Radiation Map Research Articles

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

Solar Photovoltaic Potential In article number 2100478, Hesan Ziar and co-workers developed a semi-automatized workflow to estimate residential solar photovoltaic (PV) potential, which only requires LiDAR data and building footprints as inputs, and delivers accurate geo-referenced 3D building models, annual solar irradiation map, annual DC/AC yield maps, and prioritizes roof segments based on their PV potential.

ASSESSMENT OF SOLAR ENERGY POTENTIAL OF NIGERIA FOR SOLAR POWER GENERATION THROUGH NUMERICAL SOLAR IRRADIANCE MAPPING

Any thorough analysis of solar energy applications in the country requires a solar resources map. Many maps have been developed, but they only show distributions presented in colour intensities. Solar irradiance can only be estimated from such maps. Using on the spot experimental data for solar map production does not provide accurate maps because various climatic and environmental conditions such as dust haze and cloud cover affect the amount of solar energy that reaches the ground in various locations in Nigeria. This is particularly true during the harmattan period. Therefore data generated from such methods cannot be used to develop accurate numerical solar maps. Data for such applications should be collected from outer space and over a long time for various locations. The National Aeronautics and Space Administration (NASA) provides a resources base for such data. The data used in this study covered 25 years (1994-2018). The average daily global solar irradiance for various longitude-latitude nodes is calculated from such data. With these data available, it is possible to estimate the average daily global solar irradiance for any location provided the longitude and latitude is known. Irradiance values for 300 locations in the country are evaluated from details presented by the maps. To validate the map, experimental irradiance values for selected locations are compared with values extracted from the solar irradiance map. Calculated irradiance values are found to agree satisfactorily with experimental values. The maximum percentage difference between calculated and experimental values is 6.8%. This proved that the solar map developed is a satisfactory provides a satisfactory representation of solar data for the various locations and can be used for other locations where such data does not exist. KEYWORDS: Solar Energy, Solar Maps, Irradiance, Energy Patterns,

ASSESSMENT OF SOLAR ENERGY POTENTIAL OF NIGERIA FOR SOLAR POWER GENERATION THROUGH NUMERICAL SOLAR IRRADIANCE MAPPING

Any thorough analysis of solar energy applications in the country requires a solar resources map. Many maps have been developed, but they only show distributions presented in colour intensities. Solar irradiance can only be estimated from such maps. Using on the spot experimental data for solar map production does not provide accurate maps because various climatic and environmental conditions such as dust haze and cloud cover affect the amount of solar energy that reaches the ground in various locations in Nigeria. This is particularly true during the harmattan period. Therefore data generated from such methods cannot be used to develop accurate numerical solar maps. Data for such applications should be collected from outer space and over a long time for various locations. The National Aeronautics and Space Administration (NASA) provides a resources base for such data. The data used in this study covered 25 years (1994-2018). The average daily global solar irradiance for various longitude-latitude nodes is calculated from such data. With these data available, it is possible to estimate the average daily global solar irradiance for any location provided the longitude and latitude is known. Irradiance values for 300 locations in the country are evaluated from details presented by the maps. To validate the map, experimental irradiance values for selected locations are compared with values extracted from the solar irradiance map. Calculated irradiance values are found to agree satisfactorily with experimental values. The maximum percentage difference between calculated and experimental values is 6.8%. This proved that the solar map developed is a satisfactory provides a satisfactory representation of solar data for the various locations and can be used for other locations where such data does not exist. KEYWORDS: Solar Energy, Solar Maps, Irradiance, Energy Patterns,

Bionic orientation method based on polarization imaging in HDR scenes.

An increasing number of bio-inspired navigation approaches have been designed based on polarization cameras. However, digital cameras can sense a much narrower field of vision than the vision of insects or human beings. In this study, we propose an adaptive skylight polarized orientation method for high dynamic range (HDR) scenes. Initially, we built a model of the image acquisition pipeline that can recover HDR irradiance maps from polarization images. Subsequently, the orientation method was designed based on a combination of the irradiance maps and the least squares methods. Some preprocessing steps were utilized to eliminate occlusion interference. In addition, an autoexposure adjustment method was proposed using information entropy and heuristic segmentation. Finally, the experimental results show that the proposed method can improve the accuracy of bionic orientation and adaption to skylight with occlusions and interference in natural conditions.

