Various Methodologies for Calculating the Impacts on Delta-T From Independent Spent Fuel Storage Installations (ISFSI) Jim Holian and Steve Mirsky, SAIC.

Slides:



Advertisements
Similar presentations
21M062007D The Shaw Group Inc. ® An Analytical Screening Technique to Estimate the Effect of Cooling Ponds on Meteorological Measurements – A Case Study.
Advertisements

Conduction Conceptests
The Compass Rose. N N S N S E W N S E W SW NE SE NW.
Heat Exchanger Network Retrofit
Determining a Backup Source of Meteorological Data for Dispersion Characteristics (Wind and Stability) Mark T. Carroll Heather A. McDonald Andrew J. Lotz.
Case Study: Impact of Above Ground Spent Fuel Storage on Nearby Meteorological Systems Jim Holian SAIC NUMUG Meeting Charlotte, NC June 2008.
Lesson 17 HEAT GENERATION
X/Q for Releases From Area Sources 2008 RETS-REMP and NUMUG Workshop Jim Key Key Solutions, Inc.
 Provides natural ventilation and usually cools buildings/people because it accelerates the rate of heat transfer  Speed and direction change throughout.
Temporal Comparison of Atmospheric Stability Classification Methods
Dispersion and Deposition Estimation Issues Presented at NUMUG San Francisco, CA 2009.
Setting Acceptable Odor Criteria Using Steady-state and Variable Weather Data Z. Yu 1, H. Guo 2, C. Lague 3 1.Division of Environmental Engineering, University.
Eurocode 1: Actions on structures – Part 1–2: General actions – Actions on structures exposed to fire Part of the One Stop Shop program Annex B (informative)
Weather and X/Q 1 Impact Of Weather Changes On TVA Nuclear Plant Chi/Q (  /Q) Kenneth G. Wastrack Doyle E. Pittman Jennifer M. Call Tennessee Valley Authority.
2. Dispersion We’re going to move on to the second major step in doing dose assessment.
Sonic vs. Cup/Vane Data Comparison at the Cooper Nuclear Station Jim Holian SAIC Jim Holian SAIC NUMUG Meeting St. Louis, MO October 2006 NUMUG Meeting.
The Compass Rose.
X/Q for Releases From Area Sources 2009 RETS-REMP Workshop Jim Key Key Solutions, Inc.
Using ARCON96 for Control Room Radiological Habitability Assessments
MET 61 1 MET 61 Introduction to Meteorology MET 61 Introduction to Meteorology - Lecture 2 “The atmosphere (II)” Dr. Eugene Cordero San Jose State University.
Module 9 Atmospheric Stability Photochemistry Dispersion Modeling.
MET 10 - Lecture 4 Chapter 3: Air Temperature Dr. Craig Clements San Jose State University.
Craig Clements San José State University Shaorn Zhong Michigan State University Xindi Bian and Warren Heilman Northern Research Station, USDA Scott Goodrick.
Module 9 Atmospheric Stability MCEN 4131/ Preliminaries I will be gone next week, Mon-Thur Tonight is design night, 7:30ish, meet in classroom.
NATS 101 Lecture 12 Vertical Stability
Enclosure Fire Dynamics
Module 3 Fluid Flow. Lesson 20 CONTINUITY EQUATION DESCRIBE how the density of a fluid varies with temperature. DEFINE the term buoyancy. DESCRIBE the.
Calculation of wildfire Plume Rise Bo Yan School of Earth and Atmospheric Sciences Georgia Institute of Technology.
How Much Does a Cooling Pad Help Your Laptop?
Strategies for the Selection of Substitute Meteorological Data Ken Sejkora Entergy Nuclear Northeast – Pilgrim Station Presented at the 14 th Annual RETS-REMP.
Unit 8 POE Ballistic Device
MECHANISMS OF HEAT TRANSFER
Waste Treatment Plant Project Adapting Dispersion Software to DOE Standard 3009 Jorge Schulz Thomas R. McDonnell Bechtel National, Inc EFCOG Safety.
Lapse Rates and Stability of the Atmosphere
1 U N C L A S S I F I E D Modeling of Buoyant Plumes of Flammable Natural Gas John Hargreaves Analyst Safety Basis Technical Services Group LA-UR
Investigation of Meteorological Tower Siting Criteria Ken Sejkora Entergy Nuclear Northeast – Pilgrim Station Presented at the 15 th Annual RETS-REMP Workshop.
CHAPTER 5 Concentration Models: Diffusion Model.
Session 4, Unit 7 Plume Rise
AMBIENT AIR CONCENTRATION MODELING Types of Pollutant Sources Point Sources e.g., stacks or vents Area Sources e.g., landfills, ponds, storage piles Volume.
Meteorology & Air Quality Lecture-1
Further Topics in Regression Analysis Objectives: By the end of this section, I will be able to… 1) Explain prediction error, calculate SSE, and.
The Surprising Impact Stuff on the Tower has on Meteorological Data NUMUG Meeting Chicago June 2011 Jim Holian, SAIC.
Meteorology & Air Pollution Dr. Wesam Al Madhoun.
BFN Sigmas1 EVALUATING METEOROLOGICAL MONITORING SITES USING SIGMA-THETA Kenneth G. Wastrack Doyle E. Pittman T ENNESSEE V ALLEY A UTHORITY.
CLIC Prototype Test Module 0 Super Accelerating Structure Thermal Simulation Introduction Theoretical background on water and air cooling FEA Model Conclusions.
10. DENSITY  In addition to building design, there are other elements that can impact the passive potential of a site. Density, measured in Vancouver.
Comparison of the AEOLUS3 Atmospheric Dispersion Computer Code with NRC Codes PAVAN and XOQDOQ 13th NUMUG Conference, October 2009, San Francisco, CA.
Transport and dispersion of air pollution
Example 2 Chlorine is used in a particular chemical process. A source model study indicates that for a particular accident scenario 1.0 kg of chlorine.
Potential temperature In situ temperature is not a conservative property in the ocean. Changes in pressure do work on a fluid parcel and changes its internal.
TS/CV/DC CFD Team CFD Study of the L3 Thermal Environment Sara C. Eicher
Air Pollution Meteorology Ñ Atmospheric thermodynamics Ñ Atmospheric stability Ñ Boundary layer development Ñ Effect of meteorology on plume dispersion.
Lecture 7: Bivariate Statistics. 2 Properties of Standard Deviation Variance is just the square of the S.D. If a constant is added to all scores, it has.
Heat Transfer Su Yongkang School of Mechanical Engineering # 1 HEAT TRANSFER CHAPTER 7 External flow.
Regulatory background How these standards could impact the permitting process How is compliance with the standards assessed.
TS Cool Down Studies TSu Unit Coils (24-25) N. Dhanaraj and E. Voirin Tuesday, 10 March 2015 Reference: Docdb No:
A revised formulation of the COSMO surface-to-atmosphere transfer scheme Matthias Raschendorfer COSMO Offenbach 2009 Matthias Raschendorfer.
Lesson 7: Thermal and Mechanical Element Math Models in Control Systems ET 438a Automatic Control Systems Technology 1lesson7et438a.pptx.
A.Liudchik, V.Pakatashkin, S.Umreika, S.Barodka
Quench estimations of the CBM magnet
Consequence Analysis 2.1.
COOLING & VENTILATION INFRASTRUCTURE
Compass points and Bearings bingo
Stability.
Stability and Cloud Development
ET 438a Automatic Control Systems Technology
Eurocode 1: Actions on structures –
PURPOSE OF AIR QUALITY MODELING Policy Analysis
Meteorology & Air Pollution Dr. Wesam Al Madhoun
Wind Velocity One of the effects of wind speed is to dilute continuously released pollutants at the point of emission. Whether a source is at the surface.
Presentation transcript:

