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This paper addresses the protection capability of a runway pavement by executing a field blast test on an airfield pavement subjected to blast loading from a CBU (cluster bomb unit), and by confirming the numerical simulation of warhead penetration and the form of damage. The CBU's blast loading applies the BAP 100 of an air-to-ground munition in a similar scale. Penetration depth is calculated by a formula which incorporates the terminal speed of a free-falling cluster munition dispersed 20 km above the ground. According to the result of the calculation, the penetration depth by a cluster munition is 33 cm from the surface of the pavement. The field blast test was conducted based on this result. Furthermore, LS-DYNA software simulation was used to assess the condition of damage, determined by the depth of penetration and explosive pressure from a free-falling CBU landing on the airfield pavement from 20 km above the ground. The condition was ultimately used to verify the result of field testing and to confirm the scale of damage repair. The depth of explosion was 78 cm, from the surface to the crushed stone and sand layer below the pavement, and the diameter was 30 cm. The size of the crushed concrete that needed to be removed was an average diameter of 156 cm. The simulation result confirms that the diameter and depth of the crater are 67.6 cm and 67 cm, respectively, when the CBU is detonated under the same depth as the field testing, and the height of upheaval is 12 cm. The most appropriate method for repair, after a series of reviews, is to cut and remove a concrete slab 1.8 m × 1.8 m and cast the crushed stone layer disrupted from the explosion, followed by repairing the removed damaged concrete slab sections using rapid hardening concrete. [ABSTRACT FROM AUTHOR]

This paper presents a duty cycle correction scheme based on asynchronous sampling and associated settling analysis. The proposed duty cycle corrector circuit consumes less power and area compared to other corrector circuits due to the low-frequency operation of asynchronous sampling. However, the settling behavior of an asynchronous sampling duty cycle corrector is limited in some operation conditions, which degrades its robustness and performance. This paper, therefore, performs analysis on the settling behavior of the asynchronous sampling in various operating conditions and proposes a control scheme to avoid the lagged settling. To verify the proposed duty cycle corrector and its analysis, a prototype design is implemented in a 40-nm CMOS process and its performance is verified by post-layout simulations. The proposed duty cycle corrector achieved very small duty cycle errors (less than 0.8%) and consumed 540 uW per one DCC unit. [ABSTRACT FROM AUTHOR]

An imaging system has natural statistics that reflect its intrinsic characteristics. For example, the gradient histogram of a visible light image generally obeys a heavy-tailed distribution, and its restoration considers natural statistics. Thermal imaging cameras detect infrared radiation, and their signal processors are specialized according to the optical and sensor systems. Thermal images, also known as long wavelength infrared (LWIR) images, suffer from distinct degradations of LWIR sensors and residual nonuniformity (RNU). However, despite the existence of various studies on the statistics of thermal images, thermal image processing has seldom attempted to incorporate natural statistics. In this study, natural statistics of thermal imaging sensors are derived, and an optimization method for restoring thermal images is proposed. To verify our hypothesis about the thermal images, high-frequency components of thermal images from various datasets are analyzed with various measures (correlation coefficient, histogram intersection, chi-squared test, Bhattacharyya distance, and Kullback–Leibler divergence), and generalized properties are derived. Furthermore, cost functions accommodating the validated natural statistics are designed and minimized by a pixel-wise optimization method. The proposed algorithm has a specialized structure for thermal images and outperforms the conventional methods. Several image quality assessments are employed for quantitatively demonstrating the performance of the proposed method. Experiments with synthesized images and real-world images are conducted, and the results are quantified by reference image assessments (peak signal-to-noise ratio and structural similarity index measure) and no-reference image assessments (Roughness (Ro) and Effective Roughness (ERo) indices). [ABSTRACT FROM AUTHOR]