Autonomous Environment Disinfection Based on Dynamic UV-C Irradiation Map.

The COVID-19 pandemic has become a worldwide concern and has motivated the entire scientific community to join efforts to fight it. Studies have shown that SARS-CoV-2 remains viable onsurfaces for days, increasing the chances of human infection. Environmental disinfection is thus an important action to prevent the transmission of the virus. Despite the valuable contribution of the research community to the field of UV-C disinfection by robots, there still lacks a disinfection system that is fully autonomous and computes its trajectory in real-time and in unknown environments. To meet this need, we propose an autonomous UV-C disinfection strategy for indoor environments based on a dynamic Irradiation Map that indicates the amount of energy applied in each region. Our method was tested in different scenarios and compared with other disinfection strategies. Experiments show that our approach delivers better results, especially when targeting high ideal UV-C doses.

Contributed Session I: Negative dysphotopsia evaluation using individualized eye models

Building on our previously communicated results, the current study evaluates the predictive ability of individualized eye models to localize negative dysphotopsia (ND) in the peripheral field of view (PFoV) In a prospective study conducted at Hanusch Hospital, Vienna, Austria, post-operative biometrical data were acquired from five patients implanted with monofocal IOLs and with ND complaints. A Harms tangent screen subjective method was used to localize in PFoV the perceived shadow (HvF). For computing theoretical retinal irradiance maps, individualized Liou-Brennan (non)-sequential eye models were generated using the acquired biometrical data. Mean axial length was 22.83 (21.05 - 24.80) mm, mean IOL power 24.4 (20.5 - 30.0) D, mean IOL tilt -1.86 (-6.21 - 2.96) degrees and mean decentration 0.16 (-0.27 - 0.44) mm. Average residual astigmatism difference between theoretical and measured data was 0.49 (0.02 - 0.97) D. Aligned with HvF data, the irradiance maps localized ND in the peripheral visual field up to 85 degrees. Previously presented theoretical results evidenced that in identical biometrical conditions, IOLs from different manufacturers with similar mechanical platforms but different optic edge designs are characterized by comparable ND profiles with the peripheral location of the shadows between 69 and 76 degrees. Further expanding the utilization of these eye models, the current results demonstrate their clinical relevance in terms of PFoV localization of ND.

An optimized approach for mapping solar irradiance in a mid-low latitude region based on a site-adaptation technique using Himawari-8 satellite imageries

Solar technologies play an important role in the renewable electric energy budget, so accurate solar maps are a crucial point for finding a suitable place for solar panel installation. This study proposes a method for solar irradiance mapping in mid-low latitude regions, and the method's site-adaptation process is performed by optimizing the Heliosat method through the REST2 clear-sky model, cloud albedo selection, new clear-sky index, and linear subtraction for bias removal. A local station with two pyranometers provided ground measurements. Site-adapted model results were used to create a calibrated solar map by linear regression adaptation. This study also provides the evaluation and site-adaption of another irradiance dataset in the Asian region from the Japan Aerospace Exploration Agency (JAXA). Heliosat model results with optimal cloud albedo showed high accuracy of 4.78 W/m2 MBE and 63.11 W/m2 RMSE, which can be improved using the site-adaptation process to 0.71 W/m2 MBE and 57.42 W/m2 RMSE. The selection of an optimal cloud albedo improved the model by approximately 20%. The JAXA dataset obtained a large overestimation of 56.72 W/m2 MBE, thereby highlighting the importance of site adaptation. This research's findings pave a new way for the creation of accurate site-adapted solar maps and databases.

