Temperature Control Strategy Research Articles

Temperature Control and Crack Prevention Strategies in the Construction of Large Volume Concrete

This paper delves into the intricacies of temperature control and crack prevention in the construction of large volume concrete structures, emphasizing their criticality for maintaining structural integrity and longevity. The primary challenges arise from the exothermic hydration of cement, leading to substantial internal temperature variations and consequent thermal stresses. To address these, the paper explores a comprehensive approach starting with the selection of raw materials and mix design. It advocates for the use of low-heat cement, supplementary cementitious materials like fly ash and slag, and strategic aggregate selection to mitigate heat generation. The paper further discusses the importance of optimizing the water-cement ratio and incorporating admixtures to enhance workability without compromising strength.During the construction processes, the paper highlights the significance of scheduling placements to avoid peak heat, using chilled water and ice in the mix, and implementing proper curing practices to manage temperature gradients effectively. It also underscores the role of temperature monitoring and hydration control through the use of slow-release admixtures. In the context of crack prevention, the paper outlines proactive measures such as material selection, mix design optimization, and construction practices that help preempt the formation of cracks. For existing cracks, it discusses treatment techniques like epoxy injection and the application of fiber-reinforced polymers to restore structural integrity.

Temperature Control Strategy for Hydrogen Fuel Cell Based on IPSO-Fuzzy-PID

Hydrogen fuel cell water-thermal management systems suffer from slow response time, system vibration, and large temperature fluctuations of load current changes. In this paper, Logistic chaotic mapping, adaptively adjusted inertia weight and asymmetric learning factors are integrated to enhance the particle swarm optimization (PSO) algorithm and combine it with fuzzy control to propose an innovative improved particle swarm optimization-Fuzzy control strategy. The use of chaotic mapping to initialize the particle population effectively enhances the variety within the population, which subsequently improves the ability to search globally and prevents the algorithm from converging to a local optimum solution prematurely; by improving the parameters of learning coefficients and inertia weight, the global and local search abilities are balanced at different stages of the algorithm, so as to strengthen the algorithm’s convergence certainty while reducing the dependency on expert experience in fuzzy control. In this article, a fuel cell experimental platform is constructed to confirm the validity and efficiency of the recommended strategy, and the analysis reveals that the improved particle swarm optimization (IPSO) algorithm demonstrates better convergence performance than the standard PSO algorithm. The IPSO-Fuzzy-PID management approach is capable of providing a swift response and significantly diminishing the overshoot in the system’s performance, to maintain the system’s safe and stable execution.

A Deeper Understanding of Climate Variability Improves Mitigation Efforts, Climate Services, Food Security, and Development Initiatives in Sub-Saharan Africa

This research utilized the bagging machine learning algorithm along with the Thornthwaite moisture index (TMI) to enhance the understanding of climate variability and change, with the objective of identifying the most efficient climate service pathways in Sub-Saharan Africa (SSA). Monthly datasets at a 0.5° resolution (1960–2020) were collected and analyzed using R 4.2.2 software and spreadsheets. The results indicate significant changes in climatic conditions in Sudan, with aridity escalation at a rate of 0.37% per year. The bagging algorithm illustrated that actual water use was mainly influenced by rainfall and runoff management, showing an inverse relationship with increasing air temperatures. Consequently, sustainable strategies focusing on runoff and temperature control, such as rainwater harvesting, agroforestry and plant breeding were identified as the most effective climate services to mitigate and adapt to climate variability in SSA. The findings suggest that runoff management (e.g., rainwater harvesting) could potentially offset up to 22% of the adverse impacts of climate variability, while temperature control strategies (e.g., agroforestry) could account for the remaining 78%. Without these interventions, climate variability will continue to pose serious challenges to food security, livelihood generations, and regional stability. The research calls for further in-depth studies on the attributions of climate variability using finer datasets.

