Radiant heating and cooling systems integrating active terminals with building envelopes offer high thermal comfort potential; however, the transient complementarity between active radiate terminals and passive building envelopes remains insufficiently quantified. This study aims to clarify how dynamic energy transmission mechanisms between air-carrying energy radiant terminals and building envelopes jointly influence indoor thermal environment and thermal comfort. Dynamic heating and cooling experiments were conducted for three terminal configurations (sidewall, ceiling, and composite walls), and a novel energy transfer decoupling model was developed to separately characterize heat exchange among the building envelope, occupied zone, and energy storage zone, accounting for radiation, convection, conduction, and air diffusion. In addition, a complementary model based on regression analysis and principal component analysis was established to quantify the relative influence of envelope surface temperatures on indoor air temperature and predicted mean vote (PMV). The proposed decoupling model predicts indoor air temperature with high accuracy (error < +/- 0.5 degrees C). The composite walls exhibited the fastest response (heating rate: 12.9 degrees C/h for air and about 16-9 degrees C/h for envelopes; cooling rate: 7.4 degrees C/h for air and about 6-8 degrees C/h for envelopes) with vertical temperature differences <= 0.3 degrees C in summer and <= 1.5 degrees C in winter, achieving thermal neutrality within 25 min. Radiative heat transfer dominated in the ceiling terminal, accounting for 68 % in winter and 50 % in summer. The complementary model further reveals that radiant surface temperatures exert a stronger influence on thermal comfort in heating than in cooling conditions. These findings provide quantitative insights into the synergistic interaction between radiant terminals and building envelopes, offering practical guidance for optimizing terminal design and improving energy efficiency in buildings.

Vacuum membrane dehumidification can be effectively integrated with diverse refrigeration technologies due to its capability for nearly isothermal dehumidification, making it a promising environmentally friendly alternative for dehumidification approach. This study develops a low-selectivity vacuum dehumidification membrane using a PTFE substrate and a PVA/LiCl active layer. The effects of permeate side vacuum level, inlet air flowrate, and LiCl concentration on dehumidification performance are experimentally investigated. Results show that the dehumidification effectiveness increases with vacuum level, whereas the COP decreases. Meanwhile, increasing inlet air flowrate can lower dehumidification effectiveness but have limited influence on membrane selectivity. Besides, under a vacuum level of approximately 48 kPa, the dynamic response times for membranes prepared using casting solutions containing 4 g, 5 g, and 6 g of LiCl are 250 s, 750 s, and 1000 s, respectively. The results demonstrate that higher LiCl concentration in the casting solution may longer the response time, but with better dehumidification performance. Finally, CFD results reveal the internal flow characteristics of the vacuum membrane dehumidification module, which can be used to design and improve the airflow organization inside the dehumidification module, thereby achieving effective utilization of the membrane. These findings can provide reference for further application of vacuum membrane dehumidification air conditioning systems in building energy conservation.

The form of building ventilation has an important impact on building energy consumption and indoor environmental quality. As a typical ventilation method, wall jet is widely used in engineering practice with its unique flow characteristics and efficient heat transfer capability. In this investigation, based on the velocity distribution of the wall jet, the new models of the jet centerline trajectory, the attachment length and the jet core length are established by considering the multi-buoyancy effect. The “inertia effect travel” parameter is innovatively proposed to quantitatively characterize the influence of buoyancy on jet inertia. The results show that compared with the traditional model which ignores the multi-buoyancy effect, the calculated results of the new model are in much better agreement with the experimental data, especially in the conditions of small temperature difference and high Reynolds number, where the prediction accuracy is much better. The theoretical calculations and numerical simulation results further confirm that the indoor air stability conditions affect the inertia flow of the jet. The unstable condition inhibits the jet inertia, while the stable condition is conducive to maintaining the jet inertia. The established new model provides an important theoretical basis for the optimal design of the wall jet ventilation system and the regulation of indoor environment.

