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In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

The present study assesses the impact resistance of the shear thickening fluids-filled (STFs-filled) foam through drop-hammer impact tests.

The maximum residual impact load and specific impact energy absorption rate of STF-filled foam are studied with varying thickness (4–14 mm), densities (0.35–0.6 g/cm3) and hardness (40–50 Rockwell Hardness C Scale (HRC)) under different ambient temperatures (−20−20 °C) and impact energies (25–75 J).

The following conclusions are obtained from this study: (1) the higher the impact energy, the greater the maximum residual impact force and energy absorption efficiency of the material; (2) the impact resistance of STF-filled foam can be improved with the decrease of ambient temperature, achieving the highest energy absorption rate at −10?. (3) STF-filled foam substrate has the highest impact resistance, the lowest maximum residual impact force and the highest energy absorption coefficient when the density is 0.35  g/cm3, the hardness is 45HC and the thickness is 10 mm.

This is the first paper to analyze the impact of both environmental factors and material properties on the impact resistance of STF-filled foam. The results show that the decrease in temperature and the increase in hardness can enhance the impact resistance of STF-filled foam.

The purpose of this paper is to realize the lightweight of connecting rod and meet the requirements of low energy consumption and vibration. Based on the structural design of the original connecting rod, the finite element analysis was conducted to reduce the weight and increase the natural frequencies, so as to reduce materials consumption and improve the energy efficiency of internal combustion engine.

The finite element analysis, structural optimization design and topology optimization of the connecting rod are applied. Efficient hybrid method is deployed: static and modal analysis; and structure re-design of the connecting rod based on topology optimization.

After the optimization of the connecting rod, the weight is reduced from 1.7907 to 1.4875 kg, with a reduction of 16.93%. The maximum equivalent stress of the optimized connecting rod is 183.97 MPa and that of the original structure is 217.18 MPa, with the reduction of 15.62%. The first, second and third natural frequencies of the optimized connecting rod are increased by 8.89%, 8.85% and 11.09%, respectively. Through the finite element analysis and based on the lightweight, the maximum equivalent stress is reduced and the low-order natural frequency is increased.

This paper presents an optimization method on the connecting rod structure. Based on the statics and modal analysis of the connecting rod and combined with the topology optimization, the size of the connecting rod is improved, and the static and dynamic characteristics of the optimized connecting rod are improved.

This study investigates the impact of the fire decay phase on structural damage using the sectional analysis method. The primary objective of this work is to forecast the non-dimensional capacity parameters for the axial and flexural load-carrying capacity of reinforced concrete (RC) sections for heating and the subsequent post-heating phase (decay phase) of the fire.

The sectional analysis method is used to determine the moment and axial capacities. The findings of sectional analysis and heat transfer for the heating stage are initially validated, and the analysis subsequently proceeds to determine the load capacity during the fire’s heating and decay phases by appropriately incorporating non-dimensional sectional and material parameters. The numerical analysis includes four fire curves with different cooling rates and steel percentages.

The study’s findings indicate that the rate at which the cooling process occurs after undergoing heating substantially impacts the axial and flexural capacity. The maximum degradation in axial and flexural capacity occurred in the range of 15–20% for cooling rates of 3 °C/min and 5 °C/min as compared to the capacity obtained at 120 min of heating for all steel percentages. As the fire cooling rate reduced to 1 °C/min, the highest deterioration in axial and flexural capacity reached 48–50% and 42–46%, respectively, in the post-heating stage.

The established non-dimensional parameters for axial and flexural capacity are limited to the analysed section in the study owing to the thermal profile, however, this can be modified depending on the section geometry and fire scenario.

The study primarily focusses on the degradation of axial and flexural capacity at various time intervals during the entire fire exposure, including heating and cooling. The findings obtained showed that following the completion of the fire’s heating phase, the structural capacity continued to decrease over the subsequent post-heating period. It is recommended that structural members' fire resistance designs encompass both the heating and cooling phases of a fire. Since the capacity degradation varies with fire duration, the conventional method is inadequate to design the load capacity for appropriate fire safety. Therefore, it is essential to adopt a performance-based approach while designing structural elements' capacity for the desired fire resistance rating. The proposed technique of using non-dimensional parameters will effectively support predicting the load capacity for required fire resistance.

The fire-resistant requirements for reinforced concrete structures are generally established based on standard fire exposure conditions, which account for the fire growth phase. However, it is important to note that concrete structures can experience internal damage over time during the decay phase of fires, which can be quantitatively determined using the proposed non-dimensional parameter approach.

This paper aims to investigate the optimization of window and shading designs to reduce the building energy consumption of a standard office room while improving occupants' comfort in Tehran and Auckland.

The NSGA-II algorithm, as a multi-objective optimization method, is applied in this study. First, a comparison of the effects of each variable on all objectives in both cities is conducted. Afterwards, the optimal solutions and the most undesirable scenarios for each city are presented for architects and decision-makers to select or avoid.

The results indicate that, in both cities, the number of slats and their distance from the wall are the most influential variables for shading configurations. Additionally, occupants' thermal comfort in Auckland is much better than in Tehran, while the latter city can receive more daylight. Furthermore, the annual energy use in Tehran can be significantly reduced by using a proper shading device and window-to-wall ratio (WWR), while building energy consumption, especially heating, is negligible in Auckland.

