In the field of length, a gauge block is one of the representative gauges used as a standard for length. The main management items of the gauge block are central length, flatness, parallelism, hardness, and surface by visual inspection. The surface of the gauge block may wear over time due to repeated wringing. This phenomenon may deteriorate the precision accuracy and affect the reliability of the measurement results. In this study, the parameters of the surface roughness of the gauge blocks used repeatedly for about 10,000 hours were analyzed. The paired t-test of population mean difference was compared by using the gauge block that has changed over the years as a preliminary experiment and the gauge block with little frequency of use for less than 1 year as the reference value.

Ti-6Al-4V alloy has a wide range of applications, ranging from turbine blades that require smooth surfaces for aerodynamic purposes to biomedical implants, where a certain surface roughness promotes biomedical compatibility. Therefore, it would be advantageous if the high volumetric density is maintained while controlling the surface roughness during the LPBF of Ti-6Al-4V. In this study, the volumetric energy density is varied by independently changing the laser power and scan speed to document the changes in the relative sample density and surface roughness. The results where the energy density is similar but the process parameters are different are compared. For comparable energy density but higher laser power and scan speed, the relative density remained similar at approximately 99%. However, the surface roughness varies, and the maximum increase rate is approximately 172%. To investigate the cause of the increased surface roughness, a nonlinear finite element heat transfer analysis is performed to compare the maximum temperature, cooling rate, and lifetime of the melt pool with different process parameters.

The development of IOT technology and artificial intelligence technology is promoting the smartization of manufacturing system. In this study, data extracted from acceleration sensor and current sensor were obtained through experiments in the cutting process of SKD11, which is widely used as a material for special mold steel, and the amount of tool wear and product surface roughness were measured. SVR (Support Vector Regression) is applied to predict the roughness of the product surface in real time using the obtained data. SVR, a machine learning technique, is widely used for linear and non-linear prediction using the concept of kernel. In particular, by applying GSVQR (Generalized Support Vector Quantile Regression), overestimation, underestimation, and neutral estimation of product surface roughness are performed and compared. Furthermore, surface roughness is predicted using the linear kernel and the RBF kernel. In terms of accuracy, the results of the RBF kernel are better than those of the linear kernel. Since it is difficult to predict the amount of tool wear in real time, the product surface roughness is predicted with acceleration and current data excluding the amount of tool wear. In terms of accuracy, the results of excluding the amount of tool wear were not significantly different from those including the amount of tool wear.

PURPOSES : This study aims to develop and evaluate computer vision-based algorithms that classify the road roughness index (IRI) of road specimens with known IRIs. The presented study develops and compares classifier-based and deep learning-based models that can effectively determine pavement roughness grades. METHODS : A set road specimen was developed for various IRIs by generating road profiles with matching standard deviations. In addition, five distinct features from road images, including mean, peak-to-peak, standard variation, and mean absolute deviation, were extracted to develop a classifier-based model. From parametric studies, a support vector machine (SVM) was selected. To further demonstrate that the model is more applicable to real-world problems, with a non-integer road grade, a deep-learning model was developed. The algorithm was proposed by modifying the MNIST database, and the model input parameters were determined to achieve higher precision. RESULTS : The results of the proposed algorithms indicated the potential of using computer vision-based models for classifying road surface roughness. When SVM was adopted, near 100% precision was achieved for the training data, and 98% for the test data. Although the model indicated accurate results, the model was classified based on integer IRIs, which is less practical. Alternatively, a deep-learning model, which can be applied to a non-integer road grade, indicated an accuracy of over 85%. CONCLUSIONS : In this study, both the classifier-based, and deep-learning-based models indicated high precision for estimating road surface roughness grades. However, because the proposed algorithm has only been verified against the road model with fixed integers, optimization and verification of the proposed algorithm need to be performed for a real road condition.