Various Methodologies for Calculating the Impacts on Delta-T From Independent Spent Fuel Storage Installations (ISFSI) Jim Holian and Steve Mirsky, SAIC NUMUG Meeting San Francisco October 2009 NUMUG Meeting San Francisco October 2009

Background Original study performed for Cooper Nuclear Station (Nebraska Public Power) Results presented at 2008 NUMUG in Charlotte Study based on very conservative assumptions Floods delayed new met tower construction Additional study requested to reduce conservativeness in impact analyses

Three Methods Analyzed Single-node adiabatic plume (initial study) Multi-node plume with heat transfer (dilution) Multi-node plume with heat transfer and buoyancy

Baseline Based on NUHOMS Horizontal Storage Module (HSM) ISFSI Design Other designs, i.e. Historm, VSC-24, NAC, may provide varying results due to different material, geometries, and flow areas Calculations provided for comparisons between methods and are not specific to any plant

Factors Impacting Results Independent of Method Distance from ISFSI to the met tower Stability class distribution Wind speed Wind direction frequency ISFSI heat load

Single Node Adiabatic Plume First quick estimate of thermal impacts at the meteorological tower (if any) No mixing with air outside plume No heat loss/gain with surrounding air Buoyancy is assumed zero Only calculation node is at the cross section of plume where it intersects met tower

Key Assumption HSM exit air temperature (HSM ext ) above ambient is linearly proportional to HSM heat load (HL) H ext = Actual HL /Design HL X Design HSM ext Example: 50°F = 12 kW/24 kW X 100°F