To the best of the authors' knowledge, this is the first study that compares the differences in window and shading design between two cities, Tehran and Auckland, with similar latitudes but located in different hemispheres. The outcomes of this study can benefit two groups: firstly, architects and decision-makers can choose an appropriate WWR and shading to enhance building energy efficiency and occupants' comfort. Secondly, researchers who want to study window and shading systems can implement this approach for different climates.

The purpose of this study is to investigate the influence of light intensity and sources of carbon and nitrogen on the cultivation of Spirulina maxima.

Cultures were carried out in a modified Zarrouk medium using urea, sodium acetate and glycerol. A Taguchi experimental design was used to evaluate the effect on the production of biocompounds: productivities in biomass, carbohydrates, phycocyanin and biochar were analyzed.

Statistical data analysis revealed that light intensity and sodium acetate concentration were the most important factors, being significant in three of the four response variables studied. The highest productivities in biomass (46.94 mg.L⁻¹.d⁻¹), carbohydrates (6.11 mg.L⁻¹.d⁻¹), phycocyanin (3.62 mg.L⁻¹.d⁻¹) and biochar (22, 48 mg.L⁻¹.d⁻¹) were achieved in experiment 4 of the Taguchi matrix, highlighting as the ideal condition for the production of biomass, carbohydrates and phycocyanin.

Sodium acetate and urea can be considered, respectively, as potential sources of carbon and nitrogen to increase Spirulina maxima productivity. From the results, an optimized cultivation condition for the sustainable production of bioproducts was obtained.

This work focuses on the study of the influence of light intensity and the use of alternative sources of nitrogen and carbon on the growth of Spirulina maxima, as well as on the influence on the productivity of biomass and biocompounds. There are few studies in the literature focused on the phycocyanin production from microalgae, justifying the need to deepen the subject.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

Needs change as people get older. Procuring resources to satisfy them can generate anguish and insecurities in consumers due to their financial situation. This study aims to analyze the relationship between age and financial stress among Mexican adults and estimate the age of their maximum financial stress.

This study is based on constructing a financial stress indicator using the confirmatory factor analysis and linear regression models with a quadratic term, employing data from the National Survey on Financial Inclusion 2021.

Results show that the relationship between age and financial stress follows a quadratic pattern, with a maximum level at age 56, which varies according to sex, marital status, number of dependents, education and regions. These findings interest financial product designers and policy developers who aim to improve consumers' well-being.

Longitudinal studies and indicators, such as financial fragility, are needed to facilitate refining models over time.

There is no evidence of studies that have addressed the age of maximum financial stress in Latin America. Doing so is relevant because identifying the stages in life when adults are most vulnerable to financial stress helps assess its causes more precisely, thus mitigating its adverse effects.

The purpose of this paper is to investigate the nonsimultaneous impact of three impactors with spherical tip on the response of a low-velocity impact on a beam.

In this research, the third-order shear deformation theory of the beam with hyperbolic shear-strain function is used. Hamilton’s principle is applied to derive the motion equations. To simulate nonsimultaneous impacts, by using the Hertz nonlinear contact law, the contact of the impactors with different times is simulated. Comparisons with other articles are carried out in the one impactor form.

In the parametric study, the histories of the contact force and displacement of the beam are investigated in the presence of only one impactor in the center of the beam and also in the presence of three impactors, one in the center of the beam and the other two around the first impactor with a delay. One of the important and noteworthy points is that the presence of two impactors with a delay causes the maximum contact force and contact time to decrease and the maximum displacement of the beam center to increase.

The original point of this paper is what is the difference between the impact response of one projectile and three nonsimultaneous projectiles on the beam.

Soft robots are known for their excellent safe interaction ability and promising in surgical applications for their lower risks of damaging the surrounding organs when operating than their rigid counterparts. To explore the potential of soft robots in cardiac surgery, this paper aims to propose an adaptive iterative learning controller for tracking the irregular motion of the beating heart.

In continuous beating heart surgery, providing a relatively stable operating environment for the operator is crucial. It is highly necessary to use position-tracking technology to keep the target and the surgical manipulator as static as possible. To address the position tracking and control challenges associated with dynamic targets, with a focus on tracking the motion of the heart, control design work has been carried out. Considering the lag error introduced by the material properties of the soft surgical robotic arm and system delays, a controller design incorporating iterative learning control with parameter estimation was used for position control. The stability of the controller was analyzed and proven through the construction of a Lyapunov function, taking into account the unique characteristics of the soft robotic system.

The tracking performance of both the proportional-derivative (PD) position controller and the adaptive iterative learning controller are conducted on the simulated heart platform. The results of these two methods are compared and analyzed. The designed adaptive iterative learning control algorithm for position control at the end effector of the soft robotic system has demonstrated improved control precision and stability compared with traditional PD controllers. It exhibits effective compensation for periodic lag caused by system delays and material characteristics.

Tracking the beating heart, which undergoes quasi-periodic and complex motion with varying accelerations, poses a significant challenge even for rigid mechanical arms that can be precisely controlled and makes tracking targets located at the surface of the heart with the soft robot fraught with considerable difficulties. This paper originally proposes an adaptive interactive learning control algorithm to cope with the dynamic object tracking problem. The algorithm has theoretically proved its convergence and experimentally validated its performance at the cable-driven soft robot test bed.