COMPUTATIONAL MODELLING Dr Marina Neophytou University of Cambridge, Department of Engineering Scope: Test the appropriateness and validity of models of.

Slides:



Advertisements
Similar presentations
Chun-Ho Liu, Wai Chi Cheng, James Cheung, Tracy Chung Cynthia Poon, Pei Shui and Colman Wong Department of Mechanical Engineering, The University of Hong.
Advertisements

1 IS:01UDM -2 CONCEPTS IN HAZARDS TALK 1 NATURAL PHENOMENA OF LAND, SEA AND ATMOSPHERE. n HAZARD DUE TO RELEASE OF STRESS n TRIGGER EVENTS: NATURAL i.e,
Integrated modelling and monitoring for use in forecasting Jørgen Brandt and Finn Palmgren National Environmental Research Institute Department of Atmospheric.
Phoenics User Conference on CFD May 2004 Vipac Engineers & Scientists Ltd COMPUTATIONAL FLUID DYNAMICS Simulation of Turbulent Flows and Pollutant Dispersion.
Fine-Scale Variations in Aerosol Transport within a Street Canyon – a Pilot Field Study I.D. Longley, M.W. Gallagher, M. Flynn, J.R. Dorsey, P.I. Williams.
Bridging the Gap Between Statistics and Engineering Statistical calibration of CFD simulations in Urban street canyons with Experimental data Liora Malki-Epshtein.
Earth is calling… Will you answer?. Earth scientists use repeatable observations and testable ideas to understand and explain our planet.
BC 3722 HVAC Engineering Semester A 2003/04 Dr. Richard K K Yuen Department of Building & Construction.
Predicting the yield of small wind turbines in the roof-top urban environment S J Watson, D G Infield and M R Harding Centre for Renewable Energy Systems.
Odour offensiveness of a mink farm Dependence of annoyance spread on the size of a farm Milena Połeć Part of a master thesis carried out in the Laboratory.
Introduction to SCREEN3 smokestacks image from Univ. of Waterloo Environmental Sciences Marti Blad NAU College of Engineering and Technology.
Mike Hightower and Anay Luketa-Hanlin Sandia National Laboratories Albuquerque, New Mexico Sandia is a multiprogram laboratory operated by Sandia Corporation,
Assessing PM 2.5 Background Levels and Local Add-On Prepared by Bryan Lambeth, PE Field Operations Support Division Texas Commission on Environmental Quality.
Maricopa County Air Quality Department 1001 North Central Ave. Phoenix, Arizona Maricopa County Air Quality Department Protecting and improving our.
SEATTLE PLANNING COMMISSION Thursday, April 9, 2015 Chair’s Report & Minutes Approval3:00 – 3:10 PM Briefing: City of Seattle Transportation Levy3:10 –
Source apportionment of PM in the ADMS model David Carruthers Workshop on Source Apportionment of Particulate Matter Imperial College London Friday, 23.
University of Aveiro Final Meeting and Project Review 23/24 June 2003 Gdansk University of Aveiro Emissions and Air Quality Modelling Department of Environment.
B. Carissimo, S. Lacour, H. Foudhil,L. Musson-Genon, E. Dupont, M. Milliez, B. Albriet, E. Demael, L. Laporte, Tunnel modelling : the collaboration with.
Airflows and the spread of airborne pathogens in the ICU Dr Collette W
Modelling Pollution Dispersion in Urban Areas Silvana Di Sabatino Universita’ di Lecce, Dipartimento Scienza dei Materiali, Via Arnesano, Lecce (I)
fluidyn – PANAIR Fluidyn-PANAIR
Jenny Stocker, Christina Hood, David Carruthers, Martin Seaton, Kate Johnson, Jimmy Fung The Development and Evaluation of an Automated System for Nesting.
AIAA SciTech 2015 Objective The objective of the present study is to model the turbulent air flow around a horizontal axis wind turbine using a modified.
Applied Transportation Analysis ITS Application SCATS.
Development and Testing of Comprehensive Transport and Dispersion Model Evaluation Methodologies Steven Hanna (GMU and HSPH) OFCM Hanna 19 June 2003.
An importer of Herbs and Spices claims that average weight of packets of Saffron is 20 grams. However packets are actually filled to an average weight,
CDS 130 Fernando E. Camelli Department of Computational and Data Sciences George Mason University Web:
Environmental Modeling Steven I. Gordon Ohio Supercomputer Center June, 2004.
Modeling the Urban Energy Balance Anders Nottrott University of California, San Diego Department of Mechanical and Aerospace Engineering Anders Nottrott,
Tracer release experiments
School of something FACULTY OF OTHER THE SENSITIVITY OF A 3D STREET CANYON CFD MODEL TO UNCERTAINTIES IN INPUT PARAMETERS James Benson*, Nick Dixon, Tilo.
Modelling of Complex Urban Systems and Areas of Possible Improvements
NCAS/APRIL Meeting on Urban Air Quality Modelling Dispersion modelling at Imperial College London Professor Helen ApSimon and Dr Roy Colvile Page 1/N ©
Hiromasa Nakayama*, Klara Jurcakova** and Haruyasu Nagai*
10a. Univariate Analysis Part 1 CSCI N207 Data Analysis Using Spreadsheet Lingma Acheson Department of Computer and Information Science,
Draft-rosen-dns-sos-02 Brian Rosen. The basic idea 123.main.pittsburgh.allegheny.pa.us.sos.arpa contains a NAPTR, sos+psap, of something like
D ispersion of A ir P ollutants & their P enetration into the L ocal E nvironment EPSRC Infrastructure & Environment Programme Dr Samantha Arnold (C.Geog.)
UK Consortium Project funded by the EPSRC S. Arnold (1&2), H. ApSimon (1), J. Barlow (2), S. Belcher (2), M. Bell (3), R. Britter (4), H. Cheng (5), R.
Neighbourhoods and housing submarkets in the city of Barcelona Dionysia Lambiri The University of Reading 19 th Advanced Summer School in Regional Science.
EPA’s DRAFT SIP and MODELING GUIDANCE Ian Cohen EPA Region 1 December 8, 2011.
DAPPLE D ispersion of A ir P ollutants and their P enetration into the L ocal E nvironment EPSRC Infrastructure and Environment Programme The DAPPLE Consortium.
Combining Theory and Systems Building Experiences and Challenges Sotirios Terzis University of Strathclyde.
Building Aware Flow and T&D Modeling Sensor Data Fusion NCAR/RAL March
UNIVERSITY OF LEEDS Aerobiological Simulations Using Arc 1 Dr Cath Noakes; Dr Andy Sleigh; Dr Carl Gilkeson; Dr Miller Camargo-Valero; Dr Amir Khan.
Copyright  2003 by Dr. Gallimore, Wright State University Department of Biomedical, Industrial Engineering & Human Factors Engineering Human Factors Research.
The Evolving Roles and Responsibilities of Federal Agencies in Providing Transport and Dispersion Support -- an ARL Perspective Bruce B. Hicks Director,
CEN st Lecture CEN 4021 Software Engineering II Instructor: Masoud Sadjadi Monitoring (POMA)
A METHODOLOGY FOR ESTIMATING WIND FARM PRODUCTION THROUGH CFD CODES. DESCRIPTION AND VALIDATION Daniel Cabezón, Ignacio Martí CENER, National Renewable.
Session 3, Unit 5 Dispersion Modeling. The Box Model Description and assumption Box model For line source with line strength of Q L Example.
M.K. Neophytou 1&2, D. Goussis 2, E. Mastorakos 1, R.E. Britter 1 1 University of Cambridge, Department of Engineering, Trumpington Street, Cambridge CB2.
Sandia National Laboratories
Inferences from sample data Confidence Intervals Hypothesis Testing Regression Model.
PAG/ASG Meeting Monday, 14th July, 2003 University of Surrey 30BC03.
Types of Models Marti Blad Northern Arizona University College of Engineering & Technology.
DAPPLE Science Meeting Tuesday 30 th November 2004, Imperial College London. Air Flow – Fieldwork: Sam Arnold (1&2), Adrian Dobre (2), Rob Smalley (3),
Computational Fluid Dynamics ( CFD ) Modeling of Building-scale Dispersion Shuming Du September 12, 2002 Air Resources Board California Environmental Protection.
1 Giovanni Langella PhD at ETH Zurich/ EMPA Presentation Urban Physics spring school 2016.
Summary of the Report, “Federal Research and Development Needs and Priorities for Atmospheric Transport and Diffusion Modeling” 22 September 2004 Walter.
7. Air Quality Modeling Laboratory: individual processes Field: system observations Numerical Models: Enable description of complex, interacting, often.
Exposure to air pollution in the transport microenvironment: how important is short-term exposure to high concentrations, and what are the determinants.
Steven Hanna (GMU and HSPH) OFCM Hanna 19 June 2003
EXPOSURE OF CHILDREN TO ULTRAFINE PARTICLES AROUND AN URBAN INTERSECTION S Kaur, M J Nieuwenhuijsen & R Colvile Environmental Processes & Systems Research.
SHERPA for e-reporting
DAPPLE Dispersion of Air Pollutants and Penetration into the Local
Inter-Relations within DAPPLE - The Determinants for Exposure
Department of Computer Science University of York
QUANTIFYING THE UNCERTAINTY IN Wind Power Production Using Meteodyn WT
Forest fires and air pollution in Portugal
Federal Disaster Recovery Coordination And Roles for
Air Quality and Health Dr Liz Robin Director of Public Health
Presentation transcript:

