scholarly journals Large-Scale Reality Modeling of a University Campus Using Combined UAV and Terrestrial Photogrammetry for Historical Preservation and Practical Use

Drones ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 136
Author(s):  
Bryce E. Berrett ◽  
Cory A. Vernon ◽  
Haley Beckstrand ◽  
Madi Pollei ◽  
Kaleb Markert ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Large Scale ◽  
Point Clouds ◽  
Absolute Error ◽  
Development Planning ◽  
High Accuracy ◽  
Scale Model ◽  
University Campus ◽  
Historical Preservation ◽  
Historical Building

Unmanned aerial vehicles (UAV) enable detailed historical preservation of large-scale infrastructure and contribute to cultural heritage preservation, improved maintenance, public relations, and development planning. Aerial and terrestrial photo data coupled with high accuracy GPS create hyper-realistic mesh and texture models, high resolution point clouds, orthophotos, and digital elevation models (DEMs) that preserve a snapshot of history. A case study is presented of the development of a hyper-realistic 3D model that spans the complex 1.7 km2 area of the Brigham Young University campus in Provo, Utah, USA and includes over 75 significant structures. The model leverages photos obtained during the historic COVID-19 pandemic during a mandatory and rare campus closure and details a large scale modeling workflow and best practice data acquisition and processing techniques. The model utilizes 80,384 images and high accuracy GPS surveying points to create a 1.65 trillion-pixel textured structure-from-motion (SfM) model with an average ground sampling distance (GSD) near structures of 0.5 cm and maximum of 4 cm. Separate model segments (31) taken from data gathered between April and August 2020 are combined into one cohesive final model with an average absolute error of 3.3 cm and a full model absolute error of <1 cm (relative accuracies from 0.25 cm to 1.03 cm). Optimized and automated UAV techniques complement the data acquisition of the large-scale model, and opportunities are explored to archive as-is building and campus information to enable historical building preservation, facility maintenance, campus planning, public outreach, 3D-printed miniatures, and the possibility of education through virtual reality (VR) and augmented reality (AR) tours.

The Application of 3D Laser Scanning Technology in Ancient Architecture Protection

2013 ◽  
Vol 353-356 ◽  
pp. 3476-3479
Author(s):  
Jun Lan Zhao ◽  
Ran Wu ◽  
Lei Wang ◽  
Yi Qin Wu
Keyword(s):  
3D Reconstruction ◽  
Data Acquisition ◽  
High Speed ◽  
Laser Scanning ◽  
Large Scale ◽  
High Efficiency ◽  
Image Data ◽  
High Accuracy ◽  
3D Laser Scanning ◽  
3D Data

The study of 3D laser scanning technology in Category Conservation is one of the hot researches in recent years. Through the high-speed laser scanning, catching the 3D data of an object in large-scale with high efficiency, high accuracy and excellent resolution, is a new way in 3D reconstruction and image data acquisition. The method has achieved good results through the experiment.

scholarly journals ALBIS: integrated system for risk-based surveillance of invasive mosquito Aedes albopictus

2018 ◽  
Author(s):  
Milan P. Antonovic ◽  
Massimiliano Cannata ◽  
Andrea Danani ◽  
Lukas Engeler ◽  
Eleonora Flacio ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Data Transmission ◽  
Urban Areas ◽  
Large Scale ◽  
Winter Season ◽  
Integrated System ◽  
Scale Model ◽  
Climate Conditions ◽  
Catch Basins ◽  
The City

According to predictions bases on a climate-driven large-scale model the areas surrounding Lake Léman and, to some extent, the Swiss Plateau are suitable for the spread of Ae. albopictus North of the Alps, while other areas in Switzerland (e.g., the city of Zürich) seem currently too cold in winter for the survival of eggs. However, this model does not take into account particular micro-climate conditions in urban areas where the specie thrives. Climate conditions in urban micro-habitats (in particular catch basins) increase the probability of the survival of diapausing eggs in the winter season favoring the colonization of new cities that were thought to be too cold for the survival of the eggs. Therefore, there is an urgent need for appropriate monitoring tools and risk-based surveillance of Ae. albopictus populations. In 2018 a multidisciplinary group of researchers from the University of Applied Sciences and Arts of Southern Switzerland (SUPSI) has joined launching the project ALBIS (Albopictus Integrated System). The designed system focuses on the monitoring of urban catch basins, primarily on micro-climate environmental sensing, data transmission, data acquisition and data dissemination. The gathered data are the input for an empirical machine learning model for the prediction of spatial and temporal distribution of the Ae. albopictus. The first real time monitoring tests are in progress in the pilot area in the city of Lugano in the Canton Ticino. Fully functional prototypes have been engineered by the Institute of Earth Science in collaboration with a local electronics manufacturer (TECinvent) combined with the Open Source istSOS OGC Sensor Observation Service software for data acquisition and dissemination, and in the first tests cases have demonstrated good quality in terms of energy efficiency, data quality and data transmission reliability. The first results demonstrated that temperature in catch basins can be different from outside temperature that is detected by traditional terrain measures: in February 2018 during a period of cold air temperature in Canton Ticino of down to -8°C, the prototype sensor monitoring the catch basins' wall surface shows temperatures up to 6°C higher. Considering that one of the Ae. albopictus establishment thresholds is to have a mean January temperature of >0°C to allow egg overwintering, taking into account this micro-climate environments could lead to more realistic predictions.