Street-level solar radiation mapping and patterns profiling using Baidu Street View images

• Street-level solar radiation mapping and patterns profiling with Baidu Street View (BSV) images are studied. • A BSV-based radiation estimation method considering weather conditions is established to map the hourly street-level solar radiation. • A two-stage clustering method is proposed to profile the solar radiation patterns. • Eight types of daily radiation patterns and six types of multifaceted radiation patterns are discovered. • Maps of street-level solar radiation can provide useful datasets for urban study. The variability of urban landscapes and weather conditions makes it challenging to quantify the solar radiation of urban streets. In this study, we propose a framework to map and profile the street-level solar radiation using Baidu Street View (BSV) images. In our framework, a BSV-based radiation estimation method considering weather conditions is established to map the hourly street-level solar radiation. Then, a two-stage clustering method is proposed to profile the radiation patterns, including daily radiation patterns (DRP) and multifaceted radiation patterns (MRP), from the estimated radiation data. Taking Chongqing as a case, results show that (1) the estimated solar radiation of the proposed method is closer to the real situation than the two existing methods. (2) The solar radiation of streets varies greatly among different road grades and streetscapes; the street environment and weather conditions have a significant impact on solar radiation in mountain cities. (3) Eight types of DRP and six types of MRP are discovered by the two-stage clustering method. Moreover, the features, geographical distribution and applications of the radiation patterns are investigated in detail to support urban planning. This work can greatly promote studies relating the solar radiation at the street-level in the future.

Anisotropic radiation source models for computational thermal manikin simulations based on common radiation field measurements

The balanced design of extreme heat adaptation strategies that engineer the radiative properties of infrastructure or human clothing requires realistic methods of spectrally and spatially resolving irradiation from a complex built environment on the human body. Current irradiation measurement methods oversimplify the human body as points, spheres, or cylinders. In contrast, computational thermal manikins often used in convective simulations resolve the 3D body shape but have predominantly been used to model radiation exchange only with a large isothermal surrounding. To bridge this gap, we formulated six anisotropic radiation source models for thermal manikin simulations based on net-radiometer 6-directional, acrylic globe, and cylindrical radiation thermometer measurements. In some cases, we augmented the models with solar zenith angle and theoretical global solar irradiation. The models predict similar diffuse longwave (LW) as well as direct and diffuse shortwave (SW) radiation for measurements taken during a representative hot, sunny day with an unobstructed sky view. For three times of the day, we simulated irradiation distributions on an average male thermal manikin. Comparing the resulting irradiation maps showed that the direct SW component should be based on solar direction instead of the 6-directional "box" approach. Results also highlight the importance of the diffuse irradiation implementation method. However, experimental benchmarking (e.g., using physical thermal manikins in real-world settings) is required to determine whether the volumetric, box, or spherical diffuse source specification is the most realistic approach. The introduced techniques can be applied to realistically simulate irradiation from real-world built environments on a wide range of individuals.

A Comprehensive Workflow for High Resolution 3D Solar Photovoltaic Potential Mapping in Dense Urban Environment: A Case Study on Campus of Delft University of Technology

Photovoltaic (PV) technology is the most promising renewable energy source to be integrated on urban building surfaces. Modeling and simulating urban PV systems pose more challenges than the conventional ones installed in open field due to rich urban morphology. Herein, a comprehensive workflow to estimate urban solar PV potential is developed where TU Delft campus is used as a case study. This workflow only requires light detection and ranging data and building footprints as data inputs, and multiple levels of result can be delivered including accurate geo‐referenced 3D building models, annual solar irradiation map, annual DC/AC yield maps and classified roof segments according to the specific yield of mounted PV system. The study reports a total of ≈8.1 GWh year−1of PV energy which can be collected from campus building roofs and facades. Given the total electricity demand on the entire campus being 82.6 GWh/year, this PV potential can cover roughly 10% of the current electricity demand. The results constitute an initial assessment of solar PV potential on TU Delft campus buildings that is currently being used to prioritize PV integration on buildings and accelerate the transition toward a climate‐neutral campus.

