Solving nonlinear PDEs using the higher order Haar wavelet method on nonuniform and adaptive grids

The higher order Haar wavelet method (HOHWM) is used with a nonuniform grid to solve nonlinear partial differential equations numerically. The Burgers’ equation, the Korteweg–de Vries equation, the modified Korteweg–de Vries equation and the sine–Gordon equation are used as model equations. Adaptive as well as nonadaptive nonuniform grids are developed and used to solve the model equations numerically. The numerical results are compared to the known analytical solutions as well as to the numerical solutions obtained by application of the HOHWM on a uniform grid. The proposed methods of using nonuniform grid are shown to significantly increase the accuracy of the HOHWM at the same number of grid points

Higher Order Haar Wavelet Method for Solving Differential Equations

The study is focused on the development, adaption and evaluation of the higher order Haar wavelet method (HOHWM) for solving differential equations. Accuracy and computational complexity are two measurable key characteristics of any numerical method. The HOHWM introduced recently by authors as an improvement of the widely used Haar wavelet method (HWM) has shown excellent accuracy and convergence results in the case of all model problems studied. The practical value of the proposed HOHWM approach is that it allows reduction of the computational cost by several magnitudes as compared to HWM, depending on the mesh and the method parameter values used

Safety System Assessment Case Study of Automated Vehicle Shuttle

Automated vehicle (AV) minibuses, i.e., AV shuttles, are gaining popularity in the testing of new types of transportation services in real traffic conditions. AV shuttles have moved from closed test areas to low-traffic public sites such as local residential areas, technology parks, university campuses, etc. These types of vehicles are usually low-speed and rely on a lidar-camera sensor set and a self-driving software stack. These new use cases are increasing these systems’ safety demands. In addition to functional safety, many other aspects need to be considered. In this study, a risk analysis model is developed, combining the fuzzy analytical hierarchy process and the Technique for Order of Preference by Similarity to Ideal Solution method. The proposed model is utilized to prioritize risks corresponding to the particular case study, based on real AV shuttle bus development, and focuses on the low-level hardware/software safety issues and improvements

Safety System Assessment Case Study of Automated Vehicle Shuttle

Automated vehicle (AV) minibuses, i.e., AV shuttles, are gaining popularity in the testing of new types of transportation services in real traffic conditions. AV shuttles have moved from closed test areas to low-traffic public sites such as local residential areas, technology parks, university campuses, etc. These types of vehicles are usually low-speed and rely on a lidar-camera sensor set and a self-driving software stack. These new use cases are increasing these systems’ safety demands. In addition to functional safety, many other aspects need to be considered. In this study, a risk analysis model is developed, combining the fuzzy analytical hierarchy process and the Technique for Order of Preference by Similarity to Ideal Solution method. The proposed model is utilized to prioritize risks corresponding to the particular case study, based on real AV shuttle bus development, and focuses on the low-level hardware/software safety issues and improvements

Application of artificial intelligence and machine learning for BIM: review

Quality control is very important aspect in Building Information Modelling (BIM) workflows. Whatever stage of the lifecycle it is important to get and to follow building indicators. The BIM it is very data consuming field and analysis of these data require advance numerical tools from image processing to big data analysis. Artificial intelligent (AI) and machine learning (ML) had proven their efficiency to deal with automate processes and extract useful sources of data in different industries. In addition to the indicators tracking, AI and ML can make a good prediction about when and where to provide maintenance and/or quality control. In this article, a review of the AI and ML application in BIM will be presented. Further suggestions and challenges will be also discussed. The aim is to provide knowledge on the needs nowadays into building and landscaping domain, and to give a wide understanding on how those technics would impact industries and future studies

Real time production monitoring system in SME

Abstract. Real time production monitoring systems (PMSs) is an alternative to manual data collection and captures most of the required production data without human intervention. The general objective of the current study is to analyse PMSs and to offer particular solutions for small and medium sized enterprises (SMEs). The subtasks to be solved in the case of each particular PMS include determining relevant parameters, designing PMS and development of the data analysis and prognosis model for short term and long term planning. The selection of suitable PMS components and relevant parameters and the development of lathe cutting unit measuring system are described in the case study. Defendec Inc. and National Instruments Corporation wireless components were adopted to implement a part of the PMS

Influence of hollow glass microspheres on the mechanical and physical properties and cost of particle reinforced polymer composites

Abstract. The goal of the study was to find a cost-effective composition of a particle reinforced composite that is light in weight but has sufficient mechanical properties. The matrix of the particulate composite is unsaturated polyester resin that is reinforced with alumina trihydrate particles. Part of the alumina trihydrate proportion was replaced with hollow glass microspheres to reduce weight and save costs. In order to find out the influence of the light filler on the physical and mechanical properties of composites, materials with different percentages of the light filler were prepared. Test specimens were cut from moulded sheets that were fabricated with vacuum assisted extruder. Tensile strength, indentation hardness measured with a Barcol impressor, and density were determined. Based on the experimental data a multi-criteria optimization problem was formulated and solved to find the optimal design of the material. Artificial neural networks and a hybrid genetic algorithm were used. The optimal solution is given as a Pareto curve to represent the distinction between the density and selected mechanical properties of the composite material. The composite material filled with 6% hollow glass microspheres showed 3% loss in the tensile strength and 26% loss in the surface hardness compared to the composition without the filler. The weight decreased by 13% compared with the initial composition. The addition of hollow glass microspheres did not lower the net value of the material, it increased 7%

Function Approximation Using Haar Wavelets

The generalized approach for function approximation using Haar wavelets is proposed. An approach proposed is based on higher order wavelet expansion and algorithms for determining integration constants. The theoretical study is validated by numerical analysis. The decrease of the absolute error and increase of the numerical rate of convergence with respect to mesh has been observed in comparison with approach available in literature

Experimental Evaluation and Numerical Modelling Residual Stresses in Glass Panel

During last decade increased usage of laminated composite glass structures, also annealed and tempered glass can be observed in civil engineering, automobile and space structures, solar panels, etc. Latter trend is caused by high strength properties of laminated glass, also sound and vibration attenuation capabilities. However, heat treatment of glass causes residual stresses, which are not often covered in structural analysis. Current study is focused on experimental evaluation and numerical modelling of residual stresses in glass panels