and response duration (RD) under realistic operational and thermal comfort constraints. This study presents a coupled data–physical simulation framework integrating a Particle Swarm Optimization–Long Short-Term Memory–Random Forest (PSO-LSTM-RF) hybrid load forecasting model with EnergyPlus(24.1.0)-based building simulation. The PSO-LSTM-RF model achieves high-accuracy short-term load prediction, with an average R² of 0.985 and mean absolute percentage errors of 1.92–5.75%. Predicted load profiles are mapped to physically consistent baseline and demand-response scenarios using a similar-day matching mechanism, enabling joint quantification of BAM and RD under explicit thermal comfort constraints. Case studies on offices, shopping malls, and hotels reveal significant heterogeneity: hotels exhibit the largest BAM (up to 579.27 kWh) and longest RD (up to 135 min), shopping malls maintain stable high flexibility, and offices show moderate BAM with minimal operational disruption. The framework establishes a closed-loop link between data-driven prediction and physics-based simulation, providing interpretable flexibility indicators to support demand-response planning, virtual power plant aggregation, and coordinated optimization of source–grid–load interactions. Full article

In response to the decline in the inertia level of the power system caused by the large-scale integration of new energy, this paper proposes a grid-side pumped storage configuration strategy considering inertia constraints. The general pumped storage configuration ignores the duration of pumped storage and selects only single-duration units for capacity and power configuration. A single unit cannot balance rapid frequency response and long-term energy transfer, forcing thermal power to operate at high costs continuously to provide inertia support, while also causing a sharp increase in wind and solar power curtailment. This paper breaks through the limitations of the traditional single-duration pumped storage configuration and proposes a configuration-operation collaborative optimization strategy that combines inertia constraints and pumped storage duration selection. Firstly, starting from the system’s inertia requirements, the minimum inertia required by the system is obtained, respectively, based on the constraints of the system’s frequency change rate and the lowest point of the frequency. Furthermore, the minimum inertia demand constraint of the power system is constructed, and a capacity configuration strategy for grid-side pumped storage is proposed with the goal of minimizing the total operating cost of the power system throughout its entire cycle, taking into account the penalty term of the peak-valley difference index of the load curve and the penalty of the inertia guarantee value of medium and long-term units, while considering the inertia constraint. Finally, the effectiveness and superiority of the proposed method were verified through simulation analysis. Full article

This study focuses on the operational energy consumption of existing thermal power plant buildings in China’s hot-summer, cold-winter regions. Unlike conventional civil buildings, thermal power plant structures feature intense internal heat sources, large spatial dimensions, specialized ventilation requirements, and year-round industrial waste heat. Consequently, the energy consumption characteristics and energy-saving logic of their building envelopes remain understudied. This paper innovatively employs a combined experimental approach of field monitoring and energy consumption simulation to quantify the actual thermal performance of building envelopes (particularly exterior walls, doors, and windows) under current operating conditions, identifying key components for energy-saving retrofits of the main plant building envelope. Due to the fact that most thermal power plants were designed relatively early, their envelope structures generally have problems such as poor insulation performance and insufficient air tightness, resulting in severe energy loss under extreme weather conditions. An energy consumption simulation model was established using GBSEARE software. By focusing on heat transfer coefficients of exterior walls and windows as key parameters, a design scheme for energy-saving retrofits of building envelopes in thermal power plants located in hot-summer, cold-winter regions was proposed. The results show that there is a temperature gradient along the height direction inside the main plant, and the personnel activity area in the middle activity level of the steam engine room is the most unfavorable area of the thermal environment of the steam engine room. The heat transfer coefficient of the envelope structure does not meet the current code requirements. The over-standard rate of the exterior walls is 414.55%, and that of the exterior windows is 177.06%. An energy-saving renovation plan is proposed by adopting a composite color compression panel for the external wall, selecting 50 mm flame-retardant polystyrene EPS foam board for the heat preservation layer, adopting 6 high-transmittance Low-E + 12 air + 6 plastic double-cavity for the external windows, and adding movable shutter sunshade. The energy-saving rate of the building reached 55.32% after the renovation. This study provides guidance for energy-efficient retrofitting of existing thermal power plants and for establishing energy-efficient design standards and specifications for future new power plant construction. Full article