Dynamic simulation of wind-powered alkaline water electrolysis system for hydrogen production

Alkaline water electrolysis (AWE) is a mature and cost-effective technology, especially suited for large-scale deployment, yet faces challenges in adapting to the dynamic nature of renewable energy sources. Evaluating AWE's adaptability to fluctuating renewable energy inputs is crucial. This study introduces a dynamic model to assess the influence of wind energy on a 250 kW industrial-scale AWE system for hydrogen production. This paper pioneers the utilization of Aspen Plus Dynamics for dynamic modeling, offering a comprehensive approach that incorporates all vital components and controllers of the balance of plant, such as gas-liquid separator, heat exchangers, deionized water supply, pumps, and the cooling loop. This methodology allows comprehensive simulation at the system level, revealing the real dynamic characteristics of the system under fluctuating wind energy conditions. Due to the absence of a dedicated module for AWE in Aspen Plus Dynamics, an integrated dynamic operation unit for the electrolyzer is constructed using Aspen Custom Modeler. The study analyzes the dynamic characteristics of the AWE system, specifically focusing on temperature, voltage, and liquid level. The study compares two temperature control strategies, before-stack and after-stack, with the refined after-stack method effectively addressing over-temperature issues and improving system energy efficiency by 1.44%.

Research on the psychology, physiology and cognitive ability of the work efficiency of special vehicle members

The combat effectiveness of special vehicles is related to the comprehensive national strength of the country. In addition to the performance of the vehicle itself, the combat capability of the crew is also crucial, and the work efficiency will affect the combat capability of the crew.This paper summarizes the effects of thermal and noise environments on crew efficiency and the evaluation methods of work efficiency using special vehicles as experimental platforms. A total of 12 environmental conditions were designed, the experimental temperature covers 25 °C, 29 °C, 33 °C, 37 °C, noise covers 50 dB, 70 dB, 85 dB. The effects of temperature and noise on the physiological, psychological and cognitive abilities of the occupants were quantitatively analyzed through human ergonomics simulation experiments. The results show that the noise has a significant effect on the occupant's work efficiency in a low-temperature environment, while the temperature becomes the dominant influence factor in a high-temperature environment. When operating temperatures reached 29 °C, occupant combat performance was optimal, whereas at 33 °C and above, the efficiency decreased significantly. This research provides a theoretical basis for optimizing the environment of special vehicle cabins, and offers a scientific temperature control scheme to improve the crew's efficiency.

Cooperative control strategy of variable evaporation temperature and variable superheat degree for a VRF system to improve temperature stability in multiple rooms

The energy consumption of variable refrigerant flow (VRF) systems can be reduced by adopting the variable evaporation temperature and constant superheat degree (VECS) control strategy instead of constant evaporation temperature and constant superheat degree (CECS) control strategy. However, the constant superheat degree control strategy may weaken the adjustment ability of cooling capacity of indoor units, and result in obvious room temperature fluctuations. In order to decrease room temperature fluctuations and reduce energy consumption simultaneously, a cooperative control strategy of variable evaporation temperature and variable superheat degree (VEVS) is proposed, i.e. one indoor unit is chosen to be controlled by variable evaporation temperature and the rest of the indoor units are controlled by variable superheat degrees. In this control strategy, the target value of evaporation temperature is the lowest value among the upper limits of the evaporation temperatures of all indoor units, and the target values of the superheat degrees of indoor units are predicted according to the cooling demands of rooms. Comparative experiments on room temperature fluctuation and energy consumption among the control strategies of CECS, VECS and VEVS are done. It is shown that both the control strategies of VECS and VEVS achieve smaller room temperature fluctuation and lower energy consumption than those of CECS; compared with the VECS control strategy, the average room temperature fluctuation of the VEVS control strategy is decreased from 1.1 °C to 0.5 °C due to variable superheat degree, and the energy consumption of the VEVS control strategy is reduced by 4.4 %.