scholarly journals ALBIS: integrated system for risk-based surveillance of invasive mosquito Aedes albopictus

2018 ◽  
Author(s):  
Milan P. Antonovic ◽  
Massimliano Cannata ◽  
Andrea Danani ◽  
Lukas Engeler ◽  
Eleonora Flacio ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Data Transmission ◽  
Urban Areas ◽  
Large Scale ◽  
Winter Season ◽  
Integrated System ◽  
Scale Model ◽  
Climate Conditions ◽  
Catch Basins ◽  
The City

According to predictions bases on a climate-driven large-scale model the areas surrounding Lake Léman and, to some extent, the Swiss Plateau are suitable for the spread of Ae. albopictus North of the Alps, while other areas in Switzerland (e.g., the city of Zürich) seem currently too cold in winter for the survival of eggs. However, this model does not take into account particular micro-climate conditions in urban areas where the specie thrives. Climate conditions in urban micro-habitats (in particular catch basins) increase the probability of the survival of diapausing eggs in the winter season favoring the colonization of new cities that were thought to be too cold for the survival of the eggs. Therefore, there is an urgent need for appropriate monitoring tools and risk-based surveillance of Ae. albopictus populations. In 2018 a multidisciplinary group of researchers from the University of Applied Sciences and Arts of Southern Switzerland (SUPSI) has joined launching the project ALBIS (Albopictus Integrated System). The designed system focuses on the monitoring of urban catch basins, primarily on micro-climate environmental sensing, data transmission, data acquisition and data dissemination. The gathered data are the input for an empirical machine learning model for the prediction of spatial and temporal distribution of the Ae. albopictus. The first real time monitoring tests are in progress in the pilot area in the city of Lugano in the Canton Ticino. Fully functional prototypes have been engineered by the Institute of Earth Science in collaboration with a local electronics manufacturer (TECinvent) combined with the Open Source istSOS OGC Sensor Observation Service software for data acquisition and dissemination, and in the first tests cases have demonstrated good quality in terms of energy efficiency, data quality and data transmission reliability. The first results demonstrated that temperature in catch basins can be different from outside temperature that is detected by traditional terrain measures: in February 2018 during a period of cold air temperature in Canton Ticino of down to -8°C, the prototype sensor monitoring the catch basins' wall surface shows temperatures up to 6°C higher. Considering that one of the Ae. albopictus establishment thresholds is to have a mean January temperature of >0°C to allow egg overwintering, taking into account this micro-climate environments could lead to more realistic predictions.

Benchmark of Simplified Time-Dependent Density Functional Theory for UV-Vis Spectral Properties of Porphyrinoids

2019 ◽  
Author(s):  
Kamal Batra ◽  
Stefan Zahn ◽  
Thomas Heine
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Large Scale ◽  
Absolute Error ◽  
Time Dependent ◽  
Basis Set ◽  
Basis Sets ◽  
Functional Theory ◽  
Framework Materials ◽  
Dependent Density

<p>We thoroughly benchmark time-dependent density- functional theory for the predictive calculation of UV/Vis spectra of porphyrin derivatives. With the aim to provide an approach that is computationally feasible for large-scale applications such as biological systems or molecular framework materials, albeit performing with high accuracy for the Q-bands, we compare the results given by various computational protocols, including basis sets, density-functionals (including gradient corrected local functionals, hybrids, double hybrids and range-separated functionals), and various variants of time-dependent density-functional theory, including the simplified Tamm-Dancoff approximation. An excellent choice for these calculations is the range-separated functional CAM-B3LYP in combination with the simplified Tamm-Dancoff approximation and a basis set of double-ζ quality def2-SVP (mean absolute error [MAE] of ~0.05 eV). This is not surpassed by more expensive approaches, not even by double hybrid functionals, and solely systematic excitation energy scaling slightly improves the results (MAE ~0.04 eV). </p>