COMPUTATIONAL MODELLING Dr Marina Neophytou University of Cambridge, Department of Engineering Scope: Test the appropriateness and validity of models of different levels of complexity and improvement Simple rules of thumb Operational models (e.g UDM, ASUDM, ESUDM, OSPM, ADMS-URBAN) Computational Fluid Dynamics (CFD) models (e.g. RANS, LES) Models: Themes: Urban Air Quality Accidental releases of hazardous materials Purposes:Prediction/forecasting Design of mitigation strategies

A. FIELD CAMPAIGN Location Distance from source (m) Measured average concentration (ppqv) Estimated maximum concentration (ppqv) Westminster Council House Bickenhall Mansions End of York Street Thornton Place Some concluding remarks: Measurements and estimates are consistent Significant variations over the 30 minute (long) period (possibly due to wind meandering) Rule of Thumb: C ~ 10 Q U -1 x -2

York Street Library Bickenhall Street Westminster Council House Thornton Place Bickenhall Mansions x A. FIELD CAMPAIGN Source-Receptor Positions

B. SCALE-VARIANT MODELLING Address urban dispersion in terms of different processes occurring at different scales On what basis one could define different scales is an open issue One way is through physically meaningful scales such as: Regional City Subdistricts Neighbourhood Street-canyons

An example:A source apportionment study for Central London