PURPOSES : For large-scale construction, such as a concrete pavement, design and construction are not entirely consistent. If the inconsistency between design and construction is very large, construction quality is significantly degraded, affecting performance life span and driving comfort. The quality of pavement construction is managed according to standards. However, it is difficult to improve construction quality as the standard measures construction quality after construction is completed. Therefore, this study developed a system to measure the construction quality of concrete pavement in real-time and presented the corresponding standards. METHODS : A basic module for simultaneously measuring the width, thickness, and roughness of the concrete pavement was designed. Based on the measurement results of the distance measurement sensor, a calibration method is presented that can remove noise. The system process was developed to measure construction quality based on location and distance data, measured in real-time using GPSs and sensors. The field application experiment was conducted and the results were analyzed. RESULTS : The measurement module is properly designed to be used in concrete pavement construction sites. Noise was removed from the distance measurement sensor results according to the presented calibration method, leaving only the wave of pavement surface irregularities. As a result of applying the system process in the field application, a reasonable level of PRI was observed. CONCLUSIONS : In the past, the width, thickness, and roughness were measured after construction was completed and, if the standard was not met, construction quality control was performed via reconstruction or repair. Through this study, it is expected that the width, thickness, and roughness of the concrete pavement can be measured in real-time and, if the standard is not met, construction quality can be immediately controlled during construction to maintain high quality.

PURPOSES : The purpose of this study is to propose the certification process of International Roughness Index measuring device, i.e., a method for evaluating riding quality on road surfaces. METHODS : ROMDAS was selected as a reference device for verifying the accuracy of the IRI measuring device and the reliability of ROMDAS was checked through leveling in the laboratory and outdoors. To verify four different IRI measuring devices in Korea, the proper field test section was selected and IRI evaluation was conducted. A distance measuring instrument (DMI) - for verifying the accuracy of mileage - and IRI (as an index of roughness) were selected as the main evaluation parameters. For DMI verification, five repeated experiments were conducted for a 1 km section and, for IRI verification, speed variables of 40 km/h, 60 km/h, and 80 km/h were selected. Each device was tested at each speed 10 times. The accuracy of the measurement device was analyzed by comparing the measurement results with the verification criteria. RESULTS : As a result of the comparative experiment between the leveling and ROMDAS devices, the deviation of each measurement point value was within 1 mm and the R2 value was 0.8, demonstrating an excellent correlation. As a result of DMI verification, the tolerance of the three devices was found to be within 0.1 %; however, one device had a tolerance of 0.8 %, indicating that correction was necessary. For IRI evaluation, the average IRI value of the two reference devices was 2.02 m/km and the Minnesota standard was used as an analysis criterion. After the test, only one of the four devices was found to be effective across all speed ranges. Therefore, it was determined that additional sensor calibration is required to improve accuracy. CONCLUSIONS : In this study, the IRI device accuracy was evaluated through field tests. Hence, a new certification process for the IRI test device was proposed via four steps. To improve the accuracy of the IRI measurement, it is necessary to periodically verify the device. If this proposed certification process is applied, the accuracy of the IRI devices can be improved.

필로티는 현대건축에서 주차공간의 활용, 보행자의 통로 등 여러 가지 이점을 가지고 있기 때문에 아파트와 오피스텔과 같은 고층건축물에 많이 사용되고 있다. 이러한 고층건축물의 필로티 형태 특성상 강풍이 불 때 바람이 집중되기 때문에 필로티 천장과 벽 면에 위치하고 있는 외장재 및 주골조가 파손되기 쉽다. 그리고 이러한 외장재 및 주골조의 탈락으로 인해 2차 피해가 발생할 우려가 있다. 하지만 건축구조기준(KBC-2016)에서는 고층건축물에 대한 천장 및 벽면의 풍압계수만을 제시할 뿐 필로티에 대한 기준이 명시 되어 있지 않다. 본 논문은 고층건축물에서 사용되는 필로티의 종류로서 관통형, 개방형 필로티를 선정하였고, 필로티의 폭과 깊이를 변수로 하여 풍동실험을 진행하였다. 그리고 변수에 따른 풍압계수의 특성을 파악하였고 비교 및 분석하였고 본 논문의 실험결과를 통 하여 필로티 설계 시 활용할 수 있는 주골조 및 외장재 설계용 풍압계수를 제시하였다.

