DDR Presentation

P13621: CONDUCTIVE HEAT TRANSFER LAB EQUIPMENT HTTPS://EDGE.RIT.EDU/EDGE/P13621/PUBLIC/HOME

MSD 1: Detailed Design Review 2 November, 2012 RIT KGCOE

Project Participants Project Sponsor : RIT KGCOE, Chemical Engineering Dept. Dr. Karuna S. Koppula Mr. Paul Gregorius

MSD 1 Team Guides : Neal Eckhaus Steve Possanza

Chinmay Patil (field expert)

Team P13621: Shannon McCormick - (ChemE) PM Tatiana Stein - (ChemE) Team Facilitator Shayne Barry - (ME) Procurement Jordan Hill - (EE) Piotr Radziszowski - (ME) Meka Iheme - (ChemE) Risk Manager Rushil Rane - (ISE) Lead Engineer

Agenda • Project Overview

• Customer Needs and Engineering Metrics • Assembly Drawing & CAD Drawings • Feasibility Analysis • Specimen dimension analysis • Cooling Capacity • Insulation Analysis • Experimental Basis • Safety Analysis

• Bill of Materials • Spec Sheets • Project Plan • Risk Assessment • Test Plan

Project Overview Mission Statement: To provide students with the ability to observe conductive heat transfer and the ability to measure the thermal conductivity of a material.

Background: • A material’s ability to transfer heat is a measurable quantity • RIT ChemE department would like to procure lab equipment that would demonstrate

heat transfer such that students may be able to calculate thermal conductivity • Experimental results would be comparable to published data

Customer Needs

Engineering Metrics

Engineering Metrics

Assembly Drawing Assembly/ disassembly instructions Transfer of heat Linear profile Size of cold plate Constant pressure application Thermal stickers for visual Losses

CAD Drawings

CAD Drawings

CAD Drawings

Specimen Dimension Analysis

Specimen Dimension Analysis

Specimen Dimension Analysis

Cooling Capacity

Insulation Dimension Analysis 𝑋=

𝑘𝐴 𝑇1 − 𝑇2 𝑞

X = Ideal Insulation Thickness (m) K = Thermal Conductivity (W/mK) A = Area of Sample (m2) T2 = Outside Temperature (K or C) T1 = Sample Temperature (K or C) Q = Power in (W) It is infeasible to use deterministic methods due to the many non-converging values of X resulting from combinations of Q and T1 . T2 values also change along the length of the sample, adding to the complexity of a deterministic model.

Monte Carlo Analysis K – Held Constant (0.2 W/mK) A – Held Constant (0.0079 m2) T2 – Held Constant (20 C)

-Q and T1 are varied simultaneously -Generate large data set and use stochastic methods to determine best insulation thickness

Error Minimized using Excel Solver Function

Insulation Dimension Analysis

Insulation Dimension Analysis

Current Lab Set-Up

Experimental Basis

Conclusions from Lab •Aluminum graph was more linear than the copper graph •Aluminum sample was longer than the copper sample  the longer the sample size, the better the accuracy that was achieved

ANSYS – Thermal Model

ANSYS – Heat Generation Model

ANSYS – Temperature Boundary Model

ANSYS – Heat Flux Model

Safety Analysis

Safety Analysis

Bill of Materials

Bill of Materials

Spec Sheets – cartridge heater

Spec Sheets – cold plate

Spec Sheets – cooling unit

NI 9211 DAQ vs. NI USB-TC01

DAQ comparison

Power Supply • 0 to 48 voltage range • 0-1 A current range • P=I*V

• Provides exact method

of calculating energy into the system

Project Plan

Project Plan

Risk Assessment

Risk Assessment

Test Plan

Test Procedures

Test Procedures

Test Template

Questions?