The thermal performance of building envelopes significantly impacts indoor temperature stability and building energy efficiency. However, existing research has paid limited attention to the comprehensive effects of interactions among envelope components on the indoor thermal environment, making it challenging to achieve ideal indoor thermal conditions through optimal envelope configuration in practical design. To address this research gap, this work has developed complementary heat transfer models in the form of radiation and convection based on fundamental thermodynamic principles. The accuracy and applicability of these models are validated using cross-seasonal experimental data. Results demonstrate that both the Radiation-air temperature correlation-complementary model and the convection-air temperature correlationcomplementary model exhibit high predictive precision, with maximum mean relative errors of only 2.03 % and 1.93 %, respectively. Sensitivity analysis further reveals distinct characteristics between the two models, with the radiation model exhibiting stronger nonlinearity (mean 6/mu* = 0.893) and greater sensitivity under large temperature differences and complex radiation conditions. Conversely, the convection model demonstrates more pronounced linearity (mean 6/mu* = 0.565) and higher sensitivity to small temperature differences and strong ventilation conditions. This study provides a high-performance simulation tool for optimizing the thermal performance of building envelopes, which contributes to enhanced indoor thermal comfort and reduced energy consumption in architectural design and operation.

This work aims to simultaneously improve thermal management, energy efficiency, and operational reliability of data centers through the regulation of air stability and the proposed dimensionless indicator. Three different types of local indoor air stability in data centers are constructed: unstable, stable and neutral conditions. Computational fluid dynamics was used to analyze the thermal environment of data centers. The results show that a uniform distribution of servers has the best heat dissipation effect, and this layout is a form of weak air stability. The heat dissipation effect of the data center is the best in the stable condition, followed by neutral condition, and worst when unstable. And the most unfavorable temperature has decreased by nearly 12.5% compared with the unstable condition, especially in low-flow cabinets near air conditioning units. A new evaluation index for judging the thermal environment of data rooms is proposed. Cabinets with a small HDEI number have poor heat dissipation effects, and local hotspots in data centers occur near servers with a small HDEI number. The evaluation index provides a new approach to identifying hotspots in data centers. This research provides new insights into the layout of data centers and has practical significance for thermal management in data centers.

The lattice Boltzmann method (LBM) has been applied to dynamic simulations of hyperelastic solids. However, when a single distribution function is used, the nonlinear part of the hyperelastic stress is difficult to represent through the moment terms of the distribution function. As a result, the constitutive relation of hyperelastic materials cannot be completely recovered, which limits the computational accuracy of LBM simulations. To address this issue, a dual-distribution-function formulation is introduced in this work. In this formulation, an additional set of distribution functions is assigned specifically to the deformation-gradient tensor, so that the complete hyperelastic stress can be naturally obtained through the evolution of the deformation gradient. Based on the D2Q9 lattice and BGK relaxation, a LBM algorithm with third-order accuracy is developed for dynamic simulations of compressible Neo-Hookean materials through a fourth-order Chapman--Enskog expansion. The implementation of Dirichlet and Neumann boundary conditions under the dual-distribution-function formulation is also discussed. Numerical experiments demonstrate that the proposed algorithm achieves higher computational accuracy than existing methods, and the admissible range of Poisson's ratio is substantially extended.

Accurate reconstruction of indoor airflow fields is essential for improving ventilation performance and enabling data-assisted control of indoor environments. However, conventional PINNs often suffer from degraded physical consistency when applied to high Reynolds number wall jet flows because pointwise differential constraints alone are insufficient to accurately capture strong gradients, nonlinear interactions, and complex flow topology. This investigation develops a physics-informed framework for physically stable reconstruction of indoor wall jet ventilation flow fields by integrating finite-volume weak constraints and physics-guided regularization. A control-volume-based weak formulation is introduced to enforce integral conservation of mass and momentum, while a wall-corrected turbulence-model-inspired effective viscosity correction and regularization strategy are incorporated to improve near-wall stability and suppress non-physical fluctuations. Furthermore, a decoupled neural architecture is developed to enhance the representation of velocity and pressure fields with different physical characteristics. The proposed framework is evaluated using a two-dimensional indoor wall jet flow case through comprehensive comparisons, ablation analyses, and sensitivity investigations. Results demonstrate that the proposed framework achieves more accurate reconstruction than a conventional PINN while providing more physically stable recovery of flow topology and near-wall flow structures, particularly in high-gradient regions and recirculation zones. The results further reveal that reliable flow reconstruction depends not only on measurement fitting accuracy but also on the recovery of physically consistent flow structures. By balancing observational information and governing physical constraints, the proposed framework provides an effective approach for reconstructing complex indoor ventilation flows and offers a promising foundation for physics-consistent data-driven airflow reconstruction.

