This document presents a finite element analysis of a seat belt frame assembly. It aims to analyze deformation and von misses stress in the latch plate under different loads and thicknesses. Five case studies are conducted varying the thickness from 8mm to 4mm and loads from 63.5N to 350N. The results show that as thickness decreases, von misses stress increases. Failure occurs at 7mm thickness and 350N load. The latch plate is safe up to 250N for all thicknesses. An 8mm thick plate can withstand loads up to 350N. Deformations are negligible for all loads and thicknesses. Therefore, the optimal thickness for withstanding all loads is 8mm.
Shree Ji Steel Corporation, Mild steel beams wholesaler in India deals with steel and structural steel products. These products are useful for construction and industrial sector companies.
Polymers are presently broadly utilized as substitute material for steel gear in low
load devices. Its malfunction differs from gears made of steel, thus it is imperitive to sort
out the failures shown by polymer gears. Numerous earlier studies noted that wear
recognition, microstructure surface condition monitoring, weight loss and temperature
detection can be used in the analysis for the failure of polymer gear. The principle
objective of the current work is to conduct an analysis for failure detection methods as
defined above. Other researcher works were studied and their findings were extracted in
order to identify the methods they used. The most common method used was wear
detection and it was supplemented by other methods such as microstructure surface
condition monitoring. Failures shown by polymer can be concluded to be tooth breakage,
tooth deformation, material removal and surface fatigue.
Shree Ji Steel Corporation, Mild steel beams wholesaler in India deals with steel and structural steel products. These products are useful for construction and industrial sector companies.
Polymers are presently broadly utilized as substitute material for steel gear in low
load devices. Its malfunction differs from gears made of steel, thus it is imperitive to sort
out the failures shown by polymer gears. Numerous earlier studies noted that wear
recognition, microstructure surface condition monitoring, weight loss and temperature
detection can be used in the analysis for the failure of polymer gear. The principle
objective of the current work is to conduct an analysis for failure detection methods as
defined above. Other researcher works were studied and their findings were extracted in
order to identify the methods they used. The most common method used was wear
detection and it was supplemented by other methods such as microstructure surface
condition monitoring. Failures shown by polymer can be concluded to be tooth breakage,
tooth deformation, material removal and surface fatigue.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers