On-site Measurements Research Articles

Comprehensive Review of Tunnel Blasting Evaluation Techniques and Innovative Half Porosity Assessment Using 3D Image Reconstruction

To meet the increasing demand for rapid and efficient evaluation of tunnel blasting quality, this study presents To meet the increasing demand for rapid and efficient evaluation of tunnel blasting quality, this study presents a comprehensive review of the current state of the art in tunnel blasting evaluation, organized into five key areas: Blasting Techniques and Optimization, 3D Reconstruction and Visualization, Monitoring and Assessment Technologies, Automation and Advanced Techniques, and Half Porosity in Tunnel Blasting. Each section provides an indepth analysis of the latest research and developments, offering insights into enhancing blasting efficiency, improving safety, and optimizing tunnel design. Building on this foundation, we introduce a digital identification method for assessing half porosity through 3D image reconstruction. Utilizing the Structure from Motion (SFM) technique, we re-construct the 3D contours of tunnel surfaces and bench faces after blasting. Curvature values are employed as key indicators for extracting 3D point cloud data from boreholes. The acquired postblasting point cloud data is processed using advanced software that incorporates the RANSAC algorithm to accurately project and fit the borehole data, leading to the determination of the target circle and borehole axis. The characteristics of the boreholes are analyzed based on the fitting results, culminating in the calculation of half porosity. Field experiments conducted on the Huangtai Tunnel (AK20 + 970.5 to AK25 + 434), part of the new National Highway 109 project, provided data from shell holes generated during blasting. These data were analyzed and compared with traditional onsite measurements to validate the proposed method’s effectiveness. The computed half porosity value using this technique was 58.7%, showing minimal deviation from the traditional measurement of 60%. This methodology offers significant advantages over conventional measurement techniques, including easier equipment acquisition, non-interference with construction activities, a comprehensive detection range, rapid processing speed, reduced costs, and improved accuracy. The findings demonstrate the method’s potential for broader application in tunnel blasting assessments.

Integrating observational and modelled data to advance the understanding of heat stress effects on pregnant subsistence farmers in the gambia

Studies on the effect of heat stress on pregnant women are scarce, particularly in highly vulnerable populations. To support the risk assessment of pregnant subsistence farmers in the West Kiang district, The Gambia we conducted a study on the pathophysiological effects of extreme heat stress and assessed the applicability of heat stress indices. From ERA5 climate reanalysis we added location-specific modelled solar radiation to datasets of a previous observational cohort study involving on-site measurements of 92 women working in the heat. Associations between physiological and environmental variables were assessed through Pearson correlation coefficient analysis, mixed effect linear models with random intercepts per participant and confirmatory composite analysis. We found Pearson correlations between r-values of 0 and 0.54, as well as independent effects of environmental variables on skin- and tympanic temperature, but not on heart rate, within a confidence interval of 98%. Pregnant women experienced stronger pathophysiological effects from heat stress in their third rather than in their second trimester. Environmental heat stress significantly altered maternal heat strain, particularly under humid conditions above a 50% relative humidity threshold, demonstrating interactive effects. Based on our results, we recommend including heat stress indices (e.g. UTCI or WBGT) in local heat-health warning systems.

Application of PV on Commercial Building Facades: An Investigation into the Impact of Architectural and Structural Features

The rapid global transition toward renewable energy necessitates innovative solar PV deployment strategies beyond conventional roof installations. In this context, commercial building facades represent an expansive yet underutilized resource for solar energy harvesting in urban areas. However, existing studies on commercial rooftop solar PV predominantly focus on European contexts, neglecting the unique design constraints and performance trade-offs present in regions such as the Middle East. This study addresses this gap by specifically investigating the impact of architectural and structural features on the utilizable facade area for PV deployment in commercial buildings within the hot desert climate of Saudi Arabia. Detailed case studies of twelve representative buildings are conducted, combining architectural drawing analysis, on-site measurements, and stakeholder surveys. The methodology identified sixteen parameters across three categories—facade functionality, orientation suitability, and surrounding obstructions—that impose technical and non-technical restrictions on photovoltaic integration 3D modeling, and irradiance simulations revealed that, on average, just 31% of the total vertical facade area remained suitable for PV systems after accounting for the diverse architectural and contextual limitations. The study considered 698 kWh/m2 of solar irradiance as the minimum threshold for PV integration. Shopping malls displayed the lowest utilizability, with near-zero potential, as extensive opaque construction, brand signage, and shading diminish viability. Offices exhibited the highest utilizability of 36%, owing to glazed facades and unobstructed surroundings. Hotels and hospitals presented intermediate potential. Overall, the average facade utilizability factor across buildings was a mere 16%, highlighting the significant hurdles imposed by contemporary envelope configurations. Orientation unsuitability further eliminated 12% of the initially viable area. Surrounding shading contributed an additional 0.92% loss. The results quantify the sensitivity of facades to aspects such as material choices, geometric complexity, building form, and urban context. While posing challenges, the building facade resource holds immense untapped potential for solar-based urban renewal. The study highlights the need for early architectural integration, facade-specific PV product development, and urban planning interventions to maximize the renewable energy potential of commercial facades as our cities rapidly evolve into smart solar energy landscapes.