This study introduced a novel method to determine the water vapour permeability of composite porous materials. The permeability of a composite material as a combination of porous solid-phase with micropores and gas-phase with macropores in a unit cell of material was evaluated. The method mainly considered element structure models for total porous materials and the density-concentration averaging method for the porous solid phase. Literature comparison results show that the element structure model can clearly reflect the characteristics of permeability variations with porosity. The verification results of literature experiments show that the permeability of composite porous materials can be effectively predicted with an average error 13% when the density-concentration averaging method of porous solid-phase was introduced into the element structure model. For highly porous materials, a higher increase in the porous solid-phase permeability coefficient did not significantly change the overall permeability of the material. The results show that the porous materials with cylindrical and circular truncated cone pores have poor permeability enhancement potential. In general, this study provides a reliable experimental supplement method for determining the water vapour permeability, which can guide the design of new materials, the optimization of building envelope and the simulation of energy consumption in building environment.

The transmission of pollutants and viral aerosols is an important way to cause indoor respiratory infections. Influence of ventilation modes and indoor air stability (IAS) on infection risk of the sitting breathing microenvironment of four people were simulated by CFD. Ventilation efficiency and infection risk were assessed using the contaminant dispersion index (CDI) and a Wells-Riley model based on SF6. The results show that unstable, upper supply and lower return contribute to the uniform indoor airflow and the average indoor wind speed is approximately twice that of other working conditions. Under the upper supply and lower return, the average SF6 concentration in the breathing microenvironment under unstable condition was 20.4 % lower than stable condition. Unstable can increase the intensity of turbulent fluctuations, enhance vertical diffusion, break the accumulation of pollutants, rapidly dilute and remove SF6 in the breathing microenvironment. Upper supply and lower return can reduce the average CDIb by 30-65 % within 15-30 min under unstable condition which has the strongest pollutant diffusion capacity. Under stable condition, the transient infection risk at the location next to the infected person is lower than that under unstable condition. Ventilation strategies and indoor air stability will have an impact on infection risk after 16 min. The combination of upper supply lower return and unstable condition can reduce the infection risk of three susceptible individuals by 51.3 %, 35.6 % and 11.4 % than that under stable condition, respectively.

Evaluation metrics and prediction methods for carbon dioxide (CO2) concentration play a critical role in Demand-Controlled Ventilation (DCV) optimization. However, the non-uniform impact of pollution sources on transient CO2 distribution in personal air quality (PAQ) is frequently overlooked. This study aims to propose a new equivalent CO2 index (ECO2) and a computational CO2 concentration (CCO2) model to investigate transient CO2 diffusion. This method defines uniformly mixed reference concentration per unit time, background index for pinpointing the most disadvantaged breathing-zone with excessive CO2 accumulation, and the correction factor for exhaled CO2 at different heights; the model consists of air changes per hour (ACH), characteristics of occupant, temperature, pressure gradients, CO2 exhaled rates, pollutant diffusion duration, and correction factor for varying breathing-zone heights. Transient CO2 diffusion patterns for various ceiling and sidewall terminals of heating and cooling systems were investigated through analyzing experimental and computational fluid dynamics (CFD) simulation results. Transient CFD simulation and the computation model were validated for effective prediction of CO2 concentrations at varying breathing-zone heights. Under the unstable dynamic airflow system, CO2 distribution was primarily governed by vertical convection/thermal plumes. The ceiling cooling has the smallest CO2 concentration difference at different heights, which has a higher average ECO2 value. Under the stable thermally stratified system, the ceiling heating promoted horizontal pollutant diffusion. Moreover, the average positive ECO2 had increased by 4.9 % by optimizing the design scheme based on individual demand. This investigation quantifies non-uniform CO2 distributions from pollution sources, enabling PAQ-based prediction and ventilation optimization.

