Optimizing heat source distribution in sintering molds: Integrating response surface model with sequential quadratic programming

The sintering mold imposes strict requirements for temperature uniformity. The mold geometric parameters and the power configuration of heating elements exert substantial influence. In this paper, we introduce an optimization approach that combines response surface models with the sequential quadratic programming algorithm to optimize the geometric parameters and heating power configuration of a heating system for sintering mold. The response surface models of the maximum temperature difference, maximum temperature, and minimum temperature of the sintering area are constructed utilizing the central composite design method. The model's reliability is rigorously confirmed through variance analysis, residual analysis, and generalization capability validation. The models demonstrate remarkable predictive accuracy within the design space. A nonlinear constrained optimization model is established based on the response surface models, and the optimal parameters are obtained after 9 iterations using the sequential quadratic programming algorithm. Under the optimal parameters, the maximum temperature difference is maintained at less than 5 °C, confirming exceptional temperature uniformity. We conduct parameter analysis based on standardized effects to determine the main influencing factors of temperature uniformity, revealing that the distance between adjacent heating rods and the power density of the inner heating rods exert significant influence. Enhanced temperature uniformity can be achieved by adopting a larger distance between heating rods and configuring the power density of the heating rods to a relatively modest level. This work introduces a practical approach to optimize the heating systems for sintering molds, with potential applications in various industrial mold optimization.

Measurement and Control of an Incubator Temperature by Using Conventional Methods and Fiber Bragg Grating (FBG) Based Temperature Sensors

Incubator is a medical device that provide a climatic environment for a newborn and a preterm infant. In the incubator environment, especially, the temperature significantly increases the survival rate of infants. In this study, the incubator air temperature, temperature uniformity and infant skin temperature were measured and controlled with conventional methods and FBG based temperature sensors, and their results and related literature results were compared among them. To this end, in addition to classical sensors, six FBG sensors were used during the measurements, and very close results were obtained between them (R² = 0.9989). In addition, since real time monitoring of the FBG bands were ensured with a user-friendly interface, measurement processes have been made more ergonomic. In this way, the insulation required for the measurements is also provided perfectly. Measurement errors caused by conventional sensors' properties, which are different for each of them, change over/with time, and also change with different values, have been minimized by using this method. Moreover, in case of increasing the number of sensors for multi-point, continuous and real time temperature measurement in conventional methods, some of the problems such as monitoring of these sensors, obstructing or changing the air flow due to the confusions of these sensors and their cables in the incubator cabinet, and following these, control errors caused by these reasons, and difficulties that may be happened during the infant care and resuscitation procedures have been eliminated. Thus, thermoneutrality in closed incubators were also able to validated and assessed fast and more accurately for preterm and neonates.