This paper describes how the thermal treatment of 3D-printed PLA samples, fabricated by Fused Deposition Modeling (FDM), affects elastic properties by means of vibrational spectroscopy and ultrasonic echography. Longitudinal and shear sound velocities were measured experimentally to determine Young’s, bulk, shear, and longitudinal moduli, as well as Poisson’s ratio. The results were complemented with two different simulation approaches—the elastodynamic finite integration technique (EFIT) and the equivalent electric analog technique implemented with LPSpice—whose predictive performance was assessed using statistical performance metrics. The circuit-based simulation method demonstrated superior agreement with experimental behavior compared to EFIT. Both measured and simulated data reveal that PLA chains undergo overall structural strengthening and enhanced packing up to 2 h of heating, followed by a clear reduction in these enhancements as thermal degradation emerges with further heating. Poisson’s ratio remained relatively stable throughout, indicating minimal impact on strain distribution characteristics despite observable stiffening and subsequent softening. Vibrational ATR (Attenuated Total Reflection) spectra corroborated these findings through systemic shifts in C-COO, C-O-C, and C-O stretching modes associated with the same structural modifications. Overall, this combined experimental–simulation framework provides an integrated understanding of thermally induced mechanical and molecular evolution in 3D-printed PLA relevant to defense applications. Full article

Net-shaped casting processes in the automotive industry have proved to be difficult to simulate due to the complexities of the interactions amongst thermal, fluid, and solute transport regimes in the solidifying domain, along with the interface. The existing casting simulation software lacks the necessary real-time estimation of thermophysical properties (thermal diffusivity and thermal conductivity) and the interfacial heat-transfer coefficient (IHTC) to evaluate the thermal resistances in a casting process and solve the temperature in the solidifying domain. To address these shortcomings, an axial directional solidification experiment setup was developed to map the thermal data as the melt solidifies unidirectionally from the chill surface under unsteady-state conditions. A Dilute Eutectic Cast Aluminum (DECA) alloy, Al-5Zn-1Mg-1.2Fe-0.07Ti, Eutectic Cast Aluminum (ECA) alloys (A365 and A383), and pure Al (P0303) were used to demonstrate the validity of the experiments to evaluate the thermal diffusivity (α) of both the solid and liquid phases of the solidifying metal using an inverse heat-transfer analysis (IHTA). The thermal diffusivity varied from 0.2 to 1.9 cm²/s while the IHTC changed from 9500 to 200 W/m²K for different alloys in the solid and liquid phases. The heat flux was estimated from the chill side with transient temperature distributions estimated from IHTA for either side of the mold–metal interface as an input to compute the interfacial heat-transfer coefficient (IHTC). The results demonstrate the reliability of the axial solidification experiment apparatus in accurately providing input to the casting simulation software and aid in reproducing casting numerical simulation models efficiently. Full article

Aviation permanent magnet synchronous motors (PMSMs) operate with high power density under high-altitude conditions, where the thermal sensitivity of permanent magnet materials and reduced air density make them prone to demagnetization faults. Even small performance degradation can therefore pose a risk to operational safety, and reliable demagnetization diagnosis is required. This paper analyzes the operating characteristics of an aviation interior PMSM under demagnetization faults and develops a dedicated diagnostic approach. A coupled electromagnetic–thermal finite element model is established to evaluate no-load and rated performance, compute losses under rated conditions, and obtain temperature distributions; the electromagnetic model is further corroborated using an RT-LAB semi-physical real-time simulation of the motor body. Altitude-dependent ambient air properties corresponding to 5000 m are then incorporated to assess the magneto–thermal field distribution and reveal the impact of high-altitude operation on temperature rise and demagnetization risk. Based on the thermal analysis, overall demagnetization faults are classified into several temperature-based levels, and representative local demagnetization cases are constructed; for each fault case, time-domain torque and phase-voltage signals and their frequency-domain components are extracted to form a fault dataset. Building on these features, an intelligent diagnostic method integrating a deep belief network (DBN) and an extreme learning machine (ELM) optimized by an enhanced fireworks algorithm (EnFWA) is proposed. Comparative results show that the proposed DBN–ELM–EnFWA framework achieves a favorable trade-off between diagnostic accuracy and training time compared with several benchmark deep learning models, providing a practical and effective tool for demagnetization fault diagnosis in aviation interior PMSMs. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by memory loss, cognitive decline, and oxidative stress-driven neuronal damage. Catalase, a key antioxidant enzyme, plays a vital role in decomposing hydrogen peroxide (H₂O₂) into water and oxygen, thereby protecting neurons from reactive oxygen species (ROS)-mediated toxicity. In AD, the catalase function is compromised due to reduced enzymatic activity and aggregation, which not only diminishes its protective role but also contributes to amyloid plaque formation through catalase-Aβ co-oligomers. Hence, therapeutic strategies aimed at simultaneously preventing catalase aggregation and enhancing its enzymatic function are of great interest. In this study, we screened twelve naturally occurring metabolites for their ability to modulate catalase aggregation and activity. Among these, dimethylglycine (DMG) emerged as the most potent candidate. DMG significantly inhibited thermally induced aggregation of catalase and markedly enhanced its enzymatic activity in a concentration-dependent manner. Biophysical analyses revealed that DMG stabilizes catalase by promoting its native folded conformation, as evidenced by increased melting temperature (T_m), higher Gibbs free energy of unfolding (ΔG°), and reduced exposure of hydrophobic residues. TEM imaging and Thioflavin T assays further confirmed that DMG prevented amyloid-like fibril formation. Molecular docking and dynamics simulations indicated that DMG binds to an allosteric site on catalase, providing a structural basis for its dual role in stabilization and activation. These findings highlight DMG as a promising therapeutic molecule for restoring catalase function and mitigating oxidative stress in AD. By maintaining catalase stability and activity, DMG offers potential for slowing AD progression. Full article

