To identify cracks in a structure, an inverse analysis has been performed using the static and dynamic response of the structure. The accuracy of the inverse analysis is highly dependent on the form of the objective function and the choice of optimization method. Generally, the optimization method searching the solution by using the gradient of the objective function is adopted. However, for the crack problem interested in this study, it is known to have the drawback that the search solution strongly depends on the initial value setting. The biomimetics-based cuckoo optimization algorithm (COA) is a method that can overcome this drawback. However, few examples of this method for identifying the crack depth and location in a structure are available. In this study, an inverse analysis method for determining crack depth and location in beam-like structures by the COA was developed. The size and location of the crack were identified by the COA. In this study, the transfer matrix method (TMM) was utilized to numerically calculate the deformation and rotation angle of the beams, which are required in the inverse analysis. For this purpose, the fundamental theory was extended to the cracked element. Consequently, it was confirmed that the crack depth, crack location, and magnitude of the applied load can be predicted by the developed method with good accuracy.

The effects of cross-sectional shapes of flat-plate pulsating heat pipes (PHPs) on heat-transfer performance were experimentally investigated. The flat-plate PHP, made of aluminum alloy, has a closed-end serpentine channel with 22 turns. Four PHP samples with different channel shape (square or circular), the hydraulic diameter of the channel (1 or 1.2 mm), and plate thickness (3 or 2 mm) were prepared. The working fluid in the channel is R1336mzz(Z), and its filling ratio was increased from 30 mass% to 70 mass% in increments of 10 mass%. The heating section of the PHP is heated at power from 20 to 180 W in one of three heating orientations (vertical bottom, top, and horizontal) and the cooling section of the PHP is kept at 40 °C. Equivalent thermal conductivity is calculated from temperature on the surface of the PHP and heat transport rate. The experimental results indicate that the larger the cross-sectional area of the channel-wall material, the more likely it is that working-fluid oscillation will occur in the case of the top and horizontal heating orientations. Within the scope of this study, The PHP sample with a 1.2×1.2-mm square channel, the thickness of 3 mm, and filling ratio of 40 mass% has the highest equivalent thermal conductivity, namely, 2880 W/(m･K) at heat-transport rate Q of 146 W in top-heating orientation, 2750 W/(m･K) at Q = 146 W in horizontal-heating orientation, and 6540 W/(m･K) at Q = 36 W in bottom-heating orientation. As for that PHP, when Q is 80 W or more, equivalent thermal conductivities are the same regardless of heating orientation. It is thus considered that under that condition, working-fluid behaviors of the PHP become equivalent regardless of the heating orientation.

Repetitive motions of automatic machines induce a periodic disturbance, and the periodic disturbance deteriorates precision of motion control of the machines. A periodic-disturbance observer (PDOB) was proposed to suppress the periodic disturbance, but variation of the periodic disturbance frequency deteriorates the periodic disturbance suppression because its band-stop bandwidths in the sensitivity function for harmonics elimination are narrow. This paper proposes an infinite impulse response (IIR)-PDOB. The IIR-filter realizes wider frequency bandwidths in the sensitivity function than the PDOB, which achieves robustness against the variation of the periodic disturbance frequency. We confirmed that the IIR-PDOB was robust against the variation of the periodic disturbance frequency using a parallel robot.

A multi-material structure that is composed of several different material properties is promising for achieving an ideal functionality that can outperform a single material structure. In the course of automotive design, the combination of lightweight and stiff materials can reduce the weight of a car body without sacrificing its performance. This paper proposes a multi-material topology optimization (MMTO) framework for the eigenfrequency maximization problem based on the Multi-material level set (MMLS) based topology optimization. The key idea of MMLS is to use M level set functions to represent M material regions and one void region without overlap. To demonstrate the proposed method, first, we formulate an MMTO problem for maximizing the eigenfrequency based on the shape representation by the MMLS method. Next, we derive the topological derivatives of multiple materials in the eigenfrequency problem and construct an optimization algorithm in which the level set functions are evolved by solving a reaction–diffusion equation (RDE) based on the topological derivatives. Several numerical examples are provided to validate the proposed methodology.

To sustainably reduce carbon dioxide (CO₂) emissions at ambient temperature and atmospheric pressure, CO₂ is reduced to carbon monoxide (CO) using nonthermal plasma (NTP) flow and a catalyst. In a liquefied natural gas (LNG) gas-turbine combined power generation plant with high power generation efficiency, CO₂ zero-emission can be achieved for the power plant if the energy efficiency of CO₂ reduction by NTP is at least 49%. In this study, CO₂ reduction performance is evaluated for a two-step process using different gas mixtures. First, CO₂ is adsorbed from a gas flow mixture of nitrogen (N₂) and CO₂ (~10% concentration) by an adsorbent; second, CO₂ is desorbed and concentrated by NTP flow to a higher concentration from 19% to 25% and reduced by N₂ NTP flow and a catalyst under all experimental conditions. γ-alumina, copper, and copper doped alumina are used as catalysts, and the results are compared with those of a previous study where zeolite was used. The energy efficiency increases with the elapsed time and can reach 9−11%. When using copper doped alumina, plasma-catalysis promotes CO₂ reduction even in low-temperature environments at ~80 ℃, resulting in a higher CO concentration relative to the CO₂ concentration and the highest efficiency of all tested catalysts: conversion efficiency is 18% and energy efficiency is 11%.