Analysis of the slump test for on-site yield stress measurement of thickened tailings

Yield stress of thickened tailings is a basic parameter in the design of tailings pipeline transport and discharge systems. To accurately determine the yield stress of thickened tailings, it is essential to develop a rapid determination method suitable for engineering applications and explore the relationship among various factors. In this paper, a high-precision velocity-controlled slump test system was designed to investigate the effects of thickened tailings temperature, lifting speed, slump cylinder shape, and tailings slurry mass concentration on the slump value. The test results indicate that the slump value decreases with the increases in thickened tailings temperature, resulting in a higher yield stress. Lifting speed significantly affects the yield stress, a faster lifting speed produces a larger slump value, which in turn leads to a smaller calculated yield stress. The lifting speed of 0.01 m/s provides a yield stress calculation that is close to the actual value. Moreover, among the tested slump cylinder shapes, the results obtained from the cylinder with dimensions of 100 mm (height) × 100 mm (diameter) are the closest to the actual values. These findings offer technical support for rapid and accurate on-site testing of the rheological parameters of thickened tailings and provide theoretical support for developing disposal methods for tailings.

Construction of Energy Consumption Model in Asphalt Mixture Production Stage Based on Field Measurements

To better construct an energy consumption model for the asphalt mixture production stage, this study divides the production process into four phases: aggregate dust removal, aggregate drying, asphalt heating, and mixture blending. Utilizing measured data from various regions in Anhui Province, the model considers factors such as season, mixture type, and energy consumption type. The study quantitatively compares and analyzes the energy consumption results obtained from three calculation methods: the theoretical method, the quota method, and the energy consumption model method. The results indicate that the total energy consumption shares of the aggregate dust removal, aggregate drying, asphalt heating, and mixture blending phases are 4.23%, 69.50%, 17.75%, and 8.52%, respectively. The primary energy consumption during the asphalt mixture production stage is concentrated in the aggregate drying and asphalt heating phases. The energy consumption model based on on-site measurements effectively reflects the actual energy consumption levels during the asphalt mixture production stage. Moreover, the total energy consumption calculated by the three methods follows the order quota method > energy consumption model method > theoretical method. By constructing an energy consumption model based on measured data, it is possible to more accurately assess the energy usage during the asphalt mixture production process. This helps optimize production techniques, reduce energy consumption and carbon emissions, and provide a scientific basis for sustainable road construction.

Identification of High-Photosynthetic-Efficiency Wheat Varieties Based on Multi-Source Remote Sensing from UAVs

