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Environmental management for collections : alternative conservation strategies for hot and humid climates
\"A practical guide to the conservation of museum and other cultural heritage collections in hot and humid climates\"--Provided by publisher.
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WAAM system with interpass temperature control and forced cooling for near-net-shape printing of small metal components
In an attempt to find a solution similar to the FDM 3D printers which would allow cost-effective and reliable additive manufacturing of metal components, this paper proposes a three-axis WAAM system capable of reliably printing small, near-net-shape metal objects. The system consists of gas metal arc (GMA) process equipment, a three-axis CNC positioning system, the interpass temperature control and forced cooling of the base plate and the deposit. The main challenge addressed is the minimisation of shape distortions caused by excessive heat accumulation when printing small objects. The interpass temperature control uses an IR pyrometer to remotely measure the last deposited layer and a control system to keep the interpass temperature below the predefined value by stopping the deposition after each layer in order to allow the deposit to cool. This results in a stable and more repeatable shape of the deposit, even when the heat transfer conditions are changing during the build-up process. The combination of adaptive interlayer dwell time and forced cooling significantly improves system productivity. Open-source NC control and path generation software is used, which enables fast and easy creation of the control code. Different control methods are evaluated through the printing of simple walls, and the printing accuracy is evaluated by printing small shell objects. As the results show, the interpass temperature control allows small objects to be printed at near-net shape with a deviation of 2%, which means that successful printing of 3D shapes can be achieved without trial and error approach.
Journal Article
Alleviation of Field Low-Temperature Stress in Winter Wheat by Exogenous Application of Salicylic Acid
Low temperature in later spring severely limits plant growth and causes considerable yield loss in wheat. In this study, the impacts of exogenous salicylic acid (SA) on plant growth, grain yield and key physiological parameters of wheat plants were investigated under field low-temperature conditions using a field air temperature control system (FATC). The results showed that low-temperature stress significantly decreased leaf net photosynthetic rate, plant height and biomass production of wheat plants at the jointing stage, resulting in a reduction in grain yield. Moreover, the growth period of wheat plants was prolonged by low-temperature stress. However, SA-treated plants significantly improved the photochemical efficiency of photosystem II, accumulation of osmo-protectants, activities of enzymatic antioxidants, and pool of non-enzymatic low molecular substances compared with non-SA-treated plants under low-temperature stress. Pretreatment with SA effectively alleviated low-temperature-induced reduction in leaf net photosynthetic rate, plant height, biomass production and grain yield as well as prolonging of growth period of wheat plants. However, SA-treated plants had no significant effects on the expression levels of cold-responsive genes compared with non-SA-treated plants under low-temperature stress. Our results demonstrated that exogenous application of SA is an appropriate strategy for wheat to resist late spring low-temperature stress under field conditions.
Journal Article
Internal Gas-Assisted Mold Temperature Control for Improving the Filling Ability of Polyamide 6 + 30% Glass Fiber in the Micro-Injection Molding Process
In micro-injection molding, the plastic filling in the cavity is limited by the frozen layer due to the rapid cooling of the hot melt when it comes into contact with the surface of the cavity at a lower temperature. This problem is more serious with composite materials, which have a higher viscosity than pure materials. Moreover, this issue is also more serious with composite materials that have a higher weight percentage of glass filer. In this article, a pre-heating step with the internal gas heating method was used to heat the cavity surface to a high temperature before the filling step to reduce the frozen layer and to improve the filling ability of the composite material (polyamide 6 + 30% glass fiber) in the micro-injection molding process. To heat the cavity surface, an internal gas-assisted mold temperature control (In-GMTC) system was used with a pulsed cooling system. We assessed different mold insert thicknesses (t) and gaps between the gas gate and the heating surface (G) to achieve rapid mold surface temperature control. The heating process was observed using an infrared camera, and the temperature distribution and the heating rate were analyzed. Thereafter, along with the local temperature control, the In-GMTC was used for the micro-injection molding cycle. The results show that, with a gas temperature of 300 °C and a gas gap of 3.5 mm, the heating rate reached 8.6 °C/s. The In-GMTC was also applied to the micro-injection molding process with a part thickness of 0.2 mm. It was shown that the melt flow length had to reach 24 mm to fill the cavity completely. The results show that the filling ability of the composite material increased from 65.4% to 100% with local heating at the melt inlet area when the gas temperature rose from 200 to 400 °C with a 20 s heating cycle.