Development of technical and statistical algorithm using Business Intelligence tools for energy yield assessment of large rooftop photovoltaic system ensembles

The aim of this paper is to develop a methodology for the energy yield assessment of a large ensemble of residential rooftop photovoltaic (PV) generators. The exploration and strategic analysis of data were applied for the first time, through Business Intelligence (BI) concepts combined with a technical-statistical algorithm for 1250 identical distributed rooftop PV systems installed in Santa Catarina, South of Brazil. Tilted solar irradiation maps were divided into four Ranges (statistical-quartiles) and, for the base year of 2019, the case-study results showed, with 95% reliability, an average annual daily energy yield of 3.35 kWh/kWp/day (Range 1); 3.74 kWh/kWp/day (Range 2); 3.82 kWh/kWp/day (Range 3); and 3.90 kWh/kWp/day (Range 4) for the four different quartiles into which the Santa Catarina state surface area was divided. The annual average PV generation of each PV rooftop analyzed was 3,353 kWh/year, which corresponds to an avoided CO2 emission of 268.25 kgCO2/year. For the combined 1250 PV rooftops ensemble, the average avoided CO2 emission was 335.30 tCO2/year. The implementation of BI concepts combined with the technical-statistical algorithm, provided relevant information about the performance of the PV systems, supporting fast decision-making strategies. The methodology applied can be used to predict the monthly/annual generation of future PV ensembles to be installed in any location for distributed generation asset allocation planning.

SECONDARY RADIATION MAPPING

Radiation protection for personnel working with X-rays is of vital importance. Several studies have been published regarding the secondary radiation and the shielding requirements to areas that are adjacent to the X-ray units. In this work, secondary radiation in a conventional radiographic room, in terms of dose rate (mSv/hr), as a function of different radiographic exposure factors has been studied. The measurements were performed with a 451P Fluke Biomedical survey meter on a Philips Medio 65 CP-H X-ray generator with a cylindrical water phantom. It was found that the dose rate from the scatter radiation decreases with distance. An added filtration of 2.0 mmAl at 100 kVp reduced the secondary dose rate further by 21.4%. The results of this study may be of value during exposure of personnel that are not protected by shielding materials. Highlights Ÿ It was found that the dose rate from the scatter radiation decreases with distance. An added filtration of 2.0 mmAl at 100 kVp reduced the secondary dose rate further by 21.4%. Ÿ The mean secondary X-ray energies for 60, 80, 100 and 100 kV with 2 mmAl added, were calculated as 34.41, 51.12, 69.03 and 71.29 keV respectively. Ÿ The results of this study are of value during exposure of people such as radiographers, and patients during the use of mobile X-ray units.

Polaris-LAMP: Multi-Modal 3-D Image Reconstruction With a Commercial Gamma-Ray Imager

The Polaris-LAMP multi-modal 3-D gamma-ray imager is a radiation mapping and imaging platform which uses a commercial off-the-shelf (COTS) detector integrated with a contextual sensor localization and mapping platform. The integration of these systems enables a free-moving radiation imaging capability with proximity mapping, coded-aperture, and Compton imaging modalities, which can create 3-D reconstruction of photon sources from tens of keV to several MeV. Gamma-ray events are recorded using a segmented cadmium zinc telluride (CZT) detector (Polaris-H Quad by H3D Inc., Ann Arbor, MI, USA), while scene data are derived from a contextual sensor and computation package developed by Lawrence Berkeley National Laboratory which includes GPS, laser ranging, and inertial measurement sensors. An onboard computer uses these inputs to create rapidly updating pose (10 Hz) and 3-D scene estimates using a simultaneous localization and mapping (SLAM) algorithm. The precise gamma-ray event location and timing resolution of the Polaris CZT sensor enables Compton imaging above several hundred keV, while photon sources at lower images are localized using coded-aperture imaging techniques. The multi-modal imaging concept enables imaging of diverse radiation sources spanning from the 59-keV emission of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">241</sup> Am to the 1.1 and 1.3 MeV lines of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> Co. This work focuses on the description of the operational principles of the detector system and demonstrating the 3-D imaging performance in a variety of source detection and mapping scenarios. As a proof of concept, we demonstrate mapping complex environments, including both point source and distributed-source environments using proximity, coded-aperture, and Compton imaging modalities. Furthermore, we show the successful use of the system to perform measurements in high-background environments through analysis of arrays of uranium hexafluoride cylinders at the Paducah UF6 project site.

