Software Implementation of the Algorithm for Recognizing Protective Elements on The Face

The quarantine restrictions introduced during COVID-19 are necessary to minimize the spread of coronavirus disease. These measures include a fixed number of people in the room, social distance, wearing protective equipment. These restrictions are achieved by the work of technological control workers and the police. However, people are not ideal creatures, quite often the human factor makes its adjustments. That is why in this work we have developed software for determining the protective elements on the face in real time using the Python scripting language, the open software libraries OpenCV v4.5.4, TensorFlow v2.6.0, Keras v2.6.0 and MobileNetV2 using the camera. The training program uses a prepared set of photos from KAGGLE — with a mask and without a mask. This set has been expanded by the authors to include different types of masks and their location. Using TensorFlow, Keras, MobileNetV2, a model is created to study the neural network by analyzing images. The generated neural network uses a model to determine the masks. You can preview the learning result of the network — it is presented as a graphic file. A program that uses the connected camera is then launched and the user can test the operation. This model can be easily deployed on embedded systems such as Raspberry Pi, Google Coral, and become a hardware and software automated system that can be used in crowded places — airports, shopping malls, stadiums, government agencies and more.

Digital Twin Geometry for Fibrous Air Filtration Media

Computational modeling of air filtration is possible by replicating nonwoven nanofibrous meltblown or electrospun filter media with digital representative geometry. This article presents a methodology to create and modify randomly generated fiber geometry intended as a digital twin replica of fibrous filtration media. Digital twin replicas of meltblown and electrospun filter media are created using Python scripting and Ansys SpaceClaim. The effect of fiber stiffness, represented by a fiber relaxation slope, is analyzed in relation to resulting filter solid volume fraction and thickness. Contemporary air filtration media may also be effectively modeled analytically and tested experimentally in order to yield valuable information on critical characteristics, such as overall resistance to airflow and particle capture efficiency. An application of the Single Fiber Efficiency model is incorporated in this work to illustrate the estimation of performance for the generated media with an analytical model. The resulting digital twin fibrous geometry compares well with SEM imagery of fibrous filter materials. This article concludes by suggesting adaptation of the methodology to replicate digital twins of other nonwoven fiber mesh applications for computational modeling, such as fiber reinforced additive manufacturing and composite materials.

Advance Injection Strategy Optimization: Maximize Benefit-Cost Ratio by Integration of Economic Spreadsheet in Excel to Assisted History Matching Using Python Scripting

Oil prices see large fluctuations peculiarly over the last eight years due to natural disasters, political instability, and Covid-19 pandemic shock. These prompt to anxiety towards expenditure in planning and forecasting of a field development plan (FDP). Economic optimization of a reservoir under water drive can be extremely tedious and time consuming especially for complex field. Traditionally, upon completion of forecast optimization on fluid production, reservoir engineer willhand over the reservoir models to petroleum economist for economical evaluation. If the chosen development strategy is not economically viable, the model strategies will have to be updated, and continue the repetition of financial evaluation all over again. Hence, this paper established an automated workflow that diminished the dilemma on iterations obligation between simulation runs and financial reviews in searching for most efficient waterflooding strategy. The automated workflow is accomplished by bridging three tools together seamlessly utilizing python scripting. These include the cash flow economic spreadsheet model, the dynamic simulator, and an assisted uncertainty analysis tool. The process first started with defining the economic parameters such as OPEX, CAPEX, oil price, taxes, discounted rates, and other financial parameters on an annual basis in spreadsheet. The uncertainty parameters: water injection rate, maximum water cut, and injection duration will be evaluated during forecast optimization to produce project efficiency indexes: Net Present Value (NPV) and Benefit-Cost Ratio (BCR). This integration was achieved by python script that automatically creates a coding path which exchanges simulation production and economic spreadsheet data at every simulation time step and each development strategy, that require no manual intervention. The integrated economic-dynamic model workflow has successfully applied on West Malaysian field and Olympus model, a development strategy that maximize oil recovery without neglecting cost of water disposal, storage for total water produced from the reservoir. This paper successfully identified the most efficient waterflooding strategy and production constraints for each well using BCR as objective function for optimization. The optimum development scenario does have a BCR which is more than 2 which show that investment on that particular development strategy is profitable. The results also demonstrated a crucial impression that the highest oil cumulative production may not results in high BCR due to cost involvement in resolving water production and field maintenance services. This paper outlined the methodology, python scripting codes, and how integration automation works that successfully optimized an injection strategy in a development project using economic model from third-party application. The results of this automated workflow demonstrate a successful utilization of new technologies and simple customize programming knowledge that promote cross-discipline integration for enhanced work-time efficiencies in problem solving that is suitable for all reservoir model type to determine its success rate and economic viability during FDP.