Breeding high-photosynthetic-efficiency wheat varieties is a crucial link in safeguarding national food security. Traditional identification methods necessitate laborious on-site observation and measurement, consuming time and effort. Leveraging unmanned aerial vehicle (UAV) remote sensing technology to forecast photosynthetic indices opens up the potential for swiftly discerning high-photosynthetic-efficiency wheat varieties. The objective of this research is to develop a multi-stage predictive model encompassing nine photosynthetic indicators at the field scale for wheat breeding. These indices include soil and plant analyzer development (SPAD), leaf area index (LAI), net photosynthetic rate (Pn), transpiration rate (Tr), intercellular CO2 concentration (Ci), stomatal conductance (Gsw), photochemical quantum efficiency (PhiPS2), PSII reaction center excitation energy capture efficiency (Fv’/Fm’), and photochemical quenching coefficient (qP). The ultimate goal is to differentiate high-photosynthetic-efficiency wheat varieties through model-based predictions. This research gathered red, green, and blue spectrum (RGB) and multispectral (MS) images of eleven wheat varieties at the stages of jointing, heading, flowering, and filling. Vegetation indices (VIs) and texture features (TFs) were extracted as input variables. Three machine learning regression models (Support Vector Machine Regression (SVR), Random Forest (RF), and BP Neural Network (BPNN)) were employed to construct predictive models for nine photosynthetic indices across multiple growth stages. Furthermore, the research conducted principal component analysis (PCA) and membership function analysis on the predicted values of the optimal models for each indicator, established a comprehensive evaluation index for high photosynthetic efficiency, and employed cluster analysis to screen the test materials. The cluster analysis categorized the eleven varieties into three groups, with SH06144 and Yannong 188 demonstrating higher photosynthetic efficiency. The moderately efficient group comprises Liangxing 19, SH05604, SH06085, Chaomai 777, SH05292, Jimai 22, and Guigu 820, totaling seven varieties. Xinmai 916 and Jinong 114 fall into the category of lower photosynthetic efficiency, aligning closely with the results of the clustering analysis based on actual measurements. The findings suggest that employing UAV-based multi-source remote sensing technology to identify wheat varieties with high photosynthetic efficiency is feasible. The study results provide a theoretical basis for winter wheat phenotypic monitoring at the breeding field scale using UAV-based multi-source remote sensing, offering valuable insights for the advancement of smart breeding practices for high-photosynthetic-efficiency wheat varieties.

Modelling and experimental study on pipeline defect characterisations using a pulsed eddy current measurement

ABSTRACT Pipelines are widely used as the main transportation method in petrochemical and metallurgical industries. However, the special nature of the materials transported in pipelines means they are often subjected to high temperature, high pressure and corrosive conditions. This can lead to defects, such as thinning and cracking, resulting in pipeline failure and causing serious economic losses. Therefore, regular non-destructive testing of pipelines is particularly important. This paper uses the non-destructive testing method with pulsed eddy current technology to characterise pipeline thinning and defects. A preliminary study is conducted on the pulsed eddy current detection signal patterns for pipeline crack defects with varying orientations and quantities. A more portable pulsed eddy current detection device with an extended wall thickness detection range is developed. It can achieve measurements with a maximum thickness of 30 mm for detections of pipelines with rectangular defects and thickness-stepped reduced. The experimental results are consistent with modelling results, and the accuracy for pipelines with insulation layer is also investigated. On-site measurements using the PEC system are conducted on equipment sections with pipe thickness within 20 mm in a petrochemical plant. It is confirmed that the developed PEC inspection device can accurately characterises the thickness of pipelines with 0–50 mm cladding.

Optimizing soil conservation through comprehensive benefit assessment in river basins

Land degradation from water erosion poses a significant threat to water security and ecosystem stability, driving global efforts in soil conservation. Quantitative assessment of soil conservation benefits—both on-site and off-site—is crucial for guiding effective conservation strategies. However, existing methodologies often fall short in quantifying the value of these combined benefits. Here, we present a comprehensive framework for quantifying soil conservation service flows in monetary terms, evaluating the effectiveness of both on-site and off-site measures. Applying this framework to the Yellow River Basin (YRB), we employ cost-avoidance algorithms related to soil fertility maintenance, dredging cost reduction, and mitigation of nonpoint source pollution. Our results reveal that while many areas contribute to both on-site and off-site benefits, over half of the YRB relies predominantly on off-site services. By strategically enhancing key regions—which constitute 30% of the basin—we demonstrate that the overall soil conservation service supply can increase by 64.2% over the multi-year average from 2001 to 2020 compared to a consideration of on-site only. These findings underscore the essential role of off-site services in fully understanding soil conservation needs, particularly in large river basins, and the identified priority areas can offer valuable insights for optimizing soil conservation efforts.

Radiation Monitoring for Volatilized Zinc Contamination Using Gamma-Ray Imaging and Spectroscopy