What’s the optimal temperature control strategy in patients receiving ECPR after cardiac arrest? A network meta-analysis

BackgroundThe optimal temperature control strategy in extracorporeal cardiopulmonary resuscitation (ECPR) patients is unknown, and several trials have reported conflicting results regarding its effectiveness. We aimed to conduct a systemic review and network meta-analysis (NMA) to assess the efficacy of temperature control in ECPR patients. MethodsDatabase searching of studies reporting data on temperature control strategy during ECPR in MEDLINE, EMBASE, Scopus, and Cochrane Library was performed. Primary outcomes were overall survival and neurological outcome. Pairwise meta-analysis and Bayesian NMA were performed on studies comparing outcomes among groups of moderate hypothermia (32–34 °C), mild hypothermia (34.1–36 °C) and normothermia (36.1–37.5 °C). ResultsNineteen retrospective studies were included (5622 patients). Statistically significant differences in good neurological outcome were observed in the direct comparison of moderate hypothermia and mild hypothermia (OR, 1.73; 95 % CI: 1.07–2.81) as well as moderate hypothermia and normothermia (OR, 2.14; 95 % CI: 1.24–3.67), but no significant differences were found in the NMA result. There was no difference in either survival outcome or the incidence of bleeding complications among any groups according to direct or indirect analysis. ConclusionsDirect evidence suggests that moderate hypothermia might be associated with improved neurological outcomes in ECPR patients. However, no significant differences in survival outcomes were observed in either the direct or NMA results. Given the lower level of the evidence, interpretation should be made with caution.

Research on temperature control in additive manufacturing of thermosetting carbon fiber composites using DMC-IEPO-PID algorithm

Abstract This study presents a novel temperature control strategy for Additive Manufacturing (AM) of thermosetting carbon fiber composites, integrating Dynamic Matrix Control (DMC), Improved Eagle Perching Optimization (IEPO), and a Proportional-Integral-Derivative (PID) controller, termed the DMC-IEPO-PID algorithm. This approach addresses traditional PID controller limitations like sluggish response, overshoot, and poor adaptability in complex manufacturing. By combining the simplicity of PID, adaptability of IEPO, and predictive accuracy of DMC, the algorithm improves temperature regulation in AM. Simulations and experiments at 250°C, 300°C, and 350°C showed superior performance in reducing fluctuations, stabilization time, and improving accuracy. The findings confirm the DMC-IEPO-PID’s effectiveness in handling nonlinearities and time-varying characteristics, optimizing AM processes for thermosetting composites.

Enhanced d-pantothenic acid biosynthesis by plasmid-free Escherichia coli through sodium pyruvate addition combined with glucose and temperature control strategy.

d-pantothenic acid (d-PA) is an important vitamin widely used in the feed, pharmaceutical, and food industries. This study aims to enhance the d-PA production of a recombinant Escherichia coli without plasmid and inducer induction. The fermentation medium in shake flask was optimized, resulting in a 39.50% increased d-PA titer (3.32g l-1). Subsequently, the fed-batch fermentation in a 5-l fermenter was specifically investigated. First, a two-stage temperature control strategy led to a d-PA titer of 52.09g l-1. Additionally, a two-stage glucose feeding was proposed and d-PA titer was increased to 65.29g l-1. It was also found that an appropriate amount of sodium pyruvate was beneficial to cell growth and d-PA synthesis. Finally, a two-stage glucose feeding combined with sodium pyruvate addition resulted in a substantially improved d-PA production with a titer of 72.90g l-1. The d-PA synthesis was significantly improved through the fermentation process established in this work, i.e. sodium pyruvate addition combined with the temperature and glucose control strategy. The results of this study could provide significant reference for the industrial fermentation production of d-PA.

The Influence of Temperature Disturbance on Space Inertial Sensors.

The TianQin program is an independently proposed space-borne detection initiative from China. The inertial sensor, as a crucial component, is susceptible to disturbances from temperature fluctuations, the impact of which on acceleration measurements remains elusive. Therefore, a comprehensive analysis on the influence of temperature disturbance is necessary to avoid errors in acceleration measurement. In this study, we proposed a complete scheme for calculating the level of acceleration noise. Based on the traditional temperature control scheme of using a heat pipe, we developed a systematic heat transfer simulation model to obtain the temperature signals. These signals can then be converted into the frequency domain and used to calculate the acceleration noise level within the target bandwidth. Our results indicate that, with a temperature control of 0.13 K/Hz1/2@1 mHz, the largest contributions to acceleration noise come from the outgassing effect, radiometer effect, and radiative pressure effect, in descending order. The total noise peak is 3.6×10-12 m/(s2⋅Hz1/2) at 1 mHz, which is more than three orders of magnitude higher than the TianQin target of 10-15 m/(s2⋅Hz1/2). This study provides new avenues for evaluating measurement errors and solutions for the TianQin program.