Creating a comfortable and healthy indoor environment is very important for indoor occupants. It is difficult to obtain complete information about the indoor airflow field from experimental measurements only, but traditional computational fluid dynamics methods require a lot of time and complex boundary conditions. With the advent of data-driven methods, the cost of the reconstruction of indoor airflow fields has been greatly reduced. Therefore, a two-dimensional airflow field with only a limited amount of experimental measurement data is reconstructed using a physics-informed neural network (PINN), and the constructed PINN model increases the physical interpretability of the neural network through the Navier-Stokes equations. Subsequently, the influence of the number and spatial location of the experimental measurement points on the accuracy of the PINN model for the reconstruction of the indoor airflow field is discussed, and the influence of different spatial locations of the measurement points on the PINN model for the reconstruction of the indoor airflow field is analyzed in more detail by orthogonal experiments with non-global information and orthogonal experiments with global information. The results show that the indoor airflow field can be reconstructed accurately by using only a limited amount of measurement points to participate in the training of the PINN model, and the measurement points that can reflect the vortex information in the airflow field are more favorable for the reconstruction of the airflow field. Moreover, only orthogonal experiments with global information can effectively infer the optimal spatial location for sampling measurement points in the airflow field.

An air-carrying energy system (ACES) is a novel terminal for air conditioning with energy-saving potential. However, there is a challenge for optimizing the system by reducing energy consumption while improving thermal comfort. Thus, this study coupling simulated non-uniform thermal environment and human body by a transient three-dimensional model integrating with the thermophysiological model. Based on the experimental and simulated results, the local thermal comfort over time was evaluated by energy and exergy analysis to explore the convenient predicted formula of exergy consumption, and then the energy consumptions of different heating/cooling radiant diffuse terminals were compared under the same thermal comfort. The results showed that the simulated temperature of indoor air and human thermal plume were consistent with the experiments (Average error is less than 5 %). Local human-body exergy analysis was correlated with PMV by being divided into the torso and other body parts. The convenient predicted formula of exergy consumption for multiple body parts was accurate with the goodness of fit R-2 > 0.98. The ceiling cooling was 36 % more energy efficient than the sidewall cooling. Optimized system of the ceiling heating reduced by 14 % energy consumption. This paper provides a valuable reference for optimizing systems based on comfort and energy saving.

This paper introduces an accelerated lattice Boltzmann method (LBM) tailored for both fluid and solid simulations, utilizing the inertial relaxed Bhatnagar-Gross-Krook (IR-BGK) operator, referred to as IR-LBM. The Navier-Stokes equations and the elastic lamina deformation equation are derived from the Boltzmann equation using the Chapman-Enskog expansion. It is demonstrated that the Boltzmann equation based the IR-BGK operator exhibits a second-order error related to both the time step and the inertia term. Numerical tests employing the D2Q9 and D3Q15 lattice velocity models are conducted to simulate the streamline distribution of cavity flow across various Reynolds numbers and the deformation of elastic lamina under different load patterns using IR-LBM. Results indicate that IR-LBM achieves acceptable accuracy and superior convergence rates compared to the original LBM. Optimal configurations for the inertia term in fluid and solid simulations are provided. This work potentially offers a new approach for enhancing LBM-based algorithms for fluid-structure interaction in future applications.

This paper concerns with the symmetric generalized eigenvalue complementarity problem (GEiCP) in large-scale settings. A block Lanczos method is presented in this paper to solve the symmetric GEiCP, based on the fact that a large-scale symmetric GEiCP is equivalent to its corresponding small-scale symmetric GEiCP at the event of the exact breakdown of the block Lanczos projection process. The quadratically constrained quadratic programming (QCQP) formulation is employed to solve the small-scale symmetric GEiCP for an approximate solution to the original symmetric GEiCP. The convergence analysis is presented for the case in which the block Lanczos projection process experiences no breakdown, and the convergence rate of the block Lanczos method for solving GEiCP is elaborated in detail. We compare three types of QCQP solvers based on the block Lanczos method, and numerical results demonstrate the efficiency of the block Lanczos method in solving the symmetric GEiCP.