Abstract Gamma-ray imaging is a tool that has grown in importance in the applications of non-destructive assay (NDA) for radioactive survey and analysis of nuclear facilities. Imaging techniques have shown great promise in providing valuable information involving radioactive waste management and contamination prevention. For the application studied in this work, 65Zn has been identified as a radioactive contaminant during tritium extraction. Due to the volatile nature of 65Zn under the pressure and temperature changes during extraction operations, 65Zn can easily travel through components of the extraction system as vapor, making it difficult to trap. Previous research involving the development of a filtration system showed that the 65Zn can be trapped, mitigating product contamination. However, during the extraction process, direct analysis of the equipment to confirm that zinc contamination is trapped in the filter and has not spread to other components is impractical. In this situation, the need to assay the location of the contamination with little-to-no interference with operations is vital. In this work, we demonstrate the use of a commercialized 3D position-sensitive CdZnTe (CZT) gamma-ray imaging spectrometer to provide analysis of the 65Zn contamination. Onsite measurements during an extraction process are studied to assess the location and migration of the 65Zn. The results obtained from real-time glovebox monitoring demonstrate the feasibility of gamma-ray imaging for localizing the contamination and providing a preliminary qualitative assessment that is intended to be used in future work quantifying the contamination build-up and activity over time.

Grating pitch comparator traceable to the Cr atom transition frequency

Calibration of the grating pitch typically requires metrological instruments or diffraction techniques. The traceability and stability demands for laser wavelength in these techniques present substantial challenges for on-site grating calibration. This paper introduces a novel traceability approach to grating pitch calibration using a grating pitch comparator that utilizes the transition frequency of the chromium. The chromium transition frequency is converted into a chromium grating through atom lithography, establishing a self-traceable length standard dCr = 212.7787 ± 0.0049 nm. Calibration of the test grating’s pitch is achieved by comparing the phase shift caused by the simultaneous movement of the chromium grating and the test grating. By using the dCr, this approach combines the high-accuracy of fundamental physical constants with the environmental stability of grating interferometers, eliminating the need for measuring laser wavelength, air refraction, diffraction angles. It significantly enhances the precision and makes more straightforward and portable, crucial for facilitating traceable on-site grating measurements.

Refinement method of equivalent source power level determination for traffic noise in urban noise mapping

For traffic noise prediction, the predictive models of source power level determination commonly in use are the Technical Guidelines for Noise Impact Assessment in China or the Calculation of Road Traffic Noise model in the United Kingdom, which incorporate traffic flow and car speeds. However, the accuracy of these models is often compromised due to urban traffic's complexity, vehicle diversity, and unforeseen events. This study investigates a refinement method based on noise on-site measurement and aforementioned approaches for equivalent source power level determination for traffic noise in urban noise mapping. In the study, onsite measurements are conducted to collect noise and traffic data, and source power level calculated by refinement method is validated using measurement data. Different prediction methods are employed for measurement sites calculations. By comparisons between predictions with noise on-site measurement data, the refinement method proposed in the study demonstrates a significant accuracy enhancement in traffic noise prediction over previous models for determining equivalent source power level. This enhancement highlights the efficacy of adopting noise measurement-based methods for setting traffic noise source power levels, leading to more precise traffic noise predictions in complex urban settings, particularly in areas surrounding urban arterial roads.

Evaluation of the influence of traditional village square layout factors on wind comfort

The layout factors of traditional village squares play a significant role in determining the comfortable outdoor wind environment, making them the primary venue for outdoor communication activities among residents. This study focuses on the traditional village square spaces within the jurisdiction of Quanzhou City, Fujian Province, China. Through onsite measurements and CFD simulations, the effects of various layout factors on the wind environment are compared and analyzed. The results are as follows: (1) The plane permeability index of the enclosed square space layout impacts wind speed, comfort, and ventilation performance. Lowering the index will decrease wind speed, but it will improve comfort. (2) Increasing the height-to-cross-section ratio index of the enclosed layout of the square space will reduce wind speed, thereby improving wind comfort. (3) Increasing the enclosure rate index of the square space enclosure layout will decrease wind speed, resulting in better wind comfort. Overall, the research findings indicate that careful consideration should be given to the enclosed layout of traditional village square spaces to ensure optimal wind conditions.

Prediction and validation of flanking sound transmission in cross-laminated timber junctions with resilient interlayers

Propelled by its small carbon footprint, low weight and high stiffness, cross-laminated timber (CLT) has experienced a significant commercial growth in the last decade. However, these latter two features potentially contribute to poor acoustic performance. A critical factor is flanking sound, in which vibrational energy is transmitted between two elements connected through a common junction, driving the need to include vibration isolation solutions such as resilient interlayers in the junction design. In this work, the vibration reduction index across CLT junctions is predicted with an analytical wave approach for semi-infinite thin plates. Each CLT panel is modelled as an orthotropic or isotropic equivalent single layer (ESL). Multiple options to determine the ESL properties are compared, including the law of mixtures and the modified gamma method. The interlayer is considered to be a thick, flexible waveguide, whose out-of-plane motion is governed by shear. The prediction model is validated experimentally with on-site measurements for a vertical T-junction with a polyurethane foam interlayer. The predictions are moderately accurate in the entire frequency range, with deviations below 10 dB across all 1/3 octave bands. Depending on the layer configuration, the orthotropy of the ESL can significantly influence the predictions.