Lyapunov-derived fuzzy temperature control for thermoelectric cooling system using dynamic updating law

In this paper, an intelligent temperature control strategy is proposed for thermoelectric cooling systems. The Lyapunov-based control method allows a dynamic updating law to be employed in the fuzzy logic system to improve the system performance in the presence of unmodeled dynamics. A new smooth function is also integrated into the control loop to limit input voltage, effectively addressing potential energy waste issue. Furthermore, the controller design challenges posed by even-power input are resolved using the adaptive fuzzy control method and Lagrange’s mean value theorem. Performance analysis indicates that the control function and state signals of the refrigeration system are bounded under our proposed method. Compared with the traditional intelligent control strategy, we only need to design a dynamic update law, which effectively reduces the complexity of the algorithm and is favorable for implementation. Finally, simulation and experimental results demonstrate the effectiveness of the method proposed in this paper. Compared to the traditional PID method, our control method reduces the maximum error by 29.4% and the setting time by 35.7% in the experiment.

Internal temperature prediction and control strategy design of anode-supported solid oxide fuel cell for hot start-up process

Anode-supported solid oxide fuel cell (SOFC) has a high energy efficiency while suffering from a poor transient performance such as start-up. In this study, a model-based design method is proposed to develop a suitable strategy for the rapid hot start-up of anode-supported SOFC (AS-SOFC). First, a mathematical model is established for a 25-kW SOFC system and the internal temperature is predicted. Subsequently, three different strategies are compared during hot start-up process. The results indicate that the positive-electrolyte-negative (PEN) temperature variation magnitude is 50 K and the response time is 1300 s when the hydrogen and the air flow rates are fixed for the afterburner and the cathode. If a PID controller is employed to regulate the flow rate of H2 to the afterburner, the PEN temperature variation magnitude decreases to 16 K with a shorter response time of 158 s. When increasing the air flow rate synchronously, the PEN temperature variation magnitude is merely 8 K, reduced by 84 % and 50 % compared with the previous strategies. Additionally, the gas temperature exiting from the afterburner declines significantly for the third control strategy. Thus, the lifetime and reliability of AS-SOFC is enhanced. The results provide a reference for the SOFC systems control such as domestic combined heat and power (CHP) and mobile applications.

Experimental investigation on heat transfer characteristics and thermal optimization methods of the storage-type downhole visual tool

The storage-type downhole visual tool is a crucial device for monitoring the technical condition of the downhole tubing string. However, prolonged exposure to the high-temperature downhole environment leads to an increase in the internal temperature of the tool, causing instability in the operation of electronic devices. To address this issue, a thermal optimization scheme for the tool’s internal cavity has been proposed, combining a distributed lens structure with vacuum phase-change composite materials. An environmental-tool heat transfer model has been established to study the temperature rise characteristics during the entry stage (ES) and the operation stage (OS). Comparative analysis shows that this optimization scheme can effectively reduce the internal cavity temperature by 32.5 °C, a decrease of 41.7 %, during the entry stage. During the operation stage, the heat absorption by the composite phase-change material results in a 6.3 °C drop in the internal cavity temperature and a 30.1 °C reduction in the circuit board temperature. The model was validated through the high-temperature oil bath experiment, with the calculation results showing errors below 8 % compared to experimental results. Implementing this thermal optimization scheme in case wells ensures the tool’s continuous and stable operation for 6 h, with the internal cavity temperature maintained below 100 °C and the circuit board temperature kept within 140 °C. This significantly enhances the safety and stability of downhole electronic devices and provides guidance for the selection of temperature control strategies for downhole tools in high-temperature environments.

