This study aims to design a novel air cleaning facility which conforms to the current situation in China, and moreover can satisfy our demand on air purification under the condition of poor air quality, as well as discuss the development means of a prototype product. Air conditions in the operating room of a hospital were measured as the research subject of this study. First, a suitable turbulence model and boundary conditions were selected and computational fluid dynamics (CFD) software was used to simulate indoor air distribution. The analysis and comparison of the simulation results suggested that increasing the area of air supply outlets and the number of return air inlets would not only increase the area of unidirectional flow region in main flow region, but also avoid an indoor vortex and turbulivity of the operating area. Based on the summary of heat and humidity management methods, the system operation mode and relevant parameter technologies as well as the characteristics of the thermal-humidity load of the operating room were analyzed and compiled. According to the load value and parameters of indoor design obtained after our calculations, the airflow distribution of purifying the air-conditioning system in a clean operating room was designed and checked. The research results suggested that the application of a secondary return air system in the summer could reduce energy consumption and be consistent with the concept of primary humidity control. This study analyzed the feasibility and energy conservation properties of cleaning air-conditioning technology in operating rooms, proposed some solutions to the problem, and performed a feasible simulation, which provides a reference for practical engineering.
In the paper, a procedure for precise and expedited design optimization of unequal power split patch couplers is proposed. Our methodology aims at identifying the coupler dimensions that correspond to the circuit operating at the requested frequency and featuring a required power split. At the same time, the design process is supposed to be computationally efficient. The proposed methodology involves two types of auxiliary models (surrogates): an inverse one, constructed from a set of reference designs optimized for particular power split values, and a forward one which represents the circuit S-parameter gradients as a function of the power split ratio. The inverse model directly yields the values of geometry parameters of the coupler for any required power split, whereas the forward model is used for a post-scaling correction of the circuit characteristics. For the sake of illustration, a 10-GHz circular sector patch coupler is considered. The power split ratio of the structure is re-designed within a wide range of ��6 dB to 0 dB. As demonstrated, precise scaling (with the power split error smaller than 0.02 dB and the operating frequency error not exceeding 0.05 GHz) can be achieved at the cost of less than three full-wave EM simulations of the coupler. Numerical results are validated experimentally.
In order to explore creativity in design, a computational model based on Case-Based Reasoning (CBR) (an approach to employing old experiences to solve new problems) and other soft computing techniques from machine learning, is proposed in this paper. The new model is able to address the four challenging issues: generation of a design prototype from incomplete requirements, judgment and improvement of system performance given a sparse initial case base library, extraction of critical features from a given feature space, adaptation of retrieved previous solutions to similar problems for deriving a solution to a given design task. The core principle within this model is that different knowledge from various level cases can be explicitly explored and integrated into a practical design process. In order to demonstrate the practical significance of our presented computational model, a case-based design system for EM devices, which is capable of deriving a new design prototype from a real-world device case base with high dimensionality, has been developed.
In this work we investigate the present capabilities of computational fluid dynamics for wall boiling. The computational model used combines the Euler/Euler two-phase flow description with heat flux partitioning. This kind of modeling was previously applied to boiling water under high pressure conditions relevant to nuclear power systems. Similar conditions in terms of the relevant non-dimensional numbers have been realized in the DEBORA tests using dichlorodifluoromethane (R12) as the working fluid. This facilitated measurements of radial profiles for gas volume fraction, gas velocity, bubble size and liquid temperature as well as axial profiles of wall temperature. After reviewing the theoretical and experimental basis of correlations used in the ANSYS CFX model used for the calculations, we give a careful assessment of the necessary recalibrations to describe the DEBORA tests. The basic CFX model is validated by a detailed comparison to the experimental data for two selected test cases. Simulations with a single set of calibrated parameters are found to give reasonable quantitative agreement with the data for several tests within a certain range of conditions and reproduce the observed tendencies correctly. Several model refinements are then presented each of which is designed to improve one of the remaining deviations between simulation and measurements. Specifically we consider a homogeneous MUSIG model for the bubble size, modified bubble forces, a wall function for turbulent boiling flow and a partial slip boundary condition for the liquid phase. Finally, needs for further model developments are identified and promising directions discussed.