A pilot study: developing acoustic model for immersive environment

In the landscape of higher education in Malaysia, the adoption of immersive technologies still in its infancy, particularly within the field of building science education. This research endeavors to elevate the learning experiences of Indoor Environmental Quality (IEQ) concepts, with a specific focus on lighting and acoustics. The ongoing study seeks to revolutionize current learning methodologies by converting traditional modules into an immersive virtual environment, offering learners an interactive, and sensory-rich experience with the subject matter. To ensure the effectiveness of the acoustic immersive environment, this paper prioritizes the initial step of developing the acoustic simulation model. In an early pilot study, on-site measurements of sound pressure levels were recorded at various points within a basic classroom setting and an acoustic model will be developed subsequently. Consequently, the alignment between the developed acoustic model and real-world physical measurements establishes a solid foundation for the subsequent calibration process, during which the acoustic model will be tailored to meet VR-ready specifications delve into immersive environment model. This finding ensures a seamless transition of real-world acoustic conditions into the virtual realm, amplifying the authenticity and educational impact of the VR learning experience, thereby contributing to the advancement of immersive technologies in higher education.

The problem of obtaining vehicles speed input for road traffic noise microscopic models: a comparison between field measurements and a stochastic approach

Mitigating environmental noise harmful effects is a relevant goal in the EU "Zero Pollution Action Plan", which targets a 30% reduction in chronic annoyance from transportation noise by 2030. Since road traffic is a major noise source in urban and non-urban settings, much effort has been invested in analyzing and modeling it. To assess noise levels, numerous Road Traffic Noise Models (RTNMs) exist, each requiring multiple inputs like vehicle flows, percentage of heavy vehicles, and average speed. Specifically, when dealing with microscopic models, the single vehicle speeds are needed. To obtain them, on-site measurements offer accurate data but are time consuming and expensive. This paper explores two approaches: an alternative measurement approach, based on video processing and object detection tools, and a stochastic approach, which randomly assigns a speed to each vehicle from a distribution curve, depending on traffic conditions and vehicle category. These methodologies are used to provide input data to a road traffic noise microscopic model, whose results are compared with field measured data. This comparison will allow to get useful insights on the performances of the proposed techniques in providing reliable inputs and their potential applications in different scenarios where single vehicle measured speeds are not available.

Validation of Noise Barrier Insertion Loss Simulation in Reducing Road Traffic Noise by Site Measurement Data

A noise barrier serves as a method to control noise pollution resulting from road traffic, particularly prevalent in rural areas near heavy traffic routes such as highways. This study focuses on simulating the sound Insertion Loss (IL) of existing noise barriers designed to mitigate road traffic noise around school areas. The primary goal is to assess the precision of the Finite Element Modeling (FEM) program. Utilizing the finite element analysis software, COMSOL, the study models the noise barrier and its surroundings in two-dimensional acoustic radiation problem based on on-site dimensions and parameters. By examining the often-neglected aspect of noise leakage and its impact on noise reduction, the research aims to provide specific guidance for urban planners and architects to optimize noise mitigation in various urban settings. The study reveals a strong agreement between the simulated IL and on-site measurements, with a minimal difference ranging from 0.4 dB to 1.1 dBA on average. Additionally, the research suggests potential improvements to simulation accuracy through adjustments in aperture sizes. The findings demonstrate that finite element simulation can be a valuable tool for designers to assess the effectiveness of noise barriers before construction begins.

