Primitive controllers used in the early version for HVAC systems, like the on-off (Bang-Bang) controller, are inefficient, inaccurate, unstable, and suffer from highlevel mechanical wear. On the other hand, other controllers like PI and cascade controllers, overcome these disadvantages but when an offset response (inaccurate response) occurs, power consumption will increase. In order to acquire better performance in the central air-conditioning system, PIP-cascade control is investigated in this paper and compared to the traditional PI and PID, in simulation of experimental data. The output of the system is predicted through disturbances. Based on the mathematical model of air-conditioning space, the simulations in this paper have found that the PIP-cascade controller has the capability of self-adapting to system changes and results in faster response and better performance.
There are successful and less successful maintenance systems (MS). As a dynamic category, the success of the maintenance function must be taken into consideration both for the present day and the future. This is the reason why it is necessary to continuously evaluate, improve and redesign MS. Business process modelling is a good methodology for this purpose. A business process model basically encompasses a formal description of the concept of the system, evaluation methods and process improvement techniques. This paper presents a concept of MS evaluation by using statistical process control in connection with performance indicators and MS improvement by modelling and simulation system. The maintenance model is used for simulation and experimentation. The simulation helps to visualise, understand, analyse and improve processes. The proposed concept is extendable and could be applied in different MS.
The mathematical modeling of ion channel kinetics is an important tool for studying the electrophysiological mechanisms of the nerves, heart, or cancer, from a single cell to an organ. Common approaches use either a Hodgkin–Huxley (HH) or a hidden Markov model (HMM) description, depending on the level of detail of the functionality and structural changes of the underlying channel gating, and taking into account the computational effort for model simulations. Here, we introduce for the first time a novel system theory-based approach for ion channel modeling based on the concept of transfer function characterization, without a priori knowledge of the biological system, using patch clamp measurements. Using the shaker-related voltage-gated potassium channel Kv1.1 (KCNA1) as an example, we compare the established approaches, HH and HMM, with the system theory-based concept in terms of model accuracy, computational effort, the degree of electrophysiological interpretability, and methodological limitations. This highly data-driven modeling concept offers a new opportunity for the phenomenological kinetic modeling of ion channels, exhibiting exceptional accuracy and computational efficiency compared to the conventional methods. The method has a high potential to further improve the quality and computational performance of complex cell and organ model simulations, and could provide a valuable new tool in the field of next-generation in silico electrophysiology.
This paper highlights the changes of polyethylene behaviour during various loading rates as well as the influence of test temperature on the material characteristics. Passive infrared thermography method and a high speed infrared camera were used to observe the temperature changes of the sample surface during the tests. The experimental program was carried out on samples taken from PE80 polyethylene gas pipes with simulated imperfections with bilateral V-notch, U-notch, and central hole. Samples have been tensile tested and the results are correlated with the temperature distribution of the samples surface.
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