Experimental and numerical validation of vibration-based sound power measurements of arbitrarily curved panels

Vibration-based sound power (VBSP) measurement methods are of interest due to their potential versatility in application compared to methods based on sound-pressure or sound-intensity. The VBSP method is based on the elementary radiator approach that relies on the acoustic radiation resistance matrix. Previous work has validated the form of the radiation resistance matrix for flat plates, cylindrical- and spherical-shells, and simple-curved plates. A form specific to arbitrarily curved structures has not been developed. Experimental VBSP measurements of two arbitrarily curved panels are shown to have excellent agreement with results from the ISO 3741 method. The VBSP method was applied by using the simple-curved plate form of the radiation resistance matrix and mapping each arbitrarily curved panel with a constant-radius curve fit. Numerical boundary element models, that inherently use the true form of the radiation resistance matrix, were also used to compute the sound power from the same curved panels. Surface velocity data from the numerical models were used to also compute sound power using the VBSP method with the simple-curved plate form of the radiation resistance matrix. Sound power results show excellent agreement between the numerical model and VBSP method. [Work supported by the National Science Foundation.]

GIS-AIDED GEOGRAPHICAL AND METEOROLOGICAL DATA OVERVIEW OF SOLAR RADIATION MAPPING FOR MALAYSIA – AN EXPLANATORY STUDY BASED ON SOLAR RADIATION PREDICTION MODELING USING NEURAL NETWORK APPROACH

Solar radiation mapping has used geographical and meteorological data. To obtain geographical and meteorological data, a Geographic Information System (GIS) is required. GIS is defined as an integrated geographic resource that presents data in terms of spatial information. This data is important for Neural Networks as it will be used as input parameters for the development of solar radiation prediction models. Solar radiation prediction is one way to map the sun's rays in certain places where there are insufficient resources or space to build a complete solar radiation measurement station. Since predictions about solar radiation require meteorological and geographical data, this paper will give an overview of GIS-assisted geographical and meteorological data to be used as input parameters for solar radiation mapping which will eventually be used as input for prediction models developed for the whole country of Malaysia using Neural Networks. Based on the results, the prediction model developed managed to obtain a coefficient of determination, R2 value of 0.9329.

Joint Environmental Radiation Survey by JAEA and KAERI Around the Fukushima Daiichi Nuclear Power Plant: Performance of Mobile Gamma-Ray Spectrometry Using Backpack and Carborne Survey Platforms.

According to the implementing arrangement between the Japan Atomic Energy Agency (JAEA) and the Korea Atomic Energy Research Institute (KAERI) in the field of radiation protection and environmental radiation monitoring, a joint survey program was performed to assess ground deposition of radioactive cesium in areas surrounding the Fukushima Daiichi Nuclear Power Plants. The purpose of this joint survey was to evaluate the field applications of the developed survey systems and methodologies. Understanding the performance of each system within a cesium-deposited contaminated zone is important for ensuring an appropriate response following a nuclear accident. The results of the measured ambient dose rates determined using each survey method were compared. Two kinds of survey system were used in the mobile gamma-ray spectrometry, which were MARK-M1 (Monitoring of Ambient Radiation of KAERI-the 1st Multipurpose system) based on two LaBr3(Ce) detectors of KAERI and KURAMA-II (Kyoto University Radiation Mapping - II) system with one CsI(Tl) detector of JAEA. First, mobile gamma-ray spectrometry using a backpack survey platform was conducted to assess the distribution of dose rates around specific survey sites, which were expected to be slightly contaminated by radioactive cesium in Minamisoma and Tomioka. A carborne survey using two gamma-ray spectrometers loaded inside a vehicle was successfully conducted to compare the measured dose rates in routes from site to site and verify evaluation methods, including attenuation correction.

A Cooperation Project in Lesotho: Renewable Energy Potential Maps Embedded in a WebGIS Tool

In this paper the background, activities undertaken, and main outcomes of the cooperation project “Renewable Energy Potential Maps for Lesotho” are presented. The project was launched in 2018 in fulfilment of the Paris Agreement by the Italian Ministry for the Environment and the Lesotho Ministry of Energy and Meteorology, with the aim to facilitate the local Government in the future planning and development of renewable energy in the country. A user-oriented WebGIS platform was utilised to share and analyse the outcomes of the project: a hydrological map to recognize potential areas for power generation; a wind atlas to identify specific sites with the most potential for wind energy generation; a solar radiation map, defining the different levels of radiation intensity, useful to localise sites for photovoltaic production. Human capacity building and technology transfer were carried out to strengthen the local expertise and ability to manage and plan renewable energy sources exploitation. The implementation of the project was based on a fruitful collaboration between scientists and stakeholders at the same time giving the local authorities a useful dataset and tool for renewable energy growth in Lesotho.