Assessing the Impact of Rainfall Inputs on Short-Term Flood Simulation with Cell2Flood: A Case Study of the Waryong Reservoir Basin

This study explored the impacts of various rainfall input types on short-term runoff simulations using the Cell2Flood model in the Waryong Reservoir Basin, South Korea. Six types of rainfall data were assessed: on-site gauge measurements, spatially interpolated data from 39 Automated Synoptic Observing System (ASOS) and 117 Automatic Weather System (AWS) stations using inverse distance weighting (IDW), and Hybrid Surface Rainfall (HSR) data from the Korea Meteorological Administration. The choice of rainfall input significantly affected model accuracy across the three rainfall events. The point-gauged ASOS (P-ASOS) data demonstrated the highest reliability in capturing the observed rainfall patterns, with Pearson’s r values of up to 0.84, whereas the radar-derived HSR data had the lowest correlations (Pearson’s r below 0.2), highlighting substantial discrepancies. For runoff simulation, the P-ASOS and ASOS-AWS combined interpolated dataset (R-AWS) achieved relatively accurate predictions, with P-ASOS and R-AWS exhibiting Normalized Peak Error (NPE) values of approximately 0.03 and Peak Time Error (PTE) within 20 min. In contrast, the HSR data produced large errors, with NPE up to 4.66 and PTE deviations exceeding 200 min, indicating poor temporal accuracy. Although input-specific calibration improved performance, significant errors persisted because of the inherent uncertainty of rainfall data. These findings underscore the importance of selecting and calibrating appropriate rainfall inputs to enhance the reliability of short-term flood modeling, particularly in ungauged and data-sparse basins.

Model for Estimating Soil Chemical Properties with RGB Drone Images

Precision agriculture optimizes crop management by providing accurate data on soil chemical properties, thereby improving agricultural productivity and sustainability. This study aims to develop models to estimate soil chemical properties, such as pH, electrical conductivity (EC), and organic matter (OM), by analyzing drone-captured RGB images. The methodology included photogrammetric flights with a DJI Phantom 4 Pro drone equipped with a 20 Mpx camera and simultaneous sampling, laboratory analysis and on-site measurements, with Royal Eijkelkamp EC meter set voor grond multiparameter sensors and pH meter set for soil and water. The aerial images were processed with the PIX4Dmapper software, to generate the orthophoto and spectral bands. With the resulting orthophoto of 1.6 cm/pixel, eight spectral indices were calculated, using the spatial analysis tools of ArcGIS software. The in situ results showed an average pH value of 5.83, indicating a slightly acidic soil, and an EC of 1.09 dS/m, suggesting a soil with a low concentration of dissolved salts. Laboratory analyses showed a medium-high content of OM, with an average of 5.19 %. A strong correlation was found between OM and pH_index with coefficients of determination R2=0.55, while moderate correlations were also observed between pH with pH_index and EC with sal_index6 with coefficients of determination R2=-0.39 and R2=0.42 respectively. The aforementioned results allowed the generation of two models for the estimation of these variables from RGB images.

Rapid crack-based assessment of deep beams based on a single crack measurement

Deep beams in concrete infrastructure often exhibit wide diagonal shear cracks that extend from the supports to concentrated loads. A key problem in these cases is to assess the residual capacity against shear failure across such cracks. This problem can be solved by establishing a relationship between the opening of the crack and the residual capacity, expressed in percentage of the shear strength. The current study establishes such a relationship that requires minimal input information. The input consists of only three on-site measurements: the depth of the critical loading zone (CLZ) determined by the diagonal crack; the angle of the crack in the CLZ; and a single crack measurement: the vertical crack displacement in the vicinity of the CLZ. The physical basis of the proposed crack-based assessment (CBA) is established with the help of a targeted test and advanced modelling. It is shown that only three input parameters and two simple closed-form equations are sufficient to accurately evaluate the residual capacity of diagonally cracked deep beams with various properties. Furthermore, in the presence of loading and unloading cycles, the proposed CBA reveals how close the member has come to shear failure throughout its entire service life. These properties render the CBA not only suitable for rapid assessment, but also for long-term monitoring of deep beams with diagonal cracks.

Current Progress of EUV Spectral Responsivity Calibration for EUV Lithography at CMS/ITRI

Abstract To support the development of advanced EUV lithography for the semiconductor industry in Taiwan, a calibration system for photodiodes’ spectral responsivity was established. The current system utilizes the synchrotron radiation light source and the method is traceable to PTB, Germany. The wavelength range is from 10 nm to 15 nm, including the most often used 13.5 nm. Several techniques were studied to compensate for light source fluctuation and to reduce the measurement uncertainty. The relative expanded uncertainty of the spectral responsivity calibration at 13.5 nm is 4.6 % (k=2). A wafer-type EUV radiant power meter designed to be used in EUV lithography chambers is being developed. Our goal is to develop simple and reliable methods for on-site EUV optical power measurement and dose estimation.