RANCANG BANGUN PERANGKAT EKSPERIMENTASI PROSES PIROLISIS BIOMASA GELOMBANG MIKRO

2013 ◽  
Vol 14 (2) ◽  
Author(s):  
Noor Fachrizal
Keyword(s):  
Large Scale ◽  
Continuous Model ◽  
Biomass Energy ◽  
Scale Model ◽  
Small Scale ◽  
Laboratory Apparatus ◽  
Liquid Form ◽  
Large Scale Model ◽  
Bio Oil ◽  
Pyrolysis Of Biomass

Biomass such as agriculture waste and urban waste are enormous potency as energy resources instead of enviromental problem. organic waste can be converted into energy in the form of liquid fuel, solid, and syngas by using of pyrolysis technique. Pyrolysis process can yield higher liquid form when the process can be drifted into fast and flash response. It can be solved by using microwave heating method. This research is started from developing an experimentation laboratory apparatus of microwave-assisted pyrolysis of biomass energy conversion system, and conducting preliminary experiments for gaining the proof that this method can be established for driving the process properly and safely. Modifying commercial oven into laboratory apparatus has been done, it works safely, and initial experiments have been carried out, process yields bio-oil and charcoal shortly, several parameters are achieved. Some further experiments are still needed for more detail parameters. Theresults may be used to design small-scale continuous model of productionsystem, which then can be developed into large-scale model that applicable for comercial use.

scholarly journals Stator Non-Uniform Radial Ventilation Design Methodology for a 15 MW Turbo-Synchronous Generator Based on Single Ventilation Duct Subsystem

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2760
Author(s):  
Ruiye Li ◽  
Peng Cheng ◽  
Hai Lan ◽  
Weili Li ◽  
David Gerada ◽  
...  
Keyword(s):  
Finite Element ◽  
Temperature Distribution ◽  
Design Methodology ◽  
Large Scale ◽  
Synchronous Generator ◽  
Axial Direction ◽  
Scale Model ◽  
Element Analysis ◽  
Axial Temperature ◽  
Ventilation Duct

Within large turboalternators, the excessive local temperatures and spatially distributed temperature differences can accelerate the deterioration of electrical insulation as well as lead to deformation of components, which may cause major machine malfunctions. In order to homogenise the stator axial temperature distribution whilst reducing the maximum stator temperature, this paper presents a novel non-uniform radial ventilation ducts design methodology. To reduce the huge computational costs resulting from the large-scale model, the stator is decomposed into several single ventilation duct subsystems (SVDSs) along the axial direction, with each SVDS connected in series with the medium of the air gap flow rate. The calculation of electromagnetic and thermal performances within SVDS are completed by finite element method (FEM) and computational fluid dynamics (CFD), respectively. To improve the optimization efficiency, the radial basis function neural network (RBFNN) model is employed to approximate the finite element analysis, while the novel isometric sampling method (ISM) is designed to trade off the cost and accuracy of the process. It is found that the proposed methodology can provide optimal design schemes of SVDS with uniform axial temperature distribution, and the needed computation cost is markedly reduced. Finally, results based on a 15 MW turboalternator show that the peak temperature can be reduced by 7.3 ∘C (6.4%). The proposed methodology can be applied for the design and optimisation of electromagnetic-thermal coupling of other electrical machines with long axial dimensions.

scholarly journals A Lagrange Relaxation Based Decomposition Algorithm for Large-Scale Offshore Oil Production Planning Optimization

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1257
Author(s):  
Xiaoyong Gao ◽  
Yue Zhao ◽  
Yuhong Wang ◽  
Xin Zuo ◽  
Tao Chen
Keyword(s):  
Production Planning ◽  
Large Scale ◽  
Oil Production ◽  
Original Model ◽  
Decomposition Algorithm ◽  
Scale Model ◽  
Lagrange Relaxation ◽  
Planning Optimization ◽  
Offshore Oil Production ◽  
Offshore Oil

In this paper, a new Lagrange relaxation based decomposition algorithm for the integrated offshore oil production planning optimization is presented. In our previous study (Gao et al. Computers and Chemical Engineering, 2020, 133, 106674), a multiperiod mixed-integer nonlinear programming (MINLP) model considering both well operation and flow assurance simultaneously had been proposed. However, due to the large-scale nature of the problem, i.e., too many oil wells and long planning time cycle, the optimization problem makes it difficult to get a satisfactory solution in a reasonable time. As an effective method, Lagrange relaxation based decomposition algorithms can provide more compact bounds and thus result in a smaller duality gap. Specifically, Lagrange multiplier is introduced to relax coupling constraints of multi-batch units and thus some moderate scale sub-problems result. Moreover, dual problem is constructed for iteration. As a result, the original integrated large-scale model is decomposed into several single-batch subproblems and solved simultaneously by commercial solvers. Computational results show that the proposed method can reduce the solving time up to 43% or even more. Meanwhile, the planning results are close to those obtained by the original model. Moreover, the larger the problem size, the better the proposed LR algorithm is than the original model.

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