Research on Temperature Control of Mass Concrete for Multi-Tower Cable-Stayed Bridge Cap during Construction

In the construction process of mass concrete structures, the large temperature gradient due to exothermic hydration makes the mass concrete highly susceptible to cracking. This paper carried out research on temperature control methods of mass concrete for the purpose of ensuring construction quality based on the construction of Fengyi cable-stayed bridge caps. Firstly, the temperature and stress change rule in the concrete pouring process of the caps was analyzed though the finite element method (FEM). Then, targeted-oriented comprehensive temperature control schemes were formulated according to the structural characteristics and construction environment of the cap, including the optimization of the material ratio, the arrangement of crack-resistant reinforcing steel, the design of a water pipe cooling scheme and reasonable maintenance. Finally, the whole bridge cap construction process using the optimized water pipe cooling solution was monitored, and the temperature gap between inside and outside the concrete satisfied the specification requirements rigorously. In the concrete demolding session, the concrete surface was smooth and no cracks were found, which indicates the temperature control scheme is reasonable and effective. The research results have reference significance for the pouring and temperature control of mass concrete for bridge caps.

A Comprehensive Flow–Mass–Thermal–Electrochemical Coupling Model for a VRFB Stack and Its Application in a Stack Temperature Control Strategy

In this work, a comprehensive multi-physics electrochemical hybrid stack model is developed for a vanadium redox flow battery (VRFB) stack considering electrolyte flow, mass transport, electrochemical reactions, shunt currents, and as heat generation and transfer simultaneously. Compared with other VRFB stack models, this model is more comprehensive in considering the influence of multiple factors. Based on the established model, the electrolyte flow rate distribution across cells in the stack is investigated. The distribution and variation in shunt currents, single-cell current and single-cell voltage are analyzed. The distribution and variation in temperature and heat generation and heat transfer are also researched. It can be found that the VRFB stack temperature will exceed 40 °C when operating at 60 A and 100 mA cm−2 at an ambient temperature of 30 °C, which will lead to electrolyte ion precipitation, affecting the performance and safety of the battery. To control the stack temperature below 40 °C, a new tank cooling control strategy is proposed, and the suitable starting cooling point and the controlled temperature are specified. Compared with the common room cooling strategy, the new tank cooling strategy reduces energy consumption by 27.18% during 20 charge–discharge cycles.

Design of Oil Mist and Volatile-Organic-Compound Treatment Equipment in the Manufacturing Plant

To effectively confront the acute challenge of global warming, at the present stage, the Chinese government has designated carbon reduction as the core objective to accomplish the coordinated control of greenhouse gas and pollutant emissions. As China is a major manufacturing country, with the continuous improvement of air emission standards, it is particularly necessary to carry out the design of more efficient volatile organic pollutant emission devices. This study takes a treatment system with a waste gas ventilation volume of 6 × 104 m3·h−1 as an example, adopts the end treatment approach of adsorption and catalytic combustion coupling, and designs a purification device composed of multistage oil-mist recovery, electrostatic adsorption, dry filtration, activated-carbon adsorption and desorption, catalytic combustion, etc. It also employs the fuzzy proportional-integral-derivative fine temperature control algorithm, and the temperature overshoot was decreased by 85%. The average emission concentration of volatile organic compounds at the equipment outlet is 6.56 mg·m−3, and the average removal rate is 93.99%, far surpassing the national emission standards. The device operates efficiently and stably, confirming that the end-coupled treatment system based on the adaptive fuzzy proportional-integral-derivative temperature control strategy can effectively handle volatile organic compounds with oil mist and holds significant promotion and research value.

Modeling the Effects of Temperature in Enzymatic Biodiesel Synthesis of Jatropha Oil: An Optimal Control Approach.