Journal Article
Active temperature control method based on time grating principle for the feed system of precision machine tool and its application
Variations in running conditions cause fluctuation in the temperature field of precision machine tools, which inevitably results in thermal errors. To meet the demands of dynamic and time-varying temperature control capability, an active temperature control (ATC) method based on time grating principle is proposed, and the ATC system is developed. The ATC system contains main-loop and sub-loops. The oil target temperature in the sub-loop is determined according to the running parameters and the matching principle of the generalized heat generation–dissipation power. In accordance with the time grating principle, dynamic and differential oil temperature control of each sub-loop is achieved via the inlet time regulation of high-temperature (H-t) or low-temperature (L-t) oil in the main-loop. The main-loop H-t and L-t oil target temperatures are determined by the target range of the sub-loop temperature. The dynamic distribution of the refrigeration capacity and proportional heating mode is adopted to control the temperatures of H-t and L-t oil. By focusing on the feed system of precision machine tool, we carry out both dynamic simulation study and verification experiments, and the results show that the ATC method and system can effectively regulate the temperature field of precision machine tools, thus improving the thermal accuracy of the precision machine tool.
Journal Article
Flexible and elastic thermal regulator for multimode intelligent temperature control
As nonlinear thermal devices, thermal regulators can intelligently respond to temperature and control heat flow through changes in heat transfer capacities, which allows them to reduce energy consumption without external intervention. However, current thermal regulators generally based on high‐quality crystalline‐structure transitions are intrinsically rigid, which may cause structural damage and functional failure under mechanical strain; moreover, they are difficult to integrate into emerging soft electronic platforms. In this study, we develop a flexible, elastic thermal regulator based on the reversible thermally induced deformation of a liquid crystal elastomer/liquid metal (LCE/LM) composite foam. By adjusting the crosslinking densities, the LCE foam exhibits a high actuation strain of 121% with flexibility below the nematic–isotropic phase transition temperature (TNI) and hyperelasticity above TNI. The incorporation of LM results in a high thermal resistance switching ratio of 3.8 over a wide working temperature window of 60°C with good cycling stability. This feature originates from the synergistic effect of fragmentation and recombination of the internal LM network and lengthening and shortening of the bond line thickness. Furthermore, we fabricate a “grid window” utilizing photic‐thermal integrated thermal control, achieving a superior heat supply of 13.7°C at a light intensity of 180 mW/cm2 and a thermal protection of 43.4°C at 1200 mW/cm2. The proposed method meets the mechanical softness requirements of thermal regulator materials with multimode intelligent temperature control. A soft thermal regulator is developed based on the thermally reversible deformation of a liquid crystal elastomer/liquid metal composite foam, which achieves a high thermal resistance switching ratio of 3.8 over a wide working temperature window of approximately 60°C with flexibility below TNI and hyperelasticity above TNI, exhibiting multimode intelligent temperature control.
Journal Article
A new intelligent control strategy for CSTH temperature regulation based on the starfish optimization algorithm
Temperature regulation in nonlinear and highly dynamic processes such as the continuous stirred-tank heater (CSTH) is a challenging task due to the inherent system nonlinearities and disturbances. This study proposes a novel metaheuristic-driven control strategy, combining the two degrees of freedom-PID acceleration (2DOF-PIDA) controller with the recently developed starfish optimization algorithm (SFOA) for temperature control of the CSTH process. The 2DOF-PIDA controller enhances system performance by decoupling setpoint tracking and disturbance rejection, while the SFOA ensures optimal tuning of controller parameters by leveraging its powerful exploration and exploitation capabilities. Simulation results validate the effectiveness of the proposed approach, demonstrating improved tracking accuracy, disturbance rejection, and robustness compared to conventional methods. The combination of 2DOF-PIDA and SFOA provides a flexible and efficient solution for controlling highly nonlinear systems, with significant implications for industrial temperature regulation applications.