Method 1 Calculation The effect on air temperature at the met tower is the ratio of the flow rate at the HSMs (FR HSM ) and the flow rate at the tower (FR TWR ) along the insulated plume times HSM ext : ΔT twr = FR HSM / FR TWR X HSM ext FR TWR has huge influence on ΔT twr

What Influences FR TWR ? Greatest is Stability - G stable plume cross section at a met tower 600 feet away is over 70 times smaller than an unstable A plume Wind Speed Combination of stable plume and light winds (typical nighttime scenario) results in large ΔT twr

Met Tower ΔT (°F) at 500 Feet from ISFSI (8 HSMs – G & D Stability) HSM Heat kW Wind Speed (m/s) G G D D

Met Tower ΔT (°F) at 150 Feet from ISFSI (10 HSMs – G & E Stability) HSM Heat kW Wind Speed (m/s) G G E E

Multi-Node Plume With Heat Transfer Includes heat transfer with air outside plume Calculation node every 50 feet from ISFSI to met tower No heat loss/gain with ground Buoyancy is still assumed zero Reduces some conservatism from Method 1

Heat Transfer Methodology Determine flow area, heat transfer area, and plume volume for each node Calculate the natural convection heat transfer correlation Calculate the average and exit temperature of each node

Heat Transfer Calculations Natural Convection Heat Transfer Coefficient Selected: HTC = 0.18 Δt For each node, the heat transfer Q is: Q i = HTC i x Area i x Δt i Temperature change across the node is: T i+1 =T i -Q i /V i ρ i c p where V i is volume, ρ i is density, and c p is air specific heat.

Heat Transfer Methodology Results Reduced overall temperature change at tower by approximately 23% from simple adiabatic method (at 600 feet and 12 kW heat load for HSM geometry) Demonstrates the impact of temperature change versus distance

Multi-Node Plume With Heat Transfer and Buoyancy Utilizes same approach as the Heat Transfer Methodology except buoyancy is calculated into plume height Reduces additional conservatism from first two methodologies

Buoyancy Methodology Archimedes Law applied to each node Calculate the vertical displacement of each node Sum displacements to determine height of plume when it reaches met tower

Buoyancy Calculations Determine Buoyancy Force for each node i: F i =(ρ out -ρ iplume ) V iplume g Heated air buoyancy acceleration is: A ib = F i / V i ρ iplume Vertical plume displacement for each node is: Z i =0.5 A ib t 2

Buoyancy Results Including buoyancy reduced the overall temperature change at tower by over 40% from the simple adiabatic method In some instances, plume may go over tower, impact sensors at another level, or traverse between sensor levels Extremely dependent on HSM heat load and wind speed

ISFSI Effects on Radiological Dose Assessment

Impacts Thermal impacts of HSM designed heat load dissipation – (direct thermal 24/7) Structural – thousands of square feet of solid concrete in ISFSI HSMs sitting on a large concrete base often rimmed with gravel (passive thermal – urban heat island) Physical – ISFSI size impacting wind speed and direction if inside 10:1 ratio (Reg. Guide 1.23). Usually not a large impact

NRC XOQDOQ Comparison Ran standard Χ/Qs using 5 years of data Added 0.4°F to ΔT to account for passive thermal impacts holding all other parameters equal Added 3.0°F to ΔT only when wind is blowing from ISFSI to account for direct thermal impacts holding all other parameters equal Calculated the % change in sector Χ/Qs

Impacts on Delta-T Stability Distribution

Χ/Q Impact (%) When Lower Temperature Increased by 0.4°F Distance (Miles) SECTOR S SSW SW WSW W WNW NW NNW N NNE NE ENE E ESE SE SSE

Χ/Q Impact (%) When Lower Temperature Increased by 3.0°F for ISFSI to South of Tower Distance (Miles) SECTOR WNW NW NNW N NNE NE ENE E

Conclusions Various methods exist for calculating the change in temperature at the met tower from the ISFSI The conservative adiabatic method provides a quick first estimate The heat transfer method is less conservative and reduces the overall estimate by around 23% Adding buoyancy to the adiabatic and heat transfer method reduces the estimate by over 40%, is the least conservative, and approximates the height of impact at the tower Distance from the tower, stability, wind speed, and heat load have huge impacts on the results

Conclusions (cont’d) Heat Transfer is most important in unstable to neutral environments with wind speeds > 2 m/s Buoyancy has significant impacts in stable light wind conditions The impact on downwind dose assessment is large for changes in temperature at the tower >0.4°F In general, the analyses suggest that ISFSIs should be located further than 600 feet from the meteorological tower

Questions?