Biodiesel, an alternative to diesel, is produced through the enzymatic transesterification of vegetable oil or animal fats. Enzymatic transesterification of oil is gaining more importance, as this method possesses no such disadvantages that are associated with the chemical process. Temperature is the most important factor in enzymatic transesterification for biodiesel synthesis. In this study, a mathematical model is developed to understand the effects of temperature on the enzymatic transesterification of Jatropha curcas oil. Reaction rates are expressed as a function of temperature using an appropriate function, and the effects of temperature on the overall enzymatic system are investigated using the mathematical model. A suitable temperature is determined using the mathematical model, keeping the other reaction conditions unchanged that gives maximum yield. Furthermore, an optimal control problem (OCP) is formulated to identify the temperature control strategy that maximizes the biodiesel yield while minimizing production costs. Simulated outcomes obtained from the mathematical model are analogized with the experimental results to make them acceptable. The optimal profile of temperature is determined from the developed OCP, which maximizes the biodiesel yield.

Optimization for the temperature range of radiator for preventing draught risk of cold window

High surface temperature of radiator can provide thermal plume with enough momentum intensity and thus counteracts the downdraft caused by window. Meanwhile, it is necessary to avoid causing indoor temperature to exceed upper limit of thermal comfort zone. In this paper, influence of heat transfer coefficients of window and exterior wall, outdoor temperature, and average surface temperature of radiator on operative temperature (Top) and temperature difference between indoor air and window (Td) was investigated. Based on response surface method, single factor and interaction effects for the four influencing factors on Top and Td were analyzed. A framework optimizing average surface temperature of radiator for preventing draught risk of window was established. When the heat transfer coefficient of window was around 1.4 W/m2·°C and satisfied related energy-conservation standard, cold draught could be eliminated without causing indoor environment overheating. Based on the optimized temperature range, the supply water temperature was controlled, and seasonal performance using the variable temperature strategy was investigated based on TRNSYS simulation. With the variable water temperature control strategy, the output hourly indoor air temperature was within the comfortable range. In the whole heating season, hours that did not meet cold draught requirement occupied 77.22 %, as the heat transfer coefficients of window dis-satisfied the energy-saving design standard. As meeting the design standard, the proportion decreased to 12.97 %. Utilizing the optimized temperature interval can prevent discomfort caused by cold draught to the greatest extent. This study is conducive to improving thermal environment with the convective–heating system and may lead to the reduction of energy consumption for heating.

The impact of induction heating time on the temperature distribution of high-temperature alloy discs

Abstract The induction heating time is directly related to the temperature uniformity of high-temperature alloy disc components. Therefore, investigating the influence of induction heating time on the temperature field distribution of disc components provides guidance for temperature control strategies in the forming process. In this study, the finite element analysis software COMSOL Multiphysics was employed to examine the impact of induction heating time on the radial and thickness-wise temperature fields of GH4169 discs. The results indicate that the heating time affects the thickness of the heating layer, and appropriately extending the heating time can improve the temperature uniformity in the thickness direction, achieving a temperature difference of ±5 °C in the disc component thickness direction under certain conditions. When the heating time ranges from 1229 s to 1239 s, the temperature in the R=30 mm to R=100 mm range reaches the suitable forging temperature.

Distributed Cooperative Dispatch Method of Distribution Network with District Heat Network and Battery Energy Storage System Considering Flexible Regulation Capability

Flexible resources, including district heat networks (DHN) and battery energy storage systems (BESS), can provide flexible regulation capability for distribution networks (DN), thereby increasing the absorption capacity for renewable energy. In order to improve the operation economy of DN and ensure the information privacy of different operators, a distributed cooperative dispatch method of DN with DHN and BESS considering flexible regulation capability is proposed. First, a distributed cooperative dispatch framework of DN-DHN-BESS is constructed. Then, an optimal dispatch model of DHN under constant flow-variable temperature control strategy is established in order to utilize the heat storage capacity to provide flexible regulation capability for DN. Next, the optimal dispatch models of BESS and DN are established with the objective of minimizing the operation cost, respectively. Finally, a solution method based on the alternating direction multiplier method of distributed cooperative dispatch for DN-DHN-BESS is proposed. Case studies are performed on a system consisting of a 33-node DN and a 44-node DHN, and simulation results demonstrate that the proposed method differs from the centralized dispatch method by only 0.52% in the total system cost, and the proposed method reduces the total system cost by 34.5% compared to that of the independent dispatch method.