The rapid development of detection technologies has increased the demand for multispectral camouflage materials capable of broadband concealment and effective thermal management. To address the conflicting optical requirements between infrared camouflage and LiDAR camouflage, we propose a composite design combining a germanium–ytterbium fluoride (Ge/YbF₃) selective emitter with an amorphous silicon (a-Si) two-dimensional periodic microstructure. The multilayer film, optimized using the transfer-matrix method and a particle swarm optimisation algorithm, achieves low emissivity in the 3–5 μm and 8–14 μm infrared atmospheric windows and high emissivity within 5–8 μm for radiative cooling, while introducing a narrowband absorption peak at 1.55 μm. Additionally, the a-Si microstructure provides strong narrowband absorption at 10.6 μm via a grating-resonance mechanism. FDTD simulations confirm low emissivity in the infrared windows, high absorptance at LiDAR wavelengths, and good angular and polarization robustness. This work demonstrates a multifunctional photonic structure capable of integrating infrared camouflage, laser camouflage, and thermal-radiation control. Full article

Medical personnel wearing barrier clothing protecting against infectious agents are at risk of heat stress resulting from limited heat exchange with the environment. The aim of the study was to assess the impact of changing underwear on the thermal parameters of protective clothing sets and on the expected safe working time. The study used a Newton thermal manikin to determine the thermal insulation and water vapor resistance of clothing sets consisting of three types of underwear (standard medical underwear and short and long thermal underwear) worn under two types of barrier suits. The obtained data were used to conduct physiological simulations in the Predicted Heat Strain (PHS) program, estimating the time it takes for core body temperature to rise to 38 °C in conditions of 22 °C and 35 °C. The results showed that replacing medical underwear with thermal underwear at 22 °C extended safe working time by 24%. In hot conditions (35 °C), the positive impact was smaller, extending working time by a maximum of 4%. Changing the inner layer is an effective method of improving comfort and safety in barrier clothing, especially in thermoneutral conditions. Full article

In order to effectively reveal the nonlinear characteristics of a dish concentrating solar thermal power system (DCSTPS) under pulsating wind-induced loads, a fluid simulation model of the DCSTPS was established, and the simulated pulsating winds were developed via the user-defined function (UDF) combined with the autoregressive (AR) model using MATLAB (R2015b). And based on the fluid simulation calculations of the DCSTPS, the time-range data of the relevant wind vibration coefficients under different working conditions were obtained. The research results show the following: (1) When the altitude angle α is 0° or 180° due to the azimuth angle β = 0°, the maximum values of their drag coefficient C_x, lateral force coefficient C_y, and lift coefficient C_z are similar, and the maximum of rolling moment coefficient C_Mx is significantly smaller than the values at the other two angles; the maximum of the pitch moment coefficient C_My and maximum of the azimuth moment coefficient C_Mz are significantly larger than the values of the other two angles. (2) The increase in altitude angle α leads to a reduction in the drag coefficient C_x, an increase in the lift force coefficient C_z, and an increase of the pitch moment C_Mx. Moreover, an improved phase space delay reconstruction method was developed to calculate the delay time, Lyapunov exponent, and Kolmogorov entropy of the DCSTPS, and the research results show that (1) the maximum Lyapunov exponent and Kolmogorov entropy of the DCSTPS are greater than zero under the action of pulsating wind; (2) the action of pulsating wind will cause increases in the maximum Lyapunov exponent and Kolmogorov entropy of the DCSTPS and will accelerate the divergence speed of the DCSTPS trajectory; and (3) the time for the DCSTPS to enter the chaotic state will be shortened, while the time of entering a chaotic state and degree of subsequent chaotic states will be significantly affected by relevant wind vibration coefficients but without regularity. Full article