Aluminum alloys are the light weight materials, they are commonly used in many industrial applications such as electronic, aerospace, automotive, and medical industry. Because they are used in these such applications. Therefore, their light weight and high surface quality are required. In this paper, the surface improvement round flat aluminum alloy using lapping finishing method was explored. In order to find the optimal condition, lapping parameters such as, rotational speeds, abrasive grain sizes of pad, processing times, and lapping oils were investigated in this study. The improvement in surface roughness was found to be highest with optimal condition at 200 rpm of rotational speed, 1 ㎛ abrasive grain size of pad, 0.5ml of light oil for 720 sec. By using the optimal condition, the initial surface roughness Ra of round flat aluminum alloy can be enhanced from 2.59㎛ to 0.02 ㎛. This can be concluded that the small CNC machine with lapping finishing method can be used to enhance the surface roughness of round flat aluminum alloy effectively.

본 연구는 거친 표면에서의 유동장 특성에 대해 실험 및 수치해석적 연구를 수행하였다. 완전 발달한 두꺼운 난류경계층은 풍동 내 바닥에 깔린 거친 표면을 이용하여 생성하였다. 평균유동과 난류강도 및 왜도와 같은 난류경계층의 특성을 열선유속계를 이용해 측정하였다. 풍동실험결과와의 비교를 위해 난류경계층은 수치해석을 이용하여 모사하였다. 거친 벽표면은 기본적으로 난류경계층 생성에 사용되었으며 입출구면에는 주기경계조건이 적용되었다. 본 연구결과로서 난류경계층이 거친 표면 위에서 성공적으로 생성 되었으며 평균유동과 난류강도 및 왜도와 같은 난류경계층의 특성은 지표면조도에 따라 달라진다는 것을 확인하였다.

As product diversity increases and product life cycle gets shorter, lead time reduction and manufacturing cost saving of die & mold are getting important in machinery, automotive, and electronics industries. To develop a novel free-machining die & mold steel, we try to modify the chemical compositions of AISI P20 mold steel by adding boron, nitride, and sulfur. After making three types of mold steels which are base metal of AISI P20 mod., boron and nitrogen added, and boron, nitrogen, and sulfur added to the base metal. Milling tests are carried out using TiN, TiCN, and TiAlN coated WC end-mills under various cutting conditions. Boron and nitrogen added steel machined by TiN coated tool shows the most excellent tool wear and surface roughness characteristics. The results might come from BN inclusions in base metal acting as a stress concentration source and lowering strain resistance during cutting process. The relationship between tool wear and surface roughness are also discussed including feed rate effects.

Roller Compacted Concrete Pavement (RCCP) is a pavement placed and compacted using an asphalt paver and a compaction roller by applying a small amount of concrete mixture and shows excellent structural performance as a result of hydration reaction of cement and interlocking of aggregates by roller compaction. It also provides economic advantages over conventional concrete pavements by reducing unit cement content and construction period, simplifying construction process, and decreasing traffic closure time (Wayne, 2006). However, given that it tends to show lower IRI levels than common concrete pavements since its low unit water content and binder weight ratios make uniform quality control difficult and roller compaction after paving makes the surface irregular and rough, with rough profile at the bottom of the pavement being reflected on the surface, RCCP is used mainly in port and industrial roads for low speed (60km/h or less) traffic (Dale Harringtion, 2010; Gregory, 2009). In order to apply RCCP to high-speed roadways, diamond grinding (DG) or asphalt overlay that is highly effective in improving roughness is needed (Fares Abdo, 2014; Gregory, 2009). Applying DG over RCCP leads to excellent skid resistance and noise reduction effects as a great percentage of aggregates makes the pavement surface rough, enhancing durability of concrete and the life of DG functionality. In addition, RCCP can be used as a high performance base layer of composite pavements, as it can reduce reflecting cracking at joints and cracked sections thanks to early strength development and low drying shrinkage of concrete. In this study, we assessed longitudinal roughness improvement effects by roughness-affecting factor by applying DG methods and asphalt overlays to three RCCP sites with a variety of sub-structural conditions and analyzed the effects on roughness of existing RCC pavements depending on surfacing method (DG, APOverlay).