Journal Article
AI powered blockchain framework for predictive temperature control in smart homes using wireless sensor networks and time shifted analysis
In the context of smart homes, efficiently managing temperature control while optimizing energy consumption and ensuring data security remains a significant challenge. Traditional thermostat-based systems lack predictive capabilities, and energy consumption often spikes during peak hours, leading to inefficiency. Additionally, the security of sensitive data in smart home environments is a growing concern. This paper presents a novel AI-powered blockchain framework for predictive temperature control in smart homes, leveraging wireless sensor networks (WSNs) and time-shifted analysis. The framework integrates machine learning (ML) algorithms for predictive temperature management, blockchain technology for secure data handling, and edge computing for real-time data processing, resulting in a highly efficient and secure system. Key innovations include the dynamic detection of heating and cooling events, predictive scheduling based on historical data, and blockchain-based decentralized energy trading. Performance evaluation demonstrates that the system accurately detects radiator heat-on events with a 28.5% success rate, while radiator cooling event detection achieves 37.3% accuracy. Scheduled heat-on events were triggered with 68.4% reliability, and the system’s machine learning component successfully reduced energy consumption by 15.8% compared to traditional thermostat controls, by adjusting heating based on predictive analysis. Additionally, the time-shifted data processing reduces peak-time computational load by 22%, contributing to overall energy efficiency and system scalability. The integration of blockchain ensures tamper-proof data security, eliminating unauthorized data access, and improving trust in smart home environments. These results illustrate the potential of combining AI, blockchain, and WSNs to create a robust, energy-efficient, and secure smart home temperature control system, offering significant improvements over traditional solutions.
Journal Article
Machine learning-based optimal temperature management model for safety and quality control of perishable food supply chain
The management of a food supply chain is difficult and complex because of the product's short shelf-life, time-sensitivity, and perishable nature which must be carefully considered to minimize food waste. Temperature-controlled perishable food supply chain provides the highly crucial facilities necessary to maintain the quality and safety of the product. The storage temperature is the most vital factor in maintaining both the quality and shelf-life of a perishable food. Adequate storage temperature control ensures that perishable foods are transported to the end-users in good quality and safe to consume. This paper presents perishable food storage temperature control through mathematical optimal control model where the storage temperature is regarded as the control variable and the deterioration of the perishable food’s quality follows the first-order reaction. The optimal storage temperature for a single perishable food is determined by applying the Pontryagin's maximum principle to solve the optimal control model problem. For multi-temperature commodities supply chain, an unsupervised machine learning (ML) method, called
k
-means clustering technique is used to determine the temperature clusters for a range of perishables. Based on descriptive analysis, it is observed that the
k
-means clustering technique is effective in identifying the best suitable storage temperature clusters for quality control of multi-commodity supply chain.
Journal Article
External Gas-Assisted Mold Temperature Control Improves Weld Line Quality in the Injection Molding Process
Simulations and experiments were conducted with gas temperatures of 200–400 °C to investigate the impact of external gas-assisted mold temperature control (Ex-GMTC) on the quality of weld line of molding products. In the heating step, the heating rate was 19.6 °C/s from 30 to 128.5 °C in the first 5 s in a 400 °C gas environment. When applied to heating the weld line area of an injection mold, Ex-GMTC improved the appearance of the weld line when the cavity temperature was preheated to 150 °C. For the tensile strength test, a melt flow simulation comparing the packing pressure of different mesh thicknesses revealed that Ex-GMTC helped maintain a high pressure in the weld line area in different packing periods. This was verified by an experiment where Ex-GMTC was applied with 400 °C gas to change the mesh area temperature. The result indicated that an increase in the weld line area temperature from 60 to 180 °C improves the tensile strength of all mesh thicknesses, which was more pronounced with thinner parts, especially at 0.4 mm. The simulations revealed that high temperature is concentrated in the weld line area of the cavity surface, thus reducing the energy wasted during heating.
Journal Article