A Geometry-Based Welding Distortion Prediction Tool

The prediction of welding distortion requires expertise in computer simulation programs, a clear definition of the nonlinear material properties, and mesh settings together with the nonlinear solution settings of a coupled thermal–structural analysis. The purpose of this paper is to present the validation of an automatic simulation tool implemented in Ansys using Python scripting. This tool allows users to automate the preparation of the simulation model with a reduced number of inputs. The goal was, based on some assumptions, to provide an automated simulation setup that enables users to predict accurate distortion during the welding manufacturing process. Any geometry prepared in a CAD software can be used as the input, which gave us much geometrical flexibility in the shapes and sizes to be modeled. A thermomechanical loosely coupled analysis approach together with element birth and death technology was used to predict the distortions. The automation of the setup enables both simulation and manufacturing engineers to perform welding-induced distortion prediction. The results showed that the method proposed predicts distortion with 80–98% accuracy.

gmxapi: a Gromacs-native Python interface for molecular dynamics with ensemble and plugin support

Gmxapi provides an integrated, native Python API for both standard and advanced molecular dynamics simulations in GROMACS. The Python interface permits multiple levels of integration with the core GROMACS libraries, and legacy support is provided via an interface that mimics the command-line syntax, so that all GROMACS commands are fully available. Gmxapi has been officially supported since the GROMACS 2019 release and is installed by default in current versions of the software. Beyond simply wrapping GROMACS library operations, the API permits several advanced operations that are not feasible using the prior command-line interface. First, API allows custom user plugin code within the molecular dynamics force calculations, so users can execute custom algorithms without modifying the GROMACS source. Second, the Python interface allows tasks to be dynamically defined, so high-level algorithms for molecular dynamics simulation and analysis can be coordinated with loop and conditional operations. Gmxapi makes GROMACS more accessible to custom Python scripting while also providing support for high-level data-flow simulation algorithms that were previously feasible only in external packages.

Creating an Electronic Course on Programming in Python for the Android Platform

The description and principles of developing a mobile application for the Android platform that provides free access to electronic courses on teaching the basic structures of the Python language and the construction of template programming algorithms based on them are presented. The content of the course is based on the principle of comparative analysis with the C++ language, one of the goals of which is to differentiate the tasks for which it is more efficient to use either the Python scripting language or the C++ compiler. The developed application is logically integral, allows the possibility of supplementing with new data — examples, types of algorithms — and, no less important, is free.

A NEW ELEMENT-BASED METHOD FOR SOLVING STRUCTURAL TOPOLOGY OPTIMIZATION PROBLEMS WITH NON-UNIFORM MESHES

This study proposes a new element-based method to solve structural topology optimization problems with non-uniform meshes. The objective function is to minimize the compliance of a structure, subject to a volume constraint. For a structure of a fixed volume, the method is intended to find a topology that could almost conform to the compliance minimum. The method is refined from the evolutionary switching method, whose policy of exchanging elements is improved by replacing some empirical decisions with ones according to optimization theories. The method has the evolutionary stage and the element exchange stage to conduct topology optimization. The evolutionary stage uses the evolutionary structural optimization method to remove inefficient elements until the volume constraint is satisfied. The element exchange stage performs a procedure refined from the element exchange method. Notably, the procedures of both stages are refined to conduct non-uniform finite element meshes. The proposed method was implemented to use the Abaqus Python scripting interface to call the services of Abaqus such as running analysis and retrieving the output database of an analysis. Numerical examples demonstrate that the proposed optimization method could determine the optimal topology of a structure that is subject to a volume constraint and whose mesh is non-uniform.