Since the road management paradigm has changed into the user-oriented circumstance, the functionality of the crucial road maintenance factors became important than before. Among these factors, the roughness directly related to the ride quality for driver became to get more attention. IRI(International Roughness Index) is recently the most widely used roughness indices in the world. IRI is a reasonable index that reflects the vertical displacement(bounce) of vehicle as the road profile changes. Since IRI reflects the vertical behavior of vehicle, it reflects ride quality indirectly. However, there are various rotational behaviors such as roll, yaw, and pitch in addition to the vertical displacement. Profiles, which MRI range was 1.13-4.12m/km, were measured in five sections and the profiles were entered into CarSIM to simulate vehicle behavior. As a result, the pitch was the largest in all sections, followed by roll and yaw, relatively. Especially, the amount of yaw is about 5% of the pitch or about 7% of the roll. The behavior of moving vehicle was measured using INS(inertial navigation system) and accelerometer in the section where the road surface profile was measured. As a result, as in the simulation, the pitch was the largest in all the sections and the amount of yaw is only about 7% of the pitch or about 18% of the roll. Field experiments were conducted to analyze the effect of the rotational behavior of the actual driving vehicle on the ride quality. 33 panels evaluated the ride quality on a ten-point scale while driving on 35 sections with various roughnesses. 35 test sections were selected considering the roughness distribution of actual expressway. The panel was selected considering age, driving experience, gender, and expertise. Of the total 1,155 responses, 964 responses were used for the analysis, except 191 responses measured at low driving speeds. In addition, the amount of vehicle behavior and road surface profile were measured using INS and laser. As a result of correlation analysis between MPR(mean panel rating) and vehicle behavior, correlation coefficient of bounce was the highest with 0.814, and the order of pitch was 0.798, and roll was 0.734, relatively. As a result of regression analysis for predicting ride quality, regression model combining bounce and roll was statistically the most suitable. This model is expected to reflect the ride quality more effectively because it can consider the vehicle behavior due to the longitudinal profile change of the road surface as well as the vehicle behavior due to the difference between the left and right wheel path road profile.

In general, the road roughness is managed by the roughness factor(or level, index) which is numerically or quantitatively generated(or converted) from the surface profile. However, it should be mentioned that the various roughness indexes including IRI(i.e. International Roughness Index) consider only vertical displacement and one longitudinal profile. In this research, the new roughness index, which evaluates reasonably the ride quality, was developed through the extensive correlation analysis between various vehicle behavior and ride quality. The bounce and pitch of moving vehicle are caused by the change of longitudinal profile. On the other hand, the roll is caused by the difference of the left and right profiles. Since the pitch is caused by the bounce difference between the front and rear axles of a vehicle, the two values occur in a similar pattern. In this study, the bounce and roll of a vehicle were predicted with a half car model, which is connected with two quarter car models. A half-car model was used to calculate the roll rotation angle of the vehicle body according to the change of the road profile. The roll rotation angle was used to calculate the coordinates of the head position of the passenger in the passenger seat. Finally, the coordinates were used to calculate the horizontal and vertical displacement of the head position. The new roughness index is the cumulative RMS value of the horizontal and vertical displacement occurring at the head position while moving at a speed of 80 km/h per km. The first and second experiment results presented that the coefficient of determination(i.e. R2) for the new roughness index was the highest with 0.80. Moreover, the R2 values of MRI, HRI, and RN were also relatively high such as 0.73 ~ 0.79. The feasibility test was conducted on sections that show the greater IRI variation between left and right wheel-pass among the pilot sites. Because a prediction result came from MRI and IRI, the difference between KERI and MRI was relatively lager with the increment of IRI difference between right and left wheel-pass. In this case, the roll was high, and the satisfaction of the ride quality was relatively low. Based on the other field survey results obtained in Seoul, the portion of IRI difference between left and right wheel-pass was above 0.4m/km that presented approximately seven times higher value than the measured IRI values on the expressway. In addition, the sectors showed IRI difference level higher than 2.0m/km were approximately 70 times higher than those in expressway. Thus, it is possible that the KERI could successfully and reasonably evaluate the ride quality on various road types.

