A5089796689- Wind and Air Flow Studies
- Probabilistic and Robust Engineering Design
- Markov Chains and Monte Carlo Methods
- Nuclear Engineering Thermal-Hydraulics
- Air Quality Monitoring and Forecasting
- Gaussian Processes and Bayesian Inference
- Nuclear reactor physics and engineering
- Target Tracking and Data Fusion in Sensor Networks
- Meteorological Phenomena and Simulations
- Risk and Safety Analysis
- Groundwater and Isotope Geochemistry
- Atmospheric chemistry and aerosols
- Radioactive contamination and transfer
- Statistical and Computational Modeling
- Nuclear and radioactivity studies
- Mass Spectrometry Techniques and Applications
- Fire dynamics and safety research
- Tropical and Extratropical Cyclones Research
- Radioactivity and Radon Measurements
- Water Quality Monitoring and Analysis
- Radiation Detection and Scintillator Technologies
- Urban Heat Island Mitigation
- Oil Spill Detection and Mitigation
- Air Quality and Health Impacts
- High-Energy Particle Collisions Research
National Centre for Nuclear Research
2012-2023
Polish Academy of Sciences
2012-2014
Institute of Computer Science
2012
The purpose of the presented research is estimation performance characteristics economic Total-Body Jagiellonian-PET system (TB-J-PET) constructed from plastic scintillators. are estimated according to NEMA NU-2-2018 standards utilizing GATE package. simulated detector consists 24 modules, each built out 32 scintillator strips (each with cross section 6 mm times 30 and length 140 cm or 200 cm) arranged in two layers regular 24-sided polygon circumscribing a circle diameter 78.6 cm. For...
Abstract In many areas of application it is important to estimate unknown model parameters in order precisely the underlying dynamics a physical system. this context Bayesian approach powerful tool combine observed data along with prior knowledge gain current (probabilistic) understanding parameters. We have applied methodology combining inference Markov chain Monte Carlo (MCMC) problem atmospheric contaminant source localization. The algorithm input are on-line arriving information about...
In a complex environment such as an urban area, accurate prediction of the atmospheric dispersion airborne harmful materials radioactive substances is necessary for establishing response actions and assessing risk or damage. Given variety models available, evaluation inter-comparison exercises are vital quantitatively qualitatively their capabilities differences. To that end, European Commission/Directorate General Joint Research Centre with support from General-Migration Home Affairs,...
The capabilities of nine atmospheric dispersion models in predicting near-field from puff releases an urban environment are addressed under the Urban Dispersion INternational Evaluation Exercise (UDINEE) project. model results evaluated using tracer observations Joint 2003 (JU2003) experiment where neutrally-buoyant puffs were released downtown area Oklahoma City, USA. Sulphur hexafluoride concentration time series measured at ten sampling locations during four daytime and night-time used to...
The work deals with the implementation of methodology for assessment possible consequences an accidental release radioactive material space distant receptors, and then application to planned Polish nuclear power plant. basic idea is, first identify worst case scenario each considered receptor using trajectory analysis, perform integrated simulations atmospheric dispersion dose estimation models. study shows that identification selection meteorological conditions based on analysis is adequate...
The multiplication factor (keff) and its uncertainty are critical design parameters in nuclear reactors. keff must be considered for operation, safety, economic reasons. Consequently, reducing has been of interest to the industry as long reactors were designed. Two methods this use – Generalized Linear Least Squares (GLLS) A General Monte Carlo-Bayes Procedure Improved Predictions Integral Functions Nuclear Data (MOCABA). Both have ability reduce by cross-sections through assimilation...
Realistic modeling of complex physical phenomena is always quite a challenging task. The main problem usually concerns the uncertainties surrounding model input parameters, especially when not all information about modeled phenomenon known. In such cases, Approximate Bayesian Computation (ABC) methodology may be helpful. ABC based on comparison output data with experimental data, to estimate best set parameters particular model. this paper, we present framework applying Forbush decrease (Fd)...
The Quick Urban and Industrial Complex (QUIC) atmospheric transport dispersion modelling system, developed by the Los Alamos National Laboratory, is evaluated using measurement data from Joint 2003 gas-tracer measurements conducted in Oklahoma City, USA. This activity has been coordinated within Dispersion International Evaluation Exercise (UDINEE) project, led European Commission–Joint Research Centre. Four different set-ups for QUIC program are types of wind-speed data, such as local...
Accidental atmospheric releases of hazardous material pose high risks to human health and the environment. Thus a valuable is develop emergency reaction system recognizing probable location release source based on measurement released substance concentration by sensors network. We apply methodology combining Bayesian inference with Sequential Monte Carlo (SMC) problem contaminant localization. The algorithm input data are real-time incoming concentrations given substance. employ settled...
We propose a general concept for the analysis of results urban dispersion simulations high temporal resolution, taking into account multi-model ensembles. are motivated by theoretical considerations related both to characteristics measurements and representation ensemble. Based on typical mathematical notions, we present several indices, apply them UDINEE dispersion-modelling exercise. demonstrate that median model is proper ensemble presented methodology.
In many areas of application, a central problem is solution to the inverse problem, especially estimation unknown model parameters underlying dynamics physical system precisely. this situation, Bayesian inference powerful tool combine observed data with prior knowledge gain probability distribution searched parameters. We have applied modern methodology named Sequential Approximate Computation (S-ABC) tracing atmospheric contaminant source. The ABC technique commonly used in analysis complex...
Realistic modeling of the complicated phenomena as Forbush decrease galactic cosmic ray intensity is a quite challenging task. One aspect numerical solution Fokker-Planck equation in five-dimensional space (three spatial variables, time and particles energy). The second difficulty arises from lack detailed knowledge about profiles parameters responsible for creation decrease. Among these parameters, central role plays diffusion coefficient. Assessment correctness proposed model can be done...