Comprehensive feasibility assessment of building integrated photovoltaics (BIPV) on building surfaces in high-density urban environments

Deployment of building integrated photovoltaics (BIPV) requires smart planning to optimise the production of renewable energies, while preserving the aesthetic quality of the urban landscape, especially in densely built-up urban environments. A comprehensive mapping tool is proposed here to investigate the feasibility of BIPV applications, by introducing a quantitative visual impact assessment in addition to the traditional energy yield projections. The concept is tested in a case study of buildings along Orchard Road, the main commercial and tourist boulevard in the South-East Asian city state of Singapore. First, a visibility analysis of each building surface is conducted from the perspective of simulated pedestrians at street-level, based on line-of-sight. This is followed by an assessment of the solar energy harvesting potential based on simulated annual solar irradiation values on the various building surfaces. Lastly, the visibility assessment is overlaid on the 3D solar irradiation map to identify and visualise the most suitable building surfaces for BIPV applications. In addition, the influence of road-side trees on the feasibility of BIPV has been studied. Depending on the degree of visual impact, different strategies are proposed for the optimum deployment of BIPV, ranging from high-efficiency technologies to aesthetic BIPV and media walls. The proposed methodology could evolve as a standard tool for the decision-making process in high-density urban environments and thus further assist in promoting the large-scale adoption of BIPV.

Use of Gaussian process regression for radiation mapping of a nuclear reactor with a mobile robot

Collection and interpolation of radiation observations is of vital importance to support routine operations in the nuclear sector globally, as well as for completing surveys during crisis response. To reduce exposure to ionizing radiation that human workers can be subjected to during such surveys, there is a strong desire to utilise robotic systems. Previous approaches to interpolate measurements taken from nuclear facilities to reconstruct radiological maps of an environment cannot be applied accurately to data collected from a robotic survey as they are unable to cope well with irregularly spaced, noisy, low count data. In this work, a novel approach to interpolating radiation measurements collected from a robot is proposed that overcomes the problems associated with sparse and noisy measurements. The proposed method integrates an appropriate kernel, benchmarked against the radiation transport code MCNP6, into the Gaussian Process Regression technique. The suitability of the proposed technique is demonstrated through its application to data collected from a bespoke robotic system used to conduct a survey of the Joz̆ef Stefan Institute TRIGA Mark II nuclear reactor during steady state operation, where it is shown to successfully reconstruct gamma dosimetry estimates in the reactor hall and aid in identifying sources of ionizing radiation.

A new rendering algorithm based on multi-space for living soft tissue

High fidelity display has a big impact on the user’s sense of immersion in virtual surgery. To achieve a high degree of visual realism, we propose a new subsurface scattering method, which is based on screen-space and texture-space and an improved two-layer surface reflection model, for living soft tissue rendering. The method can be described as a two-step strategy. First, the subsurface scattering in the screen space is computed. The biggest difference from traditional methods is that the back light information stored in the irradiance map of the texture space and the diffusion profile in the dipole model are used to calculate the subsurface scattering distribution formed by the light from the back of the object, which can render more rich details. Second, considering that the living soft tissues are usually covered with a thin layer of mucus, a mucus texture is mapped to the soft tissues as the second layer texture and an improved two-layer surface reflection model is proposed to render the mucus. Moreover, to show the viscosity and smoothness of the mucus, the calculation of highlight component is used in our model, which further enhances the reality of living soft tissue. Experimental results show that our method outperforms the two traditional methods of subsurface scattering based on texture space and screen space, and the rendering time of the proposed two-layer surface reflection model is 2/3 of that of the traditional model. We conducted a survey on the fidelity of soft tissues rendered using different algorithms, and the professional surgeons (60%-85%) thought that the rendered soft tissue with our method is more consistent with the characteristics of the in vivo soft tissues under a real surgical scene.