Recently, as road users have become increasingly important, the importance of functional performance as much as structural one has been important to provide comfortable and safe road services. As a result of the survey on the customer satisfaction of the highway, the road surface condition is selected as the most important area of the road service, and the functional performance such as driving comfort and noise is pointed out as an important problem. Therefore, many studies have been conducted to improve this problem. In most cases, there is a fundamental limitation in providing a comfortable road to the user through the roughness management of the final layer. In this paper, a study was carried out to improve the roughness of the final layer by controlling the roughness of each layer. In construction field of Busan-ChangWon expressway, roughness was measured by three methods according to construction phases of subbase, 1st and 2nd base layer, intermedia layer and surface layer. As a result of the analysis, it was found that the roughness of the lower layer affects the roughness of the upper layer. Especially, the roughness of 1st base layer was relatively clear correlation with the intermedia and the surface layer IRI. In the future, after getting more field data and establishing the management standards, it is possible to provide a comfortable road to users.

본 논문은 3차원 축대칭 몰수체에 대해 소스 코드가 공개된 OpenFOAM 4.0을 이용하여 첫 번째 격자의 높이와 레이놀즈 수에 따른 마찰저항 변화에 대해 연구하였다. 마찰저항 계산을 위해 경계조건, 수치조건을 정립하였다. 축대칭 물체의 3차원 효과로 인해 거칠 기가 매우 작은 12 μΜ에서도 부드러운 표면과 비교해 마찰저항이 다르게 계산되었다. 레이놀즈 수가 커질수록 경계층의 두께 증가가 감소되었으며 이로 인해 마찰저항의 증가량이 감소되었다. 첫 번째 격자의 크기인 y+에 대한 영향에 대해서도 검토하였다. 첫 번째 격자가 log layer에 위치하고 있지 않으면 마찰저항과 표면의 전단력이 과도하게 예측되는 것을 확인하였다. 이는 경계층이 두껍게 예측되어 난류 에너지가 과도하게 예측되었기 때문으로 판단된다. 표면의 거칠기가 커질수록 경계층이 두꺼워지고 표면의 난류에너지가 증가되는 것을 확인하였다. 마찰저항을 정확하게 예측하기 위해서는 y+ 값, 거칠기 및 벽함수가 적절한 영역에 위치해야 함을 알 수 있었다.

최근 강풍으로 인한 시설물 피해가 증가함에 따라 구조물 설계 시 설계풍속을 반영하고 있으며, 설계풍속 산정 시 기상청에서 제공하고 있는 연최대풍속 년도별 풍속 자료를 활용한다. 하지만 기상청에서 제공하고 있는 연최대풍속은 지형이나 지표면조도에 의해 할증되거나 감소된 관측풍속 중 최댓값을 제공하고 있어 실제 기본풍속 조건에서의 연최대풍속과는 상이하기 때문에 기상청에서 제공하는 연최대풍속을 활용하여 통계적 빈도분석을 수행할 경우 풍속이 과소 또는 과대평가 될 수 있다. 따라서 본 연구에서는 40 년치 이상의 관측자료가 있는 전국 60개 지점의 기상관측소의 일최대풍속을 지형 및 지표면 조도에 따라 기본풍속 조건으로 보정하고 보정된 일최대풍속 중 연최대풍속을 선별하여 빈도분석을 통해 재현기간 풍속을 산정하였으며, 보정하기 전의 일최대풍속을 이용하여 연최대풍속을 선별한뒤 선별된 연최대풍속을 보정하여 산정된 재현기간풍속과 비교·분석하였다. 분석 결과 100년 재현기간 풍속 기준으로 최대 4.2m/s 차이를 보였으며, 평균적으로 약 0.33m/s의 차이를 보였다.