Simulation of Energy and Media Demand of Beverage Bottling Plants by Automatic Model Generation

Facing environmental challenges, high energy costs and a growing public awareness, the global brewing industry is increasingly publishing ambitious targets toward a more sustainable production. Small and medium-sized enterprises of the brewing and beverage industry cannot ensure energy and media efficiency mainly due to capital and knowledge inadequacy. This article addresses this problem and presents a pragmatic method to determine the energy and media demand. Accordingly, a modeling editor as well as a standardized data structure and automatic simulation parameter determination tools were developed to implement the method. A given production plant can be modeled with adequate details using the presented editor. Based on a configuration file, a holistic simulation model can be generated automatically in a simulation environment. A beverage bottling plant was studied, and the necessary datasets were obtained for implementing the proposed editor and, thereby, the method. It was confirmed that the simulated values of electrical energy and compressed air consumption match the measured empirical data. The measures to increase energy and media efficiency were also found effective. Using the presented method, enterprises of the brewing and beverage industry can easily uncover avenues for potential savings, test the effectiveness of optimization strategies, and substantiate possible investment decisions.

REGULARIZED REBUILD WORKFLOW OF HBIM FOR BUILT HERITAGE DOCUMENTATION

Historic Building Information Modelling is a continuous process based on reverse engineering of built heritage. By reviewing the research on HBIM with the case study, this article analyzes the combination logic between different components, based on which designs an algorithm program for automatic model generation, and proposes a regularized rebuild workflow to realize the informatization and parameterized documentation of built heritage. This article proposes the parametric workflow based on Rhino + Grasshopper + Revit / OpenBuildings Designer, establishes the information index framework under the guidance of the HBIM model, and proposes the key technologies of informatization and parameterization of architectural heritage protection records. With reference to the point cloud, mapping map, survey photos, and documents, the regularized rebuild is carried out, and all the parameter nodes are visualized to facilitate error correction and modification. The framework of the regularized rebuild workflow is defined, and the problems of packet grouping principle, component combination mode, and output type are solved, and the algorithm principle is described in detail. According to the construction logic, the single building consists of six parts: tile roof, rafter, wooden carpentry, wall, decoration, and foundation. The work of investigation, modeling, and additional professional data are carried out by parts and items to create a "digital twin". This article solves the modeling problem of complex shape and node, and further improves the working method during the survey, and proposes to use an algorithm module to realize real-time association between professional data and model. Taking the grid system, wall brick, balustrade, tile roof, rafter as examples, through compiling and debugging in Grasshopper compiler environment, according to different input parameters, the program automatically outputs the corresponding model and contains professional data, which proves that the program is fast and accurate. The regularized rebuild workflow for HBIM by reference to point cloud is realized.

Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation

Knee osteoarthritis (OA) is a painful joint disease, causing disabilities in daily activities. However, there is no known cure for OA, and the best treatment strategy might be prevention. Finite element (FE) modeling has demonstrated potential for evaluating personalized risks for the progression of OA. Current FE modeling approaches use primarily magnetic resonance imaging (MRI) to construct personalized knee joint models. However, MRI is expensive and has lower resolution than computed tomography (CT). In this study, we extend a previously presented atlas-based FE modeling framework for automatic model generation and simulation of knee joint tissue responses using contrast agent-free CT. In this method, based on certain anatomical dimensions measured from bone surfaces, an optimal template is selected and scaled to generate a personalized FE model. We compared the simulated tissue responses of the CT-based models with those of the MRI-based models. We show that the CT-based models are capable of producing similar tensile stresses, fibril strains, and fluid pressures of knee joint cartilage compared to those of the MRI-based models. This study provides a new methodology for the analysis of knee joint and cartilage mechanics based on measurement of bone dimensions from native CT scans.

The Newton’s Polynomial Based - Automatic Model Generation (AMG) for Sensor Calibration to Improve the Performance of the Low-Cost Ultrasonic Range Finder (HC-SR04)

The ultrasonic range finder sensors is a general-purpose sensor to measure the distance contactless. This sensor categorized as low-cost sensor that widely used in various application. This sensor has a significant deviation that lead to significant error in the measurement result. The error that produced by this sensor tends to increase proportionally to the measured distance. The implementation of the particular algorithm is required to reduce the error value. The model-based calibration is a solution to increase the accuracy. The model-based solutions are no longer feasible if the states of the model have changed. The longer of the usage of the sensor lead to sensor fatigue. Sensor fatigue is one of the causes of model state changes. As long as the drift still within the tolerance limit, the performance of the sensor still can be restored by using calibration method. The model-based calibration calibrates the sensor by using the model. The update of the model must be made whenever the changing of the model state occurred. Since the manual model making process is not an easy task, time and cost required, then the Newton polynomial-based AMG (Automatic Model Generation) have been implemented to this research. The AMG algorithm generates the new sensor model automatically based on the most updated states. This automatic model generation is implemented in the calibration process of the ultrasonic sensor. The implementation of polynomial-based AMG algorithm for sensor calibration have been succeeded to improve the accuracy of the calibrated sensor by 96.4% and reduce the MSE level from 25.6 to 0.914.