While up-right build structures are under construction, an over-hung crane has a major role in efficient lifting and transporting heavy materials from one point to another. There are several types of cranes for a variety of construction sites, such as bridge/overhead, barge lift, tower crane, etc. The mobile crane is one of the most widely used types of construction equipment due to its mobility. Unfortunately, the number of crane accidents including casualties and deaths has increased over the last decade. In order to reduce these fatal tragedies, a dynamic simulator of mobile cranes based on analyzed overturn limit data has been developed and analysis results have been applied to site tests. The test bench is formulated to simulate the actual construction field and some practical experiments have been performed in realistic manners of operation. Moreover, wireless network communication systems are applied for monitoring the status of the crane from a distance where visibility is not secure. Consequently, the applicability in the field derived from operating the simulator and actual vehicle testing confirmed the feasibility of applying it to construction sites.

Aluminum 6061 is a precipitation-hardened alloy, containing magnesium and silicon as its major alloying element, and it is widely used in industries due to its remarkable mechanical properties and weld ability. Several types of machining manners are researched for aluminum 6061 alloys, and micro-abrasive jet blasting (μ-AJM) is one of the most developed processes for improving surface roughness. When operating μ-AJM on aluminum alloys, sufficient consideration of environmental variables such as particle types, nozzle diameter, pressure, standoff distance, and injection time is a prerequisite for the appropriate degree of roughness. To find the optimal conditions, a statistical method of analysis of variables was used to investigate the maximum value for depth, diameter, width, etc., of the blasting surface. According to experimental results, multiple factors have a great influence on the condition of surface roughness. The blasting processes were conducted as square and cylindrical experiments, and the parameters for optimal conditions have been derived from a surface roughness measurement system.

With the increasing demand to find new energy resources instead of using fossil fuels, for the protection of the environment, one of most attractive areas in renewable energy is hydrogen. Hydrogen gas has high energy efficiency, generates the least greenhouse gases and produces no noise. Moreover, overland transportation industries have been researching and developing hydrogen gas storage systems worldwide. Such a manner of fuel system consists of a hydrogen gas tank, high pressure regulator and solenoid valve, etc. In this paper, a test bed is suggested for ultra-high pressure systems integrating a valve and regulator with precision control. We carried out performance tests by applying voltage with wide ranges of input pressure, response time and output flow rate and pulsation repetition tests considering increases in temperature, etc. Moreover, the results indicated good potential for application in fuel charging and transporting commercial hydrogen vehicles.

The turbulence intensity (TI) is defined as the ratio of fluctuation from the standard deviation of wind velocity to the mean value. Many studies have been performedon TI for flow dynamics and adapted various field such as aerodynamics, jets, wind turbines, wind tunnel apparatuses, heat transfer, safety estimation of construction, etc.The TI represents an important parameter for determining the intensity of velocity variation and flow quality in industrial fluid mechanics. In this paper, computational fluid dynamic (CFD) simulation of TI alteration with increasing temperature has been performed using the finite volume method. A high-temperature—maximum 300 degrees Celsius (°C)—wind tunnel test rig has been used as theapparatus, and velocity was measured by an I-type hot-wire anemometer. The velocity and TI of the core test section were operated at several degrees of inlet temperatures at anair velocity of 20 m/s. The magnitude of TI has a relationship with boundary layer development. The TI increased as temperature increased due to turbulence created by the non-uniformities.

Recently, research on applying artificial intelligence (AI) to various industries, especially manufacturing, is being actively conducted. In the field of smart factory, the purpose is to improve productivity based on data generated in the process of producing or processing products. The tool breakage during metal product processing causes fatal difficulties of predicting tool life. Moreover, if tool life is not predicted, defects may occur product reliability deteriorate, which may adversely affect product performance or economic aspects. In this paper, data related to machining is collected from CNC equipment in real time, and through machine learning and deep learning, which factors affect the wear of cutting tools are identified and the lifespan of cutting tools is predicted. An AI-based solution was applied to the system, productivity improved due to an increase in tool life.

This paper deals with simulator development for an underwater aquaculture surveillance system. The aim is to prevent the intrusion of objects into the water. The simulator checks the performance of the alarm system prior to installation in the underwater surveillance system. The simulator tests virtual environments, but reliable experimental results are obtained using two different methods. First, the state space underwater intruder dynamic models is expressed to control several variables at once. Second, the sensor model is designed using a statistical approach, because detection performance decreases for a various reason when detecting objects using the sensor. This simulator uses Matlab GUI as a tool. Setting various test environments (i.e., sensor configuration and sensor detection range) allows the user to analyze the performance of the underwater surveillance system.