This study investigates the impact of surface coating on the humidity control capability of porous hygroscopic material, and proposes a dual-scale correlation method for moisture buffering (MBV). First, the findings indicate that the primary factors that influence the negative effects of coatings are the moisture response ability of the material and the temperature and relative humidity difference in the measuring environment. As these factors increase, the impact of the coating on the wet physical properties decreases, such as the moisture buffering effect, the deviation can be reduced from 28% to 3%. Furthermore, this research considers the moisture resistance of the air layer on the material surface as the main reason for the deviation between the ideal MBV model and the measured value. And an optimized ideal MBV model is proposed in this study, which demonstrates improved accuracy and is better suited for calculating MBV of materials. Finally, this study presents a dual-scale method that correlates the material-scale results obtained from laboratory tests with the full-scale results obtained from application simulations. Research and sensitivity results indicate that this dual-scale method is effective and reliable. Moreover, the impact of the coating on the actual indoor humid environment is acceptable when the comfortable requirements are not high. In conclusion, this study establishes a research foundation for simulating and applying coupled coatings on hygroscopic materials, facilitating enhanced passive control of indoor humidity environment and improved building energy efficiency.

Air source heat pump (ASHP) faces problems of performance deterioration when operating at low ambient temperature due to the low compression ratio, high discharge temperature, frost accumulation, etc., and may even become nonfunctional at sub-zero-centigrade ambient temperature, requiring attention and tools for studying. This paper proposed a kind of holistic process distributed parameter simulation approach of ASHP system adopting the hybrid PID-bisection (PID: proportional-integral-derivative) control algorithm. Main components of the ASHP are modeled with the distributed parameter method. An adiabatic compression model of two-phase fluid based on thermodynamics is proposed. The PID-bisection control algorithm and variable speed integral PID & bisection control algorithm are proposed and applied to iterative computation of the model. A single/two-stage compression ASHP with an intercooler is simulated by this approach. The average deviation of simulation results of the model from experimental data is not more than 7 %, and the maximum deviation is not more than 18 %. For simulation of single-stage compression mode, the maximum error is not more than 4%. For simulation of two-stage compression mode under low-evaporating-temperature operating conditions, the maximum error is not more than 4%. Computational speed of the ASHP model is significantly improved by using the PID-bisection control algorithm, and could be further accelerated by using the variable speed integral PID & bisection control algorithm. The proposed simulation approach is not only effective in sophisticated simulation of performance of single-stage and two-stage compression ASHP, but also potential for research on the optimization of the ASHP in cold regions.

A novel air-carrying energy radiant diffuse terminal is proposed, and the response of the terminal is investigated by field experiment and numerical simulation. This paper explores the dynamic operation characteristics of the new system to guide the optimal operation of the system. A transient simulation method of three factors (conduction, convection, and radiation) with dual-circulation (air-carrying energy zone and occupied zone) is put forward for the radiant diffuse terminal with a fresh air system. This transient simulation sets up the porous baffle model coupling radiation model concurrently, revealing the dynamic thermal performance for the system's response accurately, quickly, and comprehensively. This method avoids the limits for the complexity of mini porous (Pore size of 1 mm-3mm) geometric models and the transient uncertainty in multiple combination models. The results show that the average error between the convective-conductive model and the convectiveconductive-radiative model is about 8% at five different heights. This system has high response performance, which can quickly heat the room while maintaining the comfort requirements of vertical temperature. The radiated heat transfer between the radiant diffuse terminal and the occupied zone is greater than the convective heat transfer (Radiation accounts for 74%). This system has a short response time, high energy efficiency, uniform airflow, and eliminates draught rating. Moreover, the indoor non-uniform transient thermal and humid environments, the thermal comfort, and air quality for the response of the terminal with fresh air system under four different diffuser placements are compared using computational fluid dynamic simulation. The results indicate that introducing heating strategies featuring higher-positioned fresh air inlet and lower-positioned recirculation return air outlet for this system leads to a temperature efficiency increase by 5%, velocity uniformity by 8%, and age of air reduction by 16-50% in human-breathed zone and the response time by 25%, which shows substantial potential for energy savings. The transient simulation and experiments in the paper are beneficial to optimize design parameters and carry out energy-saving applications of operation energy consumption for the response of this terminal with a fresh air system in the future.